tnau – tnslub project introduction - tamil nadu · enforcement of rules and stringent action...

TNAU – TNSLUB Project Introduction

1

Natural resources include an array of exhaustible and renewable resources.

Natural resources comprising land, water, forests and fisheries constitute the

basic support systems of life on earth. Among the range of natural resources,

land and water are the prime and basic resources for human survival, agriculture

and industrial development. According to a recent available official figure, out of

324 million hectares of total cultivated land area, as much as 175 million hectare

is subjected to environmental degradation. The rate of degradation is also said to

be very high. Every year 2.5 million hectare i.e., about one per cent of India’s

land area turns into wasteland. About 90 million hectare of the 175 million

hectare of degraded land, are almost completely unproductive. Land degradation

of this order has serious ecological and economic implications. Apart from the 50

per cent of the land area that is degraded in the above ways, about 27 per cent

are degraded by flood and salinity and alkalinity. It is estimated that our national

soil loss is about 6000 million tonnes annually, 18.5 per cent of the total soil loss

at the global level. This is very serious considering the fact that India has only 2.4

per cent of the total land area of the World. With this soil we lose about six million

tonnes of nutrients, which is greater than the quantity of fertilizers applied to our

soil every year.

1.1 Environment and Natural Resources The environment is both a biological and physical source of all natural resources.

Some natural resources are renewable while others are non renewable. The

major environmental problems we face today are externality, degradation of

renewable resources and depletion of non-renewable resources. Since all kind of

production activities involve pollution in one form or another, externality is likely

to be with us in some form or another. No production activity is hundred per cent

perfect in terms of technology and hence some pollution will always be

1. INTRODUCTION


2

generated. Most economic activities involve transformation of resources and this

transformation processes generate pollution at different stages and often the

environment is used as a repository for waste products. When waste deposited in

the environment exceed the assimilative capacity, degradation of environmental

resources take place. Degradation of the environment affects quality of

resources, production system, public health, physical assets, plant and animal

system and scenic beauty.

The environmental costs occur in the forms of larger expenditure on health care,

provision of protected water supply and maintenance of assets, enhancement in

the use of resources to achieve a given level of output over time in order to

compensate for the decline in the quality of resources, abatement and defensive

expenditures incurred by consumers and enforcement authorities. As the impact

on the natural resource system is expected to increase with the expanding

population and industrial activities, seeking a higher standard of living becomes

the absolute need of the day. Hence what is required at this stage is a package

of policy measures to identify and monitor externalities, to identify their economic,

ecological and sociological effects and to internalize their effects within levels,

which are not only safe for survival but also appropriate to the quality of life.

1.2. Industrial Development, Agriculture and Externality Textile dyeing industry is one of the important industries in our country that

consumes substantial volume of water and chemicals. Many dyeing factories do

not have adequate provision for treating the effluents and hence it is discharged

into the river without any proper treatment thus making the river water unusable.

This also pollutes the sub-soil and ground water table. Though industrial growth

plays an important role in the economic development of the developing countries

it is apparent that the pollution effects of various industrial units in India had been

alarming. Even in early eighties, there were instances that the poly fibre factories


3

in Dharwad district of Karnataka had polluted the Thungabhadra river resulting in

health disorders, drinking water quality deterioration, crop and milk yield decline

in buffaloes and mass mortality of fish (Anonymous, 1985). Krupanidhi and

Bhushan (1988) in their study indicated the effects of distillery effluents in

Udaipur where the dug wells located 200 – 300 meters away from the polluting

units were found to be affected, which resulted in unsuitability of water for

drinking and irrigation.

As far as western Tamil Nadu is concerned the rivers Amaravathy, Noyyal,

Cauvery and Bhavani are polluted by the discharge of effluent water from the

nearby industries of various kinds. Rivers are important in these regions as they

are the lifeline of agricultural development and economic growth. They also

provide recreational facilities - fishing, boating etc. and support a large variety of

fauna and flora and they are part of the natural scenic heritage. Industrial

development, improvements in living standards and changes in agricultural

practices, especially since the 1960s, have resulted in an increased demand for

good quality water. However, such developments have resulted in the production

of increased amounts of sewage, industrial wastewater, agricultural discharges

and run-off. Due to continuous drought during the past five years, the run off

water in the rivers is very minimum. So the effluents penetrated into the soil and

caused ground water pollution. The quality of both soil and ground water has

deteriorated and directly impacted the agricultural production system. 1.3. Textile Dyeing Industry and Externality of Effluents on Land and Water - A Historical Perspective

The textile dyeing industries in the western Tamil Nadu comprising the districts of

Coimbatore, Erode and Karur occupy a major role in developing the local

economy as well as polluting the land and ground water sources extensively. For


4

instance there are about 720 bleaching and dyeing industries located in and

around Tirupur. The cluster of industries located in Tirupur alone release around

100 million litres of effluent per day, which is discharged into the river Noyyal

after treatment, partial-treatment or without proper treatment. Similarly, in Karur

the liquid waste water is discharged into the river Amaravathy and in Erode and

Bhavani Taluks, the effluent is let off into the river Cauvery. But due to the recent

enforcement of rules and stringent action initiated by Tamil Nadu Pollution

Control Board, almost all the industries have constructed either Effluent

Treatment Plant (ETP) or have become a member of the Common Effluent

Treatment Plant (CETP). Many industries, of late have installed Reverse

Osmosis (RO) plants to neutralize and recycle the effluents. However, some of

the industries with medium capacity are not having the adequate treatment plant

capacity because of high initial investment cost.

Some of the earlier studies conducted during different points of time have also

highlighted the ill-effects of the industrial effluents. One such study conducted by

Prabhakaran and Lakshmanan (1995) reported that waste water discharged from

textile industries affected the river basins of Noyyal, Bhavani and Amaravathi and

tributaries of river Cauvery rendering the downstream unusable for drinking,

bathing, irrigation and fish culture. Prabhakaran (1995) revealed that the effluent

of textile industries had affected the ground water quality through infiltration by

way of increased EC, SAR and RSC. The influence of such untreated effluents

on underground water was also reported by Muthusamy et al., (1987) and Gupta

and Jain (1992). The observation made by Paul (1995) also showed that the

discharging of chemicals in Tiruppur turned the ground water as well as the

surface water unsuitable for irrigation and domestic applications. All the above

studies have clearly pointed out the external effects of the industrial wastewater

on the local environment.


5

1.4. Effects of Effluents on Human and Animal Health The effluents released from the dyeing factories are variously coloured (dark

blue, black, red, green, etc.), aesthetically unpleasant, invariably turbid, not

conducive for aquatic organisms and unfit for drinking and other domestic

purposes leading to serious human health hazards like itching, cracks, cough,

fever, wheezing, etc., and in animals, weight loss, poor milk yield and reduced

reproduction rate. The ecological consequences of the effluents are associated

with the degradation of the quality of the surface water body that receives the

effluents, sedimentation of soil, poor ground water quality and air pollution.

1.5. Industrial Pollution, Crop Growth and Yield The crops cultivated in the area that is located nearer to the area where

wastewater stagnates have led to poor yield due to soil salinity and sodicity. Crop

establishment and productivity are greatly affected and none of the food crops

grow in these affected locations. Besides, the hygienic condition is also

disturbed. This inhibits the germination rate, plant height and the overall crop

stand significantly. It is understood that in many instances, the effluents

drastically reduced establishment of crop, vigor index in the seedlings of crops

like paddy, finger millet, cowpea, soybean and maize. As indicated elsewhere,

the textile dyeing industry consumes huge amount of freshwater and

consequently generates an equally large quantity of wastewater. The disposal of

sludge generated at large level from CETP is not a simple task. Large quantities

of sludge are also generated depending on the suspended solids in the

wastewater, the type and dosage of the coagulants and the degree to which the

solids are concentrated. This sludge contains salts and toxic metals and organic

impurities causing pollution to the ground water and land resources. Hence the

workers and the nearby population are at significant health risk. In addition, the

volume of accumulated sludge is increasing day by day. Hence the safe and


6

sound disposal of sludge is essential to mitigate the problem. The sludge

contains spent dyestuff and coagulants. It is slightly alkaline and having various

dyes and other organics.

Some of the recent reports have also highlighted the substantial degradation of

cropland, water and production agriculture in and around the areas, where

dyeing factories are located. Besides natural resources degradation, there were

occurrences of people suffering from health disorders and other morbidity related

incidences. However it is a matter of fact that the dyeing industries have created

opportunities for the people and labourers to get additional manpower

employment, increased wage earnings and enhanced family income. There

were also reports of migration of farm labourer towards dyeing industries in order

to get a better standard of living and modern way of life. Hence it is clear that

the dyeing industries have created both positive and negative externalities. It is a

matter of pride that the dyeing industries have contributed significantly in the

GDP growth of the country and add considerable amount of foreign exchange but

at the same time created resource degradation, health disorders, migration etc.

So it is of utmost importance to examine the long term sustainability of resources,

carrying capacity, ecology, environment as well as human welfare, while

addressing the issues of economic development. Considering the foregoing

issues in mind, a study was undertaken with the following specific objectives.

1.6. Objectives a. to analyze the external effects of industrial development on the quality

of land, water resources, crop land, crop output, employment, income, migration, health and other related socio-economic attributes.

b. to study the environmental implications of dyeing factories on the agricultural eco-systems and

c. to study the attitude of the stakeholders in conserving the valuable land and water resources and to suggest workable policy prescriptions for internalizing the externalities.


7

The methodology for this study was finalized in consonance with the objectives,

sampling design, data collection and tools of analysis. This section thus deals

with the criteria for the selection of study area, sampling design for determining

the responses under question, collection of data, analytical tools etc. 2.1. Selection of Study Area For the present study, only three districts namely Coimbatore, Karur and Erode

were purposively selected since the deterioration of land and ground water

qualities and its impact on cropland, irrigation and drinking water, crop

production, human and animal health, labour employment, farm income etc.,

were significantly pronounced only in these districts due to the high intensity of

dyeing and bleaching units. Besides, the time as well as the financial constraints

also restricted the extent of study area limited only to these three districts.

Tiruppur taluk in Coimbatore district, Karur taluk in Karur district and Bhavani and

Erode taluks in Erode district were selected based on the extent of external

effects on land and water. Four villages, two affected and two unaffected were

selected from each taluk. Based on the discussions held with the Government

departments like TNPCB, Revenue department, Agricultural department, experts

of textile and dyeing factory associations, the sample villages were classified as

affected and un-affected. The critical parameters which influence crop growth

like pH, EC, TDS, TSS, chloride and sulphate concentrations were also

considered while selecting the study villages. Since the impact of land and

ground water degradation was not uniform in terms of intensity across zones,

three locations were considered for this study. The unaffected study villages

selected were located near by the affected study villages to ensure otherwise

2. METHODOLOGY


8

similarity in agro-climatic conditions. In the second stage, two different

categories of the respondents namely, (i) farm households and (ii) industrial

workers were selected from each of the selected villages to represent all the

categories. From each taluk, four villages were purposively selected; two

villages to represent the affected category and the remaining two to compare the

impact with the unaffected category. Thus, altogether 16 villages were chosen

purposively. From each village 40 respondents were contacted for collecting the

data. Thus, the total sample size comprised of 640 respondents. The sample

households were subjected to detailed enquiries. The category of industrial

workers selected for the study included employees of the local organisations,

petty shop owners as well as the workers in the nearby dyeing, bleaching and

knitting units. The details of the taluks, blocks and the sample villages identified

for the study are reported in Table 2.1.

Table 2.1 Sample Districts, Taluks and Villages selected for the study

District Taluk Villages

Affected Unaffected

Coimbatore Tiruppur Veerapandi Muthanampalayam

Nallur Velampalayam

Karur Karur Panchamadevi Somur

Sanapparetti Pallapalayam

Erode Erode Periasemur Gangapuram

S.P.Agraharam Soorianpalayam

Erode Bhavani Bhavani Jambai

Andikulam Ooratchikottai


9

2.2. Data The data collection for the current investigation, unlike socio-economic research

was done with greater flexibilities and caution and logistic approaches and non-

conventional means of information gathering was resorted to for collecting the

oral history, the dynamics of land and ground water use, management, effluent

treatment methods adopted, etc. It was noticed during data collection that the

degradation of land and ground water quality has consequently resulted in

reduction of the cultivated area, poor soil and water quality, crop productivity,

reduction in farm labour employment, farm income etc.

Data were collected both from primary and secondary sources for the study. The

primary data collected for the study pertained to the year 2004-06. In the first

stage, the socio-physical environment of the study area was understood. Details

on the temporal distribution of physical, climatological, institutional, demographic,

socio-economic, cultural and historical components were collected from the

village records maintained by the grass root level functionaries of the

Government departments.

2.3. Method of Enquiry The micro economic behaviour of the village inhabitants depending on land and

ground water and the trend in income pattern, impact on water bodies, and the

indirect effects like equity, environmental sustainability and change in quality of

water and soil were studied. The impact of land and ground water quality

degradation on the crop production, environment, the averting and defensive

expenditures incurred, the respondents’ Willingness to Pay (WTP) for

replenishing the original status of their cropland or averting the influence were

derived through econometric analysis for micro level planning.


10

The study also explored linkages between crop productions. The farm level

losses were viewed primarily due to the degradation of land and ground water

quality, changes in agricultural production systems, labour employment, etc. The

study mainly focused its attention to analyze the changes in land and water

quality, share of income from farming and changes in income and employment

due to reduction in the cropland area over years. The study also attempted to

quantify how the earnings of the respondents varied as a result of the

degradation of land and ground water quality.

2.3.1. Externalities on Land The effluents let out by the industries have created external effects on land

namely, land quality deterioration, decline in crop land value, poor crop yield,

abandoning of farm lands, etc., in spite of expenditure incurred by the sample

respondents on averting and defensive inputs. The impacts on agricultural land

were assessed based on enquiry with respondents regarding declining cropland

area, labour employment, cropping pattern and expenditure incurred on

defensive and averting inputs and secondary information collected from

development departments.

2.3.2. Externalities on Water The discharge of improperly treated effluents had changed the water quality

significantly. The change in water quality led to poor land quality and resulted in

loss of crop yields, loss of manpower employment in agriculture, etc. The water

quality was assessed through the quality parameters such as taste, colour, odour

and turbidity. The water quality index was constructed on a three-point scale of

one for poor water quality, two for average water quality and three for good water

quality for each of the quality parameters namely, taste, colour, odour and

turbidity. The combined effect of all these qualitative attributes formed the said

index.


11

2.3.3. Averting and Defensive Expenditure The averting and defensive expenditures for land included the additional input

costs on seed materials, organic fertilizers, tank silt and green manures, soil

amendments like gypsum, etc. As such, farmers did not incur any expenditure

towards the treatment of water used for irrigation purposes, while the

respondents spent substantial amount on averting and defensive inputs for good

quality drinking water, which included fetching good quality water from the nearby

non polluted or less polluted areas. The opportunity cost of spending time to get

drinking water was also considered and quantified.

2.3.4. Externalities on Human Health The externalities caused by the changes in the qualities of surface and sub-

surface water included the common health disorders namely; fever, jaundice,

dysentery, headache, allergies and to some extent skin rashes, etc. The

expenditure incurred on human health included the cost of treatment namely,

physician cost, cost of medicine and also the opportunity cost of time spent for

taking treatment in health clinics.

2.3.5. Externalities on Animal Health Reduction in animal population, poor health status of animals, reduction in milk

yield, reduced calving rate were the external effects observed on animals due to

the degradation of land and water quality parameters. Expenditure on cost of

treatment and loss in value of milk were also recorded to study the impact on

livestock.

2.3.6. Externalities on Socio-Economic Characteristics Non availability of adequate period of farm employment, poor crop stand and

declining livestock income and reduction in farm and non-farm income, land


12

selling, diversion of farm lands for non agricultural activities and labour mobility

towards non farm sector were the consequences of pollution externalities

observed in the study villages.

2.4. Impact Assessment Techniques Impact assessment techniques viz., loss in productivity, agricultural and

aggregate damage functions, analysis for averting and defensive expenditures

on cropland and drinking water, hedonic pricing techniques for valuation of

croplands, and Contingent Valuation Techniques (CVT) to study the willingness

to pay of the individuals for improved environmental status were employed for

analyzing the data. The details of the models used for the analysis of the data

for studying the various attributes are presented below.

2.4.1. Damage Function The damage function links pollution to yield. There are two types of damage

functions observed in agriculture viz., agricultural damage functions and

aggregate value damage functions. (For details refer Cropper and Oaters, 1992).

For the present study, value damage functions were developed and employed.

While the agricultural damage function was limited to agricultural damages alone,

the aggregate damage function considered loss in productivity of cropland and

labour, crop output, livestock production, change in quality of water, damage on

human and animal health, etc. The damage function used for the study was of

the following form.

YDDMGE = f {AVERTECP, LQI, WQI, PCLDI}

AGDMGE = f {AEXHH, AEXDW, WQI, PCLDI}

Where,


13

YDDMGE - Yield Damage (Rs./ha)

AGDMGE - Aggregate Damage (Rs./household)

PCLDI - Proximity of Crop Land to Dyeing / bleaching Industries

AVERTECP - Averting Input Expenditure for Crop (Rs./ha)

LQI - Land Quality Index*

WQI - Water Quality Index*

AEXHH - Averting Expenditure on Human Health (Rs./household)

AEXDW - Averting Input Expenditure for Drinking Water (Rs./ha)

*Poor-1; Average-2; Good-3

It was expected that the averting expenditure for land inputs, the quality of land

and water would have a direct impact on the crop yield. It was also believed that

averting expenditures on land and drinking water might have negative influence

on aggregate damage. Similarly, the averting expenditures on animal and

human health would have negative association with household aggregate

damage. It was also assumed that the proximity of croplands to the dyeing or

bleaching units would influence agricultural as well as the aggregate damages

significantly. Hence, it was also considered as a variable for functional analysis.

Agricultural and aggregate value damages were computed as the differences in

the value of each affected farm over the value of the each item before the

occurrences of such damages. The agricultural and aggregate damage functions

were estimated employing log-log regression model.

2.4.2. Hedonic Model A hedonic model was chosen to study the influence of land and ground water

quality and their effect on cropland in deciding the final value of croplands.

Miranowski (1984), Bartick (1987) and Palmquist (1989) in their studies had

demonstrated the application of hedonic techniques to value croplands, cropland


14

sales and land improvements, respectively. Literature on hedonic pricing

methods also suggested that quality attributes of land, area under fallow,

distance between farm and the adjacent pollution source, crop productivity and

household characteristics would influence the value of agricultural land

significantly. The model used was of the following form.

VCLN = f {LQI, WQI, PCLDI, CINSY, SCATFA}

Where,

VCLN - Value of Crop Land (Rs./ha)

LQI - Land Quality Index (scale*)

WQI - Water Quality Index (scale*)

PCLDI - Proximity of Cropland to Dyeing and Bleaching Industries (distance in kilometers)

CINSY - Cropping Intensity

SCATFA - Share of Cropped Area to Total Farmland Area

(percentage)

*Poor-1; Average-2; Good-3

Several qualitative characteristics determine the value of land. Land and water

quality indices were considered in the model. Besides, the proximity of cropland

to the dyeing units, cropping intensity, percentage of cropped area to total

farmland area were expected to exert significant influence on value of land.

It was expected that LQI, WQI would have positive impact on land value and

there was no a priori assumption about the behavior of variable PCLDI. After

experimenting with various functional forms, the double log form of the

regression model was specified.


15

2.4.3. Models on Averting or Defensive Expenditure Averting and defensive expenditures were incurred to counteract the

consequences of pollution externalities. The mitigating expenditure involved

before the occurrences of pollution, investment made on inputs for reduction of

harmful effects after the occurrence of pollution and the expenditure incurred by

the respondents to protect their lands, animals, water resources from the health

hazards were included under this category. With and without concept was not

followed since the externality effects of land and water quality degradation was

found to occur throughout the village.

For instance, the cost involved in using additional quantity of seeds, organic

manures, application of soil amendments like gypsum, coir pith were considered

to be the land based averting expenditure due to the degradation of croplands

consequent to the degradation of the quality of land and ground water by the

discharge of untreated effluents. As stated earlier, the farmers in general did not

undertake any treatment for irrigation water. Expenditure incurred in getting

protected water from the nearby areas was considered under averting

expenditure for drinking water.

The actual expenditure incurred towards human health included the cost of the

physician, the cost of the medicine and the opportunity cost of time spent in

taking treatment. It was assumed that the expenditures were perfect substitutes

for estimating the ill effects of the dyeing factory effluents on human health.

The determinants of actual averting and defensive expenditures for croplands

were estimated for the farm respondents of all the villages considered for the

study and for drinking water, the determinants of averting and defensive

expenditures were calculated for the affected categories of the respondents. The

determinants of averting and defensive expenditure were studied by using the

following Model.


16

Y1 = f {FSIZE, EDN, SCATFA, PCLDI, LQI, QOMA, AWARE, WQI}

Y 2 = f {HI, EDN, HHSIZE, WQI, AWARE}

Where,

Y1 = Actual per hectare expenditure on averting actions for croplands (Rs. /ha)

Y 2= Actual household expenditures on averting actions for drinking water (Rs. /household)

HI - Household Income (in Rs.)

FSIZE - Farm Size (in ha)

EDN - Education (scale*)

SCAFTA - Share of Cropped Area to Total Farmland Area (per

centage)

QOMA - Quantity of Organic Manure Applied (t/ha)

WQI - Water Quality Index (scale**)

LOI - Land Quality Index (scale**)

AWARE - Awareness of Environmental Externality (scale***)

HHSIZE - Size of the Family (numbers)

PCLDI - Proximity of Cropland to Dyeing unit (in km)

________________________________________________ * Illiterate-0; Primary-1; Secondary-2; Graduates-3. ** Poor-1; Average-2; Good-3 *** Poor-1; Medium-2; High-3. The model for the actual per hectare expenditure on averting actions of cropland

as well as for drinking water was constructed for the sample respondents. The

household income, age and educational level were expected to have a positive

influence on averting actions of cropland. It was also hypothesized that

education would also influence the averting actions of the respondents positively.


17

The proximity of the cropland to the dyeing unit was also considered because it

was thought that it would influence averting actions significantly.

2.4.4. Contingent Valuation Technique (CVT) The CVT determines consumer’s preferences by constructing hypothetical

markets. CVT arrives at the Willingness to Pay (WTP) to continue receiving

benefits. An attempt was made to examine the economic valuation of the land

and water quality using CVT. Willingness to Pay was used to assess the value

of changes in the quantity and quality of agricultural land, irrigation and drinking

water in the study area. The survey schedule was designed in such a way that it

did encapsulate the knowledge and the attribute of the respondents towards the

land and water quality degradation, their perception and interest in correcting

actions. Information was also elicited to study the dependence of the households

on agriculture for employment, income, etc., problems faced by them in the

collection of water, measures if any taken by the users when shortage was

realized and their WTP for protecting irrigation water.

In order to get responses for the WTP, the following hypothetical situation was

created. The households were asked what was their major requirement to

improve their agricultural activities. Their response was good quality irrigation

water and also they wanted either to deepen their well or to draw water from the

unaffected locations. The households were asked to assume that local

institutions sponsor a part of the expected expenditure that would be incurred.

The capital cost was taken to be rupees one lakh. For meeting the rest of the

expenses, each household’s WTP towards its capital in monetary terms and their

mode of payment was sought. (Note: The capital cost were fixed based on the

information obtained during the survey from the farmers, experts and field level

functionaries, income, living standards of the village inhabitants, etc).


18

The WTP of the households towards the capital cost for the deepening or

drawing good quality water from the nearby sources was added after annualizing

the capital investment, taking a life annualized capital cost time of 15 years for

the capital investment at 12 per cent rate of interest. Similarly, using the wage

rate per day as prevalent in the study areas during the time of survey, the labour

time or days, the villagers who were willing to contribute towards the capital cost

in their region were converted in to monetary values. Hence WTP for good

quality water and ecological functions was the sum total of WTP for annualized

capital and the mode of payment.

The explanatory variables used for analyzing maximum WTP were; age of the

respondent, household composition, educational level, per capita agricultural

land, per capita standard cattle unit, interest in improving agricultural activities,

perception of quality of degradation of land and water, distance of dyeing units

from the farm, etc.

WTP = f {AGE, HHSIZE, HHEDN, HHINCOME, PCAL, PCSCU,

IIAGA, PLGWD, PCLDI}

WTP - Willingness to Pay (Rs. / household)

AGE - Chronological Age of the Respondent (in years)

HHSIZE - Size of the Household (in number)

HHEDN - Household Head’s Education (scale)*

HHINCOME - Household Income (Rs. /annum)

PCAL - Per Capita Agricultural Land (in hectare)

PCSCU - Per Capita Standard Cattle units (number)

IIAGA - Interest in Improving Agricultural Activities (scale)**


19

PLGWD - Perception of Land and Ground Water Degradation

(scale)***

PCLDI - Proximity of Cropland to Dyeing units (in km)

* Illiterate-0; Primary-1; Secondary-2; Graduate-3 ** Not interested-1, Somewhat-2, Fairly-3, Verymuch-4 *** Not at all-0; Somewhat-1; Very much-2

2.4.4.1 Expected Relationship The economic theories and existing literature on CVT suggest that WTP for

improved environmental quality is directly related to the age of the respondent. It

was also expected that with an increase in the number of members in the

household, dependency on input for agricultural land would also increase.

Higher the perception of degradation as well as the interest in improving the

agricultural activities, the more was expected about the WTP. It was also

expected that a person with higher education would be more concerned with the

protection of the environment. The nature of the relationship also depended on

other factors like income of the household, etc. Similarly, distance between the

farm and the dyeing units were yet another variable expected to affect WTP

significantly. Another important variable having direct link with the degradation of

the quality of water was the livestock number, which was taken as per capita

standard cattle units, which was assumed to have a positive coefficient

particularly for the farm households. It was also expected that the per capita

agricultural land would be correlated positively with WTP. Similarly, it was

assumed that the proximity of the cropland to the dyeing unit would capture the

effect of distance on WTP. A person residing nearer to the dyeing unit was

expected to pay more for the improvement of agricultural activities due to the

maximum realization of benefits.


20

2.4.5. Impact of effluent on the quality of groundwater and soil characteristics In order to assess the changes in the quality of groundwater and the physico –

chemical properties of soils, both water samples and soil samples were collected

from selected villages of Tiruppur, Karur, Bhavani and Erode taluks and analyzed

for various physico chemical properties.

2.4.5.1. Collection of water samples Groundwater samples were collected from the earmarked wells as per the

standard procedure. Containers were rinsed 3 or 4 times with the water sample

before the sample were drawn. Collected water samples were stored in the

refrigerator at 4ºC for further analysis. To avoid changes from chemical and

biological activities minimum time were given between the time of collection and

laboratory evaluation. The collected water samples were subjected to various

physico- chemical characteristics as per the methods prescribed in Table.2.2.

2.4.5.2. Collection of soil samples The soil samples were collected from the sample villages of four taluks as per the

standard methods described below.

The land was selected at random and the surface litters were removed at the

sampling spots. Then the auger was used to take the sample upto a depth of 15

cm and samples were drawn. At least 10 to 15 samples were collected from

each sampling unit, mixed thoroughly and from the composite samples,

representative samples were taken for further processing. The sample collected

from the field was dried in shade by spreading on a clean sheet of paper after

breaking the large lumps. Then the soil material was sieved through a 2mm


21

sieve. The material passing through the sieve was collected and stored in a clean

container with proper labeling for laboratory analysis.

Table 2.2. Standard methods followed for the analysis of water samples

Estimation Remarks References

pH 1:2.5 organic waste: distilled water using pH meter

Falcon et al. (1987)

EC (dS/m) 1:2.5 organic waste: distilled water using conductivity bridge.


Chloride (mg l-1) Mohr’s method Jackson (1973)

Sulphate (mg l-1) Turbidimetric method using spectrophotometer at 420 nm

Jackson (1973)

Calcium (mg l-1) Versenate titration method Jackson (1973)

Magnesium (mg l-1) Versenate titration method Jackson (1973)

BOD (mg l-1) Standard procedure APHA (1989)

COD (mg l-1) Standard procedure APHA (1989)

Heavy metals (mg l-1)

AAS Lindsay and Norwell (1973)

The processed soil samples were subjected to various physico- chemical

characteristics as per the methods prescribed in the following Table 2.3.

Table 2.3. Standard methods followed for the analysis of Soil samples

Estimation Remarks References

pH 1: 2.5 organic waste: distilled water using pH meter



22

water using pH meter

EC (dS/m) 1: 2.5 organic waste: distilled water using conductivity bridge.


Preparation of di acid extract

H2SO4 : HClO4 @5:2 Biswas et al. (1977)

Preparation of triacid extract

HNO3 : H2SO4 : HClO4 @ 9:2:1

Piper et al. (1966)

Available Nitrogen (kg/ha)

Alkaline permanganate method

Subbiah and Asija (1956)

Available Phosphorus (kg/ha)

Colorimetric method Olsen et al. (1954)

Available Potassium (kg/ha)

Neutral normal ammonium acetate extract

Stanford and English (1949)

Heavy metals AAS Lindsay and Norwell (1973)

The data collected from the sample respondents of the study villages were

analyzed using the statistical tools explained in section 2 of this report and the

results are presented in consonance with the specific objectives of the study.

4. MAJOR FINDINGS OF THE STUDY


23

In this section, results are discussed separately for the sample taluks namely,

Tiruppur, Karur, Erode and Bhavani.

4.1. Tiruppur 4.1.1. Demographic Details The family size of the respondents is presented in the Table 4.1. The overall

family size of the respondents in the affected village was 3.87 whereas in

unaffected category it was 3.73. The overall family size of the study villages of

Tiruppur taluk was 3.80.

Table 4.1. Family Size (Numbers)

Sl. No. Category Average Size

1. Affected 3.87

2. Unaffected 3.73

Overall 3.80

4.1.2. Distribution of Respondents Based on Education Knowledge about educational status of the respondents is indispensable to

decide the awareness and the attitude of people about their surroundings. From

Table 4.2, it is clear that about 75 per cent were literates in the affected villages

while in the unaffected villages it was only 69 per cent. Out of the 75 per cent,

about 23 per cent had completed at least their secondary education. But, in the

unaffected area out of 69 per cent of the literate population over 23 per cent had

completed their secondary education. The vast employment opportunities

available in the industrial sector might have been the main reason for not

continuing education after secondary level. It could be noted that 15 to 17 per

cent of the respondents had college level education in commerce and fashion

technology for getting employment in the dyeing, bleaching and knitting


24

industries. With the exception of primary education and illiterates all other

categories had similar levels of coverage in the affected and unaffected localities.

Table 4.2. Educational Status

Affected Area Unaffected Area Sl. No.

Particulars

Number Percentage Number Percentage

1. Illiterates 57 24.57 70 31.25

2. Primary 52 22.41 34 15.18

3. Secondary 53 22.84 53 23.66

4. Higher secondary 23 9.91 22 9.82

5. Graduates 47 20.27 45 20.09

6. Literates 175 75.43 154 68.75

Total 232 100.00 224 100.00

4.1.3. Land Holding Details The land area possessed by sample respondents and the area under cultivation

are presented in Table 4.3. The land area comprises of wet, dry and garden

lands. It is obvious from the table that there was no wetland. The area owned

was 1.72 and 1.80 hectares in the affected and unaffected areas. Whereas, the

average area under cultivation was 1.03 ha in the affected areas and 1.15 ha in

the unaffected areas. The average garden land owned by a household in the

affected category was 1.33 ha whereas it was 1.65 ha in the unaffected

category. The area under dry land accounted for 22.59 per cent and 8.60 per

cent of total area owned in the study villages. The percentage of area under

cultivation accounted for only 8.04 and 2.35 per cent of the total area cultivated in

the affected and unaffected areas.


25

Table 4.3. Land Holding Details

(Average ha)

Particulars Affected Villages Unaffected Villages

Area Owned Area Cultivated

Area Owned

Area Cultivated

Garden land

1.33 (77.41)

0.95 (91.96)

1.65 (91.40)

1.12 (97.65)

Dry land 0.39 (22.59)

0.08 (8.04)

0.16 (8.60)

0.03 (2.35)

Total 1.72 (100.00)

1.03 (100.00)

1.80 (100.00)

1.15 (100.00)

Figures in parentheses indicate percentage to total

4.1.4. Details of Irrigation Formerly, the river Noyyal, open wells and bore wells were the chief sources of

irrigation in the study villages. Now, as the river Noyyal is polluted, the farmers

depend on only wells for irrigation. The details of the irrigation wells are presented

in Table 4.4. The total number of open wells in the affected area was 59 while it

was 64 in the unaffected area. The average depth of the wells in the affected area

was 54.32mts. The number of wells abandoned was nine (15.25 per cent) in the

affected category where as it was only five (7.81 per cent) in the unaffected

category. This was due to the non-availability of good quality water in shallow

depths and improper maintenance. The quality of water was affected due to the

dyeing factory effluent in and around the study villages. The number of bore wells

in the affected area was 15 where as it was only seven in the unaffected areas. It

was reported that the dyeing factory owners had dug bore wells to a depth of

around 300 mts. This had led to depletion of the ground water table also. So,

some farmers had dug deeper bore wells (up to 250 mts) in order to sustain their


26

agricultural activities. They were of the view that water at greater depths would be

of better quality with less pollutants.

Table 4.4. Details of Irrigation Wells

Sl. No.

Particulars Affected Area

Unaffected Area

1. Total number of wells in the sample farms 59 64

2. Average depth of open well (in mts.) 54 23

3. Percentage of wells with good quality water throughout the year

1.69 40.63

4. Percentage of wells with water only during rainy season

83.05 51.56

5. Number of bore wells in the sample farms 15 7

6. Average depth of bore wells (mts.) 221 149

7. Water quality* (Per centage)

Good - 19.23

Medium 27.27 80.77

Poor 72.73 - *As perceived by the respondents

4.1.5. Area Irrigated by Different Sources of Irrigation The details on sources of irrigation are reported in Table 4.5. In both the affected

and non- affected villages there was no area under canal irrigation. Area

irrigated by open wells in the unaffected area was about 47 per cent, whereas it

was only 12.04 per cent in the affected area. About four per cent of the farmers

in the affected area transported water by lorries to maintain their existing coconut

gardens whereas in the unaffected villages it was only 0.27 per cent. About 58

per cent of the area was under rain fed cultivation in the affected area, which was

about 23 per cent higher than that of the unaffected villages.


27

Table 4.5. Sources of Irrigation

Sl. No.

Sources of Irrigation Affected (%)

Unaffected (%)

1. Open well 12.04 46.24

2. Bore well 21.28 3.28

3. Open well + Bore well 5.18 15.06

4. Well + Purchased water 3.70 -

5. Purchased water - 0.27

6. Rain fed 57.79 35.15

Sources of Irriga tion

12.04

21.28

5.18 3.700.00

57.79

46.24

3.28

15.06

0.00 0.27

35.15

-10.00

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

Open well Bore well Open well +Bore well

Well +Purchased

water

Purchasedwater

Rain fed

Sources of IrrigationAffected (%)Unaffected (%)

4.1.6. Area and Productivity of Different Crops: A Detailed Analysis The area and productivity of the crops grown in the study area are reported in

Table 4.6. Though the area under coconut in both affected and unaffected

villages was about 35 per cent, the productivity in the affected area was only

4,531 nuts whereas in the unaffected area it was about 12,605 nuts. This huge

Fig.13 Sources of Irrigation – Tiruppur Taluk


28

difference was due to the deterioration of land and water quality. The same trend

was observed in other crops too. The difference in yield ranged between (-) 8.23

and (-) 65 per cent. It was revealed by farmers that during the past years crops

like tobacco, turmeric, sugarcane, paddy, cotton, coconut, vegetables and

banana were cultivated. However, vegetables and cash crops are not at all

present in the current crop plan. The poor quality soil and water has driven the

farmers to cultivate only rain fed cholam (fodder cholam) and farmers were

maintaining their existing coconut gardens with great difficulty.

Table 4.6. Area and Productivity of Crops

Affected Villages

Unaffected Villages

Difference Sl. No

Crops

Area (%)

Yield (t/ha)

Area (%)

Yield (t/ha)

Yield Percentage

1. Fodder Cholam

60.38 6.80 51.58 7.41 0.61 (-)8.23

2. Coconut* 34.07 4531 35.29 12605 8074 (-)64.05 3. Grain

Cholam 4.81 0.99 2.19 1.82 0.83 (-)45.60

4. Banana 0.73 86.45 2.19 96.21 9.76 (-)10.14

5. Vegetables - - 6.57 65.65 - -

6. Groundnut - - 1.64 2.47 - -

7. Turmeric - - 0.54 3.50 - - * Yield in nuts/ha

4.1.7 Proximity of Cultivated Lands to Dyeing Industries The distance between the respondent’s farm holdings and the dyeing industries

was less than a kilometre (0.78 km). Out of 60 respondents interviewed, 59 were

of the opinion that dyeing was their main activity in the villages (Table 4.7).

About 34 respondents opined that knitting was also carried out in their

area and 30 respondents in Nallur village expressed that bleaching was


29

the main activity in their locality. The period of operation of factories ranged

from 10 months to 12 months.

Table 4.7. Location of Dyeing Industries

Sl.No Particulars Affected Villages 1. Proximity 0.78 2. Average months in operation / year 10-12

4.1.8. Farmers’ Opinion about Decline in Agricultural Activities The farmers’ perceptions about the decline in agricultural activities are reported

in Table 4.8. Out of the 60 respondents interviewed, about 68 per cent were of

the view that the failure was due to water scarcity, 60 per cent opined that it was

due to labour scarcity and 78 per cent expressed that it was due to poor water

quality. Inadequate water supply, decline in water table, reduction in agricultural

income, poor crop stand were the other reasons for the failure of agricultural

activities. Table 4.8. Opinion of Sample Farmers on Decline in Agricultural Activities (Per cent)

Sl.No Reasons for decline in agricultural activity

Affected Category

1. Poor water quality 78.33 2. Water scarcity 68.33 3. Labour scarcity 60.00 4. Poor crop stand 36.67 5. Decline in agricultural income 30.00 6. Decline in water table 18.33

Fig.14 Opinion of Sample Farmers on Decline in Agricultural Activities –

Tiruppur Taluk


30

Opinion of Sample Farmers on Decline in Agricultura l Activities

78.33

68.33

60.00

36.6730.00

18.33

0.00

20.00

40.00

60.00

80.00

100.00

Poor waterquality

Waterscarcity

Labourscarcity

Poor cropstand

Decline inagricultural

income

Decline inwater table

Affected ca tegory

4.1.9. Change in the Value of Agricultural Lands It is obvious from Table 4.9 that in the unaffected villages, the value of

agricultural land had increased gradually. In the affected villages, because of the

increasing levels of textile industry activities during the last few decade, the

demand for land increased and most of the farmers sold their crop lands for

house sites and industrial activities. Due to shortage of lands, the value of crop

lands increased six to nine times in the affected areas compared to unaffected

areas. During the year of survey the land value was Rs.75, 17,033 per ha in the

affected villages whereas it was only Rs 12, 90,575 per ha in the unaffected

villages. The real estate business has also flourished well in this taluk in the

recent past since the demand for land exceeds the supply.

Table 4.9. Change in Value of Agricultural Lands (Rs/ha) Sl. No Particulars Affected villages Unaffected

villages


31

1. 5 years back 37,33,816 4,17,224 2. 2003 – 04 75,17,033 12,90,575

4.1.10 Employment Pattern The employment pattern of the household members is reported in the Table 4.10.

Among the 60 respondent households, 100 persons were earning members in

the affected villages whereas it was 111 in the unaffected villages. In the

affected villages, none of the households depended on farm activities alone. The

employment of respondents in on - farm activities was reported to be higher

(28.33 per cent) in the unaffected villages where as it was only about two per

cent in the affected villages. Employment through the combination of both on -

farm and non - farm activities was observed to be much higher (81.67 per cent)

in the affected villages, whereas it was 63.33 per cent in unaffected villages.

Table 4.10 Occupational Distribution of the Households

S.No Particulars Affected Villages Unaffected Villages

Number Per cent Number Per cent1. Crop alone - - 4 6.67

2. Crop + Dairy activities 1 1.67 17 28.33 Total households engaged in on-farm activities alone

1 1.67 21 35.00

3. On-farm+ Non-farm activity

49 81.67 38 63.33

4. On-farm + Off-farm +Non farm activity

4 6.67 1 1.67

5. Non –farm activity 6 10.00 - - Total 60 100.00 60 100.00 Earning members in the sample households (in Numbers)

100 111


32

0.00 1.67

81.67

6.67 10.00 6.67

28.33

63.33

1.67 0.00

0.00

20.00

40.00

60.00

80.00

100.00

Perc

enta

ge

Affected Unaffected

Fig.15 Occupational Distribution of Households - Tiruppur Taluk

Crop alone Crop + dairy activities On farm+ non farm

On farm+off farm+non farm Non farm activity

4.1.11 Income The details of income generated by the household are reported in Table 4.11. It

is understood from the table that in the affected villages about 11.00 per cent of

the average annual income was earned through non farm activities like dyeing,

knitting, renting out houses and so on whereas there was no sample household

depending on crop activity alone. In the unaffected villages, none of the farm

households depended on non - farm activities alone. The average annual

income earned through the combination of on- farm and non-farm activities was

found to be higher (84.98 per cent) in the affected villages compared to 70 per

cent in the unaffected villages. In the unaffected area, the income from the on

farm activities alone was higher (22.50 per cent) when compared to the affected

area (0.84 per cent). The combination of all the three activities (on-farm, off-

farm and non-farm) was observed to be much higher (3.44 per cent) in the

affected villages than in the unaffected villages (0.71 per cent). The average


33

annual income of households were Rs.1,31,264 in affected villages and

marginally higher at Rs.1,45,023 in unaffected villages.

Table 4.11 Pattern of Income of the Sample Households (Average Annual Income - in Rs.)

Sl.No

Particulars Affected Villages Unaffected Villages

Amount Per cent Amount Per cent 1 Farm only - - 9,324 6.43 2. Farm + Dairy activities 1,100 0.84 32,630 22.50

Average annual income earned from on-farm activities alone

1,100 0.84 41,954 28.93

3. On-farm +Non-farm income

1,11,547 84.98 1,02,046 70.37

4. On-farm + Off-farm +Non farm income

4,517 3.44 1,023 0.71

5. Non-farm income 14,100 10.74 - - Average Annual income per household

1,31,264 100.00 1,45,023 100.00

0.00 0.84

84.98

3.4410.74 6.43

22.50

70.37

0.71 0.00

0.0010.0020.0030.0040.0050.0060.0070.0080.0090.00

Perc

enta

ge

Affected Unaffected

Fig.16 Pattern of Income - Tiruppur Taluk

Farm only Farm + Dairy activities

On farm+ non farm income On farm+off farm+non farm income

Non farm income


34

4.1.12. Migration The migration details are presented in Table 4.12. Earning members in about 75

per cent of the households in the affected villages have migrated whereas in the

unaffected villages, it was only 11.67 per cent. In the affected area, among those

migrated the permanent migration was high (about 94 per cent). The reasons for

migration were poor household income, to earn more, poor water quality,

restricted crop activities etc. Out of these reasons, poor income from agricultural

operations alone accounted for 71.43 per cent. Next was their desire to earn

more from other sources (about 61.90 per cent). In the unaffected villages

desire to earn more was the predominant reason (62.5 per cent).

Table 4.12. Migration Details (Per cent)

Sl.No Particulars Affected Area

Unaffected Area

1. Percentage of migration 75.00 11.67 2. Average percentage migration

from sample Household 25.03 26.86

3. Per centage of permanent migration by family members

93.65 87.50

4. Average number of days migration

83.72 (305.57)

78.28 (285.71)

Sl.No Particulars Affected

Area Unaffected

Area Reasons

1. Poor household income from agriculture 71.43 12.5 2. To earn more 61.90 62.5 3. Poor water quality 26.98 - 4. Labour problem 9.52 - 5. Employment in public institutions 1.59 - 6. Education 14.29 25.0 7. Restricted crop activity 39.68 -

Note: Figures in parentheses denotes the average days of migration in a year.


35

4.1.13. Sale of Assets The extent of sale of assets by the farmers during the last 10 years is reported in

Table 4.13. About 17 per cent of the respondents in the affected area sold at

least part of their land during the last ten years but none of the respondents in

the unaffected area had sold their cropland during the same period. The reasons

for the sale of lands were poor crop income, migration, poor water quality and

water scarcity. The croplands are now converted as house sites. Forty five per

cent of the respondents in the affected villages had sold their livestock due to

various reasons like reduced milk yield, loss in weight, water scarcity and

inadequate man power (for maintenance). In the unaffected villages 41.67 per

cent of the respondents sold their livestock. Farmers who sold their livestock only

due to drying of the cattle accounted for 21.67 per cent, followed by labour

problem with 10.00 per cent.

Table 4.13. Sale of Assets

Sl. No

Particulars Affected Area

Unaffected Area

I Sale of Land

1. Percentage of respondents sold their land 16.67 -

2. Area of land sold (%) 4.89 -

3. Value of the sold land (Rs./ha) 50,087 -

Percentage of respondents sold the animals

45.00 41.67

II Reason for Sale of Animals

1. Water scarcity 10.00 6.67

2. Loss in weight 3.33 3.33

3. Reduction in milk yield 11.67 -

4. Labour problem 3.38 10.00


36

5. Drying / Aged 16.67 21.67 4.1.14. Farm Level Availability of Livestock Results presented in table 4.14 would reveal that the number of animals in the

unaffected villages was relatively high compared to the affected villages. Many

of the respondents were rearing sheep in the unaffected villages (about 85

numbers) to supplement household income.

Table 4.14. Availability of Livestock (Average/household)

Sl.No Particulars Affected village Un affected village

1. Cow 1.25 1.87

2. Buffalo 0.67 1.13

3. Bullock 0.07 0.07

4. Sheep 0.03 1.42

5. Calf 0.12 0.08

4.1.15. Sufferings of Human and Animals The table 4.15 reveals the fact that no one has reported any sufferings in the

unaffected villages. In the affected villages, an individual spends on an average

of Rs.136.67/- towards physician cost and Rs.30/- towards medicine annually. In

case of animals, the loss of milk production was about nine per cent of the

average production. The common ill effects noticed were weight loss, poor

calving and reduction in milk yield in animals.


37

Table 4.15. External Effects on Human and Animals

Sl.No. Particulars Affected Villages

1. Cost to Physician (Rs./ annum / individual) 136.67 2. Cost of medicine (Rs. / annum / individual) 29.97 Animals

1. Loss in milk production (Rs./ annum) 1910 2. Percentage loss in milk production 9.06

4.1.16. Drinking Water Supply The results presented in Table 4.16 reveals that the only drinking water source in

the affected villages was the tap water. The frequency of water supply was once

in two days in Nallur and once in 20 days in Veerapandi whereas in the

unaffected areas, the people were using their own well water and to some extent

the tap water. In affected villages, all the respondents depended on the public

taps (municipality water) for drinking compared to 55 per cent of farmers in the

unaffected group. The respondents at Veerapandi were paying Rs.10/- per

family per month for drawing water from the public tap. In affected villages,

purchase of a tanker water at Rs.900/- was not uncommon and no respondent

was found using their own well water while in unaffected areas, 45 per cent were

using their own well water for household purposes.

In the affected villages, people were paying Re.0.75 for 12 liters of potable water

for domestic use. Average water use per month was high in unaffected locations

(6,660 litres/household) when compared to affected areas (4,745

litres/household). The distance to fetch water was also more (0.71kms) in

affected villages than in the unaffected villages (0.62kms). The problem for

drinking water exists for the past 15 years due to non availability of potable

water.


38

Table 4.16. Drinking Water Quality

Affected village Un affected village Sl.No

Particulars Number of

Respondent

Expense (Rs./

family/ annum)

Number of Respondent

Expense (Rs./

family)

1. Source of drinking water Mettupalayam water Mettupalayam water and well

a. Public Tap* 60 120 33 -

b. Purchase of lorry water 9 5,400** - -

c. Well water - - 27 -

2. Average Water Requirement and Expense to buy / fetch water

a. Monthly water use (litres /household)

4,745 - 6,660 -

b. Monthly water Requirement (lit / household)

14,040 900 - -

c. Amount paid for 12 litres of water (Rs.)

- 0.75 - -

3. Distance to fetch drinkable water (km)

0.71 0.62

* Municipality water supplied in the public taps ** purchasing lorry water six times per year 4.1.17. Details of Well Water Quality The well water quality in the affected village was compared with unaffected

category and results are reported in Table 4.17. The water quality parameters

like taste, colour, turbidity and odour were found to be medium. But in the

affected villages, the taste of the well water was poor (98.25 per cent) in summer

whereas in the rainy season it was good. In 98 per cent of the wells the colour of

water was red with yellow and black tinge. Turbidity was low (91 per cent) in

both the seasons. Medium to moderate chemical odour was reported in all these

wells.


39

Table 4.17. Details of Well Water Quality (Per cent)

Sl.No Water Quality Characteristics Affected Villages

Unaffected Villages

1. Taste – Summer Season Poor 98.25 - Medium 1.75 2.00 Good - 98.00 Rainy Season Poor 54.39 - Medium 42.11 - Good 3.51 100.00

2. Colour – Summer Season

High 98.25 -

Medium - - Low 1.75 100.00 Rainy Season High 98.25 - Medium - - Low 1.75 100.00

3. Turbid – Summer Season

High 8.77 -

Medium - - Low 91.23 100.00 Rainy Season High 8.77 - Medium - - Low 91.23 100.00

4. Odour – Summer Season

High 100.00 -

Medium - - Low - 100.00 Rainy Season High 100.00 - Medium - - Low - 100.00

4.1.18. Opinion of the Farmers about Irrigation Water In one of the unaffected village, Muthanampalayam, the respondents were getting

water from PAP canal (Parambikulam Aliyar Project) once in 2 years (4 times) for

irrigation. The respondents of the affected village Nallur were getting canal water

only during the rainy season and the quality of water was reported to be medium

(Table 4.18).


40

Table 4.18. Attitude of Farmers towards Irrigation Water

Affected Village Un affected Village** Sl. No

Particulars Numbers Per cent Numbers Per cent

I. Availability 1. Rainy season 30* 50.00 30*** 50.00 2. Through out year - - - - II. Quality 1. Poor - - - - 2. Medium 30 50.00 30 50.00 3. Good - - - -

Total 30 50.00 30 50.00 * Canal water available only in Nallur (Affected village); ** PAP canal once in 2 years –4 times (Muthanampalayam) . *** 30 respondents in Velampalayam

4.1.19. Willingness to Pay Out of 60 respondents interviewed in the affected villages, only 51.67 per cent

were willing to pay for improving the soil and water quality parameters. About 40

per cent of the respondents were under the category of paying Rs.25000 to

Rs.50000. Nobody was willing to pay above Rs.75000. Most of the respondents

were willing to pay in quarterly (16.67 per cent) and half yearly (16.67 per cent)

installments.

Table 4.19. Willingness to Pay

Sl.No. Particulars Number of Respondents

Per cent

1. Households willing to pay 31 51.67 2. Households not willing to pay 29 48.33 3. WTP Less than Rs.20, 000 2 3.33 Rs.20, 001 – Rs.25,000 3 5.00 Rs.25, 001 – Rs.50,000 24 40.00 Rs.50, 001 – Rs.75,000 2 3.33

4. Mode of Payment Single payment 4 6.67 Quarterly installments 10 16.67 Half yearly installments 10 16.67


41

Annual installments 7 11.67

Willingness to Pay

3.33 5.00

40.00

3.33

0.00

10.00

20.00

30.00

40.00

50.00

Less than Rs.20, 000 Rs.20, 001 – Rs.25,000 Rs.25, 001 – Rs.50,000 Rs.50, 001 – Rs.75,000

Amount willing to pay

4.1.20. Averting Expenditure The additional expenditure incurred by the farmers with the expectation of

obtaining the desired yield is reported in the Table 4.20. The averting

expenditure for the crop coconut and fodder cholam was Rs.5605 and 1041

respectively for an area of one hectare. The amount was spent mainly on

irrigation and application of organic manure. Some farmers cultivating fodder

cholam had taken even second sowing. On an average, about Rs.389 was lost

per annum in the process of bringing drinking water from the nearby resources,

where the quality of water was found good.

Table 4.20. Averting Expenditure for Crops

Sl.No. Particulars Expenditure (Rs./ha)

1. Coconut 5605

2. Mancha cholam (Sorghum) 1041

3. Opportunity cost of procuring drinking water (per household)

389

Fig. 17 Willingness to Pay – Tiruppur Taluk


42

Soil and Water Sample Analysis 4.1.21. Physico - Chemical characteristics of water samples collected at Tiruppur before monsoon In Tiruppur taluk, water samples were collected before and after monsoon and

the results are presented in the tables 4.21 and 4.22.

The water samples collected from Tiruppur taluk before monsoon showed not

much variation in pH both in affected and unaffected villages recording 7.53 –

8.61 and 7.6 – 8.84 respectively. In both the samples, a slight increase in pH

above the critical limit of 6.5 – 8.5 was recorded. The EC Value is found to be

higher in affected regions which recorded 0.99 to 7.33 ds/m compared to

unaffected regions which has 0.58 –1.27 ds/m. which outranges the critical value

of 1 ds/m for drinking but lies within the maximum permissible limit of 2.25 ds/m

for irrigation; Whereas, the EC of the well water from affected villages exceeded

the critical limit for irrigation thus indicating its unsuitability for drinking.

The chloride content accounted maximum of about 205.9 – 4224 mg l-1 in

affected regions compared to unaffected regions, which is 91 - 511.2 mg l-1.

Chloride content in affected regions is nearly 8 fold higher than the limit of 500

mg l-1 prescribed for irrigation; whereas, the sulphate content of the water

samples collected from both affected and unaffected villages are well below the

critical limits.

The water samples collected from affected and unaffected villages recorded the

calcium content ranging from 580 – 3100 mg l-1 and 310 – 1850 mg l-1

respectively, which exceeded the critical limit of 100 mg l-1. The magnesium

content was found to be maximum in affected regions (20 – 65 mg l-1 ) compared

to the unaffected regions which ranged between 12– 48 mg l-1. In addition, the

BOD and COD of the water samples collected from affected regions ranged


43

between 45 – 85 mg l-1, and 48-110 l-1 respectively; whereas the samples from

unaffected regions recorded a BOD of 48-110 l-1, and a COD of 95 – 380 l-1.

Both the regions exceeded the critical limit of BOD for drinking water, 6 l-1 . The

COD content of both the samples also higher than the critical limit of 250 l-1 to be

followed for irrigation. The Sodium Absorption Ratio (SAR) of water samples of

affected villages ranged between 46 - 52, which are higher than the maximum

limit of 26 whereas, the SAR of unaffected villages ranged between 24 – 29.

Further, the results on heavy metal analysis of water samples also showed the

presence of heavy metals such as chromium, nickel, cadmium and lead to some

extent. Water samples of affected villages recorded BDL - 0.10 mg l-1 chromium,

0.25 - 0.70 mg l-1 of lead, BDL - 0.05 l-1 of cadmium and 0.2 – 0.50 l-1 of nickel;

whereas the unaffected samples had BDL - 0.05, BDL - 0.40, BDL - 0.01 and

BDL - 0.25 mg l-1 of Cr, Pb, Cd and Ni respectively. Chromium, cadmium and

nickel contents of both the samples lies within the maximum permissible limits of

0.05 mgl-1, 0.10, and 0.05 mg l-1 respectively whereas, the lead content of both

the samples exceeded the prescribed limit 0.01 mg l-1 for drinking water. Table 4.21. Physico - Characteristics of water samples collected at Tiruppur

Taluk (Before monsoon) Parameters Affected Villages Unaffected

Villages pH 7.53 – 8.61 7.60 -8.84 EC (ds/m) 0.99 – 7.33 0.58 – 1.27 BOD (mg/l) 45 – 85 48 – 110 COD (mg/l) 95 – 285 95 – 380 Chloride (mg/l) 205.9 - 4224 91 – 511.2 Sulphate (mg/l) 10.7 – 51.6 29.4 – 56.5 Calcium (mg/l) 580 – 3100 310 – 1850 Magnesium (mg/l) 20 - 65 12– 48 SAR 46-52 24 - 29 Chromium (mg/l) BDL - 0.10 BDL - 0.05 Lead (mg/l) 0.25 - 0.70 BDL - 0.40 Cadmium (mg/l) BDL - 0.05 BDL - 0.01


44

Nickel (mg/l) 0.2 – 0.50 BDL - 0.25 4.1.22. Physico - Chemical characteristics of water samples collected at Tiruppur taluk after monsoon

The water samples collected from the same villages of Tiruppur taluk after

monsoon showed variation on pH ranging from 7.85 – 9.12 in affected villages

and 6.5 – 7.85 in the unaffected villages. The pH of the water samples from

affected villages is slightly higher than the limit of 8.5 but the samples of

unaffected villages recorded pH in near neutral range. The EC was high in

affected villages ranging from 2.53 – 4.05 ds/m and 1.15 – 2.85 ds/m in

unaffected villages. Both the affected and unaffected regions exhibited higher

EC value than the maximum permissible limit.

The BOD content of water samples from affected and unaffected villages ranged

between 95 – 145 mg l-1 and 42 and 65 mg l-1 respectively; Both the values

exceeded the prescribed limits of drinking (2 mg l-1 ) as well as irrigation water

(30 mg l-1). The COD value is found to be greater in affected villages ranging

from 185 to 310 mg l-1compared to unaffected villages which recorded 85 – 135

and 30 mg l-1. The COD values of water samples from affected villages are

significantly higher than the prescribed limit of 250 mg l-1 as prescribed for

irrigation water. The chloride content of the samples varies widely between 315

to 650 mg l-1 in affected villages, which exceeded the limit of 500 mg l-1 for

irrigation purpose and 220 – 415 mg l-1 in unaffected villages, which lies within

the limit. The sulphate content accounts to about 28 – 54 ppm in affected villages

compared to unaffected villages which is about 22 – 44 ppm, which are well

below the limits. Calcium contents of water samples of both affected and

unaffected villages are found to be higher which ranged between 420 – 2300 mg

l-1 and 210 – 1150 mg l-1 respectively, which are far higher than the prescribed

limit. But the magnesium content of both the samples was found to be below the


45

critical limits. The SAR of affected and unaffected villages samples were in the

range of 36 – 49 and 22-27 respectively.

In the affected villages the chromium content ranges between BDL to 0.08 mg l-1

whereas in the unaffected villages it is found to be between BDL – 0.06 mg l-1.

The heavy metal lead accounts to about 0.18 – 0.55 mg l-1 in the affected

villages and BDL to 0.32 mg l-1 in unaffected villages. These values are little

higher when compared to the limit of 0.1 mg l-1. The cadmium content is about

BDL – 0.02 mg l-1 in the affected villages samples and BDL – 0.01 mg

l-1 in the water samples of unaffected villages . The standard limit prescribed for

this heavy metal is 0.01 mg l-1. The samples from affected and unaffected

regions recorded a nickel content of about 0.1 – 0.35 mg l-1 and BDL – 0.35 mg l-

1 respectively which are higher than the maximum prescribed limit.

Table 4.22. Physico - Characteristics of water samples collected at Tiruppur Taluk

(After monsoon)

Parameters Affected Villages Unaffected Villages pH 7.85 – 9.12 6.85 - 7.85 EC (ds/m) 2.53 - 4.05 1.15 - 2.85 BOD (mg/l) 95 - 145 42 – 65 COD (mg/l) 185 - 310 85 – 135 Chloride (mg/l) 315 - 650 220 – 415 Sulphate (mg/l) 28 – 54 22 – 44 Calcium 420 - 2300 210 – 1150 Magnesium 56 - 96 16 - 35 SAR 36 - 49 22- 27 Chromium (mg/l) BDL - 0.08 BDL - 0.06 Lead (mg/l) 0.18 - 0.55 BDL - 0.32 Cadmium (mg/l) BDL - 0.02 BDL - 0.01 Nickel (mg/l) 0.1 – 0.35 BDL - 0.35

4.1.23. Assessing the changes in soil properties of Tiruppur taluk The results of the soil samples collected from the study villages of Tiruppur taluk

are presented in table 4.23. The results showed that the pH values ranging from


46

6.10 – 7.50 in affected regions and 6.15 – 7.36 in the unaffected regions. The

EC values were found to be higher in the affected villages (0.69 - 1.80 ds/m)

when compared to unaffected villages (0.12 - 0.29 ds/m).

The available N content was found to be greater in affected villages (240 – 450

mg/kg) which comes under the medium rating (280 – 450 kg/ha) when compared

to the unaffected regions which recorded 100 – 267 kg/ha which comes under

the low rating (0 – 280 kg/ha) status. The available P content in affected regions

was in the range of 8 – 25 kg/ha which exhibited high rating (>22 kg/ha)

whereas, in the unaffected region it varies from 14 – 34 kg/ha which is classified

under high rating (>22 kg/ha). Similarly, the higher available K content was

observed in affected regions (124 – 282 kg/ha) which is classified under high

rating (>280 kg/ha). The unaffected villages recorded 48 – 197 kg/ha, of

available K which comes under medium status of 118 – 280 kg/ha.

The chromium content was found to be maximum in the soils of affected regions

(55 – 87 ppm) when compared to the unaffected regions, which ranges from 25 –

58 ppm. But the samples of both the regions do not exceed the critical limit of

100 ppm. The heavy metal lead accounts for higher value of about 38 – 87 ppm

in affected regions when compared to unaffected regions ranging from 0.14 –

2.10 ppm. Both the regions come under the standard limit of 100 ppm. The

samples of affected villages recorded 2.36 – 3.85 ppm of cadmium which is

slightly higher than the maximum allowable concentration of 3.0 ppm. . Whereas,

the cadmium level of soil samples of unaffected villages were in the range of 0.12

– 1.89 ppm.. The nickel content was higher in affected regions recording about

25 – 58 ppm which is higher than the limit and it was only 8–18 ppm in

unaffected regions.


47

Table 4.23. Characteristics of soil samples collected at selected villages of Tiruppur taluk

Parameters Affected Villages Unaffected Villages pH 6.10 - 7.50 6.15 - 7.36 EC (ds/m) 0.69 - 1.80 0.12 - 0.29 Available N (kg/ha) 240 – 450 100 – 267 Avail.P (kg/ha) 8 – 25 14 – 34 Avail. K (kg/ha)) 124 – 282 48 – 197 Chromium (mg/kg) 55 – 87 25 – 58 Lead (mg/kg) 38 – 87 0.14 - 2.10 Cadmium (mg/kg) 2.36 - 3.85 0.12 - 1.89 Nickel (mg/kg) 25 – 58 8 – 18

Workers Majority of the workers interviewed were migrants from the other taluks. They

were either from Trichy or Karur. Many of the migrants have settled in the study

area.

4.1.24. Nature of Work The nature of work carried out by the respondents in both affected and

unaffected villages is presented in Table 4.24. It could be seen from the table

that most of the respondents in the affected area were engaged in industrial

activities such as Dye-master (20 per cent), Supervisor (15 per cent), Chemical

Supervisor (15 per cent), Winch runner (15 per cent), Hydropher (15 per cent)

and Dye mixer (10 per cent) whereas in the unaffected areas, occupations

related to knitting and garment export were found high. A vast majority of 45 per

cent of the respondents were engaged in maintaining the quality of the yarn in

the near by knitting factories.


48

Table 4.24. Nature of Work (Per cent)

Sl.No Nature of Work Affected Villages

Un Affected Villages

1. Dye master 20 -

2. Supervisor 15 10

3. Cashier 5 -

4. Chemical supervisor 15 -

5. Winch runner 15 -

6. Hydropher 15 -

7. Dye mixer 10 -

8. Fitter 5 5

9. Quality control supervisor - 45

10. Other type of labourers - 20

11. Sweeper - 5

12. Accountant - 5

13. Labour – Colouring - -

14. Watchman - 5

15. Office boy - 5

Total 100 100

4.1.25 Employment From Table 4.25 it could be understood that the average days of employment per

month did not show much variation and it was only 22.70 days in affected areas

while in unaffected areas it was 25 days. Monthly wages earning was higher in

affected villages (Rs.3200) compared to unaffected locations (Rs.2580). The

average annual income of the respondents was Rs.38, 400 in affected locations

compared to Rs.30, 960 in unaffected areas.


49

Table 4.25. Employment Particulars of the Head of the Family

Sl. No

Particulars Affected Villages

Unaffected Villages

1. Average days of monthly employment 22.70 25.00

2. Average Wage earning (Rs./Month) 3200 2580

3. Average Number of Family Members Working in Dyeing Industry

0.15 -

4. Average Number of Family Members Working in Other Industries

- 0.50

5. Average Annual Income of the Respondent 38,400 30,960

4.1.26. Benefits Availed by the workers The industrial workers were availing the benefits as detailed in Table 4.26. In the

affected villages about 39 per cent were claiming ESI and 25 per cent availing

medical benefits when compared to 6.90 per cent in unaffected villages. About

four per cent was getting personal loan also from industries. Most of the workers

in the unaffected area were working in knitting company and they were enjoying

the benefits of both ESI and bonus.

Table 4.26. Benefits Availed by the Workers

Sl. No Benefits Affected Villages Un Affected Villages

1. Accident Claims 10.71 13.79

2. Medical Benefits 25.00 6.90

3. ESI* 39.29 44.83

4. Personal loan 3.57 -

5. Bonus 21.43 34.48 *Eligible after 5 years


50

4.1.27. Problem of Illness No chronic illness was reported in both affected as well as unaffected areas. The

details are presented in table 4.27. Fifteen per cent of the respondents reported

problem of skin cracks and another 15 per cent expressed the problem of skin

rashes. Five per cent reported weight loss. The affected respondents were

spending annually Rs.93 towards the cost to physician and Rs.135 towards

medicine.

Table 4.27. Externality effects to Workers

Affected Villages Sl. No

Particulars Number Per cent

1. Weight loss 1 5 2. Skin cracks 3 15 3. Skin rashes/itching 3 15 4. No illness 13 65 5. Cost to Physician

(Rs./annum/individual) 93.00 -

6. Cost of medicine (Rs./annum/individual))

135.00 -

4.2. Karur 4.2.1. Family Size The family size of the sample respondents is presented in the table 4.28. The

overall size of the family of the sample farmer was 4.19. Between the two

categories, the average size of the family was found to be comparatively large in

the unaffected areas.

Table 4.28. Average Family Size (Numbers)

Sl. No Category Average Size 1. Affected 4.13 2. Unaffected 4.25


51

Overall 4.19 4.2.2. Educational Status It is obvious from Table 4.29 that the percentage of illiterates in the affected

village was higher (29.44 per cent) than that of unaffected village (24.71 per

cent). There was not much difference in literacy levels of both categories.

Table 4.29. Educational Status Sl.No Particulars Affected Villages Unaffected Villages

Numbers Percentage

Numbers

Percentage

1. Illiterates 73 29.44 63 24.71 2. Primary 48 19.35 68 26.67 3. Secondary 66 26.61 54 21.18 4. Higher Secondary 22 8.87 23 9.02 5. Graduates 39 15.72 47 18.43

Total 248 100.00 255 100.00

4.2.3. Land Holding Pattern The land area possessed by the sample households and the area under

cultivation are presented in Table 4.30. There were wet, dry and garden lands.

The average operational area of the sample households in the unaffected area

was higher (2.09 ha) than the affected area (1.28 ha). The average area under

cultivation was 1.61/ha in unaffected villages when compared to 0.89 ha in

affected villages.

Table 4.30. Land Holding Pattern (Average ha)

Affected Villages Unaffected Villages Nature of land Operational

Area Area

Cultivated Operational

Area Area

Cultivated Wet land 0.34

(26.47) 0.23

(25.29) 0.83

(39.88) 0.54

(33.80) Garden land

0.83 (64.84)

0.64 (71.69)

1.00 (47.86)

0.97 (60.55)

Dry land 0.11 (8.69)

0.03 (3.02)

0.26 (12.26)

0.09 (5.66)

Total 1.28 0.89 2.09 1.61


52

(100.00) (100.00) (100.00) (100.00) Figures in parentheses indicate the percentage to total

4.2.4. Irrigation The river Amaravathy and its canals, openwells and bore wells are the chief

sources of irrigation in both affected and unaffected villages. Somur is benefited

by both Cauvery and Amaravathy rivers. There are three canals and the area

covered is 245.79 ha. The village Pallapalayam is benefited by Raja Vaykal,

which is about two km long and covers an area of about 335 ha. Due to the

dyeing factory effluents both the canal and the open wells are not used by many

farmers for irrigation in the Sanapparetti village. In the affected villages, many of

the sample farmers reported that the well water quality has been affected by

effluents.

Table 4.31. Well Irrigation

Sl. No.

Particulars Affected

Villages

Unaffected Villages

1. Total number of wells in the sample farms 55 35

2. Average depth of open well (in mts.) 13.67 12.33

3. Percentage of well with water throughout the year *

74.55 57.14

4. Percentage of well with water only during the rainy season *

21.82 40.00

5. Percentage of abandoned wells * 13.64 2.86

6. Number of bore wells in the sample farms 1 9

7. Average depth of bore wells (mts.) 13.33 14.33

8. Percentage of wells affected by effluents in the sample farms

100.00 -

* Percentage calculated upon the total number of wells in the sample farms

4.2.5. Sources of Irrigation


53

The sources of irrigation are given in Table 4.32. Area under canal irrigation in

the affected villages was very less (9.33%) when compared to unaffected areas

(18.06%). Rainfed cultivation did not show any significant difference between the

unaffected (32.67 %) and affected (32.59 %) villages. No area is irrigated by

bore well in affected villages while in the unaffected villages it accounted for 8.49

per cent.

Table 4.32. Irrigation Sources (Per cent)

Sl.No Particulars Affected Villages Unaffected Villages

1. Canal 9.33 18.06

2. Open well 43.33 25.92

3. Canal + Open well 14.75 8.62

4. Canal + River water Scheme* - 5.95

5. Openwell + Bore well - 8.49

6. Water purchased from outside - 0.29

7. Purely Rainfed 32.59 32.67 *In the village Somur the farmers pay a deposit of Rs.12,000/annum for availing water from the canal of the river “Cauvery”.

Fig. 18 Sources of Irrigation – Karur Taluk


54

Sources of Irriga tion

43.33

14.75

0 0 0

18.06

8.625.95

8.49

0.29

9.33

32.59

25.92

32.67

-10

0

10

20

30

40

50

Canal Open well Canal +Open well

Canal +River waterScheme*

Openwell +Bore well

Waterpurchased

fromoutside

PurelyRainfed

Sources of IrrigationAffected VillagesUnaffected Villages

4.2.6. Area and Productivity of Crops The area and productivity of crops grown in the affected and unaffected sample

households are presented in Table 4.33. The table shows that the area under

coconut in the unaffected area was higher (28.67 %) than in affected area

(11.19%). Also, the area under paddy was higher (22.68%) in unaffected areas

compared to affected villages (19.34 %). The same trend was observed for

fodder cholam also. Even the major crop of this taluk ‘korai’ was not grown well

in the affected localities due to poor soil and water qualities.

The productivity of almost all the crops was found higher in unaffected villages

compared to affected locations. Ten years back sugarcane, turmeric and paddy

were the major crops grown in both affected and unaffected villages. These

crops occupied an area of about 60 per cent of the total cultivable lands. By

now, the area under turmeric is almost zero in the affected villages. Sugarcane

and paddy occupied only less than 20 per cent of the total cultivated area. Total

area under cultivation had also declined during recent years.


55

Table 4.33. Crop Area and Productivity

Affected Area Unaffected Area Difference Sl. No.

Name of the Crop Area

(%) Yield (tons/

ha)

Area (%)

Yield (tons/

ha)

Yield (tons/

ha)

Percen-tage

1. Coconut* 11.19 14705 28.67 26073 11368 (-)44 2. Paddy 19.34 4.35 22.68 5.07 0.72 (-)14 3. Turmeric - - 4.25 5.79 - - 4. Fodder

Cholam 35.37 6.17 16.32 8.15 1.98 (-)24

5. Grain Cholam

7.46 1.85 0.86 1.24 0.61 49

6. Ragi - - 0.69 0.99 - - 7. Banana - - 0.87 98.12 - - 8. Sunflower 1.69 0.62 - - - - 9. Sugarcane 9.84 59.21 4.30 93.83 34.62 (-)37

10. Cotton 10.04 1.36 0.86 2.49 1.13 (-)83 11. Groundnut 0.67 1.73 3.65 2.19 0.46 (-)21 12. Vegetables 3.38 61.75 - - - - 13. Greens 1.02 741 - - - - 14. Korai - - 16.65 6.99 - - 15. Tapioca - - 0.25 74.10 - -

Total 100.00 - 100.00 - * yield in nuts/ha.

Fig. 19 Crop Area and Productivity – Karur Taluk


56

Crop Area and Productivity

6.170.00 1.73

61.75

5.07 8.15

98.1293.83

2.19 0.004.35

59.21

0.00

20.00

40.00

60.00

80.00

100.00

120.00

Paddy FodderCholam

Banana Sugarcane Groundnut Vegetables

Crops Affected villagesUnaffected villages

4.2.7. Farmers Opinion about Decline in Agricultural Activities The respondent’s opinion towards decline in agricultural operations are reported

in the Table 4.34. Scarcity of good quality water and non-availability of farm

labourers were the main reasons for decline in agricultural operations, which

accounted for 83.33 and 73.33 per cent, respectively. Labour scarcity was due

to the mobility of agricultural labourers from farming to industrial sector. Due to

the deterioration of land and water quality, the crop stand was also observed

poor. All these factors together contributed to huge decline in agricultural

activities.

Table 4.34. Farmers’ Opinion Towards Decline in Agricultural Activities

Sl.No Opinion Affected Category 1. Water scarcity 83.33 2. Labour scarcity 73.33


57

3. Poor water quality 70.00 4. Decline in water table 28.33 5. Decline in agricultural income 30.00 6. Poor crop stand 43.33

Opinion of Sample Farmers on Decline in Agricultura l Activities

83.33

73.33 70.00

28.33 30.00

43.33

0.00

20.00

40.00

60.00

80.00

100.00

Waterscarcity

Labourscarcity

Poor waterquality

Decline inwater table


income

Poor cropstand

Affected ca tegory

4.2.8. Changes in the Value of Agricultural Lands The changes in the value of agricultural lands are compared over years and the

details are presented in Table 4.35. The agricultural land value in the affected

villages declined considerably (9 per cent) due to poor soil and water qualities

while the land price had improved by 55 per cent in the unaffected area. Fifteen

years back, the value of agricultural lands in the affected village was higher than

the unaffected villages. The same trend was noticed till early part of nineties. By

now, the value of the land had been reduced by 9.32 per cent in the affected

villages. Whereas in the unaffected villages, an increase of 55 per cent in the

value of agricultural land was noticed over years.

Fig. 20 Opinion of Sample Farmers on Decline in Agricultural Activities – Karur Taluk


58

Table 4.35. Value of Crop Land

(Rs per ha)

Sl.No Particulars Affected Village Unaffected Village

1. 5 years back 1,56,600.00 1,25,000.00

2. 2003 – 04 1,42,000.00 1,94,000.00

3. Change in value of land

(in per cent)

(-)9.32 55

4.2.9 Employment Pattern The employment distribution of the household is presented in the Table 4.36. In

the affected villages none of the households was found to undertake farm activity

alone. About two per cent of the sample households in the unaffected villages

were engaged in agricultural activities alone. In the affected villages, about 12

per cent of the sample households were employed in the combined activities of

agriculture and dairy while in the unaffected villages it was about 17 per cent.

The percentage of sample households engaged in the combined activities of on-

farm plus non-farm (36.67 per cent) and off farm plus non farm (3.33 per cent)

were found to be equal in both the categories. About 22 per cent of the

households in the affected villages were employed in the combined activities of

both on-farm and off-farm while it was only about 13 per cent in the unaffected

villages.

Table 4.36 Occupational Distribution of the Households

Affected Villages Unaffected Villages

S. No

Particulars

Number Per cent

Number Per cent


59

On-farm

1. Crop alone - - 1 1.67

2. Crop alone + dairy activities 7 11.67 10 16.67

Total households engaged in on- farm activities alone

7 11.67 11 18.34

3. On-farm + Off farm activity 13 21.67 8 13.33

4. On-farm + Non-farm activity 22 36.67 22 36.67

5. On-farm + Off- farm + Non- farm activity

14 23.33 17 28.33

6. Off-farm + Non-farm activity 2 3.33 2 3.33

7. Non-farm activity (petty shop) 2 3.33 - -

Total Sample Households 60 100.00 60 100.00

Earning members in the sample households

133 121


60

Fig.21 Occupational D istribution o f Households - Karur Ta luk

0

11.6

7

21.6

7

36.6

7

23.3

3

3.3

3

3.3

3

1.6

7

16.6

7

13.3

3

36.6

7

28.3

3

3.3

3

005

10152025303540

Crop alone Crop + dairyactivities

On farm +off farmactivity

On farm+non farmactivity

On farm+offfarm+non

farm

Off farm +non farmactivity

Non farmactivity

Per

cen

tag

e

Affected Unaffected

4.2.10. Income The income pattern of the household is presented in the Table 4.37. In the

affected villages, 11.70 per cent of the household income was from both

agriculture and dairy, but it was high (29.24 per cent) in the unaffected villages.

About five per cent of the income in the affected villages were involved from non

farm activities like money lending, wage earning in private companies and so on.

Income from both on-farm and non-farm activities was observed higher at 52.44

and 50.32 per cent respectively, in the affected and unaffected villages. About

18 per cent of income of households in the affected villages were from the

combination of all the three activities viz, on-farm, off-farm and non-farm

activities. The average annual income earned by the households was Rs.74,

666 and Rs 1, 30,072 respectively, in the affected and unaffected sample

households where the difference happened to be larger.

Table 4.37 Pattern Average Annual Income of the Sample Household


61

(in Rs.) Affected Villages Unaffected

Villages Sl.No Particulars

Amount Percent

Amount Percent

On -farm 1. Farm income - - 1,000 0.77 2. Farm + Dairy activities 8,733 11.70 38,033 29.24

Average annual income from on-farm activities only

8,733 11.70 39,033 30.01

3. On-farm + Off -farm income 6,525 8.74 7,033 5.41

4. On-farm+Non-farm income 39,158 52.44 65,458 50.32 5. On-farm + Off-farm + Non-

farm income 14,050 18.82 17,231 13.25

6. Off-farm + Non -farm income

2,400 3.21 1,317 1.01

7. Non-farm income 3,800 5.09 - - Average Annual Income Per Household

74,666 100.00 1,30,072

100.00

Fig.22 Pattern of Inc ome - Karur Taluk

0.00

11.7

0

8.74

52.4

4

18.8

2

3.21 5.09

0.77

29.2

4

5.41

50.3

2

13.2

5

1.01

0.00

0.0010.0020.0030.0040.0050.0060.00

Farmincome

Farm +dairy

activities

On farm +off farm income

On farm+non farmincome

Onfarm+offfarm+non

farmincome

Off farm +non farm income

Non farm income

Per

cen

tag

e

Affected Unaffected


62

4.2.11. Labour Migration In the affected villages, earning members in 55 per cent of the households

interviewed have migrated in search of employment. The details of the labour

migration are reported in the Table 4.38. The analysis of reasons for the

migration of farm households had indicated that poor water quality was found to

be the main reason (52.22 per cent) followed by poor income from agriculture

(48.94).

Table 4.38. Labour Migration

Sl.No Particulars Affected (Percent)

1. Percentage of migration (out of 60 households) 55.00 2. Percentage migration from sample households 18.12

3. Percentage of permanent migration by the family members

95.74

4. Number of days migration 79.66 5. Reasons for migration a. Poor water quality 52.22 b. Less income from agriculture 48.94 c. To earn more income 40.43 d. Employment in public / private institutions 14.89 e. To pursue higher education 12.77

4.2.12. Sale of Assets It is inferred from Table 4.39 that in the affected villages 30 per cent of the

respondents had disposed off at least part of their land due to poor water quality

and labour scarcity. In these villages 75 per cent of the respondents interviewed

had sold their livestock due to various reasons like poor water quality, non

availability of water, labour shortage, poor milk yield and reduced calving rate. In


63

the unaffected villages these values were only 10 and 46.67 per cent,

respectively.

Table 4.39. Sale of Assets (Per cent)

Sl.No Particulars Affected Villages

Un affected Villages

I. Sale of Land 1. Percentage of respondents sold

land 25 10

2. Extent of land sold (%) 4.60 1.74 II. Sale of Animals 1. Percentage of respondents sold

animals 75 46.67

Reasons for sale of animals a. Poor Water Quality 15 5 b. Labour Scarcity 10 25 c. Drying / Aged animal 35 16.67 d. Poor Milk Yield 1.67 - e. Reduced Calving rate 10 - f. To meet out unexpected expenses 3.33 -

4.2.13. Farm Level Availability of Livestock From the Table 4.40 it is understood that the number of animals in the affected

village had been marginally low compared to unaffected villages. Sheep was

reared by majority of the farmers in the unaffected villages because of the

availability of grazing lands and good quality water, whereas in affected areas, it

was only 50 per cent of the animals available with farmers in unaffected areas

because of the non-availability of good quality water, fodder and grazing lands.

Table 4.40. Possession of Livestock

(Numbers) Sl.No Category Affected Area Unaffected Area

1. Cow 0.78 0.82 2. Buffalo 1.03 1.02


64

3. Bullock 0.08 0.02 4. Sheep 0.28 0.60

4.2.14. Sufferings by Human and Animals Occasionally the people in the affected areas have been experiencing morbidity

problems viz., itching, skin rashes, eye boils etc. In animals also, reduction of

milk yield, weight loss and poor calving were reported. Milk production in the

affected area was reported to be reduced by 12.35 per cent.

Table 4.41. Externalities on Human and Animal Health

Sl.No. Particulars Affected Villages (per individual)

Human Health 1. Average cost of medicine (Rs./annum) 70.25 2. Average cost to physician

(Rs./annum) 110

Animal Health 1. Loss in value (Rs./ annum) 4170 2. Percentage loss in milk production 12.35

4.2.15. Sources of Drinking Water The river Cauvery is the chief source of drinking water in the affected villages

whereas in unaffected villages, river Amaravathy is the major source of water

supply. The respondents of Panchamadevi were getting drinking water daily

either from their own tap or public tap; whereas in Sanapparatti, people were

getting water only once in 15 days from the public tap. They were forced to bring

water from Vadakupalayam, located about 5 km from the village and about 97

per cent of the respondents depended on public tap only (Table 4.42). Six

respondents were also purchasing mineral water (45 lts. can) and seven

respondents reported purchasing water transported by lorries. But in the

unaffected villages, the availability of drinking water was not a severe problem.

About 85 per cent of the respondents depended on public taps while 15 per cent


65

of the respondents had their own tap. The water use in the affected households

was found to be marginally less (5,250 litres/month) than the unaffected villages

(5,336 litres/month). Water was however not purchased from outside in the

unaffected areas and availability of good quality water is reported to be acute

during the last ten years in the affected villages.

Table 4.42. Sources of Drinking Water

Affected Village Unaffected Village Sl. No

Particulars

Number Expense (Rs. /

household/annum)

Number

Expense (Rs. /

household)

1. Sources of Drinking Water Cauvery Amaravathy

a. No. of people having own water connection

2 360 9 360

b. No. of people having public water connection

58 - 51 -

c. No. of people purchasing water from outside (in 45 lts cans)

6 195 - -

e. No. of people using water transported by lorries

7 6,146 - -

f. No. of people using well water

1 - - -

2. Average Water Requirement and Expense towards procuring water

a. Average water requirement per month (litres/family)

5,250 - 5,336 -

b. Average quantity of water transported by lorries per month/family (in litres)

10,320 753.00 - -


66

3. Average Distance between the household and the source of water (km)

0.64 - 0.50 -

4.2.16. Well Water Quality Out of 51 wells in the affected area, ten wells were reported to be having very

poor water quality during summer. The quality was reported as poor in 37 wells

out of 50. In the unaffected villages, the quality of water was good to medium

and very few wells had poor quality water. The colour of water was normal in

unaffected localities whereas in affected area, it was black, occasionally red or

dull white in few cases. Mild odour was also present in affected areas.

Table 4.43. Quality of Well Water (Per cent)

Affected Area Unaffected Area Sl.No Particulars Summer Season

Rainy Season

Summer Season

Rainy Season

Total No. of Wells* 51 31 Taste

1. Poor 92.16 49.02 6.45 - 2. Medium 7.84 50.98 83.87 83.87 3. Good - - 9.68 16.13 Colour

1. High 1.96 1.96 - - 2. Medium 3.92 3.92 - - 3. Low 94.12 94.12 100.00 100.00 Turbidity

1. High 1.96 - - - 2. Low 98.04 - 100.00 100.00 Odour

1. High 100 - - - 2. Low 0 - 100.00 100.00

* One well has no water. Three respondents are having two wells.

4.2.17. Willingness to Pay (WTP)


67

The problem of water and soil quality was comparatively high only in the affected

areas and out of 60 respondents about 62 per cent were willing to pay some

amount to replenish the degraded resources. About 57 per cent of the

respondents were willing to pay in the range of Rs.25,000 to Rs.50,000 and

about 43 per cent were willing to pay annually.


Sl.No. Particulars Numbers Value (Per cent) 1. Households willing to pay 37 61.67 2. Households not willing to pay 23 38.33 3. Willingness to pay a. Less than Rs.20, 000 3 8.11 b. Rs.21, 000 – Rs.25, 000 8 21.62 c. Rs.25, 001 – Rs.50, 000 21 56.76 d. Rs.50, 001 – Rs.75, 000 5 13.51 4. Mode of Payment a. Monthly 7 18.92 b. Quarterly 5 13.51 c. Half yearly 9 24.32 d. Annual 16 43.24

Fig.23 Willingness to Pay – Karur Taluk


68

Willingness to Pay

8.11

21.62

56.76

13.51

0

10

20

30

40

50

60

Less than Rs.20, 000 Rs.20, 001 – Rs.25,000 Rs.25, 001 – Rs.50,000 Rs.50, 001 – Rs.75,000


4.2.18. Averting Expenditure From the table 4.45 it could be understood that the farmers cultivating paddy and

fodder cholam spent about Rs.687 and Rs.510 per ha respectively, towards

averting expenditure on seeds, organic manure, etc. Similarly, for sugarcane

about Rs.1122 per ha was spent as averting expenditure and for sunflower it was

Rs.200 per ha. For getting good quality drinking water from the nearby locations,

respondents had to spend 8.44 man-days amounting to Rs.844 / annum /

household.

Table 4.45. Averting Expenditure

Sl. No.

Particulars Averting Expenditure (Rs./ha)

1. Paddy 687 2. Fodder Cholam 510 3. Sugarcane 1123 4. Sunflower 200 5. Drinking water (Rs. / annum) 844

Soil and Water Sample Analysis


69

4.2.19. Physico - Chemical characteristics of water samples collected at Karur taluk (Before monsoon) The results of the water sample analysis of Karur taluk, before and after

monsoon are given in the tables 4.46 and 4.47.

The water samples taken from villages of Karur before monsoon showed not

much variations in pH values in both affected and unaffected regions (7.38 – 8.50

and 7.56 – 8.30 respectively) and are well within the standard limit of 6.5 – 8.50.

The EC values were found to be more or less similar in both the regions

exhibiting 0.95 – 3.20 ds/m in affected regions and 0 – 3.15 ds/m in unaffected

regions water samples. Both the samples exceeded the maximum permissible

limit of 2.25 prescribed for irrigation water.

The chloride content was maximum in affected regions (49 – 134 mg l-1)

compared to unaffected villages ranging from 56 – 110 mg l-1. Both the regions

are well within the prescribed limits (500 mg l-1). The sulphate content was

maximum in affected villages of about 110-386 mg l-1 compared to unaffected

villages ranging from 180 - 380 mg l-1.

The calcium content in affected villages was found to be 435 – 3550 mg l-1 and

550 – 3850 mg l-1 in the unaffected villages. Both the regions exceed to a

greater extent when compared with critical limit of 100 mg l-1. The magnesium

content ranges from 13 –65 mg l-1 in affected regions and 15 – 67 mg l-1 in

unaffected regions. Both the regions fall with in the critical limit of 150 mg l-1.

In general, the BOD and COD values affected villages water samples were

higher than the samples from unaffected villages. Water samples collected from

affected villages recorded a BOD value ranging from 35 – 110 mg l-1 and 27 –

104 mg l-1 in unaffected regions. Whereas the COD values ranged between 165

– 420 mg l-1 and 95 – 240 mg l-1 in affected and unaffected regions respectively.


70

Though the BOD values of unaffected samples are higher than the limit, the COD

lies within the limit but both the BOD and COD values of samples from affected

villagers are higher than the maximum permissible limit of 250 mg l-1. The

samples of affected villages recorded the SAR ranging between 39 – 46, which

are higher than the maximum limit of 26, whereas, the unaffected villages

samples recorded SAR of below permissible level.

With regard to heavy metal contents of samples, all the samples collected from

affected and unaffected villages recorded the presence of heavy metals such as

chromium, lead, nickel and cadmium. The water samples from affected villages

recorded 0.02 - 0.10, 0.02 - 0.55, 0.02 - 0.05 and 0.25- 0.50 and unaffected

villages recorded BDL - 0.05, BDL - 0.42, BDL - 0.05 and 0.10 - 0.48 mg l-1 of

Cr, Pb, Cd and Ni respectively. All the four heavy metal contents of affected

villages’ samples exceeded the critical limits and water samples from unaffected

villages have higher levels of heavy metals except Cr, which is within the limit.

4.2.20. Physico - Chemical characteristics of water samples collected at Karur taluk after monsoon

The water samples collected after monsoon recorded more or less similar pH

values in both affected and unaffected regions ranging from 6.82 - 8.45 and 6.99

- 7.85 respectively. These values in both the regions do not vary from the critical

limit of about 6.5 – 8.50. The EC value was recorded as 2.05 - 4.12 ds/m in

affected villages compared to 1.22 - 3.11 ds/m in unaffected regions, which are

exceeding the standard limit of 2.25 ds/m for irrigation water.

Table 4.46. Physico - Characteristics of water samples collected at Karur Taluk

(Before monsoon)


71

The BOD values in affected regions ranged between 99 – 148 mg l-1 when

compared to 34 – 60 mg l-1 in unaffected regions and the COD values are also

found to be greater in affected villages ranging from 215 – 305 mg l-1 compared

to unaffected villages which recorded about 85 - 120 mg l-1. There was no much

variation between the chloride and sulphate contents of both the samples. The

samples of affected villages and unaffected villages recorded 245 – 415 mg l-1

and 215 – 445 mg l-1 of chloride respectively, and 25 – 50 mg l-1 and 23 – 45 mg

l-1 of sulphate respectively, which are well between the critical limits. Calcium

and magnesium contents of affected villages are higher recording 585– 3150

and 45-75 mg l-1 respectively. The SAR values of affected samples exceeded the

critical limit but unaffected samples lies within the limit of 26.

Regarding heavy metal analysis, chromium content was found to be higher in the

affected regions ranging from 0.02 –0.08 mg l-1 whereas in the unaffected

villages, it is found between BDL – 0.06 mg l-1 which is slightly higher than the

limit. The water samples colleted from unaffected region also recorded the

presence of other heavy metals such as lead, cadmium and nickel well above

critical limits.

Parameter Affected Villages Unaffected Villages pH 7.38 – 8.50 7.56 – 8.30 EC (ds/m) 0.95 – 3.20 0.50 – 3.15 Chloride (ppm) 49 – 134 56 – 110 Sulphate (ppm) 110 – 386 180 – 380 Ca (ppm) 435 – 3550 550 – 3850 Mg (ppm) 13 – 65 15 – 67 COD (mg/l) 165 – 420 95 – 240 BOD (mg/l) 35 - 110 27 – 104 SAR 39 - 46 18 - 24 Chromium (mg/l) 0.02 - 0.10 BDL - 0.05 Lead (mg/l) 0.02 - 0.55 BDL - 0.42 Cadmium (mg/l) 0.02 - 0.05 BDL - 0.05 Nickel (mg/l) 0.25- 0.50 0.10 - 0.48


72

Table 4.47. Physico - Characteristics of water samples collected at Karur Taluk (Aftermonsoon)

Parameters Affected Villages Unaffected Villages pH 6.82 - 8.45 6.99 - 7.85 EC (ds/m) 2.05 - 4.12 1.22 - 3.11 BOD (mg/l) 99 - 148 34 – 60 COD (mg/l) 215 - 305 85 – 120 Calcium 585– 3150 510– 2850 Magnesium 45-75 32-56 Chloride (mg/l) 245 – 415 215 – 445 Sulphate (mg/l) 25 -50 23 – 45 SAR 32 - 38 20 - 24 Chromium (mg/l) 0.02 – 0.08 BDL – 0.06 Lead (mg/l) BDL – 0.34 BDL – 0.40 Cadmium (mg/l) BDL – 0.04 BDL – 0.04 Nickel (mg/l) BDL – 0.45 BDL – 0.52

4.2.21. Assessing the changes in soil properties of Karur taluk The results of analysis of soil samples collected from the study villages of Karur

taluk are presented in table 4.48. pH values ranged between 7.56 – 8.31 in

affected villages and 6.10 and 7.23 in unaffected regions. The EC value too was

greater in the affected villages recording 1.25 – 4.10 ds/m when compared with

the values in the unaffected villages (0.14 - 1.28 ds/m).

The available N content was higher in affected villages (189 – 547 kg/ha) which

comes under high rating (>450 kg/ha); whereas, the unaffected regions showed

values between 102 – 178 kg/ha which comes under the low rating (0 – 28

kg/ha). The available P content showed values ranging from 19 – 89 kg/ha in

affected regions and in the unaffected region (23 – 64 kg/ha). Both the regions

come under high rating (>22 kg/ha). Similarly, the available K content was

maximum in affected regions (189 – 359 kg/ha) and comes under high rating

(>280 kg/ha) when compared with the unaffected villages which recorded 20 – 91

kg/ha which lies in low rating (0 - 118 kg/ha).


73

Chromium content was found to be high in the affected regions (39 -99 ppm) and

low (23 – 58 ppm) in soil samples of unaffected villages. But both the samples lie

well within the critical limit of 100 ppm. Soil samples of affected villages of Karur

taluk recorded 2.36 – 5.69 ppm of lead, 1.89 – 5.96 ppm of cadmium, and 12 - 45

ppm of nickel when compared to unaffected regions which recorded 1.37 – 2.10

ppm of Pb, 1.10 - 2.10 ppm of Cd and 9 – 24 ppm of nickel.


74

Table 4.48. Characteristics of soil samples collected at selected villages of Karur taluk

Parameters Affected Villages Unaffected Villages

pH 7.56 - 8.31 6.10 - 7.23

EC (ds/m) 1.25 – 4.10 0.14 - 1.28

Available N (kg/ha) 189 – 547 102 - 178

Avail.P (kg/ha) 19 – 89 23 - 64

Avail. K (kg/ha) 189 – 359 20 - 91

Chromium (mg/kg) 39 – 99 23 - 58

Lead (mg/kg) 2.36 -5.69 1.37 - 2.10

Cadmium (mg/kg) 1.89 -5.96 1.10 - 2.10

Nickel (mg/kg) 12 – 45 9 - 24

Workers – Karur Majority of the workers interviewed were mainly natives of this taluk. Both the

educated and uneducated youth of the farm families were employed themselves

in the nearby dyeing or bleaching industries. The main reason for this was the

higher wage rate in the industry when compared to agricultural sector. Physical

strain was also reported to be less in non-farm industrial occupations.

4.2.22. Nature of Work The table 4.49 reveals the occupational distribution of the labourers in the

sample villages. Almost all the respondents in the affected areas maintained

their livelihood by working as wage earners in the dyeing factories. They were

employed in the categories such as; supervisor, cashier, accountant, dye master,

skilled labourers (colouring and dyeing), and so on. In the unaffected villages

about 25 per cent of the workers interviewed were agricultural labourers, 15 per

cent were masons and 10 per cent were casual workers. Of the remaining 50


75

per cent, 15 per cent were either working as dye master or in the boiler section,

10 per cent as RO plant operators and 10 per cent as ETP managers.

Table 4.49. Nature of work (Per cent)

Sl.No Category Affected Area

Unaffected Area

1. Dye master 25 15 2. Labour (doing colouring of yarn) 30 - 3. Supervisor 10 - 4. Cashier 10 - 5. Accountant 5 - 6. Typist 5 - 7. Hydropher 5 - 8. Unskilled Labour (Sweeper) 5 - 9. Watchman 5 -

10. Agricultural labourer - 25 11. Mason - 15 12. Casual labourer - 10 13. Boiler operators - 15 14. RO (Reverse Osmosis) Plant operator - 10 15. ETP (Effluent Treatment Plant)

Managers - 10

4.2.23. Employment It is implicit from the table 4.50, that the average days of employment for the

workers in the affected area were more by 15 per cent. The average annual

income earned by the worker respondent in the affected village was also high by

Rs.8535 compared to the earnings of workers in the unaffected area due to

continued employment and high wage rate in industries.

Table 4.50. Employment Particulars


76


Unaffected Villages

1. Mandays of employment (per month) 25 (82 %)

20.5 (67.39 %)

2. Number of family members in dyeing factories

0.60 -

3. Number of people in knitting companies

0.20 -

4. Annual income of the respondent (in Rs)

29,040 20,505

4.2.24. Benefits Availed by Workers Twenty per cent of the respondents in the affected study villages had availed

accident and medical claims (for the accidents or disorders that had happened

while working) from the owners. It was reported that 15 per cent of the workers

in affected area were under ESI coverage and it was 25 per cent for accident

claims and 10 per cent in ESI (Table 4.51) in unaffected villages.

Table 4.51 Benefits Availed by the Workers

(Per cent)


Unaffected Villages

1. Accident and Medical Claims

20 25

2. ESI Coverage 15 10 4.2.25. Sufferings Faced by the Respondents It could be seen from the table 4.52 that a vast majority of about 60 per cent of

the workers were found to suffer from skin rashes, (skin rashes were reported to

occur throughout the year), 25 per cent from dysentery, 10 per cent from either


77

fever or headache and only five per cent reported that they were not

encountering any health oriented problems. The respondents were reported to

spend on an average Rs.225 per annum towards cost to physician and Rs.415

per annum towards cost of medicine. They also reported to have lost on an

average of 2.33 man days of employment per annum. In the unaffected villages

only 15 per cent were reported to suffer from skin rashes and they spent on an

average about Rs.150 per annum towards cost of illness.

Table 4.52. Sufferings of the Respondents (Per cent)


Unaffected Villages

1. Skin rashes 60 15

2. Dysentery 25 -

3. Occasional fever / Head ache 10 -

4. Not encountering any problems 5 85

5. Frequency of occurrence of the above diseases

Four- five times/year

Occasionally

6. Working days lost per annum 2.33 -

7. Loss of earnings (Rs./annum/individual)

217 -

8. Average physician cost (Rs./annum) 225 -

9. Ave. medical expenses (Rs./ annum) 415 - 4.2.26. Drinking Water In the affected village Panchamadevi, Cauvery water is supplied daily for drinking

purpose through public taps by the municipality whereas in the other affected

village Sanapparetti, the workers used to fetch water from Vadakkupalayam. It

was observed that none of the respondents was provided with individual tap

connection.


78

Table 4.53. Drinking Water Quality


Unaffected Villages

1. Public tap and well (numbers) 20 20

2. Time taken to fetch good quality water from the unaffected areas (minutes/day)

54 52.5

3. Water usage (lts/month) 1855 1932 4.3. Bhavani 4.3.1. Family Size It is clear from table 4.54 that the overall family size of the respondents was 3.67

and it was 3.93 for the unaffected category and 3.40 for the affected groups.

Table 4.54. Average Family Size

(Numbers)

Sl.No. Category Average Size of the Family

1 Affected area 3.40

2 Unaffected area 3.93

Overall 3.67 4.3.2 Educational status From the table 4.55, it is inferred that about 29 per cent were illiterates in the

affected villages where as it was only 18.64 per cent in the unaffected area.

About 22 per cent had completed their secondary education in the affected area.

This might be due to the availability of immense employment opportunities in and

around the sample villages.


79


Affected Area Unaffected Area Sl.No. Particulars

Numbers Per cent Numbers Per cent

1. Illiterates 60 29.41 44 18.64

2. Primary 42 20.59 75 31.78

3. Secondary 45 22.06 89 37.71

4. Higher secondary 18 8.82 11 4.66

5. Graduates 39 19.12 17 7.21

Total 204 100.00 236 100.00

4.3.3. Land Holding Pattern The land area possessed by the sample farmers and area under cultivation are

presented in Table 4.56. The average area under cultivation was 1.54 ha in the

affected area whereas in the unaffected area it was 1.72 ha. It was revealed that

the effluents of the dyeing factories had reduced the usage of water for irrigation

purposes. This has forced many farmers to convert their croplands to non-

agricultural purposes. The declivity of cropland area in the affected villages was

5.17 per cent. This has brought down to a great extend the crop income. The

main reasons for the decline in crop income were change in cropping pattern and

low crop productivity. The pollution has also created changes in cropping area

and employment opportunities.


80

Table 4.56. Land Holding Pattern (Ha)

Affected Villages Unaffected Village Sl.No Land

Average Land

Holding

Net Area Sown

Average Land Holding

Net Area Sown

1

Wet 0.64 (39.22)

0.61 (39.61)

0.37 (20.52)

0.36 (20.83)

2 Garden 0.92 (56.44)

0.86 (55.81)

1.33 (73.67)

1.33 (77.60)

3 Dry 0.07 (4.34)

0.07 (4.58)

0.11 (5.81)

0.03 (1.57)

Total 1.63 (100.00)

1.54 (100.00)

1.86 (100.00)

1.72 (100.00)

Percentage of cropland under cropping

94.83 92.38

Decline in the area (%)

5.17 7.2

Note: figures in parentheses indicate the percentage to total.

4.3.4. Details of Irrigation The river Bhavani and both the open and bore wells are the major sources of

irrigation. From table 4.57 it could be revealed that the total numbers of open

wells in the affected villages were 43 whereas, it was 56 in unaffected area. The

average depth of the open well was almost equal in both the categories. But, the

depth of bore well in the unaffected villages was deep by 15mts. The

examination of the results also shows that the percentage of open wells

abandoned in the affected villages was 6.98 whereas it was only 1.79 per cent in

the unaffected area. This might be due to the non-availability of quality water in

the shallow depth and improper maintenance of water table by conservation and

abatement techniques.


81

4.3.5. Sources of Irrigation The table 4.58 reveals the share of area irrigated by various sources in the

affected and unaffected areas. From the table, it is clear that in the affected

villages, the crop area is irrigated only by canal and wells. But, the area irrigated

by canal and wells together has increased by 24.10 per cent over the last 10 year

period. The total area under irrigation has increased by 1.55 times in the

affected villages, whereas, an increase of about 2.79 folds was noticed in the

unaffected villages, which is marginally higher than the affected area.


Sl. No.

Particulars Affected Village

Unaffected Village

1. Number of wells 43 56

2. Depth of open well (in mts.) 18.80 18.78

3. Percentage of wells abandoned 6.98 1.79

4. Percentage of wells with quality water throughout the year*

16.28 98.21

5. Percentage of wells with water only during rainy season*

76.74 -

6. No of bore wells in the sample farms 17 25

7. Average depth of bore wells (mts.) 101 116

8. Water quality (%) **

Good 62.50 56.36

Medium 12.50 43.64

Poor 25.00 - *Percentage calculated based on the total number of open wells in the sample farms ** - As perceived by the respondents



82

(Per cent)

Affected Villages Unaffected Villages Sl.No Sources

10 years Back 2003-04

10 years Back

2003-04

1. Canal 46.63 27.91 12.87 7.80

2. Well 15.45 12.45 64.35 75.90

3. Canal+ well 8.78 32.86 15.86 8.51

4. Rainfed 23.08 21.50 6.92 5.31

5. Bore well - 0.23 - -

6. Open well+ Bore well

6.04 5.05 - 2.48

Sources of Irrigation

12.45

32.86

21.50

5.057.80 8.51

5.312.48

27.91

75.90

-10.00

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

90.00

Canal Well Canal+ well Rainfed Open well+Bore well


4.3.6. Area and Productivity

Fig.24 Sources of Irrigation - Bhavani Taluk


83

The critical analysis of the area and productivity of crops in the study area

reported in table 4.59 reveals that the productivity of the crops declined in the

affected villages. In the past, the major crops grown in the affected areas were

turmeric, sugarcane, paddy, fodder cholam, cotton, vegetables, gingelly and

banana. In the unaffected villages area under turmeric was about 17 per cent

whereas in the affected villages it was only 8 per cent. The productivity of

sugarcane was higher (97 tons) in the unaffected villages when compared to the

productivity in the affected villages (90 tons). In the affected villages, about 16

per cent of the total cultivated area was under fodder cholam compared to five

per cent in the unaffected area.

Table 4. 59. Cropped area, Productivity and Cropping Intensity

Affected Villages

Unaffected Villages

Difference Sl.No

Crops

Area (%)

Yield ( t /ha)

Area (%)

Yield (t /ha)

Yield (t /ha)

Per centage

1. Turmeric 8.17 7.79 17.01 12.87 (-)5.08 (-)39.47 2. Sugarcane 23.34 90.26 23.04 96.96 (-)6.07 (-)6.91 3. Paddy 38.41 5.02 30.49 5.11 (-)0.09 (-)1.76 4. Fodder

Cholam 16.57 6.17 5.31 6.91 (-)0.74 (-)10.71

5. Gingelly 8.07 0.68 10.64 0.75 (-)0.07 (-)9.33 6. Banana 3.30 110.10 - - - - 7. Coconut* 0.38 9880 2.84 16,207 (-)6327 (-)39.04 8. Tapioca 1.36 36.68 0.71 37.05 (-)0.37 (-)1.00 9. Green

gram 0.39 1.01 - - - -

10. Groundnut - - 9.96 20.4 - - * yield in Nuts/ha.

Fig.25 Crop Area and Productivity


84


90.26

5.02

36.68

12.87

96.96

5.11 6.91

37.05

7.796.17

0.00

20.00

40.00

60.00

80.00

100.00

120.00

Turmeric Sugarcane Paddy Fodder Cholam Tapioca

C ro ps

Affected villagesUnaffected villages

4.3.7. Proximity of Cultivated Lands to Dyeing Industries The distance between the respondents’ farm and the dyeing industries was less

than a kilometer (0.80 km). Dyeing, bleaching, tanning and sago units are

located all around the villages (Bhavani and Andikulam). The factories are in

operation almost throughout year, and the type of effluents let out was

predominantly liquid in nature.

Table 4.60. Proximity of Dyeing Industries

Sl. No Particulars Affected Village

1. Proximity (Km) 0.80

2. Average months in operation / year 11.45


85

4.3.8. Attitude of the Respondents Towards the Decline in Agricultural Activities It is obvious from the table 4.61 that the interest of the farmers towards agriculture

is declining. It is clear that about 95 per cent of the respondents in the affected

villages expressed that the scarcity of water was the main reason for this decline.

About 75 per cent were of the view that the labour scarcity was the major reason

for the poor performance of agriculture and about 53 per cent of the respondents

opined that poor water quality might be the reason for the declivity.

Table 4.61. Farmers Opinion Towards Decline in Agricultural Activities

Sl. No Particulars Percentage 1. Water Scarcity 95 2. Labour Scarcity 75 3. Poor Water Quality 53 4. Decline in Agricultural Income 40 5. Poor Crop Stand 5

Fa rme rs opinion towards de cline in Agricultura l Activities

95

75

53

40

5

0

20

40

60

80

100

Water Scarcity Labour Scarcity Poor WaterQuality

Decline inAgricultural

Income

Poor Crop Stand

Affe cted ca te gory

Fig.26 Farmers Opinion towards decline in Agricultural Activities - Bhavani Taluk


86

4.3.9 Employment Pattern The employment distribution of the household is reported in Table 4.62. In the

affected villages only about two per cent of the households were engaged in

agriculture alone whereas it was about 43 per cent in the unaffected villages. In

the affected villages about 37 per cent of the households were employed in farm

and non-farm activities whereas it was about 22 per cent in the affected villages.

The farm and diary activities constituted the second largest proportion at 31.67

per cent in affected villages and it was only 6.67 per cent in the unaffected

villages. The combination of all the three activities constituted 21.67 per cent in

affected villages and it was 13.33 per cent in unaffected villages.

Table 4.62 Occupational Distribution of Households

Affected Villages Un affected Villages

Sl.No Particulars

Number

Percent Number

Percent

1. Farm activity only 1 1.67 26 43.33

2. Farm + Dairy activities 19 31.67 4 6.67

Households engaged in on-farm activities only

20 33.34 30 50.00

3. Farm and off-farm activity 5 8.33 9 15.00

4. Farm, non- farm and off-farm activity

13 21.67 8 13.33

5. Farm and non-farm activity 22 36.67 13 21.67

Total Sample households 60 100.00 60 100.00

Earning members in Sample Households (in numbers)

116 106


87

Fig.27 Occupational Distribution of Households - Bhavani Taluk

1.67

31.6

7

8.33

21.6

7

36.6

743.3

3

6.67

15.0

0

13.3

3 21.6

7

0.005.00

10.0015.0020.0025.0030.0035.0040.0045.0050.00

Farm activityonly

Farm + dairyactivities

Farm and offfarm activity

Farm, non farmand off farm

activity

Farm and nonfarm activity

Per

cen

tag

e

Affected Unaffected

4.3.10 Income The income distribution of the sample households is given in the Table 4.63.

When the households are considered, majority earned their wages through the

combination of farm with non farm activities like working in private companies or

by running own bleaching and dyeing units or renting their land either for

factories or for residential purposes. The average annual income of the affected

household was Rs. 1,33,610/- where as in the unaffected area the average

annual income was Rs. 1,19,582/-Since the respondents has either been

employed as wage earners or running their own industrial unit, the share of non-

farm income is found to be substantial. In the affected villages, the income from

farm activities alone constituted 44.38 per cent. This was 57.39 per cent in

unaffected villages. In other categories, farm income formed a part.


88

Table 4.63 Pattern of Average Annual Income in the Sample Households (in Rs.)

Affected Villages Un affected Villages Sl.No Particulars Amount Per

cent Amount Per cent

1. Farm income only 1,500 1.12 53,687 44.90

2. Farm + Dairy activities 52,327 39.16 11,366 9.51

Total income from on-farm activities alone

53,827 40.28 65,053 54.41

3. Farm and off- farm income

5,483 4.10 3,562 2.98

4 Farm, non-farm and off- farm income

20,967 15.69 14,433 12.07

5. Farm and non- farm income

53,333 39.92 36,533 30.55

Average Annual income per Household

1,33,610 100.00 1,19,582 100.00

Fig.28 Pattern of Income - Bhavani Taluk

1.12

39.1

6

4.10

15.6

9

39.9

2

44.9

0

9.51

2.98

12.0

7

30.5

5

0.005.00

10.0015.0020.0025.0030.0035.0040.0045.0050.00

Farm Income Farm + dairyactivities

Farm and offfarm income

Farm, non farmand off farm

income

Farm and nonfarm income

Per

cen

tag

e

Affected Unaffected

4.3.11 Labour Migration


89

From the table 4.64 it is implicit that in the affected area about 53 per cent of the

households migrated from agriculture to other non-farm activities when compared

to 20 per cent in the unaffected area. The percentage of people migrated from

the households in the affected village was 19.92 per cent which was about 10 per

cent high when compared to the unaffected area. The main reasons contributed

for this migration was poor income from agricultural activities and their interest to

earn more from the assured sources without much hard work.

Table 4.64. Migration Details


Unaffected Villages

1. Percentage of Migration 53.33 20.00 2. Percentage of migration in the sample

households 19.92 9.25

3. Permanent migration of the family members

95.00 -

4. Average number of days migrated 296 74 Reasons for Migration

1. Poor income 65.00 4.55 2. To Earn more 45.00 95.45 3. Poor water quality 27.56 - 4. Labour problem 20.00 - 5. To pursue higher education 20.00 -

4.3.12 Assets Position It is observed from the table 4.65 that in the affected villages, about 15 per cent

of the respondents sold atleast part of their lands. Similarly, about 18 per cent of

the respondents sold their livestock due to various reasons like non-availability of

water, labour scarcity etc.


90


Sl. No


Unaffected Villages

1. Land a. Percentage of respondents sold their

lands 15 28

b. Extent of area sold (%) 3.12 8.77 c. Value of sold cropland (Rs./ha) 2,98,472 2,47,915 2. Animals a. Percentage of Respondents sold their

Cattle 18.33 26.67

b. Reasons for sale of livestock i Water Scarcity 9.36 3.33 ii Labour Scarcity 13.21 7.21 iii Drying of animals 10.00 6.67 iv To meet unexpected Expenses 1.67 4.33

4.3.13. Live stock Position From the table 4.66, it is noticed that the possession of livestock was found to be

less in affected villages. In the affected villages, the percentage of buffalo

population was high and in the unaffected area cow population was more by 18.8

per cent. Degradation of water has contributed to changes in the composition of

livestock population. It was observed that the farmers in the affected villages have

invested more in buffalo. Rearing of livestock was less because of the non-

availability of fodder due to restricted agricultural activities. Owing to the

deterioration of water quality, farmers in the affected villages had to spend more on

purchasing fodder. Majority of the farmers have largely engaged themselves in

non-farm activities as wage earners and attached only secondary importance to

agricultural occupations. Now the farmers are of the habit of allowing their livestock

to graze their own fallow croplands, which were once the promising fields for

bumper crop outputs.


91

Table 4.66. Possession of Live stock

(Number/household) Affected Villages Unaffected Villages Sl.No Category Number Per cent Number Per cent

1. Cow 1.18 36.98 1.37 55.78 2. Buffalo 1.57 48.96 0.98 40.14 3. Bullock 0.02 0.52 - - 4. Sheep 0.33 10.42 0.03 1.36 5. Calf 0.02 0.52 - - 6. Poultry 0.08 2.60 0.07 2.72

4.3.14. Externalities on Human and Animal Health As stated already, the effluents discharged from the industries have affected

substantially the quality of water and soil, which in turn created disorders in

human and animal health. It could be understood from the table 4.67 that the

respondents in the affected area had to spend more than the unaffected area. In

the affected area, an average amount of Rs.100 was spent towards physician

cost and Rs.30 towards the medicine. About six per cent loss in milk production

was reported in the dairy sector. Other disorders like no calving and weight loss

were also witnessed.

Table 4.67. Externalities on Human and Animal Health Sl.No Particulars Affected village Human Health

1. Cost to physician (Rs/annum/household) 1200 2. Cost of medicine (Rs./month/household) 360 Animal Health

1. Loss of income from milk production (Rs./ annum) 2719 2. Percentage loss in milk yield 6.32

4.3.15. Opinion of Respondents about Water Quality The respondents in the unaffected villages use their well water for drinking and

other domestic purposes whereas, their counter parts in the affected areas

depend on the public taps (municipality water). On an average people travel a


92

distance of about 0.52 km to fetch water. The respondents were also asked

about the deterioration in water quality in terms of taste, colour, turbidity and

odour and the results obtained are reported in Table 4.68. As noticed in other

sample villages, the quality was observed to be poor in the summer season when

compared to rainy season.

Table 4.68. Opinion of Respondents about Water Quality Sl.No Characters Parameters Per cent

Poor - medium 25

1. Taste Summer Season

Good 75 Poor - medium 25

Rainy Season

Good 75 High - Medium 25

2. Colour Summer Season

Low 75 High - Medium 25

Rainy Season

Low 75 High 25 Medium -

3. Turbidity Summer Season

Low 75 High 25 Medium -

Rainy Season

Low 75 High - Medium -

4. Odour Summer Season

Low 100 High - Medium -

Rainy Season

Low 100 4.3.16. Willingness to Pay (WTP)


93

The WTP of the households to pay for improving their agricultural activities and

for internalizing externalities was estimated. Majority of the households

expressed that poor income was the major hurdle affecting the ability to pay.

About 53 per cent of the farmers were willing to pay between Rs.25, 001 and

Rs.50, 000 towards internalizing externalities. About 42 per cent were for

quarterly mode of payment, 10 per cent for half yearly mode and 15 per cent for

annual mode of payment.


Sl.No Particulars Number Per cent

1. Households’ willing to pay 40 66.67

2. Amount

Rs.20, 001-Rs.25,000 3 5.00

Rs.25, 001-Rs.50,000 32 53.33

Rs.50, 001-Rs.75,000 5 8.33

3. Not willing to pay 20 33.33

4. Mode of Payment

Quarterly 25 41.67

Half yearly 6 10.00

Annual 9 15.00

Fig.29 Willingness to Pay – Bhavani Taluk


94

Willingness to Pay

5.00

53.33

8.33

0.00

10.00

20.00

30.00

40.00

50.00

60.00

Rs.20, 001 – Rs.25,000 Rs.25, 001 – Rs.50,000 Rs.50, 001 – Rs.75,000


4.3.17. Averting and Defensive Expenditure Dyeing factory effluents have made the farmers to incur the averting expenditure

on cropland and irrigation water, which is indicated in Table 4.70. It is obvious

from the table that farmers had to spend more for banana.


Sl.No Particulars Expenditure Rs/ha

1. Paddy 988

2. Sugarcane 844

3. Turmeric 823

4. Banana 3705

5. Tapioca 988

Soil and Water Sample Analysis


95

4.3.18. Physico – Chemical characteristics of water samples collected at Bhavani taluk

The results of the water sample analysis of Bhavani taluk is presented in table

4.71.

Table 4.71. Physico – Characteristics of water samples collected at

Bhavani Taluk S.No Parameters Affected Unaffected

1. pH 8.56 – 9.20 6.55 – 7.22

2. EC (ds/m) 2.56 – 5.27 0.58 – 1.98

3. BOD (mg/l) 96 – 170 24 – 85

4. COD (mg/l) 235 – 425 60 – 210

5. Chloride (mg/l) 198 – 490 85 – 147

6. Sulphate (mg/l) 30 – 60 15 – 45

7. Calcium 610-3650 356– 1850

8. Magnesium 25-85 20-48

9. SAR 32 - 37 24 - 28

10. Chromium (mg/l) 0.25 – 0.89 BDL – 0.003

11. Lead (mg/l) 0.14 – 0.79 BDL – 0.003

12. Cadmium (mg/l) 0.12 – 0.48 BDL – 0.005

13. Nickel (mg/l) 0.17 – 0.87 0.001 – 0.08

The pH of the water samples collected from affected villages of Bhavani taluk

were high (8.56 to 9.20) when compared to samples collected from unaffected

villages of same taluk (6.55 to 7.22). Samples of affected region recorded higher

EC value of 2.56 to 5.27ds/m which is much higher than the critical limit of 2.25

dsm-1 prescribed for irrigation water; It is very high when compared to unaffected

regions which recorded 0.58 – 1.98ds/m which is slightly higher than the critical

limit.


96

In general, the BOD values of samples from affected villages were found to be

higher recording 96 to 170mg l-1 compared to 24 to 85 mg l-1 in the unaffected

regions. The BOD values of both the regions are much higher than

recommended limit 2 mg l-1 for drinking and also 30 mg l-1 for irrigation. The COD

in affected area water samples are 235 – 425 mg l-1, which are higher than the

prescribed limit whereas in the unaffected villages it ranges between 60 and 120

mg l-1 only.

The chloride content recorded higher value of about 198 to 490 mg l-1 in the

affected regions than in the unaffected areas which recorded 85 – 147 mg l-1.

The sulphate content in the affected regions accounts to about 30 – 60 mg l-

1.compared to 15 – 45 mg l-1 in unaffected regions. Both the chloride and

sulphate values of water samples of both the affected and unaffected regions are

well below the critical limits. Calcium contents of the affected samples are also

very high when compared to unaffected region samples. The water samples of

affected villages recorded 32-37 sodium absorption ratio which is well above the

critical limit and the samples of unaffected villages also recorded SAR, which is

slightly higher than the limit.

The heavy metals like chromium, lead and cadmium contents were higher in

affected areas compared to unaffected areas where they are below detectable

limits. Whereas, the water samples collected from affected regions recorded the

Cr ranging from 0.25 – 0.89, Pb ranging from 0.14 – 0.79, Cd ranging from 0.12 –

0.48 and 0.17 – 0.87 mg l-1 of Ni which are higher than the maximum permissible

limits.

4.3.19. Assessing the changes in soil properties of Bhavani taluk


97

The soil samples collected from the study villages of Bhavani taluk are presented

in table 4.72. Table 4.72. Characteristics of soil samples collected at selected villages of

Bhavani taluk

Parameters Affected Unaffected

pH 7.70 – 8.94 6.20 – 7.12

EC (ds/m) 2.14 – 3.99 0.12 – 0.69

Available Nitrogen (kg/ha) 120 – 350 115 – 169

Available Phosphorus (kg/ha) 20 – 78 10 – 36

Available Potash (kg/ha) 105 – 174 21 – 147

Chromium (mg/kg) 23 – 85 BDL

Lead (mg/kg) 1.47 – 4.25 BDL – 0.05

Cadmium (mg/kg) 1.36 – 4.78 BDL

Nickel (mg/kg) 9 - 19 0.001 – 0.07

The soil samples collected from Bhavani recorded the highest pH in affected

regions (7.70 – 8.94) compared to unaffected regions (6.20 – 7.12). The

EC value was also higher in samples of affected villages which recorded 2.14 –

3.99 ds/m when compared to EC values of samples of unaffected villages (0.12 –

0.69 ds/m).

The available N content higher in affected villages (120 – 350 kg/ha) which

comes under the medium rating (280 - 450kg/ha). The unaffected regions

showed values between 115 – 169 kg/ha which comes under the low rating (0 –

280 kg/ha). The available P content was ion the range of 20 – 78 kg/ha in

affected regions and in the unaffected region, it was between 10 – 36 kg/ha.

Both the samples come under high rating of >22 kg/ha. The available K content

was maximum in affected regions (105 – 174/ha) which is classified under low


98

rating (<280kg/ha) when compared with the unaffected villages which exhibited

an available K content of 21 – 147 kg/ha and lies in medium rating (118 -

280kg/ha).

In general, all the four heavy metal contents were maximum in soil samples

collected from affected villages than unaffected villages. The level of chromium

was found to be in the range of 23 -85 ppm in affected regions but it was below

detectable limit in unaffected regions. However, the chromium level of affected

villages is also well with in the critical limit of 100 ppm.

Concentration of lead in affected soil samples ranged between 1.47 – 4.25 ppm

when compared to unaffected regions which recorded BDL – 0.05 ppm, which

are well below the permissible limit 100 ppm. The heavy metal cadmium was at

higher level (1.36 – 4.78 ppm) in affected villages when compared to unaffected

villages (BDL). The affected villages contain higher values than the unaffected

villages. It exceeds the critical limit of 3.0 ppm. The soil samples of affected

villages recorded a nickel content ranged between 9- 19 ppm whereas, it was in

the range of 0.001 and 0.07 in samples of unaffected regions, which are well

within the prescribed limit of 50 ppm.

Workers The youths in the affected villages employed themselves in the industries located

in and around the sample villages. The wage rate of the industrial units was high

when compared to the agricultural labour wage. It was reported that the work

culture was quite comfortable when compared to the agricultural activities.

4.3.20. Nature of Work In the affected villages almost all the workers were employed in dyeing

industries. Whereas, in the unaffected area about 70 per cent of the workers earn


99

their wages by being in agricultural operations. About 15 per cent worked as

permanent agricultural labourers and only 15 per cent employed in spinning mills

and five per cent have run their own business and about five per cent employed

in government services.

Table 4.73. Nature of Work

Sl.No. Nature of Work Affected Area Unaffected Area

1. Dye master 30.00 -

2. Hydropher (Dye unit) 20.00 -

3. Supervisior (Dye unit) 5 -

4. Labourer (Dye unit) 35 -

5. Sampler (Dye unit) 10 -

6. Agricultural labourers - 55

7. Permanent agricultural labourers - 15

8. Worker in Spinning mills - 15

9. Petty shop owners - 5

10. Employed in Government services - 5

4.3.21. Employment The duration of the employment and the wages earned by the sample

respondents of the workers category are presented in Table 4.74. It is revealed

that the average days of employment in the affected area are more. Also, the

average wage earning is high in the affected area by 25.39%. This is due to the

luring employment opportunities provided by the industry to the people in the

affected area. Also, the annual income is high in the affected area when

compared to unaffected area. The employment of other family members in the

affected area shows that only 36.84 per cent were found to depend on agriculture

while it was about 87 per cent for the unaffected category. Employment in


100

private sectors was 15.79 per cent in the affected area whereas it was only 6.25

per cent in the unaffected area. The income earned by the other family members

in the affected area was found to be more by Rs.9,895 when compared to

unaffected villages.

Table 4.74. Pattern of Employment

Sl. No. Particulars Affected

Area Unaffected

Area 1. Days of monthly employment 23.25 21 2. Average wages earning (Rs./month) 2530 2170 3. Number of family members working in their own

industry 0.45 -

4. Number of family members working in other industries

0.50 0.75

5. Annual income of respondents (in Rs.) 30,360 24,211 Employment of the Family Members

1. Dyeing 47.37 - 2. Agricultural labourers 36.84 87.5 3. Private company 15.79 6.25 4. SHG - 6.25

4.3.22. Benefits Availed by the Workers The nature of benefits enjoyed by the workers of the private companies is given

in Table 4.75. About 11 per cent has availed accident claims and that too for the

accidents that happened in the work spot. About 89 per cent enjoyed the benefit

of availing bonus. This benefit was extended to the workers based on their

experience. An average of Rs.740/- was given as bonus to celebrate pongal

festival. Other benefits like medical, ESI, and provident fund are not extended to

the workers in this study area.


101

Table 4.75. Benefits Availed by the Workers

Sl.No Benefits Per cent 1. Accident claims 11.11 2. Bonus 88.89

4.3.23. Sufferings Faced About 20 per cent of workers were suffering from skin related ailment and

tuberculosis (TB). The TB patients are undertaking free treatment. Some

patients are undergoing treatment at their own cost by spending about Rs.250

towards physician and Rs.300 towards medicine per month. Other acute

problems like cracks, boils, itching, skin rashes are also reported throughout the

year. On an average, an individual spends about Rs.40 and Rs.56.67 towards

physician cost and medicine cost per annum. About 40 per cent reported for no

illness. The results are presented in Table 4.76 below.

Table 4.76. Sufferings Faced by the Respondents

Sl.No Particulars Affected (Per cent) 1. Skin Cracks 35 2. Boils, itching, etc. 20 3. Skin rashes 5 4. No problem 40 5. Working days lost Nil 6. Cost to physician (Rs/annum) 40 7. Cost of medicine (Rs/annum) 56.67

4.4. Erode 4.4.1. Family Size The details on total number of persons and the overall family size are presented

in Table 4.77. The overall size of family was 3.86. Between the two categories,

the average family size was found to be relatively high at 3.93 for the unaffected

category as compared to 3.78 for the affected groups.


102

Table 4.77. Family Size (Numbers)

Sl. No. Category of Respondents

Family Size

1. Affected area 3.78 2. Unaffected area 3.93

Overall 3.86

4.4.2. Education In the affected and unaffected villages, 20 per cent and 22 per cent of the sample

respondents were observed to be illiterates, respectively (Table 4.78). Mainly the

elders of the households were observed to be illiterates. About 30 per cent had

primary education in the affected villages, which was higher by 4.11 per cent

when compared to the respondents in unaffected area. Only 26.87 per cent and

6.62 per cent of the affected villages were observed to have secondary and

higher secondary education. About 17 per cent of households in the affected

villages was reported to hold a diploma and / or degrees. This was marginally

higher than that of the unaffected category.


Affected Area Unaffected Area Sl. No.

Particulars Numbers Percentage Numbers Percentage

1. Illiterates 45 19.82 52 22.03 2. Primary 68 29.96 61 25.85 3. Secondary 61 26.87 74 31.36 4. Higher

Secondary 15 6.62 19 8.05

5. Graduates 38 16.73 30 12.71 Total 227 100.00 236 100.00

4.4.3. Land Holding Pattern


103

The land area possessed by individual household and area under cultivation are

presented in Table 4.79.

Table 4.79. Land Holding Details

(in ha)

Affected Area Unaffected Area Type of land Area

Owned Area

Cultivated Area

Owned Area

Cultivated Wet 0.94

(55.91) 0.89

(58.84) 0.58

(31.51) 0.58

(31.51) Garden 0.59

(35.07) 0.55

(36.25) 1.22

(66.30) 1.22

(66.30) Dry 0.15

(9.02) 0.07

(4.92) 0.04

(2.19) 0.04

(2.19) Total 1.68

(100.00) 1.51

(100.00) 1.85

(100.00) 1.85

(100.00) Percentage of crop land under cropping

89.58 100.00

Figures in parentheses indicate percentage

It may be seen from the table that the average size of land possessed by the

sample households in the affected village was 1.68 ha which less by 0.17 is ha

than the unaffected category with 1.85 hectares. In the affected areas, the

average size of the area owned was1.68 ha of which only 1.51 ha was under

crops, compared to 1.85 ha in unaffected regions. As discussed already,

the effluents had created changes in the cropping pattern and employment

opportunities. 4.4.4. Well Irrigation The irrigation canals namely Kalingarayan, Lower Bhavani Project Canal and

Perumpallam Oodai are the major sources of irrigation. As the quality of the

water has deteriorated, now the respondents are relying on open wells and bore


104

wells for irrigation. In wetlands, the ground water level ranges between 5 metres

and 15.3 metres whereas in garden lands the depth ranges between 15.3

metres and 36.33 metres. The total number of wells in the sample farms was 42

and 48 in the affected and unaffected villages, respectively. The depth of well

was 1.54 metres more in the affected areas. Only about 52 per cent of the wells

in the affected villages were found to have water throughout the season. The

number of bore wells in the unaffected villages was about two times high when

compared to the affected villages. However, none of the wells was abandoned.

In the affected villages only 2.5 per cent of the respondents perceived that the

quality of the well water was medium and the rest perceived it to be poor. In the

unaffected area, about 70 per cent perceived that their well water was of medium

quality.


Sl. No.


Unaffected Villages

1. Number of wells 42 48 2. Average depth of open well (in mts.) 16.50 15.00 3. Percentage of well with water

throughout** 52.38 83.33

4. Percentage of well with water in rainy season**

47.62 16.67

5. Number of bore wells in sample farms 13 28 6. Average depth to bore wells (mts.) 200 94.34 7. Water quality* (Per cent) ( Per cent)

Good - - Medium 2.50 70.73 Poor 97.50 29.27

* As perceived by the respondents. ** Percentage calculated upon the total number of wells in the sample farms

4.4.5. Sources of Irrigation


105

It is implicit from the table 4.81 that in the affected locality area irrigated by canal

has declined by about 24 per cent. The area irrigated by wells has marginally

increased by about six per cent during the year 2004-05. In the unaffected area,

the overall area under irrigation has increased. In both the study villages the

main source of irrigation was found to be canal and open wells. In the

unaffected areas, bore wells have started gaining importance as 2.77 and 23.36

per cent area were being irrigated by bore well alone and by the bore wells and

open wells together, respectively. While the rainfed area declined substantially in

unaffected area, it increased by about 22 per cent in the affected area.


Affected Area (Percentage)

Unaffected Area (Percentage)

Sl. No.

Particulars

10 years back

2004-05 10 years back

2004-05

1. Canal 66.30 42.72 39.48 11.07

2. Open well 15.87 21.46 43.22 43.41

3. Canal + Open well - 14.18 - 16.22

4. Bore well - - - 2.77

5. Open well + Bore well - - - 23.36

Total Irrigated Area 82.17 78.36 82.70 96.83

6. Rain fed area 17.83 21.64 17.31 3.17

Fig. 30 Sources of Irrigation – Erode Taluk


106

Sources of Irrigation

0 0

21.64

11.07

16.22

2.77

23.36

3.17

14.18

21.46

42.72 43.41

-10

0

10

20

30

40

50

Canal Open well Canal + Openwell

Bore well Open well +Bore well

Rain fed area


4.4.6. Area and Productivity – A Detailed Analysis The area and productivity of crops grown in the study area are reported in Table

4.82. In the affected area, the area under paddy declined by about ten per cent.

The main crops grown ten years back were paddy, fodder cholam, sugarcane,

banana, gingelly, turmeric, coconut, cotton and vegetables. Though the area

under coconut increased over years the productivity has comedown by 9500

nuts/ha. Also, new crops like daincha and mango were included in the cropping

pattern recently.

The reason for the productivity decline was due to poor soil and water qualities.

The farmers were unable to make much profit in agriculture and they had started

doing non-farm activities like undertaking job works in textile factories and

employing themselves as wage earners in the private companies.

Table 4.82. Area and Productivity of Crops


107

Affected Area Unaffected Area Difference Sl.No

Crops

Area (%)

Yield Area (%)

Yield Yield Percen tage

1. Paddy 55.36 5.06 57.67 5.78 (-)0.72 (-)12.46

2. Fodder Cholam

25.67 6.17 3.17 6.92 (-)0.75 (-)10.84

3. Sugarcane 1.53 80.28 2.21 104.45 (-)24.17

(-)23.14

4. Banana 0.77 86.45 - - - -

5. Gingelly 3.07 0.60 15.66 1.80 (-)1.20 (-)66.67

6. Turmeric 1.53 3.21 0.95 4.32 (-)1.11 (-)25.69

7. Coconut* 7.85 13675 4.74 26346 (-) 12671

(-)48.09

8. Cotton - - 0.63 0.90 - -

9. Cholam - - 2.63 4.06 - -

10. Groundnut 0.38 0.72 8.54 1.86 (-)1.14 (-)61.29

11. Tapioca - - 3.80 23.05 - -

12. Mango 2.07 - - - - -

13. Daincha 0.77 1.24 - - - - * Yield in tons/ha except Coconut (nuts/ha.)


108


6.170.00

5.78 6.92

104.45

4.32

23.05

80.28

5.06 3.210.00

20.00

40.00

60.00

80.00

100.00

120.00

Paddy Fodder Cholam Sugarcane Turmeric Tapioca

Crops

Affected villagesUnaffected villages

4.4.7. Farmers Opinion about Decline in Agricultural Activity It could be seen from the table 4.83 that almost the entire group in the affected

categories expressed the scarcity of water as the main reason for the decline in

agriculture. About 84 per cent were of the view that poor water quality was the

main reason for the weak performance of agriculture. Similarly, 78.33 per cent

attributed labour scarcity as the prime reason for the poor agricultural operations.

Many found it difficult to get labour for the agricultural activities, as the

agricultural laborers had migrated to the nearby industries. About 57 per cent of

farmers in the affected category reported decline in agricultural income as one of

the factors that led to sluggishness in agricultural activities.

Fig. 31 Crop Area and Productivity – Erode Taluk


109

Table 4.83. Opinion of Sample Farmers towards Decline in Agricultural Activities

(Per cent)

Sl.No. Particulars Affected Category

1. Water scarcity 100.00 2. Labour scarcity 78.33 3. Poor water quality 83.33 4. Decline in agricultural income 56.67 5. Poor crop stand 58.33

Farmers opinion towards decline in Agricultura l Activities

100.00

78.3383.33

56.67 58.33

0.00

20.00

40.00

60.00

80.00

100.00

Water scarcity Labour scarcity Poor waterquality


income

Poor crop stand

Affected ca tegory

4.4.8. Changes in Value of Agricultural Lands

Fig. 32 Farmers Opinion towards decline in Agricultural Activities - Erode Taluk


110

The details on the changes in the value of agricultural land as perceived by the

respondents of the study villages are presented in Table 4.84.

Table 4.84. Changes in Value of Agricultural Lands (Rs./ha)

Sl.No. Particulars Affected Area Unaffected Area

1. 10 years back 4,72,000 9,97,674

2. 2004-05 11,17,000 12,73,079

3. Change in value of land (per cent)

136.65 27.60

A close examination of Table 4.84 reveals that the percentage increase in the

affected area in the last 10 years was about 136 per cent whereas it is only 27.60

per cent in the unaffected area. This huge increase noticed in the affected area

might be due to the gaining importance of industries. The agricultural lands are

getting converted into industries or as house sites. Moreover in one of the

affected village (S.P.Agraharam) farmers are selling their wetlands to the

government @ Rs. 4, 00,000 for the construction of EB barrage.

4.4.9 Employment Pattern The particulars of employment of the households in the study area are given in

Table 4.85. The total number of workers was found to be more by about 23 per

cent in the affected study villages. Only 1.67 per cent of the sample households

depended only on agriculture in the affected villages whereas it was about 20 per

cent in the unaffected villages. In the affected areas, a vast majority of about 32

per cent depended on on -farm, non-farm and off-farm activities like agriculture,

agricultural labourers, dairy, money lending, employing in private companies as

wage earners etc.


111

Table 4.85 Occupational Distribution of Households

Affected Area Unaffected Area Sl.No Particulars Number

s Per cent Numbers Per

cent 1. Farm only 1 1.67 12 20.00 2. Farm + Dairy activities 3 5.00 5 8.33

Total Households engaged in on-farm activities alone

4 6.67 17 28.33

3. On - farm + Non-farm activities

26 43.33 26 43.33

4. Farm + Off-farm activities 11 18.33 2 3.33 5. Farm + Non-farm and

Off-farm activities 19 31.67 15 25.00

Total 60 100.00 60 100.00 Earning members in Sample Households (in numbers)

124 110

Fig.33 Occupational Distribution of Households - Erode Taluk

1.67 5.

00

48.3

3

18.3

3

31.6

7

20.0

0

8.33

43.3

3

3.33

25.0

0

0.00

10.00

20.00

30.00

40.00

50.00

60.00

Farm only Farm + dairyactivities

On farm + nonfarm activities

Farm + off farmactivities

Farm + non farmand off farm

activities

Perc

enta

ge

Affected Unaffected

4.4.10 Income Distribution The income distribution of the household is given in the Table 4.86. Only one

per cent of the households income came through farm activity in the affected


112

area as against 16.57 per cent in the unaffected area. Income from farm

activities overall constituted 5.30 per cent in affected villages as against 34.89

per cent in unaffected villages. In the affected villages, about 55 per cent of the

income came from the combined activities of on-farm and non-farm whereas it

was relatively less at 42 per cent in the unaffected villages.

Table 4.86 Pattern of Annual Income in Sample Household (in Rs.)

Affected Area Unaffected Area S.No Particulars Amount Per

cent Amount Per cent

1. Farm only 1,166 1.00 16,209 16.57 2. Farm + Dairy activities 5,000 4.30 17,917 18.32

Income from on-farm activities alone

6,166 5.30 34,126 34.89

3. Farm + Off-farm 16,500 14.19 1,512 1.55 4. On-farm + Non-farm 63,375 54.50 41,109 42.03 5. Farm + Non and Off-

farm 30,242 26.01 21,061 21.53

Average Annual Income per Household

1,16,283 100.00 97,808 100.00

Fig.34 Pattern of Income - Erode Taluk

1.00 4.

30

54.5

0

14.1

9 26.0

1

16.5

7

18.3

2

42.0

3

1.55

21.5

3

0.00

10.00

20.00

30.00

40.00

50.00

60.00

Farm only Farm + dairyincome

On farm + nonfarm income

Farm + off farmincome

Farm + non farmand off farm

income

Perc

enta

ge

Affected Unaffected


113

4.4.11. Migration It is implicit from the table 4.87 that in the affected areas about 58 per cent of the

households were found to migrate when compared to 30 per cent in unaffected

area. Percentage of the earning members migrated from the sample households

in the affected villages was 33.05 per cent and it was 3.5 per cent more than the

average migration in the unaffected area. Over 68 per cent of the labour force

had migrated permanently. The main reason attributed for the migration was to

earn more and also due to the poor income from the agricultural operations.

Table 4.87. Migration


Unaffected Area

1. Percentage of Households migrated 58.33 30.00 2. Percentage of migration from sample

household 33.05 29.54

3. Percentage of permanent migration of the family members

68.33 15.00

4. Number of days migration 164 87 Reasons for migration

1. Poor income 54.29 100.0 2. To Earn more 71.43 50.00

4.4.12. Asset Position It is obvious that over 16 per cent of the respondents in the affected area had

disposed atleast 3.43 per cent of their cropland due to poor water quality and labour

scarcity. In the affected villages, 31.67 per cent of the respondents had sold their

livestock due to various reasons like poor water quality, water and labour scarcity. In

the affected villages however, the extent of land area disposed off was higher (11.69

per cent) and the respondents selling livestock was marginally lower (23.33 per

cent).


114


Sl.No Particulars Affected Village

Un affected Village

I. Sale of Land 1. Percentage of Respondents

sold land 16.67 26.67

2. Average land area sold (ha) 0.34 0.37 3. Percentage of land sold 3.43 11.69 4. Value of the sold area (Rs./ha) 2,16,488 9,62,448 II. Sale of Animals 1. Percentage of Respondents

sold animals 31.67 23.33

2. Value of animals sold (Rs) 14,095 1,407 III Reasons for sale of livestock a. Poor Water Quality 11.67 1.67 b. Water Scarcity 10.00 8.33 c. Labour Scarcity 6.67 10.00 d. Drying / Aged animal 3.33 1.67 e. To meet out unexpected

expenses - 1.67

4.4.13. Farm Level Availability of Livestock The possession of livestock was found to be less particularly with respect to cow,

buffalo and sheep (Table 4.89). Though the number of livestock possessed

seemed to be high in affected villages, the average possession was similar in

both cases. This was because the water in the river, community tank and well

were polluted and it affected the very basic original characteristics and the fertility

of the soil due to the accumulation of effluents in and around the affected

villages. It was observed that the farmers invested more in buffalo (than cow) in

the affected area. The number of bullocks owned by the farmers was also

significantly less due to partial farm mechanization and poor agricultural

activities.


115

Owing to the poor land and water qualities, farmers had to spend more on

purchasing fodder from outside and more time in maintenance of animal’s viz.,

cows, buffaloes, goats, sheep, etc. Majority of the farmers in the affected

villages were engaged in non-farm activities like undertaking job works and

attached only secondary importance to agricultural occupation.

Table 4.89. Possession of Livestock (Number / household)

Sl.No. Category Affected Villages

Unaffected Villages

1. Cow 0.58 0.50

2. Buffalo 1.47 0.48

3. Bullock 0.03 -

4. Sheep 0.03 0.55

5. Calf 0.05 0.03

4.4.14. Externalities on Human and Animal Health The effluents discharged from the industries have affected the quality of water

and soil, which in turn had created disorder in animal and human health. The

results on externalities on human and animals health are reported in Table 4.90.

It could be seen that the respondents apply coconut oil and salt mix on the

infected area to heal the wounds caused by dyes. General problems like cracks,

boils, skin irritation and wheezing were witnessed. The respondents in the

affected area spent on an average about Rs.125/- towards the cost of medicine.

Expenses towards physician are not reported. About 6.25 per cent loss

(Rs.1,759) in milk production was observed in animals. Besides, reduction in

weight and decline in reproduction rate were also noticed in animals.


116

Table 4.90. Externalities on Human and Animal Health

Sl.No. Particulars Affected Villages I Humans

1. Cost of medicine (Rs. / annum) 125 2. Cost to Physician (Rs./ annum) - II Animals 1. Loss of milk Yield (Rs./ per annum) 1,759 2. Per centage loss in milk production 6.25

4.4.15. Opinion of Respondents about Well Water Quality The respondents in the affected villages use well water and public tap for

drinking purposes. Whereas the sample households of unaffected areas use

only well water. On an average, they travel about 0.32 km/day to fetch drinking

water. The respondents were also asked about the deterioration in water quality

in terms of taste, colour, turbidity and odour. Their responses are reported in the

Table 4.91.

Table 4.91. Opinion of Farmers’ on Well Water Quality

Sl.No. Water Quality Characters Summer Season Rainy Season 1. Taste Poor 97.50 70.00 Medium 2.50 30.00 Good - -

2. Colour High - - Medium 45 45 Low 55 55

3. Turbidity High 97.50 97.50 Medium - - Low 2.50 2.50

4. Odour High 100.00 100.00 Medium - - Low - -


117

4.4.16. Willingness to Pay (WTP) The willingness of the household to pay for the expenses towards improving

agricultural land and water quality was estimated and reported in Table 4.92.

About 58 per cent were willing to pay a minimum of Rs.25, 000 and a maximum

of Rs.60, 000. Majority of the household expressed that poor income was the

major constraint affecting their ability to pay. A vast majority of about 74 per cent

of the sample household were willing to pay between Rs.25, 001 and Rs.50, 000.

About 23 per cent were willing to pay between Rs.50, 001 and Rs.75, 000.

None were interested to pay more than Rs.75, 000. While 85.71 per cent opted

for the quarterly mode of payment and only 2.86 per cent preferred monthly

payment.


Sl.No. Particulars Number Per cent

1. Household willing to pay 35 58

2. Household not willing to pay 25 42

3. Amount of WTP

Rs.20, 001 – Rs.25,000 1 2.89

Rs.25,001 – Rs.50,000 26 74.29

Rs.50, 001 – Rs.75,000 8 22.86

4. Mode of payment

Monthly 1 2.86

Quarterly 30 85.71

Half yearly 1 2.86

Annual 3 8.57

Total 35 100.00


118

Willingness to Pay

2.89

74.29

22.86

01020304050607080

Rs.20, 001 – Rs.25,000 Rs.25, 001 – Rs.50,000 Rs.50, 001 – Rs.75,000


4.4.17. Averting Expenditure The dyeing factory effluents made the farmers to incur additional expenditure on

cropland. From the table 4.93 it could be observed that the farmers had to spend

a major share on soil amendments by applying FYM (Farm Yard Manure). A

farmer cultivating paddy and cholam had to spend on an average over Rs.919

and Rs.468 per ha respectively towards averting expenditure for extra seeds,

organic manure etc. No additional expenditure was made on irrigation and

drinking water.


Sl. No. Crops Expenditure Rs./ha

1. Paddy 919

2. Cholam 468

Fig. 35 Willingness to Pay – Erode Taluk


119

Soil and Water Sample Analysis 4.4.18. Physico – Chemical characteristics of water samples collected at Erode taluk In Erode taluk, water samples were collected from the affected and unaffected

villages and the results are presented in the table 4.94.

The water samples taken from Erode district recorded a pH of 8.60 to 9.26 in

affected regions compared to a pH of 7.12 to 8.01 in unaffected regions. The EC

value was high in affected area recording 2.98 to 5.55ds/m compared to

unaffected area which recorded about 1.12 to 2.36 ds/m. The EC value of

affected samples indicated its unsuitability for irrigation.

The water samples of affected region recorded a maximum BOD of about 80 to

140 mg l-1 compared to about 27 – 67 mg l-1 in unaffected regions. These values

are much higher than the maximum permissible limits. Maximum COD level of

200 – 350 mg l-1 was recorded in water samples of affected regions which

exceeds the permissible limit and a low COD value was recorded in unaffected

regions (70 to 170 mg l-1).

The chloride (225 to 490 mg l-1) and sulphate contents (28 –65 mg l-1) were

maximum in water samples of affected villages of Erode taluk than the samples

collected from unaffected villages which recorded 95 to130 mg l-1 and 25 – 58

mg l-1 of chloride and sulphate respectively, which are below the critical limits of

500 and 1000 mg l-1 respectively. The calcium content in affected villages was

found to be 410-3150mg l-1 and 245– 2150 mg l-1 in the unaffected villages. Both

the regions exceed to a greater extent when compared with critical limit of 100

mgl-1. The magnesium content ranges from 35 – 80 mg l-1 in affected regions and

15-52 mg l-1 in unaffected regions. Both the regions fall with in the critical limit of


120

150 mg l-1. The SAR of affected and unaffected samples were in the range of 28

– 36 and 20 -24 respectively.

The heavy metals like chromium, lead, nickel and cadmium contents were found

to be higher in affected areas compared to unaffected areas. The water samples

of affected region recorded the Cr level ranging from BDL – 0.96 mg l-1, Pb of

BDL –0.58 mg l-1, Cd of BDL – 0.11 mg l-1 and 0.10 – 0.88 mg l-1 of Ni. All the

metal contents exceeded their respective critical limits. Whereas, the water

samples collected from unaffected regions have higher levels of lead and nickel

exceeding the critical limits but the level of chromium and cadmium are very less

when compared to the limits. Table 4.94. Physico – Characteristics of water samples collected at Erode

Taluk

S.No Parameters Affected Unaffected 1. pH 8.60 - 9.26 7.12 – 8.01 2. EC (ds/m) 2.98 - 5.55 1.12 – 2.36 3. BOD (mg/l) 80 – 140 27 – 67 4. COD (mg/l) 200 – 350 70 – 170 5. Chloride (mg/l) 225 – 490 95 – 130 6. Sulphate (mg/l) 28 – 65 25 – 58 7. Calcium (mg/l) 410-3150 245– 2150 8. Magnesium (mg/l) 35 - 80 15-52 9. SAR 28 - 36 20 -24

10.. Chromium (mg/l) BDL – 0.96 BDL 11. Lead (mg/l) BDL –0.58 BDL – 0.23 12. Cadmium (mg/l) BDL – 0.11 BDL – 0.004 13 Nickel (mg/l) 0.10 – 0.88 BDL – 0.26

4.4.19. Assessing the changes in soil properties of Erode taluk


121

The soil samples collected from the study villages of Erode taluk are presented in

table 4.95.

The soil samples taken from Erode taluk recorded a higher pH of about 7.96 to

8.99 in affected regions compared to unaffected regions (6.50 to 7.56). The EC

was also higher in affected regions (2.58 to 4.57ds/m) when compared to

unaffected regions which recorded 0.12 to 1.57ds/m.

The available N was found to be higher in affected regions (214 – 440 kg/ha) and

this comes under medium rating (280 – 450 kg/ha). In the unaffected regions the

values ranged between 105 and 245 kg/ha which is classified under low rating (0

– 280 kg/ha). The available P content in affected regions was about 10 – 25

kg/ha which according to the standard limit comes under high rating (>22 kg/ha)

and unaffected region samples recorded 10 – 19 kg/ha of available P which is

classified under medium rating. Similarly, the available K content accounts for

higher value in affected regions (122 – 247 kg/ha) whereas, the unaffected

villages recorded between 12 – 156 kg/ha of available K, which comes under

medium rating (118-280 kg/ha).

Table 4.95. Characteristics of soil samples collected at selected villages of Erode taluk

Parameters Affected Unaffected pH 7.96 – 8.99 6.5 – 7.56 EC (ds/m) 2.58 – 4.57 0.12 – 1.57 Available Nitrogen (kg/ha) 214 – 440 105 – 245 Available Phosphorus (kg/ha) 10 – 25 10 – 19 Available Potash (kg/ha) 122 – 247 12 – 156 Chromium (mg/kg) 27 – 84 BDL Lead (mg/kg) 1.58 – 74 BDL – 0.06 Cadmium (mg/kg) 1.20 – 3.26 BDL – 0.003 Nickel (mg/kg) 9 - 65 0.001 – 0.09

The chromium content in the affected regions was (27 – 84 ppm) when

compared to the unaffected regions which is below detectable levels (BDL). Both

the regions do not exceed the critical limit of 100 ppm. The heavy metal lead


122

accounts for about 1.58 – 74 ppm in affected regions when compared to

unaffected regions ranging from BDL – 0.06 ppm. Both he samples lies within

the standard limit of 100 ppm.

Cadmium concentration was higher (1.20 – 3.26 ppm) in soil samples from

affected villages and it was in the range of BDL – 0.003 ppm in unaffected

regions and they are well within the critical limit of 3.0 ppm. The samples of

affected villages recorded maximum nickel content that ranged between 9 –

65mg/kg, which are above the critical limit of 50 ppm than the samples of

unaffected villages which recorded 0.001 – 0.09mg/kg of nickel.

Workers A vast majority of the workers interviewed in this taluk were employed in private

factories located in and around Erode. They preferred working in dyeing

industries rather than employing in agricultural activities because of the relatively

high wage rate and less drudgery. It was also reported that mobilization of fund

is easy for those who go for a salaried job than those who take up agriculture, at

times of crisis. 4.4.20 Distribution of Labour Force The distribution of industrial labourers is presented in Table 4.96. All the

labourers interviewed were found to work in private companies for various

activities ranging from cashier or supervisor to sweeper on weekly wage basis.

Only 15 per cent were found to be employed as labourers in agricultural activities

in the unaffected areas.

Table 4.96. Nature of Work


123

Affected Area Unaffected Area Sl.No Nature of Work

Number Per cent Number Per cent

1. Dye Master 3 15 6 30

2. Dye Mixer 2 10 - -

3. Supervisor 1 5 2 10

4. Hydropher 2 10 1 5

5. Winch runner 1 5 - -

6. Unskilled Labour 4 20 5 25

7. Cashier 1 5 - -

8. Office assistant 1 5 - -

9. Agricultural labourer

- - 3 15

10. Mason 5 25 1 5

11. Handloom worker - - 2 10

4.4.21. Employment of Workers The duration of employment and the wages earned by the sample respondents

of the worker category are presented in Table 4.97. It is revealed that the

average days of employment per month in the affected villages were marginally

less.


124

Table 4.97. Employment Particulars


Unaffected Area

1. Man days of employment in farm operations

21.95 23.75

2. Number of family members working in dying unit

0.25 0.15

3. Number of Family members working in other dyeing factories

0.65 0.90

Annual Income of Head of the Worker Family (in Rs.)

1. Dye Master 38,000 43,750

2. Dye Mixer 27,000 -

3. Supervisor 42,000 54,000

4. Hydropher 30,000 36,000

5. Winch Runner 30,800 -

6. Unskilled Labour 52,400 21,000

7. Cashier 36,000 -

8. Office Assistant 30,000 -

9. Agricultural Labourer - 28,200

10. Mason 26,000 30,000

11. Handloom labour - 23,250

Employment of other Family Members (Percentage)

1. Dye Master 17.65 -

2. Labour in dyeing units 17.65 5.00

3. Unskilled labourers 35.29 70.00

4. Tailor 5.88 -

5. Mason 23.52 5.00

6. Handloom worker - 15.00

7. Supervisor - 5.00


125

4.4.22. Benefits Availed About 20 per cent of the workers had availed claims over accidents that occurred

during working. Forty per cent of the workers in the affected area were covered

under ESI while, it was only 10 per cent in the unaffected area. The details are

reported in Table 4.98.

Table 4.98. Benefits Availed by Workers (Per cent)

S.No Particulars Affected Area Unaffected Area 1. Accident claims 20 5 2. Medical Benefits - 15 3. ESI enrollment 40 10 4. Bonus 75 30

4.4.23. Sufferings Faced by the Respondents It is implicit from the table 4.99, that no chronic illness was reported by any of the

respondents. However, about ten per cent of the respondents reported that they

had to suffer often from skin irritation and ulcer. About five per cent reported to

suffer from skin cracks, stomach pain, indigestion problem and hair fall. A

majority of 60 per cent opined that they did not encounter any major health

related problems except some minor problems like skin irritation, etc.

Table 4.99 Sufferings Faced by the Respondents (Per cent)

Sl.No Particulars Affected Area 1. Skin Irritation 10 2. Cracks 5 3. Stomach Pain 5 4. Digestion problem 5 5. Hair fall 5 6. Ulcer 10 7. No problem 60

4.4.24 Particulars of Drinking Water


126

The Industrial labourers used to get water from both public taps as well as from

open and bore wells. To fetch water from the public tap, they had to travel on an

average a distance of about 0.67 km. They spent about 53 minutes per day to

fetch water. The labourers used to get water daily in the village Periasemur

whereas it was supplied once in two days in S.P.Agraharam. In the unaffected

villages, water was supplied daily and five of the respondents had their own

connections.

Table 4.100. Sources of Drinking Water (Number)

4.5 Damage Function 4.5.1 Yield Damage (Agricultural) Agricultural yield damage was estimated for the following households and the

results are presented in Table 4.101. From the table it could be inferred that 57

per cent of variation in agricultural yield damage was contributed by averting

input expenditure to land, proximity of cropland to dyeing or bleaching industries,

water quality and land qualities. Land quality, water quality and proximity to

dyeing or bleaching industries have significant influence on agricultural yield

damage and the impact is found to be negative. If the land quality index shifts

from poor to medium, agricultural yield damage decreases by Rs.2932.49/ha and

if proximity of cropland to industries increases by one km, the agricultural yield

damage decreases by Rs.2961/ha.

S.No Particulars Affected Area

Unaffected Area

1. Well + Public pipe 20 15

2. Well + Own tap - 5

3. Distance Travelled (km) 0.67 0.63

4. Time (min/day) 53 39


127

Table 4.101 Estimates of Yield Damage Function

S.No Variable Co-efficient t-ratio

1. Constant 20909.92 15.096**

2. Averting Expenditure -0.2711 -1.052

3. Land Quality -2932.49 -3.495**

4. Water Quality -594.38 -2.192*

5. Proximity -2960.89 -3.476** R2 = 0.57, * significant at five per cent, ** significant at one per cent level

4.5.2 Aggregate Damage Function The results of the aggregate damage function for the household is presented in

Table 4.102. One could observe from the table that 32 per cent of aggregate

damage was influenced by independent variables like averting expenditure on

drinking water, human health, water quality and proximity of cropland to dyeing or

bleaching industries. Influence of averting expenditure on human health and

water quality was found to be negative. When water quality shifts from poor to

medium aggregate damage will reduce by Rs.240 per household.

Table 4.102. Estimates of Aggregate Damage Function

Sl.No Variable Co-efficient t-ratio

1. Constant 3817.64 8.37**

2. Averting Expenditure on Drinking Water -0.5363 -1.316

3. Averting Expenditure on Human Health -4.2791 -3.649*

4. Water Quality -240.03 -3.418**

5. Proximity of Cropland to Industries -82.03 -0.250 R2 = 0.32, * significant at five per cent, ** significant at one per cent level

4.5.3. Hedonic Model


128

A Hedonic model was employed to estimate the influence of land quality, water

quality, proximity of cropland to industries, cropping intensity and share of

cropped area to total farmland area on the value of cropland and the influence

was found to be 52 per cent. The results presented in the Table 4.103, shows

that water quality, proximity of cropland to dyeing / bleaching industries and

share of cropped area have significant influence on value of cropland with

proximity and share of cropped area having negative impact. When the proximity

to the dyeing or bleaching industry increases by one kilometre, value of cropland

decreases by Rs.10, 265 per ha. This is because of reduction in the impact of

pollution on farmland and water quality parameters and that is the reason why the crop land close to industries fetches low price than the agricultural land at a

distance.

Table 4.103. Estimates of Hedonic Model

Sl.No Variable Co-efficient t-value

1. Constant 3670.12 0.461

2. Land Quality 179.19 0.058

3. Water Quality 903.31 -5.194**

4. Proximity to Industries -10265.22 -4.196**

5. Cropping Intensity -86.02 -0.574

6. Share of Cropped area -269.01 -5.440** R2 = 0.52, ** significant at one per cent level

4.5.4. Land Averting Expenditure Model The results of land averting expenditure model is presented in Table 4.104. It is

revealed that 53 per cent of variation in land averting expenditure was explained

by independent variables like farm size, education, share of cropped area to total

farm land area, proximity of cropland to industries, land quality, quantity of

organic manure applied, awareness on environmental externalities and water


129

quality. Land averting expenditure was significantly influenced by household

education, quantity of organic manure applied and water quality. Among the

variables, farm size, proximity to dyeing / bleaching industries, land quality,

quantity of organic manure applied and water quality did not influence the

averting expenditure significantly. Increase in one tonne of organic manure per

ha results in decrease of land averting expenditure by Rs. 553 per ha.

Table 4.104. Estimates on Land Averting Expenditure Model


1. Constant 2175.26 1.203

2. Farm Size -12.198 -0.073

3. Household Education 554.811 3.353**

4. Share of cropped area 7.634 0.932

5. Proximity of Cropland to Industries -295.591 -0.787

6. Land Quality -187.673 -0.476

7. Quantity of organic manure -552.966 -2.539*

8. Awareness on environmental externalities 307.770 0.754

9. Water Quality -190.731 -2.636*

R2 = 0.53, * significant at five per cent, ** significant at one per cent level

4.5.5. Drinking Water Averting Expenditure Drinking water averting expenditure was found to be influenced by

household income, education, household size, water quality, awareness etc.

From the table 4.105, it could be inferred that the household income and

awareness on environmental externalities have positive influence on drinking


130

water averting expenditure. When awareness on environmental externality

increases by one stage ie, poor to medium drinking water averting expenditure

increases by Rs.187 per household.

Table 4.105. Drinking Water Averting Expenditure


1. Constant -119.91 -0.847

2. Household Income 0.0759 2.496*

3. Education 46.90 1.767

4. Household Size -6.746 -0.332

5. Water Quality Index -5.032 -0.543

6. Awareness on environmental externalities

187.45 5.935**

R2 = 0.58, * significant at five per cent, ** significant at one per cent level

4.5.6 Willingness to Pay (WTP) WTP was used to assess the values of change in the quality of agricultural land,

irrigation and drinking water in the study area. The results of WTP presented in

table 4.106 reveals that 57 per cent variation in WTP was explained by the

independent variables like age, household size, education, income, per capita

agricultural land, per capita standard cattle units, interest in improving agricultural

activities, perception of land and ground water degradation and proximity. Per

capita agricultural land, per capita standard cattle units, interest in improving

agricultural activities had significant influence on WTP. If interest increases by

one stage (not interested to somewhat interested) WTP increases by Rs.933 /

household.

Table 4.106. Estimates on Willingness to Pay



131

1. Constant -9341.351 -0.827

2. Age 153.816 1.214

3. Household size -287.469 -0.379

4. Education 601.714 0.575

5. Per capita agricultural land 868.324 2.932*

6. Per capita standard cattle units

464.618 12.805**

7. Interest in improving agricultural activities

932.532 2.654*

8. Perception on land and ground water degradation

298.982 10.200**

9. Proximity to dyeing/bleaching units

-333.970 -1.137

10. Income 88.834 0.856 R2 = 0.57, * significant at five per cent level, ** significant at one per cent level


132

Though industrial growth plays an important role in the economic development of

the developing countries it is apparent that the pollution effects of various

industrial units in India had been alarming. In the western Tamil Nadu, the textile

dyeing industries are located in large numbers in the districts of Coimbatore,

Karur and Erode. They play a significant role in developing the local economy

and at the same time pollute the land and water resources to a large extent. To

understand the above issues a micro level study was undertaken with the

following specific objectives.

a. to analyze the external effects of industrial development on the quality of land, water resources, crop land, crop output, employment, income, migration, health and other related socio-economic attributes.

b. to study the long term environmental implications of dyeing factories on the agricultural eco-systems and

c. to study the attitude of the stakeholders in conserving the valuable land and water resources and to suggest workable policy prescriptions for internalizing the externalities.

The study was conducted during the period 2004 -2006. Three districts namely

Coimbatore, Karur and Erode were selected since the deterioration of land and

ground water qualities and its impact on cropland, irrigation and drinking water,

crop production, human and animal health, labour employment, farm income,

etc., were significantly pronounced only in these districts due to the high intensity

of dyeing and bleaching units. Tiruppur taluk in Coimbatore district, Karur taluk

in Karur district and Bhavani and Erode taluks in Erode district were selected

based on the extent of external impacts on land and water. Four villages, two

affected and two unaffected were selected from each taluk. Based on the

discussions held with the regulatory authorities and development departments

5. SUMMARY AND CONCLUSION


133

like TNPCB (Tamil Nadu Pollution Control Board), Revenue department,

Agricultural department, experts of textile and dyeing associations the study

villages were selected and classified as affected and non-affected. The critical

parameters which influence crop growth like pH, EC (Electrical Conductivity),

TDS (Total Dissolved Salts), TSS (Total Soluble salts), chloride and sulphate

concentrations were also considered while selecting the study villages.

Altogether sixteen villages were chosen and the total sample size was 640. The

households selected were of two categories viz., (i) farm households and (ii) non

farm workers. The respondents were selected randomly at the rate of 60

numbers from category (i) and ten from category (ii) in all the sixteen villages.

Soil and groundwater samples were also collected from the earmarked wells as

per the standard procedure to analyse various physico-chemical characteristics.

Besides the conventional percentage analysis, econometric tools viz., aggregate

damage function, hedonic regression model and contingent valuation technique

were adopted to analyze the resource degradation, environmental quality and the

stakeholders’ involvement in conservation compliance.

Farmers in Tiruppur depend to some extent on wells for irrigation as the river

Noyyal is polluted to a great extent. The quality of water was affected due to the

dyeing factory effluent in and around the study villages. In the affected area,

about 58 per cent of the cropped area was under rain fed condition against 35

per cent in the unaffected area. The productivity of many of the crops was

reported to be less; for instance the yield of coconut in the affected area was

reduced by more than 40 per cent. The averting expenditure for the crops namely

coconut and fodder cholam was Rs.5605 and Rs.1041 respectively, for an area

of one hectare.


134

A vast majority of 81.67 per cent of the households in the affected villages

depended on both on-farm and non-farm activities and about 10 per cent of the

households were found employed only in non-farm activities. The major non

farm activities of these villages were renting out houses, running own dyeing or

bleaching units, knitting units, money lending and water trading. In 75 per cent of

the households in affected villages atleast one family member has migrated,

whereas in the unaffected villages, it was only 11.67 per cent. In the affected

area, among those migrated, the permanent migration was found high. The

reasons for migration were poor income, desire to earn more, poor water quality,

and unremunerative crop activities. Among the reasons, poor income from

agricultural operations alone was reported by 71.43 per cent of the sample

farmers.

The reasons attributed for the sale of croplands were less crop income,

migration, poor water quality and water scarcity. Forty five per cent of the

respondents in the affected villages had sold their livestock due to various

reasons like reduced milk yield, loss in weight, water scarcity and inadequate

man power to tend them. In the affected villages, only 51.67 per cent were

willing to pay for improving the soil and water qualities. About 40 per cent of the

respondents were willing to pay less than Rs.50,000 for internalizing

externalities.

Most of the worker respondents in the affected area were engaged in industrial

activities as Dye-master, Supervisor, Winch runner, Hydropher, Dye mixer etc.

A vast majority of 45 per cent of the workers were engaged in maintaining the

quality of the yarn in the near-by knitting factories. About 30 per cent of the

respondents reported problems of skin cracks and rashes.

The water samples collected from wells in the affected regions of Tiruppur taluk

before monsoon showed moderately high pH and EC values which exceeding


135

their critical limits indicating its unsuitability for drinking and irrigation. Further,

the results of heavy metal analysis showed the presence of metals such as

chromium, cadmium and nickel which were below the maximum permissible

limits whereas, the lead content of the sample exceeded the prescribed limit of

0.01 mg/l for drinking water.

The same water sample collected after monsoon showed variation in pH (> 8.5)

and EC (2.53 – 4.05 dSm-1) which lie above the critical limits. The heavy metals

such as lead and cadmium were slightly above the permissible limit (0.18–0.55

mg/l and BDL to 0.02 mg/l respectively). The results of the soil samples

collected from the study villages of Tiruppur taluk showed the pH values ranged

from 6.10 – 7.50, EC of 0.69 – 1.80 dSm-1 which were found to be higher than in

the unaffected region and also they lie above the maximum permissible limit. The

soil samples of affected villages recorded 2.36–3.85 ppm of cadmium which is

marginally slightly higher than the maximum allowable concentration of 3.0 ppm.

It is understood that in Karur, due to the discharge of dyeing factory effluent in

the river Amaravathy, both the canal and open wells remained largely unusable

for irrigation, particularly during summer season. The river Cauvery is the chief

source of drinking water in the affected villages whereas in unaffected villages,

river Amaravathy is the major source of water supply. The productivity of almost

all the crops was found higher in unaffected villages compared to the affected

villages. Even the economically less important crop like “korai” did not grow well

in the affected study villages due to poor soil and water qualities. The productivity

of major crops of the taluk, viz., coconut, paddy and fodder sorghum has

declined by 44, 14 and 24 per cent, respectively over the yields of the said crops

in the unaffected locality.


136

In the affected area about 62 per cent were willing to contribute some amount to

replenish the degraded resources. For getting good quality drinking water from

the nearby area they had to spend Rs.844/year/household. Scarcity of good

quality water and non-availability of farm labourers were the major reasons

reported for decline in agricultural operations by 83.33 and 73.33 per cent of

respondents respectively. Labour scarcity was due to the mobility of agricultural

labourers from farming to industrial sector. Poor water quality was attributed to

be the main reason (52.22 per cent) for labour mobility. Due to the deterioration

of land and water quality, the crop stand was also observed to be poor. Non-

remunerative crop income from agriculture was reported by 48.94 per cent of

respondents for labour migration. In the affected villages 25 per cent of the

respondents had disposed off at least part of their land due to poor water quality

and labour scarcity. While the agricultural land value in the affected villages

declined considerably (9 per cent) due to poor soil and water qualities, the

cropland (only agricultural land) price had increased over 50 per cent in the

unaffected area. About 75 per cent of the respondents interviewed had sold their

livestock due to various reasons like poor water quality, non availability of water,

labour scarcity, reduced milk yield and reduction in calving rate.

The people in the affected areas experienced occasional skin problems, viz.,

itching, skin rashes, eye boils, etc. Milk production in the affected area was

reduced by 12.35 per cent. Farmers growing paddy and fodder sorghum had to

spend about Rs.687 and Rs.510 per ha, respectively, towards averting

expenditure. For getting good quality drinking water from the nearby places,

households had to spend 8.44 man-days a month. Almost all the worker

respondents in the affected areas of Karur taluk maintained their livelihood by

working as wage earners in the dyeing factories. They are employed as


137

supervisors, accountants, dye masters, etc. In the unaffected villages only about

25 per cent of the workers interviewed were agricultural labourers.

The water samples taken from villages of Karur before monsoon recorded normal

pH, but the EC values were found to exceed the maximum permissible limit.

The BOD and COD values were found to be in the range of 35-110 mg/l and 165-

420 mg/l respectively and also, SAR value of 39-46 which was higher than the

limit of 26. The water samples collected after monsoon recorded more or less

similar pH values in both affected and unaffected regions. The EC value was

recorded as 2.05 – 4.12 dSm-1 in affected villages compared to 1.22 – 3.11 dSm-1

in unaffected regions that exceeded the standard limit of 2.25 dSm-1 for irrigation

water. The water sample collected after monsoon recorded similar pH values in

both affected and unaffected regions. The water samples collected from affected

region exhibited an EC of 2.05-4.12 dSm-1, BOD of 99-148 mg/l, COD of 215-305

mg/l compared to unaffected region which recorded 1.22-3.11 dSm-1 EC, 34-60

mg/l of BOD and 85-120 mg/l of COD. The SAR values of affected samples

exceeded the critical limit but that of unaffected samples were within the limit of

26.

The results of analysis of soil samples collected from the study villages of Karur

taluk showed a pH range of 7.56 – 8.31 and EC of 1.25 – 4.10 dSm-1 which was

greater than the maximum permissible limit. Soil samples of affected villages of

Karur taluk recorded 2.36 – 5.69 ppm of lead, 1.89 – 5.96 ppm of cadmium and

12 - 45 ppm of nickel while the unaffected regions, recorded 1.37 – 2.10 ppm of

Pb, 1.10 - 2.10 ppm of Cd and 9 – 24 ppm of nickel.

The critical analysis of the area and productivity of crops in Bhavani reveals that

the productivity of majority of the crops declined in the affected villages. As in the


138

case of other two study areas discussed earlier, in the unaffected villages area

under turmeric was about 17 per cent, whereas in the affected villages it was

only eight per cent. The productivity of sugarcane was higher (97 tonnes) in the

unaffected villages when compared to the productivity in the affected villages (90

tonnes). In the affected villages, about 16 per cent of the total cultivated area

was under fodder sorghum compared to five per cent in the unaffected area. The

yield of gingelly and coconut in the affected area were less by 9.33 and 39.04 per

cent, respectively. The averting expenditure for banana was to a tune of

Rs.3705/ha.

Only 33.34 per cent of the affected village households depended on on-farm

activities exclusively for their livelihood sustenance, while it was about 50 per

cent in unaffected area. About eight per cent of the households alone were

undertaking both on-farm and off-farm activities. But it was 15 per cent in the

unaffected villages. In the affected area, about 53 per cent migrated from

agriculture to other non-farm activities compared to 20 per cent in the unaffected

area. The main reasons attributed for migration was poor income from

agricultural activities and their interest to earn more from the assured sources of

employment without much drudgery.

Majority of the households expressed that poor income was the major hurdle

affecting the ability to pay and replenish the degraded resources. About 53 per

cent of the farmers were willing to pay between Rs.25,000 and Rs.50,000

towards internalizing externalities (mainly for getting good quality water). About

42 per cent favoured quarterly mode of payment, 10 per cent for half yearly and

15 per cent for annual payment. It could however, be observed that the average

wage earning is higher in the affected area by 25.39 per cent. This is due to the

employment opportunities provided by the industry to the people in the affected


139

area. The employment of other family members in the affected area showed that

only 36.84 per cent were found to depend on agriculture while it was about 87

per cent for the unaffected category.

About 20 percent of non-farm workers have been suffering from skin related

ailment and tuberculosis (TB). The TB patients were undertaking free treatment.

Other acute problems like skin cracks, boils, itching, skin rashes were also

reported by some sections of the sample respondents. On an average, an

individual had to spend about Rs.40 and Rs.57 a year towards the cost to

physician and medicine.

The pH and EC of the water samples collected from affected villages of Bhavani

taluk were higher (8.56 to 9.20 and 2.56 – 5.27 dSm-1) when compared to

unaffected villages of the same taluk. In general, the BOD and COD values of

the samples from the affected villages were found to be higher recording 96 to

170 mg/l and 235-425 mg/l respectively compared to 24 to 85 mg/l and 60-210

mg/l of BOD and COD respectively in the unaffected regions. Heavy metals like

chromium, lead and cadmium contents were higher in affected areas compared

to unaffected areas. The soil samples collected from Bhavani recorded a

relatively higher pH in affected regions (7.70 – 8.94) compared to unaffected

regions (6.20 – 7.12). The EC value was also higher in samples of affected

villages, which recorded 2.14–3.99 dSm-1 when compared to EC values of

samples of unaffected villages (0.12 – 0.69 dSm-1). The level of chromium was

found to be in the range of 23 - 85 ppm in affected regions but it was below

detectable limit in unaffected regions.

In Erode taluk, the area irrigated by canal had declined by about 21 per cent

during the recent decade. The rain fed area had increased by about 25 per cent

in the affected area. Also, in the affected area, the area under paddy declined by


140

about ten per cent. Though the area under coconut increased over years, the

productivity has comedown by more than 40 per cent. The yields of major crops

like paddy, sugarcane, turmeric and groundnut had declined by 12, 23, 26 and 61

per cent, respectively compared to unaffected study villages. A majority of 74 per

cent of the sample households were willing to pay between Rs.25, 000/- and

Rs.50, 000/- per household to replenish the degraded resource with financial

support from the institutions like government.

A farmer cultivating paddy and sorghum had to spend on an average over

Rs.919/- and Rs.468/- per hectare respectively towards averting expenditure.

About 84 per cent were of the view that poor water quality was the main reason

for the weak performance of agriculture. About 57 per cent of farmers in the

affected category reported decline in agricultural income as one of the

contributing factors that led to sluggishness in agricultural activities. The

percentage of income earned by the households from agricultural activities alone

was only 5.30 in the affected villages whereas it was 34.89 per cent in the

unaffected villages. The respondents in the affected area spent on an average

about Rs.125/- towards the cost of medicine. About six per cent loss in milk

production was reported in milch -animals. Besides, reduction in weight and

decline in reproduction rate was also noticed.

Majority of the labourers interviewed were found to work in private companies for

various activities ranging from cashier to supervisor on weekly wage basis. Only

15 per cent were found to be employed as labourers in agricultural activities in

the unaffected areas. About 10 per cent of the respondents reported that they

had to suffer often from skin irritation. About five percent reported to suffer from

skin cracks, stomach pain, indigestion and occasional hair fall.


141

The water samples taken from affected regions of Erode taluk recorded a pH of

8.60 to 9.26, EC of 2.98 to 5.55 dSm-1 compared to a pH of 7.12 to 8.01 and EC

of 1.12 – 2.36 dSm-1 in unaffected regions. Highest BOD of about 80 to 140 mg/l

and COD of 200-350 mg/l were recorded in affected region which are higher than

the limit compared to about 27 – 67 mg/l of BOD and 70-170 mg/l of COD in

unaffected regions. The heavy metals like chromium, lead, nickel and cadmium

were found to be higher and exceeded their critical limits in affected areas

compared to unaffected areas.

The soil samples taken from affected region of Erode taluk recorded a higher pH

(7.96 to 8.99) and EC of 2.58 – 4.57 dSm-1 than unaffected region (6.5-7.56 pH

and 0.12-1.57 dSm--1). The heavy metal contents of the samples from affected

region were found to be higher than unaffected region but they were below the

critical limits.

A critical analysis of the yield damage function revealed the fact that about 57 per

cent variation in agricultural yield damage was contributed by averting input

expenditure to land, proximity of cropland to dyeing or bleaching industries, water

and land qualities. If the land quality index shifts from poor to medium,

agricultural yield damage would decrease by Rs.2932/ha and if proximity of

cropland to industries increase by one km, the agricultural yield damage would

decrease by Rs.2961/ha. The analysis of hedonic pricing techniques implied that

water quality, proximity of cropland and share of cropped area had significant

influence on value of cropland with proximity and share of cropped area having

negative impact. When the proximity to the dyeing or bleaching industry

increased by one kilometer, value of cropland would decrease by Rs.10,265 per

ha. It was also found out that the household income and awareness on

environmental externalities had positive influence on drinking water averting

expenditure. When awareness on environmental externality increased by one


142

stage i.e., poor to medium, drinking water averting expenditure would increase by

Rs.188 per household.

It is interesting to note that about 57 per cent variation in Willingness To Pay

(WTP) was explained by age, household size, education, per capita income, per

capita agricultural land, standard cattle units, interest in improving agricultural

activities, perception of land and ground water degradation and proximity. The

functional analysis revealed that the interest in improving agricultural activities if

increased by one stage (not interested to somewhat interested) WTP would

increase by Rs.933/household. From the foregoing discussions, the following

policy prescriptions could be made for further action by the technocrats and the

enforcement authorities.

Policy Options

The Tamil Nadu Pollution Control Board (PCB) may periodically publish the results of the analysis of effluent samples taken from the industries along with permissible levels so as to bring in accountability and create public awareness.

Quality monitoring of water courses and point and non-point sources of pollution on a continuous basis may be entrusted to research institutions like universities, colleges etc. for reporting back to Government for remedial measures and designing conservation compliance programmes.

The affected parties should be compensated adequately, by working out the third party effects created by the industries. Effort should also be taken so that the compensation amount to be paid to the affected parties is sufficiently higher than the damage cost incurred by the farmers and other stakeholders of the local resources.

A working group comprising of farmers, industry, technocrats, policy makers, researchers, enforcement agencies, etc., should be constituted to look into the physical, economic, social, environmental and ecological issues of industrial pollution, remedial and abatement measures.


143

tnau – tnslub project introduction - tamil nadu · enforcement of rules and stringent action...

Documents