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EARTH SCIENCES CENTRE UNIVERSITY OF GOTHENBURG B547 2008
Department of Earth Sciences Geology
GÖTEBORG 2008
MINING ACTIVITY IMPACT ON FLUVIAL SEDIMENTS IN THE SW AMAZON
DRAINAGE BASIN, PERU
Martin Persson
GÖTEBORG UNIVERSITET Institutionen för geovetenskaper Avdelningen för geologi Geovetarcentrum ISSN 1400-3821 B547 Projektarbete Göteborg 2008
Postadress Besöksadress Telefon Telefax Earth Scienceses Centre Geovetarcentrum Geovetarcentrum 031-786 19 51 031-786 19 86 Göteborg University S 405 30 Göteborg Guldhedsgatan 5A S-405 30 Göteborg SWEDEN
MINING ACTIVITY IMPACT ON FLUVIAL SEDIMENTS IN THE SW AMAZON
DRAINAGE BASIN, PERU
Martin Persson
Abstract
There are environmental problems involved in large scale exploitation of natural recourses in
Peru. Mining and resulting tailings and smelters contribute to raised metal levels in the
surrounding sediments. The objective of this study is to consider the environmental impact of
mining activity on metal contents of fluvial sediments. One aim is to assess the spatial
distribution of possibly mine derived sediment metal and arsenic anomalies. The fieldwork
was done in the Peruvian regions Cusco, Madre de Dios and Loreto. These represent different
settings; mountainous Andean and tropical lowland forest of different latitudes and altitudes.
The primary data source is from analyzing samples collected during the Fall of 2007. The
samples have been subjected to two types of leaching, followed by ICP-MS multi elemental
analysis. Powder XRD, loss on ignition and grain size analysis by wet sieving and Sedigraph
were also carried out. The heavy metal (and arsenic) contents have been evaluated using
various normalization approaches and guideline comparisons.
Two of the investigated sediments are interpreted as mining impacted. Other anthropogenic
sources do also contribute to raised metal and arsenic levels, primarily in Cusco.
Keywords: Amazonia, Peru, Mining, trace metal distribution, Amazon River, Rio Vilcanota,
Rio Urubamba, Rio Manu, Loreto, Madre de Dios, and Cusco.
Sammanfattning
Miljöproblem finns då naturtillgångar stora som Perus exploateras. Gruvdrift och därmed
relaterade varphögar och smältverk bidrar till höjda metallhalter i omgivande sediment. Syftet
med denna studie är att undersöka miljöpåverkan från gruvindustrin och hur denna påverkar
metallinnehållet i fluviala sediment. Ett mål är också att uppskatta den geografiska
spridningen av möjliga gruvrelaterade anomalier i sedimentens metallhalt. Fältarbetet gjordes
i de peruanska regionerna Cusco, Madre de Dios och Loreto. Dessa representerar olika
miljöer; bergiga Anderna och tropisk låglandsskog av olika latitud och höjd.
Den primära datakällan är analyser av provmaterial som insamlades under hösten 2007.
Proverna har utsatts för två typer av lakning med efterföljande ICP-MS multielementanalys.
Pulver-XRD, glödgningsförlust samt kornstorleksanalys med våtsikt och Sedigraph har också
utförts. Tungmetall- och arsenikhalterna har utvärderats genom olika normaliseringstekniker,
statistikbehandling och jämförelser med befintliga sedimentbedömningsgrunder.
Två av de undersökta sedimenten tolkas som påverkade av gruvaktivitet. Andra mänskliga
källor bidrar också till höjda metall- och arsenikhalter, huvudsakligen i Cusco.
Nyckelord: Amazonas, Peru, gruvindustri, spårmetallspridning, Amazonfloden, Rio
Vilcanota, Rio Urubamba, Rio Manu, Loreto, Madre de Dios och Cusco.
2
Table of contents Introduction ................................................................................................................................ 4
Objectives ............................................................................................................................... 4
Theoretical and historical framework .................................................................................... 4 Andean mining history and extent ..................................................................................... 4 Trace and major elements in river sediment systems ......................................................... 6 Sulfide weathering and Acid mine drainage formation ..................................................... 7 River transport of sediment and trace elements ................................................................. 8
A summary of Peruvian environments ................................................................................... 9 The Peruvian Amazon basin ............................................................................................ 10 The Peruvian Andes ......................................................................................................... 14
Study areas ............................................................................................................................... 14 The state of Cusco ................................................................................................................ 14
Geology and sedimentology ............................................................................................. 15 Rio Urubamba .................................................................................................................. 15
Laguna Huarcarpay .......................................................................................................... 17
Climate ............................................................................................................................. 18 Mining activity intensity .................................................................................................. 18 Land use and coverage ..................................................................................................... 19
The state of Madre de Dios .................................................................................................. 19
Geology and sedimentology ............................................................................................. 20 Rio Manu .......................................................................................................................... 21
Rio Alto Madre de Dios ................................................................................................... 21 Climate ............................................................................................................................. 22 Land use and coverage ..................................................................................................... 22
The state of Loreto ............................................................................................................... 22 Geology and sedimentology ............................................................................................. 23
Rio Marañón ..................................................................................................................... 23
Climate ............................................................................................................................. 23
Land use and coverage ..................................................................................................... 24 Methods .................................................................................................................................... 24
Fieldwork and sampling ....................................................................................................... 24 Visual examination of soil samples .................................................................................. 25
Analytical procedures ........................................................................................................... 25 Grain size distribution analyses ........................................................................................ 25 Loss on ignition analysis .................................................................................................. 26
XRD ................................................................................................................................. 26 Geochemistry ................................................................................................................... 27
Acid digestion of samples ................................................................................................ 27 ICP-MS ............................................................................................................................. 28
Normalization and statistics ................................................................................................. 28 Statistics ............................................................................................................................... 28
Sediment quality guidelines and enrichment factors ........................................................ 29 Pollution Index ................................................................................................................. 29
Results ...................................................................................................................................... 29
Visual examination of soil samples ...................................................................................... 29 Grain size distribution .......................................................................................................... 30 XRD ..................................................................................................................................... 32 Loss on ignition analysis ...................................................................................................... 32 ICP-MS ................................................................................................................................. 33
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Normalization and statistics ................................................................................................. 35
Soil quality guidelines and Enrichment Factors ............................................................... 39 Discussion ................................................................................................................................ 42
Uncertainties ......................................................................................................................... 44
Conclusions .......................................................................................................................... 45 Further research .................................................................................................................... 45
References ................................................................................................................................ 46 Appendix A. Sample record and Field observations ................................................................ 50 Appendix B. Grain size distribution and statistics ................................................................... 54
Appendix C. ICP-MS results .................................................................................................... 57 Appendix D. Normalized metal content ................................................................................... 59 Appendix F. XRD results ......................................................................................................... 62 Appendix G. LOI results .......................................................................................................... 63 Appendix H. Population densities in study areas ..................................................................... 63
Appendix I. Sediment and Soil quality guidelines ................................................................... 64
Appendix J. List of Acronyms and words ................................................................................ 64
Appendix K. Epilogue .............................................................................................................. 65 Appendix L. Additional images cd-rom ................................................................................... 65
4
Introduction Mining together with Colombian use of herbicides, Ecuadorian oil exploitation and Amazon
deforestation are the main environmental issues on the South American continent (ABN,
2006). The mining impact of sediments has traditionally been considered a short range
feature. This Master’s thesis aims at describing the regional affects of Peruvian mines.
Fieldwork was carried out in the states of Cusco, Madre de Dios and Loreto in August and
September 2007.
Objectives
This study was made to present how mining and other anthropogenic metal sources
contaminate fluvial sediments in Southwestern Amazonia, Peru. One aim of this study is to
understand the parameters controlling the distribution of trace metals and the interplay
between them. Natural and anthropogenic contribution will be studied. Part of the goal of this
Master’s thesis is to answer the following questions.
• What levels could be expected (mg/kg)?
– Background assessment
– Deviations from background
• What differences in metal/As content are there?
– Andean tributaries vs. downstream Amazon Rain forest
– Spatially close and distant samples
• What Parameters and Elements covary? – Are any correlations possible?
• Which parameters affect where high levels of trace and major elements are
found?
• What sources are there for raised metal and arsenic levels in sediments? – Anthropogenic vs. Natural factors
• Could the mining industry impact be assessed? – What chemical and mineralogical features could be considered evidence for
mining impact?
– What range of impact is likely?
Theoretical and historical framework
To understand and evaluate the problems stated under the previous headline it is necessary to
have an understanding in historical, sedimentological and geochemical aspects of the
Southwestern Amazon drainage.
Andean mining history and extent
The earliest archeological findings suggest that mining has occurred at least since 1,400 B.C
in the Peruvian Andes. Early Andean mining were limited primarily to copper and tin (Abbot
et al., 2003). The pre-Columbian and Incan empires as well as the Spanish conquistadors
have all been involved in mining activities. During colonial times mainly gold, silver and
mercury was extracted. Guano (bird and bat droppings used as fertilizer) and saltpeter were
popular mining products during early republican times. Since the mid 1970´s political actions
and a modernized legal system has made the mining industry open for foreign investments.
Relative political stability and rich natural recources have made Peru interesting for foreign
investments (Baker, 1996 and INGEMMET, 2007a). In 2006, more than 60% of the Peruvian
5
export revenue or 14,700 million US$ were generated by the mining industry (MEM, 2006b
and INGEMMET, 2007a). See figure 1 for metal production quantities.
Figure 1. Peruvian metal production in metric tons unless otherwise specified (Modified from USGS,
2006) .
Figure 2 shows the main distribution of Peruvian mines. Mining is fundamentally limited to
the Andes Mountains. The most widespread are the non-metallic mines which are located
mainly on an axis parallel to the strike of the Andes. Alluvial gold production occurs in the
southern parts (States of Madre de Dios, Puno, Arequipa and Ayacucho-Ica). Gold mining are
also well represented in the north-western corner in and around La Libertad state.
Polymetallic ores are extracted in a large part of the Peruvian Andes (INGEMMET, 2000). At
present there are close to 33,000 registered mining rights in Peru (INGEMMET, 2007a).
Mining is forbidden in the Peruvian rain forests. Roughly 45,000,000 hectares of land or
35.5% of the total area is protected by law and thus excluded from metal exploitation.
Authorities estimate the presence of about 1,200 illegal miners in the area (ABN, 2006 and
INGEMMET, 2007b).
1 10 100 1 000 10 000 100 000 1 000 000
Arsenic
Cadmium
Copper
Gold (kg)
Iron (MTx1000)
Lead
Silver (kg)
Tin
Zinc
6
Figure 2. Principal distribution of Peruvian mines (Modified from INGEMMET, 2000) .
Trace and major elements in river sediment systems
River and flood sediment have trace (and major) element compositions that are influenced by
a variety of factors. These factors are both natural and human induced. Some examples are
listed in Figure 3.
Point- as well as non-point sources exist. Many possible transport ways such as atmospheric,
riverine and groundwater aided transport are available. (Drever, 2005) Lakes and rivers derive
their trace and major element content from atmospheric deposition, soil processes (including
podogenesis and sorption to soil organic matter). The natural component can fluctuate
through time due to local catchment evolution or climate change.
To answer the questions in the introductory part of this report it is necessary to distinguish the
different metal sources. Mining alone do not account for all elevated metal levels in sediments
of the researched areas. Land usage and natural geological parameters also governs the levels.
Municipal waste, sewage and landfill leakage, air transported particles and boat traffic could
potentially result in elevated metal and arsenic levels. Differences in weathering, source rock,
climate and other parameters result in different metal levels. Background levels of metals
should be considered a local phenomenon. Slope and relief affects how the sediment is
transported. Greater relief produces more locally derived sediment in a stream. Small
gradients surrounding a flood plain cause for long transported material to dominate (Foster
and Charlesworth, 1996).
7
Figure 3. Natural and anthropogenic sources of river sediment trace metal contents (Modified from Foster
and Charlesworth, 1996).
Sulfide weathering and Acid mine drainage formation
Acid mine drainage (AMD) is a product of sulfide weathering. AMD arises after the metals
have been extracted from the ore with waste rock piles remaining. A series of weathering
reactions are initiated (see equations 1-5 below) when previously buried rock material are
brought up to an oxidizing environment on the earth´s surface. This causes sulfuric acid to
form and metal oxides to be mobile. The metal concentrations could often reach toxic levels
(Robbed and Robinson, 1995; Butler, 2007; Baker, 1996).
AMD is analogous to natural weathering but the active time involved is shorter. AMD could
potentially release large amounts of acid and resulting soluble metals (and other elements) to
the environment. The AMD range of impact is often considered limited to a few kilometers.
Leached mine tailing trace metals have been proven to be transported over 3 km. Significant
levels of Zn and Cd were found 3.3 km downstream from the Daduk Au/Ag/Pb/Zn mine,
Korea (Lee et al., 2001). Few studies have investigated the regional scale degradation of
sediment. Four principal oxidation processes, or a combination, are responsible for the
formation of acid mine drainage.
Chemical oxidation
Electrochemical oxidation
Bacterial (i.e. Acidithiobacillus spp.) oxidation
A combination of chemical, electrochemical and bacterial oxidation.
(Ritcey, 2005)
The general AMD reaction involves the following components.
Sulfide mineral (often pyrite) + Moist/Water + Oxygen (Air) Metal ions + SO4 + Acidity
(Ritcey, 2005)
Iron disulfide mineral example weathering reactions:
2 FeS2 + 7 02 + 2 H2O → 2 Fe2+
+ 4 SO4 + 4 H+ (Equation 1)
4 Fe2+
+ O2 + 4 H+ → 4 Fe
3+ + 2 H2O (Equation 2)
4 Fe3+
+ 12 H2O → 4 Fe(OH)3 + 12 H+ (Equation 3)
FeS2 + 14 Fe3+
+ 8 H2O → 15 Fe2+
+2 SO42-
+ 16 H+ (Equation 4)
4Fe2+
+ O2+ 10 H2O → 4 Fe(OH) 3(s) + 8H+ (Equation 5)
Natural sources
Volcanic activity
Geothermal activity
Weathering
Soil/Plant interaction
Antropogenic sources
Transport
Industry
Mining
Municipal waste
Landfill leachates
Agriculture
Total sediment content
8
The first part of the complex series of reactions (eqn. 1) involves the oxygen and water aided
production of ferrous iron, sulfate and acidity. If the Fe2+
is exposed to atmospheric oxygen it
could oxidize to form Fe3+
with even further acidity involved.
In the second reaction (eqn. 2) the ferrous iron is being transformed to ferric iron. In the third
step (eqn. 3) hydrolysis of the ferric iron with water produces solid ferrihydrite. Release of
further acidity is another effect of the hydrolysis. This reaction is pH dependent. The solid
mineral cannot be formed if pH is under 3.5 but the ferric iron remains in solution. The fourth
reaction does not require free oxygen as the oxidation of additional pyrite oxidizes with ferric
iron. The acid formation of iron is rapid since the cyclic nature of the reactions. The iron
conversion reaction described above can be accelerated by the bacterial species hiobacillus
ferroxidans by a factor 100 - 1 000 000 (Hulshof et al., 2006).
Underground mining operations in pyritic environments generally have Eh values ranging
from -0.04V to +0.08V and pH values of 5.4 and 3.9 respectively. Rich presences in Fe2+
have
been proven to cause pH as low as 3.5 and Eh values over 0.5. The air exposure causes open
pit mines to have higher Eh (Ritcey, 2005).
Sulfide minerals carry a latent acidity. Pyrite, [FeS2] and Pyrrhotite, [Fe1-xS] are two
examples. X is usually between 0 and 0.2. The sulfide mineral acidity is step by step
transformed to H+ by ferrous-iron oxidation by atmospheric O2. Mineral-dissolution increases
metal concentrations (e.g. Fe, Al, Cu, Pb, Zn, and Cd) in the pore water when exposed to the
Fe2+
and sulfide oxidation.
Pyrite bearing minerals found in mine tailings weather quickly (months-years) in neutral –
slightly alkaline conditions. One product of this weathering is extreme acidity. In addition
AMD usually is related to high levels of heavy metals. Dissolved metal ions (e.g. Cu2+
, Cd2+
and Al3+
) will be released from the tailings under these extreme conditions.
The worst case scenario in AMD is when the pyrite content is high in an environment where
the base content is low. Other factors, for example porosity, influence the acid formation
rates. Pyritic sandstones release its acid load more rapidly than do argillaceous rocks. If
present, acid consuming carbonate minerals and other basic minerals could prevent low pH
drainage. Also, below the zone of sulfide oxidation the carbonates cause a decline in pore
water metal content. Calcium carbonates are the most reactive of these and tend to react
readily with water. The peak acid production is 5 – 10 years after mining and a declination
occurs approximately 20-40 years after mining. (OSM, 2007)
River transport of sediment and trace elements
Sedimentological principles provide a basic understanding of the interaction between source
(e.g. mine tailings and landfill deposits) and recipients (downstream channels, flood plains
and the Atlantic Ocean). Water transported pollutants are contributed by direct runoff into the
streams and rivers. Surface runoff from mine waste piles, landfills and other similar facilities
could raise metal and arsenic contents. The elevated levels of major and trace elements may
have numerous influences. Pollutants entering the Amazon watershed are likely to be
transported and deposited elsewhere. This makes it hard to predict what effect a contaminant
will have and where it will have greatest impact. The meandering character and annual
floodings of rivers complicates pollution patterns.
Sediment is transported in moving water by three mechanisms. Suspended sediment transport
is the major way of transport for the Amazon Basin Rivers and tributaries. Saltation and bed
9
load transport is a minor way of transport. A majority of the Amazon sediment is transported
as suspended load. The percentages transported by each mechanism vary among tributaries
(Gibbs, 1967).
Fine material, especially clay particles (<2m) are of importance in transporting trace metals.
Clay particles have an ability to bind ions due to their negative electrical surface charge. This
attracts positively charged metal and metalloid ions (for example Cu2+
and As5+
). Since the
clay particles are small they could easily be transported (mainly as suspended load) and
potentially spread and dilute trace elements over a large area (Foley, 1999). This is especially
true for colloidal transport. Colloids generally range from 1 nm to 0.2 m. The term refers to
particulate matter too small to be easily deposited (Drever, 2005).
Sediment sources (with related trace metals) could be found both upstream and perpendicular
to the river channel itself. The downstream transport of sediment could potentially reach
several thousand km. The sideways or perpendicular transport of sediment and ions occurs
due to surface run off, groundwater movement and mass movement towards the channel low
point. Few theoretical limits except groundwater divides can limit the potential source-target
distance. The final recipient of the east-Andean river sediment is the Atlantic Ocean. Rivers
can also deposit sediment over vast areas of land. This effect could also be described as a
(more temporal) recipient. If crops are grown on the potentially contaminated fluvial plains
humans could also be regarded recipients.
A summary of Peruvian environments
Geologic, geomorphologic, sedimentary, climatic, chemical, geochemical and biological
information is necessary to fully recognize the large sedimentary systems of the Andes and
Amazon basin and how these are affected by metallic and arsenic pollution. Three general
type settings are found in Peru. These are, from west to east:
The arid coastal plain – La Costa
The foothills and high mountainous Andes area – La Sierra
The tropical rain forests of the Amazon basin – La Selva
There are transition forms between these settings. The Montane forest on the eastern side of
the Andes is one example. Large differences in altitude cause high erosion rates. Mass waste
actions with resulting colluvial deposits are common. Wedge shaped scars are a common
feature in the Andean landscape. The tropical forest are further divided into Tierra firme
(Spanish: Dry land) and the Várzea (annually flooded forest).
Due to the subduction of the oceanic Nazca plate under the continental South American plate
and resulting orogenic activity the different rocks show a complex pattern (Méndez, 2005).
Bed Rock types are principally distributed parallel to the subduction zone to the west. Plutons
and massifs are stretched in a southeast-northwesterly direction. This pattern is developed by
plate tectonic movements. Rocks are young in the western part of the Andes and generally
getting older to the east (INGEMMET, 2001).
Climate plays a role in the mine waste – environment interplay. Temperature, air moist
content and precipitation govern weathering intensity. Temperature and precipitation are often
considered less important than deposit geology (du Bray, 1996). The Peruvian climate varies
with the Humboldt Current, vicinity to the Andes, latitude and other local and regional
factors. The largest differences are found when comparing the main type settings (La Costa,
La Sierra and La Selva). The coastal strip is dominated by an arid climate affected by the
Pacific Ocean and the associated Humboldt Current to the west. The Pacific evens the
10
temperature throughout the year (yearly mean approximately 20°C).
Fogs (May-Nov) and absence of rain is typical features of the
Peruvian coastal weather. The yearly precipitation amounts vary
locally but are under 50 mm/year (Encarta, 2007). The Peruvian
Andes principally receives 300-1,000 mm/year. The eastern side of
the mountain range generally receives more precipitation. The
coldest mean temperature is in June, ~3ºC and the warmest period is
April-October with a 12º C mean. The eastern part of the Cordillera
is most humid. A few areas on the eastern slopes (at an altitude in
the 2,000 m a.s.l. range.) receive up to 7,000 mm precipitation a
year. Dry season in Cusco occurs from May to October. November
to April is the wet season characterized by an increase in humidity
and rain fall. The Peruvian Amazon forest receives 1,500-2,500 mm
rain/year. The year is divided into a rainy and a dry season which
roughly corresponds to the wet and dry season in the Andes. Peru is
subjected to El Niño events every 3-7 years. Heavy rainstorms
along the coast and can cause severe floodings (Agrotechnologica
Amazonica, 2005).
The human water consumption (Table 1) is predominated by
agriculture. Public and household use is roughly a tenth. Mining and other industry consumes
comparable amounts of water (Justo, 2006).
Table 1. Use of water in the Peruvian Amazon drainage in comparison to the total Peruvian use (Justo,
2006).
Million m3 Public
use
Livestock Agriculture Industrial Mining Total
consumption
Atlantic parts of
the Amazon
drainage
0.229 0.041 1.996 0.049 0.053 2.367
Peru 1.265 0.079 16.267 1.155 0.207 18.972
The Peruvian Amazon basin
The Amazon basin (Fig. 4.) is the largest fluvial system in the world in terms of drainage area
(6.1 x106 km
2), number of tributaries and water discharge (between 34,000 m
3/s and 121,000
m3/s) (Encarta, 2007). Its length is second only to the Nile. The exact length is debatable and
range from 6,240 km (Baumgartner and Reichel, 1975) to 6,850 km (Gelli, 2007). The
Atlantic part of the total Peruvian discharge is 97.8 %. The remaining percents are shared by
the Pacific Ocean and Lake Titicaca (Guyot, 2007).
The Amazon River width (Brazil) at low stage ranges between 1.6 and 10 km. During annual
floodings the width reaches 48 km or more. Ocean liners are able to navigate the first 2/3 of
the River course. The Manaus harbor (1,600 km upstream, Brazil) can receive Trans Atlantic
ships. Smaller ships can reach Iquitos at a distance of 3,700 km from the River mouth (Butler,
2007). Population density of the Amazon Basin is 4 inhabitants/ km2 (INEI, 2000).
The geographic extent of the Amazon basin is limited by the Rio Chamaya, Peru (79° W), Rio
Pará, Brazil (48° W), Rio Cotingo, Brazil (5° N), Rio Parapeti, Bolivia (20° S) and the
Atlantic Ocean. (Guyot et al., 2007) The two principal headstreams of the Rio Amazon are the
Ucayali and Marañón rivers. Both rivers originate from high Andean glacial meltwater. The
most distant source for the Rio Amazon is the peak Nevado Mismi, southern Peru. Melt water
Figure 4. Geographical
extent of the Amazon Basin
(Modified from WRI,
2002).
11
feeds Rio Apurimac which in turn feeds Rio Ucayali. The origin of Rio Marañón is in the
Pasco watershed of the Cordillera Blanca.
The Rio Ucayali - Marañón joint is located near Nauta (90 km SSW of Iquitos). The Amazon
flow is primarily easterly towards the Atlantic Ocean (Encyclopædia Britannica, 2007). The
river delivers approximately 7 million km3 of fresh water a year to the Atlantic Ocean. This is
equivalent to 58% of the total South American runoff (Baumgartner and Reichel, 1975). The
Amazon estuary (estimated to be 240 km wide) is characterized by deltaic deposits. A
network of islands separates the river into branches. The mouth of the main stream, or the
Pará branch, is roughly 80 km wide.
The Floresta de Terra Firme, or the dry land forest unit covers the majority of the Amazon
forest (7 million km2). The Floresta de Terra Firme stretches across a large plain ranging from
130-200 m a.s.l. This forest never gets flooded even during the wet season. The extent of this
forest is largely equivalent of the Miocene - Pliocene great lake Belterra (25,000 – 1.8 million
ybp). Silt and clay deposits from this lake are still a notable landscape factor.
Another forested land cover type is the flooded forest closest to modern rivers and tributaries.
Fluctuations of water level involves a river water rise of >10 m in March-September (Fonseca
and Por, 2007).
The three principal suspended sediment sources according to the 2007 study by Guyot are:
The Andes Mountains, the Amazon Shields and Piedmont Basins. Andean sediment
comprises 87% of the total sediment load carried by the Amazon. This is in contrast to that
the Andean part of the watershed is only 12% of the total area. Also the classical study by
Gibbs (1967) recognizes the Andean part of the drainage as the principal sediment source.
The tropical tributaries are generally poor in suspended material and affect the system by
diluting the sediment concentration. The Andean sediment source area comprises only 10% of
the basin (Chakrapani, 2005). The majority (>95%) of the sediment carried by the Rio
Amazon is classed as suspended load (Ritchey et al., 1985). concludes that suspension is the
major mean of transport. Bedload on the other hand comprises only one or two percent. Most
of the suspended particles carried by the river are in the silt and clay fractions. The suspended
solid concentrations decrease as the river advances from the Andes to the ocean. During the
wet season typical concentrations in the mountainous tributaries are over 500 mg/l. East of
Xingu, Brazil concentrations are <200 mg/l (Gibbs, 1967). In the <2µm fraction of tropical
Amazon River tributaries kaolinite (88%) is the dominating mineral followed by quartz (6%)
and mica (5%). Mountainous (Andean) tributaries are subject to an even distribution of
kaolinite (29%), mica (30%) and montmorillonite (29%). The Rio Amazon mouth shares
similar characteristics as the mountainous tributaries. In the coarser 2-20µm fraction the
quartz content is between 40 and 48% for all classes. As in the <2 µm part tropical tributaries
tend to have a large portion of kaolinite (26%) with some mica (13%). Plagioclase represents
5%. Again, mountainous have the same character as Rio Amazon mouth. In the 2-20µm size
class the most common clay minerals are micas (26-27%), kaolinite (13-14%), k-feldspar (6-
7%) and plagioclase (7-8%) (Gibbs, 1967). Guyot et al. (2007) concludes that the clay
mineral signature of the Peruvian Andes is characterized by high illite and chlorite contents
(~75%). Further, there is a downstream smectite enrichment resulting from tributary input and
lateral bank erosion. Outside the mouth, Amazon fan clay minerals from depths ranging from
1,000-4,300 m were analyzed by Debrabant et al. (1997). Composition seems constant with
smectites (30-50%), illite (20-35%), kaolinite (15-25%), chlorite (8-20%) and random mixed
layer clays (trace-20%).
12
Clay percentage generally decreases as the Rio Urubamba descends from 4810 m a.s.l. (and
>60% clay) to 1890 m a.s.l. (20-30% clay). Where the Marañón joins the Ucayali the mean
clay percentage is 38.1. Downstream from Iquitos, where Rio Napa joins the Amazon River,
the clay fraction is 48.7% (Aufdenkempe, 2007).
Table 2. Mineralogic composition by size fraction and sedimentologic setting of solid material transported
(Wt %) (Gibbs, 1967).
Quartz Plagioclase K-feldspar Kaolinite Mica Montmorillonite Chlorite
Tropical tributaries (n=6)
<2µm 6 0 0 88 5 <1 <1
2-20
µm
48 5 9 26 13 0 <1
Mountainous tributaries (n=5
<2
µm
8 0 0 29 30 29 3
2-20
µm
42 8 6 13 26 0 5
Rio Amazon mouth
<2
µm
7 0 0 31 33 27 2
2-20
µm
40 7 7 14 27 0 5
Water color of the river waters in Amazonian Peru is an indicator for the drainage area and its
physical and chemical properties. Closely associated with color and trace metal transport is
organic content. Roughly 50% of the total organic carbon transported by the Rio Amazon is
dissolved organic carbon (DOC). This form is the most predominant in most tributaries. DOC
in the mainstem ranges from 2.7-4.7 mg/l. Black water tributaries can locally cause an
increase in DOC. (Rybicka et al., 1995) Total dissolved inorganic constituents transported by
the Amazon River are 232 x 106 t/year. (Richey et al., 1985) Generally the temperature
fluctuations in the Amazon basin are small throughout the year. The temperatures during the
days are approximately 26.5°C. The Amazonian lowlands are subjected to heavy rainfall all
year (average 2460 mm yr-1
). The wettest time is between January and June when vast areas
of land get flooded. Flow rates, discharge, and, river width are all affected by the seasonal
variability of precipitation. Of the total 2,044 million m3 precipitation that yearly falls on
Peru, 1,999 falls over the Atlantic part of the Amazon drainage (INRENA website, 2008).
13
Geologic history The proto-Amazon was formed during the Triassic – Cretaceous. The river system back tilted
and formed the Amazon as we know it. The modern Amazon drainage, or watershed, dates
back to the mid-Miocene. The most important geologic events related to the formation are
tectonic action or more specific: large scale convergence of the South American western
margin and the Pacific crustal plate (Potter and Hamblin, 2006).
The tectonic evolution of the Andes extends back into the Paleozoic. Plate tectonics is
ultimately responsible for the development of the Andes mountain range(s). The oceanic
Nazca plate is subducted beneath the continental South American plate with resulting trench
and present day volcanic arc and a foreland thrust-fold belt. The Peru-Chile oceanic trench is
visible evidence on the surface. The Nazca plate, being oceanic, is made up by young and
buoyant lithosphere. The buoyancy counter acts the subduction. The result of this is frequent
earthquakes (Zandt, 2002). Terrane accretion was the dominant process up to the Mesozoic.
However, it is generally believed that the present day mountain belt was developed mainly
during the Mesozoic to Recent, due to the east dipping tectonic slab and the opening of the
Atlantic Ocean (Zandt, 2002).
Subduction has occurred on the western margin of South America since early Cambrian or
late Precambrian. The Peruvian part of the Andean cordillera evolved primarily from the
Triassic to present. Mariana type subduction (extension and crustal attenuation with resulting
ocean trench, island arcs and a back arc basin) occurred from the late Triassic to late
Cretaceous. Andean type subduction (pulses of compression) occurred from the late
Cretaceous to present.
Subduction along the South American western margin is considered one of the biggest events
affecting modern drainage.
Highland production and continental tilt away from active margins and mega
structures
Drainage parallel and following fold belts
Rivers following regional strike-slip and transform faults (Potter and Hamblin, 2006).
Cenosoic Era - Opposite direction of flow. Outlet in the pacific
Rise of the Andes (23-8Ma) -River dammed and formation of massive lake Pebas (Miocene) and associated wetlands
Ucayali Peneplaination due to sea level drop 14.5-11.3 Ma
Tidal sedimentation and Madre de Dios formation ended peneplaination during middle and late Miocene (11-8Ma). Renewed Andean compression/uplift.
8Ma: Lago Pebas drained due to plate tectonic action
Megalake Lago Amazon or series of mega lakes during latest Miocene-~2.5 Ma
Amazon function as one or a series of sedimentary basin. Development corrolated with Andean tectonics
Modern Amazon drainage established during the late pliocene at ~2.5 Ma
Deforestation since the mid 1960's. south-east Brazil
Dams built in for exampel Tucuruí and Curua-Una, Brazil
Figure 5. Natural and humanly induced factors of the Amazon basin evolution (Data from Rodaz et
al., 2005; Campbell, 2006).
14
The Peruvian Andes
With its 9,000 km the Andes is the longest mountain range in the world. It runs along the
entire western margin of South America. The northern extreme is marked by the Caribbean
submerged peak islands of Aruba, Bonaire, and Curaçao. The Andes range is approximately
200–300 km wide throughout its length, except in the Bolivian flexure where it is 640 km
wide. The average height is close to 4,000 m. The Andes is composed of two major parts, the
Cordillera Oriental and the Cordillera Occidental. These are often separated by an
intermediate depression. In Peru the mountain range splits further in the smaller units:
Cordillera Negra and Cordillera Blanca (Wikipedia, 2007).
Study areas Three areas (Fig. 6) representing
different settings were chosen for
the sampling and fieldwork. In the
Southeastern states (Spanish:
departemento) of Cusco and
Madre de Dios mainly the
Amazon headwater Rio Urubamba
and the Amazon tributary Rio
Manú were studied. A few
locations outside these rivers were
also researched (i.e. Laguna
Huarcarpay and Rio Alto Madre
de Dios). The bordering regions
Cusco and Madre de Dios differ in
topography, geology, sediment-
ology, climate, population density
and land use.
Approximately 1,000 km north of
Cusco the north-central part of the
Peruvian Amazon was visited.
Sampling here was limited to one
sample each in the Amazon
mainstem and the Rio Marañón.
See appendix A for details on
sample locations.
Figure 6. Locations treated in this paper: Upper left; Detail map over the Loreto research area, Lower
left; Detailed map over the Cusco - Madre de Dios research area. The sample sites are indicated by the
small, open stars.
15
The state of Cusco
The Cusco region is located in the southern Peruvian Andes. The regional capital Cusco city
is located roughly 500 km south-east of Lima at approximately 3,400 m a.s.l. The landscape is
hilly and slopes are generally moderate. Elevations on the Pampa are in the range of 4,200 –
4,600 m. Gorges are set at a height of 3,000 – 4,200 m. This area was chosen because of a)
the effect of man is contributed over a relative short distance compared to the Amazon
mainstem b) easy access due to the Cusco Airport and drivable roads to the sampling sites and
c) the high altitude (>3,000 m) which is different from the other areas in this study.
Figure 7. Sample map of the Cusco area.
Geology and sedimentology
The complex Andean geology contains intrusive igneous rocks (such as the white-gray
Paleozoic Vilcapampa batholith) as well as sedimentary and volcanic rocks. At Aguas
Calientes, not far from Maccu Picchu, Paleozoic plutons (Plutones Tardihercinicos) constitute
the local geology. The Rio Urubamba/Vilcanota at Urcos is right at the limit between early
Cretaceous - Paleocene bed rock formations on the western side and older Silurian - Devonian
metasediment on the eastern flank. Sedimentary rocks are the most common in the
investigated areas of Cusco. The oldest rocks are further to the north-east and vice versa. To
the west of these areas igneous and volcanic rocks are more common (INGEMMET, 1999b).
Mollisols, rocky land and inceptisols comprises most soils in the State of Cusco (USDA,
1998).
Rio Urubamba
Rio Urubamba is the largest river in the Cusco region. The total Urubamba watershed area is
7,000 km2 (MINAG, 2007). The river is partly navigable and a headwater of the Rio Ucayali.
The river passes south-east of Cusco near the Puno state border where it’s called the Rio
Vilcanota (Figure 8). In the Sacred valley between the villages of Pisac and Ollantaytambo
16
the local name is Rio Wilcamayu (Quechua for The Sacred River). After this point the
Urubama flow north-north-west for approximately 724 kilometers before joining with the
lower Rio Apurimac to form the Rio Ucayali. At Aguas Calientes (Figure 9) a steeper
gradient causes faster flow.
The bed rock at Urcos is dominated by Late Cretaceous Huaro and Lucre formations on the
southwestern side. The Paleozoic Urcos formation takes over on the other side of the river.
Further downstream, towards Cusco, the Urcos formation occupies both sides of the river
(MEM, 1999b).
Figure 8. View of the Rio Vilcanota in the rural areas of Urcos city. Samples were taken on the western
bank (the one closest to the camera; Author, 2007).
Rio Urubamba is often divided into Upper and Lower Urubamba. The divide separating the
two is the whitewater canyon of Pongo de Mainique. The Upper Urubamba (Alto Urubamba)
valley is more densely populated than the lower. The use of irrigation is also more frequent
here. The valley features ruins, including the Incan city Machu Picchu. Other than the town of
Sepahua population around the Lower Urubamba (Bajo Urubamba) is relatively sparse.
The river is affected by wastewaters from the Cusco city landfill. 310,000 kg of household
wastes daily affects the Rio Huatanay which directly feeds the Rio Urubamba. The Huatanay
– Vilcanota confluence is located near Laguna Huarcarpay at the city of Huambuito. Also, a
large portion of people living near the river throw their garbage into the river, partly due to
the lack of regulated landfills (USAID, 2007; Bolanos and Carranza, 2006). During sampling
in the Rio Vilcanota cars were being washed into the river and garbage was spread on the
river side beaches.
17
Figure 9. Rio Urubamba near the central parts of Aguas Calientes downhill the Machu Picchu world
heritage site, 150 km downstream Cusco (Author, 2007).
Laguna Huarcarpay
Laguna Huarcarpay (48 km drive S of Cusco at 3,170 m a.s.l.) is one of three lakes in the
3,800 Ha Lucre-Huarcarpay wetland systems. The lake depth is 8.6 m (Austermühle, 2002).
The wetland occupies the Rio Lucre sub-basin, characterized by being a sub narrow rocky
canyon. The basin bottom is wide (4km). The dominating soil type in the area is alluvial
deposits made up by layers of clay, silt, sand and gravel. Lacustrine sediments are inherited
from a Pleistocene lake covering large part of the basin. Colluvium and fluvial sediment
deposits are also present. Rocks are sedimentary and volcanic in origin and were formed from
the Paleozoic to the Quaternary. Conglomerates and sandstones dominate the surroundings
(Ihue, 1992). The rocks dominating in Laguna Huarcarpay area is the cretaceous Lucre
formation of the Chitapampa group (MEM, 1999).
Around the wetland, mountains dominate the view in all directions. The inclination reaches
25 to 50%. The land use and coverage includes Totora sedge, prairie type plants, thorny
shrubs and bushes. Small scale farming and grazing occurs in the region.
Typical for the governing climatic conditions is the Kaztanozem type soil with high organic
content, calcareous nature and a pH range from 6.8-7.18. A more or less pronounced salinity
characterizes most soils in the valley (ACUÑA, 2003).
18
Figure 10. Laguna Huarcarpay (Author, 2007).
Climate
The heterogeneous climate characteristics of the Cusco region originate from the topographic
and geographic properties. The year is divided into a rainy (November-April) and a dry
season (May-October). The driest month is June. Most precipitation events occur in January.
Cusco City receives approximately 700 mm of precipitation a year. The 24 hour temperature
mean varies little throughout the year and is typically around 12°C. The dry period is
generally colder (MINAG, 2007).
Mining activity intensity
Mining activities in the Cusco state are limited to a few (with Andean standards) copper, iron
and polymetallic mines. Fe- and Cu skarn and porphyry copper occurrences dominates. There
are 1,226 registered mining rights in the region. Mining projects and operations are mainly
located to the south or south-west of Cusco city. Morosayhuas (Cu, Au, Zn, Pb and Ag),
Cotabambas (Cu, Au), Accha (Titiminas) (Zn, Pb), The Cerro Ccopane are among the most
important. The Cusco state also has 44 passive or abandoned mines (INGEMMET, 2007a and
MEM, 2006). The copper producing San Antonio de Cobre Cjata mine could possibly affect
the sediments downstream Urcos (DGM, 2002).
Of the abandoned mines two are located close to the Rio Huatanay (which feeds the Rio
Urubamba). The first is the Cancharahuay mine (abandoned 1988). Minerals found at the site
are crisocola, malakite, quartz, limonite and hematite. The mine and tailings drain to larger
water bodies only in the wet season. The 2000 MEM survey of the area showed no signs of
acid mine drainage. The same study considered the environmental effect of the mine and
tailing piles small. The other abandoned mine is the Kasapata (abandoned in 1983). Redish
19
sedimentary rocks dominates local bedrock outcrops. The mineral assemblage is similar to
that of the Cancharahuay mine. No indications of acid mine drainage. The former mining
activity is considered too small to cause any serious environmental damage (MEM, 2000).
The Mayutincco mine (abandoned in 1993, altitude 3,625 m a.s.l.) and Viscapata mine
(abandoned 1988, altitude 3,680 m a.s.l.) could potentially affect the metal contents of the
Laguna Huarcarpay sediment. The former mines of Mantanay (abandoned in 1988, altitude
3,400m) and San Cristobal (abandoned in 1997, Altitude 4,220 m a.s.l.) are close to the
Urubamba river town of Aguas Calientes and could thus have an effect on the sediment trace
metal pattern (MEM, 1999A).
Land use and coverage
The Pampa (from Quechua meaning plain) is usually covered by grass species. At lower
elevations shrubs and trees are common although the grass cover is still dominant. Small
herds of sheep, llamas, alpacas and cattle graze the land. The population density in the state of
Cusco is 16 inhabitants/km2. In some urban areas (such as Cusco city) the density reaches
over 1,000 inhabitants/km2(INEI, 2000).
The state of Madre de Dios
The entire area of Madre de Dios is situated within the Amazon River basin. Here, the
research area is in the western parts of the region. The Madre de Dios watershed is the largest
Amazonian sub-watershed in the area. Most rivers are considered white water rivers. The
main reason for choosing this area is that the human impact is virtually non-existing.
Figure 11. Madre de Dios sample location map.
20
Geology and sedimentology
Sediment is deposited on a seasonal basis and forms alluvial plains along the modern rivers
and tributaries throughout the state. The meandering character of many of the rivers has left a
number of oxbow lakes on the river plains. The lowlands between the rivers have a hilly
topography with slopes between 15 and 50% (UNEP-WCMC, 1997).
The area is part of the Madre de Dios foredeep of the South Amazonian foreland basin
system. The sediment source according to REE patterns are probably Brazilian shied and
Paleozoic - Mesozoic terrains (Roddaz et al., 2005). Large areas are covered by Quaternary
colluvial deposits. The soil material is characterized as Leptosols and regosols. Fluvisols
occupies the zones next to rivers (INRENA, 2007).
The few bedrock outcrops are reddish and grey sedimentary rocks (MEM, 2000). Sedimentary
rocks (superior Tertiary-Recent Quaternary) principally comprise the bed rock up to 1500 m
a.s.l. Over this level sedimentary and metamorphic rocks of the Precambrian and Paleozoic
eras (>440 ma) take over. On the western side of the Madre de Dios basin Cretaceous and
Precambrian – Devonian sedimentary rocks lies side by side with Cretaceous−Tertiary
volcanic and further away Mesozoic−Cenozoic intrusives (Schenk et al., 1997). On the
eastern rim, Permian and Mesozoic batholitic rocks intrude the Precambrian unit called the
Arequipa massif, which in turn thrust eastwards over marginal Mesozoic rocks. It is generally
believed that the Arequipa massif has been part of the South American Shield at least since
the Paleozoic. This corresponds to the Peru flat slab segment of the subducting Nazca Plate.
Young (Holocene) alluvial deposits cover most of Madre de Dios department. Large recently
deposited quaternary to recent sediments in the vicinity of modern rivers and flood plains.
Also, tertiary deposits of colluvial character (Schenk et al., 1997). Ultisols covers most of the
low-lying areas of the Madre de Dios sub-basin. Inceptisols are in abundance when elevation
gets higher to the west (Andes). Some patches of oxisoils could also be present (USDA,
1998).
21
Figure 12. Rio Manu, near sample site 8 (Author, 2007).
Rio Manu
The total length of the river is approximately 300 km. High water is from December to March
(Ziesler and Ardizzone, 1979). Rio Manu (Figure 12) is joining the Rio Alto Madre de Dios at
Bocca Manu to form the Rio Madre de Dios (Spanish for Mother of God).
The river flow is from west to east before entering Bolivian territory. After this point the river
course is diverted to the north and joining with the Rio Beni. After yet another joint (with the
Rio Mamore) the River changes name to Rio Madeira. The Madeira – Amazon joint is located
some 120 km east of Manaus, Brazil. Rio Manu and Rio Madre de Dios are characterized by a
high degree of meandering, murky brown waters and numerous oxbow lakes (cochas).
Rio Alto Madre de Dios
Rio Alto Madre de Dios (Figure 13) translates to the High Mother of God. This name is a
consequence of its high altitude origin and course. The river gets its water from the narrow
Alto Madre de Dios Basin. Flow is generally from south-west to north-east before joining Rio
Manu at Bocca Manu.
The river is follows the border between the Pleistocene Madre de Dios formation and
Holocene alluvial and fluvial deposits. Through a long part of its course the Paleocene
Yahuarango and Chambira formations are present (INGEMMET, 1999a).
22
Figure 13. Rio Alto Madre de Dios
Climate
Most of Madre de Dios is characterized by a humid tropical climate. The period between
November and April is marked by heavy rainfall (7,000 mm/year locally) whereas May to
October is considered a dry period (MINAG, 2007).
Land use and coverage
The remote locations make the sediments rather untouched by human activities. Some
downstream alluvial gold mining and very limited tourism occurs. With a population density
of <1 inhabitants/km2 the direct human impact is small (INEI, 2000). The state of Madre de
Dios has 1,334 registered mining rights. Mostly small scale and informal gold mining of
placer deposits occupy the mining sector in this region. In 2006, there were 22 abandoned
mines in the entire state (MEM, 2006).
Manu National Park, located in the Department of Madre de Dios is one of the most
biologically diverse protected areas in the world. Tropical lowland forest, montane forests and
puna (grasslands) all give good conditions for 850 bird species, 15,000 species of plants and
at least 13 threatened wild life species makes Manu an area of preservation value (IUCN
Technical Evaluation, 1989).
The state of Loreto
The state of Loreto occupies the northwestern corner of Peru. This is the largest region in the
country. Loreto shares borders with Ecuador, Colombia and Brazil. The area is completely
within the Amazon basin. The area studied in this work is in the Iquitos – Pacaya Samiria
23
reserve area in the central parts of the region. The goal of the sampling here were to
investigate an area which receives water from the majority of the Peruvian mining areas.
Geology and sedimentology
Flood plain deposits are common are
common throughout Loreto. The
geomorphology is hilly topography
(McElwee, 1999). The Loreto samples
are located in the Putamayo-Orient-
Marañón basin which is dominated by
Quaternary colluvial and alluvial
sediments. Tertiary rocks and sediments
could be found away from the modern
rivers (Schenk et al., 1997).
The river is constantly changing its path
and thus dumping silt over a large area.
Lower lying areas are flooded as the
river rises 10-15 meters during the wet
season. The loose soil of Loreto is
composed mainly of sand, with little clay
and silt content. The Amazon River
islands are composed mainly of silt
(McElwee, 1999).
Oxisoils covers large areas of the Loreto
state (and the rest of the Amazon basin).
Inceptisols are found near the present
fluvial channels (USDA, 1998). Highly
erodible Lixisols are related to
subsurface kaolinitic deposits. Acrisols that is naturally low in plant nutrients and Aluminum.
Alisols could be found in areas with higher temperature and precipitation. The Alisols
typically have high and mobile Al-contents (INRENA, 2007). The Amazon River is already
described above.Sampling was carried out near Iquitos, about 3,700 km from the river mouth.
Rio Marañón
Rio Marañón (together with Rio Ucayali) is the main headwater for the Amazon River. The
river reaches 1,600 km in length. Flow is more or less from south to north and in the latter
part of its course turning east to join Rio Marañón near the city of Nauta.
Climate
The Loretian climate is uniform throughout the year. There is no formal rain season since the
rainfall in the driest month exceeds 60 mm of precipitation. The wettest period occurs from
November - March. The yearly mean temperature is 26.5ºC. Annual precipitation is over
2,500 mm. Annual mean humidity is close to 60% (McElwee, 1999). The Iquitos climate is
hot and humid, with an average relative humidity of 85%. The wet season lasts from
approximately November to May, with the river reaching its highest point in May. The river
is at its lowest in October.
Figure 14. Loreto sample location map.
24
Land use and coverage
Land use is composed of secondary succession tropical forests, industrial areas near and
around Iquitos. Deforestation is a problem in the region. Iquitos is an urban centre (260,000
inhabitants) in the middle of the Amazon rain forest. The high population density (with
Amazonian standards) causes problems in waste management and water resource policies.
When sampling in Iquitos, Loreto household waste was observed on the river beaches (even
more so than in the Urubamba samples). Municipal waste is let out in the Amazon River on a
continuous basis. Population density in the Loreto region is 2.39 people/km2 (INEI, 2000).
88% of the region is covered by primary and secondary forests and the remaining part is
largely used for agricultural activities (MINAG, 2007). The Loreto state has 40 registered
mining rights. Mining is virtually non-existing and limited to the south western margin of the
region and could thus be left out of this study.
Figure 15. Western Rio Amazon beach close to Iquitos (Author, 2007).
Methods
Fieldwork and sampling
12 sediment samples and 4 bedrock pieces were retrieved in mid-August to mid-September.
Most samples were taken in the fluvial channel-fluvial plain near the river (<25 meters). In
meandering river setting the depositional inner curve was selected to prevent erosion effects.
Here fine material (such as silt and clay) accumulates during seasonal flooding events marked
by discoloration of nearby tree stems. Discrete levees were observed in Madre de Dios. These
were marked with differences in vegetation and a gentle topographic bulge. The average
amount of sediment in each sediment sample was approximately 200±50 grams dry weight. A
diary (Appendix A. Sample record and Field observations) was used to keep track of the
geological settings, altitude, locations and other important details involved. All samples were
25
kept in zip-lock bags at room temperature except when traveling in tropical areas. Positioning
of the sample sites was done by using a handheld Magellan Xplorist 100 GPS-unit (reported
accuracy of 3m).
Figure 16. Approximate sample location and environment features.
Visual examination of soil samples
Samples were described in the field. Sediment colors were described using the Munsell rock
color chart. The color and smell were used to characterize differences in the redox status.
Grain size distributions and grain shapes for the coarse fractions (>sand) of the samples were
also assessed.
The field determination was complemented by laboratory analyses (see p.30). Also, a more
precise grain shape determination was done using a stereo microscope. Basic grain
mineralogy was done using the same equipment. If available, the >2 mm fraction from the
wet sieving has been used. In practice, fractions ranging from 250 µm to 1 mm have been
used since the coarser material is very limited or not available. For each sample 200 grains
have been counted.
Analytical procedures
All analyses listed below were carried out in the University of Gothenburg Quaternary
Geology laboratory at Earth Science Centre, Gothenburg in the fall and winter of 2007-2008.
Grain size distribution analyses
Wet sieving and Sedigraph were used to construct histograms and plots. Descriptive statistics
were calculated using the Gradistat v5 Excel spreadsheet. The geometric Folk and Ward
(1957) method was used.
The distribution of fractions coarser than 63 μm (i.e. the silt-sand transition using the Udden-
Wentworth scale) has been determined by wet sieving. Following removal of organics (H2O2)
and dispersion (Na6(PO3)6) the 2000, 1000, 500, 250,180, 125, 90, 63 μm 3 inch diameter
sieves were used to isolate each size class. A Micrometrics 5100 sedigraph was used for the
Annual flood limit
Levee
Erosion (outer
curve) vs.
Deposition
(inner curve)
Sample point
26
sizes smaller than 63μm. Residual material from the wet-sieving was used for the distribution
analysis of the silt and clay fractions of the total sediment. The Sedigraph uses X-ray
absorption to measure changes in mass concentrations as used, particles settling in a liquid
with known properties. The liquid in this study was deionized water.
The sedimentation analysis is based on Stokes’ Law.
The method assumes that a single solid sphere settling in a fluid has a terminal settling
velocity which is uniquely related to its diameter.
Aluminum contents from the ICP-MS analysis have been used as a grain size proxy in
normalizations.
Loss on ignition analysis
The sediment samples were subjected to the Loss on ignition (LOI) procedure described by
Dean (1974). The LOI analysis gives only a rough estimation of organic content. The organic
content is well correlated to LOI though (R2=>0.9). Samples were first dried overnight at
105°C and weighed. After this, samples were burnt at 550°C for three hours, cooled in a
dessicator and weighed. To incinerate the CaCO3 carbon dioxide the samples were further
heated to 950°C for another three hours. By calculating the weight loss after each of the steps
organic and inorganic carbonate contents could be roughly approximated. Each LOI sample
contained 20 g±1g dry weight.
LOI550 = ((DW105–DW550)/DW105)*100 (Equation 7)
LOI950 = ((DW550–DW950)/ DW105)*100 (Equation 8)
A correction factor of 1.36 was applied to the LOI950 results to account for the difference in
CO3 and CO2 molecular weights. Samples were made in duplicates to assure satisfying
results.
XRD
A Siemens D5005 X-ray diffractometer were used to determine and quantify the mineralogy
for four selected samples (3, 4, 7 and 12). Samples were chosen to cover all settings with a
limited amount of samples. The fine sand fraction (125-250µm) was separated, grind and 2g
of sample was mounted in a plastic sample holder. The analyzed interval was 2θ = 5-65°, in
0.02° steps. The samples were rotated at 30 rpm. The samples used are listed in Appendix F.
Siemens EVA was used for the mineral identification. Quantitative estimation of mineral
assemblages was done by using the SIROQUANT™ software. Typical detection limits for
this setup is generally 1%.
2
1
1s
stg)(
V18D
Equation 6. Dst = Stokes’ diameter
η = fluid viscosity
ρs = de ensity of the solid ρ1 = density of the liquid
V = settling velocity
g = acceleration due to gravity
27
Geochemistry
The geochemical work of this report is limited to the acid digestion and ICP-MS
multielemental analysis described below. Various normalizers have been used and statistical
techniques have been applied to evaluate the results.
Acid digestion of samples
Duran 100 ml sample bottles were soaked in 10% HNO3 and thoroughly rinsed before use.
The <63m samples for the inductively coupled mass spectrometer (ICP-MS) were divided in
two series. These were subjected to two different treatments.
Nitric acid digestion: 1g of sample dry weight exposure to 20 ml 1:1 HNO3/Deionized water
(Milli-Q) for 3 hours at 121˚C in an Autoclave. The residual matter was removed by using a
centrifuge for 5 minutes at 4000 rpm. The method used is a modified version of SIS (1997).
(du Bray, 1996)
Aqua Regia digestion: 1 g of sample were subjected to 20 ml (3:1 HCL/HNO3 ratio) at
121˚C 3hrs followed by 16 hours at room temperature. The centrifuge procedure for particle
removal is described above. The method used does not digest the total metal contents of the
samples. Aqua Regia will dissolve all “environmentally available” elements. Refer to US
EPA, (1996) for more detailed information.
(du Bray, 1996)
HNO3
Easily soluble phases
Humic materials
Carbonate phases
Aqua Regia
Easily soluble phases
Humic materials
Carbonate phases
Organic matter
Maximize mobility
Sulfide minerals
28
The basis for using the first method (see above) is to extract the biologically available part of
the total sediment content of the analyzed metals and arsenic. The second method aims at
extracting the total metal content of the sediment. Aqua Regia extraction leaves undissolved
residual material which comprises the most immobile phases. Recovery rate, accuracy and
precision are further discussed elsewhere in the discussion.
ICP-MS
The prepared samples were run through a HP 4500 series ICP-MS. Acid leachable
multielement analysis included eight elements. The investigated metals and metalloids were
Al, Cr, Fe, Cu, Zn, As, Cd and Pb. A blank sample was used to account for metal
contamination by the acids used. The raw data from the ICP-MS analysis were recalculated
and conversed from µg/l to mg/kg. The initial 1 g of sample and 20 ml acid was put in the
beaker as stated in the Swedish Standard (SIS, 2003). Typical detection limits for the HP
4500 series is in the ppt range. Conversion of raw data (µg/l) to desired unit (mg/kg):
𝐴2 = 𝐶2 ∗ 𝐿2
𝑀𝐷+
𝑀𝐶
100 (Equation 9)
Extraction with Aqua Regia is element dependent but 70-80% has been reported by Davies et
al. (1999). Additional content could be extracted using hydrofluoric acid. A true total content
is not available using this digestion agent.
Normalization and statistics
The ICP-MS results have been normalized to selected parameters to avoid natural variability
of metal concentrations. Since positive metal ions bond extensively to organic matter and clay
sized particles these parameters have been taken into account for the normalization. Loss on
ignition serves here as substitute for true organic content. Grain size normalization have been
done using two fraction intervals, clay (<2µm) and mud (<63µm). Aluminum has been used
because most anthropogenic activities do not cause enrichment of this conservative metal
(refractory lithophilic element). Population density has also been used in normalizations. All
elements have finally been plotted against each other to see which show similarities in their
relative distribution. Five different normalizers were tested to statistically evaluate relations
between the above mentioned parameters and metal concentrations:
([Me+]sample / Alsample) * Alaverage (Equation 10)
([Me+] sample / LOIsample) * LOIaverage (Equation 11)
([Me+] sample / Clay%sample)* Clay%average (Equation 12)
([Me+] sample / <63µm %sample)*<63µmaverage (Equation 13)
([Me+] sample /Pop. density sample)*Pop. densityaverage (Equation 14)
Element contents have been plotted against population density and altitude to further
determine any significant anthropogenic or naturally occurring trends.
Statistics
Statistical parameters like R2 and 95% confidence limits (2) were used to quantify deviations
from what is considered a natural content. The confidence limits have been used in ICP MS to
find data outliers. Sample points outside these limits are considered impacted by man. The
main statistical analysis conducted in this study is a principal component analysis to evaluate
29
which elements and parameters are related to each other. A correlation matrix was constructed
to evaluate which parameters to include in the following analytical steps.
Grain size statistics like kurtosis and skewness have been calculated to be able to tell
something about transport and deposition of the sediments.
Statistical analyses were made using SPSS release 13 for Windows. Microsoft Excel 2007 and
The Gradistat v5 and Sediment Quality Index 1.0 spreadsheet were used for grain size
statistics.
Sediment quality guidelines and enrichment factors
At present there are no available guidelines for the tropical Americas. The Canadian Sediment
Quality Guidelines, CCME (1999), have been used as a substitute. The method uses scope,
frequency and amplitude to rank the samples from 0=bad to 100=good. Below The Interim
Sediment Quality Guidelines threshold biological effects are not likely. The probable effects
level defines the bio affecting metal content (CCME 1999). The Swedish SEPA (1999) and
the American NOOA, (1999) sediment quality guidelines have been employed for comparison
of CCME results. Enrichment factors have been calculated. The lowest sample concentration
of each element has been used in the element background assessment. Refer to Appendix E
for suggested background contents used in the enrichment factor calculations.
Enrichment factor = Element contentsample / Element contentbackground
(Equation 15)
Pollution Index
Although slightly controversial the PI-method (employed by Kloke 1979) has been used to
get an idea of the total toxicity of the samples. The idea is to account for the effect of the total
metal cocktail of the sediments rather from the single metallic elements toxicity.
P. I. = Cd
3+Cu
100+Pb
100+Zn
300 /4
(Equation 16)
Results The ICP-MS results are crucial to assess the contaminant levels at the various sampling
localities. The other results (i.e. LOI, GSD and XRD) were mainly used to put the metal
concentrations into a context.
Visual examination of soil samples
The visual examination shows that the grain assembly matures lower in the drainage. The
largest variation in mineralogy exists in the Cusco region samples. Madre de Dios samples
have a larger variety of minerals than the Loreto samples. Rock fragments were found in the
Rio Urubamba samples and to some degree in the Rio Alto Madre de Dios. The Rio Marañón
sample is less mature than the Rio Amazon sample and has more in common with Rio Alto
Madre de Dios in terms of grain roundness and shape.
30
Table 3. Mineralogic features observed using hand lens or stereo microscope. The 1-2 mm fraction was
examined if not otherwise noted.
Sample Description
1 Quartz grains sub angular – surrounded semi spheres. Sample dominated by arkose and
sandstone rock fragments. Feldspars surrounded spheroids. Less than 5% dark mineral
grains.
2 A mixture between a number of sedimentary rock fragments. Calcite not as abundant as
sandstone and arkose. Quartz grains immature and sub angular. Dark minerals constitute
7%
3 A bit enriched in rounded sphere shaped quartz compared to other Andean samples.
Feldspars well rounded. Dark minerals make up <10%.
4 Quartz angular rods-blades constitute ~ 50% of sample. Feldspars sub rounded-sub
angular and rod shaped. Dark minerals and slate 25%. Sedimentary rock fragments 25%.
5 40% dark minerals. Magnetite about 10% of the dark portion. Quartz sub rounded and
spheroid-disc shaped. Feldspar sub angular spheroid-rods.
6 About 50 % dark minerals. Magnetite about 10% of the dark portion. Quartz sub
rounded and spheroid-disc shaped. Some sulfur coating on grains. Feldspar sub angular
spheroid-rods.
7 About 50 % dark minerals. Quartz sub rounded and spheroid-disc shaped. Some
sulfurcoated grains. Feldspar sub angular spheroid-rods.
8 Quartz sub rounded-sub angular and spherical. Feldspar rounded disks. Sedimentary
rock fragments of various kinds. Dark and silvery mineral predominance.
9 Beige sandstone fragments predominate. Quartz grains sub angular-rounded and shaped
like partly spheroidal rods.
10 Mud dominated sample. Dark minerals and rock fragments constitutes 25% respectively.
11 75 % of sediment is spheroid formed and rounded – well rounded quartz. Few dark
minerals, feldspars and rock fragments.
12 Quartz grains dominate in the 250-500µm grain size fractions. These are rounded-well
rounded and spheroid-disc shaped. Few dark minerals of which about half magnetite.
Generally more immature than sample 11.
Grain size distribution
The clay content is higher in the lower altitude river samples researched. Rio Madre de Dios,
Rio Amazon and Rio Marañón have similar mud levels (<63µm). The smallest fine material
fractions are found in the Andean samples of the Cusco region. Further details and statistical
parameters listed in Appendix B. Grain size distribution and statistics.
31
Figure 17. Clay, silt, sand and gravel distributions of samples.
Sample 1 has a large fraction that is coarser than sand. The remaining fine material portion is
too small to obtain satisfying results. The sample 1 skewness and other statistics could not be
correctly determined. A sieve with coarser meshes and larger sample quantity is necessary too
obtain more accurate results. Samples 2 and 3 have dominating sand fractions (>90%). Stream
velocity prevents fine material from accumulation in sample 3. Sample 4 and 5 have a
dominant silt fraction and lack a significant gravel fraction. Rio Manu samples (6-8) are not
dominated by a single size fraction. The large silt and clay fraction in sample 10 is explained
by lee side deposition of fine material due to large rocks and complex channel form that
creates calm portions of the river. Differences in samples 11 and 12 are due to different terrain
sample locations rather than any large sedimentological variations
Mean grain size (µm)
Sorting ()
Skewness
Kurtosis
Figure 18. Descriptive statistics for the grain size samples.
0% 20% 40% 60% 80% 100%
1
2
3
4
5
6
8
9
10
11
12
Gravel >
2mm
Sand
63μm-
2mm
Silt 2-
63μm
Clay
<2μm
1.0
10.0
100.0
1000.0
1 2 3 4 5 6 8 9 10 11 12
0.0
10.0
20.0
1 2 3 4 5 6 8 9 10 11 12
-1.5
-1.0
-0.5
0.0
0.5
1 2 3 4 5 6 8 9 10 11 12
0.0
1.0
2.0
3.0
1 2 3 4 5 6 8 9 10 11 12
32
XRD
Some minerals not included in the SIROQUANT database have been excluded from the
quantification. Quartz and feldspars dominate all samples. Heavy minerals are more common
and the mineralogy is more diverse in the Andean samples than in samples from the other
environments.
Table 4. SIROQUANT results.
1Low.
2Monoclinic.
Sample Mineral Formula Contrast corrected weight % Error Chi2
3 Albite1 NaAlSi3O8 12.90 0.54 2.36
Quartz SiO2 66.60 0.79
Anorthite2 CaAl2Si2O8 2.50 0.51
Jarosite KFe3(SO4)2(OH)6 1.20 0.25
Muscovite KAl2(AlSi3O10)(F,OH)2 16.80 0.71
Σ 100.00
4 Microcline KAlSi3O8 35.00 0.74 2.27
Quartz SiO2 65.00 0.74
Σ 100.00
7 Quartz SiO2 91.50 1.58 2.33
Microcline KAlSi3O8 7.50 1.26
(Wollastonite) CaSiO3 1.00 1.05
Σ 100.00
12 Albite NaAlSi3O8 46.00 2.32 3.00
Quartz SiO2 54.00 2.32
Σ 100.00
Sample 3 is the most mineralogical diverse sample in this study. Quartz (~67%) predominates
accompanied by plagioclase (mainly albite and anorthite) and muscovite. Jarosite is a heavy
mineral found in this sample. Madre de Dios samples (4 and 7) are comprised mainly of
Quartz (65 and 91.5 % respectively). The K-feldspar Microcline dominates the residual part
of the mineralogy. The Amazon sample (p.12) is principally all albite and quartz. The quartz
fraction (54%) is the lowest in the study.
Loss on ignition analysis
Loss on ignition generally ranges from a couple
percent to 12% (See Appendix G. LOI results).
Sample 1 and 2 are anomalously high though with
percentages loosed of 62 and 23% respectively.
Both samples are affected by ongoing biological
production. Sample 6 and 8 have low LOIs of about
1%.
0 20 40 60
123456789
101112
LOI %
Sa
mp
le
550°C 950°CFigure 19. Loss on ignition at 550 and 950 ºC.
33
Trends in the various sedimentological settings are weak. Samples of Andean origin have the
highest mean organic content. There are large variations in both the organic and the CaCO3
fractions. Not surprisingly, the Madre de Dios samples show similarities in CaCO3 content
although the organic content varies from next to nothing to about 8 wt%. The Loreto samples
have similar contents of organics and CaCO3 of about 9 wt% and 11 wt%, respectively.
ICP-MS
The Aqua Regia and the HNO3 extractable phases show similar element distribution patterns
between the samples. Al, Cr and Fe are more immobile than the other elements and only
~70% of the Aqua Regia contents are extracted in the HNO3 extraction compared to 80-100%
for the other elements. Arithmetical means for each state of the HNO3 and Aqua Regia
extractable contents are provided below.
Areas with a large human presence generally have sediments with a higher metal and As
contents. Samples with low population or little land use have low copper content (roughly one
third - half) even if the normalization techniques employed. Zn is nearly three times higher in
populated areas. As is higher in samples taken near active or abandoned mines. Comparably
high Cd and Pb levels are found at sites near larger roads and heavily used river sections.
Figure 20. Left: Arithmetical means for the HNO3/H2O leachable fractions. Right: Arithmetical means of
Aqua Regia extractable content. Rio Alto Madre de Dios samples are included in the Cusco values.
Cusco state including Rio Alto Madre de Dios
The metal contents of sample 1 is close to the mean of the Cusco samples although low in Zn,
Cd and As. Sample 2 has a relatively low element contents, comparable with the Madre de
Dios samples. Sample 3 has the study’s highest Fe concentration and is second only to sample
10 in Zn, As and Pb. The locations of these samples are characterized by a high population
density and a short distance from mining activities. The sample is lower than the Cusco mean
in Al, Cr and Cd. Sample 4 has the highest contents of Cr and Cu. Al, Fe, Cd are also rather
high in comparison to the other Cusco sediments. Sample 9 is comparable to sample 4
although slightly lower in all element contents. Sample 10 is high in all elements except Al
0.01 0.1 1 10 100
Al (%)
Cr
Fe (%)
Cu
Zn
As
Cd
Pb
mg/kg
Cusco Madre de Dios Loreto
0.01 0.1 1 10 100
Al (%)
Cr
Fe (%)
Cu
Zn
As
Cd
Pb
mg/kg
34
and Cr. This site has the study’s highest Zn, As, Cd and Pb contents (2-3 times the Cusco
mean respectively). The fact that the Rio Alto Madre de Dios samples are here included in
Cusco lowers the Cusco mean metal and As contents.
The state of Madre de Dios
Sample 6, 7 and 8 are only separated by kilometers. Differences in metal content could be
observed despite the limited spatial distribution. While sample site 8 generally has the lowest
metal and arsenic contents site 7 show moderate to high levels. Sample 5 and 6 have low
contents of all analyzed elements and are close to the Madre de Dios mean. Sample 7 has the
highest contents of all elements compared to the other Madre de Dios samples (excluding the
Rio Alto Madre de Dios). Sample 8 has the lowest total metal and As load of the state.
The state of Loreto
Sediment metal content in the two Loreto samples (sample 11 and 12) does not vary
significantly. All elements except As are above the study mean.
Figure 21. HNO3 extractables. Note the logarithmic scale and refer to Appendix C for complete data.
If the HNO3 fraction is correlated to the Aqua Regia fraction R2-values are over 0.9 (Lower
for Fe and Pb). The HNO3 fraction constitutes close to 80% of the Aqua Regia extractable
metals. The differences between Aqua Regia and HNO3 extractables are element specific.
0.01 0.1 1 10 100
1
2
3
4
5
6
7
8
9
10
11
12
mg/kg
Sam
ple
Al (%) Cr Fe (%) Cu Zn As Cd Pb
35
Figure 22. Aqua Regia extractable metal and arsenic content. Note the logarithmic scale and refer to
Appendix C for complete data.
Normalization and statistics
Similar patterns among sampling stations are visible for most elements. Andean samples 3
and 10 are generally higher than the other samples whereas the Rio Manu samples 8, 7 and 6
are considerably lower. Cr does not have a clear Andean peak. Cu is decreasing downstream
except for an Andean anomaly. Pb has a weak linear trend with little downstream effect.
0.01 0.1 1 10 100
1
2
3
4
5
6
7
8
9
10
11
12
mg/kg
Sam
ple
Al Cr Fe Cu Zn As Cd Pb
36
Cr (mg/kg)
Fe (%)
Cu
Zn
As
Cd
Pb
Figure 23. Al normalized, Aqua regia extracted element concentrations (mg/kg). Samples ordered with the
highest elevation (3799 m a.s.l.) to the left and the lowest to the right (110 m a.s.l.).
0
20
40
1 3 2 10 4 9 6 7 8 5 12 11
0
10
20
1 3 2 10 4 9 6 7 8 5 12 11
0
50
100
1 3 2 10 4 9 6 7 8 5 12 11
0
200
400
1 3 2 10 4 9 6 7 8 5 12 11
0
100
200
1 3 2 10 4 9 6 7 8 5 12 11
0
0.5
1
1 3 2 10 4 9 6 7 8 5 12 11
0
50
1 3 2 10 4 9 6 7 8 5 12 11
37
Cr (mg/kg)
Fe (%)
Cu (mg/kg)
Zn (mg/kg)
As (mg/kg)
Cd (mg/kg)
Pb (mg/kg)
Figure 24. Al normalized, Aqua regia extracted element concentrations (mg/kg). Samples ordered with the
highest population densities (15.69) to the left and the lowest to the right (0.9).
0
20
40
3 2 1 10 11 12 4 5 6 7 8 9
0
10
20
3 2 1 10 11 12 4 5 6 7 8 9
0
50
100
3 2 1 10 11 12 4 5 6 7 8 9
0
200
400
3 2 1 10 11 12 4 5 6 7 8 9
0
100
200
3 2 1 10 11 12 4 5 6 7 8 9
0
0.5
1
3 2 1 10 11 12 4 5 6 7 8 9
0
50
3 2 1 10 11 12 4 5 6 7 8 9
38
Two element groupings could be observed in the correlation matrix below. The first group
contains Pb, As, Cd and Zn. The second grouping contains Cr, Cu and Al. Fe could best be
placed in group 1 although this element seems related to both groups. The second group has a
weaker relationship than the first (see table 7).
Table 5. Elements and parameters statistics. 2 anomalous LOI samples have been replaced with the
variable mean.
Mean Std. Deviation Data Outliers
Al 16784.44 9086.567 s.11
Cr 23.59167 10.43348 s.4
Fe 36399.64 19443.46 s.3
Cu 26.44833 17.31098 s.4
Zn 78.2025 52.04336 s.10
As 17.18917 26.83757 s.10
Cd 0.168333 0.152901 s.10
Pb 14.9475 8.796153 s.10
LOI 4.86432 3.150748 -
Population 6.06 7.13046 -
Mud 28.69246 32.24506 -
Table 6. Correlation matrix of metal, arsenic and associated parameters.
Al Cr Fe Cu Zn As Cd Pb LOI Pop. Mud
Al 1.00 0.84 0.26 0.61 0.34 -0.08 0.49 0.41 0.58 -0.23 -0.08
Cr 0.84 1.00 0.45 0.83 0.33 -0.05 0.31 0.27 0.39 -0.23 0.19
Fe 0.26 0.45 1.00 0.63 0.73 0.66 0.38 0.65 0.26 0.24 0.18
Cu 0.61 0.83 0.63 1.00 0.51 0.25 0.34 0.39 0.45 0.11 0.14
Zn 0.34 0.33 0.73 0.51 1.00 0.89 0.88 0.96 0.78 0.38 0.46
As -0.08 -0.05 0.66 0.25 0.89 1.00 0.70 0.86 0.58 0.62 0.42
Cd 0.49 0.31 0.38 0.34 0.88 0.70 1.00 0.91 0.94 0.27 0.43
Pb 0.41 0.27 0.65 0.39 0.96 0.86 0.91 1.00 0.82 0.42 0.30
LOI 0.58 0.39 0.26 0.45 0.78 0.58 0.94 0.82 1.00 0.37 0.35
Population -0.23 -0.23 0.24 0.11 0.38 0.62 0.27 0.42 0.37 1.00 0.08
Mud -0.08 0.19 0.18 0.14 0.46 0.42 0.43 0.30 0.35 0.08 1.00
Table 7. Communalities for parameters used in the principal component analysis. The communality
indicates the proportion of the variance explained by the factor structure.
Initial Extraction Initial Extraction
Al 1 0.90775 Cd 1 0.97444
Cr 1 0.93684 Pb 1 0.92569
Fe 1 0.90366 LOI 1 0.91952
Cu 1 0.86212 Population 1 0.5795
Zn 1 0.96495 Mud 1 0.29155
As 1 0.98311
39
Table 8. Tested principal components and statistics.
PC Initial Eigenvalues Extraction Sums of Squared Loadings
Total % of Variance Cumulative % Total % of Variance Cumulative %
1 5.7 52.2 52.2 5.7 52.2 52.2
2 2.4 21.6 73.8 2.4 21.6 73.8
3 1.1 10.3 84.1 1.1 10.3 84.1
4 0.9 8.6 92.7
5 0.6 5.6 98.2
6 0.2 1.4 99.6
7 0.0 0.2 99.8
8 0.0 0.1 99.9
9 0.0 0.1 100.0
10 0.0 0.0 100.0
11 0.0 0.0 100.0
Figure 25. Principal components with eigenvalues >1.
The first principal component contributes with 52.2% of the variance. LOI, Pb, Cd, As, Zn
and Cu are all included as key variables. Population correlations are weak but are highest for
component 1. Component 2 (21.6 % of the variance) derives its properties mainly from Cr
and Al. Also Cu could be included here. Component 3 has a total impact of 10.3 % and is less
well defined than component 1 and 2. Fe shares characteristics with component 1 and 3.
Soil quality guidelines and Enrichment Factors
Loreto and the populated areas of the Andes have the highest P.I. values (Pollution Indexes).
Remote areas of the Andes and the Madre de Dios region are generally low. The variability
within each setting could be as large as a factor 2. The lowest P.I. is found in the Madre de
Dios sample 8. The highest is from the Aguas Calientes (sample 10) of the Cusco region.
Sample 3 and 10 have the highest general Enrichment Factors.
-1.00 -0.50 0.00 0.50 1.00
Al
Cr
Fe
Cu
Zn
As
Cd
Pb
LOI
Pop
Mud
1 2 3
40
Table 9. Enrichment factors for each element and sample. Shaded cells marks EFs >5.
Sample: 1 2 3 4 5 6 7 8 9 10 11 12
Al 3.8 1.4 1.9 4.3 2.0 1.8 3.8 1.0 2.7 2.9 6.4 5.6
Cr 1.4 1.0 1.7 1.6 1.6 1.2 1.1 1.6 2.0 1.3 0.9 1.1
Fe 1.5 1.0 7.7 2.0 2.4 1.9 1.4 3.1 2.9 3.0 1.1 1.3
Cu 2.9 2.2 5.5 4.6 2.5 1.0 1.3 1.0 2.7 3.4 1.5 2.0
Zn 1.0 1.7 5.9 1.6 1.8 1.7 1.3 2.1 1.9 5.8 1.4 1.5
As 1.2 3.1 24.8 1.1 1.0 1.2 1.5 1.0 1.4 21.9 1.2 1.7
Cd 1.0 2.7 3.6 1.3 1.4 1.7 1.9 2.0 1.5 9.0 2.2 2.8
Pb 1.0 1.5 3.9 0.7 1.3 1.5 1.2 2.0 1.0 3.7 1.1 1.2
For Andean samples copper is generally rated as class 3 according to the SEPA system. Zn
has a larger variability among samples. The highest content is in samples 3 and 10 (both rated
class 2). Cadmium and lead is very low in all samples. Chromium is rated class 1 or 2 in all
samples. Arsenic is rated high in samples 3 and 10, otherwise low.
The Madre de Dios samples have very low Cu contents except for sample 4 (moderately
high). Zn is highest in sample 5 but all samples are all rated class 1. Cd and Pb contents are
very low in all samples. Cr is rated moderately high in sample 4 otherwise low. Samples 4
and 9, originating from the Alto Madre de Dios have a higher content of As and heavy metals
than the other Madres de Dios samples (Rio Manu).
The two Loreto samples are moderately high in copper and chromium but low in Arsenic.
All samples are very low in Zn, Cd and Pb compared to SEPA (1999).
Figure 26. Pollution index results. Left: Samples ordered from highest to lowest population. Right:
Samples ordered from highest to lowest altitude.
Canadian sediment quality guidelines
6 samples are over the ISQG (Interim Sediment Quality Guidelines) for As. Samples 3 and 10
have contents over the PEL (Probable effects level). No samples reach the Cd ISQG. Sample
4 is slightly over the ISQG limit for Cr. Cu for sample 1, 4 and 12 are higher than ISQG. No
samples except number 10 are close to ISQG for Pb. Samples 3 and 10 are over the Zn ISQG.
R² = 0.216
00.10.20.30.4
3 2 1 10 11 12 4 5 6 7 8 9
P.I
.
Sample
R² = 0.0179
00.10.20.30.4
1 3 2 10 4 9 6 7 8 5 12 11
P.I
.
Sample
41
Table 10. Canadian Sediment Quality index. ISQG= PEL=Probable effects level (CCME, 1999).
Sample Freshwater,
ISQG
Freshwater,
PEL
1 88 100
2 100 100
3 50 75
4 63 100
5 100 100
6 100 100
7 88 100
8 100 100
9 100 100
10 45 75
11 86 100
12 74 100
Al contents are close to the NOOA (1999) background in samples 2, 6 and 8. Only the two
samples from Loreto have Al contents over the Hyalella azteca (freshwater amphipod used
for sediment toxicity analysis) treshold effects level (TEL). Only sample 8 is close to the As
background. Samples 3 and 10 are well over the Probable effects limit. Sample 10, 11 and 12
are close to the upper limit or over the Cd background. All other samples are low. Samples 2,
6 and 8 are within the background level for Cr. All other samples are higher than the
established background level. Only sample 4 reaches the H. azteca TEL. Samples 1, 4 and 12
are over the Cu threshold effects level. Other samples are considered equal or slightly over the
background level. Only samples 2 and 8 have Fe contents within the background interval.
Samples 3, 10, 11 and 12 have Pb contents over the background. Only sample 10 is close to
the threshold effects level. Four samples (3, 10, 11 and 13) are over the H. azteca TEL. Only
samples 2, 6 and 8 are within the background limits.
Guidelines summary
The SEPA guidelines agrees with NOOA SQuiRT card limits in that Cr, Cu is enriched in
most samples in relation to natural background. NOOA guidelines rate all samples except
sample 8 over As background whereas SEPA rates 5, 6, 8 and 9 class 1. Both methods rates
Pb and Cd low in most samples. NOOA rates Pb and Cd over background in samples 10, 11
and 12 though (and 3 for Pb).
42
Discussion The Andean landscape has more relief than the rain forest of the States of Loreto and Madre
de Dios. The amount of short transported sediment (such as mass movements and surface
runoff) is greater in steep slope areas. This is visible in the samples as a general increase in
roundness, sphericity and quartz contents downstream. Grains from the Andean samples are
less rounded and have less pronounced quartz content than samples originating further
downstream in the Amazon drainage (i.e. Rio Manu and Rio Amazon). The Amazon main
stem sample and Rio Manu share characteristics in that quartz constitutes a larger portion of
the bulk sediment than the other samples. Both samples taken in Loreto are within the Iquitos
forebulge depozone part of the North Amazonian foreland basin. According to REE patterns
Neogene sediments of the area derived from Andean volcanic rocks and cratonic shield rocks
(Roddaz et al., 2005). Tropical rain forest samples (Cusco; Loreto) are significantly more
rounded than the Andes ones. This agrees with surveys by Gibbs (1967) who concludes that
the main portion of the material carried by the Amazon River has an Andean provenance.
The Rio Alto Madre de Dios samples are recognized as a gradual transition between the two
main sedimentary settings described above. The Rio Marañón sediment maturity is visibly
lower and the mineralogy is more diverse than in the Iquitos sample (Rio Amazon). The
resulting cause of this is that the Marañón branch is more proximal to the Andes than the
Ucayali/Urubamba. Areas with high precipitation are generally densely forested and are
protected against erosion (Bridge, 2003). The highly meandering character of Rio Manu and
Rio Madre de Dios are likely to erode previously deposited sediment. Effects hereof are not
considered in this report. Rio Alto Madre de Dios has a more “Andean” signature in mineral
composition and grain shape and are more related to the Cusco area than the Madre de Dios
state samples.
Grain size distribution patterns usually govern the trace metal concentrations. This is the case
in this study too. Other factors also seem to have a large importance as the relationship
between fine material (<0.2µm or <63µm) and metal content are weaker than excepted for
some samples and elements. Natural geological properties and anthropogenic factors govern
the metal and arsenic contents at the scale of this work. Local factors affect the deposition and
transport of various size fractions. Tropical Madre de Dios samples are governed by a
stronger relationship between grain size and element content (correlation R2>0.8 for most
elements). This suggests that the human contribution disturbs the grain size signal in the other
samples. The human impact in the state of Madre de Dios is very limited compared to other
localities. The poor sorting of sediments in the environments sampled indicates that the
energy has been inconsistent. This has promoted dumping rather than washing. The limited
sample quantity affects the possibilities in grain size trend assessments. Considering the
floodplain nature and the grain size distribution in the samples several factors are likely to
affect the investigated samples. These could be flooding intensity, stagnation of water and
erosion. GSD (poor – very poor sorting) gives a clue that river processes is dominating the
river bank environments. Muddy sediments have most likely been transported as suspended
load whereas the coarser fractions have been moved by bedload actions. Each overbank
flooding event generally deposits a unit of mm-dm thickness. (Bridge, 2003) The floodplains
of this study are considered active in this study since they are annually flooded.
The metal contents variability associated with principal component 1 is partly explained by
human population density differences. Al, Cr and Cu are relatively constant throughout the
samples. Sample 2 is comparably low in most metals. This is explained by the very limited
possible impact from anthropogenic sources, as the sample location is a remote Andean lake.
43
The lowest concentrations of sediment metal and Arsenic contents have been used as a
geochemical baseline. Rio Manu samples together with little impacted sites in the Andes
serves as principal background sources. Loreto samples have been excluded due to the vast
geographical distance from the other samples. The deviation from the Al normalized
background content is element specific. The content diversity is largest in the As content. A
factor 20 separates the lowest from the highest Al normalized contents. Cr has the lowest
variability of all analyzed elements. The highest sample concentration is two times the lowest.
All samples have sediment chemistry with naturally low contents of Cu, Cr, Zn compared to
Upper continental crust (Taylor and McLennan, 1985). This suggest that sediment quality
guidelines needs to be local and at least some element classes should be lower than in the
SEPA (1999) or the CCME (1999) in the study areas. It is worth mention that the nature of
the bedload material is heterogeneous because of natural processes such as sorting and
deposition of heavy minerals. The correlation between population density and sediment
element content is positive and strong. Some elements seem related to one another. Cd, As,
Zn and Pb covary with each other in most samples. This is substantiated by the principal
component analysis. Varying Al content appears related to Cu, Zn, Cd and Cr variability. Cr
and Cu variations are closely linked to Al contents (R2>0.8). The Cu-Al relationship is
disturbed by samples 3 and 4, which are believed to be largely anthropogenic in sediment
chemistry character. Zn also has a connection to Al. However three samples (3, 10 and 5)
interfere and lower the total R2. These samples have slightly high metal content that could not
fully be explained by Al-variations alone. As and Cu behave more independent from grain
size and organics than do the other examined metals. A mining induced factor is a plausible
explanation. Arsenic concentrations are higher in more populated areas.
Rio Marañón and Rio Amazon mainstem samples are characterized by high Al and Fe
contents. Al is about 2 times and Fe 1.3 times the geometric mean of all samples. The element
could be released during weathering and transport. It is also possible that the Loreto samples
are too few to exclude local anomalies. The moderately high Fe levels in Loreto are rated
lower in the Al normalization. The Al-normalized content reveals that Cr varies little if
grainsize effects are considered. Each element investigated is related to different properties.
Pb, Cd and Zn covary with organic contents (e.g. LOI). The normalizations to LOI show a
weaker correlation than for the Al and grain size. The organic content of these samples have
been severely enriched by human and/or natural processes. Al and Al normalized Cr
decreases throughout the drainage. The Laguna Huarcarpay sediment (Sample 2) is here used
as natural background. The other elements also have a tendency to increase downstream but
the trend is weaker. Zn, As, Cd and Pb increase from the Laguna Huarcarpay to the Agua
Calientes and then decrease towards the Iquitos site. Cu is the least affected metal during
downstream transport. Clay % has a large impact on the Al content of the sediment. This is
not surprisingly as Al is often used as a grain size proxy. Also Cd is largely governed by the
Clay fraction. Population density has an effect on the two first principal components and thus
has an impact on all analyzed elements. The LOI is governed by the population density. The
other parameters effect on Cr is weak and therefore interpreted as being dominated by natural
geological factors not included in the analysis.
The low Madre de Dios contents are explained by low regional population density and human
presence. The alluvial gold mining activities near the Bolivian border are located downstream
and do not directly affect the sediment at the sample stations. A liable explanation for higher
concentrations in Rio Alto Madre de Dios than in Rio Manu sediment is higher population
density and shorter distance to the principal sediment source. If the less impacted sediments
are compared with the sites at Urcos and Aguas Calientes it is evident that aluminum is not
44
significantly enriched by human activities and are thus useable as a lithophilic element in
normalizations.
The Jarosite occurrence in sample 3 could be indicative of mining activities and AMD.
Jarosite – AMD associations are described in McCubbin and Lang (1999). The quantity
determined by Siroquant is near the detection limit (1.2%) but the EVA peaks are well
defined. Previous workers have concluded that mining derived sediment metal concentrations
are usually not measurable more than a few kilometers downstream (i.e. Lee et al., 2001).
This makes the Loreto samples useful for comparison since there are no mining activities in
the area. Municipal waste treatment (or lack of it) has similar effects as in the Cusco region
and the sediment source is the same (Andes) even though the Cusco landfill is a major point
source. Most element contents of the ICP-MS samples plots well within the 95 % confidence
limits (2). Samples within these boundaries are often explained by a natural geological
variability. Mining induced elevated metal levels would plot well out of the confidence limit.
Samples 3 and 10 stands out with high metal and arsenic contents and are believed to be
mining impacted. The samples stand out with a significantly higher levels of primarily As and
Cd. The levels in these samples are however much lower than samples investigated closer to
mine tailings (described in Méndez, 1999, Lee et al., 2001)
As a developing country, waste management leaves much to be desired. Andean samples 3
and 10 are interpreted as being impacted by diffuse and point human sources. Rio Urubamba
samples are affected by poor waste management in Cusco and the surrounding Sacred Valley.
Samples are considerably higher than the suggested geochemical background. This is
supported by Bolaños and Carranza, (2006) and Allende Ccahuana (2002) who investigated
the pollution sources in the Urubamba area. Samples are comparably high in element
contents if compared with the Pluspetrol (2006) samples. Except the general municipal waste
effect this could be explained by Cu and polymetallic mining activities. Short distances to the
closest mines upstream support this (fig. 7). Also, the sediment element patterns are different
from the Loreto samples. The soluble sulfate mineral jarosite occurrence in sample 3 together
with high metal and As contents than other samples is indicative of a mining impact more
distant from the tailings than is usually recorded in similar studies. Also, both Loreto samples
comparably high metal and arsenic consents. If the ICP-MS data is normalized to Al the
levels are among the studies lowest Cr, Fe, Pb and As. The mentioned four samples are
characterized by high Pb and Cd likely due to use of leaded gasoline (phased out 2005; El
Comercio, 2004). The Loreto samples are potentially affected by diffuse natural and
anthropogenic sources from several thousands of kilometers of headwaters and tributaries.
Uncertainties
It was not possible to process the samples before arrival in Sweden (approximately 4 weeks
after the initial sampling). The sediment samples were not kept in a freezer or fridge during
the field stay. ICP MS sample 5 should be regarded with caution as the rubber seal gave up
during the end of the extraction procedure. Also, spectral interference caused by the HCl Cl-
could affect primarily Cr and As of the Aqua Regia leached samples. LOI samples 1 and 2
contain insufficient material to be righteously compared to the other samples. The two
duplicates do not deviate significantly though. Exceptional results could be explained by a
large local factor in organic content of the samples. This pattern is also apparent in the study
by Aufdenkempe et al. (2007). LOI is hard to use for element-organic content correlations in
Andean samples since the sites at Urcos and Aguas Calientes are clearly organically polluted
by municipal waste. The samples analyzed are sufficient to characterize the overall situation
in the state of Cusco.
45
Conclusions
Populated Andean areas are affected by elevated metal concentrations due to human
activities.
The highest levels of Fe, Zn, Cd, As and Pb documented in this study are found in the
Aguas Calientes and Urcos urban samples.
Madre de Dios ICP-MS samples have no raised levels of arsenic or metals.
The Amazon mainstem sample has elevated metal and arsenic levels from diffuse
sources. Loreto samples are characterized by metal levels higher than could be
explained by natural processes.
No analyzed sediment sample is considered severely impacted or toxic.
Samples 3 and 10 motivate further research in the Cusco region of the Peruvian
Andes. Higher levels of metals and arsenic could be expected locally. Mining
alteration of sediment geochemistry could be seen as a large amplitude but short
distance phenomenon whereas household waste and landfills potentially act as more
diffuse sources with a relatively small impact but geographically extensive.
Further research
The results presented in this study motivate further research to gain a deeper understanding of
the weathering, transport and deposition of trace metals in the complex Amazon watershed. It
could potentially be a massive work with a denser sampling pattern including stratigraphy and
more geochemical samples. To fully understand the principal contaminant patterns a tighter
sampling pattern is necessary. Undisturbed cores could provide more accurate geochemical
background concentrations than the ones suggested in Appendix E. Results from global
geochemical background assessments could prove useful. The XRD analysis should be done
on more samples (ranging from the actual tailing and a few kilometers downstream) to spot
pyrite weathering minerals (i.e. Jarosite and Goethite) closely associated with AMD. The LOI
method used in this study could be excluded in favor of a more accurate method. More
elements (like Li) could be included in the ICP MS analysis. PH measurements could
accompany the geochemical studies to help pointing out severe AMD sites. There could be an
problem in that there are several countries involved. This complicates for national geological
surveys to undertake such a project. Rio Marañón and Rio Ucayali contribute with
approximately equal amounts of water (and sediment) to the Rio Amazon. To gain better
understanding also the Rio Ucayali branch should be covered. Airborne imaging spectroscopy
and other advanced remote sensing techniques have been used successfully on other areas (i.e.
in Kuosmanen, 2003 and Mineo, 2003) and could be an alternative to in situ studies.
46
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50
Appendix A. Sample record and Field observations Table A-1. Summary of the environments at the sample sites.
ID: Location: Locality: Setting: Sediment: Land usage and coverage: Sediment
Color:
r1 13°25.727'S
071°51.766'W
Alt. 3200 m
a.s.l.
Rio Urubamba Valley look out, not
far from the Incan ruins at Pisac.
Southern side of the Rio Urubamba.
Stony, gravelly hill. Frequent
wedge shaped scars and
resulting colluvial deposits in
the area.
Bedrock sample Unimportant due to the elevation and
sample type
N/A
r2 13°29.024'S
071°57.780'W
Alt. 3795 m
a.s.l.
North of Cusco City on the valley
side. West of Rio Urubamba. Near
Puca Pucara ruins (Puka=Quechua
for red fortress)
Road cut Cemented and hard bed
rock sample
Not much. A few grazing cattle N/A
1 13°28.776'S
071°57.965'W
Alt. 3799 m
a.s.l.
Located at the modern Indian
market. Bottom sediment from an
unnamed stream (width=2m during
sampling). Stream is feeding the
Urubamba.
Fresh, rapid water movement.
Mountain stream of limited
size (width=1m). Abundant
biologic matter such as twigs
and leaves is present in and
around the river. Marginal
smell of decomposing organic
matter
Stream sediment taken at
d=0-15 cm. Loads of
organic matter in various
decomposed stages.
Grazing cattle and limited tourist
activities.
5 YR 2/2
2 13°36.925'S
071°43.463'W
Alt. 3090 m
a.s.l.
Half way between Cusco and
Urcos. Laguna Huarcarpay,
downhill from the main road by the
school
Andean wetland lake. Size
approximately 200x200
meters during sampling.
Fine sandy with some finer
contents. Obvious and
large peaty/organic
content.
Lake surrounded by wetlands and
mountains. Limited farming and
grazing. Asphalted and by Andean
standards well trafficated road, 150
m from the lake. Reed and other
typical wetland vegetation occupies
the lake margin.
5 YR 2/2
3 13°41.097'S Rio Vilcanota (Urubamba), at the River, around 50 meters in River beach sediment. Steep valley sides exploited by small 10 YR 5/2
51
071°36.723'W
Alt. 3713 m
a.s.l.
urban border of Urcos city.
Approximately 40 km south east of
Cusco City. Sample taken in the
vicinity of the bridge.
width Sediment taken 5 meters
from the water-land
interface. Decimeter sized
slate pieces and stones and
boulders available in the
river sediments. Sample
mainly sand and coarser.
scale farmers. The river is used for
every household activity imaginable
(i.e. car washing).
R3 13°23.284'S
071°35.626'W
Alt. 3520 m
a.s.l.
200 meters from pre-Columbian
tombs located near Rio Pichihua
approximately 70 km East-north-
east of Cusco.
Arid Andean with shrub and
grass vegetation..
Heavily weathered bed
rock sample. Loose
sediment in the area
mostly fine sand-silt. Silty
flour in conjunction with
bedrock.
Grazing sheep and occasional
donkeys and cattle.
4 12°49.586'S
071°23.334'W
Alt. 488 m a.s.l.
Upper course of Rio Alto Madre de
Dios
Tropical rain forest. Clear
water. Boulder (=0,3-0,6
m) accumulation in the river –
bank transition.
A stone removed from
sample because of weight.
6*5*2 cm sub angular
disc. Otherwise sandy with
a minor gravel content.
Primary rain forest. Absence of local
human impact.
5 Y 3/2
5 12°16.268'S
070°53.271'W
Alt. 303 m a.s.l.
Downstream Boca Manu, Rio
Madre de Dios
Tropical rain forest. River
width roughly 60 m.
Muddy Beach sediment. Small river boat dock for 2-3
motorized canoes surrounded by
primary rain forest. Population of
Bocca Manu approximated to a few
hundred. Last outpost of civilization.
5 Y 5/2
6 12°02.288'S
071°11.473'W
Alt. 317 m a.s.l.
Rio Manu Tropical rain forest. Less see
through water ability than in
Rio Alto Madre de Dios.
Stones (=0,1m) common in
the river sediment.
Sampling done in
conjunction with a
200x40m river beach. Fine
sand + finer.
Primary rain forest. Absence of local
human impact. Nearest village is
Boca Manu some 40km downstream.
Strictly regulated and limited boat
traffic.
5 YR 4/4
7 12° 00.230'S
071°13.459'W
Alt. 307 m a.s.l.
Rio Manu Tropical rain forest Beaches are common
during dry period. The
river sand is chocolate
colored.
River bank sand deposits
8 km upstream S.9. Primary rain
forest. Absence of local human
impact.
5 YR 4/2
52
>10 m thick. The surface
sand is darker than a few
centimeters down. Beaches
are made up by fine to
coarse sands.
8 12°00.260'S
071°14.071'W
Alt. 306 m a.s.l.
Rio Manu Tropical rain forest. River beach. Poorly sorted
Gravelly sand.
1 km upstream sample 7. Primary
rain forest. Absence of local human
impact.
10 YR 3/2
9 12°25.203'S
071°05.471'W
Alt. 321 m
a.s.l.
Rio Alto Madre de Dios Tropical rain forest. Fine silt accompanied with
gravel and stone bars in
the central channel. Water
relatively clear. 0,3-0,4
meter depth of sight. River
bank loose deposits >7 m
thick.
Primary rain forest. Absence of local
human impact.
10 YR 3/2
10 13°09.264'S
072°31.470'W
Alt. Approx.
2060 m a.s.l.
Rio Urubamba. Downstream Aguas
Calientes 200-300 m west of the
train station (i.e. city border).
Andean tributary. Very poorly sorted
sediment. Grains ranging
from =0,2-10m.
Sample taken in a calm
muddy area of the section.
Building debris (bricks)
have filled up one of the
river sides. Sediment is
dark Cafe latte colored on
the surface, changing
abrupt to almost black at
d>1cm. Smell is descent.
River clearly impacted by waste
resulting from Aguas Calientes.
10YR 4/2
11 3°71.758'S
073°22.421'W
Alt. 110
M a.s.l.
Rio Amazon, Iquitos urban border Urban impact secondary rain
forest.
Previously flooded area.
Large grass covered areas
surrounds the sampling
site. Waste in the form of
plastic bottles and general
household waste occupy
Except for the urban centre of Iquitos
both river banks are cultivated.
10 YR 3/2
53
the river banks. Mainly
sand/silt.
12 4°48.319'S
073°43.301'W
113 M a.s.l.
Piranha lodge. Rio Marañón, 180
km upstream Iquitos only a few
kilometers from the Ucayali-
Marañón joint at the rim of the
Pacaya Samiria National Reserve.
Primary and secondary Rain
forest
River banks shows no sign
of human activities. Rice
plantations a few
kilometers away on the
opposite side. Gravelly
sand.
Rice plantations within 100m from
the river channel.
10 YR 3/2
54
Appendix B. Grain size distribution and statistics
Sample: 1
Sample type: Trimodal,
Very Poorly
Sorted
Textural group: Muddy Sand
Sediment name: Very Coarse
Silty Very
Coarse Sand
MEAN, )(x 521.0
SORTING, σ 5.048
SKEWNESS, Sk -1.226
KURTOSIS, K 2.789
Clay (%) 4
Total fines (<63
µm)
15.6
Sample: 2
Sample type: Bimodal,
Moderately
Sorted
Textural group: Sand
Sediment name: Moderately
Sorted Fine
Sand
MEAN, )(x 183.7
SORTING, σ 1.702
SKEWNESS, Sk 0.029
KURTOSIS, K 0.770
Clay (%) 1.4
Total fines (<63
µm)
3.7
Sample: 3
Sample type: Unimodal,
Moderately
Sorted
Textural group: Sand
Sediment name: Moderately
Sorted
Medium
Sand
MEAN, )(x 396.0
SORTING, σ 1.987
SKEWNESS, Sk -0.134
KURTOSIS, K 1.993
Clay (%) 1.6
Total fines (<63
µm)
5.3
Sample: 4
Sample type: Polymodal,
Very Poorly
Sorted
Textural group: Sandy Mud
Sample: 5
Sample type: Polymodal,
Very
Poorly
Sorted
Sample: 6
Sample type: Bimodal,
Very Poorly
Sorted
Textural group: Muddy sand
0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
55
Sediment name: Fine Sandy
Coarse Silt
MEAN, )(x 11.64
SORTING, σ 7.433
SKEWNESS, Sk 0.002
KURTOSIS, K 0.978
Clay (%) 19.6
Total fines (<63
µm)
80.1
Textural group: Sandy mud
Sediment name: Very Fine
Sandy
Very
Coarse Silt
MEAN, )(x 11.81
SORTING, σ 7.248
SKEWNESS, Sk -0.280
KURTOSIS, K 0.808
Clay (%) 20.9
Total fines (<63
µm %)
76.5
Sediment name: Coarse Silty
Medium
Sand
MEAN, )(x 72.07
SORTING, σ 6.966
SKEWNESS, Sk -0.611
KURTOSIS, K 0.885
Clay (%) 7.1
Total fines (<63
µm)
36
Sample 7 N/A
Sample: 8
Sample type: Polymodal,
Very Poorly
Sorted
Textural group: Muddy sand
Sediment name: Muddy Very
Coarse Sand
MEAN, )(x 108.4
SORTING, σ 15.18
SKEWNESS, Sk -0.570
KURTOSIS, K 0.606
Clay (%) 13.1
Total fines (<63
µm)
39.2
Sample: 9
Sample type: Trimodal,
Very Poorly
Sorted
Textural group: Mud
Sediment name: Coarse Silt
MEAN, )(x 5.511
SORTING, σ 5.586
SKEWNESS, Sk -0.228
KURTOSIS, K 0.839
Clay (%) 27.2
Total fines (<63
µm)
95.3
0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
56
Sample: 10
Sample type: Unimodal,
Poorly Sorted
Textural
group:
Mud
Sediment
name:
Fine silt
MEAN, )(x 3.471
SORTING, σ 3.734
SKEWNESS,
Sk
-0.201
KURTOSIS,
K
1.055
Clay (%) 27.9
Total fines
(<63 µm)
99.4
Sample: 11
Sample type: Trimodal,
Very Poorly
Sorted
Textural group: Sandy Mud
Sediment name: Fine Sandy
Coarse Silt
MEAN, )(x 20.04
SORTING, σ 7.395
SKEWNESS, Sk -0.030
KURTOSIS, K 0.776
Clay (%) 12.7
Total fines (<63
µm)
66.8
Sample: 12
Sample type: Bimodal, Very
Poorly Sorted
Textural
group:
Muddy sand
Sediment
name:
Very Coarse
Silty Very
Coarse Sand
MEAN, )(x 328.0
SORTING, σ 4.740
SKEWNESS,
Sk
-0.250
KURTOSIS,
K
0.911
Clay (%) 3.4
Total fines
(<63 µm)
11.9
0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
0%
20%
40%
60%
80%
100%
57
Appendix C. ICP-MS results Table C-1. Metals leachable by 1M HNO3 (mg/kg).
Sample Al Cr Fe Cu Zn As Cd Pb
1 15311 21.19 13378 34.27 48.42 6.157 0.0988 9.942
2 5785 7.78 6604 10.34 33.77 6.240 0.0756 6.341
3 7097 11.19 38129 30.89 200.78 32.824 0.1240 13.149
4 18662 31.89 38512 66.31 77.52 6.577 0.1163 9.802
5 8958 16.56 22176 16.20 154.35 4.606 0.0728 7.507
6 6011 9.99 13322 5.88 30.68 3.639 0.0484 6.714
7 13065 18.35 24277 16.54 56.88 5.692 0.1250 12.853
8 3908 6.85 9180 3.25 26.68 2.470 0.0324 4.783
9 11287 20.27 28342 22.42 51.90 5.005 0.0582 7.907
10 9703 13.17 29003 24.88 165.24 68.378 0.4087 21.286
11 24424 27.83 35213 33.68 109.47 9.136 0.3125 21.036
12 19997 26.16 33973 34.12 96.88 12.243 0.2688 18.517
Table C-2. Metals leachable by Aqua Regia (3:1 HNO3:HCl) (mg/kg).
Sample Al. % Cr Fe. % Cu Zn As Cd Pb
1 2.017 31.15 3.0902 36.37 45.68 5.896 0.0804 12.499
2 0.732 7.86 0.7690 10.22 27.86 5.629 0.0798 6.791
3 1.031 18.90 8.3063 35.48 137.10 63.330 0.1479 24.423
4 2.318 39.65 4.7771 65.67 85.70 6.219 0.1229 10.503
5 1.087 19.20 2.7335 16.84 45.55 2.720 0.0615 8.817
6 0.953 12.65 1.9305 6.06 36.80 2.768 0.0640 8.547
7 2.056 24.47 3.0327 17.14 61.55 7.401 0.1549 14.814
8 0.535 8.96 1.7357 3.33 24.94 1.327 0.0426 6.345
9 1.434 30.96 4.3230 24.39 62.85 4.815 0.0864 8.683
10 1.542 22.01 4.8066 32.31 201.03 83.678 0.5526 34.592
11 3.451 33.38 4.0363 32.79 110.02 10.030 0.2973 22.215
12 2.980 33.91 4.1387 36.78 99.35 12.436 0.3378 21.150
Table C-3. ICP-MS statistics for the Andean samples.
Andean Samples.
n=4
g/kg Al Cr Fe Cu Zn As Cd Pb
Mean 9473.96 13.33 21778.79 25.09 112.05 28.40 0.18 12.68
S.D 4218.10 5.69 14380.14 10.58 83.42 29.46 0.16 6.38
Min 5785.20 7.78 6604.42 10.34 33.77 6.16 0.08 6.34
Max 15310.62 21.19 38129.48 34.27 200.78 68.38 0.41 21.29
Table C-4. ICP-MS statistics for the Madre de Dios state samples.
Madre de Dios samples. n=6
g/kg Al Cr Fe Cu Zn As Cd Pb
Mean 10315.20 17.32 22634.81 21.77 66.34 4.66 0.08 8.26
S.D 5283.60 8.78 10538.73 22.97 46.93 1.46 0.04 2.78
Min 3908.34 6.85 9179.67 3.25 26.68 2.47 0.03 4.78
Max 18661.79 31.89 38511.63 66.31 154.35 6.58 0.12 12.85
Table C-5. ICP-MS statistics for the Loreto state samples.
Loreto samples. n=2
g/kg Al Cr Fe Cu Zn As Cd Pb
58
Mean 22210.23 26.99 34593.22 33.90 103.18 10.69 0.29 19.78
S.D 3130.23 1.18 876.93 0.31 8.90 2.20 0.03 1.78
Min 19996.83 26.16 33973.14 33.68 96.88 9.14 0.27 18.52
Max 24423.64 27.83 35213.30 34.12 109.47 12.24 0.31 21.04
Table C-6. ICP-MS statistics for all samples in this study.
All samples. n=12
g/kg Al Cr Fe Cu Zn As Cd Pb
Mean 16784.44 23.59 36399.64 26.45 78.20 17.19 0.17 14.95
S.D 3130.23 1.18 876.93 0.31 8.90 2.20 0.03 1.78
Min 19996.83 26.16 33973.14 33.68 96.88 9.14 0.27 18.52
Max 24423.64 27.83 35213.30 34.12 109.47 12.24 0.31 21.04
Figure C-1. Geometric mean and spread (%) of elements analyzed.
1
100
10000
Al Cr Fe Cu Zn As Cd Pb
Min
Max
Geometric mean
59
Appendix D. Normalized metal content Table D-1. Element contents normalized to Al.
Al Cr Fe Cu Zn As Cd Pb
1 1.68 25.91 2.57 30.26 38.00 4.90 0.07 10.40
2 1.68 18.02 1.76 23.42 63.86 12.90 0.18 15.56
3 1.68 30.77 13.52 57.75 223.17 103.09 0.24 39.76
4 1.68 28.70 3.46 47.55 62.05 4.50 0.09 7.60
5 1.68 29.62 4.22 25.99 70.28 4.20 0.09 13.60
6 1.68 22.28 3.40 10.67 64.80 4.88 0.11 15.05
7 1.68 19.97 2.48 13.99 50.24 6.04 0.13 12.09
8 1.68 28.09 5.44 10.43 78.20 4.16 0.13 19.89
9 1.68 36.23 5.06 28.54 73.54 5.63 0.10 10.16
10 1.68 23.95 5.23 35.16 218.73 91.05 0.60 37.64
11 1.68 16.23 1.96 15.94 53.50 4.88 0.14 10.80
12 1.68 19.09 2.33 20.71 55.94 7.00 0.19 11.91
Table D-2. Element contents normalized to LOI.
Al Cr Fe Cu Zn As Cd Pb
1 0.82 12.62 1.25 14.74 18.51 2.39 0.03 5.06
2 0.30 3.23 0.32 4.19 11.44 2.31 0.03 2.79
3 5.64 103.34 45.41 193.96 749.55 346.24 0.81 133.53
4 3.66 62.56 7.54 103.62 135.23 9.81 0.19 16.57
5 8.04 141.84 20.20 124.45 336.59 20.10 0.45 65.15
6 11.26 149.52 22.82 71.62 434.87 32.72 0.76 101.02
7 3.71 44.10 5.47 30.90 110.94 13.34 0.28 26.70
8 17.17 287.43 55.67 106.73 800.09 42.56 1.37 203.51
9 7.92 171.00 23.87 134.67 347.07 26.59 0.48 47.95
10 1.55 22.12 4.83 32.47 202.02 84.09 0.56 34.76
11 2.34 22.66 2.74 22.25 74.68 6.81 0.20 15.08
12 2.44 27.74 3.39 30.10 81.28 10.17 0.28 17.30
Table D-3. Element contents normalized to Clay%.
Al Cr Fe Cu Zn As Cd Pb
1 4.12 63.68 6.32 74.36 93.39 12.05 0.16 25.55
2 6.49 69.66 6.81 90.51 246.82 49.87 0.71 60.16
3 6.03 110.48 48.55 207.36 801.34 370.17 0.86 142.75
4 1.91 32.67 3.94 54.11 70.62 5.12 0.10 8.65
5 0.57 10.04 1.43 8.80 23.81 1.42 0.03 4.61
6 2.12 28.20 4.30 13.51 82.02 6.17 0.14 19.05
7 2.30 27.35 3.39 19.16 68.80 8.27 0.17 16.56
8 0.49 8.14 1.58 3.02 22.66 1.21 0.04 5.76
9 0.59 12.67 1.77 9.98 25.72 1.97 0.04 3.55
10 0.72 10.21 2.23 14.99 93.24 38.81 0.26 16.04
11 4.45 43.04 5.20 42.27 141.87 12.93 0.38 28.64
12 10.59 120.50 14.71 130.73 353.07 44.20 1.20 75.17
60
Table D-4. Element contents normalized to % material <63µm.
Al Cr Fe Cu Zn As Cd Pb
1 6.26 96.67 9.59 112.88 141.76 18.30 0.25 38.79
2 9.25 99.33 9.71 129.07 351.95 71.11 1.01 85.79
3 9.15 167.70 73.70 314.77 1216.41 561.90 1.31 216.69
4 1.36 23.27 2.80 38.54 50.30 3.65 0.07 6.16
5 0.68 12.01 1.71 10.54 28.50 1.70 0.04 5.52
6 1.24 16.49 2.52 7.90 47.96 3.61 0.08 11.14
7 2.76 32.89 4.08 23.05 82.75 9.95 0.21 19.92
8 0.62 10.44 2.02 3.88 29.06 1.55 0.05 7.39
9 0.71 15.28 2.13 12.03 31.01 2.38 0.04 4.28
10 0.73 10.42 2.27 15.29 95.13 39.60 0.26 16.37
11 2.43 23.48 2.84 23.07 77.40 7.06 0.21 15.63
12 11.80 134.26 16.39 145.65 393.38 49.24 1.34 83.75
Table D-5. Element contents normalized to population density.
Al Cr Fe Cu Zn As Cd Pb
1 0.89 13.81 1.37 16.12 20.25 2.61 0.04 5.54
2 0.32 3.49 0.34 4.53 12.35 2.50 0.04 3.01
3 0.38 6.98 3.07 13.11 50.65 23.40 0.05 9.02
4 51.39 878.82 105.89 1455.71 1899.71 137.85 2.73 232.81
5 24.11 425.51 60.59 373.34 1009.72 60.29 1.36 195.45
6 21.13 280.42 42.79 134.33 815.63 61.36 1.42 189.46
7 45.58 542.34 67.22 380.01 1364.36 164.05 3.43 328.38
8 11.87 198.64 38.47 73.76 552.93 29.41 0.95 140.64
9 31.80 686.38 95.83 540.58 1393.14 106.74 1.92 192.48
10 0.57 8.13 1.78 11.94 74.27 30.91 0.20 12.78
11 3.83 36.99 4.47 36.34 121.94 11.12 0.33 24.62
12 3.30 37.58 4.59 40.77 110.11 13.78 0.37 23.44
61
Appendix E. Geochemical background assessment results
Table E-1. Normalized metal and As concentrations
Al
normalized
Background
Derived
from
sample
Al. % 0.54 8
Cr. mg/kg 18.02 2
Fe. % 1.76 2
Cu. mg/kg 10.43 8
Zn. mg/kg 38.00 1
As. mg/kg 4.16 8
Cd . mg/kg 0.07 1
Pb . mg/kg 7.60 9
62
Appendix F. XRD results
Figure F-1. Sample 3, XRD pattern of the fine sand fraction
Figure F-2. Sample 4, XRD pattern of the fine sand fraction
Figure F-3. Sample 7, XRD pattern of the fine sand fraction
FigureF-4. Sample 12, XRD pattern of the fine sand fraction
63
Appendix G. LOI results Table G-1. Loss on ignition results
Series 1 Series 2 Series 1 Series 2 Mean Mean
Sam
ple
Loss on
550°C, 2h,
Corrected
Loss on
550°C, 2h,
Corrected
Loss on
950°C, 2h,
Corrected
Loss on
950°C, 2h,
Corrected
Loss on
550°C, 2h,
Corrected
Loss on
950°C, 2h,
Corrected
1 27.09 18.69 11.47 12.03 22.89 11.75
2 68.44 56.00 0.00 0.00 62.22 0.00
3 3.33 3.31 10.46 10.96 3.32 10.71
4 4.93 5.29 14.57 4.99 5.11 9.78
5 2.67 1.99 14.68 16.02 2.33 15.35
6 1.24 2.08 15.38 13.98 1.66 14.68
7 5.14 4.96 8.40 9.62 5.05 9.01
8 1.04 1.14 4.98 4.92 1.09 4.95
9 2.68 2.04 5.83 6.35 2.36 6.09
1
0 11.17
12.97
14.74
13.24 12.07 13.99
1
1 7.88
8.08
15.49
13.89 7.98 14.69
1
2 8.10
7.24
33.62
31.44 7.67 32.53
Appendix H. Population densities in study areas Table H-1. Population densities of sampled areas (INEI, 2000)
Sample Population density
1 100
2 100
3 120
4 2
5 2
6 2
7 2
8 2
9 2
10 120
11 40
12 40
64
Appendix I. Sediment and Soil quality guidelines
Table I-1. Environmental quality guideline values (mg/kg) for sediment contamination. N/A = Not
available (Modified from SEPA, 1999).
Class Contents Cu Zn Cd Pb Cr As Fe Al
1 Very low <15 <150 <0.8 <50 <10 <5 N/A N/A
2 Low 15-25 150-300 0.8-2 50-150 10-20 5-10 N/A N/A
3 Moderately high 25-100 300-1000 2-7 150-400 20-100 10-30 N/A N/A
4 High 100-500 1000-5000 7-35 400-2000 100-500 30-150 N/A N/A
5 Very high >500 >5000 >35 >2000 >500 >150 N/A N/A
Table I-2. Canadian Soil Quality Guidelines (mg/kg) for Protection of Environmental and Human Health
(CCME, 1999).
Land Use Cu Zn Cd Pb Cr As Fe Al
Agricultural 63 200 1.4 70 64 12 N/A N/A
Residential 63 200 10 140 64 12 N/A N/A
Industrial/
Commercial
91 360 22 600 87 12 N/A N/A
Table I-3. Concentrations in g/kg (recalculated from NOOA, 1999).
Class Al As Cd Cr Cu Fe Pb
Background 0.26% 1.1 0.100-
0.300
7.000-
13.000
10.000-
25.000
0.99-
1.88%
4.0-17.0
Lowest ARCS
H. Azteca
TEL
2.55% 10.798 0.583 36.286 28.012 18.84% 37.0
Threshold
effects level.
TEL
N/A 5.900 0.596 37.300 35.700 N/A 35.0
Probable
effects level.
PEL
N/A 17.000 3.530 90.000 19.700 N/A 91.3
Upper effects
threshold.
UET
N/A 17.000 3.000 95.00 86.000 4% 127.0
Appendix J. List of Acronyms and words AMD – Acid mine drainage
Cochas – Oxbow lake (Spanish)
GSD – Grain size distribution
INGEMMET - Instituto Geológico Minero y Metalúrgico
LOI - Loss on ignition
M a.s.l. – Meters above sea level.
MCE – Multi Criteria Evaluation
MEM – Peruvian Ministry of Energy and Mining
PEL – Probable effects level
Ppt – parts per thousand
REE – Rare earth elements
Skarn - Old Swedish term for silicate gangue also including rock composed of calcium or
magnesium-bearing silicates derived from contact metamorphic and metasomatic processes.
UCC – Upper Continental Crust (Taylor and McLennan, 1985)
65
Appendix K. Epilogue Arrival in Lima was one day after the 8.0 magnitude magnitude earthquake that struck outside
the coast of Ica approximately 100 km south of Lima the 15th
of August 2007. This caused for
some rescheduling of plans. Other than this most went smoother than expected. Well, a few
incidents during the route were inevitable. One lost cell phone (including my music), a few
hundred mosquito bites (with resulting fever) and a minor landslide blocking the road while
crossing the Andes in off-road equipped bus. Another close call was in the Pacaya-Samiria
reserve (Loreto region) where a Fer-de-Lance snake tried its best. But some machete work
from the guide made me and my 2 companion travelers safe.
The biggest issue in working or travelling in Peru was my lack of Spanish. Another problem
is their poor English (or Swedish for that matter). You could have a hard time explaining that
you need a permit for bringing soil samples back to Sweden. The government officials at
Jorge Javez international airport had an interesting time as they guessed what my sediment
samples were. Among their guesses were orchids, insects, bromelias and only god knows
what else.
A tight budget made using high tech gadgets during sampling impossible. As a substitute for
large and heavy equipment creativity had to been used. Public busses are an excellent way of
transport where available. There are no regular stops and the driver lets you off wherever you
like. Also, motorized canoes, although expensive were used to get to the localities.
The reference site in the Nauta-Iquitos area had to be reached by plane since no roads could
take you there and going by boat would have ruined my time schedule.
All in all I am very satisfied with the expedition which got me to know people from around
the globe. It is also satisfying to see that the skills received at University of Gothenburg were
useable on such a different location than Sweden.
I wish to thank the following people, in no particular order. Ylva Ståhl, Sven Ardung and
Micke Persson for nice chitchat in the lab. My advisor, Professor Rodney Stevens for advice
and guidance. Nicasio Miranda for helping getting me around in the Cusco region. Andy and
his crew in the Manu area and excellent guidance from Mr. Israel in the Pacaya Samiria
reserve. And, thank you Anna.
Martin Persson, January 2008
Appendix L. Additional images cd-rom Run
Browse
F:\ (or your DVD/CD player of choice)
66
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