a model for cost‐benefit analysis of cooking fuel...

Aerosol and Air Quality Research Lab (AAQRL)

A model for cost‐benefit analysis of cooking fuel alternatives

Sameer Patel, Anish Khandelwal, Anna Leavey and Pratim Biswas

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Aerosol & Air Quality Research Laboratory (AAQRL)Department of Energy, Environmental & Chemical Engineering

Washington University in St. LouisSt. Louis MO 63130

ETHOS 2016Northwest University, Seattle WA


Solid Fuel Combustion: Issues• Product of incomplete combustion (PICs) from solid fuel combustion in

cookstoves have adverse impact on both health and environment

• On a global scale, biomass burning is estimated to contribute up to 90 % of the combustion generated primary particulate organic carbon (OC) (Bond et al. 2008)

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Two Possible Solutions

1) Introduce better technology for more efficient combustion of solid fuels

2) Transition from solid fuels to cleaner fuel alternatives

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However both solutions generate a range of technological and policy challenges


Technology Based Studies in AAQRL

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Lab Studies: • Understanding particle formation during controlled biomass pyrolysis in a flat flame reactor

(Fang et al. Fuel 116, 350-357 (2014))• Chemical and physical characterization of PM and understanding effects of cookstove design

and operating principle (Patel et al. Energy for Sus. Dev., in review)• Simulation of particle formation using an integrated combustion and particle growth dynamic

model compatible with different type fuel and cookstove designs (Patel et al. in preparation)

• Developing, assessing and comparing new instrumentation for air quality monitoring (Leavey et al. AS&T 47, 966-978 (2013) and Wang et al. AS&T 49, 1063-1077 (2015))

Field Studies:• Introducing real-time instrumentation in the field and development of emissions indices (Sahu

et al. ES&T 45, 2428-2434 (2011))• Comparing traditional and improved cookstoves with uncontrolled cooking test (UCT) (Leavey

et al. ES&T, 49, 7423−7431 (2015)) • An ongoing two year long intervention field study in India to assess the efficacy of improved

cookstove in reducing health risks in collaboration with Brown School of Social work and Medical School at WUSTL


Why Focus on Fuel Transitioning

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• Improved cookstoves, though better than traditional stoves, still generate high levels of pollutants

• It is extremely difficult to burn biomass cleanly enough to meet guidelines to protect health (K. R. Smith, Science 345, 603 (2014))

• Cleaner fuel alternatives should be seen as the ultimate goal

• Brazil and Indonesia undertook such fuel transitioning projects which can serve as an example (Coelho et al. Energy Policy, 2013, Budya et al. Energy Policy, 2011)


Factors Governing Fuel Transitioning

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• A household’s fuel selection process must be understood before targeting any fuel transitioning

• A household’s fuel preference is an intricate function of multiple factors, such as cost, fuel availability and ease of use. These factors contribute to an overall cost and benefit that is associated with different fuel alternatives

• Modelling a household's decision-making process is critical to gain better insight into how important different factors are perceived, and how they affect a household’s fuel preference

• Such models can be exploited as a powerful tool by policymakers


Cost-Benefit Analysis Model

7Patel et al., Renewable and Sustainable Energy Reviews 56 (2016) 291–302


Cost-Benefit Analysis Model

8Patel et al., Renewable and Sustainable Energy Reviews 56 (2016) 291–302


Quantification of Different Factors Governing Fuel Preference

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• Analytical Hierarchy Process (AHP) was used to quantify all constituent factors of cost and benefit associated with different fuel alternatives

• AHP provides a comprehensive and rational framework for structuring a decision making problem (Saaty, European Journal of Operational Research 48, 9-26 (1990))

• Based pairwise comparison, AHP assigns weights to the alternatives on a common scale

Aerosol and Air Quality Research Lab (AAQRL)B

enef

it-to

-Cos

t Rat

io

0.0

0.5

1.0

1.5

2.0

Biomass

BiogasDung

Charcoal

LPG

Kerose

ne

Electri

city

% o

f Hou

seho

lds

0

5

10

70

75 74.8

0.4 0.10.7

11.4

0.8

10.9

Results: Model Validation

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• This CBA model cannot predict the fraction of households using a particular kind of fuel but ranks them in the order of a household’s preference

• The CBA model predicted the current cooking fuel usage pattern in rural India

Model results

Current fuel usage pattern in rural India

1.3


Biomass Dung Charcoal

Ben

efit

to C

ost R

atio

0.0

0.5

1.0

1.5

2.0

2.5

Traditional cookstoveICS w/o subsidy ICS with subsidy

Why Improved Cookstoves Suffer Low Retention Rate

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• A significant fraction of improved cookstove (ICS) dissemination initiatives fail to ensure continued use of the cookstoves (Urmee et al. Renewable and Sustainable Energy Reviews 33, 625-635 (2014))

• The CBA model explained the low retention of ICS

Patel et al., Renewable and Sustainable Energy Reviews 56 (2016) 291–302


Biomass

DungLPG

Ben

efit

to C

ost R

atio

0.0

0.5

1.0

1.5

2.0

2.5Base case30% subsidy on LPG 60% subsidy on LPG

Biomass

DungLPG

Electri

city

Ben

efit-

to-C

ost R

atio

0.0

0.5

1.0

1.5

2.0Base CaseBiomass & LPG equally accessibleBiomass & Electricity equally accessible

What Would it Take for Fuel Transitioning

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• Just subsidizing LPG alone cannot replace biomass as the most preferred fuel• The rural rich are still energy poor due to the lack of a reliable supply of cleaner fuel

alternatives Patel et al., Renewable and Sustainable Energy Reviews 56 (2016) 291–302


A CBA Model to Understand a Household’s Fuel Preference

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Conclusions

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• A novel approach to model a household’s decision-making process for cooking fuel selection was demonstrated

• A lack of robust user-friendly cookstoves and after-sales services were found to be critical reasons for low retention rates of ICS in rural India

• Subsidies alone cannot lead to LPG adoption in rural India which explains why the rural rich is still energy poor

• This model could be easily translated to both the rural and urban populations of other countries with only minor modifications to suit the demographics, geography, market conditions and policies of that country


Acknowledgements

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MAGEEP

Thank You!!

[email protected]@wustl.edu

a model for cost‐benefit analysis of cooking fuel...

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