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Assessing Factors Responsible for Differences in Household Energy Access Across Brazil, India, Uganda

Assessing Factors Responsible for Differences in Household Energy Access Across Brazil, India, Uganda. Yu Nagai Regina Fuchs Shonali Pachauri International Institute of Applied Systems Analysis. Basic Information. Source: WDI, UNDP, WHO. Residential Sector.

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Assessing Factors Responsible for Differences in Household Energy Access Across Brazil, India, Uganda

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  1. Assessing Factors Responsible for Differences in Household Energy Access Across Brazil, India, Uganda

    Yu Nagai Regina Fuchs ShonaliPachauri International Institute of Applied Systems Analysis
  2. Basic Information Source: WDI, UNDP, WHO
  3. Residential Sector Final energy use in the residential sector in 2005: Brazil – 24.6%, 1400 TJ, 4909 MJ/cap-yr India – 78.8%, 6570 TJ, 5991 MJ/cap-yr Uganda – 70.4%, 214 TJ, 5246 MJ/cap-yr Source: IEA Energy Balances, Uganda Energy Balance
  4. Final vs. Useful Energy Figure: Example final and useful cooking energy of south Asia Efficiencies used:- Biomass: 15% - Other Solids: 15%- Kerosene: 40% - LPG: 60% - Electricity: 75%
  5. Lack of access to modern energy Low quality lighting Difficulty in reading at night Negative health impacts WHO estimates nearly 1.5 million are killed yearly from incomplete combustion. Time consumption to collect firewood Less time spend on more productive work or education Gender inequality Emissions GHG’s and black carbon from incomplete combustion
  6. Main questions How do energy poverty, access and equity in every access and use differ between and across countries? What are the underlying factors causing the heterogeneity in the consumption pattern? How can we design policies that will lead to energy poverty reduction?
  7. Heterogeneity in energy use Aggregated data can show the overall problem, but different groups faces different severity of problems Physical and financial constraints Lack of distribution line, pipeline connection, or roads Affordability of modern fuels Other demographic and social, cultural differences Not understanding harmful effects of using biomass
  8. Education Level Source: IIASA POP Group
  9. Expenditure Comparison Energy expenditure makes up less than 10% of total Electricity increases as kerosene decreases Biomass share decrease with higher education Source: Brazil POF 2002/03, India NSSO 2004/05 and Uganda UNHS3 2005/06
  10. Income difference Brazil Gini coefficient: 58 (2003) India Gini coefficient: 37 (2005) Uganda Gini coefficient: 44 (2005) Source: WDI
  11. Energy Use (Brazil) Source: Brazil POF 2002/03
  12. Energy Use (India) Source: India NSSO 2004/05
  13. Energy Use (Uganda) Source: Uganda UNHS3 2005/06
  14. Conclusions Energy use pattern correlates highly with education and income. Education and income are highly correlated. From the current analysis, a clear independent effect could not be observed. Future work Separating groups by infrastructure availability Energy use pattern within a same education group Analysingdata sets by generation
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