Characterizing Kerosene Demand for Lighting India and Evaluating the Impact of Measures Affecting Access and Dependence

Characterizing Kerosene Demand for Light in India and Evaluating the Impact of Measures Affecting Access and Dependence

Presenter: Nicholas L. Lam, ( University of California, Berkeley,USA)

Rapporteurs: Jonathan Lee andCarmen Iten

Overview

A national expenditure survey of India was analyzed to characterize demand for kerosene used for residential lighting. Results were use to model demand within MESSAGE-Access. Five scenarios were developed to explore the impact of policies that could alter fuel access (e.g. fuel subsidies) and dependence (e.g. electricity reliability), and the associated impacts on fuel demand, pollutant emissions, air quality, and health estimated. Approximately 65-70% of kerosene consumed in the residential sector in 2005-6 was used for lighting (4700Gg). Over half (65%) was used by homes with an electricity connection, but unreliable supply. Estimated kerosene demand curves are highly elastic across population groups, and thus highly sensitive to fuel price (e.g. subsidy phase-out). Even under optimistic electrification scenarios, dependence on fuel-based lighting will likely continue without efforts to improve supply reliability. Considering both primary and backup kerosene users increases current BC emission estimates from the residential sector in India by 30- 40%, but has only modest impacts on outdoor PM2.5 concentrations. Estimates of health impacts from outdoor air quality and household-level exposures are forthcoming. Results thus far emphasize the importance of electricity reliability in driving fuel demand for light and, likely, associated burdens. With efforts to reduce fossil fuel subsidies, mechanisms for providing affordable lighting, not dependent on centralized grid expansion, will be needed.

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Main Issues Discussed

 Important to think about holistic household energy. Interactions between light, cooking, heat, etc. are important
 Kerosene for lighting is an important source of climate warming “black carbon”
 A national survey informed a demand model, outputs and gains evaluated, feed back into demand
 Demand curves developed for different groups
 Consumption and fuel costs highest among lowest access group. The more access to electricity, the less demand for conventional fuel
 Highly elastic demand for conventional fuels found
 Most kerosene is used as backup lighting in households that have access to electricity

Introduce the term Household Energy (HHE) including cooking, heating, lighting.

 What are the actual impacts of lighting? That is why lighting is often not included in the reports.

 A lot of the time the health impacts are only analyzed in community or regional level -> in this study they focused on the household level.

 2005: A lot of the lightings are in households that do have electricity. They use it as a backup. So this numbers were missing in previous studies.

Questions Posed

 What needs to be done to influence policy? Baselines need to be established, as well as quantifying the effect of interventions. Surprisingly little quantitative data exists for the health and economic effects of lighting interventions.
 What kind of rebound effects in energy consumption are observed? Empirically, energy use in cooking saturates. Audience comment that it has also been observed over the last 200-300 years that in general 0.7% of energy is expended on lighting.

 What do people do when they stop using kerosene? What is the substitute? Audience members have found that often candles or flashlights are used

 Need to better uncover some of the complex relationships between uses and energy stacking. The use of conventional fuels for backup was found to be very significant and more of these relationships need to be uncovered and incorporated into models
 There needs to be more quantitative data for baselines and interventions

What happens exactly if the subsidies phase out? They demand goes to 0 but the model does not say what they shift to.

 Rural vs. urban usage? Urban consumption way lower than rural because of electrification rate, type of devices etc.

 Rebound effect? Survey/Model showed that there is no rebound effect for cooking or lighting. But other papers show that there is a huge rebound effect.

 Use red light to get rid of mosquitoes.

What are the impacts of lighting? Almost no studies.