Quantifying the air quality, climate and equity implications of India's household energy transition

Energy for Sustainable Development 55 (2020) 37–47

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Energy for Sustainable Development

Quantifying the air quality, climate and equity implications of India's household energy transition Poushali Maji a,⁎, Milind Kandlikar a,b a b

Institute for Resources Environment and Sustainability, The University of British Columbia, 2202 Main Mall, Vancouver, BC V6T 1Z4, Canada School of Public Policy and Global Affairs, The University of British Columbia, 6476 N.W. Marine Drive, Vancouver, BC V6T 1Z2, Canada

a r t i c l e

i n f o

Article history: Received 21 June 2019 Revised 21 November 2019 Accepted 25 November 2019 Available online xxxx Keywords: Household energy transition Co-benefits Indoor air quality Non-Kyoto Scenario modelling

a b s t r a c t Economic growth, urbanization and changes in lifestyles are leading to a transition from traditional fuels to liquefied petroleum gas (LPG) and electricity in Indian households. We use National Sample Survey data – 43rd (1987–88) and 68th (2011−12) rounds – to show that contrary to concerns about rising greenhouse gas (GHG) emissions from fossil-fuel use, switching to LPG and electricity provides health and climate benefits, if non-Kyoto emissions are considered. Our modelled household energy transition scenarios (2011–2030) show that: one, adoption of LPG by 2030 in Business-As-Usual (BAU) projections results in 80% of urban India meeting the World Health Organization's (WHO) indoor PM 2.5 guidelines. In rural households, persistent use of firewood does not significantly improve indoor air quality across the income spectrum. Two, BAU scenario projects only a 3% rise in rural GHG emissions by 2030, driven by a transition away from kerosene lighting in spite of rising electricity consumption. Three, a complete transition to LPG and electricity by 2030 reduces PM 2.5 exposure to below WHO guidelines across all urban and rural households. This is not achieved in the other partial transition scenarios. Four, across scenarios improving coal-based power plant efficiency to 40% and increasing renewables' share to 40% lead to a decrease of 14–18% in GHG emissions by 2030 relative to 2011. Finally, improved biomass cookstoves can reduce indoor exposure by 75–86% but not below the WHO guideline, and result in higher GHG emissions compared to LPG replacement due to non-Kyoto emissions from burning firewood. © 2019 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

Introduction Rapid economic growth, urbanization and changes in lifestyles have led to a transition away from traditional solid fuels (firewood, dung and coal) and towards modern energy services like liquefied petroleum gas (LPG) and electricity in the Indian household energy sector. Residential electricity and LPG consumption in India grew at 7% and 8% respectively in 2016–2017 and the residential sector accounted for 87% of LPG and 24% of final electricity consumption (CSO, 2019) in India. However, as of 2015, India still housed 300 million people who did not have electricity connections and about 800 million people who relied on biomass

Abbreviations: GHG, greenhouse gas; PM 2.5, particulate matter b2.5 μm in diameter; CO2, carbon dioxide; CO2eq, carbon dioxide equivalent; CH4, methane; N2O, nitrous oxide; CO, carbon monoxide; NMVOC, non-methane volatile organic compounds; BC, black carbon; OC, organic carbon; SO2, sulfur dioxide; GWP, global warming potential; NSS, National Sample Survey; WHO, World Health Organization; ITG, interim target guideline; LPG, liquefied petroleum gas; ICS, improved cookstove; PNG, piped natural gas; BAU, Business-As-Usual; PMUY, Pradhan Mantri Ujjwala Yojana; MJ, megajoule; Mt, million tons. ⁎ Corresponding author. E-mail address: [email protected] (P. Maji).

fuels for cooking (Government of India, 2015), the majority of these energy-deprived households being low-income and/or residing in rural areas (Ailawadi & Bhattacharyya, 2006; Pachauri & Jiang, 2008; Pachauri, 2014). Access to modern energy, i.e. both affordable and reliable physical availability as well as availability of a threshold value for meeting basic needs, plays a key role in poverty eradication, improving the general quality of life and improved health. And yet, both LPG and electricity are fossil fuel-based – coal contributes towards about 65% of electricity generation in India (CSO, 2019) – and have implications for rising greenhouse gas (GHG) emissions. LPG and electricity are considered ‘cleaner’ household fuels as they do not contribute towards significant air pollution at their end-use stage, i.e. inside homes, relative to burning solid fuels. Burning solid fuels indoors is inefficient and polluting and is widely known to adversely affect indoor air quality and health. Incomplete combustion of biomass and kerosene in lamps releases fine particulate matter. PM 2.5 – particles b2.5 μm in diameter – are especially harmful to respiratory and cardiovascular health (Po, FitzGerald, & Carlsten, 2011; Lam, Smith, Gauthier, & Bates, 2012; Bruce, Perez-Padilla, & Albalak, 2000; Gordon et al., 2014). The negative impacts of solid fuels are particularly significant for women and children who spend more time collecting firewood as well as indoors (Smith et al., 2014; Ezzati & Kammen,

https://doi.org/10.1016/j.esd.2019.11.006 0973-0826/© 2019 International Energy Initiative. Published by Elsevier Inc. All rights reserved.

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2001). PM 2.5 also includes pollutants like black carbon which has significantly higher global warming potential than CO2 (Lam et al., 2012; Venkataraman, Ghosh, & Kandlikar, 2016; Bond, 2004). Analyses of different cookstove technologies have shown that LPG stoves may have both health and climate benefits — they lead to lower particulate matter exposure and help avoid products of incomplete combustion (PICs) which are global warming pollutants (Grieshop, Marshall, & Kandlikar, 2011). Modern energy services provide a number of other developmental benefits such as reliable lighting for evening study hours and savings in time, particularly for women who are primarily responsible for fuel collection in India (Cabraal, Barnes, & Agarwal, 2005; Asian Development Bank, 2010; Khandker, Barnes, & Samad, 2013; ESMAP, 2002; ESMAP, 2004; Barnes, Kumar, & Openshaw, 2012). The Government of India has prioritized improved and accelerated access to LPG and electricity (Government of India, 2015). Government subsidy schemes like the Pradhan Mantri Ujjwala Yojana (PMUY) and Power for All provide low-cost access to LPG equipment and electricity infrastructure, respectively, to poor households (Kar, Pachauri, Bailis, & Zerriffi, 2019; Ebinger, 2016). On the other hand, in India, modern energy services like LPG and electricity are fossil-fuel centric and as the share of such energy services surpasses traditional biomass use, the fuel transition will also contribute towards household CO2 emissions (van Ruijven et al., 2011a; Cameron et al., 2016). India's Intended Nationally Determined Contributions (INDC) for the period 2021–2030, as outlined in response to the Paris Agreement under the United Nations Framework Convention on Climate Change (2016), emphasizes the need for inclusive economic development, concurrent with a ‘low carbon path to progress’ (Government of India, 2015). In this paper, we analyze indoor air quality and GHG emission impacts of household energy transition pathways for 2030 and assesses whether future energy transition pathways in India can improve indoor air quality while helping realize climate goals at a household level. We analyze India's household energy transition in a retrospective as well as a prospective manner. We use household-level data from a nationwide consumer expenditure survey (National Sample Survey) for the years 1987–88 and 2011–2012 to represent the transition in types and quantities of household fuel across urban-rural populations and income groups. We calculate shifts in GHG emissions (including CO2 and other short-lived climate pollutants such as black carbon (BC) and non-methane volatile organic compounds (NMVOC)) as well as in householdlevel emissions of and exposure to PM 2.5 across income groups. We use the retrospective data to prospectively model five near-term fuel transition scenarios (to 2030) based on varying levels of adoption of clean fuels and technologies such as LPG, electricity and improved cookstoves, and particularly focusing on rural energy transition. In addition to household consumption scenarios, changes in the fuel mix and efficiency of India's power sector are incorporated to evaluate the climate and indoor air quality outcomes of India's household fuel transition pathways. We estimate indoor air quality benefits and greenhouse emission co-benefits for these pathways, accounting for different household energy consumption scenarios, thermal power plant efficiency and renewables' share in power generation. The results allow us to examine the role that new cooking and power generation technologies and government policy can play in maximizing co-benefits for climate and health across income classes. The remainder of the paper is structured as follows. India's household energy transition section provides a brief overview of household energy consumption in India, with a focus on emissions of GHGs and indoor air pollution. Equity, Indoor air quality and Climate impacts of India’s household fuel transition (1987–2011) section presents a retrospective assessment of the effect of India's household energy transition from 1987 to 2011 on GHG emissions and exposure to indoor air pollution. In Climate and indoor exposure outcomes for scenarios of future energy use (2030) section, we model five nearterm (2030) household energy transition scenarios to examine the

possible role of government policies on equitable access to energy, GHG emissions, and air pollution exposure. We conclude in Results and discussion section with our findings. India's household energy transition Studies on household fuel consumption patterns in India have approached the topic on different scales — at macro (or national level) as well as micro (or household level). While a macro-level analysis allows the study of both direct and indirect household energy use (Pachauri & Spreng, 2002; Das & Paul, 2014), household-level data, such as from the National Sample Survey (NSS) in India, captures the heterogeneity among household groups. It enables us to make distinctions in consumption patterns between urban and rural households, as well as among household groups by income, geographical location and other characteristics like household size. Clean fuel adoption has been more rapid in India's urban areas; however, within urban and rural populations there are vast differences in income and lifestyles and consequent differences in energy consumption patterns, with LPG and electricity use being more widespread in higher income households (Pachauri & Jiang, 2008; Gangopadhyay, Ramaswami, & Wadhwa, 2005; Reddy, 2003; Viswanathan & Kavi Kumar, 2005). A number of studies find that increasing per capita expenditure is the biggest driver of rising household energy requirements (Pachauri & Spreng, 2002; Lenzen et al., 2006) as well as clean cooking fuel choice (Reddy, 1995; Rao & Reddy, 2007; Farsi, Filippini, & Pachauri, 2007). Despite a general transition to modern energy services over the last few decades, households often practice ‘fuel stacking’, i.e. instead of giving up traditional fuels, they use a combination of traditional and modern fuels, primarily due to unaffordable and/or unreliable supply, or even cultural preferences (Masera, Saatkamp, & Kammen, 2000; Kowsari & Zerriffi, 2011). More than 60% of rural households and about 40% of urban households used both kerosene and electricity in 2009–2010, while about 15% of rural households and 10% of urban households used both LPG and biomass (Cheng & Urpelainen, 2014). In fact, LPG and biomass stacking grew in Indian households between 1987 and 2009 (Cheng & Urpelainen, 2014), implying that households are adopting modern energy services, but often only partially. Modern energy services provide a number of direct and indirect developmental benefits — direct benefits include reduction in firewood collection time due to a transition to LPG and longer hours of productive work in the evening due to electrification; a significant indirect benefit is improvement in indoor air quality as households move away from biomass burning and kerosene lamps, and this is particularly significant for women, who are responsible for most of the cooking activities in Indian households and young children, who spend more time at home (Cabraal et al., 2005; Asian Development Bank, 2010; Barnes et al., 2012; Khandker, Samad, Ali, & Barnes, 2012). Both kerosene lamps and biomass burning contribute significantly to high indoor PM 2.5 exposure — personal exposure in wood-using Indian households is estimated to be two orders of magnitude higher than in those that use LPG (Grieshop et al., 2011; Balakrishnan et al., 2002; Shupler et al., 2018). Shupler et al. (2018) estimate 24-hour mean exposures for women and men in wood-using households in rural India to be 274 μg/m3 and 197 μg/m3 respectively, which is well above the WHO interim target guideline (ITG-I) of 75 μg/m3 for 24-hour PM 2.5 concentrations (WHO, 2006). This is consistent with average national 24-hour exposure estimates by Balakrishnan et al. (2013) of 337 μg/m3 for women, 285 μg/m3 for children and 204 μg/m3 for men. Kerosene wick lamps are known to result in indoor PM 2.5 concentrations that exceed the WHO guidelines by an order of magnitude as well (Lam, Chen, et al., 2012; Apple et al., 2010; Muyanja et al., 2017). High exposure to PM 2.5 has a number of adverse cardiovascular and pulmonary impacts — it is associated with chronic obstructive pulmonary disorder, acute respiratory tract infections and chronic cough (Naeher et al., 2010; Bruce, Perez-Padilla, & Albalak, 2002; Smith, Rogers, & Cowlin, 2005; Liu et al.,

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Equity, indoor air quality and climate impacts of India's household fuel transition (1987–2011)

rural areas (47% of the income group) was roughly equal to that of the second lowest urban income class (50%), even though the rural group's mean consumption levels were 3 times greater, indicating a very strong urban bias in the supply and use of LPG. Average per capita useful energy consumption by fuel type and by income decile was calculated using fuel energy density and assumed stove efficiency values from the literature (Fig. S.4 in SI). Energy consumption in middle and high-income urban households was dominated by electricity use, while cooking energy requirement saturated in 2011 in these households at a monthly value of about 85 MJ per capita (details on dividing reported kerosene consumption into cooking and lighting uses are provided in SI Section S2). In 2011, individuals in the top 10% of urban households used almost six times as much useful modern energy (LPG and electricity) as those in the bottom 10%, while individuals in the top 10% of rural households used 14 times as much as the bottom 10% in rural areas. The data also show that inequity in modern energy access is greater than inequity in income, particularly in rural India. The calculated Gini coefficient for per capita modern energy use is 0.49 and 0.65 in urban and rural households respectively, which is considerably higher than the corresponding values of Gini coefficient for income per capita which are 0.39 and 0.32. Urban consumers use more electricity than rural counterparts in all income deciles, but the gap rose dramatically at the highest income levels. In addition to the presence of a general transition in primary cooking fuel used among urban and high-income rural households, many households use multiple fuels simultaneously (aka fuel stacking). Among households that adopted LPG for cooking by 2011, the share of LPG in useful cooking energy ranged from 87 to 99% in urban households and 62–78% in rural households, with LPG's share rising with income and firewood and kerosene as supplemental cooking fuels. Kerosene use as a primary cooking fuel has declined over the years (from 20% of urban households in 1987 to 6% in 2011, while it has remained the primary cooking fuel for b1.5% of rural households across the years) — the Government of India discourages the use of kerosene as a cooking fuel by restricting the quantities of subsidized kerosene available, since a substantial portion is sold through the black market for adulteration of other fuels (Gangopadhyay et al., 2005; Clarke, 2014).

Household energy transition across income classes

Greenhouse gas emissions

The National Sample Survey (NSS) provides India-wide socio-economic data at a household level. Data is collected through interviews on a range of expenditure items including fuel, along with household characteristics like household size, monthly expenditure on each item, etc. We use data from the 43rd (July 1987–June 1988) (National Sample Survey Organisation, 1988) and 68th (July 2011–June 2012) (National Sample Survey Organisation, 2010) rounds (see SI Section S1 for details on each round), to examine the household energy transition across income groups and urban-rural India over a span of 24 years. The NSS dataset also records quantities of fuel used per household by fuel type and can be used for calculating GHG and PM 2.5 emissions from direct fuel use in the household. Urban and rural households were divided into 10 income groups corresponding to per capita expenditure deciles in the urban and rural populations, where expenditure is used as a proxy variable for income (Figs. S.1 and S.2 in SI Section S1 show details of fuel transition across income groups). The NSS data shows that while urban India experienced an almost complete transition to electrification by 2011, low-income and middle-income rural households formed the majority of those without access to electricity (about 25% of all Indian households). 47% of rural households in the bottom 30% and 30% in the middle 30% used kerosene as their primary lighting fuel. Firewood dominated as the primary choice for cooking fuel in rural households in 1987 (80%) as well as 2011 (67%) while 68% of urban India, primarily middle and high-income households, adopted LPG by 2011 (up from 22% in 1987). Strikingly, the adoption of LPG in the highest income class in

Fuel consumption data allow GHG emission calculations at the household level, including gases covered under the Kyoto protocol – CO2, CH4, and N2O – as well as ‘non-Kyoto’ emissions — CO, BC, NMVOC, OC and SO2 (see SI Section S2 for emission factors for fuels and 100-year global warming potentials (GWP) used). Although there is a level of uncertainty associated with non-Kyoto emissions, uncertainty analyses show that the global warming impact of particles such as BC is significantly higher than CO2 (Bond, 2007). GHG emission profiles assume average power grid transmission and distribution losses to be 25% (Buckley, 2015) and biomass sustainability to be 70% (van Ruijven et al., 2011a; Singh et al., 2017). Total Kyoto and non-Kyoto emissions in rural and urban households in each year are calculated as follows:

2007; Dennis, Maldonado, Norman, Baena, & Martinez, 2016; Johnson et al., 2011; Ellegard, 1996; Mbatchou Ngahane et al., 2015), with higher risks for women than men (Smith et al., 2014; Ezzati & Kammen, 2001). From a climate perspective, studies on household-level fuel transition and corresponding climate impacts focus primarily on only CO2 emissions (Pachauri, 2014; Ahmad, Baiocchi, & Creutzig, 2015; van Ruijven et al., 2011b). Pachauri (2014) concludes that growth in access to electricity in India between 1983 and 2009 is responsible for 39–53% of the rise in household CO2 emissions from electricity use, but only 3– 4% of the rise in national CO2 emissions in this period. Van Ruijven et al. (2011a) developed a model that shows that a more equitable income distribution and higher electrification rates in India may have developmental and air quality advantages, but would lead to higher electricity consumption and consequently, CO2 emissions. Cameron et al. (2016) model LPG adoption and the cost of access for different carbon tax scenarios, concluding that trade-offs between access to modern fuel and CO2 mitigation can be large, particularly for the urban poor and rural rich who are more vulnerable to price changes. However, transition to clean cooking fuel and electricity may also provide climate benefits since short-lived climate forcers (like black carbon) add to GHG emissions. A few previous studies account for non-CO2 global warming pollutants, but they are either a technology-specific analysis of climate and air quality synergies (Grieshop et al., 2011) or fuel-specific analysis of the climate impacts of household energy transition (Singh, Pachauri, & Zerriffi, 2017). There are three key differences between previous work and this study. First, we conduct a nation-wide empirical assessment of household energy transition, integrating the net climate impact of GHGs (accounting for both Kyoto and non-Kyoto warming agents) and indoor air quality. Second, we analyze GHGs and indoor air quality consequences of the household energy transition across the income spectrum. Third, we use historical data to project future scenarios of household energy transition and analyze potential air quality and climate cross-impacts.

1. For cooking fuel and kerosene use in lamps Emissions ¼ Σhfp Fuel consumption ðMJ Þhf x Emission factorðg=MJ Þfp x GWP p ð1Þ

where (h) is each household, (f) is a fuel-technology combination and (p) is a pollutant. Emission factors give the emissions of a pollutant (p) per unit consumption of fuel (f). For the purpose of this analysis, emission factor of CO2 from biomass is assumed to be 30% of its value from literature, to account for 70% renewability. Cooking fuel emission factors are collated from Grieshop et al. (2011), Pandey, Sadavarte, Rao, and Venkataraman (2014), and Smith et al. (2000) and the GAINS database for South Asia (IIASA, n.d.).

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2. For electricity Emissions ¼ Σhfp ðElectricity=ηÞhf ðkWhÞ x Power share f

ð2Þ

x Emission factor ðg=kWhÞfp x GWPp where (h) is each household, (η) is the power grid efficiency, (f) is the power plant type by fuel, and (p) is the pollutant. Power sharef is the generation share of power plant type f in 1987 and 2011 obtained from CEA (2011). All emission factors are collated from CEA (2011), Sadavarte and Venkataraman (2014) and GAINS database for South Asia. Calculated nation-wide Kyoto emissions from household fuel use in 2011 were 346 Mt CO2eq, which is about 20% of estimated nation-wide Kyoto emissions from all sectors in 2007 (MOEF, 2010). Of this, household electricity consumption in 2011 accounted for 175 Mt CO2eq (or about 10% of total emissions in 2007; MOEF, 2010). This estimate is consistent with Pachauri's (2014) estimate of 159 Mt CO2 from household electricity use or 10% of total emissions in 2011. Including non-Kyoto emissions increases total household carbon equivalent emissions in 2011 by about 43%. Firewood accounted for about 48% of total household emissions (Kyoto and non-Kyoto) while kerosene lighting and electricity each accounted for about 20%. Non-Kyoto emissions are key to this accounting and contribute 95% of emissions from kerosene lighting and 55% of firewood emissions. Total (Kyoto and non-Kyoto) household GHG emissions in rural India (76% in 2009) are higher than in urban India (24% in 2011), with firewood contributing the majority of emissions, both in 1987 and 2011 (see Table 1). This is true even if firewood is considered 100% renewable. Between 1987 and 2011, total household GHG emissions rose by 60% (Fig. 1). Rural firewood consumption, driven by rise in population as well as higher per capita usage, has increased between 1987 and 2011 — increase in non-Kyoto emissions from rural firewood use is almost equivalent to increase in Kyoto emissions, implying that accounting for only Kyoto emissions is significant underestimate of the impact of firewood usage on climate. In urban households, electricity consumption is the most significant contributor to rising GHG emissions. The negative bar for non-Kyoto emissions from electricity use in both years is driven by the SO2 emissions from thermal power plants, implying adverse air quality impacts, in spite of providing climate advantages. Fig. 2 shows the change in per capita GHG emission profiles across income groups between 1987 and 2011. In urban households, emissions from kerosene lighting and firewood have dramatically reduced, particularly in middle and high-income groups, while emissions from per capita electricity use have risen exponentially. LPG emissions have stabilized in the high-income households as cooking energy requirements are met entirely by LPG. In rural households, per capita firewood emissions have risen, except in the top decile where LPG displaced some firewood. Emissions reduction from kerosene lighting in the top rural decile led to a 3% reduction in total per capita emissions (cooking fuel emissions remaining constant) in spite of a rise in electricity consumption, indicating that a complete transition away from kerosene lighting can play a significant role in reducing the climate impact of household

fuel use. The relationship between emissions and income is stronger in urban India where emissions are driven by rising electricity consumption; in rural India emissions are primarily due to firewood usage, with electricity consumption gaining significance in the top 2 deciles. Air quality and exposure to indoor PM 2.5 Daily exposure to PM 2.5 is calculated as below: Daily PM 2:5 intake per capita ¼ f TE  ðBR=ðV  kex  mÞÞ  ∑ f emf f ðmg=MJÞ  FU f ðMJÞ

ð3Þ

where, fTE = fraction of time exposed to emissions = 90%; BR = breathing rate in m3/day = 16 m3/day; V = volume of air per person in m3 = 30 m3 and kex = exchange rate between indoor and outdoor air = 14/h corresponding to high occupancy and high air exchange between indoors and outdoors (Fantke et al., 2017); m = mixing factor = 1 (Humbert et al., 2011); emff = emission factor of fuel (f) and FU = daily fuel use in MJ. We estimate the daily PM 2.5 intake or dose for those who remain in the same room as emission generating activities for majority of their time, and do not attempt to estimate mean 24hour exposure concentrations which would depend on time activity patterns of individuals. We do not account for variations in the location of other household members not directly exposed to emissions, time spent indoors or breathing rates of individuals. (V ∗ kex) is assumed to be constant across income groups — high-income households may have higher volume of air available per person but can be expected to be more airtight than low-income households. We calculate an iF (i.e. intake fraction or fraction of emissions inhaled by the exposed population) of 1430 ppm, which is within the range of estimates (1300– 2400 ppm) of daily intake from unvented cookstoves described in Grieshop et al. (2011)) and consistent with iF of 1600 ppm calculated by Fantke et al. (2017) for high occupancy and high air exchange indoor settings typical of India. Fig. 3 shows average per capita PM 2.5 intake across income groups in 1987 and 2011. PM 2.5 exposure is driven by firewood usage — in rural households, PM 2.5 exposure has increased over the years and rises with income with greater firewood usage, except in the top 30% where LPG adoption and a shift away from kerosene lamps has reduced exposure. However, mean PM 2.5 exposure in 2011 was well above the 24-hour WHO ITG-I of 75 μg/m 3 (WHO, 2006) across income groups in rural households and low/middle income urban households, with the household fuel transition making a notable difference only in high (top 3 deciles) income urban households. Climate and indoor exposure outcomes for scenarios of future energy use (2030) This section estimates the climate impact and indoor exposure to PM 2.5 of potential fuel transition pathways to 2030 for urban and rural households. Five household energy consumption scenarios are defined

Table 1 Household cooking and lighting fuels: Contribution to household GHG emissions in 2011.

Firewood Kerosene lighting (primary and supplemental) LPG Electricity Total

% of total household emissions

Share of Kyoto/non-Kyoto emissions from each fuel

Rural

Urban

Kyoto

Non-Kyoto

44% 17% 2% 9.5% 76%⁎

4% 2% 4% 11% 24%⁎

45% 5% 94% 178%

55% 95% 6% −78%

⁎ kerosene (for cooking), coke, coal and charcoal contributed an additional 5% to GHG emissions. Firewood considered 70% renewable.

P. Maji, M. Kandlikar / Energy for Sustainable Development 55 (2020) 37–47

Fig. 1. Change in total annual household Kyoto and non-Kyoto emissions in India (1987–2011).

Fig. 2. Annual per capita CO2eq (Kyoto + non-Kyoto) emissions from direct household fuel use in rural and urban India (1987–2011).

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Fig. 3. Mean daily per capita PM 2.5 intake in urban and rural households (1987–2011). (24-hour WHO Interim Target Guideline (ITG) = 75 μg/m3 (WHO, 2006) or 1.2 mg/day at average breathing rate of 16m3/day (Fantke et al., 2017); inhaled PM 2.5/cigarette = 12 mg (Pope et al., 2009)).

in order to examine the effect of government policies. Fuel consumption patterns from 2011 are used with projections of per capita expenditure, population and household size to 2030, and assumptions about future energy access trends to quantify energy consumption by fuel type in households. Details are provided in the SI Section S3. In addition to household consumption scenarios, changes in the fuel mix and efficiency of India's power sector are incorporated to evaluate the climate and indoor air quality outcomes of India's household fuel transition pathways. Household fuel consumption scenarios Scenario 1: Business-As-Usual (BAU) 2030 The BAU 2030 scenario assumes that urban and rural patterns of cooking fuel and electricity consumption change with per capita income and that these follow the past pattern of energy expenditures, with no additional policies addressing the GHG content of electricity or the power grid efficiency. No additional effort in increasing rural availability of LPG or improving the quantum of electricity supply is made, i.e., fuel use patterns follow projected trends in population and income growth. This scenario does not consider the impacts of recent government schemes such as PMUY or Power for All to increase rural adoption of LPG or electricity respectively, and models household energy consumption patterns in the absence of these initiatives. The price of fuels is assumed to remain constant relative to 2011 income levels and cultural preferences for a specific fuel type are not considered. We also assume that un-electrified households in 2030 use 4 l of kerosene a month for lighting (Rao, 2012), and that no electrified household in 2030 uses kerosene for lighting.

The 2011 NSS data is used to model three key fuel consumption parameters – the share of households electrified, per capita electricity consumption and the share of LPG in per capita cooking energy requirements – as functions of the mean per capita expenditure for each income decile in rural and urban households. Rural and urban households are considered separately to account for the different trends of fuel consumption in each category. Sigmoid or S-shaped curves, such as the Gompertz and Richard's curves have been used to model and make future projections of electrification (World Bank, 2008) and electricity consumption (Mohamed & Bodger, 2005), respectively. Gompertz, Richards and Logistic functions differ in terms of their point of inflexion and shape parameters. A logistic curve is symmetrical about the point of inflexion (point where rate of growth starts decreasing), the Gompertz model allows asymmetry about the point of inflexion, while the Richards function allows flexibility in the position of point of inflexion through a shape parameter (Höök, Li, Oba, & Snowden, 2011; Teleken, Galvão, & Robazza, 2017). We use the ‘grofit’ package in R to select the best fitting sigmoid growth curve — Gompertz curve for electrification and LPG adoption, and Richards curve for electricity use. All parameters and model details are provided in SI Section S3. Shares of cooking fuels and cooking energy requirements per capita are considered specific to income groups — wealthier households are smaller in size and per capita cooking requirements are higher. As per capita expenditure rises, the household fuel mix curve for cooking of a particular income decile shifts rightward to reflect this increase. For the BAU scenario, we assume that per capita consumption of LPG and electricity in rural and urban households are capped at the 2011 level of the highest income group, i.e., households in the top rural decile do

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not increase LPG/electricity consumption with increase in income (LPG meets a maximum of 41% of rural household fuel requirements in the top decile), either due to barriers to supply of these fuels or other factors, while the highest income urban household deciles have reached saturation in terms of per capita electricity and LPG demand. The saturation levels of LPG adoption and electricity use in rural households are raised in the following scenarios, assuming that physical availability of LPG and electricity, currently a constraint in rural areas, will improve by 2030 (see SI Section S3 for further details). Firewood's share in the cooking energy requirements is adjusted according to LPG adoption. LPG and electricity consumption from 2018 help validate the aggregate BAU outcomes. BAU estimates for LPG consumption in India in 2018 are lower than government estimates for domestic LPG supply (CSO, 2019) by 4%. NSS consumption figures are generally lower than national accounts data (CSO, 2015; Kulshreshtha & Kar, 2005); additionally a portion of the subsidized domestic LPG supply is diverted illegally for commercial purposes. BAU electricity consumption estimates for 2018 exceed national-level government estimates for domestic electricity consumption (CSO, 2019) by 30%. However, modelled BAU estimates are based on NSS data which include imputed values for electricity consumption based on expenditure and market price, and so are expected to capture illegal electricity consumption, unlike official reported government estimates. Sub-scenario 1a) BAU with PMUY (Pradhan Mantri Ujjwala Yojana). In the BAU scenario, the share of LPG is only about 25% of a household's cooking requirements in low-income (bottom 30%) rural households. We model a sub-scenario to account for the PMUY which aims to enable greater use of LPG in the poorest households. Under the PMUY scheme, launched in 2016, the Indian government provides subsidized LPG connections (the initial cost of a cylinder, set-up equipment such as regulator and connecting pipe, and administrative fees (70 USD)) to poor households in order to remove the barrier of high upfront costs of clean cooking fuel. However, households are expected to purchase LPG at government-subsidized rates. While government figures show that N80 million new LPG connections have been distributed through this scheme between 2016 and 2019, LPG consumption under PMUY has not grown in tandem with growth in customer base, as the subsidized cost of fuel is still too high for poor households (Pradhan Mantri Ujjwala Yojana, 2018; The Hindu Business Line, 2018a). According to government figures, households under this scheme use 3.5–4 cylinders annually (The Hindu Business Line, 2018b). The PMUY scheme is modelled as a subset of the BAU scenario for 2030 by assuming a minimum of 4.5 kg of LPG used each month by each of the bottom 3 rural deciles (3.8 cylinders annually); this accounts for about 35% of each household's fuel requirements, which is 10% greater than BAU levels. Scenario 2: medium effort: rural LPG and electricity In scenario 2, the BAU scenario is modified to include rural LPG and electricity supply increases, along with universal electrification in rural and urban households (wherein every household has access to a minimum threshold of 30 kWh of electricity per month), and the elimination of all kerosene use for lighting. In this and following scenarios (3, 4 and 5) where universal electrification is assumed, households that would have been excluded from the estimated share of electrified households in each income group in the BAU scenario based on modelled income in 2030, are assigned 30 kWh of electricity/month (the Government of India aims to provide a minimum of 1 kWh/day to each household as part of its inclusive growth targets for 2030; Planning Commission, 2014). We assume that availability and reliability of supply of LPG and electricity in rural India improve between 2011 and 2030 and thus rural households in the top decile increase their consumption of LPG and electricity beyond those projected in the BAU scenario. Relative to BAU scenario, LPG and electricity supply thus increase by 34% and 25% of the total rural supply respectively. These changes correspond to a saturation level of 65% of a rural household's cooking energy requirements

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in the top decile being met with LPG, as well as a doubling of per capita electricity use in the top rural decile. Urban households follow similar LPG adoption and electricity consumption trends as in BAU scenario. Scenario 3: strong push: rural LPG and electricity In scenario 3, there are no barriers in physical availability of rural LPG and electricity (modelled through higher saturation level in growth equations and universal electrification). LPG and electricity use by rural households is determined by their income levels (using expenditure as a proxy), with no restrictions on availability or reliability of supply. Kerosene use for lighting is eliminated. Given the widespread availability of firewood in rural areas, we assume that a maximum of 90% of rural households' energy requirements being met with LPG. As a result, total rural LPG and electricity consumption increase by 58% and 32% respectively. Urban households follow the similar LPG adoption and electricity consumption trend as in BAU scenario. Scenario 4: sustainable development goals (SDG) or all LPG-cooking scenario In scenario 4, all solid fuel use is replaced with LPG, irrespective of affordability, along with universal electrification and no barriers to electricity supply. There is no kerosene used for lighting and no solid fuels used for cooking. This is an ideal scenario where clean household energy for all as a sustainable development goal has been achieved. This leads to a 162% increase in rural LPG supply and only 5% increase in urban LPG supply relative to BAU scenario, with electricity use patterns in rural and urban households similar to Scenario 3. Scenario 5: multi-fuel scenario with the following assumptions • A complete transition from solid fuels to induction stove cooking in urban India. • Replacement of traditional biomass cookstoves to improved cookstoves (ICS) in rural India. For improved cookstove type, we consider a portable unvented natural draft stove used in India that corresponds to a 66% reduction in PM 2.5 emissions relative to a traditional biomass cookstove (Grieshop et al., 2011). Additionally, we compare the relative exposure reduction on using a forced draft improved cookstove, which has a better emission performance compared to the natural draft improved cookstove considered (Grieshop et al., 2011). • Universal access to electricity and the elimination of kerosene from lighting. • Urban and rural households follow the same pattern of LPG adoption as in the BAU scenario — there is no additional effort to improve LPG supply or promote its adoption as a clean fuel. Additionally, 20% of urban households (the top 2 income deciles) switch to piped natural gas (PNG) for cooking.

Induction stoves, although requiring specific cooking vessels, are non-polluting devices that can be used by households with a reliable electricity connection. They are efficient, safe, long lasting and lowcost (average cost of 20–30 USD for the stove, with monthly electricity cost lower than subsidized LPG) (Smith & Sagar, 2014). PNG is a relatively new primarily urban commodity, being part of the city gas distribution sector. As of 2011, there were 2.6 million households with PNG connections but it is currently not an option for the urban poor due to the ability of gas distribution companies to pass on price increases to consumers (Sen, 2015) and the cost of PNG currently being slightly higher than subsidized LPG (3%) (Singh, 2015), along with higher connection costs (85 USD for PNG connection vs. 70 USD for an LPG connection). The WWF-TERI modelling study for 2030 (WWF-India, 2013) assumes a similar transition pathway for its alternate renewable energy scenario.

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Table 2 Power sector variables used in scenario analysis. Coal power plant efficiency 2011 value 30%a Alternate model value 40% for 2030 a b

Renewable energy share in generation (incl. hydro) 16%b 40%

Buckley (2015). CEA (2011).

Transition pathway models Fuel transition pathways are modelled using two key variables related to changes to the Indian electricity grid — coal power plant efficiency and renewable energy's share in power generation. These variables in addition to the five future scenarios for household fuel consumption described in the Household fuel consumption scenarios section drive the analysis (Table 2). The model's alternate values for coal power plant efficiency and renewable power in 2030 are based on current government targets, specifically in light of India's climate commitments in the form of Intended Nationally Determined Contributions (INDC), in response to the Paris Agreement of 2016. The Government of India is promoting a shift towards supercritical technologies for coal-based power plants (Government of India, 2015) — these power plants have higher thermal efficiencies (40% and above) compared to existing power plants in India (30–32% efficiency, Buckley, 2015), and are expected to reduce India's coal consumption. We assume an alternate value of 40% efficiency for coal-based power plants in 2030. Renewables, including hydropower,

accounted for 28% of power generation in 2018 (CSO, 2019) and given the Government of India's target for 40% installed power capacity from non-fossil fuel sources by 2030 (Government of India, 2015), we assume an alternate value of 40% renewable energy share in power generation for 2030. GHG emissions are calculated using Eqs. (1) and (2) stated in the India's household energy transition section and PM 2.5 intake per person is calculated using Eq. (3) in the Equity, Indoor air quality and Climate impacts of India’s household fuel transition (1987–2011) section. Nation-wide household GHG emissions are projected to increase by 34% relative to 2011 in the BAU scenario for 2030. If only Kyoto emissions are considered and the potential non-Kyoto emission reductions from transitioning away from kerosene lighting and firewood are excluded, the projected increase in the BAU scenario relative to 2011 is 136%, driven by LPG adoption and electricity consumption. Alternate high LPG adoption and universal electrification scenarios, for the same grid parameter assumptions, show even higher rise in Kyoto emissions, implying a trade-off between climate and clean energy access. Including non-Kyoto emissions shows that high LPG adoption and universal electrification in fact reduces non-Kyoto emissions from firewood and kerosene lighting, thus indeed providing a climate benefit. Fig. 4 shows the change in net GHG and mean per capita PM 2.5 intake for each household fuel scenario for rural and urban households, assuming coal power plant efficiency and renewables' share in power remain at 2011 levels — vertical error bars show the range of estimated GHG reductions for increasing coal power plant efficiency to 40% and/or renewables' share in power to 40%. Horizontal error bars in Fig. 4 show the range of projected reduction in mean per capita intake across income groups. Fig. 5 expands on the inequity in indoor exposure

Fig. 4. Transition pathways to 2030: Climate (Kyoto + non-Kyoto) and indoor air quality co-benefits in urban and rural households. (Note: 100% decline implies a complete reduction relative to 2011).

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Fig. 5. Household fuel transition pathways: Equity in indoor air quality benefits in 2030. (Natural draft ICS represented in rural Multiple fuels scenario).

reduction across scenarios and shows the mean daily per capita PM 2.5 intake for each income group in each scenario. Results and discussion The 2030 BAU scenario for household energy consumption estimates a 3% rise in GHG (Kyoto + non-Kyoto) emissions in rural households and 134% increase in urban households. The minimal rise in emissions in rural households in the BAU scenario, in spite of rising electricity consumption, is driven primarily by a transition away from kerosene lighting and consequent reduction in non-Kyoto emissions. If only Kyoto gases are considered in the BAU scenario for 2030, GHG emissions in rural households increase by 81% and those in urban households increase by 224% relative to 2011. In the BAU PMUY sub-scenario, the additional transition from firewood to LPG by low-income rural households leads to a further reduction of 1% in rural GHG emissions. This assumes biomass is 70% renewable (Singh et al., 2017) and includes non-Kyoto emissions. In urban households, widespread adoption of LPG in the BAU projections results in all urban households, except the bottom 20%, meeting the 24-hour WHO ITG-I PM 2.5 exposure threshold value of 75 μg/m3; in rural households persistent use of firewood does not significantly improve indoor air quality across the income spectrum. The BAU PMUY sub-scenario, through greater LPG usage in bottom 30% of rural households, reduces PM 2.5 exposure in these households by 15% relative to BAU without the PMUY scheme. The resultant exposure values, at an average of 35 mg PM 2.5/day are still high, but now comparable to those of middle/high income rural households. Projected GHG emissions in Scenarios 2 and 3, with medium and high LPG adoption respectively in rural households and universal electrification, are within a range of 2–3% of emissions in BAU scenario. Greater LPG use and additional electricity consumption due to universal

electrification in rural households do not lead to significant changes in net GHG emissions. Mean per capita PM 2.5 intake is lower in these scenarios compared to BAU scenario, but largely for middle-income and high-income rural households who can afford to transition from firewood to LPG. Scenario 4 (All LPG-cooking) offers the greatest climate and health benefits. Universal LPG and electricity adoption across urban and rural households leads to a rise of only 3–10% in GHG emissions, or even a decrease of about 18%, relative to 2011, depending on power plant efficiency and renewables' share in power generation; indoor PM 2.5 exposure is reduced to below 75 μg/m3 across urban and rural households. Compared to the BAU scenario for 2030, this All LPG-cooking scenario leads to 24% lower GHG (Kyoto + nonKyoto) emissions. Scenario 5 or Multi-fuel scenario is similar to BAU and scenarios 2 and 3 in terms of climate impact but offers greater and more equitable health benefits, as all wood-using rural and urban households move from traditional to improved cookstoves (natural draft) and solid fuels to induction cooking respectively. This scenario offers greater health benefits than improving LPG availability in rural areas (Scenarios 2 and 3) due to complete transition to improved cookstoves across income groups; whereas in Scenarios 2 and 3, in spite of better LPG availability, adoption of LPG in low and middle income rural households is still constrained by affordability in 2030. Switching to ICS, however, does not reduce PM 2.5 exposure to below the WHO threshold value of 75 μg/m3 in rural areas — forced draft improved biomass cookstoves reduce PM 2.5 exposure by about 40% relative to natural draft improved cookstoves but it still exceeds the WHO indoor air quality guideline. Forced draft improved biomass cookstoves result in 10% lower GHG emissions compared to natural draft improved biomass cookstoves, but emissions are still 11% higher than switching completely to LPG (Scenario 4).

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Higher levels of clean fuel (LPG and PNG) use and electricity consumption scenarios (Scenarios 2, 3 and 5) do not have a large effect on the range of GHG emissions increase estimated in the BAU scenario. One exception is when all households use only LPG for cooking (Scenario 4); this leads to emission reductions for rural households by 26– 40% relative to 2011, predominantly due to reduction of non-Kyoto emissions from firewood and kerosene lighting. For any household fuel consumption scenario in 2030, improving coal-based power plant efficiency (to 40%) and renewables' share in electricity (to 40%) could lead to a reduction of 26–28% of total GHG emissions relative to the BAU scenario, in which both parameters are kept at 2011 levels. Across scenarios, projected emission reductions are a function of the transition away from firewood, higher thermal power plant efficiency and lower share of coal in power. The multi-fuel scenario where urban households switch from solid fuels to electricity for cooking offers similar health and climate benefits to urban households as would a complete switch to LPG. In rural India, improved cookstoves (ICS) offer lower benefits than those that result from switching to LPG. The estimated per-capita intake in ICS households of about 9 mg/day from ICS (or about 5 mg/day from forced draft ICS) is far higher than that implied by WHO guidelines (about 0.6 mg/day). Relative to switching to LPG, ICS also leads to about 20– 30% higher GHG emissions in rural households, depending on the type of ICS used, assuming biomass is 70% renewable (Singh et al., 2017) and including non-Kyoto emissions. One limitation of this work is that the uncertainty in renewability of biomass (assumed to be 70% here) and global warming potential of non-Kyoto pollutants is not analyzed. Additionally, in modelling energy transition scenarios for 2030, examining the role of cultural preferences or social pressure to use a specific fuel was beyond the scope of this paper. From this analysis, the greatest health and climate benefits are achieved through a complete transition to LPG and electricity, particularly if India manages to meet its INDC targets for renewable generation and high efficiency thermal power plants — moving away from firewood and kerosene lighting offers significant climate benefits, particularly in terms of non-Kyoto emission reductions. Using firewood in improved cookstoves in rural households can reduce PM 2.5 exposure compared to traditional cookstoves by N75%, but it is still estimated to exceed the 24-hour WHO ITG-I guideline of 75 μg/m3. Improved cookstove programmes in India have also faced multiple challenges in adoption and maintenance of cookstoves and long-term emissions reduction. Better access to clean fuels in 2030, i.e. higher levels of LPG adoption and electricity in rural India, does not significantly affect GHG emissions relative to lower levels of clean fuel access in BAU scenario. Increasing the physical availability or supply of LPG without addressing affordability will largely benefit middle-income and high-income rural households and provide unequitable health benefits and limited climate benefits, as poorer households continue to use firewood. Subsidy schemes like the PMUY aim to make LPG more affordable by reducing upfront costs without further subsidizing the fuel; but LPG use affords minimal climate and health benefits if it meets only part of the cooking energy requirements of low-income households. A complete transition away from firewood also has strong developmental implications such as better education for girls and empowerment of women, by reducing the opportunity cost associated with collecting and cooking with firewood, which are primarily women's responsibilities in India. Government efforts should focus on both affordability and improving the quantum and reliability of supply of clean fuels like LPG and electricity.

Funding sources This research was supported by the University of British Columbia's Four Year Doctoral Fellowship and the Canadian Institutes of Health Research-Bridge Fellowship Program.

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