This is a writeup of a medium investigation, a brief look at an area that we use to decide how to prioritize further research.

In a nutshell

  • What is the problem? South Asia experiences some of the world’s highest levels of population-weighted PM2.5 air pollution. Our understanding is that poor air quality contributes significantly to negative health outcomes for the more than 1.8 billion people in the region, and that reducing the levels of particulate matter present in the air could save millions of lives.
  • What are possible interventions? Possible interventions, many of which require coordinated state action, include improving air quality monitoring programs and crafting and implementing sector-specific policies to reduce emissions. A philanthropist interested in reducing South Asia’s air pollution levels could support efforts to inform the design, implementation, and enforcement of more effective air pollution abatement policies, such as funding monitoring programs, research, and technical assistance.
  • Who else is working on this? Philanthropic interest in South Asian air quality appears to be limited but growing rapidly, although many major philanthropic actors seem to address air pollution as a climate concern rather than as a health issue. Outside of the philanthropic sector, we think it’s likely that governments are the biggest spenders on improving air quality. We remain substantially uncertain about the exact levels of funding South Asian governments are directing toward the issue.

The problem

South Asia – and in particular the Indo-Gangetic Plain that covers parts or all of India, Pakistan, Bangladesh, and Nepal – experiences some of the world’s highest population-weighted air pollution levels.1 Our understanding is that poor air quality contributes significantly to negative health outcomes for the more than 1.8 billion people in this area.2 Of the pollutants present in South Asia’s air, we focus on PM2.5 – particulate matter no larger than 2.5 micrometers in diameter – which we understand to be associated with the greatest health costs.3 In total, the State of Global Air report – a collaboration between the Health Effects Institute and the Institute for Health Metrics and Evaluation’s Global Burden of Disease project – attributes approximately 71.4 million disability-adjusted life years (DALYs) across South Asia annually to air pollution.4 According to the Institute for Health Metrics and Evaluation, air pollution in South Asia accounts for nearly 3% of all DALYs worldwide – i.e. eliminating dangerous levels of air pollution in South Asia alone would reduce the number of prematurely lost years of healthy life by 3% each year.5

Exposure to PM2.5 air pollution can occur outdoors or within households, with the two settings associated with different concentrations, health outcomes, and interventions. Sources of outdoor, or ambient, air pollution in South Asia include brick kilns, vehicles, coal power plants, and crop burning.6 According to the State of Global Air report, South Asia’s average experienced ambient air pollution in 2019 was 78.2 µg/m3, a concentration higher than both the World Health Organization’s recommended standard of 10 µg/m3 and its intermediate standard of 35 µg/m3.7

While we have not investigated the overall evidence base thoroughly, we have encountered widespread agreement that long-term exposure to ambient PM2.5 pollution can result in significant negative health effects, such as chronic respiratory and cardiovascular diseases, that reduce life expectancy. The State of Global Air report, for example, estimates that, in 2019, almost 40 million DALYs in South Asia were attributable to ambient PM2.5 air pollution.8 This number appears to be stable in some South Asian countries and increasing in others.9 While we have not independently vetted this or other mortality and morbidity estimates, it seems reasonably plausible to us based on South Asia’s population-weighted air pollution levels and what the literature we’ve reviewed says about air pollution’s role in chronic illnesses.10

Concentrations of household (as opposed to ambient) air pollution in South Asia appear to be far more difficult to measure, with estimates we found ranging from 35 µg/m3 to over 2,000 µg/m3.11 We found more certainty, however, that household air pollution is widespread: one source estimates that roughly 60% of people in South Asia use solid cooking fuels, the primary source of household air pollution.12 This percentage is apparently decreasing as people switch to cleaner energy sources.13

The lack of reliable household PM2.5 concentration data makes it difficult to confidently discern health effects. The available evidence indicates that negative health outcomes of household air pollution in South Asia may include low birth weight, preterm birth, and other conditions that are correlated with an increased risk of infant death.14 The State of Global Air report, for example, attributed approximately 95,000 infant deaths within the first month of life to household air pollution in South Asia in 2019, estimating an overall impact of approximately 30 million DALYs within the region for that year.15

Of the nations comprising South Asia, India appears to experience among the highest average annual population-weighted ambient air pollution levels – 83.2 µg/m3 – and to contain the greatest number of DALYs attributable to both ambient and household air pollution – 31.1 million and 20.9 million, respectively.16 South Asia’s growing and aging population means that the burden from air quality – all else equal – is rising. In the case of household air pollution, this appears to be more than offset by people switching to cleaner cooking fuels, reducing the burden over time.17 However, the number of DALYs attributable to ambient air pollution appears to be increasing as outdoor air quality is worsening, accentuating demographic trends.18 The outsize impact of air pollution in India relative to other South Asian nations suggests to us that improving India’s air quality could greatly reduce South Asia’s population-weighted annual PM2.5 concentrations and DALYs resulting from air pollution.19

Why believe these estimated harms

We often have concerns about the quality and reliability of non-experimental social scientific evidence, and prefer to be able to replicate key inputs to our calculations ourselves. That is not possible with the State of Global Air report, which does not have open data and code. So we start with some skepticism that these large DALY estimates should be taken at face value. However, we did a review of the underlying literature and – while, as with all social science literatures, we think there could be room for improvement – we came away thinking that we would probably not want to adjust the State of Global Air burden estimates downward by more than a factor of two.

More specifically, biological mechanisms appear to support the conclusion that exposure to air pollution results in significant negative health effects, including mortality, in humans. Both the American Heart Association and the Lancet Commission on pollution and health, as well as epidemiologists we have spoken with, state that breathing particulate matter generates inflammation and vascular damage. These effects in turn are linked to conditions such as atherosclerosis and high blood pressure, which are known to cause life-threatening diseases such as ischemic heart disease and ischemic stroke.20 In infants, the proposed pathway seems to be that particulate pollution causes lower transmission of nutrients to fetuses, resulting in lower birth weight and nutrient deficiencies associated with higher infant mortality and lifelong health complications.21

There are various animal and human RCTs and studies on these biological mechanisms. The studies generally find that particulate pollution causes vascular inflammation, atherosclerosis, and low birth weight.22 More recent animal studies, however, do not seem to use mortality as an outcome of interest, and some much older studies found null effects of air pollution exposure on mortality.23 According to Open Philanthropy’s scientific research team, the null mortality results in animal models in the older studies are not necessarily evidence against mortality effects in humans, largely due to innate differences in biology and lifespans, though we do take them to be a mild negative update.

Outside of studies on the relevant biological mechanisms, we have found various natural experiments conducted by economists that attempt to isolate the causal effect of particulate pollution on mortality. Ebenstein et al., 2017 in particular examines the health effects of air pollution in conditions similar to those in South Asia, although we’re skeptical of this paper’s headline mortality effects.24 Other quasi-experimental papers, many of which focus on short-term exposure to particulates, generally find meaningful effects on mortality on both infants and adults.25 These papers have reassured us that the non-experimental social science literature we have found is likely not detecting the mortality effects of a confounding variable.

We have not found any meta-analyses that look for publication bias in the quasi-experimental evidence mentioned above. There is an epidemiological literature, however, that contains funnel plots that aim to identify publication bias. In a literature with no publication bias, one would expect to see a symmetric, triangle-shaped pattern of dots in the scatter, with the lower-powered analyses equally likely to fall on the right or left of the high-powered analyses. The plots within Pope et al., 2020 (specifically Figure 4), which examines epidemiological papers on the causal effect of air pollution on mortality in cohort studies, appear to have some asymmetry in the middle of the funnels.26 We very tentatively believe that a publication-bias adjustment based on these charts would reduce the mortality effect size to a number slightly to moderately below the consensus in the epidemiological literature.27

Possible Interventions

Government action

Many potential air quality improvements require coordinated state action. The following abatement policies are some of the ones that we thought had a mix of potentially addressing a large portion of the pollution problem and were likely administratively feasible.28

Retrofitting and building efficient brick kilns

20% of clay bricks are produced in South Asia, although PM2.5 emissions attributable to the sector seem to vary by country and be concentrated in urban areas.29 A report by the World Bank estimates that the brick sector is the second-largest PM2.5 contributor in Bangladesh and Nepal, responsible for 11% and 3% of PM2.5 emissions, respectively.30 In India, meanwhile, the share of PM2.5 emissions attributable to brick kilns appears to be comparatively lower, although we have encountered substantial uncertainty around this point. The Health Effects Institute offers one of the lower estimates we found, tracing approximately 2% of India’s PM2.5 pollution and 2 to 3% of its PM2.5-related deaths to brick kilns.31 The World Bank’s report has the highest estimate of the sources we gathered, attributing 8% of India’s PM2.5 emissions to the brick sector.32 The World Bank estimates that retrofitting existing kilns could reduce PM2.5 by 30-50%, as well as improving energy efficiency.33

Despite the uncertainties around emission levels, we think it is plausible (but by no means decisive) that a government-championed effort (e.g., regulations and/or subsidies) to retrofit and build efficient brick kilns would be administratively feasible and could meaningfully reduce PM2.5 pollution from the brick sector.34

Implementing and enforcing a ban on older vehicles

At least since 2015, government bodies in India have indicated an interest in limiting the use of older vehicles.35 There are some regional bans, but it’s unclear to us to what extent they have been implemented or enforced.36 This existing – if inconsistent – interest in banning older vehicles, along with what appears to be a low number of vehicles over 10 years old (meaning political/economic costs of a ban are smaller), suggests that this is a potentially promising area for further government action.37

We’re uncertain about the percentage of the population-weighted PM2.5 pollution in South Asia that is vehicular, although it appears fairly significant. A report by India’s Ministry of Environment, Forest and Climate Change estimates that vehicles contribute approximately 28% of population-weighted PM2.5 emissions in Delhi during the winter and 4% nationally when accounting for all modes of transportation.38 The Energy and Resources Institute attributes 50% of Bangalore’s PM2.5 load to automobile emissions.39 A source apportionment study of Mangalore attributed 70% of particulate pollution to vehicles.40 Older vehicles in particular appear to be a significant contributor to vehicle emissions, with one estimate we found claiming that vehicles older than 15 years account for 15% of total vehicular pollution, and tend to pollute 10 to 25 times as much as newer vehicles.41 Based on these numbers, we think it is likely that a ban on older vehicles could reduce total PM2.5 pollution, although we’re very uncertain about the total reduction we could reasonably expect and how enforceable (and beneficial) a ban would realistically be.

Mandating and enforcing coal scrubbers

Most of the estimates we found attribute approximately 15% of India’s PM2.5 emissions to coal power generation.42 It seems plausible to us that coal is a significant source of PM2.5 emissions, given the prominence of coal in India’s electricity generation and CO2 emissions.43

One report we saw claims that installing wet coal scrubbers in power plants could reduce PM2.5 emissions by as much as 98% and newer fabric filters can reach efficiencies as high as 99.7%.44 While we have not independently vetted this estimate, if accurate, it indicates to us that coal scrubbers could significantly improve India’s air quality.45

The Indian government has already mandated that plants install coal scrubbers to limit emissions, although compliance appears to be limited.46 Given the apparent magnitude of coal power emissions and the government’s existing interest in pursuing mitigation measures, additional efforts to install coal scrubbers might be a promising intervention.

Below, we share our rough back-of-the-envelope calculations (BOTECs) on the potential cost-effectiveness of philanthropic support for the installation of coal scrubbers.

Reducing crop burning with better targeted tractor subsidies

Our impression is that crop burning is a relatively minor source of emissions in India; one article claims that it constitutes an average of 5% of annual PM2.5 pollution in Delhi, although it reaches up to 40% at certain points in the year.47 The vast majority of farmers appear to burn their crops, with only an estimated 20% using tractors to till their fields.48 It seems plausible that better targeting tractor subsidies to increase the percentage of farmers using tractors, while decreasing the percentage of those who burn stubble, could moderately improve Delhi’s air quality.49 We are unsure of the potential impact tractor subsidies might have on air quality across the broader South Asian region.

Better targeting liquified petroleum gas subsidies

From what we have found, solid cooking fuels – still used by approximately 60% of households – account for roughly 40% of the health burden from PM2.5 pollution in South Asia.50 We tentatively assume that substantial reductions in solid cooking fuel use could lead to large reductions in health impacts. The main replacement for solid cooking fuel (e.g. wood, agricultural refuse, charcoal, etc.) is liquified petroleum gas (LPG).

The Indian government already subsidizes LPG use, currently entitling each household to 12 LPG cylinders per year.51 The subsidies, however, do not provide significant discounts to the market price, suggesting that LPG cylinder prices may remain too high for many poor households to afford.52 As a means of increasing the subsidies available to the poor, the government has unsuccessfully attempted to convince wealthier households to voluntarily pay for unsubsidized LPG.53 Better targeting the subsidies by increasing availability and subsidy size for poorer households could plausibly help reduce the number of households that use solid cooking fuels.

What could a philanthropist support?

We have encountered widespread uncertainty around the share total and population-weighted PM2.5 that is attributable to different sources in India and across South Asia. Addressing this information deficiency seems to be crucial to appropriately targeting abatement strategies. As such, it seems likely that philanthropic efforts may be able to productively focus on 1) improving the information ecosystem for local decision makers and other stakeholders and 2) increasing the technical capacity of key governmental agencies to address air quality. A philanthropist interested in supporting either of these two outcomes might pursue any of a variety of activities, some of which we’ve listed below.

Source apportionment studies

As we mentioned previously, we have found that the deficiency in pollution source apportionment data has made it difficult to gauge the potential impacts of available interventions. Source apportionment studies are scientific studies that attempt to measure what share of the total PM2.5 concentration in a given city or region can be attributed to different sources, e.g. transportation, power generation, other industrial sources, etc.54

Source apportionment studies could be conducted in partnership with interested cities needing technical assistance.55 Such localized studies, in providing governments with rough estimates of their cities’ largest sources of air pollution, could potentially improve governments’ (and philanthropists’) abatement strategies.

Below, we share our rough back-of-the-envelope calculations on the potential cost-effectiveness of philanthropist support for source apportionment studies.

Air quality monitoring

A philanthropist might fund either low-cost sensors or advanced monitoring stations. Low-cost sensors, which we have already supported, can be installed locally and could contribute data to real-time air quality maps that report shifts in pollution amounts. We assume that these maps could help improve public awareness of local pollution levels and precipitate minor behavior change, as well as enable governments and other entities to track the impacts of abatement methods. The limited accuracy of low-cost sensors may impede pollution measurements, however, as individual sensors may not be able to detect small changes in concentrations.56

Advanced monitoring stations are much more accurate – also significantly more expensive – and could be installed in each of India’s airsheds. Potentially combining the stations with sun photometers to measure the atmospheric column could allow for significantly more accurate and frequent satellite measurements of air pollution sources and concentrations.57 These measurements could, in turn, provide governments with more precise pollution targets, enable the effects of abatement policies to be tracked, and contribute to general air quality reporting.

We think that air quality monitoring could be a fairly large source of philanthropic spending in the short term, with smaller ongoing costs after the initial implementation. From our conversations, we also received the impression that Indian air monitoring is comparatively well-funded, and that supporting monitoring in other South Asian regions might generate more impact on the margin. We have not independently vetted these claims.

Research on the abatement curve and air pollution health effects in India

We perceive research on the abatement curve (the graph describing the financial costs and volumes of PM2.5 reductions by intervention pursued) and air pollution health effects in India as having a variety of benefits. A better defined abatement curve data could serve as a menu of options for interested philanthropists or policymakers. Research on health effects could provide more targeted data on the health effects of PM2.5 pollution, including potentially distinguishing between the health effects of different types of pollutants.

In addition, such research could help drive awareness among governments and the public of the extent of the problem and accordingly encourage the adoption of targeted abatement measures (particularly if this research identifies a more narrow set of lower cost policy changes that could solve a large share of the total problem). We have heard that this may be more effective if the research is based at national institutions that also provide expertise to local governments or non-governmental organizations working on this issue.

Technical assistance

Providing technical assistance to government entities could improve the outcomes of pollution abatement measures by increasing governmental capacity to implement, enforce, and monitor air pollution abatement measures. A funder interested in this outcome could, for example, work with outside consultants to provide technical assistance to India’s pollution control boards, which, for a number of reasons, have struggled to enforce air quality regulations.58 We have found conflicting estimates of the pollution control boards’ current spending, although it seems to be between $100 million to $300 million a year, split between air pollution, water pollution, noise pollution, and waste management.59

Policy outreach

The interventions outlined in the section above are largely under the purview of the government. As such, philanthropic efforts might focus on providing decision makers with data and resources to craft effective air pollution abatement policies. Potential funding areas could include source apportionment and concentration research, real-time air quality maps, and reporting on air quality in local news outlets. Other means of increasing the salience of air quality might include funding programs like the Clean Air Fund’s Doctors for Clean Air, which raises awareness of the health impacts of air pollution, or supporting air quality programs at universities.

How cost effective could spending in this area be?

If air pollution costs 71.4 million DALYs annually in South Asia, and we were spending $20 million per year, we would need to be pulling forward solutions to approximately 0.06% of the problem by 10 years for every year of our spending in order to clear our 1,000x bar.60 It is difficult to reason about small numbers like that but given the relatively limited scale of other philanthropy in this space, we do not think that would be an unreasonable bar for us to clear.

We do not have a specific plan for how to spend money cost-effectively on this problem at that level, but we’ve done a few back-of-the-envelope calculations on promising-seeming potential projects, described in more detail below, that also make us think they could clear the 1,000x bar.

Air quality monitoring

We have already recommended funding, totalling $3 million, to install a network of low-cost air quality sensors in India. We have removed our current BOTEC since it’s related to our hiring process for a South Asian air quality program officer.

Source apportionment studies

By our rough calculations, a source apportionment study would need to accelerate a reduction of 0.8 µg/m3 in pollution by 10 years for a city of 5 million to reach our 1,000x bar.61 This calculation assumes that:

  • The cost of a source apportionment study would scale as a function of population size. We roughly estimate that a study in a city of 5 million would cost $500,000.
  • Source apportionment studies would only measure, and thus impact, ambient air pollution levels.
  • The PM2.5 concentration in cities is proportional to the national concentration. The average annual population-weighted concentration of ambient air pollution in India is 83.2 µg/m3. Approximately 31,140,452 DALYs in India are due to ambient air pollution, and every DALY is valued at $50,000.62
  • India’s population is 1,366,000,000.63

Coal scrubbers

According to a report by the Disease Control Priorities Network, installing coal scrubbers in all power plants would cost approximately $1.7 billion.64 The same report estimates that to retrofit the plants with the lowest cost per life saved would cost $615 million, although other sources we’ve encountered estimate costs that are more than an order of magnitude higher.65 If the $615 million figure were correct, paying to install coal scrubbers could reach and perhaps surpass our 1,000x bar, assuming the following conditions are true:

  • As we discussed above, coal power generation contributes approximately 15% of India’s PM2.5 emissions.
  • Installing scrubbers reduces PM2.5 emissions by at least 80%.66
  • The selected coal power plants are responsible for 75% of the sector’s DALY costs.67
  • The health effects of air pollution in India cost approximately $2.68 trillion/year.68
  • Given that the government is already mandating the installation of coal scrubbers, our funding speeds installation up by five years.

Under these conditions, we would estimate an ROI of $2.68 trillion (total cost of ambient air pollution) × .15 (power sector share of total PM2.5) × .75 (selected plants’ share of power sector DALYs) × .8 (reduction in PM2.5 from scrubbers) × 5 (years of speed-up) / $615 million (cost of scrubbers) = ~1,960x, though again we do not know these assumptions to be correct and have seen much higher cost estimates in the literature.

What scale could a program in this area possibly reach?

Based on our understanding of the available funding opportunities, we think there is a high likelihood that a program in this area could spend at least $25 million per year on activities such as air quality monitoring, abatement and source apportionment studies, technical assistance, scaling existing organizations working on air quality, and policy outreach, at a cost-effectiveness level comparable to other funding opportunities we pursue. We think there is a lower likelihood of significantly more than $25M/year of capacity in opportunities we would consider quite cost-effective.

Who else is working on this?

Philanthropic organizations

Philanthropic interest in South Asian air quality appears to be limited but growing rapidly: an estimate by the Clean Air Fund, which was cited to us in multiple conversations, puts the philanthropic spending in this area at roughly $7 million in 2019, up from $1 million in 2015.69 We have not vetted the report’s estimates and would guess there are structural underestimates because the report is based on self-reported data from foundations, some of whom may not participate in data sharing, but the estimates are broadly consistent with what we heard in conversations.

The international philanthropic actors working on South Asian air quality that we have heard mentioned most frequently are Bloomberg Philanthropies, the Children’s Investment Fund Foundation, ClimateWorks, the IKEA Foundation, the MacArthur Foundation, the Oak Foundation, Pisces Foundation, and the William and Flora Hewlett Foundation. Some major Indian funders, such as Ashish Dhawan, have also come up in our conversations with experts and funders in the field. We do not believe that this is an exhaustive list: we would guess that we have accounted for the largest philanthropic funders working in this area, but we are certainly missing smaller investments from non-profits and activists.

Many of these major philanthropic actors appear to address air pollution as a contributor to climate change rather than in terms of direct negative health effects from particulates. Climate-focused philanthropic spending on air quality is part of a broader effort to mitigate emissions in India, with philanthropic annual spending on emissions reductions that we think is on the order of $100M-$350M.70

It is unclear to us to what extent treating air quality as a climate concern versus as a health issue would result in significantly different funding strategies. There is definite potential for overlap between climate and air quality spending, as many interventions that reduce greenhouse gasses tend to reduce PM2.5 emissions as well (e.g., limiting reliance on coal for electricity generation). But the two goals can also come apart (e.g., flue-gas desulphurization units on coal plants help improve air quality for health, but as far as we know do not mitigate climate impacts). Overall, we do not think that the presence of significant climate funders mitigates the need for more focused work to improve air quality from a health perspective.71

Government

We found it difficult to find reliable estimates of governmental spending on air quality. According to one source we found, in the 2019-2020 budget cycle, the Indian government created and allocated a fund of Rs 44 billion (approximately $609 million at the time of conversion) to address air pollution in large cities.72 Additionally, a 2020 report released by the Council on Energy, Environment and Water and UrbanEmissions notes that the National Clean Air Plan, which directs cities to create action plans to reduce particulate matter concentrations by 20-30% by 2024, receives Rs 4.6 billion (approximately $63 million at the time of conversion). However, the report also noted that there are no penalties for non-achievement or “legal mandate for reviewing and updating plans.”73 In fact, only nine cities seem to have noted the costs of execution, which ranged from Rs 890 million to Rs 160 billion (approximately $11.9 million to $2 billion at the time of conversion, respectively).74 We remain substantially uncertain of the accuracy of these estimates and recognize that it’s plausible that there may be additional state funds we do not know about. Overall, we think it’s likely that the government is the biggest spender on improving air quality, but that the current spending is substantially lower than the amount required to adequately reduce air pollution.

What have we done so far?

Air quality monitoring stood out to us as a particularly tractable abatement strategy that has the capacity to absorb immediate funding. We have accordingly recommended grants totalling $3 million to support a three-year collaboration between Professor Joshua Apte of UC Berkeley, the Indian Institute of Technology Delhi (IIT Delhi), and the Council on Energy, Environment, and Water (CEEW) to install a network of low-cost air quality sensors in South Asia.

The aim of the collaboration is that the data from the sensors will inform the design, implementation, and enforcement of more effective air pollution abatement policies. Additionally, we also see this project as an early learning opportunity for the testing and deployment of low-cost sensors across South Asia; if successful, we predict that the sensors could have spillover effects on the speed at which other low-cost sensors are deployed, although we have not consulted experts on this point. Both of these outcomes could plausibly result in significant reductions to South Asian air pollution levels.

For our back-of-the-envelope calculations on the potential cost-effectiveness of these grants, see above.

Potential risks and downsides

We have identified a number of potential risks and downsides to funding air quality improvements efforts in South Asia, including:

  • Immediate spending capacity appears to be limited. We have identified a few abatement activities – such as air quality monitoring and certain forms of technical assistance – that could benefit from immediate funding. We have otherwise struggled, however, to identify areas that have the capacity for large-scale recurring support, and we expect that a philanthropist hoping to make South Asian air quality a long-term funding area may need to consistently find novel grantmaking opportunities.75
  • Air quality interventions largely depend on government regulation and enforcement. Accordingly, most philanthropic efforts in South Asian air quality would be limited to activities that inform government policies but that may not directly impact air quality (for example, funding air quality monitoring stations that in turn provide decision makers with data to craft effective abatement measures). It will likely be difficult to predict what the likely impact of these efforts might be.
  • There are risks and restrictions specific to funding work in India. The Indian government has historically regulated foreign grantmaking within India and recently implemented additional restrictions on foreign funding to Indian NGOs.76 It is our impression that all of the potential philanthropic efforts listed in this writeup are permissible under current laws, but there is a risk that the Indian government could implement additional restrictions that would change that.
  • Philanthropic efforts could lead to overly restrictive policies in some domains, which in turn could create space for corruption or potentially slow economic growth. While this writeup does not take into account risks from air pollution beyond mortality, we recognize that some abatement strategies may not be economically feasible or desirable after accounting for their costs.
  • Philanthropic interest in South Asian air quality appears to be growing, so additional funding now could risk crowding out other funders who would otherwise enter.

Our process and next steps

We talked to a number of experts and major funders in the field in the process of researching South Asian air quality. The following individuals agreed to being named as sources for this report, though this should not be interpreted to mean that any experts named here endorse our conclusions in part or in total:

  • Aaron Van Donkelaar
  • Ambuj Sagar
  • Amita Ramachandran
  • Arden Pope
  • Avijit Michael
  • Brikesh Singh
  • Dan Kass
  • Ishwar Gawande
  • Jarnail Singh
  • Josh Apte
  • Kanchi Gupta
  • Matt Whitney
  • Melanie Hammer
  • Michael Greenstone
  • Pallavi Pant
  • Randall Martin
  • Reecha Upadhyay
  • Rohini Pande
  • Sam Ori
  • Sangita Vyas
  • Santosh Harish
  • Siddarthan Balasubramania
  • Vinuta Gopal

We continue to be open to learning about more opportunities in this space and may make additional grants in the future.

Sources



Document Source Text
Air Quality Life Index, “India Fact Sheet” Source
Anderson et al. (2005) Source
Apte et al. (2018) Source
Arceo et al. (2016) Source
Belis et al. (2014) Source
Berger (2020) Source
BreatheLife, “Cities at the Centre of India’s New National Clean Air Programme” Source
Brook et al. (2009) Source
Brook et al. (2010) Source
Burnett et al. (2018) Source
Business Insider, “Indian Government Will No Longer Pay Out Direct Benefit Transfer for Cooking Gas — Subsidy Eliminated as Oil Prices Fall” Source
Centre for Science and Environment, “What Will India Do With Its Old Vehicles?” Source
Chay and Greenstone (2003) Source
Chen et al. (2013) Source
Clancy et al. (2002) Source
Clean Air Fund, “The State of Global Air Quality Funding” Source
Correia et al. (2013) Source
Council on Foundations, “New Indian FCRA Amendments Impact Foreign Grants to Indian NGOs” Source
Cropper (2016) Source
Cropper et al. (2017) Source
Currie (2013) Source
Deryugina et al. (2019) Source
Doctors for Clean Air, “Homepage” Source
DW, “India Pollution: How a Farming Revolution Could Solve Stubble Burning” Source
Ebenstein et al. (2017) Source
Eil et al. (2020) Source
EPA, “Particulate Matter (PM) Basics” Source
Ganguly et al. (2020) Source
Gao et al. (2018) Source
Gardener (1966) Source
Ghosh (2021) Source
GiveWell, “Interpreting the Disability-Adjusted Life-Year (DALY) Metric” Source
Goel et al. (2013) Source
Greenstone et al. (2015) Source
Haryana State Pollution Control Board, “Budget Estimate” Source
Health Effects Institute, “Burden of Disease Attributable to Major Air Pollution Sources in India” Source
Health Effects Institute, “Household Air Pollution and Noncommunicable Disease | Summary for Policy Makers” Source
Heft-Neal et al. (2020) Source
Hindustani Times (2021) Source
Johnson et al. (2020) Source
Kalaiarasan et al. (2018) Source
Koshy (2019) Source
Landrigan et al. (2017) Source
Maharashtra Pollution Control Board, “Budget 2019-2020” Source
Martin et al. (2019) Source
McCormick (1985) Source
Menon (2016) Source
Mohan (2020) Source
Myllyvirta et al. (2016) Source
Narayan (2020) Source
National Clean Air Programme, “Final Proposal” Source
Open Philanthropy, “Scientific Research” Source
Peng et al. (2020) Source
Police et al. (2018) Source
Pope et al. (2009) Source
Pope et al. (2016) Source
Pope et al. (2020) Source
Rakshit (2020) Source
Roeyer et al. (2020) Source
Sharma and Dikshit (2016) Source
Sharma and Kumar (2016) Source
Sharma and Nagpure (2019) Source
Snider et al. (2015) Source
SS Rana & Co (2020) Source
State of Global Air 2020, “Explore the Data” Source
State of Global Air 2020, “Homepage” Source
Task Force on Hemispheric Transport of Air Polution, “Questions and Answers” Source
The Financial Express, “To Curb Stubble Burning, Pay Attention to EPCA on Making Straw Management Machines Affordable” Source
The New Indian Express, “Three Years on, Not Many Willing to Give Up LPG Subsidy” Source
The World Bank, “Population, Total — India” Source
Times of India, “Centre Cuts Pollution Control Budget, Draws Flak From Experts” Source
Times of India, “Foreign Contribution Regulation Act” Source
Tripathi (2020a) Source
Tripathi (2020b) Source
Tuli (2020) Source
Varadhan (2019) Source
Veras et al. (2008) Source
Zhang (2016) Source
  • 1. Health Effects Institute, “State of Global Air 2020”, Figure 3, pg. 7.
  • 2. India has almost 1.37B people, followed by Pakistan at 217M, and Bangladesh at 163M – Afghanistan, Bhutan, Maldives, Nepal, and Sri Lanka combine for an additional ~89M.
  • 3. “Particulate matter contains microscopic solids or liquid droplets that are so small that they can be inhaled and cause serious health problems. Some particles less than 10 micrometers in diameter can get deep into your lungs and some may even get into your bloodstream. Of these, particles less than 2.5 micrometers in diameter, also known as fine particles or PM2.5, pose the greatest risk to health.” United States Environmental Protection Agency, “Particulate Matter (PM) Basics.”“Although exposures to both smaller and larger airborne particles can also be harmful, studies have shown that exposure to high average concentrations of PM2.5 over the course of several years has been the most consistent and robust predictor of mortality from cardiovascular, respiratory, and other types of diseases.” “State of Global Air 2020”, pg. 5.
  • 4. We use disability-adjusted life years (DALYs) as our measurement of air pollution’s health mortality effects throughout this writeup; we do not consider health costs beyond mortality and morbidity (such as lost work and school days), though we are aware of some evidence that such effects could be substantial.

    This estimate includes DALYs resulting from ambient, household, and ozone pollution. State of Global Air, “Explore the Data”. We frequently cite the State of Global Air, which uses Global Burden of Disease (GBD) data, throughout this writeup. From what we have gathered, GBD air pollution concentration figures are among the most up to date, as they incorporate the latest satellite air quality data, and are comprehensive in their estimates of health effects. GBD also distinguishes between ambient and household air pollution, an approach we found helpful in comparing various air pollution sources and interventions.
  • 5. The Institute for Health Metrics and Evaluation, Global Burden of Disease Results Tool.
  • 6. We have encountered substantial uncertainty regarding the percentage of experienced pollution in South Asia attributable to specific sources, so this should not be interpreted as a comprehensive list.
  • 7. “Average experienced air pollution” refers to the population-weighted annual average for a given area. Health Effects Institute, “State of Global Air 2020”, Figure 3, pg. 7.

    Air pollution concentration recommendations vary by source. Air Quality Life Index, “India Fact Sheet,” pg. 2.

    Health Effects Institute, “State of Global Air 2020”, pg. 7.
  • 8. “There is broad scientific consensus that long-term exposures to air pollution contribute to increased risk of illness and death from ischemic heart disease, lung cancer, chronic obstructive pulmonary disease (COPD), lower-respiratory infections (e.g., pneumonia), stroke, type 2 diabetes, and, more recently, adverse birth outcomes, and that the public health burden from these exposures is much larger than that from short-term exposures.” Health Effects Institute, “State of Global Air 2020”, pg. 15; State of Global Air, “Explore the Data”.
  • 9. State of Global Air, “Explore the Data”.
  • 10. See Figure 2 in Apte et al., 2018. Additional resources on air pollution’s mortality effects include Burnett et al., 2018 and Chen et al., 2013.
  • 11. Health Effects Institute, “Household Air Pollution and Noncommunicable Disease,” 2018, Summary Figure 1, pg. 3. Note that the particle size measured also differs across studies.
  • 12. Health Effects Institute, “State of Global Air 2020”, Figure 8, pg. 12.
  • 13. Health Effects Institute, “State of Global Air 2020”, Figure 9, pg. 12.
  • 14. Health Effects Institute, “State of Global Air 2020”, pg. 24.
  • 15. Health Effects Institute, “State of Global Air 2020”, Figure 25, pg. 23; State of Global Air, “Explore the Data”.
  • 16. At 83.1 µg/m3 in 2019, Nepal’s average annual population-weighted air pollution level comes the closest to India’s among other South Asian nations. For Bangladesh, Nepal, and Pakistan, DALYs attributed to ambient PM2.5 air pollution in 2019 were 2.2 million, 517,100, and 5.3 million, respectively. For household air pollution, the 2019 DALY estimates for the same countries were 3.1 million, 6.5 million, and 5.8 million, respectively. State of Global Air, “Explore the Data”.
  • 17. “As for the other pollutants, these trends reflect not only reductions in exposures, but also declining mortality rates from improved treatment of and survival from air pollution–attributable diseases. In the case of household air pollution, those two factors have, on average, more than offset increases in population size and the aging of populations,” Health Effects Institute, “State of Global Air 2020”, pg. 21.
  • 18. “Overall, changes in population size and age structure sometimes have the largest impacts on these trends. Even if exposures to air pollution are decreasing, the overall attributable burden of disease can increase if a population is growing faster than exposures are falling. By the same token, a population that is aging will likely face a higher burden of disease because older people develop, and are more susceptible to, diseases linked with air pollution. Together, population growth and aging of the global population are estimated to account for more than half of the increased deaths attributed to PM2.5 exposure over the past decade,” Health Effects Institute, “State of Global Air 2020”, Figure 17, pg. 18. State of Global Air, “Explore the Data”.
  • 19. There is limited evidence that air pollution can travel and thus that PM2.5 reductions in one country could affect pollution levels in neighboring countries/regions, which would further strengthen the case for reducing air pollution levels in heavily affected places. According to the Task Force on Hemispheric Transport of Air Pollution, “The relative impact of extra-regional anthropogenic sources on PM2.5 concentrations is smaller than on O3 concentrations. The sensitivity of the deposition of sulfur (S), oxidized nitrogen (NOy), and reduced nitrogen (NHx) to changes in extra-regional anthropogenic emissions is similar to the sensitivity of PM2.5 concentrations. In North America, 83% of S deposition, 83% of NOy deposition, and 93% of NH3 deposition are due to sources within North America. In Europe, the fractions are 64%, 66%, and 88% for S, NOy, and NHx deposition, respectively.” The Task Force on Hemispheric Transport of Air Pollution, “Questions and Answers.”
  • 20. “On the basis of the findings of this review, several new conclusions were reached, including the following: Exposure to PM <2.5 μm in diameter (PM2.5) over a few hours to weeks can trigger cardiovascular disease–related mortality and nonfatal events; longer-term exposure (eg, a few years) increases the risk for cardiovascular mortality to an even greater extent than exposures over a few days and reduces life expectancy within more highly exposed segments of the population by several months to a few years; reductions in PM levels are associated with decreases in cardiovascular mortality within a time frame as short as a few years; and many credible pathological mechanisms have been elucidated that lend biological plausibility to these findings. It is the opinion of the writing group that the overall evidence is consistent with a causal relationship between PM2.5 exposure and cardiovascular morbidity and mortality.” The American Heart Association, “Particulate Matter Air Pollution and Cardiovascular Disease,” 2010.

    “PM2.5 is the best studied form of air pollution and is linked to a wide range of diseases in several organ systems. The strongest causal associations are seen between PM2.5 pollution and cardiovascular and pulmonary disease. Specific causal associations have been established between PM2.5 pollution and myocardial infarction, hypertension, congestive heart failure, arrhythmias, and cardiovascular mortality.” Landrigan et al., 2017 pg. 14.
  • 21. Currie 2013 and fig. 3b. of Heft-Neal et al. 2020 explore this phenomenon. See also McCormick 1985, which was frequently cited in the papers we found on the health effects of air pollution exposure in infants.
  • 22. For the effect of particulate pollution on animal model cardiovascular health, see “Particulate Matter Air Pollution and Cardiovascular Disease” by The American Heart Association, 2010. Veras et al., 2008, an RCT on pregnant mice, discusses the relationship between air pollution exposure and placental nutrition.

    In humans, Brook et al., 2009 found that two hours of exposure to high levels of particulates caused meaningful increases in blood pressure in healthy adults. Similarly, Pope et al., 2016 finds that short-term exposure to particulates generates inflammatory cascades and damage to blood vessels in adult humans. The American Heart Association’s “Particulate Matter Air Pollution and Cardiovascular Disease” reviews many other studies linking particulate exposure to cardiovascular risk factors. Meanwhile, many of the studies of infant mortality in the quasi-experiments literature examine low birth weight as an outcome of interest – see especially the many studies on birth weight cited in Currie 2013.
  • 23. See Gardener 1966.
  • 24. More specifically, Ebenstein et al., 2017, which focuses on the Huai River region in China, measures the mortality effect on chronic (rather than acute) exposure, focuses on very high concentrations of particulates (similar to those in South Asia), and is set in a relatively low-income country. These conditions seem analogous to those in South Asia.

    The statistical significance and magnitude of the paper’s findings seem to be dependent on the functional form the authors use. If they were to use a linear model rather than a cubic one, for example, the mortality effect would not be statistically significant. This isn’t to say that no effect exists (the scatter of life expectancy in Figure 3 here is suggestive) – just that this paper may not decisively measure the effect. For a linear finding, see table S11 here.
  • 25. Many of these studies focus on infant mortality as a consequence of short-term exposure to particulates. Arceo et al., 2016 use weather inversions as a source of quasi-random variation in week-to-week particulate concentrations by locale. Chay and Greenstone 2003 use a policy discontinuity stemming from the 1970 Clean Air Act Amendments as an instrument for yearly changes in particulates. Heft-Neal et al. 2020 uses weather in the Sahara as an instrument for annual variation in the dust present in populous parts of West Africa thousands of miles away. As fig. 3b. of Heft-Neal et al., 2020 shows, these and other quasi-experimental analyses find roughly similar effects of particulate exposure on infant mortality. These papers often have wide confidence intervals, since their natural variation often involves a fairly small effective sample size. Still, papers like this provide, in aggregate, what appears to be meaningful evidence for a meaningful effect size. Deryugina et al. 2019, which examines daily variation in exposure among adults due to wind variation, similarly finds causal effects of acute fine particulate matter exposure on mortality.

    For longer-term exposure to particulates, we have identified a few studies beyond Ebenstein et al., 2017, including Clancy et al., 2002, Correia et al., 2013, and Pope et al., 2009. Their effect sizes are within a factor of two or three of the Ebenstein et al., 2017 findings, as shown in Table 1 of Greenstone et al., 2015.
  • 26. That said, the authors state that these plots “do not provide substantive evidence of publication or selection bias,” based on what we assume to be a visual inspection for asymmetry. Pope et al., 2020.
  • 27. This assumption is based on the meta-analysis of a related literature conducted in Anderson et al., 2005, which has funnel plots that, to us, look roughly as asymmetrical as the plots in Pope et al., 2020. The 2005 meta analysis adjusts effect size down by approximately 16% due to inferred publication bias. If we doubled this adjustment on a general principle of conservatism, then a publication-bias adjustment would reduce the effect size by roughly a third below the consensus in the epidemiological literature.
  • 28. We define “administratively feasible” policies in this instance as policies that are politically palatable (e.g. already have been suggested or legislated in some states in India) and seem to not require much additional financial outlay or unreasonable demand for state capacity.

    While we are fairly certain that we have identified policies that would best target South Asia’s largest sources of air pollution, we encountered substantial uncertainty among those we spoke with about the share of total and population-weighted PM2.5 pollution that is attributable to various pollution sources. The uncertainty of the source attribution data made it difficult to confidently predict the potential impact of many of the source-specific air pollution abatement policies listed below.
  • 29. “South Asia is home to 20% of clay bricks produced globally, concentrated particularly in four countries – India, Pakistan, Bangladesh and Nepal…Bricks account for 84%, 24%, and 15% of the PM2.5 emissions in Dhaka, Chittagong, and Delhi, respectively.” The World Bank, “Dirty Stacks, High Stakes: An Overview of Brick Sector in South Asia,” 2020, pgs. 59-60.
  • 30. The World Bank, “Dirty Stacks, High Stakes: An Overview of Brick Sector in South Asia,” 2020, pg. 60.
  • 31. Health Effects Institute, “Burden of Disease Attributable to Major Air Pollution Sources in India,” January 2018, Summary Figures 4 and 5, pg. 7.
  • 32. The World Bank, “Dirty Stacks, High Stakes: An Overview of Brick Sector in South Asia,” 2020, Table 3.3, pg. 60.
  • 33. “A cost-benefit analysis done by the World Bank (2011)* for Bangladeshi kilns found that the retrofitted fixed chimney kiln (IFCK) fared competitively against newer technologies VSBK and HHK in terms of private profit, but lagged far behind in terms of net social profit. On average, the retrofit approach improved energy efficiency by 20% and reduced PM emissions by 50%. The newer technologies, however, demonstrated 30% greater reduction in PM emissions and 20-30% greater energy efficiency than retrofitted kilns.” The World Bank, “Dirty Stacks, High Stakes: An Overview of Brick Sector in South Asia,” 2020, pg. 42.
  • 34. We think this based on the concentration of brick sector emissions in urban areas, the apparent effectiveness of retrofitting existing kilns, and the limited number of brick kilns that would need to be retrofitted or rebuilt in order to improve emission levels (i.e. particularly those in close proximity to population centers), but have not discussed with any experts or reviewed the literature closely.
  • 35. “The National Green Tribunal (“NGT”) in 2015 imposed a ban on all diesel vehicles older than 10 years and all petrol vehicles older than 15 years, in Delhi NCR. Previously, only diesel vehicles that were over 15 years of age were banned in the region.” Lexology, “Ban on Old Vehicles in Delhi NCR – What does the future hold?” August 17, 2020.
  • 36. In 2015, the National Green Tribunal enacted a regional ban on older vehicles in Delhi. More recently, the Indian government announced plans to implement a national tax on and scrapping incentives for certain vehicles older than 15 years old, although it appears that implementation has been delayed. We remain uncertain over the Indian government’s current thinking on vehicle bans.
  • 37. Apparently 1-3% of vehicles in India are greater than 10 years old (the numbers we saw on this were approximately consistent across sources we found). Goel et al., “Methods to Estimate Vehicular Characteristics in Indian Cities,” 2013, pg. 17.
  • 38. Ministry of Environment, Forest & Climate Change, Government of India, “National Clean Air Programme,” 2019, pgs. 6, 8.
  • 39. “To add to its woes, India has seen very rapid growth in vehicles, especially across its urban centres that has contributed to increase in particulate emissions from vehicular sources; accounting for up to 50 per cent in the particulate matter less than 2.5 microns (PM2.5) concentrations in a city like Bangalore (CPCB, 2010).” The Energy and Resources Institute, “Air Pollutant Emissions Scenario for India,” 2016, pg. 93.
  • 40. “The current study depicts that the PM10 and PM2.5 in ambient air of Mangalore region has 70% of its contribution from vehicular emissions (both exhaust and non-exhaust).” Kalaiarasan et al. 2018.
  • 41. Centre for Science and Environment, “What will India do with its old vehicles?” 2020.
  • 42. A report by the Health Effects Institute (pg. 9) estimated that coal power generation is responsible for approximately 15% of PM2.5 emissions and predicted that power plant coal is projected to add ~25 ug of PM2.5 by 2050 (without additional interventions). Similarly, a report by Greenpeace found that roughly one third of PM2.5 pollution in Kanpur and Delhi originates from secondary particles, and that coal power contributes over half of these particles (pg. 28). A separate report on an earlier time period states that “In India, power generation emissions contribute about 33.1% of the YLL attributable to PM2.5 exposure.”
  • 43. “Due to the dominance of coal (76% of total generation), power generation currently contributes to about 40% of total CO2 emissions, as well as 53% and 40% of energy-related sulfur dioxide (SO2) and nitrogen oxides (NOx) emissions, respectively.” Peng et al., 2020.
  • 44. “Currently, more than 90% coal-fired power plants [sic] in China have ESPs [electrostatic precipitators] installed. But their PM2.5 removal efficiency is low. The PM2.5 collection efficiency can reach ~98% when combined with wet FGD [flue gas desulphurization]…Fabric filters, also known as baghouses, operate on relatively simple principles compared to ESPs but have a high collection efficiency, 99.9 to 99.99% over a broad range of particle sizes, and ~99.7% for PM2.5Zhang, 2016.
  • 45. Aside from reducing PM2.5 emissions, coal scrubbers also appear to reduce SO2 levels. One report, for example, indicates that the installation of flue-gas desulfurization units, a type of scrubber, could reduce total SO2 emissions by 90%. Disease Control Priorities, 3rd ed., pg. 243.
  • 46. “India has a phased plan for plants to comply with the emission norms, with some plants having until end-December 2019, while others have up to the end of 2022 to comply. A total of 440 coal-fired units that produce 166.5 gigawatts (GW) have to comply with the regulations by December 2022…at least 51% of all coal-fired units which have the emission targets could fail to comply with the deadlines.” Reuters, “Exclusive: Over half of India’s coal-fired power plants set to miss emission norm deadline,” November 15, 2019. See also “Air Pollution, Environmental Regulation and the Indian Electricity Sector,” presented by Maureen Cropper at the IIEP-NIPFP Conference, October 5, 2016.
  • 47. DW, “India Pollution: How a farming revolution could solve stubble burning,” August 11, 2019.
  • 48. DW, “India Pollution: How a farming revolution could solve stubble burning,” August 11, 2019.
  • 49. The Indian government already appears to subsidize tractor use, although the subsidies’ impact on crop burning is unclear to us. The Financial Express, “To curb stubble burning, pay attention to EPCA on making straw management machines affordable,” October 2, 2020.
  • 50. Health Effects Institute, State of Global Air 2020.
  • 51. Mint, “Cooking gas prices may see monthly revision to contain subsidy,” February 18, 2020. Poor households tend to use around three cylinders a year, and the average household uses a little more than twice that. DownToEarth, “Overcoming India’s clean cooking challenge,” December 26, 2019.
  • 52. Business Insider India, “Indian government will no longer pay out direct benefit transfer for cooking gas – subsidy eliminated as oil prices fall,” September 1, 2020.
  • 53. The Indian News Express, “Three years on, not many willing to give up LPG subsidy,” July 29, 2019.
  • 54. We have not examined the methods behind source apportionment in detail, but our understanding is that one main methodology, “receptor-oriented methodology,” mathematically solves a series of equations trying to match total concentrations of different types of PM by weighting different (known) pollution signatures accordingly and uses the weights to measure sourcing. See e.g. Belis et al. 2014 for more details.
  • 55. Localized source apportionment studies that have come up in our conversations include a 2015 study by the Indian Institute of Technology Kanpur of Delhi and a 2011 study of Trombay, a suburb of Mumbai. We have not vetted either study.
  • 56. “PurpleAir particulate matter (PM) sensors are increasingly used in the United States and other countries by a variety of individuals and organizations for continuous monitoring of ambient air pollutant conditions…The performance of these sensors must be evaluated during smoke impacted times, and nominally corrected for bias if necessary, to ensure accurate data are reported to inform appropriate health protective actions…For the national data set of sensors collocated with regulatory-grade monitors, results show that PurpleAir sensors, when corrected, accurately report NowCast AQI categories 90% of the time as opposed to uncorrected PurpleAir data, which are accurate only 75% of the time.” The United States Environmental Protection Agency, “PurpleAir PM2.5 performance across the U.S. #2,” 2020.
  • 57. “A hybrid monitoring approach could accelerate the availability and quality of information about PM2.5 within India. Such an approach could build upon recent advancement in satellite-based assessment of air quality, and the emergence of strategically located ground-based monitoring stations that combine measurements of PM2.5 chemical composition with sun-photometer measurements of aerosol optical depth to improve the accuracy of satellite-based estimates from both global and regional perspectives (Snider et al., 2015). Such strategic measurement nodes can also provide important evaluation data for chemical transport model simulations and provide necessary inputs for receptor modeling source apportionment. This information on source contributions could inform forecasting and evaluation of air quality management options and initiatives.” Martin et al., 2019.
  • 58. Some sources indicate that India’s pollution control boards have faced limitations due to an excessively long hiring process, inadequate funding and salaries too low to attract talent, a lack of subject matter expertise, their reliance on political appointees, or because employees feel disempowered to regulate pollution.
  • 59. The Haryana Pollution Control Board spent 45.7 cr INR in 2013 (less than $10 million) and the Maharashtra Pollution Control Board spent roughly twice as much in 2020. This article, however, suggests much lower figures. We are uncertain about the share spent on air pollution, but the Maharashtra PCB reports 4422 lakhs on air quality in their proposed projects out of a proposed projects budget of 10,040 lakhs, or about 44% (see pages 37-38 of this PDF).
  • 60. 20 million annual spending × 1000x hurdle rate / (71.4 million DALYs/year × $50 thousand (value of DALY) × 10 year duration ) = .00056. Note that we are currently re-examining our value per DALY, but expect that value to either rise or remain the same, so the overall importance of this cause would increase or remain the same.
  • 61. ($500,000 (cost of study)/5,000,000 (city size))((1,000 (ROI bar) × 1,366,000,000 (India size) × 83.2 (current PM2.5))/(10 (years) × $50,000 (value per DALY) × 31,140,452 (ambient DALYs in India/year))) = 0.8.
  • 62. State of Global Air’s “Explore the Data”. $50,000 is our standard figure for the value of a DALY. See note earlier that this figure may change in the future.
  • 63. The World Bank.
  • 64. “Costs and Benefits of Installing Flue-Gas Desulfurization Units at Coal-Fired Power Plants in India,” Table 13.6, pg. 244.
  • 65. “Costs and Benefits of Installing Flue-Gas Desulfurization Units at Coal-Fired Power Plants in India,” Table 13.6, pg. 244.

    The Association of Power Producers “estimates it will cost private companies roughly $38 billion to comply with the norms and install FGD units to tackle sulfur dioxide emissions,” Reuters, “Exclusive: Over half of India’s coal-fired power plants set to miss emission norm deadline,” November 15, 2019. Another source estimates that the installation of coal scrubbers in most plants will cost Rs 800,000,000,000 ($10.9 billion at the time of conversion).
  • 66. This is potentially conservative, since scrubbers, as discussed above, may reduce PM2.5 by 98% or more, but reflects our uncertainty about installation quality, maintenance, and real-world performance.
  • 67. The 30 plants with the lowest cost per life saved cost 9,196 lives/year out of the total of 12,890 or ~71%. “Air Pollution, Environmental Regulation and the Indian Electricity Sector,” presented by Maureen Cropper at the IIEP-NIPFP Conference, October 5, 2016.
  • 68. According to the State of Global Air’s “Explore the Data”, air pollution in India is responsible for approximately 53.5 million DALYs. Our standard figure for the value of a quality-adjusted life year is $50,000 (see note earlier that this value may change in the future). Therefore, 53.5 million DALYs × $50,000/DALY = $2.69 trillion.
  • 69. The Clean Air Fund (CAF), “The State of Global Air Quality Funding 2020”, Figure 2, pg. 9.
  • 70. ClimateWorks Foundation reports that, between 2015 and 2019, philanthropic foundations spent 55 million USD a year on average on mitigating emissions in India. According to the same report, a total of ~7 B USD were spent globally on climate in 2019, with only 1.6 B USD from foundations. Further, they report that foundation spending increased from less than .9 B to 1.6 B between 2015 and 2019. If we assume that the share of India spending remains constant over time and between foundation and non-foundation philanthropic spending, we can roughly estimate the total spending on emissions mitigation in India in 2019. They state the average total yearly foundation funding over the time period was 1.1 B, so we calculate foundation funding in India in 2019 as 1.6/1.1 × 55 M = 80 M. We then calculate total India climate funding as 7/1.6 × 80M = 350 M USD in 2019. This could be an overestimate (e.g. if individual climate funding skewed even more heavily towards interventions in wealthy countries) or underestimate (e.g. if funding in India has grown faster than total funding since 2015). We think it’s most likely an overestimate, but think that philanthropic climate spending is still very likely $100M+. “Funding trends: Climate change mitigation in philanthropy,” ClimateWorks Foundation, 2019, pg. 5.
  • 71. There was a general consensus among those we spoke with that climate and air quality are related but that the top abatement interventions for each will differ.
  • 72. The Times of India, “Mumbai to get biggest chunk of grant from Centre to fight air pollution,” March 12, 2020. We assume (but could be wrong) that this is a one-time fund that will not automatically renew.
  • 73. The Council on Energy, Environment and Water and UrbanEmissions, “How Robust Are Urban India’s Clean Air Plans?” June 2020, pg. 18. BreatheLife, “Cities at the Centre of India’s New National Clean Air Programme,” January 18, 2019.
  • 74. The Council on Energy, Environment and Water and UrbanEmissions, “How Robust Are Urban India’s Clean Air Plans?” June 2020, pg. 18.
  • 75. It’s possible that there are opportunities in technical assistance, research, and policy outreach that could absorb large scale recurring funding, although we have not thoroughly investigated this possibility.
  • 76. “The Foreign Contribution Regulations Act or FCRA is a law enacted by Parliament to regulate foreign contribution (especially monetary donation) provided by certain individuals or associations to NGOs and others within India. The act, in its consolidating form, was originally passed in 1976 and majorly modified in 2010. The government has used the act over the years to freeze bank accounts of certain NGOs who it found were affecting India’s national interest for wrong purposes,” The Times of India, “Foreign Contribution Regulation Act,” February 7, 2020. Council on Foundations, “New Indian FCRA Amendments Impact Foreign Grants to Indian NGOs,” November 12, 2020.