South Asia â and in particular the Indo-Gangetic Plain that covers parts or all of India, Pakistan, Bangladesh, and Nepal â experiences some of the worldâs highest population-weighted air pollution levels.1Â Our understanding is that poor air quality contributes significantly to negative health outcomes for the more than 1.8 billion people in this area.2Â Of the pollutants present in South Asiaâs air, we focus on PM2.5Â â particulate matter no larger than 2.5 micrometers in diameter â which we understand to be associated with the greatest health costs.3Â In total, the State of Global Air report â a collaboration between the Health Effects Institute and the Institute for Health Metrics and Evaluationâs Global Burden of Disease project â attributes approximately 71.4 million disability-adjusted life years (DALYs) across South Asia annually to air pollution.4Â According to the Institute for Health Metrics and Evaluation, air pollution in South Asia accounts for nearly 3% of all DALYs worldwide â 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 Asiaâs average experienced ambient air pollution in 2019 was 78.2 Âľg/m3, a concentration higher than both the World Health Organizationâs recommended standard of 10 Âľg/m3 and its intermediate standard of 35 Âľg/m3.7
While we have not investigated the overall evidence base thoroughly, we have encountered widespread agreement that long-term exposure to ambient PM2.5Â 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 PM2.5Â air pollution.8Â This number appears to be stable in some South Asian countries and increasing in others.9Â While we have not independently vetted this or other mortality and morbidity estimates, it seems reasonably plausible to us based on South Asiaâs population-weighted air pollution levels and what the literature weâve reviewed says about air pollutionâs 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 Âľg/m3Â to over 2,000 Âľg/m3.11Â 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.12Â This percentage is apparently decreasing as people switch to cleaner energy sources.13
The lack of reliable household PM2.5Â 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.14Â 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 â 83.2 Âľg/m3Â â and to contain the greatest number of DALYs attributable to both ambient and household air pollution â 31.1 million and 20.9 million, respectively.16Â South Asiaâs growing and aging population means that the burden from air quality â all else equal â 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.17Â However, the number of DALYs attributable to ambient air pollution appears to be increasing as outdoor air quality is worsening, accentuating demographic trends.18Â The outsize impact of air pollution in India relative to other South Asian nations suggests to us that improving Indiaâs air quality could greatly reduce South Asiaâs population-weighted annual PM2.5Â concentrations and DALYs resulting from air pollution.19
1.1 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 â while, as with all social science literatures, we think there could be room for improvement â 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.20Â 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 Philanthropyâs 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 weâre skeptical of this paperâs 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
2.1 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
2.1.1 Retrofitting and building efficient brick kilns
20% of clay bricks are produced in South Asia, although PM2.5Â emissions attributable to the sector seem to vary by country and be concentrated in urban areas.29Â A report by the World Bank estimates that the brick sector is the second-largest PM2.5Â contributor in Bangladesh and Nepal, responsible for 11% and 3% of PM2.5Â emissions, respectively.30Â In India, meanwhile, the share of PM2.5Â 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 Indiaâs PM2.5Â pollution and 2 to 3% of its PM2.5-related deaths to brick kilns.31Â The World Bankâs report has the highest estimate of the sources we gathered, attributing 8% of Indiaâs PM2.5Â emissions to the brick sector.32Â The World Bank estimates that retrofitting existing kilns could reduce PM2.5Â 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 PM2.5Â pollution from the brick sector.34
2.1.2 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.35Â There are some regional bans, but itâs unclear to us to what extent they have been implemented or enforced.36Â This existing â if inconsistent â 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
Weâre uncertain about the percentage of the population-weighted PM2.5Â pollution in South Asia that is vehicular, although it appears fairly significant. A report by Indiaâs Ministry of Environment, Forest and Climate Change estimates that vehicles contribute approximately 28% of population-weighted PM2.5Â emissions in Delhi during the winter and 4% nationally when accounting for all modes of transportation.38Â The Energy and Resources Institute attributes 50% of Bangaloreâs PM2.5Â load to automobile emissions.39Â A source apportionment study of Mangalore attributed 70% of particulate pollution to vehicles.40Â 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.41Â Based on these numbers, we think it is likely that a ban on older vehicles could reduce total PM2.5Â pollution, although weâre very uncertain about the total reduction we could reasonably expect and how enforceable (and beneficial) a ban would realistically be.
2.1.3 Mandating and enforcing coal scrubbers
Most of the estimates we found attribute approximately 15% of Indiaâs PM2.5Â emissions to coal power generation.42Â It seems plausible to us that coal is a significant source of PM2.5Â emissions, given the prominence of coal in Indiaâs electricity generation and CO2Â emissions.43
One report we saw claims that installing wet coal scrubbers in power plants could reduce PM2.5Â emissions by as much as 98% and newer fabric filters can reach efficiencies as high as 99.7%.44Â While we have not independently vetted this estimate, if accurate, it indicates to us that coal scrubbers could significantly improve Indiaâs air quality.45
The Indian government has already mandated that plants install coal scrubbers to limit emissions, although compliance appears to be limited.46Â Given the apparent magnitude of coal power emissions and the governmentâs 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.
2.1.4 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 PM2.5Â pollution in Delhi, although it reaches up to 40% at certain points in the year.47Â The vast majority of farmers appear to burn their crops, with only an estimated 20% using tractors to till their fields.48Â 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 Delhiâs air quality.49Â We are unsure of the potential impact tractor subsidies might have on air quality across the broader South Asian region.
2.1.5 Better targeting liquified petroleum gas subsidies
From what we have found, solid cooking fuels â still used by approximately 60% of households â account for roughly 40% of the health burden from PM2.5Â pollution in South Asia.50Â 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.51Â 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.52Â 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.53Â 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.
2.2 What could a philanthropist support?
We have encountered widespread uncertainty around the share total and population-weighted PM2.5Â 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 weâve listed below.
2.2.1 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 PM2.5Â 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.55Â Such localized studies, in providing governments with rough estimates of their citiesâ largest sources of air pollution, could potentially improve governmentsâ (and philanthropistsâ) abatement strategies.
Below, we share our rough back-of-the-envelope calculations on the potential cost-effectiveness of philanthropist support for source apportionment studies.
2.2.2 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 â also significantly more expensive â and could be installed in each of Indiaâs 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.57Â 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.
2.2.3 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 PM2.5Â 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 PM2.5Â 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.
2.2.4 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 Indiaâs pollution control boards, which, for a number of reasons, have struggled to enforce air quality regulations.58Â We have found conflicting estimates of the pollution control boardsâ 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
2.2.5 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 Fundâs Doctors for Clean Air, which raises awareness of the health impacts of air pollution, or supporting air quality programs at universities.
2.3 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 weâve 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.
2.3.1 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 itâs related to our hiring process for a South Asian air quality program officer.
2.3.2 Source apportionment studies
By our rough calculations, a source apportionment study would need to accelerate a reduction of 0.8 ¾g/m3 in pollution by 10 years for a city of 5 million to reach our 1,000x bar.61 This calculation assumes that:
2.3.3 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 weâve 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:
Under these conditions, we would estimate an ROI of $2.68 trillion (total cost of ambient air pollution) Ă .15 (power sector share of total PM2.5) Ă .75 (selected plantsâ share of power sector DALYs) Ă .8 (reduction in PM2.5Â from scrubbers) Ă 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.
2.4 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.
3.1 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 2015.69Â We have not vetted the reportâs 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 Childrenâs 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 PM2.5Â 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
3.2 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.72Â 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 âlegal mandate for reviewing and updating plans.â73Â 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).74Â We remain substantially uncertain of the accuracy of these estimates and recognize that itâs plausible that there may be additional state funds we do not know about. Overall, we think itâs 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.
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.
We have identified a number of potential risks and downsides to funding air quality improvements efforts in South Asia, including:
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:
We continue to be open to learning about more opportunities in this space and may make additional grants in the future.
Â
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This work is licensed under a Creative Commons Attribution 4.0 International License.
| Air Quality Life Index, âIndia Fact Sheetâ | 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, âCities at the Centre of Indiaâs New National Clean Air Programmeâ | Source |
| Brook et al. (2009) | Source |
| Brook et al. (2010) | Source |
| Burnett et al. (2018) | Source |
| Business Insider, âIndian Government Will No Longer Pay Out Direct Benefit Transfer for Cooking Gas â Subsidy Eliminated as Oil Prices Fallâ | Source |
| Centre for Science and Environment, âWhat Will India Do With Its Old Vehicles?â | Source |
| Chay and Greenstone (2003) | Source |
| Chen et al. (2013) | Source |
| Clancy et al. (2002) | Source |
| Clean Air Fund, âThe State of Global Air Quality Fundingâ | Source |
| Correia et al. (2013) | Source |
| Council on Foundations, âNew Indian FCRA Amendments Impact Foreign Grants to Indian NGOsâ | Source |
| Cropper (2016) | Source |
| Cropper et al. (2017) | Source |
| Currie (2013) | Source |
| Deryugina et al. (2019) | Source |
| Doctors for Clean Air, âHomepageâ | Source |
| DW, âIndia Pollution: How a Farming Revolution Could Solve Stubble Burningâ | Source |
| Ebenstein et al. (2017) | Source |
| Eil et al. (2020) | Source |
| EPA, âParticulate Matter (PM) Basicsâ | Source |
| Ganguly et al. (2020) | Source |
| Gao et al. (2018) | Source |
| Gardener (1966) | Source |
| Ghosh (2021) | Source |
| GiveWell, âInterpreting the Disability-Adjusted Life-Year (DALY) Metricâ | Source |
| Goel et al. (2013) | Source |
| Greenstone et al. (2015) | Source |
| Haryana State Pollution Control Board, âBudget Estimateâ | Source |
| Health Effects Institute, âBurden of Disease Attributable to Major Air Pollution Sources in Indiaâ | Source |
| Health Effects Institute, âHousehold Air Pollution and Noncommunicable Disease | Summary for Policy Makersâ | 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, âBudget 2019-2020â | 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, âFinal Proposalâ | Source |
| Open Philanthropy, âScientific Researchâ | 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, âExplore the Dataâ | Source |
| State of Global Air 2020, âHomepageâ | Source |
| Task Force on Hemispheric Transport of Air Polution, âQuestions and Answersâ | Source |
| The Financial Express, âTo Curb Stubble Burning, Pay Attention to EPCA on Making Straw Management Machines Affordableâ | Source |
| The New Indian Express, âThree Years on, Not Many Willing to Give Up LPG Subsidyâ | Source |
| The World Bank, âPopulation, Total â Indiaâ | Source |
| Times of India, âCentre Cuts Pollution Control Budget, Draws Flak From Expertsâ | Source |
| Times of India, âForeign Contribution Regulation Actâ | Source |
| Tripathi (2020a) | Source |
| Tripathi (2020b) | Source |
| Tuli (2020) | Source |
| Varadhan (2019) | Source |
| Veras et al. (2008) | Source |
| Zhang (2016) | Source |
hi, I am new so please bear with me. This is a brilliant research but I am struggling to get a 1,000bar in this BOTEC calucation. I assume a DALY is valued at $50,000 - and only manage to get to 100bar. What am I missing here pls?
I tam taking DALY value ($50,000) Â x Annual air pullution DALY Cost (74.4mm)Â x Improvement per year (0.06%) = $2.1bn, which is 100x of $20mm spending per year
It seems that footnotes got lost when the article was copied to the forum.
From the original article (scroll to the bottom and expand footnotes)