Residential energy use emissions dominate health impacts from exposure to ambient particulate matter in India

Outdoor air pollution in India is not only an urban problem

Urban outdoor air pollution in the developing world, mostly due to particulate matter with diameters smaller than 2.5 µm (PM2.5), has been highlighted in recent years. It leads to millions of premature deaths. Outdoor air pollution has also been viewed mostly as an urban problem. We use satellite-derived demarcations to parse India's population into urban and nonurban regions, which agrees with the census data. We also use the satellite-derived surface PM2.5 levels to calculate the health impacts in the urban and nonurban regions. We show that outdoor air pollution is just as severe in nonurban regions as in the urban regions of India, with implications to monitoring, regulations, health, and policy.

Cross-validation of biomonitoring methods for polycyclic aromatic hydrocarbon metabolites in human urine: Results from the formative phase of the Household Air Pollution Intervention Network (HAPIN) trial in India

The Household Air Pollution Intervention Network (HAPIN) trial is evaluating health benefits of a liquefied petroleum gas (LPG) stove intervention in biomass cook-fuel using homes (n = 3200) in four low-and middle-income countries (LMICs) that include Peru, Guatemala, Rwanda and India. Longitudinal urine samples (n = 6000) collected from enrolled pregnant women, infants and older women will be analyzed for biomarkers associated with exposure and health outcomes. We report results from cross-validation of a lower cost high-performance liquid chromatography with fluorescence detection (HPLC-FLD) method with a higher resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the measurement of 1-hydroxypyrene (1PYR) and 2-naphthol (2NAP). Twenty-five split urine samples were analyzed by HPLC-FLD method at the India trial site in Chennai, India and by LC-MSMS method at the trial wide Biomarker Coordinating Center, Emory University, USA. The limits of detection (LOD) for the HPLC-FLD method were 0.02 ng/mL and 0.07 ng/mL for 2NAP and 1PYR, respectively. Bland-Altman analysis estimated a bias of 2.98 ng/ml for 2NAP (95% CI: -5.22, -0.75) and 0.09 ng/mL for 1PYR (95% CI: -0.02, 0.21) with HPLC-FLD levels being lower than LC-MSMS levels at higher concentrations. Analyses of additional urine samples (n = 119) collected during the formative phase of the HAPIN trial in India, showed 2NAP and 1PYR levels to be consistently above the limit of quantification (LOQ) and demonstrated the applicability of the method. The HPLC-FLD method can serve as a cost-effective and reliable analytical method to measure 2NAP and 1PYR in human urine in LMICs, within and beyond the HAPIN trial.

Systems Science Approaches for Global Environmental Health Research: Enhancing Intervention Design and Implementation for Household Air Pollution (HAP) and Water, Sanitation, and Hygiene (WASH) Programs

BACKGROUND

Two of the most important causes of global disease fall in the realm of environmental health: household air pollution (HAP) and poor water, sanitation, and hygiene (WASH) conditions. Interventions, such as clean cookstoves, household water treatment, and improved sanitation facilities, have great potential to yield reductions in disease burden. However, in recent trials and implementation efforts, interventions to improve HAP and WASH conditions have shown few of the desired health gains, raising fundamental questions about current approaches.

OBJECTIVES

We describe how the failure to consider the complex systems that characterize diverse real-world conditions may doom promising new approaches prematurely. We provide examples of the application of systems approaches, including system dynamics, network analysis, and agent-based modeling, to the global environmental health priorities of HAP and WASH research and programs. Finally, we offer suggestions on how to approach systems science.

METHODS

Systems science applied to environmental health can address major challenges by a) enhancing understanding of existing system structures and behaviors that accelerate or impede aims; b) developing understanding and agreement on a problem among stakeholders; and c) guiding intervention and policy formulation. When employed in participatory processes that engage study populations, policy makers, and implementers, systems science helps ensure that research is responsive to local priorities and reflect real-world conditions. Systems approaches also help interpret unexpected outcomes by revealing emergent properties of the system due to interactions among variables, yielding complex behaviors and sometimes counterintuitive results.

DISCUSSION

Systems science offers powerful and underused tools to accelerate our ability to identify barriers and facilitators to success in environmental health interventions. This approach is especially useful in the context of implementation research because it explicitly accounts for the interaction of processes occurring at multiple scales, across social and environmental dimensions, with a particular emphasis on linkages and feedback among these processes. https://doi.org/10.1289/EHP7010.

Particle-induced oxidative damage by indoor size-segregated particulate matter from coal-burning homes in the Xuanwei lung cancer epidemic area, Yunnan Province, China

Size-segregated samples of airborne particulate matter were collected at the coal-burning homes of the Hutou high lung cancer epidemic village and a comparison site Xize village of the Xuanwei County, Yuanan Province, by an Anderson Cascade Impact Sampler in winter and spring to study the toxicological characteristics of different-sized particles. The DNA damage caused by the water-soluble fractions of these size-segregated particles was analyzed by the plasmid scission assay, and the trace element compositions were determined by Inductively Coupled Plasma Mass Spectrometry. The DNA damage rate from the airborne particles in the high lung cancer incidence area was higher than that in Xize village. The different-sized particles have highly varying DNA damage rates, with the values being greater in the small size range than in the large size range. The particle-induced DNA damage rates had a significantly positive correlation with total water-soluble trace elements. Further analysis of the individual elements indicated that the water-soluble heavy metals Zn, Cu, Cd, Rb, Cs, and Sb had a positive correlation with the particle-induced DNA damage, implying that these water-soluble heavy metals played an important role in the DNA damage. The Sr had a negative correlation with the particle-induced DNA damage, suggesting that the water-soluble Sr might counter DNA damage. The mass concentrations of the total and individual water-soluble trace elements were mostly enriched in the small particle size ranges, thus implying the indoor airborne particles in the small size ranges would have a higher health risk.

Tradeoffs between air pollution mitigation and meteorological response in India

To curb the staggering health burden attributed to air pollution, the sustainable solution for India would be to reduce emissions in future. Here we project ambient fine particulate matter (PM_2.5) exposure in India for the year 2030 under two contrasting air pollution emission pathways for two different climate scenarios based on Representative Concentration Pathways (RCP4.5 and RCP8.5). All-India average PM_2.5 is expected to increase from 41.4 ± 26.5 μg m^-3 in 2010 to 61.1 ± 40.8 and 58.2 ± 37.5 μg m^-3 in 2030 under RCP8.5 and RCP4.5 scenarios, respectively if India follows the current legislation (baseline) emission pathway. In contrast, ambient PM_2.5 in 2030 would be 40.2 ± 27.5 (for RCP8.5) and 39.2 ± 25.4 (for RCP4.5) μg m^-3 following the short-lived climate pollutant (SLCP) mitigation emission pathway. We find that the lower PM_2.5 in the mitigation pathway (34.2% and 32.6%, respectively for RCP8.5 and RCP4.5 relative to the baseline emission pathway) would come at a cost of 0.3-0.5 °C additional warming due to the direct impact of aerosols. The premature mortality burden attributable to ambient PM_2.5 exposure is expected to rise from 2010 to 2030, but 381,790 (5-95% confidence interval, CI 275,620-514,600) deaths can be averted following the mitigation emission pathway relative to the baseline emission pathway. Therefore, we conclude that given the expected large health benefit, the mitigation emission pathway is a reasonable tradeoff for India despite the meteorological response. However, India needs to act more aggressively as the World Health Organization (WHO) annual air quality guideline (10 µg m^-3) would remain far off.

Combining Biomass Gasification and Solid Oxid Fuel Cell for Heat and Power Generation: An Early-Stage Life Cycle Assessment

Biomass-fueled combined heat and power systems (CHPs) can potentially offer environmental benefits compared to conventional separate production technologies. This study presents the first environmental life cycle assessment (LCA) of a novel high-efficiency bio-based power (HBP) technology, which combines biomass gasification with a 199 kW solid oxide fuel cell (SOFC) to produce heat and electricity. The aim is to identify the main sources of environmental impacts and to assess the potential environmental performance compared to benchmark technologies. The use of various biomass fuels and alternative allocation methods were scrutinized. The LCA results reveal that most of the environmental impacts of the energy supplied with the HBP technology are caused by the production of the biomass fuel. This contribution is higher for pelletized than for chipped biomass. Overall, HBP technology shows better environmental performance than heat from natural gas and electricity from the German/European grid. When comparing the HBP technology with the biomass-fueled ORC technology, the former offers significant benefits in terms of particulate matter (about 22 times lower), photochemical ozone formation (11 times lower), acidification (8 times lower) and terrestrial eutrophication (about 26 times lower). The environmental performance was not affected by the allocation parameter (exergy or economic) used. However, the tested substitution approaches showed to be inadequate to model multiple environmental impacts of CHP plants under the investigated context and goal.

On the widespread enhancement in fine particulate matter across the Indo-Gangetic Plain towards winter

Fine particulate matter (PM2.5, aerodynamic diameter ≤2.5 µm) impacts the climate, reduces visibility and severely influences human health. The Indo-Gangetic Plain (IGP), home to about one-seventh of the world's total population and a hotspot of aerosol loading, observes strong enhancements in the PM2.5 concentrations towards winter. We performed high-resolution (12 km × 12 km) atmospheric chemical transport modeling (WRF-Chem) for the post-monsoon to winter transition to unravel the underlying dynamics and influences of regional emissions over the region. Model, capturing the observed variations to an extent, reveals that the spatial distribution of PM2.5 having patches of enhanced concentrations (≥100 µgm-3) during post-monsoon, evolves dramatically into a widespread enhancement across the IGP region during winter. A sensitivity simulation, supported by satellite observations of fires, shows that biomass-burning emissions over the northwest IGP play a crucial role during post-monsoon. Whereas, in contrast, towards winter, a large-scale decline in the air temperature, significantly shallower atmospheric boundary layer, and weaker winds lead to stagnant conditions (ventilation coefficient lower by a factor of ~4) thereby confining the anthropogenic influences closer to the surface. Such changes in the controlling processes from post-monsoon to winter transition profoundly affect the composition of the fine aerosols over the IGP region. The study highlights the need to critically consider the distinct meteorological processes of west-to-east IGP and changes in dominant sources from post-monsoon to winter in the formulation of future pollution mitigation policies.

Forecasting Air Quality in Taiwan by Using Machine Learning

This study proposes a gradient-boosting-based machine learning approach for predicting the PM_2.5 concentration in Taiwan. The proposed mechanism is evaluated on a large-scale database built by the Environmental Protection Administration, and Central Weather Bureau, Taiwan, which includes data from 77 air monitoring stations and 580 weather stations performing hourly measurements over 1 year. By learning from past records of PM_2.5 and neighboring weather stations’ climatic information, the forecasting model works well for 24-h prediction at most air stations. This study also investigates the geographical and meteorological divergence for the forecasting results of seven regional monitoring areas. We also compare the prediction performance between Taiwan, Taipei, and London; analyze the impact of industrial pollution; and propose an enhanced version of the prediction model to improve the prediction accuracy. The results indicate that Taipei and London have similar prediction results because these two cities have similar topography (basin) and are financial centers without domestic pollution sources. The results also suggest that after considering industrial impacts by incorporating additional features from the Taichung and Thong-Siau power plants, the proposed method achieves significant improvement in the coefficient of determination (R²) from 0.58 to 0.71. Moreover, for Taichung City the root-mean-square error decreases from 8.56 for the conventional approach to 7.06 for the proposed method.

Longitudinal survey of microbiome associated with particulate matter in a megacity

BACKGROUND

While the physical and chemical properties of airborne particulate matter (PM) have been extensively studied, their associated microbiome remains largely unexplored. Here, we performed a longitudinal metagenomic survey of 106 samples of airborne PM_2.5 and PM₁₀ in Beijing over a period of 6 months in 2012 and 2013, including those from several historically severe smog events.

RESULTS

We observed that the microbiome composition and functional potential were conserved between PM_2.5 and PM₁₀, although considerable temporal variations existed. Among the airborne microorganisms, Propionibacterium acnes, Escherichia coli, Acinetobacter lwoffii, Lactobacillus amylovorus, and Lactobacillus reuteri dominated, along with several viral species. We further identified an extensive repertoire of genes involved in antibiotic resistance and detoxification, including transporters, transpeptidases, and thioredoxins. Sample stratification based on Air Quality Index (AQI) demonstrated that many microbial species, including those associated with human, dog, and mouse feces, exhibit AQI-dependent incidence dynamics. The phylogenetic and functional diversity of air microbiome is comparable to those of soil and water environments, as its composition likely derives from a wide variety of sources.

CONCLUSIONS

Airborne particulate matter accommodates rich and dynamic microbial communities, including a range of microbial elements that are associated with potential health consequences.

In situ-Like Aerosol Inhalation Exposure for Cytotoxicity Assessment Using Airway-on-Chips Platforms

Lung exposure to inhaled particulate matter (PM) is known to injure the airway epithelium via inflammation, a phenomenon linked to increased levels of global morbidity and mortality. To evaluate physiological outcomes following PM exposure and concurrently circumvent the use of animal experiments, in vitro approaches have typically relied on traditional assays with plates or well inserts. Yet, these manifest drawbacks including the inability to capture physiological inhalation conditions and aerosol deposition characteristics relative to in vivo human conditions. Here, we present a novel airway-on-chip exposure platform that emulates the epithelium of human bronchial airways with critical cellular barrier functions at an air-liquid interface (ALI). As a proof-of-concept for in vitro lung cytotoxicity testing, we recapitulate a well-characterized cell apoptosis pathway, induced through exposure to 2 μm airborne particles coated with αVR1 antibody that leads to significant loss in cell viability across the recapitulated airway epithelium. Notably, our in vitro inhalation assays enable simultaneous aerosol exposure across multiple airway chips integrated within a larger bronchial airway tree model, under physiological respiratory airflow conditions. Our findings underscore in situ-like aerosol deposition outcomes where patterns depend on respiratory flows across the airway tree geometry and gravitational orientation, as corroborated by concurrent numerical simulations. Our airway-on-chips not only highlight the prospect of realistic in vitro exposure assays in recapitulating characteristic local in vivo deposition outcomes, such platforms open opportunities toward advanced in vitro exposure assays for preclinical cytotoxicity and drug screening applications.

Electrospinning of Metal-Organic Frameworks for Energy and Environmental Applications

Herein, recent developments of metal-organic frameworks (MOFs) structured into nanofibers by electrospinning are summarized, including the fabrication, post-treatment via pyrolysis, properties, and use of the resulting MOF nanofiber architectures. The fabrication and post-treatment of the MOF nanofiber architectures are described systematically by two routes: i) the direct electrospinning of MOF-polymer nanofiber composites, and ii) the surface decoration of nanofiber structures with MOFs. The unique properties and performance of the different types of MOF nanofibers and their derivatives are explained in respect to their use in energy and environmental applications, including air filtration, water treatment, gas storage and separation, electrochemical energy conversion and storage, and heterogeneous catalysis. Finally, challenges with the fabrication of MOF nanofibers, limitations for their use, and trends for future developments are presented.

Improving and Expanding Estimates of the Global Burden of Disease Due to Environmental Health Risk Factors

BACKGROUND

The Global Burden of Disease (GBD) study, coordinated by the Institute for Health Metrics and Evaluation (IHME), produces influential, data-driven estimates of the burden of disease and premature death due to major risk factors. Expanded quantification of disease due to environmental health (EH) risk factors, including climate change, will enhance accuracy of GBD estimates, which will contribute to developing cost-effective policies that promote prevention and achieving Sustainable Development Goals.

OBJECTIVES

We review key aspects of the GBD for the EH community and introduce the Global Burden of Disease-Pollution and Health Initiative (GBD-PHI), which aims to work with IHME and the GBD study to improve estimates of disease burden attributable to EH risk factors and to develop an innovative approach to estimating climate-related disease burden-both current and projected.

METHODS

We discuss strategies for improving GBD quantification of specific EH risk factors, including air pollution, lead, and climate change. We highlight key methodological challenges, including new EH risk factors, notably evidence rating and global exposure assessment.

DISCUSSION

A number of issues present challenges to the scope and accuracy of current GBD estimates for EH risk factors. For air pollution, minimal data exist on the exposure-risk relationships associated with high levels of pollution; epidemiological studies in high pollution regions should be a research priority. For lead, the GBD's current methods do not fully account for lead's impact on neurodevelopment; innovative methods to account for subclinical effects are needed. Decisions on inclusion of additional EH risk-outcome pairs need to be guided by findings of systematic reviews, the size of exposed populations, feasibility of global exposure estimates, and predicted trends in exposures and diseases. Neurotoxicants, endocrine-disrupting chemicals, and climate-related factors should be high priorities for incorporation into upcoming iterations of the GBD study. Enhancing the scope and methods will improve the GBD's estimates and better guide prevention policy. https://doi.org/10.1289/EHP5496.

Impacts of air pollutants from rural Chinese households under the rapid residential energy transition

Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM2.5, avoiding 130,000 (90,000-160,000) premature deaths associated with PM2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m2 in 1992 to 0.031 ± 0.008 W/m2 in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 μg/m3 to population-weighted PM2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent.

Indian annual ambient air quality standard is achievable by completely mitigating emissions from household sources

Exposures to ambient and household fine-particulate matter (PM2.5) together are among the largest single causes of premature mortality in India according to the Global Burden of Disease Studies (GBD). Several recent investigations have estimated that household emissions are the largest contributor to ambient PM2.5 exposure in the country. Using satellite-derived district-level PM2.5 exposure and an Eulerian photochemical dispersion model CAMx (Comprehensive Air Quality Model with Extensions), we estimate the benefit in terms of population exposure of mitigating household sources--biomass for cooking, space- and water-heating, and kerosene for lighting. Complete mitigation of emissions from only these household sources would reduce India-wide, population-weighted average annual ambient PM2.5 exposure by 17.5, 11.9, and 1.3%, respectively. Using GBD methods, this translates into reductions in Indian premature mortality of 6.6, 5.5, and 0.6%. If PM2.5 emissions from all household sources are completely mitigated, 103 (of 597) additional districts (187 million people) would meet the Indian annual air-quality standard (40 μg m-3) compared with baseline (2015) when 246 districts (398 million people) met the standard. At 38 μg m-3, after complete mitigation of household sources, compared with 55.1 μg m-3 at baseline, the mean annual national population-based concentration would meet the standard, although highly polluted areas, such as Delhi, would remain out of attainment. Our results support expansion of programs designed to promote clean household fuels and rural electrification to achieve improved air quality at regional scales, which also has substantial additional health benefits from directly reducing household air pollution exposures.

Modeling the Impact of an Indoor Air Filter on Air Pollution Exposure Reduction and Associated Mortality in Urban Delhi Household

Indoor exposure to fine particulate matter (PM_2.5) is a prominent health concern. However, few studies have examined the effectiveness of long-term use of indoor air filters for reduction of PM_2.5 exposure and associated decrease in adverse health impacts in urban India. We conducted 20 simulations of yearlong personal exposure to PM_2.5 in urban Delhi using the National Institute of Standards and Technology's CONTAM program (NIST, Gaithersburg, MD, USA). Simulation scenarios were developed to examine different air filter efficiencies, use schedules, and the influence of a smoker at home. We quantified associated mortality reductions with Household Air Pollution Intervention Tool (HAPIT, University of California, Berkeley, CA, USA). Without an air filter, we estimated an annual mean PM_2.5 personal exposure of 103 µg/m³ (95% Confidence Interval (CI): 93, 112) and 137 µg/m³ (95% CI: 125, 149) for households without and with a smoker, respectively. All day use of a high-efficiency particle air (HEPA) filter would reduce personal PM_2.5 exposure to 29 µg/m³ and 30 µg/m³, respectively. The reduced personal PM_2.5 exposure from air filter use is associated with 8-37% reduction in mortality attributable to PM_2.5 pollution in Delhi. The findings of this study indicate that air filter may provide significant improvements in indoor air quality and result in health benefits.

Spatial-Temporal Evolution of PM2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014⁻2017

PM_2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM_2.5 data in 338 Chinese cities during 2014–2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the temporal and spatial characteristics of PM_2.5 patterns and a spatial econometric model to quantify the socio-economic driving factors of PM_2.5 concentration changes. The results are as follows: (1) The annual average value of PM_2.5 concentration decreased year by year and the monthly average showed a U-shaped curve from January to December. The daily mean value of PM_2.5 concentration had the characteristics of pulse-type fluctuation and the hourly variation presented a bimodal curve. (2) During 2014–2017, the overall PM_2.5 pollution reduced significantly, but that of more than two-thirds of cities still exceeded the standard value (35 μg/m³) regulated by Chinese government. PM_2.5 pollution patterns showed high values in central and eastern Chinese cities and low values in peripheral areas, with the distinction evident along the same line that delineates China’s uneven population distribution. (3) Population agglomeration, industrial development, foreign investment, transportation, and pollution emissions contributed to the increase of PM_2.5 concentration. Urban population density contributed most significantly while economic development and technological progress reduced PM_2.5 concentration. The results also suggest that China in general remains a “pollution shelter” for foreign-funded enterprises.

Premature Mortality Due to PM2.5 Over India: Effect of Atmospheric Transport and Anthropogenic Emissions

The annual premature mortality in India attributed to exposure to ambient particulate matter (PM2.5) exceeds 1 million (Cohen et al., 2017, https://doi.org/10.1016/S0140-6736(17)30505-6). Studies have estimated sector-specific premature mortality from ambient PM2.5 exposure in India and shown residential energy use is the dominant contributing sector. In this study, we estimate the contribution of PM2.5 and premature mortality from six regions of India in 2012 using the global chemical-transport model. We calculate how premature mortality in India is determined by the transport of pollution from different regions. Of the estimated 1.1 million annual premature deaths from PM2.5 in India, about ~60% was from anthropogenic pollutants emitted from within the region in which premature mortality occurred, ~19% was from transport of anthropogenic pollutants between different regions within India, ~16% was due to anthropogenic pollutants emitted outside of India, and ~4% was associated with natural PM2.5 sources. The emissions from Indo Gangetic Plain contributed to ~46% of total premature mortality over India, followed by Southern India (13%). Indo Gangetic Plain also contributed (~8%) to the most premature mortalities in other regions of India through transport. More than 50% of the premature mortality in Northern, Eastern, Western, and Central India was due to transport of PM2.5 from regions outside of these individual regions. Our results indicate that reduction in anthropogenic emissions over India, as well as its neighboring regions, will be required to reduce the health impact of ambient PM2.5 in India.

The impact of air pollution on deaths, disease burden, and life expectancy across the states of India: the Global Burden of Disease Study 2017

BACKGROUND

Air pollution is a major planetary health risk, with India estimated to have some of the worst levels globally. To inform action at subnational levels in India, we estimated the exposure to air pollution and its impact on deaths, disease burden, and life expectancy in every state of India in 2017.

METHODS

We estimated exposure to air pollution, including ambient particulate matter pollution, defined as the annual average gridded concentration of PM2.5, and household air pollution, defined as percentage of households using solid cooking fuels and the corresponding exposure to PM2.5, across the states of India using accessible data from multiple sources as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. The states were categorised into three Socio-demographic Index (SDI) levels as calculated by GBD 2017 on the basis of lag-distributed per-capita income, mean education in people aged 15 years or older, and total fertility rate in people younger than 25 years. We estimated deaths and disability-adjusted life-years (DALYs) attributable to air pollution exposure, on the basis of exposure-response relationships from the published literature, as assessed in GBD 2017; the proportion of total global air pollution DALYs in India; and what the life expectancy would have been in each state of India if air pollution levels had been less than the minimum level causing health loss.

FINDINGS

The annual population-weighted mean exposure to ambient particulate matter PM2·5 in India was 89·9 μg/m3 (95% uncertainty interval [UI] 67·0-112·0) in 2017. Most states, and 76·8% of the population of India, were exposed to annual population-weighted mean PM2·5 greater than 40 μg/m3, which is the limit recommended by the National Ambient Air Quality Standards in India. Delhi had the highest annual population-weighted mean PM2·5 in 2017, followed by Uttar Pradesh, Bihar, and Haryana in north India, all with mean values greater than 125 μg/m3. The proportion of population using solid fuels in India was 55·5% (54·8-56·2) in 2017, which exceeded 75% in the low SDI states of Bihar, Jharkhand, and Odisha. 1·24 million (1·09-1·39) deaths in India in 2017, which were 12·5% of the total deaths, were attributable to air pollution, including 0·67 million (0·55-0·79) from ambient particulate matter pollution and 0·48 million (0·39-0·58) from household air pollution. Of these deaths attributable to air pollution, 51·4% were in people younger than 70 years. India contributed 18·1% of the global population but had 26·2% of the global air pollution DALYs in 2017. The ambient particulate matter pollution DALY rate was highest in the north Indian states of Uttar Pradesh, Haryana, Delhi, Punjab, and Rajasthan, spread across the three SDI state groups, and the household air pollution DALY rate was highest in the low SDI states of Chhattisgarh, Rajasthan, Madhya Pradesh, and Assam in north and northeast India. We estimated that if the air pollution level in India were less than the minimum causing health loss, the average life expectancy in 2017 would have been higher by 1·7 years (1·6-1·9), with this increase exceeding 2 years in the north Indian states of Rajasthan, Uttar Pradesh, and Haryana.

INTERPRETATION

India has disproportionately high mortality and disease burden due to air pollution. This burden is generally highest in the low SDI states of north India. Reducing the substantial avoidable deaths and disease burden from this major environmental risk is dependent on rapid deployment of effective multisectoral policies throughout India that are commensurate with the magnitude of air pollution in each state.

FUNDING

Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.

Current and Future Disease Burden From Ambient Ozone Exposure in India

Long-term ambient ozone (O₃) exposure is a risk factor for human health. We estimate the source-specific disease burden associated with long-term O₃ exposure in India at high spatial resolution using updated risk functions from the American Cancer Society Cancer Prevention Study II. We estimate 374,000 (95UI: 140,000-554,000) annual premature mortalities using the updated risk function in India in 2015, 200% larger than estimates using the earlier American Cancer Society Cancer Prevention Study II risk function. We find that land transport emissions dominate the source contribution to this disease burden (35%), followed by emissions from power generation (23%). With no change in emissions by 2050, we estimate 1,126,000 (95UI: 421,000-1,667,000) annual premature mortalities, an increase of 200% relative to 2015 due to population aging and growth increasing the number of people susceptible to air pollution. We find that the International Energy Agency New Policy Scenario provides small changes (+1%) to this increasing disease burden from the demographic transition. Under the International Energy Agency Clean Air Scenario we estimate 791,000 (95UI: 202,000-1,336,000) annual premature mortalities in 2050, avoiding 335,000 annual premature mortalities (45% of the increase) compared to the scenario of no emission change. Our study highlights that critical public health benefits are possible with stringent emission reductions, despite population growth and aging increasing the attributable disease burden from O₃ exposure even under such strong emission reductions. The disease burden attributable to ambient fine particulate matter exposure dominates that from ambient O₃ exposure in the present day, while in the future, they may be similar in magnitude.

Population-weighted exposure to PM2.5 pollution in China: An integrated approach

Fine particulate matter air pollution (PM_2.5) is a major risk factor for premature death globally. Studies of the PM_2.5 health burden usually treat exposure to ambient air pollution (AAP) and household air pollution from solid fuels (HAP) as separate risk factors. AAP and HAP can, however, be closely interrelated. Taking as the starting point that the total exposure to PM_2.5 is what matters for health, and recognizing the curvilinear form of exposure-response functions for important health effects, we develop a method for estimating the total annual mean population-weighted personal exposure, denoted integrated population-weighted exposure (IPWE). To establish the IPWE in China, we used recent emission inventories, Chemical Transport Models, China Census data on population and residential fuel use, and estimates of the PM_2.5 exposure among solid fuel users. We found an IPWE of 151 [123-179] μg/m³, of which 62-74% was attributable to residential solid fuels through HAP exposure and the residential sector emissions' contribution to AAP. We found large disparities in the PM_2.5 exposure burden, with an estimated IPWE in rural populations nearly twice the level in urban populations. Using the IPWE metric, we estimated that 1.15 [1.09-1.19] million premature deaths were attributable to PM_2.5 exposure annually in the period 2010-2013. Using the same data set, but calculating premature deaths from AAP and HAP in isolation, the estimated number was nearly 50% higher. The IPWE metric enables integration across AAP and HAP in policy analyses and could mitigate the concern of a potential double counting of the health burden that may arise from treating AAP and HAP as separate health risk factors.

LPG as a Clean Cooking Fuel: Adoption, Use, and Impact in Rural India

Liquefied petroleum gas (LPG) is by far the most popular clean cooking fuel in rural India, but how rural households use it remains poorly understood. Using the 2014-2015 ACCESS survey with over 8,500 households from six energy-poor Indian states, we offer a broad but detailed survey of LPG use in rural India. We find that (i) fuel costs are a critical obstacle to widespread adoption, (ii) fuel stacking is the prevailing norm as few households stop using firewood when adopting LPG, and (iii) both users and non-users have highly positive views of LPG as a convenient and clean cooking fuel. These findings show that expanding LPG use offers great promise in rural India, but affordability prevents a complete transition from traditional biomass to clean cooking fuels.

Global Sources of Fine Particulate Matter: Interpretation of PM2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model

Exposure to ambient fine particulate matter (PM_2.5) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM_2.5 sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM_2.5 to interpret globally dispersed PM_2.5 mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM_2.5 composition varies substantially for secondary inorganic aerosols (2.4-19.7 μg/m³), mineral dust (1.9-14.7 μg/m³), residual/organic matter (2.1-40.2 μg/m³), and black carbon (1.0-7.3 μg/m³). Interpretation of these measurements with the GEOS-Chem model yields insight into sources affecting each site. Globally, combustion sectors such as residential energy use (7.9 μg/m³), industry (6.5 μg/m³), and power generation (5.6 μg/m³) are leading sources of outdoor global population-weighted PM_2.5 concentrations. Global population-weighted organic mass is driven by the residential energy sector (64%) whereas population-weighted secondary inorganic concentrations arise primarily from industry (33%) and power generation (32%). Simulation-measurement biases for ammonium nitrate and dust identify uncertainty in agricultural and crustal sources. Interpretation of initial PM_2.5 mass and composition measurements from SPARTAN with the GEOS-Chem model constrained by satellite-based PM_2.5 provides insight into sources and processes that influence the global spatial variation in PM_2.5 composition.

Stringent Emission Control Policies Can Provide Large Improvements in Air Quality and Public Health in India

Exposure to high concentrations of ambient fine particulate matter (PM2.5) is a leading risk factor for public health in India causing a large burden of disease. Business-as-usual economic and industrial growth in India is predicted to increase emissions, worsen air quality, and increase the associated disease burden in future decades. Here we use a high-resolution online-coupled model to estimate the impacts of different air pollution control pathways on ambient PM2.5 concentrations and human health in India. We find that with no change in emissions, the disease burden from exposure to ambient PM2.5 in 2050 will increase by 75% relative to 2015, due to population aging and growth increasing the number of people susceptible to air pollution. We estimate that the International Energy Agencies New Policy Scenario (NPS) and Clean Air Scenario (CAS) in 2050 can reduce ambient PM2.5 concentrations below 2015 levels by 9% and 68%, respectively, offsetting 61,000 and 610,000 premature mortalities a year, which is 9% and 91% of the projected increase in premature mortalities due to population growth and aging. Throughout India, the CAS stands out as the most effective scenario to reduce ambient PM2.5 concentrations and the associated disease burden, reducing the 2050 mortality rate per 100,000 below 2015 control levels by 15%. However, even under such stringent emission control policies, population growth and aging results in premature mortality estimates from exposure to particulate air pollution to increase by 7% compared to 2015, highlighting the challenge facing efforts to improve public health in India.