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

Effectiveness of respiratory face masks in reducing acute PM2.5 pollution exposure during peak pollution period in Delhi

The cities of North India, such as Delhi, face a significant public health threat from severe air pollution. Between October 2021 and January 2022, 79 % of Delhi's daily average PM2.5 (Particulate matter with an aerodynamic diameter ≤ 2.5 μm) values exceeded 100 μg/m3 (the permissible level being 60 μg/m3 as per Indian standards). In response to this acute exposure, using Respiratory Face Masks (RFMs) is a cost-effective solution to reduce immediate health risks while policymakers develop long-term emission control plans. Our research focuses on the health and economic benefits of using RFMs to prevent acute exposure to PM2.5 pollution in Delhi for different age groups. Our findings indicate that, among the fifty chosen RFMs, M50 has greatest potential to prevent short-term excess mortality (908 in age ranges 5-44), followed by M49 (745) and M48 (568). These RFMs resulted in estimated economic benefits of 500.6 (46 %), 411.1 (37 %), and 313.4 (29 %) million Indian Rupee (INR), respectively during October-January 2021-22. By wearing RFMs such as M50, M49, and M48 during episodes of bad air quality, it is estimated that 13 % of short-term excess mortality and associated costs could be saved if at least 30 % of Delhi residents followed an alert issued by an operational Air Quality Early Warning System (AQEWS) developed by the Ministry of Earth Sciences. Our research suggests that RFMs can notably decrease health and economic burdens amid peak PM2.5 pollution in post-monsoon and winter seasons until long-term emission reduction strategies are adopted. It is suggested that an advisory may be crafted in collaboration with statutory bodies and should be disseminated to assist the vulnerable population in using RFMs during winter. The analysis presented in this research is purely science based and outcomes of study are in no way to be construed as endorsement of product.

Hotspot driven air pollution during crop residue burning season in the Indo-Gangetic Plain, India

Intensive crop residue burning (CRB) in northern India triggers severe air pollution episodes over the Indo-Gangetic Plain (IGP) each year during October and November. We have quantified the contribution of hotspot districts (HSDs) and total CRB to poor air quality over the IGP. Initially, we investigated the spatiotemporal distribution of CRB fire within the domain and pinpointed five HSD in each Punjab and Haryana. Furthermore, we have simulated air quality and quantified the impact of CRB using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), incorporating recent anthropogenic emissions (EDGAR v5) and biomass burning emissions (FINN v2.4) inventories, along with MOZART-MOSAIC chemistry. The key finding is that HSDs contributed ∼80% and ∼50% of the total fire counts in Haryana and Punjab, respectively. The model effectively captured observed PM₂.₅ concentrations, with a normalized mean bias (NMB) below 0.2 and R-squared (R2) exceeding 0.65 at the majority of validation sites. However, some discrepancies were observed at a few sites in Delhi, Punjab, Haryana, and West Bengal. The National Capital Region experienced the highest PM₂.₅ concentrations, followed by Punjab, Haryana, Uttar Pradesh, Bihar, and West Bengal. Moreover, HSDs were responsible for about 70% of the total increase in CRB-induced PM₂.₅ in the western, central, and eastern cities, and around 50% in the northern cities. By eliminating CRB emissions across the domain, we could potentially save approximately 18,000 lives annually. Policymakers, scientists, and institutions can leverage the framework to address air pollution at national and global scales by targeting source-specific hotspots. This approach, coupled with appropriate technological and financial solutions, can contribute to achieving climate change and sustainable development goals.

Local incomplete combustion emissions define the PM2.5 oxidative potential in Northern India

The oxidative potential (OP) of particulate matter (PM) is a major driver of PM-associated health effects. In India, the emission sources defining PM-OP, and their local/regional nature, are yet to be established. Here, to address this gap we determine the geographical origin, sources of PM, and its OP at five Indo-Gangetic Plain sites inside and outside Delhi. Our findings reveal that although uniformly high PM concentrations are recorded across the entire region, local emission sources and formation processes dominate PM pollution. Specifically, ammonium chloride, and organic aerosols (OA) from traffic exhaust, residential heating, and oxidation of unsaturated vapors from fossil fuels are the dominant PM sources inside Delhi. Ammonium sulfate and nitrate, and secondary OA from biomass burning vapors, are produced outside Delhi. Nevertheless, PM-OP is overwhelmingly driven by OA from incomplete combustion of biomass and fossil fuels, including traffic. These findings suggest that addressing local inefficient combustion processes can effectively mitigate PM health exposure in northern India.

Global economic structure transition boosts PM2.5-related human health impact in Belt and Road Initiative

The Belt and Road Initiative (BRI) is an open platform for international cooperation proposed by China to promote common global development and prosperity. The BRI can promote the optimal allocation of resources and promote in-depth cooperation in international trade. Meanwhile, it can establish a green supply chain cooperation network to help BRI countries achieve green transformation. BRI has made a notable contribution to the rapid growth of cross-border trade. However, it has also brought environmental impacts. Given that little attention has been paid to the trade-embodied particulate matter 2.5 related human health impacts (PM2.5-HHI) throughout the BRI, this study accounts for and traces the embodied PM2.5-HHI flows between the BRI countries and non-Belt and Road Initiative (non-BRI) countries. Moreover, this study also uncovers the critical socioeconomic drivers of PM2.5-HHI changes in BRI countries during 1990-2015, based on the multi-regional input-output based structural decomposition analysis (MRIO-SDA). Results show that, firstly, BRI countries had significantly increased their economic added value by exporting products to the non-BRI countries. They also have brought PM2.5-HHI to themselves. Secondly, the final demand of BRI countries was the largest potential driving force of PM2.5-HHI of BRI countries. Thirdly, the emission intensity change of BRI is the key socioeconomic factor for reducing PM2.5-HHI. While per capita final demand level change of BRI and production structure change of non-BRI are the key socioeconomic factors for increasing PM2.5-HHI. The study's findings on the one hand can help reduce the PM2.5-HHI and impacts of environmental pollution of BRI countries from a global perspective by providing scientific support. On the other hand, they can help provide relevant policy recommendations for the green transformation of BRI and the construction of green BRI.

A district-level emission inventory of anthropogenic PM2.5 from the primary sources over the Indian Indo Gangetic Plain: Identification of the emission hotspots

A district-wise emission inventory was made for the states and union territories (UTs) of the Indian Indo-Gangetic Plain for the base year of 2018 to estimate the emissions of PM2.5 from various sectors. In addition to conventional sectors, emissions from road dust, fossil-fuelled irrigation pumps, and construction dust were also taken into account. Total primary anthropogenic PM2.5 emission was estimated to be 3157.3 Gg (or kilo-tones) for the year 2018 of which 32 % originated from the industrial sector, 27 % from domestic fuel consumption, 23 % from open burning, 14 % from road dust, 2 % from vehicular and 2 % from various unorganized sectors. The highest emissions were observed during the premonsoon (1013 Gg/year) followed by postmonsoon (802Gg/year), winter (788 Gg/year), and lowest during the monsoon (554Gg/year). Among the states and UTs, Uttar Pradesh contributes the most in total emissions (39 %), followed by Punjab (19 %), Bihar (17 %), West Bengal (13 %), Haryana (11 %), Delhi (0.9 %) and Chandigarh (0.1 %). Emission for per capita and for billion-rupee of state gross domestic product (GDP) were the highest for Punjab and Haryana. Results have identified the districts of Punjab (Firozpur, Ludhiana, Jalandhar), scattered pockets of Uttar Pradesh (Sonbhadra, Agra, Varanasi, Kanpur, Lucknow, Prayagraj) and lower Gangetic delta (Gaya, Muzaffarpur, Burdwan, both 24-parganas and Murshidabad) as potent hotspots of cumulative PM2.5 emissions. On the other hand, the districts of Punjab (Faridkot, Mansa, Muktsar, Fatehgarh) were found to be the hotspots for per capita emissions. High emissions were observed from the domestic sector, brick kilns, and micro and small-scale industries, and regulating norms should be more stringent for these sectors. Such a study will be a value add for the policymakers and health experts to assess emission hot spots, pollution simulation, and associated mortality analysis of the region.

Disease burden and health risk to rural communities of northeastern India from indoor cooking-related exposure to parent, oxygenated and alkylated PAHs

Exposure to a total of 51 targeted and non-targeted polycyclic aromatic hydrocarbons (PAHs) and their oxygenated and alkylated derivatives associated with size-segregated aerosol was investigated in rural kitchens using liquefied petroleum gas (LPG), mixed biomass (MB) and firewood (FW) fuels in northeastern India. The averaged PM10-associated parent-, alkylated-, and oxygenated-PAHs concentrations increased notably from LPG (257, 54, and 116 ng m-3) to MB (838, 119, and 272 ng m-3) to FW-using kitchens (2762, 225, and 554 ng m-3), respectively. PAHs were preferentially associated with the PM1 fraction with contributions increasing from 80 % in LPG to 86 % in MB and 90 % in FW-using kitchens, which in turn was dominated by <0.25 μm particles (54-75 % of the total). A clear profile of enrichment of low-molecular weight PAHs in cleaner fuels (LPG) and a contrasting enrichment of high-molecular weight PAHs in biomass-based fuels was noted. The averaged internal dose of Benzo[a]pyrene equivalent was the lowest in the case of LPG (19 ng m-3), followed by MB (161 ng m-3) and the highest in FW users (782 ng m-3). Estimation of incremental lifetime cancer risk (ILCR) from PAH exposure revealed extremely high cancer risk in biomass users (factors of 8-40) compared to LPG. The potential years of life lost (PYLL) and PYLL rate averaged across kitchen categories was higher for lung cancer (PYLL: 10.55 ± 1.04 years; PYLL rate: 204 ± 426) compared to upper respiratory tract cancer (PYLL: 10.02 ± 0.05 years; PYLL rate: 4 ± 7), and the PYLL rates for biomass users were higher by factors of 9-56 as compared to LPG users. These findings stress the need for accelerated governmental intervention to ensure a quick transition from traditional biomass-based fuels to cleaner alternatives for the rural population of northeastern India.

A Gender Differentiated Analysis of Healthy Life Expectancy in South Asia: The Role of Greenhouse Gas Emission

The sluggish progress concerning SDG-9 and SDG 13 has made South Asia an epicentre of household and ambient greenhouse gases emissions. Furthermore, the regional progress concerning attainment of SDG-3 is considerably low. The major research objectives are twofold. First, to explore the impact of GHGs emissions from agriculture, transportation, and manufacturing sector on disaggregated life expectancy. Second, to examine the mitigating impact of renewable energy use, trade integration, and human capital development for practice policy recommendations. These research objectives are realized by employing recently advanced cross-sectional auto regressive distributed lag (CS-ARDL) model on panel data of five South Asian countries such as Bangladesh, India, Pakistan, Nepal, and Sri Lanka from 1990 to 2019. The estimation outcome reveals that the emissions from transportation, manufacturing, and agricultural sectors significantly deteriorate healthy life expectancy of male and female healthy life expectancy in South Asia with different intensity. Especially, we find that long-run impact of GHG is more profound on male healthy life expectancy than female life expectancy. The result further shows that renewable energy and human capital substantially improve healthy life expectancy, whereas the effects of trade integration are insignificant. The finding of moderating variables shows that renewable energy, human capital development, and trade integration have high potential to reduce GHGs emissions. The findings of this study urge South Asia for investments in human capital development and renewable energy along with fostering regional integration to decrease GHG and improve healthy life expectancy.

Differences in particulate matter retention and leaf microstructures of 10 plants in different urban environments in Lanzhou City

Particulate matter (PM) is a major primary environmental air pollutant and poses a threat to human health. Differences in the environment and leaf microstructures of plants will result in varying abilities to retain PM, but the effects of changes in these factors on PM retention are not yet well understood. This study selected 10 plant species in four urban areas (sports field, park, residential green space, and greenway) as the study objects. The amount of retained PM by the different species was measured, and the leaf microstructures were observed. It was found that the environment significantly affected both PM retention and leaf microstructure. The ranking of PM retention in the 10 species in four areas was greenway > residential green space > park > sports field. The ranking of average stomatal width and length was park > sports field > residential green space > greenway, while that of average stomatal density was greenway > residential green space > park > sports field. Different environments affected the length and density of trichomes in the leaves. These changes represented the adaptation of plant species to the growth environment. The stomata and grooves of the leaf surface significantly affected the ability of plants to retain PM. The amount of PM retained by different species varied. In all four urban areas, Prunus × cistena N. E. Hansen ex Koehne (purple leaf sand cherry), Prunus cerasifera Ehrhart f. atropurpurea (Jacq.) Rehd. (cherry plum), Buxus sinica var. parvifolia M. Cheng (common boxwood), and Ligustrum × vicaryi Rehder (golden privet) showed strong PM retention. The results of this study will provide information for planners and urban managers for the selection of plant species.

Health benefits from risk information of air pollution in China

Risk-related information regarding air pollution can help people understand the risk involved and take preventive measures to reduce health loss. However, the health benefits through these protective behaviors and the health threat of information inequality have not been systematically measured. This article reports the health gains and losses caused by the interaction of "air pollution-air pollution information-human", and studies the heterogeneity and impact of this interaction. Based on field investigations and transfer learning algorism, this study compiled the first nationwide city-level risk-related information (ERI) response parameter set in China. Then, we developed a Information-Behavioral Equivalent PM2.5 Exposure Model (I-BEPEM) model to project the health benefits caused by the impact of environmental risk-related information on residents' protective behaviors under different scenarios. The protective behavior led by air pollution risk information reduces 5.7% PM2.5-related premature deaths per year. With a 1% increase in regional ERI reception, PM2.5-related premature mortality decreases by 0.1% on average; If the level of information perception and behavioral protection in all cities is the same as that in Beijing, PM2.5-related premature deaths will decrease by 6.9% annually in China. Further, changing the air quality standard issued by China to the American standard can reduce the overall PM2.5-related premature deaths by 9.9%. Meanwhile, compared with men, other age groups and rural residents, women, older persons, and urban residents are more likely to conceive risk information and adopt protective behaviors to reduce the risk of premature death from air pollution. Air pollution risk information can significantly reduce people's health loss. Changing the real-time air quality monitoring information indicator standard to a more stringent level can quickly and effectively enhance this effect. However, the uneven distribution of this information in regions and populations has resulted in the inequality of health gains and losses.

Systems toxicology of complex wood combustion aerosol reveals gaseous carbonyl compounds as critical constituents

Epidemiological studies identified air pollution as one of the prime causes for human morbidity and mortality, due to harmful effects mainly on the cardiovascular and respiratory systems. Damage to the lung leads to several severe diseases such as fibrosis, chronic obstructive pulmonary disease and cancer. Noxious environmental aerosols are comprised of a gas and particulate phase representing highly complex chemical mixtures composed of myriads of compounds. Although some critical pollutants, foremost particulate matter (PM), could be linked to adverse health effects, a comprehensive understanding of relevant biological mechanisms and detrimental aerosol constituents is still lacking. Here, we employed a systems toxicology approach focusing on wood combustion, an important source for air pollution, and demonstrate a key role of the gas phase, specifically carbonyls, in driving adverse effects. Transcriptional profiling and biochemical analysis of human lung cells exposed at the air-liquid-interface determined DNA damage and stress response, as well as perturbation of cellular metabolism, as major key events. Connectivity mapping revealed a high similarity of gene expression signatures induced by wood smoke and agents prompting DNA-protein crosslinks (DPCs). Indeed, various gaseous aldehydes were detected in wood smoke, which promote DPCs, initiate similar genomic responses and are responsible for DNA damage provoked by wood smoke. Hence, systems toxicology enables the discovery of critical constituents of complex mixtures i.e. aerosols and highlights the role of carbonyls on top of particulate matter as an important health hazard.

The Air Pollution Human Health Burden in Different Future Scenarios That Involve the Mitigation of Near-Term Climate Forcers, Climate and Land-Use

Elevated surface concentrations of ozone and fine particulate matter (PM2.5) can lead to poor air quality and detrimental impacts on human health. These pollutants are also termed Near-Term Climate Forcers (NTCFs) as they can also influence the Earth's radiative balance on timescales shorter than long-lived greenhouse gases. Here we use the Earth system model, UKESM1, to simulate the change in surface ozone and PM2.5 concentrations from different NTCF mitigation scenarios, conducted as part of the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). These are then combined with relative risk estimates and projected changes in population demographics, to estimate the mortality burden attributable to long-term exposure to ambient air pollution. Scenarios that involve the strong mitigation of air pollutant emissions yield large future benefits to human health (25%), particularly across Asia for black carbon (7%), when compared to the future reference pathway. However, if anthropogenic emissions follow the reference pathway, then impacts to human health worsen over South Asia in the short term (11%) and across Africa (20%) in the longer term. Future climate change impacts on air pollutants can offset some of the health benefits achieved by emission mitigation measures over Europe for PM2.5 and East Asia for ozone. In addition, differences in the future chemical environment over regions are important considerations for mitigation measures to achieve the largest benefit to human health. Future policy measures to mitigate climate warming need to also consider the impact on air quality and human health across different regions to achieve the maximum co-benefits.

Lead pollution-related health of children in China: Disparity, challenge, and policy

Lead (Pb) is a neurotoxic metal, and no level of lead exposure is safe for children. China has still experienced problems on child lead poisoning even though the Chinese government has phased out leaded gasoline since 2000. The underlying problem affecting the lead pollution-related health of children in China remains to be comprehensively investigated. It is found that although the significant decline of BLLs, as the Geometric Mean (GM), from 91.40 μg/L^GM in 2001 to 37.52 μg/L^GM in 2018 is observed, the average BLLs of children are still above 50 μg/L or more [average 59.70 (60.50-65.02, 95 % CI) μg/L^GM] after phasing out leaded gasoline since 2000 in China. Lead exposure causes 29.67 MID per 1000 children with a loss of 98.23 (59.40-146.21, 95 % CI) DALYs per 1000 in China, which is greater than the levels reported from the Western Pacific Region and other low- and middle-income countries. A significant correlation is observed between the number of child crimes (NoCCs) and the outcomes of long-term lead exposure for children in China. Although the disparities in BLLs in China are strongly influenced by unequal distributions of potential multi-lead related sources (soil lead, PM2.5 lead, dust lead), unbalance development of local industrialization and economies, as well as incorrect health care for younger children, the notable emissions from coal combustion (CC) and non-ferrous metals (NMS) exploitation dominate the crucial sources of low-level lead exposure to children after phasing out leaded gasoline in China currently. Faced with the unequal and disparate distribution of BLLs in China, the big bottleneck is to decrease the BLLs exertions of 36-45 μg/L in the next few decades. The Chinese government needs to make more efforts on developing more strict guidelines, implementing more policy strategies on prevention and management of blood Pb poisoning, and monitoring the nationwide changes in children's BLLs continuously.

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region

Fine particulate matter (PM_2.5) exposure is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM_2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM_2.5, and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM_2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM_2.5-attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM_2.5 (>95 μg/m³). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM_2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sectors in South Asia.

Understanding population exposure to size-segregated aerosol and associated trace elements during residential cooking in northeastern India: Implications for disease burden and health risk

Mass-size distribution of respirable aerosol and 13 associated trace elements (TEs) were investigated in rural kitchens using liquefied petroleum gas (LPG), firewood and mixed biomass fuels across three northeastern Indian states. The averaged PM10 (particulate matter with aerodynamic diameter ≤ 10 μm) and ΣTE concentrations were 403 and 30 μg m-3 for LPG, 2429 and 55 μg m-3 for firewood, and 1024 and 44 μg m-3 for mixed biomass-using kitchens. Mass-size distributions were tri-modal with peaks in the ultrafine (0.05-0.08 μm), accumulation (0.20-1.05 μm), and coarse (3.20-4.57 μm) modes. Respiratory deposition, estimated using the multiple path particle dosimetry model, ranged from 21 % to 58 % of the total concentration across fuel types and population age categories. Head, followed by pulmonary and tracheobronchial, was the most vulnerable deposition region, and children were the most susceptible age group. Inhalation risk assessment of TEs revealed significant non-carcinogenic as well as carcinogenic risk, especially for biomass fuel users. The potential years of life lost (PYLL) was the highest for chronic obstructive pulmonary disease (COPD: 15.9 ± 3.8 years) followed by lung cancer (10.3 ± 0.3 years) and pneumonia (10.1 ± 0.1 years), while the PYLL rate was also highest for COPD, with Cr(VI) being the major contributor. Overall, these findings reveal the significant health burden faced by the northeastern Indian population from indoor cooking using solid biomass fuels.

Widespread Clean Cooking Fuel Scale-Up and under-5 Lower Respiratory Infection Mortality: An Ecological Analysis in Ecuador, 1990-2019

BACKGROUND

Nationwide household transitions to the use of clean-burning cooking fuels are a promising pathway to reducing under-5 lower respiratory infection (LRI) mortality, the leading cause of child mortality globally, but such transitions are rare and evidence supporting an association between increased clean fuel use and improved health is limited.

OBJECTIVES

This study aimed to investigate the association between increased primary clean cooking fuel use and under-5 LRI mortality in Ecuador between 1990 and 2019.

METHODS

We documented cooking fuel use and cause-coded child mortalities at the canton (county) level in Ecuador from 1990 to 2019 (in four periods, 1988-1992, 1999-2003, 2008-2012, and 2015-2019). We characterized the association between clean fuel use and the rate of under-5 LRI mortalities at the canton level using quasi-Poisson generalized linear and generalized additive models, accounting for potential confounding variables that characterize wealth, urbanization, and child health care and vaccination rates, as well as canton and period fixed effects. We estimated averted under-5 LRI mortalities accrued over 30 y by predicting a counterfactual count of canton-period under-5 LRI mortalities were clean fuel use to not have increased and comparing with predicted canton-period under-5 LRI mortalities from our model and observed data.

RESULTS

From 1990 to 2019, the proportion of households primarily using a clean cooking fuel increased from 59% to 95%, and under-5 LRI mortality fell from 28 to 7 per 100,000 under-5 population. Canton-level clean fuel use was negatively associated with under-5 LRI mortalities in linear and nonlinear models. The nonlinear association suggested a threshold at approximately 60% clean fuel use, above which there was a negative association. Increases in clean fuel use between 1990 and 2019 were associated with an estimated 7,300 averted under-5 LRI mortalities (95% confidence interval: 2,600, 12,100), accounting for nearly 20% of the declines in under-5 LRI mortality observed in Ecuador over the study period.

DISCUSSION

Our findings suggest that the widespread household transition from using biomass to clean-burning fuels for cooking reduced under-5 LRI mortalities in Ecuador over the last 30 y. https://doi.org/10.1289/EHP11016.

A global review of the state of the evidence of household air pollution's contribution to ambient fine particulate matter and their related health impacts

Direct exposure to household fine particulate air pollution (HAP) associated with inefficient combustion of fuels (wood, charcoal, coal, crop residues, kerosene, etc.) for cooking, space-heating, and lighting is estimated to result in 2.3 (1.6-3.1) million premature yearly deaths globally. HAP emitted indoors escapes outdoors and is a leading source of outdoor ambient fine particulate air pollution (AAP) in low- and middle-income countries, often being a larger contributor than well-recognized sources including road transport, industry, coal-fired power plants, brick kilns, and construction dust. We review published scientific studies that model the contribution of HAP to AAP at global and major sub-regional scales. We describe strengths and limitations of the current state of knowledge on HAP's contribution to AAP and the related impact on public health and provide recommendations to improve these estimates. We find that HAP is a dominant source of ambient fine particulate matter (PM2.5) globally - regardless of variations in model types, configurations, and emission inventories used - that contributes approximately 20 % of total global PM2.5 exposure. There are large regional variations: in South Asia, HAP contributes ∼ 30 % of ambient PM2.5, while in high-income North America the fraction is ∼ 7 %. The median estimate indicates that the household contribution to ambient air pollution results in a substantial premature mortality burden globally of about 0.77(0.54-1) million excess deaths, in addition to the 2.3 (1.6-3.1) million deaths from direct HAP exposure. Coordinated global action is required to avert this burden.

Development of Volatility Distributions for Organic Matter in Biomass Burning Emissions

The volatility distribution of organic emissions from biomass burning and other combustion sources can determine their atmospheric evolution due to partitioning/aging. The gap between measurements and models predicting secondary organic aerosol has been partially attributed to the absence of semi- and intermediate volatility organic compounds (S/I-VOC) in models and measurements. However, S/I-VOCs emitted from these sources and typically quantified using the volatility basis framework (VBS) are not well understood. For example, the amount and composition of S/I-VOCs and their variability across different biomass burning sources such as residential woodstoves, open field burns, and laboratory simulated open burning are uncertain. To address this, a novel filter-in-tube sorbent tube sampling method collected S/I-VOC samples from biomass burning experiments for a range of fuels and combustion conditions. Filter-in-tube samples were analyzed using thermal desorption-gas chromatography-mass spectrometry (TD/GC/MS) for compounds across a wide range of volatilities (saturation concentrations; -2 ≤ logC* ≤ 6). The S/I-VOC measurements were used to calculate volatility distributions for each emissions source. The distributions were broadly consistent across the sources with IVOCs accounting for 75% - 90% of the total captured organic matter, while SVOCs and LVOCs were responsible for 6% - 13% and 1% - 12%, respectively. The distributions and predicted partitioning were generally consistent with literature. Particulate matter emission factors spanned two orders of magnitude across the sources. This work highlights the potential of inferring gas-particle partitioning behavior of biomass burning emissions using filter-in-tube sorbent samples analyzed offline. This simplifies both sampling and analysis of S/I-VOCs for studies focused on capturing the full range of organics emitted.

Impact of lowering fine particulate matter from major emission sources on mortality in Canada: A nationwide causal analysis

Emissions of fine particulate matter (PM_2.5) from human activities have been linked to substantial disease burdens, but evidence regarding how reducing PM_2.5 at its sources would improve public health is sparse. We followed a population-based cohort of 2.7 million adults across Canada from 2007 through 2016. For each participant, we estimated annual mean concentrations of PM_2.5 and the fractional contributions to PM_2.5 from the five leading anthropogenic sources at their residential address using satellite observations in combination with a global atmospheric chemistry transport model. For each source, we estimated the causal effects of six hypothetical interventions on 10-y nonaccidental mortality risk using the parametric g-formula, a structural causal model. We conducted stratified analyses by age, sex, and income. This cohort would have experienced tangible health gains had contributions to PM_2.5 from any of the five sources been reduced. Compared with no intervention, a 10% annual reduction in PM_2.5 contributions from transportation and power generation, Canada's largest and fifth-largest anthropogenic sources, would have prevented approximately 175 (95%CI: 123-226) and 90 (95%CI: 63-117) deaths per million by 2016, respectively. A more intensive 50% reduction per year in PM_2.5 contributions from the two sources would have averted 360 and 185 deaths per million, respectively, by 2016. The potential health benefits were greater among men, older adults, and low-income earners. In Canada, where PM_2.5 levels are among the lowest worldwide, reducing PM_2.5 contributions from anthropogenic sources by as little as 10% annually would yield meaningful health gains.

Achieving Brazil's Deforestation Target Will Reduce Fire and Deliver Air Quality and Public Health Benefits

Climate, deforestation, and forest fires are closely coupled in the Amazon, but models of fire that include these interactions are lacking. We trained machine learning models on temperature, rainfall, deforestation, land-use, and fire data to show that spatial and temporal patterns of fire in the Amazon are strongly modified by deforestation. We find that fire count across the Brazilian Amazon increases by 0.44 percentage points for each percentage point increase in deforestation rate. We used the model to predict that the increased deforestation rate in the Brazilian Amazon from 2013 to 2020 caused a 42% increase in fire counts in 2020. We predict that if Brazil had achieved the deforestation target under the National Policy on Climate Change, there would have been 32% fewer fire counts across the Brazilian Amazon in 2020. Using a regional chemistry-climate model and exposure-response associations, we estimate that the improved air quality due to reduced smoke emission under this scenario would have resulted in 2,300 fewer deaths due to reduced exposure to fine particulate matter. Our analysis demonstrates the air quality and public health benefits that would accrue from reducing deforestation in the Brazilian Amazon.

Air quality impacts of crop residue burning in India and mitigation alternatives

Crop residue burning contributes to poor air quality and imposes a health burden on India. Despite government bans and other interventions, this practice remains widespread. Here we estimate the impact of changes in agricultural emissions on air quality across India and quantify the potential benefit of district-level actions using an adjoint modeling approach. From 2003 to 2019, we find that agricultural residue burning caused 44,000-98,000 particulate matter exposure-related premature deaths annually, of which Punjab, Haryana, and Uttar Pradesh contribute 67-90%. Due to a combination of relatively high downwind population density, agricultural output, and cultivation of residue-intensive crops, six districts in Punjab alone contribute to 40% of India-wide annual air quality impacts from residue burning. Burning two hours earlier in Punjab alone could avert premature deaths up to 9600 (95% CI: 8000-11,000) each year, valued at 3.2 (95% CI: 0.49-7.3) billion US dollars. Our findings support the use of targeted and potentially low-cost interventions to mitigate crop residue burning in India, pending further research regarding cost-effectiveness and feasibility.

Prenatal PM2.5 exposure contributes to neuronal tau lesion in male offspring mice through mitochondrial dysfunction-mediated insulin resistance

The epidemiological evidence has linked prenatal exposure to fine particulate matter (PM_2.5) pollution with neurological diseases in offspring. However, the biological process and toxicological mechanisms remain unclear. Tau protein is a neuronal microtubule-associated protein expressed in fetal brain and plays a critical role in mediating neuronal development. Aberrant expression of tau is associated with adverse neurodevelopmental outcomes. To study whether prenatal exposure to PM_2.5 pollution induce tau lesion in mice offspring and elucidate the underlying pathogenic mechanism, we exposed pregnant mice to PM_2.5 (3 mg/kg b.w.) by oropharyngeal aspiration every other day. The results indicate that prenatal PM_2.5 exposure induced hyperphosphorylation of tau in the cortex of postnatal male offspring, which was accompanied by insulin resistance through the IRS-1/PI3K/AKT signaling pathway. Importantly, we further found that prenatal PM_2.5 exposure induced mitochondrial dysfunction by disrupting mitochondrial ultrastructure and decreasing the expression of rate-limiting enzymes (CS, IDH2 and FH) in the Krebs cycle and the subunits of mitochondrial complex IV and V (CO1, CO4, ATP6, and ATP8) during postnatal neurodevelopment. The findings suggest that prenatal PM_2.5 exposure could induce tauopathy-like changes in male offspring, in which mitochondrial dysfunction-induced insulin resistance might play an important role.

Compositional Constraints are Vital for Atmospheric PM2.5 Source Attribution over India

India experiences some of the highest levels of ambient PM_2.5 aerosol pollution in the world. However, due to the historical dearth of in situ measurements, chemical transport models that are often used to estimate PM_2.5 exposure over the region are rarely evaluated. Here, we conduct a novel model comparison with speciated airborne measurements of fine aerosol, revealing large biases in the ammonium and nitrate simulations. To address this, we incorporate process-level changes to the model and use satellite observations from the Cross-track Infrared Sounder (CrIS) and the TROPOspheric Monitoring Instrument (TROPOMI) to constrain ammonia and nitrogen oxide emissions. The resulting simulation demonstrates significantly lower bias (NMB_Modified: 0.19; NMB_Base: 0.61) when validated against the airborne aerosol measurements, particularly for the nitrate (NMB_Modified: 0.08; NMB_Base: 1.64) and ammonium simulation (NMB_Modified: 0.49; NMB_Base: 0.90). We use this validated simulation to estimate a population-weighted annual PM_2.5 exposure of 61.4 μg m^-3, with the RCO (residential, commercial, and other) and energy sectors contributing 21% and 19%, respectively, resulting in an estimated 961,000 annual PM_2.5-attributable deaths. Regional exposure and sectoral source contributions differ meaningfully in the improved simulation (compared to the baseline simulation). Our work highlights the critical role of speciated observational constraints in developing accurate model-based PM_2.5 aerosol source attribution for health assessments and air quality management in India.

Emission factors and chemical profile of I/SVOCs emitted from household biomass stove in China

Household combustion of biomass straw for cooking or heating is one of the most important emission sources of intermediate volatility and semi-volatile organic compounds (I/SVOCs). However, there are limited studies on the emission factors (EFs) and speciation profiles of I/SVOCs from household stoves burning biomass straw. In this study, experiments were conducted in a typical Chinese stove to test the EFs and species of I/SVOCs in three commonly used straws. It was revealed that EFs of I/SVOCs emitted from the burning of corn straw, rice straw, and wheat straw were 6.7, 1.9, and 9.8 g/kg, respectively, which accounted for 48.3 %, 36.8 %, and 48.6 % of total organic compounds emitted. Particulate organic compounds were dominated by ketones, oxygenated aromatics, acids, esters, and nitrogen-containing compounds, whereas the gaseous phase was dominated by aldehydes, acids, and aromatics. Although I/SVOCs only accounted for 18.1-23.6 % of the gaseous emissions from burning of straw, they represented 64.8-72.9 % of the secondary organic aerosol formation potential (SOAFP). The EFs of 16 priority polycyclic aromatic hydrocarbons (PAHs) were 362.0, 262.5, and 1145.2 mg/kg for corn straw, rice straw, and wheat straw, respectively, among which 3-ring and 4-ring PAHs were the main components. Thus, the results of this study provide new reliable I/SVOCs data that are useful for the development of an accurate emission inventory of organic compounds, simulation of secondary organic aerosol (SOA) formation, and health risk assessment.

Exports Widen the Regional Inequality of Health Burdens and Economic Benefits in India

Both the ever-complex international and subnational supply chains could relocate health burdens and economic benefits across India, leading to the widening of regional inequality. Here, we simultaneously track the unequal distribution of fine particle matter (PM_2.5) pollution, health costs, and value-added embodied in inter- and intranational exports for Indian states in 2015 by integrating a nested multiregional input-output (MRIO) table constructed based on EXIOBASE and an Indian regional MRIO table, Emissions Database for Global Atmospheric Research (EDGAR), the Community Multi-Scale Air Quality (CMAQ) model, and a concentration-response function. The results showed that the annual premature deaths associated with PM_2.5 pollution embodied in inter- and intranational exports were 757,356 and 388,003 throughout India, accounting for 39% and 20% of the total premature deaths caused by PM_2.5 pollution, respectively. Richer south and west coastal states received around half of the national Gross Domestic Product (GDP) induced by exports with a quarter of the health burden, while poorer central and east states bear approximately 60% of the health burden with less than a quarter of national GDP. Our findings highlight the role of exports in driving the regional inequality of health burdens and economic benefits. Therefore, tailored strategies (e.g., air pollution compensation, advanced technology transfer, and export structure optimization) could be formulated.

Four year long simulation of carbonaceous aerosols in India: Seasonality, sources and associated health effects

India's air quality is in a dismal state, with many studies ascribing it to PM_2.5. Most of these corroborate that carbonaceous aerosol (CA) constitute significant fraction of PM_2.5. However, investigations on the effect of long-term meteorological or emission changes on PM_2.5 and its components, and their associated health effects are rare. In this work, WRF-Chem simulations for three seasons over four years (2016-2019) were carried out to cogitate the spatial and temporal changes in PM_2.5 and its components in India. Model predicted PM_2.5 concentrations were in good agreement with the ground-based observations for 25 cities. PM_2.5 was highest in winter and lowest in pre-monsoon. PM_2.5 reduced by ∼8% in Indo-Gangetic Plain (IGP) but increased by ∼38% and ∼130% in south and northeast India, respectively, from 2016 to 2019. IGP witnessed three times higher average PM_2.5 concentrations than south India. No significant interannual change in CA contributions was observed, however, it peaked in the winter season. Other inorganics (OIN) were the major component of PM_2.5, contributing more than 40%. Primary organic aerosol (POA) fractions were higher in north India, while secondary inorganic aerosol (SIA) dominated south India. Transport and residential sectors were the chief contributors to CA across India. Biomass burning contributed up to ∼23% of PM_2.5 in regions of IGP during post-monsoon, with CA fractions up to 50%. Associations between PM_2.5 and its components with daily inpatient admissions from a tertiary care centre in Delhi showed that PM_2.5 and OIN had lower associations with daily hospital admissions than CA. Every 10 μg/m³ increase in POA, black carbon (BC), and secondary organic aerosol (SOA) were associated with ∼1.09%, ∼3.07% and ∼4.93% increase in the risk of daily hospital admissions. This invigorates the need for more policies targeting CA rather than PM_2.5 to mitigate associated health risks, in India.

Assessing the Effects of Stove Use Patterns and Kitchen Chimneys on Indoor Air Quality during a Multiyear Cookstove Randomized Control Trial in Rural India

We conducted indoor air quality (IAQ) measurements during a multiyear cookstove randomized control trial in two rural areas in northern and southern India. A total of 1205 days of kitchen PM_2.5 were measured in control and intervention households during six ∼3 month long measurement periods across two study locations. Stoves used included traditional solid fuel (TSF), improved biomass, and liquefied petroleum gas (LPG) models. Intent-to-treat analysis indicates that the intervention reduced average 24 h PM_2.5 and black carbon in only one of the two follow-up measurement periods in both areas, suggesting mixed effectiveness. Average PM_2.5 levels were ∼50% lower in households with LPG (for exclusive LPG use: >75% lower) than in those without LPG. PM_2.5 was 66% lower in households making exclusive use of an improved chimney stove versus a traditional chimney stove and TSF-exclusive kitchens with a built-in chimney had ∼60% lower PM_2.5 than those without a chimney, indicating that kitchen ventilation can be as important as the stove technology in improving IAQ. Diurnal trends in real-time PM_2.5 indicate that kitchen chimneys were especially effective at reducing peak concentrations, which leads to decreases in daily PM_2.5 in these households. Our data demonstrate a clear hierarchy of IAQ improvement in real world, "stove-stacking" households, driven by different stove technologies and kitchen characteristics.

Emission Sector Impacts on Air Quality and Public Health in China From 2010 to 2020

Anthropogenic emissions and ambient fine particulate matter (PM_2.5) concentrations have declined in recent years across China. However, PM_2.5 exposure remains high, ozone (O₃) exposure is increasing, and the public health impacts are substantial. We used emulators to explore how emission changes (averaged per sector over all species) have contributed to changes in air quality and public health in China over 2010-2020. We show that PM_2.5 exposure peaked in 2012 at 52.8 μg m^-3, with contributions of 31% from industry and 22% from residential emissions. In 2020, PM_2.5 exposure declined by 36% to 33.5 μg m^-3, where the contributions from industry and residential sources reduced to 15% and 17%, respectively. The PM_2.5 disease burden decreased by only 9% over 2012 where the contributions from industry and residential sources reduced to 15% and 17%, respectively 2020, partly due to an aging population with greater susceptibility to air pollution. Most of the reduction in PM_2.5 exposure and associated public health benefits occurred due to reductions in industrial (58%) and residential (29%) emissions. Reducing national PM_2.5 exposure below the World Health Organization Interim Target 2 (25 μg m^-3) would require a further 80% reduction in residential and industrial emissions, highlighting the challenges that remain to improve air quality in China.

How Does COVID-19 Lockdown Impact Air Quality in India?

Air pollution is a severe environmental problem in the Indian subcontinent. Largely caused by the rapid growth of the population, industrialization, and urbanization, air pollution can adversely affect human health and environment. To mitigate such adverse impacts, the Indian government launched the National Clean Air Programme (NCAP) in January 2019. Meanwhile, the unexpected city-lockdown due to the COVID-19 pandemic in March 2020 in India greatly reduced human activities and thus anthropogenic emissions of gaseous and aerosol pollutants. The NCAP and the lockdown could provide an ideal field experiment for quantifying the extent to which various levels of human activity reduction impact air quality in the Indian subcontinent. Here, we study the improvement in air quality due to COVID-19 and the NCAP in the India subcontinent by employing multiple satellite products and surface observations. Satellite data shows significant reductions in nitrogen dioxide (NO2) by 17% and aerosol optical depth (AOD) by 20% during the 2020 lockdown with reference to the mean levels between 2005–2019. No persistent reduction in NO2 nor AOD is detectable during the NCAP period (2019). Surface observations show consistent reductions in PM2.5 and NO2 during the 2020 lockdown in seven cities across the Indian subcontinent, except Mumbai in Central India. The increase in relative humidity and the decrease in the planetary boundary layer also play an important role in influencing air quality during the 2020 lockdown. With the decrease in aerosols during the lockdown, net radiation fluxes show positive anomalies at the surface and negative anomalies at the top of the atmosphere over most parts of the Indian subcontinent. The results of this study could provide valuable information for policymakers in South Asia to adjust the scientific measures proposed in the NCAP for efficient air pollution mitigation.

Oxidative potential and water-soluble heavy metals of size-segregated airborne particles in haze and non-haze episodes: Impact of the "Comprehensive Action Plan" in China

Air pollution is a major environmental health challenge in megacities, and as such a Comprehensive Action Plan (CAP) was issued in 2017 for Beijing, the capital city of China. Here we investigated the size-segregated airborne particles collected after the implementation of the CAP, intending to understand the change of oxidative potential and water-soluble heavy metal (WSHM) levels in 'haze' and 'non-haze' days. The DNA damage and the levels of WSHM were analyzed by Plasmid Scission Assay (PSA) and High-Resolution Inductively Coupled Plasma Mass Spectrometry (HR-ICP-MS) techniques. The PM mass concentration was higher in the fine particle size (0.43-2.1 μm) during haze days, except for the samples affected by mineral dust. The particle-induced DNA damage caused by fine sized particles (0.43-2.1 μm) exceeded that caused by the coarse sized particles (4.7-10 μm). The DNA damage from haze day particles significantly exceeded those collected on non-haze days. Prior to the instigation of the CAP, the highest value of DNA damage decreased, and DNA damage was seen in the finer size (0.43-1.1 μm). The Pearson correlation coefficient between the concentrations of water-soluble Pb, Cr, Cd and Zn were positively correlated with DNA damage, suggesting that these WSHM had significant oxidative potential. The mass concentrations of water-soluble trace elements (WSTE) and individual heavy metals were enriched in the finer particles between 0.43 μm to 1.1 μm, implying that smaller sized particles posed higher health risks. In contrast, the significant reduction in the mass concentration of water-soluble Cd and Zn, and the decrease of the maximum and average values of DNA damage after the CAP, demonstrated its effectiveness in restricting coal-burning emissions. These results have demonstrated that the Beijing CAP policy has been successful in reducing the toxicity of 'respirable' ambient particles.

Spatiotemporal characteristics of NO2, PM2.5 and O3 in a coastal region of southeastern China and their removal by green spaces

Understanding the spatio-temporal characteristics of air pollutants is essential to improving air quality. One aspect is the question of whether green spaces can reduce air pollutant concentrations. However, previous studies on this issue have reported mixed results. This study analyzed the spatio-temporal characteristics of NO₂, PM_2.5 and O₃ in Fujian Province, Southeast China in 2015. In order to reduce uncertainties in the conclusions drawn, the effects landscape metrics describing green spaces have on air pollutants have been analyzed using Pearson correlation analysis at six different spatial scales for the four seasons, considering the influence of meteorological conditions. The results show that PM_2.5 and O₃ are major pollutants whose relative importance varies with the seasons. Significant differences in pollutant concentrations were observed in suburban and urban areas, highlighting the importance of ensuring a reasonable spatial distribution of monitoring stations. Moreover, significant correlations between air pollutants and green space landscape patterns during the four seasons were found, revealing increased air pollutant concentrations with increasing landscape fragmentation and reduced connectivity and aggregation. This probably indicates that interconnected green spaces have the potential to improve air quality. Utilizing green space function regulations can alleviate NO₂ and PM_2.5 pollution effectively, but it is still difficult to reduce O₃ concentrations because green spaces are likely to not only serve as sinks for O_3, but can also promote O₃ formation.

Global Burden of Disease from Major Air Pollution Sources (GBD MAPS): A Global Approach

Ambient fine particulate matter (particles <2.5 μm in aerodynamic diameter [PM2.5]) is the world's leading environmental health risk factor. Reducing the PM2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. The Global Burden of Disease from Major Air Pollution Sources (GBD MAPS) project provides a contemporary and comprehensive evaluation of contributions to the ambient PM2.5 disease burden from source sectors and fuels across 21 regions, 204 countries, and 200 subnational areas. We first derived quantitative contributions from 24 emission sensitivity simulations using an updated global atmospheric chemistry-transport model, input with a newly developed detailed anthropogenic emissions dataset that includes emissions specific to source sector and fuels. These simulation results were integrated with newly available high-resolution satellite-derived PM2.5 exposure estimates and disease-specific concentration-response relationships consistent with the GBD project to quantify contributions of specific source sector and fuel to the ambient PM2.5 disease burden across all regions, countries, and subnational areas. To improve the transparency and reproducibility of this and future work, we publicly provided the global atmospheric chemistry-transport model source code, emissions dataset and emissions model source code, analysis scripts, and source sensitivity results, and further described the emissions dataset and source contribution results in two publications.

We found that nearly 1.05 million (95% uncertainty interval [UI]: 0.74-1.36 million) deaths worldwide (27.3% of the total mortality attributable to PM2.5) would be avoidable by eliminating fossil fuel combustion, with coal contributing over half of that burden. Residential (19.2%; 736,000 deaths [95% UI: 521,000-955,000]), industrial (11.7%; 448,000 deaths [95% UI: 318,000-582,000]), and energy (10.2%; 391,000 deaths [95% UI: 277,000-507,000]) sector emissions are among the dominant global sources Uncertainty in these estimates reflects those of the input datasets. Regions with the largest anthropogenic contributions generally have the highest numbers of attributable deaths, which clearly demonstrates the importance of reducing these emissions to realize reductions in global air pollution and its disease burden.

Importance of meteorology and chemistry in determining air pollutant levels during COVID-19 lockdown in Indian cities

Indian cities can experience severe air pollution, and the reduction in activity during the first national COVID-19 lockdown (2020) offered a natural experiment to study the contribution of local sources. The current work aimed to quantify the changes due to the lockdown in NO_x, O₃ and PM_2.5 in two contrasting cities in India (Delhi and Hyderabad) using a boosted regression tree model to account for the influence of meteorology. The median NO_x and PM_2.5 concentrations were observed to decrease after lockdown in both cities, up to 57% and 75% for PM_2.5 and NO_x, respectively when compared to previous years. After normalization due to meteorology the calculated reduction after lockdown for PM_2.5 was small (<8%) in both cities, and was likely less attributable to changes in local emissions, but rather due changes in background levels (i.e. regional source(s)). The reduction of NO_x due to lockdown varied by site (on average 5-30%), likely reflecting differences in relative proximity of local sources to the monitoring site, demonstrating the key influence of meteorology on ambient levels post-lockdown. Ozone was observed to increase after lockdown at both sites in Delhi, likely due to changes in relative amounts of precursor concentrations promoting ozone production, suggesting a volatile organic compound (VOC)-limited regime in Delhi. Thus, the calculated reduction in air pollutants due to lockdown in the current work cannot be extrapolated to be solely from a reduction in emissions and instead reflects the overall change in ambient levels, as meteorology and atmospheric chemical processes also contributed.

Impact of the 2019/2020 Australian Megafires on Air Quality and Health

The Australian 2019/2020 bushfires were unprecedented in their extent and intensity, causing a catastrophic loss of habitat, human and animal life across eastern-Australia. We use a regional air quality model to assess the impact of the bushfires on particulate matter with a diameter less than 2.5 μm (PM2.5) concentrations and the associated health impact from short-term population exposure to bushfire PM2.5. The mean population Air Quality Index (AQI) exposure between September and February in the fires and no fires simulations indicates an additional ∼437,000 people were exposed to "Poor" or worse AQI levels due to the fires. The AQ impact was concentrated in the cities of Sydney, Newcastle-Maitland, Canberra-Queanbeyan and Melbourne. Between October and February 171 (95% CI: 66-291) deaths were brought forward due to short-term exposure to bushfire PM2.5. The health burden was largest in New South Wales (NSW) (109 (95% CI: 41-176) deaths brought forward), Queensland (15 (95% CI: 5-24)), and Victoria (35 (95% CI: 13-56)). This represents 38%, 13% and 30% of the total deaths brought forward by short-term exposure to all PM2.5. At a city-level 65 (95% CI: 24-105), 23 (95% CI: 9-38) and 9 (95% CI: 4-14) deaths were brought forward from short-term exposure to bushfire PM2.5, accounting for 36%, 20%, and 64% of the total deaths brought forward from all PM2.5. Thus, the bushfires caused substantial AQ and health impacts across eastern-Australia. Climate change is projected to increase bushfire risk, therefore future fire management policies should consider this.

Vertical profile of aerosols in the Himalayas revealed by lidar: New insights into their seasonal/diurnal patterns, sources, and transport

Atmospheric aerosols play a crucial role in climate change, especially in the Himalayas and Tibetan Plateau. Here, we present the seasonal and diurnal characteristics of aerosol vertical profiles measured using a Mie lidar, along with surface black carbon (BC) measurements, at Mt. Qomolangma (QOMS), in the central Himalayas, in 2018-2019. Lidar-retrieved profiles of aerosols showed a distinct seasonal pattern of aerosol loading (aerosol extinction coefficient, AEC), with a maximum in the pre-monsoon (19.8 ± 22.7 Mm^-1 of AEC) and minimum in the summer monsoon (7.0 ± 11.2 Mm^-1 of AEC) seasons. The diurnal variation characteristics of AEC and BC were quite different in the non-monsoon seasons with enriched aerosols being maintained from 00:00 to 10:00 in the pre-monsoon season. The major aerosol types at QOMS were identified as background, pollution, and dust aerosols, especially during the pre-monsoon season. The occurrence of pollution events influenced the vertical distribution, seasonal/diurnal patterns, and types of aerosols. Source contribution of BC based on the weather research and forecasting chemical model showed that approximately 64.2% ± 17.0% of BC at the QOMS originated from India and Nepal in South Asia during the non-monsoon seasons, whereas approximately 47.7% was from local emission sources in monsoon season. In particular, the high abundance of BC at the QOMS in the pre-monsoon season was attributed to biomass burning, whereas anthropogenic emissions were the likely sources during the other seasons. The maximum aerosol concentration appeared in the near-surface layer (approximately 4.3 km ASL), and high concentrations of transported aerosols were mainly found at 4.98, 4.58, 4.74, and 4.88 km ASL in the pre-monsoon, monsoon, post-monsoon, and winter seasons, respectively. The investigation of the vertical profiles of aerosols at the QOMS can help verify the representation of aerosols in the air quality model and satellite products and regulate the anthropogenic disturbance over the Tibetan Plateau.

Health Benefits and Costs of Clean Heating Renovation: An Integrated Assessment in a Major Chinese City

China has been promoting one of the world's largest campaigns for clean heating renovation since 2017. Here, we present an integrated cost-benefit analysis in a major prefecture-level city by combining a large-scale household energy survey and PM_2.5 exposure measurement, high-resolution chemical transport simulation, and health impact assessment. We find that the completed renovation decreases the share of solid fuels in the heating energy mix from 96 to 6% and achieves a concomitant reduction of cooking solid-fuel use by 70%. The completed renovation decreases the ambient PM_2.5 concentration in Linfen by 0.5-5 μg m^-3 (2.4 μg m^-3 on average) and decreases the integrated PM_2.5 exposure by 4.2 (3.5-5.0) μg m^-3. The renovation is estimated to avoid 162 (125-225) and 328 (254-457) premature deaths annually based on two health impact assessment methods. The ratios of monetized health benefits to cost are 1.51 (0.73-2.59) and 3.06 (1.49-5.23) based on the above two methods. The benefit-to-cost ratio is projected to remain high if the renovation is further expanded. More polluted and less wealthy households enjoy larger health benefits but also experience a higher expense increase, suggesting that a more carefully designed subsidy policy is needed to protect low-income households.

Reducing Planetary Health Risks Through Short-Lived Climate Forcer Mitigation

Global air pollution and climate change are major threats to planetary health. These threats are strongly linked through the short-lived climate forcers (SLCFs); ozone (O3), aerosols, and methane (CH4). Understanding the impacts of ambitious SLCF mitigation in different source emission sectors on planetary health indicators can help prioritize international air pollution control strategies. A global Earth system model is applied to quantify the impacts of idealized 50% sustained reductions in year 2005 emissions in the eight largest global anthropogenic source sectors on the SLCFs and three indicators of planetary health: global mean surface air temperature change (∆GSAT), avoided PM2.5-related premature mortalities and gross primary productivity (GPP). The model represents fully coupled atmospheric chemistry, aerosols, land ecosystems and climate, and includes dynamic CH4. Avoided global warming is modest, with largest impacts from 50% cuts in domestic (-0.085 K), agriculture (-0.034 K), and waste/landfill (-0.033 K). The 50% cuts in energy, domestic, and agriculture sector emissions offer the largest opportunities to mitigate global PM2.5-related health risk at around 5%-7% each. Such small global impacts underline the challenges ahead in achieving the World Health Organization aspirational goal of a 2/3 reduction in the number of deaths from air pollution by 2030. Uncertainty due to natural climate variability in PM2.5 is an important underplayed dimension in global health risk assessment that can vastly exceed uncertainty due to the concentration-response functions at the large regional scale. Globally, cuts to agriculture and domestic sector emissions are the most attractive targets to achieve climate and health co-benefits through SLCF mitigation.

In-use emissions and usage trend of pellet heating stoves in rural Yangxin, Shandong Province

The use of coal in Chinese households for winter heating emits harmful pollutants that severely affect indoor air quality and climate. Therefore, China has made efforts to transition into clean heating using improved heating stoves and biomass pellets. Although the economic and policy implications of such demonstration projects have been extensively investigated, little has been done to understand the real-world performance and adoption trends of such stoves. This study measured in-use emissions from nine different pellet stoves used for heating among 52 rural households in Yangxin, Shandong Province. The temperature of the stove chimney of 21 households was monitored and 56 households were surveyed to explore the stove use trend. The particulate and gaseous emission concentrations for most of the stoves exceeded the limits specified in the Chinese national standard. The measured fuel energy-based emission factors (mean ± standard deviation) for CO₂, CO, NOx, and PM_2.5 were 103 ± 3, 1.41 ± 1.19, 0.336 ± 0.237, and 0.146 ± 0.108 g/MJ, respectively. Between January to February, the average daily heating duration was 8.71 h, and the sustained use of heating stoves was seen among over 85% of the households. On average, the households used their heating stoves for 3.28 months and the estimated annual pellets consumption for a household was 2.7 tons. Besides inherent variabilities associated with user habits, the stove's design-related shortcomings and low-grade pellets hindered the performance and effectiveness of pellet stoves. This study provides insights into opportunities and challenges for the promotion of cleaner fuels and heating technologies. Furthermore, it will provide information on emissions from rural residential sources to build the emission inventory and inform policymaking for successful stove promotion programs.

Chemical source profiles of fine particles for five different sources in Delhi

Increasing emissions from sources such as construction and burning of biomass from crop residues, roadside and municipal solid waste have led to a rapid increase in the atmospheric concentrations of fine particulate matter (≤2.5 μm; PM_2.5) over many Indian cities. Analyses of their chemical profiles are important for receptor models to accurately estimate the contributions from different sources. We have developed chemical source profiles for five important pollutant sources - construction (CON), paved road dust (PRD), roadside biomass burning (RBB), solid waste burning (SWB), and crop residue burning (CPB) - during three intensive campaigns (winter, summer and post-monsoon) in and around Delhi. We obtained chemical characterisations of source profiles incorporating carbonaceous material such as organic carbon (OC) and elemental carbon (EC), water-soluble ions (F^-, Cl^-, NO₂^-, NO₃^-, SO₄^2-, PO₄^3-, Na⁺ and NH₄⁺), and elements (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Br, Rb, Sr, Ba, and Pb). CON was dominated by the most abundant elements, K, Si, Fe, Al, and Ca. PRD was also dominated by crustal elements, accounting for 91% of the total analysed elements. RBB, SWB and CPB profiles were dominated by organic matter, which accounted for 94%, 86.2% and 86% of the total PM_2.5, respectively. The database of PM emission profiles developed from the sources investigated can be used to assist source apportionment studies for accurate quantification of the causes of air pollution and hence assist governmental bodies in formulating relevant countermeasures.

Large Air Quality and Public Health Impacts due to Amazonian Deforestation Fires in 2019

Air pollution from Amazon fires has adverse impacts on human health. The number of fires in the Amazon has increased in recent years, but whether this increase was driven by deforestation or climate has not been assessed. We analyzed relationships between fire, deforestation, and climate for the period 2003 to 2019 among selected states across the Brazilian Legal Amazon (BLA). A statistical model including deforestation, precipitation and temperature explained ∼80% of the variability in dry season fire count across states when totaled across the BLA, with positive relationships between fire count and deforestation. We estimate that the increase in deforestation since 2012 increased the dry season fire count in 2019 by 39%. Using a regional chemistry-climate model combined with exposure-response associations, we estimate this increase in fire resulted in 3,400 (95UI: 3,300-3,550) additional deaths in 2019 due to increased exposure to particulate air pollution. If deforestation in 2019 had increased to the maximum recorded during 2003-2019, the number of active fire counts would have increased by an additional factor of 2 resulting in 7,900 (95UI: 7,600-8,200) additional premature deaths. Our analysis demonstrates the strong benefits of reduced deforestation on air quality and public health across the Amazon.

Rapid increase in mortality attributable to PM2.5 exposure in India over 1998-2015

PM_2.5-attributable deaths and years of life lost (YLL) due to specific causes during 1998-2015 in India were estimated using the integrated exposure-response (IER) model. The estimated PM_2.5-mortality in India revealed an annual increasing rate of 2.7% during the study period. Spatially, deaths due to the exposure to ambient PM_2.5 concentrated mostly in populated North India, and four northern states contributed 43% to the national PM_2.5-attributable deaths in 2015. PM_2.5-attributable deaths in India increased by 21% during 1998-2015 due to the changes of PM_2.5 only, and deaths due to lung cancer (LC) revealed the largest sensitivity to increasing ambient PM_2.5. The findings of this study suggest that aggressive air pollution control strategies should be implemented in North India due to their dominant contributions to the current health risks. Moreover, the rapid growth of LC related deaths with increasing ambient PM_2.5 should not be neglected.

Survey-based inventory for atmospheric emissions from residential combustion in Vietnam

Local questionnaire surveys were conducted to collect representative activity data for calculation of annual emissions from residential combustion in Red River Delta (RRD), Vietnam, for 2010-2015. Multistage statistical sampling was implemented in the surveys for Hanoi Metropolitan Region (HMR) and deep rural area of Ninh Binh province (Con Thoi, Ninh Binh (CTNB)). Emission factors were scrutinized to select relevant ranges and central values for typical cookstoves in RRD. Large differences in the activity data (cooking activities, fuel-stove types, and fuel consumption) were found between three HMR strata (urban, suburban, and rural populations) and CTNB, respectively, which resulted in distinctly different annual emissions per capita. Annual 2010 emissions from residential combustion in RRD were estimated for toxic pollutants, in Gg/year, of 217 for CO, 1.5 NO_x, 7.4 SO₂, 33 NMVOC, 3.7 NH₃, 16.9 PM_2.5, 1.4 BC, and 7.1 OC, along with 171 t/year of total PAHs with 0.7 t/year of BaP, and greenhouse gases of 5395 CO₂, 17.2 CH₄, and 0.7 N₂O Gg/year. Emissions increased by 1.5-7.8%, varying with species, over the 6-year period. Prevalent use of crop residue in CTNB induced its dominant shares in the residential combustion emissions not only in this deep rural area but also in the entire RRD domain. Spatial emission distribution exhibited high intensities over districts having high rural population density. Global warming potential results indicated the dominant role of black carbon, especially over the 20-year horizon. Switching from solid fuels to liquefied petroleum gas would reduce the emissions from this sector and bring in multiple benefits.

In-use emissions from biomass and LPG stoves measured during a large, multi-year cookstove intervention study in rural India

We conducted an emission measurement campaign as a part of a multiyear cookstove intervention trial in two rural locations in northern and southern India. 253 uncontrolled cooking tests measured emissions in control and intervention households during three ~3-month-long measurement periods in each location. We measured pollutants including fine particulate matter (PM_2.5), organic and elemental carbon (OC, EC), black carbon (BC) and carbon monoxide (CO) from stoves ranging from traditional solid fuel (TSF) to improved biomass stoves (rocket, gasifier) to liquefied petroleum gas (LPG) models. TSF stoves showed substantial variability in pollutant emission factors (EFs; g kg^-1 wood) and optical properties across measurement periods. Multilinear regression modeling found that measurement period, fuel properties, relative humidity, and cooking duration are significant predictors of TSF EFs. A rocket stove showed moderate reductions relative to TSF. LPG stoves had the lowest pollutant EFs, with mean PM_2.5 and CO EFs (g MJ_delivered^-1) >90% lower than biomass stoves. However, in-home EFs of LPG were substantially higher than lab EFs, likely influenced by non-ideal combustion performance, emissions from food and possible influence from other combustion sources. In-home emission measurements may depict the actual exposure benefits associated with dissemination of LPG stoves in real world interventions.

Impacts of Global Solid Biofuel Stove Emissions on Ambient Air Quality and Human Health

Global solid biofuel stove emissions strongly impact air quality, climate change, and human health. However, investigations of the impacts of global solid biofuel stove emissions on human health associated with PM2.5 (particulate matter with aerodynamic diameter ≤2.5 μm) and ozone (O3) are limited. Here, we quantify the impacts of global solid biofuel stove emissions on ambient PM2.5 and O3 air quality and the associated human health effects for the year 2010, using the Community Atmosphere Model coupled with Chemistry version 5.3. Annual mean surface PM2.5 concentrations from global solid biofuel stove emissions averaged over 2006-2010 are up to 23.1 μg m-3, with large impacts found over China, India, sub-Saharan Africa, and eastern and central Europe. For surface O3 impacts, we find that global solid biofuel stove emissions lead to increases in surface O3 concentrations by up to 5.7 ppbv for China, India, and sub-Saharan Africa, and negligible impacts or reductions of up to 0.5 ppbv for the US, Europe, and parts of South America. Global solid biofuel stove emissions for the year 2010 contribute to 382,000 [95% confidence interval (95CI): 349,000-409,000] annual premature deaths associated with PM2.5 and O3 exposure, with the corresponding years of life lost as 8.10 million years (95CI: 7.38-8.70 million years). Our study highlights air quality and human health benefits of mitigating emissions from the global solid biofuel stove sector, especially over populous regions of low-income and middle-income countries, through promoting clean household energy programs for the residential energy supply.

Quantitative Structure-Activity Relationship of Nanowire Adsorption to SO2 Revealed by In Situ TEM Technique

A quantitative structure-activity relationship (QSAR) is revealed based on the real-time sulfurization processes of ZnO nanowires observed via gas-cell in situ transmission electron microscopy (in situ TEM). According to the in situ TEM observations, the ZnO nanowires with a diameter of 100 nm (ZnO-100 nm) gradually transform into a core-shell nanostructure under SO₂ atmosphere, and the shell formation kinetics are quantitatively determined. However, only sparse nanoparticles can be observed on the surface of the ZnO-500 nm sample, which implies a weak solid-gas interaction between SO₂ and ZnO-500 nm. The QSAR model is verified with heat of adsorption (-ΔH°) and aberration-corrected TEM characterization. With the guidance of the QSAR model, the following adsorbing/sensing applications of ZnO nanomaterials are explored: (i) breakthrough experiment demonstrates the application potential of the ZnO-100 nm sample for SO₂ capture/storage; (ii) the ZnO-500 nm sample features good reversibility (RSD = 1.5%, n = 3) for SO₂ sensing, and the detection limit reaches 70 ppb.

Pollution, economic growth, and COVID-19 deaths in India: a machine learning evidence

This study uses two different approaches to explore the relationship between pollution emissions, economic growth, and COVID-19 deaths in India. Using a time series approach and annual data for the years from 1980 to 2018, stationarity and Toda-Yamamoto causality tests were performed. The results highlight unidirectional causality between economic growth and pollution. Then, a D2C algorithm on proportion-based causality is applied, implementing the Oryx 2.0.8 protocol in Apache. The underlying hypothesis is that a predetermined pollution concentration, caused by economic growth, could foster COVID-19 by making the respiratory system more susceptible to infection. We use data (from January 29 to May 18, 2020) on confirmed deaths (total and daily) and air pollution concentration levels for 25 major Indian cities. We verify a ML causal link between PM_2.5, CO₂, NO₂, and COVID-19 deaths. The implications require careful policy design.

Avoiding high ozone pollution in Delhi, India

Quantify the influence of aerosol light extinction on surface ozone photochemistry, highlight controlling VOC for improving air quality in Delhi.

Exceedances and trends of particulate matter (PM2.5) in five Indian megacities

Fine particulate matter (PM_2.5) is the leading environmental risk factor that requires regular monitoring and analysis for effective air quality management. This work presents the variability, trend, and exceedance analysis of PM_2.5 measured at US Embassy and Consulate in five Indian megacities (Chennai, Kolkata, Hyderabad, Mumbai, and New Delhi) for six years (2014-2019). Among all cities, Delhi is found to be the most polluted city followed by Kolkata, Mumbai, Hyderabad, and Chennai. The trend analysis for six years for five megacities suggests a statistically significant decreasing trend ranging from 1.5 to 4.19 μg/m³ (2%-8%) per year. Distinct diurnal, seasonal, and monthly variations are observed in the five cities due to the different site locations and local meteorology. All cities show the highest and lowest concentrations in the winter and monsoon months respectively except for Chennai which observed the lowest levels in April. All the cities consistently show morning peaks (~08: 00-10:00 h) and the lowest level in late afternoon hours (~15:00-16:00 h). We found that the PM_2.5 levels in the cities exceed WHO standards and Indian NAAQS for 50% and 33% of days in a year except for Chennai. Delhi is found to have more than 200 days of exceedances in a year and experiences an average 15 number of episodes per year when the level exceeds the Indian NAAQS. The trends in the exceedance with a varying threshold (20-380 μg/m³) suggest that not only is the annual mean PM_2.5 decreasing in Delhi but also the number of exceedances is decreasing. This decrease can be attributed to the recent policies and regulations implemented in Delhi and other cities for the abatement of air pollution. However, stricter compliance of the National Clean Air Program (NCAP) policies can further accelerate the reduction of the pollution levels.

Estimating Health Impacts Due to the Reduction of Particulate Air Pollution from the Household Sector Expected under Various Scenarios

Emissions from the household sector are the most significant source of air pollution in Poland, one of the most polluted countries in the EU. Estimated health impacts of the reduction of these emissions under three scenarios are presented. The EMEP4PL model and base year emission inventory were used to estimate average annual PM10 and PM2.5 concentrations with spatial resolution of 4 km × 4 km. The change in emissions under each of the scenarios was based on data from a survey on household boilers and insulation. Scenario 1 included replacement of all poor-quality coal-fired boilers with gas boilers; Scenario 2 included replacement of all poor-quality coal-fired boilers with low-emission boilers but still using solid fuels; and Scenario 3 included the thermal refurbishment of houses with the worst insulation. Impacts on the following health parameters were estimated: premature deaths (PD), Chronic Bronchitis (CB), Bronchitis in Children (BiC) and Work Days Lost (WDL). The concentration–response functions recommended by the WHO HRAPIE project were used. The analysis was conducted for two regions: Lower Silesia and Lodzkie province. The largest reduction of health impact was observed for Scenario 1. For Lower Silesia, the annual PD decreased by 1122 (34.3%), CB by 1516 (26.6%), BiC by 9602 (27.7%) and WDL by 481k (34.7%). For Lodzkie province, the largest impacts were estimated as decreases in PD by 1438 (29.9%), CB by 1502 (25.3%), BiC by 9880 (26.8%) and WDL by 669k (30.4%).

A Satellite-Based High-Resolution (1-km) Ambient PM2.5 Database for India over Two Decades (2000–2019): Applications for Air Quality Management

Fine particulate matter (PM2.5) is a major criteria pollutant affecting the environment, health and climate. In India where ground-based measurements of PM2.5 is scarce, it is important to have a long-term database at a high spatial resolution for an efficient air quality management plan. Here we develop and present a high-resolution (1-km) ambient PM2.5 database spanning two decades (2000–2019) for India. We convert aerosol optical depth from Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved by Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm to surface PM2.5 using a dynamic scaling factor from Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) data. The satellite-derived daily (24-h average) and annual PM2.5 show a R2 of 0.8 and 0.97 and root mean square error of 25.7 and 7.2 μg/m3, respectively against surface measurements from the Central Pollution Control Board India network. Population-weighted 20-year averaged PM2.5 over India is 57.3 μg/m3 (5–95 percentile ranges: 16.8–86.9) with a larger increase observed in the present decade (2010–2019) than in the previous decade (2000 to 2009). Poor air quality across the urban–rural transact suggests that this is a regional scale problem, a fact that is often neglected. The database is freely disseminated through a web portal ‘satellite-based application for air quality monitoring and management at a national scale’ (SAANS) for air quality management, epidemiological research and mass awareness.

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.