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Air pollution in Asia and the Pacific: Science-based solutions

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... These high pollution levels cause significant health impacts (Balakrishnan et al., 2014;Cohen et al., 2017;Landrigan et al., 2017;David et al., 2019;Hong et al., 2019). While for India their exact quantification remains uncertain, the scientific literature estimates large numbers, ranging between 483,000 and 1,267,000 cases of premature deaths annually from outdoor pollution, and 748,000-1,254,000 cases from indoor pollution (Lim et al., 2012;Forouzanfar et al., , 2016Chowdhury and Dey, 2016;WHO, 2016;Balakrishnan et al., 2019). ...
... It brings together information on future economic, energy and agricultural development, emission control potentials and costs, atmospheric dispersion and environmental sensitivities towards air pollution as shown in the SI (section S.2). The GAINS model has been applied widely for policy analyses in Europe (Amann et al., 2011), South Asia (Purohit et al., 2010Dholakia et al., 2013;Mir et al., 2016;Amann et al., 2017;Bhanarkar et al., 2018;Karambelas et al., 2018) and East Asia (Amann et al., 2008;Klimont et al., 2009;Zhao et al., 2013;Chen et al., 2015;Dong et al., 2015;Hong et al., 2019;Liu et al., 2019). ...
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Exposure to ambient particulate matter is a leading risk factor for environmental public health in India. While Indian authorities implemented several measures to reduce emissions from the power, industry and transportation sectors over the last years, such strategies appear to be insufficient to reduce the ambient fine particulate matter (PM2.5) concentration below the Indian National Ambient Air Quality Standard (NAAQS) of 40 μg/m3 across the country. This study explores pathways towards achieving the NAAQS in India in the context of the dynamics of social and economic development. In addition, to inform action at the subnational levels in India, we estimate the exposure to ambient air pollution in the current legislations and alternative policy scenarios based on simulations with the GAINS integrated assessment model. The analysis reveals that in many of the Indian States emission sources that are outside of their immediate jurisdictions make the dominating contributions to (population-weighted) ambient pollution levels of PM2.5. Consequently, most of the States cannot achieve significant improvements in their air quality and population exposure on their own without emission reductions in the surrounding regions, and any cost-effective strategy requires regionally coordinated approaches. Advanced technical emission control measures could provide NAAQS-compliant air quality for 60% of the Indian population. However, if combined with national sustainable development strategies, an additional 25% population will be provided with clean air, which appears to be a significant co-benefit on air quality (totaling 85%).
... This is not surprising as, due to its physical features, air pollution is often considered as a local/regional and short-term problem, even if it is of universal nature, i.e. occurring as a concomitant of development in most industrialized areas throughout the world. However, a global perspective is of interest due to the intercontinental transport of pollution [43,44], the serious global health burden of air pollution [1] and the intimate interactions between clean air policies and efforts to achieve the UN global sustainable development goals [45][46][47]. ...
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Importance When combusted indoors, solid fuels generate a large amount of pollutants such as fine particulate matter. Objective To assess the associations of solid fuel use for cooking and heating with cardiovascular and all-cause mortality. Design, Setting, and Participants This nationwide prospective cohort study recruited participants from 5 rural areas across China between June 2004 and July 2008; mortality follow-up was until January 1, 2014. A total of 271 217 adults without a self-reported history of physician-diagnosed cardiovascular disease at baseline were included, with a random subset (n = 10 892) participating in a resurvey after a mean interval of 2.7 years. Exposures Self-reported primary cooking and heating fuels (solid: coal, wood, or charcoal; clean: gas, electricity, or central heating), switching of fuel type before baseline, and use of ventilated cookstoves. Main Outcomes and Measures Death from cardiovascular and all causes, collected through established death registries. Results Among the 271 217 participants, the mean (SD) age was 51.0 (10.2) years, and 59% (n = 158 914) were women. A total of 66% (n = 179 952) of the participants reported regular cooking (at least weekly) and 60% (n = 163 882) reported winter heating, of whom 84% (n = 150 992) and 90% (n = 147 272) used solid fuels, respectively. There were 15 468 deaths, including 5519 from cardiovascular causes, documented during a mean (SD) of 7.2 (1.4) years of follow-up. Use of solid fuels for cooking was associated with greater risk of cardiovascular mortality (absolute rate difference [ARD] per 100 000 person-years, 135 [95% CI, 77-193]; hazard ratio [HR], 1.20 [95% CI, 1.02-1.41]) and all-cause mortality (ARD, 338 [95% CI, 249-427]; HR, 1.11 [95% CI, 1.03-1.20]). Use of solid fuels for heating was also associated with greater risk of cardiovascular mortality (ARD, 175 [95% CI, 118-231]; HR, 1.29 [95% CI, 1.06-1.55]) and all-cause mortality (ARD, 392 [95% CI, 297-487]; HR, 1.14 [95% CI, 1.03-1.26]). Compared with persistent solid fuel users, participants who reported having previously switched from solid to clean fuels for cooking had a lower risk of cardiovascular mortality (ARD, 138 [95% CI, 71-205]; HR, 0.83 [95% CI, 0.69-0.99]) and all-cause mortality (ARD, 407 [95% CI, 317-497]; HR, 0.87 [95% CI, 0.79-0.95]), while for heating, the ARDs were 193 (95% CI, 128-258) and 492 (95% CI, 383-601), and the HRs were 0.57 (95% CI, 0.42-0.77) and 0.67 (95% CI, 0.57-0.79), respectively. Among solid fuel users, use of ventilated cookstoves was also associated with lower risk of cardiovascular mortality (ARD, 33 [95% CI, −9 to 75]; HR, 0.89 [95% CI, 0.80-0.99]) and all-cause mortality (ARD, 87 [95% CI, 20-153]; HR, 0.91 [95% CI, 0.85-0.96]). Conclusions and Relevance In rural China, solid fuel use for cooking and heating was associated with higher risks of cardiovascular and all-cause mortality. These risks may be lower among those who had previously switched to clean fuels and those who used ventilation.
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Exposure to ambient fine particulate matter (PM2.5) is a leading contributor to diseases in India. Previous studies analysing emission source attributions were restricted by coarse model resolution and limited PM2.5 observations. We use a regional model informed by new observations to make the first high-resolution study of the sector-specific disease burden from ambient PM2.5 exposure in India. Observed annual mean PM2.5 concentrations exceed 100 μg m−3 and are well simulated by the model. We calculate that the emissions from residential energy use dominate (52%) population-weighted annual mean PM2.5 concentrations, and are attributed to 511,000 (95UI: 340,000–697,000) premature mortalities annually. However, removing residential energy use emissions would avert only 256,000 (95UI: 162,000–340,000), due to the non-linear exposure–response relationship causing health effects to saturate at high PM2.5 concentrations. Consequently, large reductions in emissions will be required to reduce the health burden from ambient PM2.5 exposure in India.
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Background: Household air pollution (HAP) from combustion of solid fuels is an important contributor to disease burden in low- and middle-income countries (LIC, and MIC). However, current HAP disease burden estimates are based on integrated exposure response curves that are not currently informed by quantitative HAP studies in LIC and MIC. While there is adequate evidence supporting causal relationships between HAP and respiratory disease, large cohort studies specifically examining relationships between quantitative measures of HAP exposure with cardiovascular disease are lacking. Objective: We aim to improve upon exposure proxies based on fuel type, and to reduce exposure misclassification by quantitatively measuring exposure across varying cooking fuel types and conditions in diverse geographies and socioeconomic settings. We leverage technology advancements to estimate household and personal PM2.5(particles below 2.5 μm in aerodynamic diameter) exposure within the large (N~250,000) multi-country (N~26) Prospective Urban and Rural Epidemiological (PURE) cohort study. Here, we detail the study protocol and the innovative methodologies being used to characterize HAP exposures, and their application in epidemiologic analyses. Methods/design: This study characterizes HAP PM2.5exposures for participants in rural communities in ten PURE countries with >10% solid fuel use at baseline (Bangladesh, Brazil, Chile, China, Colombia, India, Pakistan, South Africa, Tanzania, and Zimbabwe). PM2.5monitoring includes 48-h cooking area measurements in 4500 households and simultaneous personal monitoring of male and female pairs from 20% of the selected households. Repeat measurements occur in 20% of households to assess impacts of seasonality. Monitoring began in 2017, and will continue through 2019. The Ultrasonic Personal Aerosol Sampler (UPAS), a novel, robust, and inexpensive filter based monitor that is programmable through a dedicated mobile phone application is used for sampling. Pilot study field evaluation of cooking area measurements indicated high correlation between the UPAS and reference Harvard Impactors (r = 0.91; 95% CI: 0.84, 0.95; slope = 0.95). To facilitate tracking and to minimize contamination and analytical error, the samplers utilize barcoded filters and filter cartridges that are weighed pre- and post-sampling using a fully automated weighing system. Pump flow and pressure measurements, temperature and RH, GPS coordinates and semi-quantitative continuous particle mass concentrations based on filter differential pressure are uploaded to a central server automatically whenever the mobile phone is connected to the internet, with sampled data automatically screened for quality control parameters. A short survey is administered during the 48-h monitoring period. Post-weighed filters are further analyzed to estimate black carbon concentrations through a semi-automated, rapid, cost-effective image analysis approach. The measured PM2.5data will then be combined with PURE survey information on household characteristics and behaviours collected at baseline and during follow-up to develop quantitative HAP models for PM2.5exposures for all rural PURE participants (~50,000) and across different cooking fuel types within the 10 index countries. Both the measured (in the subset) and the modelled exposures will be used in separate longitudinal epidemiologic analyses to assess associations with cardiopulmonary mortality, and disease incidence. Discussion: The collected data and resulting characterization of cooking area and personal PM2.5exposures in multiple rural communities from 10 countries will better inform exposure assessment as well as future epidemiologic analyses assessing the relationships between quantitative estimates of chronic HAP exposure with adult mortality and incident cardiovascular and respiratory disease. This will provide refined and more accurate exposure estimates in global CVD related exposure-response analyses.
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Rationale: Forty percent of households worldwide burn biomass fuels for energy, which may be most the important contributor to household air pollution. Objective: To examine the association between household air pollution exposure and COPD outcomes in 13 resource-poor settings. Methods: We analyzed data from 12,396 adult participants living in 13 resource-poor, population-based settings. Household air pollution exposure was defined as using biomass materials as the primary fuel source in the home. We used multivariable regressions to assess the relationship between household air pollution exposure and COPD outcomes, evaluated for interactions, and conducted sensitivity analyses to test the robustness of our findings. Results: Average age was 54.9 years (44.2-59.6 years across settings), 48.5% were women (38.3%-54.5%), prevalence of household air pollution exposure was 38% (0.5%-99.6%), and 8.8% (1.7%-15.5%) had COPD. Participants with household air pollution exposure were 41% more likely to have COPD (adjusted OR=1.41, 95% CI 1.18 to 1.68) than those without the exposure, and 13.5% (6.4% to 20.6%) of COPD prevalence may due to household air pollution exposure, compared with 12.4% due to cigarette smoking. The association between household air pollution exposure and COPD was stronger in women (1.70, 1.24 to 2.32) than in men (1.21, 0.92 to 1.58). Conclusions: Household air pollution exposure was associated with a higher prevalence of COPD, particularly among women, and it is likely a leading population attributable risk factor for COPD in resource-poor settings.