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Ravishankara AR, David LM, Pierce JR, Venkataraman C. Outdoor air pollution in India is not only an urban problem. Proc Natl Acad Sci U S A 2020; 117:28640-28644. [PMID: 33139542 PMCID: PMC7682420 DOI: 10.1073/pnas.2007236117] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
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.
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Affiliation(s)
- A R Ravishankara
- Department of Chemistry, Colorado State University, Fort Collins, CO 80523;
- Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523
| | - Liji M David
- Department of Chemistry, Colorado State University, Fort Collins, CO 80523
- Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523
| | - Jeffrey R Pierce
- Department of Atmospheric Science, Colorado State University, Fort Collins, CO 80523
| | - Chandra Venkataraman
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, 400076 Mumbai, India
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52
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Puttaswamy N, Saidam S, Rajendran G, Arumugam K, Gupton S, Williams EW, Johnson CL, Panuwet P, Rajkumar S, Clark ML, Peel JL, Checkley W, Clasen T, Balakrishnan K, Barr DB. Cross-validation of biomonitoring methods for polycyclic aromatic hydrocarbon metabolites in human urine: Results from the formative phase of the Household Air Pollution Intervention Network (HAPIN) trial in India. J Chromatogr B Analyt Technol Biomed Life Sci 2020; 1154:122284. [PMID: 32755815 PMCID: PMC7501734 DOI: 10.1016/j.jchromb.2020.122284] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2020] [Revised: 07/17/2020] [Accepted: 07/24/2020] [Indexed: 01/23/2023]
Abstract
The Household Air Pollution Intervention Network (HAPIN) trial is evaluating health benefits of a liquefied petroleum gas (LPG) stove intervention in biomass cook-fuel using homes (n = 3200) in four low-and middle-income countries (LMICs) that include Peru, Guatemala, Rwanda and India. Longitudinal urine samples (n = 6000) collected from enrolled pregnant women, infants and older women will be analyzed for biomarkers associated with exposure and health outcomes. We report results from cross-validation of a lower cost high-performance liquid chromatography with fluorescence detection (HPLC-FLD) method with a higher resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the measurement of 1-hydroxypyrene (1PYR) and 2-naphthol (2NAP). Twenty-five split urine samples were analyzed by HPLC-FLD method at the India trial site in Chennai, India and by LC-MSMS method at the trial wide Biomarker Coordinating Center, Emory University, USA. The limits of detection (LOD) for the HPLC-FLD method were 0.02 ng/mL and 0.07 ng/mL for 2NAP and 1PYR, respectively. Bland-Altman analysis estimated a bias of 2.98 ng/ml for 2NAP (95% CI: -5.22, -0.75) and 0.09 ng/mL for 1PYR (95% CI: -0.02, 0.21) with HPLC-FLD levels being lower than LC-MSMS levels at higher concentrations. Analyses of additional urine samples (n = 119) collected during the formative phase of the HAPIN trial in India, showed 2NAP and 1PYR levels to be consistently above the limit of quantification (LOQ) and demonstrated the applicability of the method. The HPLC-FLD method can serve as a cost-effective and reliable analytical method to measure 2NAP and 1PYR in human urine in LMICs, within and beyond the HAPIN trial.
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Affiliation(s)
- Naveen Puttaswamy
- Department of Environmental Health Engineering, Faculty of Public Health, Sri Ramachandra Institute of Higher Education and Research, Chennai, TN, India.
| | - Sudhakar Saidam
- Department of Environmental Health Engineering, Faculty of Public Health, Sri Ramachandra Institute of Higher Education and Research, Chennai, TN, India
| | - Gayathri Rajendran
- Department of Environmental Health Engineering, Faculty of Public Health, Sri Ramachandra Institute of Higher Education and Research, Chennai, TN, India
| | - Kokila Arumugam
- Department of Environmental Health Engineering, Faculty of Public Health, Sri Ramachandra Institute of Higher Education and Research, Chennai, TN, India
| | - Savannah Gupton
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Erin W Williams
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Cierra L Johnson
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Parinya Panuwet
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Sarah Rajkumar
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA
| | - Maggie L Clark
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA
| | - Jennifer L Peel
- Department of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, CO, USA
| | - William Checkley
- Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, MD, USA; Center for Global Non-Communicable Diseases, Johns Hopkins University, Baltimore, MD, USA
| | - Thomas Clasen
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Kalpana Balakrishnan
- Department of Environmental Health Engineering, Faculty of Public Health, Sri Ramachandra Institute of Higher Education and Research, Chennai, TN, India
| | - Dana Boyd Barr
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
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53
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Rosenthal J, Arku RE, Baumgartner J, Brown J, Clasen T, Eisenberg JN, Hovmand P, Jagger P, Luke DA, Quinn A, Yadama GN. Systems Science Approaches for Global Environmental Health Research: Enhancing Intervention Design and Implementation for Household Air Pollution (HAP) and Water, Sanitation, and Hygiene (WASH) Programs. ENVIRONMENTAL HEALTH PERSPECTIVES 2020; 128:105001. [PMID: 33035121 PMCID: PMC7546437 DOI: 10.1289/ehp7010] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 09/13/2020] [Accepted: 09/15/2020] [Indexed: 05/23/2023]
Abstract
BACKGROUND Two of the most important causes of global disease fall in the realm of environmental health: household air pollution (HAP) and poor water, sanitation, and hygiene (WASH) conditions. Interventions, such as clean cookstoves, household water treatment, and improved sanitation facilities, have great potential to yield reductions in disease burden. However, in recent trials and implementation efforts, interventions to improve HAP and WASH conditions have shown few of the desired health gains, raising fundamental questions about current approaches. OBJECTIVES We describe how the failure to consider the complex systems that characterize diverse real-world conditions may doom promising new approaches prematurely. We provide examples of the application of systems approaches, including system dynamics, network analysis, and agent-based modeling, to the global environmental health priorities of HAP and WASH research and programs. Finally, we offer suggestions on how to approach systems science. METHODS Systems science applied to environmental health can address major challenges by a) enhancing understanding of existing system structures and behaviors that accelerate or impede aims; b) developing understanding and agreement on a problem among stakeholders; and c) guiding intervention and policy formulation. When employed in participatory processes that engage study populations, policy makers, and implementers, systems science helps ensure that research is responsive to local priorities and reflect real-world conditions. Systems approaches also help interpret unexpected outcomes by revealing emergent properties of the system due to interactions among variables, yielding complex behaviors and sometimes counterintuitive results. DISCUSSION Systems science offers powerful and underused tools to accelerate our ability to identify barriers and facilitators to success in environmental health interventions. This approach is especially useful in the context of implementation research because it explicitly accounts for the interaction of processes occurring at multiple scales, across social and environmental dimensions, with a particular emphasis on linkages and feedback among these processes. https://doi.org/10.1289/EHP7010.
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Affiliation(s)
- Joshua Rosenthal
- Division of Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Department of Health and Human Services, Washington, DC, USA
| | - Raphael E. Arku
- Department of Environmental Health Sciences, Department of Environmental Health Sciences, University of Massachusetts, Amherst, Amherst, Massachusetts, USA
| | - Jill Baumgartner
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada
| | - Joe Brown
- Department of Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Thomas Clasen
- Department of Environmental Health, Emory University, Atlanta, Georgia, USA
| | | | - Peter Hovmand
- Center for Community Health Integration, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Pamela Jagger
- School for Environment and Sustainability, University of Michigan, Ann Arbor, Michigan, USA
| | - Douglas A. Luke
- Center for Public Health Systems Science, Brown School, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Ashlinn Quinn
- Division of Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Department of Health and Human Services, Washington, DC, USA
| | - Gautam N. Yadama
- School of Social Work, Boston College, Boston, Massachusetts, USA
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54
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Feng X, Shao L, Xi C, Jones T, Zhang D, BéruBé K. Particle-induced oxidative damage by indoor size-segregated particulate matter from coal-burning homes in the Xuanwei lung cancer epidemic area, Yunnan Province, China. CHEMOSPHERE 2020; 256:127058. [PMID: 32450353 DOI: 10.1016/j.chemosphere.2020.127058] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 05/05/2020] [Accepted: 05/10/2020] [Indexed: 06/11/2023]
Abstract
Size-segregated samples of airborne particulate matter were collected at the coal-burning homes of the Hutou high lung cancer epidemic village and a comparison site Xize village of the Xuanwei County, Yuanan Province, by an Anderson Cascade Impact Sampler in winter and spring to study the toxicological characteristics of different-sized particles. The DNA damage caused by the water-soluble fractions of these size-segregated particles was analyzed by the plasmid scission assay, and the trace element compositions were determined by Inductively Coupled Plasma Mass Spectrometry. The DNA damage rate from the airborne particles in the high lung cancer incidence area was higher than that in Xize village. The different-sized particles have highly varying DNA damage rates, with the values being greater in the small size range than in the large size range. The particle-induced DNA damage rates had a significantly positive correlation with total water-soluble trace elements. Further analysis of the individual elements indicated that the water-soluble heavy metals Zn, Cu, Cd, Rb, Cs, and Sb had a positive correlation with the particle-induced DNA damage, implying that these water-soluble heavy metals played an important role in the DNA damage. The Sr had a negative correlation with the particle-induced DNA damage, suggesting that the water-soluble Sr might counter DNA damage. The mass concentrations of the total and individual water-soluble trace elements were mostly enriched in the small particle size ranges, thus implying the indoor airborne particles in the small size ranges would have a higher health risk.
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Affiliation(s)
- Xiaolei Feng
- State Key Laboratory of Coal Resources and Safe Mining and College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, 100083, China.
| | - Longyi Shao
- State Key Laboratory of Coal Resources and Safe Mining and College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, 100083, China.
| | - Chunxiu Xi
- State Key Laboratory of Coal Resources and Safe Mining and College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing, 100083, China.
| | - Tim Jones
- School of Earth and Ocean Sciences, Cardiff University, Museum Avenue, Cardiff, CF10, 3YE, UK.
| | - Daizhou Zhang
- Faculty of Environmental and Symbiotic Sciences, Prefectural University of Kumamoto, Kumamoto, 62-8502, Japan.
| | - Kelly BéruBé
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff, CF10, 3US, UK.
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55
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Tradeoffs between air pollution mitigation and meteorological response in India. Sci Rep 2020; 10:14796. [PMID: 32908156 PMCID: PMC7481194 DOI: 10.1038/s41598-020-71607-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Accepted: 07/30/2020] [Indexed: 11/08/2022] Open
Abstract
To curb the staggering health burden attributed to air pollution, the sustainable solution for India would be to reduce emissions in future. Here we project ambient fine particulate matter (PM2.5) exposure in India for the year 2030 under two contrasting air pollution emission pathways for two different climate scenarios based on Representative Concentration Pathways (RCP4.5 and RCP8.5). All-India average PM2.5 is expected to increase from 41.4 ± 26.5 μg m-3 in 2010 to 61.1 ± 40.8 and 58.2 ± 37.5 μg m-3 in 2030 under RCP8.5 and RCP4.5 scenarios, respectively if India follows the current legislation (baseline) emission pathway. In contrast, ambient PM2.5 in 2030 would be 40.2 ± 27.5 (for RCP8.5) and 39.2 ± 25.4 (for RCP4.5) μg m-3 following the short-lived climate pollutant (SLCP) mitigation emission pathway. We find that the lower PM2.5 in the mitigation pathway (34.2% and 32.6%, respectively for RCP8.5 and RCP4.5 relative to the baseline emission pathway) would come at a cost of 0.3-0.5 °C additional warming due to the direct impact of aerosols. The premature mortality burden attributable to ambient PM2.5 exposure is expected to rise from 2010 to 2030, but 381,790 (5-95% confidence interval, CI 275,620-514,600) deaths can be averted following the mitigation emission pathway relative to the baseline emission pathway. Therefore, we conclude that given the expected large health benefit, the mitigation emission pathway is a reasonable tradeoff for India despite the meteorological response. However, India needs to act more aggressively as the World Health Organization (WHO) annual air quality guideline (10 µg m-3) would remain far off.
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56
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Combining Biomass Gasification and Solid Oxid Fuel Cell for Heat and Power Generation: An Early-Stage Life Cycle Assessment. ENERGIES 2020. [DOI: 10.3390/en13112773] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Biomass-fueled combined heat and power systems (CHPs) can potentially offer environmental benefits compared to conventional separate production technologies. This study presents the first environmental life cycle assessment (LCA) of a novel high-efficiency bio-based power (HBP) technology, which combines biomass gasification with a 199 kW solid oxide fuel cell (SOFC) to produce heat and electricity. The aim is to identify the main sources of environmental impacts and to assess the potential environmental performance compared to benchmark technologies. The use of various biomass fuels and alternative allocation methods were scrutinized. The LCA results reveal that most of the environmental impacts of the energy supplied with the HBP technology are caused by the production of the biomass fuel. This contribution is higher for pelletized than for chipped biomass. Overall, HBP technology shows better environmental performance than heat from natural gas and electricity from the German/European grid. When comparing the HBP technology with the biomass-fueled ORC technology, the former offers significant benefits in terms of particulate matter (about 22 times lower), photochemical ozone formation (11 times lower), acidification (8 times lower) and terrestrial eutrophication (about 26 times lower). The environmental performance was not affected by the allocation parameter (exergy or economic) used. However, the tested substitution approaches showed to be inadequate to model multiple environmental impacts of CHP plants under the investigated context and goal.
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57
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Ojha N, Sharma A, Kumar M, Girach I, Ansari TU, Sharma SK, Singh N, Pozzer A, Gunthe SS. On the widespread enhancement in fine particulate matter across the Indo-Gangetic Plain towards winter. Sci Rep 2020; 10:5862. [PMID: 32246046 PMCID: PMC7125076 DOI: 10.1038/s41598-020-62710-8] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 03/09/2020] [Indexed: 11/20/2022] Open
Abstract
Fine particulate matter (PM2.5, aerodynamic diameter ≤2.5 µm) impacts the climate, reduces visibility and severely influences human health. The Indo-Gangetic Plain (IGP), home to about one-seventh of the world's total population and a hotspot of aerosol loading, observes strong enhancements in the PM2.5 concentrations towards winter. We performed high-resolution (12 km × 12 km) atmospheric chemical transport modeling (WRF-Chem) for the post-monsoon to winter transition to unravel the underlying dynamics and influences of regional emissions over the region. Model, capturing the observed variations to an extent, reveals that the spatial distribution of PM2.5 having patches of enhanced concentrations (≥100 µgm-3) during post-monsoon, evolves dramatically into a widespread enhancement across the IGP region during winter. A sensitivity simulation, supported by satellite observations of fires, shows that biomass-burning emissions over the northwest IGP play a crucial role during post-monsoon. Whereas, in contrast, towards winter, a large-scale decline in the air temperature, significantly shallower atmospheric boundary layer, and weaker winds lead to stagnant conditions (ventilation coefficient lower by a factor of ~4) thereby confining the anthropogenic influences closer to the surface. Such changes in the controlling processes from post-monsoon to winter transition profoundly affect the composition of the fine aerosols over the IGP region. The study highlights the need to critically consider the distinct meteorological processes of west-to-east IGP and changes in dominant sources from post-monsoon to winter in the formulation of future pollution mitigation policies.
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Affiliation(s)
- Narendra Ojha
- Space and Atmospheric Sciences division, Physical Research Laboratory, Ahmedabad, India.
| | - Amit Sharma
- EWRE Division, Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India
- Laboratory for Atmospheric Research, Washington State University, Pullman, USA
| | - Manish Kumar
- Atmospheric Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
| | - Imran Girach
- Space Physics Laboratory, Vikram Sarabhai Space Centre, Thiruvananthapuram, India
| | - Tabish U Ansari
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | - Som K Sharma
- Space and Atmospheric Sciences division, Physical Research Laboratory, Ahmedabad, India
| | - Narendra Singh
- Aryabhatta Research Institute of observational sciencES (ARIES), Nainital, India
| | - Andrea Pozzer
- Atmospheric Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
| | - Sachin S Gunthe
- EWRE Division, Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India.
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58
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Lee M, Lin L, Chen CY, Tsao Y, Yao TH, Fei MH, Fang SH. Forecasting Air Quality in Taiwan by Using Machine Learning. Sci Rep 2020; 10:4153. [PMID: 32139787 PMCID: PMC7057956 DOI: 10.1038/s41598-020-61151-7] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 02/20/2020] [Indexed: 01/09/2023] Open
Abstract
This study proposes a gradient-boosting-based machine learning approach for predicting the PM2.5 concentration in Taiwan. The proposed mechanism is evaluated on a large-scale database built by the Environmental Protection Administration, and Central Weather Bureau, Taiwan, which includes data from 77 air monitoring stations and 580 weather stations performing hourly measurements over 1 year. By learning from past records of PM2.5 and neighboring weather stations’ climatic information, the forecasting model works well for 24-h prediction at most air stations. This study also investigates the geographical and meteorological divergence for the forecasting results of seven regional monitoring areas. We also compare the prediction performance between Taiwan, Taipei, and London; analyze the impact of industrial pollution; and propose an enhanced version of the prediction model to improve the prediction accuracy. The results indicate that Taipei and London have similar prediction results because these two cities have similar topography (basin) and are financial centers without domestic pollution sources. The results also suggest that after considering industrial impacts by incorporating additional features from the Taichung and Thong-Siau power plants, the proposed method achieves significant improvement in the coefficient of determination (R2) from 0.58 to 0.71. Moreover, for Taichung City the root-mean-square error decreases from 8.56 for the conventional approach to 7.06 for the proposed method.
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Affiliation(s)
- Mike Lee
- Far Eastern Group, Taipei, Taiwan
| | - Larry Lin
- Department of Electrical Engineering, Yuan Ze University, Taoyuan City, Taiwan.,MOST Joint Research Center for AI Technology and All Vista Healthcare, Taipei, Taiwan
| | - Chih-Yuan Chen
- Department of Geography, Chinese Culture University, Taipei, Taiwan
| | - Yu Tsao
- Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan
| | - Ting-Hsuan Yao
- Department of Electrical Engineering, Yuan Ze University, Taoyuan City, Taiwan.,MOST Joint Research Center for AI Technology and All Vista Healthcare, Taipei, Taiwan
| | - Min-Han Fei
- Department of Electrical Engineering, Yuan Ze University, Taoyuan City, Taiwan.,MOST Joint Research Center for AI Technology and All Vista Healthcare, Taipei, Taiwan
| | - Shih-Hau Fang
- Department of Electrical Engineering, Yuan Ze University, Taoyuan City, Taiwan. .,MOST Joint Research Center for AI Technology and All Vista Healthcare, Taipei, Taiwan.
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59
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Qin N, Liang P, Wu C, Wang G, Xu Q, Xiong X, Wang T, Zolfo M, Segata N, Qin H, Knight R, Gilbert JA, Zhu TF. Longitudinal survey of microbiome associated with particulate matter in a megacity. Genome Biol 2020; 21:55. [PMID: 32127018 PMCID: PMC7055069 DOI: 10.1186/s13059-020-01964-x] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 02/18/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND While the physical and chemical properties of airborne particulate matter (PM) have been extensively studied, their associated microbiome remains largely unexplored. Here, we performed a longitudinal metagenomic survey of 106 samples of airborne PM2.5 and PM10 in Beijing over a period of 6 months in 2012 and 2013, including those from several historically severe smog events. RESULTS We observed that the microbiome composition and functional potential were conserved between PM2.5 and PM10, although considerable temporal variations existed. Among the airborne microorganisms, Propionibacterium acnes, Escherichia coli, Acinetobacter lwoffii, Lactobacillus amylovorus, and Lactobacillus reuteri dominated, along with several viral species. We further identified an extensive repertoire of genes involved in antibiotic resistance and detoxification, including transporters, transpeptidases, and thioredoxins. Sample stratification based on Air Quality Index (AQI) demonstrated that many microbial species, including those associated with human, dog, and mouse feces, exhibit AQI-dependent incidence dynamics. The phylogenetic and functional diversity of air microbiome is comparable to those of soil and water environments, as its composition likely derives from a wide variety of sources. CONCLUSIONS Airborne particulate matter accommodates rich and dynamic microbial communities, including a range of microbial elements that are associated with potential health consequences.
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Affiliation(s)
- Nan Qin
- Institute of Intestinal Diseases, Department of General Surgery, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China. .,Realbio Genomics Institute, Shanghai, 200050, China.
| | - Peng Liang
- School of Life Sciences, Peking University, Beijing, 100871, China.,School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, Ministry of Education Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology, Ministry of Education Key Laboratory of Bioinformatics, Tsinghua University, Beijing, 100084, China
| | - Chunyan Wu
- Realbio Genomics Institute, Shanghai, 200050, China
| | - Guanqun Wang
- School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, Ministry of Education Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology, Ministry of Education Key Laboratory of Bioinformatics, Tsinghua University, Beijing, 100084, China
| | - Qian Xu
- Institute of Intestinal Diseases, Department of General Surgery, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China.,Realbio Genomics Institute, Shanghai, 200050, China
| | - Xiao Xiong
- Realbio Genomics Institute, Shanghai, 200050, China
| | | | - Moreno Zolfo
- Centre for Integrative Biology, University of Trento, 38123, Trento, Italy
| | - Nicola Segata
- Centre for Integrative Biology, University of Trento, 38123, Trento, Italy
| | - Huanlong Qin
- Institute of Intestinal Diseases, Department of General Surgery, Shanghai Tenth People's Hospital, Tongji University School of Medicine, Shanghai, 200072, China
| | - Rob Knight
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA.,Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA.,Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Jack A Gilbert
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA. .,Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA. .,Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, 92093, USA.
| | - Ting F Zhu
- School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Beijing Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, Ministry of Education Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology, Ministry of Education Key Laboratory of Bioinformatics, Tsinghua University, Beijing, 100084, China.
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60
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Elias-Kirma S, Artzy-Schnirman A, Das P, Heller-Algazi M, Korin N, Sznitman J. In situ-Like Aerosol Inhalation Exposure for Cytotoxicity Assessment Using Airway-on-Chips Platforms. Front Bioeng Biotechnol 2020; 8:91. [PMID: 32154228 PMCID: PMC7044134 DOI: 10.3389/fbioe.2020.00091] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 01/31/2020] [Indexed: 12/02/2022] Open
Abstract
Lung exposure to inhaled particulate matter (PM) is known to injure the airway epithelium via inflammation, a phenomenon linked to increased levels of global morbidity and mortality. To evaluate physiological outcomes following PM exposure and concurrently circumvent the use of animal experiments, in vitro approaches have typically relied on traditional assays with plates or well inserts. Yet, these manifest drawbacks including the inability to capture physiological inhalation conditions and aerosol deposition characteristics relative to in vivo human conditions. Here, we present a novel airway-on-chip exposure platform that emulates the epithelium of human bronchial airways with critical cellular barrier functions at an air-liquid interface (ALI). As a proof-of-concept for in vitro lung cytotoxicity testing, we recapitulate a well-characterized cell apoptosis pathway, induced through exposure to 2 μm airborne particles coated with αVR1 antibody that leads to significant loss in cell viability across the recapitulated airway epithelium. Notably, our in vitro inhalation assays enable simultaneous aerosol exposure across multiple airway chips integrated within a larger bronchial airway tree model, under physiological respiratory airflow conditions. Our findings underscore in situ-like aerosol deposition outcomes where patterns depend on respiratory flows across the airway tree geometry and gravitational orientation, as corroborated by concurrent numerical simulations. Our airway-on-chips not only highlight the prospect of realistic in vitro exposure assays in recapitulating characteristic local in vivo deposition outcomes, such platforms open opportunities toward advanced in vitro exposure assays for preclinical cytotoxicity and drug screening applications.
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Affiliation(s)
| | | | | | | | | | - Josué Sznitman
- Department of Biomedical Engineering, Technion – Israel Institute of Technology, Haifa, Israel
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61
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Dou Y, Zhang W, Kaiser A. Electrospinning of Metal-Organic Frameworks for Energy and Environmental Applications. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2020; 7:1902590. [PMID: 32042570 PMCID: PMC7001619 DOI: 10.1002/advs.201902590] [Citation(s) in RCA: 87] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Revised: 11/01/2019] [Indexed: 05/05/2023]
Abstract
Herein, recent developments of metal-organic frameworks (MOFs) structured into nanofibers by electrospinning are summarized, including the fabrication, post-treatment via pyrolysis, properties, and use of the resulting MOF nanofiber architectures. The fabrication and post-treatment of the MOF nanofiber architectures are described systematically by two routes: i) the direct electrospinning of MOF-polymer nanofiber composites, and ii) the surface decoration of nanofiber structures with MOFs. The unique properties and performance of the different types of MOF nanofibers and their derivatives are explained in respect to their use in energy and environmental applications, including air filtration, water treatment, gas storage and separation, electrochemical energy conversion and storage, and heterogeneous catalysis. Finally, challenges with the fabrication of MOF nanofibers, limitations for their use, and trends for future developments are presented.
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Affiliation(s)
- Yibo Dou
- Department of Energy Conversion and StorageTechnical University of DenmarkAnker Engelunds Vej, Building 301DK‐2800Kongens LyngbyDenmark
| | - Wenjing Zhang
- Department of Environmental EngineeringTechnical University of DenmarkMiljøvej 113DK‐2800Kongens LyngbyDenmark
| | - Andreas Kaiser
- Department of Energy Conversion and StorageTechnical University of DenmarkAnker Engelunds Vej, Building 301DK‐2800Kongens LyngbyDenmark
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Air Pollution in Rural Households Due to Solid Biomass Fuel Use and Its Health Impacts. LECTURE NOTES IN CIVIL ENGINEERING 2020. [DOI: 10.1007/978-981-15-1334-3_4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Shaffer RM, Sellers SP, Baker MG, de Buen Kalman R, Frostad J, Suter MK, Anenberg SC, Balbus J, Basu N, Bellinger DC, Birnbaum L, Brauer M, Cohen A, Ebi KL, Fuller R, Grandjean P, Hess JJ, Kogevinas M, Kumar P, Landrigan PJ, Lanphear B, London SJ, Rooney AA, Stanaway JD, Trasande L, Walker K, Hu H. Improving and Expanding Estimates of the Global Burden of Disease Due to Environmental Health Risk Factors. ENVIRONMENTAL HEALTH PERSPECTIVES 2019; 127:105001. [PMID: 31626566 PMCID: PMC6867191 DOI: 10.1289/ehp5496] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2019] [Revised: 08/20/2019] [Accepted: 09/25/2019] [Indexed: 05/22/2023]
Abstract
BACKGROUND The Global Burden of Disease (GBD) study, coordinated by the Institute for Health Metrics and Evaluation (IHME), produces influential, data-driven estimates of the burden of disease and premature death due to major risk factors. Expanded quantification of disease due to environmental health (EH) risk factors, including climate change, will enhance accuracy of GBD estimates, which will contribute to developing cost-effective policies that promote prevention and achieving Sustainable Development Goals. OBJECTIVES We review key aspects of the GBD for the EH community and introduce the Global Burden of Disease-Pollution and Health Initiative (GBD-PHI), which aims to work with IHME and the GBD study to improve estimates of disease burden attributable to EH risk factors and to develop an innovative approach to estimating climate-related disease burden-both current and projected. METHODS We discuss strategies for improving GBD quantification of specific EH risk factors, including air pollution, lead, and climate change. We highlight key methodological challenges, including new EH risk factors, notably evidence rating and global exposure assessment. DISCUSSION A number of issues present challenges to the scope and accuracy of current GBD estimates for EH risk factors. For air pollution, minimal data exist on the exposure-risk relationships associated with high levels of pollution; epidemiological studies in high pollution regions should be a research priority. For lead, the GBD's current methods do not fully account for lead's impact on neurodevelopment; innovative methods to account for subclinical effects are needed. Decisions on inclusion of additional EH risk-outcome pairs need to be guided by findings of systematic reviews, the size of exposed populations, feasibility of global exposure estimates, and predicted trends in exposures and diseases. Neurotoxicants, endocrine-disrupting chemicals, and climate-related factors should be high priorities for incorporation into upcoming iterations of the GBD study. Enhancing the scope and methods will improve the GBD's estimates and better guide prevention policy. https://doi.org/10.1289/EHP5496.
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Affiliation(s)
- Rachel M. Shaffer
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Samuel P. Sellers
- Center for Health and the Global Environment, University of Washington, Seattle, Washington, USA
| | - Marissa G. Baker
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
| | - Rebeca de Buen Kalman
- Evans School of Public Policy and Governance, University of Washington, Seattle, Washington, USA
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
- Department of Health Metrics Sciences, University of Washington, Seattle, Washington, USA
| | - Megan K. Suter
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Susan C. Anenberg
- Milken Institute School of Public Health, George Washington University, Washington, DC, USA
| | - John Balbus
- Office of the Director, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA
| | - Niladri Basu
- Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Quebec, Canada
| | - David C. Bellinger
- Department of Neurology, Harvard Medical School, Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Linda Birnbaum
- Office of the Director, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA
| | - Michael Brauer
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Aaron Cohen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
- Health Effects Institute, Boston, Massachusetts, USA
| | - Kristie L. Ebi
- Center for Health and the Global Environment, University of Washington, Seattle, Washington, USA
| | | | - Philippe Grandjean
- Department of Public Health, University of Southern Denmark, Odense, Denmark
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Jeremy J. Hess
- Center for Health and the Global Environment, University of Washington, Seattle, Washington, USA
| | | | - Pushpam Kumar
- United Nations Programme on the Environment, Nairobi, Kenya
| | - Philip J. Landrigan
- Program in Global Public Health and the Common Good, Boston College, Chestnut Hill, Massachusetts, USA
- Global Observatory on Pollution and Health, Boston College, Chestnut Hill, Massachusetts, USA
| | - Bruce Lanphear
- Simon Fraser University, Vancouver, British Columbia, Canada
| | - Stephanie J. London
- Epidemiology Branch, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA
| | - Andrew A. Rooney
- Division of the National Toxicology Program, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA
| | - Jeffrey D. Stanaway
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, USA
| | - Leonardo Trasande
- Department of Pediatrics, New York University School of Medicine, New York, New York, USA
- NYU Global Institute of Public Health, New York University, New York, New York, USA
| | - Katherine Walker
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Howard Hu
- Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, Washington, USA
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
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Shen G, Ru M, Du W, Zhu X, Zhong Q, Chen Y, Shen H, Yun X, Meng W, Liu J, Cheng H, Hu J, Guan D, Tao S. Impacts of air pollutants from rural Chinese households under the rapid residential energy transition. Nat Commun 2019; 10:3405. [PMID: 31363099 PMCID: PMC6667435 DOI: 10.1038/s41467-019-11453-w] [Citation(s) in RCA: 86] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 07/16/2019] [Indexed: 12/25/2022] Open
Abstract
Rural residential energy consumption in China is experiencing a rapid transition towards clean energy, nevertheless, solid fuel combustion remains an important emission source. Here we quantitatively evaluate the contribution of rural residential emissions to PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 μm) and the impacts on health and climate. The clean energy transitions result in remarkable reductions in the contributions to ambient PM2.5, avoiding 130,000 (90,000-160,000) premature deaths associated with PM2.5 exposure. The climate forcing associated with this sector declines from 0.057 ± 0.016 W/m2 in 1992 to 0.031 ± 0.008 W/m2 in 2012. Despite this, the large remaining quantities of solid fuels still contributed 14 ± 10 μg/m3 to population-weighted PM2.5 in 2012, which comprises 21 ± 14% of the overall population-weighted PM2.5 from all sources. Rural residential emissions affect not only rural but urban air quality, and the impacts are highly seasonal and location dependent.
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Affiliation(s)
- Guofeng Shen
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
| | - Muye Ru
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
- Nicholas school of the Environment, Duke University, Durham, NC, 27705, USA
| | - Wei Du
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
| | - Xi Zhu
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
| | - Qirui Zhong
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
| | - Yilin Chen
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Huizhong Shen
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA
| | - Xiao Yun
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
| | - Wenjun Meng
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
| | - Junfeng Liu
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
| | - Hefa Cheng
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
| | - Jianying Hu
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China
| | - Dabo Guan
- School of International Development, University of East Anglia, Norwich, Norfolk, NR4 7TJ, UK
| | - Shu Tao
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Peking University, 100871, Beijing, China.
- Sino-French Institute for Earth System Science, Peking University, 100871, Beijing, China.
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Chowdhury S, Dey S, Guttikunda S, Pillarisetti A, Smith KR, Di Girolamo L. Indian annual ambient air quality standard is achievable by completely mitigating emissions from household sources. Proc Natl Acad Sci U S A 2019; 116:10711-10716. [PMID: 30988190 PMCID: PMC6561163 DOI: 10.1073/pnas.1900888116] [Citation(s) in RCA: 109] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
Exposures to ambient and household fine-particulate matter (PM2.5) together are among the largest single causes of premature mortality in India according to the Global Burden of Disease Studies (GBD). Several recent investigations have estimated that household emissions are the largest contributor to ambient PM2.5 exposure in the country. Using satellite-derived district-level PM2.5 exposure and an Eulerian photochemical dispersion model CAMx (Comprehensive Air Quality Model with Extensions), we estimate the benefit in terms of population exposure of mitigating household sources--biomass for cooking, space- and water-heating, and kerosene for lighting. Complete mitigation of emissions from only these household sources would reduce India-wide, population-weighted average annual ambient PM2.5 exposure by 17.5, 11.9, and 1.3%, respectively. Using GBD methods, this translates into reductions in Indian premature mortality of 6.6, 5.5, and 0.6%. If PM2.5 emissions from all household sources are completely mitigated, 103 (of 597) additional districts (187 million people) would meet the Indian annual air-quality standard (40 μg m-3) compared with baseline (2015) when 246 districts (398 million people) met the standard. At 38 μg m-3, after complete mitigation of household sources, compared with 55.1 μg m-3 at baseline, the mean annual national population-based concentration would meet the standard, although highly polluted areas, such as Delhi, would remain out of attainment. Our results support expansion of programs designed to promote clean household fuels and rural electrification to achieve improved air quality at regional scales, which also has substantial additional health benefits from directly reducing household air pollution exposures.
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Affiliation(s)
- Sourangsu Chowdhury
- Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi 110016, India
- School of Public Health, University of California, Berkeley, CA 94720-7360
| | - Sagnik Dey
- Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi 110016, India;
- School of Public Policy, Indian Institute of Technology Delhi, New Delhi 110016, India
| | | | - Ajay Pillarisetti
- School of Public Health, University of California, Berkeley, CA 94720-7360
| | - Kirk R Smith
- School of Public Health, University of California, Berkeley, CA 94720-7360;
- Collaborative Clean Air Policy Centre, Delhi 110003, India
| | - Larry Di Girolamo
- Department of Atmospheric Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801
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Modeling the Impact of an Indoor Air Filter on Air Pollution Exposure Reduction and Associated Mortality in Urban Delhi Household. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16081391. [PMID: 30999693 PMCID: PMC6518106 DOI: 10.3390/ijerph16081391] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Revised: 04/13/2019] [Accepted: 04/14/2019] [Indexed: 11/16/2022]
Abstract
Indoor exposure to fine particulate matter (PM2.5) is a prominent health concern. However, few studies have examined the effectiveness of long-term use of indoor air filters for reduction of PM2.5 exposure and associated decrease in adverse health impacts in urban India. We conducted 20 simulations of yearlong personal exposure to PM2.5 in urban Delhi using the National Institute of Standards and Technology's CONTAM program (NIST, Gaithersburg, MD, USA). Simulation scenarios were developed to examine different air filter efficiencies, use schedules, and the influence of a smoker at home. We quantified associated mortality reductions with Household Air Pollution Intervention Tool (HAPIT, University of California, Berkeley, CA, USA). Without an air filter, we estimated an annual mean PM2.5 personal exposure of 103 µg/m3 (95% Confidence Interval (CI): 93, 112) and 137 µg/m3 (95% CI: 125, 149) for households without and with a smoker, respectively. All day use of a high-efficiency particle air (HEPA) filter would reduce personal PM2.5 exposure to 29 µg/m3 and 30 µg/m3, respectively. The reduced personal PM2.5 exposure from air filter use is associated with 8-37% reduction in mortality attributable to PM2.5 pollution in Delhi. The findings of this study indicate that air filter may provide significant improvements in indoor air quality and result in health benefits.
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Spatial-Temporal Evolution of PM 2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014⁻2017. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16060985. [PMID: 30893835 PMCID: PMC6466118 DOI: 10.3390/ijerph16060985] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 03/11/2019] [Accepted: 03/17/2019] [Indexed: 11/17/2022]
Abstract
PM2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM2.5 data in 338 Chinese cities during 2014–2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the temporal and spatial characteristics of PM2.5 patterns and a spatial econometric model to quantify the socio-economic driving factors of PM2.5 concentration changes. The results are as follows: (1) The annual average value of PM2.5 concentration decreased year by year and the monthly average showed a U-shaped curve from January to December. The daily mean value of PM2.5 concentration had the characteristics of pulse-type fluctuation and the hourly variation presented a bimodal curve. (2) During 2014–2017, the overall PM2.5 pollution reduced significantly, but that of more than two-thirds of cities still exceeded the standard value (35 μg/m3) regulated by Chinese government. PM2.5 pollution patterns showed high values in central and eastern Chinese cities and low values in peripheral areas, with the distinction evident along the same line that delineates China’s uneven population distribution. (3) Population agglomeration, industrial development, foreign investment, transportation, and pollution emissions contributed to the increase of PM2.5 concentration. Urban population density contributed most significantly while economic development and technological progress reduced PM2.5 concentration. The results also suggest that China in general remains a “pollution shelter” for foreign-funded enterprises.
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David LM, Ravishankara AR, Kodros JK, Pierce JR, Venkataraman C, Sadavarte P. Premature Mortality Due to PM 2.5 Over India: Effect of Atmospheric Transport and Anthropogenic Emissions. GEOHEALTH 2019; 3:2-10. [PMID: 32159019 PMCID: PMC7007096 DOI: 10.1029/2018gh000169] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 11/09/2018] [Accepted: 11/19/2018] [Indexed: 05/20/2023]
Abstract
The annual premature mortality in India attributed to exposure to ambient particulate matter (PM2.5) exceeds 1 million (Cohen et al., 2017, https://doi.org/10.1016/S0140-6736(17)30505-6). Studies have estimated sector-specific premature mortality from ambient PM2.5 exposure in India and shown residential energy use is the dominant contributing sector. In this study, we estimate the contribution of PM2.5 and premature mortality from six regions of India in 2012 using the global chemical-transport model. We calculate how premature mortality in India is determined by the transport of pollution from different regions. Of the estimated 1.1 million annual premature deaths from PM2.5 in India, about ~60% was from anthropogenic pollutants emitted from within the region in which premature mortality occurred, ~19% was from transport of anthropogenic pollutants between different regions within India, ~16% was due to anthropogenic pollutants emitted outside of India, and ~4% was associated with natural PM2.5 sources. The emissions from Indo Gangetic Plain contributed to ~46% of total premature mortality over India, followed by Southern India (13%). Indo Gangetic Plain also contributed (~8%) to the most premature mortalities in other regions of India through transport. More than 50% of the premature mortality in Northern, Eastern, Western, and Central India was due to transport of PM2.5 from regions outside of these individual regions. Our results indicate that reduction in anthropogenic emissions over India, as well as its neighboring regions, will be required to reduce the health impact of ambient PM2.5 in India.
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Affiliation(s)
- Liji M. David
- Department of ChemistryColorado State UniversityFort CollinsCOUSA
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - A. R. Ravishankara
- Department of ChemistryColorado State UniversityFort CollinsCOUSA
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - John K. Kodros
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - Jeffrey R. Pierce
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - Chandra Venkataraman
- Department of Chemical EngineeringIndian Institute of Technology BombayMumbaiIndia
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Balakrishnan K, Dey S, Gupta T, Dhaliwal RS, Brauer M, Cohen AJ, Stanaway JD, Beig G, Joshi TK, Aggarwal AN, Sabde Y, Sadhu H, Frostad J, Causey K, Godwin W, Shukla DK, Kumar GA, Varghese CM, Muraleedharan P, Agrawal A, Anjana RM, Bhansali A, Bhardwaj D, Burkart K, Cercy K, Chakma JK, Chowdhury S, Christopher DJ, Dutta E, Furtado M, Ghosh S, Ghoshal AG, Glenn SD, Guleria R, Gupta R, Jeemon P, Kant R, Kant S, Kaur T, Koul PA, Krish V, Krishna B, Larson SL, Madhipatla K, Mahesh PA, Mohan V, Mukhopadhyay S, Mutreja P, Naik N, Nair S, Nguyen G, Odell CM, Pandian JD, Prabhakaran D, Prabhakaran P, Roy A, Salvi S, Sambandam S, Saraf D, Sharma M, Shrivastava A, Singh V, Tandon N, Thomas NJ, Torre A, Xavier D, Yadav G, Singh S, Shekhar C, Vos T, Dandona R, Reddy KS, Lim SS, Murray CJL, Venkatesh S, Dandona L. The impact of air pollution on deaths, disease burden, and life expectancy across the states of India: the Global Burden of Disease Study 2017. Lancet Planet Health 2019; 3:e26-e39. [PMID: 30528905 PMCID: PMC6358127 DOI: 10.1016/s2542-5196(18)30261-4] [Citation(s) in RCA: 273] [Impact Index Per Article: 54.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Revised: 10/18/2018] [Accepted: 11/02/2018] [Indexed: 05/19/2023]
Abstract
BACKGROUND Air pollution is a major planetary health risk, with India estimated to have some of the worst levels globally. To inform action at subnational levels in India, we estimated the exposure to air pollution and its impact on deaths, disease burden, and life expectancy in every state of India in 2017. METHODS We estimated exposure to air pollution, including ambient particulate matter pollution, defined as the annual average gridded concentration of PM2.5, and household air pollution, defined as percentage of households using solid cooking fuels and the corresponding exposure to PM2.5, across the states of India using accessible data from multiple sources as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. The states were categorised into three Socio-demographic Index (SDI) levels as calculated by GBD 2017 on the basis of lag-distributed per-capita income, mean education in people aged 15 years or older, and total fertility rate in people younger than 25 years. We estimated deaths and disability-adjusted life-years (DALYs) attributable to air pollution exposure, on the basis of exposure-response relationships from the published literature, as assessed in GBD 2017; the proportion of total global air pollution DALYs in India; and what the life expectancy would have been in each state of India if air pollution levels had been less than the minimum level causing health loss. FINDINGS The annual population-weighted mean exposure to ambient particulate matter PM2·5 in India was 89·9 μg/m3 (95% uncertainty interval [UI] 67·0-112·0) in 2017. Most states, and 76·8% of the population of India, were exposed to annual population-weighted mean PM2·5 greater than 40 μg/m3, which is the limit recommended by the National Ambient Air Quality Standards in India. Delhi had the highest annual population-weighted mean PM2·5 in 2017, followed by Uttar Pradesh, Bihar, and Haryana in north India, all with mean values greater than 125 μg/m3. The proportion of population using solid fuels in India was 55·5% (54·8-56·2) in 2017, which exceeded 75% in the low SDI states of Bihar, Jharkhand, and Odisha. 1·24 million (1·09-1·39) deaths in India in 2017, which were 12·5% of the total deaths, were attributable to air pollution, including 0·67 million (0·55-0·79) from ambient particulate matter pollution and 0·48 million (0·39-0·58) from household air pollution. Of these deaths attributable to air pollution, 51·4% were in people younger than 70 years. India contributed 18·1% of the global population but had 26·2% of the global air pollution DALYs in 2017. The ambient particulate matter pollution DALY rate was highest in the north Indian states of Uttar Pradesh, Haryana, Delhi, Punjab, and Rajasthan, spread across the three SDI state groups, and the household air pollution DALY rate was highest in the low SDI states of Chhattisgarh, Rajasthan, Madhya Pradesh, and Assam in north and northeast India. We estimated that if the air pollution level in India were less than the minimum causing health loss, the average life expectancy in 2017 would have been higher by 1·7 years (1·6-1·9), with this increase exceeding 2 years in the north Indian states of Rajasthan, Uttar Pradesh, and Haryana. INTERPRETATION India has disproportionately high mortality and disease burden due to air pollution. This burden is generally highest in the low SDI states of north India. Reducing the substantial avoidable deaths and disease burden from this major environmental risk is dependent on rapid deployment of effective multisectoral policies throughout India that are commensurate with the magnitude of air pollution in each state. FUNDING Bill & Melinda Gates Foundation; and Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.
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Conibear L, Butt EW, Knote C, Spracklen DV, Arnold SR. Current and Future Disease Burden From Ambient Ozone Exposure in India. GEOHEALTH 2018; 2:334-355. [PMID: 32159006 PMCID: PMC7007144 DOI: 10.1029/2018gh000168] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 10/09/2018] [Accepted: 10/09/2018] [Indexed: 05/22/2023]
Abstract
Long-term ambient ozone (O3) exposure is a risk factor for human health. We estimate the source-specific disease burden associated with long-term O3 exposure in India at high spatial resolution using updated risk functions from the American Cancer Society Cancer Prevention Study II. We estimate 374,000 (95UI: 140,000-554,000) annual premature mortalities using the updated risk function in India in 2015, 200% larger than estimates using the earlier American Cancer Society Cancer Prevention Study II risk function. We find that land transport emissions dominate the source contribution to this disease burden (35%), followed by emissions from power generation (23%). With no change in emissions by 2050, we estimate 1,126,000 (95UI: 421,000-1,667,000) annual premature mortalities, an increase of 200% relative to 2015 due to population aging and growth increasing the number of people susceptible to air pollution. We find that the International Energy Agency New Policy Scenario provides small changes (+1%) to this increasing disease burden from the demographic transition. Under the International Energy Agency Clean Air Scenario we estimate 791,000 (95UI: 202,000-1,336,000) annual premature mortalities in 2050, avoiding 335,000 annual premature mortalities (45% of the increase) compared to the scenario of no emission change. Our study highlights that critical public health benefits are possible with stringent emission reductions, despite population growth and aging increasing the attributable disease burden from O3 exposure even under such strong emission reductions. The disease burden attributable to ambient fine particulate matter exposure dominates that from ambient O3 exposure in the present day, while in the future, they may be similar in magnitude.
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Affiliation(s)
- Luke Conibear
- Engineering and Physical Sciences Research Council (EPSRC) Centre for Doctoral Training (CDT) in BioenergyUniversity of LeedsLeedsUK
- Institute for Climate and Atmospheric Science, School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - Edward W. Butt
- Institute for Climate and Atmospheric Science, School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | | | - Dominick V. Spracklen
- Institute for Climate and Atmospheric Science, School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - Stephen R. Arnold
- Institute for Climate and Atmospheric Science, School of Earth and EnvironmentUniversity of LeedsLeedsUK
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Aunan K, Ma Q, Lund MT, Wang S. Population-weighted exposure to PM 2.5 pollution in China: An integrated approach. ENVIRONMENT INTERNATIONAL 2018; 120:111-120. [PMID: 30077943 DOI: 10.1016/j.envint.2018.07.042] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 07/19/2018] [Accepted: 07/27/2018] [Indexed: 05/22/2023]
Abstract
Fine particulate matter air pollution (PM2.5) is a major risk factor for premature death globally. Studies of the PM2.5 health burden usually treat exposure to ambient air pollution (AAP) and household air pollution from solid fuels (HAP) as separate risk factors. AAP and HAP can, however, be closely interrelated. Taking as the starting point that the total exposure to PM2.5 is what matters for health, and recognizing the curvilinear form of exposure-response functions for important health effects, we develop a method for estimating the total annual mean population-weighted personal exposure, denoted integrated population-weighted exposure (IPWE). To establish the IPWE in China, we used recent emission inventories, Chemical Transport Models, China Census data on population and residential fuel use, and estimates of the PM2.5 exposure among solid fuel users. We found an IPWE of 151 [123-179] μg/m3, of which 62-74% was attributable to residential solid fuels through HAP exposure and the residential sector emissions' contribution to AAP. We found large disparities in the PM2.5 exposure burden, with an estimated IPWE in rural populations nearly twice the level in urban populations. Using the IPWE metric, we estimated that 1.15 [1.09-1.19] million premature deaths were attributable to PM2.5 exposure annually in the period 2010-2013. Using the same data set, but calculating premature deaths from AAP and HAP in isolation, the estimated number was nearly 50% higher. The IPWE metric enables integration across AAP and HAP in policy analyses and could mitigate the concern of a potential double counting of the health burden that may arise from treating AAP and HAP as separate health risk factors.
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Affiliation(s)
- Kristin Aunan
- Center for International Climate Research (CICERO), P.O. Box 1129 Blindern, N-0318 Oslo, Norway.
| | - Qiao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Marianne T Lund
- Center for International Climate Research (CICERO), P.O. Box 1129 Blindern, N-0318 Oslo, Norway
| | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
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73
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Gould CF, Urpelainen J. LPG as a Clean Cooking Fuel: Adoption, Use, and Impact in Rural India. ENERGY POLICY 2018; 122:395-408. [PMID: 32581420 PMCID: PMC7314235 DOI: 10.1016/j.enpol.2018.07.042] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Liquefied petroleum gas (LPG) is by far the most popular clean cooking fuel in rural India, but how rural households use it remains poorly understood. Using the 2014-2015 ACCESS survey with over 8,500 households from six energy-poor Indian states, we offer a broad but detailed survey of LPG use in rural India. We find that (i) fuel costs are a critical obstacle to widespread adoption, (ii) fuel stacking is the prevailing norm as few households stop using firewood when adopting LPG, and (iii) both users and non-users have highly positive views of LPG as a convenient and clean cooking fuel. These findings show that expanding LPG use offers great promise in rural India, but affordability prevents a complete transition from traditional biomass to clean cooking fuels.
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74
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Weagle CL, Snider G, Li C, van Donkelaar A, Philip S, Bissonnette P, Burke J, Jackson J, Latimer R, Stone E, Abboud I, Akoshile C, Anh NX, Brook JR, Cohen A, Dong J, Gibson MD, Griffith D, He KB, Holben BN, Kahn R, Keller CA, Kim JS, Lagrosas N, Lestari P, Khian YL, Liu Y, Marais EA, Martins JV, Misra A, Muliane U, Pratiwi R, Quel EJ, Salam A, Segev L, Tripathi SN, Wang C, Zhang Q, Brauer M, Rudich Y, Martin RV. Global Sources of Fine Particulate Matter: Interpretation of PM 2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2018; 52:11670-11681. [PMID: 30215246 DOI: 10.1021/acs.est.8b01658] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Exposure to ambient fine particulate matter (PM2.5) is a leading risk factor for the global burden of disease. However, uncertainty remains about PM2.5 sources. We use a global chemical transport model (GEOS-Chem) simulation for 2014, constrained by satellite-based estimates of PM2.5 to interpret globally dispersed PM2.5 mass and composition measurements from the ground-based surface particulate matter network (SPARTAN). Measured site mean PM2.5 composition varies substantially for secondary inorganic aerosols (2.4-19.7 μg/m3), mineral dust (1.9-14.7 μg/m3), residual/organic matter (2.1-40.2 μg/m3), and black carbon (1.0-7.3 μg/m3). Interpretation of these measurements with the GEOS-Chem model yields insight into sources affecting each site. Globally, combustion sectors such as residential energy use (7.9 μg/m3), industry (6.5 μg/m3), and power generation (5.6 μg/m3) are leading sources of outdoor global population-weighted PM2.5 concentrations. Global population-weighted organic mass is driven by the residential energy sector (64%) whereas population-weighted secondary inorganic concentrations arise primarily from industry (33%) and power generation (32%). Simulation-measurement biases for ammonium nitrate and dust identify uncertainty in agricultural and crustal sources. Interpretation of initial PM2.5 mass and composition measurements from SPARTAN with the GEOS-Chem model constrained by satellite-based PM2.5 provides insight into sources and processes that influence the global spatial variation in PM2.5 composition.
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Affiliation(s)
- Crystal L Weagle
- Department of Chemistry , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Graydon Snider
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Chi Li
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Aaron van Donkelaar
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Sajeev Philip
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
- NASA Ames Research Center , Moffett Field , California 94035-0001 , United States
| | - Paul Bissonnette
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Jaqueline Burke
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - John Jackson
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Robyn Latimer
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Emily Stone
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Ihab Abboud
- Centre for Atmospheric Research Experiments , Environment and Climate Change Canada , Egbert , Ontario L0L 1N0 , Canada
| | | | - Nguyen Xuan Anh
- Institute of Geophysics , Vietnam Academy of Science and Technology , Hanoi , Vietnam
| | - Jeffrey Robert Brook
- Department of Public Health Sciences , University of Toronto , Toronto , Ontario M5S 1A8 , Canada
| | - Aaron Cohen
- Health Effects Institute , Boston , Massachusetts 02110-1817 , United States
| | - Jinlu Dong
- Department of Earth System Science , Tsinghua University , Beijing 100084 , China
| | - Mark D Gibson
- Department of Civil and Resource Engineering , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Derek Griffith
- Council for Scientific and Industrial Research (CSIR) , Pretoria , South Africa 0001
| | - Kebin B He
- Department of Earth System Science , Tsinghua University , Beijing 100084 , China
| | - Brent N Holben
- Earth Science Division , NASA Goddard Space Flight Center , Greenbelt , Maryland 21046 , United States
| | - Ralph Kahn
- Earth Science Division , NASA Goddard Space Flight Center , Greenbelt , Maryland 21046 , United States
| | - Christoph A Keller
- Universities Space Research Association/Goddard Earth Science Technology and Research , Columbia , Maryland 20771 , United States
- Global Modeling and Assimilation Office , NASA Goddard Space Flight Center , Greenbelt , Maryland 20771 , United States
| | - Jong Sung Kim
- Department of Community Health and Epidemiology , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
| | - Nofel Lagrosas
- Manila Observatory , Ateneo de Manila University campus , Quezon City , 1108 , Philippines
| | - Puji Lestari
- Faculty of Civil and Environmental Engineering , ITB , JL. Ganesha No.10 , Bandung 40132 , Indonesia
| | - Yeo Lik Khian
- Center for Global Change Science , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States
| | - Yang Liu
- Rollins School of Public Health , Emory University , Atlanta , Georgia 30322 , United States
| | - Eloise A Marais
- School of Geography, Earth and Environmental Sciences , University of Birmingham , Birmingham B15 2TT , United Kingdom
| | - J Vanderlei Martins
- Department of Physics and Joint Center for Earth Systems Technology , University of Maryland , Baltimore County , Baltimore , Maryland 21201 , United States
| | - Amit Misra
- Center for Environmental Science and Engineering , Indian Institute of Technology Kanpur , Kanpur , 208016 , India
| | - Ulfi Muliane
- Faculty of Civil and Environmental Engineering , ITB , JL. Ganesha No.10 , Bandung 40132 , Indonesia
| | - Rizki Pratiwi
- Faculty of Civil and Environmental Engineering , ITB , JL. Ganesha No.10 , Bandung 40132 , Indonesia
| | - Eduardo J Quel
- UNIDEF (CITEDEF-CONICET) Juan B. de la Salle 4397 - Villa Martelli , Buenos Aires B1603ALO , Argentina
| | - Abdus Salam
- Department of Chemistry , University of Dhaka , Dhaka 1000 , Bangladesh
| | - Lior Segev
- Department of Earth and Planetary Sciences , Weizmann Institute , Rehovot 76100 , Israel
| | - Sachchida N Tripathi
- Center for Environmental Science and Engineering , Indian Institute of Technology Kanpur , Kanpur , 208016 , India
| | - Chien Wang
- Center for Global Change Science , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States
| | - Qiang Zhang
- Department of Earth System Science , Tsinghua University , Beijing 100084 , China
| | - Michael Brauer
- School of Population and Public Health , University of British Columbia , Vancouver , British Columbia V6T 1Z2 , Canada
| | - Yinon Rudich
- Department of Earth and Planetary Sciences , Weizmann Institute , Rehovot 76100 , Israel
| | - Randall V Martin
- Department of Chemistry , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
- Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada
- Harvard-Smithsonian Center for Astrophysics , Cambridge , Massachusetts 02138 , United States
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75
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Conibear L, Butt EW, Knote C, Arnold SR, Spracklen DV. Stringent Emission Control Policies Can Provide Large Improvements in Air Quality and Public Health in India. GEOHEALTH 2018; 2:196-211. [PMID: 32395679 PMCID: PMC7203661 DOI: 10.1029/2018gh000139] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 05/03/2018] [Accepted: 05/03/2018] [Indexed: 05/28/2023]
Abstract
Exposure to high concentrations of ambient fine particulate matter (PM2.5) is a leading risk factor for public health in India causing a large burden of disease. Business-as-usual economic and industrial growth in India is predicted to increase emissions, worsen air quality, and increase the associated disease burden in future decades. Here we use a high-resolution online-coupled model to estimate the impacts of different air pollution control pathways on ambient PM2.5 concentrations and human health in India. We find that with no change in emissions, the disease burden from exposure to ambient PM2.5 in 2050 will increase by 75% relative to 2015, due to population aging and growth increasing the number of people susceptible to air pollution. We estimate that the International Energy Agencies New Policy Scenario (NPS) and Clean Air Scenario (CAS) in 2050 can reduce ambient PM2.5 concentrations below 2015 levels by 9% and 68%, respectively, offsetting 61,000 and 610,000 premature mortalities a year, which is 9% and 91% of the projected increase in premature mortalities due to population growth and aging. Throughout India, the CAS stands out as the most effective scenario to reduce ambient PM2.5 concentrations and the associated disease burden, reducing the 2050 mortality rate per 100,000 below 2015 control levels by 15%. However, even under such stringent emission control policies, population growth and aging results in premature mortality estimates from exposure to particulate air pollution to increase by 7% compared to 2015, highlighting the challenge facing efforts to improve public health in India.
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Affiliation(s)
- Luke Conibear
- Engineering and Physical Sciences Research Council Centre for Doctoral Training in BioenergyUniversity of LeedsLeedsUK
- Institute for Climate and Atmospheric Science, School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - Edward W. Butt
- Institute for Climate and Atmospheric Science, School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | | | - Stephen R. Arnold
- Institute for Climate and Atmospheric Science, School of Earth and EnvironmentUniversity of LeedsLeedsUK
| | - Dominick V. Spracklen
- Institute for Climate and Atmospheric Science, School of Earth and EnvironmentUniversity of LeedsLeedsUK
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