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Yue H, He C, Huang Q, Zhang D, Shi P, Moallemi EA, Xu F, Yang Y, Qi X, Ma Q, Bryan BA. Substantially reducing global PM 2.5-related deaths under SDG3.9 requires better air pollution control and healthcare. Nat Commun 2024; 15:2729. [PMID: 38548716 PMCID: PMC10978932 DOI: 10.1038/s41467-024-46969-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 03/14/2024] [Indexed: 04/01/2024] Open
Abstract
The United Nations' Sustainable Development Goal (SDG) 3.9 calls for a substantial reduction in deaths attributable to PM2.5 pollution (DAPP). However, DAPP projections vary greatly and the likelihood of meeting SDG3.9 depends on complex interactions among environmental, socio-economic, and healthcare parameters. We project potential future trends in global DAPP considering the joint effects of each driver (PM2.5 concentration, death rate of diseases, population size, and age structure) and assess the likelihood of achieving SDG3.9 under the Shared Socioeconomic Pathways (SSPs) as quantified by the Scenario Model Intercomparison Project (ScenarioMIP) framework with simulated PM2.5 concentrations from 11 models. We find that a substantial reduction in DAPP would not be achieved under all but the most optimistic scenario settings. Even the development aligned with the Sustainability scenario (SSP1-2.6), in which DAPP was reduced by 19%, still falls just short of achieving a substantial (≥20%) reduction by 2030. Meeting SDG3.9 calls for additional efforts in air pollution control and healthcare to more aggressively reduce DAPP.
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Affiliation(s)
- Huanbi Yue
- Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of Education, Beijing Normal University, Beijing, China
- School of International Affairs and Public Administration, Ocean University of China, Qingdao, China
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
| | - Chunyang He
- Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of Education, Beijing Normal University, Beijing, China.
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China.
- Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management & Ministry of Education, Beijing Normal University, Beijing, China.
- Academy of Plateau Science and Sustainability, People's Government of Qinghai Province & Beijing Normal University, Xining, China.
| | - Qingxu Huang
- Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of Education, Beijing Normal University, Beijing, China
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
| | - Da Zhang
- College of Geography and Ocean Sciences, Yanbian University, Yanji, China.
| | - Peijun Shi
- Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of Education, Beijing Normal University, Beijing, China
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
- Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management & Ministry of Education, Beijing Normal University, Beijing, China
- Academy of Plateau Science and Sustainability, People's Government of Qinghai Province & Beijing Normal University, Xining, China
| | - Enayat A Moallemi
- Commonwealth Scientific and Industrial Research Organization (CSIRO), Melbourne, Victoria, Australia
| | - Fangjin Xu
- Key Laboratory of Environmental Change and Natural Disasters of Chinese Ministry of Education, Beijing Normal University, Beijing, China
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, China
- College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Yang Yang
- School of International Affairs and Public Administration, Ocean University of China, Qingdao, China
- Institute of Marine Development, Ocean University of China, Qingdao, China
| | - Xin Qi
- Frontiers Science Center for Deep Ocean Multispheres and Earth System (FDOMES), Ocean University of China, Qingdao, China
| | - Qun Ma
- School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai, China
| | - Brett A Bryan
- School of Life and Environmental Sciences, Deakin University, Melbourne, Victoria, Australia
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Gordon JND, Bilsback KR, Fiddler MN, Pokhrel RP, Fischer EV, Pierce JR, Bililign S. The Effects of Trash, Residential Biofuel, and Open Biomass Burning Emissions on Local and Transported PM 2.5 and Its Attributed Mortality in Africa. GEOHEALTH 2023; 7:e2022GH000673. [PMID: 36743737 PMCID: PMC9884662 DOI: 10.1029/2022gh000673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 12/22/2022] [Accepted: 01/03/2023] [Indexed: 06/18/2023]
Abstract
Long-term exposure to ambient fine particulate matter (PM2.5) is the second leading risk factor of premature death in Sub-Saharan Africa. We use GEOS-Chem to quantify the effects of (a) trash burning, (b) residential solid-fuel burning, and (c) open biomass burning (BB) (i.e., landscape fires) on ambient PM2.5 and PM2.5-attributable mortality in Africa. Using a series of sensitivity simulations, we excluded each of the three combustion sources in each of five African regions. We estimate that in 2017 emissions from these three combustion sources within Africa increased global ambient PM2.5 by 2%, leading to 203,000 (95% confidence interval: 133,000-259,000) premature mortalities yr-1 globally and 167,000 premature mortalities yr-1 in Africa. BB contributes more ambient PM2.5-related premature mortalities per year (63%) than residential solid-fuel burning (29%) and trash burning (8%). Open BB in Central Africa leads to the largest number of PM2.5-attributed mortalities inside the region, while trash burning in North Africa and residential solid-fuel burning in West Africa contribute the most regional mortalities for each source. Overall, Africa has a unique ambient air pollution profile because natural sources, such as windblown dust and BB, contribute strongly to ambient PM2.5 levels and PM2.5-related mortality. Air pollution policies may need to focus on taking preventative measures to avoid exposure to ambient PM2.5 from these less-controllable sources.
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Affiliation(s)
- Janica N. D. Gordon
- Department of PhysicsNorth Carolina Agricultural and Technical State UniversityGreensboroNCUSA
- Applied Sciences and Technology PhD programNorth Carolina Agricultural and Technical State UniversityGreensboroNCUSA
| | - Kelsey R. Bilsback
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
- PSE Healthy EnergyOaklandCAUSA
| | - Marc N. Fiddler
- Department of ChemistryNorth Carolina Agricultural and Technical State UniversityGreensboroNCUSA
| | - Rudra P. Pokhrel
- Department of PhysicsNorth Carolina Agricultural and Technical State UniversityGreensboroNCUSA
- NOAA Chemical Sciences LaboratoryBoulderCOUSA
- Cooperative Institute for Research in Environmental SciencesUniversity of Colorado BoulderBoulderCOUSA
| | - Emily V. Fischer
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - Jeffrey R. Pierce
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | - Solomon Bililign
- Department of PhysicsNorth Carolina Agricultural and Technical State UniversityGreensboroNCUSA
- Applied Sciences and Technology PhD programNorth Carolina Agricultural and Technical State UniversityGreensboroNCUSA
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3
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Yun G, Yang C, Ge S. Understanding Anthropogenic PM 2.5 Concentrations and Their Drivers in China during 1998-2016. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:695. [PMID: 36613014 PMCID: PMC9819118 DOI: 10.3390/ijerph20010695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 12/09/2022] [Accepted: 12/14/2022] [Indexed: 06/17/2023]
Abstract
Air pollution poses serious challenges for human health and wellbeing. It also affects atmospheric visibility and contributes to climate change. As social and economic processes have increased, anthropogenic PM2.5 pollution caused by intensive human activities has led to extremely severe air pollution. Spatiotemporal patterns and drivers of anthropogenic PM2.5 concentrations have received increasing attention from the scientific community. Nonetheless, spatiotemporal patterns and drivers of anthropogenic PM2.5 concentrations are still inadequately understood. Based on a time series of remotely sensed anthropogenic PM2.5 concentrations, this study analyzed the spatiotemporal patterns of this crucial pollutant in China from 1998 to 2016 using Sen's slope estimator and the Mann-Kendall trend model. This, in combination with grey correlation analysis (GCA), was used to reveal the socioeconomic factors influencing anthropogenic PM2.5 concentrations in eastern, central, and western China from 1998 to 2016. The results were as follows: (1) the average annual anthropogenic concentration of PM2.5 in China increased quickly and reached its peak value in 2007, then remained stable in the following years; (2) only 63.30 to 55.09% of the land area reached the threshold value of 15 μg/m3 from 1998 to 2016; (3) regarding the polarization phenomenon of anthropogenic PM2.5 concentrations existing in eastern and central China, the proportion of gradient 1 (≤15 μg/m3) gradually decreased and gradient 3 (≥35 μg/m3) gradually increased; and (4) the urbanization level (UR), population density (PD), and proportion of secondary industry to gross domestic product (SI) were the dominant socioeconomic factors affecting the formation of anthropogenic PM2.5 concentrations in eastern, central, and western China, independently. The improvements in energy consumption per gross domestic product (EI) have a greater potential for mitigating anthropogenic PM2.5 emissions in central and western China. These findings allow an interpretation of the spatial distribution of anthropogenic PM2.5 concentrations and the mechanisms influencing anthropogenic PM2.5 concentrations, which can help the Chinese government develop effective abatement strategies.
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Affiliation(s)
- Guoliang Yun
- College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes, Ministry of Education, Peking University, Beijing 100871, China
| | - Chen Yang
- College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes, Ministry of Education, Peking University, Beijing 100871, China
| | - Shidong Ge
- College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
- College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes, Ministry of Education, Peking University, Beijing 100871, China
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4
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Irankunda E, Török Z, Mereuță A, Gasore J, Kalisa E, Akimpaye B, Habineza T, Shyaka O, Munyampundu G, Ozunu A. The comparison between in-situ monitored data and modelled results of nitrogen dioxide (NO 2): case-study, road networks of Kigali city, Rwanda. Heliyon 2022; 8:e12390. [PMID: 36590563 PMCID: PMC9800557 DOI: 10.1016/j.heliyon.2022.e12390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/11/2022] [Accepted: 12/08/2022] [Indexed: 12/23/2022] Open
Abstract
The incomplete combustion of fossil fuels from petrol, natural gas, and fuel oil in the engine of vehicles contributes to air quality degradation through traffic-related air pollutant emissions. The Real-time affordable multi-pollutant (RAMPs) monitors were installed in Kigali, the capital of Rwanda, to fill the gap in air quality datasets. Using RAMPs, this is the first air quality modelling research in Rwanda aiming to report the concentration of NO2 by comparing In-situ monitored data and modelled results. We targeted NO2 emissions from 27 road networks of Kigali to address the impacts of traffic emissions on air quality over 2021. The American Meteorological Society and Environmental Protection Agency regulatory models (AERMOD and ISCST3) were used for simulation. Statistical indexes include fractional bias (FB), the fraction of the prediction within the factor of two of the observations (FAC2), normalized mean square error (NMSE), geometric mean bias (MG), and geometric variance (VG) used to assess models' reliability. Monitoring shows the annual mean of 16.07 μg/m3, 20.35 μg/m3, and 15.46 μg/m3 at Mont-Kigali, Gacuriro, and Gikondo-Mburabuturo stations, respectively. Modelling shows the daily mean of 111.77 μg/m3 and annually mean of 50.42 μg/m3 with AERMOD and daily mean of 200.26 μg/m3 and annually mean of 72.26 μg/m3 with ISCST3. The FB, NMSE, and FAC2 showed good agreement, while MG and VG showed moderate agreement with AERMOD. The FB, NMSE, and MG showed moderate agreement, while FAC2 and VG disagreed with ISCST3. Traffic and urban residential emissions were identified as potential sources of NO2. Results indicated that Kigali residents are exposed to a significant level of NO2 exceeding World Health Organisation limits. Findings will help track the effectiveness of Rwanda's recently executed pollution-control policy, suggest evidence based on the recommendations to reduce NO2, and use further dispersion models to support ground-based observations to improve public health.
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Affiliation(s)
- Elisephane Irankunda
- Faculty of Environmental Science and Engineering, University of Babeş-Bolyai, 30 Fantanele Street, RO-400294 Cluj-Napoca, Romania
- Corresponding author.
| | - Zoltán Török
- Faculty of Environmental Science and Engineering, University of Babeş-Bolyai, 30 Fantanele Street, RO-400294 Cluj-Napoca, Romania
| | - Alexandru Mereuță
- Faculty of Environmental Science and Engineering, University of Babeş-Bolyai, 30 Fantanele Street, RO-400294 Cluj-Napoca, Romania
| | - Jimmy Gasore
- College of Science and Technology, University of Rwanda, KK737 Street, PO BOX 4285, Kigali, Rwanda
| | - Egide Kalisa
- College of Science and Technology, University of Rwanda, KK737 Street, PO BOX 4285, Kigali, Rwanda
| | - Beatha Akimpaye
- Division of Environmental Compliance and Enforcement, The Rwanda Environment Management Authority, KG 7 Street, Kigali Rwanda, PO BOX 7436, Kigali, Rwanda
| | - Theobald Habineza
- Department of Technical Expert, Rwanda Space Agency, KG 7 Street, PO BOX 6205, Kigali, Rwanda
| | - Olivier Shyaka
- Department of Technical Expert, Rwanda Space Agency, KG 7 Street, PO BOX 6205, Kigali, Rwanda
| | - Gaston Munyampundu
- Department of Technical Expert, Rwanda Space Agency, KG 7 Street, PO BOX 6205, Kigali, Rwanda
| | - Alexandru Ozunu
- Faculty of Environmental Science and Engineering, University of Babeş-Bolyai, 30 Fantanele Street, RO-400294 Cluj-Napoca, Romania
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5
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Ogunjo S, Olaniyan O, Olusegun C, Kayode F, Okoh D, Jenkins G. The Role of Meteorological Variables and Aerosols in the Transmission of COVID-19 During Harmattan Season. GEOHEALTH 2022; 6:e2021GH000521. [PMID: 35229057 PMCID: PMC8865058 DOI: 10.1029/2021gh000521] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 01/06/2022] [Accepted: 01/11/2022] [Indexed: 05/26/2023]
Abstract
The role of atmospheric parameters and aerosols in the transmission of COVID-19 within tropical Africa, especially during the harmattan season, has been under-investigated in published papers. The harmattan season within the West African region is associated with significant dust incursion from the Bodele depression and biomass burning. In this study, the correlation between atmospheric parameters (temperature and humidity) and aerosols with COVID-19 cases and fatalities within seven locations in tropical Nigeria during the harmattan period was investigated. COVID-19 infection cases were found to be significantly positively correlated with atmospheric parameters (temperature and humidity) in the southern part of the country while the number of fatalities showed weaker significant correlation with particulate matters only in three locations. The significant correlation values were found to be between 0.22 and 0.48 for particulate matter and -0.19 to -0.32 for atmospheric parameters. Although, temperature and humidity showed negative correlations in some locations, the impact is smaller compared to particulate matter. In December, COVID-19 cases in all locations showed strong correlation with particulate matter except in Kano State. It is suggested that a reduction in atmospheric particulate matter can be used as a control measure for the spread of COVID-19.
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Affiliation(s)
- S. Ogunjo
- Department of PhysicsFederal University of TechnologyAkureNigeria
| | - O. Olaniyan
- National Weather Forecasting and Climate Research CentreNigerian Meteorological AgencyAbujaNigeria
| | - C.F. Olusegun
- Centre for Atmospheric ResearchNational Space Research and Development AgencyKogi State University CampusAnyigbaNigeria
| | - F. Kayode
- Centre for Atmospheric ResearchNational Space Research and Development AgencyKogi State University CampusAnyigbaNigeria
| | - D. Okoh
- Centre for Atmospheric ResearchNational Space Research and Development AgencyKogi State University CampusAnyigbaNigeria
| | - G. Jenkins
- Department of Meteorology and Atmospheric SciencesPenn State UniversityUniversity ParkPAUSA
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6
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Nisbet EG, Allen G, Fisher RE, France JL, Lee JD, Lowry D, Andrade MF, Bannan TJ, Barker P, Bateson P, Bauguitte SJB, Bower KN, Broderick TJ, Chibesakunda F, Cain M, Cozens AE, Daly MC, Ganesan AL, Jones AE, Lambakasa M, Lunt MF, Mehra A, Moreno I, Pasternak D, Palmer PI, Percival CJ, Pitt JR, Riddle AJ, Rigby M, Shaw JT, Stell AC, Vaughan AR, Warwick NJ, E. Wilde S. Isotopic signatures of methane emissions from tropical fires, agriculture and wetlands: the MOYA and ZWAMPS flights. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2022; 380:20210112. [PMID: 34865533 PMCID: PMC8646140 DOI: 10.1098/rsta.2021.0112] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 08/11/2021] [Indexed: 06/13/2023]
Abstract
We report methane isotopologue data from aircraft and ground measurements in Africa and South America. Aircraft campaigns sampled strong methane fluxes over tropical papyrus wetlands in the Nile, Congo and Zambezi basins, herbaceous wetlands in Bolivian southern Amazonia, and over fires in African woodland, cropland and savannah grassland. Measured methane δ13CCH4 isotopic signatures were in the range -55 to -49‰ for emissions from equatorial Nile wetlands and agricultural areas, but widely -60 ± 1‰ from Upper Congo and Zambezi wetlands. Very similar δ13CCH4 signatures were measured over the Amazonian wetlands of NE Bolivia (around -59‰) and the overall δ13CCH4 signature from outer tropical wetlands in the southern Upper Congo and Upper Amazon drainage plotted together was -59 ± 2‰. These results were more negative than expected. For African cattle, δ13CCH4 values were around -60 to -50‰. Isotopic ratios in methane emitted by tropical fires depended on the C3 : C4 ratio of the biomass fuel. In smoke from tropical C3 dry forest fires in Senegal, δ13CCH4 values were around -28‰. By contrast, African C4 tropical grass fire δ13CCH4 values were -16 to -12‰. Methane from urban landfills in Zambia and Zimbabwe, which have frequent waste fires, had δ13CCH4 around -37 to -36‰. These new isotopic values help improve isotopic constraints on global methane budget models because atmospheric δ13CCH4 values predicted by global atmospheric models are highly sensitive to the δ13CCH4 isotopic signatures applied to tropical wetland emissions. Field and aircraft campaigns also observed widespread regional smoke pollution over Africa, in both the wet and dry seasons, and large urban pollution plumes. The work highlights the need to understand tropical greenhouse gas emissions in order to meet the goals of the UNFCCC Paris Agreement, and to help reduce air pollution over wide regions of Africa. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 2)'.
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Affiliation(s)
- MOYA/ZWAMPS Team
- Department of Earth Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK
| | - Euan G. Nisbet
- Department of Earth Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK
| | - Grant Allen
- Centre for Atmospheric Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | - Rebecca E. Fisher
- Department of Earth Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK
| | - James L. France
- Department of Earth Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK
- British Antarctic Survey, Natural Environment Research Council, Cambridge CB3 0ET, UK
| | - James D. Lee
- National Centre for Atmospheric Sciences, Department of Chemistry, University of York, Heslington, York YO10 5DD, UK
| | - David Lowry
- Department of Earth Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK
| | - Marcos F. Andrade
- Laboratory for Atmospheric Physics, Institute for Physics Research, Universidad Mayor de San Andrés-UMSA, Campus Universitario, Cota-Cota Calle No 27, La Paz, Bolivia
- Department Atmospheric and Oceanic Sciences, University of Maryland, College Park, MD 20742, USA
| | - Thomas J. Bannan
- Centre for Atmospheric Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | - Patrick Barker
- Centre for Atmospheric Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | - Prudence Bateson
- Centre for Atmospheric Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | - Stéphane J.-B. Bauguitte
- Facility for Airborne Atmospheric Measurement, Cranfield University, College Road, Cranfield MK43 0AL, UK
| | - Keith N. Bower
- Centre for Atmospheric Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | | | - Francis Chibesakunda
- Geological Survey of Zambia, Ministry of Mines and Mineral Development, PO Box 50135, Ridgeway, Lusaka, Zambia
| | - Michelle Cain
- Centre for Environment and Agricultural Informatics, Cranfield University, College Road, Cranfield MK43 0AL, UK
| | - Alice E. Cozens
- Department of Earth Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK
| | - Michael C. Daly
- Department of Earth Sciences, University of Oxford, South Parks Road, Oxford OX1 3AN, UK
| | - Anita L. Ganesan
- School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK
| | - Anna E. Jones
- British Antarctic Survey, Natural Environment Research Council, Cambridge CB3 0ET, UK
| | - Musa Lambakasa
- Geological Survey of Zambia, Ministry of Mines and Mineral Development, PO Box 50135, Ridgeway, Lusaka, Zambia
| | - Mark F. Lunt
- School of GeoSciences, University of Edinburgh, Edinburgh EH9 3FF, UK
| | - Archit Mehra
- Centre for Atmospheric Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK
- Now at Faculty of Science and Engineering, University of Chester, Chester, UK
| | - Isabel Moreno
- Laboratory for Atmospheric Physics, Institute for Physics Research, Universidad Mayor de San Andrés-UMSA, Campus Universitario, Cota-Cota Calle No 27, La Paz, Bolivia
| | - Dominika Pasternak
- National Centre for Atmospheric Sciences, Department of Chemistry, University of York, Heslington, York YO10 5DD, UK
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York YO10 5DD, UK
| | - Paul I. Palmer
- School of GeoSciences, University of Edinburgh, Edinburgh EH9 3FF, UK
- National Centre for Earth Observation, University of Edinburgh, Edinburgh EH9 3FF, UK
| | - Carl J. Percival
- Now at Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
| | - Joseph R. Pitt
- School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook, NY 11794, USA
| | - Amber J. Riddle
- Department of Earth Sciences, Royal Holloway, University of London, Egham TW20 0EX, UK
| | - Matthew Rigby
- School of Chemistry, University of Bristol, Bristol BS8 1TS, UK
| | - Jacob T. Shaw
- Centre for Atmospheric Sciences, University of Manchester, Oxford Road, Manchester M13 9PL, UK
| | - Angharad C. Stell
- School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK
| | - Adam R. Vaughan
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York YO10 5DD, UK
| | - Nicola J. Warwick
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
| | - Shona E. Wilde
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York YO10 5DD, UK
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7
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Source sector and fuel contributions to ambient PM 2.5 and attributable mortality across multiple spatial scales. Nat Commun 2021; 12:3594. [PMID: 34127654 PMCID: PMC8203641 DOI: 10.1038/s41467-021-23853-y] [Citation(s) in RCA: 133] [Impact Index Per Article: 44.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 05/17/2021] [Indexed: 12/27/2022] Open
Abstract
Ambient fine particulate matter (PM2.5) is the world's leading environmental health risk factor. Reducing the PM2.5 disease burden requires specific strategies that target dominant sources across multiple spatial scales. We provide a contemporary and comprehensive evaluation of sector- and fuel-specific contributions to this disease burden across 21 regions, 204 countries, and 200 sub-national areas by integrating 24 global atmospheric chemistry-transport model sensitivity simulations, high-resolution satellite-derived PM2.5 exposure estimates, and disease-specific concentration response relationships. Globally, 1.05 (95% Confidence Interval: 0.74-1.36) million deaths were avoidable in 2017 by eliminating fossil-fuel combustion (27.3% of the total PM2.5 burden), with coal contributing to over half. Other dominant global sources included residential (0.74 [0.52-0.95] million deaths; 19.2%), industrial (0.45 [0.32-0.58] million deaths; 11.7%), and energy (0.39 [0.28-0.51] million deaths; 10.2%) sectors. Our results show that regions with large anthropogenic contributions generally had the highest attributable deaths, suggesting substantial health benefits from replacing traditional energy sources.
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8
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Vohra K, Vodonos A, Schwartz J, Marais EA, Sulprizio MP, Mickley LJ. Global mortality from outdoor fine particle pollution generated by fossil fuel combustion: Results from GEOS-Chem. ENVIRONMENTAL RESEARCH 2021; 195:110754. [PMID: 33577774 DOI: 10.1016/j.envres.2021.110754] [Citation(s) in RCA: 188] [Impact Index Per Article: 62.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 01/12/2021] [Accepted: 01/14/2021] [Indexed: 05/12/2023]
Abstract
The burning of fossil fuels - especially coal, petrol, and diesel - is a major source of airborne fine particulate matter (PM2.5), and a key contributor to the global burden of mortality and disease. Previous risk assessments have examined the health response to total PM2.5, not just PM2.5 from fossil fuel combustion, and have used a concentration-response function with limited support from the literature and data at both high and low concentrations. This assessment examines mortality associated with PM2.5 from only fossil fuel combustion, making use of a recent meta-analysis of newer studies with a wider range of exposure. We also estimated mortality due to lower respiratory infections (LRI) among children under the age of five in the Americas and Europe, regions for which we have reliable data on the relative risk of this health outcome from PM2.5 exposure. We used the chemical transport model GEOS-Chem to estimate global exposure levels to fossil-fuel related PM2.5 in 2012. Relative risks of mortality were modeled using functions that link long-term exposure to PM2.5 and mortality, incorporating nonlinearity in the concentration response. We estimate a global total of 10.2 (95% CI: -47.1 to 17.0) million premature deaths annually attributable to the fossil-fuel component of PM2.5. The greatest mortality impact is estimated over regions with substantial fossil fuel related PM2.5, notably China (3.9 million), India (2.5 million) and parts of eastern US, Europe and Southeast Asia. The estimate for China predates substantial decline in fossil fuel emissions and decreases to 2.4 million premature deaths due to 43.7% reduction in fossil fuel PM2.5 from 2012 to 2018 bringing the global total to 8.7 (95% CI: -1.8 to 14.0) million premature deaths. We also estimated excess annual deaths due to LRI in children (0-4 years old) of 876 in North America, 747 in South America, and 605 in Europe. This study demonstrates that the fossil fuel component of PM2.5 contributes a large mortality burden. The steeper concentration-response function slope at lower concentrations leads to larger estimates than previously found in Europe and North America, and the slower drop-off in slope at higher concentrations results in larger estimates in Asia. Fossil fuel combustion can be more readily controlled than other sources and precursors of PM2.5 such as dust or wildfire smoke, so this is a clear message to policymakers and stakeholders to further incentivize a shift to clean sources of energy.
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Affiliation(s)
- Karn Vohra
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK.
| | - Alina Vodonos
- Harvard T.H. Chan School of Public Health, Department of Environmental Health, Harvard University, Boston, MA, USA
| | - Joel Schwartz
- Harvard T.H. Chan School of Public Health, Department of Environmental Health, Harvard University, Boston, MA, USA
| | - Eloise A Marais
- Department of Physics and Astronomy, University of Leicester, Leicester, UK
| | - Melissa P Sulprizio
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Loretta J Mickley
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
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Marais EA, Silvern RF, Vodonos A, Dupin E, Bockarie AS, Mickley LJ, Schwartz J. Air Quality and Health Impact of Future Fossil Fuel Use for Electricity Generation and Transport in Africa. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:13524-13534. [PMID: 31647871 DOI: 10.1021/acs.est.9b04958] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Africa has ambitious plans to address energy deficits and sustain economic growth with fossil fueled power plants. The continent is also experiencing faster population growth than anywhere else in the world that will lead to proliferation of vehicles. Here, we estimate air pollutant emissions in Africa from future (2030) electricity generation and transport. We find that annual emissions of two precursors of fine particles (PM2.5) hazardous to health, sulfur dioxide (SO2) and nitrogen oxides (NOx), approximately double by 2030 relative to 2012, increasing from 2.5 to 5.5 Tg SO2 and 1.5 to 2.8 Tg NOx. We embed these emissions in the GEOS-Chem model nested over the African continent to simulate ambient concentrations of PM2.5 and determine the burden of disease (excess deaths) attributable to exposure to future fossil fuel use. We calculate 48000 avoidable deaths in 2030 (95% confidence interval: 6000-88000), mostly in South Africa (10400), Nigeria (7500), and Malawi (2400), with 3-times higher mortality rates from power plants than transport. Sensitivity of the burden of disease to either population growth or air quality varies regionally and suggests that emission mitigation strategies would be most effective in Southern Africa, whereas population growth is the main driver everywhere else.
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Affiliation(s)
- Eloise A Marais
- School of Physics and Astronomy , University of Leicester , Leicester , LE1 7RH , United Kingdom
| | - Rachel F Silvern
- Department of Earth and Planetary Sciences , Harvard University , Cambridge , Massachusetts 02138 , United States
| | - Alina Vodonos
- Harvard T.H. Chan School of Public Health , Harvard University , Boston , Massachusetts 02115 , United States
| | - Eleonore Dupin
- Department of Chemical Engineering , INSA , Cedex , 76800 , France
| | - Alfred S Bockarie
- School of Geography, Earth and Environmental Sciences , University of Birmingham , Birmingham , B15 2SA , United Kingdom
| | - Loretta J Mickley
- John A. Paulson School of Engineering and Applied Sciences , Harvard University , Cambridge , Massachusetts 02138 , United States
| | - Joel Schwartz
- Harvard T.H. Chan School of Public Health , Harvard University , Boston , Massachusetts 02115 , United States
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Pfotenhauer DJ, Coffey ER, Piedrahita R, Agao D, Alirigia R, Muvandimwe D, Lacey F, Wiedinmyer C, Dickinson KL, Dalaba M, Kanyomse E, Oduro A, Hannigan MP. Updated Emission Factors from Diffuse Combustion Sources in Sub-Saharan Africa and Their Effect on Regional Emission Estimates. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:6392-6401. [PMID: 31070029 DOI: 10.1021/acs.est.8b06155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Diffuse emission sources outside of kitchen areas are poorly understood, and measurements of their emission factors (EFs) are sparse for regions of sub-Saharan Africa. Thirty-one in-field emission measurements were taken in northern Ghana from combustion sources common to rural regions worldwide. Sources sampled included commercial cooking, trash burning, kerosene lanterns, and diesel generators. EFs were calculated for carbon monoxide (CO), carbon dioxide (CO2), as well as carbonaceous particulate matter, specifically elemental carbon (EC) and organic carbon (OC). EC and OC emissions were measured from kerosene lighting events (EFEC = 25.1 g/kg-fuel SD = 25.7, EFOC = 9.5 g/kg-fuel SD = 10.0). OC emissions from trash burning events were large and highly variable (EFOC = 38.9 g/kg-fuel SD = 30.5). Combining our results with other recent in-field emission factors for rural Ghana, we explored updated emission estimates for Ghana using a region specific emissions inventory. Large differences are calculated for all updated source emissions, showing a 96% increase in OC and 78% decrease in EC compared to prior estimates for Ghana's emissions. Differences for carbon monoxide were small when averaged across all updated source types (-1%), though the household wood use and trash burning categories individually show large differences.
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Affiliation(s)
- David J Pfotenhauer
- University of Colorado Boulder , Mechanical Engineering , 1111 Engineering Dr. Boulder , Colorado 80309 , United States
| | - Evan R Coffey
- University of Colorado Boulder , Mechanical Engineering , 1111 Engineering Dr. Boulder , Colorado 80309 , United States
| | - Ricardo Piedrahita
- Berkeley Air , 1900 Addison Street Suite 350 Berkeley , California 94704 , United States
| | - Desmond Agao
- Navrongo Health Research Centre , Navrongo Upper East , Ghana
| | - Rex Alirigia
- Navrongo Health Research Centre , Navrongo Upper East , Ghana
| | - Didier Muvandimwe
- University of Colorado Boulder , Mechanical Engineering , 1111 Engineering Dr. Boulder , Colorado 80309 , United States
| | - Forrest Lacey
- National Center for Atmospheric Research , 3450 Mitchell Ln. Boulder , Colorado 80301 , United States
| | - Christine Wiedinmyer
- National Center for Atmospheric Research , 3450 Mitchell Ln. Boulder , Colorado 80301 , United States
| | - Katherine L Dickinson
- Colorado School of Public Health , 13001 E. 17th Place Aurora , Colorado 80045 , United States
| | - Maxwell Dalaba
- Navrongo Health Research Centre , Navrongo Upper East , Ghana
| | - Ernest Kanyomse
- Navrongo Health Research Centre , Navrongo Upper East , Ghana
| | - Abraham Oduro
- Navrongo Health Research Centre , Navrongo Upper East , Ghana
| | - Michael P Hannigan
- University of Colorado Boulder , Mechanical Engineering , 1111 Engineering Dr. Boulder , Colorado 80309 , United States
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Cai S, Ma Q, Wang S, Zhao B, Brauer M, Cohen A, Martin RV, Zhang Q, Li Q, Wang Y, Hao J, Frostad J, Forouzanfar MH, Burnett RT. Impact of air pollution control policies on future PM 2.5 concentrations and their source contributions in China. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2018; 227:124-133. [PMID: 30172931 DOI: 10.1016/j.jenvman.2018.08.052] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Revised: 08/10/2018] [Accepted: 08/11/2018] [Indexed: 05/09/2023]
Abstract
To investigate the impact of air pollutant control policies on future PM2.5 concentrations and their source contributions in China, we developed four future scenarios for 2030 based on a 2013 emission inventory, and conducted air quality simulations for each scenario using the chemical transport model GEOS-Chem (version 9.1.3). Two energy scenarios i.e., current legislation (CLE) and with additional measures (WAM), were developed to project future energy consumption, reflecting, respectively, existing legislation and implementation status as of the end of 2012, and new energy-saving policies that would be released and enforced more stringently. Two end-of-pipe control strategies, i.e., current control technologies (until 2017) and more stringent control technologies (until 2030), were also developed. The combinations of energy scenarios and end-of-pipe control strategies constitute four emission scenarios (2017-CLE, 2030-CLE, 2017-WAM, and 2030-WAM) evaluated in simulations. PM2.5 concentrations at national level were estimated to be 57 μg/m3 in the base year 2013, and 58 μg/m3, 42 μg/m3, 42 μg/m3, and 30 μg/m3 under the 2017-CLE, 2030-CLE, 2017-WAM, and 2030-WAM scenarios in 2030, respectively. Large PM2.5 reductions between 2013 and 2030 were estimated for heavily polluted regions (Sichuan Basin, Middle Yangtze River, North China). The energy-saving policies show similar effects to the end-of-pipe emission control measures, but the relative importance of these two groups of policies varies in different regions. Absolute contributions to PM2.5 concentrations from most major sources declined from 2017-CLE to 2030-WAM. With respect to fractional contributions, most coal-burning sectors (including power plant, industrial and residential coal burning) increased from 2017-CLE to 2030-WAM, due to larger reductions from non-coal sources, including transportation and biomass open burning. Residential combustion and open burning had much lower fractional contribution to ambient PM2.5 concentrations in the 2017-WAM/2030-WAM compared to the 2017-CLE/2030-CLE scenarios. Fractional contributions from transportation were reduced dramatically in 2030-CLE and 2030-WAM compared to 2017-CLE/2017-WAM, due to the enforcement of stringent end-of-pipe emission controls. Across all scenarios, coal combustion remained the single largest contributor to PM2.5 concentrations in 2030. Reducing PM2.5 emissions from coal combustion remains a strategic priority for air quality management in China.
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Affiliation(s)
- Siyi Cai
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Qiao Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China; School of Energy and Power Engineering, Shandong University, Jinan, 250061, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China.
| | - Bin Zhao
- Joint Institute for Regional Earth System Science and Engineering, Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, 90095, USA
| | - Michael Brauer
- School of Population and Public Health, The University of British Columbia, Vancouver, British Columbia V6T1Z3, Canada
| | - Aaron Cohen
- Health Effects Institute, Boston, MA, 02110, USA; Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98195, USA
| | - Randall V Martin
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, B3H 4R2, Canada
| | - Qianqian Zhang
- National Satellite Meteorological Center, Beijing, 100089, China
| | - Qinbin Li
- Joint Institute for Regional Earth System Science and Engineering, Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, 90095, USA
| | - Yuxuan Wang
- Department of Earth and Atmospheric Sciences, University of Houston, Houston, TX, USA
| | - Jiming Hao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, 100084, China
| | - Joseph Frostad
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98195, USA
| | - Mohammad H Forouzanfar
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98195, USA
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