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Rowlinson MJ, Evans MJ, Carpenter LJ, Read KA, Punjabi S, Adedeji A, Fakes L, Lewis A, Richmond B, Passant N, Murrells T, Henderson B, Bates KH, Helmig D. Revising VOC emissions speciation improves the simulation of global background ethane and propane. ATMOSPHERIC CHEMISTRY AND PHYSICS 2024; 24:8317-8342. [PMID: 39376463 PMCID: PMC11457074 DOI: 10.5194/acp-24-8317-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/09/2024]
Abstract
Non-Methane Volatile Organic Compounds (NMVOCs) generate ozone (O3) when they are oxidized in the presence of oxides of nitrogen, modulate the oxidative capacity of the atmosphere and can lead to the formation of aerosol. Here, we assess the capability of a chemical transport model (GEOS-Chem) to simulate NMVOC concentrations by comparing ethane, propane and higher alkane observations in remote regions from the NOAA Flask Network and the World Meteorological Organization's Global Atmosphere Watch (GAW) network. Using the Community Emissions Data System (CEDS) inventory we find a significant underestimate in the simulated concentration of both ethane (35%) and propane (64%), consistent with previous studies. We run a new simulation where the total mass of anthropogenic NMVOC emitted in a grid box is the same as that used in CEDS, but with the NMVOC speciation derived from regional inventories. For US emissions we use the National Emissions Inventory (NEI), for Europe we use the UK National Atmospheric Emissions Inventory (NAEI), and for China, the Multi-resolution Emission Inventory for China (MEIC). These changes lead to a large increase in the modelled concentrations of ethane, improving the mean model bias from -35% to -4%. Simulated propane also improves (from -64% to -48% mean model bias), but there remains a substantial model underestimate. There were relatively minor changes to other NMVOCs. The low bias in simulated global ethane concentration is essentially removed, resolving one long-term issue in global simulations. Propane concentrations are improved but remain significantly underestimated, suggesting the potential for a missing global propane source. The change in the NMVOC emission speciation results in only minor changes in tropospheric O3 and OH concentrations.
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Affiliation(s)
- Matthew J. Rowlinson
- National Centre for Atmospheric Science, University of York, York, YO10 5DD, UK
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UK
| | - Mat J. Evans
- National Centre for Atmospheric Science, University of York, York, YO10 5DD, UK
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UK
| | - Lucy J. Carpenter
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UK
| | - Katie A. Read
- National Centre for Atmospheric Science, University of York, York, YO10 5DD, UK
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UK
| | - Shalini Punjabi
- National Centre for Atmospheric Science, University of York, York, YO10 5DD, UK
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UK
| | - Adedayo Adedeji
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UK
| | - Luke Fakes
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UK
| | - Ally Lewis
- National Centre for Atmospheric Science, University of York, York, YO10 5DD, UK
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York, YO10 5DD, UK
| | - Ben Richmond
- Ricardo, Fermi Avenue, Harwell, Oxon, OX11 0QR, UK
| | - Neil Passant
- Ricardo, Fermi Avenue, Harwell, Oxon, OX11 0QR, UK
| | - Tim Murrells
- Ricardo, Fermi Avenue, Harwell, Oxon, OX11 0QR, UK
| | - Barron Henderson
- United States Environmental Protection Agency, Research Triangle Park, Durham, North Carolina 27709, USA
| | - Kelvin H. Bates
- NOAA Chemical Sciences Laboratory, Boulder, CO, 80305, USA
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, 80305, USA
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Lin X, Yang R, Zhang W, Zeng N, Zhao Y, Wang G, Li T, Cai Q. An integrated view of correlated emissions of greenhouse gases and air pollutants in China. CARBON BALANCE AND MANAGEMENT 2023; 18:9. [PMID: 37208447 DOI: 10.1186/s13021-023-00229-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 05/03/2023] [Indexed: 05/21/2023]
Abstract
BACKGROUND Air pollution in China has raised great concerns due to its adverse effects on air quality, human health, and climate. Emissions of air pollutants (APs) are inherently linked with CO2 emissions through fossil-energy consumption. Knowledge of the characteristics of APs and CO2 emissions and their relationships is fundamentally important in the pursuit of co-benefits in addressing air quality and climate issues in China. However, the linkages and interactions between APs and CO2 in China are not well understood. RESULTS Here, we conducted an ensemble study of six bottom-up inventories to identify the underlying drivers of APs and CO2 emissions growth and to explore their linkages in China. The results showed that, during 1980-2015, the power and industry sectors contributed 61-79% to China's overall emissions of CO2, NOx, and SO2. In addition, the residential and industrial sectors were large emitters (77-85%) of PM10, PM2.5, CO, BC, and OC. The emissions of CH4, N2O and NH3 were dominated by the agriculture sector (46-82%) during 1980-2015, while the share of CH4 emissions in the energy sector increased since 2010. During 1980-2015, APs and greenhouse gases (GHGs) emissions from residential sources generally decreased over time, while the transportation sector increased its impact on recent emissions, particularly for NOx and NMVOC. Since implementation of stringent pollution control measures and accompanying technological improvements in 2013, China has effectively limited pollution emissions (e.g., growth rates of -10% per year for PM and -20% for SO2) and slowed down the increasing trend of carbon emissions from the power and industrial sectors. We also found that areas with high emissions of CO, NOx, NMVOC, and SO2 also emitted large amounts of CO2, which demonstrates the possible common sources of APs and GHGs. Moreover, we found significant correlations between CO2 and APs (e.g., NOx, CO, SO2, and PM) emissions in the top 5% high-emitting grid cells, with more than 60% common grid cells during 2010-2015. CONCLUSIONS We found significant correlation in spatial and temporal aspects for CO2, and NOx, CO, SO2, and PM emissions in China. We targeted sectorial and spatial APs and GHGs emission hot-spots, which help for management and policy-making of collaborative reductions of them. This comprehensive analysis over 6 datasets improves our understanding of APs and GHGs emissions in China during the period of rapid industrialization from 1980 to 2015. This study helps elucidate the linkages between APs and CO2 from an integrated perspective, and provides insights for future synergistic emissions reduction.
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Affiliation(s)
- Xiaohui Lin
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Ruqi Yang
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Wen Zhang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
| | - Ning Zeng
- Department of Atmospheric and Oceanic Science, and Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
| | - Yu Zhao
- State Key Laboratory of Pollution Control & Resource Reuse and School of the Environment, Nanjing University, 163 Xianlin Ave, Nanjing, Jiangsu, China
| | - Guocheng Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Tingting Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, Guangdong, China
| | - Qixiang Cai
- State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
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3
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Carbo-Bustinza N, Belmonte M, Jimenez V, Montalban P, Rivera M, Martínez FG, Mohamed MMH, De La Cruz ARH, da Costa K, López-Gonzales JL. A machine learning approach to analyse ozone concentration in metropolitan area of Lima, Peru. Sci Rep 2022; 12:22084. [PMID: 36543811 PMCID: PMC9769486 DOI: 10.1038/s41598-022-26575-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022] Open
Abstract
The main objective of this study is to model the concentration of ozone in the winter season on air quality through machine learning algorithms, detecting its impact on population health. The study area involves four monitoring stations: Ate, San Borja, Santa Anita and Campo de Marte, all located in Metropolitan Lima during the years 2017, 2018 and 2019. Exploratory, correlational and predictive approaches are presented. The exploratory results showed that ATE is the station with the highest prevalence of ozone pollution. Likewise, in an hourly scale analysis, the pollution peaks were reported at 00:00 and 14:00. Finally, the machine learning models that showed the best predictive capacity for adjusting the ozone concentration were the linear regression and support vector machine.
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Affiliation(s)
- Natalí Carbo-Bustinza
- Doctorado Interdisciplinario en Ciencias Ambientales, Universidad de Playa Ancha, Valparaíso, Chile
| | - Marisol Belmonte
- Laboratorio de Biotecnología, Medio Ambiente e Ingeniería (LABMAI), Facultad de Ingeniería, Universidad de Playa Ancha, Avda. Leopoldo Carvallo 270, Valparaíso, Chile
- HUB-Ambiental, Universidad de Playa Ancha, Avda. Leopoldo Carvallo 270, Valparaíso, Chile
| | - Vasti Jimenez
- Facultad de Ingeniería y Arquitectura, Universidad Peruana Unión, Lima, Peru
| | - Paula Montalban
- Facultad de Ingeniería y Arquitectura, Universidad Peruana Unión, Lima, Peru
| | - Magiory Rivera
- Facultad de Ingeniería y Arquitectura, Universidad Peruana Unión, Lima, Peru
| | | | | | - Alex Rubén Huamán De La Cruz
- E.P. de Ingenieria Ambiental, Universidad Nacional Intercultural de la Selva Central Juan Santos Atahualpa, La Merced, Peru
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Sun Y, Zhang Q, Li K, Huo Y, Zhang Y. Trace gas emissions from laboratory combustion of leaves typically consumed in forest fires in Southwest China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 846:157282. [PMID: 35835195 DOI: 10.1016/j.scitotenv.2022.157282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 06/28/2022] [Accepted: 07/06/2022] [Indexed: 06/15/2023]
Abstract
Forest fires are becoming increasingly severe and frequent due to global climate change. Trace gases emitted from forest fires significantly affect atmospheric chemistry and climate change on a regional and global scale. Forest fires occur frequently in Southwest China, but systematic studies on trace gas emissions from forest fires in Southwest China are rare. Leaves of seven typical vegetation fuels based on their prominence in forest fires consumption in Southwest China were burned in a self-designed combustion device and the emission factors of eighteen trace gases (greenhouse gases, non-methane organic gases, nitrogenous gases, hydrogen chloride, and sulfur dioxide) at specific combustion stages (flaming and smoldering) were determined by using Fourier transform infrared spectroscopy, respectively. The emission factors data presented were compared with previous studies and can aid in the construction of an emission inventory. Pine needle combustion released a greater amount of methane in the smoldering stage than other broadleaf combustion. Peak values of emission factors for methane and non-methane organic gas are emitted by the smoldering of vegetation (Pinus kesiya and Pinus yunnanensis), which is endemic to forest fires in Southwest China. The emission factor for oxygenated volatile organic compounds (OVOCs) in the smoldering stage is greater than the flaming stage. This work established the relationship between modified combustion efficiency (MCE) with emission factors of hydrocarbons (except acetylene) and OVOCs. The results show that exponential fitting is more suitable than linear fitting for the seven leaf fuels (four broadleaf and three coniferous). However, the emission factors from the combustion of three coniferous fuels relative to all fuels are linear with MCE. Findings demonstrated that different combustion stages and fuel types have significant impacts on the emission factors, which also highlighted the importance of studying regional emissions.
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Affiliation(s)
- Yuping Sun
- State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230026, Anhui, China
| | - Qixing Zhang
- State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230026, Anhui, China.
| | - Kaili Li
- State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230026, Anhui, China
| | - Yinuo Huo
- State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230026, Anhui, China
| | - Yongming Zhang
- State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230026, Anhui, China
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Laughner JL, Neu JL, Schimel D, Wennberg PO, Barsanti K, Bowman KW, Chatterjee A, Croes BE, Fitzmaurice HL, Henze DK, Kim J, Kort EA, Liu Z, Miyazaki K, Turner AJ, Anenberg S, Avise J, Cao H, Crisp D, de Gouw J, Eldering A, Fyfe JC, Goldberg DL, Gurney KR, Hasheminassab S, Hopkins F, Ivey CE, Jones DBA, Liu J, Lovenduski NS, Martin RV, McKinley GA, Ott L, Poulter B, Ru M, Sander SP, Swart N, Yung YL, Zeng ZC. Societal shifts due to COVID-19 reveal large-scale complexities and feedbacks between atmospheric chemistry and climate change. Proc Natl Acad Sci U S A 2021; 118:e2109481118. [PMID: 34753820 PMCID: PMC8609622 DOI: 10.1073/pnas.2109481118] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/18/2021] [Indexed: 11/21/2022] Open
Abstract
The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.
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Affiliation(s)
- Joshua L Laughner
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125;
| | - Jessica L Neu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109;
| | - David Schimel
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109;
| | - Paul O Wennberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125;
- Division of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125
| | - Kelley Barsanti
- Department of Chemical and Environmental Engineering, University of California, Riverside, CA 92521
- Center for Environmental Research and Technology, Riverside, CA 92507
| | - Kevin W Bowman
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
| | - Abhishek Chatterjee
- Goddard Earth Sciences Technology and Research, Universities Space Research Association, Columbia, MD 21046
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771
| | - Bart E Croes
- Energy Research and Development Division, California Energy Commission, Sacramento, CA 95814
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309
| | - Helen L Fitzmaurice
- Department of Earth and Planetary Science, University of California, Berkeley, CA 94720
| | - Daven K Henze
- Department of Mechanical Engineering, University of Colorado, Boulder, CO 80309
| | - Jinsol Kim
- Department of Earth and Planetary Science, University of California, Berkeley, CA 94720
| | - Eric A Kort
- Department of Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI 48109
| | - Zhu Liu
- Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Kazuyuki Miyazaki
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
| | - Alexander J Turner
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
- Department of Earth and Planetary Science, University of California, Berkeley, CA 94720
- Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195
| | - Susan Anenberg
- Milken Institute School of Public Health, George Washington University, Washington, DC 20052
| | - Jeremy Avise
- Modeling and Meteorology Branch, California Air Resources Board, Sacramento, CA 95814
| | - Hansen Cao
- Department of Mechanical Engineering, University of Colorado, Boulder, CO 80309
| | - David Crisp
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
| | - Joost de Gouw
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309
- Department of Chemistry, University of Colorado, Boulder, CO 80309
| | - Annmarie Eldering
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
| | - John C Fyfe
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC, V8W 2Y2 Canada
| | - Daniel L Goldberg
- Milken Institute School of Public Health, George Washington University, Washington, DC 20052
| | - Kevin R Gurney
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ 86011
| | - Sina Hasheminassab
- Science and Technology Advancement Division, South Coast Air Quality Management District, Diamond Bar, CA, 91765
| | - Francesca Hopkins
- Department of Environmental Sciences, University of California, Riverside, CA 92521
| | - Cesunica E Ivey
- Department of Chemical and Environmental Engineering, University of California, Riverside, CA 92521
- Center for Environmental Research and Technology, Riverside, CA 92507
| | - Dylan B A Jones
- Department of Physics, University of Toronto, Toronto, ON, M5S 1A1 Canada
| | - Junjie Liu
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
| | - Nicole S Lovenduski
- Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, CO 80309
- Institute of Arctic and Alpine Research, University of Colorado, Boulder, CO 80309
| | - Randall V Martin
- McKelvey School of Engineering, Washington University in St. Louis, St. Louis, MO 63130
| | - Galen A McKinley
- Department of Earth and Environmental Sciences, Lamont Doherty Earth Observatory, Columbia University, Palisades, NY 10964
| | - Lesley Ott
- Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771
| | - Benjamin Poulter
- Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD 20771
| | - Muye Ru
- The Earth Institute, Columbia University, New York, NY 10025
- Nicholas School of the Environment, Duke University, Durham, NC 27707
| | - Stanley P Sander
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
| | - Neil Swart
- Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, Victoria, BC, V8W 2Y2 Canada
| | - Yuk L Yung
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109
| | - Zhao-Cheng Zeng
- Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA 90095
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Skowron A, Lee DS, De León RR, Lim LL, Owen B. Greater fuel efficiency is potentially preferable to reducing NO x emissions for aviation's climate impacts. Nat Commun 2021; 12:564. [PMID: 33495470 PMCID: PMC7835228 DOI: 10.1038/s41467-020-20771-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 12/10/2020] [Indexed: 01/30/2023] Open
Abstract
Aviation emissions of nitrogen oxides (NOx) alter the composition of the atmosphere, perturbing the greenhouse gases ozone and methane, resulting in positive and negative radiative forcing effects, respectively. In 1981, the International Civil Aviation Organization adopted a first certification standard for the regulation of aircraft engine NOx emissions with subsequent increases in stringency in 1992, 1998, 2004 and 2010 to offset the growth of the environmental impact of air transport, the main motivation being to improve local air quality with the assumed co-benefit of reducing NOx emissions at altitude and therefore their climate impacts. Increased stringency is an ongoing topic of discussion and more stringent standards are usually associated with their beneficial environmental impact. Here we show that this is not necessarily the right direction with respect to reducing the climate impacts of aviation (as opposed to local air quality impacts) because of the tradeoff effects between reducing NOx emissions and increased fuel usage, along with a revised understanding of the radiative forcing effects of methane. Moreover, the predicted lower surface air pollution levels in the future will be beneficial for reducing the climate impact of aviation NOx emissions. Thus, further efforts leading to greater fuel efficiency, and therefore lower CO2 emissions, may be preferable to reducing NOx emissions in terms of aviation's climate impacts.
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Affiliation(s)
- Agnieszka Skowron
- grid.25627.340000 0001 0790 5329Faculty of Science and Engineering, Manchester Metropolitan University, Manchester, UK
| | - David S. Lee
- grid.25627.340000 0001 0790 5329Faculty of Science and Engineering, Manchester Metropolitan University, Manchester, UK
| | - Rubén Rodríguez De León
- grid.25627.340000 0001 0790 5329Faculty of Science and Engineering, Manchester Metropolitan University, Manchester, UK
| | - Ling L. Lim
- grid.25627.340000 0001 0790 5329Faculty of Science and Engineering, Manchester Metropolitan University, Manchester, UK
| | - Bethan Owen
- grid.25627.340000 0001 0790 5329Faculty of Science and Engineering, Manchester Metropolitan University, Manchester, UK
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7
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Kuylenstierna JCI, Heaps CG, Ahmed T, Vallack HW, Hicks WK, Ashmore MR, Malley CS, Wang G, Lefèvre EN, Anenberg SC, Lacey F, Shindell DT, Bhattacharjee U, Henze DK. Development of the Low Emissions Analysis Platform - Integrated Benefits Calculator (LEAP-IBC) tool to assess air quality and climate co-benefits: Application for Bangladesh. ENVIRONMENT INTERNATIONAL 2020; 145:106155. [PMID: 33027737 DOI: 10.1016/j.envint.2020.106155] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 09/17/2020] [Accepted: 09/21/2020] [Indexed: 06/11/2023]
Abstract
Low- and middle-income countries have the largest health burdens associated with air pollution exposure, and are particularly vulnerable to climate change impacts. Substantial opportunities have been identified to simultaneously improve air quality and mitigate climate change due to overlapping sources of greenhouse gas and air pollutant emissions and because a subset of pollutants, short-lived climate pollutants (SLCPs), directly contribute to both impacts. However, planners in low- and middle-income countries often lack practical tools to quantify the air pollution and climate change impacts of different policies and measures. This paper presents a modelling framework implemented in the Low Emissions Analysis Platform - Integrated Benefits Calculator (LEAP-IBC) tool to develop integrated strategies to improve air quality, human health and mitigate climate change. The framework estimates emissions of greenhouse gases, SLCPs and air pollutants for historical years, and future projections for baseline and mitigation scenarios. These emissions are then used to quantify i) population-weighted annual average ambient PM2.5 concentrations across the target country, ii) household PM2.5 exposure of different population groups living in households cooking using different fuels/technologies and iii) radiative forcing from all emissions. Health impacts (premature mortality) attributable to ambient and household PM2.5 exposure and changes in global average temperature change are then estimated. This framework is applied in Bangladesh to evaluate the air quality and climate change benefits from implementation of Bangladesh's Nationally Determined Contribution (NDC) and National Action Plan to reduce SLCPs. Results show that the measures included to reduce GHGs in Bangladesh's NDC also have substantial benefits for air quality and human health. Full implementation of Bangladesh's NDC, and National SLCP Plan would reduce carbon dioxide, methane, black carbon and primary PM2.5 emissions by 25%, 34%, 46% and 45%, respectively in 2030 compared to a baseline scenario. These emission reductions could reduce population-weighted ambient PM2.5 concentrations in Bangladesh by 18% in 2030, and avoid approximately 12,000 and 100,000 premature deaths attributable to ambient and household PM2.5 exposures, respectively, in 2030. As countries are simultaneously planning to achieve the climate goals in the Paris Agreement, improve air quality to reduce health impacts and achieve the Sustainable Development Goals, the LEAP-IBC tool provides a practical framework by which planners can develop integrated strategies, achieving multiple air quality and climate benefits.
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Affiliation(s)
- Johan C I Kuylenstierna
- Stockholm Environment Institute, Department of Environment and Geography, University of York, United Kingdom
| | - Charles G Heaps
- US Center, Stockholm Environment Institute, Somerville, MA, United States
| | - Tanvir Ahmed
- Department of Civil Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - Harry W Vallack
- Stockholm Environment Institute, Department of Environment and Geography, University of York, United Kingdom
| | - W Kevin Hicks
- Stockholm Environment Institute, Department of Environment and Geography, University of York, United Kingdom
| | - Mike R Ashmore
- Stockholm Environment Institute, Department of Environment and Geography, University of York, United Kingdom
| | - Christopher S Malley
- Stockholm Environment Institute, Department of Environment and Geography, University of York, United Kingdom.
| | - Guozhong Wang
- Stockholm Environment Institute, Department of Environment and Geography, University of York, United Kingdom
| | - Elsa N Lefèvre
- Climate and Clean Air Coalition Secretariat, United Nations Environment Programme, Paris, France
| | - Susan C Anenberg
- Milken Institute, School of Public Health, George Washington University, Washington D.C., United States
| | - Forrest Lacey
- Department of Mechanical Engineering, University of Colorado, Boulder, CO, United States; National Center for Atmospheric Research, Boulder, CO, United States
| | - Drew T Shindell
- Nicholas School of the Environment, Duke University, Durham, NC, United States
| | | | - Daven K Henze
- Department of Mechanical Engineering, University of Colorado, Boulder, CO, United States
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8
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Liang CK, West JJ, Silva RA, Bian H, Chin M, Davila Y, Dentener FJ, Emmons L, Flemming J, Folberth G, Henze D, Im U, Jonson JE, Keating TJ, Kucsera T, Lenzen A, Lin M, Lund MT, Pan X, Park RJ, Pierce RB, Sekiya T, Sudo K, Takemura T. HTAP2 multi-model estimates of premature human mortality due to intercontinental transport of air pollution and emission sectors. ATMOSPHERIC CHEMISTRY AND PHYSICS 2018; 18:10497-10520. [PMID: 33204242 PMCID: PMC7668558 DOI: 10.5194/acp-18-10497-2018] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
Ambient air pollution from ozone and fine particulate matter is associated with premature mortality. As emissions from one continent influence air quality over others, changes in emissions can also influence human health on other continents. We estimate global air pollution-related premature mortality from exposure to PM2.5 and ozone, and the avoided deaths from 20% anthropogenic emission reductions from six source regions, North America (NAM), Europe (EUR), South Asia (SAS), East Asia (EAS), Russia/Belarus/Ukraine (RBU) and the Middle East (MDE), three global emission sectors, Power and Industry (PIN), Ground Transportation (TRN) and Residential (RES) and one global domain (GLO), using an ensemble of global chemical transport model simulations coordinated by the second phase of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP2), and epidemiologically-derived concentration-response functions. We build on results from previous studies of the TF-HTAP by using improved atmospheric models driven by new estimates of 2010 anthropogenic emissions (excluding methane), with more source and receptor regions, new consideration of source sector impacts, and new epidemiological mortality functions. We estimate 290,000 (95% CI: 30,000, 600,000) premature O3-related deaths and 2.8 million (0.5 million, 4.6 million) PM2.5-related premature deaths globally for the baseline year 2010. While 20% emission reductions from one region generally lead to more avoided deaths within the source region than outside, reducing emissions from MDE and RBU can avoid more O3-related deaths outside of these regions than within, and reducing MDE emissions also avoids more PM2.5-related deaths outside of MDE than within. Our findings that most avoided O3-related deaths from emission reductions in NAM and EUR occur outside of those regions contrast with those of previous studies, while estimates of PM2.5-related deaths from NAM, EUR, SAS and EAS emission reductions agree well. In addition, EUR, MDE and RBU have more avoided O3-related deaths from reducing foreign emissions than from domestic reductions. For six regional emission reductions, the total avoided extra-regional mortality is estimated as 6,000 (-3,400, 15,500) deaths/year and 25,100 (8,200, 35,800) deaths/year through changes in O3 and PM2.5, respectively. Interregional transport of air pollutants leads to more deaths through changes in PM2.5 than in O3, even though O3 is transported more on interregional scales, since PM2.5 has a stronger influence on mortality. For NAM and EUR, our estimates of avoided mortality from regional and extra-regional emission reductions are comparable to those estimated by regional models for these same experiments. In sectoral emission reductions, TRN emissions account for the greatest fraction (26-53% of global emission reduction) of O3-related premature deaths in most regions, in agreement with previous studies, except for EAS (58%) and RBU (38%) where PIN emissions dominate. In contrast, PIN emission reductions have the greatest fraction (38-78% of global emission reduction) of PM2.5-related deaths in most regions, except for SAS (45%) where RES emission dominates, which differs with previous studies in which RES emissions dominate global health impacts. The spread of air pollutant concentration changes across models contributes most to the overall uncertainty in estimated avoided deaths, highlighting the uncertainty in results based on a single model. Despite uncertainties, the health benefits of reduced intercontinental air pollution transport suggest that international cooperation may be desirable to mitigate pollution transported over long distances.
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Affiliation(s)
- Ciao-Kai Liang
- Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - J. Jason West
- Department of Environmental Sciences and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Raquel A. Silva
- Oak Ridge Institute for Science and Education at US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Huisheng Bian
- Goddard Earth Sciences and Technology Center, University of Maryland, Baltimore, MD, USA
| | - Mian Chin
- Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Yanko Davila
- Department of Mechanical Engineering, University of Colorado, Boulder, CO, USA
| | | | - Louisa Emmons
- Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research (NCAR), Boulder, CO, USA
| | | | | | - Daven Henze
- European Commission, Joint Research Center, Ispra, Italy
| | - Ulas Im
- Aarhus University, Department of Environmental Science, Frederiksborgvej, DK-4000, Roskilde, Denmark
| | | | - Terry J. Keating
- US Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Tom Kucsera
- Universities Space Research Association, Greenbelt, MD, USA
| | - Allen Lenzen
- Space Science & Engineering Center, University of Wisconsin -Madison, WI, USA
| | - Meiyun Lin
- Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA
| | | | - Xiaohua Pan
- Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
| | | | - R. Bradley Pierce
- NOAA National Environmental Satellite, Data, and Information Service, Madison, WI, USA
| | | | - Kengo Sudo
- Nagoya University, Furocho, Chigusa-ku, Nagoya, Japan
| | - Toshihiko Takemura
- Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan
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9
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Zhang Y, Cooper OR, Gaudel A, Nédélec P, Ogino SY, Thompson AM, West JJ. Tropospheric ozone change from 1980 to 2010 dominated by equatorward redistribution of emissions. NATURE GEOSCIENCE 2016; 9:875-879. [PMID: 33117431 PMCID: PMC7591124 DOI: 10.1038/ngeo2827] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
Since 1980, anthropogenic emissions of ozone precursors have decreased in developed regions, but increased in developing regions, particularly East and South Asia, redistributing emissions equatorwards1-4. Modeling studies have shown that the tropospheric ozone burden (B O3) is much more sensitive to emission changes in the tropics and Southern Hemisphere (SH) than other regions5-9. However, the effect of the spatial redistribution of emissions has not been isolated. Here we use a global chemical transport model to consider changes in anthropogenic short-lived emissions from 1980 to 2010, and separate the influence of changes in the spatial distribution of emissions from the total emission increase, on B O3 and surface ozone. We estimate that the spatial distribution change increased B O3 by slightly more than the combined influences of changes in the global emission magnitude itself and in global methane. These results are explained by the strong convection, fast reaction rates, and strong NOx sensitivity in the tropics and subtropics. Emissions increases in Southeast, East, and South Asia may be most important for the B O3 change. The spatial distribution of emissions has a dominant effect on global tropospheric ozone, suggesting that the future ozone burden will be determined mainly by emissions from the tropics and subtropics.
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Affiliation(s)
- Yuqiang Zhang
- Environmental Sciences and Engineering Department, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Owen R Cooper
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA
- Chemical Sciences Division, NOAA Earth System Research Laboratory, Boulder, CO 80305, USA
| | - Audrey Gaudel
- Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO 80309, USA
- Chemical Sciences Division, NOAA Earth System Research Laboratory, Boulder, CO 80305, USA
| | - Philippe Nédélec
- Laboratoire d'Aérologie, CNRS, Université Paul Sabatier Toulouse III, FR-31062 Toulouse, France
| | - Shin-Ya Ogino
- Japan Agency for Marine-Earth Science and Technology, Yokosuka 237-0061, Japan
| | | | - J Jason West
- Environmental Sciences and Engineering Department, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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10
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Li B, Gasser T, Ciais P, Piao S, Tao S, Balkanski Y, Hauglustaine D, Boisier JP, Chen Z, Huang M, Li LZ, Li Y, Liu H, Liu J, Peng S, Shen Z, Sun Z, Wang R, Wang T, Yin G, Yin Y, Zeng H, Zeng Z, Zhou F. The contribution of China's emissions to global climate forcing. Nature 2016; 531:357-61. [PMID: 26983540 DOI: 10.1038/nature17165] [Citation(s) in RCA: 76] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2014] [Accepted: 01/19/2016] [Indexed: 11/09/2022]
Abstract
Knowledge of the contribution that individual countries have made to global radiative forcing is important to the implementation of the agreement on "common but differentiated responsibilities" reached by the United Nations Framework Convention on Climate Change. Over the past three decades, China has experienced rapid economic development, accompanied by increased emission of greenhouse gases, ozone precursors and aerosols, but the magnitude of the associated radiative forcing has remained unclear. Here we use a global coupled biogeochemistry-climate model and a chemistry and transport model to quantify China's present-day contribution to global radiative forcing due to well-mixed greenhouse gases, short-lived atmospheric climate forcers and land-use-induced regional surface albedo changes. We find that China contributes 10% ± 4% of the current global radiative forcing. China's relative contribution to the positive (warming) component of global radiative forcing, mainly induced by well-mixed greenhouse gases and black carbon aerosols, is 12% ± 2%. Its relative contribution to the negative (cooling) component is 15% ± 6%, dominated by the effect of sulfate and nitrate aerosols. China's strongest contributions are 0.16 ± 0.02 watts per square metre for CO2 from fossil fuel burning, 0.13 ± 0.05 watts per square metre for CH4, -0.11 ± 0.05 watts per square metre for sulfate aerosols, and 0.09 ± 0.06 watts per square metre for black carbon aerosols. China's eventual goal of improving air quality will result in changes in radiative forcing in the coming years: a reduction of sulfur dioxide emissions would drive a faster future warming, unless offset by larger reductions of radiative forcing from well-mixed greenhouse gases and black carbon.
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Affiliation(s)
- Bengang Li
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.,Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, 210023, China
| | - Thomas Gasser
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France.,Centre International de Recherche en Environnement et Développement, CNRS-PontsParisTech-EHESS-AgroParisTech-CIRAD, 94736 Nogent-sur-Marne, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
| | - Shilong Piao
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.,Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing 100085, China
| | - Shu Tao
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Yves Balkanski
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
| | - Didier Hauglustaine
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
| | - Juan-Pablo Boisier
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
| | - Zhuo Chen
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Mengtian Huang
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Laurent Zhaoxin Li
- Laboratoire de Météorologie Dynamique, CNRS, Université Pierre et Marie Curie-Paris 6, 75252 Paris, France
| | - Yue Li
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Hongyan Liu
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Junfeng Liu
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Shushi Peng
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Zehao Shen
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Zhenzhong Sun
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Rong Wang
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
| | - Tao Wang
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
| | - Guodong Yin
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Yi Yin
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, 91191 Gif-sur-Yvette, France
| | - Hui Zeng
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Zhenzhong Zeng
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Feng Zhou
- Sino-French Institute for Earth System Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
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11
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Fiore AM, Naik V, Leibensperger EM. Air quality and climate connections. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2015; 65:645-85. [PMID: 25976481 DOI: 10.1080/10962247.2015.1040526] [Citation(s) in RCA: 157] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
UNLABELLED Multiple linkages connect air quality and climate change. Many air pollutant sources also emit carbon dioxide (CO2), the dominant anthropogenic greenhouse gas (GHG). The two main contributors to non-attainment of U.S. ambient air quality standards, ozone (O3) and particulate matter (PM), interact with radiation, forcing climate change. PM warms by absorbing sunlight (e.g., black carbon) or cools by scattering sunlight (e.g., sulfates) and interacts with clouds; these radiative and microphysical interactions can induce changes in precipitation and regional circulation patterns. Climate change is expected to degrade air quality in many polluted regions by changing air pollution meteorology (ventilation and dilution), precipitation and other removal processes, and by triggering some amplifying responses in atmospheric chemistry and in anthropogenic and natural sources. Together, these processes shape distributions and extreme episodes of O3 and PM. Global modeling indicates that as air pollution programs reduce SO2 to meet health and other air quality goals, near-term warming accelerates due to "unmasking" of warming induced by rising CO2. Air pollutant controls on CH4, a potent GHG and precursor to global O3 levels, and on sources with high black carbon (BC) to organic carbon (OC) ratios could offset near-term warming induced by SO2 emission reductions, while reducing global background O3 and regionally high levels of PM. Lowering peak warming requires decreasing atmospheric CO2, which for some source categories would also reduce co-emitted air pollutants or their precursors. Model projections for alternative climate and air quality scenarios indicate a wide range for U.S. surface O3 and fine PM, although regional projections may be confounded by interannual to decadal natural climate variability. Continued implementation of U.S. NOx emission controls guards against rising pollution levels triggered either by climate change or by global emission growth. Improved accuracy and trends in emission inventories are critical for accountability analyses of historical and projected air pollution and climate mitigation policies. IMPLICATIONS The expansion of U.S. air pollution policy to protect climate provides an opportunity for joint mitigation, with CH4 a prime target. BC reductions in developing nations would lower the global health burden, and for BC-rich sources (e.g., diesel) may lessen warming. Controls on these emissions could offset near-term warming induced by health-motivated reductions of sulfate (cooling). Wildfires, dust, and other natural PM and O3 sources may increase with climate warming, posing challenges to implementing and attaining air quality standards. Accountability analyses for recent and projected air pollution and climate control strategies should underpin estimated benefits and trade-offs of future policies.
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Affiliation(s)
- Arlene M Fiore
- a Department of Earth and Environmental Sciences and Lamont-Doherty Earth Observatory of Columbia University , Palisades , NY , USA
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12
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von Schneidemesser E, Monks PS. Air quality and climate--synergies and trade-offs. ENVIRONMENTAL SCIENCE. PROCESSES & IMPACTS 2013; 15:1315-25. [PMID: 23743609 DOI: 10.1039/c3em00178d] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Air quality and climate are often treated as separate science and policy areas. Air quality encompasses the here-and-now of pollutant emissions, atmospheric transformations and their direct effect on human and ecosystem health. Climate change deals with the drivers leading to a warmer world and the consequences of that. These two science and policy issues are inexorably linked via common pollutants, such as ozone (methane) and black carbon. This short review looks at the new scientific evidence around so-called "short-lived climate forcers" and the growing realisation that a way to meet short-term climate change targets may be through the control of "air quality" pollutants. None of the options discussed here can replace reduction of long-lived greenhouse gases, such as CO2, which is required for any long-term climate change mitigation strategy. An overview is given of the underlying science, remaining uncertainties, and some of the synergies and trade-offs for addressing air quality and climate in the science and policy context.
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13
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Aamaas B, Peters GP, Fuglestvedt JS. Simple emission metrics for climate impacts. EARTH SYSTEM DYNAMICS 2013. [PMID: 0 DOI: 10.5194/esd-4-145-2013] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Abstract. In the context of climate change, emissions of different species (e.g., carbon dioxide and methane) are not directly comparable since they have different radiative efficiencies and lifetimes. Since comparisons via detailed climate models are computationally expensive and complex, emission metrics were developed to allow a simple and straightforward comparison of the estimated climate impacts of emissions of different species. Emission metrics are not unique and variety of different emission metrics has been proposed, with key choices being the climate impacts and time horizon to use for comparisons. In this paper, we present analytical expressions and describe how to calculate common emission metrics for different species. We include the climate metrics radiative forcing, integrated radiative forcing, temperature change and integrated temperature change in both absolute form and normalised to a reference gas. We consider pulse emissions, sustained emissions and emission scenarios. The species are separated into three types: CO2 which has a complex decay over time, species with a simple exponential decay, and ozone precursors (NOx, CO, VOC) which indirectly effect climate via various chemical interactions. We also discuss deriving Impulse Response Functions, radiative efficiency, regional dependencies, consistency within and between metrics and uncertainties. We perform various applications to highlight key applications of emission metrics, which show that emissions of CO2 are important regardless of what metric and time horizon is used, but that the importance of short lived climate forcers varies greatly depending on the metric choices made. Further, the ranking of countries by emissions changes very little with different metrics despite large differences in metric values, except for the shortest time horizons (GWP20).
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14
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Fiore AM, Naik V, Spracklen DV, Steiner A, Unger N, Prather M, Bergmann D, Cameron-Smith PJ, Cionni I, Collins WJ, Dalsøren S, Eyring V, Folberth GA, Ginoux P, Horowitz LW, Josse B, Lamarque JF, MacKenzie IA, Nagashima T, O'Connor FM, Righi M, Rumbold ST, Shindell DT, Skeie RB, Sudo K, Szopa S, Takemura T, Zeng G. Global air quality and climate. Chem Soc Rev 2012; 41:6663-83. [PMID: 22868337 DOI: 10.1039/c2cs35095e] [Citation(s) in RCA: 114] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Emissions of air pollutants and their precursors determine regional air quality and can alter climate. Climate change can perturb the long-range transport, chemical processing, and local meteorology that influence air pollution. We review the implications of projected changes in methane (CH(4)), ozone precursors (O(3)), and aerosols for climate (expressed in terms of the radiative forcing metric or changes in global surface temperature) and hemispheric-to-continental scale air quality. Reducing the O(3) precursor CH(4) would slow near-term warming by decreasing both CH(4) and tropospheric O(3). Uncertainty remains as to the net climate forcing from anthropogenic nitrogen oxide (NO(x)) emissions, which increase tropospheric O(3) (warming) but also increase aerosols and decrease CH(4) (both cooling). Anthropogenic emissions of carbon monoxide (CO) and non-CH(4) volatile organic compounds (NMVOC) warm by increasing both O(3) and CH(4). Radiative impacts from secondary organic aerosols (SOA) are poorly understood. Black carbon emission controls, by reducing the absorption of sunlight in the atmosphere and on snow and ice, have the potential to slow near-term warming, but uncertainties in coincident emissions of reflective (cooling) aerosols and poorly constrained cloud indirect effects confound robust estimates of net climate impacts. Reducing sulfate and nitrate aerosols would improve air quality and lessen interference with the hydrologic cycle, but lead to warming. A holistic and balanced view is thus needed to assess how air pollution controls influence climate; a first step towards this goal involves estimating net climate impacts from individual emission sectors. Modeling and observational analyses suggest a warming climate degrades air quality (increasing surface O(3) and particulate matter) in many populated regions, including during pollution episodes. Prior Intergovernmental Panel on Climate Change (IPCC) scenarios (SRES) allowed unconstrained growth, whereas the Representative Concentration Pathway (RCP) scenarios assume uniformly an aggressive reduction, of air pollutant emissions. New estimates from the current generation of chemistry-climate models with RCP emissions thus project improved air quality over the next century relative to those using the IPCC SRES scenarios. These two sets of projections likely bracket possible futures. We find that uncertainty in emission-driven changes in air quality is generally greater than uncertainty in climate-driven changes. Confidence in air quality projections is limited by the reliability of anthropogenic emission trajectories and the uncertainties in regional climate responses, feedbacks with the terrestrial biosphere, and oxidation pathways affecting O(3) and SOA.
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Affiliation(s)
- Arlene M Fiore
- Department of Earth and Environmental Sciences and Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY, USA.
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