1
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Baublitz CB, Fiore AM, Ludwig SM, Nicely JM, Wolfe GM, Murray LT, Commane R, Prather MJ, Anderson DC, Correa G, Duncan BN, Follette-Cook M, Westervelt DM, Bourgeois I, Brune WH, Bui TP, DiGangi JP, Diskin GS, Hall SR, McKain K, Miller DO, Peischl J, Thames AB, Thompson CR, Ullmann K, Wofsy SC. An observation-based, reduced-form model for oxidation in the remote marine troposphere. Proc Natl Acad Sci U S A 2023; 120:e2209735120. [PMID: 37579162 PMCID: PMC10451388 DOI: 10.1073/pnas.2209735120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 06/26/2023] [Indexed: 08/16/2023] Open
Abstract
The hydroxyl radical (OH) fuels atmospheric chemical cycling as the main sink for methane and a driver of the formation and loss of many air pollutants, but direct OH observations are sparse. We develop and evaluate an observation-based proxy for short-term, spatial variations in OH (ProxyOH) in the remote marine troposphere using comprehensive measurements from the NASA Atmospheric Tomography (ATom) airborne campaign. ProxyOH is a reduced form of the OH steady-state equation representing the dominant OH production and loss pathways in the remote marine troposphere, according to box model simulations of OH constrained with ATom observations. ProxyOH comprises only eight variables that are generally observed by routine ground- or satellite-based instruments. ProxyOH scales linearly with in situ [OH] spatial variations along the ATom flight tracks (median r2 = 0.90, interquartile range = 0.80 to 0.94 across 2-km altitude by 20° latitudinal regions). We deconstruct spatial variations in ProxyOH as a first-order approximation of the sensitivity of OH variations to individual terms. Two terms modulate within-region ProxyOH variations-water vapor (H2O) and, to a lesser extent, nitric oxide (NO). This implies that a limited set of observations could offer an avenue for observation-based mapping of OH spatial variations over much of the remote marine troposphere. Both H2O and NO are expected to change with climate, while NO also varies strongly with human activities. We also illustrate the utility of ProxyOH as a process-based approach for evaluating intermodel differences in remote marine tropospheric OH.
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Affiliation(s)
- Colleen B. Baublitz
- Department of Earth and Environmental Sciences, Columbia University, New York, NY10027
- Division of Ocean and Climate Physics, Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY10964
| | - Arlene M. Fiore
- Department of Earth and Environmental Sciences, Columbia University, New York, NY10027
- Division of Ocean and Climate Physics, Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY10964
| | - Sarah M. Ludwig
- Department of Earth and Environmental Sciences, Columbia University, New York, NY10027
- Division of Ocean and Climate Physics, Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY10964
| | - Julie M. Nicely
- Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD20740
- Atmospheric Chemistry and Dynamics Laboratory, National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MD20771
| | - Glenn M. Wolfe
- Atmospheric Chemistry and Dynamics Laboratory, National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MD20771
| | - Lee T. Murray
- Department of Earth and Environmental Sciences, University of Rochester, Rochester, NY14627
| | - Róisín Commane
- Department of Earth and Environmental Sciences, Columbia University, New York, NY10027
- Division of Ocean and Climate Physics, Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY10964
| | - Michael J. Prather
- Department of Earth System Science, University of California, Irvine, CA92697
| | - Daniel C. Anderson
- Atmospheric Chemistry and Dynamics Laboratory, National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MD20771
- Goddard Earth Sciences Technology and Research II, University of Maryland Baltimore County, Baltimore, MD21250
| | - Gustavo Correa
- Division of Ocean and Climate Physics, Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY10964
| | - Bryan N. Duncan
- Atmospheric Chemistry and Dynamics Laboratory, National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MD20771
| | - Melanie Follette-Cook
- Atmospheric Chemistry and Dynamics Laboratory, National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MD20771
- Goddard Earth Sciences Technology and Research II, Morgan State University, Baltimore, MD21251
| | - Daniel M. Westervelt
- Division of Ocean and Climate Physics, Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY10964
- National Aeronautics and Space Administration Goddard Institute for Space Studies, New York, NY10025
| | - Ilann Bourgeois
- Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO80309
- National Oceanic and Atmospheric Administration Chemical Sciences Laboratory, Boulder, CO80305
| | - William H. Brune
- Department of Meteorology and Atmospheric Science, Pennsylvania State University, University Park, PA16802
| | - T. Paul Bui
- Atmospheric Science Branch, National Aeronautics and Space Administration Ames Research Center, Moffett Field, CA94035
| | - Joshua P. DiGangi
- National Aeronautics and Space Administration Langley Research Center, Hampton, VA23666
| | - Glenn S. Diskin
- National Aeronautics and Space Administration Langley Research Center, Hampton, VA23666
| | - Samuel R. Hall
- Atmospheric Chemistry Observations & Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO80307
| | - Kathryn McKain
- Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO80309
- National Oceanic and Atmospheric Administration Global Monitoring Laboratory, Boulder, CO80305
| | - David O. Miller
- Department of Meteorology and Atmospheric Science, Pennsylvania State University, University Park, PA16802
| | - Jeff Peischl
- Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO80309
- National Oceanic and Atmospheric Administration Chemical Sciences Laboratory, Boulder, CO80305
| | - Alexander B. Thames
- Department of Meteorology and Atmospheric Science, Pennsylvania State University, University Park, PA16802
| | - Chelsea R. Thompson
- Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO80309
- National Oceanic and Atmospheric Administration Chemical Sciences Laboratory, Boulder, CO80305
| | - Kirk Ullmann
- Atmospheric Chemistry Observations & Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO80307
| | - Steven C. Wofsy
- Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA02138
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2
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Raheja G, Nimo J, Appoh EKE, Essien B, Sunu M, Nyante J, Amegah M, Quansah R, Arku RE, Penn SL, Giordano MR, Zheng Z, Jack D, Chillrud S, Amegah K, Subramanian R, Pinder R, Appah-Sampong E, Tetteh EN, Borketey MA, Hughes AF, Westervelt DM. Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM 2.5 Monitoring in Accra, Ghana. Environ Sci Technol 2023; 57:10708-10720. [PMID: 37437161 PMCID: PMC10373484 DOI: 10.1021/acs.est.2c09264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 06/01/2023] [Accepted: 06/02/2023] [Indexed: 07/14/2023]
Abstract
Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair-PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 μg/m3, followed by PurpleAir PA-II (4.54 μg/m3) and Clarity Node-S (13.68 μg/m3). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2: 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 μg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 μg/m3, which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 μg/m3. While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly grow.
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Affiliation(s)
- Garima Raheja
- Department
of Earth and Environmental Sciences, Columbia
University, New York, New York 10027, United States
- Lamont-Doherty
Earth Observatory of Columbia University, Palisades, New York 10964, United States
| | - James Nimo
- Department
of Physics, University of Ghana, Legon, Ghana, Ghana
- African
Institute of Mathematical Sciences, Kigali, Rwanda
| | | | | | - Maxwell Sunu
- Ghana
Environmental Protection Agency, Accra, Ghana
| | - John Nyante
- Ghana
Environmental Protection Agency, Accra, Ghana
| | | | | | - Raphael E. Arku
- Department
of Environmental Health Sciences, School of Public Health and Health
Sciences, University of Massachusetts, Amherst, Massachusetts 01003, United States
| | - Stefani L. Penn
- Industrial
Economics, Inc, Cambridge, Massachusetts 02140, United States
| | - Michael R. Giordano
- Univ
Paris Est Creteil, CNRS UMS 3563, Ecole Nationale des Ponts et Chaussés,
Université de Paris, OSU-EFLUVE—Observatoire Sciences
de L’Univers-Envelopes Fluides de La Ville à L’Exobiologie, F-94010 Créteil, France
| | - Zhonghua Zheng
- Department
of Earth and Environmental Sciences, The
University of Manchester, Manchester M13 9PL, U.K.
| | - Darby Jack
- Department of Environmental Health Sciences, Mailman
School of Public
Health, Columbia University, New York, New York 10032, United States
| | - Steven Chillrud
- Department of Environmental Health Sciences, Mailman
School of Public
Health, Columbia University, New York, New York 10032, United States
| | | | - R. Subramanian
- Univ
Paris Est Creteil, CNRS UMS 3563, Ecole Nationale des Ponts et Chaussés,
Université de Paris, OSU-EFLUVE—Observatoire Sciences
de L’Univers-Envelopes Fluides de La Ville à L’Exobiologie, F-94010 Créteil, France
- Kigali Collaborative
Research Centre, Kigali, Rwanda
| | - Robert Pinder
- Environmental Protection Agency, Raleigh, North Carolina 27709, United States
| | | | | | | | | | - Daniel M. Westervelt
- Lamont-Doherty
Earth Observatory of Columbia University, Palisades, New York 10964, United States
- NASA Goddard Institute for Space Science, New York, New York 10025, United States
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3
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Ivey CE, Amegah AK, Hodoli CG, Kelly KE, Lawal AS, Pant P, Singh S, Subramanian R, Torres I, Westervelt DM, Yu H. To Share or Not To Share? Academic Incentives May Hamper Public Good. Environ Sci Technol 2022; 56:15186-15188. [PMID: 36223644 PMCID: PMC9671041 DOI: 10.1021/acs.est.2c05721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Indexed: 06/16/2023]
Affiliation(s)
- Cesunica E. Ivey
- Department
of Civil and Environmental Engineering, University of California, Berkeley, Davis Hall, Berkeley, California 94720, United States
| | - A. Kofi Amegah
- Public
Health Research Group, Department of Biomedical Sciences, University of Cape Coast, New Administration Block, Cape Coast, Central RU8217, Ghana
| | - Collins Gameli Hodoli
- School
of Built Environment, University of Environment
and Sustainable Development, Private Mail Bag, Somanya, Eastern Region, Ghana
- Clean
Air One Atmosphere, Accra, Ghana
| | - Kerry E. Kelly
- Department
of Chemical Engineering, University of Utah, 50 South Central Campus Drive, 3290
MEB, Salt Lake City, Utah 84112, United States
| | - Abiola S. Lawal
- Department
of Civil and Environmental Engineering, University of California, Berkeley, Davis Hall, Berkeley, California 94720, United States
- School
of
Civil and Environmental Engineering, Georgia
Institute of Technology, Atlanta, Georgia 30332, United States
| | - Pallavi Pant
- Health Effects
Institute, 75 Federal
Street, Suite 1400, Boston, Massachusetts 02110, United States
- Women
in Air Quality in South Asia, New
Delhi 110088, India
| | - Saumya Singh
- Department
of Civil and Environmental Engineering, University of California, Berkeley, Davis Hall, Berkeley, California 94720, United States
- Women
in Air Quality in South Asia, New
Delhi 110088, India
| | - R. Subramanian
- Qatar
Environment and Energy Research Institute, Environment & Sustainability Center, Doha, Qatar
- Kigali
Collaborative Research Center, Carnegie Mellon Africa Campus, Kigali Innovation Center, Kigali, Rwanda
| | - Ivette Torres
- Department
of Civil and Environmental Engineering, University of California, Berkeley, Davis Hall, Berkeley, California 94720, United States
- People’s
Collective for Environmental Justice, 224400 Barton Road, #21-296, Grand Terrace, California 92313, United States
| | - Daniel M. Westervelt
- Lamont
Doherty Earth Observatory, Columbia University, 61 Route 9W, Palisades, New York 10964, United States
- NASA Goddard Institute for Space Studies, 2880 Broadway, New York, New York 10025, United States
| | - Haofei Yu
- Department
of Civil, Environmental, and Construction Engineering, University of Central Florida, 12760 Pegasus Drive, Orlando, Florida 32816, United States
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4
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Raheja G, Sabi K, Sonla H, Gbedjangni EK, McFarlane CM, Hodoli CG, Westervelt DM. A Network of Field-Calibrated Low-Cost Sensor Measurements of PM 2.5 in Lomé, Togo, Over One to Two Years. ACS Earth Space Chem 2022; 6:1011-1021. [PMID: 35495364 PMCID: PMC9036579 DOI: 10.1021/acsearthspacechem.1c00391] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 02/18/2022] [Accepted: 02/23/2022] [Indexed: 05/07/2023]
Abstract
Air pollution is a leading cause of global premature mortality and is especially prevalent in many low- and middle-income countries (LMICs). In sub-Saharan Africa, preliminary monitoring networks, satellite retrievals of air-quality-relevant species, and air quality models show ambient fine particulate matter (PM2.5) concentrations that far exceed the World Health Organization guidelines, yet many areas remain largely unmonitored and understudied. Deploying a network of five low-cost PurpleAir PM2.5 monitors over 2 years (2019-2021), we present the first multiyear ambient air pollution monitoring data results from Lomé, Togo, a major West African coastal city with a population of about 1.4 million people. The full-study time period network-wide mean measured daily PM2.5 concentration is 23.5 μg m-3 m-3. The strong regional influence of the dry and dusty Harmattan wind increases the local average PM2.5 concentration by up to 58% during December through February, but the diurnal and weekly trends in PM2.5 are largely controlled by local influences. At all sites, more than 87% of measured days exceeded the new WHO Daily PM2.5 guidelines; these first measurements highlight the need for air quality improvement in a rapidly growing urban metropolis.
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Affiliation(s)
- Garima Raheja
- Lamont-Doherty
Earth Observatory of Columbia University, 61 Route 9W, Palisades, New York 10964, United States
- Department
of Earth and Environmental Science, Columbia
University, 1200 Amsterdam Avenue, New York, New York 10027, United
States
| | - Kokou Sabi
- Université
de Lomé (UL), 01BP, 1515 Lomé, Togo
| | | | | | - Celeste M. McFarlane
- Lamont-Doherty
Earth Observatory of Columbia University, 61 Route 9W, Palisades, New York 10964, United States
| | | | - Daniel M. Westervelt
- Lamont-Doherty
Earth Observatory of Columbia University, 61 Route 9W, Palisades, New York 10964, United States
- NASA
Goddard Institute for Space Studies, 2880 Broadway, New York, New York 10025, United
States
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5
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Liu S, Xing J, Westervelt DM, Liu S, Ding D, Fiore AM, Kinney PL, Zhang Y, He MZ, Zhang H, Sahu SK, Zhang F, Zhao B, Wang S. Role of emission controls in reducing the 2050 climate change penalty for PM 2.5 in China. Sci Total Environ 2021; 765:144338. [PMID: 33401063 DOI: 10.1016/j.scitotenv.2020.144338] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 12/02/2020] [Accepted: 12/03/2020] [Indexed: 05/22/2023]
Abstract
Previous studies demonstrated that global warming can lead to deteriorated air quality even when anthropogenic emissions were kept constant, which has been called a climate change penalty on air quality. It is expected that anthropogenic emissions will decrease significantly in the future considering the aggressive emission control actions in China. However, the dependence of climate change penalty on the choice of emission scenario is still uncertain. To fill this gap, we conducted multiple independent model simulations to investigate the response of PM2.5 to future (2050) climate warming (RCP8.5) in China but with different emission scenarios, including the constant 2015 emissions, the 2050 CLE emissions (based on Current Legislation), and the 2050 MTFR emissions (based on Maximum Technically Feasible Reduction). For each set of emissions, we estimate climate change penalty as the difference in PM2.5 between a pair of simulations with either 2015 or 2050 meteorology. Under 2015 emissions, we find a PM2.5 climate change penalty of 1.43 μg m-3 in Eastern China, leading to an additional 35,000 PM2.5-related premature deaths [95% confidence interval (CI), 21,000-40,000] by 2050. However, the PM2.5 climate change penalty weakens to 0.24 μg m-3 with strict anthropogenic emission controls under the 2050 MTFR emissions, which decreases the associated PM2.5-related deaths to 17,000. The smaller MTFR climate change penalty contributes 14% of the total PM2.5 decrease when both emissions and meteorology are changed from 2015 to 2050, and 24% of total health benefits associated with this PM2.5 decrease in Eastern China. This finding suggests that controlling anthropogenic emissions can effectively reduce the climate change penalty on PM2.5 and its associated premature deaths, even though a climate change penalty still occurs even under MTFR. Strengthened controls on anthropogenic emissions are key to attaining air quality targets and protecting human health in the context of future global climate change.
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Affiliation(s)
- Song Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
| | - Jia Xing
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China.
| | - Daniel M Westervelt
- Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York, NY, USA; NASA Goddard Institute for Space Studies, New York, NY, USA
| | - Shuchang Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
| | - Dian Ding
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
| | - Arlene M Fiore
- Lamont-Doherty Earth Observatory, Columbia University, Palisades, New York, NY, USA; Department of Earth and Environmental Sciences, Columbia University, Palisades, New York, NY, USA
| | | | - Yuqiang Zhang
- Nicholas School of the Environment, Duke University, Durham, NC, USA
| | - Mike Z He
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Hongliang Zhang
- Department of Environmental Science and Engineering, Fudan University, Shanghai, China
| | - Shovan K Sahu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
| | - Fenfen Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China
| | - Bin Zhao
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing, China.
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6
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Fanourgakis GS, Kanakidou M, Nenes A, Bauer SE, Bergman T, Carslaw KS, Grini A, Hamilton DS, Johnson JS, Karydis VA, Kirkevåg A, Kodros JK, Lohmann U, Luo G, Makkonen R, Matsui H, Neubauer D, Pierce JR, Schmale J, Stier P, Tsigaridis K, van Noije T, Wang H, Watson-Parris D, Westervelt DM, Yang Y, Yoshioka M, Daskalakis N, Decesari S, Gysel-Beer M, Kalivitis N, Liu X, Mahowald NM, Myriokefalitakis S, Schrödner R, Sfakianaki M, Tsimpidi AP, Wu M, Yu F. Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation. Atmos Chem Phys 2019; 19:8591-8617. [PMID: 33273898 PMCID: PMC7709872 DOI: 10.5194/acp-19-8591-2019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB -13% and -22% for updraft velocities 0.3 and 0.6 ms-1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (∂N d/∂N a) and to updraft velocity (∂N d/∂w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities ∂N d/∂N a and ∂N d/∂w; models may be predisposed to be too "aerosol sensitive" or "aerosol insensitive" in aerosol-cloud-climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.
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Affiliation(s)
- George S. Fanourgakis
- Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, 70013, Greece
| | - Maria Kanakidou
- Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, 70013, Greece
| | - Athanasios Nenes
- Laboratory of Atmospheric Processes and their Impacts, School of Architecture, Civil & Environmental Engineering, École Polytechnique Federale de Lausanne, Lausanne, 1015, Switzerland
- Institute of Chemical Engineering Sciences, Foundation for Research and Technology (FORTH/ICE-HT), Hellas, 26504, Patras, Greece
| | - Susanne E. Bauer
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Center for Climate Systems Research, Columbia University, New York, NY, USA
| | - Tommi Bergman
- Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
| | - Ken S. Carslaw
- School of Earth and Environment, University of Leeds, UK
| | | | - Douglas S. Hamilton
- Department of Earth and Atmospheric Sciences, Atkinson Center for a Sustainable Future, Cornell University, Ithaca, NY, USA
| | | | - Vlassis A. Karydis
- Department of Atmospheric Chemistry, Max Planck Institute for Chemistry, Mainz, Germany
- Forschungszentrum Jülich, Inst Energy & Climate Res IEK-8, 52425 Jülich, Germany
| | - Alf Kirkevåg
- Norwegian Meteorological Institute, Oslo, Norway
| | - John K. Kodros
- Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado, USA
| | - Ulrike Lohmann
- Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
| | - Gan Luo
- Climate Atmospheric Sciences Research Center , of the State University of New York at Albany, Albany, 12203, New York, USA
| | - Risto Makkonen
- Climate System Research, Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki, Finland
- Institute for Atmospheric and Earth System Research/Physics, University of Helsinki, P.O. Box 64, 00014 Helsinki, Finland
| | - Hitoshi Matsui
- Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan
| | - David Neubauer
- Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
| | - Jeffrey R. Pierce
- Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado, USA
| | - Julia Schmale
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen, Switzerland
| | - Philip Stier
- Atmospheric, Oceanic & Planetary Physics, Department of Physics, University of Oxford, Oxford OX1 2JD, UK
| | - Kostas Tsigaridis
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Center for Climate Systems Research, Columbia University, New York, NY, USA
| | - Twan van Noije
- Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
| | - Hailong Wang
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Duncan Watson-Parris
- Atmospheric, Oceanic & Planetary Physics, Department of Physics, University of Oxford, Oxford OX1 2JD, UK
| | - Daniel M. Westervelt
- NASA Goddard Institute for Space Studies, New York, NY, USA
- Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY 10964, USA
| | - Yang Yang
- Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | | | - Nikos Daskalakis
- Laboratory for Modeling and Observation of the Earth System (LAMOS) Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
| | - Stefano Decesari
- Institute of Atmospheric Sciences and Climate, National Research Council of Italy, Via Piero Gobetti, 101, 40129 Bologna, Italy
| | - Martin Gysel-Beer
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen, Switzerland
| | - Nikos Kalivitis
- Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, 70013, Greece
| | - Xiaohong Liu
- Department of Atmospheric Science, University of Wyoming, Laramie, Wyoming, USA
| | - Natalie M. Mahowald
- Department of Earth and Atmospheric Sciences, Atkinson Center for a Sustainable Future, Cornell University, Ithaca, NY, USA
| | - Stelios Myriokefalitakis
- Institute for Environmental Research and Sustainable Development (IERSD), National Observatory of Athens, Penteli, Greece
| | - Roland Schrödner
- Centre for Environmental and Climate Research, Lund University, Lund, Sweden
| | - Maria Sfakianaki
- Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, 70013, Greece
| | - Alexandra P. Tsimpidi
- Department of Atmospheric Chemistry, Max Planck Institute for Chemistry, Mainz, Germany
| | - Mingxuan Wu
- Department of Atmospheric Science, University of Wyoming, Laramie, Wyoming, USA
| | - Fangqun Yu
- Climate Atmospheric Sciences Research Center , of the State University of New York at Albany, Albany, 12203, New York, USA
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