Articles | Volume 22, issue 11
https://doi.org/10.5194/acp-22-7575-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-7575-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Jun 2022
Research article |
| 13 Jun 2022
| 13 Jun 2022
The relationship between PM2.5 and anticyclonic wave activity during summer over the United States
Ye Wang
CORRESPONDING AUTHOR
College of General Aviation and Flight, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China
Department of Earth and Atmospheric Science, Cornell University, Ithaca, NY, USA
Natalie Mahowald
Department of Earth and Atmospheric Science, Cornell University, Ithaca, NY, USA
Peter Hess
Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY, USA
Wenxiu Sun
Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY, USA
now at: BloomSky Inc., Burlingame, CA, USA
Gang Chen
Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA, USA
Related authors
No articles found.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, P. Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankararaman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Johann Engelbrecht, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbigniew Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gómez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal L. Weagle, and Xi Zhao
Atmos. Chem. Phys., 25, 4665–4702, https://doi.org/10.5194/acp-25-4665-2025, https://doi.org/10.5194/acp-25-4665-2025, 2025
Short summary
Short summary
Aerosol particles are an important part of the Earth system, but their concentrations are spatially and temporally heterogeneous, as well as being variable in size and composition. Here, we present a new compilation of PM2.5 and PM10 aerosol observations, focusing on the spatial variability across different observational stations, including composition, and demonstrate a method for comparing the data sets to model output.
Danny M. Leung, Jasper F. Kok, Longlei Li, David M. Lawrence, Natalie M. Mahowald, Simone Tilmes, and Erik Kluzek
Atmos. Chem. Phys., 25, 2311–2331, https://doi.org/10.5194/acp-25-2311-2025, https://doi.org/10.5194/acp-25-2311-2025, 2025
Short summary
Short summary
This study derives a gridded dust emission dataset for 1841–2000 by employing a combination of observed dust from core records and reanalyzed global dust cycle constraints. We evaluate the ability of global models to replicate the observed historical dust variability by using the emission dataset to force a historical simulation in an Earth system model. We show that prescribing our emissions forces the model to better match observations than other mechanistic models.
Mingxu Liu, Hitoshi Matsui, Douglas S. Hamilton, Sagar D. Rathod, Kara D. Lamb, and Natalie M. Mahowald
Atmos. Chem. Phys., 24, 13115–13127, https://doi.org/10.5194/acp-24-13115-2024, https://doi.org/10.5194/acp-24-13115-2024, 2024
Short summary
Short summary
Atmospheric aerosol deposition provides bioavailable iron to promote marine primary production, yet the estimates of its fluxes remain highly uncertain. This study, by performing global aerosol simulations, demonstrates that iron-containing particle size upon emission is a critical factor in regulating soluble iron input to open oceans. Further observational constraints on this are needed to reduce modeling uncertainties.
Katrine A. Gorham, Sam Abernethy, Tyler R. Jones, Peter Hess, Natalie M. Mahowald, Daphne Meidan, Matthew S. Johnson, Maarten M. J. W. van Herpen, Yangyang Xu, Alfonso Saiz-Lopez, Thomas Röckmann, Chloe A. Brashear, Erika Reinhardt, and David Mann
Atmos. Chem. Phys., 24, 5659–5670, https://doi.org/10.5194/acp-24-5659-2024, https://doi.org/10.5194/acp-24-5659-2024, 2024
Short summary
Short summary
Rapid reduction in atmospheric methane is needed to slow the rate of global warming. Reducing anthropogenic methane emissions is a top priority. However, atmospheric methane is also impacted by rising natural emissions and changing sinks. Studies of possible atmospheric methane removal approaches, such as iron salt aerosols to increase the chlorine radical sink, benefit from a roadmapped approach to understand if there may be viable and socially acceptable ways to decrease future risk.
Weiming Ma, Hailong Wang, Gang Chen, Yun Qian, Ian Baxter, Yiling Huo, and Mark W. Seefeldt
Atmos. Chem. Phys., 24, 4451–4472, https://doi.org/10.5194/acp-24-4451-2024, https://doi.org/10.5194/acp-24-4451-2024, 2024
Short summary
Short summary
Extreme warming events with surface temperature going above 0°C can occur in the high-Arctic winter. Although reanalysis data show that these events were short-lived and occurred rarely during 1980–2021, they have become more frequent, stronger, and longer lasting latterly. A dipole pattern, comprising high- and low-pressure systems, is found to be the key in driving them. These findings have implications for the recent changes in sea ice, hydrological cycle, and ecosystem over the Arctic.
Danny M. Leung, Jasper F. Kok, Longlei Li, Natalie M. Mahowald, David M. Lawrence, Simone Tilmes, Erik Kluzek, Martina Klose, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 24, 2287–2318, https://doi.org/10.5194/acp-24-2287-2024, https://doi.org/10.5194/acp-24-2287-2024, 2024
Short summary
Short summary
This study uses a premier Earth system model to evaluate a new desert dust emission scheme proposed in our companion paper. We show that our scheme accounts for more dust emission physics, hence matching better against observations than other existing dust emission schemes do. Our scheme's dust emissions also couple tightly with meteorology, hence likely improving the modeled dust sensitivity to climate change. We believe this work is vital for improving dust representation in climate models.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankarararman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Hannele Hakola, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbiginiw Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gomez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal Weagle, and Xi Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-1, https://doi.org/10.5194/essd-2024-1, 2024
Preprint withdrawn
Short summary
Short summary
Aerosol particles can interact with incoming solar radiation and outgoing long wave radiation, change cloud properties, affect photochemistry, impact surface air quality, and when deposited impact surface albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. Here we present a new compilation of aerosol observations including composition, a methodology for comparing the datasets to model output, and show the implications of these results using one model.
Natalie M. Mahowald, Longlei Li, Samuel Albani, Douglas S. Hamilton, and Jasper F. Kok
Atmos. Chem. Phys., 24, 533–551, https://doi.org/10.5194/acp-24-533-2024, https://doi.org/10.5194/acp-24-533-2024, 2024
Short summary
Short summary
Estimating past aerosol radiative effects and their uncertainties is an important topic in climate science. Aerosol radiative effects propagate into large uncertainties in estimates of how present and future climate evolves with changing greenhouse gas emissions. A deeper understanding of how aerosols interacted with the atmospheric energy budget under past climates is hindered in part by a lack of relevant paleo-observations and in part because less attention has been paid to the problem.
María Gonçalves Ageitos, Vincenzo Obiso, Ron L. Miller, Oriol Jorba, Martina Klose, Matt Dawson, Yves Balkanski, Jan Perlwitz, Sara Basart, Enza Di Tomaso, Jerónimo Escribano, Francesca Macchia, Gilbert Montané, Natalie M. Mahowald, Robert O. Green, David R. Thompson, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 23, 8623–8657, https://doi.org/10.5194/acp-23-8623-2023, https://doi.org/10.5194/acp-23-8623-2023, 2023
Short summary
Short summary
Dust aerosols affect our climate differently depending on their mineral composition. We include dust mineralogy in an atmospheric model considering two existing soil maps, which still have large associated uncertainties. The soil data and the distribution of the minerals in different aerosol sizes are key to our model performance. We find significant regional variations in climate-relevant variables, which supports including mineralogy in our current models and the need for improved soil maps.
Danny M. Leung, Jasper F. Kok, Longlei Li, Gregory S. Okin, Catherine Prigent, Martina Klose, Carlos Pérez García-Pando, Laurent Menut, Natalie M. Mahowald, David M. Lawrence, and Marcelo Chamecki
Atmos. Chem. Phys., 23, 6487–6523, https://doi.org/10.5194/acp-23-6487-2023, https://doi.org/10.5194/acp-23-6487-2023, 2023
Short summary
Short summary
Desert dust modeling is important for understanding climate change, as dust regulates the atmosphere's greenhouse effect and radiation. This study formulates and proposes a more physical and realistic desert dust emission scheme for global and regional climate models. By considering more aeolian processes in our emission scheme, our simulations match better against dust observations than existing schemes. We believe this work is vital in improving dust representation in climate models.
Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, https://doi.org/10.5194/gmd-15-8181-2022, 2022
Short summary
Short summary
This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; and 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust–climate interactions using CAM, such as the dust-radiation and dust–cloud interactions.
Julius Vira, Peter Hess, Money Ossohou, and Corinne Galy-Lacaux
Atmos. Chem. Phys., 22, 1883–1904, https://doi.org/10.5194/acp-22-1883-2022, https://doi.org/10.5194/acp-22-1883-2022, 2022
Short summary
Short summary
Ammonia is one of the main components of nitrogen deposition. Here we use a new model to assess the ammonia emissions from agriculture, the largest anthropogenic source of ammonia. The model results are consistent with earlier estimates over industrialized regions in agreement with observations. However, the model predicts much higher emissions over sub-Saharan Africa compared to earlier estimates. Available observations from surface stations and satellites support these higher emissions.
Jasper F. Kok, Adeyemi A. Adebiyi, Samuel Albani, Yves Balkanski, Ramiro Checa-Garcia, Mian Chin, Peter R. Colarco, Douglas S. Hamilton, Yue Huang, Akinori Ito, Martina Klose, Danny M. Leung, Longlei Li, Natalie M. Mahowald, Ron L. Miller, Vincenzo Obiso, Carlos Pérez García-Pando, Adriana Rocha-Lima, Jessica S. Wan, and Chloe A. Whicker
Atmos. Chem. Phys., 21, 8127–8167, https://doi.org/10.5194/acp-21-8127-2021, https://doi.org/10.5194/acp-21-8127-2021, 2021
Short summary
Short summary
Desert dust interacts with virtually every component of the Earth system, including the climate system. We develop a new methodology to represent the global dust cycle that integrates observational constraints on the properties and abundance of desert dust with global atmospheric model simulations. We show that the resulting representation of the global dust cycle is more accurate than what can be obtained from a large number of current climate global atmospheric models.
Jasper F. Kok, Adeyemi A. Adebiyi, Samuel Albani, Yves Balkanski, Ramiro Checa-Garcia, Mian Chin, Peter R. Colarco, Douglas S. Hamilton, Yue Huang, Akinori Ito, Martina Klose, Longlei Li, Natalie M. Mahowald, Ron L. Miller, Vincenzo Obiso, Carlos Pérez García-Pando, Adriana Rocha-Lima, and Jessica S. Wan
Atmos. Chem. Phys., 21, 8169–8193, https://doi.org/10.5194/acp-21-8169-2021, https://doi.org/10.5194/acp-21-8169-2021, 2021
Short summary
Short summary
The many impacts of dust on the Earth system depend on dust mineralogy, which varies between dust source regions. We constrain the contribution of the world’s main dust source regions by integrating dust observations with global model simulations. We find that Asian dust contributes more and that North African dust contributes less than models account for. We obtain a dataset of each source region’s contribution to the dust cycle that can be used to constrain dust impacts on the Earth system.
Longlei Li, Natalie M. Mahowald, Ron L. Miller, Carlos Pérez García-Pando, Martina Klose, Douglas S. Hamilton, Maria Gonçalves Ageitos, Paul Ginoux, Yves Balkanski, Robert O. Green, Olga Kalashnikova, Jasper F. Kok, Vincenzo Obiso, David Paynter, and David R. Thompson
Atmos. Chem. Phys., 21, 3973–4005, https://doi.org/10.5194/acp-21-3973-2021, https://doi.org/10.5194/acp-21-3973-2021, 2021
Short summary
Short summary
For the first time, this study quantifies the range of the dust direct radiative effect due to uncertainty in the soil mineral abundance using all currently available information. We show that the majority of the estimated direct radiative effect range is due to uncertainty in the simulated mass fractions of iron oxides and thus their soil abundance, which is independent of the model employed. We therefore prove the necessity of considering mineralogy for understanding dust–climate interactions.
Julius Vira, Peter Hess, Jeff Melkonian, and William R. Wieder
Geosci. Model Dev., 13, 4459–4490, https://doi.org/10.5194/gmd-13-4459-2020, https://doi.org/10.5194/gmd-13-4459-2020, 2020
Short summary
Short summary
Mostly emitted by the agricultural sector, ammonia has an important role in atmospheric chemistry. We developed a model to simulate how ammonia emissions respond to changes in temperature and soil moisture, and we evaluated agricultural ammonia emissions globally. The simulated emissions agree with earlier estimates over many regions, but the results highlight the variability of ammonia emissions and suggest that emissions in warm climates may be higher than previously thought.
Cited articles
Aghedo, A. M., Bowman, K. W., Worden, H. M., Kulawik, S. S., Shindell, D. T., Lamarque, J. F., Faluvegi, G., Parrington, M., Jones, D. B. A., and Rast, S.: The vertical distribution of ozone instantaneous radiative forcing from satellite and chemistry climate models, J. Geophys. Res., 116, D01305, https://doi.org/10.1029/2010jd014243, 2011.
Albrecht, B.: Aerosols, cloud microphysics and fractional cloudiness, Science, 245, 1227–1230, 1989.
Arimoto, R.: Eolian dust and climate: Relationships to sources, tropospheric chemistry, transport and deposition, Earth Sci. Rev., 54, 29–42, 2001.
Ashley, W. S., Strader, S., Dziubla, D. C., and Haberlie, A.: Driving blind: Weather related vision hazards and fatal motor vehicle crashes, B. Am. Meteorol. Soc., 96, 755–778, https://doi.org/10.1175/BAMS-D-14-00026.1, 2015.
Avise, J., Chen, J., Lamb, B., Wiedinmyer, C., Guenther, A., Salathé, E., and Mass, C.: Attribution of projected changes in summertime US ozone and PM2.5 concentrations to global changes, Atmos. Chem. Phys., 9, 1111–1124, https://doi.org/10.5194/acp-9-1111-2009, 2009.
Aw, J. and Kleeman, M. J.: Evaluating the first-order effect of intraannual temperature variability on urban air pollution, J. Geophys. Res.-Atmos., 108, 4365, https://doi.org/10.1029/2002jd002688, 2003.
Bernard, S. M., Samet, J. M., Grambsch, A., Ebi, K. L., and Romieu, I.: The potential impact of climate variability and change on air pollution-related health effects in the United States, Environ. Health Perspect., 109, 199–209, 2001.
Bertram, T. H., Heckel, A., Richter, A., Burrows, J. P., and Cohen, R. C.: Satellite measurements of daily variations in soil NOx emissions, Geophys. Res. Lett., 32, L24812, https://doi.org/10.1029/2005gl024640, 2005.
Brasseur, G. P., Schultz, M., Granier, C., Saunois, M., Diehl, T., Botzet, M., Roeckner, E., and Walters, S.: Impact of climate change on the future chemical composition of the global troposphere, J. Climate, 19, 3932–3951, 2006.
Charlson, R. J., Schwartz, S. E., Hales, J. M., Cess, R. D., Coakley Jr., J. A., Hansen, J. E., and Hofmann, D. J.: Climate forcing by anthropogenic aerosols, Science, 255, 423–430, 1992.
Cheng, C. S., Campbell, M., Li, Q., Li, G., Auld, H., Day, N., Pengelfly, D., Gingrich, S., and Yap, D.: A synoptic climatological approach to assess climatic impact on air quality in south-central Canada. Part II: future estimates, Water Air Soil Pollut., 182, 117–130, 2007.
Chen, G. and Plumb, A.: Effective isentropic diffusivity of tropospheric transport, J. Atmos. Sci., 71, 3499–3520, 2014.
Chen, G., Lu, J., Burrows, D. A., and Leung, L. R.: Local finite-amplitude wave activity as an objective diagnostic of midlatitude extreme weather, Geophys. Res. Lett., 42, 10952–10960, https://doi.org/10.1002/2015GL066959, 2015.
Chen, Z., Xie, X., Cai, J., Chen, D., Gao, B., He, B., Cheng, N., and Xu, B.: Understanding meteorological influences on PM2.5 concentrations across China: a temporal and spatial perspective, Atmos. Chem. Phys., 18, 5343–5358, https://doi.org/10.5194/acp-18-5343-2018, 2018.
Cook, R.: Influential Observations in Linear Regression, J. Am. Stat. Assoc., 74, 169–174, https://doi.org/10.2307/2286747, 1979.
Coumou, D., Lehmann, J., and Beckmann, J.: The weakening summer circulation in the Northern Hemisphere mid-latitudes, Science, 348, 324–327, 2015.
Dawson, J. P., Adams, P. J., and Pandis, S. N.: Sensitivity of PM2.5 to climate in the Eastern US: a modeling case study, Atmos. Chem. Phys., 7, 4295–4309, https://doi.org/10.5194/acp-7-4295-2007, 2007.
Dawson, J. P., Bloomer, B. J., Winner, D. A., and Weaver, C. P.: Understanding the meteorological drivers of U.S. particulate matter concentrations in a changing climate, B. Am. Meteorol. Soc., 95, 521–532, https://doi.org/10.1175/BAMS-D-12-00181.1, 2014.
Dee, D., Uppala, S., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hersbach, H., Holm, E., Isaksen, L., Kallberg, P., Kohler, M., Matricardi, M., McNally, A., MongeSanz, B., Morccrette, J. J., Park, B. K., Peubey, C., Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitarts, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, 2011.
ECMWF: ECMWF Reanalysis – Interim (ERA-Interim), European Centre for Medium-Range Weather Forecasts [data set], https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-interim, last access: 1 September 2021.
Eyring, V., Lamarque, J. F., Hess, P., Arfeuille, F., Bowman, K., Chipperfield, M. P., Duncan, B., Fiore, A., Gettelman, A., Giorgetta, M. A., Granier, C., Hegglin, M., Kinnison, D., Kunze, M., Langematz, U., Luo, B., Martin, R., Matthes, K., Newman, P. A., Peter, T., Robock, A., Ryerson, T., Saiz-Lopez, A., Salawitch, R., Schultz, M., Shepherd, T. G., Shindell, D., Staehelin, J., Tegtmeier, S., Thomason, L., Tilmes, S., Vernier, J. P., Waugh, D. W., and Young, P. J.: Overview of IGAC/SPARC Chemistry-Climate Model Initiative (CCMI) community simulations in support of upcoming ozone and climate assessments, SPARC Newsletter, 40, 48–66, 2013.
Fang, Y., Fiore, A. M., Horowitz, L. W., Gnanadesikan, A., Held, I., Chen, G., Vecchi, G., and Levy, H. I.: The impacts of changing transport and precipitation on pollutant distributions in a future climate, J. Geophys Res., 116, D18303, https://doi.org/10.1029/2011JD015642, 2011.
Granier, C., Bessagnet, B., Bond, T., D’Angiola, A., Denier Van Der Gon, H., Frost, G. J., Heil, A., Kaiser, J. W., Kinne, S., Klimont, Z., Kloster, S., Lamarque, J. F., Liousse, C., Masui, T., Meleux, F., Mieville, A., Ohara, T., Raut, J. C., Riahi, K., Schultz, M. G., Smith, S. J., Thompson, A., Van Aardenne, J., Van Der Werf, G. R., and Van Vuuren, D. P.: Evolution of anthropogenic and biomass burning emissions of air pollutants at global and regional scales during the 1980–2010 period, Clim. Change, 109, 163–190, https://doi.org/10.1007/s10584-011-0154-1, 2011.
Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., and Wang, X.: The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions, Geosci. Model Dev., 5, 1471–1492, https://doi.org/10.5194/gmd-5-1471-2012, 2012.
Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron, C.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181–3210, https://doi.org/10.5194/acp-6-3181-2006, 2006.
Hack, J. J., Caron, J. M., Yeager, S. G., Oleson, K. W., Holland, M. M., Truesdale, J. E., and Rasch, P. J.: Simulation of the Global Hydrological Cycle in the CCSM Community Atmosphere Model Version 3 (CAM3): Mean Features, J. Climate, 19, 2199–2221, https://doi.org/10.1175/jcli3755.1, 2006.
Hand, J., Copeland, S., Day, D., Dillner, A., Indresand, H., Malm, W., McDade, C., Moore, C., Pitchford, M. L., Schichtel, B., and Watson, J.: IMPROVE (Interagency Monitoring of Protected Visual Environments): Spatial and seasonal patterns and temporal variability of haze and its constituents in the United States: Report V June 2011, Coop. Inst. for Res. in the Atmos., Fort Collins, Colo., http://vista.cira.colostate.edu/Improve/spatial-and-seasonal-patterns-and-temporal-variability-of-haze-and-its-constituents-in-the-united-states-report-v-june-2011 (last access: 1 September 2021), 2011 (data available at: http://views.cira.colostate.edu/fed/QueryWizard/, last access: 1 September 2021).
Hand, J., Schichtel, B., Pitchford, M., Malm, W., and Frank, N.: Seasonal composition of remote and urban fine particulate matter in the United States, J. Geophys. Res., 117, D05209, https://doi.org/10.1029/2011JD017122, 2012.
Hersbach, H. and Dee, D.: ERA5 reanalysis is in production, ECMWF Newsletter, 147, https://www.ecmwf.int/en/newsletter/147/news/era5-reanalysis-production (last access: 1 September 2021), 2016.
Holtslag, A. A. M. and Boville, B. A.: Local versus nonlocal boundary-layer diffusion in a global climate model, J. Climate, 6, 1825–1842, https://doi.org/10.1175/1520-0442(1993)006<1825:lvnbld>2.0.co;2, 1993.
Huang, C. S. and Nakamura, N.: Local finite-amplitude wave activity as a diagnostic of anomalous weather events, J. Atmos. Sci., 73, 211–229, 2016.
Hunke, E. C. and Lipscomb, W. H.: CICE: The Los Alamos Sea Ice Model, documentation and software, version 4.0, Tech. Rep., LA-CC-06-012, Los Alamos Natl. Lab., Los Alamos, N. M., 2008 (https://csdms.colorado.edu/w/images/CICE_documentation_and_software_user's_manual.pdf, last access: 1 September 2021), 2008.
Hurrell, J. W., Holland, M. M., Gent, P. R., Ghan, S., Kay, J. E., Kushner, P. J., Lamarque, J. F., Large, W. G., Lawrence, D., Lindsay, K., Lipscomb, W. H., Long, M. C., Mahowald, N., Marsh, D. R., Neale, R. B., Rasch, P., Vavrus, S., Vertenstein, M., Bader, D., Collins, W. D., Hack, J. J., Kiehl, J., and Marshall, S.: The Community Earth System Model: A framework for collaborative research, B. Am. Meteorol. Soc., 94, 1339–1360, 2013.
Jacob, D. J. and Winner, D. A.: Effect of climate change on air quality, Atmos. Environ., 43, 51–63, 2009.
Kappos, A. D., Bruckmann, P., Eikmann, T., Englert, N., Heinrich, U., Hoppe, P., Koch, E., Krause, G. H. M., Kreyling, W. G., Rauchfuss, K., Rombout, P., Schulz-Klemp, V., Thiel, W. R., and Wichmann, H. E.: Health effects of particles in ambient air, Int. J. Hyg. Environ. Health, 207, 399–407, 2004.
Kleeman, M. J.: A preliminary assessment of the sensitivity of air quality in California to global change, Clim. Change, 87, S273–S292, https://doi.org/10.1007/S10584-007-9351-3, 2008.
Kloster, S., Dentener, F., Feichter, J., Raes, F., Lohmann, U., Roeckner, E., and Fischer- Bruns, I.: A GCM study of future climate response to aerosol pollution reductions, Clim. Dynam., 34, 1177–1194, 2010.
Kloster, S., Mahowald, N. M., Randerson, J. T., and Lawrence, P. J.: The impacts of climate, land use, and demography on fires during the 21st century simulated by CLM-CN, Biogeosciences, 9, 509–525, https://doi.org/10.5194/bg-9-509-2012, 2012.
Koch, D., Park, J., and Del Genio, A.: Clouds and sulfate are anticorrelated: A new diagnostic for global sulfur models, J. Geophys. Res., 108, 4781, https://doi.org/10.1029/2003JD003621, 2003.
Koenker, R. and Bassett, G.: Regression Quantiles, Econometrica, 46, 33–50, 1978.
Krewski, D., Jerrett, M., Burnett, R. T., Ma, R., Hughes, E., Shi, Y., Turner, M. C., Pope, C. A., Thurston, G., Calle, E. E., and Thunt, M. J.: Extended follow-up and spatial analysis of the American
Cancer Society study linking particulate air pollution and mortality,
HEI Research Report, 140, 5–114, https://pubmed.ncbi.nlm.nih.gov/19627030 (last access: 1 Spetember 2021), 2009.
Kutner, M. H., Nachtsheim, C. J., Neter, J., and Li, W.: Applied linear statistical models, McGraw-Hill/Irwin, New York, NY, USA, ISBN: 9780073108742, 2004.
Lamarque, J. F. and Solomon, S.: Impact of changes in climate and halocarbons on recent lower stratosphere ozone and temperature trends, J. Climate, 23, 2599–2611, https://doi.org/10.1175/2010jcli3179.1, 2010.
Lamarque, J. F., Kyle, G., Meinshausen, M., Riahi, K., Smith, S., van Vuuren, D., Conley, A., and Vitt, F.: Global and regional evolution of short-lived radiatively-active gases and aerosols in the Representative Concentration Pathways, Clim. Change, 109, 191–212, https://doi.org/10.1007/s10584-011-0155-0, 2011a.
Lamarque, J. F., McConnell, J. R., Shindell, D. T., Orlando, J. J., and Tyndall, G. S.: Understanding the drivers for the 20th century change of hydrogen peroxide in Antarctic ice-cores, Geophys. Res. Lett., 38, L04810, https://doi.org/10.1029/2010gl045992, 2011b.
Lamarque, J.-F., Emmons, L. K., Hess, P. G., Kinnison, D. E., Tilmes, S., Vitt, F., Heald, C. L., Holland, E. A., Lauritzen, P. H., Neu, J., Orlando, J. J., Rasch, P. J., and Tyndall, G. K.: CAM-chem: description and evaluation of interactive atmospheric chemistry in the Community Earth System Model, Geosci. Model Dev., 5, 369–411, https://doi.org/10.5194/gmd-5-369-2012, 2012.
Leibensperger, E. M., Mickley, L. J., and Jacob, D. J.: Sensitivity of US air quality to mid-latitude cyclone frequency and implications of 1980–2006 climate change, Atmos. Chem. Phys., 8, 7075–7086, https://doi.org/10.5194/acp-8-7075-2008, 2008.
Liao, H., Chen, W. T., and Seinfeld, J. H.: Role of climate change in global predictions of future tropospheric ozone and aerosols, J. Geophys. Res., 111, D12304, https://doi.org/10.1029/2005JD006852, 2006.
Liu, J., Zheng, Y., Geng, G., Hong, C., Li, M., Li, X., Liu, F., Tong, D., Wu, R., Zheng, B., He, K., and Zhang, Q.: Decadal changes in anthropogenic source contribution of PM2.5 pollution and related health impacts in China, 1990–2015, Atmos. Chem. Phys., 20, 7783–7799, https://doi.org/10.5194/acp-20-7783-2020, 2020.
Liu, Y., Zhao, N., Vanos, J., and Cao, G.: Effects of synoptic weather on ground-level PM2.5 concentrations in the United States, Atmos. Environ., 148, 297–305, 2017.
Lu, J., Chen, G., Leung, L. R., Burrows, D. A., Yang, Q., Sakaguchi, K., and Hagos, S.: Toward the dynamical convergence on the Jetstream in aquaplanet AGCMs, J. Climate, 28, 6763–6782, 2015.
Mahowald, N., Ward, D., Kloster, S., Flanner, M. G., Heald, C. L., Heavens, N. G., Hess, P. G., Lamarque, J. F., and Chuang, P. Y.: Aerosol impacts on climate and biogeochemistry, Ann. Rev. Environ. Resour., 36, 45–74, 2011.
Martineau, P., Chen, G., and Burrows, D. A.: Wave events: climatology, trends, and relationship to Northern Hemisphere winter blocking and weather extremes, J. Climate, 30, 5675–5697, 2017.
Methven, J.: Wave activity for large-amplitude disturbances described by the primitive equations on the sphere, J. Atmos. Sci., 70, 1616–1630, 2013.
Michel, C. and Rivière, G.: The link between Rossby wave breakings and weather regime transitions, J. Atmos. Sci., 68, 1730–1748, 2011.
Mickley, L. J., Jacob, D. J., Field, B. D., and Rind, D.: Effects of future climate change on regional air pollution episodes in the United States, Geophys. Res. Lett., 31, L24103, https://doi.org/10.1029/2004gl021216, 2004.
Nakamura, H., Nakamura, M., and Anderson, J.: The role of high- and low-frequency dynamics in blocking formation, Mon. weather rev., 125, 2074–2093, 1997.
Nakamura, N. and Zhu, D.: Finite-amplitude wave activity and diffusive flux of potential vorticity in eddy-mean flow interaction, J. Atmos. Sci., 67, 2701–2716, 2010.
Nakamura, N. and Solomon, A.: Finite-amplitude wave activity and mean flow adjustments in the atmospheric general circulation. Part II: Analysis in the isentropic coordinate, J. Atmos. Sci., 68, 2783–2799, 2011.
Neale, R. B., Richter, J. H., and Jochum, M.: The impact of convection on ENSO: From a delayed oscillator to a series of events, J. Climate, 21, 5904–5924, 2008.
Neale, R. B., Richter, J. H., Conley, A. J., Park, S., Lauritzen, P. H., Gettelman, A., Williamson, D. L., Rasch, P. J., Vavrus, S. J., Taylor, M. A., Collins, W. D., Zhang, M., and Lin, S.-J.: Description of the NCAR Community Atmosphere Model (CAM 4.0), NCAR Tech. Note, TN–485, 212 pp., Natl. Cent. for Atmos. Res., Boulder, Colo, http://www.cesm.ucar.edu/models/cesm1.0/cam/docs/description/cam4_desc.pdf (last access: 1 September 2021), 2010.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Flanner, M. G., Kluzek, E., Lawrence, P. J., Levis, S., Swenson, S. C., Thornton, P. E., Dai, A., Decker, M., Dickinson, R., Feddema, J., Heald, C. L., Hoffman, F., Lamarque, J., Mahowald, N., Niu, G., Qian, T., Randerson, J., Running, S., Sakaguchi, K., Slater, A., Stockli, R., Wang, A., Yang, Z., Zeng, X., Zeng, X., and Decker, M.: Technical Description of version 4.0 of the Community Land Model (CLM), NCAR Technical Note NCAR/TN-478+STR, https://doi.org/10.5065/D6FB50WZ, 2010.
Painter, T. H., Barrett, A. P., Landry, C. C., Neff, J. C., Cassidy, M. P., Lawrence, C. R., McBride, K. E., and Farmer, G. L.: Impact of disturbed desert soils on duration of mountain snow cover, Geophys. Res. Lett., 34, L12502, https://doi.org/10.1029/2007GL030284, 2007.
Park, R. J., Jacob, D. J., and Logan, J. A.: Fire and biofuel contributions to annual mean aerosol mass concentrations in the United States, Atmos. Environ., 41, 7389–7400, 2007.
Pfahl, S. and Wernli H.: Quantifying the relevance of atmospheric blocking for co-located temperature extremes in the Northern Hemisphere on (sub-)daily time scales, Geophys. Res. Lett., 39, L12807, https://doi.org/10.1029/2012GL052261, 2012.
Phalitnonkiat, P., Hess, P. G. M., Grigoriu, M. D., Samorodnitsky, G., Sun, W., Beaudry, E., Tilmes, S., Deushi, M., Josse, B., Plummer, D., and Sudo, K.: Extremal dependence between temperature and ozone over the continental US, Atmos. Chem. Phys., 18, 11927–11948, https://doi.org/10.5194/acp-18-11927-2018, 2018.
Pinder, R. W., Pekney, N. J., Davidson, C. I., and Adams, P. J.: A process-based model of ammonia emissions from dairy cows: Improved temporal and spatial resolution, Atmos. Environ., 38, 1357–1365, 2004.
Porter, W. C., Heald, C. L., Cooley, D., and Russell, B.: Investigating the observed sensitivities of air-quality extremes to meteorological drivers via quantile regression, Atmos. Chem. Phys., 15, 10349–10366, https://doi.org/10.5194/acp-15-10349-2015, 2015.
Pye, H. O. T., Liao, H., Wu, S., Mickley, L. J., Jacob, D. J., Henze, D. K., and Seinfeld, J. H.: Effect of changes in climate and emissions on future sulfate-nitrate-ammonium aerosol levels in the United States, J. Geophys. Res., 114, D01205, https://doi.org/10.1029/2008JD010701, 2009.
Racherla, P. N. and Adams, P. J.: Sensitivity of global tropospheric ozone and fine particulate matter concentrations to climate change, J. Geophys. Res., 111, D24103, https://doi.org/10.1029/2005JD006939, 2006.
Rasch, P. and Kristjánsson, J.: A comparison of the CCM3 model climate using diagnosed and predicted condensate parameterizations, J. Climate, 11, 1587–1614, 1998.
Richter, J. H. and Rasch, P. J.: Effects of convective momentum transport on the atmospheric circulation in the Community Atmosphere Model, version 3, J. Climate, 21, 1487–1499, 2008.
Riddick, S., Ward, D., Hess, P., Mahowald, N., Massad, R., and Holland, E.: Estimate of changes in agricultural terrestrial nitrogen pathways and ammonia emissions from 1850 to present in the Community Earth System Model, Biogeosciences, 13, 3397–3426, https://doi.org/10.5194/bg-13-3397-2016, 2016.
Rienecker, M. M., Suarez, M. J., Gelaro, R., Todling, R., Bacmeister, J., Liu, E., Bosilovich, M. G., Schubert, S. D., Takacs, L., Kim, G. K., Bloom, S., Chen, J., Collins, D., Conaty, A., da Silva, A., Gu, W., Joiner, J., Koster, R. D., Lucchesi, R., Molod, A., Owens, T., Pawson, S., Pegion, P., Redder, C. R., Reichle, R., Robertson, F. R., Ruddick, A. G., Sienkiewicz, M., and Woollen, J.: MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications, J. Climate, 24, 3624–3648, https://doi.org/10.1175/JCLI-D-11-00015.1, 2011.
Rosenfeld, D., Lohmann, U., Raga, G. B., O’Dowd, C. D., Kulmala, M., Fuzzi, S., Reissel, A., and Andreae, M. O.: Flood or drought: How do aerosols affect precipitation? Science, 321, 1309–1313, 2008.
Ryoo, J. M., Kaspi, Y., Waugh, D. W., Kiladis, G. N., Waliser, D. E., Fetzer, E. J., and Kim, J.: Impact of Rossby wave breaking on U. S. West Coast winter precipitation during ENSO events, J. Climate, 26, 6360–6382, https://doi.org/10.1175/JCLI-D-12-00297.1, 2013.
Shen, L. and Mickley, L. J.: Seasonal prediction of US summertime ozone using statistical analysis of large scale climate patterns, P. Natl. Acad. Sci. USA, 114, 2491–2496, 2017.
Smith, R., Jones, P., Briegleb, B., Bryan, F., Danabasoglu, G., Dennis, J., Dukowicz, J., Eden, C., Fox-Kemper, B., Gent, P., Hecht, M., Jayne, S., Jochum, M., Large, W., Lindsay, K., Maltrud, M., Norton, N., Peacock, S., Vertenstein, M., and Yeager, S.: The Parallel Ocean Program (POP) reference manual, Ocean component of the Community Climate System Model (CCSM), LANL Tech. Report, LAUR-10-01853, 141 pp., https://www.cesm.ucar.edu/models/cesm2/ocean/doc/sci/POPRefManual.pdf (last access: 1 September 2021), 2010.
Spracklen, D. V., Mickley, L. J., Logan, J. A., Hudman, R. C., Yevich, R., Flannigan, M. D., and Westerling, A. L.: Impacts of climate change from 2000 to 2050 on wildfire activity and carbonaceous aerosol concentrations in the western United States, J. Geophys. Res.-Atmos., 114, D20301, https://doi.org/10.1029/2008jd010966, 2009.
Sun, W., Hess, P., and Tian, B.: The response of the equatorial tropospheric ozone to the Madden–Julian Oscillation in TES satellite observations and CAM-chem model simulation, Atmos. Chem. Phys., 14, 11775–11790, https://doi.org/10.5194/acp-14-11775-2014, 2014.
Sun, W., Hess, P., and Liu, C.: The impact of meteorological persistence on the distribution and extremes of ozone, Geophys. Res. Lett., 44, 1545–1553, 2017.
Sun, W., Hess, P., Chen, G., and Tilmes, S.: How waviness in the circulation changes surface ozone: a viewpoint using local finite-amplitude wave activity, Atmos. Chem. Phys., 19, 12917–12933, https://doi.org/10.5194/acp-19-12917-2019, 2019.
Tagaris, E., Manomaiphiboon, K., Liao, K. J., Leung, L. R., Woo, J. H., He, S., Amar, P., and Russell, A. G.: Impacts of global climate change and emissions on regional ozone and fine particulate matter concentrations over the United States, J. Geophys. Res., 112, D14312, https://doi.org/10.1029/2006jd008262, 2007.
Tai, A. P. K., Mickley, L. J., and Jacob, D. J.: Correlations between fine particulate matter (PM2.5) and meteorological variables in the United States: Implications for the sensitivity of PM2.5 to climate change, Atmos. Environ., 44, 3976–3984, 2010.
Tai, A. P. K., Mickley, L. J., Jacob, D. J., Leibensperger, E. M., Zhang, L., Fisher, J. A., and Pye, H. O. T.: Meteorological modes of variability for fine particulate matter (PM2.5) air quality in the United States: implications for PM2.5 sensitivity to climate change, Atmos. Chem. Phys., 12, 3131–3145, https://doi.org/10.5194/acp-12-3131-2012, 2012.
Takaya, K. and Nakamura, H.: A formulation of a phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow, J. Atmos. Sci., 58, 608–627, 2001.
Thishan Dharshana, K. G., Kravtsov, S., and Kahl, J. D. W.: Relationship between synoptic weather disturbances and particulate matter air pollution over the United States, J. Geophys. Res.-Atmos., 115, D24219, https://doi.org/10.1029/2010jd014852, 2010.
Tilmes, S., Lamarque, J.-F., Emmons, L. K., Kinnison, D. E., Marsh, D., Garcia, R. R., Smith, A. K., Neely, R. R., Conley, A., Vitt, F., Val Martin, M., Tanimoto, H., Simpson, I., Blake, D. R., and Blake, N.: Representation of the Community Earth System Model (CESM1) CAM4-chem within the Chemistry-Climate Model Initiative (CCMI), Geosci. Model Dev., 9, 1853–1890, https://doi.org/10.5194/gmd-9-1853-2016, 2016 (data available at: http://data.ceda.ac.uk/badc/wcrp-ccmi/data/CCMI-1/output/, last access: 1 September 2021).
Titchner, H. A. and Rayner, N. A.: The Met Office Hadley Centre sea ice and sea surface temperature data set, version 2:1. sea ice concentrations, J. Geophys. Res.-Atmos., 119, 2864–2889, https://doi.org/10.1002/2013JD020316, 2014.
VanCuren, R. and Gustin, M. S.: Identification of sources contributing to PM2.5 and ozone at elevated sites in the western U.S. by receptor analysis: Lassen Volcanic National Park, California, and at Great Basin National Park, Nevada, Sci. Total Environ., 530, 505–518, https://doi.org/10.1016/j.scitotenv.2015.03.091, 2015.
Vavrus, S. J., Wang, F., Martin, J. E., Francis, J. A., Peings, Y., and Cattiaux, J.: Changes in North American atmospheric circulation and extreme weather: Influence of Arctic amplification and Northern Hemisphere snow cover, J. Climate, 30, 4317–4333, 2017.
Wang, X. and Zhang, R.: Effects of atmospheric circulations on the interannual variation in PM2.5 concentrations over the Beijing–Tianjin–Hebei region in 2013–2018, Atmos. Chem. Phys., 20, 7667–7682, https://doi.org/10.5194/acp-20-7667-2020, 2020.
Wang, Y., Le, T., Chen, G., Yung, Y. L., and Jiang, J. H.: Reduced European aerosol emissions suppress winter extremes over northern Eurasia, Nat. Clim. Chang., 10, 225–230, https://doi.org/10.1038/s41558-020-0693-4, 2020.
Wang, Z., Chen, G., Gu, Y., Zhao, B., and Liou, K.: Large-scale meteorological control on the spatial pattern of wintertime PM2.5 pollution over china, Atmos. Sci. Lett., 20, e938, https://doi.org/10.1002/asl.938, 2019.
Wise, E. K. and Comrie, A. C.: Meteorologically adjusted urban air quality trends in the Southwestern United States, Atmos. Environ., 39, 2969–2980, https://doi.org/10.1016/j.atmosenv.2005.01.024, 2005.
Woolings, T. J., Hoskins, B. J., Blackburn, M., and Berrisford, P.: A new Rossby wave breaking interpretation of the North Atlantic Oscillation, J. Atmos. Sci., 65, 609–626, https://doi.org/10.1175/2007JAS2347.1, 2008.
Wu, S., Mickley, L. J., Leibensperger, E. M., Jacob, D. J., Rind, D., and Streets, D. G.: Effects of 2000–2050 global change on ozone air quality in the United States, J. Geophys. Res., 113, D06302, https://doi.org/10.1029/2007JD008917, 2008.
Zhang, G. J. and McFarlaneb, N. A.: Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model, Atmos. Ocean, 33, 407–446, 1995.
Zhang, M., Lin, W., Bretherton, C. S., Hack, J. J., and Rasch P. J.: A modified formulation of fractional stratiform condensation rate in the NCAR Community Atmospheric Model (CAM2), J. Geophys. Res., 108, 4035, https://doi.org/10.1029/2002JD002523, 2003.
Short summary
PM2.5 is positively related to anticyclonic wave activity (AWA) changes close to the observing sites. Changes between current and future climates in AWA can explain up to 75 % of PM2.5 variability at some stations using a linear regression model. Our analysis indicates that higher PM2.5 concentrations occur when a positive AWA anomaly is prominent, which could be critical for understanding how pollutants respond to changing atmospheric circulation and for developing robust pollution projections.
PM2.5 is positively related to anticyclonic wave activity (AWA) changes close to the observing...
Altmetrics
Final-revised paper
Preprint