Articles | Volume 24, issue 11
https://doi.org/10.5194/acp-24-6583-2024
© Author(s) 2024. 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-24-6583-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Technical note: Influence of different averaging metrics and temporal resolutions on the aerosol pH calculated by thermodynamic modeling
Haoqi Wang
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, 300350 Tianjin, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, 300350 Tianjin, China
Xiao Tian
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, 300350 Tianjin, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, 300350 Tianjin, China
Wanting Zhao
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, 300350 Tianjin, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, 300350 Tianjin, China
Jiacheng Li
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, 300350 Tianjin, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, 300350 Tianjin, China
Haoyu Yu
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, 300350 Tianjin, China
Yinchang Feng
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, 300350 Tianjin, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, 300350 Tianjin, China
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, 300350 Tianjin, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, 300350 Tianjin, China
Related authors
No articles found.
Jinwen Zhang, Yongjian Liang, Chenglei Pei, Bo Huang, Yingyan Huang, Xiufeng Lian, Shaojie Song, Chunlei Cheng, Cheng Wu, Zhen Zhou, Junjie Li, and Mei Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-3215, https://doi.org/10.5194/egusphere-2025-3215, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Inadequate characterization of carbon dioxide (CO2) dynamics limits understanding of coastal megacity carbon cycles. Using a novel framework integrating high-precision observations, this study reveals nonlinear sea–land breeze effects, quantifies urban vegetation’s role in CO2 budgets, and tracks policy-driven combustion efficiency via declining ΔCO/ΔCO2 ratios, offering new insights into coastal CO2 cycling.
Baoshuang Liu, Yao Gu, Yutong Wu, Qili Dai, Shaojie Song, Yinchang Feng, and Philip K. Hopke
Atmos. Chem. Phys., 24, 12861–12879, https://doi.org/10.5194/acp-24-12861-2024, https://doi.org/10.5194/acp-24-12861-2024, 2024
Short summary
Short summary
Reactive loss of volatile organic compounds (VOCs) is a long-term issue yet to be resolved in VOC source analyses. We assess common methods of, and existing issues in, reducing losses, impacts of losses, and sources in current source analyses. We offer a potential supporting role for solving issues of VOC conversion. Source analyses of consumed VOCs that reacted to produce ozone and secondary organic aerosols can play an important role in the effective control of secondary pollution in air.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
Short summary
Short summary
This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
Baoshuang Liu, Yanyang Wang, He Meng, Qili Dai, Liuli Diao, Jianhui Wu, Laiyuan Shi, Jing Wang, Yufen Zhang, and Yinchang Feng
Atmos. Chem. Phys., 22, 8597–8615, https://doi.org/10.5194/acp-22-8597-2022, https://doi.org/10.5194/acp-22-8597-2022, 2022
Short summary
Short summary
Understanding effectiveness of air pollution regulatory measures is critical for control policy. Machine learning and dispersion-normalized approaches were applied to decouple meteorologically deduced variations in Qingdao, China. Most pollutant concentrations decreased substantially after the Clean Air Action Plan. The largest emission reduction was from coal combustion and steel-related smelting. Qingdao is at risk of increased emissions from increased vehicular population and ozone pollution.
Xinyao Feng, Yingze Tian, Qianqian Xue, Danlin Song, Fengxia Huang, and Yinchang Feng
Atmos. Chem. Phys., 21, 16219–16235, https://doi.org/10.5194/acp-21-16219-2021, https://doi.org/10.5194/acp-21-16219-2021, 2021
Short summary
Short summary
This study focused on PM2.5 compositions and sources and explored their spatiotemporal and policy-related variations based on observation at 19 sites during wintertime of 2015–2019 in a fast-developing megacity. We found that PM2.5 compositions for the outermost zone in 2019 were similar to those for the core zone 2 or 3 years ago. Percentage contributions of coal and biomass combustion dramatically declined in the core zone, while the traffic source showed an increasing trend.
Athanasios Nenes, Spyros N. Pandis, Maria Kanakidou, Armistead G. Russell, Shaojie Song, Petros Vasilakos, and Rodney J. Weber
Atmos. Chem. Phys., 21, 6023–6033, https://doi.org/10.5194/acp-21-6023-2021, https://doi.org/10.5194/acp-21-6023-2021, 2021
Short summary
Short summary
Ecosystems and air quality are affected by the dry deposition of inorganic reactive nitrogen (Nr, the sum of ammonium and nitrate). Its large variability is driven by the large difference in deposition velocity of N when in the gas or particle phase. Here we show that aerosol liquid water and acidity, by affecting gas–particle partitioning, modulate the dry deposition velocity of NH3, HNO3, and Nr worldwide. These effects explain the rapid accumulation of nitrate aerosol during haze events.
Peter Sherman, Meng Gao, Shaojie Song, Alex T. Archibald, Nathan Luke Abraham, Jean-François Lamarque, Drew Shindell, Gregory Faluvegi, and Michael B. McElroy
Atmos. Chem. Phys., 21, 3593–3605, https://doi.org/10.5194/acp-21-3593-2021, https://doi.org/10.5194/acp-21-3593-2021, 2021
Short summary
Short summary
The aims here are to assess the role of aerosols in India's monsoon precipitation and to determine the relative contributions from Chinese and Indian emissions using CMIP6 models. We find that increased sulfur emissions reduce precipitation, which is primarily dynamically driven due to spatial shifts in convection over the region. A significant increase in precipitation (up to ~ 20 %) is found only when both Indian and Chinese sulfate emissions are regulated.
Shaojie Song, Tao Ma, Yuzhong Zhang, Lu Shen, Pengfei Liu, Ke Li, Shixian Zhai, Haotian Zheng, Meng Gao, Jonathan M. Moch, Fengkui Duan, Kebin He, and Michael B. McElroy
Atmos. Chem. Phys., 21, 457–481, https://doi.org/10.5194/acp-21-457-2021, https://doi.org/10.5194/acp-21-457-2021, 2021
Short summary
Short summary
We simulate the atmospheric chemical processes of an important sulfur-containing organic aerosol species, which is produced by the reaction between sulfur dioxide and formaldehyde. We can predict its distribution on a global scale. We find it is particularly rich in East Asia. This aerosol species is more abundant in the colder season partly because of weaker sunlight.
Jingsha Xu, Shaojie Song, Roy M. Harrison, Congbo Song, Lianfang Wei, Qiang Zhang, Yele Sun, Lu Lei, Chao Zhang, Xiaohong Yao, Dihui Chen, Weijun Li, Miaomiao Wu, Hezhong Tian, Lining Luo, Shengrui Tong, Weiran Li, Junling Wang, Guoliang Shi, Yanqi Huangfu, Yingze Tian, Baozhu Ge, Shaoli Su, Chao Peng, Yang Chen, Fumo Yang, Aleksandra Mihajlidi-Zelić, Dragana Đorđević, Stefan J. Swift, Imogen Andrews, Jacqueline F. Hamilton, Ye Sun, Agung Kramawijaya, Jinxiu Han, Supattarachai Saksakulkrai, Clarissa Baldo, Siqi Hou, Feixue Zheng, Kaspar R. Daellenbach, Chao Yan, Yongchun Liu, Markku Kulmala, Pingqing Fu, and Zongbo Shi
Atmos. Meas. Tech., 13, 6325–6341, https://doi.org/10.5194/amt-13-6325-2020, https://doi.org/10.5194/amt-13-6325-2020, 2020
Short summary
Short summary
An interlaboratory comparison was conducted for the first time to examine differences in water-soluble inorganic ions (WSIIs) measured by 10 labs using ion chromatography (IC) and by two online aerosol chemical speciation monitor (ACSM) methods. Major ions including SO42−, NO3− and NH4+ agreed well in 10 IC labs and correlated well with ACSM data. WSII interlab variability strongly affected aerosol acidity results based on ion balance, but aerosol pH computed by ISORROPIA II was very similar.
Cited articles
Ault, A. P.: Aerosol Acidity: Novel Measurements and Implications for Atmospheric Chemistry, Acc. Chem. Res, 53, 1703–1714, https://doi.org/10.1021/acs.accounts.0c00303, 2020.
Chen, Y., Cheng, Y., Ma, N., Wolke, R., Nordmann, S., Schüttauf, S., Ran, L., Wehner, B., Birmili, W., van der Gon, H. A. C. D., Mu, Q., Barthel, S., Spindler, G., Stieger, B., Müller, K., Zheng, G.-J., Pöschl, U., Su, H., and Wiedensohler, A.: Sea salt emission, transport and influence on size-segregated nitrate simulation: a case study in northwestern Europe by WRF-Chem, Atmos. Chem. Phys., 16, 12081–12097, https://doi.org/10.5194/acp-16-12081-2016, 2016.
Chen, Y., Wolke, R., Ran, L., Birmili, W., Spindler, G., Schröder, W., Su, H., Cheng, Y., Tegen, I., and Wiedensohler, A.: A parameterization of the heterogeneous hydrolysis of N2O5 for mass-based aerosol models: improvement of particulate nitrate prediction, Atmos. Chem. Phys., 18, 673–689, https://doi.org/10.5194/acp-18-673-2018, 2018.
Cheng, Y., Zheng, G., Wei, C., Mu, Q., Zheng, B., Wang, Z., Gao, M., Zhang, Q., He, K., Carmichael, G., Pöschl, U., and Su, H.: Reactive nitrogen chemistry in aerosol water as a source of sulfate during haze events in China, Sci. Adv., 2, e1601530, https://doi.org/10.1126/sciadv.1601530, 2016.
Cui, X., Tang, M., Wang, M., and Zhu, T.: Water as a probe for pH measurement in individual particles using micro-Raman spectroscopy, Anal. Chim. Acta, 1186, 339089, https://doi.org/10.1016/j.aca.2021.339089, 2021.
Ding, J., Zhao, P., Su, J., Dong, Q., Du, X., and Zhang, Y.: Aerosol pH and its driving factors in Beijing, Atmos. Chem. Phys., 19, 7939–7954, https://doi.org/10.5194/acp-19-7939-2019, 2019.
Fountoukis, C. and Nenes, A.: ISORROPIA II: a computationally efficient thermodynamic equilibrium model for K+–Ca2+–Mg2+– –Na+– – –Cl−–H2O aerosols, Atmos. Chem. Phys., 7, 4639–4659, https://doi.org/10.5194/acp-7-4639-2007, 2007.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Geng, G., Zhang, Q., Tong, D., Li, M., Zheng, Y., Wang, S., and He, K.: Chemical composition of ambient PM2.5 over China and relationship to precursor emissions during 2005–2012, Atmos. Chem. Phys., 17, 9187–9203, https://doi.org/10.5194/acp-17-9187-2017, 2017.
Guo, H., Sullivan, A. P., Campuzano-Jost, P., Schroder, J. C., Lopez-Hilfiker, F. D., Dibb, J. E., Jimenez, J. L., Thornton, J. A., Brown, S. S., Nenes, A., and Weber, R. J.: Fine particle pH and the partitioning of nitric acid during winter in the northeastern United States, J. Geophys. Res.-Atmos, 121, 10355–10376, https://doi.org/10.1002/2016jd025311, 2016.
Guo, H., Weber, R. J., and Nenes, A.: High levels of ammonia do not raise fine particle pH sufficiently to yield nitrogen oxide-dominated sulfate production, Sci. Rep.-UK, 7, 12109, https://doi.org/10.1038/s41598-017-11704-0, 2017.
Guo, H., Nenes, A., and Weber, R. J.: The underappreciated role of nonvolatile cations in aerosol ammonium-sulfate molar ratios, Atmos. Chem. Phys., 18, 17307–17323, https://doi.org/10.5194/acp-18-17307-2018, 2018.
Haskins, J. D., Jaeglé, L., Shah, V., Lee, B. H., Lopez-Hilfiker, F. D., Campuzano-Jost, P., Schroder, J. C., Day, D. A., Guo, H., Sullivan, A. P., Weber, R., Dibb, J., Campos, T., Jimenez, J. L., Brown, S. S., and Thornton, J. A.: Wintertime Gas-Particle Partitioning and Speciation of Inorganic Chlorine in the Lower Troposphere Over the Northeast United States and Coastal Ocean, J. Geophys. Res.-Atmos, 123, 12897–12916, https://doi.org/10.1029/2018JD028786, 2018.
Hennigan, C. J., Izumi, J., Sullivan, A. P., Weber, R. J., and Nenes, A.: A critical evaluation of proxy methods used to estimate the acidity of atmospheric particles, Atmos. Chem. Phys., 15, 2775–2790, https://doi.org/10.5194/acp-15-2775-2015, 2015.
Jia, S., Wang, X., Zhang, Q., Sarkar, S., Wu, L., Huang, M., Zhang, J., and Yang, L.: Technical note: Comparison and interconversion of pH based on different standard states for aerosol acidity characterization, Atmos. Chem. Phys., 18, 11125–11133, https://doi.org/10.5194/acp-18-11125-2018, 2018.
Li, M., Kan, Y., Su, H., Pöschl, U., Parekh, S. H., Bonn, M., and Cheng, Y.: Spatial homogeneity of pH in aerosol microdroplets, Chem, 9, 1036–1046, https://doi.org/10.1016/j.chempr.2023.02.019, 2023.
Li, W. and Kuwata, M.: Detecting pH of Sub-Micrometer Aerosol Particles Using Fluorescent Probes, Environ. Sci. Technol., 57, 8701–8707, https://doi.org/10.1021/acs.est.3c01517, 2023.
Lippmann, M.: Toxicological and epidemiological studies of cardiovascular effects of ambient air fine particulate matter (PM2.5) and its chemical components: Coherence and public health implications, Crit. Rev. Toxicol., 44, 299–347, https://doi.org/10.3109/10408444.2013.861796, 2014.
Liu, S., Geng, G., Xiao, Q., Zheng, Y., Liu, X., Cheng, J., and Zhang, Q.: Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000, Environ. Sci. Technol., 56, 16517–16527, https://doi.org/10.1021/acs.est.2c06510, 2022.
Liu, Y. C., Wu, Z. J., Qiu, Y. T., Tian, P., Liu, Q., Chen, Y., Song, M., and Hu, M.: Enhanced Nitrate Fraction: Enabling Urban Aerosol Particles to Remain in a Liquid State at Reduced Relative Humidity, Geophys. Res. Lett., 50, e2023GL105505, https://doi.org/10.1029/2023GL105505, 2023.
Meskhidze, N., Chameides, W. L., Nenes, A., and Chen, G.: Iron mobilization in mineral dust: Can anthropogenic SO2 emissions affect ocean productivity?, Geophys. Res. Lett., 30, 2085, https://doi.org/10.1029/2003GL018035, 2003.
Möller, D. and Zierath, R.: On the composition of precipitation water and its acidity, Tellus B, 38B, 44–50, https://doi.org/10.1111/j.1600-0889.1986.tb00086.x, 1986.
Nah, T., Guo, H., Sullivan, A. P., Chen, Y., Tanner, D. J., Nenes, A., Russell, A., Ng, N. L., Huey, L. G., and Weber, R. J.: Characterization of aerosol composition, aerosol acidity, and organic acid partitioning at an agriculturally intensive rural southeastern US site, Atmos. Chem. Phys., 18, 11471–11491, https://doi.org/10.5194/acp-18-11471-2018, 2018.
Peng, X., Vasilakos, P., Nenes, A., Shi, G., Qian, Y., Shi, X., Xiao, Z., Chen, K., Feng, Y., and Russell, A. G.: Detailed Analysis of Estimated pH, Activity Coefficients, and Ion Concentrations between the Three Aerosol Thermodynamic Models, Environ. Sci. Technol., 53, 8903–8913, https://doi.org/10.1021/acs.est.9b00181, 2019.
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.-Atmos, 114, D01205, https://doi.org/10.1029/2008JD010701, 2009.
Pye, H. O. T., Pinder, R. W., Piletic, I. R., Xie, Y., Capps, S. L., Lin, Y., Surratt, J. D., Zhang, Z., Gold, A., Luecken, D. J., Hutzell, W. T., Jaoui, M., Offenberg, J. H., Kleindienst, T. E., Lewandowski, M., and Edney, E. O.: Epoxide Pathways Improve Model Predictions of Isoprene Markers and Reveal Key Role of Acidity in Aerosol Formation, Environ. Sci. Technol., 47, 11056–11064, https://doi.org/10.1021/es402106h, 2013.
Pye, H. O. T., Nenes, A., Alexander, B., Ault, A. P., Barth, M. C., Clegg, S. L., Collett Jr., J. L., Fahey, K. M., Hennigan, C. J., Herrmann, H., Kanakidou, M., Kelly, J. T., Ku, I.-T., McNeill, V. F., Riemer, N., Schaefer, T., Shi, G., Tilgner, A., Walker, J. T., Wang, T., Weber, R., Xing, J., Zaveri, R. A., and Zuend, A.: The acidity of atmospheric particles and clouds, Atmos. Chem. Phys., 20, 4809–4888, https://doi.org/10.5194/acp-20-4809-2020, 2020.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric chemistry and physics: from air pollution to climate change, John Wiley & Sons, Inc., Hoboken, New Jersey, USA, ISBN 978-1118947401, 2016.
Shah, V., Jacob, D. J., Moch, J. M., Wang, X., and Zhai, S.: Global modeling of cloud water acidity, precipitation acidity, and acid inputs to ecosystems, Atmos. Chem. Phys., 20, 12223–12245, https://doi.org/10.5194/acp-20-12223-2020, 2020.
Song, S.: shaojiesong/GC14.1.1_output_for_pH: First release (publish), Zenodo [data set], https://doi.org/10.5281/zenodo.11480367, 2024.
Song, S., Gao, M., Xu, W., Shao, J., Shi, G., Wang, S., Wang, Y., Sun, Y., and McElroy, M. B.: Fine-particle pH for Beijing winter haze as inferred from different thermodynamic equilibrium models, Atmos. Chem. Phys., 18, 7423–7438, https://doi.org/10.5194/acp-18-7423-2018, 2018.
Straub, D. J., Hutchings, J. W., and Herckes, P.: Measurements of fog composition at a rural site, Atmos. Environ., 47, 195–205, https://doi.org/10.1016/j.atmosenv.2011.11.014, 2012.
Sun, M., Wang, Y., Wang, T., Fan, S., Wang, W., Li, P., Guo, J., and Li, Y.: Cloud and the corresponding precipitation chemistry in south China: Water-soluble components and pollution transport, J. Geophys. Res.-Atmos, 115, D22303, https://doi.org/10.1029/2010JD014315, 2010.
The International GEOS-Chem User Community: geoschem/geoschem: GEOS-Chem 14.1.1 (Version 14.1.1), Zenodo [code], https://doi.org/10.5281/zenodo.7696632, 2023.
Tilgner, A., Schaefer, T., Alexander, B., Barth, M., Collett Jr., J. L., Fahey, K. M., Nenes, A., Pye, H. O. T., Herrmann, H., and McNeill, V. F.: Acidity and the multiphase chemistry of atmospheric aqueous particles and clouds, Atmos. Chem. Phys., 21, 13483–13536, https://doi.org/10.5194/acp-21-13483-2021, 2021.
Vasilakos, P., Russell, A., Weber, R., and Nenes, A.: Understanding nitrate formation in a world with less sulfate, Atmos. Chem. Phys., 18, 12765–12775, https://doi.org/10.5194/acp-18-12765-2018, 2018.
Wang, S., Su, H., Chen, C., Tao, W., Streets, D. G., Lu, Z., Zheng, B., Carmichael, G. R., Lelieveld, J., Pöschl, U., and Cheng, Y.: Natural gas shortages during the “coal-to-gas” transition in China have caused a large redistribution of air pollution in winter 2017, P. Natl. Acad. Sci. USA, 117, 31018–31025, https://doi.org/10.1073/pnas.2007513117, 2020.
Wang, S. W., Zhang, Q., Streets, D. G., He, K. B., Martin, R. V., Lamsal, L. N., Chen, D., Lei, Y., and Lu, Z.: Growth in NOx emissions from power plants in China: bottom-up estimates and satellite observations, Atmos. Chem. Phys., 12, 4429–4447, https://doi.org/10.5194/acp-12-4429-2012, 2012.
Wang, X., Jacob, D. J., Eastham, S. D., Sulprizio, M. P., Zhu, L., Chen, Q., Alexander, B., Sherwen, T., Evans, M. J., Lee, B. H., Haskins, J. D., Lopez-Hilfiker, F. D., Thornton, J. A., Huey, G. L., and Liao, H.: The role of chlorine in global tropospheric chemistry, Atmos. Chem. Phys., 19, 3981–4003, https://doi.org/10.5194/acp-19-3981-2019, 2019.
Wang, Y., Chen, Y., Wu, Z., Shang, D., Bian, Y., Du, Z., Schmitt, S. H., Su, R., Gkatzelis, G. I., Schlag, P., Hohaus, T., Voliotis, A., Lu, K., Zeng, L., Zhao, C., Alfarra, M. R., McFiggans, G., Wiedensohler, A., Kiendler-Scharr, A., Zhang, Y., and Hu, M.: Mutual promotion between aerosol particle liquid water and particulate nitrate enhancement leads to severe nitrate-dominated particulate matter pollution and low visibility, Atmos. Chem. Phys., 20, 2161–2175, https://doi.org/10.5194/acp-20-2161-2020, 2020.
Weber, R. J., Guo, H., Russell, A. G., and Nenes, A.: High aerosol acidity despite declining atmospheric sulfate concentrations over the past 15 years, Nat. Geosci., 9, 282–285, https://doi.org/10.1038/ngeo2665, 2016.
Wu, D., Zheng, H., Li, Q., Wang, S., Zhao, B., Jin, L., Lyu, R., Li, S., Liu, Y., Chen, X., Zhang, F., Wu, Q., Liu, T., Jiang, J., Wang, L., Li, X., Chen, J., and Hao, J.: Achieving health-oriented air pollution control requires integrating unequal toxicities of industrial particles, Nat. Commun., 14, 6491, https://doi.org/10.1038/s41467-023-42089-6, 2023.
Yuan, A. E. and Shou, W.: Data-driven causal analysis of observational biological time series, eLife, 11, e72518, https://doi.org/10.7554/eLife.72518, 2022.
Yuan, J., Stein, M. L., and Kopp, R. E.: The Evolving Distribution of Relative Humidity Conditional Upon Daily Maximum Temperature in a Warming Climate, J. Geophys. Res.-Atmos, 125, e2019JD032100, https://doi.org/10.1029/2019JD032100, 2020.
Zhang, B., Shen, H., Liu, P., Guo, H., Hu, Y., Chen, Y., Xie, S., Xi, Z., Skipper, T. N., and Russell, A. G.: Significant contrasts in aerosol acidity between China and the United States, Atmos. Chem. Phys., 21, 8341–8356, https://doi.org/10.5194/acp-21-8341-2021, 2021.
Zhang, T., Shen, Z. X., Su, H., Liu, S. X., Zhou, J. M., Zhao, Z. Z., Wang, Q. Y., Prévôt, A. S. H., and Cao, J. J.: Effects of Aerosol Water Content on the formation of secondary inorganic aerosol during a Winter Heavy PM2.5 Pollution Episode in Xi'an, China, Atmos. Environ., 252, 118304, https://doi.org/10.1016/j.atmosenv.2021.118304, 2021.
Zheng, G., Su, H., Wang, S., Andreae, M., Pöschl, U., and Cheng, Y.: Multiphase buffer theory explains contrasts in atmospheric aerosol acidity, Science, 369, 1374–1377, https://doi.org/10.1126/science.aba3719, 2020.
Zheng, G. J., Su, H., and Cheng, Y. F.: Revisiting the Key Driving Processes of the Decadal Trend of Aerosol Acidity in the U.S., ACS Environ. Au, 2, 346–353, https://doi.org/10.1021/acsenvironau.1c00055, 2022.
Short summary
pH is a key property of ambient aerosols, which affect many atmospheric processes. As aerosol pH is a non-conservative parameter, diverse averaging metrics and temporal resolutions may influence the pH values calculated by thermodynamic models. This technical note seeks to quantitatively evaluate the average pH using varied metrics and resolutions. The ultimate goal is to establish standardized reporting practices in future research endeavors.
pH is a key property of ambient aerosols, which affect many atmospheric processes. As aerosol pH...
Altmetrics
Final-revised paper
Preprint