45 citations as recorded by crossref.

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2. Fine Particulate Air Pollution from Electricity Generation in the US: Health Impacts by Race, Income, and Geography M. Thind et al. https://doi.org/10.1021/acs.est.9b02527
3. ISORROPIA‐MCX: Enabling Sensitivity Analysis With Multicomplex Variables in the Aerosol Thermodynamic Model, ISORROPIA B. Berman et al. https://doi.org/10.1029/2022EA002729
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5. Diminishing Returns or Compounding Benefits of Air Pollution Control? The Case of NOx and Ozone A. Pappin et al. https://doi.org/10.1021/acs.est.5b00950
6. Influence of fossil-fuel power plant emissions on the surface fine particulate matter in the Seoul Capital Area, South Korea B. Kim et al. https://doi.org/10.1080/10962247.2016.1175392
7. Inverse Relations of PM2.5 and O3 in Air Compound Pollution between Cold and Hot Seasons over an Urban Area of East China M. Jia et al. https://doi.org/10.3390/atmos8030059
8. PM2.5 Source Apportionment Analysis to Investigate Contributions of the Major Source Areas in the Southeastern Region of South Korea H. Ju et al. https://doi.org/10.5572/KOSAE.2018.34.4.517
9. Health benefits of reducing NO x emissions in the presence of epidemiological and atmospheric nonlinearities A. Pappin et al. https://doi.org/10.1088/1748-9326/11/6/064015
10. Analysis of chemical characteristics of PM2.5 in Beijing over a 1-year period Z. Wang et al. https://doi.org/10.1007/s10874-016-9334-8
11. The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2 J. Liu et al. https://doi.org/10.5194/gmd-17-567-2024
12. New approach for optimal electricity planning and dispatching with hourly time-scale air quality and health considerations P. Kerl et al. https://doi.org/10.1073/pnas.1413143112
13. Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System W. Li et al. https://doi.org/10.5194/gmd-18-1635-2025
14. Exploring the heavy air pollution in Beijing in the fourth quarter of 2015: assessment of environmental benefits for red alerts T. Nie et al. https://doi.org/10.1007/s11707-017-0673-9
15. WITHDRAWN: The chemical and physical processes of ambient ozone simulated by a photochemical air quality modeling system in urban and rural areas in the Pearl River Delta region, China X. Hou et al. https://doi.org/10.1016/j.apr.2018.06.010
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17. Examining single-source secondary impacts estimated from brute-force, decoupled direct method, and advanced plume treatment approaches J. Kelly et al. https://doi.org/10.1016/j.atmosenv.2015.04.004
18. Ecological risk source distribution, uncertainty analysis, and application of geographically weighted regression cokriging for prediction of potentially toxic elements in agricultural soils P. Agyeman et al. https://doi.org/10.1016/j.psep.2022.06.051
19. Evaluation on Provincial NOX and SO2 Emissions in CAPSS 2016 Based on Photochemical Model Simulation O. Kim et al. https://doi.org/10.5572/KOSAE.2020.36.1.064
20. Estimation of Contribution and Emission-to-PM2.5 Conversion Rate by Each Local Government for Policy Support N. Moon et al. https://doi.org/10.5572/KOSAE.2021.37.6.891
21. Changes in first- and second-order sensitivities of ozone concentration to its precursors over the Yangtze River Delta region of China due to COVID-19 lockdown: Insights from CMAQ-HDDM modeling study E. Yaluk et al. https://doi.org/10.1016/j.atmosenv.2023.119931
22. InMAP: A model for air pollution interventions C. Tessum et al. https://doi.org/10.1371/journal.pone.0176131
23. Implementation of an On-Line Reactive Source Apportionment (ORSA) Algorithm in the FARM Chemical-Transport Model and Application over Multiple Domains in Italy G. Calori et al. https://doi.org/10.3390/atmos15020191
24. Assessments of levels, potential ecological risk, and human health risk of heavy metals in the soils from a typical county in Shanxi Province, China L. Pan et al. https://doi.org/10.1007/s11356-016-7044-z
25. Assessing the importance of nonlinearity for aircraft emissions' impact on O3 and PM2.5 C. Arter & S. Arunachalam https://doi.org/10.1016/j.scitotenv.2021.146121
26. Ground-level ozone in urban Beijing over a 1-year period: Temporal variations and relationship to atmospheric oxidation Z. Wang et al. https://doi.org/10.1016/j.atmosres.2015.05.005
27. Temporal distribution, source apportionment, and pollution assessment of metals in the sediments of Beas river, India V. Kumar et al. https://doi.org/10.1080/10807039.2018.1440529
28. A high resolution multipollutant assessment of health damages due to the onroad sector in Boston, Massachusetts M. Soni et al. https://doi.org/10.1016/j.scitotenv.2025.178847
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30. Source impact and contribution analysis of ambient ozone using multi-modeling approaches over the Pearl River Delta region, China T. Fang et al. https://doi.org/10.1016/j.envpol.2021.117860
31. Global Sensitivity Analysis of the Regional Atmospheric Chemical Mechanism: An Application of Random Sampling-High Dimensional Model Representation to Urban Oxidation Chemistry S. Chen et al. https://doi.org/10.1021/es301565w
32. Novel Method for Ozone Isopleth Construction and Diagnosis for the Ozone Control Strategy of Chinese Cities H. Shen et al. https://doi.org/10.1021/acs.est.1c01567
33. Fine particulate matter source apportionment using a hybrid chemical transport and receptor model approach Y. Hu et al. https://doi.org/10.5194/acp-14-5415-2014
34. Spatio-temporal characteristics of PM2.5 and O3 synergic pollutions and influence factors in the Yangtze River Delta Q. Zhu et al. https://doi.org/10.3389/fenvs.2022.1104013
35. Effects of climate change on PM2.5 formation chemistry, and the associated human health impacts and economic costs in Southeast Asia T. Fang et al. https://doi.org/10.1016/j.envint.2025.109835
36. Emissions Reductions at Coal Power Plants Continue to Offer Routes to Meet New US PM2.5 Standards M. Rasel et al. https://doi.org/10.1021/acs.est.5c13420
37. A Feasible Methodological Framework for Uncertainty Analysis and Diagnosis of Atmospheric Chemical Transport Models Z. Huang et al. https://doi.org/10.1021/acs.est.8b06326
38. Changes in Inorganic Fine Particulate Matter Sensitivities to Precursors Due to Large-Scale US Emissions Reductions J. Holt et al. https://doi.org/10.1021/acs.est.5b00008
39. Origin of Fine Particulate Carbon in the Rural United States B. Schichtel et al. https://doi.org/10.1021/acs.est.7b00645
40. An evaluation of CMAQ NO2 using observed chemistry‐meteorology correlations M. Harkey et al. https://doi.org/10.1002/2015JD023316
41. Impact of Stack Parameters on Modeled PM2.5Conversion Rates: A Case Study of Chungnam during the KORUS-AQ 2016 H. Ju et al. https://doi.org/10.5572/KOSAE.2019.35.5.593
42. PM2.5 Simulations for the Seoul Metropolitan Area: (II) Estimation of Self-Contributions and Emission-to-PM2.5 Conversion Rates for Each Source Category S. Kim et al. https://doi.org/10.5572/KOSAE.2017.33.4.377
43. Characterization factors and other air quality impact metrics: Case study for PM2.5-emitting area sources from biofuel feedstock supply M. Thind et al. https://doi.org/10.1016/j.scitotenv.2022.153418
44. Source attribution of particulate matter in Berlin J. Pültz et al. https://doi.org/10.1016/j.atmosenv.2022.119416
45. Use of high-order sensitivity analysis and reduced-form modeling to quantify uncertainty in particulate matter simulations in the presence of uncertain emissions rates: A case study in Houston W. Zhang et al. https://doi.org/10.1016/j.atmosenv.2015.08.091