Articles | Volume 14, issue 11
https://doi.org/10.5194/acp-14-5415-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-14-5415-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
04 Jun 2014
Research article |
| 04 Jun 2014
Fine particulate matter source apportionment using a hybrid chemical transport and receptor model approach
Y. Hu
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
S. Balachandran
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
J. E. Pachon
now at: Program of Environmental Engineering, Universidad de La Salle, Bogota, Colombia
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
J. Baek
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
C. Ivey
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
H. Holmes
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
M. T. Odman
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
J. A. Mulholland
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
A. G. Russell
School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
Related authors
Baolei Lyu, Ran Huang, Xinlu Wang, Weiguo Wang, and Yongtao Hu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-198, https://doi.org/10.5194/gmd-2024-198, 2024
Preprint under review for GMD
Short summary
Short summary
FastCTM is a neural network model to simulate key criteria air pollution levels, offering an efficient alternative to traditional chemical transport models. Its structure is informed by the physical and chemical principles of the atmosphere, allowing it to learn and replicate complex atmospheric processes. FastCTM demonstrated matching accuracy to traditional models with less computational demand. It also provides analysis of how different atmospheric processes contribute to air quality changes.
Baolei Lyu, Ran Huang, Xinlu Wang, Weiguo Wang, and Yongtao Hu
Geosci. Model Dev., 15, 1583–1594, https://doi.org/10.5194/gmd-15-1583-2022, https://doi.org/10.5194/gmd-15-1583-2022, 2022
Short summary
Short summary
Data fusion is used to estimate spatially completed and smooth reanalysis fields from multiple data sources of observations and model simulations. We developed a well-designed deep-learning model framework to embed spatial correlation principles of atmospheric physics and chemical models. The deep-learning model has very high accuracy to predict reanalysis data fields from isolated observation data points. It is also feasible for operational applications due to computational efficiency.
Hao He, Xinrong Ren, Sarah E. Benish, Zhanqing Li, Fei Wang, Yuying Wang, Timothy P. Canty, Xiaobo Dong, Feng Lv, Yongtao Hu, Tong Zhu, and Russell R. Dickerson
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-248, https://doi.org/10.5194/acp-2019-248, 2019
Revised manuscript not accepted
Short summary
Short summary
We conducted aircraft measurements of air pollution in the North China Plain. Concentrations of air pollutants higher than the air quality standards were observed. Our modeling study indicates that the rate of ozone (one major air pollutant) production is determined by volatile organic compounds (VOCs), which is confirmed by satellite observations. Currently, VOCs are not well regulated in China, so this study suggests the future direction of control measures to improve air quality in China.
C. E. Ivey, H. A. Holmes, Y. T. Hu, J. A. Mulholland, and A. G. Russell
Geosci. Model Dev., 8, 2153–2165, https://doi.org/10.5194/gmd-8-2153-2015, https://doi.org/10.5194/gmd-8-2153-2015, 2015
Short summary
Short summary
An integral part of air quality management is knowledge of the impact of pollutant sources on ambient concentrations of particulate matter (PM). This work presents a novel spatiotemporal source apportionment method that generates source impacts for the continental USA. Key sources presented include fossil fuel combustion, biomass burning, dust, sea salt, as well as agricultural activities, biogenics, and aircraft.
M. Trail, A. P. Tsimpidi, P. Liu, K. Tsigaridis, Y. Hu, A. Nenes, and A. G. Russell
Geosci. Model Dev., 6, 1429–1445, https://doi.org/10.5194/gmd-6-1429-2013, https://doi.org/10.5194/gmd-6-1429-2013, 2013
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Baolei Lyu, Ran Huang, Xinlu Wang, Weiguo Wang, and Yongtao Hu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-198, https://doi.org/10.5194/gmd-2024-198, 2024
Preprint under review for GMD
Short summary
Short summary
FastCTM is a neural network model to simulate key criteria air pollution levels, offering an efficient alternative to traditional chemical transport models. Its structure is informed by the physical and chemical principles of the atmosphere, allowing it to learn and replicate complex atmospheric processes. FastCTM demonstrated matching accuracy to traditional models with less computational demand. It also provides analysis of how different atmospheric processes contribute to air quality changes.
Rime El Asmar, Zongrun Li, David J. Tanner, Yongtao Hu, Susan O'Neill, L. Gregory Huey, M. Talat Odman, and Rodney J. Weber
Atmos. Chem. Phys., 24, 12749–12773, https://doi.org/10.5194/acp-24-12749-2024, https://doi.org/10.5194/acp-24-12749-2024, 2024
Short summary
Short summary
Prescribed burning is an important method for managing ecosystems and preventing wildfires. However, smoke from prescribed fires can have a significant impact on air quality. Here, using a network of fixed sites and sampling throughout an extended prescribed burning period in 2 different years, we characterize emissions and evolutions of up to 8 h of PM2.5 mass, black carbon (BC), and brown carbon (BrC) in smoke from burning of forested lands in the southeastern USA.
Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Khanh Do, and Armistead G. Russell
Geosci. Model Dev., 15, 9015–9029, https://doi.org/10.5194/gmd-15-9015-2022, https://doi.org/10.5194/gmd-15-9015-2022, 2022
Short summary
Short summary
While the national ambient air quality standard of ozone is based on the 3-year average of the fourth highest 8 h maximum (MDA8) ozone concentrations, these predicted extreme values using numerical methods are always biased low. We built four computational models (GAM, MARS, random forest and SVR) to predict the fourth highest MDA8 ozone in Southern California using precursor emissions, meteorology and climatological patterns. All models presented acceptable performance, with GAM being the best.
Baolei Lyu, Ran Huang, Xinlu Wang, Weiguo Wang, and Yongtao Hu
Geosci. Model Dev., 15, 1583–1594, https://doi.org/10.5194/gmd-15-1583-2022, https://doi.org/10.5194/gmd-15-1583-2022, 2022
Short summary
Short summary
Data fusion is used to estimate spatially completed and smooth reanalysis fields from multiple data sources of observations and model simulations. We developed a well-designed deep-learning model framework to embed spatial correlation principles of atmospheric physics and chemical models. The deep-learning model has very high accuracy to predict reanalysis data fields from isolated observation data points. It is also feasible for operational applications due to computational efficiency.
Bingqing Zhang, Huizhong Shen, Pengfei Liu, Hongyu Guo, Yongtao Hu, Yilin Chen, Shaodong Xie, Ziyan Xi, T. Nash Skipper, and Armistead G. Russell
Atmos. Chem. Phys., 21, 8341–8356, https://doi.org/10.5194/acp-21-8341-2021, https://doi.org/10.5194/acp-21-8341-2021, 2021
Short summary
Short summary
Extended ground-level measurements are coupled with model simulations to comprehensively compare the aerosol acidity in China and the United States. Aerosols in China are significantly less acidic than those in the United States, with pH values 1–2 units higher. Higher aerosol mass concentrations and the abundance of ammonia and ammonium in China, compared to the United States, are leading causes of the pH difference between these two countries.
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.
Yilin Chen, Huizhong Shen, Jennifer Kaiser, Yongtao Hu, Shannon L. Capps, Shunliu Zhao, Amir Hakami, Jhih-Shyang Shih, Gertrude K. Pavur, Matthew D. Turner, Daven K. Henze, Jaroslav Resler, Athanasios Nenes, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Tianfeng Chai, Lieven Clarisse, Pierre-François Coheur, Martin Van Damme, and Armistead G. Russell
Atmos. Chem. Phys., 21, 2067–2082, https://doi.org/10.5194/acp-21-2067-2021, https://doi.org/10.5194/acp-21-2067-2021, 2021
Short summary
Short summary
Ammonia (NH3) emissions can exert adverse impacts on air quality and ecosystem well-being. NH3 emission inventories are viewed as highly uncertain. Here we optimize the NH3 emission estimates in the US using an air quality model and NH3 measurements from the IASI satellite instruments. The optimized NH3 emissions are much higher than the National Emissions Inventory estimates in April. The optimized NH3 emissions improved model performance when evaluated against independent observation.
Shunliu Zhao, Matthew G. Russell, Amir Hakami, Shannon L. Capps, Matthew D. Turner, Daven K. Henze, Peter B. Percell, Jaroslav Resler, Huizhong Shen, Armistead G. Russell, Athanasios Nenes, Amanda J. Pappin, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Charles O. Stanier, and Tianfeng Chai
Geosci. Model Dev., 13, 2925–2944, https://doi.org/10.5194/gmd-13-2925-2020, https://doi.org/10.5194/gmd-13-2925-2020, 2020
Dong Gao, Krystal J. Godri Pollitt, James A. Mulholland, Armistead G. Russell, and Rodney J. Weber
Atmos. Chem. Phys., 20, 5197–5210, https://doi.org/10.5194/acp-20-5197-2020, https://doi.org/10.5194/acp-20-5197-2020, 2020
Short summary
Short summary
This study provides a direct intercomparison between two assays for quantifying oxidative potential (OP) of ambient particles: the synthetic respiratory-tract-lining fluid (RTLF) assay and the dithiothreitol (DTT) assay. The results suggest that the DTT assay and the ascorbic acid depletion in RTLF are associated with organic species, transition metal ions, and antagonistic interactions between species. The glutathione depletion in RTLF is strongly dependent on water-soluble copper.
Athanasios Nenes, Spyros N. Pandis, Rodney J. Weber, and Armistead Russell
Atmos. Chem. Phys., 20, 3249–3258, https://doi.org/10.5194/acp-20-3249-2020, https://doi.org/10.5194/acp-20-3249-2020, 2020
Short summary
Short summary
We show that aerosol acidity (pH) and liquid water content naturally emerge as previously ignored parameters that drive particulate matter formation in the atmosphere, and its sensitivity to emissions of ammonia and nitric acid. The simple framework presented is easily applied to ambient measurements or model output, and it provides the
chemical regimeof PM sensitivity to ammonia and nitric acid availability.
Hao He, Xinrong Ren, Sarah E. Benish, Zhanqing Li, Fei Wang, Yuying Wang, Timothy P. Canty, Xiaobo Dong, Feng Lv, Yongtao Hu, Tong Zhu, and Russell R. Dickerson
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-248, https://doi.org/10.5194/acp-2019-248, 2019
Revised manuscript not accepted
Short summary
Short summary
We conducted aircraft measurements of air pollution in the North China Plain. Concentrations of air pollutants higher than the air quality standards were observed. Our modeling study indicates that the rate of ozone (one major air pollutant) production is determined by volatile organic compounds (VOCs), which is confirmed by satellite observations. Currently, VOCs are not well regulated in China, so this study suggests the future direction of control measures to improve air quality in China.
Petros Vasilakos, Armistead Russell, Rodney Weber, and Athanasios Nenes
Atmos. Chem. Phys., 18, 12765–12775, https://doi.org/10.5194/acp-18-12765-2018, https://doi.org/10.5194/acp-18-12765-2018, 2018
Short summary
Short summary
In this work, we investigated the role of emission reductions on aerosol acidity and particulate nitrate. We found that models exhibit positive biases in pH predictions, attributed to very high levels of crustal elements (Mg, Ca, K) in model simulations, which in turn led to an increasing aerosol pH trend over the past decade and allowed nitrate to become an important component of aerosol, which is inconsistent with the measurements, highlighting the importance of accurate pH prediction.
Theodora Nah, Hongyu Guo, Amy P. Sullivan, Yunle Chen, David J. Tanner, Athanasios Nenes, Armistead Russell, Nga Lee Ng, L. Gregory Huey, and Rodney J. Weber
Atmos. Chem. Phys., 18, 11471–11491, https://doi.org/10.5194/acp-18-11471-2018, https://doi.org/10.5194/acp-18-11471-2018, 2018
Short summary
Short summary
We present measurements from a field study conducted in an agriculturally intensive region in the southeastern US during the fall of 2016 to investigate how NH3 affects particle acidity and SOA formation via gas–particle partitioning of semi-volatile organic acids. For this study, higher NH3 concentrations relative to what has been measured in the region in previous studies had minor effects on PM1 organic acids and their influence on the overall organic aerosol and PM1 mass concentrations.
Xing Peng, Jian Gao, Guoliang Shi, Xurong Shi, Yanqi Huangfu, Jiayuan Liu, Yuechong Zhang, Yinchang Feng, Wei Wang, Ruoyu Ma, Cesunica E. Ivey, and Yi Deng
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-997, https://doi.org/10.5194/acp-2017-997, 2018
Preprint withdrawn
Short summary
Short summary
A finding here is that source emission dominates the level of pollutants and short-term meteorological condition determines the variation of pollutants. Primary source impact levels are mainly influenced by source emissions, and secondary source impact levels are mainly influenced by synoptic scale fluctuations and source emissions. The implications of results are for source apportionment analyses conducted with data from different geographical locations and under various weather conditions.
Amelia F. Longo, David J. Vine, Laura E. King, Michelle Oakes, Rodney J. Weber, Lewis Gregory Huey, Armistead G. Russell, and Ellery D. Ingall
Atmos. Chem. Phys., 16, 13389–13398, https://doi.org/10.5194/acp-16-13389-2016, https://doi.org/10.5194/acp-16-13389-2016, 2016
Short summary
Short summary
New synchrotron-based techniques were applied to characterize the oxidation state and composition of sulfur in ambient aerosol and emission sources. Individual particles were found to contain surprisingly high levels of elemental sulfur, a form of sulfur found in only one of the emission sources analyzed. We also show metal sulfates as a key component of urban aerosols. These metal sulfate phases are highly soluble and are indicative of acidic processes transforming metals in the environment.
Ting Fang, Vishal Verma, Josephine T. Bates, Joseph Abrams, Mitchel Klein, Matthew J. Strickland, Stefanie E. Sarnat, Howard H. Chang, James A. Mulholland, Paige E. Tolbert, Armistead G. Russell, and Rodney J. Weber
Atmos. Chem. Phys., 16, 3865–3879, https://doi.org/10.5194/acp-16-3865-2016, https://doi.org/10.5194/acp-16-3865-2016, 2016
Short summary
Short summary
Ascorbic acid (AA) and Dithiothreitol (DTT) assay measures of water-soluble PM2.5 oxidative potential (OP) are compared in terms of spatiotemporal trends, chemical selectivity, sources, and health impacts based on an epidemiological study with backcast estimated OP. Both assays point to metals from brake/tire wear, but only the DTT assay also identifies organics from combustion. DTT is associated with emergency department visits for asthma/wheeze and congestive heart failure, whereas AA is not.
Karoline K. Johnson, Michael H. Bergin, Armistead G. Russell, and Gayle S. W. Hagler
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2015-331, https://doi.org/10.5194/amt-2015-331, 2016
Revised manuscript not accepted
Short summary
Short summary
Low-cost air quality sensors were evaluated in Atlanta, GA, in Hyderabad, India and also in lab experiments. Freeway emissions were also quantified in Atlanta. The performance of these sensors were evaluated against current measurement instruments. Results show potential usefulness for these sensors in polluted areas. The ability to inexpensively measure air pollution will enable researches, citizens, and policy makers to make informed decisions to reduce health impacts from air pollution.
C. E. Ivey, H. A. Holmes, Y. T. Hu, J. A. Mulholland, and A. G. Russell
Geosci. Model Dev., 8, 2153–2165, https://doi.org/10.5194/gmd-8-2153-2015, https://doi.org/10.5194/gmd-8-2153-2015, 2015
Short summary
Short summary
An integral part of air quality management is knowledge of the impact of pollutant sources on ambient concentrations of particulate matter (PM). This work presents a novel spatiotemporal source apportionment method that generates source impacts for the continental USA. Key sources presented include fossil fuel combustion, biomass burning, dust, sea salt, as well as agricultural activities, biogenics, and aircraft.
V. Verma, T. Fang, H. Guo, L. King, J. T. Bates, R. E. Peltier, E. Edgerton, A. G. Russell, and R. J. Weber
Atmos. Chem. Phys., 14, 12915–12930, https://doi.org/10.5194/acp-14-12915-2014, https://doi.org/10.5194/acp-14-12915-2014, 2014
Short summary
Short summary
The major emission sources of the reactive oxygen species (ROS) associated with ambient particulate matter in the southeastern United States were identified. The study shows biomass burning and secondary aerosol formation as the major sources contributing to the ROS-generating capability of ambient particles. The ubiquitous nature of these two sources suggests widespread population exposures to the toxic aerosol components.
M. Trail, A. P. Tsimpidi, P. Liu, K. Tsigaridis, Y. Hu, A. Nenes, and A. G. Russell
Geosci. Model Dev., 6, 1429–1445, https://doi.org/10.5194/gmd-6-1429-2013, https://doi.org/10.5194/gmd-6-1429-2013, 2013
Related subject area
Subject: Aerosols | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
Trends and drivers of soluble iron deposition from East Asian dust to the Northwest Pacific: a springtime analysis (2001–2017)
Modelling of atmospheric variability in gas and aerosols during the ACROSS campaign 2022 of the greater Paris area: evaluation of the meteorology, dynamics and chemistry
Spatial–temporal patterns in anthropogenic and biomass burning emission contributions to air pollution and mortality burden changes in India from 1995 to 2014
A comprehensive global modeling assessment of nitrate heterogeneous formation on desert dust
AERO-MAP: a data compilation and modeling approach to understand spatial variability in fine- and coarse-mode aerosol composition
Long-term trends in aerosol properties derived from AERONET measurements
Impacts of sea ice leads on sea salt aerosols and atmospheric chemistry in the Arctic
Dimethyl sulfide chemistry over the industrial era: comparison of key oxidation mechanisms and long-term observations
Driving factors of aerosol acidity: a new hierarchical quantitative analysis framework and its application in Changzhou, China
Understanding the long-term trend of organic aerosol and the influences from anthropogenic emission and regional climate change in China
Population exposure to outdoor NO2, black carbon, and ultrafine and fine particles over Paris with multi-scale modelling down to the street scale
Predicted impacts of heterogeneous chemical pathways on particulate sulfur over Fairbanks (Alaska), the Northern Hemisphere, and the Contiguous United States
Critical load exceedances for North America and Europe using an ensemble of models and an investigation of causes of environmental impact estimate variability: an AQMEII4 study
Impacts of meteorology and emission reductions on haze pollution during the lockdown in the North China Plain
Impact of mineral dust on the global nitrate aerosol direct and indirect radiative effect
The surface tension and cloud condensation nuclei (CCN) activation of sea spray aerosol particles
Exploring the processes controlling secondary inorganic aerosol: evaluating the global GEOS-Chem simulation using a suite of aircraft campaigns
Atmospheric fate of organosulfates through gas-phase and aqueous-phase reaction with hydroxyl radicals: implications in inorganic sulfate formation
Changes in the impacts of ship emissions on PM2.5 and its components in China under the staged fuel oil policies
Influence of land cover change on atmospheric organic gases, aerosols, and radiative effects
Quantifying the impacts of marine aerosols over the southeast Atlantic Ocean using a chemical transport model: implications for aerosol–cloud interactions
Quantifying the impact of global nitrate aerosol on tropospheric composition fields and its production from lightning NOx
Source-explicit estimation of brown carbon in the polluted atmosphere over North China Plain: implications for distribution, absorption and direct radiative effect
Aerosol Composition Trends during 2000–2020: In depth insights from model predictions and multiple worldwide observation datasets
Rapid oxidation of phenolic compounds by O3 and HO●: effects of the air–water interface and mineral dust in tropospheric chemical processes
Uncertainties in the effects of organic aerosol coatings on polycyclic aromatic hydrocarbon concentrations and their estimated health effects
Modeling the contribution of leads to sea spray aerosol in the high Arctic
Exploring Atmospheric Nitrate Formation Mechanisms during the Winters of 2013 and 2018 in the North China Region via Modeling and Isotopic Analysis
Implications of Reduced-Complexity Aerosol Thermodynamics on Organic Aerosol Mass Concentration and Composition over North America
Importance of aerosol composition and aerosol vertical profiles in global spatial variation in the relationship between PM2.5 and aerosol optical depth
The co-benefits of a low-carbon future for PM2.5 and O3 air pollution in Europe
Assessing the effectiveness of SO2, NOx, and NH3 emission reductions in mitigating winter PM2.5 in Taiwan using CMAQ
Modelling of atmospheric concentrations of fungal spores: a 2-year simulation over France using CHIMERE
Cluster-dynamics-based parameterization for sulfuric acid–dimethylamine nucleation: comparison and selection through box and three-dimensional modeling
Opinion: The Impact of AerChemMIP on Climate and Air Quality Research
Observed and CMIP6-model-simulated organic aerosol response to drought in the contiguous United States during summertime
Cooling radiative forcing effect enhancement of atmospheric amines and mineral particles caused by heterogeneous uptake and oxidation
Source-resolved atmospheric metal emissions, concentrations, and deposition fluxes into the East Asian seas
Analysis of secondary inorganic aerosols over the greater Athens area using the EPISODE–CityChem source dispersion and photochemistry model
Global estimates of ambient reactive nitrogen components during 2000–2100 based on the multi-stage model
The role of naphthalene and its derivatives in the formation of secondary organic aerosol in the Yangtze River Delta region, China
Unveiling the optimal regression model for source apportionment of the oxidative potential of PM10
Investigating the contribution of grown new particles to cloud condensation nuclei with largely varying preexisting particles – Part 2: Modeling chemical drivers and 3-D new particle formation occurrence
Technical note: Influence of different averaging metrics and temporal resolutions on the aerosol pH calculated by thermodynamic modeling
Dual roles of the inorganic aqueous phase on secondary organic aerosol growth from benzene and phenol
Global source apportionment of aerosols into major emission regions and sectors over 1850–2017
Modeling atmospheric brown carbon in the GISS ModelE Earth system model
Observation-constrained kinetic modeling of isoprene SOA formation in the atmosphere
Significant impact of urban tree biogenic emissions on air quality estimated by a bottom-up inventory and chemistry transport modeling
Secondary organic aerosols derived from intermediate-volatility n-alkanes adopt low-viscous phase state
Hanzheng Zhu, Yaman Liu, Man Yue, Shihui Feng, Pingqing Fu, Kan Huang, Xinyi Dong, and Minghuai Wang
Atmos. Chem. Phys., 25, 5175–5197, https://doi.org/10.5194/acp-25-5175-2025, https://doi.org/10.5194/acp-25-5175-2025, 2025
Short summary
Short summary
Dust-soluble iron deposition from East Asia plays an important role in the marine ecology of the Northwest Pacific. Using the developed model, our findings highlight a dual trend: a decrease in the overall deposition of soluble iron from dust but an increase in the solubility of the iron itself due to the enhanced atmospheric processing. The study underscores the critical roles of both dust emission and atmospheric processing in soluble iron deposition and marine ecology.
Ludovico Di Antonio, Matthias Beekmann, Guillaume Siour, Vincent Michoud, Christopher Cantrell, Astrid Bauville, Antonin Bergé, Mathieu Cazaunau, Servanne Chevaillier, Manuela Cirtog, Joel F. de Brito, Paola Formenti, Cecile Gaimoz, Olivier Garret, Aline Gratien, Valérie Gros, Martial Haeffelin, Lelia N. Hawkins, Simone Kotthaus, Gael Noyalet, Diana L. Pereira, Jean-Eudes Petit, Eva Drew Pronovost, Véronique Riffault, Chenjie Yu, Gilles Foret, Jean-François Doussin, and Claudia Di Biagio
Atmos. Chem. Phys., 25, 4803–4831, https://doi.org/10.5194/acp-25-4803-2025, https://doi.org/10.5194/acp-25-4803-2025, 2025
Short summary
Short summary
The summer of 2022 has been considered a proxy for future climate scenarios due to its hot and dry conditions. In this paper, we use the measurements from the Atmospheric Chemistry of the Suburban Forest (ACROSS) campaign, conducted in the Paris area in June–July 2022, along with observations from existing networks, to evaluate a 3D chemistry transport model (WRF–CHIMERE) simulation. Results are shown to be satisfactory, allowing us to explain the gas and aerosol variability at the campaign sites.
Bin Luo, Yuqiang Zhang, Tao Tang, Hongliang Zhang, Jianlin Hu, Jiangshan Mu, Wenxing Wang, and Likun Xue
Atmos. Chem. Phys., 25, 4767–4783, https://doi.org/10.5194/acp-25-4767-2025, https://doi.org/10.5194/acp-25-4767-2025, 2025
Short summary
Short summary
India is facing a severe air pollution crisis that poses significant health risks, particularly from PM2.5 and O3. Our study reveals rising levels of both pollutants from 1995 to 2014, leading to increased premature mortality. While anthropogenic emissions play a significant role, biomass burning also impacts air quality, in particular seasons and regions in India. This study underscores the urgent need for localized policies to protect public health amid escalating environmental challenges.
Rubén Soussé Villa, Oriol Jorba, María Gonçalves Ageitos, Dene Bowdalo, Marc Guevara, and Carlos Pérez García-Pando
Atmos. Chem. Phys., 25, 4719–4753, https://doi.org/10.5194/acp-25-4719-2025, https://doi.org/10.5194/acp-25-4719-2025, 2025
Short summary
Short summary
Desert dust forms nitrate coatings as it travels through the atmosphere. However, current models that predict this process vary greatly due to different methods and inaccuracies. We examined how nitrate forms in a global model, focusing on how gases condense on dust, the lifespan of different particles, and the impact of alkalinity. Our findings show that models work best when they consider reversible gas condensation with alkalinity. This should lead to better estimates of climate impacts.
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.
Zhenyu Zhang, Jing Li, Huizheng Che, Yueming Dong, Oleg Dubovik, Thomas Eck, Pawan Gupta, Brent Holben, Jhoon Kim, Elena Lind, Trailokya Saud, Sachchida Nand Tripathi, and Tong Ying
Atmos. Chem. Phys., 25, 4617–4637, https://doi.org/10.5194/acp-25-4617-2025, https://doi.org/10.5194/acp-25-4617-2025, 2025
Short summary
Short summary
We used ground-based remote sensing data from the Aerosol Robotic Network to examine long-term trends in aerosol characteristics. We found aerosol loadings generally decreased globally, and aerosols became more scattering. These changes are closely related to variations in aerosol compositions, such as decreased anthropogenic emissions over East Asia, Europe, and North America; increased anthropogenic sources over northern India; and increased dust activity over the Arabian Peninsula.
Erin J. Emme and Hannah M. Horowitz
Atmos. Chem. Phys., 25, 4531–4545, https://doi.org/10.5194/acp-25-4531-2025, https://doi.org/10.5194/acp-25-4531-2025, 2025
Short summary
Short summary
There is uncertainty in the sources of Arctic cold-season (November–April) sea salt aerosols. Using a chemical transport model and satellite observations, we quantify Arctic-wide sea salt aerosol emissions from fractures in sea ice, called open sea ice leads, and their atmospheric chemistry impacts for the cold season. We show that sea ice leads contribute to Arctic sea salt aerosols and bromine, especially in under-observed regions.
Ursula A. Jongebloed, Jacob I. Chalif, Linia Tashmim, William C. Porter, Kelvin H. Bates, Qianjie Chen, Erich C. Osterberg, Bess G. Koffman, Jihong Cole-Dai, Dominic A. Winski, David G. Ferris, Karl J. Kreutz, Cameron P. Wake, and Becky Alexander
Atmos. Chem. Phys., 25, 4083–4106, https://doi.org/10.5194/acp-25-4083-2025, https://doi.org/10.5194/acp-25-4083-2025, 2025
Short summary
Short summary
Marine phytoplankton emit dimethyl sulfide (DMS), which forms methanesulfonic acid (MSA) and sulfate. MSA concentrations in ice cores decreased over the industrial era, which has been attributed to pollution-driven changes in DMS chemistry. We use a model to investigate DMS chemistry compared to observations of DMS, MSA, and sulfate. We find that modeled DMS, MSA, and sulfate are influenced by pollution-sensitive oxidant concentrations, characterization of DMS chemistry, and other variables.
Xiaolin Duan, Guangjie Zheng, Chuchu Chen, Qiang Zhang, and Kebin He
Atmos. Chem. Phys., 25, 3919–3928, https://doi.org/10.5194/acp-25-3919-2025, https://doi.org/10.5194/acp-25-3919-2025, 2025
Short summary
Short summary
Aerosol acidity is an important parameter in atmospheric chemistry, while its driving factors, especially chemical profiles versus meteorological conditions, are not yet fully understood. Here, we established a hierarchical quantitative analysis framework to understand the driving factors of aerosol acidity on different timescales. Its application in Changzhou, China, revealed distinct driving factors and corresponding mechanisms of aerosol acidity from annual trends to random residuals.
Wenxin Zhang, Yaman Liu, Man Yue, Xinyi Dong, Kan Huang, and Minghuai Wang
Atmos. Chem. Phys., 25, 3857–3872, https://doi.org/10.5194/acp-25-3857-2025, https://doi.org/10.5194/acp-25-3857-2025, 2025
Short summary
Short summary
Understanding long-term organic aerosol (OA) trends and their driving factors is important for air quality management. Our modeling revealed that OA in China increased by 5.6 % from 1990 to 2019, primarily due to a 32.3 % increase in secondary organic aerosols (SOAs) and an 8.1 % decrease in primary organic aerosols (POAs), both largely driven by changes in anthropogenic emissions. Biogenic SOA increased due to warming but showed little response to changes in anthropogenic nitrogen oxide emissions.
Soo-Jin Park, Lya Lugon, Oscar Jacquot, Youngseob Kim, Alexia Baudic, Barbara D'Anna, Ludovico Di Antonio, Claudia Di Biagio, Fabrice Dugay, Olivier Favez, Véronique Ghersi, Aline Gratien, Julien Kammer, Jean-Eudes Petit, Olivier Sanchez, Myrto Valari, Jérémy Vigneron, and Karine Sartelet
Atmos. Chem. Phys., 25, 3363–3387, https://doi.org/10.5194/acp-25-3363-2025, https://doi.org/10.5194/acp-25-3363-2025, 2025
Short summary
Short summary
To accurately represent the population exposure to outdoor concentrations of pollutants of interest to health (NO2, PM2.5, black carbon, and ultrafine particles), multi-scale modelling down to the street scale is set up and evaluated using measurements from field campaigns. An exposure scaling factor is defined, allowing regional-scale simulations to be corrected to evaluate population exposure. Urban heterogeneities strongly influence NO2, black carbon, and ultrafine particles but less strongly PM2.5.
Sara L. Farrell, Havala O. T. Pye, Robert Gilliam, George Pouliot, Deanna Huff, Golam Sarwar, William Vizuete, Nicole Briggs, Fengkui Duan, Tao Ma, Shuping Zhang, and Kathleen Fahey
Atmos. Chem. Phys., 25, 3287–3312, https://doi.org/10.5194/acp-25-3287-2025, https://doi.org/10.5194/acp-25-3287-2025, 2025
Short summary
Short summary
In this work we implement heterogeneous sulfur chemistry into the Community Multiscale Air Quality (CMAQ) model. This new chemistry accounts for the formation of sulfate via aqueous oxidation of SO2 in aerosol liquid water and the formation of hydroxymethanesulfonate (HMS) – often confused by measurement techniques as sulfate. Model performance in predicting sulfur PM2.5 in Fairbanks, Alaska, and other places that experience dark and cold winters is improved.
Paul A. Makar, Philip Cheung, Christian Hogrefe, Ayodeji Akingunola, Ummugulsum Alyuz, Jesse O. Bash, Michael D. Bell, Roberto Bellasio, Roberto Bianconi, Tim Butler, Hazel Cathcart, Olivia E. Clifton, Alma Hodzic, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Jason A. Lynch, Kester Momoh, Juan L. Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Thomas Scheuschner, Mark W. Shephard, Ranjeet S. Sokhi, and Stefano Galmarini
Atmos. Chem. Phys., 25, 3049–3107, https://doi.org/10.5194/acp-25-3049-2025, https://doi.org/10.5194/acp-25-3049-2025, 2025
Short summary
Short summary
The large range of sulfur and nitrogen deposition estimates from air quality models results in a large range of predicted impacts. We used models and deposition diagnostics to identify the processes controlling atmospheric sulfur and nitrogen deposition variability. Controlling factors included the uptake of gases and aerosols by hydrometeors, aerosol inorganic chemistry, particle dry deposition, ammonia bidirectional fluxes, gas deposition via plant cuticles and soil, and land use data.
Lang Liu, Xin Long, Yi Li, Zengliang Zang, Fengwen Wang, Yan Han, Zhier Bao, Yang Chen, Tian Feng, and Jinxin Yang
Atmos. Chem. Phys., 25, 1569–1585, https://doi.org/10.5194/acp-25-1569-2025, https://doi.org/10.5194/acp-25-1569-2025, 2025
Short summary
Short summary
This study uses WRF-Chem to assess how meteorological conditions and emission reductions affected fine particulate matter (PM2.5) in the North China Plain (NCP). It highlights regional disparities: in the northern NCP, adverse weather negated emission reduction effects. In contrast, the southern NCP featured a PM2.5 decrease due to favorable weather and emission reductions. The research highlighted the interaction between emissions, meteorology, and PM2.5.
Alexandros Milousis, Klaus Klingmüller, Alexandra P. Tsimpidi, Jasper F. Kok, Maria Kanakidou, Athanasios Nenes, and Vlassis A. Karydis
Atmos. Chem. Phys., 25, 1333–1351, https://doi.org/10.5194/acp-25-1333-2025, https://doi.org/10.5194/acp-25-1333-2025, 2025
Short summary
Short summary
This study investigates the impact of dust on the global radiative effect of nitrate aerosols. The results indicate both positive and negative regional shortwave and longwave radiative effects due to aerosol–radiation interactions and cloud adjustments. The global average net REari and REaci of nitrate aerosols are −0.11 and +0.17 W m−2, respectively, mainly affecting the shortwave spectrum. Sensitivity simulations evaluated the influence of mineral dust composition and emissions on the results.
Judith Kleinheins, Nadia Shardt, Ulrike Lohmann, and Claudia Marcolli
Atmos. Chem. Phys., 25, 881–903, https://doi.org/10.5194/acp-25-881-2025, https://doi.org/10.5194/acp-25-881-2025, 2025
Short summary
Short summary
We model the cloud condensation nuclei (CCN) activation of sea spray aerosol particles with classical Köhler theory and with a new model approach that takes surface tension lowering into account. We categorize organic compounds into weak, intermediate, and strong surfactants, and we outline for which composition surface tension lowering is important. The results suggest that surface tension lowering allows sea spray aerosol particles in the Aitken mode to be a source of CCN in marine updraughts.
Olivia G. Norman, Colette L. Heald, Solomon Bililign, Pedro Campuzano-Jost, Hugh Coe, Marc N. Fiddler, Jaime R. Green, Jose L. Jimenez, Katharina Kaiser, Jin Liao, Ann M. Middlebrook, Benjamin A. Nault, John B. Nowak, Johannes Schneider, and André Welti
Atmos. Chem. Phys., 25, 771–795, https://doi.org/10.5194/acp-25-771-2025, https://doi.org/10.5194/acp-25-771-2025, 2025
Short summary
Short summary
This study finds that one component of secondary inorganic aerosols, nitrate, is greatly overestimated by a global atmospheric chemistry model compared to observations from 11 flight campaigns. None of the loss and production pathways explored can explain the nitrate bias alone. The model’s inability to capture the variability in the observations remains and requires future investigation to avoid biases in policy-related studies (i.e., air quality, health, climate impacts of these aerosols).
Narcisse Tsona Tchinda, Xiaofan Lv, Stanley Numboniu Tasheh, Julius Numboniu Ghogomu, and Lin Du
EGUsphere, https://doi.org/10.5194/egusphere-2025-29, https://doi.org/10.5194/egusphere-2025-29, 2025
Short summary
Short summary
This study examines the chemical transformation of selected organosulfates by reactions with HO• radicals both in the gas-phase and in the aqueous-phase. Results show that the nature of the substituents on the carbon chain can effectively alter the decomposition of organosulfates and ozone is highlighted as a key oxidant in the intermediate steps of this decomposition. The primary products from these reactions include inorganic sulfate and carbonyl compounds.
Guangyuan Yu, Yan Zhang, Qian Wang, Zimin Han, Shenglan Jiang, Fan Yang, Xin Yang, and Cheng Huang
EGUsphere, https://doi.org/10.5194/egusphere-2024-3892, https://doi.org/10.5194/egusphere-2024-3892, 2025
Short summary
Short summary
China has carried out staged low-sulfur fuel policies since 2017. This study simulated the changing spatiotemporal patterns of the impacts of ship emissions on PM2.5 from 2017 to 2021 based on the updated emission inventories and mapping of chemical species in the CMAQ. Fuel policies caused evident relative changes in inorganic and organic components of the shipping-related PM2.5 over China’s port cities. The driving factors of the interannual, seasonal, and diurnal patterns were discussed.
Ryan Vella, Matthew Forrest, Andrea Pozzer, Alexandra P. Tsimpidi, Thomas Hickler, Jos Lelieveld, and Holger Tost
Atmos. Chem. Phys., 25, 243–262, https://doi.org/10.5194/acp-25-243-2025, https://doi.org/10.5194/acp-25-243-2025, 2025
Short summary
Short summary
This study examines how land cover changes influence biogenic volatile organic compound (BVOC) emissions and atmospheric states. Using a coupled chemistry–climate–vegetation model, we compare present-day land cover (deforested for crops and grazing) with natural vegetation and an extreme reforestation scenario. We find that vegetation changes significantly impact global BVOC emissions and organic aerosols but have a relatively small effect on total aerosols, clouds, and radiative effects.
Mashiat Hossain, Rebecca M. Garland, and Hannah M. Horowitz
Atmos. Chem. Phys., 24, 14123–14143, https://doi.org/10.5194/acp-24-14123-2024, https://doi.org/10.5194/acp-24-14123-2024, 2024
Short summary
Short summary
Our research examines aerosol dynamics over the southeast Atlantic, a region with significant uncertainties in aerosol radiative forcings. Using the GEOS-Chem model, we find that at cloud altitudes, organic aerosols dominate during the biomass burning season, while sulfate aerosols, driven by marine emissions, prevail during peak primary production. These findings highlight the need for accurate representation of marine aerosols in models to improve climate predictions and reduce uncertainties.
Ashok K. Luhar, Anthony C. Jones, and Jonathan M. Wilkinson
Atmos. Chem. Phys., 24, 14005–14028, https://doi.org/10.5194/acp-24-14005-2024, https://doi.org/10.5194/acp-24-14005-2024, 2024
Short summary
Short summary
Nitrate aerosol is often omitted in global chemistry–climate models, partly due to the chemical complexity of its formation process. Using a global model, we show that including nitrate aerosol significantly impacts tropospheric composition fields, such as ozone, and radiation. Additionally, lightning-generated oxides of nitrogen influence both nitrate aerosol mass concentrations and aerosol size distribution, which has important implications for radiative fluxes and indirect aerosol effects.
Jiamao Zhou, Jiarui Wu, Xiaoli Su, Ruonan Wang, Xia Li, Qian Jiang, Ting Zhang, Wenting Dai, Junji Cao, Xuexi Tie, and Guohui Li
EGUsphere, https://doi.org/10.5194/egusphere-2024-3468, https://doi.org/10.5194/egusphere-2024-3468, 2024
Short summary
Short summary
Brown carbon (BrC) is a type of airborne particle produced from various combustion sources which is light absorption. Historically, climate models have categorizing organic particles as either non-absorbing or purely reflective. Our study shows that BrC can reduce the usual cooling effect of organic particles. While BrC is often linked to biomass burning, however, BrC from fossil fuels contributes significantly to atmospheric heating.
Alexandra P. Tsimpidi, Susanne M. C. Scholz, Alexandros Milousis, Nikolaos Mihalopoulos, and Vlassis A. Karydis
EGUsphere, https://doi.org/10.5194/egusphere-2024-3590, https://doi.org/10.5194/egusphere-2024-3590, 2024
Short summary
Short summary
This study examines global changes in air pollution from 2000 to 2020, focusing on fine aerosols that impact climate and health. Using models and global data, it finds organic aerosols dominate in many regions, especially with wildfires or natural emissions. Pollution from sulfate and nitrate has decreased in Europe and North America due to regulations, while trends in Asia are more complex. The findings improve understanding and support policies for cleaner air and healthier environments.
Yanru Huo, Mingxue Li, Xueyu Wang, Jianfei Sun, Yuxin Zhou, Yuhui Ma, and Maoxia He
Atmos. Chem. Phys., 24, 12409–12423, https://doi.org/10.5194/acp-24-12409-2024, https://doi.org/10.5194/acp-24-12409-2024, 2024
Short summary
Short summary
This work found that the air–water (A–W) interface and TiO2 clusters promote the oxidation of phenolic compounds (PhCs) to varying degrees compared with the gas phase and bulk water. Some byproducts are more harmful than their parent compounds. This work provides important evidence for the rapid oxidation observed in O3/HO• + PhC experiments at the A–W interface and in mineral dust.
Sijia Lou, Manish Shrivastava, Alexandre Albinet, Sophie Tomaz, Deepchandra Srivastava, Olivier Favez, Huizhong Shen, and Aijun Ding
EGUsphere, https://doi.org/10.5194/egusphere-2024-3269, https://doi.org/10.5194/egusphere-2024-3269, 2024
Short summary
Short summary
PAHs, emitted from incomplete combustion, pose serious health risks due to their carcinogenic properties. This research demonstrates that viscous organic aerosol coatings significantly hinder PAH oxidation, with spatial distributions sensitive to the degradation modelling approach. Our findings underscore the importance of accurately modelling these processes for risk assessments, highlighting the need to consider both fresh and oxidized PAHs in evaluating human exposure and health risks.
Rémy Lapere, Louis Marelle, Pierre Rampal, Laurent Brodeau, Christian Melsheimer, Gunnar Spreen, and Jennie L. Thomas
Atmos. Chem. Phys., 24, 12107–12132, https://doi.org/10.5194/acp-24-12107-2024, https://doi.org/10.5194/acp-24-12107-2024, 2024
Short summary
Short summary
Elongated open-water areas in sea ice, called leads, can release marine aerosols into the atmosphere. In the Arctic, this source of atmospheric particles could play an important role for climate. However, the amount, seasonality and spatial distribution of such emissions are all mostly unknown. Here, we propose a first parameterization for sea spray aerosols emitted through leads in sea ice and quantify their impact on aerosol populations in the high Arctic.
Zhenze Liu, Jianhua Qi, Yuanzhe Ni, Likun Xue, and Xiaohuan Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3044, https://doi.org/10.5194/egusphere-2024-3044, 2024
Short summary
Short summary
Our study explores the formation of nitrate in the atmosphere of inland and coastal cities in China during the winters of 2013 & 2018. Through air quality modelling & isotope analysis, we found regional differences between these cities; coastal cities show another contribution from the heterogeneous reaction of dinitrogen pentoxide (N2O5). It turns out that the combined reduction of nitrogen oxides (NOx), volatile organic compounds (VOCs) and ammonia (NH3) is critical to reducing nitrate levels.
Camilo Serrano Damha, Kyle Gorkowski, and Andreas Zuend
EGUsphere, https://doi.org/10.5194/egusphere-2024-2712, https://doi.org/10.5194/egusphere-2024-2712, 2024
Short summary
Short summary
Organic aerosol water content impacts the gas–particle partitioning of semivolatile organics. We used an aerosol thermodynamic model in the GEOS-Chem chemical transport model to efficiently account for organic aerosol water uptake and nonideal mixing. This led to a substantial enhancement in mean organic aerosol mass concentration with respect to GEOS-Chem's most advanced scheme. The water-sensitive scheme could be a valuable tool for reconciling model estimations and field measurements.
Haihui Zhu, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Chi Li, Jun Meng, Christopher R. Oxford, Xuan Liu, Yanshun Li, Dandan Zhang, Inderjeet Singh, and Alexei Lyapustin
Atmos. Chem. Phys., 24, 11565–11584, https://doi.org/10.5194/acp-24-11565-2024, https://doi.org/10.5194/acp-24-11565-2024, 2024
Short summary
Short summary
Ambient fine particulate matter (PM2.5) contributes to 4 million deaths globally each year. Satellite remote sensing of aerosol optical depth (AOD), coupled with a simulated PM2.5–AOD relationship (η), can provide global PM2.5 estimations. This study aims to understand the spatial patterns and driving factors of η to guide future measurement and modeling efforts. We quantified η globally and regionally and found that its spatial variation is strongly influenced by aerosol composition.
Connor J. Clayton, Daniel R. Marsh, Steven T. Turnock, Ailish M. Graham, Kirsty J. Pringle, Carly L. Reddington, Rajesh Kumar, and James B. McQuaid
Atmos. Chem. Phys., 24, 10717–10740, https://doi.org/10.5194/acp-24-10717-2024, https://doi.org/10.5194/acp-24-10717-2024, 2024
Short summary
Short summary
We demonstrate that strong climate mitigation could improve air quality in Europe; however, less ambitious mitigation does not result in these co-benefits. We use a high-resolution atmospheric chemistry model. This allows us to demonstrate how this varies across European countries and analyse the underlying chemistry. This may help policy-facing researchers understand which sectors and regions need to be prioritised to achieve strong air quality co-benefits of climate mitigation.
Ping-Chieh Huang, Hui-Ming Hung, Hsin-Chih Lai, and Charles C.-K. Chou
Atmos. Chem. Phys., 24, 10759–10772, https://doi.org/10.5194/acp-24-10759-2024, https://doi.org/10.5194/acp-24-10759-2024, 2024
Short summary
Short summary
Models were used to study ways to reduce particulate matter (PM) pollution in Taiwan during winter. After considering various factors, such as physical processes and chemical reactions, we found that reducing NOx or NH3 emissions is more effective at mitigating PM2.5 than reducing SO2 emissions. When considering both efficiency and cost, reducing NH3 emissions seems to be a more suitable policy for the studied environment in Taiwan.
Matthieu Vida, Gilles Foret, Guillaume Siour, Florian Couvidat, Olivier Favez, Gaelle Uzu, Arineh Cholakian, Sébastien Conil, Matthias Beekmann, and Jean-Luc Jaffrezo
Atmos. Chem. Phys., 24, 10601–10615, https://doi.org/10.5194/acp-24-10601-2024, https://doi.org/10.5194/acp-24-10601-2024, 2024
Short summary
Short summary
We simulate 2 years of atmospheric fungal spores over France and use observations of polyols and primary biogenic factors from positive matrix factorisation. The representation of emissions taking into account a proxy for vegetation surface and specific humidity enables us to reproduce very accurately the seasonal cycle of fungal spores. Furthermore, we estimate that fungal spores can account for 20 % of PM10 and 40 % of the organic fraction of PM10 over vegetated areas in summer.
Jiewen Shen, Bin Zhao, Shuxiao Wang, An Ning, Yuyang Li, Runlong Cai, Da Gao, Biwu Chu, Yang Gao, Manish Shrivastava, Jingkun Jiang, Xiuhui Zhang, and Hong He
Atmos. Chem. Phys., 24, 10261–10278, https://doi.org/10.5194/acp-24-10261-2024, https://doi.org/10.5194/acp-24-10261-2024, 2024
Short summary
Short summary
We extensively compare various cluster-dynamics-based parameterizations for sulfuric acid–dimethylamine nucleation and identify a newly developed parameterization derived from Atmospheric Cluster Dynamic Code (ACDC) simulations as being the most reliable one. This study offers a valuable reference for developing parameterizations of other nucleation systems and is meaningful for the accurate quantification of the environmental and climate impacts of new particle formation.
Paul T. Griffiths, Laura J. Wilcox, Robert J. Allen, Vaishali Naik, Fiona M. O'Connor, Michael J. Prather, Alexander T. Archibald, Florence Brown, Makoto Deushi, William Collins, Stephanie Fiedler, Naga Oshima, Lee T. Murray, Christopher J. Smith, Steven T. Turnock, Duncan Watson-Parris, and Paul J. Young
EGUsphere, https://doi.org/10.5194/egusphere-2024-2528, https://doi.org/10.5194/egusphere-2024-2528, 2024
Short summary
Short summary
The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) aimed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. In this paper, we review its contribution to AR6, and the wider understanding of the role of these species in climate and climate change. We identify remaining challenges concluding with recommendations aimed to improve the utility and uptake of climate model data to address the role of short-lived climate forcers in the Earth system.
Wei Li and Yuxuan Wang
Atmos. Chem. Phys., 24, 9339–9353, https://doi.org/10.5194/acp-24-9339-2024, https://doi.org/10.5194/acp-24-9339-2024, 2024
Short summary
Short summary
Droughts immensely increased organic aerosol (OA) in the contiguous United States in summer (1998–2019), notably in the Pacific Northwest (PNW) and Southeast (SEUS). The OA rise in the SEUS is driven by the enhanced formation of epoxydiol-derived secondary organic aerosol due to the increase in biogenic volatile organic compounds and sulfate, while in the PNW, it is caused by wildfires. A total of 10 climate models captured the OA increase in the PNW yet greatly underestimated it in the SEUS.
Weina Zhang, Jianhua Mai, Zhichao Fan, Yongpeng Ji, Yuemeng Ji, Guiying Li, Yanpeng Gao, and Taicheng An
Atmos. Chem. Phys., 24, 9019–9030, https://doi.org/10.5194/acp-24-9019-2024, https://doi.org/10.5194/acp-24-9019-2024, 2024
Short summary
Short summary
This study reveals heterogeneous oxidation causes further radiative forcing effect (RFE) enhancement of amine–mineral mixed particles. Note that RFE increment is higher under clean conditions than that under polluted conditions, which is contributed to high-oxygen-content products. The enhanced RFE of amine–mineral particles caused by heterogenous oxidation is expected to alleviate warming effects.
Shenglan Jiang, Yan Zhang, Guangyuan Yu, Zimin Han, Junri Zhao, Tianle Zhang, and Mei Zheng
Atmos. Chem. Phys., 24, 8363–8381, https://doi.org/10.5194/acp-24-8363-2024, https://doi.org/10.5194/acp-24-8363-2024, 2024
Short summary
Short summary
This study aims to provide gridded data on sea-wide concentrations, deposition fluxes, and soluble deposition fluxes with detailed source categories of metals using the modified CMAQ model. We developed a monthly emission inventory of six metals – Fe, Al, V, Ni, Zn, and Cu – from terrestrial anthropogenic, ship, and dust sources in East Asia in 2017. Our results reveal the contribution of each source to the emissions, concentrations, and deposition fluxes of metals in the East Asian seas.
Stelios Myriokefalitakis, Matthias Karl, Kim A. Weiss, Dimitris Karagiannis, Eleni Athanasopoulou, Anastasia Kakouri, Aikaterini Bougiatioti, Eleni Liakakou, Iasonas Stavroulas, Georgios Papangelis, Georgios Grivas, Despina Paraskevopoulou, Orestis Speyer, Nikolaos Mihalopoulos, and Evangelos Gerasopoulos
Atmos. Chem. Phys., 24, 7815–7835, https://doi.org/10.5194/acp-24-7815-2024, https://doi.org/10.5194/acp-24-7815-2024, 2024
Short summary
Short summary
A state-of-the-art thermodynamic model has been coupled with the city-scale chemistry transport model EPISODE–CityChem to investigate the equilibrium between the inorganic gas and aerosol phases over the greater Athens area, Greece. The simulations indicate that the formation of nitrates in an urban environment is significantly affected by local nitrogen oxide emissions, as well as ambient temperature, relative humidity, photochemical activity, and the presence of non-volatile cations.
Rui Li, Yining Gao, Lijia Zhang, Yubing Shen, Tianzhao Xu, Wenwen Sun, and Gehui Wang
Atmos. Chem. Phys., 24, 7623–7636, https://doi.org/10.5194/acp-24-7623-2024, https://doi.org/10.5194/acp-24-7623-2024, 2024
Short summary
Short summary
A three-stage model was developed to obtain the global maps of reactive nitrogen components during 2000–2100. The results implied that cross-validation R2 values of four species showed satisfactory performance (R2 > 0.55). Most reactive nitrogen components, except NH3, in China showed increases during 2000–2013. In the future scenarios, SSP3-7.0 (traditional-energy scenario) and SSP1-2.6 (carbon neutrality scenario) showed the highest and lowest reactive nitrogen component concentrations.
Fei Ye, Jingyi Li, Yaqin Gao, Hongli Wang, Jingyu An, Cheng Huang, Song Guo, Keding Lu, Kangjia Gong, Haowen Zhang, Momei Qin, and Jianlin Hu
Atmos. Chem. Phys., 24, 7467–7479, https://doi.org/10.5194/acp-24-7467-2024, https://doi.org/10.5194/acp-24-7467-2024, 2024
Short summary
Short summary
Naphthalene (Nap) and methylnaphthalene (MN) are key precursors of secondary organic aerosol (SOA), yet their sources and sinks are often inadequately represented in air quality models. In this study, we incorporated detailed emissions, gas-phase chemistry, and SOA parameterization of Nap and MN into CMAQ to address this issue. The findings revealed remarkably high SOA formation potentials for these compounds despite their low emissions in the Yangtze River Delta region during summer.
Vy Dinh Ngoc Thuy, Jean-Luc Jaffrezo, Ian Hough, Pamela A. Dominutti, Guillaume Salque Moreton, Grégory Gille, Florie Francony, Arabelle Patron-Anquez, Olivier Favez, and Gaëlle Uzu
Atmos. Chem. Phys., 24, 7261–7282, https://doi.org/10.5194/acp-24-7261-2024, https://doi.org/10.5194/acp-24-7261-2024, 2024
Short summary
Short summary
The capacity of particulate matter (PM) to generate reactive oxygen species in vivo is represented by oxidative potential (OP). This study focuses on finding the appropriate model to evaluate the oxidative character of PM sources in six sites using the PM sources and OP. Eight regression techniques are introduced to assess the OP of PM. The study highlights the importance of selecting a model according to the input data characteristics and establishes some recommendations for the procedure.
Ming Chu, Xing Wei, Shangfei Hai, Yang Gao, Huiwang Gao, Yujiao Zhu, Biwu Chu, Nan Ma, Juan Hong, Yele Sun, and Xiaohong Yao
Atmos. Chem. Phys., 24, 6769–6786, https://doi.org/10.5194/acp-24-6769-2024, https://doi.org/10.5194/acp-24-6769-2024, 2024
Short summary
Short summary
We used a 20-bin WRF-Chem model to simulate NPF events in the NCP during a three-week observational period in the summer of 2019. The model was able to reproduce the observations during June 29–July 6, which was characterized by a high frequency of NPF occurrence.
Haoqi Wang, Xiao Tian, Wanting Zhao, Jiacheng Li, Haoyu Yu, Yinchang Feng, and Shaojie Song
Atmos. Chem. Phys., 24, 6583–6592, https://doi.org/10.5194/acp-24-6583-2024, https://doi.org/10.5194/acp-24-6583-2024, 2024
Short summary
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.
Jiwon Choi, Myoseon Jang, and Spencer Blau
Atmos. Chem. Phys., 24, 6567–6582, https://doi.org/10.5194/acp-24-6567-2024, https://doi.org/10.5194/acp-24-6567-2024, 2024
Short summary
Short summary
Persistent phenoxy radical (PPR), formed by phenol gas oxidation and its aqueous reaction, catalytically destroys O3 and retards secondary organic aerosol (SOA) growth. Explicit gas mechanisms including the formation of PPR and low-volatility products from the oxidation of phenol or benzene are applied to the UNIPAR model to predict SOA mass via multiphase reactions of precursors. Aqueous reactions of reactive organics increase SOA mass but retard SOA growth via heterogeneously formed PPR.
Yang Yang, Shaoxuan Mou, Hailong Wang, Pinya Wang, Baojie Li, and Hong Liao
Atmos. Chem. Phys., 24, 6509–6523, https://doi.org/10.5194/acp-24-6509-2024, https://doi.org/10.5194/acp-24-6509-2024, 2024
Short summary
Short summary
The variations in anthropogenic aerosol concentrations and source contributions and their subsequent radiative impact in major emission regions during historical periods are quantified based on an aerosol-tagging system in E3SMv1. Due to the industrial development and implementation of economic policies, sources of anthropogenic aerosols show different variations, which has important implications for pollution prevention and control measures and decision-making for global collaboration.
Maegan A. DeLessio, Kostas Tsigaridis, Susanne E. Bauer, Jacek Chowdhary, and Gregory L. Schuster
Atmos. Chem. Phys., 24, 6275–6304, https://doi.org/10.5194/acp-24-6275-2024, https://doi.org/10.5194/acp-24-6275-2024, 2024
Short summary
Short summary
This study presents the first explicit representation of brown carbon aerosols in the GISS ModelE Earth system model (ESM). Model sensitivity to a range of brown carbon parameters and model performance compared to AERONET and MODIS retrievals of total aerosol properties were assessed. A summary of best practices for incorporating brown carbon into ModelE is also included.
Chuanyang Shen, Xiaoyan Yang, Joel Thornton, John Shilling, Chenyang Bi, Gabriel Isaacman-VanWertz, and Haofei Zhang
Atmos. Chem. Phys., 24, 6153–6175, https://doi.org/10.5194/acp-24-6153-2024, https://doi.org/10.5194/acp-24-6153-2024, 2024
Short summary
Short summary
In this work, a condensed multiphase isoprene oxidation mechanism was developed to simulate isoprene SOA formation from chamber and field studies. Our results show that the measured isoprene SOA mass concentrations can be reasonably reproduced. The simulation results indicate that multifunctional low-volatility products contribute significantly to total isoprene SOA. Our findings emphasize that the pathways to produce these low-volatility species should be considered in models.
Alice Maison, Lya Lugon, Soo-Jin Park, Alexia Baudic, Christopher Cantrell, Florian Couvidat, Barbara D'Anna, Claudia Di Biagio, Aline Gratien, Valérie Gros, Carmen Kalalian, Julien Kammer, Vincent Michoud, Jean-Eudes Petit, Marwa Shahin, Leila Simon, Myrto Valari, Jérémy Vigneron, Andrée Tuzet, and Karine Sartelet
Atmos. Chem. Phys., 24, 6011–6046, https://doi.org/10.5194/acp-24-6011-2024, https://doi.org/10.5194/acp-24-6011-2024, 2024
Short summary
Short summary
This study presents the development of a bottom-up inventory of urban tree biogenic emissions. Emissions are computed for each tree based on their location and characteristics and are integrated in the regional air quality model WRF-CHIMERE. The impact of these biogenic emissions on air quality is quantified for June–July 2022. Over Paris city, urban trees increase the concentrations of particulate organic matter by 4.6 %, of PM2.5 by 0.6 %, and of ozone by 1.0 % on average over 2 months.
Tommaso Galeazzo, Bernard Aumont, Marie Camredon, Richard Valorso, Yong B. Lim, Paul J. Ziemann, and Manabu Shiraiwa
Atmos. Chem. Phys., 24, 5549–5565, https://doi.org/10.5194/acp-24-5549-2024, https://doi.org/10.5194/acp-24-5549-2024, 2024
Short summary
Short summary
Secondary organic aerosol (SOA) derived from n-alkanes is a major component of anthropogenic particulate matter. We provide an analysis of n-alkane SOA by chemistry modeling, machine learning, and laboratory experiments, showing that n-alkane SOA adopts low-viscous semi-solid or liquid states. Our results indicate few kinetic limitations of mass accommodation in SOA formation, supporting the application of equilibrium partitioning for simulating n-alkane SOA in large-scale atmospheric models.
Cited articles
Appel, K. W., Bhave, P. V., Gilliland, A. B., Sarwar, G., and Roselle, S. J.: Evaluation of the community multiscale air quality (CMAQ) model version 4.5: Sensitivities impacting model performance; Part II – particulate matter, Atmos. Environ., 42, 6057–6066, 2008.
Appel, K. W., Pouliot, G. A., Simon, H., Sarwar, G., Pye, H. O. T., Napelenok, S. L., Akhtar, F., and Roselle, S. J.: Evaluation of dust and trace metal estimates from the Community Multiscale Air Quality (CMAQ) model version 5.0, Geosci. Model Dev., 6, 883–899, https://doi.org/10.5194/gmd-6-883-2013, 2013.
Baek, J.: Improving aerosol simulations: Assessing and improving emissions and secondary organic aerosol formation in air quality modeling, 140 pp., Georgia Institute of Tecnology, Atlanta, GA, Ph.D. Dissertation, 2009.
Balachandran, S., Pachon, J. E., Hu, Y., Lee, D., Mulholland, J. A., and Russell, A. G.: Ensemble-trained source apportionment of fine particulate matter and method uncertainty analysis, Atmos. Environ., 61, 387–394, 2012.
Binkowski, F. S. and Roselle, S. J.: Models-3 Community Multi-scale Air Quality (CMAQ) model aerosol component: 1. Model description, J. Geophys. Res., 108, 4183, https://doi.org/10.1029/2001JD001409, 2003.
Blanchard, C. L., Tanenbaum, S., and Hidy, G. M.: Source Contributions to Atmospheric Gases and Particulate Matter in the Southeastern United States, Environ. Sci. Technol., 46, 5479–5488, 2012.
Boylan, J. W. and Russell, A. G.: PM and light extinction model performance metrics, goals, and criteria for three-dimensional air quality models, Atmos. Environ., 40, 4946–4959, 2006.
Boylan, J. W., Odman, M. T., Wilkinson, J. G., Russell, A. G., Doty, K. G., Norris, W. B., and McNider, R. T.: Development of a comprehensive, multiscale "one-atmosphere" modeling system: application to the Southern Appalachian Mountains, Atmos. Environ., 36, 3721–3734, 2002.
Boylan, J. W., Odman, M. T., Wilkinson, J. G., and Russell, A. G.: Integrated assessment modeling of atmospheric pollutants in the Southern Appalachian Mountains: Part II – PM2.5 and visibility, J. Air Waste Manage., 56, 12–22, 2006.
Bullock, K. R., Duvall, R. M., Norris, G. A., McDow, S. R., and Hays, M. D.: Evaluation of the CMB and PMF models using organic molecular markers in fine particulate matter collected during the Pittsburgh Air Quality Study, Atmos. Environ., 42, 6897–6904, 2008.
Burr, M. J. and Zhang, Y.: Source apportionment of fine particulate matter over the Eastern U.S. Part II: source apportionment simulations using CAMx/PSAT and comparisons with CMAQ source sensitivity simulations, Atmospheric Pollution Research, 2, 318–336, https://doi.org/10.5094/APR.2011.037, 2011a.
Burr, M. J. and Zhang, Y.: Source apportionment of fine particulate matter over the Eastern U.S. Part I: source sensitivity simulations using CMAQ with the Brute Force method, Atmospheric Pollution Research, 2, 300–317, https://doi.org/10.5094/APR.2011.036, 2011b.
Byun, D. and Schere, K. L.: Review of the Governing Equations, Computational Algorithms, and Other Components of the Models-3 Community Multiscale Air Quality (CMAQ) Modeling System, Appl. Mech. Rev., 59, 51–77, 2006.
Carter, W. P. L.: Documentation of the SAPRC-99 Chemical Mechanism for VOC Reactivity Assessment, Contract No. 92-329 and 95-308, California Air Resources Board, 2000.
CEP: Sparse Matrix Operator Kernel Emissions Modeling System (SMOKE) User Manual, Carolina Environmental Program – The University of North Carolina at Chapel Hill, Chapel Hill, NC, 2003.
Chang, W. L., Bhave, P. V., Brown, S. S., Riemer, N., Stutz, J., and Dabdub, D.: Heterogeneous Atmospheric Chemistry, Ambient Measurements, and Model Calculations of N2O5: A Review, Aerosol Sci. Tech., 45, 665–695, 2011.
Chen, L. W. A., Watson, J. G., Chow, J. C., DuBois, D. W., and Herschberger, L.: Chemical mass balance source apportionment for combined PM2.5 measurements from U.S. non-urban and urban long-term networks, Atmos. Environ., 44, 4908–4918, 2010.
Chen, L. W. A., Watson, J. G., Chow, J. C., DuBois, D. W., and Herschberger, L.: PM2.5 Source Apportionment: Reconciling Receptor Models for US Nonurban and Urban Long-Term Networks, J. Air Waste Manage., 61, 1204–1217, 2011.
Chow, J. C., Watson, J. G., Lowenthal, D. H., Solomon, P. A., Magliano, K. L., Ziman, S. D., and Richards, L. W.: PM10 Source Apportionment in California San-Joaquin Valley, Atmos. Environ. A-Gen., 26, 3335–3354, 1992.
Chow, J. C., Watson, J. G., Lowenthal, D. H., Chen, L. W. A., Zielinska, B., Mazzoleni, L. R., and Magliano, K. L.: Evaluation of organic markers for chemical mass balance source apportionment at the Fresno Supersite, Atmos. Chem. Phys., 7, 1741–1754, https://doi.org/10.5194/acp-7-1741-2007, 2007.
Cohan, D. S., Hakami, A., Hu, Y., and Russell, A. G.: Nonlinear response of ozone to emissions: source apportionment and sensitivity analysis, Environ. Sci. Technol., 39, 6739–6748, 2005.
Cooper, J. A. and Watson, J. G.: Reseptor Oriented Methods of Air Particulate Source Apportionment, JAPCA J. Air Waste Ma., 30, 1116–1125, 1980.
Coutant, B. W., Holloman, C. H., Swinton, K. E., and Hafner, H. R.: Eight-Site Source Apportionment of PM2.5 Speciation Trend Data, EPA Contract No. 68-D-02-061, Work Assignment 1-05, 2003.
Dockery, D. W., Pope, C. A., Xu, X., Spengler, J. D., Ware, J. H., Fay, M. E., Ferris, B. G., and Speizer, F. E.: An Association between Air Pollution and Mortality in Six U.S. Cities, The New England Journal of Medicine, 329, 24, 1753–1759, 1993.
Doraiswamy, P., Davis, W. T., Miller, T. L., and Fu, J. S.: Source apportionment of fine particles in Tennessee using a source-oriented model, J. Air Waste Manage., 57, 407–419, 2007.
Dunker, A. M.: Efficient Calculation of Sensitivity Coefficients for Complex Atmospheric Models, Atmos. Environ., 15, 1155–1161, 1981.
Dunker, A. M.: The Decoupled Direct Method for Calculating Sensitivity Coefficients in Chemical-Kinetics, J. Chem. Phys., 81, 2385–2393, 1984.
Dunker, A. M., Yarwood, G., Ortmann, J. P., and Wilson, G. M.: Comparison of source apportionment and source sensitivity of ozone in a three-dimensional air quality model, Environ. Sci. Technol., 36, 2953–2964, 2002.
Emery, C., Tai, E., and Yarwood, G.: Enhanced meteorological modeling and performance evaluation for two Texas ozone episodes, Prepared for the Texas Natural Resource Conservation Commissions, ENVIRON International Corporation, Novato, CA, 2001.
Gildemeister, A. E., Hopke, P. K., and Kim, E.: Sources of fine urban particulate matter in Detroit, MI, Chemosphere, 69, 1064–1074, 2007.
Grell, G., Dudhia, J., and Stauffer, D.: A description of the Fifth-Generation Penn State/NCAR Mesoscale Model (MM5), NCAR/TN 398+STR, NCAR Technical Note: NCAR/TN-398+STR, 1994.
Hakami, A., Odman, M. T., and Russell, A. G.: Nonlinearity in atmospheric response: A direct sensitivity analysis approach, J. Geophys. Res.-Atmos., 109, D15303, https://doi.org/10.1029/2003JD004502, 2004.
Hanna, S., Chang, J., and Fernau, M.: Monte Carlo estimates of uncertainties in predictions by a photochemical grid model (UAM-IV) due to uncertainties in input variables, Atmos. Environ., 32, 3619–3628, 1998.
Hanna, S. R. and Yang, R.: Evaluations of mesoscale models' simulations of near-surface winds, temperature gradients, and mixing depths, J. Appl. Meteorol., 40, 1095–1104, 2001.
Hanna, S. R., Lu, Z., Frey, H. C., Wheeler, N., Vukovich, J., Arumachalam, S., and Fernau, M. E.: Uncertainties in predicted ozone concentration due to input uncertainties for the UAM-V photochemical grid model applied to the July 1995 OTAG domain, Atmos. Environ., 35, 891–903, 2001.
Hanna, S. R., Russell, A. G., Wilkinson, J., Vukovich, J., and Hansen, D. A.: Monte Carlo estimation of uncertainties in BEIS3 emission outputs and their effects on uncertainties in Chemical Transport Model predictions, J. Geophys. Res., 110, D01302, https://doi.org/10.01029/2004JD004986, 2005.
Held, T., Ying, Q., Kleeman, M. J., Schauer, J. J., and Fraser, M. P.: A comparison of the UCD/CIT air quality model and the CMB source-receptor model for primary airborne particulate matter, Atmos. Environ., 39, 2281–2297, 2005.
Henze, D. K., Seinfeld, J. H., and Shindell, D. T.: Inverse modeling and mapping US air quality influences of inorganic PM2.5 precursor emissions using the adjoint of GEOS-Chem, Atmos. Chem. Phys., 9, 5877–5903, https://doi.org/10.5194/acp-9-5877-2009, 2009.
Herndon, S. C., Jayne, J. T., Lobo, P., Onasch, T. B., Fleming, G., Hagen, D. E., Whitefield, P. D., and Miake-Lye, R. C.: Commercial aircraft engine emissions characterization of in-use aircraft at Hartsfield-Jackson Atlanta International Airport, Environ. Sci. Technol., 42, 1877–1883, 2008.
Hu, Y., Odman, M. T., and Russell, A. G.: Mass conservation in the Community Multiscale Air Quality model, Atmos. Environ., 40, 1199–1204, 2006.
Kleeman, M. J., Ying, Q., Lu, J., Mysliwiec, M. J., Griffin, R. J., Chen, J. J., and Clegg, S.: Source apportionment of secondary organic aerosol during a severe photochemical smog episode, Atmos. Environ., 41, 576–591, 2007.
Koo, B., Wilson, G. M., Morris, R. E., Dunker, A. M., and Yarwood, G.: Comparison of Source Apportionment and Sensitivity Analysis in a Particulate Matter Air Quality Model, Environ. Sci. Technol., 43, 6669–6675, 2009.
Kraft, D.: A software package for sequential quadratic programming, Technical Report DFVLR-FB 88-28, Institut für Dynamik der Flugsysteme, Oberpfaffenhofen, July, 1988.
Kraft, D.: Algorithm 733: TOMP–Fortran modules for optimal control calculations, ACM T. Math. Software, 20, 262–281, 1994.
Kwok, R. H. F., Napelenok, S. L., and Baker, K. R.: Implementation and evaluation of PM2.5 source contribution analysis in a photochemical model, Atmos. Environ., 80, 398–407, 2013
Laupsa, H., Denby, B., Larssen, S., and Schaug, J.: Source apportionment of particulate matter (PM2.5) in an urban area using dispersion, receptor and inverse modelling, Atmos. Environ., 43, 4733–4744, 2009.
Lee, B. H., Wood, E. C., Miake-Lye, R. C., Herndon, S. C., Munger, J. W., and Wofsy, S. C.: Reactive Chemistry in Aircraft Exhaust Implications for Air Quality, Transp. Res. Record, 2206, 19–23, 2011.
Lee, D., Balachandran, S., Pachon, J., Shankaran, R., Lee, S., Mulholland, J. A., and Russell, A. G.: Ensemble-Trained PM2.5 Source Apportionment Approach for Health Studies, Environ. Sci. Technol., 43, 7023–7031, 2009.
Lee, S. and Russell, A. G.: Estimating uncertainties and uncertainty contributors of CMB PM2.5 source apportionment results, Atmos. Environ., 41, 9616–9624, 2007.
Lee, S., Liu, W., Wang, Y. H., Russell, A. G., and Edgerton, E. S.: Source apportionment of PM2.5: Comparing PMF and CMB results for four ambient monitoriniz sites in the southeastern United States, Atmos. Environ., 42, 4126–4137, 2008.
Lin, C. and Milford, J. B.: Decay-Adjusted Chemical Mass-Balance Receptor Modeling for Volatile Organic-Compounds, Atmos. Environ., 28, 3261–3276, 1994.
Liu, D. C. and Nocedal, J.: On the Limited Memory Method for Large Scale Optimization, Mathematical Programming B, 45, 503–528, 1989.
Liu, W., Wang, Y. H., Russell, A., and Edgerton, E. S.: Enhanced source identification of southeast aerosols using temperature-resolved carbon fractions and gas phase components, Atmos. Environ., 40, S445–S466, 2006.
Lowenthal, D. H., Watson, J. G., Koracin, D., Chen, L. W. A., Dubois, D., Vellore, R., Kumar, N., Knipping, E. M., Wheeler, N., Craig, K., and Reid, S.: Evaluation of Regional-Scale Receptor Modeling, J. Air Waste Manage., 60, 26–42, 2010.
Malm, W. C., Schichtel, B. A., and Pitchford, M. L.: Uncertainties in PM2.5 gravimetric and speciation measurements and what we can learn from them, J. Air Waste Manage., 61, 1131–1149, 2011.
Maranche, J.: Allegheny County PM2.5 Source Apportionment Results using the Positive Matrix Factorization Model, Allegheny County Health Department, Pittsburgh, PA (http://www.achd.net/airqual/pubs/pdf/pmf0106.pdf), 2006.
Marmur, A., Unal, A., Mulholland, J. A., and Russell, A. G.: Optimization-based source apportionment of PM2.5 incorporating gas-to-particle ratios, Environ. Sci. Technol., 39, 3245–3254, 2005.
Marmur, A., Park, S. K., Mulholland, J. A., Tolbert, P. E., and Russell, A. G.: Source apportionment of PM2.5 in the southeastern United States using receptor and emissions-based models: Conceptual differences and implications for time-series health studies, Atmos. Environ., 40, 2533–2551, 2006.
Marmur, A., Mulholland, J. A., and Russell, A. G.: Optimized variable source-profile approach for source apportionment, Atmos. Environ., 41, 493–505, 2007.
Martello, D. V., Pekney, N. J., Anderson, R. R., Davidson, C. I., Hopke, P. K., Kim, E., Christensen, W. F., Mangelson, N. F., and Eatough, D. J.: Apportionment of ambient primary and secondary fine particulate matter at the Pittsburgh National Energy Laboratory particulate matter characterization site using positive matrix factorization and a potential source contributions function analysis, J. Air Waste Manage., 58, 357–368, 2008.
Martin, D., Petersson, K. F., and Shallcross, D. E.: The use of cyclic perfluoroalkanes and SF6 in atmospheric dispersion experiments, Q. J. Ror. Meteor. Soc., 137, 2047–2063, 2011.
Napelenok, S. L., Cohan, D., Hu, Y., and Russell, A. G.: Decoupled Direct 3D Sensitivity Analysis For Particulate Matter (DDM-3D/PM), Atmos. Environ., 40, 6112–6121, 2006.
Nocedal, J.: Updating Quasi-Newton Matrices with Limited Storage, Math. Comput., 35, 773-782, 1980.
Pattero, P. and Tapper, U.: Positive Matrix Factorization – a Nonnegative Factor Model with Optimal Utilization of Error-Estimates of Data Values, Environmetrics, 5, 111–126, 1994.
Pham, T.-L., Kim, B. M., Katzenstein, A., and Goss, T.: PM2.5 Source Apportionment for the South Coast Air Basin Using Chemical Mass Balance Receptor Model, MATES III Final Report, available at: http://www.aqmd.gov/prdas/matesIII/Final/Appendices/g-MATESIIIAppendixVIIFinal92008.pdf (last access: 16 May 2013), 2008.
Pleim, J. E. and Xiu, A.: Development and testing of a surface flux and planetary boundary layer model with explicit soil moisture parameterization for application in mesoscale models, J. Appl. Meteorol., 34, 16–32, 1995.
Reff, A., Eberly, S. I., and Bhave, P. V.: Receptor modeling of ambient particulate matter data using positive matrix factorization: Review of existing methods, J. Air Waste Manage., 57, 146–154, 2007.
Reff, A., Bhave, P. V., Simon, H., Pace, T. G., Pouliot, G. A., Mobley, J. D., and Houyoux, M.: Emissions Inventory of PM2.5 Trace Elements across the United States, Environ. Sci. Technol., 43, 5790–5796, 2009.
Rizzo, M. J., and Scheff, P. A.: Fine particulate source apportionment using data from the USEPA speciation trends network in Chicago, Illinois: Comparison of two source apportionment models, Atmos. Environ., 41, 6276–6288, 2007.
Roy, A. A., Wagstrom, K. M., Adams, P. J., Pandis, S. N., and Robinson, A. L.: Quantification of the effects of molecular marker oxidation on source apportionment estimates for motor vehicles, Atmos. Environ., 45, 3132–3140, 2011.
Russell, A. G.: EPA Supersites Program-related emissions-based particulate matter modeling: Initial applications and advances, J. Air Waste Manage., 58, 289–302, 2008.
Schauer, J. J., Rogge, W. F., Hildemann, L. M., Mazurek, M. A., and Cass, G. R.: Source apportionment of airborne particulate matter using organic compounds as tracers, Atmos. Environ., 30, 3837–3855, 1996.
Schichtel, B. A., Malm, W. C., Gebhart, K. A., Barna, M. G., and Knipping, E. M.: A hybrid source apportionment model integrating measured data and air quality model results, J. Geophys. Res.-Atmos., 111, D07301, https://doi.org/10.1029/2005JD006238, 2006.
Sheesley, R. J., Schauer, J. J., Zheng, M., and Wang, B.: Sensitivity of molecular marker-based CMB models to biomass burning source profiles, Atmos. Environ., 41, 9050–9063, 2007.
Shi, G. L., Li, X., Feng, Y. C., Wang, Y. Q., Wu, J. H., Li, J., and Zhu, T.: Combined source apportionment, using positive matrix factorization-chemical mass balance and principal component analysis/multiple linear regression-chemical mass balance models, Atmos. Environ., 43, 2929–2937, 2009.
Simon, H., Beck, L., Bhave, P. V., Divita, F., Hsu, Y., Luecken, D., Mobley, J. D., Pouliot, G. A., Reff, A., Sarwar, G., and Strum, M.: The development and uses of EPA's SPECIATE database, Atmospheric Pollution Research, 1, 196–206, 2010.
Simon, H., Baker, K. R., and Phillips, S.: Compilation and interpretation of photochemical model performance statistics published between 2006 and 2012, Atmos. Environ., 61, 124–139, 2012.
Subramanian, R., Donahue, N. M., Bernardo-Bricker, A., Rogge, W. F., and Robinson, A. L.: Contribution of motor vehicle emissions to organic carbon and fine particle mass in Pittsburgh, Pennsylvania: Effects of varying source profiles and seasonal trends in ambient marker concentrations, Atmos. Environ., 40, 8002–8019, 2006.
Subramanian, R., Donahue, N. M., Bernardo-Bricker, A., Rogge, W. F., and Robinson, A. L.: Insights into the primary-secondary and regional-local contributions to organic aerosol and PM2.5 mass in Pittsburgh, Pennsylvania, Atmos. Environ., 41, 7414–7433, 2007.
Swietlicki, E., Puri, S., Hansson, H. C., and Edner, H.: Urban air pollution source apportionment using a combination of aerosol and gas monitoring techniques, Atmos. Environ., 30, 2795–2809, 1996.
Tesche, T. W., Morris, R., Tonnesen, G., McNally, D., Boylan, J., and Brewer, P.: CMAQ/CAMx annual 2002 performance evaluation over the eastern US, Atmos. Environ., 40, 4906–4919, 2006.
Thurston, G. D., Ito, K., and Lall, R.: A source apportionment of U.S. fine particulate matter air pollution, Atmos. Environ., 45, 3924–3936, 2011.
Tian, D., Hu, Y., Wang, Y., Boylan, J., Zheng, M., and Russell, A. G.: Assessment of Biomass Burning Emissions and Their Impacts on Urban and Regional PM2.5: A Georgia Case Study, Environ. Sci. Technol., 43, 299–305, https://doi.org/210.1021/es801827s, 2009.
Unal, A., Hu, Y. T., Chang, M. E., Odman, M. T., and Russell, A. G.: Airport related emissions and impacts on air quality: Application to the Atlanta International Airport, Atmos. Environ., 39, 5787–5798, 2005.
USEPA: Protocol for Applying and Validating the CMB Model for PM2.5 and VOC, Report Number EPA-451/R-04-001, U.S. Environmental Protection Agency, Research Triangle Park, NC, 2004.
Viana, M., Pandolfi, M., Minguillon, M. C., Querol, X., Alastuey, A., Monfort, E., and Celades, I.: Inter-comparison of receptor models for PM source apportionment: Case study in an industrial area, Atmos. Environ., 42, 3820–3832, 2008a.
Viana, M., Kuhlbusch, T. A. J., Querol, X., Alastuey, A., Harrison, R. M., Hopke, P. K., Winiwarter, W., Vallius, A., Szidat, S., Prevot, A. S. H., Hueglin, C., Bloemen, H., Wahlin, P., Vecchi, R., Miranda, A. I., Kasper-Giebl, A., Maenhaut, W., and Hitzenberger, R.: Source apportionment of particulate matter in Europe: A review of methods and results, J. Aerosol Sci., 39, 827–849, 2008b.
Wagstrom, K. M., Pandis, S. N., Yarwood, G., Wilson, G. M., and Morris, R. E.: Development and application of a computationally efficient particulate matter apportionment algorithm in a three-dimensional chemical transport model, Atmos. Environ., 42, 5650–5659, 2008.
Wang, Z. S., Chien, C. J., and Tonnesen, G. S.: Development of a tagged species source apportionment algorithm to characterize three-dimensional transport and transformation of precursors and secondary pollutants, J. Geophys. Res.-Atmos., 114, D21206, https://doi.org/ 10.1029/2008JD010846, 2009.
Watson, J. G.: Overview of Receptor Model Principles, J. Air Pollut. Control Assoc., 34, 619–623, 1984.
Watson, J. G., Cooper, J. A., and Huntzicker, J. J.: The Effective Variance Weighting for Least-Squares Calculations Applied to the Mass Balance Receptor Model, Atmos. Environ., 18, 1347–1355, 1984.
Watson, J. G., Chen, L. W. A., Chow, J. C., Doraiswamy, P., and Lowenthal, D. H.: Source apportionment: Findings from the US Supersites program, J. Air Waste Manage., 58, 265–288, 2008.
Watson, J. G., Chow, J. C., Lowenthal, D. H., Robinson, N. F., Cahill, C. F., and Blumenthal, D. L.: Simulating changes in source profiles from coal-fired power stations: Use in chemical mass balance of PM2.5 in the Mount Zirkel Wilderness, Energy & Fuels, 16, 311–324, 2002.
Wittig, A. E. and Allen, D. T.: Improvement of the Chemical Mass Balance model for apportioning – sources of non-methane hydrocarbons using composite aged source profiles, Atmos. Environ., 42, 1319–1337, 2008.
Xie, M. J., Piedrahita, R., Dutton, S. J., Milford, J. B., Hemann, J. G., Peel, J. L., Miller, S. L., Kim, S. Y., Vedal, S., Sheppard, L., and Hannigan, M. P.: Positive matrix factorization of a 32-month series of daily PM2.5 speciation data with incorporation of temperature stratification, Atmos. Environ., 65, 11–20, 2013.
Xiu, A. and Pleim, J. E.: Development and application of a land-surface model. I: Application in a mesoscale meteorology model, J. Appl. Meteorol., 40, 192–209, 2001.
Yang, Y.-J., Wilkinson, J., and Russell, A. G.: Fast, direct sensitivity analysis of multidimensional photochemical models, Environ. Sci. Technol. 31, 2859–2868, 1997.
Ying, Q., Lu, J., Kaduwela, A., and Kleeman, M.: Modeling air quality during the California Regional PM10/PM2.5 Air Quality Study (CPRAQS) using the UCD/CIT Source Oriented Air Quality Model - Part II. Regional source apportionment of primary airborne particulate matter, Atmos. Environ., 42, 8967–8978, 2008.
Zhang, W., Capps, S. L., Hu, Y., Nenes, A., Napelenok, S. L., and Russell, A. G.: Development of the high-order decoupled direct method in three dimensions for particulate matter: enabling advanced sensitivity analysis in air quality models, Geosci. Model Dev., 5, 355–368, https://doi.org/10.5194/gmd-5-355-2012, 2012.
Zheng, M., Cass, G. R., Schauer, J. J., and Edgerton, E. S.: Source apportionment of PM2.5 in the southeastern United States using solvent-extractable organic compounds as tracers, Environ. Sci. Technol., 36, 2361–2371, 2002.
Altmetrics
Final-revised paper
Preprint