Atmosphere

19 pages, 13416 KiB

Open AccessArticle

Unveiling PM_2.5 Transport Pathways: A Trajectory-Channel Model Framework for Spatiotemporally Quantitative Source Apportionment

by Yong Pan, Jie Zheng, Fangxin Fang, Fanghui Liang, Mengrong Yang, Lei Tong and Hang Xiao

Atmosphere 2025, 16(7), 883; https://doi.org/10.3390/atmos16070883 - 18 Jul 2025

Abstract

In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM_2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory [...] Read more.

In this study, we introduced a novel Trajectory-Channel Transport Model (TCTM) to unravel spatiotemporal dynamics of PM_2.5 pollution. By integrating high-resolution simulations from the Weather Research and Forecasting (WRF) model with the Nested Air-Quality Prediction Modeling System (WRF-NAQPMS) and 72 h backward-trajectory analysis, TCTM enables the precise identification of source regions, the delineation of key transport corridors, and a quantitative assessment of regional contributions to receptor sites. Focusing on four Yangtze River Delta cities (Hangzhou, Shanghai, Nanjing, Hefei) during a January 2020 pollution event, the results demonstrate that TCTM’s Weighted Concentration Source (WCS) and Source Pollution Characteristic Index (SPCI) outperform traditional PSCF and CWT methods in source-attribution accuracy and resolution. Unlike receptor-based statistical approaches, TCTM reconstructs pollutant transport processes, quantifies spatial decay, and assigns contributions via physically interpretable metrics. This innovative framework offers actionable insights for targeted air-quality management strategies, highlighting its potential as a robust tool for pollution mitigation planning. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

12 pages, 805 KiB

Open AccessArticle

Occurrence and Mitigation of PM_2.5, NO₂, CO and CO₂ in Homes Due to Cooking and Gas Stoves

by Daniel Jaffe, Devon Nirschl and Stephanie Birman

Atmosphere 2025, 16(7), 882; https://doi.org/10.3390/atmos16070882 - 18 Jul 2025

Abstract

We surveyed the air quality conditions in 18 homes with gas stoves for PM_2.5, CO₂, NO₂ and CO using calibrated low-cost sensors. In each home, participants were asked to cook as usual, but to record their cooking activities [...] Read more.

We surveyed the air quality conditions in 18 homes with gas stoves for PM_2.5, CO₂, NO₂ and CO using calibrated low-cost sensors. In each home, participants were asked to cook as usual, but to record their cooking activities and mitigation efforts (windows, ventilation fans, etc.). All homes showed enhanced pollutants during, and immediately after, times of cooking or stove use. For each home, we quantified the minutes per day and minutes per minute of cooking over known health thresholds for each pollutant. On average, homes exhibited 38 min per day over one or more of these thresholds, with PM_2.5 and NO₂ being the pollutants of greatest concern. Six homes had much higher occurrences over the health thresholds, averaging 73 min per day. We found an average of 1.0 min over one or more of the health thresholds per minute of cooking when no mitigation was used, whereas when mitigation was used (filtration or vent fan), this value was reduced by 34%. We further investigated several mitigation methods including natural diffusion, a commercial HEPA filter unit, a commercial O₃ scrubber and a ventilation fan. We found that the HEPA unit was highly effective for PM_2.5 but had no impact on any of the gaseous pollutants. The O₃ scrubber was moderately effective for NO₂ but had little impact on the other pollutants. The ventilation fan was highly effective for all pollutants and reduced the average pollutant lifetime significantly. Under controlled test conditions, the pollutant lifetime (or time to reach 37% of the original concentration), was reduced from an average of 45 min (with no ventilation) to 7 min. While no commercial filter showed efficacy for both PM_2.5 and NO₂, the fact that each could be removed individually suggests that a combined filter for both pollutants could be developed, which would significantly reduce health impacts in homes with gas stoves. Full article

(This article belongs to the Special Issue Indoor Air Pollution: A Silent Threat to Human Health and the Atmosphere)

16 pages, 1939 KiB

Open AccessArticle

Exploring the Explainability of a Machine Learning Tool to Improve Severe Thunderstorm Wind Reports

by Elizabeth Tirone, William A. Gallus, Jr. and Alexander J. Hamilton

Atmosphere 2025, 16(7), 881; https://doi.org/10.3390/atmos16070881 - 18 Jul 2025

Abstract

Output from a machine learning tool that assigns a probability that a severe thunderstorm wind report was caused by severe intensity wind was evaluated to understand counterintuitive cases where reports that had a high (low) wind speed received a low (high) diagnosed probability. [...] Read more.

Output from a machine learning tool that assigns a probability that a severe thunderstorm wind report was caused by severe intensity wind was evaluated to understand counterintuitive cases where reports that had a high (low) wind speed received a low (high) diagnosed probability. Meteorological data for these cases was compared to that for valid cases where the machine learning probability seemed consistent with the observed severity of the winds. The comparison revealed that the cases with high winds but low probabilities occurred in less conducive environments for severe wind production (less instability, greater low-level relative humidity, weaker lapse rates) than in the cases where high winds occurred with high probabilities. Cases with a low speed but a high probability had environmental characteristics that were more conducive to producing severe wind. These results suggest that the machine learning model is assigning probabilities based on storm modes that more often have measured severe wind speeds (i.e., clusters of cells and bow echoes), and counterintuitive values may reflect events where storm interactions or other smaller-scale features play a bigger role. In addition, some evidence suggests improper reporting may be common for some of these counterintuitive cases. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling (2nd Edition))

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22 pages, 37656 KiB

Open AccessArticle

Investigating Urban Heat Islands in Miami, Florida, Utilizing Planet and Landsat Satellite Data

by Suraj K C, Anuj Chiluwal, Lalit Pun Magar and Kabita Paudel

Atmosphere 2025, 16(7), 880; https://doi.org/10.3390/atmos16070880 - 18 Jul 2025

Abstract

Miami, Florida, renowned for its cultural richness and coastal beauty, also faces the concerning challenges created by urban heat islands (UHIs). As one of the hottest cities of the United States, Miami is facing escalating temperatures and threatening heat-related vulnerabilities due to urbanization [...] Read more.

Miami, Florida, renowned for its cultural richness and coastal beauty, also faces the concerning challenges created by urban heat islands (UHIs). As one of the hottest cities of the United States, Miami is facing escalating temperatures and threatening heat-related vulnerabilities due to urbanization and climate change. Our study addresses the critical issue of mapping and investigating UHIs in complex urban settings. This study leveraged Planet satellite data and Landsat data to conceptualize and develop appropriate mitigation strategies for UHIs in Miami. Utilizing the Planet satellite imagery and Landsat data, we conducted a combined study of land cover and land surface temperature variations within the city. This approach fuses remotely sensed data to identify the UHI hotspots. This study aims for dynamic approaches for UHI mitigation. This includes studying the status of green spaces present in the city, possible expansion of urban green spaces, the propagation of cool roof initiatives, and exploring the recent climatic trend of the city. The research revealed that built-up areas consistently showed higher land surface temperatures while zones with dense vegetation have lower surface temperatures, supporting the role of urban green spaces in surface temperature reduction. This research can also set a robust model for addressing UHIs in other cities facing rapid urbanization and experiencing mounting temperatures each passing year by helping in assessing LST, land cover, and related spectral indices as well. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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40 pages, 4708 KiB

Open AccessArticle

New Challenges for Tropical Cyclone Track and Intensity Forecasting in an Unfavorable External Environment in the Western North Pacific—Part II: Intensifications near and North of 20° N

by Russell L. Elsberry, Hsiao-Chung Tsai, Wen-Hsin Huang and Timothy P. Marchok

Atmosphere 2025, 16(7), 879; https://doi.org/10.3390/atmos16070879 - 17 Jul 2025

Abstract

Part I of this two-part documentation of the ECMWF ensemble (ECEPS) new tropical cyclone track and intensity forecasting challenges during the 2024 western North Pacific season described four typhoons that started well to the south of an unfavorable external environment north of 20° [...] Read more.

Part I of this two-part documentation of the ECMWF ensemble (ECEPS) new tropical cyclone track and intensity forecasting challenges during the 2024 western North Pacific season described four typhoons that started well to the south of an unfavorable external environment north of 20° N. In this Part II, five other 2024 season typhoons that formed and intensified near and north of 20° N are documented. One change is that the Cooperative Institute for Meteorological Satellite Studies ADT + AIDT intensities derived from the Himawari-9 satellite were utilized for initialization and validation of the ECEPS intensity forecasts. Our first objective of providing earlier track and intensity forecast guidance than the Joint Typhoon Warning Center (JTWC) five-day forecasts was achieved for all five typhoons, although the track forecast spread was large for the early forecasts. For Marie (06 W) and Ampil (08 W) that formed near 25° N, 140° E in the middle of the unfavorable external environment, the ECEPS intensity forecasts accurately predicted the ADT + AIDT intensities with the exception that the rapid intensification of Ampil over the Kuroshio ocean current was underpredicted. Shanshan (11 W) was a challenging forecast as it intensified to a typhoon while being quasi-stationary near 17° N, 142° E before turning to the north to cross 20° N into the unfavorable external environment. While the ECEPS provided accurate guidance as to the timing and the longitude of the 20° N crossing, the later recurvature near Japan timing was a day early and 4 degrees longitude to the east. The ECEPS provided early, accurate track forecasts of Jebi’s (19 W) threat to mainland Japan. However, the ECEPS was predicting extratropical transition with V_max ~35 kt when the JTWC was interpreting Jebi’s remnants as a tropical cyclone. The ECEPS predicted well the unusual southward track of Krathon (20 W) out of the unfavorable environment to intensify while quasi-stationary near 18.5° N, 125.6° E. However, the rapid intensification as Krathon moved westward along 20° N was underpredicted. Full article

(This article belongs to the Special Issue Typhoon/Hurricane Dynamics and Prediction (2nd Edition))

18 pages, 1457 KiB

Open AccessArticle

Atmospheric Concentration of Particulate Air Pollutants in the Context of Projected Future Emissions from Motor Vehicles

by Artur Jaworski, Hubert Kuszewski, Krzysztof Balawender and Bożena Babiarz

Atmosphere 2025, 16(7), 878; https://doi.org/10.3390/atmos16070878 - 17 Jul 2025

Abstract

Ambient PM concentrations are influenced by various emission sources and weather conditions such as temperature, wind speed, and direction. Measurements using optical sensors cannot directly link pollution levels to specific sources. Data from roadside monitoring often show that a significant portion of PM [...] Read more.

Ambient PM concentrations are influenced by various emission sources and weather conditions such as temperature, wind speed, and direction. Measurements using optical sensors cannot directly link pollution levels to specific sources. Data from roadside monitoring often show that a significant portion of PM originates from non-traffic sources. Therefore, vehicle-related PM emissions are typically estimated using simulation models based on average emission factors. This study uses the COPERT (Computer Programme to Calculate Emissions from Road Transport) model to estimate emissions from road vehicles under current conditions and future scenarios. These include the introduction of Euro 7 standards and a shift from internal combustion engine (ICE) vehicles to battery electric vehicles (BEVs). The analysis considers exhaust and non-exhaust emissions, as well as indirect emissions from electricity generation for BEV charging. The conducted study showed, among other findings, that replacing internal combustion engine vehicles with electric ones could reduce PM2.5 emissions by approximately 6% (2% when including indirect emissions from electricity generation) and PM10 emissions by about 10% (5% with indirect emissions), compared to the Euro 7 scenario. Full article

(This article belongs to the Section Air Quality)

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23 pages, 3620 KiB

Open AccessArticle

Temperature Prediction at Street Scale During a Heat Wave Using Random Forest

by Panagiotis Gkirmpas, George Tsegas, Denise Boehnke, Christos Vlachokostas and Nicolas Moussiopoulos

Atmosphere 2025, 16(7), 877; https://doi.org/10.3390/atmos16070877 - 17 Jul 2025

Abstract

The rising frequency of heatwaves, combined with the urban heat island effect, increases the population’s exposure to high temperatures, significantly impacting the health of vulnerable groups and the overall well-being of residents. While mesoscale meteorological models can reliably forecast temperatures across urban neighbourhoods, [...] Read more.

The rising frequency of heatwaves, combined with the urban heat island effect, increases the population’s exposure to high temperatures, significantly impacting the health of vulnerable groups and the overall well-being of residents. While mesoscale meteorological models can reliably forecast temperatures across urban neighbourhoods, dense networks of in situ measurements offer more precise data at the street scale. In this work, the Random Forest technique was used to predict street-scale temperatures in the downtown area of Thessaloniki, Greece, during a prolonged heatwave in July 2021. The model was trained using data from a low-cost sensor network, meteorological fields calculated by the mesoscale model MEMO, and micro-environmental spatial features. The results show that, although the MEMO temperature predictions achieve high accuracy during nighttime compared to measurements, they exhibit inconsistent trends across sensor locations during daytime, indicating that the model does not fully account for microclimatic phenomena. Additionally, by using only the observed temperature as the target of the Random Forest model, higher accuracy is achieved, but spatial features are not represented in the predictions. In contrast, the most reliable approach to incorporating spatial characteristics is to use the difference between observed and mesoscale temperatures as the target variable. Full article

(This article belongs to the Special Issue Urban Heat Islands, Global Warming and Effects)

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18 pages, 1268 KiB

Open AccessReview

Perspectives on the Presence of Environmentally Persistent Free Radicals (EPFRs) in Ambient Particulate Matters and Their Potential Implications for Health Risk

by Senlin Lu, Jiakuan Lu, Xudong Wang, Kai Xiao, Jingying Niuhe, Xinchun Liu and Shinichi Yonemochi

Atmosphere 2025, 16(7), 876; https://doi.org/10.3390/atmos16070876 - 17 Jul 2025

Abstract

Environmental persistent free radicals (EPFRs) represent a class of long-lived, redox-active species with half lives spanning minutes to months. Emerging as critical environmental pollutants, EPFRs pose significant risks due to their persistence, potential for bioaccumulation, and adverse effects on ecosystems and human health. [...] Read more.

Environmental persistent free radicals (EPFRs) represent a class of long-lived, redox-active species with half lives spanning minutes to months. Emerging as critical environmental pollutants, EPFRs pose significant risks due to their persistence, potential for bioaccumulation, and adverse effects on ecosystems and human health. This review critically synthesizes recent advancements in understanding EPFR formation mechanisms, analytical detection methodologies, environmental distribution patterns, and toxicological impacts. While progress has been made in characterization techniques, challenges persist—particularly in overcoming limitations of electron paramagnetic resonance (EPR) spectroscopy and spin-trapping methods in complex environmental matrices. Key knowledge gaps remain, including molecular-level dynamics of EPFR formation, long-term environmental fate under varying geochemical conditions, and quantitative relationships between chronic EPFR exposure and health outcomes. Future research priorities could focus on: (1) atomic-scale mechanistic investigations using advanced computational modeling to resolve formation pathways; (2) development of next-generation detection tools to improve sensitivity and spatial resolution; and (3) integration of EPFR data into region-specific air-quality indices to enhance risk assessment and inform mitigation strategies. Addressing these gaps will advance our capacity to mitigate EPFR persistence and safeguard environmental and public health. Full article

(This article belongs to the Special Issue Composition Analysis and Health Effects of Atmospheric Particulate Matter (2nd Edition))

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17 pages, 1837 KiB

Open AccessArticle

The Impact of Meteorological Variables on Particulate Matter Concentrations

by Amaury de Souza, José Francisco de Oliveira-Júnior, Kelvy Rosalvo Alencar Cardoso, Widinei A. Fernandes and Hamilton Germano Pavao

Atmosphere 2025, 16(7), 875; https://doi.org/10.3390/atmos16070875 - 17 Jul 2025

Abstract

This study assessed the influence of meteorological conditions on particulate matter (PM) concentrations in Campo Grande, Brazil, from May to December 2021. Using statistical analyses, including Pearson’s correlation coefficient and multivariate regression, we analyzed secondary data on PM2.5 and PM10 concentrations and meteorological [...] Read more.

This study assessed the influence of meteorological conditions on particulate matter (PM) concentrations in Campo Grande, Brazil, from May to December 2021. Using statistical analyses, including Pearson’s correlation coefficient and multivariate regression, we analyzed secondary data on PM2.5 and PM10 concentrations and meteorological variables from the Federal University of Mato Grosso do Sul’s Physics Department. Daily PM concentrations complied with Brazil’s National Ambient Air Quality Standards (PQAr). The PM2.5/PM10 ratios averaged 0.436 (hourly) and 0.442 (daily), indicating a mix of fine and coarse particles. Significant positive correlations were found with temperature, while relative humidity showed a negative correlation, reducing PM levels through deposition. Wind speed had no significant impact. Meteorological influences suggest that air quality management should be tailored to regional conditions, particularly addressing local emission sources like vehicular traffic and biomass burning. Full article

(This article belongs to the Special Issue Indoor Air Pollution Monitoring: Multi-Pollutant Exposure and Risk Assessment)

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15 pages, 3070 KiB

Open AccessArticle

Characteristics and Sources of VOCs During a Period of High Ozone Levels in Kunming, China

by Chuantao Huang, Yufei Ling, Yunbo Chen, Lei Tong, Yuan Xue, Chunli Liu, Hang Xiao and Cenyan Huang

Atmosphere 2025, 16(7), 874; https://doi.org/10.3390/atmos16070874 - 17 Jul 2025

Abstract

The increasing levels of ozone pollution have become a significant environmental issue in urban areas worldwide. Previous studies have confirmed that the urban ozone pollution in China is mainly controlled by volatile organic compounds (VOCs) rather than nitrogen oxides. Therefore, a study on [...] Read more.

The increasing levels of ozone pollution have become a significant environmental issue in urban areas worldwide. Previous studies have confirmed that the urban ozone pollution in China is mainly controlled by volatile organic compounds (VOCs) rather than nitrogen oxides. Therefore, a study on the emission characteristics and source analysis of VOCs is important for controlling urban ozone pollution. In this study, hourly concentrations of 57 VOC species in four groups were obtained in April 2022, a period of high ozone pollution in Kunming, China. The ozone formation potential analysis showed that the accumulated reactive VOCs significantly contributed to the subsequent ozone formation, particularly aromatics (44.16%) and alkanes (32.46%). In addition, the ozone production rate in Kunming is mainly controlled by VOCs based on the results of the empirical kinetic modeling approach (K_NOx/K_VOCs = 0.25). The hybrid single-particle Lagrangian integrated trajectory model and polar coordinate diagram showed high VOC and ozone concentrations from the southwest outside the province (50.28%) and the south in local areas (12.78%). Six factors were obtained from the positive matrix factorization model: vehicle exhaust (31.80%), liquefied petroleum gas usage (24.16%), the petrochemical industry (17.81%), fuel evaporation (11.79%), coal burning (7.47%), and solvent usage (6.97%). These findings underscore that reducing anthropogenic VOC emissions and strengthening controls on the related sources could provide a scientifically robust strategy for mitigating ozone pollution in Kunming. Full article

(This article belongs to the Section Air Quality)

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19 pages, 2337 KiB

Open AccessArticle

Gas–Particle Partitioning and Temporal Dynamics of Pesticides in Urban Atmosphere Adjacent to Agriculture

by Dani Khoury, Supansa Chimjarn, Olivier Delhomme and Maurice Millet

Atmosphere 2025, 16(7), 873; https://doi.org/10.3390/atmos16070873 - 17 Jul 2025

Abstract

Air pollution caused by pesticide residues is an emerging concern in urban environments influenced by nearby agricultural activities. In this study, weekly air samples were collected between May 2018 and March 2020 in Strasbourg, France, to quantify 104 pesticides in both gas and [...] Read more.

Air pollution caused by pesticide residues is an emerging concern in urban environments influenced by nearby agricultural activities. In this study, weekly air samples were collected between May 2018 and March 2020 in Strasbourg, France, to quantify 104 pesticides in both gas and particle phases using GC-MS/MS and LC-MS/MS. Herbicides and fungicides were the most frequently detected classes, appearing in 98% of both phases followed by insecticides. Key compounds such as metalaxyl-M, diphenylamine, and bifenthrin were present in over 90% of samples. Concentrations ranged from 2.5 to 63 ng m⁻³ weekly, with cumulative annual loads exceeding 1200 ng m⁻³. Gas–particle partitioning revealed that highly volatile compounds like azinphos-ethyl favored the gas phase, while less volatile ones like bifenthrin and tebuconazole partitioned >95% into particles. A third-degree polynomial regression (R² of 0.74) revealed a nonlinear relationship between Kₚ and particle-phase concentrations, highlighting a threshold above Kₚ of 0.025 beyond which compounds accumulate disproportionately in the particulate phase. Seasonal variability showed that 36% of the annual pesticide load occurred in autumn, with total airborne levels peaking near 400 ng m⁻³, while the lowest load occurred during summer. Principal component analysis identified rainfall and total suspended particles as major drivers of pesticide phase distribution. The inhalation health risk assessed yielded hazard index values < 1 × 10⁻⁷ for all population groups, suggesting negligible non-cancer risk. This study highlights the prevalence, seasonal dynamics, and partition behavior of airborne pesticides in urban air and underscores the need for regulatory attention to this overlooked exposure route. Full article

(This article belongs to the Section Air Quality)

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10 pages, 1640 KiB

Open AccessCommunication

Investigating the Effects of the Solar Eclipse on the Atmosphere over Land and Oceanic Regions: Observations from Ground Stations and COSMIC2 Data

by Ghouse Basha, M. Venkat Ratnam, Jonathan H. Jiang and Kishore Pangaluru

Atmosphere 2025, 16(7), 872; https://doi.org/10.3390/atmos16070872 - 17 Jul 2025

Abstract

The impacts of the solar eclipse that occurred on 8 April 2024 over the United States on various atmospheric parameters are investigated. We analyzed surface and vertical profiles of temperature and humidity to understand how this eclipse affected the atmosphere from the ground [...] Read more.

The impacts of the solar eclipse that occurred on 8 April 2024 over the United States on various atmospheric parameters are investigated. We analyzed surface and vertical profiles of temperature and humidity to understand how this eclipse affected the atmosphere from the ground to the stratosphere. Our findings show a significant response throughout the atmospheric range. The eclipse caused a decrease in shortwave radiation, leading to cooler Earth surfaces and a subsequent drop in surface temperature. This cooling effect also resulted in high relative humidity and lower wind speeds at the surface. Furthermore, GPS radio occultation data from COSMIC-2 revealed a decrease in tropospheric temperature and increase in stratospheric temperature during the eclipse. We also observed a reduction in both the temperature and height of the tropopause. The uniqueness of the present investigations lies in delineating the solar eclipse’s effects on the land and ocean. Our analysis indicates that land regions experienced a more pronounced temperature change compared to ocean regions. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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13 pages, 2743 KiB

Open AccessCommunication

Evaluating Air Pollution in South African Priority Areas: A Qualitative Comparison of Satellite and In-Situ Data

by Nasiphi Ngcoliso, Lerato Shikwambana, Zintle Mbulawa, Moleboheng Molefe and Mahlatse Kganyago

Atmosphere 2025, 16(7), 871; https://doi.org/10.3390/atmos16070871 - 17 Jul 2025

Abstract

Validating satellite data is essential to ensure its accuracy, reliability, and practical applicability. Such validation underpins scientific research, operational use, and informed policymaking by confirming that space-based measurements reflect real-world conditions. This is typically achieved by comparing satellite observations with ground-based measurements or [...] Read more.

Validating satellite data is essential to ensure its accuracy, reliability, and practical applicability. Such validation underpins scientific research, operational use, and informed policymaking by confirming that space-based measurements reflect real-world conditions. This is typically achieved by comparing satellite observations with ground-based measurements or established reference standards. Without thorough validation, data integrity is compromised, which can negatively affect decisions and economic outcomes. In this study, we validated data from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) by comparing it with ground-based measurements from the South African Air Quality Information System (SAAQIS). The analysis focused on three monitoring stations—Kliprivier, Lephalale, and Middelburg—over the course of 2022. The pollutants examined include sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO). The results indicate that CO was the predominant pollutant across all sites, particularly in industrial areas. The study also found that satellite data generally overestimated pollution levels, especially during the winter months, emphasizing the importance of robust ground-based validation. Additionally, data quality challenges such as gaps and temporal misalignments affected the accuracy of both satellite and ground datasets. Lastly, the study shows the discrepancy between the ground-based instruments in South Africa and the TROPOMI, and it suggests how these instruments can be incorporated to provide a better understanding of the air quality. Full article

(This article belongs to the Special Issue Study of Air Pollution Based on Remote Sensing (2nd Edition))

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23 pages, 2859 KiB

Open AccessArticle

Air Quality Prediction Using Neural Networks with Improved Particle Swarm Optimization

by Juxiang Zhu, Zhaoliang Zhang, Wei Gu, Chen Zhang, Jinghua Xu and Peng Li

Atmosphere 2025, 16(7), 870; https://doi.org/10.3390/atmos16070870 - 17 Jul 2025

Abstract

Accurate prediction of Air Quality Index (AQI) concentrations remains a critical challenge in environmental monitoring and public health management due to the complex nonlinear relationships among multiple atmospheric factors. To address this challenge, we propose a novel prediction model that integrates an adaptive-weight [...] Read more.

Accurate prediction of Air Quality Index (AQI) concentrations remains a critical challenge in environmental monitoring and public health management due to the complex nonlinear relationships among multiple atmospheric factors. To address this challenge, we propose a novel prediction model that integrates an adaptive-weight particle swarm optimization (AWPSO) algorithm with a back propagation neural network (BPNN). First, the random forest (RF) algorithm is used to scree the influencing factors of AQI concentration. Second, the inertia weights and learning factors of the standard PSO are improved to ensure the global search ability exhibited by the algorithm in the early stage and the ability to rapidly obtain the optimal solution in the later stage; we also introduce an adaptive variation algorithm in the particle search process to prevent the particles from being caught in local optima. Finally, the BPNN is optimized using the AWPSO algorithm, and the final values of the optimized particle iterations serve as the connection weights and thresholds of the BPNN. The experimental results show that the RFAWPSO-BP model reduces the root mean square error and mean absolute error by 9.17 μg/m³, 5.7 μg/m³, 2.66 μg/m³; and 9.12 μg/m³, 5.7 μg/m³, 2.68 μg/m³ compared with the BP, PSO-BP, and AWPSO-BP models, respectively; furthermore, the goodness of fit of the proposed model was 14.8%, 6.1%, and 2.3% higher than that of the aforementioned models, respectively, demonstrating good prediction accuracy. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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18 pages, 3353 KiB

Open AccessArticle

An Evaluation of a Novel Air Pollution Abatement System for Ammonia Emissions Reduction in a UK Livestock Building

by Andrea Pacino, Antonino La Rocca, Donata Magrin and Fabio Galatioto

Atmosphere 2025, 16(7), 869; https://doi.org/10.3390/atmos16070869 - 17 Jul 2025

Abstract

Agriculture and animal feeding operations are responsible for 87% of ammonia emissions in the UK. Controlling NH₃ concentrations below 20 ppm is crucial to preserve workers’ and livestock’s well-being. Therefore, ammonia control systems are required for maintaining adequate air quality in livestock [...] Read more.

Agriculture and animal feeding operations are responsible for 87% of ammonia emissions in the UK. Controlling NH₃ concentrations below 20 ppm is crucial to preserve workers’ and livestock’s well-being. Therefore, ammonia control systems are required for maintaining adequate air quality in livestock facilities. This study assessed the ammonia reduction efficiency of a novel air pollution abatement (APA) system used in a pig farm building. The monitoring duration was 11 weeks. The results were compared with the baseline from a previous pig cycle during the same time of year in 2023. A ventilation-controlled room was monitored during a two-phase campaign, and the actual ammonia concentrations were measured at different locations within the site and at the inlet/outlet of the APA system. A 98% ammonia reduction was achieved at the APA outlet through NH₃ absorption in tap water. Ion chromatography analyses of farm water samples revealed NH₃ concentrations of up to 530 ppm within 83 days of APA operation. Further scanning electron microscopy and energy-dispersive X-ray inspections revealed the presence of salts and organic/inorganic matter in the solid residues. This research can contribute to meeting current ammonia regulations (NECRs), also by reusing the process water as a potential nitrogen fertiliser in agriculture. Full article

(This article belongs to the Special Issue Impacts of Anthropogenic Emissions on Air Quality)

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16 pages, 15796 KiB

Open AccessArticle

Possible Mechanisms Contributing to the Occurrence of a Waterspout in Victoria Harbour, Hong Kong, on 28 September 2024: Observational and Numerical Studies

by Pak Wai Chan, Ka Wai Lo and Kai Kwong Lai

Atmosphere 2025, 16(7), 868; https://doi.org/10.3390/atmos16070868 - 16 Jul 2025

Abstract

A numerical simulation experiment is conducted to study the first-ever waterspout observed in Victoria Harbour, Hong Kong, in 2024, namely, a mesoscale meteorological model with a spatial resolution of 200 m coupled with a computational fluid dynamics model with a spatial resolution of [...] Read more.

A numerical simulation experiment is conducted to study the first-ever waterspout observed in Victoria Harbour, Hong Kong, in 2024, namely, a mesoscale meteorological model with a spatial resolution of 200 m coupled with a computational fluid dynamics model with a spatial resolution of 4 m. It is found that the simulation could reproduce the observed wind field near the surface reasonably well, as well as the location of the waterspout and showers, as shown in the weather image. By conducting simulations with and without buildings, it is found that the inclusion of buildings is essential for the successful reproduction of the flow fields near the surface and up to several hundred metres high. This may suggest that urbanization plays a role in the occurrence of this waterspout. The resultant horizontal vorticity is then stretched by strong vertical motion at around 850 hPa, resulting in the waterspout, though no closed circulation could be simulated at the location of the waterspout. Moreover, the cyclonic feature for the flow field near the surface has a time lag of about 30 min compared with the actual waterspout occurrence. Nonetheless, the simulation is considered to be generally satisfactory and provides useful insight into the occurrence of the waterspout. Full article

(This article belongs to the Section Meteorology)

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17 pages, 5004 KiB

Open AccessArticle

Local Emissions Drive Summer PM_2.5 Pollution Under Adverse Meteorological Conditions: A Quantitative Case Study in Suzhou, Yangtze River Delta

by Minyan Wu, Ningning Cai, Jiong Fang, Ling Huang, Xurong Shi, Yezheng Wu, Li Li and Hongbing Qin

Atmosphere 2025, 16(7), 867; https://doi.org/10.3390/atmos16070867 - 16 Jul 2025

Abstract

Accurately identifying the sources of fine particulate matter (PM_2.5) pollution is crucial for pollution control and public health protection. Taking the PM_2.5 pollution event that occurred in Suzhou in June 2023 as a typical case, this study analyzed the characteristics [...] Read more.

Accurately identifying the sources of fine particulate matter (PM_2.5) pollution is crucial for pollution control and public health protection. Taking the PM_2.5 pollution event that occurred in Suzhou in June 2023 as a typical case, this study analyzed the characteristics and components of PM_2.5, and quantified the contributions of meteorological conditions, regional transport, and local emissions to the summertime PM_2.5 surge in a typical Yangtze River Delta (YRD) city. Chemical composition analysis highlighted a sharp increase in nitrate ions (NO₃⁻, contributing up to 49% during peak pollution), with calcium ion (Ca²⁺) and sulfate ion (SO₄²⁻) concentrations rising to 2 times and 7.5 times those of clean periods, respectively. Results from the random forest model demonstrated that emission sources (74%) dominated this pollution episode, significantly surpassing the meteorological contribution (26%). The Weather Research and Forecasting model combined with the Community Multiscale Air Quality model (WRF–CMAQ) further revealed that local emissions contributed the most to PM_2.5 concentrations in Suzhou (46.3%), while external transport primarily originated from upwind cities such as Shanghai and Jiaxing. The findings indicate synergistic effects from dust sources, industrial emissions, and mobile sources. Validation using electricity consumption and key enterprise emission data confirmed that intensive local industrial activities exacerbated PM_2.5 accumulation. Recommendations include strengthening regulations on local industrial and mobile source emissions, and enhancing regional joint prevention and control mechanisms to mitigate cross-boundary transport impacts. Full article

(This article belongs to the Section Air Quality)

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16 pages, 5287 KiB

Open AccessArticle

Long-Term Integrated Measurements of Aerosol Microphysical Properties to Study Different Combustion Processes at a Coastal Semi-Rural Site in Southern Italy

by Giulia Pavese, Adelaide Dinoi, Mariarosaria Calvello, Giuseppe Egidio De Benedetto, Francesco Esposito, Antonio Lettino, Margherita Magnante, Caterina Mapelli, Antonio Pennetta and Daniele Contini

Atmosphere 2025, 16(7), 866; https://doi.org/10.3390/atmos16070866 - 16 Jul 2025

Abstract

Biomass burning processes affect many semi-rural areas in the Mediterranean, but there is a lack of long-term datasets focusing on their classification, obtained by monitoring carbonaceous particle concentrations and optical properties variations. To address this issue, a campaign to measure equivalent black carbon [...] Read more.

Biomass burning processes affect many semi-rural areas in the Mediterranean, but there is a lack of long-term datasets focusing on their classification, obtained by monitoring carbonaceous particle concentrations and optical properties variations. To address this issue, a campaign to measure equivalent black carbon (eBC) and particle number size distributions (0.3–10 μm) was carried out from August 2019 to November 2020 at a coastal semi-rural site in the Basilicata region of Southern Italy. Long-term datasets were useful for aerosol characterization, helping to clearly identify traffic as a constant eBC source. For a shorter period, PM_2.5 mass concentrations were also measured, allowing the estimation of elemental and organic carbon (EC and OC), and chemical and SEM (scanning electron microscope) analysis of aerosols collected on filters. This multi-instrumental approach enabled the discrimination among different biomass burning (BB) processes, and the analysis of three case studies related to domestic heating, regional smoke plume transport, and a local smoldering process. The AAE (Ångström absorption exponent) daily pattern was characterized as having a peak late in the morning and mean hourly values that were always higher than 1.3. Full article

(This article belongs to the Section Aerosols)

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20 pages, 6439 KiB

Open AccessArticle

Spatiotemporal Patterns of Hongshan Culture Settlements in Relation to Middle Holocene Climatic Fluctuation in the Horqin Dune Field, Northeast China

by Wenping Xue, Heling Jin, Wen Shang and Jing Zhang

Atmosphere 2025, 16(7), 865; https://doi.org/10.3390/atmos16070865 - 16 Jul 2025

Abstract

Given the increasing challenges posed by frequent extreme climatic events, understanding the climate–human connection between the climate system and the transitions of ancient civilizations is crucial for addressing future climatic challenges, especially when examining the relationship between the abrupt events of the Holocene [...] Read more.

Given the increasing challenges posed by frequent extreme climatic events, understanding the climate–human connection between the climate system and the transitions of ancient civilizations is crucial for addressing future climatic challenges, especially when examining the relationship between the abrupt events of the Holocene and the Neolithic culture development. Compared with the globally recognized “4.2 ka collapse” of ancient cultures, the initial start time and the cultural significance of the 5.5 ka climatic fluctuation are more complex and ambiguous. The Hongshan culture (6.5–5.0 ka) is characterized by a complicated society evident in its grand public architecture and elaborate high-status tombs. However, the driving mechanisms behind cultural changes remain complex and subject to ongoing debate. This paper delves into the role of climatic change in Hongshan cultural shifts, presenting an integrated dataset that combines climatic proxy records with archaeological data from the Hongshan culture period. Based on synthesized aeolian, fluvial-lacustrine, loess, and stalagmite deposits, the study indicates a relatively cold and dry climatic fluctuation occurred during ~6.0–5.5 ka, which is widespread in the Horqin dune field and adjacent areas. Combining spatial analysis with ArcGis 10.8 on archaeological sites, we propose that the climatic fluctuation between ~6.0–5.5 ka likely triggered the migration of the Hongshan settlements and adjustment of survival strategies. Full article

(This article belongs to the Special Issue Desert Climate and Environmental Change: From Past to Present)

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