Atmosphere

29 pages, 1817 KB

Open AccessArticle

Examination of Long-Term Temperature Change in Türkiye: Comparative Evaluation of an Advanced Quartile-Based Approach and Traditional Trend Detection Methods

by Omer Levend Asikoglu, Harun Alp, Ibrahim Temel and Pegah Kamali

Atmosphere 2025, 16(11), 1225; https://doi.org/10.3390/atmos16111225 - 22 Oct 2025

Abstract

The fact that 2023 and subsequently 2024 were the hottest years in history makes it even more important to monitor temperature changes over time. In this study, trends in the mean, maximum, and minimum temperature data of 81 provinces in Türkiye were examined [...] Read more.

The fact that 2023 and subsequently 2024 were the hottest years in history makes it even more important to monitor temperature changes over time. In this study, trends in the mean, maximum, and minimum temperature data of 81 provinces in Türkiye were examined using three traditional methods (Mann–Kendall, Linear Regression Analysis and Sen’s slope), one innovative method (ITA), and the QuarTrend (QT) method proposed in this study, which uses quartiles of the data series. The objectives of this research are (1) to determine and evaluate the long-term temperature trends in Türkiye (1960–2022) and (2) to comparatively evaluate the trend results of the proposed QT method, traditional trend detection methods, and ITA. In the study, a statistically significant (p < 0.05) increasing trend was found in the mean (0.027 °C/year), maximum (0.031 °C/year), and minimum (0.038 °C/year) annual temperatures of Türkiye. While traditional trend tests detected similar trends with ITA and QT for mean temperatures; ITA and QT detected more trends than traditional methods for maximum and minimum temperatures. The results have direct implications for the impacts of climate change in the study region. The results have the potential to support the development of climate-resilient and adaptive policies for effective water resource planning and management to sustain the environment and agricultural productivity in Türkiye. Full article

(This article belongs to the Section Meteorology)

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25 pages, 7312 KB

Open AccessArticle

Sensitivity of Airborne Methane Retrieval Algorithms (MF, ACRWL1MF, and DOAS) to Surface Albedo and Types: Hyperspectral Simulation Assessment

by Jidai Chen, Ding Wang, Lizhou Huang and Jiasong Shi

Atmosphere 2025, 16(11), 1224; https://doi.org/10.3390/atmos16111224 - 22 Oct 2025

Abstract

Methane (CH₄) emissions are a major contributor to greenhouse gases and pose significant challenges to global climate mitigation efforts. The accurate determination of CH₄ concentrations via remote sensing is crucial for emission monitoring but remains impeded by surface spectral heterogeneity—notably [...] Read more.

Methane (CH₄) emissions are a major contributor to greenhouse gases and pose significant challenges to global climate mitigation efforts. The accurate determination of CH₄ concentrations via remote sensing is crucial for emission monitoring but remains impeded by surface spectral heterogeneity—notably albedo variations and land cover diversity. This study systematically assessed the sensitivity of three mainstream algorithms, namely, matched filter (MF), albedo-corrected reweighted-L1-matched filter (ACRWL1MF), and differential optical absorption spectroscopy (DOAS), to surface type, albedo, and emission rate through high-fidelity simulation experiments, and proposed a dynamic regularized adaptive matched filter (DRAMF) algorithm. The experiments simulated airborne hyperspectral imagery from the Airborne Visible/InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) with known CH₄ concentrations over diverse surfaces (including vegetation, soil, and water) and controlled variations in albedo through the large-eddy simulation (LES) mode of the Weather Research and Forecasting (WRF) model and the MODTRAN radiative transfer model. The results show the following: (1) MF and DOAS have higher true positive rates (TP > 90%) in high-reflectivity scenarios, but the problem of false positives is prominent (TN < 52%); ACRWL1MF significantly improves the true negative rate (TN = 95.9%) through albedo correction but lacks the ability to detect low concentrations of CH₄ (TP = 63.8%). (2) All algorithms perform better at high emission rates (1000 kg/h) than at low emission rates (500 kg/h), but ACRWL1MF performs more robustly in low-albedo scenarios. (3) The proposed DRAMF algorithm improves the F1 score (0.129) by about 180% compared to the MF and DOAS algorithms and improves TP value (81.4%) by about 128% compared to the ACRWL1MF algorithm through dynamic background updates and an iterative reweighting mechanism. In practical applications, the DRAMF algorithm can also effectively monitor plumes. This research indicates that algorithms should be selected considering the specific application scenario and provides a direction for technical improvements (e.g., deep learning model) for monitoring gas emission. Full article

(This article belongs to the Special Issue Satellite Remote Sensing Applied in Atmosphere (3rd Edition))

23 pages, 10362 KB

Open AccessArticle

Precipitation Variation Characteristics in Gannan Prefecture, China: Application of the Innovative Trend Analysis and the BEAST (Bayesian Estimator of Abrupt Change, Seasonality, and Trend) Ensemble Algorithm

by Hui Zhou, Linjing Wei and Yanqiang Cui

Atmosphere 2025, 16(11), 1223; https://doi.org/10.3390/atmos16111223 - 22 Oct 2025

Abstract

This study examined the trend changes as well as the spatial distribution of average precipitation and the abrupt change characteristics of precipitation in Gannan Prefecture, China, using daily precipitation monitoring data from 1980 to 2021 at eight meteorological stations. Analytical methods employed included [...] Read more.

This study examined the trend changes as well as the spatial distribution of average precipitation and the abrupt change characteristics of precipitation in Gannan Prefecture, China, using daily precipitation monitoring data from 1980 to 2021 at eight meteorological stations. Analytical methods employed included the climate change trend rate, anomaly analysis, Innovative Trend Analysis (ITA), ITA-change boxes (ITA-CB), ArcGIS technology, and BEAST Ensemble Algorithm. Long-term average precipitation variability was comprehensively analyzed across multiple temporal scales. Results indicated that over the 42 years, interannual precipitation exhibited a significant increasing trend, with an annual rate of 14.363 mm/decade, and abrupt changes were detected in 1984, 2003, and 2018. The distribution of average precipitation varied substantially from year to year. July was the month with the highest average monthly precipitation, and December was the month with the lowest. Summer precipitation contributed the most to annual totals (51.33%), whereas winter precipitation contributed the least (2.01%). Interdecadal precipitation exhibited a pattern of an initial decrease followed by an increase over the study period. Based on the mean and standard deviation of the series’ first half, which was divided by the ITA method, we established a three-category classification for mean precipitation (low, medium, and high). Annual average and seasonal average precipitation showed non-monotonic variations. While the overall trend of annual average precipitation showed a modest augmentation, the increasing tendencies in the middle-value and high-value categories slowed. In spring, the decreasing trend in high-value categories slowed. In summer, decreasing trends in middle-value categories and overall zones slowed, with an enhanced increasing trend observed in autumn and winter overall. At the spatial scale, the average precipitation across Gannan Prefecture exhibited a decreasing trend from south to north. Higher precipitation was recorded at meteorological stations in the southwest (Maqu), west (Luqu), and south (Diebu), primarily influenced by the interaction between the Qinghai–Tibetan Plateau monsoon and westerly circulation, as well as regional topographic effects. The research findings have significant implications for agricultural and pastoral production planning and sustainable economic development in Gannan Prefecture, China. Full article

(This article belongs to the Section Climatology)

28 pages, 2065 KB

Open AccessArticle

Airborne Microplastics: Source Implications from Particulate Matter Composition

by Hiroyuki Sasaki, Tsukasa Takahashi, Mari Futami, Tomomi Endo, Mizuho Hirano, Yuka Kotake and Kim-Oanh Pham

Atmosphere 2025, 16(11), 1222; https://doi.org/10.3390/atmos16111222 - 22 Oct 2025

Abstract

Microplastics (MPs) are emerging pollutants detected in diverse environments and human tissues. Among them, airborne MPs (AMPs) remain poorly characterized due to limited data and methodological inconsistencies. Although regarded as analogous to particulate matter (PM), detailed comparisons with its components are scarce. To [...] Read more.

Microplastics (MPs) are emerging pollutants detected in diverse environments and human tissues. Among them, airborne MPs (AMPs) remain poorly characterized due to limited data and methodological inconsistencies. Although regarded as analogous to particulate matter (PM), detailed comparisons with its components are scarce. To address this gap, this study implemented a unified and seasonal protocol for simultaneous measurement of AMPs and PM across three sites in Japan. AMPs were identified using micro-Raman spectroscopy, enabling polymer- and morphology-resolved analysis. A total of 106 AMPs were identified across all sites and seasons. Polyethylene (PE) was consistently dominant, followed by polyethylene terephthalate (PET) and polyamide (PA). Site-specific variation was evident, with certain polymers being relatively more abundant depending on the local environment. Feret diameter analysis showed a modal range of 4–6 μm, with fragments predominating over granular and fibrous particles. Significant correlations between AMP concentrations and PM components were determined, including syringaldehyde (SYAL), tungsten (W), cobalt (Co), and chromium (Cr), suggesting links to local sources, while indicating that AMP dynamics are not always aligned with PM behavior. This study provides one of the first integrated datasets of AMPs and PM components, offering insights into their occurrence, sources, and atmospheric relevance. Full article

(This article belongs to the Special Issue Micro- and Nanoplastics in the Atmosphere)

38 pages, 1773 KB

Open AccessReview

Recent Advances in Wildland Fire Smoke Dynamics Research in the United States

by Yongqiang Liu, Warren E. Heilman, Brian E. Potter, Craig B. Clements, William A. Jackson, Nancy H. F. French, Scott L. Goodrick, Adam K. Kochanski, Narasimhan K. Larkin, Pete W. Lahm, Timothy J. Brown, Joshua P. Schwarz, Sara M. Strachan and Fengjun Zhao

Atmosphere 2025, 16(11), 1221; https://doi.org/10.3390/atmos16111221 - 22 Oct 2025

Abstract

Smoke plume dynamics involve various smoke processes and mechanics in the atmosphere and provide the scientific foundation for the development of tools to simulate and predict smoke and its environmental and human impacts. The increasing occurrence of wildfires and the demands for more [...] Read more.

Smoke plume dynamics involve various smoke processes and mechanics in the atmosphere and provide the scientific foundation for the development of tools to simulate and predict smoke and its environmental and human impacts. The increasing occurrence of wildfires and the demands for more extensive application of prescribed fires in the U.S. have posed great challenges and immediate actions for advancing smoke plume dynamics and improving smoke predictions and impact assessments to mitigate smoke impacts. Numerous efforts have been made recently to address these needs and challenges. This paper synthesizes advances in smoke plume dynamics research mainly conducted in the U.S. in the recent decade, identifies gaps, and suggests future research needs. The main advances include smoke data collections from comprehensive field campaigns, new satellite products, improved understanding of smoke plume properties and chemistry, structure and evolution, evaluation and improvement of smoke modeling and prediction systems, the development of coupled smoke models, and applications of machine-learning techniques. The major remaining gaps are the lack of comprehensive simultaneous measurements of smoke, fuels, fire, and atmospheric interactions during wildfires, high-resolution coupled modeling systems of these components, and real-time smoke prediction capacity. The findings from this synthesis study are expected to support smoke research and management to meet various challenges under increasing wildland fires and impacts. Full article

(This article belongs to the Section Air Quality)

16 pages, 1293 KB

Open AccessArticle

Associations Between Air Pollution and Hospital Admissions for Cardiovascular and Respiratory Diseases in Makkah, Saudi Arabia, During the Hajj Cultural Events and the COVID-19 Outbreak

by Albaraa A. Milibari, Ivan C. Hanigan, Hatim M. Badri, Wahaj A. Khan and Krassi Rumchev

Atmosphere 2025, 16(10), 1220; https://doi.org/10.3390/atmos16101220 - 21 Oct 2025

Abstract

Air pollution is a global issue affecting health and the environment. This study investigated associations between PM₁₀, NO₂, and admissions from cardiovascular and respiratory diseases in Makkah (2019–2022), comparing Hajj cultural events and the COVID-19 lockdown with non-event periods, [...] Read more.

Air pollution is a global issue affecting health and the environment. This study investigated associations between PM₁₀, NO₂, and admissions from cardiovascular and respiratory diseases in Makkah (2019–2022), comparing Hajj cultural events and the COVID-19 lockdown with non-event periods, using time-series Poisson regression models adjusted for time and seasonality. Event interactions, particularly the impact of the Hajj and COVID-19 periods, were examined to assess potential effects on morbidity. The study findings showed that PM₁₀ was significantly associated with increased respiratory admissions during the Hajj period (lag 0: RR = 1.066; 95% CI: 1.030–1.104), and with decreased risk during the non-Hajj period (lag 0: RR = 0.966; 95% CI: 0.942–0.991) and non-COVID periods (lag 0: RR = 0.946; 95% CI: 0.920–0.973). NO₂ demonstrated a strong positive association with respiratory admissions during the Hajj period across all lags, peaking at lag 0 with a 16.2% increased risk (RR = 1.162; 95% CI: 1.118–1.207). Exposure to PM₁₀ during Hajj was associated with a 3.1% increased risk of cardiovascular admissions (lag 0: RR = 1.031; 95% CI: 1.012–1.050) and decreased risk during non-Hajj (lag 0: RR = 0.981; 95% CI: 0.963–0.999) and non-COVID periods (lag 0: RR = 0.962; 95% CI: 0.942–0.983). NO₂ exposure was positively associated with cardiovascular admissions during Hajj (lag 0: RR = 1.039; 95% CI: 1.019–1.056) and non-COVID periods (lag 0: RR = 1.037; 95% CI: 1.007–1.068). These findings provide event-specific evidence to guide targeted air quality management during mass gatherings, helping policymakers protect the health of Makkah’s residents and visitors. Full article

(This article belongs to the Section Air Quality and Health)

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25 pages, 7246 KB

Open AccessArticle

Research on the Distribution Characteristics and Health Effects of O₃ in the Fenwei Plain

by Qianqian Wang, Chunhui Yang, Man Liu and Ruifeng Yan

Atmosphere 2025, 16(10), 1219; https://doi.org/10.3390/atmos16101219 - 21 Oct 2025

Abstract

In recent years, coal-combustion-related air pollution has declined markedly, whereas tropospheric ozone (O₃) pollution has emerged as a growing environmental concern. Long-term exposure to O₃ can severely impact human health and ecosystems, constraining socioeconomic development. The Fenwei Plain has complex [...] Read more.

In recent years, coal-combustion-related air pollution has declined markedly, whereas tropospheric ozone (O₃) pollution has emerged as a growing environmental concern. Long-term exposure to O₃ can severely impact human health and ecosystems, constraining socioeconomic development. The Fenwei Plain has complex topographical conditions and a relatively simple industrial structure, and at present, O₃ is one of the main pollutants affecting air quality in this region. Therefore, studying the distribution of O₃ pollution in the Fenwei Plain can provide a reference for developing plans to control O₃ pollution in the area, which is important for safeguarding local public health and economic development. Currently, the number of pollutant monitoring stations in China is limited, spatially discontinuous, and significantly affected by environmental factors, making it difficult to obtain high-precision, large-scale observational data. Satellite-based remote sensing provides broad spatial coverage and is free from topographic constraints, thereby serving as an effective complement to ground-based monitoring networks. This provides important technical support for studying the distribution characteristics of O₃ pollution and its associated health risks. This study focuses on the Fenwei Plain, utilizing machine learning models to estimate continuous O₃ concentrations from 2015 to 2022 and analyze the spatiotemporal distribution of O₃. Based on this, an assessment and analysis of the health risks associated with near-surface O₃ exposure in the study area will be conducted, incorporating the population exposed in the Fenwei Plain and individuals with chronic obstructive pulmonary disease (COPD). Full article

(This article belongs to the Section Air Quality and Health)

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10 pages, 5749 KB

Open AccessArticle

Clear-Air Turbulence over China: Climatology and Multiscale Mechanisms from First Long-Term Aircraft Reports

by Wei Zhang, Xiaochen Zhang, Wei Yuan, Chongyu Zhang, Minghua Hu and Ting Yang

Atmosphere 2025, 16(10), 1218; https://doi.org/10.3390/atmos16101218 - 21 Oct 2025

Abstract

Clear-air turbulence (CAT), as a key meteorological hazard threatening aviation safety, urgently requires the revelation of its spatiotemporal distribution patterns and formation mechanisms within the China region. Based on the first release of 12,539 aircraft turbulence voice reports from China’s civil aviation from [...] Read more.

Clear-air turbulence (CAT), as a key meteorological hazard threatening aviation safety, urgently requires the revelation of its spatiotemporal distribution patterns and formation mechanisms within the China region. Based on the first release of 12,539 aircraft turbulence voice reports from China’s civil aviation from 2022 to 2024 and ERA5 high-resolution reanalysis data, this study constructs for the first time a climatological portrait of aircraft turbulence over China, revealing the spatiotemporal distribution characteristics and formation mechanisms of CAT in the region: turbulence occurs predominantly at 3000–8000 m (accounting for 61.0%), peaking at 7000–8000 m, driven by strong low-level jet wind shear and Kelvin–Helmholtz instability (KHI); wintertime exhibits a high frequency (33.4%) stemming from strong upper-level jets (>30 m s⁻¹), while summer is dominated by low-level thermal convection (21.0%); the high-incidence zones of Central-South and Southwest China (>2800 events) are jointly governed by a mid-level strong horizontal gradient of vertical vorticity, divergence perturbations, and jet shear, with the winter jet shifting southward (22–30° N), further intensifying the turbulence risk. The findings establish a dynamic–thermodynamic coupling mechanism for CAT over China, providing a scientific basis for aviation safety early warning. Full article

(This article belongs to the Section Aerosols)

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10 pages, 1521 KB

Open AccessArticle

Estimation of Ionosphere Electron Density Structure Related to the Solar Terminator

by Alexey Andreyev, Vyacheslav Somsikov, Vitaliy Kapytin, Yekaterina Chsherbulova and Stanislav Utebayev

Atmosphere 2025, 16(10), 1217; https://doi.org/10.3390/atmos16101217 - 20 Oct 2025

Abstract

The solar terminator, due to its unique characteristics, is a remarkable source of atmospheric disturbances. Due to its regularity and constancy, dependent solely on geometric factors, it can serve as a test source of disturbances, which can be used to test the response [...] Read more.

The solar terminator, due to its unique characteristics, is a remarkable source of atmospheric disturbances. Due to its regularity and constancy, dependent solely on geometric factors, it can serve as a test source of disturbances, which can be used to test the response of the medium through which it passes and determine its state. However, our knowledge of the atmospheric phenomena generated by the terminator is far from complete. One clear indication of the terminator’s influence is geomagnetic disturbances manifested in the vertical and eastward components of the magnetic field measured at magnetic observatories. To determine the sources of geomagnetic disturbances from the solar terminator, which can be identified by the strict phase correlation of these disturbances with the moments of terminator passage, ionospheric irregularities arising during terminator passage were studied. Ionospheric irregularities extending along the boundary of the morning solar terminator were detected in total electron content data, based on measurements by GNSS receivers. Assumptions are made about the possible parameters of the ionospheric current structure that creates variations in the magnetic field associated with the passage of the solar terminator. Full article

(This article belongs to the Special Issue Advanced GNSS for Ionospheric Sounding and Disturbances Monitoring)

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20 pages, 1428 KB

Open AccessArticle

A Framework to Minimise the Impacts of Climate Change on UK Residential Buildings and Occupants

by Ehis Lawrence Onus, Ezekiel Chinyio, Emmanuel Itodo Daniel and Michael Gerges

Atmosphere 2025, 16(10), 1216; https://doi.org/10.3390/atmos16101216 - 20 Oct 2025

Abstract

Residential buildings, the bastions of shelter and protection, are facing an escalating threat from climate change. The need to bolster the resilience of UK residential buildings is becoming more urgent, given the nature and frequency of the impact of climate change. This study [...] Read more.

Residential buildings, the bastions of shelter and protection, are facing an escalating threat from climate change. The need to bolster the resilience of UK residential buildings is becoming more urgent, given the nature and frequency of the impact of climate change. This study employed a sequential explanatory mixed-method approach. The first phase involved surveying 313 households, revealing that Climate Change on Buildings (CCB) and Climate Change Measures (CCM) significantly influenced Climate Change on Occupants (CCO). Moreover, climate-positive measures were found to have a significant impact on building occupants. The second phase involved semi-structured interviews with ten UK construction experts to gather insights into the effects of climate change on residential buildings and strategies for mitigation. The findings from both phases underscore the need for government incentives, green loans, and increased stakeholder awareness to mitigate the impacts of climate change. To fully address climate change and improve the quality of life for residents, all stakeholders, including policy makers, construction professionals, and the community, must participate actively in these efforts. Consequently, a framework was developed to minimise the impacts of climate change on UK residential buildings. Full article

(This article belongs to the Section Climatology)

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18 pages, 12942 KB

Open AccessArticle

Unfavorable Local Meteorological Conditions in the Vicinity of the Planned Nuclear Power Plant in Jordan

by Shatha S. Ali-Saleh, Marwan M. Al-Kloub, Shatha Alsadi, Safaa Marei, Alexander Baklanov, Alexander Mahura, Nahid Atashi and Tareq Hussein

Atmosphere 2025, 16(10), 1215; https://doi.org/10.3390/atmos16101215 - 20 Oct 2025

Abstract

The development of nuclear energy in Jordan necessitates a detailed understanding of local meteorological behavior, particularly during unfavorable weather conditions. This study uses the METEO mesoscale model to simulate wind fields, vertical motions, and surface–air temperature differences under unfavorable wind directions (15°, 105°, [...] Read more.

The development of nuclear energy in Jordan necessitates a detailed understanding of local meteorological behavior, particularly during unfavorable weather conditions. This study uses the METEO mesoscale model to simulate wind fields, vertical motions, and surface–air temperature differences under unfavorable wind directions (15°, 105°, and 195°) and two wind speeds (1 m/s and 5 m/s), across cold season (January) and warm season (July), near the Samra Energy Power Plant (SEPP)—a proposed location for Jordan’s nuclear plant. Simulations reveal that low wind speeds create stable atmospheric layers with limited vertical motion (±0.1 m/s), enhancing the risk of pollutant accumulation in valleys. Higher wind speeds promote vertical mixing (up to ±0.15 m/s) and lower temperature gradients (within ±0.2 °C), dispersing pollutants more efficiently. These results suggest that specific wind thresholds could determine the spatial extent of emergency response zones, including “shelter-in-place” areas and evacuation perimeters. This study offers valuable insights for nuclear safety planning and environmental risk assessment in complex terrain. Full article

(This article belongs to the Section Meteorology)

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20 pages, 2426 KB

Open AccessArticle

Comprehensive Health Risk Assessment of PM_2.5 Chemical Composition in an Urban Megacity: A Case Study from Greater Cairo Area

by Eliane Farah, Marc Fadel, Hassan R. Dhaini, Nansi Fakhri, Minas Iakovides, Salwa K. Hassan, Mohamed Boraiy, Mostafa El-Nazer, Ali Wheida, Magdy Abdelwahab, Stéphane Sauvage, Agnès Borbon, Jean Sciare, Frédéric Ledoux, Charbel Afif and Dominique Courcot

Atmosphere 2025, 16(10), 1214; https://doi.org/10.3390/atmos16101214 - 20 Oct 2025

Abstract

While many studies on the health effects of PM_2.5 exist, the risks of PM_2.5 species remain largely unexplored in Middle Eastern and North African countries. This study assesses, for the first time, the carcinogenic and non-carcinogenic health risks for elements, polycyclic [...] Read more.

While many studies on the health effects of PM_2.5 exist, the risks of PM_2.5 species remain largely unexplored in Middle Eastern and North African countries. This study assesses, for the first time, the carcinogenic and non-carcinogenic health risks for elements, polycyclic aromatic hydrocarbons (PAHs), phthalates, polychlorinated dibenzo-p-dioxins (PCDDs), dibenzofurans (PCDFs), and dioxin-like polychlorinated biphenyls (DL-PCBs) bound to PM_2.5 in the Greater Cairo Area. A total of 59 samples were collected from an urban site in Dokki (November 2019–January 2020). Chemical analysis showed higher concentrations of PCDFs (5418 fg/m³) than PCDDs (1469 fg/m³), with DL-PCBs being the most abundant (6577 fg/m³). Health risk assessment for inhalation showed non-carcinogenic risks for all age groups, especially for newborns. Manganese (Mn) and lead (Pb) posed the highest elemental non-carcinogenic risk, while the hazard quotient (HQ) for PAHs exceeded 1 across all ages. PCDDs, PCDFs, and DL-PCBs showed an estimated cancer risk reaching 10⁻⁶ in adults, indicating a significant health concern. Key contributors to cancer risk included arsenic (As), chromium (Cr(VI)), and vanadium (V), which accounted for over 80% of the total elemental cancer risk. Major and trace elements posed the highest lifetime cancer risk, nearly 37 times the acceptable level. Full article

(This article belongs to the Section Air Quality and Health)

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29 pages, 10609 KB

Open AccessArticle

High-Resolution Traffic Flow Prediction and Vehicle Emission Inventory Estimation for Chinese Cities Using Geo-Spatial Data of Jinan City, China

by Xuejun Yan, Qi Yang, Jingyang Fan, Ziyuan Cai, Pan Wang, Xiuli Zhang, Hengzhi Wang, Chenxi Zhu, Dongquan He and Chunxiao Hao

Atmosphere 2025, 16(10), 1213; https://doi.org/10.3390/atmos16101213 - 20 Oct 2025

Abstract

Motor vehicle emissions are a major air quality concern in Chinese cities. However, traditional population-based emission inventory methods fail to capture the spatial and temporal variations in emissions for effective policy design. This study proposes a high-resolution approach for traffic flow prediction and [...] Read more.

Motor vehicle emissions are a major air quality concern in Chinese cities. However, traditional population-based emission inventory methods fail to capture the spatial and temporal variations in emissions for effective policy design. This study proposes a high-resolution approach for traffic flow prediction and vehicle emission inventory estimation, using Jinan City, China, as a case study. We leverage multi-source geospatial data and employ a two-fold random forest model to predict hourly traffic flow at a road-segment level. Speed-aligned emission factors were then combined with these data to calculate hourly and road-level vehicle emission estimates. Compared to traditional methods, our approach offers substantial improvements: (1) improved spatiotemporal resolution; (2) enhanced accuracy of traffic flow prediction; and (3) support for more effective vehicle emission control strategies. Results show that heavy-duty vehicles, particularly freight trucks operating on inter-regional corridors through Jinan, contribute 78% more to NO_X emissions than local light-duty vehicles. These transient emissions are typically overlooked in static inventories but constitute a significant source of urban pollution. This study offers valuable insights for combining geospatial data and machine learning to improve the accuracy and resolution of vehicle emission inventories, supporting urban air quality policy and planning. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions (2nd Edition))

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13 pages, 1742 KB

Open AccessArticle

Black Carbon in Urban and Suburban Hangzhou: Spatiotemporal Variation, Precipitation Scavenging, and Policy Impacts

by Mengjing Zhu, Honghui Xu, Meng Shan, Huansang Chen, Yilei Dong and Yuyun Lei

Atmosphere 2025, 16(10), 1212; https://doi.org/10.3390/atmos16101212 - 20 Oct 2025

Abstract

Black carbon (BC) aerosols significantly impact regional air quality and global climate as important light-absorbing atmospheric particles. Using high-temporal resolution BC observation data from urban and suburban sites in Hangzhou and PM₁₀ concentrations, this study analyzed the temporal and spatial distribution characteristics [...] Read more.

Black carbon (BC) aerosols significantly impact regional air quality and global climate as important light-absorbing atmospheric particles. Using high-temporal resolution BC observation data from urban and suburban sites in Hangzhou and PM₁₀ concentrations, this study analyzed the temporal and spatial distribution characteristics of BC concentrations, precipitation scavenging efficiency, and the efficacy of emission mitigation policies. The results showed that (1) suburban BC concentrations presented a significant interannual decline. Seasonal variation displayed a single peak, with high concentrations in winter and low concentrations in summer. A characteristic bimodal diurnal variation pattern was observed, with peaks during morning and evening rush hours. In terms of spatial distribution, the annual average concentration in urban areas was 20.7% higher than in suburban areas, with the largest difference in winter. (2) The scavenging efficiency of precipitation showed nonlinear characteristics. The average efficiency of light rain was the highest, whereas heavy rainfall showed more complex characteristics. The scavenging efficiency of continuous 12 h precipitation was significantly higher than that of short-term heavy rainfall. (3) Emission mitigation policy implementation had a marked effect, with diesel vehicle restrictions and biomass combustion control reducing BC concentrations by 11% and 19%, respectively. Full article

(This article belongs to the Section Aerosols)

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20 pages, 4040 KB

Open AccessArticle

Spatial Correlation Network Analysis of PM2.5 in China: A Temporal Exponential Random Graph Model Approach

by Xia Wu and Linyi Zhou

Atmosphere 2025, 16(10), 1211; https://doi.org/10.3390/atmos16101211 - 20 Oct 2025

Abstract

With the rapid acceleration of industrialization and urbanization in China, PM2.5 pollution has emerged as a major challenge to public health and sustainable development of the society and economy. At the interprovincial level, PM2.5 exhibits a complex spatial correlation network structure. Using data [...] Read more.

With the rapid acceleration of industrialization and urbanization in China, PM2.5 pollution has emerged as a major challenge to public health and sustainable development of the society and economy. At the interprovincial level, PM2.5 exhibits a complex spatial correlation network structure. Using data from 31 provinces in China from 2000 to 2023, this study constructed a spatial correlation network of PM2.5 and analyzed its structural characteristics and formation mechanisms. The results reveal that China’s PM2.5 spatial correlation network is both complex and stable, underscoring the severity of the pollution problem. The network demonstrates a distinct ‘core–periphery’ distribution, with provinces such as Jiangsu, Shandong, and Henan occupying central positions and functioning as critical bridges. Block model analysis showed a clear role of differentiation among provinces in the diffusion of pollution. Temporal exponential random graph model suggests that geographical proximity, industrial structure, vehicle ownership, and government intervention are key factors shaping the network. Geographically adjacent provinces are more likely to form close connections, whereas environmental regulation and vehicle ownership tend to constrain the spread of pollution. This study provides a novel theoretical framework for understanding the spatial diffusion pathways of PM2.5 pollution and offers important policy implications for optimizing and implementing cross-regional air quality governance strategies in China. Full article

(This article belongs to the Special Issue Coordinated Control of PM2.5 and O₃ and Its Impacts in China)

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19 pages, 15745 KB

Open AccessArticle

Variability in Meteorological Parameters at the Lenghu Site on the Tibetan Plateau

by Yong Zhao, Fei He, Ruiyue Li, Fan Yang and Licai Deng

Atmosphere 2025, 16(10), 1210; https://doi.org/10.3390/atmos16101210 - 20 Oct 2025

Abstract

This study presents a comprehensive analysis of key meteorological parameters at the Lenghu site, a premier astronomical observing location, with particular emphasis on understanding their variability patterns and long-term trends. The research systematically investigates regional distribution characteristics, periodic variations, seasonal changes, and the [...] Read more.

This study presents a comprehensive analysis of key meteorological parameters at the Lenghu site, a premier astronomical observing location, with particular emphasis on understanding their variability patterns and long-term trends. The research systematically investigates regional distribution characteristics, periodic variations, seasonal changes, and the temporal evolution of critical atmospheric parameters that influence astronomical observations. Furthermore, this study explores the potential connections between these parameters and major climate oscillation patterns, including ENSO (El Niño–Southern Oscillation), PDO (Pacific Decadal Oscillation), and AMO (Atlantic Multidecadal Oscillation). Utilizing ERA5 (the fifth-generation atmospheric reanalysis from the European Centre for Medium-Range Weather Forecasts) reanalysis data, we examine the regional atmospheric conditions (82°–102° E and 31°–46° N) surrounding the Lenghu site from 2000 to 2023 (24 years). The analysis focuses on fundamental meteorological parameters: precipitable water vapor (PWV), temperature, wind speed at 200 hPa (

W_{200}

), and total cloud cover (TCC). For the Lenghu site specifically, we extend the temporal coverage to 1990–2023 (34 years) to include additional parameters such as high cloud cover (HCC) and total column ozone (TCO). The analysis reveals that the ENSO and PDO indices are negatively correlated with

W_{200}

. The AMO index has a positive correlation with PWV and a slight positive correlation with

W_{200}

, temperature, and TCO. Moreover, a comparative analysis of Lenghu, Mauna Kea, and Paranal reveals distinct variation trends across sites due to regional climate differences. Notably, while all observatory sites are affected by global climate change, their response patterns and temporal characteristics exhibit subtle variations. Full article

(This article belongs to the Section Climatology)

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31 pages, 3502 KB

Open AccessArticle

Air Pollution in Taiyuan City During 2022 to 2024: Status and Influence of Meteorological Factors

by Xiaohui Huang and Lizhen Gao

Atmosphere 2025, 16(10), 1209; https://doi.org/10.3390/atmos16101209 - 19 Oct 2025

Abstract

The deterioration of environmental air quality is an urgent global issue, and the level of air pollution is particularly severe in developing countries. This study aims to understand the air quality problems in Taiyuan City and explore the evolution of air pollution trends [...] Read more.

The deterioration of environmental air quality is an urgent global issue, and the level of air pollution is particularly severe in developing countries. This study aims to understand the air quality problems in Taiyuan City and explore the evolution of air pollution trends and their relationship with meteorological factors. The result shows that the air quality in Taiyuan has distinct temporal distribution characteristics, with summer being better than winter. Wind speed has an impact on air quality and is closely related to the season. The increase in wind speed in spring is conducive to a reduction in NO₂ concentrations, but it leads to an increase in PM₁₀ concentration. In summer, wind speed is negatively correlated with CO and positively correlated with O₃. In autumn, except for O₃, wind speed is negatively correlated with various air pollutants. During winter, wind speed has a favorable effect on most atmospheric pollutants, except for O₃ and PM₁₀. When temperatures soar, it is necessary to be vigilant about the possibility of O₃ concentration exceeding standards in summer. But, in winter, an increase in temperature often leads to an increase in PM_2.5 and PM₁₀ concentrations. An increase in humidity is very beneficial in spring, helping to lower the concentration of PM₁₀, but in winter it can lead to an increase in the concentrations of both PM_2.5 and PM₁₀. Precipitation can improve air quality, especially when it exceeds 3 mm. These findings suggest that pollutant control strategies may need to be adjusted according to the season, especially for particulate matter. Full article

(This article belongs to the Section Air Quality)

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24 pages, 31821 KB

Open AccessArticle

Response of Vegetation Net Primary Productivity to Extreme Climate in a Climate Transition Zone: Evidence from the Qinling Mountains

by Qiuqiang Zeng and Chengyuan Hao

Atmosphere 2025, 16(10), 1208; https://doi.org/10.3390/atmos16101208 - 18 Oct 2025

Abstract

The Qinling Mountains, situated in the climatic transition zone between northern and southern China, represent a critical region for climate and ecological studies due to their unique transitional characteristics and the rising frequency of extreme climate events. As net primary productivity (NPP) is [...] Read more.

The Qinling Mountains, situated in the climatic transition zone between northern and southern China, represent a critical region for climate and ecological studies due to their unique transitional characteristics and the rising frequency of extreme climate events. As net primary productivity (NPP) is a key indicator of ecosystem stability, clarifying its response to extreme climate events is essential for understanding ecological resilience in this region. In this study, daily observational data from 123 meteorological stations (1960–2023) were used to derive eight extreme temperature and precipitation indices. Combined with MODIS NPP data (2001–2023), we applied Theil–Sen slope estimation, Mann–Kendall significance testing, ridge regression, Pearson correlation analysis, and Moran’s I spatial autocorrelation to systematically investigate the spatiotemporal dynamics and driving mechanisms of NPP. The main findings are as follows: (1) From 2001 to 2023, the mean annual NPP in the Qinling region was 558.43 ± 134.27 gC·m⁻²·year⁻¹, showing a significant increasing trend of 5.44 gC·m⁻²·year⁻¹ (p < 0.05). (2) Extreme temperature indices exhibited significant changes, whereas among the precipitation indices, only the number of days with daily precipitation ≥ 20 mm (R20) showed a significant trend, suggesting that extreme temperatures exert a stronger influence in the region. (3) Correlation analysis indicated that temperature-related indices were generally positively correlated, precipitation-related indices displayed even stronger associations, and covariation existed among extreme precipitation events of varying intensities. Moreover, precipitation indices demonstrated relatively stable spatial distributions, while temperature indices fluctuated considerably. (4) Absolute contribution analysis further revealed that the number of days with daily minimum temperature below the 10th percentile (TN10p) contributed up to 3.53 gC·m⁻²·year⁻¹ to annual NPP variation in the Henan subregion, whereas maximum rainfall over five consecutive days (Rx5day) exerted an overall negative effect on NPP (−0.77 gC·m⁻²·year⁻¹). By integrating long-term meteorological observations with remote sensing products, this study quantitatively evaluates the differential impacts of extreme climate events on vegetation within a climatic transition zone, offering important implications for ecological conservation and adaptive management in the Qinling Mountains. Full article

(This article belongs to the Special Issue Vegetation–Atmosphere Interactions in a Changing Climate)

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14 pages, 3889 KB

Open AccessArticle

Runoff and Sediment Response to Rainfall Events in China’s North-South Transitional Zone: Insights from Runoff Plot Observations

by Zhijia Gu, Keke Ji, Gaohan Xu, Maidinamu Reheman, Detai Feng, Yi Shen, Qiang Yi, Jiayi Kang, Xinmiao Zhang and Sitong Pan

Atmosphere 2025, 16(10), 1207; https://doi.org/10.3390/atmos16101207 - 18 Oct 2025

Abstract

China’s North-South Transition Zone is a critical ecological transition region, marked by complex environments, climatic sensitivity, and transitional characteristics. To investigate the effects of individual rainfall events on runoff generation and sediment yield across different slopes and land uses within this zone, the [...] Read more.

China’s North-South Transition Zone is a critical ecological transition region, marked by complex environments, climatic sensitivity, and transitional characteristics. To investigate the effects of individual rainfall events on runoff generation and sediment yield across different slopes and land uses within this zone, the study collected data from slope runoff plots (20 m in length and 5 m in width, measured as horizontal projection) at three monitoring stations (Luoshan, Lushan, Shanzhou) between 2014 and 2023. Rainfall events were classified via K-means clustering. Regression and correlation analyses were applied to reveal the effects of rainfall characteristics, slope gradient and land use type (grass land, dry land, forest land, bare land and natural vegetation) on runoff and sediment. The results indicate that: (1) The most frequent rainstorms were Type C (short, low-intensity, low-volume, low-erosivity events). (2) The runoff depth of bare land is 3.6, 2.3, and 2 times that of forest land, dry land, and natural vegetation, respectively. Similarly, its sediment concentration is 134, 13, and 16 times higher, respectively. Grassland, however, showed markedly lower levels of both runoff and sediment. (3) Rainfall intensity was significantly correlated with runoff and sediment across slopes. Runoff depth depended mainly on rainfall amount. While Type A (prolonged, high-intensity) caused peak runoff, Type D (moderate but intense and erosive) yielded the highest sediment. (4) Sediment reduction efficiency (sediment reduction compared to bare land under identical conditions) consistently surpassed runoff reduction across all land types, with grassland showing the highest efficiency for both. For soil and water conservation, grass-planting was the most effective measure on 10° and 15° slopes, whereas both afforestation and grass-planting were optimal on the 25° slopes. Full article

(This article belongs to the Section Meteorology)

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