Search Results (37)

Madinah, Saudi Arabia, is a hot-desert pilgrimage city receiving millions of religious visitors annually, yet its fine particulate matter (PM_2.5) has not been chemically characterized. The city whose population is periodically influx by millions of religious visitors, generating concentrated increases in vehicular activity while simultaneously exposing a large transient population to ambient air pollution. Despite this, its fine particulate matter (PM_2.5) has not been chemically characterized. Twenty-four-hour PM_2.5 samples were collected at five urban sites between December 2014 and February 2016 and analyzed for black carbon, water-soluble inorganic ions, and trace elements; sources were resolved by enrichment factors and positive matrix factorization (PMF), and screening-level inhalation risks estimated for eight PM_2.5-bound metals. Site means ranged from 37.7 ± 20.5 µg m⁻³ at Uhad to 103 ± 50.7 µg m⁻³ at Al-Awali, exceeding the World Health Organization 24-h guideline of 15 µg m⁻³ at all sites in every season. Observed site–cycle means ranged from 37.7 ± 20.5 µg m⁻³ at Uhad to 103 ± 50.7 µg m⁻³ at Al-Awali, with concentrations exceeding the World Health Organization 24-h guideline of 15 µg m⁻³ across the monitored site–cycle datasets. Reconstructed mass was dominated by organic matter (53–80.5%) and crustal material (15–53%). Sulfate was the dominant water-soluble ion, but secondary inorganic aerosols contributed only 1–22% of mass, resembling rapidly urbanizing arid cities rather than Asian or European megacities. PMF resolved five sources: crustal dust, industrial mixed dust, oil combustion, vehicular emissions, and secondary aerosols. Hazard quotients remained below unity and cumulative carcinogenic risks below 10⁻⁶, principally from chromium and nickel. Because these measurements precede the Vision 2030 urban-transformation program, they establish a chemically resolved reference state for evaluating future air-quality change in Madinah. Full article

Air pollution is a growing environmental issue in rapidly urbanizing Asian cities, where meteorological conditions and seasonal variability strongly influence pollutant concentrations. This review synthesizes published evidence on the interactions between meteorology, seasonality, and urban air pollution across selected cities in East Asia, South Asia, and Southeast Asia. The literature was collected from major scientific databases and organized according to meteorological drivers, seasonal characteristics, and dominant emission sources. Particular emphasis was placed on particulate matter (PM_2.5 and PM₁₀), SO₂, NO₂, NO_x, CO, and O₃. The reviewed studies indicate that wind speed and direction, precipitation, temperature, atmospheric stability, and monsoon circulation strongly influence pollutant transport, dispersion, and removal. Pollutant concentrations generally reach their highest in winter due to stagnant conditions and higher human emissions. In contrast, the summer and monsoon seasons tend to have lower PM levels due to better atmospheric mixing and wet deposition. Regional differences in dominant sources were also observed, including coal combustion and heating in East Asia, traffic and biomass burning in South Asia, and biomass burning and transboundary transport in Southeast Asia. These findings highlight the importance of seasonally adaptive and region-specific air quality management strategies in Asian cities. Full article

East Asian spring dust activity has generally weakened since the early 2000s (Theil-Sen trend −1.07 × 10⁻⁶ yr⁻¹, significant over 62% of the domain), but severe events continue to occur when synoptic forcing, source-region dryness, and terrain-guided transport are favorably coupled. This study places the 19–23 March 2023 East Asian dust storm within this 2000–2024 background and provides an integrated three-dimensional analysis of its transport, vertical structure, and topographic controls. The event developed as a dual-source relay-convergence process: Taklamakan Desert dust was emitted first on 19 March and transported southeastward along the Hexi Corridor, while Mongolian Plateau dust intensified on 21 March and mainly affected North China. Independently calibrated, PM10-cross-validated FLEXPART-WRF trajectory arrays (R = 0.74–0.81) show Taklamakan contributed 100% of the calibrated near-surface dust mass at Lanzhou and Mongolian 98% at Beijing during each receptor’s event peak window. Four independent dynamical diagnostics quantify topographic control, showing the Helan Mountains attenuate westward-approaching Taklamakan dust by 23% across the range. TROPOMI AAI, CALIPSO, ground PM10, and CAMS EAC4 jointly corroborate multi-level cold-vortex/trough-frontal coupling and terrain blocking as the controlling mechanisms, demonstrating that extreme dust episodes can still occur under a weakening long-term background when dynamic lifting, dual-source activation, and topographic channeling act together. Full article

This study investigates the vertical variation and temporal characteristics and indicates the sources of black carbon (BC) and brown carbon (BrC) within particulate matter fraction PM₁ during light (November–December 2024) and heavy (January–February 2025) haze episodes in Bangkok, Thailand, a topic where data are still limited data regarding Southeast Asian megacities. Continuous measurements were conducted at 30 and 110 m above ground level, together with particle size distribution measurement, micrometeorological observations, and backward air mass trajectory analysis. During the haze periods, the highest particle number concentrations occurred in the 0.3–0.4 µm size range, indicating dominant contributions from combustion-related emissions and secondary aerosol formation. Mean PM₁ mass concentrations during the heavy haze episodes were more than 2.5 times higher than those during light haze. BC concentrations increased substantially during heavy haze, while the BC fraction of PM₁ remained relatively constant (~10%). In contrast, the BrC fraction reached nearly 20%, reflecting an increasing influence of biomass burning emissions associated with regional transport. Combined analyses of BC/BrC relationships, wind-direction dependence, and air mass trajectories demonstrate mixed contributions from local fossil fuel combustion and long-range transport of biomass burning aerosols during severe haze events. Full article

The composition of air pollutants in industrial complexes differs from that of general urban areas, often containing more hazardous substances that pose significant health risks to both workers and residents nearby. In this study, PM_2.5 and its 29 chemical components (eight ions, two carbon species, and 19 trace elements) were measured and analyzed at five monitoring sites adjacent to the Yeosu and Gwangyang industrial complexes from August 2020 to December 2024. Chemical characterization and source identification were conducted. The average PM_2.5 concentration was 18.63 ± 9.71 μg/m³, with notably higher levels observed during winter and spring. A low correlation (R = 0.56) between elemental carbon (EC) and organic carbon (OC) suggests a dominance of secondary aerosols. The charge balance analysis of [NH₄⁺] with [SO₄²⁻], [NO₃⁻], and [Cl⁻] showed slopes below the 1:1 line, indicating that NH₄⁺ is capable of neutralizing these anions. Positive matrix factorization (PMF) identified eight contributing sources—biomass burning (10.4%), sea salt (11.8%), suspended particles (7.1%), industrial sources (4.6%), Asian dust (5.2%), steel industry (21.8%), secondary nitrate (16.4%), and secondary sulfate (22.7%). These findings provide valuable insights for the development of targeted mitigation strategies and the establishment of effective emission control policies in industrial regions. Full article

Heavy rainfall events in the southern Anhui region are the main meteorological disasters, often leading to floods and secondary disasters. This article explores the mechanisms supporting extreme precipitation by studying the spatiotemporal characteristics of heavy rainfall events during 2022–2024 and their related atmospheric circulation patterns. Using high-resolution precipitation data, ERA5 and GDAS reanalysis datasets, and the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model analysis, the main sources and transport pathways of water that cause heavy rainfall in the region were determined. The results indicate that large-scale circulation systems, including the East Asian monsoon (EAM), the Western Pacific subtropical high (WPSH), the South Asian high (SAH), and the Tibetan Plateau monsoon (PM), play a decisive role in regulating water vapor flux and convergence in southern Anhui. Southeast Asia, the South China Sea, the western Pacific, and inland China are the main sources of water vapor, with multi-level and multi-channel transport. The uplift effect of mountainous terrain further enhances local precipitation. The Indian Ocean basin mode (IOBM) and zonal index are also closely related to the spatiotemporal changes in rainfall and disaster occurrence. The rainstorm disaster risk assessment based on principal component analysis, the information entropy weight method, and multiple regression shows that the power index model fitted by multiple linear regression is the best for the assessment of disaster-causing rainstorm events. The research results provide a scientific basis for enhancing early warning and disaster prevention capabilities in the context of climate change. Full article

This study analyzes the spatiotemporal characteristics of PM₁₀ across 53 Asian dust events that affected the Korean Peninsula between January 2019 and June 2024. Self-Organizing Map (SOM) analysis was applied to sea level pressure and 850 hPa wind fields from the NCEP/DOE Reanalysis II dataset, classifying synoptic patterns into four distinct clusters. Cluster 1, associated with a deep low over Manchuria and strong westerly inflow, produced the highest PM₁₀ concentrations and the longest durations across most regions, with sharp afternoon peaks and the highest skewness values, and was mainly sourced from the Gobi Desert. Cluster 2 featured a high–low pressure dipole, generating localized impacts in northwestern regions and shorter durations, with moderate afternoon increases, originating primarily from the Gobi Desert and Inner Mongolia. Cluster 3, linked to a low east of Japan, resulted in elevated PM₁₀ mainly in central and southeastern regions, with peaks often occurring earlier in the day, and was associated with Manchurian dust sources. Cluster 4 exhibited a straight northwesterly flow with the high shifted eastward, producing moderate but spatially widespread concentrations and relatively consistent afternoon peaks, also linked to Manchurian sources. These results suggest that integrating synoptic pattern classification into dust forecasting can improve accuracy, enable early recognition of high-concentration events, and support the development of timely and region-specific warning strategies. Full article

This study investigates the impacts of near-term climate forcers (NTCFs) and ozone precursor emissions on particulate matter (PM_2.5) concentrations in East Asia (EA). Our analysis used the Coupled Model Intercomparison Project Phase 6 Aerosols and Chemistry Model Intercomparison Project (AerChemMIP) dataset to assess the potential changes in air quality under varying emission scenarios for the present day (1995–2014) and near-term future (2015–2054). Present-day PM_2.5 concentrations in EA averaged 14.3 ± 2.6 μg/m³, with significant regional variation: East China (32.43 μg/m³), Korea (13.71 μg/m³), and Japan (7.51 μg/m³). A reduction in historical NTCF emissions would lower PM_2.5 concentrations by approximately 43% across EA, whereas reducing O₃ precursors would yield an approximately 10% decrease. Under the SSP370 scenario, PM_2.5 concentrations are projected to increase by 16% in the near-term future (2045–2054). However, robust NTCF mitigation could reduce PM_2.5 levels by approximately 40%, primarily by decreasing sulfate and organic aerosols, which are the dominant contributors of historical PM_2.5 variability. Despite substantial projected improvements, achieving the World Health Organization’s stringent air quality guidelines remains challenging, highlighting the necessity for enhanced emissions control targeting key pollutant sources. These insights are crucial to East Asian policymakers aiming to implement effective air quality management strategies. Full article

In recent years, frequent open biomass burning (OBB) activities such as agricultural residue burning and forest fires have led to severe air pollution and carbon emissions across South and Southeast Asia (SSEA). We selected this area as our study area and divided it into two sub-regions based on climate characteristics and geographical location: the South Asian Subcontinent (SEAS), which includes India, Laos, Thailand, Cambodia, etc., and Equatorial Asia (EQAS), which includes Indonesia, Malaysia, etc. However, existing methods—primarily emission inventories relying on burned area, fuel load, and emission factors—often lack accuracy and temporal resolution for capturing fire dynamics. Therefore, in this study, we employed high-resolution fire point data from China’s Feng Yun-4A (FY-4A) geostationary satellite and the Fire Radiative Power (FRP) method to construct a daily OBB emission inventory at a 5 km resolution in this region for 2020–2022. The results show that the average annual emissions of carbon (C), carbon dioxide (CO₂), carbon monoxide (CO), methane (CH₄), non-methane organic gases (NMOGs), hydrogen (H₂), nitrogen oxide (NO_X), sulfur dioxide (SO₂), fine particulate matter (PM_2.5), total particulate matter (TPM), total particulate carbon (TPC), organic carbon (OC), black carbon (BC), ammonia (NH₃), nitric oxide (NO), nitrogen dioxide (NO₂), non-methane hydrocarbons (NMHCs), and particulate matter ≤ 10 μm (PM₁₀) are 178.39, 598.10, 33.11, 1.44, 4.77, 0.81, 1.02, 0.28, 3.47, 5.58, 2.29, 2.34, 0.24, 0.58, 0.43, 0.99, 1.87, and 3.84 Tg/a, respectively. Taking C emission as an example, 90% of SSEA’s emissions come from SEAS, especially concentrated in Laos and western Thailand. Due to the La Niña climate anomaly in 2021, emissions surged, while EQAS showed continuous annual growth at 16.7%. Forest and woodland fires were the dominant sources, accounting for over 85% of total emissions. Compared with datasets such as the Global Fire Emissions Database (GFED) and the Global Fire Assimilation System (GFAS), FY-4A showed stronger sensitivity and regional adaptability, especially in SEAS. This work provides a robust dataset for carbon source identification, air quality modeling, and regional pollution control strategies. Full article

Accurate identification of dust emission sources is crucial for simulating dust aerosols in atmospheric chemical models. Therefore, a dynamically updated dust source function (DSF) was developed within the dust emission scheme of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to simulate an East Asian dust storm event from 13 to 16 March 2021. Utilizing satellite-derived input of vegetation cover, snow cover, soil texture, and land use, the DSF was updated to better identify dust source areas over bare soils and sparsely vegetated regions in western China and central-western Mongolia. With the updated DSF, simulated dust emissions increase significantly over western China and Mongolia. The dust aerosol simulations demonstrate substantial improvements in near-surface PM₁₀ concentrations, a better agreement with remotely sensed dust aerosol optical depth (DOD), and a more accurate representation of the vertical distribution of dust extinction coefficients compared to observations. This study highlights the importance of integrating real-time data to accurately characterize dust emission sources, thereby improving atmospheric environment simulations. Full article

This study utilized the Community Multiscale Air Quality (CMAQ) model to assess the impact of open biomass burning (OBB) in Thailand and neighboring countries—Myanmar, Laos, Cambodia, and Vietnam—on the PM_2.5 concentrations in the Bangkok Metropolitan Region (BMR) and Upper Northern Region of Thailand. The Upper Northern Region was further divided into the west, central, and east sub-regions (WUN, CUN, and EUN) based on geographical borders. The CMAQ model was used to simulate the spatiotemporal variations in PM_2.5 over a wide domain in Asia in 2019. The Integrated Source Apportionment Method (ISAM) was utilized to quantify the contributions from OBB from each country. The results showed that OBB had a minor impact on PM_2.5 in the BMR, but transboundary transport from Myanmar contributed to an increase in PM_2.5 levels during the peak burning period from March to April. In contrast, OBB substantially impacted PM_2.5 in the Upper Northern Region, with Myanmar being the major contributor in WUN and CUN and domestic burning being the major contributor to EUN during the peak months. Despite Laos having the highest OBB emissions, meteorological conditions caused the spread of PM_2.5 eastward rather than into Thailand. These findings highlight the critical impact of regional transboundary transport and emphasize the necessity for collaborative strategies for mitigating PM_2.5 pollution across Southeast Asia. Full article

Air pollutants from biomass burning, including forest fires and agricultural trash burning, have contributed significantly to the pollution of the Asian atmosphere. Burned area estimates are variable, making it difficult to measure these emissions. Improving emission quantification of these critical air pollution sources requires refining methods and collecting thorough data. This study estimates air pollutants from biomass burning, including PMs, NO_X, SO₂, BC, and OC. Machine learning (ML) with the Random Forest (RF) method was used to assess burned areas in Google Earth Engine. Forest emissions were highest in the upper north and peaked in March and April 2019. Air pollutants from agricultural waste residue were found in the lower north, but harvesting seasons made timing less reliable. Biomass burning was compared to the MODIS aerosol optical depth (AOD) and Sentinel-5P air pollutants, with all comparisons made by the Pollution Control Department (PCD) Thailand air monitoring stations. Agro-industries, mainly sugar factories, produce air pollutants by burning bagasse as biomass fuel. Meanwhile, the emission inventory of agricultural operations in northern Thailand, including that of agro-industry and forest fires, was found to have a good relationship with the monthly average levels of ambient air pollutants. Overall, the information uncovered in this study is vital for air quality control and mitigation in northern Thailand and elsewhere. Full article

PM_2.5-bound trace elements were chosen for health risk assessment because they have been linked to an increased risk of respiratory and cardiovascular illness. Since the Korean national air quality standard for ambient particulate matter is based on PM_2.5 mass concentration, there have only been a few measurements of PM_2.5 particles together with trace elements that can be utilized to evaluate their effects on air quality and human health. Thus, this study describes the trace elements bound to PM_2.5 in Seoul (urban area) and Seosan (rural area) using online nondestructive energy-dispersive X-ray fluorescence analysis from December 2020 to January 2021. At both the Seoul and Seosan sites, S, K, Si, Ca, and Fe constituted most of the PM_2.5-bound trace elements (~95%); major components such as S, K, and soil (estimatedcalculatedcalculated based on oxides of Si, Fe, Ca, and Ti) were presumably from anthropogenic and crustal sources, as well as favorable meteorological conditions. During winter, synoptic meteorology favored the transport of particles from severely contaminated regions, such as the East Asian outflow and local emissions. The total dry deposition flux for crustal elements was 894.5 ± 320.8 µg m⁻² d⁻¹ in Seoul and 1088.8 ± 302.4 µg m⁻² d⁻¹ in Seosan. Moreover, potential health risks from the trace elements were estimated. Cancer risk values for carcinogenic trace elements (Cr, As, Ni, and Pb) were within the tolerable limit (1 × 10⁻⁶), suggesting that adults and children were not at risk of cancer throughout the study period in Seoul and Seosan. Furthermore, a potential risk assessment of human exposure to remaining carcinogens (Cr, As, Ni, and Pb) and non-carcinogens (Cu, Fe, Zn, V, Mn, and Se) indicated that these trace elements posed no health risks. Nevertheless, trace element monitoring, risk assessment, and mitigation must be strengthened throughout the study area to confirm that trace-element-related health effects remain harmless. Researchers and policymakers can use the database from this study on spatial and temporal variation to establish actions and plans in the future. Full article

Particulate matter (PM), an extremely serious type of air pollution, leads to numerous human diseases. Mitigating PM in the urban city, where resident density has been increasing, has been a major challenge. The increase in residents leads to increasing traffic, the primary source of PM in urban areas. Plants play an important role in reducing PM and maintaining an ecological balance. For some Asian countries, such as Korea, with differing seasons and environmental conditions, PM accumulation and plant survival are greatly impacted by environmental conditions. In this study, we analyzed the amount of PM accumulation on the leaf surfaces and wax layers of 24 plant species during four seasons (spring, summer, autumn, and winter) to determine the PM accumulation in plants under different environmental conditions. The leaf traits of plant chlorophyll a (Chl a), chlorophyll b (Chl b), total chlorophyll (TChl), relative water content (RWC), leaf extract pH (pH), and leaf specific area (SLA) were analyzed to determine the influence of PM on plants and the relationship between PM and leaf traits. In this study, we found that the amount of PM accumulation differed among plants and seasons. Among the 24 plant species, plants Pinus strobus, P. parviflora, P. densiflora, Euonymus japonicus, and Acer palmatum were most adept at PM accumulation. Leaf structure, environmental conditions, such as PM concentration, and rainfall may be the main factors that impact the ability of plant leaves to accumulate PM. The plant leaf traits differed among the four seasons. PM accumulation on the leaf was negatively correlated with SLA (in all four seasons) and pH (in spring, summer, and autumn). PM was negatively correlated with Chl a, Chl b, and TChl in summer. Full article

Seasonal variations in atmospheric ultrafine particulate matter (PM_0.1) were monitored in Bangkok, Thailand, from 2016 to 2017. PM_0.1-bound organic carbon (OC) and elemental carbon (EC) were collected by a cascade air sampler that can collect PM_0.1 and were analyzed by a Thermal-Optical carbon analyzer following the IMPROVE-TOR protocol. The annual average PM_0.1 in Bangkok was 14.5 ± 4.7 µg/m³, which is higher than in large Asian cities such as Shanghai and Hanoi. Biomass burning from neighboring areas was shown to increase the particle concentration. Apparent increases in carbon species such as OC and EC, and the OC/EC ratios in the wet and dry seasons were observed; the Char-EC/Soot-EC ratio revealed that the PM_0.1 in the Bangkok atmosphere was influenced mainly by vehicle exhausts, even though the influence of biomass burning was greater during the dry season. The effective carbon ratio (ECR) shows that Bangkok’s carbonaceous aerosol is light-absorbing and -scattering. The higher SOC/OC in the dry season indicates the high level of secondary sources forming smaller particles from the combustion sources in Bangkok, increasing light scattering during these periods, and contributing to climate and air quality. The findings of this work are of great importance to air pollutant control policies in urban areas. Full article