During 2015–2018, eight black carbon (BC) monitoring sites were established in Nepal and Bhutan to fill a significant data gap regarding BC measurement in Central Himalaya. This manuscript analyzes ...and presents data from these eight stations and one additional station on the Tibetan plateau (TP). Complex topography, varied emission sources, and atmospheric transport pathways significantly impacted the BC concentrations across these stations, with annual mean concentrations varying from 36 ng m−3 to 45,737 ng m−3. Higher annual mean concentrations (5609 ± 4515 ng m−3) were recorded at low-altitude sites than in other locations, with seasonal concentrations highest in the winter (7316 ± 2541 ng m−3). In contrast, the annual mean concentrations were lowest at high-altitude sites (376 ± 448 ng m−3); the BC concentrations at these sites peaked during the pre-monsoon season (930 ± 685 ng m−3). Potential source contributions to the total observed BC were analyzed using the absorption angstrom exponent (AAE). AAE analysis showed the dominance of biomass burning sources (>50 %), except in Kathmandu. By combining our data with previously published literature, we put our measurements in perspective by presenting a comprehensive assessment of BC concentrations and their variability over the Hindu Kush Himalayan (HKH) region. The BC levels in all three geographic regions, high, mid, and low altitude significantly influenced by the persistent seasonal meteorology. However, the mid-altitude stations were substantially affected by valley dynamics and urbanization. The low-altitude stations experienced high BC concentrations during the winter and post-monsoon seasons. Concentration weighted trajectory (CWT) and frequency analyses revealed the dominance of long-range transported pollution during winter over HKH, from west to east. South Asian sources remained significant during the monsoon season. During pre- and post-monsoon, the local, regional, and long-distance pollution varied depending on the location of the receptor site.
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•EBC concentrations varied between 36 and 45,737 ng m−3 during 2016–2019 in the Central Himalaya.•Biomass burning is the dominant (>50 %) contributor to the EBC mass concentration.•Very high spatial heterogeneity is found in BC concentrations across HKH.
Real-time monitoring of volatile organic compounds (VOCs) was conducted in Xinxiang, China, during the implementation of Xinxiang's ozone pollution control period (CP) in June 2021. To evaluate the ...effectiveness of the control measures, three study periods were determined by combining meteorological conditions and the implementation time of the control measures: before, during, and after the CP of ozone pollution (BCP, CP, and ACP, respectively). The average concentrations of VOCs during the three periods were 41.20 ± 4.99 ppbv, 33.64 ± 5.65 ppbv, and 37.42 ± 2.59 ppbv, respectively, with the same top three components, namely oxygenated VOCs (OVOCs), alkanes, and halogenated hydrocarbons (XVOCs). However, the concentrations of these three components decreased substantially during the CP (by 19 %, 18 %, and 11 %, respectively). The ozone formation potential (OFP) during the BCP was 144.47 ppbv, which was 1.2 times and 1.3 times higher than those during the ACP and CP periods, respectively. During the CP, the proportion of alkenes that contributed to the OFP decreased significantly by 24 %. Five types of VOCs sources were determined by positive matrix factorization (PMF): (1) solvent use, (2) biogenic, (3) secondary formation, (4) industrial process, and (5) vehicle exhaust and fuel evaporation sources. The VOCs emissions from industrial processes decreased by 54 % during the CP, whereas those from vehicle exhaust and fuel evaporation sources decreased by 36 %, indicating the effectiveness of emission control measures and the importance of these two sources for VOCs control in Xinxiang. In terms of regional transport, the results of the spatial analysis revealed that Hebi and Anyang in the northeast and Zhengzhou and Pingdingshan in the southwest, affected significantly the VOCs of Xinxiang. These results highlight the importance of controlling VOCs emissions in Xinxiang. Furthermore, attention should be paid to controlling the regional transport of surrounding cities.
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•Characteristics and sources of VOCs during three different periods were analysed in Xinxiang.•Industrial process and vehicle exhaust and fuel evaporation were major VOCs sources.•Regional transport had great influences on the VOCs of Xinxiang.•Emission control measures in June 2021 effectively reduced the VOCs emission.
Measurements of volatile organic compounds (VOCs) were performed as well as other pollutants in Shanghai in winter. The whole measurements were classified into three types of periods, including ...particulate pollution episodes (PPE), VOC pollution episodes (VPE), and relatively clean periods based on the pollution characteristics. Of these types, PPE have the highest fine particulate matter (PM2.5) mass concentrations and second-highest VOC concentrations, mainly impacted by the regional transport of aged air masses from the northwest. VPE generally concern long-lasting high concentrations of VOCs under stagnant atmospheric conditions due to the accumulation of local emissions. Five sources of VOCs were identified by the positive matrix factorization (PMF) model, and furthermore, the analysis of VOCs concentration weighted trajectory (CWT) was employed to investigate the potential source region and even to validate the source identification to some extent. As a result, VOCs in Shanghai in winter were mainly from solvent usage (23.9%), vehicle emissions mixed with some petrochemical emissions (24.7%), natural gas and background (23.6%), combustion-related to regional transport (22.1%), and secondary formation (5.7%). The regional transport, usually with large combustion sources, played more important roles (41.9%) in VOCs during PPE compared to VPE and clean periods. The contribution of local emissions like vehicle exhaust and petrochemical emissions increased during VPE compared to PPE and clean periods. Clean periods have low PM2.5 and low VOC concentrations, with a large contribution from the regional background. The present study highlighted the regional transport of VOCs should be taken into account for policymakers when making the city scale controlling measures.
•Meteorological conditions strongly influenced VOCs characteristics in winter.•PPE and VPE were two kinds of typical pollution episodes in winter.•Regional transport-related combustion from the northwest played important roles during PPE.•Local emissions dominated the increase of VOCs during VPE.
Biomass-burning (BB) related air pollution is a prime concern in several regions of the world including Southeast Asia. This study aimed to identify and apportion the BB types (agricultural, forest, ...and grassland) and assess the transport of BB-derived PM2.5 which influences the air quality index (AQI) of three major regions (i.e., central, north, and northeast) in Thailand by integrating satellite fire products, air-mass trajectories, ground-based measurements, statistical approaches, and modeling tools. We accounted for the transport time of PM2.5 from source to monitoring stations by grouping the BB type with air-mass trajectory timestamps. Forest fire predominated over the north (73%) and northeast (48%) whereas agricultural burning predominated over the central (52%) region. Grassland burning was most influential in the central region (16%) followed by the northeast (11%) and north (5%) regions in Thailand. Annual PM2.5 exposure amounted to very-unhealthy to hazardous PM2.5-AQI levels for about 79% of the Thailand population. PM2.5-AQI levels over Thailand were mainly governed by transboundary BB influence (67%) whereas the local contribution was about 33%. Excess numbers of premature deaths due to PM2.5 exposure totaled 18,003, and were associated with stroke burden (53%), ischemic heart disease (30%), lung cancer (12%), and chronic obstructive pulmonary disease (5%), based on public-health data from 2016. The spatial distribution results of excess mortality showed the largest burden in the central region (44%) followed by the northeast (29%), north (18%), and south (9%). Our study results are useful for shaping effective control strategies of open burning management in Thailand and other nearby countries in peninsular Southeast Asia.
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•PM2.5 pollution level over Thailand depends on region, season, and BB source type.•Satellite fire and land-use products together with BTs are used to apportion BB types.•Forest fire predominated in the north (73%) and northeast (48%) region.•Agricultural burning was the predominate in central Thailand (52%).•Total premature deaths associated with PM2.5 exposure was 18,003 deaths in 2016.
Located in the transitional region between the Sichuan Basin (SCB) and Qinghai-Tibetan Plateau (QTP), the West China Rain Zone (WCRZ) is a large-scale ecotone and partially belongs to the Southwest ...China Mountains, which is one of the world’s 34 biodiversity hotspots. Using observation data from national air quality stations and our own monitoring data, we investigated the risk from O3 to vegetation and the major source-region of O3 for two UNESCO (i.e., United Nations Educational, Scientific and Cultural Organization) world heritage properties (Mt. Qingcheng and Mt. Emei) and one city (Ya’an) in the WCRZ. The results show that the annual mean maximum daily 8-h average (MDA8) O3 concentration in Mt. Qingcheng (54 ppb) was higher than that in the adjacent SCB cities (38–48 ppb). The acute and chronic risk levels from O3 to vegetation were also higher in Mt. Qingcheng than at all the other sites. The mean MDA8 O3 concentrations and the O3 risk levels to vegetation in Mt. Emei and Ya’an fell in the range of that at the SCB and QTP cities. However, O3 exposures at all the WCRZ, SCB, and QTP sites exceeded the empirical critical loads for natural ecosystems, forest trees, and highly O3-sensitive plants. The SCB was identified as the largest source-region of O3 for Mt. Qingcheng and Mt. Emei but other Chinese regions and northern India also had considerable contributions. To protect biodiversity and ecosystem services, there is a need to further systematically study O3 and its ecological impacts for the entire WCRZ.
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•Mean MDA8 O3 concentrations at Mt. Emei and Mt. Qingcheng were highest in spring.•O3 exposures at the WCRZ sites exceeded relevant ecological critical loads.•SCB is the main source-region of O3 at the two rural WCRZ sites.•High O3 events (>70 ppb) were also mainly associated with SCB emissions.•Further observations are needed to study O3 effects on WCRZ ecosystem services.
As one of the predominant compositions of PM2.5 (particulate matter with aerodynamic diameter ≤2.5 μm), carbonaceous aerosols not only have adverse effects on air quality, but also can affect climate ...change. Although there are extensive recent studies on carbonaceous aerosols, comprehensive studies on their socioeconomic influencing factors in a resource-based city are relatively limited. In this study, the spatial-temporal variations of organic carbon (OC), elemental carbon (EC), and secondary organic carbon (SOC) were investigated in January, July, and October in 2015 and April in 2016 in Wuhai and its surrounding areas. The population distribution and industry layout have led to the uneven spatial-temporal distribution of carbonaceous aerosols. The concentrations of carbonaceous aerosols were higher in winter due to the unfavorable meteorology and the increased emissions from heating. The SOC is a significant contributor to OC in the cold season (52.0% for January). Primary carbonaceous aerosols pollution is higher in the industrial sites of resource-based cities, whereas the SOC makes a significant contribution in the residential sites. The results of backward-trajectory and concentration-weighted trajectory analysis suggest that the local emissions and short-range atmospheric transport from nearby areas have a significant impact on PM2.5 and carbonaceous aerosols. A strong correlation between population density and OC/EC ratio was found, indicating that the megacities with high population density have a higher SOC contribution than the resource-based cities. Resource-based cities are characterized by high level of primary OC emissions, whereas cities with high energy efficiency have a more significant SOC contribution. These results provide a more comprehensive understanding of carbonaceous aerosols in a resource-based city.
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•Carbonaceous aerosols showed a distinct spatial-temporal variation due to the influence of local sources.•The highest concentration of secondary organic carbon was found in winter.•Primary carbonaceous aerosols contribute more in cities with low energy efficiency.
Measurements of PM2.5 concentrations in five major Greek cities over a two-year period using calibrated low-cost sensor-based particulate matter (PM) monitors (Purple Air PA-II) were combined with ...local meteorological parameters, synoptic patterns and air mass residence time models to investigate the factors controlling PM2.5 spatiotemporal variability over continental Greece. Fourteen sensors nodes in Athens, Patras, Ioannina, Xanthi, and Thermi (in the Metropolitan Area of Thessaloniki) were selected out of more than 100 of a countrywide network for detailed analysis. The cities have populations ranging from 65k to 3M inhabitants and cover different latitudes along the South-North axis. High correlations between the daily average PM2.5 levels were observed among all sites, indicating strong intra- and inter-city covariance of concentrations, both in cold and warm periods. Higher PM2.5 concentrations in all cities during the cold period were primarily associated with low temperatures and stagnant anticyclonic conditions, favoring the entrapment of residential heating emissions from biomass burning. Anticyclonic conditions were also connected to an increased frequency of PM2.5 episodes, exceeding the updated daily guideline value (15 μg m−3) of the World Health Organization (WHO). During the warm period, nearly uniform PM2.5 levels were encountered across continental Greece, independently of their population size. This uniformity strongly suggests the importance of long-range transport and regional secondary aerosol formation for PM2.5 during this period. Peak concentrations were associated mainly with regional northern air flows over Greece and the Balkan Peninsula. The use of the measurements from dense air quality sensor networks, provided that a robust calibration protocol and continuous data quality assurance practices are followed, appears to be an efficient tool to gain insights on the levels and variability of PM2.5 concentrations, underpinning the characterization of spatial and seasonal particularities and supporting real-time public information and warning.
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•A network of low cost PM2.5 sensors in five Greek continental cities was used.•An intra- and inter-city positive covariance of PM2.5 concentrations was detected.•Anticyclonic conditions caused daily PM2.5 episodes across Greece in cold seasons.•Uniform PM2.5 levels (8.0–10.8 μg m−3) were measured by all sensors in warm seasons.•CWT and PSCF models indicated regional PM2.5 contributions in warm seasons.
The 24-h PM2.5 samples were collected at the site of East China University of Science and Technology (ECUST) in Shanghai from 2011 to 2012, representing winter, spring, summer and autumn, ...respectively. And PM2.5 and its chemical components including organic carbon (OC), elemental carbon (EC), water-soluble organic carbon (WSOC), humic-like substance carbon (HULIS-C) and water-soluble ions were analyzed. The results suggested that the average PM2.5 concentrations were (70.35±43.75) μg/m3, (69.76±38.67) μg/m3, (51.26±28.25) μg/m3 and (82.37±48.70) μg/m3 in winter, spring, summer and autumn, respectively. Secondary inorganic ions (sulfate, nitrate and ammonium) were the dominant pollutants of PM2.5 in the four seasons. Total carbon (TC) was an important component explaining above 15% of PM2.5. OC/EC ratios were all above 2 ranging from 4.31 to 6.35; particularly in winter it reached the highest 6.35 which demonstrated that secondary organic carbon (SOC) should be a significant composition of PM2.5. The SOC calculated based on the OC/EC ratio method had stronger correlation with WSOC in summer and autumn (summer: R2=0.73 and autumn: R2=0.75). The HULIS-C and SOC most significantly correlated in autumn (R2=0.83). The data showed that PM2.5 atmospheric aerosols were more acidic in autumn and the concentrations of PM2.5 and its chemical components were much higher. Factor analysis (FA), cluster analysis of air mass back trajectories, potential source contribution function (PSCF) model and concentration weighted trajectory (CWT) model were used to investigate the transport pathways and identify potential source areas of PM2.5 in different seasons. FA identified various sources of PM2.5: secondary aerosol reactions, the aged sea salts and road dusts. The results of cluster analysis, PSCF model and CWT model demonstrated that the local sources in the Yangtze River Delta Region (YRDR) made significant contributions to PM2.5. During winter and autumn long-time transport from the Circum-Bohai-Sea Region (CBSR) and northwestern China including the Inner Mongol had adverse effects.
•The characteristics of carbonaceous components especially HULIS-C were analyzed.•The levels of OC, EC and WSOC in acidic and alkaline aerosols were compared.•FA results explained the sources of PM2.5 in Shanghai.•PSCF model identified the likely source areas affecting air quality in Shanghai.
Dust storms are a common phenomenon in arid and semi-arid regions in West Asia, which has led to high levels of PM10 in local and remote area. The Yazd city in Iran with a high PM10 level located ...downstream of dust sources in the Middle East and Central Asia. In this study, based on meteorological and PM10 monitoring data, backward trajectory modeling of air parcels related to dust events at Yazd station was performed using the HYSPLIT model in 2012–2019. The trajectory cluster analysis was used to identify the main dust transport pathways and wind systems. Three methods of Cross-referencing Backward Trajectory (CBT), Potential Source Contribution Function (PSCF) and Concentration Weighted Trajectory (CWT) were used to identify the most critical dust sources. Multi-Criteria Decision Making (MCDM) methods were also used to integrate the results. Nine dust sources affecting central Iran were determined, and six criteria from different aspects were considered. To prioritize the dust sources affecting central Iran from four new MCDM methods, including WASPAS, EDAS, ARAS and TOPSIS were used. The results showed that the Levar wind system (51%), the Shamal wind system (32%) and the Prefrontal wind system (18%) were the most important wind systems to cause dust events in central Iran. The MCDM approach to identify dust sources also showed that Dasht-e-Kavir in central Iran was the most critical dust source. The results also showed that in hot seasons (spring and summer), local and Central Asia dust sources and cold seasons (autumn and winter), Middle East dust sources have the greatest impact on dust events in central Iran. Also, a comparison of common receptor-based methods for identifying dust sources showed that CBT, CWT and PSCF were the most appropriate methods for identifying dust sources, respectively.
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•The characteristics of dust events in central Iran during 2012–2019 were examined.•The main corridors of dust transport were identified using cluster analysis.•The performance of receptor-based models for dust source detection was evaluated.•To integrate the results of receptor-based models, MCDM methods were used.
In order to achieve the targets specified in the Action Plan for Air Pollution Prevention and Control (APAPPC), a limited coal banning area (10,000 km2) was designated in the heavily polluted ...Beijing-Tianjin-Hebei region (BTH) for the first time in 2017. PM2.5 and elements were sampled by the network of BTH to evaluate the effectiveness of this policy. This study found that the fine days with PM2.5 < 75 μg m−3 accounted for 74.3% in the autumn and winter of 2017, which was significantly higher than that in 2016 (43%). The heavily polluted days (PM2.5 > 150 μg m−3) also decreased from 32.2% in 2016 to 4.9% in 2017. Arsenic (As) is an important tracer in coal consumption, which can be used to reflect the influence of the establishment of coal banning areas on north China. The cluster analysis of air mass forward trajectory identified that the number of polluted trajectories with PM2.5 and As in 2017 decreased by 47.6% and 49.7%, respectively. Under the implementation of the coal banning policy, the weighted concentration of PM2.5 and As decreased by 94.2 μg m−3 and 5.1 ng m−3 in the coal banning area, 60.9 μg m−3 and 3.4 ng m−3 in the no coal banning area in BTH, respectively. The influence of weighted concentration of PM2.5 and As in coal banning area on North China were 1.6–49.2 μg m−3 and 0.15–2.8 ng m−3, respectively, which was 38.8% and 29.7% lower than 2016. In coal banning area, BTH and other parts of North China, the reduction of the weight concentration of PM2.5 in 2017 accounted for 41.4%, 26.8% and 31.8% of the total reduction, respectively, so was the As in 39%, 26.3% and 34.6%, indicating that setting up a coal banning area scientifically in limited areas can produce remarkable regional benefit.
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•Coal banning area brought remarkable environmental benefit to the whole north China.•Fine days in the autumn and winter of BTH increased from 43% in 2016 to 74% in 2017.•Impact of PM2.5 in coal banning area (BTH) reduced by 94.2 (60.9) μg m−3 in 2017.•The impact of coal banning area on PM2.5 in North China decreased by 48.3% in 2017.
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