Contribution Of Emission Sources Research Articles

The variations in volatile organic compounds based on the policy change for Omicron in the traffic hub of Zhengzhou

Abstract. Online volatile organic compounds (VOCs) were monitored before and after the Omicron policy change at an urban site in polluted Zhengzhou from 1 December 2022 to 31 January 2023. The characteristics and sources of VOCs were investigated. The daily mean concentrations of PM2.5 and total VOCs (TVOCs) ranged from 53.5 to 239.4 µg m−3 and 15.6 to 57.1 ppbv, respectively, with mean values of 111.5 ± 45.1 µg m−3 and 36.1 ± 21.0 ppbv, respectively, throughout the period. Two severe pollution events (designated as case 1 and case 2) were identified in accordance with the National Ambient Air Quality Standards (NAAQS) (China's National Ambient Air Quality Standards (NAAQS) from 2012). Case 1 (5 to 10 December PM2.5 daily mean = 142.5 µg m−3) and case 2 (1 to 8 January PM2.5 daily mean = 181.5 µg m−3) occurred during the infection period (when the policy of “full nucleic acid screening measures” was in effect) and the recovery period (after the policy was canceled), respectively. The PM2.5 and TVOC values for case 2 are, respectively, 1.3 and 1.8 times higher than those for case 1. The precise influence of disparate meteorological circumstances on the two pollution incidents is not addressed in this study. The results of the positive matrix factor modeling demonstrated that the primary source of VOCs during the observation period was industrial emissions, which constituted 32 % of the total VOCs, followed by vehicle emissions (27 %) and combustion (21 %). In case 1, industrial emissions constituted the primary source of VOCs, accounting for 32 % of the total VOCs. In contrast, in case 2, the contribution of vehicular emission sources increased to 33 % and became the primary source of VOCs. The secondary organic aerosol formation potential for case 1 and case 2 were found to be 37.6 and 65.6 µg m−3, respectively. In case 1, the largest contribution of SOA formation potential (SOAP) from industrial sources accounted for the majority (63 %; 23.8 µg m−3), followed by vehicular sources (18 %). After the end of the epidemic and the resumption of productive activities in the society, the difference in the proportion of secondary organic aerosol (SOA) generated from various sources decreased. Most of the SOAP came from solvent use and fuel evaporation sources, accounting for 32 % (20.9 µg m−3) and 26 % (16.8 µg m−3), respectively. On days with minimal pollution, industrial sources and solvent use remain the main contributors to SOA formation. Therefore, the regulation of emissions from industry, solvent-using industries, and motor vehicles needs to be prioritized to control the PM2.5 pollution problem.

Hotspots of nitrogen losses from anthropogenic sources in the Huang-Huai-Hai Basin, China.

Poor management of nitrogen (N) can lead to serious environmental problems, such as air and water pollution. The accurate identification of priority control areas and emission sources is critical for making effective decisions regarding sustainable N management. This study aimed to identify hotspots for N losses and quantitatively analyze the relative contributions of different emission sources in the Huang-Huai-Hai Basin at the county scale. Specifically, it focused on N losses from agricultural production (crop production, livestock production, and freshwater aquaculture) and residential sources (urban sewage and rural domestic wastewater). To achieve this, we developed the Model to assess Anthropogenic Nitrogen losses to the Environment, following the mass flow analysis approach. The total N losses from agricultural production and residential sources in the Huang-Huai-Hai Basin were approximately 6.4 Tg per year in 2017, with 56% emitted to water and 44% to the air. Crop production and livestock production accounted for 46% and 45% of the total N losses, respectively. The main pathways of N loss were NH3 emissions to the air (41%) and direct nitrogen discharge to water (28%). Hotspots of total N loss were identified in 202 out of 910 counties, primarily located in the Henan and Hebei provinces. Although hotspots cover less than 7% of the total basin area, they account for 51% of the total N loss. The main driving factors leading to these hotspots are the number of livestock, followed by the use of chemical N fertilizers and the extent of cultivated area. The findings of this study can provide important insights for the targeted control of anthropogenic reactive N loss in the Huang-Huai-Hai Basin.

Research on Ozone Pollution Characteristics and Source Apportionment During the COVID-19 Lockdown in Jilin City in 2022

The increasing Ozone (O3) concentration in various regions of China has garnered significant attention, highlighting the need to understand the mechanisms of O3 formation. This study focuses on the source apportionment of O3 in Jilin City during and after the COVID-19 lockdown countermeasure, and also the influence of anthropogenic emissions on O3 concentration. The contributions of different O3 emission sources were quantified using the Weather Research and Forecasting Community Multi-Scale Air Quality (WRF-CMAQ) model in conjunction with the Integrated Source Apportionment Method (ISAM). The results indicate a significant increase in O3 concentrations during the lockdown in Jilin City, which were particularly characterized by long-distance transportation. Transportation is identified as the primary direct source of O3 in Jilin City, with Yongji County contributing the most among the six designated regions. This study highlights variations in the causes and sources of O3 pollution among the different regions of Jilin City. Simply controlling anthropogenic emissions is inadequate for effectively managing O3 pollution and may even worsen the situation. It is more effective to focus on controlling O3’s precursors. These findings improve the understanding of O3 pollution in Jilin City and provide valuable insights for developing O3 control policies. Similarly, this research is applicable to other countries and regions.

Research on ozone pollution control strategies for urban agglomerations based on ozone formation sensitivity and emission source contributions

Despite recent enhancements in China's anthropogenic emission controls, ozone (O3) concentrations have continuously increased owing to its nature as a secondary pollutant and the complexities of its production and consumption processes. This study quantified the contributions of urban and sectoral cross-emission sources to O3 levels and identified the anthropogenic emission sources requiring targeted control. Moreover, O3 sensitivity tests were conducted to determine optimal reduction ratios for nitrogen oxides (NOx) and volatile organic compounds (VOCs) emissions. The results were used to recommend effective measures for controlling O3 pollution in the Central Plains urban agglomeration (CPUA). The top 35 cities and sectoral cross-emission sources accounted for 80% of the O3 concentrations in the region, indicating the need for prioritized management of these sources. To achieve reductions in O3 concentrations across all cities, it was found that a 10% reduction in total NOx emissions would require a minimum of 18% reduction in VOCs emissions. Our results indicated that the appropriate coordination of reductions in VOCs and NOx emissions reduced the maximum daily 8-h average O3 (MDA8) concentrations in CPUA by 0.14%–4.78%. Enhancing control measures for prioritized emission sources reduced MDA8 concentrations by 0.78%–7.09%. Furthermore, adjusting the production and emission hours of the industrial sector resulted in a decrease in MDA8 concentrations by 1.10%–12.62%. Overall, our findings indicate that appropriately coordinated reduction of precursor emissions can reduce O3 levels. Further efforts to mitigate O3 pollution should include optimizing the timing of emissions from the industrial sector and other major sources of VOCs emissions.

Inverse modelling approach to assess air pollutant emission trends, and source contributions in highly polluted cities

Pollutant concentrations are regularly measured in many cities, but emission loads often remain unknown and are irregularly estimated. This paper presents a methodology to estimate total emissions in a highly polluted megacity using an inverse modeling approach. An inverted Fixed Box Model (FBM) has been used with pollutant concentrations and meteorological variables to estimate emissions of pollutants by discounting the meteorological variability from the measured concentrations. Model-predicted emissions are validated with existing inventories and then used to assess annual, monthly, and diurnal trends in emissions. The applicability of the model is demonstrated for Delhi. Trend analysis shows that pollutants are emitted in a unique pattern that also differs over time periods of consideration. Yearly trends in Delhi show that PM10, NOX, and SO2 emissions have increased by 33%, 4%, and 16%, respectively, during 2008–2018. However, due to controls, the emission intensities have been found to stabilize for PM10 and decrease for NOX and SO2 pollutants in Delhi. Monthly trends indicate that summer months have higher emission rates owing to intensive energy demands (in automobiles, power plants), dust storms, and increased re-suspension of dust due to higher wind speeds. However, due to dispersive meteorology, ambient concentrations are lower in summers. The inverse modeling shows that PM10 emissions are dominated by dust sources (73%), while PM2.5 has the largest contribution from transport sector emissions (34%). NOX and SO2 emissions in the city are contributed heavily by the transport (84%) and industrial (92%) sectors, respectively. The model helps in understanding temporal emission trends and source contributions, which can be useful to implement effective control measures and track the progress of control.

Sources and Specified Health Risks of 12 PM2.5-Bound Metals in a Typical Air-Polluted City in Northern China during the 13th Five-Year Plan.

The continuous monitoring of PM2.5 (including 12 metal elements) was conducted in Jinan, a city with poor air quality in China, during the 13th Five-Year Plan (2016-2020). Positive matrix factorization (PMF) was used to identify emission sources of PM2.5-bound metals, and the health risks of the metals and their emission sources were assessed. During the study period, the concentration of most metals showed a decreasing trend (except Al and Be), and a significant seasonal difference was found: winter > fall > spring > summer. The PMF analysis showed that there were four main sources of PM2.5-bound metals, and their contributions to the total metals (TMs) were dust emissions (54.3%), coal combustion and industrial emissions (22.3%), vehicle emissions (19.3%), and domestic emissions (4.1%). The results of the health risk assessment indicated that the carcinogenic risk of metals (Cr and As) exceeded the acceptable level (1 × 10-6), which was of concern. Under the influence of emission reduction measures, the contribution of emission sources to health risks changes dynamically, and the emission sources that contribute more to health risks were coal combustion and industrial emissions, as well as vehicle emissions. In addition, our findings suggest that a series of emission reduction measures effectively reduced the health risk from emission sources of PM2.5-bound metals.

Source attribution of carbon monoxide over Northern India during crop residue burning period over Punjab

National Capital Territory of Delhi and its satellite cities suffer from poor air quality during the post-monsoon months of October–November. In this study, a novel attempt is made to estimate the contribution of different emission sources (industrial, residential, power generation, transportation, biomass burning, photochemical production, lateral transport, etc.) towards the criteria air pollutant carbon monoxide (CO) concentration over North India. Multiple simulations of the WRF-Chem model with a tagged tracer approach with different inputs (6 anthropogenic emission inventories and 3 biomass burning emission inventories) were used. The model performance was evaluated against the MOPITT retrieved CO surface concentration. Analysis of model simulated CO over North India suggests that anthropogenic emissions contribute around 32–49% to surface CO concentration while crop residue burning contributes 27–44% of which 80% originates from Punjab. For Delhi, the contribution from anthropogenic sources is dominant (53–77%) of which 10–28% is from the domestic sector and 14–55% is from the transport sector. Agricultural waste burning contributes about 15–30% to Delhi's surface CO concentration (of which 75% originates from Punjab). Crop residue burning emission is a chief source of CO over Punjab with a contribution of about 56–76%. The results suggest that industrial, transport, and domestic sector activities are more responsible for increased CO levels over New Delhi and surrounding regions than crop residue burning over Punjab. Furthermore, critical meteorological parameters like 10 m wind speed, boundary layer height, 2 m temperature, total precipitation, and relative humidity were evaluated against CO concentration to understand their impact on CO distribution. Results conclude that deteriorating air quality over the North Indian region is caused by a combination of prevailing meteorological factors (such as slow winds, shallow mixing layer, and cold temperatures) and man-made emissions.

Characteristics and Source Analysis of VOCs Pollution During Emergency Response in Tianjin

To elucidate the characteristics of VOCs chemical components during heavy pollution episodes, hourly online VOCs data derived from 11 heavy pollution events in Tianjin from 2019 to 2020 were employed. The positive matrix factorization （PMF） and conditional bivariate probability function （CBPF） were employed to analyze the sources of VOCs during heavy pollution episodes. The results indicated that the average VOCs volume fraction during these episodes was recorded at 35.7×10-9. Furthermore, it was observed that during the winter emergency response period, there was a discernible increase in the volume fraction of VOCs when compared to that during the autumn season. Specifically, there was a notable upswing of 48% in the olefins category, whereas alkanes registered a 4% increase. Additionally, the VOCs component structure changed significantly during the heavy pollution episodes. During the orange warning period, the proportion of alkanes increased by 36%, and the proportion of acetylene decreased by 32%. During the yellow warning period, the proportion of alkanes increased by 14%, and the proportion of acetylene decreased by 5%. During the emergency response period, motor vehicle emission sources, natural gas evaporative sources, and solvent use sources were the main contributors of VOCs in environmental receptors, contributing 17.5%, 15.4%, and 15.2%, respectively. Compared with that during the period antecedent to the emergency response, the contribution of vehicle emission sources and diesel volatile sources to VOCs in environmental receptors decreased by 2.0% to 5.5% and 2.1% to 6.6%, respectively, and the contribution of solvent use sources decreased by 0.2% to 2.4% during the yellow warning period. During the orange warning period, the contribution of motor vehicle emission sources was reduced by 0.1% to 8.3%, and the contribution of solvent use sources was reduced by 0.5% to 6.2%.

Impacts of the Chengdu 2021 world university games on NO2 pollution: Implications for urban vehicle electrification promotion

Emissions of nitrogen oxides (NOx) are a dominant contributor to ambient nitrogen dioxide (NO2) concentrations, but the quantitative relationship between them at an intracity scale remains elusive. The Chengdu 2021 FISU World University Games (July 22 to August 10, 2023) was the first world-class multisport event in China after the COVID-19 pandemic which led to a substantial decline in NOx emissions in Chengdu. This study evaluated the impact of variations in NOx emissions on NO2 concentrations at a fine spatiotemporal scale by leveraging this event-driven experiment. Based on ground-based and satellite observations, we developed a data-driven approach to estimate full-coverage hourly NO2 concentrations at 1 km resolution. Then, a random-forest-based meteorological normalization method was applied to decouple the impact of meteorological conditions on NO2 concentrations for every grid cell, the resulting data were then compared with the timely bottom-up NOx emissions. The SHapley-Additive-exPlanation (SHAP) method was employed to delineate the individual contributions of meteorological factors and various emission sources to the changes in NO2 concentrations. According to the full-coverage meteorologically normalized NO2 concentrations, a decrease in NOx emissions and favorable meteorological conditions accounted for 80 % and 20 % of the NO2 reduction, respectively, across Chengdu city during the control period. Within the strict control zone, a 30 % decrease in the meteorologically normalized NO2 concentrations was observed during the control period. The normalized NO2 concentrations demonstrated a strong correlation with NOx emissions (R = 0.96). Based on the SHAP analysis, traffic emissions accounted for 73 % of the reduction in NO2 concentrations, underscoring the significance of traffic control measures in improving air quality in urban areas. This study provides insights into the relationship between NO2 concentrations and NOx emissions using real-world data, which implies the substantial benefits of vehicle electrification for sustainable urban development.

An Analysis of Primary Contributing Sources to the PM2.5 Composition in a Port City in Canada Influenced by Traffic, Marine, and Wildfire Emissions

Ambient air quality, specifically fine particulate matter (PM2.5) pollution, poses a global health concern due to its associations with adverse health effects and persistent presence in urban settings. This study investigates PM2.5 exposure in a traffic-influenced residential area in Vancouver, employing chemical speciation data sampled in the vicinity of a major road throughout 2018. Using receptor-oriented models, Positive Matrix Factorization (PMF), and Principal Component Analysis (PCA), major emission sources contributing to the total PM2.5 mass were identified. The Organic and Elemental carbon concentration time series analysis reveals impacts from traffic and episodic influences from wildfires and residential heating. Applying PMF, we attribute identified factors to specific sources: traffic (33%), secondary aerosols (27%), dust (14%), Marine Heavy Fuel Combustion (HFC) (12%), Local (9%), and rare metallic elements (5%), respectively. This apportioning is subsequently verified by PCA, which introduces a sea salt factor to the analysis. Applying the conditional probability function analysis on the integrated wind speed and direction, and the PM concentration data further confirms the partial PM mass apportionment to marine HFC, rare metallic elements, and local factors. Lastly, comparing the results with the 2015 emission inventory of Vancouver shows similarities in apportioning the share of primary sources while overlooking secondary emissions in the latter, emphasizing the importance of field sampling for accurate source characterization. This study highlights the necessity of receptor modeling coupled with field sampling in quantifying the contribution and chemical characteristics of secondary emission sources, particularly near residential neighborhoods. Precise characterization aids health exposure studies that contribute to informed air quality management and policy regulations.

Variations in the oxidation potential of PM2.5 in an old industrial city in China from 2015 to 2018

PM2.5 pollution in China has decreased dramatically, but how its health effects change is not clear. There are 120 old industrial cities in China, where the sources, composition, and health effects of PM2.5 may be significantly different with other cities. Huangshi, an old industrial city in central China, underwent intense green transformations from 2015 to 2018. In this study, we collected ambient PM2.5 samples in 2015 and 2018 at an urban site in Huangshi. The average PM2.5 concentration decreased from 83.44 ± 48.04 μg/m3 in 2015 to 68.03 ± 39.41 μg/m3 in 2018. However, the average volume-normalized dithiothreitol (DTTv) of PM2.5 increased from 1.38 ± 0.45 nmol/min/m3 to 2.14 ± 1.31 nmol/min/m3 and the DTT normalized by particulate mass (DTTm) increased from 20.6 ± 10.1 pmol/min/μg to 40.07 ± 21.9 pmol/min/μg, indicating increased exposure risk and inherent toxicity. The increased toxicity of PM2.5 might be related to the increased trace elements (TEs) concentrations. The positive matrix factorization and multiple linear regression methods were employed to quantify the contributions of emission sources to PM2.5 and DTTv. The results showed that the contribution of coal combustion, industry, and dust to PM2.5 decreased significantly from 2015 to 2018, while that of vehicle emission and secondary sources increased. Despite the decreased fraction of coal combustion and industry sources, their contribution to DTTv increased slightly, which was caused by the increased intrinsic toxicity. The increased intrinsic toxicity was possibly caused by increased TEs, such as Pb, Cu, and V. Besides, the contribution of vehicle emission to DTTv also increased. Overall, these results provide valuable insights into the effectiveness of controlling strategies in reducing particulate health impacts in old industrial cities, and stress the necessity of formulating toxicity-oriented controlling strategies, with special attention to TEs from coal combustion and industry sources as well as vehicle emissions.

Characterization of winter PM2.5 source contributions and impacts of meteorological conditions and anthropogenic emission changes in the Sichuan Basin, 2002–2020

In this study, the Weather Research and Forecasting (WRF) model and Community Multiscale Air Quality–Integrated Source Apportionment Method (CMAQ–ISAM) were utilized, which were integrated with the Multiresolution Emission Inventory for China (MEIC) emission inventory, to simulate winter PM2.5 concentrations, regional transport, and changes in emission source contributions in the Sichuan basin (SCB) from 2002 to 2020, considering variations in meteorological conditions and anthropogenic emissions. The results indicated a gradual decrease in the basin's winter average PM2.5 concentration from 300 μg/m3 to 120 μg/m3, with the most significant decrease occurring after 2014, reflecting the actual impact of China's air pollution control measures. Spatially, the main pollution area shifted from Chongqing to Chengdu and the western basin. The sources of PM2.5 at the eastern and western margins of the basin have remained stable and have been dominated by local emissions for many years, while the sources of PM2.5 in the central part of the basin have evolved from a multiregional co-influenced source during the early period to a high proportion of local emissions; except for boundary condition sources, residential sources were the main PM2.5 sources in the basin (approximately 29.70 %), followed by industrial sources (approximately 14.11 %). Industrial sources exhibited higher contributions in Chengdu and Chongqing and gradually stabilized with residential sources over the years, while residential sources dominated in the eastern and western parts of the basin and exhibited a declining trend. Meteorological conditions exacerbated pollution in the whole basin from 2008 to 2014, especially in the west (21–40 μg/m3). The eastern basin and Chongqing exhibited more years with alleviated meteorological pollution, including a 40+ μg/m3 decrease in Chongqing from 2002 to 2005. Reduced anthropogenic emissions alleviated annual pollution levels, with a greater reduction (> −20 μg/m3) after 2011 due to pollution control measures.

Sources of acellular oxidative potential of water-soluble fine ambient particulate matter in the midwestern United States

Ambient fine particulate matter (PM2.5) is associated with numerous health complications, yet the specific PM2.5 chemical components and their emission sources contributing to these health outcomes are understudied. Our study analyzes the chemical composition of PM2.5 collected from five distinct locations at urban, roadside and rural environments in midwestern region of the United States, and associates them with five acellular oxidative potential (OP) endpoints of water-soluble PM2.5. Redox-active metals (i.e., Cu, Fe, and Mn) and carbonaceous species were correlated with most OP endpoints, suggesting their significant role in OP. We conducted a source apportionment analysis using positive matrix factorization (PMF) and found a strong disparity in the contribution of various emission sources to PM2.5 mass vs. OP. Regional secondary sources and combustion-related aerosols contributed significantly (> 75 % in total) to PM2.5 mass, but showed weaker contribution (43–69 %) to OP. Local sources such as parking emissions, industrial emissions, and agricultural activities, though accounting marginally to PM2.5 mass (< 10 % for each), significantly contributed to various OP endpoints (10–50 %). Our results demonstrate that the sources contributing to PM2.5 mass and health effects are not necessarily same, emphasizing the need for an improved air quality management strategy utilizing more health-relevant PM2.5 indicators.

Ambient volatile organic compounds in the Seoul metropolitan area of South Korea: Chemical reactivity, risks and source apportionment

The chemical reactivity, contribution of emission sources, and risk assessment of volatile organic compounds (VOCs) in the atmosphere of the Seoul metropolitan area (SMA) were analyzed. Datasets collected from 6 photochemical assessment monitoring stations (PAMS) of SMA from 2018 to 2021 were used. Alkenes and aromatics contributed significantly to ozone formation relative to the emission concentrations, and aromatics accounted for most of the secondary organic aerosols (SOA) formation in the SMA. The contributions of ozone and SOA formation were found to be notably higher at measurement stations in residential areas such as Guwol (GW) and Sosabon (SS) compared to other measurement stations. From the results of an emission source analysis, it was confirmed that anthropogenic sources such as combustion sources, vehicle exhaust, fuel evaporation, and solvent use had a significant effect at all measurement stations. Assessing the health risk, non-carcinogenic compounds were at acceptable level at all measurement stations. On the other hand, carcinogenic compounds were approaching risk level (10−4), thereby demanding immediate attention. The level of exposure to carcinogenic compounds increased by age group, and male was more vulnerable than female. It was found that SS had the highest level of exposure to carcinogens in the atmosphere of the population ages 60 or older. The health threat of the SMA population is expected due to direct exposure from inhalation of ambient toxic compounds and indirect exposure from ozone and PM2.5 formations through oxidation of VOCs. This study emphasizes the importance of addressing specific emission sources within the metropolitan area and developing comprehensive regional strategies to mitigate VOCs.

Characteristics and Source Analysis of Carbonaceous Aerosols in PM2.5 in Huaxi District, Guiyang

Carbonaceous aerosol, as an important component of atmospheric aerosol, has a significant impact on atmospheric environmental quality, human health, and global climate change. To investigate the characteristics and sources of carbonaceous aerosol in atmospheric fine particulate matter (PM2.5) in Huaxi District of Guiyang, an in-situ observational study was conducted during different seasons in 2020, and the carbonaceous components of PM2.5 were measured using a thermal-optical carbon analyzer (DRI Model 2015). The results of the study showed that the average concentrations of PM2.5, total carbonaceous aerosol (TCA), organic carbon (OC), secondary organic carbon (SOC), and elemental carbon (EC) concentrations during the observation period were (39.7±22.3), (14.1±7.2), (7.6±3.9), (4.4±2.6), and (2.0±1.0) μg·m-3, respectively, and the mean value of OC/EC was (3.9±0.8). ρ(PM2.5), ρ(TCA), ρ(OC), ρ(SOC), and ρ(EC) showed a seasonal variation pattern with the highest in winter [(52.6±28.6), (17.0±9.6), (9.1±5.2), (6.1±3.9), and (2.4±1.2) μg·m-3, respectively] and the lowest in summer [(25.1±7.1), (11.6±3.6), (6.3±1.9), (3.7±1.2), and (1.6±0.6) μg·m-3, respectively]. The seasonal variation in OC/EC showed summer (4.2±0.8) > winter (3.8±0.9) > autumn (3.8±0.5) > spring (3.7±0.9), indicating the presence of SOC generation in all seasons in Huaxi District. SOC showed a significant correlation with OC (R2 =0.9), and the SOC concentration tended to increase with the increase in atmospheric oxidation. OC showed a good correlation with EC in all seasons, with the highest in autumn (R2 =0.9) and lower correlations in the other three seasons (R2 ranged from 0.74 to 0.75), indicating a common source. According to OC/EC ratio range, it was preliminarily determined that carbonaceous aerosol came from vehicle exhaust emissions, coal burning emissions, and biomass combustion emissions. In order to further quantify the contribution of major emission sources to carbonaceous aerosol, the results of this study using PMF to analyze the sources of carbonaceous aerosol showed that the main sources of carbonaceous aerosol in Huaxi District of Guiyang were coal combustion sources (29.3%), motor vehicle emission sources (21.5%), and biomass combustion sources (49.2%).

Quantifying anthropogenic emission of iron in marine aerosol in the Northwest Pacific with shipborne online measurements

Anthropogenic emissions are recognized as significant contributors to atmospheric soluble iron (Fe) in recent years, which may affect marine primary productivity, especially in Fe-limited areas. However, the contribution of different emission sources to Fe in marine aerosol has been primarily estimated by modeling approaches. Quantifying anthropogenic Fe based on field measurements remains a great challenge. In this study, online multi-element measurements and Positive Matrix Factorization (PMF) were combined for the first time to quantify sources of atmospheric Fe and soluble Fe in the Northwest Pacific during a cruise in spring 2015. Fe concentration in 624 atmospheric PM2.5 samples measured online was 74.58 ± 90.87 ng/m3. The PMF results showed anthropogenic activities, including industrial coal combustion, biomass burning, and maritime transport, were important in this region, contributing 31.4 % of atmospheric Fe on average. In addition, anthropogenic Fe concentration resolved by PMF was comparable to the simulation results of the CMAQ (Community Multiscale Air Quality) and GEOS-Chem (Goddard Earth Observing System-Chemical transport) models, with better correlation to CMAQ (r = 0.76) than GEOS-Chem (r = 0.26). This study developed a new method to estimate atmospheric soluble Fe, which integrates Fe source apportionment results and Fe solubility from different sources. Soluble Fe concentration was estimated as 3.93 ± 5.14 ng/m3, of which 87.0 % was attributed to anthropogenic emissions. Notably, ship emission alone contributed 27.5 % of soluble Fe, though its contribution to total Fe was only 2.2 %. Finally, the total deposition fluxes of atmospheric Fe (37.11 ± 38.43 μg/m2/day) and soluble Fe (1.85 ± 2.13 μg/m2/day) were estimated. This study developed a new methodology for quantifying contribution of anthropogenic emissions to Fe in marine aerosol, which could greatly help the assessment of impacts of human activities on marine environment.

Assessing local and transboundary fine particulate matter pollution and sectoral contributions in Southeast Asia during haze months of 2015–2019

While previous studies have investigated haze events over Southeast Asia (SEA), local and transboundary contributions of various emission sources to haze months over the entire SEA have yet to be assessed comprehensively and systematically. We utilized the Particle Source Apportionment Technique (PSAT) to quantify the spatial local, transboundary, and sectoral contributions to PM2.5 over SEA during the haze months of 2015–2019. Results show that local emission contributions accounted for 56.1 % ~ 94.2 % of PM2.5 in Indonesia, Philippines, Vietnam, and Thailand. Transboundary contributions (23.1 % ~ 57.6 %) from Indonesia notably influenced maritime SEA. Vietnam (15.6 % ~ 39.1 %) and super-regional (17.0 % ~ 34.3 %) contributions outside the SEA exerted remarkable impacts on mainland SEA. Among different sectors, fire emissions contributed the most to PM2.5 over maritime SEA (23.0 % ~ 68.6 %) during the studied haze months, whereas residential and other emissions were the main contributors to mainland SEA (27.2 % ~ 36.7 %). Regarding the source species, primary PM2.5 accounted for the majority of PM2.5. VOC and SO2 composed most of the secondary PM2.5 due to massive VOC emissions in the region and the priority reaction of NH3 with sulfuric acid (H2SO4) to form ammonium sulfate. Besides, the intensified haze months in Oct 2015 and Sep 2019 were characterized by more intensive fire emissions in the region and the climatic variability-induced meteorological effects that provided favorable condition for transboundary air pollution (56.9 % and 44.9 %, respectively, for maritime SEA, as well as 46.0 % and 37.7 %, respectively, for mainland SEA in the two studied haze months). The haze months can be attributed to the notable drought conditions amidst global climatic phenomena such as El Niño and positive Indian Ocean Dipole (IOD) in Oct 2015 and Sep 2019, respectively.

Chemical Characterization of Atmospheric Aerosols in Monte Fenton, Punta Arenas, Chilean Southern Patagonia

This work addresses the chemical characterization of atmospheric aerosols and precipitation in the period from May to November 2019 at Monte Fenton (53.16° S, 71.05° W, 612 m.a.s.l.), 9 km west of Punta Arenas, to study the contribution and distribution of emission sources and chemical enrichment. The main ions (Ca2+, Cl−, K+, Mg2+, Na+, NH4+, NO3− and SO42−) were studied using ion chromatography, and trace elements (Al, Br, Ca, Cl, Cr, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Se, Si, Ti, V and Zn) using energy dispersive X-ray fluorescence. Ions concentration ranged from 5.0 × 10−1 to 2.9 × 104 mg/m3 for Ca2+ and Cl−, respectively; whilst the concentration of elements varied between 8.8 × 10−11 and 2.1 × 10−2 mg/m3, for crZn (crustal Zn) and Fe, respectively. The electrical conductivity (EC, mean = 32.5 µS/cm) and the pH (mean = 6.8), showed the atmosphere of the study site was relatively neutral compared to the standard pH for rain (or snow) without contamination (pH = 5.6), and presented relatively low levels of conductivity compared to the EC standards for distilled water (0.5 to 3 µS/cm) and seawater (30,000 to 60,000 µS/cm). The main contribution to aerosols in the atmosphere of Monte Fenton came from marine and lithospheric sources, followed by local anthropogenic sources such as burning firewood and/or urban waste for heating production, etc., that led to the enrichment of aerosols with high Fe, K, Mn and V content. The results of this study contribute to filling a gap in knowledge of the chemistry of atmospheric aerosols in Southern Patagonia.

Comprehensive Assessment of Pollution Sources and Health Impacts in Suburban Area of Shanghai.

Shanghai, one of China's largest metropolises, faces significant environmental pollution challenges due to rapid economic development. Suburban areas of Shanghai are affected by both long-distance transport and local sources of pollutants. This study conducted an integrated analysis that links health-risk assessment of heavy metals and source apportionment of atmospheric constituents to distinguish the contributions of emission sources and the major sources of health risks. Source-apportionment analysis revealed that secondary sources had the greatest contribution to the local pollutants, indicating the significant influence of peripheral and long-distance transport. Health-risk assessment of Cr, Ni, As, and Cd revealed that local residents were exposed to respiratory health risks, in which Cr is the major contributor. This health risk was primarily associated with emissions from nearby industry-related sources. Our study highlights the significant effects of both long-distance transport and local source emissions on atmospheric composition and human health in large urban agglomerations. The findings can inform future efforts to develop more precise emission-reduction strategies and policy improvements to mitigate environmental pollution and protect public health.

Identification and contribution of potential sources to atmospheric lead pollution in a typical megacity: Insights from isotope analysis and the Bayesian mixing model

Atmospheric particulate matter (PM) enriched with lead (Pb) has severe irreversible effects on human health. Therefore, identifying the contribution of Pb emission sources is essential for protecting the health of residents. Using the Pb isotopic tracer method, this study explored the seasonal characteristics and primary anthropogenic Pb sources for atmospheric PM in Tianjin in 2019. We calculated the contribution of Pb sources using the end-member and MixSIAR models. The results showed that Pb loaded in PM10 was more abundant in January than in July, and was strongly influenced by meteorological conditions and anthropogenic emissions. The primary Pb sources of the aerosol samples originated from coal combustion and vehicle and steel plant emissions, mainly originating from local Pb emission sources in Tianjin. The PM10-bond Pb in January was influenced by regional transportation and local sources. The MixSIAS model calculated the contribution of coal combustion as approximately 50 %. Compared with that in January, the contribution of coal combustion decreased by 9.6 % in July. Our results indicate that some of the benefits of phased-out leaded gasoline have been short-lived, whereas other industrial activities releasing Pb have increased. Furthermore, the results emphasise the practicability of the Pb isotope tracer source approach for identifying and distinguishing between different anthropogenic Pb inputs. Based on this study, scientific and effective air pollution prevention and control programs can be formulated to provide decision support for the guidance and control of air pollutant emissions.