Concentration Weighted Trajectory Analysis Research Articles

Characterization of aerosol composition: Insights from SEM-EDX analysis and CALIPSO overpasses

The effect of atmospheric aerosols on the earth’s radiation budget is primarily through their direct effects. Understanding aerosols’ morphology and elemental composition is crucial in this context. For two years, from January 2017 to December 2018, aerosol samples (PM10) were collected on quartz filter papers using a high-volume sampler (PM10) in Chennai, a semi-urban coastal environment located at 12.81°N, 80.03°E. These filter papers were stored under ambient laboratory conditions and were subsequently subjected to ultrasonication using ethanol as the solvent to separate the aerosols from the filters. The extracted samples were then analyzed using scanning electron microscopy (SEM) for the morphology and energy dispersive X-ray analysis (EDX) for elemental composition. The EDX analysis of the samples revealed the presence of various elements such as carbon (C), oxygen (O), aluminum (Al), silicon (Si), sulfur (S), potassium (K), iron (Fe), magnesium (Mg), calcium (Ca), vanadium (V), bismuth (Bi), sodium (Na), chlorine (Cl), phosphorus (P), and technetium (Tc). High concentrations of carbon, oxygen, and aluminum–silicate particles indicated the presence of carbonaceous aerosols and wind-blown dust particles. Concentration-weighted trajectory (CWT) analysis was carried out to assess the transport pathways of aerosols in the region. CALIPSO overpasses during the study period were selected, and the Vertical Feature Mask (VFM) identifiers for different aerosol types were compared with the local experimental results. The findings show that CALIPSO possess a reasonably effective capability in detecting and characterizing the local aerosol types. CALIPSO detected Dusty marine, Clean marine, Elevated smoke and Polluted dust in the study area across all four seasons. These findings closely match the characteristics of such aerosol types obtained from SEM/EDX analysis, HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) modeling, and the Angstrom exponent derived from sunphotometer readings.

Application of quasi-empirical orthogonal functions to estimate wildfire impacts in northwestern Spain

Galicia (NW Spain) is one of the most fire-prone regions in Southern Europe. In the summer of 2022, a total of thirteen wildfires each exceeding 500 ha were reported in this area, with ten of these large fires occurring in the Ourense region. To study the impacts of wildfire smoke plumes on ambient air PM2.5 concentrations, a network of 18 PurpleAir monitors was deployed across the Galicia region during July and August 2022. The PM2.5 concentration data were then used as input to test the applicability of quasi-empirical orthogonal functions (QEOFs obtained with Positive Matrix Factorization (PMF)) to characterize the spatial variability of wildfire smoke impacts on air quality. HYSPLIT back-trajectory analysis and Concentration-Weighted Trajectory (CWT) models were implemented, and the results from these tools were combined with source contributions. As a result, 19 wildfires were identified and linked with peak ambient PM2.5 concentrations (>300 μg/m3 of PM2.5; 1-h mean). Specifically, the Folgoso do Courel fire emerged as a significant contributor to these high concentrations and played an important role in influencing a significant number of the identified factors. Moreover, the results also suggested that emissions from fires in Portugal reached the study area, contributing additional impacts on air quality. These results demonstrated that this approach was useful in identifying the emission source areas contributing to observed PM2.5 concentrations during wildfire events. The PM2.5 concentration maps resulting from the CWT analysis were also valuable in understanding the short- and long-term exposures to PM2.5 from wildfire smoke.

Seasonal variation, source identification, and health risk assessment of atmospheric polycyclic aromatic hydrocarbons (PAHs) in Ulsan, South Korea

Gaseous and particulate 21 PAHs were monitored at a residential site in Ulsan, South Korea, over three seasons (December 2013–August 2014). The mean concentrations of Σ21 PAHs were highest in winter (16.2 ± 8.2 ng/m3), followed by spring (8.37 ± 4.53 ng/m3) and summer (6.23 ± 2.53 ng/m3). The mean gaseous concentration of Σ21 PAHs (7.39 ± 4.39 ng/m3) was 2.7 times higher than that of particulate PAHs (2.70 ± 3.38 ng/m3). To identify the sources of PAHs (both types of sources and their areas), diagnostic ratios, principal component analysis, and concentration-weighted trajectory (CWT) were used. The results showed that pyrogenic sources (e.g., coal combustion) were the primary emission sources of PAHs in winter and spring. In summer, the influence of both coal and heavy oil combustion was dominant, suggesting that PAHs could be transported from industrial areas of Ulsan (e.g., petrochemical and nonferrous industrial complexes) by seasonal winds. Regarding emission source areas, the CWT analysis revealed that in winter and spring, PAHs in Ulsan could be attributed to emissions from regional areas, e.g., China and North Korea. The PAH concentrations were also used to assess the health risks associated with the inhalation of these compounds for adults aged 18–70. The results showed that the cancer risks from Σ19 PAHs and Σ13 PAHs did not exceed the guideline set by the US EPA (10−6), indicating no cancer risks for this target group. However, it is worth noting that certain PAHs, which are not listed as priority PAHs by the US EPA, make significant contributions to the benzo[a]pyrene equivalent and the associated cancer risks. Therefore, it is necessary to investigate not only the priority PAHs but also other PAH species to fully evaluate their effect on human health.

Influence of Transboundary Pollution on the Variability of Surface Ozone Concentrations in the Desert Southwest of the U.S.: Case Study for Arizona

Arizona, a rapidly growing state in the southwestern U.S., faces ozone pollution challenges, including nonattainment areas in Yuma and Maricopa counties influenced by neighboring state pollution transport. In this study, we use five-year (2017–2021) hourly back-trajectories and O3 concentration data for concentration-weighted trajectory (CWT) analysis to identify transport pathways and potential source regions of O3 at six monitoring sites in Arizona. We divide the data into five seasons (winter, spring, dry summer, monsoon summer, and fall) to examine variations in O3 concentration and transport across sites and seasons. The highest mean O3 concentrations occur during spring (37–49 ppb), dry summer (39–51 ppb), and monsoon summer (34–49 ppb), while winter (19–41 ppb) exhibits the lowest seasonal mean. The CWT results reveal that high O3 concentrations (≥40 ppb) in Arizona, with the exception of Phoenix and Tucson sites, are influenced significantly by regional and international transport, especially in spring (14.9–35.4%) and dry summer (12.7–26.9%). The major potential source areas (excluding the Phoenix and Tucson sites) are predominantly located outside Arizona. This study highlights the critical role of pollution transport in influencing O3 variability within Arizona and will be valuable in shaping pollution control strategies in the future.

Sources, gas-particle distribution and health risks of atmospheric PAHs in two typical basin cities in China

The sources of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere of various cities are highly intricate. Conducting research on the pollution characteristics of different types of PAHs in cities will help to focus on solving air pollution problems based on urban characteristics. Polycyclic aromatic hydrocarbons (PAHs) in the PM2.5-bound state and gas-phase were analyzed in the winter atmosphere of Yuncheng and Nanyang, China, to determine their pollution and spatial characteristics. The results revealed that in Yuncheng, the average concentrations of these 16 PAHs were 129.83 ± 96.63 ng m−3 in the PM2.5-bound form and 168.05 ± 88.64 ng m−3 in the gas phase, surpassing those observed in Nanyang, where the averages were 66.53 ± 32.49 ng m−3 and 112.80 ± 65.90 ng m−3 for particulate and gas phases, respectively. Gaseous samples primarily contained low molecular weight PAHs, while medium and high molecular weight PAHs were more prevalent in particulate samples. The linear relationship between the gas-particle partition coefficient (logKP) and the gas partition coefficient (PL0) and KOA value of PAHs in both cities suggested that during winter, PAHs in Yuncheng and Nanyang predominantly adsorb onto particles, failing to achieve gas-particle equilibrium. Source analysis using positive matrix factorization (PMF) identified coal combustion (26.4%–41.9%), biomass combustion (26.3%–29.6%), motor vehicle emissions (16.3%–30.4%), and evaporation sources (15.8%–26.9%) as the primary sources of atmospheric PAHs in both cities. Potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) analyses indicated that pollutants originating from the northwest direction and near-earth air masses exerted a substantial influence on both cities. According to health risk assessments, both Yuncheng City and Nanyang City exhibited a certain risk of cancer due to atmospheric PAH exposure. However, the risk of cancer was higher in Yuncheng City compared to Nanyang City. The research results uncover the pollution characteristics and primary sources of polycyclic aromatic hydrocarbons (PAHs) in different types of urban air. It emphasizes the substantial contribution of local pollution sources to atmospheric PAHs and emphasizes the necessity of prioritizing control measures.

Source apportionment of atmospheric ammonia in suburban Beijing revealed through 15N-stable isotopes

Addressing the urgent issue of atmospheric ammonia (NH3) emissions is crucial in combating poor air quality in megacities. Previous research has highlighted the significant contribution of nonagricultural sources, particularly fossil fuel emissions, to urban NH3 levels. However, there is limited assessment of NH3 dynamics in suburban areas. This study focuses on four suburban sites in Beijing, covering a 16 to 22-month observation period, to investigate spatial and temporal patterns of NH3 concentrations. The δ15N-stable isotope method is employed to identify NH3 sources and their contributions. Our results demonstrate that agricultural sources (53 %) dominate atmospheric NH3 emissions in suburban areas of Beijing, surpassing nonagricultural sources, and primarily emanate from local sources. Notably, fertilizer application (37 ± 11 %) and livestock breeding (32 ± 6 %) emerge as the primary contributors in summer and spring, respectively, leading to significantly elevated NH3 concentrations during these seasons. Even in autumn and winter, both agricultural (49 %) and nonagricultural (51 %) sources contribute almost equally to NH3 emissions. This study emphasizes the need for coordinated efforts to control atmospheric NH3 pollution in Beijing City, with particular attention to addressing both vehicular and agricultural emissions.

Variation characteristics, source analysis, and health risk assessment of carbonyl compounds in Zhangjiajie National Forest Park, China

This study presents a comprehensive analysis of carbonyls in the atmosphere of Zhangjiajie Forest from May 2016 to January 2017 following the Environmental Protection Agency (EPA) TO-11 A guidelines, including pollution characteristics, human health risks, and sources. The dominant carbonyl compounds were formaldehyde, acetaldehyde, and acetone, with average concentrations of 5.94, 1.48, and 4.24 μg/m3, respectively. A seasonal variation was observed in the total carbonyl compound concentrations in the order summer > autumn > spring > winter. The diurnal patterns showed that the concentration of the main carbonyl compounds peaked in the afternoon. The ratios of formaldehyde/acetaldehyde (C1/C2) and acetaldehyde/propionaldehyde (C2/C3) ranged from 2.82 to 5.66 and 0.76–3.14; this indicates that compared with anthropogenic sources, volatile organic compounds emitted from natural sources contributed more significantly to atmospheric carbonyl compounds in the Zhangjiajie Forest. Correlation analysis of the three main carbonyl compounds with common air pollutants revealed that formaldehyde and acetaldehyde have similar secondary sources for photochemical reactions. In autumn and winter, acetaldehyde and acetone were affected by fuel combustion and vehicle exhaust emissions. Reverse trajectory, potential source contribution function, and concentration-weighted trajectory analyses revealed that carbonyl compounds in the atmosphere of Zhangjiajie Forest were mainly polluted locally in spring and autumn and influenced by the urban air mass from the northeast in summer and winter. The health risk assessment showed that the lifetime carcinogenic risk of formaldehyde and acetaldehyde exceeded the acceptable level and that long-term exposure to this concentration poses serious carcinogenic risks. The findings of this study shed light on the characteristics of atmospheric carbonyl compound pollution in subtropical forest areas, and provide scientific basis for formulating pollution control measures.

Autumn and spring observations of PM2.5-bound polycyclic aromatic hydrocarbons and nitro-polycyclic aromatic hydrocarbons in China and Japan

The transboundary transport of polycyclic aromatic hydrocarbons (PAHs) and nitro-PAHs (NPAHs) aggravated by the East Asian winter monsoon is a major atmospheric environmental issue in East Asia. To thoroughly elucidate the role of the East Asian monsoon on regional PAH and NPAH pollution in East Asia, PM2.5-bound PAHs and NPAHs were investigated concurrently at five sites in Beijing and Shenyang in China and Tsukuba, Kanazawa, and Wajima in Japan in autumn (November 2018) and spring (March 2019). During both autumn and spring sampling periods, the concentrations of PM2.5, PAHs, and NPAHs at sites in China were 1–2 orders of magnitude higher than those at sites in Japan, and showed an opposite temporal variation, with higher concentrations during the autumn sampling period due to intensive emissions and unfavourable weather conditions. During the sampling periods, PAHs at the Beijing and Shenyang sites had mixed sources of traffic emissions and coal and biomass combustion, while those at the Tsukuba, Kanazawa, and Wajima sites were mainly characterized by domestic traffic emissions. In addition, NPAHs at the five sites were jointly affected by primary combustion sources and atmospheric generation, with a greater contribution of atmospheric generation to the Beijing and Shenyang sites. Based on backwards trajectory clustering and concentration-weighted trajectory analysis, external contributions to PM2.5, PAHs, and NPAHs at each site were relatively stable during the two sampling periods, and potential source areas were mainly distributed in domestic cities and nearby sea areas. Therefore, the apparent temporal differences in the characteristics and sources of pollutants between sites in the two countries indicate that transboundary pollution dominated by the East Asian winter monsoon was unobvious in autumn and spring. The results of the study provide a time-specific solution for the effective management of regional air pollution during the East Asian winter monsoon.

Study on O3 Variations in Nanjing and the Surrounding Source Analysis

To understand the transport patterns and major sources of ozone (O3) in Nanjing, this study carried out the 48-hour backward trajectories of air masses in Nanjing from March 2021 to March 2022, based on the HYSPLIT backward trajectory model driven by GDAS global reanalysis data. The primary transmission routes and putative source locations of O3 pollution in Nanjing were determined through the integration of trajectory clustering analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) analysis with meteorological data and O3 concentration data. The results showed that the high O3 concentrations and exceedance rates in Nanjing were in late spring and early summer, with the highest in June. The diurnal variation of O3 concentrations in all seasons exhibited a single peak with a maximum from 13:00 to 16:00. The southeasterly flow passing through Zhenjiang, Changzhou, Wuxi, Suzhou, and Shanghai dominated the O3 pollution in Nanjing. The PSCF and CWT presented a high consistency of O3 potential sources in Nanjing. Zhenjiang, Ma’anshan, Changzhou, Wuxi, Suzhou, and Huzhou were identified as the main potential source regions of O3 pollution in Nanjing. This study provides accurate theoretical references for regional joint prevention and control of O3 pollution in Nanjing.

Temporal variability, meteorological influences, and long-range transport of atmospheric aerosols over two contrasting environments Agartala and Patiala in India.

The present study focused on the temporal variability, meteorological influences, potential sources, and long-range transport of atmospheric aerosols over two contrasting environments during 2011-2013. We have chosen Agartala (AGR) city in Northeast India as one of our sites representing the rural-continental environment and Patiala (PTA) as an urban site in Northwest India. The seasonal averaged equivalent black carbon (eBC) concentration in AGR ranges from 1.55 to 38.11µg/m3 with an average value of 9.87 ± 8.17µg/m3, whereas, at an urban location, PTA value ranges from 1.30 to 15.57µg/m3 with an average value of 7.83 ± 3.51µg/m3. The annual average eBC concentration over AGR was observed to be ~ 3 times higher than PTA. Two diurnal peaks (morning and evening) in eBC have been observed at both sites but were observed to be more prominent at AGR than at PTA. Spectral aerosol optical depth (AOD) has been observed to be in the range from 0.33 ± 0.09 (post-monsoon) to 0.85 ± 0.22 (winter) at AGR and 0.47 ± 0.04 (pre-monsoon) to 0.74 ± 0.09 (post-monsoon) at PTA. The concentration of eBC and its diurnal and seasonal variation indicates the primary sources of eBC as local sources, synoptic meteorology, planetary boundary layer (PBL) dynamics, and distant transportation of aerosols. The wintertime higher values of eBC at AGR than at PTA are linked with the transportation of eBC from the Indo-Gangetic Plain (IGP). Furthermore, it is evident that eBC aerosols are transported from local and regional sources, which is supported by concentration-weighted trajectory (CWT) analysis results.

Quantifying the seasonal variations in and regional transport of PM2.5 in the Yangtze River Delta region, China: characteristics, sources, and health risks

Abstract. Given the increasing complexity of the chemical composition of PM2.5, identifying and quantitatively assessing the contributions of pollution sources has played an important role in formulating policies to control particle pollution. This study provides a comprehensive assessment between PM2.5 chemical characteristics, sources, and health risks based on sampling data conducted over 1 year (March 2018 to February 2019) in Nanjing. Results show that PM2.5 exhibits a distinct variation across different seasons, which is primarily driven by emissions, meteorological conditions, and the chemical conversion of gaseous pollutants. First, the chemical mass reconstruction shows that secondary inorganic aerosols (62.5 %) and carbonaceous aerosols (21.3 %) contributed most to the PM2.5 mass. The increasing oxidation rates of SO2 and NO2 from summer to winter indicate that the secondary transformation of gaseous pollutants is strongly positively correlated with relative humidity. Second, the positive matrix factorization (PMF) method shows that identified PM2.5 sources include secondary inorganic aerosol source (SIS, 42.5 %), coal combustion (CC, 22.4 %), industry source (IS, 17.3 %), vehicle emission (VE, 10.7 %), fugitive dust (FD, 5.8 %), and other sources (1.3 %). The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the concentration-weighted trajectory (CWT) analysis are used to further explore different spatial distributions and regional transport of sources. The concentrations (10–11 µg m−3) of SIS and CC distribute in Nanjing and central China in winter. The concentrations (8–10 µg m−3) of IS and VE are potentially located north of Jiangsu, Anhui, and Jiangxi. Finally, the health risk assessment indicates that the carcinogenic and non-carcinogenic risks of toxic elements (Cr, As, Ni, Mn, V, and Pb) mainly come from IS, VE, and CC, which are within the tolerance or acceptable level. Although the main source of pollution in Nanjing is SIS at present, we should pay more attention to the health burden of vehicle emissions, coal combustion, and industrial processes.

Tibetan Plateau is vulnerable to aromatic-related photochemical pollution and health threats: A case study in Lhasa

Anthropogenic aromatics play a key role in photochemical pollution and pose a serious threat to human health. Current knowledge on source characteristics of aromatics in the urban region of the Tibetan Plateau (TP), the “Third Pole” and ecologically sensitive area, remains limited. In this study, an intensive observation of 17 aromatic hydrocarbons was conducted in Lhasa, the cultural and economic center of TP, during the second Tibetan Plateau Scientific Expedition and Research in summer 2020. The results showed that the average concentration of aromatics in Lhasa (7.6 ± 7.4 ppbv) was unexpectedly higher than those in megacities such as Beijing, Shanghai, and Guangzhou. Tripled concentrations and corresponding ozone formation potential during pollution episodes were recorded. Further source apportionment using positive matrix factorization revealed that solvent usage (60.0 %) was the dominant source, which may be due to the extremely low atmospheric pressure. Vehicle exhaust (15.4 %), industrial emissions (12.8 %), fuel evaporation (6.2 %), and burning emissions (5.7 %) were also important sources. The concentration weighted trajectory analysis revealed that the observed high levels of aromatics were mainly driven by local anthropogenic emissions, rather than the regional transport by the Indian summer monsoon. Long-term exposure to aromatics in Lhasa was assessed to pose carcinogenic risks to the population, with the risks of benzene and ethylbenzene 5 times the criteria. Our results suggest that, given the magnified emissions of aromatics in this extreme environment (low atmospheric pressure and strong solar radiation), the implementation of targeted pollution controls is urgently needed to mitigate the aromatic-related photochemical pollution and health threats in TP.

Spatial prediction of PM[formula omitted] concentration using hyper-parameter optimization XGBoost model in China

High-fine particulate matter (PM2.5) pollution has become the main object of damaging the atmospheric environment and endangering human health. Accurate prediction of the spatial variability of PM2.5 concentrations using high-performance models is crucial for the prevention and control of atmospheric pollution. In this paper, in order to avoid the uncertainty caused by artificially setting the parameters of the prediction model, a new hyper-parameter optimization extreme gradient boosting (HPO-XGBoost) model for spatial prediction of PM2.5 concentration was proposed. We used aerosol optical depth (AOD) data of Himawari-8 satellite combined with the HPO-XGBoost model to predict and mapping the spatial variability of PM2.5 concentrations during the COVID-19 lockdown in China. The results showed that the maximum concentration of PM2.5 exhibited a downward trend and a significant seasonal fluctuation from 2015 to 2020. Compared with grid search (GS) and random grid search (RGS) optimization algorithms, the tree-structured Parzen estimator-XGBoost (TPE-XGBoost) approach has the highest prediction accuracy (R2) of 89.37% (January), 85.58% (February), 80.02% (March), and 83.68% (April) for PM2.5 concentrations in 2020, respectively. Spatial mapping of the monthly average PM2.5 concentration from January to April using the TPE-XGBoost model showed that the regions with higher PM2.5 concentrations are concentrated in northern China, eastern China and northeastern China, where PM2.5 concentrations exceed 150 μg m−3 in January. Furthermore, the spatial correlation analysis showed that factors with the highest driving effect of PM2.5 concentrations during the COVID-19 lockdown were factory (FAC) and traffic (TRA), and the strongest contribution of the double-factor synergy (q > 0.8) for all four months included factory-residence (FAC-RES) and factory-population (FAC-POP). The contribution source of PM2.5 transport showed a long-distance channel in Taiyuan, Xi’an and Shijiazhuang, while the cluster-like distribution and mixed distribution of contribution sources were embodied in Zhengzhou, Changchun and Harbin based on concentration-weighted trajectory (CWT) analysis. The above results showed that the TPE-XGBoost has strong nonlinear explanation and effective feasibility for spatial prediction of PM2.5 concentrations, and the transport of PM2.5 was dynamic effect which should be considered into account when developing prevention and control measures of atmospheric pollution in epidemic period.

Potential Source Area and Transport Route of Atmospheric Particulates in Xi’an, China

Atmospheric particulate pollution is one of the most common pollution related issues and poses a serious threat to human health. PM2.5 and PM10 are important indicators of atmospheric particulate pollution currently. Based on the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model, the hourly 72 h backward trajectory of particulate matter in Xi’an from March 2019 to February 2022 was calculated, and the main path of air flow to Xi’an was studied by cluster analysis. Combined with hourly concentration monitoring data of PM2.5 and PM10 at each station, the potential source area of particles in Xi’an was calculated by potential source contribution factor analysis and concentration weighted trajectory analysis. The results show that Xi’an was most polluted in winter, followed by autumn and spring, and cleanest in the summer. The annual average mass concentrations of PM2.5 and PM10 are 48.5 ± 28.7 μg/m3 and 89.2 ± 39.2 μg/m3, respectively, both exceeding the national secondary standard for ambient air quality. On an annual basis, back-trajectory analysis showed that predominantly transport was rapid from the northwest (44%). Transport from the other sectors were 24%, 19%, and 14% from the northeast, southeast, and southwest, respectively, and featured lower windspeeds on average. The potential source areas of particulate matter in Xi’an in the spring are mainly located at the junction of Chongqing, Hunan, and Hubei, and parts of the southeast and north of Sichuan. This study provides context for air quality and atmospheric transport conditions in this region of China.

An episode-based assessment for the adverse effects of air mass trajectories on PM2.5 levels in Astana and Almaty, Kazakhstan

PM2.5 pollution is a severe problem in most cities in Kazakhstan and is a leading cause of premature deaths globally. This study examines the temporal variation of PM2.5 levels and the effect of air mass transportation dynamics on episodic air pollution in Kazakhstan's two largest cities. In 2021 annual PM2.5 concentrations in Astana (22.5 μg m−3) and Almaty (35.3 μg m−3) exceeded the annual WHO limit by 4.5 and 7.1 times, respectively. The daily limits surpassed 151 days in Astana and 217 days in Almaty. PM2.5 levels were highest in winter averaging 35.3 μg m−3 (Astana) and 76.0 μg m−3 (Almaty) over the heating season, with coal combustion as a main contributor. The HYSPLIT model was used to assess the impact of air mass trajectories on pollution episodes and clean air events. Cluster and concentration-weighted trajectory analyses showed that air pollution episodes in both cities were associated with the anticyclone-blocking effect. While both cities were exposed to the influence of long-range transported pollutants, Astana was more frequently impacted by distant sources. Given the transboundary nature of air pollution in both cities and the complex relationship between meteorology and emission sources, a regional integrated air quality improvement strategy is needed.

Annual Variation of PM2.5 Chemical Composition in Ho Chi Minh City, Vietnam Including the COVID-19 Outbreak Period

PM2.5 was continuously collected in Ho Chi Minh City (HCMC), Vietnam, during the period from September 2019 to August 2020, which included the period of socioeconomic suppression caused by restrictions imposed in the face of the coronavirus disease of 2019. The concentrations of PM2.5 mass, water-soluble ions (WSIs), organic carbon (OC), elemental carbon (EC), and water-soluble organic carbon (WSOC) were determined to evaluate the seasonal variations in PM2.5, the effect of socioeconomic suppression on PM2.5, and potential PM2.5 sources in HCMC. The PM2.5 mass concentration during the sampling period was 28.44 ± 11.55 μg m−3 (average ± standard deviation). OC, EC, and total WSIs accounted for 30.7 ± 6.6%, 9.7 ± 2.9%, and 24.9 ± 6.6% of the PM2.5 mass, respectively. WSOC contributed 46.4 ± 10.1% to OC mass. NO3−, SO42−, and NH4+ were the dominant species in WSIs (72.7 ± 17.7% of the total WSIs’ mass). The concentrations of PM2.5 mass and total WSIs during the rainy season were lower than those during the dry season, whereas the concentrations of carbonaceous species during the rainy season were higher. The concentrations of PM2.5 mass and chemical species during the socioeconomic suppression period significantly decreased by 45%–61% compared to the values before this period. The OC/EC ratio (3.28 ± 0.61) and char-EC/soot-EC (4.88 ± 2.72) suggested that biomass burning, coal combustion, vehicle emissions, cooking activities are major PM2.5 sources in HCMC. Furthermore, the results of a concentration-weighted trajectory analysis suggested that the geological sources of PM2.5 were in the local areas of HCMC and the northeast provinces of Vietnam (where coal-fired power plants are located).

Variations in local, transported, and exposure risks of PM2.5 pollution: Insights from long-term monitoring data in mega coastal city

Urban air quality is influenced by both local and external sources of pollution. The outbreak of Coronavirus COVID-19 had led to implementation of stringent lockdowns at different levels of governance. National Level Lockdown (NLL) was imposed in 2020 and State Level Lockdown (SLL), in 2021 to curb the spread of disease. A direct consequence of lockdown is the dramatic improvement of air quality in various urban agglomerations. The present study investigated the effects of national and regional lockdown on PM2.5 levels at various urban morphological units in the Chennai Metropolitan Region, the fourth-largest urban conglomeration in India. Hourly measurements of PM2.5 over a 6-year period (2016–2021) at three monitoring sites in Chennai were segregated into Pre-lockdown Phase (PLP) (2016–2019), NLL, and SLL to analyze reductions in PM2.5 levels. Local PM2.5 sources were investigated using Conditional Bivariate Probability Function (CBPF) whereas transported PM2.5 was evaluated using Concentration Weighted Trajectory (CWT) and Cluster Analysis. The results showed that PM2.5 in Chennai Metropolitan Region reduced by 33.45% during NLL and 48.95% during SLL when compared to PLP. Mann Kendall Test showed a statistically significant (p < .001) decreasing PM2.5 trend at Manali Monitoring Site, Alandur Monitoring Site, and Velachery Monitoring Site. CBPF showed variations in local contributions for all sites during the selected time frames. CWT and Cluster analysis showed reductions in transported PM2.5 during NLL and SLL when compared to PLP. Health Risk Assessment using Integrated Exposure Response (IER) model function showed a decreasing trend of excess mortality for various health endpoints over 6-year period. Steep reductions in excess mortality cases were observed during NLL and SLL. The results show that lockdown implemented at the state level proved to be more effective than the national level in reducing PM2.5 levels over Chennai metropolitan Region.

Estimation of surface PM2.5 with MODIS Aerosol optical depth and source identification using trajectory analysis: A case of Hyderabad City, India

Satellite measurements are important for quantifying the ground observations and atmosphere columnar properties like Aerosol Optical Depth (AOD) especially in developing countries like India. In this study Moderate Resolution Imaging Spectroradiometer (MODIS) retrieval’s AOD product has been used having 3 km and 10 km spatial resolution from terra and aqua satellites, The MODIS AOD data and meteorological parameters from May 2017 to May 2019 were used. The Multiple linear regression method is implemented in this study. The study concluded that there is a good agreement in the prediction of PM2.5 at Zoopark location, whereas in other monitoring locations the agreement between AOD and measured PM2.5 is relatively poor. The particulate matter (PM) concentrations are influenced by the local source regions and the long-range transport of pollutant through the wind, whereas the source regions identified based on the Potential Source Contribution Function (PSCF), Concentration-Weighted Trajectory (CWT) and Cluster analysis indicate the dominant source regions. Results indicate that the Central India and East Indian regions are more dominating source regions at Hyderabad location in the winter season. It was found that the lower altitude layer showed the major source of local regions nearby receptor. The cluster analysis indicates that the high intensity from the East Indian regions. This paper not only demonstrates reasonable prediction accuracy but also provides the model uncertainties which lays foundation for further study.

Analysis of air pollution characteristics, transport pathways and potential source areas identification in Beijing before, during and after the COVID-19 outbreak

A series of lockdown measures in response to the Corona Virus Disease 2019 (COVID-19) outbreak resulted in a drop in anthropogenic emissions and changes in concentrations of PM2.5 and O3. Backward trajectories analysis, cluster analysis, potential source contribution function (PSCF) and concentration weighted trajectory (CWT) technologies were conducted to reveal the characteristics and potential source areas of pollutants in Beijing before the COVID-19 outbreak (BCO period), during the outbreak (COB period) and after the outbreak (ACO period), as well as the contemporaneous period in 2019 (CCO period), which is critical for exploring the efficient control measures and making policy. The results indicated that despite the significant reduction in anthropogenic emissions during the epidemic, the PM2.5 concentrations increased by 1.0% caused by unfavorable meteorological conditions. O3 concentrations increased by 174.8% compared to that during the BCO period due to the increased temperature and inappropriate precursor reduction ratios. A considerable decrease of NO3- in PM2.5 was observed under the influence of significant reductions in vehicle emissions during the lockdown. The cluster analysis revealed that short-range transport played a significant role in the accumulation of local PM2.5 pollution, while long-range northwest airflows contributed more to O3 accumulation, and weakened as the season changed. The PSCF and CWT analysis demonstrated that potential source areas of PM2.5 were mostly located in the central and southern Hebei, the southwestern Shandong in the CCO period, and expanded to central Inner Mongolia and northern Shanxi in the COB period. These areas were highly compatible with the high emission areas of the emission inventory statistics. After the outbreak, the source areas of O3 were centered in the Beijing-Tianjin-Hebei region and Shandong province, with a radial dispersion in all directions, while they were distributed in the central Mongolia and Inner Mongolia during the other periods.

Enhanced nitrate contribution during winter haze events in a megacity of Sichuan Basin, China: Formation mechanism and source apportionment

Chengdu, a typical basin city in China, still suffers from severe haze pollution in recent years. To gain a comprehensive understanding of the chemical causes and sources of fine particle matter (PM2.5) in this city, online observations of PM2.5 species and other pollutants were conducted at an urban supersite in winter of 2018. The average PM2.5 concentration during the observation period was 71.7 μg/m3, of which nearly half of the measurement days exceeded China's National Air Quality Standard (75 μg/m3). The most abundant species in PM2.5 was organic carbon (20.5%), followed by nitrate (16.0%), ammonium (13.2%), and sulfate (12.8%). Among them, nitrate formation contributed substantially to haze pollution, a phenomenon enhanced by the ammonia-rich environment and heterogeneous reactions. The positive matrix factorization model analysis showed that the largest contributor to PM2.5 was secondary aerosol formation (43.4%), while industrial process contributed the least (3.3%). In addition, two combustion sources, coal combustion and biomass burning/fireworks, accounted for 14.1% and 12.5%, respectively, and their contributions increased significantly with PM2.5 concentration. Air mass trajectory clustering analysis and concentration-weighted trajectory analysis showed that southeastern part of Chengdu was the hotspot for major pollution sources. These results suggest that sustained haze pollution improvement requires continuous strengthening control of precursors such as NOx and NH3, and strict control of combustion sources may be the key to eliminate heavy pollution, and various joint prevention and control measures should be implemented for specific pollution areas.