Atmospheric volatile halogenated hydrocarbons in air pollution episodes in an urban area of Beijing: Characterization, health risk assessment and sources apportionment

Determination of Volatile Halogenated Hydrocarbons in Drinking and Environmental Waters by Headspace Gas Chromatography

Volatile halogenated hydrocarbons (VHHs) are annually produced and released into the environment, posing a threat to public health. In this study, a simple, rapid, sensitive and automated method based on headspace and gas chromatography (GC) with electron-capture detection was described for the determination of VHHs in different concentration levels in water samples. The proposed headspace GC method was initially optimized, and the optimum experimental conditions found were 10-mL water sample containing 20% w/v sodium chloride placed in a 20-mL vial and stirred at 60°C for 35 min, and then 14 VHHs were well separated on DB-35 MS capillary column with a split ratio of 12.5: 1. The limits of detection were in the low μg/L level, ranging between 0.01 and 0.6 μg/L. Finally optimized method was applied for determination 14 VHHs in drinking and environmental waters. The total mean concentrations of VHHs were 34.962, 26.183, 3.228 and 647.344 μg/L in tap water, purified water with 1-year-old filter element, seawater and effluents, respectively. However, no VHHs was detected in purified water with a new filter element. The main composition is different among different water matrix, which may be attributed to their different sources.

The Characteristics, Sources, and Health Risks of Volatile Organic Compounds in an Industrial Area of Nanjing

This study investigates the chemical complexity and toxicity of volatile organic compounds (VOCs) emitted from national petrochemical industrial parks and their effects on air quality in an industrial area of Nanjing, China. Field measurements were conducted from 1 December 2022, to 17 April 2023, focusing on VOC concentrations and speciations, diurnal variations, ozone formation potential (OFP), source identification, and associated health risks. The results revealed an average total VOC (TVOC) concentration of 15.9 ± 12.9 ppb and an average OFP of 90.1 ± 109.5 μg m-3. Alkanes constituted the largest fraction of VOCs, accounting for 44.1%, while alkenes emerged as the primary contributors to OFP, comprising 52.8%. TVOC concentrations peaked before dawn, a pattern attributed to early morning industrial activities and nighttime heavy vehicle operations. During periods classified as clean, when ozone levels were below 160 μg m-3, both TVOC (15.9 ± 12.9 ppb) and OFP (90.4 ± 110.0 μg m-3) concentrations were higher than those during polluted hours. The analysis identified the key sources of VOC emissions, including automobile exhaust, oil and gas evaporation, and industrial discharges, with additional potential pollution sources identified in adjacent regions. Health risk assessments indicated that acrolein exceeded the non-carcinogenic risk threshold at specific times. Moreover, trichloromethane, 1,3-butadiene, 1,2-dichloroethane, and benzene were found to surpass the acceptable lifetime carcinogenic risk level (1 × 10-6) during certain periods. These findings highlight the urgent need for enhanced monitoring and regulatory measures aimed at mitigating VOC emissions and protecting public health in industrial areas. In the context of complex air pollution in urban industrial areas, policymakers should focus on controlling industrial and vehicle emissions, which can not only reduce secondary pollution, but also inhibit the harm of toxic substances on human health.

Long-Term Halocarbon Observations in an Urban Area of the YRD Region, China: Characteristic, Sources Apportionment and Health Risk Assessment

To observe the long-term variations in halocarbons in the Yangtze River Delta (YRD) region, this study analyzes halocarbon concentrations and composition characteristics in Shanxi from 2018 to 2020, exploring their origins and the health effects. The total concentration of halocarbons has shown an overall increasing trend, which is driven by both regulated substances (CFC-11 and CFC-113) and unregulated substances, such as dichloromethane, chloromethane and chloroform. The results of the study also reveal that dichloromethane (1.194 ± 1.003 to 1.424 ± 1.004 ppbv) and chloromethane (0.205 ± 0.185 to 0.666 ± 0.323 ppbv) are the predominant halocarbons in Shanxi, influenced by local and northwestern emissions. Next, this study identifies that neighboring cities in Zhejiang Province and other YRD areas are potentially affected by backward trajectory models. Notably, chloroform and 1,2-dichloroethane have consistently surpassed acceptable thresholds, indicating a significant carcinogenic risk associated with solvent usage. This research sheds light on the evolution of halocarbons in the YRD region, offering valuable data for the control and reduction in halocarbon emissions.

A novel approach for the prediction and analysis of daily concentrations of particulate matter using machine learning

Traditional air quality analysis and prediction methods depend on the statistical and numerical analyses of historical air quality data with more information related to a specific region; therefore, the results are unsatisfactory. In particular, fine particulate matter (PM2.5, PM10) in the atmosphere is a major concern for human health. The modelling (analysis and prediction) of particulate matter concentrations remains unsatisfactory owing to the rapid increase in urbanization and industrialization. In the present study, we reconstructed a prediction model for both PM2.5 and PM10 with varying meteorological conditions (windspeed, temperature, precipitation, specific humidity, and air pressure) in a specific region. In this study, a prediction model was developed for the two observation stations in the study region. The analysis of particulate matter shows that seasonal variation is a primary factor that highly influences air pollutant concentrations in urban regions. Based on historical data, the maximum number of days (92 days in 2019) during the winter season exceeded the maximum permissible level of particulate matter (PM2.5 = 15 μg/m3) concentration in air. The prediction results showed better performance of the Gaussian process regression model, with comparatively larger R2 values and smaller errors than the other models. Based on the analysis and prediction, these novel methods may enhance the accuracy of particulate matter prediction and influence policy- and decision-makers among pollution control authorities to protect air quality.

Ambient Volatile Organic Compound Characterization, Source Apportionment, and Risk Assessment in Three Megacities of China in 2019

In order to illustrate pollution characterization, source apportionment, and risk assessment of VOCs in Beijing, Baoding, and Shanghai, field observations of CO, NO, NO2, O3, and volatile organic compounds (VOCs) were conducted in 2019. Concentrations of VOCs were the highest in Beijing (105.4 ± 52.1 ppb), followed by Baoding (97.1 ± 47.5 ppb) and Shanghai (91.1 ± 41.3 ppb). Concentrations of VOCs were the highest in winter (120.3 ± 61.5 ppb) among the three seasons tested, followed by summer (98.1 + 50.8 ppb) and autumn (75.5 + 33.4 ppb). Alkenes were the most reactive VOC species in all cities, accounting for 56.0%, 53.7%, and 39.4% of ozone formation potential in Beijing, Baoding, and Shanghai, respectively. Alkenes and aromatics were the reactive species, particularly ethene, propene, 1,3,5-trimethylbenzene, and m/p-xylene. Vehicular exhaust was the principal source in all three cities, accounting for 27.0%, 30.4%, and 23.3% of VOCs in Beijing, Baoding, and Shanghai, respectively. Industrial manufacturing was the second largest source in Baoding (23.6%) and Shanghai (21.3%), and solvent utilization was the second largest source in Beijing (25.1%). The empirical kinetic modeling approach showed that O3 formation was limited by both VOCs and nitric oxides at Fangshan (the suburban site) and by VOCs at Xuhui (the urban site). Acrolein was the only substance with an average hazard quotient greater than 1, indicating significant non-carcinogenic risk. In Beijing, 1,2-dibromoethane had an R-value of 1.1 × 10-4 and posed a definite carcinogenic risk.

VOC species controlling O3 formation in ambient air and their sources in Kaifeng, China

The concentration of ozone has been in a rising crescendo in the last decade while the fine particles (PM_2.5) is gradually decreasing but still at a high level in central China. Volatile organic compounds (VOCs) are the vital precursors of ozone and PM_2.5. A total of 101 VOC species were measured in four seasons at five sites from 2019 to 2021 in Kaifeng. VOC sources and geographic origin of sources were identified by the positive matrix factorization (PMF) model and the hybrid single-particle Lagrangian integrated trajectory transport model. The source-specific OH loss rates (L_OH) and ozone formation potential (OFP) were calculated to estimate the effects of each VOC source. The average mixing ratios of total VOCs (TVOC) were 43.15 parts per billion (ppb), of which the alkanes, alkenes, aromatics, halocarbons, and oxygenated VOCs respectively accounted for 49%, 12%, 11%, 14%, and 14%. Although the mixing ratios of alkenes were comparatively low, they played a dominant role in the L_OH and OFP, especially ethene (0.55 s^-1, 7%; 27.11 μg/m³, 10%) and 1,3-butadiene (0.74 s^-1, 10%; 12.52 μg/m³, 5%). The vehicle-related source which emitted considerable alkenes ranked as the foremost contributing factor (21%). Biomass burning was probably influenced by other cities in the western and southern Henan and other provinces, Shandong and Hebei.

Chemical Characteristics and Source-Specific Health Risks of the Volatile Organic Compounds in Urban Nanjing, China

This work comprehensively investigated the constituents, sources, and associated health risks of ambient volatile organic compounds (VOCs) sampled during the autumn of 2020 in urban Nanjing, a megacity in the densely populated Yangtze River Delta region in China. The total VOC (TVOC, sum of 108 species) concentration was determined to be 29.04 ± 14.89 ppb, and it was consisted of alkanes (36.9%), oxygenated VOCs (19.9%), halogens (19.1%), aromatics (9.9%), alkenes (8.9%), alkynes (4.9%), and others (0.4%). The mean TVOC/NO_x (ppbC/ppbv) ratio was only 3.32, indicating the ozone control is overall VOC-limited. In terms of the ozone formation potential (OFP), however, the largest contributor became aromatics (41.9%), followed by alkenes (27.6%), and alkanes (16.9%); aromatics were also the dominant species in secondary organic aerosol (SOA) formation, indicative of the critical importance of aromatics reduction to the coordinated control of ozone and fine particulate matter (PM_2.5). Mass ratios of ethylbenzene/xylene (E/X), isopentane/n--pentane (I/N), and toluene/benzene (T/B) ratios all pointed to the significant influence of traffic on VOCs. Positive matrix factorization (PMF) revealed five sources showing that traffic was the largest contributor (29.2%), particularly in the morning. A biogenic source, however, became the most important source in the afternoon (31.3%). The calculated noncarcinogenic risk (NCR) and lifetime carcinogenic risk (LCR) of the VOCs were low, but four species, acrolein, benzene, 1,2-dichloroethane, and 1,2-dibromoethane, were found to possess risks exceeding the thresholds. Furthermore, we conducted a multilinear regression to apportion the health risks to the PMF-resolved sources. Results show that the biogenic source instead of traffic became the most prominent contributor to the TVOC NCR and its contribution in the afternoon even outpaced the sum of all other sources. In summary, our analysis reveals the priority of controls of aromatics and traffic/industrial emissions to the efficient coreduction of O₃ and PM_2.5; our analysis also underscores that biogenic emissions should be paid special attention if considering the direct health risks of VOCs.

Optimization of the Efficient Extraction of Organic Components in Atmospheric Particulate Matter by Accelerated Solvent Extraction Technique and Its Application

Organic components in atmospheric fine particulate matter have attracted much attention and several scientific studies have been performed, although most of the sample extraction methods are time consuming and laborious. Accelerated solvent extraction (ASE) is a new sample extraction method offering number of advantages, such as low extraction cost, reduced solvent and time consumption, and simplified extraction protocols. In order to optimize ASE methods to determine the concentrations of organic compounds in atmospheric fine particulate matter, different parameters were set out for the experiment, and the optimal method was selected according to the recoveries of the standard (i.e., n−alkanes and polycyclic aromatic hydrocarbons (PAHs)). This study also involves a comparison of the optimal method with the traditional method of ultrasonic extraction (USE). In addition, the optimized method was applied to measure the mass concentrations of organic compounds (n−alkanes and PAHs) in fine particulate matter samples collected in Beijing. The findings showed that the average recovery of target compounds using ASE was 96%, with the majority of compounds falling within the confidence levels, and the ASE recoveries and precision were consistent with the USE method tested. Furthermore, ASE combines the advantages of high extraction efficiency, automation, and reduced solvent use. In conclusion, the optimal ASE methods can be used to extract organic components in atmospheric particulate matter and serve as a point of reference for the development of analytical methodologies for assessing organic compounds in atmospheric particulate matter in China.

Characterization of VOCs during Nonheating and Heating Periods in the Typical Suburban Area of Beijing, China: Sources and Health Assessment

In recent years, the “coal to electricity” project (CTEP) using clean energy instead of coal for heating has been implemented by Beijing government to cope with air pollution. However, VOC pollution after CTEP was rarely studied in suburbs of Beijing. To fill this exigency, 116 volatile organic compounds (VOCs) were observed during nonheating (P1) and heating (P2) periods in suburban Beijing. The results showed that the total of VOCs (TVOCs) was positively correlated with PM2.5, PM10, NO2, CO, and SO2 but negatively correlated with O3 and wind speed. The average TVOCs concentration was 19.43 ± 12.41 ppbv in P1 and 16.25 ± 8.01 ppbv in P2. Aromatics and oxygenated VOCs (OVOCs) were the main contributors to ozone formation potential (OFP). Seven sources of VOCs identified by the positive matrix factorization (PMF) model were industrial source, coal combustion, fuel evaporation, gasoline vehicle exhaust, diesel vehicle exhaust, background and biogenic sources, and solvent usage. The contribution of coal combustion to VOCs increased significantly during P2, whereas industrial sources, fuel evaporation, and solvent usage exhibited opposite trends. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) were used to analyze the source distributions. The results showed that VOC pollution was caused mainly by air mass from southern Hebei during P1 but by local emissions during P2. Therefore, although the contribution of coal combustion after heating increased, TVOCs concentration during P2 was lower than that during P1. Chronic noncarcinogenic risks of all selected VOC species were below the safe level, while the carcinogenic risks of most selected VOC species were above the acceptable risk level, especially for tetrachloromethane and 1,2-dichloroethane. The cancer risks posed by gasoline vehicle emissions, industrial enterprises, and coal combustion should be paid more attention.

Quantitative Health Risk Assessment of the Chronic Inhalation of Chemical Compounds in Healthcare and Elderly Care Facilities

Previous studies have described the chemical pollution in indoor air of healthcare and care facilities. From these studies, the main objective of this work was to conduct a quantitative health risk assessment of the chronic inhalation of chemical compounds by workers in healthcare and elderly care facilities (hospitals, dental and general practitioner offices, pharmacies and nursing homes). The molecules of interest were 36 volatile and 13 semi-volatile organic compounds. Several professional exposure scenarios were developed in these facilities. The likelihood and severity of side effects that could occur were assessed by calculating the hazard quotient for deterministic effects, and the excess lifetime cancer risk for stochastic effects. No hazard quotient was greater than 1. Three compounds had a hazard quotient above 0.1: 2-ethyl-1-hexanol in dental and general practitioner offices, ethylbenzene and acetone in dental offices. Only formaldehyde presented an excess lifetime cancer risk greater than 1 × 10⁻⁵ in dental and general practitioner offices (maximum value of 3.8 × 10⁻⁵ for general practitioners). The health risk for chronic inhalation of most compounds investigated did not appear to be of concern. Some values tend to approach the acceptability thresholds justifying a reflection on the implementation of corrective actions such as the installation of ventilation systems.

Risk Assessment and Prediction of Air Pollution Disasters in Four Chinese Regions

Evaluating the regional trends of air pollution disaster risk in areas of heavy industry and economically developed cities is vital for regional sustainable development. Until now, previous studies have mainly adopted a traditional weighted comprehensive evaluation method to analyze the air pollution disaster risk. This research has integrated principal component analysis (PCA), a genetic algorithm (GA) and a backpropagation (BP) neural network to evaluate the regional disaster risk. Hazard risk, hazard-laden environment sensitivity, hazard-bearing body vulnerability and disaster resilience were used to measure the degree of disaster risk. The main findings were: (1) the air pollution disaster risk index of Liaoning Province, Beijing, Shanghai and Guangdong Province increased year by year from 2010 to 2019; (2) the mean absolute error (MAE), root mean square error (RMSE) and mean absolute percentage error (MAPE) of each regional air pollution disaster risk index in 2019, as predicted by the PCA-GA-BP neural network, were 0.607, 0.317 and 20.3%, respectively; (3) the predicted results were more accurate than those using a PCA-BP neural network, GA-BP neural network, traditional BP neural network, support vector regression (SVR) or extreme gradient boosting (XGBoost), which verified that machine learning could be used as a method of air pollution disaster risk assessment to a considerable extent.

Spatial Analysis of Environmental Impacts Linked to Changes in Urban Mobility Patterns during COVID-19: Lessons Learned from the Cartagena Case Study

The impact of the pandemic caused by COVID-19 on urban pollution in our cities is a proven fact, although its mechanisms are not known in great detail. The change in urban mobility patterns due to the restrictions imposed on the population during lockdown is a phenomenon that can be parameterized and studied from the perspective of spatial analysis. This study proposes an analysis of the guiding parameters of these changes from the perspective of spatial analysis. To do so, the case study of the city of Cartagena, a medium-sized city in Spain, has been analyzed throughout the period of mobility restrictions due to COVID-19. By means of a geostatistical analysis, changes in urban mobility patterns and the modal distribution of transport have been correlated with the evolution of environmental air quality indicators in the city. The results show that despite the positive effect of the pandemic in its beginnings on the environmental impact of urban mobility, the changes generated in the behavior patterns of current mobility users favor the most polluting modes of travel in cities.