Pollution Characteristics and Source Apportionment of Volatile Organic Compounds in Typical Solvent-using Industrial Parks in Beijing

We measured volatile organic compounds (VOCs) during the heating, non-heating, and sandstorm periods in the air of the Dushanzi district in NW China and investigated their concentrations, chemical reactivity, and sources. The observed concentrations of total VOCs (TVOCs) were 22.35 ± 17.60, 33.20 ± 34.15, and 17.05 ± 13.61 ppbv in non-heating, heating, and sandstorm periods, respectively. C2-C5 alkanes, C2-C3 alkenes, benzene, and toluene were the most abundant species, contributing more than 60% of the TVOCs. Among these VOCs, alkenes such as propene had the highest chemical reactivity, accounting for more than 60% of total hydroxyl radical loss rate (LOH) and ozone formation potential (OFP). Chemical reactivity was the highest in the heating period. The average reaction rate constant (KOH-avg) and average maximum incremental reactivity coefficient (MIR-avg) of the total observed VOCs were (8.72 ± 1.42) × 10−12 cm3/mol∙s and 2.42 ± 0.16 mol/mol, respectively. The results of the source apportionment via the Positive Matrix Factorization (PMF) model showed that coal combustion (43.08%) and industrial processes (38.86%) were the major sources of VOCs in the air of the Dushanzi district. The contribution of coal combustion to VOCs was the highest in the heating period, while that of industrial solvents and oil volatilization was the lowest.

Characterization, reactivity, source apportionment, and potential source areas of ambient volatile organic compounds in a typical tropical city

Ambient volatile organic compounds(VOCs) were determined by GC 5000 online gas chromatography in three functional areas of Shenyang, namely industrial, traffic, and mixed cultural and educational areas. The pollution characteristics of VOCs in these functional areas during the heating and non-heating periods were analyzed, and the ozone formation potential(OFP) was estimated by using maximum incremental reactivity(MIR). The results show that the average mass concentration of VOCs is(82.19±54.99) μg·m-3 in Shenyang, of which the concentration in industrial areas is significantly higher than that in traffic and cultural and educational mixed areas, and the heating period is higher. The traffic and mixed cultural and educational areas have bi-modal characteristics due to the morning and evening traffic, and the industrial area has multiple peaks affected by the irregular operation hours. The proportion of VOCs in traffic and mixed cultural and educational areas shows the order of alkanes>aromatic hydrocarbons>alkenes>alkynes, but the proportion of alkynes in industrial areas is higher than that of alkenes. The benzene to toluene(B/T) and ethane to acetylene(E/A) ratios reflects that traffic and mixed cultural and educational areas were affected by both vehicle exhaust emissions and fuel combustion. The industrial zone is therefore affected by complex sources, and there are more aged air masses during the heating period than non-heating period. The average OFP contribution of atmospheric VOCs in Shenyang is 232.89 μg·m-3. The contribution of alkenes is largest for all functional areas, and the aromatic component also contributes more due to the high concentration of industrial areas.

Effects of regional transport from different potential pollution areas on volatile organic compounds (VOCs) in Northern Beijing during non-heating and heating periods

Characteristics and source apportionment of volatile organic compounds (VOCs) at a coastal site in Hong Kong

To study the atmospheric PM2.5 pollution characteristics and sources in heating and non-heating periods in Shenyang, 113 groups of effective PM2.5 samples were collected from January 29, 2015 to January 26, 2016, and the water-soluble ions, carbon constituents and elements in PM2.5 were tested. The results indicated that the average PM2.5 mass concentration in Shenyang during the sampling period was 66 μg·m-3. Among the sampled PM2.5 concentrations, 31.0% exceeded the daily value of the secondary standard limit of the Chinese National Ambient Air Quality Standard (75 μg·m-3). The average concentration and over-standard rate of PM2.5 in the heating period (90 μg·m-3, 68.6%) was higher than that of the non-heating period (51 μg·m-3, 31.4%). The concentrations of the 21 elements (except Mg, Ti, Ca, Fe, and Si), water-soluble ions (except Ca2+), OC, and EC were all higher in the heating period than in the non-heating period. The ratio of[NO3-]/[SO42-]showed that the influence of moving source increased obviously in the non-heating period, and fixed source was still the main contributor in the heating period. The water-soluble ions were the result of the interaction of fixed source and moving source. The NOR and SOR analyses showed that the secondary conversion of NOx was weak, and the secondary conversion of SO2 was obvious, especially in the non-heating period. The enrichment factor showed that the elements with high EF value mainly came from coal burning, traffic pollution, and industrial emissions. The reconstructed PM2.5 masses were highly correlated with the measured ones. The main constituents of PM2.5 in both heating and non-heating seasons were organic matter (28.0%, 23.1%), mineral dust (14.5%, 26.0%), and sulfate (15.1%, 19.9%), and PM2.5 was mainly affected by the secondary particles, combustion sources and dust sources.

From June to August 2018, a 1-hr resolution concentration dataset of ozone and its gaseous precursors (volatile organic compounds(VOCs) and NOx), and meteorological parameters were synchronously monitored by online instruments of the Nankai University Air Quality Research Supersite. The relationships and variation characteristics between ozone and its precursors were analyzed. According to the photochemical age, the initial concentrations of VOCs were calculated, and the photochemical loss of the concentration of VOCs during the daytime (06:00-24:00) was corrected. The initial and directly monitored concentrations of VOCs were incorporated into the PMF model for source apportionment. The results indicated that the mean concentration of O3 in Tianjin in summer was (41.3±25.7)×10-9, while that of VOCs was (13.9±12.3)×10-9. The average concentration of alkane (7.0±6.8)×10-9 was clearly higher than that of other VOC species. The species with high concentrations of alkanes were propane and ethane, accounting for 47% of the total alkane concentration. The average ozone formation potential (OFP) in summer was 52.1×10-9, and the OFP value of alkene was the highest and its contribution reached 57%. During the daytime, alkene loss accounted for 75% of the total VOC loss. The major sources of VOCs that were calculated based on the initial concentration data were the chemical industry and solvent usage (25%), automobile exhaust (22%), combustion source (19%), LPG/NG (19%), and gasoline volatilization (15%), respectively. Compared with the apportionment results based on directly monitored concentrations, the contribution of the chemical industry and solvent usage decreased by 4%, while automobile exhaust decreased by 5%. By combining the results of PMF apportionment and the OFP model to analyze the relative contributions of emission sources to ozone formation, and we found that the highest contribution source of ozone was the chemical industry and solvent usage (26%) in summer. Compared with the analysis results based on the directly monitored concentrations, the OFP values of the chemical industry and solvent usage decreased by 7%, while that of NG/LPG apparently decreased by 13%.

Pollution characteristics, source apportionment and absorption spectra of size-resolved PAHs in atmospheric particles in a cold megacity of China

Health risk of heavy metal exposure from dustfall and source apportionment with the PCA-MLR model: A case study in the Ebinur Lake Basin, China

The objective was to investigate the characteristics and sources of ambient volatile organic compounds (VOCs) in the karst region in southwestern China. We monitored atmospheric VOCs in Liuzhou by the GC955 VOCs Online Monitoring System and analyzed the pollution characteristics, ozone formation potential (OFP), aerosol formation potential (AFP), and the positive matrix factorization (PMF) model in March 2019. The results show that ① 50 kinds of VOC components were detected during the supervised period, with an average daily concentration of 25.52×10-9 mol·mol-1, which was composed of alkanes (56.08%), alkenes (19.63%), alkynes (14.25%), and aromatics (10.04%), respectively. ② The concentration of VOCs was lower during the day and higher at night, with the highest value at 23:00. The VOC concentration was low in daytime and high at night. The peak value of VOCs with regard to diurnal variation was correlated with the time of morning and the evening traffic peak and may be influenced by various factors. ③ The contribution of alkenes, aromatics, and alkanes to OFP was 44.30%, 33.03%, and 19.96%, respectively. This indicates that the control of aromatic and olefin should prioritize alkanes. In addition, Liuzhou city is in the VOC sensitive area of O3 generation, and the reduction of VOCs had a controlling effect on O3 generation. ④ The contribution of aromatic hydrocarbons to AFP was up to 95.27%. Therefore, the improvement and control of the processes in motor vehicle exhaust emissions, solvent use, and the automobile industry and the chemical industry could effectively suppress ozone and haze pollution. ⑤ The emission sources of VOCs in spring were mainly industrial emission sources (28.34%), motor vehicle sources (25.47%), combustion sources (24.37%), solvent sources (13.28%), and plant emission sources (8.54%), respectively. This indicates that the control of industrial emission sources, motor vehicle sources, and combustion sources is the main way to control VOC pollution in Liuzhou City. Meanwhile, the olefin and aromatic hydrocarbons emitted by these emission sources should be mainly considered.

A comparative study of cloud condensation nuclei measured between non-heating and heating periods at a suburb site of Qingdao in the North China

Air samples were collected and analyzed by GC-MS to investigate the component characteristics of volatile organic compounds (VOCs) in winter in Jincheng. PMF, ratio analysis, and the backward trajectory model were used to investigate sources of VOCs. Ozone formation potential and secondary organic aerosol formation potential were calculated, in order to analyze the environmental implications of detected VOCs. Results showed that the average concentration of VOCs was 93.35 μg·m-3 in Jincheng, with the most abundant component being alkane (52.91 μg·m-3 and 56.68% of total VOCs). Based on PMF analysis, five sources of ambient VOCs in Jincheng were identified, namely industrial emission sources (33.71%), fuel combustion sources (30.27%), vehicle emissions (26.28%), solvent evaporation sources (9.00%), and plant emission sources (0.74%). Ratios of B/T and i-pentane/n-pentane were 1.58±0.68 and 2.07±0.43, indicating that VOCs were derived from the mixture of road and coal combustion sources. Clustered analysis of the air mass backward trajectory showed that three air masses cluster, which were accounting for 50%, 25% and 25% of the total back trajectories respectively, all came from the northwest, and industrial pollution from the northwest might therefore significantly influence VOCs in Jincheng. With low wind speed (<3 m·s-1), the air quality index, concentration of total VOCs, and contribution rate of vehicle emissions were 143, 162.48 μg·m-3, and 46.16%, respectively, higher than values at faster wind speeds (3-6.9 m·s-1). Ozone formation potential and secondary organic aerosol formation potential of aromatic hydrocarbons, which had the highest formation potential, were 98.89 μg·m-3 and 1.21 μg·m-3, respectively, accounting for 37.28% and 97.01% of total formation potential. To reduce the pollution of VOCs in Jincheng, it is important to control industrial emissions, vehicle emissions, and fuel combustion emissions.

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.

Samples of ambient volatile organic compounds （VOCs） were collected using SUMMA canisters at three Country Control Sites in Shijiazhuang during the spring of 2019, 2021, and 2022, which were detected using gas chromatography/mass spectrometry （GC/MS）. To investigate the characteristics and temporal variations of VOCs mass concentration levels, the online monitoring data of ozone （O3） and PM2.5 at the same site were also collected. Subsequently, the ozone formation potential （OFP） and secondary organic aerosol formation potential （SOAFP） were utilized to assess the chemical activity of VOCs. Additionally, the potential source areas of VOCs in spring in Shijiazhuang were further identified using the potential source contribution factor （PSCF） method and concentration weight trajectory analysis （CWT）. Hence, the major VOCs sources were evaluated with the VOCs initial mixing ratio. The results demonstrated that the averaged concentration of VOCs during the polluted period and clean period of spring in Shijiazhuang were 191.17 μg·m-3 and 122.18 μg·m-3, respectively. Meanwhile, the OFP was 361.23 μg·m-3 during the polluted period and 266.96 μg·m-3 during the clean period, whereas the SOAFP was 1.98 μg·m-3 and 1.61 μg·m-3, respectively. Therefore, effective control of benzene, toluene, ethylbenzene, and xylene （BTEX） is crucial for reducing PM2.5 and O3 pollution. Based on the results obtained from weight PSCF and CWT, the potential source areas of VOCs were further identified to be primarily located in the eastern Yuhua District, the high-tech district, and the northern Luancheng District of Shijiazhuang. These areas were influenced not only by local emissions but also by transport from neighboring regions, in which consistency between the CWT and PSCF results further supported these findings. Furthermore, the results obtained from the benzene/toluene/ethylbenzene （B/T/E） and xylene/benzene （X/B） ratios indicated that the main sources of VOCs in Shijiazhuang in spring were vehicle exhaust sources and burning sources, leading to a more serious air mass aging phenomenon. Hence, controlling vehicle emissions and implementing regional cooperative measures are the effective strategies for optimizing the air quality of Shijiazhuang.

Characteristics, source apportionment and contribution of VOCs to ozone formation in Wuhan, Central China