The Sichuan Basin is one of China's most haze-prone regions due to its unique topography and stagnant meteorological conditions. To understand the winter haze formation mechanisms in the Sichuan Basin, a field campaign was conducted in a previously identified pollution hotspot (Southern Sichuan, December 2024 to February 2025). During this campaign, PM2.5 concentration averaged 63.79 +/- 42.92 mu g m-3, and we identified three haze episodes (H1-H3) during this campaign. The chemical speciation of fine aerosol was characterized using a quadrupole aerosol chemical speciation monitor (Q-ACSM), and the apportionment of organic aerosols (OAs) was solved by EPA PMF 5.0. The results indicated that OAs dominated the PM2.5 composition throughout this campaign, with OA concentrations particularly high in H1 (64.63 +/- 20.77 mu g m-3) and H2 (64.11 +/- 19.05 mu g m-3). Biomass burning organic aerosols (BBOA) and oxygenated organic aerosols (OOA) were the primary contributors to these high concentrations. The haze episodes resulted mainly from early-stage biomass burning emissions and less-aged OOA, occurring concurrently with the highest levels of aerosol liquid water content (ALWC), suggesting the humid air can favor the formation of haze. In addition to local emissions, regional transport synergized with meteorological conditions also significantly contributed to haze formation during this campaign, especially in H2 (38.2 %), quantified by a machine learning based deweathering analysis. This study underscores the intricate interplay between emissions, regional transport, and meteorology in driving haze formation in the Sichuan Basin and demonstrates the utility of machine learning aided diagnostics for source attribution and regulatory insights.

Seven different types of industrial boilers in Sichuan Province were selected to determine the VOC emission components and the source profiles of VOCs containing 115 components were established using Teflon sampling and GC-MS/FID analysis. The ozone formation potential （OFP） and emission factors of VOCs from different types of industrial boilers were analyzed. The results showed that the VOC components emitted from different types of industrial boilers were different. Oxygenated volatile organic compounds （OVOCs） and halogenated hydrocarbons were the major components of biomass boilers, with a total contribution rate of more than 60%. The primary VOC emission species included dichloromethane, ethylene, acetone, acetaldehyde, acetylene, and toluene. Halogenated hydrocarbons （50.7%） were the chief emission components of coal-fired boilers, followed by aromatic hydrocarbons and OVOCs. Dichloromethane, ethylene, acetaldehyde, ethyl acetate, and benzene hydrocarbon were the major VOC emission species. The emission of alkanes （59.7%） in natural gas boilers was prominent, particularly ethane and isopentane. The OFP values of VOC emissions from coal-fired, biomass, and natural gas industrial boilers were 6.1, 28.7, and 4.7 mg·m-3, respectively. Alkenes were the primary OFP contributors （35.1%-59.5%） in different types of industrial boilers. OVOCs （32.8%） in biomass boilers and aromatic hydrocarbons （43.0%） in coal-fired boilers also contributed significantly to OFP. The VOC emission factors of coal-fired, biomass, and natural gas industrial boilers in Sichuan Province were （17.3 ± 10.7） g·t-1, （90.6 ± 42.1） g·t-1, and 0.10 g·m-3, respectively. The VOC emission level of biomass boilers was higher than that of coal-fired boilers and VOC emission control could not be ignored.

The meteorological conditions and monitoring data of ozone and its precursors (NOx, VOCs) in Chengdu during summer (June-August 2019) were analyzed. The average concentration of VOCs in Chengdu during the summer is 36.63 +/- 12.92 ppbv. The daily time series variation of ozone concentration presented unimodal type distribution, reaching the peak in the afternoon (4:00-6:00 p.m.). The heavy ozone pollution was basically accompanied by meteorological conditions of high temperature, low humidity, and low wind speed. The source apportionment of VOCs was conducted by using the positive matrix factorization (PMF) receptor model. The industrial sources, vehicle emission and fuel evaporation were identified as the main sources of VOCs, contributing 26.43%, 21.97% and 17.63% to VOCs respectively. The ozone formation potential (OFP) values indicated that the key active species were aromatics and alkenes represented by m/p-xylene and ethylene. The ridge line of the EKMA curve showed that the VOCs/NOx ratio was about 9.5, hence the emission reduction ratio of VOCs should be much higher than that of NOx in the summer aiming for ozone prevention and control work. The results of backward trajectory clustering, potential source contribution function (PSCF), and concentrationweighted trajectory (CWT) showed that ozone in Chengdu was affected by both local and regional sources in the summer. The potential source regions of ozone are mainly come from local urban areas and eastern and southern Sichuan cities.

Simulations of 108 emission reduction scenarios for NOx and VOCs using Comprehensive Air Quality Model with Extensions (CAMx) were conducted for eight cities in the Chengdu metropolitan area (CMA). The isopleth diagrams were drawn to explore the responses and differences of ozone (O3) concentrations to NOx and VOCs emission changes under Chengdu, CMA and Sichuan Province emission reduction scenarios. The results show that the O3-sensitive regimes of eight cities may change under different emission reduction scenarios. Under Chengdu emission reduction scenario, the Chengdu city is in the transition regime and O3 formation will shift from transition to VOC-limited when the VOCs emissions decreased by 50%, and the decreases in O3 concentrations caused by VOCs emission reductions are small. For the CMA and Sichuan Province emission reduction scenarios, all cities are NOx-limited in the baseline cases and with at least a 66% and a 77% reduction in NOx emissions, respectively, the daily maximum 8-h average O3 (MDA8) can attain the O3 standard (160 μg m−3). Although reductions in VOCs emissions can also lessen the O3 concentration, the effectiveness is relatively small. The changes in O3 concentrations under different VOCs to NOx emission reduction ratios indicate that all cities achieve a relatively high O3 concentration decrement with low VOCs to NOx emission reduction ratios and that the decreasing O3 concentrations caused by non-local emission reductions are much higher than those achieved by local emission reductions. In addition, the decreases in O3 concentrations in Chengdu are quite close when the total NOx and VOCs emissions reduction percentages are less than 30% under the CMA and Sichuan emission reduction scenarios.

NMHCs concentrations and VOCs components were sampled from 12 typical catering units in Sichuan Province. Combined with literature data, the cooking source profile containing 117 VOCs was established comprehensively, and the NMHCs emission factors were obtained. Based on the bottom-up research method, the volatile organic compounds emission inventory of cooking sources in Sichuan Province was established. The results showed that the oxygen and alkane groups were the most important components for Sichuan cuisine, barbecue, and canteen, and the total proportion of the two groups was greater than 75%. The main VOCs species were ethanol, formaldehyde, ethane, hexanal, ethylene, 1,3-butadiene, and acrolein. Oxygen-containing components contributed the most to OFP, followed by olefin. The major OFP contributors were formaldehyde, ethylene, ethanol, 1,3-butadiene, acrolein, hexanal, etc. In 2019, the VOCs emissions and OFP values of cooking sources in Sichuan Province were 32kt and 141kt, respectively, accounting for approximately 5% of the anthropogenic VOCs emissions and OFP values in Sichuan Province. The VOCs emission from cooking may have an important contribution to ozone formation, which means more attention should be paid to cooking.

Oxygenated volatile organic compounds (OVOCs) are important intermediates in the troposphere and the most important sources of ozone. Proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) was used to measure VOCs in the Chengdu Plain, Southwestern China. The diurnal variations, photochemical reactivity, O3 formation potential, and sources were also investigated. The mixing ratios of ten kinds of VOCs (acetaldehyde, acetone, isoprene, Methyl ethyl ketone, Methyl vinyl ketone and Methacrolein, benzene, toluene, styrene, C8 aromatics, and C9 aromatics) were (10.97±4.69)×10-9. The concentrations of OVOCs, aromatic hydrocarbons, and biogenic VOCs were (8.54±3.44)×10-9, (1.53±0.93)×10-9, and (0.90±0.32)×10-9, respectively. Isoprene, acetaldehyde, and m-xylene were the top three photochemically active species with the greatest O3 formation potentials. The dominant three OVOCs species (acetaldehyde, acetone, and MEK) were mainly derived from local biogenic sources and anthropogenic secondary sources, and acetone had a strong regional background level, indicating that pollution in this area is significantly affected by regional transmission. This study deepens the understanding of regional O3 formation mechanisms in southwest China and provides a basis for the scientifically informed control of O3 pollution.

To continuously improve air quality, after implementation of the “Clean Air Action Plan, 2013–2017” (CAAP), the “Three-year Action Plan to Fight Air Pollution” (TYP) was further conducted from 2018 to 2020. However, the effectiveness of the TYP remains unclear in one of the major city-clusters of China, the Sichuan Basin. In this study, the bottom-up method was used to quantify the emission reduction during TYP based on the emissions inventory in Sichuan Basin in 2017 and the air pollution control measures adopted from 2018 to 2020 in each city. The reduction of PM2.5 concentration and the avoided premature deaths due to implementation of air pollution control measures were assessed by using an integrated meteorology and air quality modeling system and a concentration-response algorithm. Emissions of SO2, NOx, PM2.5, and VOCs in the Sichuan Basin have been reduced by 42.6, 105.2, 40.2, and 136.6 Gg, respectively. The control of non-electricity industry contributed significantly to the emission reduction of all pollutants, accounting for 26–49%. In addition, the control of mobile sources contributes the most to NOx reductions, accounting for 57%. The results illustrate that the focus of air pollution control in Sichuan Basin is still industrial sources. We also found that the emission reduction of NOx, PM2.5, and VOCs in Chengdu is significantly higher than that of other cities, which were about 3.4~15.4 times, 2.2~40.1 times, and 4.3~24.4 times that of other cities, respectively. In Sichuan Basin, the average reduction rate of PM2.5 concentration due to air pollution control measures was 5% on average, with the highest contributions from industry, mobile source, and dust emission control. The decrease rate in each city ranges between 1~10%, and the decreasing ratios in Dazhou (10%), Chengdu (8%), and Zigong (7%) are relatively higher. The number of premature deaths avoided due to air pollution control measures in Sichuan Basin is estimated to be 22,934. Chengdu and Dazhou have benefitted most from the air pollution control measures, with 6043 and 2713 premature deaths avoided, respectively. Our results indicate that the implementation of TYP has achieved remarkable environmental and health benefits.

Facing the dual challenges of air pollution and climate change, China has set ambitious goals and made decisive efforts to reduce its carbon emission and win the ‘Battle for Blue Sky’. However, how the low-carbon transition and air quality targets could be simultaneously achieved at the sub-national levels remains unclear. The questions arise whether province-level climate change mitigation strategies could help ease the air pollution and close the air quality gap, and how these co-benefits can be compared with the cost of the green transition. Here, using an integrated modeling framework, we combined with local air pollutant emission inventories and issued policy documents to quantitatively evaluated the current situation and targets of the air quality and health co-benefits of deep carbon mitigation in Sichuan, a fast-developing inland province in China. We found that by 2035, without system-wide energy transformation induced by carbon mitigation policies, the improvement in air quality in Sichuan Province might be limited, even under stringent end-of-pipe emission control measures. On the contrary, the co-benefits of low-carbon policies would be significant. On top of stringent end-of-pipe controls, the implementation of carbon mitigation policy in line with China’s enhanced climate target could further reduce the average PM2.5 concentration in Sichuan by as much as 2.8 µg m−3, or the population-weighted PM2.5 concentration by 5.9 µg m−3 in 2035. The monetized health co-benefits in Sichuan Province would amount to 23 billion USD under the stringent carbon mitigation scenario, exceeding 1.7 billion USD of the mitigation cost by 2035. The results indicate that significant air quality and health benefits could both be achieved from carbon mitigation at the provincial level. Both air-pollution or carbon-reduction oriented policies would be important for improving environmental quality and public health.

To study the characteristics of O3 pollution and identify the key precursors for O3 formation in Chengdu in spring, O3 concentrations in April between 2016 and 2018 were analyzed, and on-line measurements of O3 and the precursors(VOCs and NOx) were also studied at an urban site. The results showed that the O3 pollution level in April increased year by year, and diurnal variations showed a unimodal distribution. When the ambient temperature was more than 20℃, the wind speed was between 1 and 1.5 m·s-1, and the relative humidity was less than 65%, the probability of O3 pollution occurring in April was more than 80%. In April 2018, the average concentrations of NOx and VOCs during O3 pollution days were 2.3-times and 2-times higher than non-pollution days. Furthermore, an OBM method was used to calculate the RIR values of different ozone precursors. This showed that the RIR values of anthropogenic VOCs, CO, biogenic VOCs, and NOx for ozone were 2.4, 0.87, 0.06, and -2.6, respectively, indicating that O3 formation in Chengdu was generally VOC-limited. The RIR values of the VOC species showed that m/p-xylene, ethylene, trans-2-butane, propylene, o-xylene, toluene, acetone, isoprene, isopentane, and n-butane were the key active VOC species of ozone formation.

Volatile organic compounds (VOCs) are critical precursors of secondary pollutants such as O3 and PM2.5; some VOCs are also harmful to human health directly. In recent years, O3 pollution in summer and PM2.5 pollution in winter have occurred frequently in Chengdu, a megacity in southwest China. Effective pollution control on O3 and PM2.5 require clarification of VOCs pollution characteristics. In this study, 90 VOC species were observed using the online VOC monitoring system in June 2018 and in January 2019 at an urban monitoring station in Chengdu. The positive matrix factorization (PMF) model and the potential source contribution function (PSCF) model were used to analyze the main sources and potential source regions of VOCs in summer and winter. The O3 formation potentials (OFPs) of VOCs from different species, sources, and its contribution to secondary organic aerosols (SOA) were analyzed. Additionally, the health risks of human exposure to VOCs were also assessed. The results showed that the mixing ratio of total VOCs (TVOCs) in winter (53.3 ppbv) was around twice as high as in summer (26.8 ppbv), and TVOCs were mainly composed of alkanes. From the perspective of diurnal variation, the high values of VOCs in the morning and evening were mainly affected by traffic, and the low mixing ratios of VOCs in the afternoon was mainly due to photochemical reactions. The main sources of VOCs in downtown Chengdu was LPG/NG usage, which accounted for more than 30% in both summer and winter. The main potential source regions of TVOCs were from the western and northern regions with industrial contribution. The regional transmission characteristics between the two seasons were different, pollutants diffused in short distance and moved slowly in summer, while they migrated far and spread widely in winter. The most reactive species were alkenes and aromatics which contributed most to O3 formation potentials. VOCs from solvent utilization, vehicle exhaust, and LPG/NG usage were the main precursors of O3. VOC concentration in the atmosphere is unlikely to cause evident non-carcinogenic risk to human health, but still poses potential carcinogenic risk.

采用大气挥发性有机物(VOCs)在线监测系统对成都市冬季重污染过程的VOCs进行了连续在线观测,用正交矩阵因子分解(PMF)模型开展了VOCs源解析工作,并对重污染成因进行了分析.结果表明:观测期间成都市总VOCs(TVOCs)体积分数为21.83×10-9～183.59×10-9,平均值为54.17×10-9,TVOCs中烷烃浓度最高,其次为炔烃、烯烃、芳香烃和卤代烃;成都市主要VOCs污染源为机动车排放源、液化石油气燃烧排放源、工业源、生物质燃烧源和溶剂使用源,贡献率分别为34.15％、21.57％、19.08％、15.19％、10.02％;边界层压缩和静风条件可能是导致VOCs和PM2.5浓度增加的主要原因.

选取涵盖钢铁炼制全流程的典型企业,综合采用不同核算方法估算比较了该企业挥发性有机物(VOCs)排放结果;并在此基础之上,通过氟聚化合物气袋、SUMMA罐采样及气相色谱质谱联用仪(GC-FID/MS)分析方法,对烧结、焦化、热轧和冷轧等工序废气中VOCs浓度水平及排放特征进行监测.结果表明,整个厂区VOCs年排放量为430.82t,其中工艺有组织排放占66.0％,储罐18.5％;烧结机头和焦炉推焦排放口VOCs及非甲烷总烃(NMHC)浓度高于其他点位;各工序排放的芳香烃占比较高,其中焦化装煤除尘和焦炉推焦排放口芳香烃占90％以上;烧结工序CS2占比最高(36.6％),其次为苯和甲苯;焦化工序占比靠前的物种为1,2,4-三甲基苯、邻甲乙苯、1,4-二乙基苯、1,2,3-三甲基苯和1,3,5-三甲基苯等;热轧工序与其他工序有一定区别,车间无组织排放芳香烃和烷烃占比均在35％左右,排放靠前的物种除芳香烃外还有高碳烷烃,如十一烷、十二烷和正丁烷等;冷轧工序有组织和无组织排放主要物种较为类似,均为芳香烃物种,如乙基苯、间/对二甲苯、甲苯、苯和邻二甲苯.不同工艺环节排放物种存在一定差异,但主要以焦化副产物(芳香烃)和烧结燃烧产物(CS2)为主,建议钢铁行业有针对性地加强浓度高、活性高和毒性大的组分控制.

2019年4-8月,在成都市城区开展了O3、NOx、VOCs及气象参数的连续在线观测,基于观测数据OBM模拟的方式,对O3超标日的敏感性及收支进行了分析.研究发现,成都市城区O3超标日对应的绝大部分前体物的浓度均有所上升,基于VOCs的组分变化分析推断工业源排放在超标日可能存在较大幅度的增加.相对增量反应活性(RIR)值结果表明,成都市城区O3超标日对人为源VOCs (AVOCs)敏感性最强,其次为天然源(BVOCs)和CO,而对NOx为负敏感性,控制AVOCs对站点超标日的O3浓度下降最为有利;逐月变化来看,O3对AVOCs和NOx的敏感性逐月差异较小,对BVOCs的敏感性在6-7月最强,对CO的敏感性在4-5月最强.观测点位处于典型的VOCs控制区,以O3浓度为等值线的EKMA曲线显示4-5月脊线比例约为13,6-7月及8月的脊线比例约为8.建议在开展O3防控时,VOCs的减排比例应远大于NOx,且春季的减排比例应大于夏季.典型O3污染日的日最大O3小时生成速率为10× 10-9 ～ 18× 10-9· h-1,上午存在O3输入,下午O3本地生成占主导,其余时段O3输出影响较强.

In this research, the activity data of Sichuan Province were collected using bottom-up and top-down methods. According to the second survey of pollution sources, the activity data of industrial source includes information of 11020 boilers and 60078 industrial enterprises. Data of 19152 industrial enterprises were collected in Chengdu, accounting for 32% of the total number of enterprises in Sichuan Province. The anthropogenic air pollutant emission inventory of 9 km×9 km was developed for Sichuan Province in 2017 with the use of appropriate emission estimation methods. The results showed that the total emission of SO2,NOx,CO,PM10,PM2.5,BC,OC,VOCs, and NH3 in Sichuan were 308.6×103, 725.7×103, 3131.2×103, 927.6×103, 422.4×103, 30.2×103, 72.0×103, 600.9×103, and 887.1×103 t. The fixed combustion source and process source mainly contributed as sources of SO2. The main source of CO was the process source and mobile source. Further, the dust source and process source were the main sources of PM10 and PM2.5, and the dust source was the largest source of BC and OC contributions. The emission sources of the VOCs were primarily the process sources, mobile sources and solvent use sources. The NH3 emissions were mainly from livestock and poultry breeding and nitrogen fertilizer applications. The spatial distribution results showed that the pollutants were mainly concentrated in the densely populated Sichuan basin and Panzhihua region, where industry and agriculture were relatively developed. The high value points are concentrated along the Deyang-Chengdu-Meishan-Leshan line in Chengdu Plain. The emission inventory established in this study still has certain uncertainties, and the accuracy of activity level data acquisition should be further enhanced. Moreover, pollutant emission factor testing should be carried out for typical pollution sources, and grid emission inventory should be improved to provide scientific support for the prevention and control of air pollution in Sichuan Province in the future.

四川省汽车保有量2017年位列全国第7位,油品储运销过程中挥发性有机物(VOCs)排放压力巨大.利用排放因子法,结合四川省4492座加油站的油品销售量,编制了四川省2017年加油站VOCs排放清单.另一方面,对四川省不同片区的VOCs排放特征及油气回收关键参数进行了现场实测.结果表明:四川省加油站VOCs排放量共12294.54 t,排放区域主要集中在成都市、绵阳市和宜宾市等地区;四川省四大片区VOCs排放浓度,加油环节攀西片区最高,达到7076.86μg/m3,卸油环节川东北片区最高,达到9638.53μg/m3,均是其他片区的2～3倍,加油和卸油环节排放的异戊烷最高占比(质量分数)可分别达到70.1％和67.4％;四川省油气回收系统达标情况仍然比较严峻,不达标率高达47％,密闭性和气液比不达标率尤为显著,集中式油气回收系统不达标率高于分散式.

In the research, volatile organic compounds (VOCs) were observed online in urban areas of Chengdu to study VOC concentration level, change characteristics, ozone generation contribution (OFP), and source contribution from June to September 2019. The results showed that the average concentration of TVOCs (total volatile organic compounds) was 112.66 μg·m, with alkanes (29.51%) and halogenated hydrocarbons (23.23%) forming the main components. The diurnal peak in VOCs mainly occurred from 10:00 am to 11:00 am, which is affected by urban motor vehicles, oil or gas volatilization, and industrial emissions. For OFP contribution of VOCs in summer, the contribution rate of aromatic hydrocarbons (42.7%) was the highest, followed by alkenes (27.4%). The key active species were -xylene, ethylene, propylene, -xylene, isopentane, cyclopentane, and acrolein. According to the source analysis by the PMF model, mobile sources are the main contributors of VOCs in summer in Chengdu, contributing 34% to TVOCs, followed by industrial sources (17%), volatile oil and gas (14%), and solvent use and natural sources contributing 11% and 13%. Therefore, motor vehicle and industrial emissions are the key control sources of VOCs in Chengdu, although control of pollution sources such as solvent use and oil or gas volatilization cannot be ignored.

基于现场采样监测法,对沥青铺路现场和沥青搅拌站开展挥发性有机物(VOCs)组分及浓度的监测,利用排放因子法对四川省17个城市的沥青铺路排放源VOCs排放量进行了计算.结果 表明,摊铺过程的VOCs浓度水平为1～3 mg/m3,摊铺后浓度水平在0.1～1mg/m3范围,在施工作业位旁瞬时样品浓度高达10mg/m3以上.沥青搅拌站和铺路现场的主要共同物种为萘、甲苯、间对二甲苯、异丁烷;四川省17城市对应的沥青铺路排放源VOCs的排放量为0.63万t,主要的活性贡献物种为萘、间/对-二甲苯、顺-2-丁烯、1,2,4-三甲基苯、甲苯等.

In this study, typical industries that act as sources of volatile organic compound (VOCs) emission in Sichuan, including automobile manufacturing, wooden furniture, wood-based panel manufacturing, and paint production, were selected and GC-MS national standard analysis to study the organized emission VOC components of every procedure. The spectra of VOCs in the automobile industry were obtained by means of total emission normalization. The results showed that the VOC components of automobile manufacturing, wooden furniture, and oil paint manufacturing enterprises were mainly aromatic hydrocarbons and oxygen-containing compounds, accounting for more than 70% of total VOCs; the emissions from automobile part manufacturing enterprises were mainly aromatic hydrocarbons, with a ratio of over 90%. The proportion of oxygen-containing compounds in the wood-based panel manufacturing industry was found to be up to 97%, mainly caused by the emission of formaldehyde, which accounts for 75%, followed by isopropanol, acetone, and other substances. The proportion of aromatic hydrocarbon and olefin in synthetic resin enterprises is relatively high at over 80%. The olefin species are mainly 1,3-butadiene and 1-butene. Although there are some differences in emission species between different industries, they are mainly composed of aromatic hydrocarbons and oxygenates. Therefore, it is necessary to improve the identification and control of components with high concentration, activity, and toxicity for aromatic hydrocarbons and oxygenates. The source, process, and end process control should be monitored to achieve the effect of total emission reduction.

To investigate the seasonal variations in the concentrations of atmospheric volatile organic compounds (VOCs) in the urban area of Chengdu, VOC species were monitored from December 2018 to November 2019, and the concentrations, chemical composition, chemical reactivity, and sources of VOCs were analyzed. Average volume fraction of VOCs in spring, summer, autumn, and winter are 32.29×10-9, 36.25×10-9, 40.92×10-9, and 49.48×10-9, respectively. The concentrations in winter are significantly higher than the winter concentrations measured in other areas. There is no significant difference between VOC concentrations in spring and summer, but component concentrations vary from season to season. In winter, alkanes account for the largest proportion of total VOCs owing to vehicle emissions. The proportion of oxygen (nitrogen)-containing volatile organic compounds in summer and autumn is much higher than that in spring and winter. Volatile emissions from primary sources and secondary conversions have a great contribution. The average concentration of key components of VOCs in different seasons did not change significantly. C2-C4 alkanes, ethylene, acetylene, and dichloromethane concentrations may be significantly affected by vehicle exhaust, oil and gas volatilization, solvent use, and LPG fuel use. ·OH consumption rate and OFP calculations show that key active species are mainly m/p-xylene, ethylene, propylene, 1-hexene, toluene, isopentane, and n-butane. Therefore, these species should be given priority in emissions control measures. Since the temperature in spring and summer is higher than in autumn and winter, and the UV rays are more intense, PMF analysis reveals the natural sources and the secondary emission sources as the major sources. The oil and gas volatilization source contributes to 9% of VOC concentrations in summer. The major VOC sources in autumn and winter are vehicle exhaust and combustion sources. Emissions from the combustion sources contribute to 25% and emissions from the catering sources in autumn and winter contribute to 9% of total VOC levels.