本论文基于武汉市2016.9.1-2017.8.31期间102个大气VOCs组分的观测数据，开展了大气VOCs污染变化特征、化学反应活性、来源解析以及VOCs对雾霾污染影响的研究。 结果表明，武汉市TVOCs年均浓度为34.65 ± 22.96 ppbv，烷烃是年均浓度最大的组分，占TVOCs年均浓度的45.88%。丙烷、乙烷和乙烯是VOCs中含量最丰富的组分。VOCs各组分具有明显的日变化、季节变化特征及“周末效应”现象。且O3等浓度EKMA曲线表明武汉市属于VOCs控制区，降低VOCs排放更有利于降低O3污染。 武汉市大气VOCs的总MIR值为2.53 g O3/g VOC，OH自由基反应速率常数KOH为6.42 × 10-12 cm3?molecule-1?s-1，整体化学反应活性较强。OH自由基消耗速率（LOH）结果表明烯烃是化学活性最大的组分，占42.56%，臭氧生成潜势（OFP）结果表明烯烃对O3生成的贡献最大，占48.34%。因此，控制烯烃浓度更有利于减少武汉市O3生成。大气VOCs总SOA生成潜势（SOAP）为312.44 ppbv，且芳香烃对SOA生成的贡献远高于其他VOCs组分，为96.60%。因此，控制大气芳香烃的浓度更有利于减少武汉市SOA的生成。 特征污染物比值（甲苯/苯、典型VOCs/乙炔）表明机动车尾气排放对武汉市VOCs影响显著。PMF源解析结果表明，武汉市大气VOCs共有8个潜在来源，分别为机动车尾气排放源、工业源、煤炭燃烧、喷涂/涂料行业溶剂使用源、LPG使用源、燃料挥发、生物质燃烧和天然源，贡献率分别为24.42%、16.43%、14.18%、13.48%、12.57%、11.34%、5.11%和2.47%。秋季工业源占比最大，冬、春、夏季均为机动车尾气排放源占比最大。并且与武汉市VOCs污染加重显著相关的污染源主要为喷涂/涂料溶剂使用源、液化石油气（LPG）使用源、煤炭燃烧源。结合后向轨迹和PSCF结果表明，影响武汉市VOCs污染的主要为局地短距离输送，尤其是南方及西南方向。 VOCs对雾霾污染影响的案例中，清洁天（能见度＞10km）、轻度雾霾（能见度为5-10km）、重度雾霾（能见度＜5km）TVOCs浓度分别为34.87 ± 14.89 ppbv、45.06 ± 26.69 ppbv、49.55 ± 24.82 ppbv，且不同污染过程中，烷烃均是含量最丰富的组分。SOA在雾霾天的浓度明显大于清洁天。随着雾霾污染加重，VOCs的SOA生成潜势逐渐增加，但在不同能见度条件下，芳香烃均是SOA生成的主要贡献者，占总SOAP的97%左右。乙苯与间/对二甲苯的比值表明雾霾天大气光化学反应略强于清洁天；甲苯/苯表明机动车尾气排放对不同污染阶段VOCs影响无显著变化；苯系物/CO表明涂料挥发、溶剂使用和工业排放对雾霾VOCs浓度增加影响显著。PMF源解析结果表明，雾霾污染期间VOCs来源主要为工业源、机动车尾气排放源、喷涂/涂料行业溶剂使用源、燃料挥发、LPG使用源、天然源和生物质燃烧。而喷涂/涂料行业溶剂使用源、LPG使用源和机动车尾气排放源是影响雾霾过程中VOCs污染加重的主要污染源。结合后向轨迹和PSCF结果表明，影响武汉市雾霾过程中VOCs污染的主要为局地短距离输送，尤其是南方及西南方向。

Based on the detailed data of VOCs with 102 components measured continuously from 2016.9.1 to 2017.8.31 in Wuhan, the VOC characteristics, chemical reactivity, source apportionment and the effects on haze events were analysed. The results revealed that the annual average concentration of TVOCs was 34.65 ± 22.96 ppbv. Alkanes were the species with the largest concentration, which accounted for 45.88% of TVOCs, and propane, ethane and ethene were the most abundant components. VOC species had obvious diurnal variation, seasonal variation and “weekend effects”. The results of Empirical Kinetic Modelling Approach (EKMA) showed that Wuhan belongs to a VOC limited area, and it is crucial to reduce the emission of VOCs to control O3 pollution. The total MIR of VOCs was 2.53 g O3/g VOC, and KOH was 6.42 × 10-12 cm3?molecule-1?s-1，which indicated the chemical reactivity was larger in Wuhan. The results of OH radical loss rate (LOH) showed that alkenes were the species with the largest amount of chemical reactivity, accounting for 42.56%. The results of ozone formation potential (OFP) showed that alkenes contributed the most to the formation of O3, accounting for 48.34%. Therefore, controlling the concentration of alkenes is more conducive to reducing O3 formation in Wuhan. The total SOA formation potential (SOAP) of VOCs was 312.44 ppbv, moreover, the contribution of aromatics to SOA formation was much higher than that of other VOC species, accounting for 96.60%. Therefore, controlling the concentration of aromatics is more conducive to reducing the formation of SOA in Wuhan. Diagnostic ratios (toluene/benzene, typical VOC species/acetylene) showed that vehicle exhaust emissions had significant effects on VOCs in Wuhan. Eight major sources were identified by PMF model, which included vehicular exhaust, industrial sources, coal burning, solvent usage in painting/coating, liquefied petroleum gas (LPG) usage, fuel evaporation, biomass burning and biogenic sources, the contributions were 24.42%, 16.43%, 14.18%, 13.48%, 12.57%, 11.34%, 5.11% and 2.47%, respectively. Industrial sources accounted for the most in autumn, and vehicular exhaust accounted for the most in winter, spring and summer. In addition, solvent usage in painting/coating, LPG usage and coal burning were the main sources that significantly aggravated VOC pollution in Wuhan. Based on backward trajectories and the PSCF results, short-distance transport was the main source influencing VOC pollution, especially transport from the south and southwest. In the case of the VOCs effects on haze events, TVOC concentrations on clear days (visibility > 10 km), slight haze days (visibility of 5-10 km), and severe haze days (visibility < 5 km) were 34.87 ± 14.89 ppbv, 45.06 ± 26.69 ppbv and 49.55 ± 24.82 ppbv, respectively. Alkanes were the most abundant VOC species during different haze episodes. The SOA on haze days was significantly higher than that on clear days. As the pollution increased, SOA formation potential was gradually increased, but aromatics were the dominant contributors to SOA formation under different visibility conditions, accounting for approximately 97% of the total SOAP. The ratio of ethylbenzene to m/p-xylene indicated that atmospheric photochemical reactions were slightly stronger on haze days. The ratio of toluene to benzene indicated that but no significant changes occurred in the impact of vehicle exhaust on VOCs during different haze episodes. The ratio of BTEX to CO indicated that VOCs from solvent usage in painting/coating and industrial emissions increased with increasing haze pollution. PMF results showed that the main sources during haze events were industrial sources, vehicular exhaust, solvent usage in painting/coating, fuel evaporation, LPG usage, biogenic sources and biomass burning. Moreover, solvent usage in painting/coating, LPG usage and vehicle exhaust were the most important sources that significantly aggravated VOC pollution during haze events. Based on backward trajectories and the PSCF, short-distance transport was the main source influencing VOC pollution, especially transport from the south and southwest.