环境科学  2023, Vol. 44 Issue (1): 58-65   PDF    
长三角区域人为源活性挥发性有机物高分辨率排放清单
田俊杰1, 丁祥1, 安静宇1, 李曼2, 王鑫2, 黄成1     
1. 上海市环境科学研究院, 国家环境保护城市大气复合污染成因与防治重点实验室, 上海 200233;
2. 中国环境监测总站, 北京 100012
摘要: 基于长三角区域41个城市本地实测, 结合美国EPA的SPECIATE 4.4数据库, 建立了长三角区域人为源活性挥发性有机物(VOCs)高分辨率排放清单, 分析了区域内VOCs的排放特征和组分构成; 计算了VOCs的臭氧生成潜势(OFP)和二次有机气溶胶生成潜势(SOAP).结果表明, 2017年, 长三角区域人为源VOCs排放总量为4.9×106 t, 其中工艺过程源、工业溶剂使用源、移动源、生活源、储运源、农业源和废弃物处理源排放贡献分别为: 34.3%、27.1%、19.5%、9.7%、6.1%、2.5%和0.4%.芳香烃和烷烃是VOCs的主要种类, 均各占长三角VOCs排放总量的25%.工艺过程源、工业溶剂使用源、移动源和生活源OFP贡献率分别为38.3%、21.5%、16.4%和13.2%, SOAP贡献率分别为26.2%、34.1%、18.1%和17.9%, 与VOCs排放量的主要贡献源基本一致.各城市VOCs重点排放行业存在较大差异, 重点城市群以石化化工和装备制造为主, 区域北部则以木材家具等涂装行业为主.计算表明, 丙烯、间/对-二甲苯和乙烯是臭氧主要贡献源; 甲苯、1, 2, 4-三甲苯和间/对-二甲苯是二次有机气溶胶主要贡献源.下阶段VOCs的精细化治理可向基于化学反应活性的主控行业转变, 可将化工、石化、汽车制造、纺织和木材家具等关键行业治理放在优先位置, 同时根据城市特征, 制定差异化的VOCs治理路径.
关键词: 挥发性有机物(VOCs)      活性组分      排放清单      大气污染      长三角区域     
High-resolution Emission Inventory of Reactive Volatile Organic Compounds from Anthropogenic Sources in the Yangtze River Delta Region
TIAN Junjie1 , DING Xiang1 , AN Jingyu1 , LI Man2 , WANG Xin2 , HUANG Cheng1     
1. State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China;
2. China National Environmental Monitoring Centre, Beijing 100012, China
Abstract: A high-resolution emission inventory of anthropogenic active volatile organic compounds (VOCs) for the Yangtze River Delta (YRD) region was developed based on the local measurement of 41 cities in the region and the specific 4.4 database of EPA. The emission characteristics and composition of VOCs were analyzed. The ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAP) of VOCs were calculated. The results showed that the total emission of anthropogenic VOCs in the YRD in 2017 was 4.9×106 t. The emission contributions of process sources, industrial solvent sources, mobile sources, domestic sources, storage and transportation sources, agricultural sources, and waste treatment sources were 34.3%, 27.1%, 19.5%, 9.7%, 6.1%, 2.5%, and 0.4%, respectively. Aromatic hydrocarbons and alkanes were the main components of VOCs, accounting for 25% of the total VOCs emissions in the region. The contribution rates of OFP from process sources, industrial solvent sources, mobile sources, and domestic sources were 38.3%, 21.5%, 16.4%, and 13.2%, respectively, and the contribution rates of SOAP were 26.2%, 34.1%, 18.1%, and 17.9%, respectively, which was basically consistent with the main contribution sources of VOCs emissions. The emission characteristics of the key industries in each city were obviously different. The key urban agglomeration of VOCs emission was mainly petrochemical industries and equipment manufacturing, whereas the northern part of the region was mainly wood furniture and other coating industries. The results showed that propylene, m-xylene, p-xylene, and ethylene were the main contribution sources of ozone, whereas toluene, 1, 2, 4-trimethylene, m-xylene, and p-xylene were the main contribution sources of secondary organic aerosols. In the next stage, the fine management of VOCs can be transformed into the main industries based on chemical reaction activity, which can give priority to the governance of key industries such as the chemical industry, petrochemical, automobile manufacturing, textile, wood, and furniture and can formulate different governance paths according to urban characteristics.
Key words: volatile organic compounds (VOCs)      reactive compounds      emission inventory      air pollution      the Yangtze River Delta region     

挥发性有机物(volatile organic compounds, VOCs)是近地面臭氧(O3)和二次有机气溶胶(SOA)生成的重要前体物[1~4].VOCs化学组分复杂, 不同来源和组分的VOCs组分反应活性差异较大, 对O3和SOA生成的潜势也不尽相同[5~7].因此, 建立基于化学反应活性的人为源VOCs精细化排放清单是有效制定PM2.5和O3污染协同控制措施的重要基础, 对摸清各城市各行业排放现状、满足空气质量模型模拟需求、细化实施减排政策等具有重要的指导意义.近年来, 大量研究已在全国和区域尺度建立了VOCs排放清单.全国尺度方面, 清华大学构建的多尺度排放清单模型(multi-resolution emission inventory for China, MEIC)建立了1990~2017年人为源VOCs分组分排放清单, 并取得了广泛应用[8]; 北京大学谢绍东团队也建立了详细的VOCs组分清单, 并评估了其对O3和SOA生成的潜在贡献[9, 10].此外, 各重点区域和省份也先后利用本地化污染源数据建立了高分辨率的VOCs排放清单[11~16], 源类和空间分辨率的精细度得到了大幅提升.为了进一步摸清各类人为源VOCs排放的成分谱特征, 各区域通过本地化实测结合国内外参考源谱相继形成了各源类VOCs成分谱库[7, 17~20].将高分辨率清单与详细源类成分谱资料相结合, 是科学评估区域活性VOCs组分来源及其对O3和SOA生成潜在贡献的重要手段.

长三角是我国经济活动最为频繁和工业体量最大的区域之一, 且区域行业门类十分齐全, VOCs排放强度位居全国前列[21].为掌握区域大气污染物排放特征, Huang等[22]、Fu等[23]和An等[24]先后基于本地污染源调查建立并更新了长三角区域高分辨率人为源排放清单, 并获得了VOCs分组分排放特征.在此期间, Zhao等[25]通过实测不断丰富并改进了江苏等省市的VOCs分组分排放清单[26, 27], 有效地提升了O3的模拟效果.但是, 针对长三角具体城市和详细源类的活性VOCs组分排放特征研究及其对O3和SOA贡献的综合评估仍相对较少.因此, 本研究在建立长三角区域高分辨率人为源VOCs排放清单的基础上, 结合以本地化实测为主的VOCs成分谱数据库, 以2017年为基准年, 建立精细化的基于化学反应活性的人为源活性VOCs组分排放清单, 旨在为有效制定PM2.5和O3污染协同控制措施提供科学支撑.

1 材料与方法 1.1 人为源VOCs排放清单构建

长三角地区包括了江苏、浙江、安徽和上海三省一市共41个城市.研究区域西起118.25°E, 东至122.42°E, 南抵28.90°N, 北达33.30°N, 面积约350 400 km2.本研究将研究区域划分为11 979个4 km×4 km的网格.

VOCs排放源类分为固定燃烧源、移动源、储运源、生活源、农业源和废弃物处理源, 以及大部分工业过程和溶剂使用来源, 如石油炼制、焦炭生产、化工制造、纺织、家具制造、包装印刷、汽车制造、造船和建筑涂料等, 基本覆盖涉VOCs排放的所有人为源.

VOCs排放估算方法主要采用排放因子法, 溶剂使用源则采用物料平衡法.活动水平数据主要来自2017年长三角工业源调查结果及各城市统计年鉴, 其中, 工业源包括了超过3万家企业(如固定燃烧源、工业过程和溶剂使用源, 对于点源调查不够全面的行业以最小行政单元做面源补充), 用于计算的数据包括能源消费量、工业产品产量和溶剂使用量等调查结果, 以及本地化调研获得的各行业VOCs治理技术及其效率等信息.具体的计算方法可以参见文献[24].

1.2 VOCs成分谱数据

本研究的VOCs成分谱数据主要来自长三角本地实测, 包括汽油车和柴油车[28, 29]、船舶[30, 31]、油气挥发[32]、餐饮[33]、生物质燃烧[34]和大部分的工艺过程源和溶剂使用源[32, 35, 36], 如石化、炼焦、化工、纺织、家具制造、包装印刷、汽车制造、船舶制造和建筑涂装等.对于无本地化实测结果的源类以及已有研究未识别的VOCs物种, 采用美国EPA的SPECIATE 4.4数据库[37]进行了补充.最终本研究共确定108个涉VOCs排放源类的424种组分, 含烷烃、烯烃、芳香烃、卤代烷烃和含氧有机物(OVOCs)等.图 1所示为长三角区域主要源类的VOCs物种大类构成.

图 1 长三角区域主要源类VOCs物种大类构成 Fig. 1 VOC species in major categories from the main sources in the Yangtze River Delta region

1.3 活性VOCs排放估算

根据VOCs基础排放清单, 结合各源类VOCs成分谱, 可计算获得VOCs分物种排放清单, 计算方法如式(1)所示[9].

(1)

式中, Eii物种的排放总量, t; Ejj类污染源的排放总量, t; fiji物种在j类污染源的VOCs总排放量中所占的质量分数, 无量纲.

为进一步评估各类污染源VOCs排放对O3和SOA生成的潜势贡献, 本研究分别利用各类VOCs物种的最大增量反应活性因子(MIR)和SOA产率(Y)计算臭氧生成潜势(OFP)和SOA生成潜势(SOAP), 具体如式(2)和式(3)所示.

(2)
(3)

式中, OFPjj类污染源的臭氧生成潜势, t(以O3计); SOAPjj类污染源的SOA生成潜势, t (以SOA计); Eijj类污染源中i物种的排放总量, t; MIRii物种的最大增量反应活性因子(O3/VOCs), t ·t-1; Yii物种的SOA产率, %.

1.4 不确定性分析

根据区域各源类活性VOCs活动水平数据和排放因子, 可计算各排放源活性VOCs排放水平的不确定性, 计算方法如式(4)和式(5)所示[22].

(4)
(5)

式中, CV为变异系数; U为各排放源不确定性; E为排放率; Ca为活动水平数据的不确定性, Cf为排放因子的不确定性; jk分别为物质类别和排放源类, 均无量纲.

2 结果与讨论 2.1 长三角区域人为源VOCs排放特征

2017年长三角区域人为源VOCs排放总量为487.5万t ·a-1, 排放分担率如图 2所示.工业源(含工业过程源和工业溶剂源)共计299.2万t ·a-1, 是长三角VOCs主要排放来源, 占区域VOCs总排放量的60%左右.其中, 工业过程源和工业溶剂源分别占34.3%和27.1%.工业过程源中的主要排放行业包括化工、橡塑、石化和非金属制品等, 工业溶剂源中的主要行业包括木材家具、应用设备、设备制造、电子制造、医药和纺织等.石化和化工行业是该地区重工业的支柱产业, 其产量与产值均居全国前列, VOCs排放分担率分别达到3.2%和16.4%.而该地区高速发展的房地产业, 也拉大了木材家具行业的需求, 因此其在工业溶剂源中VOCs排放占比最高.移动源、生活源、储运源、农业源和废弃物处理源的VOCs排放占比依次为19.5%、9.7%、6.1%、2.5%和0.4%.移动源、储运源、生活源和农业等源类排放均较为集中, 分别以机动车排放、储油库排放、民用溶剂排放和家用秸秆燃烧排放为主.

图 2 2017年长三角区域各类VOC人为源的排放分担率 Fig. 2 VOC emission contributions from each source in the Yangtze River Delta region for the year 2017

2.2 主要源类VOCs组分构成

图 3所示为长三角主要源类的VOCs化学组分构成.芳香烃和烷烃是长三角区域VOCs排放的主要物种, 均占VOCs排放总量的25%.OVOCs在VOCs排放中的占比也达到了21.9%, 其中醛类、酮类、醇类和酯类分别占5.0%、4.4%、9.0%和3.5%.卤代烃排放占比较小, 仅为3.1%.机动车排放是该区域烷烃(包括直链烷烃、支链烷烃和环烷烃)和芳香烃的主要来源, 分别占各物种排放总量的31.2%和15.1%.化工行业则以烯烃和芳香烃排放为主.此外, 橡塑行业烯烃排放也相对突出.生活源的芳香烃排放明显高于其他源类, 占芳香烃排放总量的23.7%.相比于生活源, 工业溶剂源门类较多, 芳香烃和OVOCs排放占比均相对较高, 分别占各自总排放量的29.3%和33.3%, 尤其是木材家具行业涉及醛、醇类OVOCs排放占比最高.

图 3 长三角区域主要源类的VOCs大类组分排放分布 Fig. 3 Emission distribution of VOC species in major categories from the main sources in the Yangtze River Delta region

2.3 各源类VOCs排放及其O3与SOA生成潜势比较

图 4所示为基于排放量、OFP和SOAP的长三角主要人为源排放占比比较.可见, 基于OFP和SOAP识别的人为源排放贡献与其原始排放占比接近, 工业溶剂源、工业过程源、移动源和生活源均为贡献最高的四大源类.从OFP贡献来看, 工业溶剂源和移动源所占的贡献略低于其排放占比, 工业过程源和生活源的OFP贡献则高于其排放占比; 从SOAP贡献来看, 工业过程源所占的贡献较其排放占比下降了20%, 工业溶剂源的SOAP贡献则超过工业过程源, 成为SOAP贡献最高的源类.图 5进一步给出了长三角地区工业过程源和工业溶剂源分行业的OFP和SOAP排放贡献.化工行业是对工业过程源OFP和SOAP贡献最大的部门, 分别占16.4%和14.8%; 其次为橡塑行业, 其大量的烯烃排放贡献了11.8%的OFP.汽车制造和纺织行业是对工业溶剂源SOAP贡献最大的部门, 分别7.7%和8.5%; 木材家具则贡献了工业溶剂源约8.9%的OFP潜势.

图 4 长三角区域基于排放量、OFP和SOAP的人为源贡献占比 Fig. 4 VOC emissions, their OFP, and SOA contributions from different sources in the Yangtze River Delta region

图 5 长三角区域关键工业行业对VOCs排放、OFP和SOAP的贡献 Fig. 5 VOC emissions, their OFP, and SOA contributions from key industrial sectors in the Yangtze River Delta region

2.4 各城市分源类VOCs排放对O3与SOA生成潜势的贡献

图 6进一步列出了长三角各城市中对OFP和SOAP潜势贡献最高的前19个二级源类.从中可知, 宁波和上海的化工行业是在长三角分城市和分源类中的OFP贡献最高, 分别占长三角人为源OFP的2.5%和1.9%.其次为无锡的橡塑行业和苏州的化工行业, 均贡献了区域OFP的1.4%.上海和南京的石化行业、宁波的橡塑行业、合肥的生活源和上海的机动车对区域OFP的贡献均大于1.0%.按城市划分的排放源中, 对SOFP贡献最高的5个源类分别为:上海的汽车制造行业(2.0%)>上海的化工行业(1.9%)>宁波的化工行业(1.8%)>合肥的生活源(1.5%); 其次为上海、南通和绍兴的生活源, 嘉兴、绍兴和南通的纺织行业也超过了1.0%.

图 6 长三角各城市排放源对OFP和SOAP生成潜势贡献 Fig. 6 Contributions of VOC emissions from different sources in each city to their OFP and SOA formation potentials

2.5 区域主要O3和SOA生成潜势物种排序

图 7所示为对长三角区域OFP和SOAP贡献最高的前20种VOCs组分.对OFP贡献最高的物种依次为丙烯(16.8%)、间/对-二甲苯(15.0%)、乙烯(10.9%)、甲苯(7.5%)和邻-二甲苯(5.7%)等, 丙烯的主要排放行业依次为橡塑、化工和炼油, 间/对-二甲苯、邻-二甲苯为民用溶剂、机动车和化工, 乙烯为化工、橡塑和油气挥发, 甲苯为纺织、化工和机动车.甲苯、1, 2, 4-三甲苯、间/对-二甲苯、邻-二甲苯和乙苯是对SOAP贡献最高的物种, 分别贡献了人为源SOAP的37.5%、27.0%、7.6%、4.2%和2.7%, 其中, 甲苯SOAP贡献较高的主要行业依次为纺织、化工和机动车, 1, 2, 4-三甲苯为化工、家具制造和炼油, 间/对-二甲苯、邻-二甲苯和乙苯为民用溶剂、机动车和化工.由此可见, 上述组分和对应的主要行业是控制长三角区域O3和SOA污染的关键.

图 7 基于OFP和SOAP贡献的长三角区域关键人为源VOCs组分 Fig. 7 Key anthropogenic VOC species in the Yangtze River Delta region based on their OFP and SOAP contributions

2.6 不确定性评估

基于本地排放因子和区域活动数据进行不确定性分析, 评估表明, 长三角区域VOCs排放的平均不确定性为-44% ~68%, 电厂、锅炉、炼油、化工制造、黑色金属制造、有色金属制造、机动车和非道路移动机械排放不确定性分别为-28% ~22%、-19% ~23%、-40% ~57%、-71% ~167%、-41% ~61%、-44% ~70%、-46% ~69%、-50% ~86%.其中, 电厂和锅炉等固定燃烧源的排放基于详细的活动数据和当地实测, 不确定更低; 黑色金属制造和有色金属制造等工业行业因为对各工艺环节相对准确的排放估算, 不确定性相对较低, 但化工行业仍存在大量未分类的工艺流程, 排放仍存在较大的不确定性; 移动源的不确定性则主要来源于活动水平的变化.

3 结论

(1) 长三角区域人为源VOCs排放主要来自工业过程源和工业溶剂源, 共占区域排放总量的60%以上.烷烃(25%)、芳香烃(25%)和OVOCs(22%)是长三角区域人为源VOCs排放的主要组分.

(2) 基于OFP和SOAP贡献识别的主要人为源与VOCs主要排放贡献源接近, 工业溶剂源、工业过程源、移动源和生活源均为贡献最高的四大来源.

(3) 长三角城市VOCs重点排放行业存在较大差异, 长三角东部重点城市群以石化化工和装备制造为主, 区域北部城市则以木材家具等涂装行业为主, 下阶段VOCs治理需根据城市特征, 制定差异化治理目标和政策措施.

(4) 对长三角区域OFP贡献占比最高的组分依次为丙烯、间/对-二甲苯、乙烯、甲苯和邻-二甲苯, 对区域SOAP贡献最高的组分依次为甲苯、1, 2, 4-三甲苯和间/对-二甲苯、邻-二甲苯和乙苯.综合来看, 化工、橡塑、机动车等行业对区域OFP和SOAP的贡献相对较高.基于本研究获得的各城市详细源类活性VOCs组分OFP和SOAP贡献, 可细化区域O3和SOA污染防治的主控行业, 推动下一阶段VOCs精细化治理向基于化学反应活性的主控行业转变.

参考文献
[1] Geng F H, Zhao C S, Tang X, et al. Analysis of ozone and VOCs measured in Shanghai: a case study[J]. Atmospheric Environment, 2007, 41(5): 989-1001. DOI:10.1016/j.atmosenv.2006.09.023
[2] Ziemann P J, Atkinson R. Kinetics, products, and mechanisms of secondary organic aerosol formation[J]. Chemical Society Reviews, 2012, 41(19): 6582-6605. DOI:10.1039/c2cs35122f
[3] Wang T, Xue L K, Brimblecombe P, et al. Ozone pollution in China: a review of concentrations, meteorological influences, chemical precursors, and effects[J]. Science of the Total Environment, 2017, 575: 1582-1596. DOI:10.1016/j.scitotenv.2016.10.081
[4] Li K, Jacob D J, Liao H, et al. A two-pollutant strategy for improving ozone and particulate air quality in China[J]. Nature Geoscience, 2019, 12(11): 906-910. DOI:10.1038/s41561-019-0464-x
[5] 梁小明, 张嘉妮, 陈小方, 等. 我国人为源挥发性有机物反应性排放清单[J]. 环境科学, 2017, 38(3): 845-854.
Liang X M, Zhang J N, Chen X F, et al. Reactivity-based anthropogenic VOCs emission inventory in China[J]. Environmental Science, 2017, 38(3): 845-854.
[6] Wang F L, Du W, Lv S J, et al. Spatial and temporal distributions and sources of anthropogenic NMVOCs in the atmosphere of China: a review[J]. Advances in Atmospheric Sciences, 2021, 38(7): 1085-1100. DOI:10.1007/s00376-021-0317-6
[7] Sha Q E, Zhu M N, Huang H W, et al. A newly integrated dataset of volatile organic compounds (VOCs) source profiles and implications for the future development of VOCs profiles in China[J]. Science of the Total Environment, 2021, 793. DOI:10.1016/j.scitotenv.2021.148348
[8] Li M, Zhang Q, Zheng B, et al. Persistent growth of anthropogenic non-methane volatile organic compound (NMVOC) emissions in China during 1990-2017: drivers, speciation and ozone formation potential[J]. Atmospheric Chemistry and Physics, 2019, 19(13): 8897-8913. DOI:10.5194/acp-19-8897-2019
[9] Wu R R, Xie S D. Spatial distribution of ozone formation in China derived from emissions of speciated volatile organic compounds[J]. Environmental Science & Technology, 2017, 51(5): 2574-2583.
[10] Wu R R, Xie S D. Spatial distribution of secondary organic aerosol formation potential in China derived from speciated anthropogenic volatile organic compound emissions[J]. Environmental Science & Technology, 2018, 52(15): 8146-8156.
[11] Liu H J, Wu B B, Liu S H, et al. A regional high-resolution emission inventory of primary air pollutants in 2012 for Beijing and the surrounding five provinces of North China[J]. Atmospheric Environment, 2018, 181: 20-33. DOI:10.1016/j.atmosenv.2018.03.013
[12] Zhou Z H, Tan Q W, Deng Y, et al. Compilation of emission inventory and source profile database for volatile organic compounds: a case study for Sichuan, China[J]. Atmospheric Pollution Research, 2020, 11(1): 105-116. DOI:10.1016/j.apr.2019.09.020
[13] Bai L, Lu X, Yin S S, et al. A recent emission inventory of multiple air pollutant, PM2.5 chemical species and its spatial-temporal characteristics in central China[J]. Journal of Cleaner Productio, 2020, 269. DOI:10.1016/j.jclepro.2020.122114
[14] Huang Z J, Zhong Z M, Sha Q G, et al. An updated model-ready emission inventory for Guangdong Province by incorporating big data and mapping onto multiple chemical mechanisms[J]. Science of the Total Environment, 2021, 769. DOI:10.1016/j.scitotenv.2020.144535
[15] Zhou M M, Jiang W, Gao W D, et al. Anthropogenic emission inventory of multiple air pollutants and their spatiotemporal variations in 2017 for the Shandong Province, China[J]. Environmental Pollution, 2021, 288. DOI:10.1016/j.envpol.2021.117666
[16] 闫雨龙, 彭林. 山西省人为源VOCs排放清单及其对臭氧生成贡献[J]. 环境科学, 2016, 37(11): 4086-4093.
Yan Y L, Peng L. Emission inventory of anthropogenic VOCs and its contribution to ozone formation in Shanxi province[J]. Environmental Science, 2016, 37(11): 4086-4093.
[17] Mo Z W, Shao M, Lu S H. Compilation of a source profile database for hydrocarbon and OVOC emissions in China[J]. Atmospheric Environment, 2016, 143: 209-217. DOI:10.1016/j.atmosenv.2016.08.025
[18] Mo Z W, Lu S H, Shao M. Volatile organic compound (VOC) emissions and health risk assessment in paint and coatings industry in the Yangtze River Delta, China[J]. Environmental Pollution, 2021, 269. DOI:10.1016/j.envpol.2020.115740
[19] Zhou Z H, Tan Q W, Deng Y, et al. Source profiles and reactivity of volatile organic compounds from anthropogenic sources of a megacity in southwest China[J]. Science of the Total Environment, 2021, 790. DOI:10.1016/j.scitotenv.2021.148149
[20] 方莉, 刘文文, 陈丹妮, 等. 北京市典型溶剂使用行业VOCs成分谱[J]. 环境科学, 2019, 40(10): 4395-4403.
Fang L, Liu W W, Chen D N, et al. Source profiles of volatile organic compounds (VOCs) from typical solvent-based industries in Beijing[J]. Environmental Science, 2019, 40(10): 4395-4403.
[21] Li M, Liu H, Geng G N, et al. Anthropogenic emission inventories in China: a review[J]. National Science Review, 2017, 4(6): 834-866. DOI:10.1093/nsr/nwx150
[22] Huang C, Chen C H, Li L, et al. Emission inventory of anthropogenic air pollutants and VOC species in the Yangtze River Delta region, China[J]. Atmospheric Chemistry and Physics, 2011, 11(9): 4105-4120. DOI:10.5194/acp-11-4105-2011
[23] Fu X, Wang S X, Zhao B, et al. Emission inventory of primary pollutants and chemical speciation in 2010 for the Yangtze River Delta region, China[J]. Atmospheric Environment, 2013, 70: 39-50. DOI:10.1016/j.atmosenv.2012.12.034
[24] An J Y, Huang Y W, Huang C, et al. Emission inventory of air pollutants and chemical speciation for specific anthropogenic sources based on local measurements in the Yangtze River Delta region, China[J]. Atmospheric Chemistry and Physics, 2021, 21(3): 2003-2025. DOI:10.5194/acp-21-2003-2021
[25] Zhao Y, Mao P, Zhou Y D, et al. Improved provincial emission inventory and speciation profiles of anthropogenic non-methane volatile organic compounds: a case study for Jiangsu, China[J]. Atmospheric Chemistry and Physics, 2017, 17(12): 7733-7756. DOI:10.5194/acp-17-7733-2017
[26] Zhang L, Zhu X Z, Wang Z R, et al. Improved speciation profiles and estimation methodology for VOCs emissions: a case study in two chemical plants in eastern China[J]. Environmental Pollution, 2021, 291. DOI:10.1016/j.envpol.2021.118192
[27] Wu R R, Zhao Y, Xia S J, et al. Reconciling the bottom-up methodology and ground measurement constraints to improve the city-scale NMVOCs emission inventory: a case study of Nanjing, China[J]. Science of the Total Environment, 2022, 812. DOI:10.1016/j.scitotenv.2021.152447
[28] Wang H L, Jing S A, Lou S R, et al. Volatile organic compounds (VOCs) source profiles of on-road vehicle emissions in China[J]. Science of the Total Environment, 2017, 607-608: 253-261. DOI:10.1016/j.scitotenv.2017.07.001
[29] Liu Y H, Wang H L, Jing S G, et al. Strong regional transport of volatile organic compounds (VOCs) during wintertime in Shanghai megacity of China[J]. Atmospheric Environment, 2021, 244. DOI:10.1016/j.atmosenv.2020.117940
[30] Huang C, Hu Q Y, Wang H Y, et al. Emission factors of particulate and gaseous compounds from a large cargo vessel operated under real-world conditions[J]. Environmental Pollution, 2018, 242: 667-674. DOI:10.1016/j.envpol.2018.07.036
[31] Wu D, Ding X, Li Q, et al. Pollutants emitted from typical Chinese vessels: potential contributions to ozone and secondary organic aerosols[J]. Journal of Cleaner Production, 2019, 238. DOI:10.1016/j.jclepro.2019.117862
[32] 王红丽, 杨肇勋, 景盛翱. 工艺过程源和溶剂使用源挥发性有机物排放成分谱研究进展[J]. 环境科学, 2017, 38(6): 2617-2628.
Wang H L, Yang Z X, Jing S A. Volatile organic compounds (VOCs) source profiles of industrial processing and solvent use emissions: a review[J]. Environmental Science, 2017, 38(6): 2617-2628.
[33] 高雅琴, 王红丽, 许睿哲, 等. 餐饮源挥发性有机物组成及排放特征[J]. 环境科学, 2019, 40(4): 1627-1633.
Gao Y Q, Wang H L, Xu R Z, et al. Characterization of volatile organic compounds from cooking emissions[J]. Environmental Science, 2019, 40(4): 1627-1633. DOI:10.3969/j.issn.1000-6923.2019.04.034
[34] Wang H L, Lou S R, Huang C, et al. Source profiles of volatile organic compounds from biomass burning in Yangtze River Delta, China[J]. Aerosol and Air Quality Research, 2014, 14(3): 818-828. DOI:10.4209/aaqr.2013.05.0174
[35] Wang H L, Qiao Y Z, Chen C H, et al. Source profiles and chemical reactivity of volatile organic compounds from solvent use in Shanghai, China[J]. Aerosol and Air Quality Research, 2014, 14(1): 301-310.
[36] 景盛翱, 王红丽, 朱海林, 等. 典型工业源VOCs治理现状及排放组成特征[J]. 环境科学, 2018, 39(7): 3090-3095.
Jing S A, Wang H L, Zhu H L, et al. Treatment status and emission characteristics of volatile organic compounds from typical industrial sources[J]. Environmental Science, 2018, 39(7): 3090-3095.
[37] Hsu Y, Divita F, Dorn J. SPECIATE version 4.4 database development documentation[R]. Research Triangle Park: U.S. EPA, 2014.