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1.
Shijiazhuang, the city with the worst air quality in China, is suffering from severe ozone pollution in summer. As the key precursors of ozone generation, it is necessary to control the Volatile Organic Compounds (VOCs) pollution. To have a better understanding of the pollution status and source contribution, the concentrations of 117 ambient VOCs were analyzed from April to August 2018 in an urban site in Shijiazhuang. Results showed that the monthly average concentration of total VOCs was 66.27 ppbv, in which, the oxygenated VOCs (37.89%), alkanes (33.89%), and halogenated hydrocarbons (13.31%) were the main composite on. Eight major sources were identified using Positive Matrix Factorization modeling with an accurate VOCs emission inventory as inter-complementary methods revealed that the petrochemical industry (26.24%), other industrial sources (15.19%), and traffic source (12.24%) were the major sources for ambient VOCs in Shijiazhuang. The spatial distributions of major industrial activities emissions were identified by using geographic information statistics system, which illustrated the VOCs was mainly from the north and southeast of Shijiazhuang. The inverse trajectory analysis using Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and Potential Source Contribution Function (PSCF) clearly demonstrated the features of pollutant transport to Shijiazhuang. These findings can provide references for local governments regarding control strategies to reduce VOCs emissions.  相似文献   

2.
北京奥运时段VOCs浓度变化、臭氧产生潜势及来源分析研究   总被引:31,自引:20,他引:11  
挥发性有机物(VOCs)是大气中光化学污染臭氧(O3)的重要前体物,其在大气中的浓度水平往往直接影响着臭氧的污染水平.以2008年夏季北京大气中VOCs浓度观测资料为基础,分析了VOCs浓度和组分随时间的变化特征,比较了各组分对臭氧产生的影响潜势,并利用主成分分析法研究了VOCs主要来源.结果表明,北京大气总VOCs在上午和下午的浓度分别是34.38×10-9(体积分数)和27.13×10-9(体积分数),组分中以烷烃最高,芳烃次之,烯烃最低,下午大气中VOCs浓度显著低于上午,烯烃、芳烃和烷烃依次下降28%、26%和15%;其中1,2,4-三甲苯等效丙烯浓度最高(8.05×10-9C),其次为间对二甲苯(6.97×10-9C)、甲苯(6.41×10-9C)和1,3,5-三甲苯(5.64×10-9C);芳烃对大气O3生成贡献最大(47%),其次是烯烃(40%),烷烃最低(13%).北京大气中VOCs主要来源于机动车(28%)、溶剂挥发(19%)、液化气泄漏(15%)和工业排放(12%).为遏制近年来夏季O污染加重趋势,北京应大力减少VOCs排放,特别是芳香烃的排放量.  相似文献   

3.
基于2019年五指山背景点、海口市和三亚市的环境空气自动监测数据和气象观测资料,分析了海南省背景区域和重点城市O3及其前体物NO2污染特征;结合挥发性有机物(VOCs)在线监测数据,分析了五指山背景点VOCs的时间变化规律、O3浓度高值月份O3及其前体物VOCs和NOx的污染特征以及VOCs的臭氧生成潜势(OFP).结果表明,O3是影响五指山背景点空气质量的关键污染物,五指山背景点O3日最大8 h浓度平均值与海口市和三亚市显著相关.背景点NO2月均浓度水平显著低于城市点,然而背景点和城市点O3月均浓度水平和变化趋势高度一致.背景点O3变化与风向密切相关,春夏季偏南风频率较高,O3浓度相对较低;秋冬季以东北风为主,易受内陆污染输送影响,O3浓度较高.五指山背景点春夏季VOCs体积分数低于秋冬季,但对应的OFP高于秋冬季;其中异戊二烯夏季体积分数显著高于秋冬季,且其夏季体积分数占总挥发性有机物的比例最高,对应的OFP贡献率可达70%以上,O3则表现出秋冬季显著高于夏季的特征.11月O3高浓度时段乙炔和芳香烃的体积分数较清洁日出现较大上升,同时其对应的OFP显著上升.VOCs优势物种和OFP主要贡献物种的分析结果表明,O3高浓度时段机动车尾气和油气挥发排放源对五指山背景点VOCs的化学组成和OFP有重要贡献.  相似文献   

4.
Volatile organic compounds (VOCs) are major precursors for ozone and secondary organic aerosol (SOA), both of which greatly harm human health and significantly affect the Earth''s climate. We simultaneously estimated ozone and SOA formation from anthropogenic VOCs emissions in China by employing photochemical ozone creation potential (POCP) values and SOA yields. We gave special attention to large molecular species and adopted the SOA yield curves from latest smog chamber experiments. The estimation shows that alkylbenzenes are greatest contributors to both ozone and SOA formation (36.0% and 51.6%, respectively), while toluene and xylenes are largest contributing individual VOCs. Industry solvent use, industry process and domestic combustion are three sectors with the largest contributions to both ozone (24.7%, 23.0% and 17.8%, respectively) and SOA (22.9%, 34.6% and 19.6%, respectively) formation. In terms of the formation potential per unit VOCs emission, ozone is sensitive to open biomass burning, transportation, and domestic solvent use, and SOA is sensitive to industry process, domestic solvent use, and domestic combustion. Biomass stoves, paint application in industrial protection and buildings, adhesives application are key individual sources to ozone and SOA formation, whether measured by total contribution or contribution per unit VOCs emission. The results imply that current VOCs control policies should be extended to cover most important industrial sources, and the control measures for biomass stoves should be tightened. Finally, discrepant VOCs control policies should be implemented in different regions based on their ozone/aerosol concentration levels and dominant emission sources for ozone and SOA formation potential.  相似文献   

5.
利用MECCA大气化学模式,考虑卤素类(Br,Cl和I)物质的化学过程,对海洋大气边界层内臭氧和NOx的日变化进行了模拟,并与实测数据进行了对比.结果表明,当考虑这些影响后,ψ(O3)略有降低并且产生峰值的时间提前,这主要是由于Br,BrO,Cl和ClO等物质浓度在日出后很快达到峰值所致,基于同样的原因,NO2变化也有类似的特点.在清洁环境下,海洋大气边界层内臭氧的消耗主要由HOx,O(1D)+H2O和卤素控制,白天以卤素对臭氧的消耗为主.此外还模拟了不同ψ(NOx)下臭氧的日变化,得出在高ψ(NOx)情况下,边界层内臭氧可由净损耗变为净增长.   相似文献   

6.
山西省人为源VOCs排放清单及其对臭氧生成贡献   总被引:4,自引:2,他引:2  
闫雨龙  彭林 《环境科学》2016,37(11):4086-4093
根据统计年年鉴中主要的人为挥发性有机物(VOCs)排放源的行业活动水平和文献中查阅到的VOCs排放因子和组分特征,计算了山西省2013年的人为源VOCs的排放量,计算了臭氧生成潜势.计算结果显示山西省2013年人为源VOCs排放量为72.37万t,最主要的排放行业是工业排放源和移动源,分别占总排放量的36.47%和24.28%;在工业源中,焦炭生产和化学品生产的VOCs排放量分别为19.06万t和3.88万t,分别占工业排放行业总排放量的72.22%和14.72%,是工业排放行业中最大的排放源;2013年山西省各个排放源排放的臭氧前驱VOCs共43.59万t,所产生的臭氧生成潜势总量为176.99万t,对总臭氧生成潜势贡献最大的是移动源、燃烧源和工业排放,分别占总臭氧生成潜势总量的40.35%、26.43%和24.95%.结果表明:煤化工行业VOCs排放量显示了山西省独特的以煤为主的单一化、重型化的产业结构;机动车保有量快速增长导致了机动车的VOCs排放量巨大;移动源和工业排放源排放的VOCs所产生的臭氧生成潜势巨大.总之控制山西省的VOCs排放及其带来的臭氧污染应主要关注于控制工业排放和机动车排放.  相似文献   

7.
陈鹏  张月  张梁  熊凯  邢敏  李珊珊 《环境科学》2021,42(8):3604-3614
汽车维修行业挥发性有机物排放是臭氧前体物VOCs的重要来源,但目前汽车维修行业的VOCs减排政策主要基于VOCs的排放量,而没有考虑其化学反应活性,这将影响VOCs减排对改善空气质量的效果.通过分析汽车维修企业不同工段VOCs的产排污节点,结合各工段油漆用量及其VOCs质量分数,采用物料衡算法获得不同工段VOCs产生量及其组分,系统分析末端尾气VOCs的排放特征,并通过计算其臭氧生成潜势评估VOCs各组分的大气反应活性.结果表明,汽车维修行业油漆中产生的VOCs组分主要为苯系物,其中乙酸丁酯和二甲苯的质量分数最高.清漆由于其本身VOCs质量分数较高且用量较大,为汽车维修行业最大的VOCs排放源(92%).企业采用油性面漆VOCs产生量(22%)比水性面漆(3%)有较大程度增大,采用水性漆对汽修企业减少VOCs排放有显著效果.排气筒尾气中共检测出49种VOCs组分,前10种VOCs组分排放量占总排放量的97.9%,种类相对集中.主要污染物类别为芳香烃类(10种,30.90%~69.30%),主要组分有间/对-二甲苯(2.89%~45.00%);其次为OVOC (12种)和卤代烃(22种),贡献率分别为8.82%~43.71%和2.40%~25.00%,其他组分相对含量较少.芳香烃是汽车维修企业VOCs排放的最大组分,但是在不同研究中主要VOCs种类差异较大.汽车维修企业排放VOCs的OFP平均值为194.04 mg·m-3,SR平均值为3.37 g·g-1.间/对-二甲苯对汽车维修行业OFP贡献率最大(70.24%),为优先控制污染物.芳香烃对OFP的贡献率达到99.29%,是化学反应活性最强的组分.酯类在汽车维修行业VOCs组分中占比较大,但对OFP的贡献率相对较低,因此汽车维修行业应重点控制芳香烃类物质的排放.  相似文献   

8.
通过集中整治,我国空气质量已经有了明显改善,但在减排背景下近地面高ρ(O3)仍是当前最复杂的大气环境问题之一.利用2011—2017年(尤其是杭州市G20峰会期间)ρ(O3)、ρ(NOx)、ρ(VOCs)和气象条件观测数据,分析了杭州市G20峰会期间及不同时间尺度下杭州市ρ(O3)的变化特征及其影响因素.结果表明:①杭州市ρ(O3)日变化呈单峰型特征,15:00左右ρ(O3)达最大值(98.55 μg/m3);ρ(O3)周变化存在“周末效应”,周末ρ(O3)明显高于工作日;1 a中4—9月为ρ(O3)高值期,ρ(O3)峰值出现在5月和9月.以2013年为界,将2011—2017年ρ(O3)变化分成下降和上升2个阶段,2011—2013年呈下降趋势,降幅约为15.02 μg/m3,2014—2017年呈上升趋势,增幅约为23.25 μg/m3.②减排措施的实施对ρ(O3)存在双重作用,其可通过降低前体物质量浓度抑制O3的生成,又能引起大气污染物质量浓度下降、太阳辐射增强,从而促进O3的生成.当O3前体物质量浓度较低时,在强太阳辐射等气象条件驱动下,近地面仍会呈现高ρ(O3)的现象.③气象条件是驱动ρ(O3)日、月变化的控制因素;相反,前体物质量浓度则是ρ(O3)周、年变化的控制因素,此时VOCs或NOx控制区、“周末效应”等ρ(O3)变化特征开始显现.研究显示,不同时间尺度下杭州市O3污染的控制因素不同.   相似文献   

9.
Volatile organic compounds (VOCs) are a kind of important precursors for ozone photochemical formation. In this study, VOCs were measured from November 5th, 2013 to January 6th, 2014 at the Second Jinshan Industrial Area, Shanghai, China. The results showed that the measured VOCs were dominated by alkanes (41.8%), followed by aromatics (20.1%), alkenes (17.9%), and halo-hydrocarbons (12.5%). The daily trend of the VOC concentration showed a bimodal feature due to the rush-hour traffic in the morning and at nightfall. Based on the VOC concentration, a receptor model of Positive Matrix Factorization (PMF) coupled with the information related to VOC sources was applied to identify the major VOC emissions. The result showed five major VOC sources: solvent use and industrial processes were responsible for about 30% of the ambient VOCs, followed by rubber chemical industrial emissions (23%), refinery and petrochemical industrial emissions (21%), fuel evaporations (13%) and vehicular emissions (13%). The contribution of generalized industrial emissions was about 74% and significantly higher than that made by vehicle exhaust. Using a propylene-equivalent method, alkenes displayed the highest concentration, followed by aromatics and alkanes. Based on a maximum incremental reactivity (MIR) method, the average hourly ozone formation potential (OFP) of VOCs is 220.49?ppbv. The most significant source for ozone chemical formation was identified to be rubber chemical industrial emissions, following one by vehicular emission. The data shown herein may provide useful information to develop effective VOC pollution control strategies in industrialized area.  相似文献   

10.
天津武清大气挥发性有机物光化学污染特征及来源   总被引:7,自引:2,他引:5  
大气VOCs(挥发性有机物)是臭氧的重要前体物之一,研究其光化学污染特征和来源对控制近地面臭氧污染具有重要意义. 于2006年8月10日—9月18日在天津郊区武清采用在线监测的方法,同步观测了VOCs、O3和NO2等气态污染物,以及温度和紫外辐射等气象因子. 对9月10—15日臭氧浓度较高时段VOCs的浓度水平、化学反应活性、臭氧生成潜势和来源进行了分析. 结果表明:天津郊区武清环境空气中VOCs体积混合比平均浓度为24.6×10-9;VOCs主要由烷烃和烯烃组成,机动车排放、轻烃工艺、生物排放、沼气和碳氢溶剂是其重要来源. 根据等效丙烯浓度和MIR方法评估,烯烃对臭氧光化学产生的贡献占主导性地位,其中异戊二烯、丙烯、二甲苯和甲苯是臭氧生成潜势较大的物种. 通过与天津城区比较发现,郊区与城区的大气VOCs不仅组成不同,而且化学活性物种也不同.   相似文献   

11.
High values of ozone (O3) occur frequently in the dry spring season; thus, understanding the evolution characteristics of volatile organic compounds (VOCs) in spring is of great significance for preventing O3 pollution. In this study, a total of 101 VOCs from April 16 to May 21, 2019, were quantified using an online gas chromatography mass spectrometer/flame ionization detector (GCMS/FID). The results indicated that the observed concentration of total VOCs (TVOCs) was 30.4 ± 17.0 ppbv, and it was dominated by alkanes (44.3%), followed by oxygenated VOCs (OVOCs) (17.4%), halocarbons (12.7%), aromatics (9.5%), alkenes (8.2%), acetylene (5.3%) and carbon disulfide (2.5%). The average mixing ratio of VOCs showed obvious diurnal variation (high at night, low during daytime). We conducted a source apportionment study based on 32 major VOCs using positive matrix factorization (PMF), and coal + biomass burning (25.2%), diesel exhaust (16.0%), gasoline exhaust + evaporation (17.4%), secondary + long-lived species (16.7%), biogenic sources (4.3%), industrial emissions (9.3%) and solvent use (11.2%) were identified as major sources of VOCs. In addition to local emissions, most of the atmospheric VOCs were derived from long-distance air masses (65.7%), and the average mixing ratio of VOCs in the northwest direction was 29.4 ppbv. Combined with the results of the potential source contribution function (PSCF) indicate that research should focus on the local emissions of combustion, transportation sources and solvents usage to control atmospheric VOCs. Additionally, transmission of the northwest air mass is an important component that cannot be ignored during spring in Beijing.  相似文献   

12.
使用SUMMA罐采集华东地区5类典型合成树脂企业有组织排口样品,通过气相色质联用技术(GC-MS)定量分析106种VOCs,计算了合成树脂行业排放量、排放系数和不确定性,分析了VOCs的排放特征和臭氧生成潜势,建立了5类合成树脂VOCs排放成分谱.结果表明:合成树脂企业VOCs排放量为346~3467kg/a,5类合成树脂排放系数为0.06~1.24g/kg,其中涂料树脂(CR)类企业排放量和排放系数均最大.芳香烃、含氧烃(OVOCs)和卤代烃是合成树脂行业VOCs排放基本组分,累计占比范围是73.2%~98.3%.涂料树脂、酚醛树脂(PF)、聚氨酯(PU)、共聚物树脂(ABS)和聚碳酸酯(PC)特征污染物分别为:甲基异丁基酮、苯、甲苯、苯乙烯和二氯甲烷.合成树脂企业臭氧生成潜势(OFP)为22.7~202.5mg/m3,源反应性(SR)为0.3~4.6g/g,CR类企业OFP和SR均最大.合成树脂行业SR处于各行业平均水平.芳香烃、OVOCs和烯炔烃是合成树脂行业的主要光化学活性组分,累计OFP贡献率为64.1%~100.0%,苯、甲苯、甲基异丁基酮、乙烯、苯乙烯是合成树脂行业关键活性物种.研究显示,合成树脂行业VOCs治理应管控芳香烃和OVOCs的排放,重视污染物恶臭问题和卤代烃溶剂的危害,减排VOCs排放量大、臭氧生成能力强的CR类企业.  相似文献   

13.
挥发性有机物(VOCs)是大气中1类具有较大健康危害的污染物,同时也是大气中二次有机气溶胶和臭氧生成的重要前体物。首次使用搭载了单光子电离质谱仪(SPI-MS)的走航观测车,在2018年3月对南京江北化工园区环境空气中的VOCs进行了为期4 d的走航观测。观测期间,总VOCs的平均浓度为133.3 μg/m3,夜间平均浓度(143.6 μg/m3)较日间(123.1 μg/m3)偏高,工作日平均浓度(226.7 μg/m3)远高于周末(39.9 μg/m3)。同时还获得了高时间和高空间分辨率的VOCs分布特征,并详细分析了走航路线途经的3个重点区域(南钢-南化、扬子石化和化工大道区域)的特征污染物、浓度变化及主要排放源(企业)。总体来看,VOCs组成以烷烃和芳香烃浓度占比最大(均为31%),其次为烯烃(25%)和卤代烃(13%);但对臭氧生成潜势的贡献,则是烯烃最大(56%),其次为芳香烃、烷烃和卤代烃,分别占32%、9%和3%。该结果为化工园区VOCs的减排管理及区域臭氧污染控制提供参考。  相似文献   

14.
为探讨东莞典型工业区夏季大气挥发性有机物(VOCs)污染特征及来源,于2020年夏季在厚街镇对大气环境中56种VOCs开展了在线观测,并同步收集了臭氧(O3)、氮氧化物(NOx)和一氧化碳(CO)等气体污染物浓度和气象因子等资料,在此基础上分析了VOCs总体积分数和主要物种体积分数特征,进一步估算了主要VOCs物种对臭氧生成潜势的贡献和不同臭氧浓度下VOCs的主要污染源贡献率.结果表明,观测期间56种VOCs的体积分数平均值为53.1×10-9,其中φ(芳香烃)、φ(烷烃)、φ(烯烃)和φ(炔烃)分别为24.7×10-9、23.7×10-9、3.9×10-9和0.7×10-9.与非臭氧污染期间相比,臭氧污染期间φ(芳香烃)、φ(烷烃)、φ(烯烃)和φ(炔烃)分别上升约10%、43%、38%和98%.无论是臭氧污染还是非臭氧污染期间,芳香烃对臭氧生成潜势的贡献率均最大,其次为烷烃、烯烃和炔烃.整个夏季观测期间,溶剂源、液化石油气泄漏、化石燃料燃烧源和油气挥发源对VOCs的贡献率分别为60%±20%、16%±11%、15%±11%和9%±6%;臭氧污染期间,溶剂源的贡献率下降到44%,而液化石油气泄漏和油气挥发源的贡献率分别上升到21%和16%.  相似文献   

15.
上海北郊大气挥发性有机物(VOCs)变化特征及来源解析   总被引:1,自引:0,他引:1  
叶露 《装备环境工程》2020,17(6):107-116
2019年1月1日到10月31日期间在上海北部郊区,采用在线气相色谱仪对58种VOCs定量检测,分析了大气VOCs组成、季节变化特征和日变化规律,并利用最大增量反应活性(MIR)估算了VOCs的臭氧生成潜势(OFP),应用因子分析法对VOCs来源进行了解析。结果表明,上海大气总VOCs体积浓度为25.79×10-9,其中烷烃占比63.2%,烯烃占比11.6%,芳香烃占比19.8%,炔烃占比5.4%。总VOCs体积浓度呈现夏季高,秋季低的季节变化特征。大气臭氧生成潜势为76.99×10-9,烷烃贡献率为22.1%,烯烃为37.5%,芳香烃为38.7%,炔烃为1.7%。VOCs特征物比值(V(TVOC)/V(NO_x)和T/B比值)法表明观测点为VOCs控制区,受周边工业区源和交通源影响。大气VOCs主要来源为机动车排放、工厂生产、燃料燃烧、工业溶剂挥发及天然源。  相似文献   

16.
Based on one-year observation, the concentration, sources, and potential source areas of volatile organic compounds (VOCs) were comprehensively analyzed to investigate the pollution characteristics of ambient VOCs in Haikou, China. The results showed that the annual average concentration of total VOCs (TVOCs) was 11.4 ppbV, and the composition was dominated by alkanes (8.2 ppbV, 71.4%) and alkenes (1.3 ppbV, 20.5%). The diurnal variation in the concentration of dominant VOC species showed a distinct bimodal distribution with peaks in the morning and evening. The greatest contribution to ozone formation potential (OFP) was made by alkenes (51.6%), followed by alkanes (27.2%). The concentrations of VOCs and nitrogen dioxide (NO2) in spring and summer were low, and it was difficult to generate high ozone (O3) concentrations through photochemical reactions. The significant increase in O3 concentrations in autumn and winter was mainly related to the transmission of pollutants from the northeast. Traffic sources (40.1%), industrial sources (19.4%), combustion sources (18.6%), solvent usage sources (15.5%) and plant sources (6.4%) were identified as major sources of VOCs through the positive matrix factorization (PMF) model. The southeastern coastal areas of China were identified as major potential source areas of VOCs through the potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models. Overall, the concentration of ambient VOCs in Haikou was strongly influenced by traffic sources and long-distance transport, and the control of VOCs emitted from vehicles should be strengthened to reduce the active species of ambient VOCs in Haikou, thereby reducing the generation of O3.  相似文献   

17.
选取深圳8类典型工业行业开展VOCs样品采集,检测分析了100种VOCs组分,从PM2.5和O3协同控制的角度分析了不同污染源的成分谱特征和对环境的影响.结果表明:加油站源谱组成以烷烃(48.4%)占主导,OVOCs (27.6%)占比突出,乙酸乙酯(14.1%)、异戊烷(13.0%)、正戊烷(12.0%)为其优势排放物种;涂料制造、胶黏剂生产、油墨制造、化工制品、纺织印染、医药制造行业排放组成均以OVOCs (42.3%~97.1%)占主导,丙酮为大多数行业的优势物种,且乙腈在部分行业中占比突出.垃圾发电行业以OVOCs (33.9%)和卤代烃(28.3%)占主导,乙醛(13.4%)、丙酮(11.0%)、一氯甲烷(6.1%)为该行业排放的优势物种.以PM2.5和O3协同控制为导向,芳香烃和烯烃是储存运输源需要控制的重点;OVOCs和芳香烃都应成为工艺过程源和废弃物处理源控制的关键.涂料制造行业的源反应活性SRO3和SRSOA值分别为6.0g/g和1.2g/g,削减单位质量排放的VOCs所减少的PM2.5和O3生成潜势最多,应成为深圳市PM2.5和O3协同控制下的优先控制行业.  相似文献   

18.
为评估河南省生活垃圾焚烧发电厂排放的挥发性有机物(VOCs)对臭氧生成的贡献,选取某典型企业进行调研. 采用气袋、苏玛罐和吸附管进行采样,通过气质联用(GC/MS)和高效液质(HPLC/MS)联用分析方法对117种VOCs物种排放水平进行监测,并计算本地化VOCs排放因子. 采用最大增量反应活性(MIR)法计算臭氧生成潜势(OFP),并识别OFP贡献率较大的物种. 结果表明:①主排放口实测的VOCs总浓度为4.28 mg/m3,VOCs排放量为3.5 t/a,计算的VOCs排放因子为0.016 g/kg (以垃圾计,下同). ②MIR系数法计算的有组织OFP总排放量为9.3 t/a,对应的MIR系数平均值为2.67. ③排放量占比较大的VOCs组分依次为芳香烃(38.37%)、卤代烃(28.79%)、含氧化合物(14.32%)和烷烃(12.75%). 对OFP贡献率较大的VOCs组分为芳香烃(53.91%)和含氧化合物(28.16%),OFP贡献率排名前5位的VOCs物种分别为乙醛(20.5%)、间/对-二甲苯(20.2%)、正丁烯(6.2%)、1,2,4-三甲苯(5.4%)和正丁醛(4.9%). ④固废间、锅炉房、锅炉房外、渗滤液泵房及房顶采样点测得的VOCs无组织排放总浓度分别为83.6、6.19、1.24、5.71、1.79 mg/m3. 研究显示,该垃圾焚烧发电厂固废间VOCs浓度较高,需要进一步提高车间内VOCs收集率,以减少无组织VOCs排放,同时可在主排放口安装合适的VOCs去除装置以进一步削减VOCs有组织排放量.   相似文献   

19.
加油站成品油销售过程产生的VOCs由于物种活性高、臭氧生成潜势大,一直是我国大气O3污染防治的重点污染源之一.为了解我国不同地区加油站VOCs污染特征和排放强度,利用美国环境保护部(USEPA)人为源空气污染物排放清单编制技术手册中推荐的加油站VOCs排放测算方法 (AP-42方法),结合2019年我国31个省(自治区、直辖市)油品消费量情况以及直辖市、省会(首府)城市的环境地理信息等(不包括港澳台地区数据,下同),定量测算了2019年我国各省份加油站VOCs排放因子和排放量,研究了不同情景下我国加油站VOCs的减排潜力.结果表明:(1)我国各直辖市、省会(首府)城市加油站汽油VOCs排放因子的平均值为2.41 kg/t,但差异性较大,海口市最高(3.46 kg/t),拉萨市最低(1.47 kg/t),二者相差1.35倍.(2)无控制情形下,2019年我国加油站VOCs排放量约为41.48×104 t,主要集中在南方部分地区(广东省、江苏省、湖北省、四川省、湖南省、浙江省、安徽省、福建省)和地域人口大省(河南省、山东省和辽宁省),占加油站VO...  相似文献   

20.
挥发性有机物(VOCs)是对流层臭氧和二次有机气溶胶等二次污染生成过程的关键前体物.研究VOCs的浓度水平、组成特征和反应活性对揭示复合型大气污染的形成机制具有重要意义.本研究利用在线气相-氢离子火焰法测量了2009年春节和"五一"节期间上海市城区大气中56种VOCs.结果表明,上海市城区大气受机动车尾气排放源影响明显,VOCs浓度日变化特征呈双峰状,与上下班交通高峰基本吻合.大气中VOCs平均体积分数为(28.39±18.35)×10-9;各组分百分含量依次为:烷烃46.6%,芳香烃27.0%,烯烃15.1%,乙炔11.2%.用OH消耗速率和臭氧生成潜势(OFP)评估了VOCs大气化学反应活性,结果表明,上海市城区大气VOCs化学反应活性与VOCs体积浓度相关性良好;VOCs活性与乙烯相当,平均化学反应活性较强;OH消耗速率贡献最大的物种是烯烃51.2%和芳香烃31.8%;OFP贡献最大的物种是芳香烃53.4%和烯烃30.2%;对臭氧生成贡献最大的关键活性物种为丙烯、乙烯、甲苯、二甲苯以及丁烯类物质.  相似文献   

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