深圳市夏季臭氧污染研究

以2009年8月为例分析了深圳市夏季臭氧污染情况及污染气象特征,基于二维空气质量模式对臭氧污染控制进行数值模拟. 结果表明:深圳市８月各监测点均存在臭氧超标现象,污染形势严峻;副热带高压控制和热带气旋外围下沉气流是造成夏季出现高浓度臭氧的主要天气过程,此时大气边界层混合层高度在500～800 m,且近地面风速约在5 ms以内,不利于污染物扩散;臭氧的生成受前体物挥发性有机物(VOC)和氮氧化物(NO_x)排放的共同影响,其中VOC排放的影响较大,深圳市臭氧控制应以降低VOC排放量为重点,模拟得出对VOC和NO_x按25∶1～40∶1的比例协同减排可有效降低臭氧污染.      

Calculation of long-term averaged and episodic oxidant concentrations for the Netherlands

Ground-level ozone and oxidant (sum of O₃ and NO₂) concentrations in The Netherlands are calculated during the growing season (May–September) by means of a Lagrangian long-range transport model. Two air parcels—one representative of the mixed layer, the other representative of the polluted layer above the mixed layer (aged smog layer)—are followed along 96 h back trajectories. Long-term averaged and 98 percentile values of hourly averaged concentrations are estimated on the basis of concentrations calculated for four arrival times per day for all days in the period considered.In a number of sensitivity runs the influence of European anthropogenic NO_x and VOC emissions on the oxidant concentrations in The Netherlands has been investigated. In general, the influence of European emissions on the 98-percentile values is 2–3 times as large as on the averaged concentrations. This indicates that long-term averaged concentrations more strongly depend on the concentrations in the free troposphere whereas the episodic concentrations are determined by photochemical production over Europe. VOC emission reduction is more effective in lowering episodic concentrations than NO_x emission reduction. For long-term averaged concentrations, however, NO_x and VOC emission reduction of 50% or more are nearly equally effective.     

Reactivity-based strategies for photochemical ozone control in Europe

A photochemical trajectory model has been used to assess reactivity-based VOC emission control strategies for Europe by implementing a detailed speciated VOC emission inventory and a highly explicit Master Chemical Mechanism. These reactivity-based strategies envisaged that the emissions of the xylenes, trimethylbenzenes and all aromatic species could be replaced or substituted by the emission of one of a potential range of 94 organic compounds, each present in current emissions. Depending on the reactivity of the substituted VOC species, ozone mixing ratios along an east–west air parcel trajectory travelling for 5 days across northwest Europe would increase or decrease relative to a base case without substitution. In all, eight alcohols, six esters, six ketones, three ethers and an alkane, a cycloalkane and a glycol ether have been identified that give greater ozone reductions when substituting for aromatic compounds than would be given by the corresponding mass-based control strategy. It is concluded that VOC substitution strategies for the stationary sources would offer significant ozone benefits compared with simple across-the-board mass emission reduction strategies of the kind proposed by the EU CAFÉ and UN ECE LRTAP convention processes.     

天津临港某仓储公司VOCs排放特征及臭氧生成潜势

为了研究储运环节VOCs的排放影响,参考HJ 732-2014《固定污染源废气挥发性有机物的采样气袋法》,选择天津临港工业园区某石化业仓储公司为重点监测对象,对企业的厂界上下风向、有组织和无组织排放源进行采样,利用在线仪器PTR-TOF-MS对采集的样品进行VOCs定量分析,并对厂界处O₃-NO_x -VOCs三者的关系和污染物的臭氧生成潜势进行研究.结果表明:有组织排放源——洗涤塔、活性炭吸附塔1号和2号的∑ρ（VOCs）（所有VOCs组分浓度之和）分别为18.91、71.48和5.65 mg/m3,无组织排放源——罐组和装卸车台∑ρ（VOCs）分别为0.39和0.087 mg/m3;甲醇为企业的特征污染物,此外还有烷烃和少量的烯烃,有组织排放中活性炭吸附塔2号是影响厂界污染特征的主要环节;有组织和无组织VOCs排放量分别为0.57和214.26 t/a.对O₃-NO_x-VOCs三者关系的分析显示,企业厂界处O₃的形成主要受VOCs控制,其臭氧生成潜势为烯烃>醇类>烷烃,除考虑醇类的影响外,烯烃也是不可忽视的环境影响因素.      

Calculation of long term averaged ground level ozone concentrations

Seasonal averaged ground level concentrations for O₃ have been calculated for The Netherlands by means of a two-layer Lagrangian long-range transport (LRT) model. The model includes emissions, nonlinear atmospheric chemistry, dry deposition, exchange between boundary layer (BL) and free troposphere (FT) and fumigation between a mixed layer and an aged smog layer. Concentrations of primary and secondary pollutants in the FT are obtained from a two-dimensional global model developed by Isaksen.In the reference calculation the modelled concentrations of Ox (sum of O₃ and NO₂) and O₃ are in fair agreement with measurements. The NO_x (sum of NO and NO₂) and NO₂ concentrations are under-estimated by the model but there is a good temporal correlation between calculated and measured concentrations. Validation of other components involved in the chemical scheme is hardly possible due to the paucity of measured data. It can only be stated that the results presented in this paper are not in disagreement with measured or modelled data presented in the literature.In a number of sensitivity runs the influence of European anthropogenic emissions of NO_x and volatile organic compounds (VOC) has been investigated. The calculations indicate that the influence of European emissions on the growing season, daytime averaged (May–September, 10–17 h) O₃ concentrations in The Netherlands is small. For European reductions in the order of tens of per cents a VOC emission reduction is more effective than a NO_x emission reduction in lowering the O₃ concentrations. For strong reductions (about 70%) VOC and NO_x are equally effective. The effects of the modelled underprediction of NO_x concentrations on the production of O₃ on a European scale are probably small. On a local scale the effects are more pronounced due to the NO/O₃ titration (photostationary equilibrium). Therefore, an empirical correction is applied on the modelled O₃ concentrations. After this correction, it is shown that daytime O₃ levels during the growing season increase when European NO_x emissions are reduced (2.0–7.7.% increase at 50% NO_x emission reduction). A reduction in VOC emission leads to decreasing O₃ levels (9% reduction for 40% VOC emission reduction, 16% reduction for 70% VOC emission reduction). For a combined reduction of both VOC and NO_x slightly decreasing ground level O₃ concentrations are expected.     

Observation and analysis of atmospheric volatile organic compounds in a typical petrochemical area in Yangtze River Delta, China

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.     

南京工业区挥发性有机物来源解析及其对臭氧贡献评估

在南京工业区连续测量了2014年5月1日~7月31日和2015年6月1日~7月16日夏季两个高臭氧期的大气中的挥发性有机化合物(VOCs).结合正交矩阵分解(PMF)模型和箱模式(OBM)分析VOCs来源对局部O3生成的贡献.2014年和2015年夏季VOCs浓度平均分别为(36.47±33.44)×10-9和(34.69±34.08)×10-9.PMF模型确定了7种源类别,其中包括汽车尾气、液化石油气(LPG)排放、生物源排放、家具制造业、化工业、化学涂料行业、化学材料工业排放源.在OBM模拟中评估O3与前体物的关系.南京工业区是VOCs控制区,VOCs具有正RIR值,NO的RIR值为负值.烯烃(1.20~1.79)和芳香烃(1.42~1.48)呈现较高的RIR值,控制这两类物种是控制O3浓度最有效的途径.烯烃排放量减少80%时烯烃RIR值达到最高.汽车尾气(1.01~1.11)、液化石油气(0.74~0.82)、生物源排放量(0.34~0.42)和家具制造业(0.32~0.49)是O3形成贡献最大的四大类VOCs来源;减少汽车尾气,生物排放,LPG和家具制造业排放应成为减少局地O3生成最有效策略.     

佛山市发展公交车尾气削减潜力分析

采用COPERTⅣ模型计算佛山市公交车、摩托车和小型客车排放因子,结合保有量、年平均行驶里程计算其排放量,对佛山市公交车出行环境效果及尾气削减潜力进行情景分析。结果表明:2011年佛山市公交车CO、VOC、NOx和PM的排放量为804.57、283.85、3 365.32和73.00 t。单人单次公交车出行CO和VOC的排放量较摩托车和小型客车低,但NOx则较高。公交车载客人数从17人上升至25、35、45人,单人单次出行每公里排放量分别下降32.00%、51.43%和57.50%。佛山市低排放标准的柴油公交车全部更换成国Ⅳ排放标准柴油车,CO、VOC、NOx和PM的年排放量分别削减611.66、151.6、1 231.18和58.39 t。EEV标准天然气公交车替代柴油公交车可减少NOx和PM的排放,但对VOC的削减并无优势。佛山市现有柴油公交车更换成EEV标准天然气公交车,CO、NOx和PM的年排放量分别削减293.71 t、2 086.87 t和70.34 t,但VOC的年排放量升高228.01 t。     

咸宁市大气臭氧敏感性和污染来源解析

为掌握咸宁市臭氧（O₃）污染状况,基于统计分析方法研究咸宁市2018年O₃地面观测数据,发现该年3~10月均有O₃浓度超标日发生,其中6、8、9、10月有浓度较高且持续时间较长的严重污染,高浓度时段集中于4~7月的每日12：00~20：00,浓度峰值出现时间约为16：00前后.使用OBM模型模拟,借助EKMA曲线、RIR分析等识别O₃敏感性,发现咸宁属于VOCs控制区,O₃生成对人为源VOCs中的二甲苯类芳香烃和烯烃类较敏感,这两类物种浓度均削减10%后分别得到RIR值为0.271和0.238.开展离线VOCs监测,经PMF方法解析得到5类源,其中工业排放为O₃污染主要贡献源,二甲苯类芳香烃绝大部分来自溶剂使用,烯烃类主要来自燃烧源.当O₃超标时,相比于非超标日,植物源、溶剂使用和燃烧源的贡献率均有增加,其中植物源的贡献增量较大,而机动车尾气和工业排放的贡献率却有一定程度的降低.     

基于PMF量化工业排放对大气挥发性有机物(VOCs)的影响:以南京市江北工业区为例

挥发性有机物(VOCs)在臭氧(O3)和二次有机气溶胶(SOA)生成中起着关键作用.南京市江北地区工业密集,为评估工业排放对大气VOCs的影响,本研究于2017年3月在工业区受体点南京信息工程大学(南信大)开展了为期近1个月的VOCs采样和测量.监测数据显示南信大站点大气VOCs浓度波动大,范围(体积分数)在10.3×10-9~200.5×10-9之间,烯烃、芳香烃和卤代烃等组分(例如:乙烯、丙烯、苯、苯乙烯、二氯甲烷等)存在明显的异常高值.利用正交矩阵因子模型(PMF)对VOCs进行来源解析,结果显示在观测期间与工业排放相关源的平均贡献为50.0%,其中石化源、化工源以及涂料和溶剂使用源的贡献分别为14.9%、19.3%和15.8%.在VOCs高污染时段,与工业排放相关源的占比高达74.9%.进一步结合风速和风向数据,确定了不同类型工业源的主导方位,追溯排放源的潜在位置.     

植物源挥发性有机化合物排放清单的研究进展

根据近期国内外相关文献,从植物VOC排放清单的角度,对不同空间尺度下植物VOC排放模型的建立与排放清单量值的估算进行了归纳,其中,中国植被VOC年排放总量的估算值(以C计)在12.4~28.4 Tg·a-1之间,2000年北京市园林绿地植物VOC年总排放量约为3.85万t.另外,以北京城市为例,为确定城市大气污染物的总体减排对策,还进一步对园林植物VOC排放清单量值对大气中O3与SOA形成的贡献进行了介绍,在同一时期内,相比园林植物,人为源排放的活性芳香烃类化合物和烯烃类对大气中O3的产生贡献最大,人为源排放的芳香烃还是北京SOA生成潜势的主要贡献源.最后建议重点控制城市人为源的VOC排放,这将对降低北京城市臭氧与二次有机气溶胶污染起到关键作用.     

某典型石油化工园区冬季大气中VOCs污染特征

利用TH-300B挥发性有机物(volatile organic compounds,VOCs)在线监测系统于2014年12月~2015年2月对我国某石油化工园区的VOCs进行连续在线监测.分析了其组成特征、时间变化特征、来源以及光化学活性特征.结果表明,研究区冬季大气中VOCs的混合体积分数较高,烷烃占据主导地位,占TVOCs的86.73%;TVOCs、烷烃、烯烃、芳香烃的昼夜变化特征均表现为夜间高而白天低,且烷烃、烯烃的变化与TVOCs较为一致.利用主成分分析-多元线性回归(PCA-MLR)模型解析得到5个因子,分别表征燃料挥发源、工业排放源、汽油车尾气和植物排放混合源、柴油车尾气排放源和燃料燃烧源,其贡献率分别为60.02%、8.50%、2.07%、12.21%、17.20%.利用Propy-equiv法和MIR法计算得出该研究区冬季大气中各类VOCs对臭氧生成的相对贡献率的大小均表现为烷烃烯烃芳香烃,其中环戊烷、正丁烷和1-戊烯的贡献率较高,气团光化学年龄较长.     

夏季长三角地区臭氧非线性响应曲面模型的建立及应用

2013年8月上旬,长三角地区发生了一次大范围高浓度臭氧污染事件.本研究基于WRF-CMAQ空气质量模型系统,结合长三角地区大气污染物排放清单,构建了臭氧与其前体物之间的非线性响应曲面模型(Response surface modeling,RSM).基于RSM探讨了长三角地区O_3化学的敏感性特征,分析了上海市O_3的来源并预测不同情景下O_3的变化,提出O_3污染的最优控制方案.研究结果表明,长三角地区夏季O3主控因素区域差别较大,上海环科院、杭州卧龙桥、南京玄武湖等城区点位属于VOC控制型;徐州铜山、合肥肥西、丽水青田等郊区属于NOx控制型.O_3的敏感性特征在不同浓度水平下也呈现较大差异,随着O_3浓度水平的升高,各地区NOx敏感性均有所增加.从区域来源来看,远距离传输对平日上海O_3贡献较大,占50%以上;而在O_3污染日,本地及区域贡献为72.1%,而远距离传输贡献下降至27.9%.快速预测了110组减排情景,表明在本地及区域前体物均减排70%的情况下,2013年8月上海O_3浓度能完全达标.     

京津冀地区严重光化学污染时段O3的时空分布特征

利用MCCM(多尺度气象空气质量模式)对京津冀地区2008年6月严重光化学污染时段的近地面φ(NO_x)和φ(O₃)进行了模拟;同时,为了检验MCCM系统模拟φ(O₃)时空分布的能力,将模拟的气象要素、φ(NO_x)和φ(O₃)与观测数据进行了比对,并利用验证后的模拟结果对该地区严重光化学污染时段O₃时空分布特征进行研究. 结果表明:①MCCM模式可较好地反映气象场和污染物浓度场的时空分布特征. 气温、露点温度和气压的观测值与模拟值的相关系数分别为0.85、0.77和0.95;模拟的化学物种浓度的时空分布与观测结果基本相符. ②城市中心地区φ(NO_x)较高,北京和天津城市地区的φ(NO_x)甚至超过了30×10-9;京津冀平原大部分地区午后14:00φ(O₃)的最大值超过了70×10-9;而太行山沿线φ(O₃)的最大值超过了80×10-9. 结合气象要素的分析表明,午后φ(O₃)在太行山沿线的高值与气压场和流场关系密切. ③利用判断O₃生成敏感性指标——H₂O₂/HNO₃(体积分数比)分析发现,φ(O₃)日最大值和φ(总氧化剂)(总氧化剂=NO₂₊O₃)平均值的高值区域与O₃生成受NO_x和VOCs协同控制的区域极为吻合. 因此,要达到降低区域的光化学污染,应以VOCs的消减为主,同时兼顾NO_x的消减.      

VOC emission caps constrained by air quality targets based on response surface model: A case study in the Pearl River Delta Region, China

Because of the recent growth in ground-level ozone and increased emission of volatile organic compounds (VOCs), VOC emission control has become a major concern in China. In response, emission caps to control VOC have been stipulated in recent policies, but few of them were constrained by the co-control target of PM_2.5 and ozone, and discussed the factor that influence the emission cap formulation. Herein, we proposed a framework for quantification of VOC emission caps constrained by targets for PM_2.5 and ozone via a new response surface modeling (RSM) technique, achieving 50% computational cost savings of the quantification. In the Pearl River Delta (PRD) region, the VOC emission caps constrained by air quality targets varied greatly with the NO_x emission reduction level. If control measures in the surrounding areas of the PRD region were not considered, there could be two feasible strategies for VOC emission caps to meet air quality targets (160 µg/m³ for the maximum 8-hr-average 90th-percentile (MDA8-90%) ozone and 25 µg/m³ for the annual average of PM_2.5): a moderate VOC emission cap with <20% NOx emission reductions or a notable VOC emission cap with >60% NO_x emission reductions. If the ozone concentration target were reduced to 155 µg/m³, deep NO_x emission reductions is the only feasible ozone control measure in PRD. Optimization of seasonal VOC emission caps based on the Monte Carlo simulation could allow us to gain higher ozone benefits or greater VOC emission reductions. If VOC emissions were further reduced in autumn, MDA8-90% ozone could be lowered by 0.3-1.5 µg/m³, equaling the ozone benefits of 10% VOC emission reduction measures. The method for VOC emission cap quantification and optimization proposed in this study could provide scientific guidance for coordinated control of regional PM_2.5 and O₃ pollution in China.     

涂料制造行业挥发性有机物排放成分谱及影响

采用不锈钢采样罐对华东地区8家涂料制造企业生产车间排口进行采集,运用气相色谱-质谱联用技术（GC-MS）测定了106种VOCs组分,识别了VOCs排放特征,建立了溶剂型涂料和水性涂料VOCs排放成分谱,分析了VOCs对臭氧生成的贡献.结果表明,涂料制造行业VOCs特征组分主要为芳香烃和含氧烃,两者浓度范围在65.5%~99.9%,溶剂型涂料VOCs排放主要以芳香烃为主,占总VOCs的63.0%~94.0%;水性涂料VOCs排放主要以含氧烃为主,占总VOCs的54.5%~99.9%.间/对-二甲苯（32.4%）、乙苯（19.0%）和乙酸乙酯（12.1%）为溶剂型涂料源排放特征,乙酸乙酯（83.7%）与2-丁酮（8.0%）为水性涂料源排放特征.芳香烃和含氧烃是涂料制造行业的主要活性组分,对臭氧生成潜势（OFP）的总贡献率在92.9%~99.9%之间.源反应活性分析（SR）表明,水性涂料单位质量VOCs对臭氧的生成贡献低于溶剂型涂料,因此可显著降低臭氧的生成潜势.研究显示,针对涂料制造行业VOCs污染治理,应重点关注芳香烃和含氧烃中对臭氧生成潜势贡献较大的VOCs组分,进行源头和精细化控制.     

Emissions of SOχ, NOχ, VOC and CO from East European countries

For the purpose of model calculations of long-term ozone levels over Europe a database, resembling that of the PHOXA project (PHotochemical OXidant and Acid deposition model application) and an inventory of SO_χ, NO_χ, VOC and CO emissions from main source types has been prepared for the reference year 1985 for all European Countries. The U.S.S.R. was included to 60° east longitude. Emissions from OECD and CEC member countries could be taken and updated where necessary, from recently compiled inventories. Emissions from East European countries, however, were only available in a form too aggregated to be applicable for the project. In this paper, the estimation of emissions from these countries is described and possibilities for improvement are discussed. This emission inventory is the first one for Eastern Europe with a rather complete structure including composition profiles of pollutants, temporal allocation procedures and temperature relations.     

东亚边界层臭氧时空分布的数值模拟研究

利用嵌套网格空气质量预报模式系统(NAQPMS)对2010年东亚地区边界层臭氧(O3)的时空分布进行了数值模拟,并评估了东亚边界层光化学反应的活性.结果表明,NAQPMS模式与观测结果较为一致,站点观测与模拟的日均值(月均值)相关系数达到0.56~0.91,模式能合理再现东亚地区地面O3的时空分布特征.东亚地区冬季边界层O3低值区出现在中国东部;春季O3浓度增加,西北太平洋沿岸地区O3浓度达60μL/m3左右;夏季东亚中纬度35°N附近大陆地区O3由于强烈的光化学反应呈现出一浓度高值带,浓度达60μL/m3以上;秋季东亚大部分地区O3浓度维持在40~45μL/m3左右.夏季中国京津冀和长江三角洲部分地区光化学净生成率已超过30×10-9/d.     

天津临港石化企业VOCs排放特征及环境影响

为研究化工园区VOCs排放特征及其环境影响,选取天津临港工业区内典型企业A、B、C、D、E进行重点监测,对其有组织、无组织排放各环节、厂界和敏感点的VOCs种类和浓度进行定性和定量分析,并利用偏相关分析方法对其厂界和敏感点进行环境影响因素研究.结果表明,企业A、B、D、E有组织排放的ρ（总VOCs）分别为2.32、1.16、3.30、35.85 mg/m3,其主要污染物分别为环己烷及其同分异构体、丙烯、丙烯腈、甲醇.企业A、B、C、D的无组织排放均以烷烃为主,主要污染物为甲基己烷及其同分异构体、正壬烷;企业E的无组织排放以醇类和烷烃为主,主要污染物为甲醇、正十一烷和乙烷.敏感点的主要污染物与各企业的主要污染物相似.研究显示,企业A、D、E的有组织排放ρ（总VOCs）比无组织大,分别以烷烃、氰化物和醇类为主,企业B、C以无组织烷烃排放为主.无组织排放是影响企业厂界ρ（VOCs）的主要因素;以生产丙烯为主的企业B对敏感点影响最大,相关系数为0.582（P≤0.01）,是影响园区敏感点的主要污染源.      

河南省某典型垃圾焚烧发电厂的VOCs排放特征

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.