VOCs气体在活性炭上的二元吸附过程研究

采用穿透曲线法研究了4种VOCs在活性炭上的的二元吸附过程。研究表明:对于甲苯-苯、甲苯-丙酮、甲苯-乙酸乙酯、苯-丙酮、丙酮-乙酸乙酯二元吸附体系,吸附过程存在置换作用,即随着高沸点组分在床层内吸附量的逐渐增加,相对挥发性大的低沸点组分重新汽化而脱附,出现高沸点组分置换低沸点组分的现象,表现为被置换组分的穿透曲线上出现峰值。之后随着高沸点组分吸附趋于饱和,置换作用停止,低沸点组分吸附也趋于平衡。但对于沸点相近的苯-乙酸乙酯二元体系,吸附过程没有明显的置换现象。吸附量的计算结果表明,有机物在二元体系中的吸附量较同等条件时的单组分吸附量均有不同程度的降低,其中被置换组分降低程度较大,但总吸附量可近似按照浓度为二元组分总浓度低沸点组分的平衡吸附量的近似法计算,平均误差为7.9%。     

植物释放挥发性有机物(BVOC)向二次有机气溶胶(SOA)转化机制研究

利用自制玻璃生态罩,研究植物挥发性有机物（BVOC）的释放机制.在紫外光诱导条件下,BVOC经历一系列的光氧化反应,最终产生了二次有机气溶胶（SOA）.运用固相微萃取（SPME）和气相色谱-质谱联用（GC-MS）技术,对目标植物（驱蚊草）释放出的BVOC进行采样分析,共检测出7种主要化合物,其中主要为单萜类、倍半萜类、醇类和酮类物质.研究发现,在紫外光的照射下,这些BVOC可以发生光氧化反应转化为SOA.利用串联差分淌度分析仪（TDMA）测定SOA的粒径分布和SOA颗粒物的吸湿性.结果表明粒径范围大致是50～320 nm,吸湿性研究发现这些SOA具有吸湿性,生长因子可以从1.05增长到1.11.     

长江三角洲地区基于喷涂工艺的溶剂源VOCs排放特征

了解挥发性有机物(volatile organic compounds,VOCs)的溶剂源排放特征是制定长江三角洲地区PM2.5和臭氧防控策略的关键.本研究通过罐采样-GC-MS/FID测定了长江三角洲地区重点喷涂行业(集装箱喷涂、造船喷涂、木器喷涂和汽车喷涂业)的VOCs排放特征.结果表明,长江三角洲地区喷涂行业排放的主要VOCs组分为甲苯、二甲苯、乙苯等芳香烃类物质,三者之和占总VOCs的质量分数为79%~99%.生产工艺的不同对VOCs的排放组成影响并不大,废气处理装置中活性炭吸附对VOCs的组成并无明显影响,而催化燃烧的处理过程会使VOCs的排放组成产生显著变化,乙烯排放明显增大,同时也使得催化燃烧处理最大增量反应活性(maximum increment reactivity,MIR)值高于活性炭吸附处理后的MIR值,说明不同的处理措施的使用将影响VOCs对臭氧的生成作用.     

国家干线公路移动源VOCs排放及臭氧生成潜势研究

基于国家干线公路4346个交通监测站日平均监测数据,采用移动源VOCs测算方法,建立国家干线移动源VOCs排放清单,使用最大增量反应活性（MIR）估算VOCs的臭氧生成潜势（OFP）,并通过动态分段技术和核密度估计方法对臭氧生成强度的空间特征进行分析.结果表明,客车是国家干线移动源VOCs年排放量最大的源,占客货总排放量70.50%;广东省年排放量最大,占全国干线公路VOCs排放量的10.7%;G15沈海高速年排放量最大,占全国干线公路VOCs排放量的5.4%.烯烃和芳香烃为移动源OFP主要的贡献者,前十种有机污染物占干线移动源总OFP的67.29%.从客货车日均OFP强度上来看,受车流量影响,各干线差异明显.北京天津呈团簇状集聚,至石家庄一线为带状分布;济南淄博潍坊青岛一线呈弯月带状分布;南京苏州上海杭州呈团状,至上海又集聚;粤港澳大湾区以深圳为中心高度聚集;沈阳、郑州、西安、武汉、重庆等交通枢纽出现次一级强度集聚.     

太原市夏季大气VOCs污染特征及臭氧生成潜势

2018年8月采集太原市大气样品,分析太原市夏季大气VOCs的污染特征,并利用最大增量反应活性系数法（MIR系数法）估算了VOCs的臭氧生成潜势（OFP）.结果表明,太原市夏季大气VOCs浓度为17.36~89.60μg/m³,其中烷烃占比58.01%、芳香烃占比20.06%、烯烃占比16.52%、炔烃占比5.40%.大气VOCs浓度变化表现为明显的早晚双高峰特征,且以早高峰影响为主.OFP分析显示,烷烃、烯烃、芳香烃、炔烃分别占总OFP的19.16%、47.74%、31.75%、1.35%,C₃~C₅类烯烃是活性较高的物种,对O₃生成贡献较大.     

The ignored emission of volatile organic compounds from iron ore sinter process

Iron ore sintering is a major source of gaseous and particulate pollutants emission in iron smelt plant. The aim of present study is to characterize the volatile organic compounds(VOCs) emission profiles from iron ore sintering process. Both sinter pot test and sinter simulation experiment were conducted and compared. Out results showed that sinter process produced large quantity of VOCs together with NOxand SO_2. VOCs and NO were produced simultaneously in sinter pot test from 3 to 24 min after ignition, flowed by SO_2 production from 15 min to the end of sintering. Total VOCs(TVOC) concentration in sinter flue gas was affected by the coal and coke ratio in sinter raw material. The maximum TVOC concentration was 34.5 ppm when using 100% coal as fuel. Sinter simulation experiments found that the number of VOCs species and their concentrations were found by sinter temperature. The largest VOCs species varieties were obtained at 500 °C. Benzene, toluene,xylene and ethylbenzene were major VOCs in sinter flue gas based on the results from both simulation test and sinter pot. It thus demonstrated that in addition to NO_x, SO_2 and metal oxide particles, sinter flue gas also contained significant amount of VOCs whose environmental impact cannot be ignored. Based on our work, it is timely needed to establish a new VOC emission standard for sinter flue gas and develop advanced techniques to simultaneously eliminate multi-pollutants in iron ore sinter process.     

Characteristics of volatile organic compounds, NO2, and effects on ozone formation at a site with high ozone level in Chengdu

Chengdu is a megacity in the southwest of China with high ozone (O₃) mixing ratio. Observation of volatile organic compounds (VOCs), NO₂ and O₃ with high temporal resolution was conducted in Chengdu to investigate the chemical processes and causes of high O₃ levels. The hourly mixing ratios of VOCs, NO₂, and O₃ were monitored by an online system from 28 August to 7 October, 2016. According to meteorological conditions, Chengdu, with relative warm weather and low wind speed, is favorable to O₃ formation. Part of the O₃ in Chengdu may be transported from the downtown area. In O₃ episodes, the average mixing ratios of NO₂ and O₃ were 20.20?ppbv and 47.95?ppbv, respectively. In non-O₃ episodes, the average mixing ratios of NO₂ and O₃ were 16.38?ppbv and 35.15?ppbv, respectively. The average mixing ratio of total VOCs (TVOCs) was 40.29?ppbv in non-O₃ episodes, which was lower than that in O₃ episodes (53.19?ppbv). Alkenes comprised 51.7% of the total O₃ formation potential (OFP) in Chengdu, followed by aromatics which accounted for 24.2%. Ethylene, trans-pentene, propene, and BTEX (benzene, ethylbenzene, toluene, m/p-xylene, o-xylene) were also major contributors to the OFP in Chengdu. In O₃ episodes, intensive secondary formations were observed during the campaign. Oxygenated VOCs (OVOCs), such as acetone, Methylethylketone (MEK), and Methylvinylketone (MVK) were abundant. Isoprene rapidly converted to MVK and Methacrolein (MACR) during O₃ episodes. Acetone was mainly the oxidant of C3-C5 hydrocarbons.     

兰州市典型企业VOCs排放特征及反应活性分析

基于兰州市大气VOCs排放清单,选取石化厂、乙烯厂、涂料厂3个典型企业采集VOCs样品,分析其无组织排放特征,并采用MIR（最大增量反应活性）法和LOH（·OH反应速率）法综合评价其化学反应活性,识别各企业的VOCs活性优势物种,同时探究不同企业特征VOCs比值.结果表明:不同排放源φ（VOCs）差异较大,范围为20.8×10-9~6 520.3×10-9.从VOCs物种构成上来看,涂料厂芳香烃占比最高,而石化厂、乙烯厂均以烷烃物种最为丰富,石化厂不同工艺VOCs物种构成略有差异.从活性上看,涂料厂VOCs活性最高,其LOH和OFP（臭氧生成潜势）分别为2 676.9 s-1和72 519.0×10-9,约为其他行业的18~1 000倍,间/对-二甲苯、乙苯、邻二甲苯等物种活性较大;其次为石化厂,其LOH和OFP分别为273.2 s-1和4 039.1×10-9,正戊烷、异戊烷、乙烯、丙烯等物种活性贡献率高,其中柴油工艺对石化厂VOCs活性贡献率最大;乙烯厂的OFP最低,其LOH和OFP分别为4.6 s-1和69.7×10-9,其VOCs活性主要来自乙烯、丙烯、正丁烯等烯烃物种.各工业源BTEX（苯、甲苯、乙苯及3种二甲苯异构体的合称）分布具有一定的差异,对于指示不同VOCs来源有一定的参考价值,但不同源比值的重叠性也表明并非全部VOCs来源可以通过特征物种比值来区分.研究显示,控制工业源特别是涂料与石化工业VOCs的排放有助于控制兰州市O₃的生成.      

低温等离子体技术在乙烯装置VOCs治理中的应用

针对乙烯裂解装置污水会逸散出少量的VOCs气体,其苯系物及烯烃类物质含量高、恶臭明显、湿度大、浓度波动大,治理难度极大,所处环境为火灾爆炸危险区域且废气可能达到爆炸下限,安全控制措施要求高这一情况,建成了国内首套防爆型低温等离子体VOCs废气治理设施,在某石化公司防爆1区安全运行一年,实践证明:苯系物、烯烃、硫化物的去除效率可达98%以上,达到国标的各项要求,电气安全控制措施能够满足防爆1区。     

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.