泡沫塑料鞋制造区VOCs污染特征及臭氧生成潜势

于泡沫塑料鞋制造集中区和周边设置了5个采样点,研究其大气VOCs的污染特征和对臭氧生成的潜在影响.结果显示泡沫塑料制鞋行业大气VOCs组成以烷烃（38.4%）、含氧挥发性有机物（33.5%）和芳香烃（19.5%）为主,80种VOCs浓度为137.1~169.0μg/m³（均值149.1μg/m³）.正戊烷、异戊烷、正丁烷、异丁烷、甲醛、甲苯、间/邻二甲苯、丙酮、丁酮、环己酮、甲基丙烯酸甲酯、乙酸乙酯为泡沫塑料鞋制造行业的特征VOCs.总VOCs、特征VOCs类型（含氧挥发性有机物、芳香烃）和特征VOCs组分（甲苯、邻二甲苯、间二甲苯、丁酮、乙酸乙酯）的浓度空间变化趋势依次为污染区 > 受影响区（下风向） > 对照区（上风向）.同时,采用最大增量反应活性（MIR）方法估算了VOCs的臭氧生成潜势（OFP）,均值为544.6μg/m³,表明泡沫塑料鞋制造导致了周边环境空气VOCs污染且对臭氧生成存在明显潜在影响.     

帕米尔高原东部PM10输送路径及潜在源分析

基于HYSPLIT后向轨迹模式和NCEP的GDAS数据（2019年3月~2020年2月）,对抵达帕米尔高原东部的48h后向气团轨迹按季节聚类,其PM₁₀和PM_2.5年均值分别为（29.4±16.4）,（9.3±5.1）μg/m³,大气颗粒物以PM₁₀为主,结合同期PM₁₀浓度数据,分析不同路径对帕米尔高原东部PM₁₀聚集的贡献,并利用潜在源贡献因子法（PSCF）和浓度权重轨迹法（CWT）,揭示研究期间帕米尔高原东部不同季节PM₁₀的潜在源分布及其贡献水平.结果表明：帕米尔高原东部PM₁₀输送路径的季节特征明显,春季来自中亚的西风气流对应PM₁₀高值,夏季来自中国新疆西部的气流也对应较高PM₁₀值,秋季各轨迹对应PM₁₀值相当,冬季来自南亚方向气流对应PM₁₀高值.PM₁₀春季贡献源区主要位于中国新疆西部、阿富汗东北部、巴基斯坦东北部、塔吉克斯坦中部及东部地区,夏季主要位于中国新疆西部喀什与和田北部地区,秋季主要位于土库曼斯坦东部、乌兹别克斯坦东南部、巴基斯坦北部、阿富汗北部与塔吉克斯坦南部接壤地区,冬季主要位于巴基斯坦东北部、印度北部以及阿富汗北部.     

Comparison of light absorption and oxidative potential of biodiesel/diesel and chemicals/diesel blends soot particles

Soot particles,mainly coming from fuel combustion,affect climate forcing through absorbing light and also result in adverse human health outcomes.Though biodiesel or additives blending with diesel was considered environmentally friendly,the understanding on absorbing and oxidative capacity of soot emitted from them are still unclear.The watersoluble organic carbon(WSOC) content,surface chemical structure,light absorption and oxidative potential(OP~(DTT)) of soot from biodiesel/diesel and chemicals/diesel blends were investigated utilizing total organic carbon analyzer,X-ray photoelectron spectrometer,ultraviolet–visible spectrophotometry and dithiothreitol(DTT) assay.The differences and correlations between soot properties were statistically analyzed.Chemicals/diesel blends soot owned significantly higher WSOC content,ratio of mass absorbing efficiency(MAE) in250 and 365 nm(E_2/E_3),OP~(DTT),and higher surface carbonyl content.Coconut biodiesel/diesel blends soot contained evidently higher aromatic carbon–oxygen single bond(Ar_C–O)content,and higher MAE365.The individual comparison of biodiesel/diesel blends showed20% coconut biodiesel blend owned the lowest WSOC,E_2/E_3 and OP~(DTT),while highest Ar_C–O and MAE365,representing strongest absorbing properties.Association analysis showed OP~(DTT)was significantly positively correlated with WSOC.Further,the evident negative correlation between MAE365 and OP~(DTT) was observed.Our results showed coconut biodiesel/diesel blends soot induced lower levels of oxidative potential,whereas absorption of light was higher,which have far reaching consequences on climate forcing.Therefore,it is important to evaluate the balance point between light-absorbing properties and oxidative potential,under the wide use of biodiesel.     

Environmental impact and health risk assessment of volatile organic compound emissions during different seasons in Beijing

Volatile organic compounds (VOCs) are major contributors to air pollution. Based on the emission characteristics of 99 VOCs that daily measured at 10 am in winter from 15 December 2015 to 17 January 2016 and in summer from 21 July to 25 August 2016 in Beijing, the environmental impact and health risk of VOC were assessed. In the winter polluted days, the secondary organic aerosol formation potential (SOAP) of VOC (199.70 ± 15.05 μg/m³) was significantly higher than that on other days. And aromatics were the primary contributor (98.03%) to the SOAP during the observation period. Additionally, the result of the ozone formation potential (OFP) showed that ethylene contributed the most to OFP in winter (26.00% and 27.64% on the normal and polluted days). In summer, however, acetaldehyde was the primary contributor to OFP (22.00% and 21.61% on the normal and polluted days). Simultaneously, study showed that hazard ratios and lifetime cancer risk values of acrolein, chloroform, benzene, 1,2-dichloroethane, acetaldehyde and 1,3-butadiene exceeded the thresholds established by USEPA, thereby presenting a health risk to the residents. Besides, the ratio of toluene-to-benzene indicated that vehicle exhausts were the main source of VOC pollution in Beijing. The ratio of m-/p-xylene-to-ethylbenzene demonstrated that there were more prominent atmospheric photochemical reactions in summer than that in winter. Finally, according to the potential source contribution function (PSCF) results, compared with local pollution sources, the spread of pollution from long-distance VOCs had a greater impact on Beijing.     

产业转移视角下京津冀石化产业碳排放因素分解与减排潜力分析

石化产业是我国经济的支柱性产业,但其大量的碳排放却给环境造成严重负担,因此提倡石化产业低碳发展能有效推动京津冀区域经济与环境绿色均衡发展.基于产业转移视角,分析2007-2016年京津冀区域石化产业碳排放量现状;运用对数平均迪式分解（Logarithmic Mean Divisia Index,LMDI）法分解并分析京津冀区域石化产业碳排放量影响因素在三地的作用效果,进而借助产业竞争力系数佐证碳排放量影响因素作用效果在区域间的关联性;最后通过合理调整京津冀区域石化产业能源结构,将未调整和调整后的能源结构类型分别设置为基准情境和低碳情境,利用SPSS拟合最优曲线来预测2017-2030年京津冀区域石化产业减排潜力.结果表明:①2007-2016年京津冀区域石化产业碳排放量增加386.79×104 t,碳排放强度由0.77 t/（104元）降至0.31 t/（104元）.②2007-2016年,能源强度因素使京津冀区域石化产业碳排放量减少13 663.77×104 t,其贡献率高达148.38%;人均GDP因素促使石化产业碳排放量增加12 327.10×104 t,贡献率达110.69%.③对于石化产业竞争力系数,北京市由0.03降至-0.02,为三地石化产业转出地;河北省由-0.14增至0.16,为转入地.④在低碳情境下,2020年、2030年京津冀区域石化产业碳排放量分别比基准情境减少502.84×104、528.95×104 t,碳排放强度分别降至0.19、0.17 t/（104元）,均达到发展目标的要求.研究显示,2007-2016年京津冀区域石化产业碳排放量逐年上升,承受巨大减排压力,该区域可以通过调整石化产业能源结构来挖掘碳减排潜力,推动石化产业绿色发展.      

Characteristics and ozone formation potential of volatile organic compounds in emissions from a typical Chinese coking plant

Coking industry is an important volatile organic compounds (VOCs) emission source in China, however, detailed information on VOCs emissions is lacking. Therefore, we selected a typical mechanized coking plant and collected air samples according to the Emission Standard of Pollutants for Coking Chemical Industry (GB16171-2012). Using gas chromatography-mass spectrometry method, we analyzed the VOCs in the air samples, and applied maximum increment reactivity (MIR) rule to estimate ozone formation potential (OFP) of the VOCs emitted from the coke production. More than 90 VOCs species were detected from the coking plant, including alkanes, alkenes, alkynes, aromatic hydrocarbons, halogenated hydrocarbons and oxygenated VOCs. The concentrations of VOCs (ρ(VOCs)) generated at different stages of the coking process are significantly different. ρ(VOCs) from coke oven chimney had the highest concentration (87.1 mg/m³), followed by coke pushing (4.0 mg/m³), coal charging (3.3 mg/m³) and coke oven tops (1.1 mg/m³). VOCs species emitted from the coke production processes were dominated by alkanes and alkenes, but the composition proportions were different at the different stages. Alkenes were the most abundant emission species in flue gases of the coke oven chimney accounting for up to 66% of the total VOCs, while the VOCs emissions from coke pushing and coal charging were dominated by alkanes (36% and 42%, respectively), and the alkanes and alkenes emitted from coke oven top were similar (31% and 29%, respectively). Based on above results, reduction of VOCs emissions from coke oven chimney flue gases is suggested to be an effective measure, especially for alkenes.     

Characteristics of atmospheric volatile organic compounds in urban area of Beijing: Variations, photochemical reactivity and source apportionment

Atmospheric volatile organic compounds (VOCs) were observed by an on-line gas chromatography-flame ionization detector monitoring system from November 2016 to August 2017 in Beijing. The average concentrations were winter (40.27 ± 25.25 μg/m³) > autumn (34.25 ± 19.90 µg/m³) > summer (32.53 ± 17.39 µg/m³) > spring (24.72 ± 17.22 µg/m³). Although benzene (15.70%), propane (11.02%), ethane (9.32%) and n-butane (6.77%) were the most abundant species, ethylene (14.07%) and propene (11.20%) were the key reactive species to ozone formation potential (OFP), and benzene, toluene, ethylbenzene, m-xylene + p-xylene and o-xylene (54.13%) were the most reactive species to secondary organic aerosol formation potential (SOAFP). The diurnal and seasonal variations indicated that diesel vehicle emission during early morning, gasoline vehicle emission at the traffic rush hours and coal burning during the heating period might be important sources. Five major sources were further identified by positive matrix factorization (PMF). The vehicle exhaust (gasoline exhaust and diesel exhaust) was found to be contributed most to atmospheric VOCs, with 43.59%, 41.91%, 50.45% and 43.91%, respectively in spring, summer, autumn and winter; while solvent usage contributed least, with 11.10%, 7.13%, 14.00% and 19.87%, respectively. Biogenic emission sources (13.11%) were only identified in summer. However, both vehicle exhaust and solvent usage were identified to be the key sources considering contributions to the OFP and SOAFP. Besides, the contributions of combustion during heating period and gasoline evaporation source during warm seasons to OFP and SOAFP should not be overlooked.     

地下水潜在污染源危害性评价方法研究

地下水污染源危害性评价对地下水资源保护及地下水污染防控区划具有重要意义,然而现有区域尺度地下水污染源荷载危害性评价弱化了点源污染复合强度对地下水的影响.因此,为更准确地进行区域地下水潜在污染源危害性评价,引入污染复合强度要素.选取工业源、农业源、生活源、地表排污河、垃圾场和加油站为研究对象,构建以污染源种类、污染物排放量、污染源释放可能性、缓冲区半径和污染复合强度为指标的综合评价模型,采用层次分析法确定各类污染源权重,基于ArcGIS 10.2软件对沧州市进行地下水综合潜在污染源荷载危害性评价.结果表明:Ⅳ、Ⅴ级风险区面积为5 560.0 km2,占总面积的41.6%,主要位于沧州市中部、北部地区,其危害性受工业源影响最大;Ⅰ、Ⅱ级风险区面积为3 303.4 km2,占总面积的25.2%,主要位于沧州市东部地区.研究显示,该评价方法强化了点源污染复合强度对地下水危害性的影响,可为区域地下水潜在污染源危害性评价提供参考,对地下水资源保护及污染防控区划具有重要意义.      

川南自贡市大气颗粒物污染特征及传输路径与潜在源分析

川南自贡市大气颗粒物污染比较严重, 2015～2018年PM_(10)和PM_(2.5)平均浓度分别为(95.42±9.53)μg·m~(-3)和(65.95±6.98)μg·m~(-3),并有明显的下降趋势,冬季PM_(10)和PM_(2.5)浓度远高于其它季节, 1月平均浓度最高,分别为(138.08±52.29)μg·m~(-3)和(108.50±18.05)μg·m~(-3),夏季平均浓度最低.PM_(2.5)与PM_(10)的平均比值为69.12%,冬季比值约为夏季的1.17倍,空气污染以PM_(2.5)为主.采用拉格朗日混合单粒子轨迹模型(HYSPLIT)和全球资料同化系统的GDAS气象数据,对自贡市细颗粒物(PM_(2.5))浓度和逐日72 h后向轨迹进行计算和聚类研究,利用潜在源贡献分析法(PSCF)和浓度权重轨迹分析法(CWT),探讨不同季节影响自贡市PM_(2.5)浓度的潜在源区以及不同源区的污染贡献.结果表明,自贡市近地面四季多受东南风、偏西风和西北风控制,高浓度PM_(2.5)多出现在0～2 m·s~(-1)的低风速区;不同季节、不同输送路径对自贡PM_(2.5)污染影响的差异显著,春季主要受到来自偏西和偏北方向短距离输送气流的影响,夏季污染轨迹主要来自短距离输送的东南气流,秋季主要受来自资阳,经遂宁、重庆和内江的短距离输送气流的影响,冬季除受到资阳、遂宁和内江等周边城市的影响外,还受到来自西藏中部的远距离输送气流影响;除夏季外,自贡市潜在源区主要位于重庆西部与川南交界区域,冬季的主要贡献区范围最广、贡献程度最大,夏季潜在源区范围最小且贡献程度最弱.     

晋城市冬季环境空气中挥发性有机物的污染特征及来源解析

采集晋城市冬季环境空气样品,利用色谱-质谱仪分析了其挥发性有机物(VOCs)的组份特征,运用PMF、特征比值、后向轨迹模型对其来源进行了研究,并计算了臭氧和二次有机气溶胶的生成潜势,探讨了其环境影响.结果表明,观测期间,晋城市VOCs平均浓度为93.35μg·m~(-3),其中烷烃类化合物浓度为52.91μg·m~(-3),在VOCs中占比较高为56.68%;PMF分析VOCs排放源有工业排放源、燃烧源、机动车源、溶剂使用源和植物源,贡献率分别为33.71%、30.27%、26.28%、9.00%和0.74%;特征比值法分析中,苯/甲苯和异戊烷/正戊烷比值分别为1.58±0.68和2.07±0.43,介于道路来源与燃煤源之间,为两者混合来源.后向轨迹聚类3个代表性气团均来自西北方向,分别占比50%、25%和25%,西北方向的工业污染可能会对晋城市VOCs造成影响;观测期间,晋城市空气质量指数、总VOCs浓度和机动车源贡献率在风速较小时(3 m·s-1)分别为143、162.48μg·m~(-3)和46.16%,各数值均高于风速较大(3~6.9 m·s-1)时(60、35.72μg·m~(-3)和16.15%);芳香烃类化合物的臭氧和二次有机气溶胶生成潜势分别为98.89μg·m~(-3)和1.21μg·m~(-3),占总生成潜势的37.28%和97.01%,是两种生成潜势最高的VOCs化合物种类.因此,控制工业、机动车和燃烧排放是控制晋城市环境空气中VOCs污染的主要途径.