Polycyclic aromatic hydrocarbons in surface sediments from drinking water sources of Taihu Lake, China: sources, partitioning and toxicological risk

Sources, partitioning and toxicological risk of 15 priority polycyclic aromatic hydrocarbons (PAHs) in surface sediments from drinking water sources of Taihu Lake, with an area of 2428 km(2) located in the most developed and populated area of China, were studied, and the results were compared with those in other lakes of China and the USA. Concentrations of the 15 PAHs in sediments ranged from 436.6 to 1334.9 ng g(-1) (dw). Gasoline combustion, coal combustion, diesel combustion from shipping and spillage of petroleum were apportioned to be the main sources of PAHs in this area by principal component analysis, which contributed 35.19%, 26.43%, 25.41% and 12.97% to the PAH sources estimated by further multiple linear regression. Levels of PAHs in sediments were negatively correlated with contents of clay and fine silt (<16 μm), while positively with contents of medium silt, coarse silt and sand (>16 μm). Humin with size larger than 16 μm contained the largest part of the burden of PAHs in sediments, but the specific partitioning domain (bound humic acid, lipid or insoluble residue) depended on properties of organic matter reflected by optical absorbance at 465 and 665 nm. Total toxic benzo[a]pyrene equivalent (TEQ(carc)) of the carcinogenic PAHs in sediments varied from 31.8 to 209.3 ngTEQ(carc) g(-1). Benzo[a]pyrene and dibenzo[a,h]anthracene contributed 45.36 and 25.31% to total TEQ(carc), posing high toxicological risk to this area.     

集合数值预报系统在上海市空气质量预测预报中的应用研究

介绍了上海市世博环境空气质量集合数值预报系统的框架,分析了各模式在上海市空气质量预报及排放源污染贡献测算中的应用情况,提出开发多种预报手段、实施集合预报是提高城市空气质量预报准确率的发展方向。     

Spatial and seasonal distribution of nitrogen in marsh soils of a typical floodplain wetland in Northeast China

Horizontal and profile distributions of nitrogen in marsh soils in different seasons were studied in a typical site within the Erbaifangzi wetland in Northeast China. Results showed that there was higher spatial heterogeneity for nitrate nitrogen (NO₃^--_{3}^{-}-N) and ammonium nitrogen (NH₄⁺_{4}^{+}–N), as well as available nitrogen (AN), in surface soils in July compared to that in September. Relative to July, the mean nitrogen contents in surface soils were slightly higher in September; however, in November, soils contained significantly lower NO₃^--_{3}^{-}-N and NH₄⁺_{4}^{+}–N, higher AN, organic nitrogen (Org-N), and total nitrogen (TN). Except for mineral nitrogen, no significant differences were observed between Org-N and TN contents in September and November. Nitrogen contents generally declined exponentially with depth along soil profiles in three sampling dates (July, September, and November), except for a significant accumulation peak of NO₃^--_{3}^{-}-N at the 20–30 cm depth in September. However, NH₄⁺_{4}^{+}–N contents showed a vertical alternation of “increasing and decreasing” in both July and September, while nearly kept constant with depth in November. The depth ranking of nitrogen showed the shallowest distribution for AN, followed by Org-N and TN, while deeper distributions for NO₃^--_{3}^{-}-N and NH₄⁺_{4}^{+}–N. TN, Org-N, and AN were significantly correlated with soil organic matter and total phosphorus. Soil pH values were significantly correlated with TN and AN contents in surface soils. Clay contents showed significant correlations with nitrogen contents except for NO₃^--_{3}^{-}-N in surface soils and NH₄⁺_{4}^{+}–N in profile soils. However, soil moisture was not significantly correlated with nitrogen contents among all soil samples.     

废气样品中甲烷的保存条件研究

气相色谱法检测废气中甲烷,样品保存容器可选择玻璃注射器、惰性气袋、真空瓶、苏码罐等,实验室对此做了比较研究。结果表明:玻璃注射器气密性较差,样品须在8 h内完成分析;真空瓶携带不方便,苏码罐价格昂贵,两者使用较少;使用玻璃注射器采集,然后注入惰性气袋保存的方法最佳,样品至少可稳定保存7d。     

常州市臭氧污染传输路径和潜在源区

利用NCEP全球再分析资料和HYSPLIT4模式,计算了2013—2015年常州市臭氧(O_3)超标日的气流后向轨迹。结合聚类分析方法和常州市PM2.5、PM10、SO2、NO2、O_3数据,分析了O_3超标日不同类型气团来源对各污染物浓度的影响,并利用引入权重因子后的潜在污染源贡献函数分析了影响常州市O_3超标的潜在污染源区分布特征。结果表明:常州市O_3超标期间易受到东南和西南方向气流影响,其中从东海和黄海途经浙江东北部、上海、江苏南部等地的东南气流占比达50%以上。自内陆途经黄山-湖州-宜兴到常州的气流对应的O_3平均质量浓度最高,为116μg/m3。自山东经枣庄-宿迁-淮安-泰州-苏州-无锡到常州的气流对应的O_3平均质量浓度最低,为78μg/m3,但该气流对应的SO2和NO2平均值为各聚类中的最高。影响常州市O_3的潜在污染源区主要在常州周边200 km以内的区域,且集中在从南京至上海的长江下游沿线区域和杭州湾区域;其中太湖湖区为重点污染源源区之一。O_3超标日影响常州NO2的潜在污染源区主要集中在江苏南部、浙江东北部和上海3个区域,太湖周边的常州、无锡、苏州和湖州等几个临近城市为潜在的重点污染源区。与影响常州O_3的WPSCF高值区相比,影响NO2的高值区分布范围更大、距离更远。影响常州O_3的潜在污染源区分布,与长江三角洲地区人为源大气污染物的高排放区域较为一致,说明长江三角洲地区的O_3污染与本区域的人为源大气污染物排放有着极为密切的关联。     

高效率颗粒物微物理模型简介与重污染过程应用分析

中国细颗粒物(PM2.5)导致的空气污染和雾霾天气问题越来越突出,在低层对流层中很多地方都有显著的二次颗粒物生成过程,因此对颗粒物物理化学转化过程的研究具有重要意义,其转化过程对空气质量模式模拟和预报的准确性有重要影响。高效率颗粒物微物理(APM)模型经过近20多年的研究和发展,在全球化学传输模型(GEOS-Chem)、区域性气象和化学预报模型(WRF-Chem)通用地球系统模型(CESM-CAM5)等气象及环境空气质量预报模型中取得了很好的应用验证,能够在全球/区域等不同尺度对粒子生成、长大、凝聚、消除等微物理过程以及气溶胶光学厚度(AOD)、直接/间接辐射强迫等进行模拟。应用GEOS-Chem-APM模式模拟了2014年2月京津冀区域的重污染过程。结果显示,湿度模拟的准确性对其他物理和污染物浓度等模拟结果有重要作用;2月20—26日的重污染过程模拟结果与实际观测较为吻合,主要污染特点是较高的湿度(90%以上),同时,二次颗粒物和包裹了二次物种的一次颗粒物(黑碳/有机碳)是低能见度的最大贡献者。     

乌鲁木齐河地表水化学组成及时空分布特征

乌鲁木齐河作为乌鲁木齐市的主要水源地,在生态保护和城市供水中均具有重要的战略意义。为了研究乌鲁木齐河水化学特征及水环境质量,于2016年4—10月逐月对乌鲁木齐河6个采样断面进行地表水样采集,获取水样41个,对主要离子(K~+、Na~+、Ca~(2+)、Mg~(2+)、Cl~-、HCO_3~-、SO_4~(2-))浓度及pH、DO、TDS、CODMn、TN、TP、NH3-N进行监测分析,探讨了水化学组成的时空差异及影响因素,研究了乌鲁木齐河的水环境质量状况。结果显示,乌鲁木齐河水域年离子总量平均值为213.27 mg/L,属弱矿化度水,年离子总量在空间上表现出沿主河道由南向北逐步增加的趋势。主要阴离子为HCO_3~-和SO_4~(2-),主要阳离子为Ca~(2+),水质类型为Ca~(2+)-HCO_3~--SO_4~(2-)型。2016年河水年内不同时期TDS平均浓度排序为:9月10月4月5月6月8月7月。对水化学离子含量基于时间序列分析,结果显示除Ca~(2+)、HCO_3~-外,其他离子含量在各月份间均存在显著差异。SO_4~(2-)浓度在年内变化最为明显,呈现先减少后增加的趋势。对主要离子含量基于空间序列进行分析,结果显示,仅Na+含量存在显著差异。现阶段乌鲁木齐河的水环境质量为轻度污染。     

春季广州城区空气中VOCs来源解析

2013年4月在广州市区对大气中挥发性有机化合物(VOCs)进行了观测,对其变化特征和来源进行了分析。结果表明,观测期间测得的VOC总平均混合比为41.35×10~(-9),表现为烷烃芳香烃烯烃炔烃;利用PMF解析出观测时段内影响广州市区的9个VOCs主要来源,各源占比情况依次为:LPG排放老化VOC汽油挥发石化、未知源汽油车排放油漆溶剂柴油车排放天然源;与机动车相关和工业相关的来源分别占到了大气VOCs的46.8%和21.0%。     

江苏沿江某化工园区有机污染调查与研究

选择沿江某典型化工园区进行有机污染调查分析,分析污染排放特征及其对长江水质影响.为了解工业园区环境污染状况、从源头控制有机毒物等提供科学依据.     

2008年1月广州颗粒物数浓度污染特征

于2008年1月利用颗粒物计数器(CPC)、颗粒物在线观测仪(TEOM1400a)、自动气象站以及现时天气现象传感器(PWV22)获得了大气颗粒物中每分钟颗粒物数浓度、每30分钟PM2.5>浓度、风速、相对湿度、降雨量等气象因子以及大气能见度.结果发现,1月份能见度低于10km的天数达到25天,其中灰霾天气有17天.灰霾天气下,颗粒物敖浓度为22032±4731个/立方厘米,PM2.5,浓度为123.1±64.5 μg/m3.非灰霾和灰霾天气下颗粒物数浓度日变化趋势总体比较接近,但在13:00～16:00时段,非灰霾天气条件下颗粒物数浓度变化比较明显,而灰霾天气条件下颗粒物数浓度变化比较平缓.现测期内颗粒物教浓度与大气能见度、相对湿度、风速呈负相关,与PM2.5质量浓度、温度呈正相关.灰霾天气下颗粒物数浓度与PM2.5浓度、相对湿度的相关性系数绝对值明显高于非灰霾天气下颗粒物数浓度与这两者的相关性系数绝对值.