Heavy metals distribution and risk assessment in soils affected by tannery effluents

Effluents collected from tanneries in Sialkot showed considerably higher levels of heavy metals. Sodium (12 660.91 mg/L) among macronutrients and Cr (592.20 mg/L) among heavy metals were found in the highest concentrations. Effluent parameters, i.e. biological oxygen demand (BOD; 12.40), chemical oxygen demand (COD; 16.53), Cd (5.90), Cr (592.20) and Fe (18.59) were the respective times higher than Pakistan National Environmental Quality Standards and their continuous unchecked discharge into agricultural soils poses a potential risk. Mean concentrations (mg/L) of Cr (592.20), Ni (2.66), Mn (1.16), Fe (37.17), Zn (0.90), Cd (0.59) and Pb (1.18) in this study exceeded levels recorded to date from different tanning hubs in Pakistan. Factor analysis/principal components analysis (FA/PCA) for the effluent parameters resulted in six varimax factors, i.e. VF1 (salinity, electrical conductivity, total dissolved solids, chloride, phosphate, BOD and COD; including characteristic tannery effluent features), VF2 (pH, Cr and alkalinity; tanning operations), VF3 (Cd and Pb; dyeing processes), VF4 (Mn and Fe; finishing operations), VF5 (Ni; retaining processes) and VF6 (hardness, Ca and Cu; bating processes). Cluster analysis performed on metal data resulted in three clusters confirming metal–metal relations obtained either from FA/PCA or a correlation matrix. The results of this study are useful for heavy metal source apportionment, assessment of risk to peripheral soils and the future management of environments around tanneries.     

城市化对北京霾日数影响统计分析

近年来,随着超大城市/城市群大气灰霾等复合污染加剧,引起人们对区域生态环境与及公共健康问题越来越多的关注。应用北京地区1980—2012年气候资料及同期城市发展统计指标,统计分析了城、郊区间霾日数的变化特征,并在此基础上探讨了北京城市化及局地气候差异对霾日数的影响。分析表明：北京城区霾日数要明显多于郊区,在2007年以前城、郊区站点均有相似的波动增长趋势,但城区站霾日数增加速率（约21 d/10 a）要远大于郊区站（约7.2 d/10 a）;北京各地霾日数与主要城市发展指数之间的相关系数均超过0.001显著性水平,随着城市化而迅速增加的能源消耗和机动车尾气排放是导致北京地区灰霾天气逐渐增多的主要污染源,污染源的不均匀分布是导致城、郊霾日数差异的主要因素。分析还发现,城市化导致的区域气候差异对局地灰霾亦有较明显的影响。伴随着城市化的快速发展,城、郊区气候差异逐渐变大,城市下垫面粗糙度增加导致近地面层风速减小。大城市热岛效应背景下,更容易出现较厚的逆温层,这将阻碍空气垂直方向的对流输送。此外,城区气温持续上升,相对湿度下降,平均风速减小,小风频率增加,也会阻碍空气的水平流通,使得城市排放颗粒污染物的扩散难以扩散,有利于霾日增加。这表明北京地区城市气候效应对区域生态环境具有不可忽视的影响。     

北京大气颗粒物碳质组分粒径分布的季节变化特征

为了解有机碳(OC)和元素碳(EC)在北京大气颗粒物中的季节变化、粒径分布和来源,于2010年3月—2011年2月采用惯性撞击分级采样器采集大气颗粒物样品,热光碳分析仪测定其中有机碳和元素碳质量浓度.结果表明,OC在粗细粒子中含量相当,EC主要存在于细粒子中,在<2.1μm颗粒物中分别占(52±11)%和(70±22)%.OC存在明显的季节变化,冬、夏季高于春、秋季,而EC则表现为冬、秋季大于春、夏季.OC和EC粒径分布呈"双峰型",细粒子段峰值分别位于0.43—1.1μm和0.43—0.65μm,粗粒子段峰值均位于4.7—5.8μm.四季峰值对应的粒径段、峰宽和峰高存在差异.OC与EC粒径分布和相关性的季节变化表明,冬季OC与EC的主要来源为燃煤排放,夏季EC的主要来源为机动车尾气.     

大型钢铁厂及其周边土壤多环芳烃污染现状调查、评价与源解析

采用气相色谱-质谱联机方法(GC-MS)分析了东北某钢铁厂及周边居住区、风景区共11个采样点表层土壤样品16种多环芳烃(PAHs),结果表明,钢铁工业区16种PAHs(∑PAHs)浓度范围为3.39×103—1.54×105ng·g-1,平均浓度3.21×104ng·g-1;居住区∑PAHs浓度范围为587—6.70×103ng·g-1,平均浓度3.82×103ng·g-1;风景区千山∑PAHs浓度385 ng·g-1.∑PAHs和Bap浓度均呈工业区>居住区>风景区趋势.与国内外其他研究结果相比,该钢铁工业区及其周边居住区土壤PAHs污染相对较为严重,11个采样点中有9个采样点土壤∑PAHs为严重污染,4个采样点苯并(a)芘(Bap)浓度超过加拿大土壤质量基准.利用特征比值法(Diagnostic Rate)和主成分分析法(Principal component analysis,PCA)对钢铁工业区及其周边地区土壤进行了源解析,结果表明,钢铁工业区土壤中PAHs主要来源于焦炉、燃煤、柴油燃烧等污染源,周边地区土壤除受工业污染源排放影响外,机动车汽油、柴油污染排放也有重要影响.     

A modeling system for drinking water sources and its application to Jiangdong Reservoir in Xiamen city

Drinking water sources are highly valued by authorities for safeguarding the life of a city. Models are widely applied as important and effective tools in the management of water sources. However, it is difficult to apply models in water source management because water managers are often not equipped with the professional knowledge and operational skills necessary for making use of the models. This paper introduces a drinking water source simulation and prediction system that consists of a watershed model, a hydrological model and a water quality model. This system provides methods and technical guidance for the conventional management of water sources and emergency water event response. In this study, the sub-models of the system were developed based on the data of the Jiangdong Reservoir in Xiamen, and the model validation was based on local monitoring data. The hydrological model and water quality model were integrated by computer programming, and the watershed model was indirectly integrated into the system through a network platform. Furthermore, three applications for Jiangdong Reservoir water protection utilizing the system were introduced in this paper, including a conventional simulation, an emergency simulation, and an emergency measures evaluation.     

苏南快速城镇化区域典型河道入河污染物调查分析与估算

针对快速城镇化区域产业快速发展、人口高度密集与排水设施建设滞后间的突出矛盾,以苏州官渎里区域的典型重污染河道——官渎花园内河为研究对象,在分析区域排污特征的基础上,系统总结点污染源、面污染源和内污染源在该类区域的具体表现形式和影响因素,对各类污染物入河量进行调查测算.根据测算结果,官渎花园内河的CODcr、NH3-N、TN和TP年入河量分别为222.54、11.16、16.63和2.56t·a-1.对各污染源贡献率的分析结果表明,工业污染和生活污染为主要污染源,其次为降雨径流污染.在上述测算分析的基础上,结合苏南快速城镇化区域发展特点,提出了若干河道污染控制的对策与建议.     

珠海2019年秋季一次大气污染过程的特征、 成因及来源分析

2019年秋季在珠三角典型沿海城市珠海观测到一次中重度污染过程,本文对此次过程的污染特征、形成机制和来源进行了研究.通过 采集PM_2.5样品,分析了9种水溶性无机离子（WSIIs）、有机碳（OC）、元素碳（EC）和水溶性有机碳（WSOC）等化学组分的浓度水平和污染特征;进一步结合污染过程中的不利天气形势、72 h后向气流轨迹及PM_2.5的潜在源贡献因子（WPSCF）和浓度权重轨迹（WCWT）等方法分析了污染的形成机制和来源.结果表明,有机物（OM）是污染时期PM_2.5中增长最快的组分,其次是占WSIIs约82.46%的SO₄^2-、NO₃^-和NH₄⁺（SNA）. NO₃^-/SO₄^2-均值为0.20,表明珠海以固定源污染为主;硫氧化率（SOR）均值为0.65,氮氧化率（NOR）均值为0.08,高温高湿的气象条件可能是 造成珠海比中国其他城市SOR偏高而NOR偏低的原因.在污染时段,二次有机碳（SOC）明显增加,WSOC/SOC随污染物的升高而降低并趋近于1,因此, 污染时期的WSOC可能主要是二次生成的.副高控制型、台风外围型和高压出海型等天气形势控制着整个珠三角地区时,不利于污染物的传输和扩散,使污染加剧.后向气流轨迹分析表明,污染时期的气团轨迹主要来自于高污染的内陆地区,这可能是造成此次污染形成的重要原因和来源.WPSCF和WCWT的高值区主要集中在江西、广东等内陆地区,因此,珠海在控制本地排放的同时,也应该关注上风向临近省市的污染排放.     

Inverse uncertainty characteristics of pollution source identification for river chemical spill incidents by stochastic analysis

Identifying source information after river chemical spill occurrences is critical for emergency responses. However, the inverse uncertainty characteristics of this kind of pollution source inversion problem have not yet been clearly elucidated. To fill this gap, stochastic analysis approaches, including a regional sensitivity analysis method, identifiability plot and perturbation methods, were employed to conduct an empirical investigation on generic inverse uncertainty characteristics under a well-accepted uncertainty analysis framework. Case studies based on field tracer experiments and synthetic numerical tracer experiments revealed several new rules. For example, the release load can be most easily inverted, and the source location is responsible for the largest uncertainty among the source parameters. The diffusion and convection processes are more sensitive than the dilution and pollutant attenuation processes to the optimization of objective functions in terms of structural uncertainty. The differences among the different objective functions are smaller for instantaneous release than for continuous release cases. Small monitoring errors affect the inversion results only slightly, which can be ignored in practice. Interestingly, the estimated values of the release location and time negatively deviate from the real values, and the extent is positively correlated with the relative size of the mixing zone to the objective river reach. These new findings improve decision making in emergency responses to sudden water pollution and guide the monitoring network design.

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氟离子慢性暴露对中国林蛙蝌蚪生长发育的毒性效应研究

氟元素以不同的结合形式广泛存在于自然界中,适量氟的摄取有益于龋齿预防和骨骼发育,然而过量氟的摄取会对动物及人体健康造成危害。近年来,大量的人类活动导致水环境中氟含量持续升高。为探究水域氟污染对中国林蛙的毒性影响,本研究以中国林蛙(Rana chensinensis)胚胎为试验材料,对卵黄栓期(G12期)胚胎进行了0、0.7、4.2、19.4、42.8 mg·L~(-1)F-慢性水体暴露直至胚胎发育到变态高峰期(G42期)的研究。分别于暴露25 d和40 d后取样测定了蝌蚪全长、体长、体重和发育分期;此外,分析了F-慢性暴露对变态率、G42期蝌蚪的全长、体长、体重和后肢长以及G42期蝌蚪骨骼发育的影响。结果表明:暴露25 d时,4.2 mg·L~(-1)F-处理组促进了林蛙蝌蚪的生长发育,而42.8 mg·L~(-1)F-处理组显著抑制了蝌蚪的生长发育;暴露40 d时,19.4 mg·L~(-1)F-和42.8 mg·L~(-1)F-处理组蝌蚪的生长发育均受到显著抑制。持续进行慢性暴露78 d后,4.2 mg·L~(-1)F-处理组蝌蚪的变态率显著升高,而42.8 mg·L~(-1)F-处理组蝌蚪的变态率受到了显著抑制。此外,42.8 mg·L~(-1)F-处理组G42期蝌蚪形态指标(全长、体长和后肢长)以及骨骼发育均受到抑制。依据G42期中国林蛙蝌蚪的生长发育指标和变态率为观察指标,氟离子慢性暴露对中国林蛙蝌蚪的最低可观察效应浓度(LOEC)为0.7 mg·L~(-1)。研究表明,水环境中高浓度的氟污染会对中国林蛙蝌蚪的生长发育、变态和骨骼发育等造成潜在的不利影响,水体氟污染的生态毒性效应理应引起高度重视。     

基于SWAT模型的流域面源污染模拟影响分析

针对流域面源污染模型往往忽略或简化河道内污染物变化过程的缺陷,探讨了河道水质模型对流域面源污染模拟的影响.以太湖流域浙西区的西苕溪流域为研究对象,选取具有一定物理机制的分布式面源污染模型SWAT模型,分别以激活和不激活其嵌套的河道水质模型QUAL2E,即SWAT模型与QUAL2E模型紧密耦合和松散耦合两种情况进行模拟,并比较了对TN及TP的模拟效果.结果表明,丰水期与平水期的模拟结果并没有显著差别;但在枯水期,由于水量较小,河道内污染物变化过程对模拟结果影响较大.同时引入QUAL2K模型,分析认为改进河道水质模型对提高SWAT模型模拟精度有一定的效果.