生物可利用性及其在重金属污染生态风险评价中的作用

通过化学方法可以确定重金属污染的生物可利用性,常用的化学方法主要有化学试剂提取法、酸挥发性硫化物方法、毒性特征浸取过程方法、薄层梯度扩散方法、同住素稀释技术。由形态分析结果得到生物可利用浓度或者剂量可以进行定量生态风险评价;通过生物可利用浓度或剂量与毒性参数的比值分析可以进行定性风险评价。     

辽宁省朝阳市城市污水BOD与COD关系的探讨

从BOD与COD的构成及降解动力学出发,探讨了BOD与COD的相关关系,得到了BOD5与COD的相关模型,应用朝阳市城市污水的实测数据和数理统计模型进行了检验。     

化工生产中环境风险及对策研究

根据当前我国化工生产发展和环境风险管理现状,探讨了我国化工生产中环境风险的类型及发生原因,从加强合理布局、修订和完善各类污染物排放标准、强化行业管理、污染物排放总量控制、改进环境影响评价体系及方法和革新环境风险防范管理机制等方面提出了相应的对策建议。     

前处理方法对测汞结果影响分析

本文通过测定三种前处理方法消解后水样中汞的浓度,分析了前处理方法对测定结果的影响,以及三种前处理方法的适用条件。     

河湖底泥修复技术的研究进展

本文综述污染底泥的修复技术,探讨其发展状况及存在的问题。指出物理修复见效快,但成本高;化学修复成本较低但易造成二次污染;生物修复投入低,处理量大,但处理效率低,。将这三类技术联合使用,取长补短,具有较广阔的发展前景。     

宁波和温州地区夏季大气中不同粒径颗粒物特征分析

对宁波地区北仑和奉化站、温州地区乐清站3个监测点夏季TSP、PM10、PM2.5和PM1.0进行监测,测试分析各种粒径颗粒物浓度水平和粒径分布特征,并通过化学质量平衡(CMB)受体模型对颗粒物进行源解析。监测结果显示,夏季宁波、温州地区TSP和PM10日均浓度为0.049～0.134mg/m3和0.025～0.084mg/m3,均未超过我国环境空气质量二级标准;PM2.5日均浓度为0.007～0.069mg/m3,按美国2006年EPA最新标准限值0.035mg/m3衡量,奉化、乐清、北仑站的超标天数占总监测天数的比例分别为75%、40%和37.5%。粒径分布统计结果显示,3个监测站点PM10占TSP的比例为48.78%～86.96%;PM2.5占TSP的比例为33.33%～72.46%;奉化和乐清监测点PM10中PM2.5和PM1.0的比例平均值在50%以上。源解析结果显示,夏季TSP主要来源于土壤尘,其次是建筑尘和煤烟尘,其贡献率分别为40.70%～55.49%、9.62%～13.64%和5.85%～17.28%。     

九龙江北溪pH值异常变化与生化因子相关性的研究

监测结果表明,九龙江北溪部分断面CODMn浓度介于中富营养～富营养之间,总氮、总磷和叶绿素a浓度均达到极富营养水平。经统计分析,pH值与甲藻显著相关(r=0.327,P=0.025),与溶解氧(r=0.762,P=0.000)、高锰酸盐指数(r=0.456,P=0.001)、总氮(r=0.482,P=0.001)、总磷(r=0.507,P=0.000)和叶绿素a(r=0.649,P=0.000)等非常显著相关。研究表明,虽然各项化学因子与pH值密切相关,但不是pH值变化的直接原因,而是由于水体富营养程度严重且已形成了藻类生境,甲藻的异常增殖才导致pH值异常升高。     

What can the trove of CSB incident investigations teach us? A detailed analysis of information characteristics among chemical process incidents investigated by the CSB

Understanding the commonalities among previous chemical process incidents can help mitigate recurring incidents in the chemical process industry and will be useful background knowledge for designers intending to foster inherent safety. The U.S. Chemical Safety and Hazard Investigation Board (CSB) reports provide detailed and vital incident information that can be used to identify possible commonalities. This study aims to develop a systematic approach for extracting data from the CSB reports with the objective of establishing these commonalities. Data were extracted based on three categories: attributed incident causes, scenarios, and consequences. Seventeen causal factors were classified as chemical indicators or process indicators. Twelve chemical indicators are associated with the hazards of the chemicals involved in the incidents, whereas five process indicators account for the hazards presented by process conditions at the time of the incident. Seven scenario factors represent incident sequences, equipment types, operating modes, process units, domino effects, detonation likelihood for explosion incidents, and population densities. Finally, three consequence factors were selected based on types of chemical incidents, casualties, population densities, and economic losses. Data from 87 CSB reports covering 94 incidents were extracted and analyzed according to the proposed approach. Based on these findings, the study proposes guidelines for future collection of information to provide valuable resources for prediction and risk reduction of future incidents.     

Determination of sources of fine particles in different ambient atmospheres in South Korea using a chemical mass balance model

Abstract

To determine the sources of particulate matter less than 2.5?μm (PM_2.5 in different ambient atmospheres (urban, roadside, industrial, and rural sites), the chemical components of PM_2.5 such as ions (Cl^-, NO₃^-, SO₄^2-, NH₄⁺, Na⁺, K⁺, Ca²⁺, and Mg²⁺), carbonaceous species, and elements (Al, As, Ba, Cd, Cu, Fe, Mn, Ni, Pb, Se, V, and Zn) were measured. The average mass concentrations of PM_2.5 at the urban, roadside, industrial, and rural sites were 31.5?±?14.8, 31.6?±?22.3, 31.4?±?16.0, and 25.8?±?12.4?μg/m³, respectively. Except for secondary ammonium sulfate and ammonium nitrate, the model results showed that the traffic source (i.e., the sum of gasoline and diesel vehicle sources) was the most dominant source of PM_2.5 (17.1%) followed by biomass burning (13.8%) at the urban site. The major primary sources of PM_2.5 were consistent with the site characteristics (diesel vehicle source at the roadside site, coal-fired plants at the industrial site, and biomass burning at the rural site). Seasonal data from the urban site suggested that ammonium sulfate and ammonium nitrate were the most dominant sources of PM_2.5 during all seasons. Further, the contribution of road dust source to PM_2.5 increased during spring and fall seasons. We conclude that the determination of the major PM_2.5 sources is useful for establishing efficient control strategies for PM_2.5 in different regions and seasons.