江苏省不锈钢产业集聚区土壤重金属污染评价与分析

随着不锈钢产业的发展,其生产加工过程中产生的含重金属的废水、废气及固体废弃物对周围土壤及地表水环境的影响也日益显现。选择江苏省不锈钢产业集聚区内溱东镇土壤为研究对象,对区域内63个采样点进行分析,发现区域内土壤中Cr、Zn、Cd、Pb质量分数平均值均未超过国家土壤环境质量标准的二级标准要求,重金属污染程度由大到小的顺序为:CdNiCrMnZnPb,并且通过SPSS13.0统计软件对分析数据进行相关性分析,数据表明,土壤中重金属Cr、Fe、Cd、Ni、Mn来自不锈钢产业的可能性较大。     

Determination of total petroleum hydrocarbons (TPH) in agricultural soils near a petrochemical complex in Guangzhou,China

The total petroleum hydrocarbons (TPH) pollution in regional agricultural soils was investigated. Seventy soil samples collected from surface layers (0–20 cm) and horizons of five selected pedons in the vicinity of a petrochemical complex in Guangzhou, China were analyzed, and the vertical variation and spatial variability of TPH were evaluated. The TPH concentration in top soils around the petrochemical complex ranged from 1,179.3 to 6,354.9 mg kg^− 1, with the average of 2,676.6 mg kg^− 1. Furthermore, significant differences between land-use types showed that the TPH concentration in top soils was strongly influenced by accidental spills. Both the TPH trends in pedons and the identified hot-spot areas also showed that the accidental explosions or burning accidents were mainly responsible for the pollution. The results reported here suggest that the regular monitoring and inspection shall be conducted for safety and to avoid or minimize the accidents, and the effective measures should be taken to remediate the contaminated areas and to assure that the important industrialization of Guangzhou area would not mean human health risks near the petrochemical complex.     

Occurrence of organotins in the Yangtze River and the Jialing River in the urban section of Chongqing, China

The occurrence of organotins in the Yangtze River and the Jialing River in the urban section of Chongqing, China and their impact on drinking water waterworks are reported in this study. Water samples were extracted by solid-phase microextraction and measured using a gas chromatograph with mass spectrometer. The results showed that the rivers studied were polluted by both butyltins and phenyltins and that the butyltin species was the dominant pollutant. Butyltins, especially monobutyltin, were detected in all 18 sampling stations, and phenyltins were detected only in 11 sampling stations. Majority of the organotins were MBTs with concentrations varying from 27.3 to 1,145.8 ng Sn L^?1. Diphenyltin and dibutyltin were the second most common with the highest levels of 113.7 and 202.5 ng Sn L^?1, respectively. Monophenyltin, tributyltin, and triphenyltin had the lowest detection rates with concentration levels of 9.7, 161.8, and 37.2 ng Sn L^?1, respectively. Some of the organotins were also detected in drinking water waterworks, which posed a threat to the water quality of Chongqing.     

Development of a multi-criteria index ranking system for urban runoff best management practices (BMPs) selection

Low impact development best management practices (LID-BMPs) are considered to be cost-effective measures for mitigating the water quantity and quality impact of urban runoff. Currently, there are many types of LID-BMPs, and each type has its own intrinsic technical and/or economical characteristics and limitations for implementation. The selection of the most appropriate BMP type(s) for a specific installation site is therefore a very important planning step. In the present study, a multi-criteria selection index system (MCIS) for LID-BMP planning was developed. The selection indexes include 12 first-level indices and 26 second-level indices which reflect the specific installation site characteristics pertaining to site suitability, runoff control performance, and economics of implementation. A mechanism for ranking the BMPs was devised. First, each individual second-level index was assigned a numeric value that was based on site characteristics and information on LID-BMPs. The quantified indices were normalized and then integrated to obtain the score for each of the first-level index. The final evaluation scores of each LID-BMP were then calculated based on the scores for the first-level indices. Finally, the appropriate BMP types for a specific installation site were determined according to the rank of the final evaluation scores. In order to facilitate the application of the MCIS BMP ranking system, the computational process has been coded into a software program, BMPSELEC. A case study demonstrating the MCIS methodology, using an LID-BMP implementation planning at a college campus in Foshan, Guangdong Province, is presented.     

Accuracy and uncertainty assessment on geostatistical simulation of soil salinity in a coastal farmland using auxiliary variable

Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (EC_e 4–8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.     

CMT监测井在黑河流域地下水监测中的应用

以CMT监测井在黑河流域的应用为基础,通过对监测数据和采集的水样进行分析,了解了黑河流域地下水水位动态变化,掌握了黑河流域地下水水化学垂向分布规律,为合理利用黑河流域水资源提供了科学依据。     

Improve Compliance with Limited Resources by a Three-Group Inspection Regime

Frequent monitoring and relatively high fines are usually necessary to bring about improvements in environmental quality, but more challenging for many countries with limited human, material, and financial resources is to put them into practice. This paper developed a three-group model of a state-dependent enforcement in a repeated game to improve the policy implementation under limited inspection capacities. A certain number of firms are grouped (group 1, group 2, group 3) for different supervision intensity (e.g., the order of inspection probability corresponding to each group is p ₁?<?p ₂?<?p ₃) based on their environmental performance. The optimal policy parameters, such as inspection probability of each group and the probability that a firm found in compliance is moved to a better reputation group, were obtained as the basis for regulator’s policy making. Numerical simulations indicated that the three-group inspection regime can significantly increase compliance rate as compared with static enforcement with the same monitoring probability. Among the number of firms in each group under steady state conditions, group 2 had the most, group 1 was the second, and group 3 had the smallest. Analysis and prediction of a three-group reputation example provided a good experiment for the model. The results give a practical reference for the policy makers with inspection capacity constraints to achieve higher compliance rate.