典型地区农用地污染调查及风险管控标准探讨

针对《土壤污染风险管控标准——农用地土壤污染风险管控标准》(GB 15618—2018),提出以土壤中全量浓度筛选值和管控值作为衡量农用地土壤污染风险管控的标准,对湖南省部分稻田农用地土壤及点对点稻米样品中镉、铅、砷、汞的总量和有效态浓度及稻米中含量进行监测,根据重金属总量浓度分为低风险、中风险、高风险3组。结果显示:(1)土壤及稻米中镉含量基本为随着风险级别的升高而增加,铅、砷在土壤和稻米中含量无规律性结果,汞监测结果均为未检出。(2)低风险组稻米镉超标率为12. 0%,高风险组稻米镉达标率为33. 3%,表明利用总量浓度对农用地土壤潜在风险进行分组存在一定的局限性。(3)依据4种重金属在土壤中总量及稻米(早稻)中含量情况,对风险级别进行调整并综合判断:有58个样品为低风险组,占样品总数的68. 2%,超标率为零;有15个样品为中风险组,占样品总数的17. 7%,超标率为80. 0%;有12个样品为高风险组,占样品总数的14. 1%,超标率为100. 0%。调整后评价结果与上述标准的划分目标更接近,能够提高上述标准的准确性和实用性。     

中国土壤环境监测方法现状、问题及建议

综述了目前中国现行的土壤环境监测国家标准方法和环保、农业、林业等行业标准方法,指出国家标准和环保行业标准方法侧重于土壤污染物的检测,而农业和林业标准方法侧重于土壤营养元素及其有效态、理化指标的检测。针对现行标准方法存在的一些问题(如检测的土壤污染物种类少、部分方法先进性不足、土壤环境监测的基础研究薄弱以及方法的标准化尚待完善等),提出加强土壤监测标准方法的顶层设计、合理增加土壤污染物的控制种类,及时更新方法、发展多组分测定方法,加强标准方法研究的系统性、协调性,以及逐步增加原位监测标准方法等建议,为土壤监测技术的发展提供借鉴和参考。     

皂素和柠檬酸复合淋洗土壤中的钍

采用振荡淋洗和土柱动态淋洗实验研究了皂素和柠檬酸复合对土壤中钍的淋洗性能。实验结果表明:将质量浓度为20 g/L的皂素与浓度为20 mmol/L的柠檬酸以体积比1∶10配制复合淋洗液对污染土壤中钍的去除效果最佳,淋洗3.0 h,钍去除率为84.98%;准一级动力学方程能更好地描述复合淋洗液对钍的淋洗动力学特征;动态淋洗实验中当复合淋洗液用量为1 600 mL时,钍的累积去除量为73.66 mg/kg;淋洗后土壤中钍的酸可提取态、氧化结合态和有机结合态含量分别减少了79.63%、38.13%和20.34%,残渣态含量变化不大;淋洗后土壤中钍的稳定性增加。     

加速溶剂同时萃取和净化-气相色谱-三重四极杆串联质谱测定土壤和沉积物中8种多溴联苯醚

建立了土壤和沉积物中8种多溴联苯醚(PBDEs,BDE-28、BDE-47、BDE-99、BDE-100、BDE-153、BDE-154、BDE-183和BDE-209)加速溶剂同时萃取和净化-气相色谱-三重四极杆串联质谱(ASE-GC-MS-MS)的分析方法。通过优化加速溶剂萃取与弗罗里硅土在线净化和串联质谱多反应监测模式的条件,较好地去除基质干扰,并提高了三重四极杆串联质谱定性的准确性及定量的灵敏性。该方法采用改进的色谱柱能同时分析包括高溴代联苯醚BDE-209在内的8种PBDEs,其浓度范围为1～100 ng/mL(BDE-209为10～1 000 ng/mL),线性良好,线性回归系数均大于0.997。方法检出限为0.004～0.1 ng/g,方法回收率为75%～110%,方法精密度为2.4%～15.6%。适于批量处理土壤和沉积物中含有多组分痕量PBDEs的样品。     

郑州市土壤与绿色植物中汞的分布特征

汞污染具有生物积累性,因而得到社会广泛关注。研究监测和评估了郑州市城区土壤和绿色植物叶片中汞浓度、分布、污染水平等。研究发现郑州市主城区土壤总汞浓度为0. 150～0. 958 mg/kg,平均浓度为0. 448 mg/kg;郑州市主城区绿色植物叶片总汞浓度为0. 017～0. 249 mg/kg,平均浓度为0. 107 mg/kg;土壤和叶片中汞浓度按功能区排序为交通枢纽区工业区商业区行政区高教区住宅区。采用地累积指数法对郑州市80个土壤样品的汞污染水平进行评估,结果显示60%受到轻度污染,35%受到偏中度污染,5%受到中度污染。研究较为全面地分析了土壤汞污染的现状及浓度,为郑州市土壤汞污染防治提供参考。     

An integrated approach for assessing the migration behavior of chlorpyrifos and carbaryl in the unsaturated soil zone

Chlorpyrifos (O, O-diethyl O-3,5,6-trichloropyridin-2-yl phosphorothioate) and carbaryl (1-naphthyl methylcarbamate) are often applied concurrently as insecticides in food production. The aim of this study was to research their migration behavior in a real environment. We researched the leaching of both pesticides by setting up field lysimeters on a farm with the typical soil used in fruit production today. In order to analyze the variables involved in this process, we performed complementary adsorption studies, we performed complementary adsorption studies using batches and undisturbed soil laboratory columns for both compounds. The results for pesticide transport through the lysimeters showed that less than 1% of chlorpyrifos was recovered in the leachates, while almost 17% was recovered for carbaryl. Having completed the experiment in undisturbed laboratory columns, soil analysis showed that chlorpyrifos mainly remained in the first 5 cm, while carbaryl moved down to the lower sections. These results can be explained in view of the sorption coefficient values (K_D) obtained in horizons A and B for chlorpyrifos (393 and 184 L kg^?1) and carbaryl (3.1 and 4.2 L kg^?1), respectively. By integrating the results obtained in the different approaches, we were able to characterize the percolation modes of these pesticides in the soil matrix, thus contributing to the sustainable use of resources.     

三峡库区水土流失特点及其环境危害防治措施探讨

水土流失是三峡库区主要环境问题之一,也是库区产生大量泥沙的根本因素,更是造成库区人民生活贫困的根源。本文就三峡库区水土流失的特点及其环境危害作了分析,提出了相应的防治措施,为水土流失防治工程提供科学依据。     

基于GIS的南京市典型蔬菜基地土壤重金属污染现状与评价

对南京市八卦洲蔬菜基地土壤中的铅、铬、铜和镉进行测定分析,利用不同的评价标准来评价其环境质量状况,同时借助GIS软件研究了污染指数的空间分布状况,并解析了其重金属污染的来源.结果表明,以自然背景值为评价标准,则蔬菜地土壤中的重金属都超过污染指标,其中镉为首要污染因子;以国标二级为评价标准,则除镉以外的三种重金属的单项污染指数值全都小于1,但其综合污染指数迭1.50,总体上属轻污染状况.南京化工因区、南京长江二桥和各种农业生产活动等可能是主要污染源.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability