加速溶剂萃取-固相萃取-高效液相色谱/三重四级杆质谱法测定土壤中6种喹诺酮类抗生素残留

为测定污染土壤中的6种低残留喹诺酮类抗生素(氧氟沙星、培氟沙星、恩诺沙星、环丙沙星、诺氟沙星、恶喹酸),全面优化了一种联合加速溶剂萃取(ASE)、固相萃取(SPE)和高效液相色谱/三重四级杆质谱(HPLC/MSMS) 3种检测技术的分析方法。样品采用甲醇和0.1 mol/L EDTA-McIlvaine缓冲液(1∶1)进行加速溶剂萃取,经Bond Elut Plexa型HLB固相萃取小柱富集纯化,土壤中6种喹诺酮类抗生素的基质效应因子控制在0.84～1.04。在0.2～100.0μg/L(以恶喹酸计)质量浓度范围内,目标化合物的线性关系良好(r0.999),6种目标化合物的检出限为0.09～0.75μg/kg,加标回收率为60.9%～89.9%。该方法自动化程度和准确度较高,可极大程度地降低基质效应,提高测定方法的灵敏度,适用于土壤中喹诺酮类抗生素残留的检测。     

高氯酸铁可见分光光度法测定水中叠氮化物研究

基于Fe~(3+)显色技术,建立了测定地表水、地下水、生活污水和工业废水中叠氮化物的高氯酸铁分光光度法。研究结果表明:N_3~-与Fe~(3+)反应生成的棕红色络合物的特征吸收峰为454 nm;氨基磺酸铵可有效掩蔽NO_2~-的干扰,蒸馏能消除色度、CN~-、SCN~-硫化物等对测定的影响;当取样体积为150 mL、蒸馏定容体积为100 mL、使用10 mm比色皿时,方法检出限为0.08 mg/L(以N_3~-计),测定下限为0.32 mg/L;平均回收率为88.0%~104%,相对标准偏差(n=6)为0.3%～5.6%。对实际工业废水样品进行了测定,结果为1.37 mg/L。该方法准确度高、精密度好、操作简单,能够满足水污染物排放标准中叠氮化物的测定要求。     

How does eliminating mercury from artisanal and small-scale gold mining lead to achieving sustainable development goals?

Artisanal and small-scale gold mining (ASGM) is the principal anthropogenic activity that globally contributes to overloading our environment with mercury. Although the Minamata Convention, led by the United Nations, is a crucial instrument to eliminate its use progressively, novel approaches to accelerate this difficult transition are welcome. This article proposes a framework for policy-making or improvement, fostering the enforcement of mercury elimination through the lens of the 17 Sustainable Development Goals (SDGs), focusing on the excluded artisanal and small-scale gold miners and their dependents. We move forward with a literature review of the Artisanal and Small Mining topic, taking each SDG as a unit of analysis. Understanding the problem as a puzzle of four sets of pieces, namely: (1) social, (2) environmental, (3) economic, and (4) institutional, the paper offers potential opportunities for the decision-makers and practitioners to accelerate the substitution of this heavy metal and develop sustainable futures for the ASGM communities. We conclude by proposing a pragmatic framework that synthesizes the means, actions, and ends to accelerate a sustainable transition.     

AI-based runoff simulation based on remote sensing observations: A case study of two river basins in the United States and Canada

Data-driven techniques are used extensively for hydrologic time-series prediction. We created various data-driven models (DDMs) based on machine learning: long short-term memory (LSTM), support vector regression (SVR), extreme learning machines, and an artificial neural network with backpropagation, to define the optimal approach to predicting streamflow time series in the Carson River (California, USA) and Montmorency (Canada) catchments. The moderate resolution imaging spectroradiometer (MODIS) snow-coverage dataset was applied to improve the streamflow estimate. In addition to the DDMs, the conceptual snowmelt runoff model was applied to simulate and forecast daily streamflow. The four main predictor variables, namely snow-coverage (S-C), precipitation (P), maximum temperature (T_max), and minimum temperature (T_min), and their corresponding values for each river basin, were obtained from National Climatic Data Center and National Snow and Ice Data Center to develop the model. The most relevant predictor variable was chosen using the support vector machine-recursive feature elimination feature selection approach. The results show that incorporating the MODIS snow-coverage dataset improves the models' prediction accuracies in the snowmelt-dominated basin. SVR and LSTM exhibited the best performances (root mean square error = 8.63 and 9.80) using monthly and daily snowmelt time series, respectively. In summary, machine learning is a reliable method to forecast runoff as it can be employed in global climate forecasts that require high-volume data processing.     

Spatial analysis of resources and environmental carrying capacity in Iran

Urbanization and mass movement of the population from rural areas and small cities to megacities have led to environmental, economic, and social problems in Iran. In dealing with these challenges, assessing resource and environmental carrying capacity (RECC) is considered an effective method to leverage space and capital to achieve sustainable development. This study aimed to rank the provincial RECC in Iran. Toward this purpose, environmental indices were generated from remotely sensed and statistical census data. Then, the provinces were scored in terms of environmental, economic, and infrastructural carrying capacities, and RECC using the mean variance analysis method. Results demonstrated that in most areas, there is no relationship between economic and infrastructural capacities and development. Statistically, a correlation coefficient of −0.53 between economic and environmental carrying capacities indicated excessive use of environmental capacities. Moreover, the spatial distribution pattern of environmental, economic, and infrastructural carrying capacity was entirely heterogeneous between the provinces; there was a northeast–southwest pattern in terms of infrastructural capacity and an economic pattern from north to south. The distribution pattern of RECC is most consistent with the environmental capacity, pointing at the high weight of the indicators of the RECC model. In conclusion, this research offers a new vision for policymakers and provides a theoretical and applicable framework for implementing sustainable strategies in land-use planning. It is recommended that the RECC concept and tools can be used not only for planning but also for measuring the efficiency of spatial development programs and establishing land balances in the region.     

液液萃取-气相色谱/串联质谱法测定水中五氯酚及其钠盐

采用液液萃取处理水样,用气相色谱-串联质谱法测定样品中五氯酚及其钠盐,通过优化测定条件,使方法在1.00μg/L~500μg/L范围内线性良好。检出限和定量限分别为1.00μg/L和5.00μg/L,空白水样五氯酚钠3个质量浓度水平的加标回收率为89.8%~98.4%,5次平行试验测定结果的RSD为5.5%~10.7%。     

基于环境监测实验室的高校实验室安全准入制度信息系统功能优化研究

梳理了高校实验室环境-安全-健康准入制度包含的管理内容,从人员管理、设备管理、试剂管理、实验环境管理角度进行了分析。根据现有实验室安全信息化系统运行情况,探讨了将实验室安全信息化系统与实验室信息化系统、设备管理信息化系统进行数据融合和功能优化的要点,重点分析了设备采购及管理系统、实验室安全教育与考试系统、实验室安全检查系统、试剂管理平台、实验室门禁管理系统在功能上的内在关联,从而通过试剂管理平台、实验室门禁控制系统、设备采购系统实现实验室环境-安全-健康准入制度的强制执行。研究发现,高校与环境监测实验室、院系实验室安全管理部门联合促进实验室安全信息化系统、实验室信息化系统、设备管理信息化系统的数据共享与功能升级,可以丰富实验室安全准入制度的内涵和管理手段,加强实验室安全准入制度的强制执行力,提高实验室安全管理效率。     

2019年扬州市公共场所健康危害因素监测结果分析

为了提升扬州市公共场所卫生状况和传染病防控能力,按照国家标准于2019年对扬州市宾馆(酒店)类、沐浴类、理发店类、美容店类和候车室类5类公共场所的健康危害因素(空气质量和公共用品用具)进行监测,按照《公共场所卫生指标及限值要求》(GB 37488—2019)进行评价。结果表明,共监测空气质量样品216份,合格率为84.26%,共监测公共用品用具1 414份,合格率为96.46%,不同场所的空气质量合格率和公共用品用具微生物指标合格率差异均具有统计学意义(P 0.05)。不同类型公共用品用具监测项目中,金黄色葡萄球菌的合格率最高(100%),而真菌总数的合格率最低(93.75%)。各类公共用品用具中,拖鞋合格率最低(91.67%),床单相对较高(99.70%)。扬州市公共卫生状况总体良好,在空气质量监测中,物理项目和微生物项目合格率较低,在公共用品用具监测中,细菌总数和大肠菌群存在不合格现象。     

面向管理的海洋修复工程生态绩效考核指标体系构建研究

目前国内关于海洋修复工程的考核研究多为修复工程的生态效果考核,极少包含成本效益考核,以致无法比较和分析不同类型、不同规模的海洋修复工程的生态绩效,不利于海洋修复工程的考核和验收管理。根据当前自然资源部实施“蓝色海湾”等整治修复工程的检查验收管理的新需求,本文构建了基于海洋生态系统健康恢复、生态系统服务价值增长和单位成本生态效益等理论的海洋修复工程生态绩效考核指标体系。此外,本文以温州海域2014—2016年海洋修复的生态绩效的考核为例,结合考核结果以及直接相关性、独立性、可测量性和业务化等指标选取原则,对指标体系进行了改进。结果表明本指标体系可以在海洋修复工程的检查验收中被用于生态绩效考核,管理部门可根据海洋修复工程的类型和管理需求,有选择性地采纳部分或全部指标进行考核。     

贵州喀斯特山区不同种植年限花椒根际土壤细菌群落结构特征研究

以贵州花江峡谷花椒(Zanthoxylum bungeamun)林为研究对象,采用16S rRNA高通量测序技术,分析种植5、10、20、30 a花椒根际土壤细菌群落结构和多样性特征,探讨不同种植年限花椒土壤理化因子对根际细菌群落分布的影响,为喀斯特石漠化地区花椒农业可持续发展提供有效的理论依据。结果表明,随着花椒种植年限的增加,土壤含水率、pH和有效磷逐渐升高,有机质、铵态氮和硝态氮含量先降低后升高(P<0.05)。根际土壤细菌Shannon、Simpson指数总体呈现上升趋势,OTUs、Chao1指数在10a较低。PCo A分析显示,不同种植年限花椒根际细菌群落组成差异显著,并且随着年限的增加,群落结构趋于相似;差异指示种分析表明,5—30a差异指示种分别为Firmicutes(厚壁菌门)、Cyanobacteria(蓝藻菌门)、Planctomycetes(浮霉菌门)、Entotheonellaeota(肠杆菌门)。RDA分析表明,有机质和含水率与细菌群落分布显著相关(P<0.05)。系统发育多样性分析表明,丰富类群多样性与环境因子存在较多的正相关,稀有类群比丰富类群有更强的发育信号。Bug Base预测分析发现:随着年限增加根际土壤好氧细菌增加,厌氧细菌下降,5、10 a氧化胁迫耐受菌低于20、30 a,致病菌在5、10 a高于20、30 a。综上,种植年限影响了花椒根际土壤细菌群落多样性,不同年限根际土壤肥力不同使得土壤细菌选择性生长,随着一定时间发育花椒抗病能力提高。