Simultaneous determination of estrogenic odorant alkylphenols,chlorophenols, and their derivatives in water using online headspace solid phase microextraction coupled with gas chromatography-mass spectrometry

A simple online headspace solid-phase microextraction (HS-SPME) coupled with the gas chromatography-mass spectrometry (GC-MS) method was developed for simultaneous determination of trace amounts of nine estrogenic odorant alkylphenols and chlorophenols and their derivatives in water samples. The extraction conditions of HS-SPME were optimized including fiber selection, extraction temperature, extraction time, and salt concentration. Results showed that divinylbenzene/Carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber was the most appropriate one among the three selected commercial fibers, and the optimal extraction temperature, time, and salt concentration were 70 °C, 30 min, and 0.25 g/mL, respectively. The developed method was validated and showed good linearity (R ²?>?0.989), low limit of detection (LOD, 0.002–0.5 μg/L), and excellent recoveries (76–126 %) with low relative standard deviation (RSD, 0.7–12.9 %). The developed method was finally applied to two surface water samples and some of these target compounds were detected. All these detected compounds were below their odor thresholds, except for 2,4,6-TCAS and 2,4,6-TBAS wherein their concentrations were near their odor thresholds. However, in the two surface water samples, these detected compounds contributed to a certain amount of estrogenicity, which seemed to suggest that more attention should be paid to the issue of estrogenicity rather than to the odor problem.     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Analysis of urban carbon emission efficiency and influencing factors in the Yellow River Basin

Environmental Science and Pollution Research - The Yellow River Basin is an energy-rich area. The low-carbon development of the Yellow River Basin is one of the ways to achieve ecological...     

游泳池中隐孢子虫卵囊替代物的去除

隐孢子虫是常见的球状寄生虫。接触含有隐孢子虫卵囊的水体可致隐孢子虫病,主要的临床表现为腹泻,严重者可致死。游泳池是主要的传播场所。采用容积为5 500 L的游泳池,进行隐孢子虫卵囊替代物的修复模拟实验,研究在游泳池条件下絮凝沙滤技术对直径为4.5μm隐孢子虫卵囊替代物的去除效果。实验结果表明,氯化铝剂量为0.1 mg/L,沙滤料高度为30 cm,内循环流速为11.5 L/min,对隐孢子虫卵囊替代物去除率在90%以上。该技术对浊度具有较好的处理效果,当进水浊度降低且接近于出水浊度时,系统进入稳定运行阶段,对虫卵囊替代物去除率可以达到96%。     

Spatial and seasonal characteristics of river water chemistry in the Taizi River in Northeast China

Anthropogenic activities have led to water quality deterioration in many parts of the world, especially in Northeast China. The current work investigated the spatiotemporal variations of water quality in the Taizi River by multivariate statistical analysis of data from the 67 sampling sites in the mainstream and major tributaries of the river during dry and rainy seasons. One-way analysis of variance indicated that the 20 measured variables (except pH, 5-day biological oxygen demand, permanganate index, and chloride, orthophosphate, and total phosphorus concentrations) showed significant seasonal (p?≤?0.05) and spatial (p?<?0.05) variations among the mainstream and major tributaries of the river. Hierarchical cluster analysis of data from the different seasons classified the mainstream and tributaries of the river into three clusters, namely, less, moderately, and highly polluted clusters. Factor analysis extracted five factors from data in the different seasons, which accounted for the high percentage of the total variance and reflected the integrated characteristics of water chemistry, organic pollution, phosphorous pollution, denitrification effect, and nitrogen pollution. The results indicate that river pollution in Northeast China was mainly from natural and/or anthropogenic sources, e.g., rainfall, domestic wastewater, agricultural runoff, and industrial discharge.     

Seasonal variation and spatial distribution of atmospheric mercury and its gas-particulate partition in the vicinity of a semiconductor manufacturing complex

This study investigated the tempospatial variation of atmospheric mercury and its gas-particulate partition in the vicinity of a semiconductor manufacturing complex, where a plenty of flat-monitor manufacturing plants using elemental mercury as a light-initiating medium to produce backlight fluorescence tubes and may fugitively emit mercury-containing air pollutants to the atmosphere. Atmospheric mercury speciation, concentration, and the partition of total gaseous mercury (TGM) and particulate mercury (Hg_p) were measured at four sites surrounding the semiconductor manufacturing intensive district/complex. One-year field measurement showed that the seasonal averaged concentrations of TGM and Hg_p were in the range of 3.30–6.89 and 0.06–0.14 ng/m³, respectively, whereas the highest 24-h TGM and Hg_p concentrations were 10.33 and 0.26 ng/m³, respectively. Atmospheric mercury apportioned as 92.59–99.01 % TGM and 0.99–7.41 % Hg_p. As a whole, the highest and lowest concentrations of TGM were observed in the winter and summer sampling periods, respectively, whereas the concentration of Hg_p did not vary much seasonally. The highest TGM concentrations were always observed at the downwind sites, indicating that the semiconductor manufacturing complex was a hot spot of mercury emission source, which caused severe atmospheric mercury contamination over the investigation region.     

生态文明制度体系研究——以江苏省为例

生态文明制度体系是由制度构成的一个相互配合、有机联系的整体。本文基于文献统计分析与实地调研咨询,从广义和狭义层面,分别对生态文明制度进行梳理。根据国家生态文明建设需求与省级层面实际情况,本文将广义的生态文明制度体系分为源头保护制度体系、损害赔偿与激励体系、追责考评制度体系和污染治理制度体系四大板块,并针对国家与省级重点生态文明制度,构建生态资源保护制度链与污染防治制度链。同时,对制度地位、制度衔接、相互关系及其优化选择进行分析,以提高环境管理效能,推进生态文明研究纵深发展。     

Assessment of urban sustainability efficiency based on general data envelopment analysis: a case study of two cities in western and eastern China

Sustainable urban development focuses on enhancing urban well-being, while also balancing the demands of urban social and economic development, natural resource consumption, and environmental pollution. This work used general data envelopment analysis to assess the urban sustainability efficiency (USE) and sustainability potential (SP) in Lanzhou and Xiamen, two cities that are characteristic of urban areas in western and eastern China. The assessment indicator system included important natural and urban welfare factors as input and output indices, respectively. The results showed that overall urban sustainability efficiency increased in Lanzhou and Xiamen from 1985 to 2010, but that the sustainability of natural resources clearly decreased. The urban sustainability efficiency of Xiamen was higher than that of Lanzhou, and the sustainability potential of Xiamen was lower than that of Lanzhou; this indicates that Xiamen performed better in terms of urban sustainable development. The urban sustainability efficiency in Xiamen has increased with increasing urban population, and the rate and scale of economic development have been higher than in Lanzhou. The assessment and analysis performed in this study show that cities with different natural resources and development characteristics have different forms, patterns, and trajectories of sustainable development.     

城市生态系统复合下垫面碳通量特征——以上海市奉贤大学城为例

随着城市化进程的加速和城市人口规模的增加,城市已成为最大的碳源,研究城市生态系统对大气二氧化碳的贡献成为碳循环研究的焦点问题之一。基于研究区域内土地利用现状和一年的涡动观测系统观测数据,结合地理信息技术(Arc GIS)和通量计算工具(Eddypro及ART Footprint Tool)以及碳通量足迹模型分析了上海奉贤大学城碳通量足迹特征,基于此探讨不同下垫面类型,包括以草本和木本等透水层为主的下垫面(称为自然系统),以建筑物、道路等不透水层为主的下垫面(称为社会系统)碳通量的变化特征。研究结果表明:1)在不同风向上,碳通量贡献区范围随着大气稳定度的增加而扩大。大气处于稳定条件下,非主风向上的碳通量贡献区范围(最大范围1 100 m)比主风向上的碳通量贡献区范围(最大范围780m)要大;当大气处于不稳定条件下时主风向和非主风向下的碳通量贡献区范围相差不大(最大范围分别为321和351m)。2)不同下垫面其源汇特征不同,以绿色植物为主的自然系统年碳通量均值为–4.1μmol/m~2/s,表现为碳汇;社会系统的年碳通量均值为8.6μmol/m~2/s,表现为碳源。3)自然系统的碳通量日变化具有较明显的季节分异,变化特征大致呈"U"型;社会系统的碳通量日变化没有明显的季节分异,变化特征大致呈"M"型。绿色植物对城市生态系统的大气二氧化碳有降低作用,结合自然和社会系统的碳通量变化特征可以为以后合理规划城市布局,建立低碳城市提供服务。     

三氯卡班对小鼠血浆内源性物质影响的代谢组学研究

三氯卡班被认定为一种新型的环境污染物,可能对动植物和人体产生危害,为探究三氯卡班的有害作用机制,选择C57BL6小鼠作为载体,利用分子生物学和报告基因方法考察了三氯卡班对肝脏的作用,同时利用代谢组学技术考察三氯卡班对血浆内源性代谢物变化的影响。结果表明,三氯卡班是核受体CAR的激活剂,可以提高肝脏CYP2b10的m RNA表达。同时血浆主要的内源性代谢物也产生了显著性变化,血浆中的脂肪酸比例都呈下降趋势,肉毒碱与乙酰肉碱的比例都呈上升趋势,花生四烯酸与肌酸的比例都呈上升趋势,这都与核受体CAR被激活密切相关,由此说明利用代谢组学技术能够全面地反映三氯卡班所造成的对机体的影响。