Harmonized assessment of nutrient pollution from urban systems including losses from sewer exfiltration: a case study in Germany

Environmental Science and Pollution Research - A growing literature indicates that untreated wastewater from leaky sewers stands among major sources of pollution to water resources of urban...     

Using a social learning configuration to increase Vietnamese smallholder farmers’ adaptive capacity to respond to climate change

Social learning is crucial for local smallholder farmers in developing countries to improve their adaptive capacity and to adapt to the current and projected impacts of climate change. While it is widely acknowledged that social learning is a necessary condition for adaptation, few studies have systematically investigated under which conditions particular forms of social learning are most successful in improving adaptive capacity of the most vulnerable groups. This study aims to design, implement and evaluate a social learning configuration in a coastal community in Vietnam. We make use of various methods during four workshop-based interventions with local smallholder farmers: interviews with key farmers and commune leaders, farmer-to-farmer learning, participatory observations and focus group discussions. The methods for evaluation of social learning configuration include in-depth interviews, focus group discussions and structured survey interviews. Our findings show that the social learning configuration used in this study leads to an increased problem ownership, an enhanced knowledge-base with regard to climate change impacts and production adaptation options, improved ability to see connections and interdependencies and finally, strengthened relationships and social cohesion. The results suggest that increased social learning in the community leads to increase in adaptive capacity of smallholder farmers and improves both their economic and environmental sustainability. We discuss the key lessons for designing learning configurations that can successfully enhance adaptive capacity and smallholder farmers’ agency and responsiveness to the challenges posed by climate change impacts.     

Measuring the bias of technical change of industrial energy and environment productivity in China: a global DEA-Malmquist productivity approach

Environmental Science and Pollution Research - Thanks to the booming industry, China has made a huge economic achievement during the past several decades. However, it is suffering severe...     

乡村空间重构与土地利用转型耦合机制及路径分析

科学揭示乡村空间重构与土地利用转型的耦合发展关系,有利于为中国乡村振兴和城乡融合发展提供理论基础和实践依据。运用文献综述、理论分析阐释二者的耦合机理及驱动因子。主要结论如下：（1）重构乡村空间是对新一轮乡村转型发展要求的积极回应,土地作为乡村地域的关键发展要素,通过其利用形态的多维转化适应不同的空间重构场景。（2）乡村空间重构是土地利用转型的重要驱力,也为土地利用转型提供不竭的现实需求,土地利用的成功转型是乡村空间重构结果的显著表征,二者交互影响,存在耦合互动关系。（3）空间规划、政策制度、产业结构、利益主体及生态理念的多轮驱动机制共同对其耦合关系施加影响,不同作用机制下的作用效力、方向有所不同。（4）新时代下促进乡村空间重构与土地利用转型耦合发展的一个重要思路是全方位探寻土地利用优化转型的多维路径,总体上应立足生态文明的价值位序,以空间规划为约束机制,以产业结构升级为诱发机制,以多方利益协调为保障机制,同时创新土地政策制度机制,从而提高耦合水平,助力乡村振兴战略实施。     

Application of soft computing to predict water quality in wetland

Prediction of water quality is a critical issue because of its significant impact on human and ecosystem health. This research aims to predict water quality index (WQI) for the free surface wetland using three soft computing techniques namely, adaptive neuro-fuzzy system (ANFIS), artificial neural networks (ANNs), and group method of data handling (GMDH). Seventeen wetland points for a period of 14 months were considered for monitoring water quality parameters including conductivity, suspended solid (SS), biochemical oxygen demand (BOD), ammoniacal nitrogen (AN), chemical oxygen demand (COD), dissolved oxygen (DO), temperature, pH, phosphate nitrite, and nitrate. The sensitivity analysis performed by ANFIS indicates that the significant parameters to predict WQI are pH, COD, AN, and SS. The results indicated that ANFIS with Nash-Sutcliffe Efficiency (NSE = 0.9634) and mean absolute error (MAE = 0.0219) has better performance to predict the WQI comparing with ANNs (NSE = 0.9617 and MAE = 0.0222) and GMDH (NSE = 0.9594 and MAE = 0.0245) models. However, ANNs provided a comparable prediction and the GMDH can be considered as a technique with an acceptable prediction for practical purposes. The findings of this study could be used as an effective reference for policy makers in the field of water resource management. Decreasing variables, reduction of running time, and high speed of these approaches are the most important reasons to employ them in any aquatic environment worldwide.

     

Visualization and quantification of transparent exopolymer particles (TEP) in freshwater using an auto-imaging approach

Most water sources are full of microscopic transparent exopolymer particles (TEP), which are currently regarded as a major initiator of biofilm formation. This study developed and applied an auto-imaging FlowCAM-based method for online observation and quantification of TEP in freshwater. Samples from reservoirs in Taiwan with a wide range of water quality were directly used to develop this methodology. Factors that potentially affect the measurement were tested. The results showed that characteristics of the particles measured instantaneously after staining samples with Alcian blue differed significantly from those measured at steady states, as a result of particle aggregation. Compared to traditional microscopic methods, this proposed method provides a simple, rapid, and less labor-intensive analysis with particle morphological conservation and a large number of particle attributes. By overcoming the limitations from the former, this technique would offer routine monitoring of these transparent particles from various freshwater sources and feed water in membrane filtration, hence facilitating the use of TEP as a critical parameter for biofouling investigation in water treatment. Application of the method for Taiwan reservoirs showed a wide variety of morphological forms of TEP and its abundance, up to 25,000 ppm.     

基于物元可拓集法的蛟龙污水处理厂出水水环境质量评价

可以从定性、定量两个角度解决问题的物元可拓法已被广泛应用于各个领域。选取具有代表性的BOD5、NH3-N、石油类、CODcr、粪大肠菌群五项指标为待评物元,取Ⅰ至Ⅴ类水质标准对应的取值范围构造经典域物元矩阵,按照污染贡献率法确定各特征的权重,应用建立的水质评价物元模型计算出关联度0.10,得出该污水处理厂出水环境质量属于Ⅲ级。研究表明,运用物元可拓集模型评价水环境质量具有可信性和实用性。     

草木灰对亚甲基蓝的吸附研究

本实验目的是研究草木灰对吸附亚甲基蓝的去除效果,探讨了亚甲基蓝初始量、吸附时间、pH值等对吸附效果的影响,并运用伪一级、伪二级反应动力学模型和Laugmuir、Freundlich等温线模型进行拟合。结果表明,草木灰对亚甲基蓝溶液的吸附在5 min~30 min速率比较快,约在65 min内达到吸附平衡,pH越大越有利于吸附,浓度在5mg/L时草木灰对亚甲基蓝的吸附最佳。与伪二级动力学曲线模型拟合效果较好,由Laugmuir等温线模型计算得出理论最大吸附容量Qm为2.275 mg/g,吸附性能优异。     

保定地区PM2.5中重金属元素的污染特征及健康风险评价

为了解保定市大气环境中PM_2.5中重金属的污染特征及其健康风险,在保定市设立观测站点,利用中流量颗粒物采样器对保定市大气PM_2.5进行了连续昼夜采集,并使用微波消解-电感耦合等离子质谱法分析了样品中的V、Cr、Mn、Co、Ni、Cu、Zn、As、Cd和Pb等10种重金属元素的质量浓度.结果表明,保定市大气PM_2.5浓度范围为16.84~476.19 μg·m^-3,采样期间有65d高于我国《环境空气质量标准》（GB 3095-2012）中的二级标准,超标率为54.2%.保定市PM_2.5中重金属元素的浓度变化趋势为：除Ni、Mn和Co外,夜间浓度略大于日间;大部分重金属元素秋冬季浓度大于春夏季.富集因子分析可知,保定市Cu、Zn、Pb、Cd主要来自于人为源,特别是受到交通源的影响较大.健康风险评估结果表明,保定市大气PM_2.5中的重金属污染的非致癌风险较小,致癌风险主要是As、Cr、Cd和Co,且成年人的致癌风险大于儿童.