新能源场群连锁故障路径的仿真预测方法

新能源场站的大规模集群化接入不仅增加了连锁故障的发生概率,也恶化了故障发生后的电网运行状态。为适应电网运行分析的新要求,以新能源机组和无功补偿装置实际运行工况为依据,研究了一种用于预测新能源场群连锁故障路径的仿真计算方法。通过基于大电网数据的仿真算例分析,得到了某新能源场群在典型约束条件下的详细连锁故障路径。结果表明:基于新能源场站机组实际情况建立的仿真模型更适宜于连锁脱网路径的仿真预测。     

低浓度Pb2+、Cd2+对鲫鱼肝脏组织中 HSP70诱导的影响

以鲫鱼(Carassius auratus)作为实验对象,经过40 d Pb2+、Cd2+不同浓度的暴露后,运用SDS-PAGE和Western Blotting方法检测鱼肝脏组织内应激蛋白HSP70的诱导表达情况.结果表明,在实验浓度下,与对照组相比,Pb2+、Cd2+对鱼肝脏内HSP70有显著的诱导(P＜0.05),但在Cd2+浓度为0.2 mg/L有停止表达HSP70的现象,可能是由于浓度过高造成了组织病理损伤而破坏了诱导表达机制.实验还发现,在实验浓度低于国家渔业用水标准时,HSP70仍然表现为明显诱导(P＜0.05),充分说明运用分子生物学指标要比传统的环境检测指标敏感,具有对污染物早期预警的作用.     

从委托代理理论谈中国的环境影响评价制度

根据委托代理理论,分析了中国环境影响评价制度中存在的问题,立足于绿色招商的理念,理顺建设项目环评委托代理关系,明确了建设单位、环评单位、招商部门、环保部门等相互之间的关系和职责,以使中国的环境影响评价制度更适应新型工业化道路发展的要求。     

Synthesis of branched allylic sulfones by regioselective boron-catalysed hydrosulfonylation

Environmental Chemistry Letters - Branched allylic sulfones are scaffolds widely distributed in bioactive molecules and organic functional materials. The synthesis of allylic sulfones has been...     

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal solid waste sorting

● MSWNet was proposed to classify municipal solid waste. ● Transfer learning could promote the performance of MSWNet. ● Cyclical learning rate was adopted to quickly tune hyperparameters. An intelligent and efficient methodology is needed owning to the continuous increase of global municipal solid waste (MSW). This is because the common methods of manual and semi-mechanical screenings not only consume large amount of manpower and material resources but also accelerate virus community transmission. As the categories of MSW are diverse considering their compositions, chemical reactions, and processing procedures, etc., resulting in low efficiencies in MSW sorting using the traditional methods. Deep machine learning can help MSW sorting becoming into a smarter and more efficient mode. This study for the first time applied MSWNet in MSW sorting, a ResNet-50 with transfer learning. The method of cyclical learning rate was taken to avoid blind finding, and tests were repeated until accidentally encountering a good value. Measures of visualization were also considered to make the MSWNet model more transparent and accountable. Results showed transfer learning enhanced the efficiency of training time (from 741 s to 598.5 s), and improved the accuracy of recognition performance (from 88.50% to 93.50%); MSWNet showed a better performance in MSW classsification in terms of sensitivity (93.50%), precision (93.40%), F1-score (93.40%), accuracy (93.50%) and AUC (92.00%). The findings of this study can be taken as a reference for building the model MSW classification by deep learning, quantifying a suitable learning rate, and changing the data from high dimensions to two dimensions.     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

Evaluation of activated sludge properties’ changes in industrial-wastewater pre-treatment: role of residual aluminum hydrolyzed species with different polymerization degree

● Medium poly Al salts dominated the PAC residual salts with a rational dosage. ● Settlement flocculation effect under medium poly Al salts showed a better trend. ● Complex of medium poly Al salts and enzymes promoted cell activity. ● Medium poly Al salts were beneficial to the effluent indexes. With the widespread introduction of pre-coagulation prior to the biological unit in various industrial wastewater treatments, it is noteworthy that long-term accumulation of residual coagulants has certains effect on both micro and macro characteristics of activated sludge (AS). In this study, the morphology distributions of residual aluminum salts (RAS) and their effects on the removal efficiency of AS were investigated under different PAC concentrations. The results showed that the dominance of medium polymeric RAS, formed under an appropriate PAC dose of 20 mg/L enhanced the hydrophobicity, flocculation, and sedimentation performances of AS, as well as the enzymatic activity in cells in the sludge system, improving the main pollutants removal efficiency of the treatment system. Comparatively the species composition with monomer and dimer / high polymer RAS as the overwhelming parts under an over-dosed PAC concentration of 55 mg/L resulted in excessive secretion of EPS with loose flocs structure and conspicuous inhibition of cellular activity, leading to the deterioration of physico-chemical and biological properties of AS. Based on these findings, this study can shed light on the role of the RAS hydrolyzed species distributions, closely relevant to Al dosage, in affecting the comprehensive properties of AS and provide a theoretical reference for coagulants dosage precise control in the pretreatment of industrial wastewater.     

Screening of indicator pharmaceuticals and personal care products in landfill leachates: a case study in Shanghai,China

● A systematic framework was developed to identify i-PPCPs for landfill leachate. ● The wide-scope target analysis offered a basis for comprehensive i-PPCP screening. ● Source-specificity and representativeness analysis helped to refine i-PPCPs. ● Erythromycin, gemfibrozil and albendazole were identified as i-PPCPs for leachate. Identifying potential sources of pharmaceuticals and personal care products (PPCPs) in the environment is critical for the effective control of PPCP contamination. Landfill leachate is an important source of PPCPs in water; however, it has barely been involved in source apportionment due to the lack of indicator-PPCPs (i-PPCPs) in landfill leachates. This study provides the first systematic framework for identifying i-PPCPs for landfill leachates based on the wide-scope target monitoring of PPCPs. The number of target PPCPs increased from < 20 in previous studies to 68 in the present study. Fifty-nine PPCPs were detected, with median concentrations in leachate samples ranging from below the method quantification limit (MQL) to 41 μg/L, and 19 of them were rarely reported previously. A total of 29 target compounds were determined to be PPCPs of high concern by principal component analysis according to multiple criteria, including occurrence, exposure potential, and ecological effect. Coupled with source-specificity and representativeness analysis, erythromycin, gemfibrozil, and albendazole showed a significant difference in their occurrence in leachate compared to other potential sources (untreated and treated municipal wastewater and livestock wastewater) and correlated with total PPCP concentrations; these were recommended as i-PPCPs for leachates. Indicator screening procedure can be used to develop a sophisticated source apportionment method to identify sources of PPCPs from adjacent landfills.     

城市地震次生火灾分析及处置对策

现代城市地震次生火灾发生概率大,扑救难度大,极易造成大量的人员伤亡以及财产损失。大量的统计数据表明,震后火灾的诱因、时空分布及消亡因素有着一定的规律性。本文在详细分析城市地震次生火灾发生的原因、火灾时空分布及危害特点的基础上,针对应急处置对策和长远处置对策等方面提出了新的观点,可供消防部队处置此类灾害时参考。     

电子废弃物中持久性有机污染物分析检测方法的研究进展

针对目前电子废弃物中持久性有机污染物(POPs)尚未形成有效快速分析检测方法的问题,介绍了溶剂萃取、固相萃取、微波萃取和超临界流体萃取等POPs前处理技术的研究进展,总结了POPs的分析方法,如:气相色谱、液相色谱、气相色谱-质谱法、高分辨率气相色谱-高分辨质谱法等化学分析方法,以及生物传感器测定法、表面胞质团共振检测法、酶联免疫检测法等生物分析方法。分析了各方法的优劣,并提出了展望。