财政分权对环境污染的空间效应

利用2006—2017年我国30个省级行政单位的面板数据,采用空间计量模型对财政分权与环境污染之间的关系进行实证分析,并通过效应分解分别计算出财政收入分权和财政支出分权对环境污染的直接效应、空间溢出效应和总效应。模型估计的结果表明:①财政收入分权与财政支出分权通过直接效应和空间溢出效应两种途径对环境污染产生显著影响,但收入分权与支出分权对环境污染的空间效应具有异质性。②财政收入分权对环境污染具有显著的负向直接效应和负向空间溢出效应,影响系数分别为-5.429和-17.572。提高财政收入分权度不仅有利于减轻本省份环境污染,也对邻近省份的环境污染起到抑制作用。而财政支出分权对环境污染具有显著的负向直接效应和正向的空间溢出效应,影响程度分别为-3.345和1.173。提高财政支出分权虽然有利于减少本省份污染的排放,但在一定程度上引起省际的污染外溢效应,提高邻近省份的污染程度。③从总效应来看,财政收入分权和财政支出分权对环境污染均呈现出显著的负向相关性,影响程度分别为-23.001和-2.172。提高财政分权可降低环境污染水平,有利于环境质量提升。④通过构建不同空间权重矩阵,检验模型的稳健性,结果表明模型估计是稳健可靠的。根据分析结论,可能的启示与建议有:①合理划分中央政府和地方政府之间的财政事权和支出责任,在提高财政支出分权度的同时提高地方政府财政收入分权度,充分发挥地方政府环境治理的积极性和主动性。②继续加大生态环境保护力度,完善绿色经济考核机制,引导地方政府加大对污染治理和环境改善的支出水平及效率。     

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.     

基于火探管式的锂离子电池灭火技术研究

为研究锂离子电池灭火方案,基于火探管灭火技术同时利用新型清洁灭火剂Novec 1230,组装成火探管灭火系统。在灭火测试平台上以功率为200 W的电热管作为外热源引发单电池或电池模组热失控,通过改变火探管的布置位置,记录相应的灭火行为以及灭火效率,并对实验结果进行了分析。研究结果表明,当火探管灭火系统直接布置在电池正上方时,在起火后的5.6s内控制火情;随着灭火剂用量增加可以显著降低体系温度,防止电池复燃以及连锁热失控现象发生;火探管有效覆盖区域外的失控电池作为热源将继续加热临近电池,引发连锁热失控,造成灭火系统失效;根据电池热失控后的燃烧行为以及传热行为,提出相应的火探管灭火系统复合方案。     

基于微型无人机遥感数据的城市水环境信息提取初探

近年来,黑臭水体整治已经成为各级政府的重要工作内容。为更好地开展黑臭水体筛查和监管工作,提出基于多旋翼无人机搭载多光谱相机的遥感监测方案,尝试采用影像特征变换结合面向对象分类方法提取黑臭水体的遥感信息。结果表明:(1)无人机影像上地物具有更加丰富的色彩和纹理;(2)与主成分变换和纹理分析方法相比,光谱指数对典型地物具有较好的判别能力;(3)采用标准最邻近分类法提取城市水环境信息,能够获得较高分类精度。     

基于变权灰色云模型的江苏省水环境系统脆弱性评价

水环境系统脆弱性是水资源利用与生态环境研究的热点问题，通过研究水环境系统的内在机理，综合考虑影响水环境系统脆弱性的资源、环境、经济、社会等因素，借助驱动力-压力-状态-影响-响应-管理（DPSIRM）框架构建水环境系统脆弱性评价指标体系。在此基础上，构建基于变权灰色云模型的评价方法，对2004~2014年江苏省水环境系统脆弱性进行评价。结果表明：2004~2014年水环境系统脆弱性指数由47.056提高到63.210，脆弱性等级由“重度脆弱”演化为“中度脆弱”，并长期维持在“中度脆弱的”等级，2014年出现了向“轻度脆弱”状态转变的趋势。分析各个子系统对水环境系统脆弱性影响程度可知，影响子系统和响应子系统对江苏省水环境脆弱性系统的影响程度逐年增加；而压力子系统和管理子系统对水环境系统脆弱性的影响程度逐年下降；其它子系统对水环境系统脆弱性的影响维持在一定水平小幅度波动。     

煤与瓦斯共采在错层位巷道布置中的机理研究及应用构想

为了完善现有煤与瓦斯共采技术，创新煤与瓦斯共采方法，对错层位巷道布置下的煤与瓦斯共采系统展开研究，利用相似模拟试验，分析错层位巷道布置覆岩运动情况，预测其开采围岩裂隙发育和瓦斯运移形式，提出了创新煤与瓦斯共采技术构想。研究结果表明:采空区覆岩三带高度随接续工作面的增加而增大，相邻采空区垮落矸石压实区呈现“O-L-O”形变化，多个相邻采空区覆岩出现大“O”形圈裂隙带；相邻采空区内瓦斯可实现相互运移，大“O”形圈裂隙带内赋存大量瓦斯气体；研究提出了地面钻井抽采瓦斯、走向高位瓦斯抽采巷和外错尾巷穿层钻孔3种煤与瓦斯共采技术，比传统巷道布置情况下的煤与瓦斯共采技术在安全、经济等方面更具优势。     

UiO-66(Zr)@多孔陶瓷复合材料的制备及对络合态重金属EDTA-Cu(Ⅱ)的去除

本文采用多孔陶瓷作为基体制备了锆基金属有机骨架UiO-66@多孔陶瓷复合材料.通过扫描电子显微镜(SEM)、粉末X射线衍射(PXRD)、氮气吸附和傅里叶变换红外光谱(FTIR)等表征手段对比了氢氧化钠脱硅和乙二胺表面改性等基体活化方式对UiO-66(Zr)在多孔陶瓷表面负载情况的影响.结果表明,经过乙二胺表面改性的多孔陶瓷对UiO-66(Zr)的负载更均匀,负载效果更好.以EDTA-Cu(Ⅱ)为考察对象,研究了UiO-66(Zr)@乙二胺表面改性多孔陶瓷复合材料对络合态重金属的净化效能.结果表明,UiO-66(Zr)@多孔陶瓷复合材料在较宽的酸碱条件下(pH=3—9)对络合态重金属EDTA-Cu(Ⅱ)均表现出良好的吸附性能,饱和吸附量为1.17 mg·g~(-1),并可通过NaOH解吸再生,从而实现材料的重复利用.     

Determination of 27 pharmaceuticals and personal care products (PPCPs) in water: The benefit of isotope dilution

• Isotope dilution method was developed for the determination of 27 PPCPs in water. • The established method was successfully applied to different types of water samples. • The correction effect of corresponding 27 ILSs over 70 d was investigated. • Benefit of isotopic dilution method was illustrated for three examples. Pharmaceuticals and personal care products (PPCPs) are a unique group of emerging and non-persistent contaminants. In this study, 27 PPCPs in various water samples were extracted by solid phase extraction (SPE), and determined by isotope dilution method using liquid chromatography coupled to tandem triple quadruple mass spectrometer (LC-MS/MS). A total of 27 isotopically labeled standards (ILSs) were applied to correct the concentration of PPCPs in spiked ultrapure water, drinking water, river, effluent and influent sewage. The corrected recoveries were 73%–122% with the relative standard deviation (RSD)<16%, except for acetaminophen. The matrix effect for all kinds of water samples was<22% and the method quantitation limits (MQLs) were 0.45–8.6 ng/L. The developed method was successfully applied on environmental water samples. The SPE extracts of spiked ultrapure water, drinking water, river and wastewater effluent were stored for 70 days, and the ILSs-corrected recoveries of 27 PPCPs were obtained to evaluate the correction ability of ILSs in the presence of variety interferences. The recoveries of 27 PPCPs over 70 days were within the scope of 72%–140% with the recovery variation<37% in all cases. The isotope dilution method seems to be of benefit when the extract has to be stored for long time before the instrument analysis.