Fabrication and characterization of lightweight aggregate prepared from steel mill sludge in one step

Journal of Material Cycles and Waste Management - The qualified green lightweight aggregate (LWA) was successfully prepared from steel mill sludge (SMS) and fly ash (FAS) in one step using the...     

Calcined Oil Shale Semi-coke for Significantly Improved Performance Alginate-Based Film by Crosslinking with Ca2+

Journal of Polymers and the Environment - Oil shale semi-coke (OSSC) is the residual solid waste after refining of oil shale, which principally contains organic matter and minerals. The common...     

Does leakage exist in China’s typical protected areas? Evidence from 13 national nature reserves

Environmental Science and Pollution Research - There is profound interest in knowing the degree to which the effectiveness of China’s nature reserves, and whether leakage is common around the...     

Near-surface wind profile test based on accuracy verification of UAV anemometer lifting height in an urban fringe built-up area

Environmental Science and Pollution Research - Multirotor UAVs (unmanned aerial vehicles) have been widely used in urban vertical wind environment testing, whereas less attention has been given to...     

How does power technology innovation affect carbon productivity? A spatial perspective in China

Power technology innovation has been positioned as an effective way to contribute to China’s carbon productivity. However, limited empirical evidence exists on the impact of power technology innovation on carbon productivity. Thus, based on the annual panel dataset of 30 China’s provinces from 2001 to 2019, this study explored whether and how power technology innovation promotes or impedes the improvement of carbon productivity. First, carbon productivity in the framework of total factor was calculated based on the metafrontier Malmquist-Luenberger productivity index. Second, the effect of power technology innovation on carbon productivity was investigated using the spatial Durbin model. And we also examined whether heterogeneous power technology innovations have a synergistic effect on carbon productivity. Third, influence mechanism of power technology innovation affecting carbon productivity was identified. Results show that (1) there are notable differences in China’s provincial carbon productivity, which is characterized by the spatial correlation. (2) Local power technology innovation has a promotion effect on carbon productivity in both local and neighboring provinces. Moreover, the promotion effect of breakthrough power technology innovation is stronger than that of incremental power technology innovation. (3) Catching-up Effect and Innovation Effect are important transmission channels through which power technology innovation improves carbon productivity. Finally, policy recommendations are provided.

     

The protective effect of green space on heat-related respiratory hospitalization among children under 5 years of age in Hanoi,Vietnam

Environmental Science and Pollution Research - Combined effects of global warming and rapid urbanization replace green spaces with urban facilities. Children in urban areas are at a higher risk of...     

A global comprehensive analysis of ambient low temperature and non-communicable diseases burden during 1990–2019

Environmental Science and Pollution Research - Climate change and health are inextricably linked, especially the role of ambient temperature. This study aimed to analyze the non-communicable...     

省会城市不同功能区大气PM2.5化学组分季节变化及来源分析

为探究城市不同功能区大气PM_2.5污染水平、成分季节差异特征以及来源,采集了省会城市济南市2019年不同季节（春、秋、冬）3类典型功能区（城市市区、工业区、城乡结合区）和环境背景点植物园区的PM_2.5样品,对其浓度[ρ(PM_2.5)]、化学组分（水溶性离子、碳质组分、元素）和来源进行分析.结果表明采样期间3类功能区ρ(PM_2.5)在空间上呈现：工业区[（89.88±49.25）μg·m^-3]>城乡结合区[（86.73±57.24）μg·m^-3]>城市市区[（70.70±44.89）μg·m^-3],远大于植物园区[（44.36±21.54）μg·m^-3].各功能区ρ(PM_2.5)秋冬季明显高于春季,冬季最高值出现在城乡结合区,春季和秋季均为工业区最高.工业区各季PM_2.5中的水溶性离子浓度较高,主要的水溶性离子NO^-₃     

北京温榆河流域耐药大肠杆菌的调查研究

采用滤膜法结合大肠杆菌显色培养基,调查了北京地区温榆河流域氨苄青霉素、四环素、磺胺(磺胺甲厄唑-甲氧苄啶联用)和左旋氧氟沙星4 类抗生素耐药大肠杆菌的发生情况.结果表明,温榆河流域总大肠杆菌数为10³~10⁷ 个/L,耐药大肠杆菌数为0~10⁶ 个/L;大肠杆菌对氨苄青霉素、四环素和磺胺耐药率分别为10%~35%、5%~25%、10%~35%,而使用时间最短的左氧氟沙星耐药率则低于15%;受渔场排放影响的采样点,四环素耐药大肠杆菌数量显著高于该点其他抗生素耐药大肠杆菌数量,而左氧氟沙星耐药大肠杆菌数量百分比相对较高的采样点推测可能源于人类排放.