Effects of climate variables on the transmission of COVID-19: a systematic review of 62 ecological studies

Environmental Science and Pollution Research - The new severe acute respiratory syndrome coronavirus 2 was initially discovered at the end of 2019 in Wuhan City in China and has caused one of the...     

Protective effects of dietary betaine on intestinal barrier function and cecal microbial community in indigenous broiler chickens exposed to high temperature environment

Environmental Science and Pollution Research - High temperature environment causes reduction in productivity in broilers by disrupting the intestinal barrier function. This study aimed to...     

Improved product selectivity of electrochemical reduction of carbon dioxide by tuning local carbon dioxide concentration with multiphysics models

Environmental Chemistry Letters - Electrochemical reduction of carbon dioxide (CO2) is promising to alleviate carbon emissions and produce fuels and materials in a circular way, yet effective...     

基于神经网络模型的千岛湖清洁水体叶绿素a遥感反演研究

叶绿素a浓度值是水体水质评价的重要指标,研究基于高分一号(GF-1)卫星遥感影像,利用神经网络模型,选用6节点的隐含层设置,构建了千岛湖清洁水体叶绿素a浓度反演模型,对其叶绿素a浓度值时空特征进行分析,并与其他常规反演方法精确度进行比较.研究结果表明,利用神经网络模型对千岛湖清洁水体叶绿素a浓度值进行反演是可行的,且与其他常规方法相比,该模型对于叶绿素a含量低的内陆清洁水体反演有着更高的相关性(R2 = 0.921 8);在空间分布上,千岛湖区域水体叶绿素a浓度整体较低,高叶绿素a浓度区域主要集中易受人类活动干扰的西南及东北区域;年际变化分析表明,千岛湖区域水体叶绿素a浓度稳定,且波动较小,平均叶绿素a浓度值皆维持在1.70～1.75 pg/L之间,清洁水体特征显著.     

Enhanced arsenate removal from aqueous solution by Mn-doped MgAl-layered double hydroxides

Environmental Science and Pollution Research - In this study, Mn-doped MgAl-layered double hydroxides (LDHs) were successfully synthesized for efficient removal arsenate from aqueous solution. The...     

地表水环境遥感监测关键技术与系统

介绍了地表水环境遥感监测的关键技术与系统及其典型应用,其代表性机理模型和应用示范成果主要来自于中国科学院遥感与数字地球研究所的高光谱遥感团队在最近几年中取得的一些研究进展,主要包括建立了基于改进双峰法的水体分布自动化遥感提取方法,实现了简单、高效和高精度的水体提取；提出了大型湖泊长时序水量估算方法,并以青藏高原湖区为例,重建了典型湖泊面积、水位和水量序列；发展了基于“软分类”的典型内陆水体叶绿素a浓度反演方法,构建了基于生物光学模型的高度浑浊水体悬浮物浓度遥感反演半解析方法,提高了反演方法的区域和季节适用性；构建了基于水色指数的大范围湖库营养状态和透明度遥感监测方法,实现了全球大型湖库营养状态遥感监测,以及全国大型湖库透明度遥感监测；在此基础上,开发了地表水环境遥感监测系统,提高了水环境遥感监测效率,促进了卫星遥感在水环境监测中的高精度业务化应用。     

A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification

● Established a quantification method of pollutant emission standard. ● Predicted the SO₂ emission intensity of single coking enterprises in China. ● Evaluated the influence of pollutant discharge standard on prediction accuracy. ● Analyzed the SO₂ emissions of Chinese provincial and municipal coking enterprises. Industrial emissions are the main source of atmospheric pollutants in China. Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely. Based on China’s coking enterprises in 2020, we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards (QRPES) into the construction of support vector regression (SVR) and random forest regression (RFR) prediction methods for SO₂ emission of coking enterprises in China. The results show that, affected by the types of coke ovens and regions, China’s current coking enterprises have implemented a total of 21 emission standards, with marked differences. After adding QRPES, it was found that the root mean squared error (RMSE) of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a, and theR² increased from 0.890 and 0.881 to 0.926 and 0.945, respectively. This shows that the QRPES can greatly improve the prediction accuracy, and the SO₂ emissions of each enterprise are highly correlated with the strictness of standards. The predicted result shows that 45% of SO₂ emissions from Chinese coking enterprises are concentrated in Shanxi, Shaanxi and Hebei provinces in central China. The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.     

4种营养元素对水华鱼腥藻和四尾栅藻增殖的影响

以水华鱼腥藻和四尾栅藻分别作为蓝藻,绿藻代表藻种,采用均匀设计实验方法(uniform design experimentation,UDE)设计藻类AGP实验。采用通径分析法(Path Analysis,PA)对氮、磷、铁和锰在不同藻种增殖过程中的影响程度进行分析。结果表明,4种营养元素对水华鱼腥藻增殖影响的决策排序为FeTNTPMn,微量金属元素铁是影响水华鱼腥藻(蓝藻)增殖的主要因素;对四尾栅藻增殖影响的决策排序为TNTPFeMn,常量元素是影响四尾栅藻(绿藻)增殖的主要因素。联合通径分析法和逐步二次方回归分析法(QRA)建立的数学模型,可用于预判藻增殖。     

磁性Fe_3O_4/石墨烯纳米复合材料催化降解水中17β-雌二醇

利用化学沉淀法制备磁性四氧化三铁/石墨烯(Fe3O4/GE)纳米复合材料,并将其与H2O2构成非均相Fenton体系用于催化降解水中微量的17β-雌二醇(E2),研究了初始p H值,初始H2O2浓度,催化剂用量对E2降解的影响。结果表明,Fe3O4/GE纳米复合材料在无需外加光源的条件下能够有效催化降解E2。在p H 7.0,E2初始浓度为1 mg/L,初始H2O2浓度为15 mmol/L,Fe3O4/GE投加量为15 mg/L的条件下,反应8 h后可去除92.9%的E2。Fe3O4/GE具有便捷的磁分离特性和稳定的催化活性,经过7次循环使用后对E2的降解效率仍保持在91.5%左右。     

页岩对污泥氨气挥发的抑制作用

氨气是城市污水污泥产生的恶臭气体之一,控制或抑制其产生是资源化利用甚至处置过程中至关重要的.通过改进氨气测量方法定量分析外掺页岩对污泥氨气挥发的抑制作用和机理,实验研究了页岩掺量、陈放形式以及环境温度对污泥氨气挥发浓度的影响.结果表明,外掺页岩对污泥氨气挥发具有明显的抑制作用,随温度升高、陈放时间延长抑制效果有所减弱但仍具有明显作用;页岩对污泥氨气挥发的抑制作用主要为对氨气的吸附作用.