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...     

China’s sponge cities alleviate urban flooding and water shortage: a review

Environmental Chemistry Letters - About one tenth of humans are impacted by water shortages around the globe. Water resilience is worsening under climate change because intensifying weather...     

生态认知对长江流域渔民退捕意愿的影响研究基于鄱阳湖区的调研数据

流域禁捕是贯彻落实长江经济带发展战略和"共抓大保护、不搞大开发"的重要举措.渔民作为禁捕政策的最终执行者和落实者,其参与的积极性和主动性是政策顺利实施和推进的重要保障.基于计划行为理论,利用鄱阳湖区实地调查数据和结构方程模型,探讨了生态认知对渔民退捕意愿的影响及作用机理.研究发现:(1)生态认知对渔民退捕意愿有显著正向影响,即渔民生态认知水平越高,其参与禁捕政策的意愿越强;(2)生态认知的主观规范、行为态度、感知行为控制3个维度均对渔民退捕意愿具有显著正向影响,且3个维度两两之间也存在显著正向影响.其中,主观规范对渔民退捕意愿的影响最为显著;(3)主观规范中指令性规范对渔民参与禁捕的带动作用大于示范性规范;行为态度受渔民对政府禁捕政策的心理预期、生态修复保护与经济发展的重要性对比认知的影响较大;感知行为控制主要受到禁捕政策对家庭生产生活的影响程度及渔民参与禁捕政策能力的影响.为此,应建立有效的监督管理体系,提高指令性规范对渔民退捕的带动和引导作用,提高渔民对长江流域生态保护重要性的认知,营造浓厚的流域生态保护及积极参与禁捕的社会氛围,同时,制定适宜的转产转业政策,且将相关政策、补偿等严格落实到每位参与退捕的渔民,增强渔民对政府的信任程度,进而提高渔民退捕意愿.     

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...     

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.     

中国省域森林公园旅游产业竞争力的时空演化特征及影响因素

分析我国各省森林公园旅游产业竞争力演变及其影响因素，有助于为处于不同发展阶段和不同发展水平的省份提供产业竞争力方面的指导。首先构建我国港澳台外31省（市、自治区）森林公园的旅游产业竞争力指标体系，然后计算各省旅游产业竞争力得分并分析其时空演变特征，最后采用分位数回归研究影响森林公园旅游产业竞争力空间差异的主要因素。结果表明：中国森林公园旅游产业平均竞争力值较低，区域差异较大，呈现东部向中西部递减的状态；2004~2014年期间西部各省森林公园旅游产业竞争力进步较小，主要原因是受到“短板效应”的制约，表现为西部各省在产业效益方面与东、中部省份存在较大差距；中国的森林公园存在东北和东南两个高层次旅游产业竞争力集聚中心，并存在逐渐向周边地区扩散，带动周边省份提升发展的趋势；回归表明，国家扶持力度、管理投入、资源禀赋、经济基础、品牌效应和交通便利性会在不同分位点上对各省森林公园旅游产业竞争力产生影响。森林公园旅游产业竞争力在不同分位点上影响因素的差异为有针对性的提高各地区竞争力提供了良好的参考。     

Road traffic injuries among riders of electric bike/electric moped in southern China

Objective: Electric bike/moped-related road traffic injuries have become a burgeoning public health problem in China. The objective of this study was to identify the prevalence and potential risk factors of electric bike/moped-related road traffic injuries among electric bike/moped riders in southern China.

Methods: A cross-sectional study was used to interview 3,151 electric bike/moped riders in southern China. Electric bike/moped-related road traffic injuries that occurred from July 2014 to June 2015 were investigated. Data were collected by face-to-face interviews and analyzed between July 2015 and June 2017.

Results: The prevalence of electric bike/moped-related road traffic injuries among the investigated riders was 15.99%. Electric bike/moped-related road traffic injuries were significantly associated with category of electric bike (adjusted odds ratio [AOR] = 1.36, 95% confidence interval [CI], 1.01–1.82), self-reported confusion (AOR = 1.77, 95% CI, 1.13–2.78), history of crashes (AOR = 6.14, 95% CI, 4.68–8.07), running red lights (AOR = 3.57, 95% CI, 2.42–5.25), carrying children while riding (AOR = 1.96, 95% CI, 1.37–2.85), carrying adults while riding (AOR = 1.68, 95% CI, 1.23–2.28), riding in the motor lane (AOR = 2.42, 95% CI, 1.05–3.93), and riding in the wrong traffic direction (AOR = 1.63, 95% CI, 1.13–2.35). In over 77.58% of electric bike/moped-related road traffic crashes, riders were determined by the police to be responsible for the crash. Major crash-causing factors included violating traffic signals or signs, careless riding, speeding, and riding in the wrong lane.

Conclusion: Traffic safety related to electric bikes/moped is becoming more problematic with growing popularity compared with other 2-wheeled vehicles. Programs need to be developed to prevent electric bike/moped-related road traffic injuries in this emerging country.     

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。