离子液体氯化1-辛基-3-甲基咪唑对酵母细胞增殖生长和细胞膜通透性的影响

为探讨咪唑类离子液体氯化1-辛基-3-甲基咪唑([C₈mim][Cl])对酵母细胞的增殖生长和细胞膜通透性的影响,以不同浓度的[C₈mim][Cl]处理酵母细胞,研究离子液体对酵母细胞增殖和菌落形成的影响,通过测定酵母细胞外液蛋白质和核酸的含量,判断膜通透性的大小和[C₈mim][Cl]对细胞膜性结构的损伤。结果显示,0.1 mmol·L^-1的[C₈mim][Cl]延长了酵母细胞到达对数生长期的时间,在6～9 h之间对酵母细胞的增殖存在明显的抑制作用。1 mmol·L^-1的[C₈mim][Cl]使酵母细胞增殖不能到达对数生长期,对酵母细胞的增殖一直具有较强的抑制作用。随着离子液体浓度的增加,小菌落的数量增多。当平板内[C₈mim][Cl]浓度达到10 mmol·L^-1时,完全抑制了菌落的形成。[C₈mim][Cl]处理酵母细胞后,细胞外液中OD₂₈₀、OD₂₆₀的值显著升高。研究表明,细胞膜等膜性结构通透性的增加是离子液体[C₈mim][Cl]抑制酵母细胞增殖生长的原因之一。     

人工甜味剂环境行为研究进展

人工甜味剂是一类人工合成或半合成的蔗糖取代物,由于人们对饮食健康的关注而被越来越广泛地应用于食品和饮料中.但是大多数人工甜味剂在人体内几乎不被代谢就随尿液和粪便直接排到生活污水中.近年,几种典型的甜味剂在水体中广泛被检出且浓度较高,同时研究发现部分甜味剂难以降解,因此人工甜味剂已被视为新型有机污染物而得到关注.本文就人工甜味剂在水处理设施中的行为及其在环境来源和分布的相关研究进行了综述,总结了水处理设施和水环境中甜味剂的污染特征规律,并对今后的研究进行了展望.     

离子液体分析方法研究进展

离子液体(ILs)由于挥发性小和化学稳定性高常称为绿色溶剂而得以广泛生产与应用.同时由于水溶性高和难降解可能给水生生物带来潜在危害,已逐渐引起广大环境化学工作者的关注.如何有效地分离分析ILs是研究其迁移、转化等环境行为及生物毒性的首要问题.为此,本文系统论述了反相液相色谱法、离子对-反相液相色谱法、极性-反相液相色谱法、离子色谱法、毛细管电泳及等速电泳等方法分析ILs的研究进展,分析了各个方法的优缺点和适用对象,展望了ILs分离分析发展的未来趋势.     

四氨基钴酞菁催化产生活性氧的性能

四氨基钴酞菁作为一种有前途的可见光催化剂,可光敏化为三线态,与溶液中的O2反应产生活性氧.实验考察了反应过程中的光照时间、光敏剂质量、光照强度和pH等4个因素对活性氧产生的影响,同时确定了一种简单可行的检测方法:活性氧与卡巴肼(DPCI)反应,生成卡巴腙(DPCO),以苯-四氯化碳萃取,在563 nm处测其吸光度,从而表示出活性氧的相对产量.实验优化了四氨基钴酞菁催化产生活性氧的条件:于50 mL的溶液中,光照时间为25 min,光敏剂质量为5 mg,光照强度为60 W,pH值为4.同时证明了在反应体系中生成了自由基和单线态氧等活性氧,并且对光催化产生活性氧的机理进行了探讨.     

土地利用方式和施肥管理对黑土物理性质的影响

为了探讨东北黑土区土壤水分的调控能力及其影响因素以及土壤水分对降水和不同植被覆盖的响应,以海伦农田生态系统国家野外科学观测研究站内的长期定位试验为基础,利用中子水分仪测定土壤体积含水量,研究裸地、休闲地以及包括单施有机肥、化肥+秸秆还田、单施化肥和不施肥4种处理的农田耕层土壤物理性质和土壤水分动态.结果表明:与休闲地相比,农田土壤容重增加7.47％,而孔隙度、饱和含水量和田间持水量均呈降低趋势,分别下降2.59、6.04和1.90百分点;肥料的施入尤其是施用有机肥和秸秆还田能够改善土壤物理性质;裸地土壤物理性质最差.由于植被耗水量较大,农田和休闲地土壤剖面年平均体积含水量显著低于裸地,施用化肥和秸秆还田可显著降低农田土壤剖面年平均体积含水量.各处理土壤剖面水分变异系数均随土壤深度的增加(0～70 cm深处)而呈先减小后增加趋势.由于植被生长的耗水作用,休闲地和农田土壤水分变化比裸地强烈,秸秆还田加剧了农田土壤水分的变异.土壤储水量的动态变化与降水量之间存在明显相关性,不同土地利用方式和施肥管理对浅层土壤储水量的影响较大,但随着土壤深度的增加,各处理对土壤储水量的影响越来越不明显.     

滇西北高原生态恢复过程中土壤侵蚀特征及其影响因子

滇西北高原由于地处生态脆弱的石灰岩区,水土流失严重,探讨该区生态恢复过程中土壤侵蚀的变化规律,为开展人工植被建设提供依据。以时空互代的方法,通过径流小区,对坡面的产沙产流特性及其影响因素进行研究。结果表明:天然次生林和人工混交林均有较好的调节径流和减少泥沙的作用,产沙量分别比坡耕地减少了51.46%、43.18%,产流量也相应降低了39.39%、24.24%。在最大次降雨条件下,荒草丛、坡耕地、次生林和混交林单次降雨的产沙量分别占试验期产沙总量的55.38%、55.58%、58.35%和58.05%,产流量相应占产流总量的64.72%、64.63%、73.85%和55.39%。而且,产流产沙量与土壤有机质质量分数均存在明显正相关,与乔、灌层植物多样性及均匀度指数等呈显著负相关性(P<0.05)。因此,乔灌草结合的群落结构配置模式是滇西北地区水土保持林营造的目标和方向。     

我国区域空气污染治理效率及其影响机制——基于超效率SBM模型和门槛回归模型

随着人民对美好生活需求的日益增长,政府空气污染治理的效率问题日益得到重视。本文从地方政府空气污染治理效率及其影响因素的视角入手,以全国30个省份为研究对象,运用超效率SBM模型测算2003—2015年各省级区域的空气污染治理效率。在此基础上,运用门槛回归模型分析政府空气污染治理效率的影响机制。研究表明:①地区间空气污染治理效率差异性较为显著。中部、西部空气污染治理效率整体呈下降趋势。东部和东北地区空气污染治理效率则上升比较平稳。②政策规划、碳源、污染物排放和环境治理投入表现出双重门槛特征,其中碳源对空气污染治理效率影响显著,而以碳为首的能源消费结构则主要对中部和西部空气污染治理效率产生影响。落后地区政府应注重产业升级,财政上应对碳税等税目进行征收,产业上应鼓励企业创新,并对落后企业进行倒逼升级。     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

Sanitation workers at the frontline: work and vulnerability in response to COVID-19

ABSTRACT

The absence of a vaccine and effective treatment for COVID-19 has created public panic and burdened the health systems in most countries. Along with health workers’, sanitation personnel are also working at the frontlines in the war against the disease by keeping cities clean. Sanitation workers are engaged in Drudgery, Dangerous, Dirty and Dehumanising work that makes them vulnerable for developing the chronic respiratory diseases due to the exposure of various hazardous materials and toxic gases that are emitted from the solid waste. The sanitation workers working on a contractual basis are excluded from the labour policies and welfare programs who are playing a vital role in fighting the pandemic. Women sanitation workers are even more vulnerable because most of them are non-literate, poor in financial management and under-represented in the sanitation employee’s union. The local and state governments should protect and safeguard sanitation workers by providing them with adequate protective equipment, ensure payment of paying adequate salaries and provide them with health insurance.     

Short-term wind speed forecasting based on random forest model combining ensemble empirical mode decomposition and improved harmony search algorithm

ABSTRACT

Wind speed forecasting plays an important role in power grid dispatching management. This article proposes a short-term wind speed forecasting method based on random forest model combining ensemble empirical modal decomposition and improved harmony search algorithm. First, the initial wind speed data set is decomposed into several ensemble empirical mode functions by EEMD, then feature extraction of each sub-modal IMF is performed using fast Fourier transform to solve the cycle of each sub-modal IMF. Next, combining the high-performance parameter optimization ability of the improved harmony search algorithm, two optimal parameters of random forest model, number of decision trees, and number of split features are determined. Finally, the random forest model is used to forecast the processing results of each submodal IMF. The proposed model is applied to the simulation analysis of historical wind data of Chaoyang District, Liaoning Province from April 27, 2015 to May 22, 2015. To illustrate the suitability and superiority of the EEMD-RF-IHS model, three types of models are used for comparison: single models including ANN, SVM, RF; EMD combination models including EMD-ANN, EMD-SVM, EMD-RF; EEMD combination models including EEMD-ANN, EEMD-SVM, EEMD-RF. The analysis results of evaluation indicators show that the proposed model can effectively forecast short-term wind data with high stability and precision, providing a reference for forecasting application in other industry fields.