循环井技术对低渗透性透镜体二级污染源的修复效率评估方法

以地下水循环井技术（GCWs）修复含水层低渗透性透镜体内污染物为研究对象,通过解析含水层内污染物浓度的空间分布规律和时间演化过程,构建了评估循环井修复低渗透性透镜体二级污染源修复效率的评价方法 .主要评价指标包括污染物平均浓度、污染物修复的时间累积效率系数和界限流线的几何特征及其上渗流入渗角度,分别用以评价瞬时修复效率、时间累积修复效率和渗流模式对污染物修复效果的影响.同时,利用COMSOL数值模拟软件,模拟了不同工况下循环井驱动的低渗透性污染源的反向扩散过程,并利用所构建的评估方法进行评估.结果表明：(1)随注水口高程降低或抽水口高程升高,循环井的修复效率总体呈递减趋势,其中,注水口略高于或抽水口略低于透镜体时修复效率较高;(2)循环井注水/抽水的质量通量越大、透镜体的长宽比系数越大、透镜体距离循环井越近,其修复效率越高;(3)界限流线位于以透镜体中心为原点的二、三象限时,循环井的修复效率较好;其上渗流入渗方向垂直于透镜体的上水平界面时,修复效率较高;随界限流线与透镜体的上界面法线夹角增大,修复效率降低.     

Mercury uptake by Paspalum distichum L. in relation to the mercury distribution pattern in rhizosphere soil

Environmental Science and Pollution Research - Paspalum distichum L. was tested to evaluate their phytoremediation capacity for Hg contaminated soil through analyzing the dissipation of Hg in soil...     

煅烧的水滑石同时去除水体中砷和氟

为探讨水滑石类材料对水体中氟、砷离子的同时去除效果,采用共沉淀法合成(Mg∶Al=2∶1)纳米类水滑石(LDHs),用傅立叶转换红外光谱、电子扫描透射电镜、X射线晶体衍射等手段对合成的材料进行了表征,并研究纳米材料在不同初始浓度、pH、吸附时间、阴离子干扰条件下其同时除砷氟性能。结果表明,煅烧后的水滑石(LDOs)对砷最大吸附量为51.02 mg/g,对氟最大吸附量为36.63 mg/g。吸附动力学实验表明,煅烧水滑石对砷的吸附在前6 h内基本完成,对氟的吸附在前10 h内基本完成。砷氟共存溶液保持pH=4~10及pH=6~8时,水滑石分别对砷、氟保持良好的吸附效率。对比不同阴离子对水滑石共除砷氟效率的影响,水滑石除砷速率受到阴离子影响力大小为:HPO2-4CO2-3NO-3Cl-SO2-4;水滑石除氟速率受到阴离子影响力大小为:CO2-3HPO2-4SO2-4Cl-NO-3。材料再生循环利用4次后,对砷和氟的吸附效率均能达到90%以上。实验结果表明,所合成的水滑石是一种优秀的能共除砷氟的吸附剂。     

不同比例乙酸和丙酸对活性污泥微生物合成聚羟基脂肪酸酯的影响

聚羟基脂肪酸酯（PHA）是一种生物可降解塑料,利用活性污泥合成PHA具有节约成本、操作方便的优点。研究选择污泥发酵液挥发性脂肪酸（VFAs）中比重相对较高的乙酸和丙酸作为碳源自配营养液,深入研究不同质量浓度比对PHA合成的影响。结果表明,乙酸为主要碳源时更有利于PHA的合成,最大合成量12.3%出现在乙酸作为唯一碳源的条件下。此外,PHA合成量随着底物中有机酸比重的增加而增加,充分展现了利用挥发性脂肪酸大量合成PHA的良好前景。     

臭氧生物活性炭有机物吸附与生物降解量化分析

以西安北石桥污水净化中心出水为研究对象,通过对臭氧-生物陶粒与臭氧-生物活性炭处理工艺的对比研究,分析比较了两种生物过滤系统的生物活性及有机物去除特性,建立了臭氧-生物活性炭工艺在有机物降解过程中吸附和生物降解作用的量化计算方法,探讨了臭氧-生物活性炭工艺有机物降解过程及去除机理.研究表明:臭氧-生物活性炭工艺对有机物的去除是活性炭吸附和生物降解的协同作用,其中生物降解占主导作用,约占有机物总去除量的65%,生物降解作用去除的有机物几乎全部是易于降解的溶解性有机物;而吸附作用去除的有机物约占有机物总去除量的35%,去除的有机物中难降解和易于降解的有机物的量基本相当.     

高温职业危害风险分级与分级管理研究

为进一步研究高温作业职业危害风险强度,探讨高温作业环境条件下环境温度与劳动强度对劳动者健康的影响及其联合作用。采用高温环境模拟仓实验与建筑行业露天高温作业现场调研和测试相结合的方法,以高温环境和心血管体能负荷值(%CVL)作为高温作业危害风险分级的主要参照指标。提出了高温作业职业危害风险分级的技术方法和针对不同程度高温职业危害风险管理措施的具体建议,为保护高温作业劳动者安全与健康提供科学依据。     

基于MMA7260QT的危险场所跌倒检测设备的研制

在石化企业生产过程中,如何正确检测判别跌倒行为已成为危险场所安全防护的关键,传统的判别方法已不适应石化行业特殊的工作环境和行为特点。通过对三轴加速度传感器MMA7260QT原理的研究,结合毒性气体传感器和无线传输技术,采用低功耗微处理器MSP430F249,研制了一种危险场所用跌倒检测设备。介绍了三轴加速度传感器MMA7260QT的结构和原理,给出了设备系统设计。根据石化行业危险场所特点,建立了跌倒模型,分析了三轴加速度传感器检测信息的处理,确定出跌倒判断阈值。实验结果表明,研制的设备跌倒检测准确,符合石化行业危险场所应用需求。     

高地下水位地区透水停车场的水文控制效果

为确定高地下水位地区透水铺装对路面径流的水文控制效果,在上海市区建造了4个实验性透水铺装单元与1个不透水铺装对照,其中3个为设有防水衬底的不透型设施分别为透水混凝土铺装(设施Ⅰ)、水泥稳定碎石基层/缝隙透水砖面层(设施Ⅱ)、碎石基层/缝隙透水砖面层(设施Ⅲ),1个普通缝隙透水砖铺装(设施Ⅳ),以及1个不透水混凝土对照(设施0).历时1年监测了实际降雨条件下4种实验设施的表面径流、排水管出流流量及表面渗透速率,考察不同设施的径流总量削减率、峰值削减及峰现延迟能力.结果表明,缝隙透水砖面层的表面稳定渗透速率明显小于透水混凝土面层,使用1年后,2种面层表面稳定渗透速率均明显下降;4种设施的表面产流均无显著差异;3种不透型设施的就地消纳水量能力均较弱,年径流总量控制率分别为24.2%、28.5%、28.4%,排水管不发生出流的控制降雨量分别为5.2 mm、7.8 mm、7.8 mm;设施Ⅰ的峰值削减与峰现延迟效果弱于设施Ⅱ及设施Ⅲ,且3种设施的峰值削减率和峰现延迟时间与降雨强度呈现显著负相关性.     

Comparison of the daily global solar radiation from different data sources in Northwest China climate

The solar radiation data are of high importance to the solar energy systems. Conventional methods to obtain the solar radiation data are from weather stations, solar radiation models, commercial software databases, and field measurements. In the present study, a new daily global solar radiation model is proposed, by combining the quadratic function of sunshine fraction and sine function of the day of the year. The solar radiation model calculated data are then compared with China Meteorological Data Sharing System (CMDSS) data, TRNSYS data, and field-measured data in Northwest China climate. It is found that the newly proposed solar radiation model has better performance than the other nine solar radiation models in the literature. The solar radiation model calculated data fit well with the CMDSS annually average data. The TRNSYS data are a bit larger than the CMDSS annually average data in summer half year and a little smaller than those in winter half year. The solar radiation model and the CMDSS annually average data have the best correlation, whereas the TRNSYS data and the field-measured data have the worst correlation. The solar radiation model calculated data have the best correlation with the other three data sources.     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.