大气污染特征研究及臭氧污染个例分析——以深圳市龙华区为例

根据深圳市龙华区观澜子站空气质量监测数据,对龙华区近年来空气质量状况、主要大气污染物浓度时间变化特征、气象条件和污染物浓度相关性,以及典型臭氧(O_3)污染过程进行了分析。结果表明龙华区空气质量以优良为主,空气质量指数(AQI)超标日中,O_3浓度超标天数最多,其次依次是PM_(2.5)、PM_(10)和二氧化氮(NO_2)。PM_(2.5)、PM_(10)和NO_2在秋冬季的浓度最高,春季次之,夏季最低;而O_3浓度则在夏秋季最高,春季次之,冬季最低。除O_3(日间浓度高于夜间浓度)以外,PM_(2.5)、PM10和NO_2晚间浓度高于日间浓度。此外,相关性研究表明,颗粒物污染以细颗粒物为主,O_3(8 h)和NO_2与颗粒物浓度均呈正相关性。由于地域差异的存在,O_3(8 h)和颗粒物浓度的相关性在不同地域表现也不同。同时,大气污染物浓度与气象条件和人为排放源的相关性较高。     

深圳市龙华区PM2.5污染与减排过程模拟分析

通过分析深圳市龙华区2018年大气环境承载力发现,NO2和PM10的实际大气环境承载量已经降到了理想大气环境容量范围内,而PM2.5的实际大气环境承载量则已超过理想大气环境容量近1 000 t,说明PM2.5仍是龙华区大气污染防治的重点工作,利用科学手段精准、有效地指导PM2.5减排工作十分重要.基于相关监测数据,结合...     

Transcriptome analysis of Plantago major as a phytoremediator to identify some genes related to cypermethrin detoxification

Environmental Science and Pollution Research - Cypermethrin (CYP) is a toxic manmade chemical compound belonging to pyrethroid insecticides contaminating the environment. Plantago major (PM) has...     

浙赣皖相邻地区A_2型花岗岩

浙赣皖相邻地区燕山期大茅山、铜山、里山岭、黄山、伏岭等岩体主要由黑云母花岗岩组成，其中斜长石属钠长石和富钠更长石，黑云母呈它形填隙状，结晶晚于浅色矿物。岩石化学成分富ＳｉＯ_２（７３.９２％－７７.５５％）、富碱（Ｎａ_２Ｏ＋Ｋ_２Ｏ为７.８１％～８. ６７％），贫ＣａＯ（０.２６％-０.９２％）、ＭｇＯ（０—０.４５％）；微量元素中富集Ｙ、Ｎｂ、Ｚｒ等ＨＦＳＥ，贫过渡元素及Ｓｒ、Ｂａ；稀土配分曲线呈“海鸥型”。这些特点与区内及华南Ｉ型和Ｓ型花岗岩明显不同，而具有Ａ_２型花岗岩的典型特征。     

内循环生物流化床处理石化废水的中试研究

进行了内循环生物流化床处理石化废水的中试研究,当进水平均ＣＯＤ为８００ｍｇ／Ｌ,流化床出水再辅这以气浮后处理,ＣＯＤ可降至２００ｍｇ／Ｌ,当进水ＣＯＤ为５００ｍｇ／Ｌ时,ＣＯＤ可达１００ｍｇ／Ｌ,本试验中的ＣＯＤ去除容积负荷可达１５ｋｇ／（ｍ＾３·ｄ）以上。     

Comparison of Machine Learning Models Performance on Simulating Reservoir Outflow: A Case Study of Two Reservoirs in Illinois,U.S.A.

Reservoir outflow is an important variable for understanding hydrological processes and water resource management. Natural streamflow variation, in addition to the streamflow regulation provided by dams and reservoirs, can make streamflow difficult to understand and predict. This makes them a challenge to accurately simulate hydrologic processes at a daily scale. In this study, three Machine Learning (ML) algorithms, Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN), were examined and compared to model reservoir outflow. Past, current, and future hydrologic and meteorological data were used as model inputs, and the outflow of next day was used as prediction. Simulation results demonstrated that all three models can reasonably simulate reservoir outflow. For Carlyle Lake, the coefficient of determination and Nash–Sutcliffe efficiency were each close to one for the three models. The coefficient of determination, relative mean bias, and root mean square error indicated that the SVM performed better than the RF and ANN, but the SVM output displayed a larger relative mean bias than that from RF and ANN. For Lake Shelbyville, the ANN model performed better than RF and SVM when considering the coefficient of determination, Nash–Sutcliffe efficiency, relative mean bias, and root mean square error. The study results demonstrate that the three ML algorithms (RF, SVM, and ANN) are all promising tools for simulating reservoir outflow. Both the accuracy and efficacy of the three ML algorithms are considered to support practitioners in planning reservoir management.     

羧基化多壁碳纳米管对雌性小鼠卵泡发育的影响

碳纳米管(carbon nanotubes, CNTs)作为一种新形式的结晶碳,在工业及医药领域具有非常广阔的应用前景。本研究采用水溶性较好的羧基化多壁碳纳米管(MWCNTs-COOH)为研究对象,探索功能化多壁碳纳米管对小鼠卵巢发育的影响。将羧基化多壁碳纳米管溶解在含0.5% Tween-20的磷酸盐缓冲溶液(PBS)中,对实验小鼠按照2.5, 5, 10 mg·kg-1进行持续64 d的灌胃处理。处理结束后通过透射电子显微镜和HE染色观察卵巢组织的形态学变化。结果显示,碳纳米管确实进入了小鼠卵巢中。同时,随着MWCNTs-COOH暴露的增加,雌性小鼠卵泡数量显著减少,而雌性小鼠卵泡的形态结构并无明显影响。     

矩形风管局部构件与直管段气溶胶粒子沉降速度比较分析

气溶胶是影响室内空气质量的重要因素之一,室外的气溶胶粒子通过风管系统进入室内,严重危害人们的健康.本文用滑石粉模拟气溶胶粒子,对矩形风管系统(材料为镀锌钢板)的直管段、渐缩段和风阀等3个位置,测定了气溶胶粒子在不同风速和粒径下的表面沉降速度,分析了它们之间的关系.结果表明,风管断面的沉降速度随风速和粒径的增加而增加;同一风管断面上底面的沉降速度最大,侧壁面次之,顶面最小;渐缩段底面、侧壁面和顶面的沉降速度均比直管段大,风阀断面的沉降速度明显高于直管段.研究表明,风管系统底面及局部构件是积尘的主要部位,也是风管系统清洗的重点.