东亚大气可吸入颗粒物时空分布的数值模拟研究

利用嵌套网格空气质量模式(Nested Air Quality Prediction Model System,NAQPMS)模拟研究了2010年东亚地区可吸入颗粒物(PM10)的时空演变,并初步评估了其对人群健康的危险度.结果表明,NAQPMS模式能够合理地反映东亚地区PM10的时空分布,不同季节观测值和模拟值的总体相关系数达到0.65~0.85.2010年东亚PM10的地面浓度高值区(100μg·m-3)出现在我国华北、华中和内蒙古中西部等地区.其中,无机盐(硫酸盐、硝酸盐和铵盐)对我国东部PM10的贡献最大(10~70μg·m-3,20%~50%);一次PM10次之(5~50μg·m-3,10%~30%),有机物(5~30μg·m-3,10%~20%)和黑炭(3~20μg·m-3,3%~5%)紧随其后.PM10可以引起我国东部人群急性总死亡率增加2%~5%,对我国居民的健康水平构成了一定威胁.     

城市环境总体规划中大气环境红线内涵及划定技术

城市环境总体规划是一项重大环境管理制度创新,目前全国已启动了24个城市的环境总体规划编制工作,其中划定环境红线是城市环境总体规划的核心内容。本文结合福州、宜昌、平潭等城市环境总体规划编制实践,首次提出了大气环境红线的技术框架,将大气环境红线划分为源头布局敏感区、污染易聚集区及敏感的环境受体三类,并创新性建立了大气环境红线划定技术方法,初步构建了适用于城市环境总体规划的空间规划技术体系。     

克山县空气质量及变化趋势

通过对克山县2003—2012年的空气监测数据分析,二氧化硫和总悬浮物颗粒物呈下降趋势,氮氧化物和降尘浓度变化不大;尘类是影响环境质量的主要污染物,县区环境空气质量呈轻度污染,根据各年度的监测数据来看,环境空气质量逐年得到改善。     

石溪水库水环境容量研究

分析了江西宜春石溪水库的水环境状况,运用沃伦威德尔模型和狄龙模型等水库水环境容量计算方法,对石溪水库COD Mn、NH 3-N、TN、TP的水环境容量进行了计算。结果表明:石溪水库2012年水质为Ⅳ类,营养状态为中营养,入库的污染物量超出其自净能力。将水环境容量按照Ⅲ类和Ⅱ类水标准分为近期目标和远期目标,按近期目标CODM n、NH 3-N、TN、TP的超标率分别为7.6%、86.1%、121.1%、40.7%。在此基础上,分析了石溪水库水污染原因,提出了水污染控制方案。     

便携β射线法手工监测PM_(2.5)的可行性研究

提出利用自动射线原理结合重量法的简捷便携特点的便携射线仪手工监测PM2.5的思路,平行比对了便携射线法和手工重量法所测60组PM2.5浓度的监测结果,采用线性回归及T检验、F检验等理论分析了两者数据结果间的有效性和可比性。结果表明,便携式射线仪监测结果与重量法监测结果之间有效可比且得到了两者间的线性回归方程;此外进行了20组数据的实样验证,换算值和真值之间相对误差在8%以内,因而确定了便携射线仪手工监测PM2.5的可行性。     

丹东生态环境监测业务系统设计与实现

丹东生态环境监测业务系统是用于生态环境监测日常业务观测,编制各类观测报文及数据上网传输的实用型业务系统。系统采取多窗157结构框架,合理布局功能窗口界面,兼容了地面气象观测数据文件格式,统一数据检查标准,观测数据处理更为准确有效。并以VB6．0可视化语言为开发工具适应不用版本Windows操作系统。基于生态环境监测数据统计、数据分析和数据发布为一体的多功能业务应用软件。     

内蒙古自治区机动车尾气污染监控体系初探

随着机动车大量开始进入普通家庭,内蒙古自治区机动车保有量快速增长,使得机动车排气污染已经成为城市大气污染的重要来源。因此,开展在用机动 车排气污染防治工作,建立切实有效的机动车排气污染监控体系刻不容缓。本文对内蒙古自治区在用机动车排气污染监控体系和保障好保障体系建设内容进行了初探。     

Assessment of the clear-sky bias issue using continuous PM10 data from two AERONET sites in Korea

A bias in clear-sky conditions that will be involved in estimating particulate matter(PM)concentration from aerosol optical depth(AOD) was examined using PM_(10) from two Aerosol Robotic Network sites in Korea. The study periods were between 2004 and 2007 at Anmyon and between 2003 and 2011 at Gosan, when both PM_(10) and AOD were available. Mean PM_(10) when AOD was available(PM AOD) was higher than that from all PM_(10)data(PM all) by 5.1 and9.9 μg/m~3 at Anmyon and Gosan, which accounted for 11% and 26% of PM all, respectively.Because of a difference between mean PM_(10) under daytime clear-sky conditions(PM clear)and PM AOD, the variations in ΔPM_(10), the difference of PM all from PM clear rather than from PM AOD, were investigated. Although monthly variations in ΔPM_(10)at the two sites were different, they were positively correlated to those in ΔT, similarly defined as ΔPM_(10)except for temperature, at both sites. ΔPM_(10)at Anmyon decreased to a negative value in January due to an influence of the Siberian continental high-pressure system while ΔPM_(10)at Gosan was high in winter due to an effect of photochemical production at higher temperatures than at Anmyon.     

基于环境质量管理的城市综合环境绩效评估研究

文章以26个省会城市2004~2013年的样本数据,从环境健康、生态保护、资源与能源利用、环境治理等4个方面开展研究,构建了包括4项二级指标、12项三级指标和26项四级指标在内的城市综合环境绩效指标体系。研究发现,大部分城市的综合环境绩效历年差异明显,东、中、西部的环境绩效有明显的差异。因此,文章认为应该进一步优化环境绩效指标体系,充分体现区域差异特点,通过实施城市综合环境绩效考核来提高城市环境质量管理水平。     

Modelling and Prediction of Diesel Engine Performance using Relevance Vector Machine

Diesel engines are being increasingly adopted by many car manufacturers today, yet no exact mathematical diesel engine model exists due to its highly nonlinear nature. In the current literature, black-box identification has been widely used for diesel engine modelling and many artificial neural network (ANN) based models have been developed. However, ANN has many drawbacks such as multiple local minima, user burden on selection of optimal network structure, large training data size, and over-fitting risk. To overcome these drawbacks, this article proposes to apply an emerging machine learning technique, relevance vector machine (RVM), to model and predict the diesel engine performance. The property of global optimal solution of RVM allows the model to be trained using only a few experimental data sets. In this study, the inputs of the model are engine speed, load, and cooling water temperature, while the output parameters are the brake-specific fuel consumption and the amount of exhaust emissions like nitrogen oxides and carbon dioxide. Experimental results show that the model accuracy is satisfactory even the training data is scarce. Moreover, the model accuracy is compared with that using typical ANN. Evaluation results also show that RVM is superior to typical ANN approach.