南昌市冬季大气PM2.5中重金属元素来源分析及健康风险评价

采集2015年南昌市冬季大气PM_(2.5)样品,利用电感耦合等离子体质谱仪(ICP-MS)测定样品中重金属(V、Mn、Cr、Co、Ni、Cu、Zn、Cd、Ba和Pb)的含量,分析重金属的分布特征和来源,并对重金属健康风险进行评价。结果表明:采样期间PM2.5浓度总平均值为(29.74±16.82)μg/m~3,其中省外办最高,武术学校最低;各重金属元素总体平均浓度从高到低次序为:ZnPbCuMnBaNiVCrCdCo。因子分析结果表明:PM_(2.5)中重金属元素的来源包括道路交通尘和冶金化工排放、机动车尾气以及混合源。健康风险评价结果显示:PM_(2.5)中Mn对人体健康存在非致癌风险,其他元素(Cr、Ba、Co、Pb、Cd、Cu、V、Zn、Ni)基本没有非致癌风险;Cr对人体有较明显的致癌风险,Cd、Ni和Co对部分年龄段的人群(尤其是成年人)存在一定的致癌风险。     

重庆九龙坡城区和城郊大气污染物浓度特征研究

为了解重庆市九龙坡区城区和城郊大气污染物浓度特征,分析了城区和城郊国控空气站点2014年3月~2015年2月典型污染物的浓度变化。结果表明,除O_3表现出夏高冬低的季节变化趋势外,其它污染物均表现出冬高夏低的季节变化趋势。PM_(2.5)污染最严重,城区和郊区日均值超标率分别为31.4%和33.4%。城区和城郊的PM_(2.5)浓度之间没有显著性差异(p0.05),城郊O_3浓度显著高于城区(p0.01),NO_2、SO_2、CO和PM_(10)则是城区显著高于城郊(p0.01)。     

环境因素对建筑工程造价的影响模型研究

现代建筑材料多数使用钢材、混凝土、木材等高能耗产品,这些材料在生产和运输的过程中会消耗较大的能量,对建筑绿色度和的影响非常大,同时也不利于降低工程预算。通过对建筑资源能源消耗和造价进行调查分析,并对建筑材料对建筑环境负荷影响和建筑工程造价进行了研究,提出基于环境因素设置的工程造价模型。通过实际操作发现,相对于传统的工程造价模型,该模型对工程造价的变化趋势反应的更为直观准确,可以大幅度提高工程造价工作的效率。     

基于环境生态发展视角的城市服务营销策略研究

城市服务营销策略的制定,依据城市环境分析、制定目标和细分市场、制定总体营销策略三大步骤完成。但在传统形势下,按照已制定的城市服务营销策略规划城市,对环境生态的发展造成了巨大影响。为有效解决此问题,通过分析不合理开发对城市服务营销策略的影响、工业三废问题对城市服务营销策略的影响、环境生态发展三要素对城市服务营销策略的影响,完成环境生态发展视角下,城市服务营销策略研究。得出减少城市内部的不合理开发、减少工业三废的排放量、重视环境生态发展三要素,是改进城市服务营销策略的有效方法。     

环保公益广告中污染防治意识接受度分析研究

环境保护和污染防治日益成为全球性重点关注问题,环境污染防治作为公益事业,也逐渐成为公众关心的热点,大量的环保公益广告进入人们的视线,在大众传媒时代,环保公益广告对提高人们的环境保护意识,形成环保和污染防治自觉具有重要促进性,分析环保公益广告中污染防治意识接受度,从公益广告的创作元素、人们的认知度和感官能力方面出发,弘扬绿色文明,倡导绿色观念,提高公众的污染防治意识。     

8-氨基喹啉-5-偶氮-对苯酚荧光光度法测定微量铬(Ⅵ)

在盐酸介质中,铬(Ⅵ)与AQAPOH形成可被氯仿萃取的荧光化合物,其λex/λem=295nm/400nm.线性范围为0-1.0μg Cr(Ⅵ)/25ml(水相),检测限为0.7μg/L.除Mn(Ⅶ)外,常见金属离子无干扰,可在数千倍Cr(Ⅲ)存在下测定废水中微量铬(Ⅵ).初步探讨了荧光反应的机理.     

浅谈烟道气现场监测的工作管理

烟道气现场监测，易出差错。监测人员必须有良好的专业理论水平、丰富的工作经验、高度的敬业精神。本文就现场监测工作易出现问题进行了分析，列举了解决问题的方法     

有关有限边界岸边排放稳态二维混合模式的几个问题的探讨

针对目前我国环境影响评价领域普遍采用的有限边界岸边排放稳态二维混合模式的局限性和不精确性，本文对由河流二维稳态水质模型的基本方程推求出的有限边界岸边排放的二维稳态混合模式的解析解的各项进行分析比较。同时针对费休的混合长度公式进行了计算比较。     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Determination of organophosphorus pesticides and related compounds in water samples by membrane extraction and gas chromatography

A membrane extraction-gas chromatography method was developed fordetermination of organophosphorus pesticides and related compounds including methamidophos, DDVP, dimethoate, methyl parathion, parathion, thiophosphoric acid trimethyl ester, and thiophosphoramidic acid dimethyl ester in water samples. In thismethod, surface-modified acetic cellulose membranes were used to extract the target analytes in water samples, the extracted analytes were back-extracted into a small amount of methanol, andgas chromatography with pulsed flame photometric detector (GC-PFPD) was used to determine the concentrations of targetanalytes in the extracts. The recoveries obtained for thetarget analytes spiked into the water samples ranged from 66to 94%. The method detection limit for each target analyte was 0.05 g L^-1. The method developed in this study had shown the advantages of being cheap, simple, fast, and reliable. It had been used successfully to determine the concentrations of target analytes in river water samples.