Long-term effects of sliver nanoparticles on the abundance and activity of soil microbiome

正Silver nanoparticles(Ag NPs)are among the most extensively used engineered nanomaterials because of their wellestablished antimicrobial and unique physicochemical properties(Yin et al.,2015).Applications of AgNPs have now been     

广东省生活垃圾焚烧设施环境与健康风险评估构架研究

生活垃圾焚烧设施的建立是解决城市生活垃圾逐年增多的有效方式之一,但其所引发的环境与健康问题成为公众关注的热点。基于广东省对生活垃圾焚烧设施的研究,以环境管理为目标,结合国内外在该领域的研究现状,提出广东省生活垃圾焚烧设施环境与健康风险评估构架。通过该构架的多年实践,总结了广东省生活垃圾焚烧设施环境与健康风险评估研究所取得的成效,有望将该成果推而广之,从而使该行业实现绿色生态的蓬勃发展。     

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。     

大型电力企业污染治理型营销策略研究

大型电力企业是国家发展电力需要重要扶持的企业。在大型电力企业电源结构中,火力发电占据重要地位,消耗煤炭的同时,会产生固体污染和废气污染,影响生态环境。为此,在提高大型电力企业完成电能输出的同时,需实现对环境的保护,提出对大型电力企业污染治理型营销策略进行研究。通过分析大型电力企业发展的生态环境、经济环境和行业发展环境,总结大型电力企业营销外部环境现状。考虑火力发电在电源结构中的地位以及对环境造成的污染,提出设计火力发电以外的电源结构,实现大型发电企业污染治理型营销策略提出与研究。     

吉林省秸秆打包减排及综合利用分析研究

为量化秸秆打包政策对防控大气污染的影响,基于吉林省2016年秸秆产量、秸秆打包地亩数、卫星火点数据以及大气污染物浓度的变化,对吉林省秸秆打包产生的大气环境及社会经济效益进行了分析,结果表明:1)吉林省打包秸秆量为220.36×10~4t,约占秸秆年产量的5.5%,假如全部加工成生物质颗粒燃料,2016年至少减少14.54×10~4t污染物排放;2)吉林省秸秆打包政策执行以来,秸秆露天燃烧量及秸秆燃烧主要月份的卫星火点数显著下降;3)随着露天燃烧量的减少,区域大气颗粒物浓度降低,空气质量改善。秸秆燃烧主要月份的PM_(2.5)和PM_(10)浓度从2014年的104.5μg·m~(-3)、164μg·m~(-3)分别下降到2016年的48.5μg·m~(-3)、69·μg·m~(-3)。研究结果可为吉林省有效减少污染物排放、综合利用农作物秸秆、改善大气环境质量等提供科技支撑。     

发光细菌生物毒性抑制率优化研究

发光细菌生物毒对水生生态环境有极大的破坏作用,为保护水体环境,提出发光细菌生物毒性抑制率优化研究。完成测试样品调制;设置菌悬液特征参数,利用pH、RLU及D600进行同步检测,完成发光细菌生物毒性重现;分析磺胺类药品于根际土壤的形态分布和生态毒性,完成发光细菌生物毒性抑制率优化研究。实验证明,三种磺胺类药品对发光细菌生物毒性的相对抑制率都小于30%,为低毒性;其中有机溶剂对发光细菌生物毒性的抑制率最大,水溶态较大,结合态最小。     

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     

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.