深圳市综合水质指数研究及其在水资源资产评估上的应用

自然资源资产评估技术是开展自然资源资产负债表实践和实行环境责任离任审计的重要技术支撑。水资源作为一项重要自然资源,如何有效评估水资源资产是不可回避的问题。论文以深圳市为研究区域,一是采用综合污染指数法和主成分分析法,以总氮、氨氮、总磷、化学需氧量、生化需氧量、固体悬浮物为指标参数构建了深圳市综合水质指数以评价水资源综合水质。二是以该综合水质评估模型为基础,通过采用治污成本法分析综合水质与治污成本间的关系,从而构建深圳市景观水和饮用水资源的价值量评估模型。论文还以深圳市大鹏新区为试点开展了水资源价值量评估,评估结果显示,2015年大鹏新区景观水和饮用水资源的价值量分别为3.60亿、0.35亿元。     

Relationship between physicochemical properties and dewaterability of hydrothermal sludge derived from different source

Sewage sludge (SS) and deinking sludge (DS) were used to comparatively study the hydrothermal dewatering of sludge with different components. For a better overview, an insight into the relationship between physicochemical properties and dewaterability of hydrothermal sludge was provided. Results found that not all kinds of sludge were suitably conditioned by hydrothermal treatment (HT) in term of the elevation of dewaterability. Higher hydrothermal temperature tended to enhance the dewaterability of SS rather than DS, which was supported by the variation of their physicochemical properties (including water distribution, bonding energy, extracellular polymeric substance (EPS), particles size, acid functional groups and zeta potential in this study). In addition, the changes in surface morphology suggested that the reverse effect of HT on sludge dewaterability was mainly due to their dewatering behavior. For SS, the destruction of EPS structure leaded to the release of bound water, thereby strengthening sludge dewatering. Conversely, “Bridging effect” generated by lignocellulose in DS was beneficial for sludge dewatering; however, the increasing hydrothermal temperature degraded part of lignocellulose and weakened “bridging effect”, finally resulting in worse dewaterability of DS.     

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.     

地震安全性评价工作在城市建设中的重要作用

地震安全性评价工作在城市建设中起着非常重要的作用,为工程抗震提供精确的设计依据,提供科学合理的地震动参数,提出科学合理的设防要求,能够在一定程度上避免破坏性地震造成的损失,从而达到有效减灾的目的。     

ASM1中废水和污泥组分浓度的测定方法研究

对呼吸计量法应用于校准ASM1作了简明的阐述。在呼吸速率与模型组分关系的基础上,介绍了ASM1中废水与污泥各组分浓度的测定方法,并指出模型组分细化的意义。     

主成份分析法在大气环境质量综合评价中的应用

介绍了主成份分析法评价大气环境质量的基本原理，并对某市的大气环境质量进行了综合评价。最后，与其它方法的评价结果进行了对比分析，进一步证实了主成份分析法的科学性、合理性。     

水环境监测点位优化数学模型探讨

根据雨山湖的环境特征和水质状况,在加密监测获取更多的信息的基础上应用多元统计定量分析,选用主成份分析统计模式,用编制计算机程序处理数据,获得优化点数和确定点位.经可靠性检验证明优化方案完全能满足环境监测和环境管理的要求.     

影响北京地区土壤元素背景值的因素分析

用主成份分析研究了影响北京地区土壤元素背景值的主要因素。分析结果表明,影响土壤元素背景值的主要因素,在平原地区是地貌条件,在山区是成土母质。     

用主成分分析法研究评价地下水质量——以邯郸市为例

运用主成分分析法(PCA)对邯郸市地下水主要污染指标年均值进行了探索性评价研究。分析结果表明,前5个主成分综合携带了全部信息的91.374%。通过对这5个新的综合指标进行分析,确定了地下水的主要污染物,同时根据其综合得分对地下水进行分级,分析了其变化趋势,为地下水资源的有效利用和保护提供了科学依据。     

2019年西安首场雾霾PM2.5关键特征的综合诊断

通过对WRF-Chem（Weather Research and Forecasting Model Coupled to Chemistry）环境模式模拟资料、HYSPLIT（HYbrid Single Particle Lagrangian Integrated Trajectory Model）前/后向气团轨迹资料、环境站监测资料，以及西安理工大学（Xi''an University of Technology，简称XUT）多波长激光雷达、米散射激光雷达、能见度仪、粒谱仪等观测资料的综合诊断，探讨了2019年1月初发生在西安的雾霾过程（记为首场雾霾）PM_2.5组分、分布及传输特征，旨在为雾霾气溶胶研究提供有益的个例积累.定性、定量双重检验表明，Chem模式较成功复制了此次雾霾气溶胶过程.利用这些可靠的模式数据分析表明，PM_2.5中碳气溶胶的主要组分为有机碳，约占85%，强盛期气溶胶各组分随高度增加均呈递减趋势，各组分近地面浓度最高.通过对两类不同方法获取的消光系数对比分析表明，相比于模式数据，激光雷达数据具有更高的垂直分辨率，因此，更善于描述消光廓线的细节特征.通过对多源资料的综合诊断最终揭示出，"北风涌"是雾霾消散的关键影响因子，沿铜川-西安-山阳一带存在着污染物传输的重要路径，雾霾由此体现出自北向南依次消散的特征.