丹东市二氧化硫叠加模式的研制及应用

采用《制定地方大气污染物排放标准的技术方法》(GB/T 3840-1991)中的高斯模式作为大气污染物地面浓度基本公式,计算丹东市区内任一点位上的点源排放SO2在下风向网格交叉点上的叠加浓度.采用点到直线的距离公式计算垂直于平均风向的水平横向距离和下风向距离,以丹东市采暖锅炉排放SO,为例计算多点源网格落地浓度.     

空气污染指数简易计算方法

环境空气质量周报、日报、预报均采用空气污染指数 (ＡＰＩ)的形式报告 ,而空气污染指数的计算方法 ,是由各污染物的实测浓度值按照分段线性方程计算 ,涉及到各空气污染物的标准浓度限值 ,计算公式繁琐 ,费时费力。今结合实践 ,由原空气污染指数计算方法推导出一组简易计算公式 ,此简易算式与原计算方法等效 ,供参考。1　简易计算法1 1　计算公式由于空气污染指数中 5 0、1 0 0、2 0 0分别对应于我国环境空气质量标准中日均值的一、二、三级标准的污染物浓度限值 ,对应的环境空气质量等级分别为优、良、轻度污染 ,同时考虑到总悬浮颗粒物在…     

聊城市春季交通源大气污染特征分析

为研究交通源空气污染状况，通过采用自动监测系统，于2009年春季期间，对在聊城市主干道附近布设的6个监测点的空气质量进行监测，获得了其空气污染物浓度特征：（1）所有监测点SO2、NOx日均值与O3小时均值均未超标，且O3污染指数很低，表明二次污染甚微；（2）CO是首要污染物，PM10次之，两者日均值超标率均为100％。分析了超标污染物与交通流量的关系，结果表明，PM10浓度与交通量有较高的线性相关性，而CO浓度与交通流量无显著相关性。     

关于废水中污染物浓度日均值的思考

在环境污染防治工作从污染物浓度控制逐步向排污总量控制转变的过渡阶段 ,污染物浓度日均值仍然发挥着十分重要的作用。文章阐述了日均值的监测时段、监测频率及计算方法等技术要求 ,并结合排污总量监测 ,提出了一些建议     

中国中东部一次大范围重污染过程特征分析

采用嵌套网格空气质量预报模式(NAQPMS)模拟与气象、污染物观测资料相结合的方式,分析了2016年12月影响中国中东部地区的一次重污染过程中PM_(2.5)时空分布特征及来源成因。结果表明,重污染过程中PM_(2.5)具有较明显的时空变化规律,污染呈现一定程度的区域性分布特点,不同地理位置条件下,污染物浓度的累积和传输方式表现出不同的特征,细颗粒物快速二次生成及不利扩散条件下的持续积累可能是此次污染过程的主要原因,不利于污染物扩散的高低空天气形势的配合抑制了污染物的快速消散,为大气污染的形成及维持提供了稳定的大气环境背景,形成了此次污染过程污染浓度高、影响范围大的态势。     

关于废水中污染物浓度日均值的思考

在环境污染防治工作从污染物浓度控制逐步向排污总量控制转变的过渡阶段中，污染物浓度日均值仍然发挥着十分重要的作用，文中阐述了日均值的监测时段、监测频率及计算方法等技术要求，并结合排污总量监测、提出了一些建议。     

获取日均值的大气监测时段选择

利用数理统计方法，以污染物瞬时监测数据为基础数据，选用控制在一定置信度下最大允许误差的统计公式确定出样本容量，并采用模糊集合运算—优化组合选择法，确定出获取日均值的最佳监测时段．     

基于GIS的唐山地区大气污染物时空分布研究

应用数据统计和ArcGIS对北方重工业城市唐山地区2014年14个县(区)18个空气自动监测站的数据进行时空分布特征分析,监测的污染物为PM_(10)、SO_2、NO_2、PM_(2.5)、O_3、CO共6项。利用ArcGIS对各个自动监测站污染物数据建立网格模型,采用反距离权重法分别对年均、采暖期、非采暖期的环境空气质量综合指数和6项污染因子浓度的空间分布进行估算,直观比较了污染物在不同时期内的空间分布状况。结果表明,空气质量时间分布较为明显,非采暖期明显好于采暖期。同时,计算出每个网格单元污染指数的标准偏差,结合气象气候、地形地势、工业发展等情况,分析得出北部山区、市中心区附近区域空气质量波动较大。为区域大气污染有针对性的综合防治、联防联控及污染物区域削减计划打下数据基础。     

获取日均值的大气监测时段选择

利用数理统计方法，以污染物瞬时监测数据为基础数据，选用控制在一定置信度下最大允许误差的统计公式确定出样本容量，并采用模糊集合集──优化组合选择法，确定出获取日均值的最佳监测时段。     

2016年秋季新乡市空气质量模式预报效果评估

基于新乡市空气质量数值预报平台，采用相关系数（r）、标准化平均偏差（NMB）等统计指标，系统评估2016年秋季新乡市嵌套网格空气质量预报模式（NAQPMS）和通用多尺度空气质量模式（CMAQ）的预报效果，对比分析2套模式不同预报时效和不同水平分辨率的空气质量等级预报准确率。结果显示：2套模式均较好地表征了各主要污染物的浓度变化特征，2套模式的等级预报准确率高于60%，其中CMAQ对中度及重度的预报等级准确率达到70%。对比模式24、48、72 h 3种预报时效效果，24 h预报时效的统计数据最优，说明24 h预报时效模拟结果可作为业务预报重要的支撑。     

Evaluation of the best compromise between the urban air quality monitoring resolution by diffusive sampling and resource requirements

The need to collect data representative of overall urban pollution is all-important in order to monitor the population exposure. High spatial resolution monitoring using diffusive samplers allows studying of the urban pollutant distribution, thus enabling deeper investigation of their generation and diffusion mechanisms. Nevertheless, such a monitoring campaign has a certain cost. In this study we point out how to find the best compromise between the number of necessary measurements and the affordable costs for monitoring campaigns. We also describe an innovative method for the proper design of a fixed urban monitoring network by means of preliminary high spatial resolution campaigns using diffusive samplers. Four European capital cities (Dublin, Madrid, Paris and Rome) were monitored six times, each time for seven days. Benzene, toluene, ethylbenzene, xylenes (BTEX) and NO(2) concentrations were measured at 146 sites in Dublin, 293 in Madrid, 339 in Paris and 290 in Rome. Multiscale grids have been drawn which ranged in mesh size from 500 m to 2 km. The statistical processing of data produced a twofold result: the creation of isoconcentration maps with geostatistical procedures, and an algorithm aimed at locating the minimum number of sampling sites where the fixed monitoring stations should be placed. Average urban levels estimated on the basis of these selected sites differ by less than 8% from those calculated on the whole populations of the sampled points. The aim of this work is to investigate how far the resolution of a monitoring campaign of urban pollution by diffusive sampling can be reduced, thus making the monitoring less expensive in terms of human and financial resources, while preserving the same quality of the results that could be achieved with a higher resolution. We found that there is no significant loss of information when the resolution of the monitoring grid for BTEX is lowered to a mesh size of 1.85 km, that is a sampling site each 3.4 km(2), and that the minimum number of sampling sites to be used is N = 0.29 A, where A is the urban surface to be monitored (in km(2)). As the spatial distribution of NO(2) is less sensitive to the distance from the emission source than that of BTEX, this relationship could be retained as a valid lower limit for the mesh grid size also for NO(2) monitoring.     

A Method for Locating Influential Pollution Sources and Estimating Their Contributions

This work develops a source-oriented approach to locate the influential pollution sources and estimate their contributions to pollutant concentrations observed at a receptor site. The domain containing possible influential pollution sources is divided into systematic grid cells, and the influential grid sources are determined based on the locations of the segment endpoints of air trajectories arriving at the receptors. The contribution of each grid source is initially calculated using a formula derived from a Lagrangian box model and including the effects of source emissions, atmospheric dilution, and chemical transformation and deposition. The formula is described in detail in this study. Finally, the average contribution of each grid source is determined based on numerous analyzed events. The proposed approach was used to locate influential pollution sources and determine their contributions to a rural monitoring station during periods of high SO₂ pollution in southern Taiwan. The contributions of sources in various 2 km by 2 km grid cells, five districts, three source categories, 8 industrial areas, and a power plant were evaluated. The results show that the major influential sources were in the northwestern region of south Taiwan, and belonged to three district and point sources. Furthermore, two industrial areas close to the evaluated stations were also very significant, and contributed about 30% of the total pollution.     

An urban observatory for quantifying phosphorus and suspended solid loads in combined natural and stormwater conveyances

Water quality in urban streams and stormwater systems is highly dynamic, both spatially and temporally, and can change drastically during storm events. Infrequent grab samples commonly collected for estimating pollutant loadings are insufficient to characterize water quality in many urban water systems. In situ water quality measurements are being used as surrogates for continuous pollutant load estimates; however, relatively few studies have tested the validity of surrogate indicators in urban stormwater conveyances. In this paper, we describe an observatory aimed at demonstrating the infrastructure required for surrogate monitoring in urban water systems and for capturing the dynamic behavior of stormwater-driven pollutant loads. We describe the instrumentation of multiple, autonomous water quality and quantity monitoring sites within an urban observatory. We also describe smart and adaptive sampling procedures implemented to improve data collection for developing surrogate relationships and for capturing the temporal and spatial variability of pollutant loading events in urban watersheds. Results show that the observatory is able to capture short-duration storm events within multiple catchments and, through inter-site communication, sampling efforts can be synchronized across multiple monitoring sites.     

黄河中上游能源化工区大气污染跨界环境影响分析

对黄河中上游能源化工区近地面和边界层顶气象流场及该区域大气污染长距离输送产生的跨界环境影响趋势特征进行了分析。结果表明,该区域近地面和边界层顶的流场总体上为西北向东南流动,大气污染物长距离输送可能影响的区域主要为华中地区;区域冷空气的活动对其大气污染物的清除起重要作用;通过CALPUFF模型的模拟结果表明,该区域SO2的影响程度和范围明显大于NO2,在区域内部存在污染物浓度较高的区域,但未对区外造成显著跨界环境影响。     

多介质模型在海湾突发性有机污染中的应用及案例分析

为弥补海洋环境监测能力不足,利用受潮汐动力控制海湾中的多介质模型,预测突发性污染发生后海洋环境中污染物的浓度变化信息,并对突发性污染物的迁移转化进行了计算.模型中使用逸度方法和质量平衡算法,预测非挥发性有机物在水、沉积物和鱼中的浓度.在象山港的应用结果表明,该模型可较快速地给出污染物在不同介质中的浓度变化信息,为环境监...     

监测数据法在工业污染核算中的若干问题探讨

简述了监测数据法应用于污染核算的工作流程.指出了监测数据法使用中监测数据本身、环境统计中以及动态更新中监测数据使用存在的主要问题,提出了应加强监测管理、钻研监测技术,提升监测数据质量,为污染核算奠定基础;修订、完善监测数据法的相关技术规定并督促严格执行;正确处理监测数据,从技术层面改进污染核算质量;加强监测数据法核算的...     

基于AGNES算法优化BP神经网络和GIS系统的大气污染物浓度预测

建立了大气污染物浓度与影响因子之间的BP神经网络,对城市中各监测点位的次日大气污染物浓度进行预测,采用GIS的插值分析进行污染物空间分布预测,其中BP神经网络的输入向量采用AGNES算法进行处理。以太原市区SO2、PM10浓度预测为例,选择气温、湿度、降水量、大气压强、风速和前5天的污染物浓度等10个参数训练BP神经网络,结果表明,BP神经网络的训练效果较好,预测结果与实际浓度显著相关,R2分别为0.988、0.976;结合太原市8个监测点位的污染物浓度预测值,运用GIS空间差值法绘出SO2、PM10的浓度分布预测图,该图与实际情况大体符合,并且与国控大气污染企业的分布显著相关,Pearson相关系数分别为0.969、0.949。     

水污染源源解析研究最新进展

采取有效措施监测监管污染物排放是实现污染减排目标的必要条件,而准确掌握流域内污染物的来源是实现污染源有效监管的技术依据,文章对水污染源源解析目标化合物选取、污染物扩散模型研究和污染区域受体模型研究的最新进展进行了评述,对其发展趋势进行了展望.     

Nonpoint Source Pollution Assessment of Wujiang RiverWatershed in Guizhou Province,SW China

The amount of pollution from nonpoint sources flowing in the streams of the Wujiang River watershed in Guizhou Province, SW China, is estimated by a geographic information system (GIS)-based method using rainfall, surface runoff and land use data. A grid of cells of 100 m in size is laid over the landscape. For each cell, mean annual surface runoff is estimated from rainfall and percent land use, and expected pollutant concentration is estimated from land use. The product of surface runoff and concentration gives expected pollutant loading from that cell. These loadings are accumulated going downstream to give the expected annual pollutant loadings in streams and rivers. By dividing these accumulated loadings by the similarly accumulated mean annual surface runoff, the expected pollutant concentration from nonpoint sources is determined for each location in a stream or river. Observed pollutant concentrations in the watershed are averaged at each sample point and compared to the expected concentrations at the same locations determined from the grid cell model. In general, annual nonpoint source nutrient loadings in the Wujiang River watershed are seen to be predominantly from the agricultural and meadow areas. The total annual loadings through the outlet of the watershed are 40,309 and 2,607 tons for total nitrogen (TN) and total phosphorus (TP), respectively.