Risk-Based Prioritization of Air Pollution Monitoring Using Fuzzy Synthetic Evaluation Technique

Air pollution monitoring programs aim to monitor pollutants and their probable adverse effects at various locations over concerned area. Either sensitivity of receptors/location or concentration of pollutants is used for prioritizing the monitoring locations. The exposure-based approach prioritizes the monitoring locations based on population density and/or location sensitivity. The hazard-based approach prioritizes the monitoring locations using intensity (concentrations) of air pollutants at various locations. Exposure and hazard-based approaches focus on frequency (probability of occurrence) and potential hazard (consequence of damage), respectively. Adverse effects should be measured only if receptors are exposed to these air pollutants. The existing methods of monitoring location prioritization do not consider both factors (hazard and exposure) at a time. Towards this, a risk-based approach has been proposed which combines both factors: exposure frequency (probability of occurrence/exposure) and potential hazard (consequence).This paper discusses the use of fuzzy synthetic evaluation technique in risk computation and prioritization of air pollution monitoring locations. To demonstrate the application, common air pollutants like CO, NO_x, PM₁₀ and SO_x are used as hazard parameters. Fuzzy evaluation matrices for hazard parameters are established for different locations in the area. Similarly, fuzzy evaluation matrices for exposure parameters: population density, location and population sensitivity are also developed. Subsequently, fuzzy risk is determined at these locations using fuzzy compositional rules. Finally, these locations are prioritized based on defuzzified risk (crisp value of risk, defined as risk score) and the five most important monitoring locations are identified (out of 35 potential locations). These locations differ from the existing monitoring locations.     

A Spatial Model to Estimate Habitat Fragmentation and Its Consequences on Long-Term Persistence of Animal Populations

The increasing use of the landscape by humans has led to important diminutions of natural surfaces. The remaining patches of wild habitat are small and isolated from each other among a matrix of inhospitable land-uses. This habitat fragmentation, by disabling population movements and stopping their spread to new habitats, is a major threat to the survival of numerous plant and animal species. We developed a general model, adaptable for specific species, capable of identifying suitable habitat patches within fragmented landscapes and investigating the capacity of populations to move between these patches. This approach combines GIS analysis of a landscape, with spatial dynamic modeling. Suitable habitat is identified using a threshold area to perimeter ratio. Potential movement pathways of species between habitat patches are modeled using a cellular automaton. Habitat connectivity is estimated by overlaying habitat patches with movement pathways. The maximum potential population is calculated within and between connected habitat patches and potential risk of inbreeding within meta-populations is considered. The model was tested on a sample map and applied to scenario maps of predicted land-use change in the Peoria Tri-county region (IL). It (1) showed area of natural area alone was insufficient to estimate the consequences on animal populations; (2) underscored the necessity to use approaches investigating the effect of land-use change spatially through the landscape and the importance of considering species-specific life history characteristics; and (3) highlighted the model's potential utility as an indicator of species likelihood to be affected negatively by land-use scenarios and therefore requiring detailed investigation.     

汉江水质评价的化学计量学研究

运用因子分析法对汉江各主要水质断面进行水质因子分析及综合评价,通过各主因子的方差贡献及因子得分得出各水质因子的赋权值,从而对所取断面进行水质污染程度的综合评价、分析与排序。同时运用聚类分析法对汉江17个断面的水质污染相似性进行分析,给出分类处理结果。     

B-P网络应用于地下水水质监测点优选

以地下水水质评价分级标准作为训练样本,构造B-P网络模型对其进行训练,用训练好的B-P网络对某地的地下水水质监测点进行评判、优选。并与其它方法的结果进行比较,结果表明,B-P网络用于环境测点优选不仅原理直观,而且具有较好的客观性和实用性。     

低浓度石油类监测与评价的问题探讨

分析表明,当地表水中石油类浓度很低时,受多方面因素影响,其监测结果的准确性和评价结论的可靠性会下降,应选用合适的监测方法,同时要注意引入污染问题。     

The Monitoring and Risk Assessment of Zn Deposition Around a Metal Smelter in Latvia

Heavy metal concentrations in Hylocomium splendens collected around a metal smelter in Latvia showed very high concentrations of Zn (>200 g/g), and elevated concentrations of Pb (38.3 g/g) and Cu (18.3 g/g). In an attempt to better evaluate the potential toxicity of the high Zn concentrations, a serial elution method was used to determine the concentrations of zinc in intercellular, extracellular exchangeable cell wall, intracellular, and particle fractions. The intercellular Zn concentrations represent the water soluble component of the total concentrations, and were low with no clear trends. Zn concentrations in the extra- and intracellular and particle fractions decreased exponentially from the pollutant source. Intracellular Zn concentrations in moss close to the emission source are within the range considered to be potentially toxic, from other single element exposure studies. The proportion of Zn in the relatively insoluble particle fraction, which is least associated with environmental risk, was greater closer to the pollution source, reaching > 30% in the oldest Hylocomium splendens segments.     

环境污染纠纷调处与环境行政处罚之区别浅析——兼与章锦华同志商榷

指出了环境污染纠纷调处与环境行政处罚的性质，程序，结果等均不相同，在理论上不能将两者混一谈，实践中应区别对待。     

关于模糊数学在环境质量综合评判中“最大隶属度”原则不适用性的讨论

通过对模糊数学在环境质量综合评判中的分析，指出“最大隶属度”原则的不适用性，并根据环境质量分级所存在的固有关系提出改进的方法。     

Euclidean贴近度水质评价法及其应用

分析了模糊综合评判在水质评价中的缺陷,将模糊数学中的贴近度与经典的Euclidean距离结合,提出Euclidean贴近度水质评价法。结果表明,该评价方法具有科学性、合理性,并且精度高,简单实用。     

灰色模型在确定关键污染因子中的应用

将灰色模型引入水环境质量评价中 ,通过对某个时间段内污染物原始监测数据的灰色处理 ,从动态演变中找出关键因子 ,客观地判定各污染因子所起的作用 ,并对各因子在下一个时间段的发展趋势作出判断 ,增加了评价的准确性。经过实例运用分析表明 ,该方法物理意义明确 ,简便易用