A framework for assessing the impact of land use policy on community exposure to air toxics

Our research focuses on the linkage between land use planning policy and the spatial pattern of exposure to air toxics emissions. Our objective is to develop a modeling framework for assessment of the community health risk implications of land use policy. The modeling framework is not intended to be a regulatory tool for small-scale land use decisions, but a long-range planning tool to assess the community health risk implications of alternative land use scenarios at a regional or subregional scale. This paper describes the development and application of an air toxic source model for generating aggregate emission factors for industrial and commercial zoning districts as a function of permitted uses. To address the uncertainty of estimating air toxics emission rates for planned general land use or zoning districts, the source model uses an emissions probability mass function that weights each incremental permitted land use activity by the likelihood of occurrence. We thus reduce the uncertainty involved in planning for development with no prior knowledge of the specific industries that may locate within the land use district. These air toxics emission factors can then be used to estimate pollutant atmospheric mass flux from land use zoning districts, which can then be input to air dispersion and human health risk assessment models to simulate the spatial pattern of air toxics exposure risk. The model database was constructed using the California Air Toxics Inventory, 1997 US Economic Census, and land assessment records from several California counties. The database contains information on more than 200 air toxics at the 2-digit Standard Industrial Classification (SIC) level. We present a case study to illustrate application of the model. LUAIRTOX, the interactive spreadsheet model that applies our methodology to the California data, is available at http://www2.bren.ucsb.edu/~mwillis/LUAIRTOX.htm.     

矿区地下水环境影响评价的关键问题探讨

随着人类社会经济的快速发展,地下水环境问题日益严重,由于地下水环境影响具有隐蔽性和滞后性,在矿区建设生产前必须对地下水环境影响进行评价。结合某拟建整合灰岩矿的地下水环境影响评价,进行了实例分析,确定了保护目标、地下水环境影响识别、矿坑涌水量的计算、预测评价方法的选取等关键技术,以期为相似矿区地下水环境影响评价提供参考。     

环境风险评价简介

本文介绍了环境风险评价的内容，方法，现状及发展趋势，并着重介绍了该类评价中污染物对人体健康危害的评价方法。     

Estimating Watershed Level Nonagricultural Pesticide Use From Golf Courses Using Geospatial Methods1

Abstract: Limited information exists on pesticide use for nonagricultural purposes, making it difficult to estimate pesticide loadings from nonagricultural sources to surface water and to conduct environmental risk assessments. A method was developed to estimate the amount of pesticide use on recreational turf grasses, specifically golf course turf grasses, for watersheds located throughout the conterminous United States (U.S.). The approach estimates pesticide use: (1) based on the area of recreational turf grasses (used as a surrogate for turf associated with golf courses) within the watershed, which was derived from maps of land cover, and (2) from data on the location and average treatable area of golf courses. The area of golf course turf grasses determined from these two methods was used to calculate the percentage of each watershed planted in golf course turf grass (percent crop area, or PCA). Turf‐grass PCAs derived from the two methods were used with recommended application rates provided on pesticide labels to estimate total pesticide use on recreational turf within 1,606 watersheds associated with surface‐water sources of drinking water. These pesticide use estimates made from label rates and PCAs were compared to use estimates from industry sales data on the amount of each pesticide sold for use within the watershed. The PCAs derived from the land‐cover data had an average value of 0.4% of a watershed with minimum of 0.01% and a maximum of 9.8%, whereas the PCA values that are based on the number of golf courses in a watershed had an average of 0.3% of a watershed with a minimum of <0.01% and a maximum of 14.2%. Both the land‐cover method and the number of golf courses method produced similar PCA distributions, suggesting that either technique may be used to provide a PCA estimate for recreational turf. The average and maximum PCAs generally correlated to watershed size, with the highest PCAs estimated for small watersheds. Using watershed specific PCAs, combined with label rates, resulted in greater than two orders of magnitude over‐estimation of the pesticide use compared to estimates from sales data.     

限制开发生态区生态风险评价--以宁夏同心县为例

采用实地考察与统计分析相结合的方法,运用PSR模型、主成分分析法和K-means聚类分析法计算生态风险度,研究限制开发生态区同心县生态环境状况。结果显示:2006—2015年的同心县生态风险度总体趋高,生态安全问题突出。     

Comparison of Stream Invertebrate Response Models for Bioassessment Metrics1

Waite, Ian R., Jonathan G. Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, and James L. Orlando, 2012. Comparison of Stream Invertebrate Response Models for Bioassessment Metrics. Journal of the American Water Resources Association (JAWRA) 48(3): 570-583. DOI: 10.1111/j.1752-1688.2011.00632.x Abstract: We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R² from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R² values than RICHTOL for the two regions tested. Modeled O/E R² values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.     

Treatment of risk in environmental impact assessment

Risk assessment and environmental impact assessment have developed as separate traditions. While environmental impact assessment is a broad field that includes all activities that attempt to analyze and evaluate the effects of human and related actions on the environment, risk assessment has been concerned with the relatively well-defined regulatory problems and employs formal quantitative analysis of the probability of specific undesired events, such as cancer. Risk analytic approaches, particularly the explicit treatment of uncertainty, can significantly contribute to environmental assessments. This article discusses the type and sources of uncertainty in environmental assessments, techniques for their quantification, and ways to use uncertainty estimates to calculate probabilities of effects or probabilities of exceeding environmental standards and to determine the need for mitigation or additional research.This article was presented at the International Institute of Applied Systems Analysis, Task Force Meeting on Risk and Policy Analysis under Conditions of Uncertainty, Laxenburg, Austria, November 1985.     

城市总体规划环评指标体系的建立及其应用

本研究首先介绍了DPSIR模型构建的原理,接着以合肥市为对象,从驱动力、压力、状态、影响、响应5个方面来构建的共36个指标,并采用层次分析法对指标权重的确定和多级灰色关联分析对指标进行综合评价,得出评价结果。合肥市在2004~2005年处于较低可持续发展水平(0.3398、0.3876)、在2010年处于中等可持续发展水平(0.5369)、在2015年处于较高可持续发展水平(0.6016)、在2020年处于较高可持续发展水平(0.7847),该预测评价结果与合肥市城市可持续发展趋势相符。最后采用改进熵值法验证多级灰色关联综合分析结论,计算得出的结果表明,该两种方法评价结论基本相同。因此,本研究对城市总体规划环境影响评价的评价方法的建立与完善,有着较强的实践意义和参考价值。