An Overview of EPA's Regional Vulnerability Assessment (ReVA) Program

Regional Vulnerability Assessment (ReVA) is an approach to place-based ecological risk assessment that is currently under development by EPA's Office of Research and Development. The pilot assessment will be done for the mid-Atlantic region and builds on data collected for the Environmental Monitoring and Assessment Program. ReVA is being developed to identify those ecosystems most vulnerable to being lost or degraded in the next 5 to 50 years and to elucidate which stressors cause the greatest risk to ecosystem goods and services. The goal here is not exact predictions, but an early warning system to identify and prioritize the undesirable environmental changes we should expect over the next few decades. As such, ReVA represents a new risk paradigm for EPA that will require innovative approaches to combine existing knowledge, focus new research, and synthesize many types of information into a meaningful assessment designed to inform environmental decision-makers about future environmental risk.     

Estimating Greenhouse Gas Emission Reduction Potential: An Assessment of Models and Methods for the Power Sector

The success of the Clean Development Mechanism of the Kyoto Protocol to reduce global greenhouse gas emissions requires that there are scientifically sound and usable measurement methods for the emission baseline. Three different methods are investigated in the context of China’s electrical sector: simulation with dispatch analysis, decomposition analysis, and operating and build margin analysis. It is found that dispatch analysis is the best method available as it is able to consider important regional and temporal dimensions, while decomposition analysis can help quantify the potential effects of different energy and environment policy choices.     

A Regional Assessment of Windbreak Habitat Suitability

The Environmental Monitoring and Assessment Programwas initiated in 1989 by the United StatesEnvironmental Protection Agency to collect, analyze,and report quantitative, statistically unbiasedinformation about the state of the nation'senvironment on a regional basis. During a pilotprogram in Nebraska we measured a habitat suitabilityindex for a probability sample of 40 windbreaks andexpanded the results to estimate the potential valueof windbreaks as wildlife habitat in Nebraska. Theindex estimates the suitability of a windbreak ashabitat for wildlife including breeding birds, smallmammals, and deer. Index values range from zero toone, where a value of one indicates maximal habitatvalue. We estimated that 50% (±13% at 90%confidence) of windbreaks in Nebraska have a habitatsuitability index of 0.25 or less and that nowindbreaks have a suitability index greater than 0.6. Our results indicate that increasing the area ofindividual windbreaks is the most effective way toimprove their value as wildlife habitat. Monitoringwindbreak condition over time would alert wildlifemanagers to changes in the resource that might affectwildlife populations. Because our data were highlyvariable, the power to detect change in habitatcondition between two measurement periods was low. Amuch larger sample would be required to detect smallchanges in habitat condition. Variability may bereduced, and power increased, by carefully andconsistently constructing the sampling frame, keepingdata collection as simple as possible, appropriatelystratifying sample selection, and using a small numberof well-trained data collection teams. However, wesuggest adapting the index for use with aerialphotography in future efforts to evaluate windbreaksas wildlife habitat in extensive areas.     

Finding Common Ground in Managing Data Used for Regional Environmental Assessments

Evaluating the overall environmental health of a region invariably involves using databases from multiple organizations. Several approaches to deal with the related technological and sociological issues have been used by various programs. Flexible data systems are required to deal with rapid changes in technology, the social and political climate for sharing and integrating data, and expectations of diverse users. Here we describe how the Environmental Monitoring and Assessment Program and the Chesapeake Bay Program manage their data for regional studies. These programs, which encompass areas of different geographic scales but face similar issues, have adopted some solutions in common, but also have tried some unique solutions suited to their needs. Understanding the tribulations and successes of these programs may help others attempting similar assessments. Both these programs have embraced distributed data systems that are managed by the organizations owning them. Both use common guidelines and policies that assure consistency and quality of data and information. These principles and tools comprise a flexible, sustainable approach that meets modern challenges of data management.     

环境水质评价方法的分析与探讨

对目前水环境质量评价中使用的各方法进行分析比较,提出评价方法应具备的基本要求,指出今后的研究方向。     

Integration of Optical and Microwave Remote Sensing Data for Agricultural Land Use Classification

An agricultural land use classification of Oltrepo' Pavese region (in Northern Italy) is performed through integration of remote sensing data from optical and radar sensors. The source of optical data was a Landsat-TM image acquired on April 1994, while the source of microwave data was a contemporaneous image of the new radar sensor SIR-C/X-SAR which was flown on-board the Space Shuttle during an experimental mission over the chosen test site. Then, they were combined through calculation of the principal components of the multidimensional data sets and a final classification was carried out and compared with the classifications obtained from optical and radar recordings separately. Results showed remarkable improvement in the classification accuracy of seedbeds and uncultivated fields with radar recordings and of herbaceous crop type with integrated data. Potential ability of a multi-sensor classification and limits of a single-temporal approach are discussed.     

Surface Water Quality Assessment by Environmetric Methods

This environmetric study deals with the interpretation of river water monitoring data from the basin of the Buyuk Menderes River and its tributaries in Turkey. Eleven variables were measured to estimate water quality at 17 sampling sites. Factor analysis was applied to explain the correlations between the observations in terms of underlying factors. Results revealed that, water quality was strongly affected from agricultural uses. Cluster analysis was used to classify stations with similar properties and results distinguished three groups of stations. Water quality at downstream of the river was quite different from the other part. It is recommended to involve the environmetric data treatment as a substantial procedure in assessment of water quality data.     

Using Slides to Test for Changes in Crown Defoliation Assessment Methods. Part I: Visual Assessment of Slides

In this study we used photographs of tree crowns to test whether the assessment methods for tree defoliation in Switzerland have changed over time. We randomly selected 24 series of slides of Norway spruce with field assessments made between 1986 and 1995. The slides were randomly arranged and assessed by three experts without prior knowledge of the year when the slide was taken or the tree number. Defoliation was assessed using the Swiss reference photo guide. Although the correlations between the field assessments and slide assessments were high (Spearman's rank correlation coefficient ranged between 0.79 and 0.83), we found significant differences between field and slide assessments (4.3 to 9% underprediction by the slide assessors) and between the slide assessments. However, no significant trends in field assessment methods could be detected. When the mean differences between field and slide assessments were subtracted, in some years, field assessors consistently underpredicted (1990, 1992) or overpredicted defoliation (1987, 1991). Defoliation tended to be overpredicted in slides taken against the light, and underpredicted for trees with more than 25% crown overlap. We conclude that slide series can be used to detect changes in assessment methods. However, potential observer bias calls for more objective methods of assessment.     

Environmental Data in Decision Making in EPA Regional Offices

The mid-Atlantic region of the United States has a wide diversity of natural resources. Human pressures on these natural resources are intense. These factors have resulted in the collection of substantial amounts of environmental information about the region by EPA (both Regional and Research Offices), other governmental agencies, industry, and environmental groups. EPA Regional Offices comprehend first hand the importance of environmental data and are extremely supportive of investments in these data. Environmental data are used prominently in a variety of strategic planning and resource management initiatives. In EPA Region 3, the use of scientifically-sound environmental data is, in fact, one of our strategic programmatic goals. Environmental information is captured and assessed continuously by Regional staff, sometimes working in partnership with other Federal and State agencies, to derive relevant resource management conclusions. The restoration goals for the Chesapeake Bay are based on environmental indicators and resulting data. Attainment of the water quality objectives for streams and coastal estuaries are predicted on monitoring data. Our initiative in the Mid-Atlantic Highlands area uses environmental indicators to measure the condition of forests and streams. Landscape-level indicators will provide unique opportunities for the use of data in planning and management activities in support of the principles of community-based activism and sustainable development. Significant value is added to these data during their use by Regional managers. Regional programs, such as the Chesapeake Bay Program and several National Estuary Programs, are founded in environmental data. Environmental information is used by the Regional program managers to ascertain whether programs are accomplishing their intended objectives. Finally, Regional programs provide a crucial means for disseminating this information to broad segments of the public, so that a better informed and educated client base for effective environmental protection will develop.     

Use of Small Forage Fish for Regional Streams Wildlife Risk Assessment: Relative Bioaccumulation of Contaminants

Selection of fish species for sampling to assess extent and potential effects of fish tissue contaminants is a criticalconsideration in the design of regional probability-designsurveys. The ideal species would be ubiquitous, bioaccumulatetoxic chemicals, and be prey of consumers of concern(piscivorous wildlife, humans). In first to third order streams,small short-lived forage fish (minnows (F. Cyprinidae), darters (F. Percidae), and sculpins (F. Cottidae), are more frequently found and therefore likely to be prey to more species ofwildlife than those of sportfish whose adults grow to a largesize (suckers (F. Catostomidae), trout (F. Salmonidae), bass, andsunfish (F. Centrarchidae), and carp). Targeting smaller foragefish should also produce a larger number of individuals persample on average than may be achieved with the larger species.An analysis of fish collected in 1993 and 1994 as part of theMid-Atlantic Highlands Assessment (MAHA) showed that, asexpected, forage fish were more ubiquitous than sportfishspecies. Analysis also revealed that, on a regional basis, forage fish bioaccumulated comparable levels to sportfish, ofsome widely occurring contaminants such as DDT, MeHg, and PCBs.Results indicated that smaller forage fish can be used asindicator species for a regional assessment for mostcontaminants (Zn being the one clear exception), that was notsignificantly different from one based on the larger species.Forage fish may therefore be an excellent choice as indicatorspecies for regional streams ecological risk assessment studies.     

The Spatial-Scale Effect of an Atmospheric Environmental Impact Assessment in Regional Strategic Environmental Assessment (R-SEA)

When evaluating the atmospheric environment in regional strategic environment assessment (R-SEA), the variation and choice of the spatial scale have a substantial influence on the conclusions of the assessment. In this study, we used numerical simulation to investigate the spatial-scale effect. Two varying spatial extents and two varying spatial details of pollutant emission data (emission inventories in this case) were provided for numerical modeling, and output distributions of atmospheric pollutants at different air pollution levels were compared. The results show that the resolution and spatial range of data collection do indeed influence the atmospheric prediction and assessment results in R-SEA. The spatial-scale effect is more significant under the air pollution condition than under excellent and good air quality conditions. A comparison of varying spatial extents of emission inventory shows that narrowing the prediction area to a local scale is more conducive to identifying the impact of local pollution sources. A comparison of varying spatial details of emission inventory indicates that a higher resolution is favorable for identifying local high concentrations of pollutants and their locations.     

Combining Logistic Models with Multivariate Methods for the Rapid Biological Assessment of Rivers Using Macroinvertebrates

This work represents an attempt to define a simple method to classify the relative degree of disturbance of sites in lotic systems on the basis of comparison of their faunistic composition with reference sites. Two ecotypes were selected in northern Portugal where benthic invertebrates were sampled in reaches with different levels of contamination. As a first stage, previous Geographic Information System information was used to define reference sites in each ecotype. Afterwards, multivariate techniques and non linear estimation models were combined to assess biological quality. This method allowed us to quantify sites according to increasing levels of contamination, after the probabilities of occurrence of taxa along a gradient of contamination taking into account the reference condition. The results suggest that this method is sensitive to organic pollution, easy to interpret, namely the species tolerance, and could be a good framework to establish regional rankings depending on the ecological impact of river sites.     

PLS and PCR Methods in the Assessment of Coastal Water Quality

Partial least squares regression analysis (PLS) and principal component regression analysis (PCR) were examined asmethodological procedures for assessing the quality of coastalwaters in a tourist area. Four variables related to the trophicstate of waters, namely nitrate, nitrite, ammonia and phosphate were analyzed. The models resulting from PLS and PCR were verysimilar. Both defined three groups of water masses characterizedby different nutrient loadings. These groups were in accordancewith those obtained by numerical classification. The PLS methodwas selected as the optimal model, on the basis of its lowerprediction errors (lower Press and Rmsd values). For managementpurposes, this statistical model allows mesotrophic conditions,reflecting some nutrient enrichment over background conditions,to be characterized and the successful diagnosis of additionalsamples within this context.     

An Overview of Contaminant-Related Issues Identified by Monitoring in San Francisco Bay

The San Francisco Estuary Regional Monitoring Program for Trace Substances (RMP) began in 1993 and is sponsored by 74 local, state, and federal agencies and companies through their discharge or Bay use permits. The RMP monitors water, sediment, toxicity, and bivalve bioaccumulation at 25 sites in the Bay that are considered to represent "background" conditions. Several major environmental issues have been identified by the RMP. Polychlorinated biphenyls and mercury were often above water quality guidelines, and often occurred in fish tissues above U.S. Environmental Protection Agency (U.S. EPA) screening values. Concentrations do not appear to be decreasing, suggesting continuing inputs. Episodes of aquatic toxicity often occurred following runoff events that transport contaminants into the Bay from urbanized and agricultural portions of the watershed. Sediment toxicity occurred throughout the Bay, and has been correlated with concentrations of specific contaminants (chlordanes, polynuclear aromatic hydrocarbons) at some locations; mixtures of contaminants were probably also important. Since the RMP does not monitor all ecosystem components, assessments of the overall condition of the Bay cannot be made. However, in terms of contamination, the RMP samples suggest that the South Bay, and North Bay sites are moderately contaminated.     

Factor-Augmenting Technical Change: An Empirical Assessment

This paper estimates factor-specific technical change and input substitution using a structural approach. It contributes to the existing literature by introducing various technology drivers for factor productivities and by assessing the impact of endogenous technical change on the elasticity of substitution. The empirical results suggest that factor productivities are indeed endogenous. In addition, technology drivers are factor-specific. Whereas the R&D stock and machinery imports are important determinants of energy and capital productivity, the education stock is statistically related to labour productivity. The rate of energy-augmenting technical change is larger than that of either labour or capital. By contrast, the productivity of these two factors grows at similar rates. Estimates of the elasticity of substitution are within the range identified by previous literature. In addition, we show that endogenous technical change reduces substitution. Because the elasticity of substitution is lower than one, knowledge and human capital can ultimately have an energy-using effect. The estimated structure of endogenous technical change suggests that Integrated Assessment models focusing on energy-saving technical change might underestimate climate policy costs.     

Assessment of Chlorophyll-a Concentration and Trophic State for Lake Chagan Using Landsat TM and Field Spectral Data

In this study, we present the digital evaluation of Landsat TM data and field spectral measurements for retrieving chlorophyll-a (chl-a) concentration and trophic state index in Lake Chagan of Northeast China. Chl-a concentration of the lake can be estimated from the band ratio (TM4/TM3) and the field spectral data at 670 nm (absorption peak) and at 700 nm (reflectance peak). The results show that the best determination coefficient (R ²) is 0.67 from the TM data, by which chl-a distribution can be mapped. Based on chl-a determination from laboratory analysis, field spectral and TM data, the modified trophic state index (TSI_M) was applied to assess the lake’s trophic state. With the available data in Lake Chagan, each algorithm demonstrates the similar result for assessing the lake’s chl-a and trophic state. Our results indicate that Landsat TM and field spectral data could be used effectively to determine chl-a concentration and evaluate the trophic state of Lake Chagan in the study.     

An Integrated Framework for Regional Studies: Emergy Based Spatial Analysis of the Province of Cagliari

This research proposes an integrated framework to investigate human-dominated systems and provide a basic approach to urban and regional studies in which the multiple interactions between economic and ecological processes are considered as a whole. Humans generate patterns of land use, infrastructures and other settings and redistribute ecosystem functions as flows of energy and matter for self-maintenance. To understand these emerging interactions between humans and ecological processes, human activities (e.g. transformation processes, land conversions, use of resources) and biophysical agents such as geomorphology, climate and natural cycles need to be considered. Emergy Analysis (spelled with an “m”) is then used as an environmental accounting method to evaluate different categories of resource use with reference to their environmental cost. A case study of the Province of Cagliari (in the island of Sardinia, Italy) is reported and the procedure for allocating emergy flows, assigning them to districts and managing point data is discussed. Outcomes plotted on a map showed non-homogeneous spatial distribution of emergy flows throughout the region, suggesting the way ecosystem functions are affected and restructured by the human economy.     

Integrated Assessment Modeling for Global Climate Change: An Infinite Horizon Optimization Viewpoint

In this paper one uses an infinite time horizon optimal control paradigm to deal with three important issues in global climate change integrated assessment, namely the equitable treatment of all the generations involved, the representation of technical progress, and the uncertainty concerning technological progress and climate change processes. The notion of economic sustainability is associated with the concept of turnpike in infinite horizon optimization models. The issue of deciding on the proper discount rate is addressed in this context and a method is proposed to reconcile long term sustainability and short term time preference for current generations. One also formulates a model where environmental damage and/or technical progress are represented as stochastic jump processes. One calls this random evolution a mode switching process. In this context, sustainability is represented by a family of turnpikes, and the economy will be driven from one steady state to the other as the modes switch. These concepts are illustrated on the DICE model and their possible implementation in other types of integrated assessment models is discussed.     

A Multilevel Modeling Approach to Assessing Regional and Local Landscape Features for Lake Classification and Assessment of Fish Growth Rates

The ecoregion and watershed frameworks are landscape-based classifications that have been used to group waterbodies with respect to measures of community structure; however, they have yet to be evaluated for grouping lakes for demographic characteristics of fish populations. We used a multilevel modeling approach to determine if variability in mean fish length at age could be partitioned by ecoregions and watersheds. For the ecoregions analysis, we then examined if within-ecoregion variability could be explained by local water quality and lake morphometry characteristics. We used data from agency surveys conducted during 1974-1984 for age 2 and 3 fish of seven common warm and coolwater fish species. Variance in mean length at age between ecoregions for all species was not significant, and between-watershed variance estimates were only significant in 3 out of 14 analyses; however, the total amount of variation between watersheds was very small (ranging from 1.8% to 3.7% of the total variance), indicating that ecoregions and watersheds were ineffective in partitioning variability in mean length at age. Within ecoregions, water quality and lake morphometric characteristics accounted for 2%-23% of the variation in mean length at age. Measures of lake productivity were the most common significant covariates, with mean length at age increasing with increasing lake productivity. Much of the variability in mean length at age was not accounted for, suggesting that other local factors such as biotic interactions, fish density, and exploitation are important. The results indicate that the development of an effective regional framework for managing inland lakes will require a substantial effort to understand sources of demographic variability and that managers should not rely solely on ecoregions or watersheds for grouping lakes with similar growth rates.