Life cycle cost evaluation of the digital opacity compliance system

The US Environmental Protection Agency (EPA) has established EPA Reference Method 9 (Method 9) as the preferred enforcement approach for verifying compliance with federal visible opacity standards. While Method 9 has an extensive history of successful employment, reliance on human observers to quantify visible emissions is inherently subjective, a characteristic that exposes Method 9 results to claims of inaccuracy, bias and, in some cases, outright fraud.The Digital Opacity Compliance System (DOCS), which employs commercial-off-the-shelf digital photography coupled with simple computer processing, is a new approach for quantifying visible opacity. The DOCS technology has been previously demonstrated to meet and, in many cases, surpass the Method 9 accuracy and reliability standards (McFarland et al., 2006). Beyond its performance relative to Method 9, DOCS provides a permanent visual record of opacity, a vital feature in legal compliance challenges.In recent DOCS field testing, the opacity analysis of two hundred and forty one (241) regulated air emissions from the following industrial processes: 1) industrial scrubbers, 2) emergency generators, 3) asphalt paving, 4) steel production and 5) incineration indicated that Method 9 and DOCS were statistically equivalent at the 99% confidence level. However, a life cycle cost analysis demonstrated that implementation of DOCS could potentially save a facility $15,732 per trained opacity observer compared to utilization of Method 9.     

Assessing ecological risk on a regional scale

Society needs a quantitative and systematic way to estimate and compare the impacts of environmental problems that affect large geographic areas. This paper presents an approach for regional risk assessment that combines regional assessment methods and landscape ecology theory with an existing framework for ecological risk assessment. Risk assessment evaluates the effects of an environmental change on a valued natural resource and interprets the significance of those effects in light of the uncertainties identified in each component of the assessment process. Unique and important issues for regional risk assessment are emphasized; these include the definition of the disturbance scenario, the assessment boundary definition, and the spatial heterogeneity of the landscape. Although the research described in this article has been funded wholly or in part by the United States Environmental Protection Agency (EPA) through Interagency Agreement Number DW89932112-01-2 to the U.S. Department of Energy, it has not been subjected to EPA review and therefore does not necessarily reflect the views of EPA and no official endorsement should be inferred.     

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.     

Evaluation of methods for determining adverse impacts of air pollution on terrestrial ecosystems

Methods used to determine adverse impacts of air pollution on four levels of biological organization of terrestrial ecosystems were evaluated for their use in decision making by federal land managers of class I areas and as guidelines for scientists employed to design field studies in these areas. At the level of the individual, visible injury, biomass, and sulfur uptake were the most often used components; at the population level, natality and mortality; at the community level, diversity; and at the ecosystem level, biogeochemical cycling. Most studies focused on structural responses of individual organisms. These components are relatively sensitive and are easy and inexpensive to measure; however, linkages of these parameters to adverse impacts on populations, communities, or ecosystems are lacking. Measurements of effects of air pollution at the higher levels of organization are confounded by natural variability, long response times, climatic variation, pathogens, and other factors. In addition, the lack of replication and of true control areas creates severe problems for design of monitoring programs and testing of hypotheses concerning effects.     

Economically optimal nitrogen rate reduces soil residual nitrate

Post-harvest residual soil NO(3)-N (RSN) is susceptible to transfer to water resources. Practices that minimize RSN levels can reduce N loss to the environment. Our objectives were (i) to determine if the RSN after corn (Zea mays L.) harvest can be reduced if N fertilizer is applied at the economically optimal N rate (EONR) as compared to current producer practices in the midwestern USA and (ii) to compare RSN levels for N fertilizer rates below, at, and above the EONR. Six experiments were conducted in producer fields in three major soil areas (Mississippi Delta alluvial, deep loess, claypan) in Missouri over 2 yr. Predominant soil great groups were Albaqualfs, Argiudolls, Haplaquolls, and Fluvaquents. At four transects in each field, six treatment N rates from 0 to 280 kg N ha(-1) were applied, the EONR was determined, and the RSN was measured to a 0.9-m depth from five treatment plots. The EONR at sampling sites varied from 49 to 228 kg N ha(-1) depending on site and year. Estimated average RSN at the EONR was 33 kg N ha(-1) in the 0.9-m profile. This was at least 12 kg N ha(-1) lower than RSN at the producers' N rates. The RSN increased with increasing Delta EONR (total N applied - EONR). This relationship was best modeled by a plateau-linear function, with a low RSN plateau at N rates well below the EONR. A linear increase in RSN began anywhere from 65 kg N ha(-1) below the EONR to 20 kg N ha(-1) above the EONR at the three sites with good data resolution near the EONR. Applying N rates in excess of the EONR produced elevated RSN values in all six experiments. Our results suggest that applying the EONR will produce environmental benefits in an economically sound manner, and that continued attempts to develop methods for accurately predicting EONR are justified.