Outsourcing,trade, technology,and greenhouse gas emissions

Environmental Economics and Policy Studies - U.S. output has steadily outpaced the rise in greenhouse gas (GHG) emissions over the past several decades. The decoupling of these two trends...     

Emergence of Indigenous Vegetation Classifications Through Integration of Traditional Ecological Knowledge and Remote Sensing Analyses

Traditional ecological knowledge (TEK) can play an important role in the understanding of ecological systems. Although TEK has complemented scientific and managerial programs in a variety of contexts, its formal incorporation into remote sensing exercises has to date been limited. Here, we show that the vegetation classifications of the Ache, an indigenous hunter-gatherer tribe of the Mbaracayu Forest Reserve in Paraguay, are reflected in a supervised classification of satellite imagery of the reserve. Accuracy of classification was toward the low end of the range of published values, but was reasonable given the difficult nature of separating forest classes from satellite images. Comparison of the resultant map with a more traditionally elaborated vegetation map highlights differences between the two approaches and the gain in information obtained by considering TEK classifications. We suggest that integration of TEK and remote sensing may provide alternative insights into the ecology of vegetation communities and land cover, particularly in remote and densely forested areas where ecological field research is often limited by roads and/or trail systems.     

An Analysis of Biomedical Waste Incineration

The California Air Resources Board (ARB) completed a series of source tests of eight operating biomedical waste incinerators (BMWI) under conditions of typical operation. The emissions of certain metals, and chlorinated dioxins and furans in the flue gases of BMWI are relatively high in comparison to emissions from other combustion sources, such as hazardous waste or municipal waste incinerators of modern design. This study reports on an analysis of the status of the existing regulatory framework and the California data base. Clarification of definitional issues at the federal level is needed to effectively treat BMWI management issues. Although few relationships among combustion parameters and emissions were uncovered, patterns of emissions were evident, suggesting commonality and relationships among the waste stream constituents and emissions. Potential implications for future research, operation of BMWI, controls and source reduction and waste segregation strategies are also discussed.     

Estimating the Cumulative Ecological Effect of Local Scale Landscape Changes in South Florida

Ecosystem restoration in south Florida is a state and national priority centered on the Everglades wetlands. However, urban development pressures affect the restoration potential and remaining habitat functions of the natural undeveloped areas. Land use (LU) planning often focuses at the local level, but a better understanding of the cumulative effects of small projects at the landscape level is needed to support ecosystem restoration and preservation. The South Florida Ecosystem Portfolio Model (SFL EPM) is a regional LU planning tool developed to help stakeholders visualize LU scenario evaluation and improve communication about regional effects of LU decisions. One component of the SFL EPM is ecological value (EV), which is evaluated through modeled ecological criteria related to ecosystem services using metrics for (1) biodiversity potential, (2) threatened and endangered species, (3) rare and unique habitats, (4) landscape pattern and fragmentation, (5) water quality buffer potential, and (6) ecological restoration potential. In this article, we demonstrate the calculation of EV using two case studies: (1) assessing altered EV in the Biscayne Gateway area by comparing 2004 LU to potential LU in 2025 and 2050, and (2) the cumulative impact of adding limestone mines south of Miami. Our analyses spatially convey changing regional EV resulting from conversion of local natural and agricultural areas to urban, industrial, or extractive use. Different simulated local LU scenarios may result in different alterations in calculated regional EV. These case studies demonstrate methods that may facilitate evaluation of potential future LU patterns and incorporate EV into decision making.     

Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande1

Abudu, S., J.P. King, Z. Sheng, 2011. Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande. Journal of the American Water Resources Association (JAWRA) 48(1): 10‐23. DOI: 10.1111/j.1752‐1688.2011.00587.x Abstract: This paper presents the application of autoregressive integrated moving average (ARIMA), transfer function‐noise (TFN), and artificial neural networks (ANNs) modeling approaches in forecasting monthly total dissolved solids (TDS) of water in the Rio Grande at El Paso, Texas. Predictability analysis was performed between the precipitation, temperature, streamflow rates at the site, releases from upstream reservoirs, and monthly TDS using cross‐correlation statistical tests. The chi‐square test results indicated that the average monthly temperature and precipitation did not show significant predictability on monthly TDS series. The performances of one‐ to three‐month‐ahead model forecasts for the testing period of 1984‐1994 showed that the TFN model that incorporated the streamflow rates at the site and Caballo Reservoir release improved monthly TDS forecasts slightly better than the ARIMA models. Except for one‐month‐ahead forecasts, the ANN models using the streamflow rates at the site as inputs resulted in no significant improvements over the TFN models at two‐month‐ahead and three‐month‐ahead forecasts. For three‐month‐ahead forecasts, the simple ARIMA showed similar performance compared to all other models. The results of this study suggested that simple deseasonalized ARIMA models could be used in one‐ to three‐month‐ahead TDS forecasting at the study site with a simple, explicit model structure and similar model performance as the TFN and ANN models for better water management in the Basin.     

Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

Institutional Constraints on Cost‐Effective Water Management: Selenium Contamination in Colorado's Lower Arkansas River Valley

Ground and surface water selenium (Se) contamination is problematic throughout the world, leading to harmful impacts on aquatic life, wildlife, livestock, and humans. A groundwater reactive transport model was applied to a regional‐scale irrigated groundwater system in the Lower Arkansas River Basin in southeastern Colorado to identify management practices that remediate Se contamination. The system has levels of surface water and groundwater Se concentrations exceeding the respective chronic standard and guidelines. We evaluate potential solutions by combining the transport model with an assessment of the cost to employ those practices. We use a framework common in economics and engineering fields alike, the Pareto frontier, to show the impact of four different best management practices on the tradeoffs between Se and cost objectives. We then extend that analysis to include institutional constraints that affect the economic feasibility associated with each practice. Results indicate that although water‐reducing strategies have the greatest impact on Se, they are the hardest for farmers to implement given constraints common to western water rights institutions. Therefore, our analysis shows that estimating economic and environmental tradeoffs, as is typically done with a Pareto frontier, will not provide an accurate picture of choices available to farmers where institutional constraints should also be considered.     

Spatiotemporal modelling of ozone distribution in the State of California

This paper is concerned with the spatiotemporal mapping of monthly 8-h average ozone (O₃) concentrations over California during a 15-years period. The basic methodology of our analysis is based on the spatiotemporal random field (S/TRF) theory. We use a S/TRF decomposition model with a dominant seasonal O₃ component that may change significantly from site to site. O₃ seasonal patterns are estimated and separated from stochastic fluctuations. By means of Bayesian Maximum Entropy (BME) analysis, physically meaningful and sufficiently detailed space–time maps of the seasonal O₃ patterns are generated across space and time. During the summer and winter months the seasonal O₃ concentration maps exhibit clear and progressively changing geographical patterns over time, suggesting the existence of relationships in accordance with the typical physiographic and climatologic features of California. BME mapping accuracy can be superior to that of other techniques commonly used by EPA; its framework can rigorously assimilate useful data sources that were previously unaccounted for; the generated maps offer valuable assessments of the spatiotemporal O₃ patterns that can be helpful in the identification of physical mechanisms and their interrelations, the design of human exposure and population health models, and in risk assessment. As they focus on the seasonal patterns, the maps are not contingent on short-time and locally prevalent weather conditions, which are of no interest in a global and non-forecasting framework. Moreover, the maps offer valuable insight about the space–time O₃ concentration patterns and are, thus, helpful for disentangling the influence of explanatory factors or even for identifying some influential ones that could have been otherwise overlooked.     

Can we trust odor databases? Example of t- and n-butyl acetate

The US EPA has exempted t-butyl acetate from VOC regulations, which increases the likelihood that it may replace other solvents in some settings. This investigation probes its chemosensory properties. In Study 1, subjects (n = 29) sought to detect the odor of t-butyl acetate and of n-butyl acetate in forced-choice testing of stable concentrations, analytically confirmed. Subjects sniffed from cones with a high enough volumetric flow to insure against dilution by nonodorized air. A subject made hundreds of judgments, enough for a psychometric function for each material. The points of 50% detection above chance (“threshold”) occurred at 8 and 2 ppb for t-butyl acetate and n-butyl acetate, respectively. In study 2, subjects (n = 26) sought to detect vapor with the eye via chemesthesis (sensory irritation) in 10-s exposures. Detection at 50% occurred at 177 and 113 ppm for t-butyl acetate and n-butyl acetate, respectively, more than 10,000 times above that for odor detection. The protocols produced results of uncommon precision compared to those in often-misleading archival databases. The nose exhibits much higher sensitivity than the databases indicate. The collections rarely exhibit accuracy better than ±1000%. Collection of accurate data for a VOC can ironically bring on stricter regulation for just it, a situation that calls for a strategy to improve the database by collection of new data, importation of better data, and development of quantitative structure–activity modeling.     

Indices of Grassland Biodiversity in the Chihuahuan Desert Ecoregion Derived from Remote Sensing

Abstract: We used a relatively simple and direct remote-sensing approach to determine biodiversity values in arid ecosystems and thus identify potential conservation sites. We developed indices based on regression models between grass, shrub, litter, exposed-soil groundcover components, and Landsat thematic mapper satellite imagery reflectance values over a reference site in the northern Chihuahuan Desert in New Mexico. This site supports low-disturbance desert grasslands that have been excluded from livestock grazing for 55 years and moderate-disturbance grasslands that have been under a continuous grazing regime for over 100 years. Greater richness and abundance of noninvasive and nonruderal plant species were associated with the low-disturbance grasslands that had lower shrub abundance, increased litter and grass cover, and lower exposed soil. Using the thematic mapper indices, we computed an additive grassland biodiversity index such that, as exposed soil and shrub values go down, litter and grass values go up, as does the biodiversity index. When the biodiversity index was applied to the reference-site landscape, grasslands previously identified for their high conservation value were detected. As a further test, we applied the indices to a site in Chihuahua, Mexico, that supports similar grasslands but for which there are few other data on condition and conservation values. The soil, grass, and shrub indices were moderately effective in describing the range of variation at the Mexico site, but the litter equation was not. Still, higher biodiversity value in terms of nonruderal plant diversity tended to correspond to higher grass cover and lower soil exposure and a higher overall biodiversity index. Some localized calibration with geologic substrate may be required along with an assessment of the temporal constraints, but generally the index shows promise for quickly and efficiently detecting desert grasslands of high biodiversity conservation value.