Design and risk assessment tool for vegetative treatment areas receiving agricultural wastewater: Preliminary results

Vegetative treatment areas (VTAs) are commonly being used as an alternative method of agricultural process wastewater treatment. However, it is also apparent that to completely prevent discharge of pollutants to the surrounding environment, settling of particulates and bound constituents from overland flow through VTAs is not sufficient. For effective remediation of dissolved agricultural pollutants, VTAs must infiltrate incoming wastewater. A simple water balance model for predicting VTA soil saturation and surface discharge in landscapes characterized by sloping terrain and a shallow restrictive layer is presented and discussed. The model accounts for the cumulative effect of successive rainfall events and wastewater input on soil moisture status and depth to water table. Nash–Sutcliffe efficiencies ranged from 0.65 to 0.81 for modeled and observed water table elevations after calibration of saturated hydraulic conductivity. Precipitation data from relatively low, average, and high annual rainfall years were used with soil, site, and contributing area data from an example VTA for simulations and comparisons. Model sensitivity to VTA width and contributing area (i.e. barnyard, feedlot, silage bunker, etc.) curve number was also investigated. Results of this analysis indicate that VTAs should be located on steeper slopes with deeper, more-permeable soils, which effectively lowers the shallow water table. In sloping landscapes (>2%), this model provides practitioners an easy-to-use VTA design and/or risk assessment tool that is more hydrological process-based than current methods.     

Factors affecting the implementation of green specifications in construction

Green specifications constitute one of the important elements in green construction. New sustainability requirements and changing priorities in construction management have spurred the emerging green specifications to a faster pace of development. A cross-sectional survey has been conducted in Hong Kong in 2007 to identify principal factors leading to the success of preparing green specifications. Based on extensive construction management literature, 20 variables concerning sustainable construction were summarized. Using the Mann–Whitney U-test, the subtle differences between stakeholders in specifying construction work have been detected even with the high consistency of the responses among the groups. Moreover, five independent factors for successful specification of green construction have been categorized by factor analysis. They are related to (1) green technology and techniques, (2) reliability and quality of specification, (3) leadership and responsibility, (4) stakeholder involvement, and (5) guide and benchmarking systems. Whilst the first and fourth factors are generally more important, different stakeholder groups have different emphases. The results of the survey have been validated against established principles.     

Evaluating the Quality of Citizen‐Scientist Data on Pollinator Communities

Abstract: Concerns about pollinator declines have grown in recent years, yet the ability to detect changes in abundance, taxonomic richness, and composition of pollinator communities is hampered severely by the lack of data over space and time. Citizen scientists may be able to extend the spatial and temporal extent of pollinator monitoring programs. We developed a citizen‐science monitoring protocol in which we trained 13 citizen scientists to observe and classify floral visitors at the resolution of orders or super families (e.g., bee, wasp, fly) and at finer resolution within bees (superfamily Apoidea) only. We evaluated the protocol by comparing data collected simultaneously at 17 sites by citizen scientists (observational data set) and by professionals (specimen‐based data set). The sites differed with respect to the presence and age of hedgerows planted to improve habitat quality for pollinators. We found significant, positive correlations among the two data sets for higher level taxonomic composition, honey bee (Apis mellifera) abundance, non‐Apis bee abundance, bee richness, and bee community similarity. Results for both data sets also showed similar trends (or lack thereof) in these metrics among sites differing in the presence and age of hedgerows. Nevertheless, citizen scientists did not observe approximately half of the bee groups collected by professional scientists at the same sites. Thus, the utility of citizen‐science observational data may be restricted to detection of community‐level changes in abundance, richness, or similarity over space and time, and citizen‐science observations may not reliably reflect the abundance or frequency of occurrence of specific pollinator species or groups.     

Uncertainty characterization for emergy values

While statistical estimation of uncertainty has not typically accompanied published emergy values, as with any other quantitative model, uncertainty is embedded in these values, and lack of uncertainty characterization makes their accuracy not only opaque, it also prevents the use of emergy values in statistical tests of hypotheses. This paper first attempts to describe sources of uncertainty in unit emergy values (UEVs) and presents a framework for estimating this uncertainty with analytical and stochastic models, with model choices dependent upon on how the UEV is calculated and what kind of uncertainties are quantified. The analytical model can incorporate a broader spectrum of uncertainty types than the stochastic model, including model and scenario uncertainty, which may be significant in emergy models, but is only appropriate for the most basic of emergy calculations. Although less comprehensive in its incorporation of uncertainty, the proposed stochastic method is suitable for all types of UEVs. The distributions of unit emergy values approximate the lognormal distribution with variations depending on the types of uncertainty quantified as well as the way the UEVs are calculated. While both methods of estimating uncertainty in UEVs have their limitations in their presented stage of development, this paper provides methods for incorporating uncertainty into emergy, and demonstrates how this can be depicted and propagated so that it can be used in future emergy analyses and permit emergy to be more readily incorporated into other methods of environmental assessment, such as LCA.     

Coupled reservoir-geomechanical analysis of CO2 injection and ground deformations at In Salah,Algeria

In Salah Gas Project in Algeria has been injecting 0.5–1 million tonnes CO₂ per year over the past 5 years into a water-filled strata at a depth of about 1800–1900 m. Unlike most CO₂ storage sites, the permeability of the storage formation is relatively low and comparatively thin with a thickness of about 20 m. To ensure adequate CO₂ flow-rates across the low-permeability sand-face, the In Salah Gas Project decided to use long-reach (about 1–1.5 km) horizontal injection wells. In an ongoing research project we use field data and coupled reservoir-geomechanical numerical modeling to assess the effectiveness of this approach and to investigate monitoring techniques to evaluate the performance of a CO₂ injection operation in relatively low-permeability formations. Among the field data used are ground surface deformations evaluated from recently acquired satellite-based inferrometry (InSAR). The InSAR data shows a surface uplift on the order of 5 mm per year above active CO₂ injection wells and the uplift pattern extends several km from the injection wells. In this paper we use the observed surface uplift to constrain our coupled reservoir-geomechanical model and conduct sensitivity studies to investigate potential causes and mechanisms of the observed uplift. The results of our analysis indicate that most of the observed uplift magnitude can be explained by pressure-induced, poro-elastic expansion of the 20-m-thick injection zone, but there could also be a significant contribution from pressure-induced deformations within a 100-m-thick zone of shaly sands immediately above the injection zone.     

Brain myelination in rats treated with ionizing radiation in utero

Abstract

Effects of ionizing radiation on brain myelination and some physical development parameters were studied in laboratory rats (Fisher F‐344 inbred strain). Rats were treated with three different doses of radiation (150 rad, 15 rad, and 6.8 rad) delivered on the 20th day of prenatal life. Exposure to 150 rad reduced body, brain, ovary, kidney, heart and spleen weights. Prenatal exposure to 150 rad of radiation reduced the cerebral cortex weight by 22 percent at 30 days of age, and 20 percent at 52 days of age which caused a reduction in cerebral cortex myelin content by 20 and 23 percent at the ages of 30 and 52 days respectively. This dose did not affect the myelin content of the cerebellum or the brain stem, or the myelin concentration (mg myelin/g brain tissue) of the cerebral cortex, cerebellum, and the brain stem. The cerebral cortex weight of the 15 rad treated rats was reduced at the age of 30 days. Exposure to 15 rad, and 6.8 rad did not affect either the myelin content or the myelin concentration of these brain areas.     

Photochemical Reactivities of Paraffinic Hydrocarbon-Nitrogen Oxide Mixtures Upon Addition of Propylene or Toluene

Effects associated with photochemical air pollution were measured during irradiation of n-butane-nitrogen oxide or n-butane-ethane-nitrogen oxide mixtures, with small amounts of propylene or toluene added. The effects measured including nitrogen dioxide and oxidant dosages, yields of formaldehyde and peroxy-acetyl nitrate, and eye irritation response. The results obtained clearly show that beneficial effects result from selective changes in hydrocarbon composition as well as from reduction of total hydrocarbon concenfration. Exclusion of olefins and alkylbenzenes was highly effective in reducing oxidant dosage, formaldehyde and peroxyacetyl nitrate concentrations, and eye irritation response. The only penalty was a modest increase in nitrogen dioxide dosage. A large reduction in nitrogen oxide concentration reduced nitrogen dioxide dosage and eye irritation response, but with the penalty of a large increase in oxidant dosage. The desirability of preferentially reducing olefins and alkylbenzenes rather than paraffinic hydrocarbons, acetylene, and benzene is strongly supported by this study. Research and development efforts should be directed toward preferential hydrocarbon control by mechanical or catalytic control     

The Role of Disaggregation of Asset Values in Flood Loss Estimation: A Comparison of Different Modeling Approaches at the Mulde River,Germany

In loss estimation there is a spatial mismatch of hazard data that are commonly modeled on an explicit raster level and exposure data that are often available only for aggregated administrative units. Usually disaggregation methods that use ancillary information to distribute lumped exposure data in a finer spatial resolution help to bridge this gap. However, the actual influence of different mapping techniques and ancillary data on the final loss estimation has not been analyzed yet. In this paper three methods are applied to disaggregate residential building assets using two kinds of land use/land cover (LULC) data. The resulting disaggregated assets are validated and compared using census data of the residential building number on the community and constituency level. In addition, the disaggregated assets are taken to estimate residential building losses due to the flood in August 2002 in 21 municipalities on the River Mulde in Saxony, Germany. Losses are calculated with the help of four loss models. In general, disaggregation helps to decrease the error variance within the loss estimation. It must, however, be stated that the application of sophisticated disaggregation methods does not lead to significant improvements compared to the straightforward binary method. Therefore more effort should instead be put into the provision of high-resolution LULC data. Finally, the remaining uncertainties in loss estimation are high and demand further improvements in all modeling aspects.     

Estimation of Ambient PM2.5 Concentrations in Maryland and Verification by Measured Values

Abstract

In 1997, Maryland had no available ambient Federal Reference Method data on particulate matter less than 2.5 μm in aerodynamic diameter (PM_2.5), but did have annual ambient data for PM smaller than 10 μm (PM₁₀) at 24 sites. The PM₁₀ data were analyzed in conjunction with local annual and seasonal zip-code-level emission inventories and with speciated PM_2.5 data from four nearby monitors in the IMPROVE network (located in the national parks, wildlife refuges, and wilderness areas) in an effort to estimate annual average and seasonal high PM_2.5 concentrations at the 24 PM₁₀ monitor sites operating from 1992 to 1996. All seasonal high concentrations were estimated to be below the 24-hr PM_2.5 National Ambient Air Quality Standards (NAAQS) at the sites operating in Maryland between 1992 and 1996. The estimates also indicated that 12 monitor sites might exceed the 3-year annual average PM_2.5 NAAQS of 15 ug/m³, but Maryland’s air quality shows signs that it has been improving since 1992. The estimates also were compared with actual measurements after the PM_2.5 monitor network was installed. The estimates were adequate for describing the chemical composition of the PM_2.5, forecasting compliance status with the 24-hr and annual standards, and determining the spatial variations in PM_2.5 across central Maryland.