A Watershed-based Cumulative Risk Impact Analysis: Environmental Vulnerability and Impact Criteria

Swine Concentrated Animal Feeding Operations (CAFOs) have received much attention in recent years. As a result, a watershed-based screening tool, the Cumulative Risk Index Analysis (CRIA), was developed to assess the cumulative impacts of multiple CAFO facilities in a watershedsubunit. The CRIA formula calculates an index number based on: 1) the area of one or more facilities compared to the area of the watershed subunit, 2) the average of the environmental vulnerability criteria, and 3) the average of the industry-specific impact criteria. Each vulnerability or impact criterion is ranked on a 1 to 5 scale, with a low rank indicating low environmental vulnerability or impact and a high rank indicating high environmental vulnerability or impact. The individual criterion ranks, as well as the total CRIA score, can be used to focus the environmental analysis and facilitate discussions with industry, public, and other stakeholders in the Agency decision-making process.     

Prenatal diagnosis using deletion studies in Duchenne muscular dystrophy

Accurate carrier testing and prenatal diagnosis in Duchenne muscular dystrophy (DMD) families is facilitated when an Xp21 deletion is found to be segregating within a family. We discuss the results of the DNA testing in two families, one in which DNA from affected males was available for study and the other in which no DNA from an affected male was available. Factors complicating the counselling of DMD deletion families are outlined.     

Probabilistic Flood Inundation Forecasting Using Rating Curve Libraries

One approach for performing uncertainty assessment in flood inundation modeling is to use an ensemble of models with different conceptualizations, parameters, and initial and boundary conditions that capture the factors contributing to uncertainty. However, the high computational expense of many hydraulic models renders their use impractical for ensemble forecasting. To address this challenge, we developed a rating curve library method for flood inundation forecasting. This method involves pre‐running a hydraulic model using multiple inflows and extracting rating curves, which prescribe a relation between streamflow and stage at various cross sections along a river reach. For a given streamflow, flood stage at each cross section is interpolated from the pre‐computed rating curve library to delineate flood inundation depths and extents at a lower computational cost. In this article, we describe the workflow for our rating curve library method and the Rating Curve based Automatic Flood Forecasting (RCAFF) software that automates this workflow. We also investigate the feasibility of using this method to transform ensemble streamflow forecasts into local, probabilistic flood inundation delineations for the Onion and Shoal Creeks in Austin, Texas. While our results show water surface elevations from RCAFF are comparable to those from the hydraulic models, the ensemble streamflow forecasts used as inputs to RCAFF are the largest source of uncertainty in predicting observed floods.     

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

Water resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.     

High-frequency measurements reveal spatial and temporal patterns of dissolved organic matter in an urban water conveyance

Stormwater runoff in urban areas can contribute high concentrations of dissolved organic matter (DOM) to receiving waters, potentially causing impairment to the aquatic ecosystem of urban streams and downstream water bodies. Compositional changes in DOM due to storm events in forested, agricultural, and urban landscapes have been well studied, but in situ sensors have not been widely applied to monitor stormwater contributions in urbanized areas, leaving the spatial and temporal characteristics of DOM within these systems poorly understood. We deployed fluorescent DOM (FDOM) sensors at upstream and downstream locations within a study reach to characterize the spatial and temporal changes in DOM quantity and sources within an urban water conveyance that receives stormwater runoff. Baseflow FDOM decreased over the summer season as seasonal flows upstream transported less DOM. FDOM fluctuated diurnally, the amplitude of which also declined as the summer season progressed. During storms, FDOM concentrations were rapidly elevated to values orders of magnitude greater than baseflow measurements, with greater concentrations at the downstream monitoring site, revealing high contributions from stormwater outfalls between the two locations. Observations from custom, in situ fluorometers resembled results obtained using laboratory methods for identifying DOM source material and indicated that DOM transitioned to a more microbially derived composition as the summer season progressed, while stormwater contributions contributed DOM from terrestrial sources. Deployment of a mobile sensing platform during varying flow conditions captured spatial changes in DOM concentration and composition and revealed contributions of DOM from outfalls during stormflows that would have otherwise been unobserved.     

Reporting central tendencies of chamber measured surface emission and oxidation

Methane emissions, concentrations, and oxidation were measured on eleven MSW landfills in eleven states spanning from California to Pennsylvania during the three year study. The flux measurements were performed using a static chamber technique. Initial concentration samples were collected immediately after placement of the flux chamber. Oxidation of the emitted methane was evaluated using stable isotope techniques. When reporting overall surface emissions and percent oxidation for a landfill cover, central tendencies are typically used to report “averages” of the collected data. The objective of this study was to determine the best way to determine and report central tendencies. Results showed that 89% of the data sets of collected surface flux have lognormal distributions, 83% of the surface concentration data sets are also lognormal. Sixty seven percent (67%) of the isotope measured percent oxidation data sets are normally distributed. The distribution of data for all eleven landfills provides insight of the central tendencies of emissions, concentrations, and percent oxidation. When reporting the “average” measurement for both flux and concentration data collected at the surface of a landfill, statistical analyses provided insight supporting the use of the geometric mean. But the arithmetic mean can accurately represent the percent oxidation, as measured with the stable isotope technique. We examined correlations between surface CH₄ emissions and surface air CH₄ concentrations. Correlation of the concentration and flux values using the geometric mean proved to be a good fit (R² = 0.86), indicating that surface scans are a good way of identifying locations of high emissions.     

A land use regression model for predicting ambient volatile organic compound concentrations in Toronto,Canada

More than 25 studies have employed land use regression (LUR) models to estimate nitrogen oxides and to a lesser extent particulate matter indicators, but these methods have been less commonly applied to ambient concentrations of volatile organic compounds (VOCs). Some VOCs have high plausibility as sources of health effects and others are specific indicators of motor vehicle exhaust. We used LUR models to estimate spatial variability of VOCs in Toronto, Canada. Benzene, n-hexane and total hydrocarbons (THC) were measured from July 25 to August 9, 2006 at 50 locations using the TraceAir organic vapor monitors. Nitrogen dioxide (NO₂) was also sampled to assess its spatial pattern agreement with VOC exposures. Buffers for land use, population density, traffic density, physical geography, and remote sensing measures of greenness and surface brightness were also tested. The remote sensing measures have the highest correlations with VOCs and NO₂ levels (i.e., explains >36% of the variance). Our regression models explain 66–68% of the variance in the spatial distribution of VOCs, compared to 81% for the NO₂ model. The ranks of agreement between various VOCs range from 48 to 63% and increases substantially – up to 75% – for the top and bottom quartile groups. Agreements between NO₂ and VOCs are much smaller with an average rank of 36%. Future epidemiologic studies may therefore benefit from using VOCs as potential toxic agents for traffic-related pollutants.     

Bioconversion of dairy manure by black soldier fly (Diptera: Stratiomyidae) for biodiesel and sugar production

Modern dairies cause the accumulation of considerable quantity of dairy manure which is a potential hazard to the environment. Dairy manure can also act as a principal larval resource for many insects such as the black soldier fly, Hermetia illucens. The black soldier fly larvae (BSFL) are considered as a new biotechnology to convert dairy manure into biodiesel and sugar. BSFL are a common colonizer of large variety of decomposing organic material in temperate and tropical areas. Adults do not need to be fed, except to take water, and acquired enough nutrition during larval development for reproduction. Dairy manure treated by BSFL is an economical way in animal facilities. Grease could be extracted from BSFL by petroleum ether, and then be treated with a two-step method to produce biodiesel. The digested dairy manure was hydrolyzed into sugar. In this study, approximately 1248.6 g fresh dairy manure was converted into 273.4 g dry residue by 1200 BSFL in 21 days. Approximately 15.8 g of biodiesel was gained from 70.8 g dry BSFL, and 96.2 g sugar was obtained from the digested dairy manure. The residual dry BSFL after grease extraction can be used as protein feedstuff.     

Compensation for risks: host community benefits in siting locally unwanted facilities

This article analyzes the recent negotiations connected with siting 24 solid-waste landfills in Wisconsin. We examine the association between the type and amount of compensation paid to host communities by facility developers and the size of facilities, certain facility characteristics, the timing of negotiated agreements, the size of the host community, and the socioeconomic status of the host area. Our findings suggest that the level of compensation after adjusting for landfill capacity is positively associated with the percentage of total facility capacity dedicated to host community use, positively associated with the percentage of people of the host area who are in poverty, and larger for public facilities that accept municipal wastes. Other explanatory variables we examined, whose association with levels of compensation proved statistically insignificant, were facility size, facility status (new vs expansion), facility use (countyonly vs multicounty), timing of negotiation, host community size, and the host area education level, population density, and per capita income. We discuss the policy implications of our principal findings and future research questions in light of the persistent opposition surrounding the siting of solid-waste and other waste-management facilities.