Empirical models based on the universal soil loss equation fail to predict sediment discharges from Chesapeake Bay catchments

The Universal Soil Loss Equation (USLE) and its derivatives are widely used for identifying watersheds with a high potential for degrading stream water quality. We compared sediment yields estimated from regional application of the USLE, the automated revised RUSLE2, and five sediment delivery ratio algorithms to measured annual average sediment delivery in 78 catchments of the Chesapeake Bay watershed. We did the same comparisons for another 23 catchments monitored by the USGS. Predictions exceeded observed sediment yields by more than 100% and were highly correlated with USLE erosion predictions (Pearson r range, 0.73-0.92; p < 0.001). RUSLE2-erosion estimates were highly correlated with USLE estimates (r = 0.87; p < 001), so the method of implementing the USLE model did not change the results. In ranked comparisons between observed and predicted sediment yields, the models failed to identify catchments with higher yields (r range, -0.28-0.00; p > 0.14). In a multiple regression analysis, soil erodibility, log (stream flow), basin shape (topographic relief ratio), the square-root transformed proportion of forest, and occurrence in the Appalachian Plateau province explained 55% of the observed variance in measured suspended sediment loads, but the model performed poorly (r(2) = 0.06) at predicting loads in the 23 USGS watersheds not used in fitting the model. The use of USLE or multiple regression models to predict sediment yields is not advisable despite their present widespread application. Integrated watershed models based on the USLE may also be unsuitable for making management decisions.     

Refinery evaluation of optical imaging to locate fugitive emissions

Fugitive emissions account for approximately 50% of total hydrocarbon emissions from process plants. Federal and state regulations aiming at controlling these emissions require refineries and petrochemical plants in the United States to implement a Leak Detection and Repair Program (LDAR). The current regulatory work practice, U.S. Environment Protection Agency Method 21, requires designated components to be monitored individually at regular intervals. The annual costs of these LDAR programs in a typical refinery can exceed US$1,000,000. Previous studies have shown that a majority of controllable fugitive emissions come from a very small fraction of components. The Smart LDAR program aims to find cost-effective methods to monitor and reduce emissions from these large leakers. Optical gas imaging has been identified as one such technology that can help achieve this objective. This paper discusses a refinery evaluation of an instrument based on backscatter absorption gas imaging technology. This portable camera allows an operator to scan components more quickly and image gas leaks in real time. During the evaluation, the instrument was able to identify leaking components that were the source of 97% of the total mass emissions from leaks detected. More than 27,000 components were monitored. This was achieved in far less time than it would have taken using Method 21. In addition, the instrument was able to find leaks from components that are not required to be monitored by the current LDAR regulations. The technology principles and the parameters that affect instrument performance are also discussed in the paper.     

Single-laboratory evaluation and modification of U.S. EPA methods 7470 and 7471 for the determination of mercury in aqueous and solid hazardous wastes

The current U.S. Environmental Protection Agency (U.S. EPA) protocols for mercury determinations in aqueous and solid waste samples (SW-846 Methods 7470 and 7471) using recirculating cold-vapor atomic absorption spectrometry (CV-AAS) have been evaluated. The U.S. EPA methods are not sufficiently flexible to permit special quality control (QC) measures, have limited detectability for low-level mercury concentrations, and are plagued by spectral interferences caused by the nonspecific absorption of primary mercury radiation by volatile organic vapors. The U.S. EPA protocols have been modified in a single-laboratory study to facilitate additional QC measures, to enhance detectability for low-level mercury concentrations, and to eliminate nonspecific vapor absorption interferences. Volumetric manipulations for additional QC measures, if required, are facilitated by performing the sample digestions in Erlenmeyer flasks rather than in the current Biochemical Oxygen Demand (BOD) reduction-aeration bottles. Typical manipulations for additional QC measures that are now feasible include dilution of concentrated samples and multiple aliquot sampling for post-digestion spike and replicate analyses. Instrument detectability is improved 10-fold by using a gas sparging bottle as a dedicated reduction-aeration vessel and a silver wool-amalgamation CV-AAS system operated in an open configuration. The on-line amalgamation/thermal desorption process of the modified CV-AAS system eliminates interfering water and organic matrix vapors prior to the mercury absorption measurement. Good accuracy and precision have been obtained with the amalgamation CV-AAS system for the analyses of four reference sediment materials. The amalgamation CV-AAS measurements on the reference sediment digests have been successfully performed at absolute mercury concentration levels that are only 1 to 4 times above the instrumental detection limit of the U.S. EPA recirculating CV-AAS method.     

Trends in snowpack chemistry and comparison to National Atmospheric Deposition Program results for the Rocky Mountains, US, 1993–2004

Seasonal snowpack chemistry data from the Rocky Mountain region of the US was examined to identify long-term trends in concentration and chemical deposition in snow and in snow-water equivalent. For the period 1993–2004, comparisons of trends were made between 54 Rocky Mountain Snowpack sites and 16 National Atmospheric Deposition Program wetfall sites located nearby in the region. The region was divided into three subregions: Northern, Central, and Southern. A non-parametric correlation method known as the Regional Kendall Test was used. This technique collectively computed the slope, direction, and probability of trend for several sites at once in each of the Northern, Central, and Southern Rockies subregions. Seasonal Kendall tests were used to evaluate trends at individual sites.Significant trends occurred during the period in wetfall and snowpack concentrations and deposition, and in precipitation. For the comparison, trends in concentrations of ammonium, nitrate, and sulfate for the two networks were in fair agreement. In several cases, increases in ammonium and nitrate concentrations, and decreases in sulfate concentrations for both wetfall and snowpack were consistent in the three subregions. However, deposition patterns between wetfall and snowpack more often were opposite, particularly for ammonium and nitrate. Decreases in ammonium and nitrate deposition in wetfall in the central and southern rockies subregions mostly were moderately significant (p<0.11) in constrast to highly significant increases in snowpack (p<0.02). These opposite trends likely are explained by different rates of declining precipitation during the recent drought (1999–2004) and increasing concentration. Furthermore, dry deposition was an important factor in total deposition of nitrogen in the region. Sulfate deposition decreased with moderate to high significance in all three subregions in both wetfall and snowpack. Precipitation trends consistently were downward and significant for wetfall, snowpack, and snow-telemetry data for the central and southern rockies subregions (p<0.03), while no trends were noted for the Northern Rockies subregion.     

The influence of work‐family culture and workplace relationships on work interference with family: a multilevel model

This research tested a multilevel model examining the influence of work‐family culture and supportive workplace relationships on work interference with family. Web‐based survey data were provided by 792 information technology employees from 10 organizations. Random coefficient modeling was used to test a path model examining the relationships between work‐family culture, leader‐member exchange (LMX), coworker support, and work interference with family. The direct effects of LMX and coworker support on work interference with family were significant. The indirect effect of work‐family culture on work interference with family was also significant. Results demonstrate the value of work‐family culture in understanding supportive supervisory and coworker relationships and work interference with family and highlight the need to employ multilevel models to understand these relationships. Copyright © 2007 John Wiley & Sons, Ltd.     

Integrated Modular Modeling of Water and Nutrients From Point and Nonpoint Sources in the Patuxent River Watershed1

Abstract: We present a simple modular landscape simulation model that is based on a watershed modeling framework in which different sets of processes occurring in a watershed can be simulated separately with different models. The model consists of three loosely coupled submodels: a rainfall‐runoff model (TOPMODEL) for runoff generation in a subwatershed, a nutrient model for estimation of nutrients from nonpoint sources in a subwatershed, and a stream network model for integration of point and nonpoint sources in the routing process. The model performance was evaluated using monitoring data in the watershed of the Patuxent River, a tributary to the Chesapeake Bay in Maryland, from July 1997 through August 1999. Despite its simplicity, the landscape model predictions of streamflow, and sediment and nutrient loads were as good as or better than those of the Hydrological Simulation Program‐Fortran model, one of the most widely used comprehensive watershed models. The landscape model was applied to predict discharges of water, sediment, silicate, organic carbon, nitrate, ammonium, organic nitrogen, total nitrogen, organic phosphorus, phosphate, and total phosphorus from the Patuxent watershed to its estuary. The predicted annual water discharge to the estuary was very close to the measured annual total in terms of percent errors for both years of the study period (≤2%). The model predictions for loads of nutrients were also good (20‐30%) or very good (<20%) with exceptions of sediment (40%), phosphate (36%), and organic carbon (53%) for Year 1.     

Watershed vulnerability predictions for the Ozarks using landscape models

Forty-six broad-scale landscape metrics derived from commonly used landscape metrics were used to develop potential indicators of total phosphorus (TP) concentration, total ammonia (TA) concentration, and Escherichia coli bacteria count among 244 sub-watersheds of the Upper White River (Ozark Mountains, USA). Indicator models were developed by correlating field-based water quality measurements and contemporaneous remote-sensing-based ecological metrics using partial least squares (PLS) analyses. The TP PLS model resulted in one significant factor explaining 91% of the variability in surface water TP concentrations. Among the 18 contributing landscape model variables for the TP PLS model, the proportions of a sub-watershed that are barren and in human use were key indicators of water chemistry in the associated sub-watersheds. The increased presence and reduced fragmentation of forested areas are negatively correlated with TP concentrations in associated sub-watersheds, particularly within close proximity to rivers and streams. The TA PLS model resulted in one significant factor explaining 93% of the variability in surface water TA concentrations. The eight contributing landscape model variables for the TA PLS model were among the same forest and urban metrics for the TP model, with a similar spatial gradient trend in relationship to distance from streams and rivers within a sub-watershed. The E. coli PLS model resulted in two significant factors explaining 99.7% of the variability in E. coli cell count. The 17 contributing landscape model variables for the E. coli PLS model were similar to the TP and TA models. The integration of model results demonstrates that forest, riparian, and urban attributes of sub-watersheds affect all three models. The results provide watershed managers in the Ozark Mountains with a broad-scale vulnerability prediction tool, focusing on TP, TA, and E. coli, and are being used to prioritize and evaluate monitoring and restoration efforts in the vicinity of the White River, a major tributary to the Mississippi River and Gulf of Mexico.     

Comparison of surface emissions and subsurface distribution of cis- and trans-1,3-dichloropropene and chloropicrin in sandy field beds covered with four different plastic films

The purpose of this study was to conduct a field study at a Florida field site on surface emissions and subsurface distribution of cis-and trans-1,3-dichloropropene (1,3-D) and chloropicrin (CP) in raised beds injected with Telone C35 with four replications. A total of 16 beds were applied with Telone C35 by chisel injection and covered with four different plastic films, 4 beds for each film. Each bed was installed with five 20-cm long soil pore air probes and a surface air collection pan at arbitrarily locations along the length of each bed for sampling soil pore air and surface air, respectively, for analysis of the three biologically active compounds, cis- and trans-1,3-D and CP. We found that average concentrations of the three compounds at 20-cm depth among the beds covered with four different plastic films generally were not statistically different. Among the four beds covered with the same plastic film, average concentrations of the three compounds were statistically different only in the four metallic PE covered beds at 5 and 24 hours after injection. Volatilization rates of the three compounds among the beds covered with four different plastic films, with the exception of CP at 48 hours after injection, were not statistically different. It appeared that initial upward diffusion and volatilization flux were influenced by solar radiation. Initial subsurface concentrations of the three compounds and volatilization flux, especially cis-1,3-D, were greater in the beds on the east side of the field than that in the beds on the west side of the field. Whether or not difference in initial subsurface concentrations of the compounds between east side beds and west side beds may influence fumigant efficacy remains to be determined.     

Percentile estimation using variable censored data

Much progress has been made in recent years to address the estimation of summary statistics, using data that are subject to censoring of results that fall below the limit of detection (LOD) for the measuring instrument. Truncated data methods (e.g., Tobit regression) and multiple-imputation are two approaches for analyzing data results that are below the LOD. To apply these methods requires an assumption about the underlying distribution of the data. Because the log-normal distribution has been shown to fit many data sets obtained from environmental measurements, the common practice is to assume that measurements of environmental factors can be described by log-normal distributions. This article describes methods for obtaining estimates of percentiles and their associated confidence intervals when the results are log-normal and a fraction of the results are below the LOD. We present limited simulations to demonstrate the bias of the proposed estimates and the coverage probability of their associated confidence intervals. Estimation methods are used to generate summary statistics for 2,3,7,8-tetrachloro dibenzo-p-dioxin (2,3,7,8-TCDD) using data from a 2001 background exposure study in which PCDDs/PCDFs/cPCBs in human blood serum were measured in a Louisiana population. Because the congener measurements used in this study were subject to variable LODs, we also present simulation results to demonstrate the effect of variable LODs on the multiple-imputation process.     

Agricultural opportunities to mitigate greenhouse gas emissions

Agriculture is a source for three primary greenhouse gases (GHGs): CO(2), CH(4), and N(2)O. It can also be a sink for CO(2) through C sequestration into biomass products and soil organic matter. We summarized the literature on GHG emissions and C sequestration, providing a perspective on how agriculture can reduce its GHG burden and how it can help to mitigate GHG emissions through conservation measures. Impacts of agricultural practices and systems on GHG emission are reviewed and potential trade-offs among potential mitigation options are discussed. Conservation practices that help prevent soil erosion, may also sequester soil C and enhance CH(4) consumption. Managing N to match crop needs can reduce N(2)O emission and avoid adverse impacts on water quality. Manipulating animal diet and manure management can reduce CH(4) and N(2)O emission from animal agriculture. All segments of agriculture have management options that can reduce agriculture's environmental footprint.