Analysis of a system for remote, dry removal of solidified mixed waste

This paper describes a novel technology for the removal of solidified radioactive waste from underground storage tanks at the DOE Hanford site in southeast Washington. The process involves the use of a unique high pressure system which pulverizes the hardened saltcake with stainless steel pellets to a powder for easy vacuum removal. The steel pellets can be magnetically separated from the waste material for re-use. Specifically this study analyzes the effects of various steel abrasives, pressure of the air stream, and stand-off distance on removal rates and penetration depth on simulated saltcake samples using the high pressure technique. A full-scale test set-up and protocol were implemented to allow for comprehensive testing. To insure reproducibility of the method, tests were then run for the optimum removal parameters. A time-dependent test was also conducted to determine the relationship of removal rates to length of pressure blasts. The results of these tests revealed that stand-off distance and pressure could be positively correlated to removal volumes. Additionally, a statistical analysis confirmed that nozzle angle is independent of removal rate. This study demonstrated that the pellet ‘blaster’ technique is a safe, effective method for removal of radioactive wastes without any increase in either waste mass or volume.     

Reform,Justice, and Sovereignty: A Food Systems Agenda for Environmental Communication

Food ecologies and economies are vital to the survival of communities, non-human species, and our planet. While environmental communication scholars have legitimated food as a topic of inquiry, the entangled ecological, cultural, economic, racial, colonial, and alimentary relations that sustain food systems demand greater attention. In this essay, we review literature within and beyond environmental communication, charting the landscape of critical food work in our field. We then illustrate how environmental justice commitments can invigorate interdisciplinary food systems-focused communication scholarship articulating issues of, and critical responses to, injustice and inequity across the food chain. We stake an agenda for food systems communication by mapping three orientations—food system reform, justice, and sovereignty—that can assist in our critical engagements with and interventions into the food system. Ultimately, we entreat environmental communication scholars to attend to the bends, textures, and confluences of these orientations so that we may deepen our future food-related inquiries.     

Human–nature connectedness as a ‘treatment’ for pro-environmental behavior: making the case for spatial considerations

The degree to which an individual feels connected to the natural world can be a positive predictor of pro-environmental behavior (PEB). This has led to calls to ‘reconnect to nature’ as a ‘treatment’ for PEB. What is not clear is the relationship between where one feels connected to nature and where one acts pro-environmentally. We propose that integrating spatial scale into the conceptualization of these constructs will provide insights into how different degrees of connectedness influence pro-environmental behavior. We discuss trends towards a spatial understanding of human–nature connectedness (HNC) and introduce three archetypes that highlight scalar relationships between scale of connectedness and scale of pro-environmental behavior: (1) equal interactions, (2) embedded interactions, and (3) extended interactions. We discuss potential policy and practice implications of taking a spatially explicit approach to HNC–PEB research, and propose a research agenda for investigating these scalar relationships that can inform nature as a ‘treatment’ intervention.     

Impact of roadside noise barriers on particle size distributions and pollutants concentrations near freeways

Increasing epidemiological evidence has established an association between a host of adverse health effects and exposure to ambient particulate matter (PM) and co-pollutants, especially those emitted from motor vehicles. Although PM and their co-pollutants dispersion profiles near the open freeway have been extensively characterized by means of both experimental measurements and numerical simulations in recent years, such investigations near freeways with roadside barriers have not been well documented in the literature. A few previous studies suggested that the presence of roadside structures, such as noise barriers and vegetation, may impact the decay of pollutant concentrations downwind of the freeway by limiting the initial dispersion of traffic emissions and increasing their vertical mixing due to the upward deflection of airflow. Since the noise barriers are now common roadside features of the freeways, particularly those running through populated urban areas, it is pertinent to investigate the impact of their presence on the particles and co-pollutants concentrations in areas adjacent to busy roadways. This study investigated two highly trafficked freeways (I-710 and I-5) in Southern California, with two sampling sites for each freeway, one with and the other without the roadside noise barriers. Particle size distributions and co-pollutants concentrations were measured in the immediate proximity of freeways and at different distances downwind of the freeways. The results showed the formation of a “concentration deficit” zone in the immediate vicinity of the freeway with the presence of roadside noise barrier, followed by a surge of pollutant concentrations further downwind at 80–100 m away from freeway. The particle and co-pollutants concentrations reach background levels at farther distances of 250–400 m compared to 150–200 m at the sites without roadside noise barriers.     

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

An integrated exposure model was developed that estimates nitrogen dioxide (NO(2)) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO(2) taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO(2) measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO(2) levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.     

Effects of the pharmaceuticals gemfibrozil and diclofenac on biomarker expression in the zebra mussel (Dreissena polymorpha) and their comparison with standardised toxicity tests

Pharmaceuticals, including the lipid regulator gemfibrozil and the non-steroidal anti-inflammatory drug diclofenac have been identified in waste water treatment plant effluents and receiving waters throughout the western world. The acute and chronic toxicity of these compounds was assessed for three freshwater species (Daphnia magna,Pseudokirchneriella subcapitata, Lemna minor) using standardised toxicity tests with toxicity found in the non-environmentally relevant mid mg L⁻¹ concentration range. For the acute endpoints (IC₅₀ and EC₅₀) gemfibrozil showed higher toxicity ranging from 29 to 59 mg L⁻¹ (diclofenac 47-67 mg L⁻¹), while diclofenac was more toxic for the chronic D. magna 21 d endpoints ranging from 10 to 56 mg L⁻¹ (gemfibrozil 32-100 mg L⁻¹). These results were compared with the expression of several biomarkers in the zebra mussel (Dreissena polymorpha) 24 and 96 h after exposure by injection to concentrations of 21 and 21,000 μg L⁻¹ corresponding to nominal concentrations of 1 and 1000 μg L⁻¹. Exposure to gemfibrozil and diclofenac at both concentrations significantly increased the level of lipid peroxidation, a biomarker of damage. At the elevated nominal concentration of 1000 μg L⁻¹ the biomarkers of defence glutathione transferase and metallothionein were significantly elevated for gemfibrozil and diclofenac respectively, as was DNA damage after 96 h exposure to gemfibrozil. No evidence of endocrine disruption was observed using the alkali-labile phosphate technique. Results from this suite of biomarkers indicate these compounds can cause significant stress at environmentally relevant concentrations acting primarily through oxidation pathways with significant destabilization of the lysosomal membrane and that biomarker expression is a more sensitive endpoint than standardised toxicity tests.     

Emission factors for high-emitting vehicles based on on-road measurements of individual vehicle exhaust with a mobile measurement platform

Fuel-based emission factors for 143 light-duty gasoline vehicles (LDGVs) and 93 heavy-duty diesel trucks (HDDTs) were measured in Wilmington, CA using a zero-emission mobile measurement platform (MMP). The frequency distributions of emission factors of carbon monoxide (CO), nitrogen oxides (NO(x)), and particle mass with aerodynamic diameter below 2.5 microm (PM2.5) varied widely, whereas the average of the individual vehicle emission factors were comparable to those reported in previous tunnel and remote sensing studies as well as the predictions by Emission Factors (EMFAC) 2007 mobile source emission model for Los Angeles County. Variation in emissions due to different driving modes (idle, low- and high-speed acceleration, low- and high-speed cruise) was found to be relatively small in comparison to intervehicle variability and did not appear to interfere with the identification of high emitters, defined as the vehicles whose emissions were more than 5 times the fleet-average values. Using this definition, approximately 5% of the LDGVs and HDDTs measured were high emitters. Among the 143 LDGVs, the average emission factors of NO(x), black carbon (BC), PM2.5, and ultrafine particle (UFP) would be reduced by 34%, 39%, 44%, and 31%, respectively, by removing the highest 5% of emitting vehicles, whereas CO emission factor would be reduced by 50%. The emission distributions of the 93 HDDTs measured were even more skewed: approximately half of the NO(x) and CO fleet-average emission factors and more than 60% of PM2.5, UFP, and BC fleet-average emission factors would be reduced by eliminating the highest-emitting 5% HDDTs. Furthermore, high emissions of BC, PM2.5, and NO(x) tended to cluster among the same vehicles.     

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.