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Institution

United States Environmental Protection Agency

GovernmentWashington D.C., District of Columbia, United States
About: United States Environmental Protection Agency is a government organization based out in Washington D.C., District of Columbia, United States. It is known for research contribution in the topics: Population & Environmental exposure. The organization has 13873 authors who have published 26902 publications receiving 1191729 citations. The organization is also known as: EPA & Environmental Protection Agency.


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Journal ArticleDOI
TL;DR: In this paper, the degradation of trichloroethene (TCE) at 2 mg L{sup {minus}1} in headspace free aqueous solution by zerovalent iron (Fe{sup 0}) and tin (Sn{sup0}) was studied in batch tests at 10, 25, 40, and 55 C.
Abstract: The degradation of trichloroethene (TCE) at 2 mg L{sup {minus}1} in headspace free aqueous solution by zerovalent iron (Fe{sup 0}) and tin (Sn{sup 0}) was studied in batch tests at 10, 25, 40, and 55 C and HCl-treated Fe{sup 0} and Sn{sup 0} at 25 and 55 C. Surface area normalized pseudo-first-order rate constants (k{sub SA}) ranged from 0.44 {times} 10{sup {minus}3} to 4.3 {times} 10{sup {minus}3} h{sup {minus}1} m{sup {minus}2} L for Fisher Fe{sup 0}, 0.029 {times} 10{sup {minus}3} to 0.27 {times} 10{sup {minus}3} h{sup {minus}1} m{sup {minus}2} L for Peerless and Master Builders Fe{sup 0}, and 0.011 {times} 10{sup {minus}3} to 1.31 {times} 10{sup {minus}3} h{sup {minus}1} m{sup {minus}2} L for Fisher and Aldrich Sn{sup 0}. The Aldrich Fe{sup 0} was the least reactive with k{sub SA} values ranging from 0.0016 {times} 10{sup {minus}3} to 0.011 {times} 10{sup {minus}3}j{sup {minus}1} m{sup {minus}2} L. The HCl-washing increased metal surface area and observed rate constant (k) values but generally decreased k{sub SA} values. The calculated apparent activation energy (E{sub a}) using the Arrhenius law for the four temperature levels ranged from 32.2 to 39.4 mol{sup {minus}1} for the untreated Fe{sup 0} metals and 40.5--76.8 kJ mol{sup {minus}1} for the untreatedmore » Sn{sup 0} metals. Greater temperature effect was observed for Sn{sup 0} than for Fe{sup 0}. Their results indicate that TCE reduction by Fe{sup 0} and Sn{sup 0} is likely controlled primarily by chemical reaction-limited kinetics rather than by mass transport of the TCE to the metal surface. Both reductive {beta}-elimination reaction and hydrogenolysis reaction are likely involved in the reduction of TCE by both Fe{sup 0} and Sn{sup 0}.« less

258 citations

Journal ArticleDOI
TL;DR: In this paper, adverse outcome pathways, constructs depicting linkages between mechanism-based molecular initiating events and impacts on individuals or populations, to assess how chemical and climate-specific variables interact to lead to adverse outcomes.
Abstract: Incorporation of global climate change (GCC) effects into assessments of chemical risk and injury requires integrated examinations of chemical and nonchemical stressors. Environmental variables altered by GCC (temperature, precipitation, salinity, pH) can influence the toxicokinetics of chemical absorption, distribution, metabolism, and excretion as well as toxicodynamic interactions between chemicals and target molecules. In addition, GCC challenges processes critical for coping with the external environment (water balance, thermoregulation, nutrition, and the immune, endocrine, and neurological systems), leaving organisms sensitive to even slight perturbations by chemicals when pushed to the limits of their physiological tolerance range. In simplest terms, GCC can make organisms more sensitive to chemical stressors, while alternatively, exposure to chemicals can make organisms more sensitive to GCC stressors. One challenge is to identify potential interactions between nonchemical and chemical stressors affecting key physiological processes in an organism. We employed adverse outcome pathways, constructs depicting linkages between mechanism-based molecular initiating events and impacts on individuals or populations, to assess how chemical- and climate-specific variables interact to lead to adverse outcomes. Case examples are presented for prospective scenarios, hypothesizing potential chemical–GCC interactions, and retrospective scenarios, proposing mechanisms for demonstrated chemical–climate interactions in natural populations. Understanding GCC interactions along adverse outcome pathways facilitates extrapolation between species or other levels of organization, development of hypotheses and focal areas for further research, and improved inputs for risk and resource injury assessments. Environ. Toxicol. Chem. 2013;32:32–48. © 2012 SETAC

258 citations

Journal ArticleDOI
TL;DR: A simple, fully model-based strategy to downscale the output from numerical models to point level and it is superior to both Bayesian melding and ordinary kriging in terms of predictive performance; predictions obtained with the method are better calibrated and predictive intervals have empirical coverage closer to the nominal values.
Abstract: Often, in environmental data collection, data arise from two sources: numerical models and monitoring networks. The first source provides predictions at the level of grid cells, while the second source gives measurements at points. The first is characterized by full spatial coverage of the region of interest, high temporal resolution, no missing data but consequential calibration concerns. The second tends to be sparsely collected in space with coarser temporal resolution, often with missing data but, where recorded, provides, essentially, the true value. Accommodating the spatial misalignment between the two types of data is of fundamental importance for both improved predictions of exposure as well as for evaluation and calibration of the numerical model. In this article we propose a simple, fully model-based strategy to downscale the output from numerical models to point level. The static spatial model, specified within a Bayesian framework, regresses the observed data on the numerical model output using spatially-varying coefficients which are specified through a correlated spatial Gaussian process.As an example, we apply our method to ozone concentration data for the eastern U.S. and compare it to Bayesian melding (Fuentes and Raftery 2005) and ordinary kriging (Cressie 1993; Chiles and Delfiner 1999). Our results show that our method outperforms Bayesian melding in terms of computing speed and it is superior to both Bayesian melding and ordinary kriging in terms of predictive performance; predictions obtained with our method are better calibrated and predictive intervals have empirical coverage closer to the nominal values. Moreover, our model can be easily extended to accommodate for the temporal dimension. In this regard, we consider several spatio-temporal versions of the static model. We compare them using out-of-sample predictions of ozone concentration for the eastern U.S. for the period May 1-October 15, 2001. For the best choice, we present a summary of the analysis. Supplemental material, including color versions of Figures 4, 5, 6, 7, and 8, and MCMC diagnostic plots, are available online.

258 citations

Journal ArticleDOI
TL;DR: In this article, the authors propose a transdisciplinary approach centered upon shared principles, an ecosystem services definition, and a classification system, which provides a common set of ecosystem goods and services that serves as the focus for and connection among multiple disciplines.

257 citations

Journal ArticleDOI
TL;DR: Of these methods, membrane-based separation processes (MBSPs) are effective over the conventional techniques for providing clean water from wastewater streams at an affordable cost with minimum energy requirement.

257 citations


Authors

Showing all 13926 results

NameH-indexPapersCitations
Joel Schwartz1831149109985
Timothy A. Springer167669122421
Chien-Jen Chen12865566360
Matthew W. Gillman12652955835
J. D. Hansen12297576198
Dionysios D. Dionysiou11667548449
John P. Giesy114116262790
Douglas W. Dockery10524457461
Charles P. Gerba10269235871
David A. Savitz9957232947
Stephen Polasky9935459148
Judith C. Chow9642732632
Diane R. Gold9544330717
Scott L. Zeger9537778179
Rajender S. Varma9567237083
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202356
202279
2021780
2020787
2019852
2018929