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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.


Papers
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Journal ArticleDOI
TL;DR: Current evidence highlighting the value of sub-lethal agents, specifically spatial repellents, and their use in global health is presented, and the primary challenges towards establishing a clearly defined and recommended role for spatial repelling products in disease control are identified.
Abstract: International public health workers are challenged by a burden of arthropod-borne disease that remains elevated despite best efforts in control programmes. With this challenge comes the opportunity to develop novel vector control paradigms to guide product development and programme implementation. The role of vector behaviour modification in disease control was first highlighted several decades ago but has received limited attention within the public health community. This paper presents current evidence highlighting the value of sub-lethal agents, specifically spatial repellents, and their use in global health, and identifies the primary challenges towards establishing a clearly defined and recommended role for spatial repellent products in disease control.

233 citations

Journal ArticleDOI
01 Jan 2014-Forestry
TL;DR: In this article, the authors presented a set of 10 consistent, national-scale aboveground biomass regression equations for US species, as well as equations for predicting biomass of tree components as proportions of total above-ground biomass.
Abstract: Historically, tree biomass at large scales has been estimated by applying dimensional analysis techniques and field measurements such as diameter at breast height (dbh) in allometric regression equations. Equations often have been developed using differing methods and applied only to certain species or isolated areas. We previously had compiled and combined (in meta-analysis) available diameter-based allometric regression equations for estimating total aboveground and component dry-weight biomass for US trees. This had resulted in a set of 10 consistent, national-scale aboveground biomass regression equations for US species, as well as equations for predicting biomass of tree components as proportions of total aboveground biomass. In this update of our published equation database and refinement of our model, we developed equations based on allometric scaling theory, using taxonomic groupings and wood specific gravity as surrogates for scaling parameters that we could not estimate. The new approach resulted in 35 theoretically based generalized equations (13 conifer, 18 hardwood, 4 woodland), compared with the previous empirically grouped 10. For trees from USDA Forest Inventory and Analysis Program (FIA) plots, with forest types grouped into conifers and hardwoods, previous and updated equations produced nearly identical estimates that predicted ~20percent higher biomass than FIA estimates. Differences were observed between previous and updated equation estimates when comparisons were made using individual FIA forest types.

233 citations

Journal ArticleDOI
TL;DR: In this article, a general theory for the flow and the generation of potential environmental impact through a chemical process has been developed, which defines six possible environmental impact indexes that characterize the potential impact within a process and the output of potential impact from a process.

233 citations

Journal ArticleDOI
TL;DR: In this article, the implicit assumption that biogenic secondary organic aerosol (SOA) is natural and can not be controlled hinders effective air quality management is examined through 3-dimensional photochemical air quality modeling.
Abstract: The implicit assumption that biogenic secondary organic aerosol (SOA) is natural and can not be controlled hinders effective air quality management. Anthropogenic pollution facilitates transformation of naturally emitted volatile organic compounds (VOCs) to the particle phase, enhancing the ambient concentrations of biogenic secondary organic aerosol (SOA). It is therefore conceivable that some portion of ambient biogenic SOA can be removed by controlling emissions of anthropogenic pollutants. Direct measurement of the controllable fraction of biogenic SOA is not possible, but can be estimated through 3-dimensional photochemical air quality modeling. To examine this in detail, 22 CMAQ model simulations were conducted over the continental U.S. (August 15 to September 4, 2003). The relative contributions of five emitted pollution classes (i.e., NOx, NH3, SOx, reactive non methane carbon (RNMC) and primary carbonaceous particulate matter (PCM)) on biogenic SOA were estimated by removing anthropogenic emissio...

233 citations

Journal ArticleDOI
TL;DR: The authors used in situ observations from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network, the Midwest Ammonia Monitoring Project, 11 surface site campaigns as well as Infrared Atmospheric Sounding Interferometer (IASI) satellite measurements with the GEOS-Chem model to investigate inorganic aerosol loading and atmospheric ammonia concentrations over the United States.
Abstract: We use in situ observations from the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network, the Midwest Ammonia Monitoring Project, 11 surface site campaigns as well as Infrared Atmospheric Sounding Interferometer (IASI) satellite measurements with the GEOS-Chem model to investigate inorganic aerosol loading and atmospheric ammonia concentrations over the United States IASI observations suggest that current ammonia emissions are underestimated in California and in the springtime in the Midwest In California this underestimate likely drives the underestimate in nitrate formation in the GEOS-Chem model However in the remaining continental United States we find that the nitrate simulation is biased high (normalized mean bias > = 10) year-round, except in Spring (due to the underestimate in ammonia in this season) None of the uncertainties in precursor emissions, the uptake efficiency of N2O5 on aerosols, OH concentrations, the reaction rate for the formation of nitric acid, or the dry deposition velocity of nitric acid are able to explain this bias We find that reducing nitric acid concentrations to 75% of their simulated values corrects the bias in nitrate (as well as ammonium) in the US However the mechanism for this potential reduction is unclear and may be a combination of errors in chemistry, deposition and sub-grid near-surface gradients This "updated" simulation reproduces PM and ammonia loading and captures the strong seasonal and spatial gradients in gas-particle partitioning across the United States We estimate that nitrogen makes up 15−35% of inorganic fine PM mass over the US, and that this fraction is likely to increase in the coming decade, both with decreases in sulfur emissions and increases in ammonia emissions

233 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