The Environmental Protection Agency (EPA) provides access to information on a variety of topics related to the environment and strives to inform citizens of health risks. The EPA also has an extensive library network that consists of 26 libraries throughout the United States, which provide access to a plethora of information to EPA employees, scientists, and researchers. The EPA implemented a reorganization project to digitize their materials so they would be more accessible to a wider range of users, but this plan was drastically accelerated when the EPA was threatened with a budget cut. It chose to close and reduce the hours and services of some of their libraries. As a result, the agency was accused of denying users the “right to know” by making information unavailable, not providing an adequate strategic plan, and discarding vital materials. This case study explores the background of the digitization project, the practices implemented, and the critiques of the project.

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The Environmental Protection Agency

[i] An inventory of air pollutant emissions in Asia in the year 2000 is developed to support atmospheric modeling and analysis of observations taken during the TRACE-P experiment funded by the National Aeronautics and Space Administration (NASA) and the ACE-Asia experiment funded by the National Science Foundation (NSF) and the National Oceanic and Atmospheric Administration (NOAA). Emissions are estimated for all major anthropogenic sources, including biomass burning, in 64 regions of Asia. We estimate total Asian emissions as follows: 34.3 Tg SO 2 , 26.8 Tg NO x , 9870 Tg CO 2 , 279 Tg CO, 107 Tg CH 4 , 52.2 Tg NMVOC, 2.54 Tg black carbon (BC), 10.4 Tg organic carbon (OC), and 27.5 Tg NH 3 . In addition, NMVOC are speciated into 19 subcategories according to functional groups and reactivity. Thus we are able to identify the major source regions and types for many of the significant gaseous and particle emissions that influence pollutant concentrations in the vicinity of the TRACE-P and ACE-Asia field measurements. Emissions in China dominate the signature of pollutant concentrations in this region, so special emphasis has been placed on the development of emission estimates for China. China's emissions are determined to be as follows: 20.4 Tg SO 2 , 11.4 Tg NO x , 3820 Tg CO 2 , 116 Tg CO, 38.4 Tg CH 4 , 17.4 Tg NMVOC, 1.05 Tg BC, 3.4 Tg OC, and 13.6 Tg NH 3 . Emissions are gridded at a variety of spatial resolutions from 1° × 1° to 30 s x 30 s, using the exact locations of large point sources and surrogate GIS distributions of urban and rural population, road networks, landcover, ship lanes, etc. The gridded emission estimates have been used as inputs to atmospheric simulation models and have proven to be generally robust in comparison with field observations, though there is reason to think that emissions of CO and possibly BC may be underestimated. Monthly emission estimates for China are developed for each species to aid TRACE-P and ACE-Asia data interpretation. During the observation period of March/ April, emissions are roughly at their average values (one twelfth of annual). Uncertainties in the emission estimates, measured as 95% confidence intervals, range from a low of ±16% for SO 2 to a high of ±450% for OC.

An inventory of gaseous and primary aerosol emissions in Asia in the year 2000 : NASA global tropospheric experiment transport and chemical evolution over the pacific (TRACE-P): Measurements and analysis (TRACEP1)

Global review and synthesis of trends in observed terrestrial near-surface wind speeds; implications for evaporation

A global assessment of precipitation chemistry and deposition of sulfur, nitrogen, sea salt, base cations, organic acids, acidity and pH, and phosphorus

Eutrophication, or excessive nutrient enrichment, threatens water resources across the globe. We show that climate change–induced precipitation changes alone will substantially increase (19 ± 14%) riverine total nitrogen loading within the continental United States by the end of the century for the “business-as-usual” scenario. The impacts, driven by projected increases in both total and extreme precipitation, will be especially strong for the Northeast and the corn belt of the United States. Offsetting this increase would require a 33 ± 24% reduction in nitrogen inputs, representing a massive management challenge. Globally, changes in precipitation are especially likely to also exacerbate eutrophication in India, China, and Southeast Asia. It is therefore imperative that water quality management strategies account for the impact of projected future changes in precipitation on nitrogen loading.

Eutrophication will increase during the 21st century as a result of precipitation changes.

http://agis.ucdavis.edu/publications/2009/Climate%20change%20sensitivity%20assessment%20of%20a%20highly%20agricultural%20watershed.pdf

Climate change sensitivity assessment of a highly agricultural watershed using SWAT

Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm

Spatiotemporal prediction of daily ambient ozone levels across China using random forest for human exposure assessment.

A novel model named random-forest-spatiotemporal-kriging (RF-STK) was developed to estimate the daily ambient NO2 concentrations across China during 2013–2016 based on the satellite retrievals and geographic covariates. The RF-STK model showed good prediction performance, with cross-validation R2 = 0.62 (RMSE = 13.3 μg/m3) for daily and R2 = 0.73 (RMSE = 6.5 μg/m3) for spatial predictions. The nationwide population-weighted multiyear average of NO2 was predicted to be 30.9 ± 11.7 μg/m3 (mean ± standard deviation), with a slowly but significantly decreasing trend at a rate of −0.88 ± 0.38 μg/m3/year. Among the main economic zones of China, the Pearl River Delta showed the fastest decreasing rate of −1.37 μg/m3/year, while the Beijing-Tianjin Metro did not show a temporal trend (P = 0.32). The population-weighted NO2 was predicted to be the highest in North China (40.3 ± 10.3 μg/m3) and lowest in Southwest China (24.9 ± 9.4 μg/m3). Approximately 25% of the population lived in nonattainment areas with annual...

Satellite-Based Estimates of Daily NO2 Exposure in China Using Hybrid Random Forest and Spatiotemporal Kriging Model.

[1] Pan‐evaporation (Epan) as the indicator of atmospheric evaporative demand has decreased worldwide with climate change in the last decades, which is called “Pan Evaporation Paradox”. This study investigates the recent changes in Epan dynamics in China using the observed Epan records for the period 1960–2007. The records show that Epan decreased in China from 1960 to 1991 by �5.4 mm yr �2 . The attribution results show that the significant decreases (P 0.1). The results show that increasing air temperature dominated the change in Epan, which offset the effect of wind speed and led to the increase in Epan. Citation: Liu, X., Y. Luo, D. Zhang, M. Zhang, and C. Liu (2011), Recent changes in pan‐evaporation dynamics in China, Geophys. Res. Lett., 38, L13404, doi:10.1029/2011GL047929.

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Yuzhou Luo

Papers

Climate change sensitivity assessment of a highly agricultural watershed using SWAT

Spatiotemporal prediction of continuous daily PM2.5 concentrations across China using a spatially explicit machine learning algorithm

Spatiotemporal prediction of daily ambient ozone levels across China using random forest for human exposure assessment.

Satellite-Based Estimates of Daily NO2 Exposure in China Using Hybrid Random Forest and Spatiotemporal Kriging Model.

Recent changes in pan-evaporation dynamics in China