United States Environmental Protection Agency

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.

Fine-particle water and pH in the southeastern United States

Abstract: . Particle water and pH are predicted using meteorological observations (relative humidity (RH), temperature (T)), gas/particle composition, and thermodynamic modeling (ISORROPIA-II). A comprehensive uncertainty analysis is included, and the model is validated. We investigate mass concentrations of particle water and related particle pH for ambient fine-mode aerosols sampled in a relatively remote Alabama forest during the Southern Oxidant and Aerosol Study (SOAS) in summer and at various sites in the southeastern US during different seasons, as part of the Southeastern Center for Air Pollution and Epidemiology (SCAPE) study. Particle water and pH are closely linked; pH is a measure of the particle H+ aqueous concentration and depends on both the presence of ions and amount of particle liquid water. Levels of particle water, in turn, are determined through water uptake by both the ionic species and organic compounds. Thermodynamic calculations based on measured ion concentrations can predict both pH and liquid water but may be biased since contributions of organic species to liquid water are not considered. In this study, contributions of both the inorganic and organic fractions to aerosol liquid water were considered, and predictions were in good agreement with measured liquid water based on differences in ambient and dry light scattering coefficients (prediction vs. measurement: slope = 0.91, intercept = 0.5 μg m−3, R2 = 0.75). ISORROPIA-II predictions were confirmed by good agreement between predicted and measured ammonia concentrations (slope = 1.07, intercept = −0.12 μg m−3, R2 = 0.76). Based on this study, organic species on average contributed 35% to the total water, with a substantially higher contribution (50%) at night. However, not including contributions of organic water had a minor effect on pH (changes pH by 0.15 to 0.23 units), suggesting that predicted pH without consideration of organic water could be sufficient for the purposes of aqueous secondary organic aerosol (SOA) chemistry. The mean pH predicted in the Alabama forest (SOAS) was 0.94 ± 0.59 (median 0.93). pH diurnal trends followed liquid water and were driven mainly by variability in RH; during SOAS nighttime pH was near 1.5, while daytime pH was near 0.5. pH ranged from 0.5 to 2 in summer and 1 to 3 in the winter at other sites. The systematically low pH levels in the southeast may have important ramifications, such as significantly influencing acid-catalyzed reactions, gas–aerosol partitioning, and mobilization of redox metals and minerals. Particle ion balances or molar ratios, often used to infer pH, do not consider the dissociation state of individual ions or particle liquid water levels and do not correlate with particle pH.

Incremental testing of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7

Abstract: . This paper describes the scientific and structural updates to the latest release of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7 (v4.7) and points the reader to additional resources for further details. The model updates were evaluated relative to observations and results from previous model versions in a series of simulations conducted to incrementally assess the effect of each change. The focus of this paper is on five major scientific upgrades: (a) updates to the heterogeneous N2O5 parameterization, (b) improvement in the treatment of secondary organic aerosol (SOA), (c) inclusion of dynamic mass transfer for coarse-mode aerosol, (d) revisions to the cloud model, and (e) new options for the calculation of photolysis rates. Incremental test simulations over the eastern United States during January and August 2006 are evaluated to assess the model response to each scientific improvement, providing explanations of differences in results between v4.7 and previously released CMAQ model versions. Particulate sulfate predictions are improved across all monitoring networks during both seasons due to cloud module updates. Numerous updates to the SOA module improve the simulation of seasonal variability and decrease the bias in organic carbon predictions at urban sites in the winter. Bias in the total mass of fine particulate matter (PM2.5) is dominated by overpredictions of unspeciated PM2.5 (PMother) in the winter and by underpredictions of carbon in the summer. The CMAQv4.7 model results show slightly worse performance for ozone predictions. However, changes to the meteorological inputs are found to have a much greater impact on ozone predictions compared to changes to the CMAQ modules described here. Model updates had little effect on existing biases in wet deposition predictions.

An indicator framework for assessing ecosystem services in support of the EU Biodiversity Strategy to 2020

Abstract: In the EU, the mapping and assessment of ecosystems and their services, abbreviated to MAES, is seen as a key action for the advancement of biodiversity objectives, and also to inform the development and implementation of related policies on water, climate, agriculture, forest, marine and regional planning. In this study, we present the development of an analytical framework which ensures that consistent approaches are used throughout the EU. It is framed by a broad set of key policy questions and structured around a conceptual framework that links human societies and their well-being with the environment. Next, this framework is tested through four thematic pilot studies, including stakeholders and experts working at different scales and governance levels, which contributed indicators to assess the state of ecosystem services. Indicators were scored according to different criteria and assorted per ecosystem type and ecosystem services using the common international classification of ecosystem services (CICES) as typology. We concluded that there is potential to develop a first EU wide ecosystem assessment on the basis of existing data if they are combined in a creative way. However, substantial data gaps remain to be filled before a fully integrated and complete ecosystem assessment can be carried out.