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.

Comparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points

Abstract: Support vector machine (SVM) was applied for land-cover characterization using MODIS time-series data Classification performance was examined with respect to training sample size, sample variability, and landscape homogeneity (purity) The results were compared to two conventional nonparametric image classification algorithms: multilayer perceptron neural networks (NN) and classification and regression trees (CART) For 2001 MODIS time-series data, SVM generated overall accuracies ranging from 77% to 80% for training sample sizes from 20 to 800 pixels per class, compared to 67–76% and 62–73% for NN and CART, respectively These results indicated that SVM’s had superior generalization capability, particularly with respect to small training sample sizes There was also less variability of SVM performance when classification trials were repeated using different training sets Additionally, classification accuracies were directly related to sample homogeneity/heterogeneity The overall accuracies for the SVM algorithm were 91% (Kappa = 077) and 64% (Kappa = 034) for homogeneous and heterogeneous pixels, respectively The inclusion of heterogeneous pixels in the training sample did not increase overall accuracies Also, the SVM performance was examined for the classification of multiple year MODIS time-series data at annual intervals Finally, using only the SVM output values, a method was developed to directly classify pixel purity Approximately 65% of pixels within the Albemarle–Pamlico Basin study area were labeled as “functionally homogeneous” with an overall classification accuracy of 91% (Kappa = 079) The results indicated a high potential for regional scale operational land-cover characterization applications

Degradation of bromothymol blue by ‘greener’ nano-scale zero-valent iron synthesized using tea polyphenols

Abstract: A green single-step synthesis of iron nanoparticles using tea (Camellia sinensis) polyphenols is described that uses no additional surfactants/polymers as capping or reducing agents. The expedient reaction between polyphenols and ferric nitrate occurs within a few minutes at room temperature and is indicated by color changes from pale yellow to dark greenish/black in the formation of iron nanoparticles. The synthesized iron nanoparticles were characterized using transmission electron microscopy (TEM), UV-visible and X-ray diffraction pattern (XRD). The obtained nanoparticles were utilized to catalyze hydrogen peroxide for treatment of organic contamination and results were compared with Fe-EDTA and Fe-EDDS. Bromothymol blue, a commonly deployed pH indicator, is used here as a model contaminant for free radical reactions, due to its stability in the presence of H2O2 and its absorbance in the visible range at pH 6. The concentration of bromothymol blue is conveniently monitored using ultraviolet-visible (UV-Vis) spectroscopy during treatment with iron-catalyzed H2O2. Various concentrations of iron are tested to allow for the determination of initial rate constants for the different iron sources.

Colloidal Properties and Stability of Graphene Oxide Nanomaterials in the Aquatic Environment

Abstract: While graphene oxide (GO) has been found to be the most toxic graphene-based nanomaterial, its environmental fate is still unexplored. In this study, the aggregation kinetics and stability of GO were investigated using time-resolved dynamic light scattering over a wide range of aquatic chemistries (pH, salt types (NaCl, MgCl2, CaCl2), ionic strength) relevant to natural and engineered systems. Although pH did not have a notable influence on GO stability from pH 4 to 10, salt type and ionic strength had significant effects on GO stability due to electrical double layer compression, similar to other colloidal particles. The critical coagulation concentration (CCC) values of GO were determined to be 44 mM NaCl, 0.9 mM CaCl2, and 1.3 mM MgCl2. Aggregation and stability of GO in the aquatic environment followed colloidal theory (DLVO and Schulze-Hardy rule), even though GO’s shape is not spherical. CCC values of GO were lower than reported fullerene CCC values and higher than reported carbon nanotube CCC value...