SUNY College of Environmental Science and Forestry
SUNY College of Environmental Science and Forestry: Digital Commons @ ESF (State University of New York)Not a member yet
1478 research outputs found
Sort by
Alternative Energy in the Andean Highlands
Get PDFAbra Malagá Thastayoc is a rural Andean community consisting of approximately 150 Quechua- speaking inhabitants practicing self-sufficient agriculture, pastoralism and traditional weaving techniques. Many in the community earn less than $1.50 per day and survive on the papa nativa (native potato) as well as their livestock consisting of llama, alpaca, pigs, cows, sheep, chickens, and guinea pigs (Abra Malaga, 2013). To supplement their crops and livestock, men work as guides on the Inca trail or work construction, and women can at times sell their textiles.
Similar to many rural communities in Peru, this community lacks a connection to the electrical grid and there is little chance of this happening in the future. Most local households do not have lighting, and community members have to travel approximately 40 km to charge basic electrical devices. Due to limited governmental action in the distribution of electricity to small communities in the Andean Highlands, Abra Malaga was seeking partnerships to complete a project to provide electricity to their community. In 2006, a Cusco, Peru non-profit, Asociacion Ecosistemas Andinos (ECOAN), began the installation of solar panels for a school house as well as for homes in high visibility areas (Vilcanota Project, 2014). The State University of New York College of Environmental Science and Forestry Engineering for a Sustainable Society (ESF-ESS) student organization became connected with Abra Malaga through ECOAN in August 2012 and has continued to support this electrification project, hereby referred to as the project (Decker, 2014).
Through this partnership, the project has provided accessible sources of electricity to nearly twenty households in Abra Malagá Thastayoc using off-grid alternative energy sources while also developing a sustainable model for rural electrification in the Peruvian highlands. The project included the installation of two micro-hydro systems, one low and one high head, and 12 solar panels
“Green” Synthesis of Compounds with Biomedical Significance Facilitated by Water-Soluble Dendritic-Palladium Complexes
Get PDFThe Suzuki-Miyaura cross-coupling reaction (Suzuki reaction) is a highly efficient method of Carbon-Carbon bond formation, making it widely used in the synthesis of biaryl intermediates of pharmaceuticals. The coupling is conventionally performed at elevated temperatures and in organic solvents leading to adverse economic and environmental impacts. Previous studies in our group suggest that water soluble dendrimers, able to complex palladium, are viable Suzuki catalysts able to afford quantitative yields of the target compounds in water at close to ambient temperatures. They are, however, not ideal for catalyzing the reaction between hydrophobic reagents due to lack of contact with water-insoluble substrates. The goals of this study are to design and test water-soluble dendritic-palladium complexes containing a hydrophobic core, able to solubilize and selectively bind hydrophobic substances, in an attempt to improve the spatial arrangement of the catalyst and reagents in water. The structure of these novel “green” catalysts consists of calix[n]arene (n= 4,6,8) as the central core with water soluble poly(ester-ether) dendrons attached at the upper rim of the cycle (see figure below). The progress in the synthesis of these unique macromolecules by Williamson ether synthesis and Cu(I)-catalyzed alkyne-azide cycloaddition is reported. Our ability to reproducibly form the depicted compound with chemical and structural purity is confirmed by diverse analyses (NMR, MALDI-TOF, DLS, ICP and TEM). Upon completion, this work aims to achieve unprecedented yields for the Suzuki reaction in water and produce the first Suzuki catalyst to mimic enzymatic character by selectively incorporating reagents
Introduction of Yeast Genes into the Green Alga, Chlamydomonas reinhardtii, to Promote Algal Flocculation
Get PDFThe ability of the flocculin (FLO) gene family, from the yeast Saccharomyces cerevisiae, to induce flocculation in green algae was investigated. Three genes of interest, FLO9, FLO10, and FLO11, were transformed into the high transgene-expressing Chlamydomonas reinhardtii strains, UVM4 and UVM11. Successfully transformed strains that contained the FLO9 gene were identified and confirmed by PCR. Of these, several showed a potential flocculating phenotype. Western Blot analysis on soluble extracts from the transformed strains identified candidate protein bands of the expected molecular weight in two of the transformed strains. Transformation and identification of transformants containing the FLO10 and FLO11 genes is in progress. Availability of naturally flocculating algal strains is expected to reduce the overall cost of biofuel production from algae
Deregulation of fatty acid transport in Escherichia coli for enhanced control of biodegradable plastic copolymer production
Get PDFPolyhydroxyalkanoates (PHA) are one possible alternative for petroleum-based plastics that have been shown to be produced effectively in bacterial systems utilizing fatty acids. The global regulatory genes arcA and ompR are known to regulate steps involved in fatty acid transport and metabolism, making them promising candidates for research. In this study, we deleted the arcA and ompR genes in order to deregulate fatty acid uptake. To measure the effect of these deletions, copolymers were produced using recombinant E. coli and the repeating unit composition was analyzed. Residual fatty acid levels in media were also measured to determine a difference in uptake. Fatty acid transport was significantly altered in the arcA mutant, which depleted twice as much dodecanoic acid as the control strain LSBJ. The arcA mutant also showed significantly increased PHA production, measured at 30.64% (by weight) PHA, compared to 21.47% in LSBJ. Other mutants did not show significant changes. These results show that arcA is a promising mutant for increased production of PHA, and that increasing intracellular dodecanoic acid concentration has no effect on the ratio of monomers in PHA produced. This could open up new areas of research into producing plastics with very specific properties, giving PHAs a wide array of modern applications
Use of Soil Apparent Electrical Conductance to Develop a Soil Drainage Class Map for a Clearcut Plot in Heiberg Forest Using Geostatistical Analysis
Get PDFSoil apparent electrical conductivity (ECa) has been shown to be a useful predictor in agricultural applications to determine variances in soil physical and chemical properties. In this study soil ECa data were collected from an 11.8 acre clearcut plot at the Heiberg Forest near Tully, New York on June 6th 2012. A geostatistical model was created to develop an ECa prediction surface, which was used to develop a soil drainage class prediction map of the site. The drainage class map was produced by calibrating the ECa model values to correspond to the drainage classes observed at test pits dug on the site. Final output of the soil drainage class prediction model produced a 2-m spatial resolution accuracy of 86%. Soil ECa data coupled with directed site sampling can provide high spatial resolution drainage class maps for use in forestry applications
Effects of landscape composition and structure on abundance and distribution of urban white-tailed deer
Get PDFExpanding urban white-tailed deer populations are causing concerns for wildlife professionals and residents. I used distance sampling to estimate deer population density and abundance in the eastside communities of Syracuse, New York. I estimated a population size of between 93 - 159 deer (mean: 121) for 28.9 square kilometers of the study area. I classified high resolution orthoimagery and identified patches of cover with deer behavior thresholds and an animal-centric delineation algorithm. I predicted deer abundance from binomial mixture models and a suite of landscape covariates. Model weight of evidence supported variables corresponding to cover, food, and water constituents on the landscape. Deer population density predicted from abundance modeling was 73% higher than the distance sampling estimate indicating a substantial bias. Because assumptions associated with distance sampling and mixture modeling were reasonably met, low encounter rates with deer during sunrise surveys are the probable cause of the observed discrepancy