A framework and methodology for reporting geographically and temporally resolved solar data: A case study of Texas

This paper presents a framework and methodology for reporting measured solar radiation data. Geographically and temporally resolved solar data have been calculated for all 254 counties in Texas using geospatial interpolation of data from 24 existing terrestrial measurement locations. Hourly global, direct, and diffuse horizontal radiation data have been obtained from 15 measurement sites at the Texas Solar Radiation Database, a project at The University of Texas at Austin, and from 9 sites at the National Solar Radiation Database. Average radiation fluxes and peak insolation have been calculated using daylight hours in addition to the total energy in kW h/m2 day. The methodology presented in this paper provides solar insolation data in a convenient format for engineers, scientists, policy-makers, homeowners, and consumers to assess the potential of solar energy at the county resolution. This methodology enables informed decisions about the economic viability of solar installations at particular locations and with useful diurnal and seasonal fidelity. These results are presented in a series of maps, figures, and tables included in this paper.Mechanical Engineerin

ES2009-90235 Assessing the Potential for Algal Biofuels Production in Texas ES2009-90235

Abstract This paper describes a unique analytical model created to assess the maximum potential for algae production in Texas. The model, which merges engineering, biology and geosciences into a singular analysis, aims to identify suitable growth locations and estimate the quantity of algae-based oils that can be potentially produced in Texas. The model incorporates geographically-and temporally-resolved data on sunlight, anthropogenic CO 2 emissions, and saline or brackish water availability. These data are then overlaid with first-order biological approximations for algae growth calculations in order to create maps of algae growth potential. Solar insolation data were obtained from measurement locations throughout the state for varying time scales spanning many years from the Texas Solar Radiation Database (TSRDB). CO 2 emissions were compiled from area and point sources (such as natural gas and coal-fired power plants) from the Energy Information Administration and Environmental Protection Agency. Water data for wastewater treatment plants and saline aquifers were obtained from the Texas Commission on Environmental Quality and the Texas Water Development Board. A home-built MATLAB code uses these data, along with engineering approximations and the ability to manipulate different assumptions to calculate algae growth by location and time period. For each location, the model calculates potential oil yield, biomass produced, growth rates, water and CO 2 consumed and land used. Standard pond and tubular photobioreactor dimensions have been used to model real world production facilities. Realistic limits for growth rates, photosynthetic efficiencies, photosynthetic flux tolerances and oil content are also incorporated. These parameters can be varied to approximate different algae strains and growth conditions. The model assumes reactors to have ideal mixing, optimal pH and temperature controls in place

Why Do Some Lineages Radiate While Others Do Not? Perspectives for Future Research on Adaptive Radiations.

Understanding the processes that drive phenotypic diversification and underpin speciation is key to elucidating how biodiversity has evolved. Although these processes have been studied across a wide array of clades, adaptive radiations (ARs), which are systems with multiple closely related species and broad phenotypic diversity, have been particularly fruitful for teasing apart the factors that drive and constrain diversification. As such, ARs have become popular candidate study systems for determining the extent to which ecological features, including aspects of organisms and the environment, and inter- and intraspecific interactions, led to evolutionary diversification. Despite substantial past empirical and theoretical work, understanding mechanistically how ARs evolve remains a major challenge. Here, we highlight a number of understudied components of the environment and of lineages themselves, which may help further our understanding of speciation and AR. We also outline some substantial remaining challenges to achieving a detailed understanding of adaptation, speciation, and the role of ecology in these processes. These major challenges include identifying factors that have a causative impact in promoting or constraining ARs, gaining a more holistic understanding of features of organisms and their environment that interact resulting in adaptation and speciation, and understanding whether the role of these organismal and environmental features varies throughout the radiation process. We conclude by providing perspectives on how future investigations into the AR process can overcome these challenges, allowing us to glean mechanistic insights into adaptation and speciation

Infection-induced colitis in mice causes dynamic and tissue-specific changes in stress response and DNA damage leading to colon cancer

This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1207829109/-/DCSupplementalHelicobacter hepaticus-infected Rag2-/- mice emulate many aspects of human inflammatory bowel disease, including the development of colitis and colon cancer. To elucidate mechanisms of inflammation-induced carcinogenesis, we undertook a comprehensive analysis of histopathology, molecular damage, and gene expression changes during disease progression in these mice. Infected mice developed severe colitis and hepatitis by 10 wk post-infection, progressing into colon carcinoma by 20 wk post-infection, with pronounced pathology in the cecum and proximal colon marked by infiltration of neutrophils and macrophages. Transcriptional profiling revealed decreased expression of DNA repair and oxidative stress response genes in colon, but not in liver. Mass spectrometric analysis revealed higher levels of DNA and RNA damage products in liver compared to colon and infection-induced increases in 5-chlorocytosine in DNA and RNA and hypoxanthine in DNA. Paradoxically, infection was associated with decreased levels of DNA etheno adducts. Levels of nucleic acid damage from the same chemical class were strongly correlated in both liver and colon. The results support a model of inflammation-mediated carcinogenesis involving infiltration of phagocytes and generation of reactive species that cause local molecular damage leading to cell dysfunction, mutation, and cell death. There are strong correlations among histopathology, phagocyte infiltration, and damage chemistry that suggest a major role for neutrophils in inflammation-associated cancer progression. Further, paradoxical changes in nucleic acid damage were observed in tissue- and chemistry-specific patterns. The results also reveal features of cell stress response that point to microbial pathophysiology and mechanisms of cell senescence as important mechanistic links to cancer.Cancer Research Institute (CA026731)National Institute of Environmental Health Sciences (5T32-ES007020-34, Training Grant in Toxicology)National Institute of Environmental Health Sciences (ES002109)Massachusetts Institute of Technology (Merck-MIT Fellowship)German Academic Exchange Servic