Thermodynamic evaluation of solar integration into a natural gas combined cycle power plant
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Engineered nanomaterials (ENMs) are currently widely incorporated in the outdoor urban environmental fabric and numerous new applications and products containing ENMs are expected in the future. As has been shown repeatedly, products containing ENMs have the potential, at some point in their lifetime, to release ENMs into their surrounding environment. However, the expanding body in environmental nanomaterial research has not yet shifted toward ENMs in the context of the complex outdoor urban environment. This is especially surprising because the world's human populations are on a steady march toward more and more urbanization and technological development, accompanied with increased applications for ENMs in the outdoor urban environment. Our objective for this paper is therefore to review, assess, and provide new information in this emerging field. We provide an overview of nanomaterials (NMs, encompassing both ENMs and incidental nanomaterials, INMs) that are likely to be released in the urban environment from outdoor sources by discussing 1) the applications of ENMs that may lead to release of ENMs in urban areas, 2) the recently published data on the release of ENMs from novel nano-enabled applications in the outdoor urban environment, 3) the available literature on the occurrence of INMs in the atmosphere and within/on dust particles, and 4) the potential pathways and fate of NMs in the outdoor urban environment. This review is then followed by three case studies demonstrating the importance of NMs in the outdoor urban environment. The first and second case studies illustrate the occurrence of NMs in urban dust and stormwater ponds, respectively, whereas the third case study discusses the lessons learned from the release of NMs (e.g. Pt, ph and Rh) from automotive vehicle catalytic convertors. This article ends with a discussion of the research priorities needed to advance this emerging field of “outdoor urban nanomaterials” and to assess the potential risks of NMs in the context of urban environments.
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A 5-year, 1-minute resolution observational dataset of clouds and solar radiation was produced that includes two metrics of the variability in surface solar irradiance due to cloud type and fractional sky cover. Multiple regression models were trained to fit observations of surface solar irradiance variability from those two cloud property predictors. We found that ensemble tree-based methods, Random Forest and Gradient Boosting Machine, have the least overfitting issues and showed the best performance with an R2 of 0.42. While the observational data trained in this study was only from one site, the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma, initial comparisons of the seasonality of the statistics suggest that these results are relatively weather regime independent; the generality of such a finding across sites will be tested in future work. The observational data and developed machine learning model are being used to create a numerical weather prediction model parameterization to enable day-ahead solar variability prediction in a computationally efficient way. This is a first step towards creating a new paradigm of predicting day-ahead variability with the potential to provide a new tool to improve grid operation, planning, and resilience.
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Isopentenyl pyrophosphate (IPP) toxicity presents a challenge in engineered microbial systems since its formation is unavoidable in terpene biosynthesis. In this work, we develop an experimental platform to study IPP toxicity in isoprenol-producing Escherichia coli. We first characterize the physiological response to IPP accumulation, demonstrating that elevated IPP levels are linked to growth inhibition, reduced cell viability, and plasmid instability. We show that IPP toxicity selects for pathway “breakage”, using proteomics to identify a reduction in phosphomevalonate kinase (PMK) as a probable recovery mechanism. Next, using multi-omics data, we demonstrate that endogenous E. coli metabolism is globally impacted by IPP accumulation, which slows nutrient uptake, decreases ATP levels, and perturbs nucleotide metabolism. We also observe the extracellular accumulation of IPP and present preliminary evidence that IPP can be transported by E. coli, findings that might be broadly relevant for the study of isoprenoid biosynthesis. Finally, we discover that IPP accumulation leads to the formation of ApppI, a nucleotide analog of IPP that may contribute to observed toxicity phenotypes. This comprehensive assessment of IPP stress suggests potential strategies for the alleviation of prenyl diphosphate toxicity and highlights possible engineering targets for improved IPP flux and high titer isoprenoid production.