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Integrated assessment models (IAMs) are playing an increasingly important role in long-run sustainability analysis. At their core is a set of global economic and environmental accounts which capture a complete set of inter-industry and inter-regional relationships in the global economy in a consistent manner. While much attention is focused on the raw data and parameterization required to expand or add sectoral detail to IAMs, only rarely is there discussion of how different matrix balancing methods (i.e. translating disparate raw data sources into the consistent database) affect modeling results. This article offers an in-depth look into the database–modeling nexus in IAMs, focusing on the electric power sector which is both a major source of CO2 emissions and a critical vehicle for climate change mitigation. Comparisons of the prevailing matrix balancing algorithms show how the choice of database reconciliation methodology affects modeling results using policy-relevant simulations in the context of the electric power sector. The resulting insights can be applied to the disaggregation of other, technology rich sectors in the economy. We conclude that appropriate selection of database reconciliation methodologies can reduce the deviation between bottom-up and top-down modeling.

Abstract The upward energy demand, along with the depletion of conventional energy sources, demands improved utilization of renewable energy resources. Among all renewable energy resources, solar energy is the most appropriate alternative to conventional energy sources owing to its inexhaustibility and green property. Solar collectors are devices that convert solar radiation into heat or energy. However, the efficiency of the solar collector is still not adequate. The competent step to enhance the efficiency of the solar collector is to use nanofluids. This study is carried out different phases viz. characterization and stabilization while both qualitative and quantitative methods used to evaluate the stability of nanofluids thermophysical properties of Al2O3 and CNC nanofluids such as thermal conductivity measured at four different temperature using KD2 Pro, viscosity and specific heat determined at similar temperature range by viscometer and differential scanning calorimetry respectively. The experiment is executed with a fixed flow rate and in steady-state conditions under extensive solar radiation. The experimental study has revealed that up to 2.48% and 8.46% efficiency of solar collector enhanced by using 0.5% Al2O3 and 0.5% CNC nanofluids respectively. Moreover, nanofluids show good to moderate stability performance. Besides, the thermal conductivity of nanofluids increased while viscosity is in a decreasing trend with increasing temperature. Nanofluids could enhance the efficiency of a flat-plate solar collector.

Abstract It is well known that Espinosa-parades et al. (Espinosa-Paredes et al., 2011) proposed a fractional neutron point kinetic (FNPK) model with multi-group of delayed neutrons to describe dynamic behavior in a nuclear reactor. In (Aboanber and Nahla, 2016b), Aboanber and Nahla presented an extension of Espinosa-parades et al. FNPK model. This new model is called as the corrected fractional neutron point kinetic (CFNPK) model. The present study is concerned with the numerical solution of the CFNPK model (Aboanber and Nahla, 2016b) with six groups of delayed neutron precursors. The fractional derivative is described in the sense of Grunwald-Letnikov. An implicit finite difference method (FDM) is constructed for the solution of CFNPK model. The stability analysis of the method is carried out. We analyze the results of neutron density for different values of anomalous diffusion order, reactivity function, relaxation time and time step size. In addition, we compare the results corresponding to CFNPK model (Aboanber and Nahla, 2016b) with the results corresponding to the FNPK model proposed by Espinosa-parades et al. (Espinosa-Paredes et al., 2011). It is shown that as anomalous diffusion order decreases or simulation time increases the difference between the values of neutron density increases. We have investigated the effects of each term of the CFNPK.

AbstractIn Laurentian Great Lakes coastal wetlands (GLCWs), dominant emergent invasive plants are expanding their ranges and compromising the unique habitat and ecosystem service values that these ecosystems provide. Herbiciding and burning to control invasive plants have not been effective in part because neither strategy addresses the most common root cause of invasion, nutrient enrichment. Mechanical harvesting is an alternative approach that removes tissue‐bound phosphorus and nitrogen and can increase wetland plant diversity and aquatic connectivity between wetland and lacustrine systems. In this study, we used data from three years of Great Lakes‐wide wetland plant surveys, published literature, and bioenergy analyses to quantify the overall areal extent of GLCWs, the extent and biomass of the three most dominant invasive plants, the pools of nitrogen and phosphorus contained within their biomass, and the potential for harvesting this biomass to remediate nutrient runoff and produce renewable energy. Of the approximately 212,000 ha of GLCWs, three invasive plants (invasive cattail, common reed, and reed canary grass) dominated 76,825 ha (36%). The coastal wetlands of Lake Ontario exhibited the highest proportion of invasive dominance (57%) of any of the Great Lakes, primarily from cattail. A single growing season's biomass of these invasive plants across all GLCWs was estimated at 659,545 metric tons: 163,228 metric tons of reed canary grass, 270,474 metric tons of common reed, and 225,843 metric tons of invasive cattail, and estimated to contain 10,805 and 1144 metric tons of nitrogen and phosphorus, respectively. A one‐time harvest and utilization for energy of this biomass would provide the gross equivalent of 1.8 million barrels of oil if combusted, or 0.9 million barrels of oil if converted to biogas in an anaerobic digester. We discuss the potential for mitigating non‐point source nutrient pollution with invasive wetland plant removal, and other potential uses for the harvested biomass, including compost and direct application to agricultural soils. Finally, we describe the research and adaptive management program we have built around this concept, and point to current limitations to the implementation of large‐scale invasive plant harvesting.

Abstract Process heaters are typically located outside and subject to the weather. Although heaters are typically tuned at a given set of conditions, actual operating conditions vary significantly from season to season and sometimes even within a given day. Unfortunately, most heaters are not properly adjusted for actual operating conditions. Ambient air temperature, pressure and humidity all significantly impact process heater efficiency. This paper shows how changing ambient conditions can reduce efficiency if proper adjustments are not made. Combustion efficiency is related to air:fuel ratio and to air–fuel mixing. A general industry rule-of-thumb is that operating at 2–3% excess O 2 (dry basis) results in the best combination of efficiency and flexibility. At higher O 2 levels, efficiency is reduced because the additional O 2 and N 2 absorb heat, much of which exits the exhaust stack. At lower O 2 levels, efficiency can be substantially reduced because some fuel is uncombusted. Low O 2 levels can also lead to soot and coke buildup on process tubes reducing heat transfer to the process fluid and reducing efficiency. Several examples demonstrate how ambient conditions affect heater efficiency. Calculations and graphs for a wide range of operating conditions demonstrate how efficiency can be affected by changes in ambient conditions for process heaters.

In this paper, we investigate how generators’ ownership of financial transmission rights (FTRs) may influence the effects of the transmission lines on competition. In order for concrete analysis, a simple symmetric market model is introduced and FTRs are modeled in two different forms: FTR options and FTR obligations. This paper shows that introducing FTRs in an appropriate manner may reduce the physical capacity needed for the full benefits of competition. Among the competitive effects of ownership of FTRs, we focus on the effects on two possible pure strategy equilibria: the unconstrained Cournot equilibrium and the passive/aggressive equilibrium. We also analyze an extension of the model: asymmetric markets. Finally, a numerical illustration of applying the analysis is presented.

Co-generation of energy derived from human movement is not new. Intentionally accumulating energy, from mass urban-mobility, provides opportunities to re-purpose power. However, when mass-mobility is predictable, yet not harnessed, this highlights critical gaps in application of interdisciplinary knowledge. This research highlights a novel application of geostatistical modelling for the built environment with the purpose of understanding where energy harvesting infrastructure should be located. The work presented argues that advanced Geostatistical methods can be implemented as an appropriate method to predict probability distribution, density, clustering of populations and mass-population mobility patterns from large-scale online distributed and heterogeneous data sets published by the Australian Urban Research Infrastructure Network. Where clear urban spatio-behavioural relationships of density and movement can be predicted – understanding such patterns supports cross-disciplinary city planning and decision-making. A data-informed – predictive spatial decision-making framework is proposed – facilitating the endeavour of cogenerating kinetic human energy within a prescribed space. This novel proposition could further sustainability strategies for compact living for cities such as in Perth, Western Australia which is increasingly economically and geographically pressured to densify. This research argues that surveillance data elucidate a capacity to interpret and understand impacts of densification strategies, efficacy of CCTV networks in existing and emerging cities.

The present study utilizes (a) recycled low density polyethylene oil extracted through catalytic pyrolysis and (b) 1-decanol and di-n-butyl ether, as a blend component with diesel to power a single...