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Abstract Improving energy efficiency sustainability is a target of the Chinese government. However, the effectiveness of energy conservation policy is affected by the energy rebound effect under which energy efficiency improvement reduces the effective price of energy services, thereby completely or partially offsetting the energy saved by efficiency improvement. Based on the output distance function, this paper develops an improved estimation model of the energy rebound effect, which is logically consistent with the quantities of energy savings and energy rebounds induced by technological progress. Results show that the aggregate energy rebound effect of 36 industrial sectors in China over 1998–2011 is 88.42%, which implies that most of the expected energy savings are mitigated. Investment-driven economic growth is not conducive to energy-saving and results in a strong energy rebound effect in the following year. The equipment and high-end manufacturing sectors have low levels of rebound effect, indicating that increasing the proportion of such firms in the total manufacturing sector can improve the performance of energy conservation. The high level and heterogeneity in rebound effects strongly suggest that varies strategies are necessary for energy conservation among China’s industrial sectors.

Abstract Biofuel production from food crops leads to debates about the increase in food prices and security of the food supply. On the other hand, biofuels derived from cellulosic (energy) crops offer positive environmental impacts. In this study, we develop a multi-objective mixed-integer optimization model to investigate the trade-offs and competition between biofuel and food production using switchgrass and corn. This model maximizes total economic and environmental benefits and provides optimal decisions regarding land allocations to food and energy crops, seeding time, harvesting time and amount, and budget allocations to farm operations. A piecewise linear lower approximation is developed to linearize the nonlinear revenue curve of corn grain sales. Spatio-temporal environmental impacts such as soil erosion prevention, carbon sequestration and emissions, and nitrogen pollution are included in the model. The application of the model in Kansas indicates that switchgrass is more profitable than corn in cropland, while it requires Conservation Research Program (CRP) incentives for production on marginal land unless priority is given to the environment. In order to ensure food security, our study advises managers and policy makers to provide CRP incentives or to adjust the sustainability factor, which restricts cropland availability for biofuel production. Our spatio-temporal optimization model can also be adapted to different regions with alternative energy and food crops under various management scenarios.

Abstract This paper presents a Nonlinear Model Predictive Controller (NMPC) designed to provide optimal control input for maximum turbine power generation in an Organic Rankine Cycle (ORC) Waste Heat Recovery (WHR) system. While the literature is rich in ORC-WHR system modeling and control approaches in simulation environments, the fundamental dynamic analysis, system aging, thermal inertia, and experimental implementation of power optimization based optimal ORC-WHR control are still lacking. These factors are key to fully understanding and controlling the dynamic behavior of the system and are the main focus of this study. In contrast to prior literature, this work experimentally evaluates the nonlinear dynamics of the ORC system to comprehensively understand the controller design requirements. A power optimization-based Nonlinear Model Predictive Controller (NMPC) is derived utilizing an Extended Kalman Filter (EKF) as a state estimator. Simulation results indicate that optimal turbine power generation is obtained with minimal working fluid superheat for the system under study. Consequently, a superheat-tracking controller is designed, and the performance of the controller is simulated over step inputs. The designed controller is then experimentally validated on an ORC test rig with a 13L Heavy Duty Diesel Engine (HDDE). During experimental evaluation of the controller, it was discovered that the control-oriented model is susceptible to system aging effects and therefore, the model was calibrated online to match the behavior of the aged system. Moreover, evaporator thermal inertia was found to play a vital role attenuating the fluctuating frequency components of the exhaust conditions. The tuned controller provided satisfactory control response for transient engine conditions and maintained the working fluid temperature within acceptable limits.

Abstract The relationship between forest management and biomass sourcing is fundamental to the achievement of sustainable bioenergy production. Few biomass-sourcing studies have directly addressed the complex interactions between sustainable forest management and additional demand created by bioenergy production. The first objective of this research was to provide a method for estimating profits for a value chain that harvests volumes scheduled in a sustainable forest management plan. The second objective was to measure the financial and sustainable benefits generated by integrating bioenergy production into this value chain. Using data from a large management unit, a forest management plan was developed to generate an annual flow of timber that can be produced sustainably. We then proposed a network flow optimization model that links the optimal solution of a long-term wood supply optimization model with the processing capacity of an industrial network. Results revealed that the weak demand for lower-quality trees could be a serious impediment to achieving full value-creation potential. Simulations of the implementation of a hardwood pellet mill improved the value-creation potential for hardwood pulp (direct effect) and also for other wood products by providing access to otherwise unprofitable mixed-wood forest strata (synergistic effect). Our experiment showed that integrating a lower-quality timber user, such as a bioenergy production unit, could lead to higher financial profits (up to three-fold), and improve alignment between the sustainable forest management objectives and the industrial network capacity (harvested scheduled area increased from 79% to 98%). Implementing a bioenergy mill also grants a higher return on capital employed compared to historical values for the manufacturing sector. Strengthening the link between strategic planning and industrial processing capacity provides new insights into the impact on value-creation of bioenergy production from forest biomass.

Abstract As a major GHG emissions source with large growth potential, the passenger transport sector plays a crucial role in deep decarbonization in China. Large disparities among provinces in private vehicle ownership, sufficiency of public transport infrastructure, affordability of clean fuel vehicles, etc. highlight the importance of regionally tailored mitigation strategies to fully exploit carbon reduction potentials. We classify 31 provinces in mainland China into three regional clusters based on their passenger transport development level, then establish a provincial level bottom-up model to project energy demand and CO2 emissions of China’s passenger transport sector by 2050. Mitigation effects of improving vehicle energy efficiency, shifting to alternative clean fuels, and promoting public transport are compared, and regionally tailored policy priorities are then proposed. The results show that CO2 emissions of China's passenger transport sector will peak around 2045 at 647 MtCO2 and slightly declined to 642 MtCO2 in 2050 in the Current Policies Scenario. If fully implemented, regionally tailor mitigation strategies that maximize techno-economic carbon reduction potentials could cut CO2 emissions substantially to net-zero in 2050. Mitigation effects of different policy options vary among time periods and regions. Improving vehicle fuel efficiency contributes the most in carbon mitigation over short time scales especially in less developed provinces, where private vehicle ownerships are projected to increase rapidly. Well-established transport infrastructure and an optimally designed public transport system could play a larger role in wealthier provinces.

Inner Mongolia Autonomous Region (IMAR) is one of China's strategic energy bases for the 21st century. While bioenergy in IMAR may play an important role in securing future energy supply, little research has been done so far, particularly for crop stalk resources as a potential source of bioenergy in this region. In this study we systematically analyzed the temporal and spatial patterns of crop stalk resources, evaluated the bioenergy potential of crop stalk resources, and explored possible pathways of developing stalk-based energy strategies in Inner Mongolia. Our results show that the total crop stalk yield in IMAR increased consistently from 1980 to 2008, with an average annual increase of 16.3%. Between 2004 and 2008, 26.14 million tons of crop stalks were produced each year in IMAR, 8.82 million tons of which could be used for biofuel production. Grain crops contributed most to the total amount of stalks for energy produc- tion, of which corn stalks were the largest contributor, accounting for 62% of the total crop stalk yield. Based on the current trend, crop stalk yields may continue to increase in the future. Geographically, the abundance of biofuelable crop stalk resources, either on a per capita or per unit of area basis, had a spatial pattern of ''high on East and West and low in the middle''. Our findings suggest that IMAR has the potential for developing stalk-based bioenergy to improve its current overwhelmingly coal-dom- inated energy structure. However, more detailed and comprehensive studies are needed to figure out how exactly such bioenergy development should be carried out in a way that would promote the regional sustainability of Inner Mongolia - i.e., simultaneously providing social, economic, and ecological benefits.

Abstract The Biofuels Directive places an onus on EU member states to ensure biofuels are available on their markets. This paper investigates the use of ethanol derived from biomass type 1 (residues and wastes) and biomass type 2 (energy crops). The technology involved in generating ethanol from energy crops is mature; the same cannot be said for generation of ethanol from residues; many proposals are mooted to generate ethanol from lignocellulosic biomass, but they are not at a commercial scale. Literature is available however on expected yields and economics of ethanol production from lignocellulosic biomass. This paper investigates three options which produce ethanol: 50 million Lpa of ethanol from sugar beet, 50 million Lpa of ethanol from waste paper and 200 million Lpa of ethanol from waste paper. The economics of ethanol production from sugar beet were the worst of the three due to the requirement to buy the sugar beet. Economies of scale are significant: larger plants produce cheaper ethanol. Indeed it was found that for the large plant, the production cost was zero if a gate fee of €100/t was charged for waste paper. The three options were applied to Ireland. It was found that an investment in an ethanol industry of €561 million would produce 5.7% of the energy value of petrol and diesel in Ireland; the reference value for the minimum portion of biofuels placed on the market in 2010 is 5.75%. The greenhouse-gas savings would equate to 18% of the 1990 transport emissions.

Current energy policies address environmental issues including environmentally friendly technologies to increase energy supplies and encourage cleaner, more efficient energy use, and address air pollution, greenhouse effect, global warming, and climate change. The biofuel policy aims to promote the use in transport of fuels made from biomass, as well as other renewable fuels. Biofuels provide the prospect of new economic opportunities for people in rural areas in oil importer and developing countries. The central policy of biofuel concerns job creation, greater efficiency in the general business environment, and protection of the environment. Projections are important tools for long-term planning and policy settings. Renewable energy sources that use indigenous resources have the potential to provide energy services with zero or almost zero emissions of both air pollutants and greenhouse gases. Biofuels are expected to reduce dependence on imported petroleum with associated political and economic vulnerability, reduce greenhouse gas emissions and other pollutants, and revitalize the economy by increasing demand and prices for agricultural products.

Abstract With the rise of advanced and affordable sensors offering continuous monitoring of city infrastructure, cities are increasingly seeking to become more ‘smart’ and are adopting data-driven approaches to help meet sustainability goals. In the area of building energy efficiency, closely coupled with this effort is the prevalence of building energy benchmarking policies, which require public disclosure of vast new quantities of building-level energy data at urban scales (i.e., open urban energy data). While existing research efforts have focused on the potential of this data to transform energy efficiency markets and investments in the real estate sector, little research has been dedicated to assessing this information’s value to the general public. Given that achieving energy reductions in the built environment will require not only energy efficiency investments, but also greater awareness, engagement, and action from ordinary citizens, we study the potential of open urban energy data in providing citizen benefits. Energy-cyber-physical systems offer a pertinent framework to link data from the virtual world to citizens’ physical reality in order to improve their understanding and decision making. Adopting an energy-cyber-physical system perspective, we aim to connect open urban energy data to citizens through the development and evaluation of a novel community-scale energy feedback system. This mobile cyber-physical system transforms building-level electricity consumption and production data across Georgia Tech’s campus into a mobile application consisting of three features: spatial feedback, energy supply feedback, and energy consumption feedback. Augmented-reality visualization elements are integrated into the system, providing Georgia Tech community members a direct link between their experienced physical environment and data stored in the virtual world. Applying a user-centered design approach, prospective users evaluate the system via thinking aloud sessions and user surveys to assess understandings and perceptions of open urban energy data for the Georgia Tech campus. The results contribute to literature seeking to create energy feedback systems at the community-scale and expand research investigating citizen reactions to and opinions of open urban energy data. This research is an integral step to further engagement and participation from the public to help achieve a sustainable and citizen-valued energy future.