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The tradeoff between economic growth and environmental protection has been a critical issue in facilitating eco-industrial park development in China. As the principal contributors to China's industrial output, many industrial parks have been addressing the issues of intensive resource consumption and pollutant generation, driven by much stricter regulations on the environment and resource management. Retuning the industrial structure is a substantial way to address the environmental issues while promoting economic development, which are the goals of eco-industrial development. This study proposes a multi-criteria industrial structure adjustment model by employing a generalized reduced gradient method to find the optimal structure of an industrial park. The model aims to increase the overall resource utilization efficiency and industrial output efficiency through a decoupling between the economic development and environmental burden of the park. A Chinese eco-industrial park located in the capital, the Beijing Economic-technological Development Area (BDA), is used as an example to uncover a transformation roadmap from a high-speed mode to a high-quality mode. The constraints of the multi-criteria decision-making model mainly focus on the limits of water consumption and pollutant emissions by targeting an appropriate economic development rate. The key findings are as follows. First, BDA could achieve 186% economic growth with 20% water consumption and 30% contaminant reduction in five years (2020-2025) by optimizing the industrial structure. Second, the advanced manufacturing industries play significant roles in stimulating the high-quality development. Third, ammonia nitrogen is a crucial factor restricting economic development under the requests of the "dual control" policy. Forth, the industry that can use reclaimed water in production will get more development opportunities and space, and vice versa. The model can be applied in diverse industrial parks by modifying the parameters and associated constraints.

Abstract With the rapid development of the economy, China is facing pressures caused by traditional energy deficiency and environmental pollution in recent years, which has forced the Chinese government to start to pay attention to the development and utilization of renewable energy (RE). This article, based on data and statistics available up to 2008, studies features of China's RE technology innovation and problems thereof. It finds that national science and technology programs are the main aspect of China's RE technology innovation, and most of R&D funds for the RE technology come from China's three main national programs. Besides, the overall expenditures on RE technology innovation constitute only a small proportion of China's total domestic R&D funding and seem not enough. This paper also finds that, compared with research and development stages of RE technology, the demonstration and diffusion of RE technology in China are given less attention and thus are relatively less sufficient. Furthermore, influenced by China's traditional scientific research system, there appears lack of sufficient incentives and opportunities for private sectors to fully participate in RE technology innovation because most national programs are undertaken by universities or research institutes.

This paper proposes a two-stage two-level model for the energy pricing and dispatch problem faced by a smart grid retailer who plays the role of an intermediary agent between a wholesale energy market and end consumers. Demand response of consumers with respect to the retail price is characterized by a Stackelberg game in the first stage, thus the first stage has two levels. A risk-aversive energy dispatch accounting for market price uncertainty is modeled by a linear robust optimization with objective uncertainty in the second stage. The proposed model is transformed to a mixed integer linear program (MILP) by jointly using the Karush-Kuhn-Tucker (KKT) condition, the disjunctive constraints, and the duality theory. We propose a heuristic method to select the parameter in disjunctive constraints based on the interpretation of Lagrange multipliers. Moreover, we suggest solving an additional linear program (LP) to acquire a possible enhanced bidding strategy that guarantees a Pareto improvement on the retailer's profit over the entire uncertainty set. Case studies demonstrate the proposed model and method is valid.

Abstract This paper tracks the energy use and changes to China's energy-efficiency regulatory framework governing the iron and steel industry for the last thirty years. The detailed institutional analysis identifies both abating and augmenting effects of the regulatory framework changes on the energy intensity changes. The paper then assesses the impacts of various other factors on the energy intensity of China's iron and steel industry by using time-series data on the sector level. The quantitative analysis shows that technology progress, specifically the production process transition from high-energy intensive open-hearth furnace (OHF) to more energy efficient basic-oxygen furnace (BOF), is the biggest contributor to energy intensity reductions in China's iron and steel industry in the last thirty years, even after controlling for regulatory change and policy incentives. The ownership reform resulting from changes in the regulatory framework change contributed to energy intensity reductions in China's iron and steel industry, while fast market expansion resulting from market liberalization and regulation decentralization served as a principal barrier for energy efficiency improvements. Government policies, represented by financial subsidies from governments, correspond with energy intensity reductions in key large and medium sized enterprises, but interestingly, seem to be ineffective at producing energy intensity reductions for the industry as a whole. As other research indicated, rising coal prices also contributed to energy intensity reductions in China's iron and steel industry. Finally, the paper concludes that, to further incentivize energy intensity reductions, the Chinese government should consider correcting the negative impacts of the regulatory framework change, as well as transferring production processes to the highly energy efficient electric-arc furnace (EAF) and extending policy regulations to wider enterprise groups.

Advanced current measurement technology is one of the key technologies to realize smart grid. The current sensor based on the giant magnetoresistance (GMR) effect has the advantages of small size, high sensitivity, high precision, low cost, and high integration, but the range is limited. In order to expand the range of the current sensor, this paper proposed a novel transient GMR current sensor with a damping coil on the magnetic ring. The theoretical model was deduced and analyzed to calculate the current range of the sensor. The frequency response characteristics and transient current response of the proposed sensor were measured, and the influence of the number of turns and resistance of the damping coil on the performance of the sensor was summarized. Compared with the current sensor without damping coil, the transient current range of the new current sensor with 315 turns of damping coil was expanded by 5.23 times, while the DC range and sensitivity were kept unchanged. The new current sensor can thus adapt to the DC and transient current measurement requirements of smart grids.

The explosive development of Information and Communication Technology (ICT) has significantly enlarged both the energy demands and the CO 2 emissions, and consequently contributes to make the energy crisis and global warming problems worse. However, as the main force of the ICT field, the mobile networks, are currently focusing on the capacity, variety and stability of the communication services, without paying too much severe concerns on the energy efficiency. The escalating energy costs and environmental concerns have already created an urgent need for more energy-efficient "green" wireless communications. In this paper, we survey and discuss various remarkable techniques toward green mobile networks to date, mainly targeting mobile cellular networks. We also summarize the current research projects related to green mobile networks, along with the taxonomy of energy-efficiency metrics. We finally discuss and elaborate future research opportunities and design challenges for green mobile networks.

The Chinese national demonstration eco-industrial park program has received significant attentions in the field of industrial ecology. The program has just passed its ten-year anniversary. This study aims to assess the economic and environmental performance of the 17 accredited sector-integrated national demonstration eco-industrial parks. A selected group of ten metrics, including resource consumption, economic development, and waste emissions, are applied to assess the performance by comparing the difference of metrics between reference years of eco-industrial park planning and accreditation. The main findings include: (1) industrial added value of the 17 eco-industrial parks as a whole increased by 56%; (2) for comprehensive energy consumption, fresh water consumption, industrial wastewater generation, and solid waste production, the 17 eco-industrial parks had an overall increase of 20%, 18%, 12%, and 6%, respectively. The quantity of energy and fresh water consumption, wastewater and solid waste generation in some eco-industrial parks started to decrease with economic growth. Meanwhile, the average intensity of the four metrics decreased by 22%, 25%, 28%, and 32%, respectively; (3) for chemical oxygen demand and sulfur dioxide, the eco-industrial parks accomplished a two-fold decrease in both total quantity of emissions and intensity. Chemical oxygen demand emissions and its intensity decreased by 25% and 52%, respectively. Sulfur dioxide emissions and its intensity decreased by 51% and 69%m respectively. Measures supporting the performance improvement of Chinese national demonstration eco-industrial parks are also discussed, which mainly include cleaner production and environmental management, infrastructure sharing, energy-saving practices at the firm level, the pillar industries, and industrial symbiosis.

AbstractThe present study investigates the effect of public‐private partnership investment in energy and technological innovation on consumption‐based carbon emissions for China from 1990Q1‐2017Q2. This study employs generalized least square (GLS) based unit root test, Maki cointegration test, fully modified ordinary least square (FMOLS), dynamic ordinary least square (DOLS), canonical cointegration regression (CCR) and frequency domain causality test. The finding of this study shows that (a) the cointegrating relationship among public‐private partnership investment in energy, technological innovation, renewable energy consumption, exports, imports, and consumption‐based carbon emissions is proved; (b) exports, renewable energy consumption and technological innovation are helpful to lower consumption‐based carbon emissions; (c) both public‐private partnership investment in energy, GDP and imports leads to increased consumption‐based carbon emissions; (d) in the long term, public‐private partnership investment and technological innovation cause consumption‐based carbon emissions in China. This study recommends technological innovation for the cleaner production process and public‐private partnership investment in renewable energy.