• Energy Research

A survey was conducted to study the attitudes of Hong Kong residents toward the safety of operations of the nuclear power plant in Daya Bay and their possible actions in case of leakage. Only 34.5% of the respondents were confident about the operational safety of the nuclear power plant, whereas 23% stated they would immediately leave Hong Kong when leakage occurs. Chi-square tests and multinomial logit analysis indicate that the degree of confidence is significantly related to the perceived ability of the Hong Kong (HK) government and the nuclear power plant company, China Light and Power Co. Ltd. (CLP), knowledge of emergency plan and responsibility, gender, and age. However, the degree of confidence is not significantly related to the distance of the residential area from the nuclear power plant. In addition, the higher the perceived ability of the HK Government and CLP to handle nuclear leakage, the greater the degree of confidence becomes. The chi-square tests suggest that higher perceived ability of the HK Government and CLP are also significantly associated with less likelihood of residents immediately leaving Hong Kong in case of leakage. Hence, the HK Government and CLP are recommended to improve their perceived ability for safety and social stability.

As one of the three high-energy consumption sectors (industry, building, and transportation) in China, the transport sector faced a devastating resource and environment challenge. The transport sector was reportedly responsible for about 15.9% of the country’s total final energy consumption in 2008. This paper investigates the energy consumption and efficiency of China’s transport sector from 2003 to 2009. The transport energy data of 30 China administrative regions were divided into “three-belts” (Eastern, Western, and Central areas), and the corresponding turnovers were reported and analyzed using an index decomposition analysis (Logarithmic Mean Divisia Index). The energy data and turnover of the transport sector indicated that the high growth rate of turnover results is attributed to the high growth rate of diesel, assuming that diesel is the major fuel for freight transport. The growth of diesel is the main contributor to the overall growth of energy consumption. The growth rate of gasoline has become minimal since 2006. Since 2005, all three-belt areas, with regard to the effectiveness of energy conservation policies, have continuously improved their energy efficiencies based on the results of decomposition analysis. The energy intensity effect shows that the energy conservation and efficiency policies were more effective in the Central and Western areas than that in the Eastern area. On the other hand, the regional shift effect indicates that the policies favor to the Eastern area since only its regional shift effect contributes energy savings since 2008. The energy-mix effect is insignificant, which indicates that it is not necessary to conduct CO2 emission decomposition analysis due to the redundant observations. At last, the activity effect dominates the energy consumption increase (98.05% of the accumulated total energy increase) from 2003 to 2009, which is consistent with the rapid development of transportation in China. That is, the policies in the transport sector mainly focused on the economic development but the energy efficiencies in the study period.

Regression analysis can be used to develop benchmarking systems for the energy performance of office buildings. A linear regression model can be developed using ordinary least squares (OLS) regression analysis to normalize the factors that affect the energy consumption performance of office buildings and develop the benchmarking model. Poor model fit and the assumption of linearity of OLS are the limitations in developing a reliable benchmarking model. In this study, we introduce and discuss the use of convex non-parametric least squares (CNLS) to develop a benchmarking model using the resulting hyperplanes. CNLS is advantageous in that (i) it is a non-parametric regression method, (ii) does not specify the functional form a priori, and (iii) is used to estimate monotonic increasing and convex functions. The resulting benchmarking model can be enhanced with a good model fit using the three advantages. An illustrative application to office buildings is also provided.