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Distribution centers are quite important for logistics. In order to save costs, reduce energy consumption and deal with increasingly uncertain demand, it is necessary for distribution centers to select the location strategically. In this paper, a two-stage model based on an improved clustering algorithm and the center-of-gravity method is proposed to deal with the multi-facility location problem arising from a real-world case. First, a distance function used in clustering is redefined to include both the spatial indicator and the socio-economic indicator. Then, an improved clustering algorithm is used to determine the optimal number of distribution centers needed and the coverage of each center. Third, the center-of-gravity method is used to determine the final location of each center. Finally, the improved method is compared with the traditional clustering method by testing data from 12 cities in Inner Mongolia Autonomous Region in China. The comparison result proves the proposed method's effectiveness. [ABSTRACT FROM AUTHOR]

The shortage of water resources has become a notable bottleneck, restricting the economic development of many countries and areas around the word, especially that of North-west China. The Inner Mongolia Autonomous Region and Shaanxi Province are important energy bases and food production areas in North-west China. However, the region is suffering from perennial drought and water shortage, which has become the most significant shortcoming for energy and food production. Guiding the decoupling between regional economic development and water consumption is a critical way to achieve sustainable development. Based on the analysis of the food and energy production value and their water consumption in North-west China from 2009 to 2019, this paper uses the Tapio model to analyze the decoupling relationship between food, energy production, and water consumption, and uses the Logarithmic Mean Divisional Index (LMDI) model to analyze the driving factors affecting decoupling. The results show that most water consumption for food and energy production in North-west China is out of the ideal strong decoupling, the decoupling status is unstable, and re-coupling occurs frequently. The increase in water intensity and the change in industrial structure are the promoting factors of decoupling between production value and water consumption in food and energy in North-west China, while the increase in production value and population size are the main restraining factors. Therefore, in pursuit of strong decoupling, the government should guide the food and energy industry to move toward implementing in water saving measures through policies and promote the enthusiasm and efficiency of the labor force through financial support and other ways. Moreover, ecological protective measures are needed to be strengthened, such as water source protection, and sewage treatment. [ABSTRACT FROM AUTHOR]

The large public building energy consumption (BEC) is the focus of Building Energy Saving, therefore, it is necessary to study the characteristics of BEC to find out the important factors affecting BEC. For this purpose, 27 office buildings in the west of Inner Mongolia Autonomous Region were studied, based on statistical analysis of the researched basic information and energy consumption bill of these buildings. This paper focused on the determination of the significant factors affecting the total and subentry energy consumption intensity (ECI) of office building, as well as the establishment of standardized linear regression models between these selected factors and total and subentry ECI. Firstly, eleven continuous variables, three independent categorical variables, and the climate factor were selected and analyzed the impact on total and subentry ECI by statistical software SPSS20.0, in order to find out the significant influencing factors. Then based on the results of curve fitting, standardized models of total and subentry ECI and their respective significant impact factors were established using multiple linear regression analysis. The regression results showed that the electricity use percentage of the total equivalent electricity consumption was an important factor affecting the total ECI of office building in the west of Inner Mongolia Autonomous Region. Finally, univariate analysis of variance (ANOVA) was conducted between the three independent categorical variables and the total and subentry ECI, and the results showed that these factors had no significant effect on the ECI of office building. Process of the regressive model establishment and the results of analysis of variance could both guide us to propose more targeted energy saving measures. [ABSTRACT FROM AUTHOR]

Daily global surface solar irradiance (SSI) is of great importance parameter in the surface energy balance, climate modelling, and solar energy utilization. However, it is still challenging to extend the estimated instantaneous solar radiation to the daily global SSI from either geostationary satellites or polar-orbiting satellites. In this study, a method for estimating the daily global SSI is proposed based on the Himawari-8 hourly SSI products using pixel-by-pixel Gaussian fitting to simulate the diurnal SSI variation. Compared with ground-based observations, the daily global SSI estimated by Gaussian fitting have higher accuracy under various weather conditions than by the simple accumulation or quadratic polynomials, and the coefficient of determination (R2) between the estimated and observed values exceeds 0.86. The verification results also show different estimation accuracies under different weather conditions. The root-mean-square errors (RMSEs) under clear-sky and all-sky conditions are 2.36 MJ/m2 and 3.06 MJ/m2, respectively. In addition, experimental results show that the daily global SSI in China has high spatial heterogeneity. For higherelevation areas with low cloud cover, such as the Qinghai-Tibet Plateau, Inner Mongolia, and Northwest China, the daily global SSI is higher than other areas. In contrast, the values of daily global SSI is relatively low in the eastern regions of Southwest and Northeast China. [ABSTRACT FROM AUTHOR]

Abstract: According to the industry ecology theory, in the simulating flowing way between substance and energy in the nature ecology, to design the industrial production systems can use less resource reasonably and reduce emissions. As the most important large iron & steel enterprise in Inner Mongolia, applying the theory of industrial ecology, the Baogang Group gains great achievement in energy saving and emission reduction in recent years. Based on the industrial ecology theory, this paper mainly analyzes the practice of energy-saving and ejection-decreasing of the BaoGang Group. [Copyright &y& Elsevier]