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Reducing the total carbon emissions of the logistics industry is one of the basic requirements for the development of a low-carbon economy. Based on the AHP analytic hierarchy process and the 1-9 value scaling method, an evaluation index system for the low-carbon development of the logistics industry is constructed. At present, the development of low-carbon logistics requires the combination of low-carbon technology and low-carbon management to ensure the integrity and dynamics of low-carbon logistics control. The results of this study show that in the AHP index analysis of the development of logistics industry in Shandong Province, compared with 13 evaluation indexes of low-carbon logistics and traditional logistics, low-carbon logistics is significantly better than traditional logistics. Among them, the implementation of low-carbon logistics policy system has increased the energy utilization rate to 88.72%, the recovery rate of warehousing and logistics waste to 92.11%, and other relevant indicators have also been improved and optimized to varying degrees. Based on the EKC model curve, the total carbon emissions from 2015 to 2019 showed a downward trend month by month. The future development of low-carbon logistics mainly starts with reducing the total carbon emission of logistics transportation and improving energy utilization. Aiming at the main influencing factors of the development of low-carbon logistics, this paper puts forward specific measures for the development of low-carbon logistics, in order to promote the development of low-carbon logistics. [ABSTRACT FROM AUTHOR]

With the depth increasing and the improvement of mining mechanization of the coal mine, heat hazard is becoming more and more serious, the ice cooling system is gradually promoted and applied in China for recent years, but the cooling capacity and energy efficiency ratio (EER) test and analysis for such system is seldom reported. The cooling capacity and EER of the refrigerating equipment of an ice cooling system of a coal mine are tested and analyzed in Shandong Province in this paper. The test result indicates that the refrigerating capacity and EER are lower and both the pre-cooling units and the ice making system have a large variable range. It points out that it should not evaluate the ice cooling system by the test data only in this mine but expect more test data and analysis of the ice cooling system in other coal mines to get a more scientific conclusion. And the test, analysis and comparison for different kinds of cooling system are also expected to explore suitable cooling system while a full consideration of the geological conditions and other factors of the mine are taken into consideration. [ABSTRACT FROM AUTHOR]

The rapid development of urbanization in China inevitably leads to a sharp increase in building energy consumption, and Passive House (PH) have received much attention in China in recent years. In this paper, the annual energy demand (AED) and summer discomfort hours (SUH) of PH are used as optimization objectives to establish a set of design solutions for multi-objective optimization (MTO) and economic analysis of a PH in Shandong Province, China. It is found that (1) the algorithm based on nearest neighbor component analysis (NCA) feature extraction applies to the sensitivity analysis of multivariate nonlinear high-dimensional data, and the NCA-GA-RBF neural network technique is proposed, which has significantly improved the goodness of fit and generalization ability for AED and SUH. (2) The NSGA-II genetic algorithm is used for the optimization search, and the results show that the overall improvement rates of AED and SUH are 25.5% and 21.6%, respectively, among the nine solutions after comprehensive evaluation; (3) Finally, the optimal scheme of energy saving and the optimal scheme of the economy are selected for economic evaluation. By comparing the economics of the two options and the improvement rates of AEDs and SUHs, the guidelines for design decision-makers are provided. In summary, the design scheme of this paper is forward-looking and reference-oriented and provides some reference suggestions for the development of PH in China. • The NCA algorithm is suitable for multivariate nonlinear sensitivity analysis. • NCA-GA-RBF has stronger and more stable generalization ability and accuracy. • In this paper, climate is the main factor affecting thermal parameters. • Global costs have a stronger economic interpretation. [ABSTRACT FROM AUTHOR]

As the world's largest developing country, China currently is undergoing rapid urbanization and motorization, which will result in far-reaching impacts on energy and the environment. According to estimates, energy use and carbon emissions in the transportation sector will comprise roughly 30% of total emissions by 2030. Since the late 1990s, transportation-related issues such as energy, consumption, and carbon emissions have become a policy focus in China. To date, most research and policies have centered on vehicle technologies that promote vehicle efficiency and reduced emissions. Limited research exists on the control of greenhouse gases through mode shifts in urban transportation-in particular, through the promotion of public transit. The purpose of this study is to establish a methodology to analyze carbon emissions from the urban transportation sector at the Chinese city level. By using Jinan, the capital of China's Shandong Province, as an example, we have developed an analytical model to simulate energy consumption and carbon emissions based on the number of trips, the transportation mode split, and the trip distance. This model has enabled us to assess the impacts of the transportation mode split on energy consumption and carbon emissions. Furthermore, this paper reviews a set of methods for data collection, estimation, and processing for situations where statistical data are scarce in China. This paper also describes the simulation of three transportation system development scenarios. The results of this study illustrate that if no policy intervention is implemented for the transportation mode split (the business-as-usual (BAU) case), then emissions from Chinese urban transportation systems will quadruple by 2030. However, a dense, mixed land-use pattern, as well as transportation policies that encourage public transportation, would result in the elimination of 1.93 million tons of carbon emissions-approximately 50% of the BAU scenario emissions. [ABSTRACT FROM AUTHOR]

With the continuous implementation of a plan for reconstruction of "Beautiful Countryside" in China, the rural environment and appearance of rural houses have been significantly improved. However, those houses in cold areas of China have great trouble with indoor temperature and heating-related energy consumption. After investigating the current situation of the layout, building envelope, indoor temperature, and energy consumption of the rural houses renovated by the plan of "Beautiful Countryside" in Shandong Province, this paper puts forward the improvement measures of raising indoor temperature and reducing energy consumption. On this basis, a typical rural house was selected, and DesignBuilder was utilized to simulate the effects before and after the application of different renovation measures for this house. The results show that the main way to raise indoor temperature and reduce energy consumption is to improve the thermal insulation performance of the building envelope, including renovation of the roof, exterior walls, doors and windows, and attached sunspace. In addition, combined with the achievements of "Beautiful Countryside" reconstruction, this paper shall propose specific renovation practices which are suitable for different rural houses. Based on the level of economic development in rural areas, it also puts forward some feasible renovation paths for different rural areas, and further provides references for other areas to carry out relevant work in the future. [ABSTRACT FROM AUTHOR]

[Display omitted] • Carbon emissions are explored in China's building operations from provincial perspective. • GDIM is employed to factorize ten affecting factors of CO 2 emissions in building sub-sectors. • CO 2 emissions of building sub-sectors are predicted with dynamic simulation. • The contribution of provinces to the change and peak of national emissions are discussed. Carbon emissions from building operations have a critical impact on achieving carbon peaking goal in China. However, the provincial emission performance in building operations are quite different and it is still unidentified how they affect the national emission change and peaking target, making national emission reduction target hard to implement at the provincial level. This paper explores the driving factors leading to emission changes and examines the prospective emission peaks in China and China's provinces by adopting generalized Divisia index method (GDIM) and the combination of scenario analysis and Monte Carlo simulation. Furthermore, the regional emission heterogeneity and the contribution of provinces to the change and peak of national emissions are discussed to identify regions and provinces that should be focused on emission monitoring. Results show that in China and most Chinese provinces, energy consumption of commercial buildings, energy consumption and floor space of urban residential buildings besides income improvement, and the per capita CO 2 emissions of rural residential buildings contributed greatly to emission growth. Under current policies, commercial and urban residential buildings in most provinces would fail to reach their emission peaks ahead of schedule. The urban residential buildings in the northern region, commercial and rural residential buildings in the eastern region caused higher CO 2 emissions. At the provincial level, Shandong, Shanxi and Hebei made the top contribution to total emissions of commercial, urban residential and rural residential buildings, respectively. Shandong and the provinces in north China of urban residential buildings and four provinces including Shandong, Guangdong, Hebei and Zhejiang of commercial and rural residential buildings had the significant impact on the uncertainty of the peaking time of CO 2 emissions. These findings provide a strong decision-making reference for Chinese government to formulate targeted regional emission reduction policies in building operations. [ABSTRACT FROM AUTHOR]

Abstract: This paper, by adopting the carbon emission calculating method for all kinds of energy proposed by IPCC in 2006, calculates the amount of carbon emissions of Shandong province. It turns out that carbon emissions in Shandong increased 2.63 times, carbon emission intensity increased 2.45 times and the carbon emission intensity and the energy intensity by GDP is obvious higher than the average level of China from 1997 to 2008.Taking into account the characteristics of carbon emissions in Shandong Province, the paper tries to propose the corresponding strategies to develop low-carbon economy. [Copyright &y& Elsevier]

Since the combustion of fossil fuel became the largest contributing factor of greenhouse gas emissions in China, the growth of energy consumption caused by urbanization has led to significant increase in carbon emissions. Applying both the carbon-emissions-coefficient and the sector-energy-consumption method, we predicted the energy consumption and carbon emissions, explored the characteristics of energy consumption and carbon emissions in different urbanization stages, and analyzed the energy crisis in Shandong which is a typical province in China. The results indicate that in 2015 and 2020, the total primary energy consumption will be 1.57 times and 1.85 times higher than that of in 2009, and the carbon emissions are estimated to be 1.48 times and 1.67 times respectively. The urbanization has distinct positive effects on energy consumption and carbon emissions, and the influence is more obvious in the intermediate-stage than in the early-stage. From a policy perspective, this paper could provide valuable information for planners and decision makers to formulate feasible and practical polices with a view to optimize energy structure and mitigate carbon emissions. [ABSTRACT FROM AUTHOR]

Total-factor energy efficiency (TFEE) is widely used to measure energy efficiency under the data envelopment analysis (DEA) framework, but the efficiencies obtained from DEA are structurally biased upward, and thus TFEE tends to overestimate energy efficiency. This research thus applies the bootstrapped DEA approach to correct the bias of TFEE. Using a dataset consisting of 30 provinces of China in the period 2016–2019, the bootstrapped-based test supports technology with variable returns to scale. The biased-corrected TFEE also indicates that energy consumption on average can be scaled down by 42.36%, rather than the biased value of 19.4%. The bootstrapped clustering partitions provinces into three groups: Cluster 1, with Guizhou as the representative medoid, includes half of the superior coastal provinces in terms of actual energy consumption and TFEE and half of the competitive inland provinces, whereas Cluster 3 outperforms Cluster 2 in terms of TFEE, but the actual energy consumption is higher, with Shandong and Hebei as the representative medoids, respectively. Lastly, empirical results imply that the northeast and central regions need more government attention and resources to practice sustainable development and improve TFEE. [ABSTRACT FROM AUTHOR]

Abstract: Nowadays, sustainable economic development is the key issue in the world. In this paper, we take Shandong Province as an example to analyze the relationship between energy use, environmental quality and economic development. Through the study, we find that the correlation between nominal income per capita and environmental quality can be shown in Kuznets inverted U-shaped curve. After 2020, with per capita income increasing, total amount of environmental pollutants will decline slowly; The relationship between per capita income and discharge amount of sulfur dioxide is consistent with EKC theory and is shown in inverted U-shaped curve, but the per capita income has no similar pattern with the other three environmental indicators; Although efficiency of energy utilization in Shandong Province increased steadily in recent years, but the rapid economic growth heavily depends on natural resources, and extensive mode of economic growth remains. Irrational industrial structure is the main cause for structural unbalance of energy consumption and environmental degradation in Shandong Province. It is argued that readjusting industrial structure and improving environment system of environmental pollution are the primary issuesin the reform. [Copyright &y& Elsevier]

Abstract: This paper analyzes the energy consumption of Shandong Province by the use of Complete Decomposition Model. We decompose three key factors: economic growth, structure and energy intensity, and study the impact on energy consumption results brought by changes in these variables. The corresponding effect coefficients is compared with national average level to identify the characteristics of energy consumption changes in Shandong and specific effect s of every stage of each factor, providing a scientific basis for the development of energy policy making. [Copyright &y& Elsevier]

Abstract: The relationship between energy consumption and economic growth has long been the focus at home and abroad. The general view is: energy consumption promotes economic growth; economic growth affects energy consumption on the other hand. In sight of the original theory, this paper adopts the statistical data of Shandong Province from 1980 to 2008, which include Gross Domestic Products (GDP), energy consumption, fixed asset investment and employees. Using unit root, co-integration and Granger causality test, we examined the relationship between energy consumption and economic growth in Shandong Province. The results show that energy consumption and economic growth have long-term trend relation, and there is two-way causality between them. The econometric model is estimated using Generalized Least Square (GLS) method. The conclusions are as follows: energy consumption and economic growth is positively correlated in Shandong province, and economic growth has highly depended on energy consumption. [Copyright &y& Elsevier]

Inter-basin water transfers are intended to have a positive impact on the development of a region, but are always accompanied by huge energy consumption. The feasibility and effectiveness of water transfer projects have not yet been clearly evaluated, especially in the light of their energy consumption and effects on social development. This paper develops a method that combines life cycle approach and system dynamic model to reveal the effectiveness of different water supply alternatives (transferred water, reclaimed wastewater and rainwater harvesting) when they are all constrained to consume equal energy. This approach is applied to the case of Jinan city in Shandong province, China, the main water-receiving city on the Eastern Route of the South-to-North Water Transfer Project (ER-SNWTP). The results show that in normal years, Jinan's reclaimed water and rainwater harvesting supply are effective replacements for transferred water under the constraints of equal energy consumption and capital costs; even in dry years these two alternatives still play an important role. The results of this study indicate the relative effectiveness of reclaimed water and rainwater harvesting in supplying urban water while conserving energy and capital. • Using a new evaluation approach for urban water supply alternatives analysis. • Local water and transferred water have similar supporting role to the receiving city in the east route of SNWTP; • Local water option has less environmental impact and lower financial cost. [ABSTRACT FROM AUTHOR]

China is experiencing severe PM2.5 (fine particles with a diameter of 2.5 μg or smaller) pollution problem. Little is known, however, about how the increasing concentration trend is spatially distributed, nor whether there are some areas that experience a stable or decreasing concentration trend. Managers and policymakers require such information to make strategic decisions and monitor progress towards management objectives. Here, we present a pixel-based linear trend analysis of annual PM2.5 concentration variation in China during the period 1999–2016, and our results provide guidance about where to prioritize management efforts and affirm the importance of controlling coal energy consumption. We show that 87.9% of the whole China area had an increasing trend. The drastic increasing trends of PM2.5 concentration during the last 18 years in the Beijing–Tianjin–Hebei region, Shandong province, and the Three Northeastern Provinces are discussed. Furthermore, by exploring regional PM2.5 pollution, we find that Tarim Basin endures a high PM2.5 concentration, and this should have some relationship with oil exploration. The relationship between PM2.5 pollution and energy consumption is also discussed. Not only energy structure reconstruction should be repeatedly emphasized, the amount of coal burned should be strictly controlled. [ABSTRACT FROM AUTHOR]