Promote Energy Conservation Research Articles

Energy saving and consumption reduction in the transportation of petroleum products: A pipeline pricing optimization perspective

Pipeline transportation is a low-energy and economical mode of transporting petroleum products in the downstream supply chain, however, there is almost no theoretical research on its pricing strategies. The unreasonable pricing strategy has resulted in low utilization of multi-product pipeline capacity as well as high energy consumption of petroleum products transportation. Therefore, this paper aims to improve pipeline turnover and promote the low-carbon transportation market from the perspective of pipeline pricing optimization. We propose an integrated framework for multi-product pipelines that couples pricing strategy and logistics optimization model. This framework simulates the pricing behavior of the pipeline carrier and the corresponding logistics planning behavior of the oil shipper. We apply the framwork to 10 pipeline pricing schemes for two regions in China with different logistics structures, and analyze the economic and environmental benefits of the new strategy. The results show that the well-performing scheme can increase pipeline carriers' revenue by 11.41 million CNY per month, significantly improve the competitive advantage of long-distance pipelines, and reduce energy consumption by 272 tce. Based on these findings, we provide recommendations for policymakers at four levels. In conclusion, the new pricing strategy will help reverse the disadvantageous situation of the pipeline in the competitive market and promote energy conservation in the petroleum products logistics industry.

Eco-friendly wood plastic composites with biomass-activated carbon-based form-stable phase change material for building energy conversion

Phase change materials (PCM) can store heat energy through the process of phase change and keep the ambient temperature in a comfortable range, thus reaching the aim of energy conservation and emission reduction. To improve the latent heat capacity, activated carbon (AC) with a dendritic pore structure was used as the carrier, and polyethylene glycol (PEG) was loaded by vacuum adsorption method. A dendritic pore structure with a nesting pattern of macropores, mesopores, and micropores was formed through the steam activation process of waste wood chips, leading to a high load capacity (70%) and uniform distribution, which showed high heat storage performance (ΔHm reached 116 J/g). Then the form-stable phase change material with satisfactory performance (AC/PEG-70) was combined with wood flour/ high-density polyethylene (WF/HDPE) through blending and hot pressing to fabricate phase change heat storage wood-plastic composite material (A-WPC). When the AC/PEG-70 content was 50%, the elongation at break increased by 167% (20%), and the rigidity of the material enhanced. ΔHm of A-WPC-50 was 19 J/g, undoubtedly at this point, achieving the expected thermal performance. Thus, we prepared an eco-friendly wood-plastic composite with high latent heat capacity and high stability by using the dendritic pore structure of biomass activated carbon-based form-stable PCM, which has great significance in promoting energy conservation and emission reduction, responding to green technological innovation and promoting the development of the green and low-carbon industry.

Energy Performance of Occupant Behaviors on Windows: A Green Building Based Study

In this paper, the window-opening behavior in a three-star green building with an operation mark in Ningbo was investigated. Four single offices facing south were selected, and the measurement lasted 20–40 days in the cooling season. An analysis of the relationship between window use and environmental factors was assessed by monitoring the occupancy state, the window action and window state, the time, and the temperature and humidity. A statistical analysis method was conducted to reveal the similarities and differences in window use among different occupants. The main findings were as follows: The window adjustment behaviors of different people vary significantly. In terms of adjustment time, there are two modes of behaviors. In addition, the occupancy state had a great impact on window action. Moreover, some people prefer to open the windows in the morning and close the windows at departure time, However, some of them prefer to open the windows at departure time and close the windows at the arrival time. Some irrational window opening behaviors were found in this research. Through correlation analysis, it was shown that the longer time the occupants were in the office, the higher window-opening duration and window-opening frequency would be. If the window was closed at arrival time, the total opening duration of window was significantly reduced. Also, window opening duration and closing duration are proportional to each other. With the help of principal component analysis (PCA) of the 12 features that affected window adjustment, the correlation between the window opening behaviors and the features could be clearly illustrated. A stochastic model of window-opening behavior based on logistics regression and uncertainty analysis was used in this paper. The cooling energy consumption of the stochastic model is 99.9% higher than the energy consumption generated by a fixed number of air changes, and the average energy consumption exceeds the fixed value by more than 21%. The findings of this study have certain guiding significance for promoting energy conservation by occupants’ behaviors in green buildings in this region.

Energy saving behavior in university organizations: The value of norm constructions in a "rational choice" action model.

In times of rising energy prices and increasing importance of climate change, saving energy becomes even more important. Universities are large public institutions with significant energy-saving potential. This study investigated the energy-saving behavior of students and employees at a German university. In contrast to previous studies, which often focused on individual buildings, this study took a comprehensive approach and addressed all university members (employees and students). A extended model of the Theory of Planned Behavior (TPB) served as the theoretical basis. Considering the specific organizational context, the main question of the study was to explore the interlinkages between the intention to save energy, corresponding consumption behavior, and the effects of injunctive and descriptive social norms within the social system of the organization. Furthermore, the impact of "not energy related" factors like the identification with the organization was tested. As methodological approach a university-wide quantitative online survey was conducted. For the survey, a standardized questionnaire containing several scales on energy consumption behavior and TBP-constructs was used. All in all, data from a total of 1,714 members of the university participating in the study was analyzed. Structural equation modeling showed that the extended TPB model yields a satisfactory amount of explained variance (approximately 40%) for intention and a moderate amount (approximately 20%) for behavior. The strongest predictors are personal norm and behavioral control. The organizational influence factor identification was also significant for intention, but only to a small extent. The results extend the understanding of the TPB in the context of energy conservation in universities and emphasize that the sense of behavioral control and the personal norm must always be considered when intervening in this context to promote energy conservation and thus provide valuable hints for practical measures.

An Empirical Study on How Financial Development Influences Carbon Emissions in Yangtze River Delta

Financial development influences economic development to some extent. China is in the important stage of economic restructuring and upgradation, while facing both the foreign and the domestic pressure of developing low-carbon economy and promoting energy conservation and emissions reduction, requiring people to understand the relationship between financial development and carbon emissions. This paper examines how financial development influences the carbon emissions using the panel data composed by 37 prefecture-level cities in Yangtze River delta during the 2008-2017 period. This paper build the multiple regression model based on modified environmental impact assessment model (EIA) and measure financial development level using the percentage of loan balance of financial institutions in GDP and the percentage of saving balance of urban residents in GDP. The result shows a negative association between financial development and carbon emissions among 37 cities in Yangtze River Delta. Therefore, the policymakers should try to maximize the supporting of financial institutions to local economies, develop green finance and promote the regional information sharing and cooperation.

The Path to Low Carbon: The Impact of Network Infrastructure Construction on Energy Conservation and Emission Reduction

Energy conservation and emission reduction are important ways to cope with global warming. An analysis of energy conservation and emission reduction from the perspective of network infrastructure construction provides an important perspective for the study of sustainable development. Based on the research sample of 263 cities in China from 2006 to 2019, and taking the policy of “Broadband China” as a quasi-natural experiment, this paper uses the double difference model to evaluate the impact of network infrastructure construction on energy conservation and emission reduction. The results show that (1) the construction of network infrastructure can significantly improve the energy utilization rate and reduce carbon emissions intensity, which helps to promote energy conservation and emission reduction. (2) From the perspective of a functional mechanism, on the one hand, network infrastructure construction affects energy conservation and emission reduction through micro-mechanisms such as green technology innovation and energy efficiency. On the other hand, network infrastructure construction also drives the development of the Internet and the digital economy, and promotes energy conservation and emission reduction through macro-mechanisms such as industrial structure and financial development. (3) The heterogeneity analysis shows that network infrastructure construction in non-resource-based cities, eastern regions and low-carbon cities has a greater impact on energy conservation and emission reduction. This study provides a new perspective for achieving low-carbon development goals.

Evaluating the effect of normative feedback on energy conservation in a shared space

Normative feedback is considered a cost-effective solution for promoting energy conservation in private homes. However, for occupants in a shared space, who have no or split financial incentives, it remains unclear whether normative feedback is effective in encouraging them to conserve energy. To fill this research gap, this study presented a field experiment to test the energy-saving effect of normative feedback in shared spaces contextualized in shared dorms. Difference-in-Differences analysis was used to examine its effectiveness. The results showed that normative feedback in the form of multi-level reference groups had a significant positive effect on occupants’ behavior change and energy savings in shared spaces, with energy savings of 7.73%. Detailed normative feedback can increase the efficacy of normative feedback in shared contexts, as it provides multi-level feedback with social comparative references. Besides, the effect of normative feedback significantly differed depending on group characteristics (i.e., genders, grades, kinds of users). Normative feedback exhibited a higher energy-saving rate for male groups than female groups. However, most of the male groups whose baseline energy is similar to that of females increased their energy consumption after receiving normative feedback. For males and females with the same baseline energy consumption level, motivating the male group to conserve energy is more challenging. Sending normative feedback to newcomers works better. The element of the injunctive message of normative feedback can partially eliminate the boomerang effect. Moreover, the effectiveness of normative feedback is affected by the duration of messaging, and its positive effect on behavioral change has a time lag of three weeks. However, the energy-saving effect of normative feedback only lasted until the intervention was discontinued. These conclusions provide insights into conserving energy in shared spaces by providing norm-based interventions.

Analysis of the Factors Affecting China’s Manufacturing Servitization from the Perspective of the Ecological Environment

Manufacturing servitization (MS) can effectively alleviate the contradiction between economic growth and ecological carrying capacity and can promote energy conservation and emission reduction in the manufacturing industry (MI). However, China’s MI is in the primary stage of servitization and lacks sufficient ability to provide services; thus, the environmental benefits of MS are not obvious. Therefore, in the context of current pressure to normalize environmental protection, how servitization can drive low-carbon development in MI while taking into account economic development has become an important topic at present. Thus, this study constructs an evaluation index system of factors based on a driver–pressure–state–impact–response (DPSIR) model, and uses the decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) model to analyze the causal relationship and key elements among the influencing factors. The results show that from the perspective of the ecological environment, many factors affect MS, although to varying degrees. Among them, the proportion of R&D personnel, input intensity, and the proportion of clean energy are the main factors. Based on the transmission mechanism among these factors, we propose two paths to realizing the service-oriented, low-carbon development of China’s MI.

Customer segmentation based on smart meter data analytics: Behavioral similarities with manual categorization for building types

Among the techniques supporting information services that promote energy conservation, clustering has been widely used for customer segmentation. However, the potential of smart meter data analytics based on clustering techniques for small- and medium-sized enterprises to recognize building types, such as offices, retail stores, and restaurants, has not been investigated sufficiently. Estimating building types based on the actual electricity consumption patterns could be a useful approach for energy service providers because manually defined building types can be inaccurate or unavailable. Thus, we evaluated a Z-score-based method and an operating time estimation-based method for clustering by applying them to an open smart meter dataset and comparing the results with manually defined building types. Although the Z-score-based method was more sensitive to drastic demand change, the operating time estimation-based method was more similar to the manual categorization, suggesting that both methods were reasonable. Buildings categorized by energy service providers as ‘Insurance’, which are usually used as offices with homogenous consumption patterns, tended not to be subdivided. In contrast, building types with diverse consumption patterns, such as ‘Restaurant’ and ‘Entertainment’, tended to be subdivided, suggesting the necessity for considering the actual electricity consumption patterns along with the use types.

A multi-objective model for cold chain logistics considering customer satisfaction

The cold chain logistics (CCL) distribution have been studied by considering customer satisfaction, we propose a multi-objective CCL model with the goals of minimal carbon transaction cost, minimal network cost and maximal customer satisfaction. According to the characteristics of the model, an improved Multi-Objective algorithm was designed, which integrates the dynamic crowding distance and differential mutation operator into non-dominated sorting genetic algorithm II (DDNSGA-II). The DDNSGA-II enhances the diversity of the initial population, the local search ability and search accuracy. Finally, the experimental data show that the proposed approaches effectively increase the customer satisfaction, reduce total distribution costs, and promote energy conservation and emission reduction.

IOT-Based Energy Monitoring System for Energy Conservation

The aim of this project is to develop an Internet of Things (IoT) based Energy Monitoring System to reduce energy waste and cutting down energy cost. Therefore, it needs a system which provide efficient energy consumption management. For the starting of designing an IoT-based Energy Monitoring System, different sensor and calculated AC measurement methods were studied. The development of this system is to integrate each of the sensor, energy measuring device and IoT system into one complete module. The concept of Wireless Sensor Network (WSN) was implemented in this project. The WSN obtained data information from sensor and send them to the cloud through the IoT network for cloud storage of the ThingSpeak platform. The system contains two input signal which is voltage and current. The device that transfers the data or information from the energy monitoring device to the cloud storage is the ESP8266 Wi-Fi module. The output is the energy consumption that has been used according to the real-time data measurement. Lastly, the data that is transmitted to the cloud can be monitored through the mobile application ThingView. In conclusion, this system is necessary because it can control and manage energy consumption to avoid wastage and promote energy conservation.

Like me or near me? Assessing which norm referents best promote energy conservation in the field

Messages about what others typically do are increasingly used to encourage sustainable behaviors. The effectiveness of such social norm interventions hinges on selecting an appropriate referent group. However, it is unclear which characteristics make norm referents effective. In a field experiment on energy conservation, in a non-WEIRD and under-studied setting, we examine the role of two referent characteristics: group identification and physical proximity. Students in university dorms (N = 584) were randomly assigned to a control group or to one of two treatment groups, in which they were given social norm information that varied only in whether it was about a group with whom they were likely to identify or a physically proximal group with whom they identify less. Tracking electricity meter reading data in the weeks before and after the intervention, we found that social norm information about the high identification group led to an 11 percent reduction in energy consumption relative to a control group. In the physical proximity condition, we did not find an overall reduction in energy use relative to controls, although the effect of the intervention was significantly moderated by identification with the referent group. We conclude that identification with a group is important for the efficacy of social norms interventions in this setting, and that physical proximity alone may be insufficient for an effective norm referent.

Energy management: DSTU ISO 50001:2020 and conditions of martial law

The authors of the article emphasize the relevance of the issue of energy management system functioning and its role for the country's economy and business entities. As the authors point out, this problem becomes particularly acute in the conditions of martial law in Ukraine. The article highlights that effective management of energy resources can contribute to the stabilization and development of the national economy, reduce dependence on imported energy, and diversify energy sources. The authors also emphasize the importance of investing in renewable energy sources and developing innovative technologies to improve energy efficiency, which contributes to environmental preservation. The article also stresses the need to adapt energy management practices to the challenging conditions of war based on the provisions and principles of DSTU ISO 50001:2020. It is emphasized that modern energy management faces a multitude of specific and critically important tasks, especially in wartime. These tasks include ensuring a stable energy supply, the rapid restoration of damaged infrastructure, promoting energy conservation, protecting energy infrastructure, and effective management of energy resources. Collaboration with government organizations and military structures is crucial, and communication with the public is also significant. All of this requires quick decision-making and flexibility, which are key to successful energy management in times of war. Particular attention should be paid to the consideration of strategies and decisions that can help overcome these challenges, including the wider adoption of renewable energy, energy conservation, and energy efficiency in the activities of businesses. In conclusion, the authors emphasize the need for a comprehensive approach and rapid adaptation to changing wartime conditions for effective energy management. They point out that such an approach will not only help Ukraine overcome current challenges but also ensure a sustainable energy future. This, in turn, will contribute to economic growth, environmental improvement, and national security.

Promoting Energy Conservation in Social Housing Districts: Cautionary Evidence of Social Comparisons

Promoting Energy Conservation in Social Housing Districts: Cautionary Evidence of Social Comparisons

Fundamental Study on System Efficiency of Vacuum-based Membrane Dehumidification System

In recent years, the sensible heat load of buildings has been decreasing due to the promotion of energy conservation, and the sensible heat factor is expected to decrease. In response, the conventional dehumidification method using overcooled condensation is likely insufficient to handle latent heat, and an advanced dehumidification method is required. The authors have focused these issues and development on a dehumidification method using membranes. Membrane dehumidification systems (MDS) are relatively simple, then it is expected to be next-generation dehumidification system. Therefore, to evaluate the energysaving performance of MDS, this study developed an energy consumption balance equation for a system that uses overcooled & reheating and MDS, and verified energy-saving performance under different conditions. The results of the study quantitatively showed the system efficiency (Specific energy consumption, vacuum pump consumption per unit of dehumidification) of MDS, which is the amount of energy saved by MDS compared to the conventional system under the specified COP of the cooled heat source equipment and reheating equipment. The system efficiency at which MDS is superior under different room sensible heat factors and membrane utilization methods are also clarified. This enables determining the required system efficiency when considering the introduction of a MDS, and understanding the conditions for introducing a system in which MDS is competitive.

Research on Spatial Difference, Distribution Dynamics and Influencing Factors of Urban Water-Use Efficiency in the Yellow River Basin

This study creatively uses the Dagum Gini coefficient, Kernel density estimation, and Markov chain to measure the spatial difference and distribution dynamics of urban water-use efficiency in the Yellow River Basin from 2008 to 2018 accurately and also analyzes its formation mechanism by using the Spatial Durbin Model. The results show that the hypervariable density and the intraregional differences constitute the main source of regional differences in the whole basin; the dynamic evolution characteristics of the urban water-use efficiency distribution in different reaches are different. The spatial factors have a non-negligible impact; the urbanization process and population density spatial spillover effects are negative in the state of spatial interaction; the spillover effect of upgrading the industrial structure is positive; the direct and spillover effects of openness are both positive; and the direct effect of the water-use structure is positive. In order to improve the urban water-use efficiency in the Yellow River Basin, it is necessary to comprehensively promote new urbanization, upgrade industrial structures, promote energy conservation and emission reduction, construct business environments, and establish an inter-regional coordination mechanism.

Energy Literacy of Residents and Sustainable Tourism Interaction in Ethnic Tourism: A Study of the Longji Terraces in Guilin, China

Energy and environment form a nexus in which residents are the owners of tourism energy resources. Only a few studies have focused on the energy literacy of residents in ethnic tourism destinations and its impact on sustainable tourism. Using a qualitative research approach through field works and in-depth interviews in the Ping’an Village, Longji Terraces Scenic Area, this study explored the relationships between the energy literacy of residents and sustainable tourism in ethnic areas. The result showed that the energy literacy of the ethnic residents of Pingan village in terms of knowledge, attitude, and behavior has increased in line with the development of tourism, and both external and internal factors contribute to the improvement. Besides, the promotion of energy literacy among the residents not only has a positive impact on the tourists’ behavior but also brings about effective improvements in the local energy use structure and infrastructure, thus contributing to the sustainable development of tourism. This research extends the understanding of energy literacy from the perspective of ethnic residents and changes in energy literacy in remote ethnic villages under tourism development. The results also deepen our understanding of such changes in the behavior of tourists and tourism destination sustainability and enrich the empirical research to promote energy conservation and sustainable tourism development in ethnic areas.

Study on Influencing Factors and Spatial Effects of Carbon Emissions Based on Logarithmic Mean Divisia Index Model: A Case Study of Hunan Province

China has committed to peaking carbon dioxide emissions by 2030 and has set a goal of working towards carbon neutrality by 2060. Hunan province is a vital undertaking place for national industrial transfer. It is of great significance for promoting energy conservation and emission reduction to investigate the influencing factors and spatial effects of carbon emissions in Hunan province. Firstly, based on the energy consumption data of Hunan province from 2005 to 2017, this paper uses the method recommended by the Intergovernmental Panel on Climate Change (IPCC) to measure the carbon emissions of Hunan province and its economic zones. Secondly, the five-factor Logarithmic Mean Divisia Index (LMDI) model is constructed to analyze the influence degree of population size, economic development, industrial structure, energy intensity, and energy structure on carbon emissions. Finally, the spatial differences of the influencing factors in the four economic zones of Hunan province are analyzed. The research shows that: (1) An overall carbon emission reduction has been achieved in Hunan province since 2011. (2) Changsha–Zhuzhou–Xiangtan Economic Zone is the key area to achieve carbon emission reduction, while there is still the phenomenon of emission increase in the other three economic zones. (3) For all economic zones, economic development contributes the most to the increase in carbon emissions, while energy intensity shows the strongest inhibitory effect. Other factors have various effects on the four economic zones.

Impact of Urban Mining on Energy Efficiency: Evidence from China

Achievement of carbon neutrality requires lowering energy consumption in China. However, only a few studies have focused on the impact of urban mining on the reduction in energy consumption, and the impact of urban mining on reducing energy consumption remains unclear. This study explored the impact of urban mining on energy efficiency by adopting the panel data of 281 prefecture-level cities in China between 2003 and 2016 using the difference-in-difference method, and tested the setting up of urban mining pilot bases on reducing urban energy consumption per unit of gross domestic product (GDP) and channel mechanisms. The empirical findings show that urban mining pilot bases have significantly reduced energy consumption per unit of GDP by 3.67%. The instrumental variable method was used to overcome endogenous problems of the empirical results and related robustness tests. The verification results of the impact mechanism show that urban mining reduces the energy consumption per unit of GDP through three channels: by improving the degree of urban marketization, enhancing the harmony between the government and the market, and increasing the abundance of factor markets. The heterogeneity analysis shows that urban mining has a significant reduction effect on energy consumption per unit of GDP in all four regions of China; however, the energy-saving effect in the northeast is higher than that in the other regions. This study provides an empirical test and policy insights for the contribution of urban mining pilot bases in promoting China’s development of green industry and circular economy. It also offers a new path for cities in developing countries to promote energy conservation and achieve urban sustainability via urban mining.

Impact of Digital Economy Development on Carbon Emission Efficiency: A Spatial Econometric Analysis Based on Chinese Provinces and Cities.

In the realistic context of the development of China's digital economy and carbon peaking and carbon neutrality goals, to efficiently achieve high-quality economic and green and low-carbon transformation, this paper investigates the impact of digital economy development on the carbon emission efficiency of 30 Chinese provinces and cities from 2011-2019. In this paper, firstly, the digital economy development index and carbon emission efficiency are calculated by the entropy method and the Super-SBM-Undesirable Model. Secondly, the Spatial Lag Model (SAR) and the Spatial Durbin Model (SDM) are respectively constructed under the adjacency matrix and the geographic distance matrix to empirically test the spatial impact of the digital economy on carbon emission efficiency. The results show that: the digital economy development and carbon emission efficiency of Chinese provinces and cities both show the spatial distribution characteristics of stronger in the East and weaker in the Middle and West; the digital economy development in Chinese provinces and cities has a significantly positive direct and spatial spillover effect on carbon emission efficiency; there are differences in the direct and spatial spillover effects of various dimensions of the digital economy development on the carbon emission efficiency in Chinese provinces and cities; the direct effect of the digital economy development on the carbon emission efficiency in Chinese provinces and cities has significant regional heterogeneity among eastern, central, and western regions. This paper provides new empirical evidence for developing countries such as China to proactively develop a digital economy to promote energy conservation and emission reduction to realize green and low-carbon transformation.