Energy Efficiency最新文献

As the world accelerates the transition to a carbon–neutral economy, the business circle has been increasingly under pressure to address climate change issues at a strategic level. Companies have paid attention to international technology transfer and clean mechanism development (CDM) as a strategic means to facilitate low-carbon innovation and help emerging countries manage carbon emission reductions at the same time. This study explores dynamic processes of low-carbon technology transfer through CDM and international cooperation. An in-depth case study about a pioneering refrigerator CDM project presents lessons on successfully implementing and creating benefits to all stakeholders engaged in cooperation. Firms should approach consumer product-focused CDM from market competition and strategy perspective, not government expenditure. Governments' role is to provide product- and market-based regulatory schemes. Technology transfer utilizing adequate-level technologies and international cooperation could generate mutual benefits for all stakeholders, creating shared value.

The aim of this study is to investigate the relationship between corporate emission reduction policies (ERPs), greenhouse gas (GHG) emissions, and the moderating role of corporate governance. Using a dataset of 18,559 firm-year observations from 28 developed and emerging countries from (Mollick, and Haidar, 2011) and 2022, the study finds that for firms with stronger corporate governance, higher ERPs are associated with more substantive emission intensity reductions. Findings remain robust across multiple specifications. Firm-level trend regression confirms that if a firm’s ERPs improve over time compared to the sector average, emission intensity decreases. Results underscore the importance of strong corporate governance in mitigating greenwashing risks and ensuring the credibility of corporate climate commitments. The study contributes to the growing literature on climate governance, and corporate environmental strategy by highlighting the interplay between corporate governance and ERPs in achieving emission intensity reductions. Research avenues, limitations, and recommendations are presented, emphasizing specifically the need for investors and regulators to not only focus on the level of ERP adoption, but scrutinize governance structures that determine ERP effectiveness in practice.

Sweden implemented a unique policy instrument over two consecutive five-year periods aimed at promoting industrial energy efficiency: a voluntary agreement programme (VAP) known as the Programme for Improving Energy Efficiency in Energy-Intensive Industries (PFE). This paper evaluates the second programme period using process and impact evaluation approaches. The impact evaluation revealed that the programme generated numerous benefits beyond the implementation of energy efficiency measures. The second programme period demonstrated impacts comparable to the first, underscoring the pivotal role of energy management within policy frameworks. Moreover, the findings suggest that VAPs may be among the few policy instruments capable of achieving substantial impact within industrial production processes. The process evaluation identified two critical gaps: a policy gap and a knowledge gap. Many of the positive elements present in the evaluated programme are currently absent from Sweden’s industrial policy mix. The role of the policy operator—as facilitator or intermediary—proved essential, particularly in the context of policies involving energy audits and certified energy management systems. In this case, the Swedish Energy Agency played a central role. The study concludes that continuous energy management, when integrated throughout the entire organization, significantly enhances companies’ capacity to identify and implement energy efficiency measures. This approach not only deepens internal knowledge but also fosters the development of more structured and effective routines. Furthermore, the findings suggest that financial incentives may be essential to ensure the long-term persistence of energy efficiency practices. Consequently, future policy design should include a strong facilitator and incorporate mechanisms that both reinforce organizational knowledge of energy end-use processes and promote sustained engagement over time, preferably involving a financial incentive.

Energy and emissions projections are essential for effective climate policymaking, yet their alignment with actual developments is rarely evaluated. This study retrospectively assesses carbon dioxide emissions projections for the buildings sector in Belgium and the Netherlands between 2000 and 2020. Using a mixed-methods approach, it combines decomposition analysis with a review of policy and socio-economic contexts to compare 43 national scenarios against historical data. Emissions were decomposed into four drivers, weather, socio-economic activity, energy intensity, and emission intensity, to identify causes of deviations. Projections in both countries consistently overestimated emissions and energy use when compared to historical data, with 2020 deviations averaging + 22% for Belgium and + 15% for the Netherlands in residential buildings, and + 29% and over in the service sector. Energy intensity was the most uncertain and typically overestimated driver, which likely reflects a combination of modest efficiency improvements embedded in the policy package at the time and limitations in how scenarios represented future savings. Emission intensity trends were more accurately captured, while socio-economic and heating degree day assumptions varied in precision. Scenarios with higher policy ambition showed notably smaller deviations. All scenarios assumed uninterrupted activity growth or swift rebounds after disruptions, which contributed to the observed deviations. This comparative assessment demonstrates the value of systematic hindsight analysis to improve projection methodologies and policy design. It highlights the need for more ambitious scenarios that move beyond prevailing concerns, draw on past policy impact assessments to improve modelling of energy intensity and behavioural change, and incorporate dynamic assumptions on economic, demographic, and weather-related uncertainties.

Buildings are not airtight, leading to air infiltration, defined as the uncontrolled flow of outdoor air into indoor spaces. These airflows have a detrimental impact on energy demand and consumption, making their accurate estimation in building energy performance assessment tools essential. In Spain, the current tools allow the use of four infiltration models: N-factor, LBL, AIM-2, and EN 16798–7. This study compares these four approaches using TRNSYS energy simulations applied to a real single-family dwelling. The building envelope was characterized by performing a Blower Door Test, and the analysis was extended to eight cities with different climatic conditions. The maximum difference in the estimated energy impact among the models ranged from 6.1% to 12.2%. In climates with mild winters and higher wind intensity, the differences between models were less pronounced, ranging from 1.29 to 2.57 kWh/m²·year. Conversely, in colder climates with lower wind intensity, the differences were substantially higher, ranging from 2.8 to 7.37 kWh/m²·year. These results highlight the importance of selecting an appropriate infiltration model based on climatic conditions. For colder climates with low wind intensity, the AIM-2 and EN 16798–7 models are recommended.

Energy innovations play a central role in driving the ongoing energy transition towards a renewable-based system. Whereas innovative energy technologies exist, their broad diffusion is still missing. Coordinated professionals are key to offering integrated services to potential adopters, thus, supporting the diffusion of innovative energy technologies. However, limited attention is paid to the role of information networks and coordination among professional actors to support the diffusion. This study analyses information networks in the sector of energy technologies in Switzerland to determine levers to improve information flows and coordination among professional actors to support innovation-diffusion. We identified and characterised relevant actors in the field and surveyed them collecting data on their geographical location, interactions, and events or associations used to exchange information. By constructing socio-spatial information networks, we measured diversity, connectivity and geographical proximity. The findings show that professional networks diffusing information on energy technologies are characterised by (i) asymmetric information flows, (ii) potential of events and associations in disseminating information and bridging different professionals, (iii) diversity of actors tightly connected, and (iv) limited relevance of geographical proximity. Strategies to support further innovation-diffusion should focus on nurturing clusters of professional actors independent from each other, fostering bi-directional information flows, leveraging events and associations to link diverse actors, and utilising proximity dimensions alternative to the geographical one to connect professionals. We also identify a need to further explore the circumstances that bring actors together into a situation of interaction.

The proclaimed goal of European energy policies is a just and sustainable energy transition. While extensive research has focused on energy transition and efficiency, micro-enterprises, a critical segment of the European economy, remain underexplored. Micro-enterprises account for 93.7% of EU companies and nearly 17% of total EU turnover. They are also a contributing factor to welfare, where entire families rely on the stability of a single micro-enterprise. Due to their size and supply chain positioning, they are disproportionately vulnerable to energy price fluctuations, supply disruptions and regulatory changes. We investigate the energy vulnerability of micro-enterprises in the EU, highlighting their unique challenges in energy transition policies, financial constraints, and market dynamics. A composite vulnerability index (MEVI) is developed, integrating factors like energy dependency, market access and business vulnerabilities, to rank EU Member States based on their micro-enterprise energy vulnerability. The findings suggest variations in vulnerability across countries, influenced by energy market structure, macroeconomic conditions or sector-specific energy needs. The research underscores the necessity for tailored policies and further data collection to better address the energy vulnerability of micro-enterprises, a sector often overlooked in energy policies.

With buildings accounting for 30% of global energy use, improving operational energy efficiency is critical to achieving climate goals. In addition to conventional retrofitting strategies, Building Automation and Control Systems (BACS) offer significant potential to reduce energy use while preserving comfort. The European standard EN ISO 52120–1 supports BACS integration using the BAC-factor method, a simplified, factor-based estimation of energy savings. However, these generic efficiency factors do not account for variations in building typologies and building characteristics, this variability has not been systematically quantified. This study provides an innovative simulation-based approach for an initial exploration of the variance in BACS savings, over multiple office typologies and building characteristics. Simulated savings show large variability across different BAC functions: 19–71% for heating emission control, 1–58% for cooling emission control, 6–46% and 4–94% respectively for heating and cooling energy in ventilation control, 14–65% for lighting energy control, and -27–74% for cooling energy with shading control. Analysis of variance (ANOVA) and effect size analysis are used to quantify how key building characteristics, i.e. typology, window-to-wall ratio, and envelope insulation, drive the variability of BACS energy savings. The findings provide quantitative evidence that BACS performance is highly context-dependent and that a uniform, fixed-factor approach like the BAC-factor method fails to capture this diversity. These findings emphasize the importance of developing context-aware evaluation methods that account for building-specific characteristics to more accurately predict BACS energy savings.

This study develops a spatially optimized solar photovoltaic (PV) expansion strategy for Budapest, Hungary, which aims to increase PV capacity from 200 MW to 1,500 MW by 2030 in line with its climate and urban development goals. Using an integrated top-down and bottom-up approach, the study combines GIS and LiDAR-based data with building typology analysis to assess technical feasibility and prioritize deployment. Results show that the raw technical PV potential of 5,000 MW reduced to 2,200 MW deemed realistically installable after spatial and regulatory constraints. Public institutions and prefabricated panel buildings offer the highest deployment efficiency, while World Heritage visibility restrictions reduce the potential by 170 MW. Two implementation scenarios (1,500 MW and 2,200 MW) highlight the importance of standardized installations and public sector involvement to reduce cost and time. The findings inform policy design by linking spatial planning, urban morphology, and economic feasibility, offering a replicable model for other EU Mission cities.

A reliable measure of the energy efficiency of housing is essential, both for evaluating the effectiveness of energy efficiency policies and for assessing energy poverty. Across the EU, Energy Performance Certificates (EPCs) or energy labels are commonly used for this purpose. However, these data are often outdated or incomplete, and only weakly correlated with actual energy consumption —a discrepancy known as the performance gap. As a result, EPCs are poorly suited for evaluating energetic housing quality or measuring energy poverty. We address these limitations by developing and implementing a model that estimates housing energy efficiency by combining EPC data with additional administrative resources. Our approach improves upon previous studies through richer data integration and more precise model calibration. The resulting model explains 51% of the variation in energy expenditure based on housing characteristics, compared to 40% when using EPCs alone. We demonstrate the model’s application in assessing energy poverty through the LILEQ indicator (i.e. Low Income, Low Energy Quality), showing that it correlates more strongly with survey-based consensual indicators of energy poverty (e.g. EU-SILC), than commonly used indicators based on actual expenditure (e.g. share of energy expenditure). Finally, we illustrate how the model can be used to detect energy underconsumption and monitoring housing quality over time. In summary, we present a calibrated, data-driven model of housing energy efficiency that outperforms EPCs and enables the development of higher-quality, policy-relevant measures of energy poverty and housing conditions.