Examining the dynamics between economic development, tourism, renewable energy and life expectancy in the Nordic economies.

As the world struggles with pressing issues like climate change and sustainable development, affecting health outcomes and environmental quality, the Nordic regionsare at the forefront of major global challenges. This paper investigates the role of human capital, renewable energy use, tourism, natural resources, and economic growth in shaping life in the Nordic region i.e., Denmark, Norway, Sweden, Finland, and Iceland).Utilizing panel data spanning from 1990 to 2020, the Driscoll and Kraay standard error (DSK) technique is employed to analyze this intricate interplay. The study reveals that in the Nordic context, sustainable economic growth, bolstered by investments in human capital and the widespread acceptance of renewable energy sources, has been positively associated with increased life expectancies. Furthermore, prudent management of natural resources has helped mitigate adverse health effects related to depletion, maintaining environmental and public health standards. The thriving tourism industry has also been shown to influence lifespan in this region positively. On the contrary, the empirical finding contended that an adverse correlation exists between carbon emissions and LEX. This research underscores the importance of a comprehensive and balanced approach that considers economic development, sustainable development, and public health in pursuing longer and healthier lives, providing valuable insights for policymakers and regions seeking to replicate these positive outcomes.The findings of this study are both conceptually reliable and empirically robust, providing important insights for the formulation of environmental and health policy.

Measuring social equity in urban energy use and interventions using fine-scale data.

Cities seek nuanced understanding of intraurban inequality in energy use, addressing both income and race, to inform equitable investment in climate actions. However, nationwide energy consumption surveys are limited (<6,000 samples in the United States), and utility-provided data are highly aggregated. Limited prior analyses suggest disparity in energy use intensity (EUI) by income is ∼25%, while racial disparities are not quantified nor unpacked from income. This paper, using new empirical fine spatial scale data covering all 200,000 households in two US cities, along with separating temperature-sensitive EUI, reveals intraurban EUI disparities up to a factor of five greater than previously known. We find 1) annual EUI disparity ratios of 1.27 and 1.66, comparing lowest- versus highest-income block groups (i.e., 27 and 66% higher), while previous literature indicated only ∼25% difference; 2) a racial effect distinct from income, wherein non-White block groups (highest quintile non-White percentage) in the lowest-income stratum reported up to a further ∼40% higher annual EUI than less diverse block groups, providing an empirical estimate of racial disparities; 3) separating temperature-sensitive EUI unmasked larger disparities, with heating-cooling electricity EUI of lowest-income block groups up to 2.67 times (167% greater) that of highest income, and high racial disparity within lowest-income strata wherein high non-White (>75%) population block groups report EUI up to 2.56 times (156% larger) that of majority White block groups; and 4) spatial scales of data aggregation impact inequality measures. Quadrant analyses are developed to guide spatial prioritization of energy investment for carbon mitigation and equity. These methods are potentially translatable to other cities and utilities.

Crude oil price volatility and environmental performance.

We study the relationship between crude oil price volatility and corporate environmental performance. Using an extensive dataset from 32 countries consisting of 18,464 firm-year observations, we provide strong evidence that oil price volatility significantly increases firms' environmental performance. Our main inference is robust when using alternative measures of oil price volatility and environmental performance, alternative econometric specifications and samples, and several approaches to control for endogeneity. In a set of additional analyses, we first conduct a difference-in-differences analysis that exploits the Arab Spring as an exogenous oil price volatility increase and document a stronger relationship between oil price volatility and environmental performance in the aftermath of the Arab Spring. We second identify (i) capital expenditures and (ii) alternative energy importation as two mechanisms through which oil price volatility influences environmental performance. We finally show that national culture plays a significant role in moderating the relationship between oil price volatility and environmental performance. Taken together, our empirical findings highlight the role of economic uncertainty in affecting firms' environmental performance and provide significant contributions to management and policymakers.

What drives the relationship between digitalization and energy demand? Exploring heterogeneity in German manufacturing firms.

The growing use of information and communication technologies (ICT) has the potential to increase productivity and improve energy efficiency. However, digital technologies also consume energy, resulting in a complex relationship between digitalization and energy demand and an uncertain net effect. To steer digital transformation towards sustainability, it is crucial to understand the conditions under which digital technologies increase or decrease firm-level energy consumption. This study examines the drivers of this relationship, focusing on German manufacturing firms and leveraging comprehensive administrative panel data from 2009 to 2017, analyzed using the Generalized Random Forest algorithm. Our results reveal that the relationship between digitalization and energy use at the firm level is heterogeneous. However, we find that digitalization more frequently increases energy use, mainly driven by a rise in electricity consumption. This increase is lower in energy-intensive industries and higher in markets with low competition. Smaller firms in structurally weak regions show higher energy consumption growth than larger firms in economically stronger regions. Our study contributes to the literature by using a non-parametric method to identify specific firm-level and external characteristics that influence the impact of digital technologies on energy demand, highlighting the need for carefully designed digitalization policies to achieve climate goals.

COP 28 Policy Perspectives: Achieving Environmental Sustainability through FDI, Technological Innovation Index, Trade Openness, Energy Consumption, and Economic Development in N-11 Emerging Economies.

Despite remarkable success in attracting foreign direct investment (FDI) to achieve maximum economic growth, the Next-11 emerging economies grappling with an undesirable situation of environmental degradation have become a hot topic at COP28. Researchers have long focused on this connection, emphasizing the urgent need for international and national environmentalists to promote sustainable development (SD) in these rapidly growing economies under the United Nations (UN) Framework Convention on Climate Change action plans. As a result, this study examines the role of FDI in the N-11 emerging economies, focusing on energy usage and technological innovation within the theoretical framework of the Halo-Haven hypothesis, covering the period from 1990 to 2022. We utilize ARDL, FMOLS, and DOLS techniques to analyze both short-term dynamics and long-term equilibrium relationships, effectively managing heterogeneity, time dynamics, and cross-sectional dependence issues to produce comprehensive results. The long-term analysis supports the haven hypothesis, demonstrating an affirmative relationship between FDI, economic growth, and carbon emissions, whereas energy usage is negatively associated with carbon emissions. Furthermore, the D-H test established a reciprocal causal relationship between variables such as FDI, economic growth, trade openness, and environmental pollution. However, we found a one-way causal correspondence in the usage of green energy, the technological innovation index, and carbon emissions. Given the mixed findings, policymakers should focus on attracting FDI to the green energy sector while reinforcing regulations and implementing stringent oversight for FDI in energy-intensive industries. This approach will ensure that such investments adhere to high environmental standards, thereby benefiting future generations.

Beyond grassland degradation: Pathways to resilience for pastoralist households in alpine grassland ecosystems.

Sustaining the development of rural and pastoral communities' hinges on livelihood resilience. Pastoralist household resilience relies on resource availability and decision-making abilities. Despite extensive studies on pastoralist livelihoods, a significant knowledge gap remains in understanding the nuanced adaptive capacities of diverse households, particularly amid grassland degradation. Thus, this study investigates the household-based livelihood resilience of pastoralists in China's Three-River Headwater Region, offering policy recommendations for resilient livelihoods. Using stratified random sampling, 758 pastoralist household heads underwent semi-structured interviews to collect data. Five household characteristics, encompassing age, gender, energy use, well-being perception, and multi-household grazing participation, were evaluated. Looking ot the nature of data, descriptive statistics and non-parametric tests were performed in this study to draw the valid inferences. The results revealed a positive correlation (p < 0.05) between household head age and livelihood resilience, with divergent resilience across age groups. Varied energy usage yielded distinct impacts; households employing solar or mixed energy sources exhibited heightened resilience (p < 0.05). Household well-being emerged as an invariant variable concerning resilience. Furthermore, engagement in multi-household grazing (an informal institution) significantly (p < 0.05) influenced pastoralist livelihood resilience. These insights advocate targeted support for young household heads and the adoption of clean energy. Exploring the deeper strategies and mechanisms of multi-household grazing can enhance understanding and policy integration, guiding eco-friendly progress within rustic landscapes for pastoral communities.

Forecasting synergistic pathways between rare earth elements, renewable energy, and product and economic complexities in achieving a low-carbon future.

Recent decades have witnessed an unprecedented transformation in the global energy landscape, driven by environmental concerns and the quest for sustainable economic growth. As the world grapples with the urgent need for decarbonization, the utilization of renewable energy technologies with the instrumental role of rare earth elements (REEs) has come to the forefront. However, empirical investigations into their synergistic pathways for product and economic complexities concerning achieving a low-carbon future remain scarce. Therefore, we forecast synergistic pathways between the REE supply, renewable energy, economic and product complexities, and GDP growth using a panel dataset of 11 REE-producing countries from 1990 to 2023. We used Common Correlated Effects and Temporal Causal Models as primary methods to estimate panel long-run elasticities and subsequently forecast mutual causal synergies between the variables. The results indicated that REE supply led to renewable energy and economic growth that further elevated the countries' product and economic complexities rankings. GDP growth increased REE production, economic complexity, and renewable energy directly, and consequently, product complexity and REE production through them. This underscores the positive role of REE production coupled with renewable energy technologies in achieving a low-carbon future based on economic diversification, enhanced industrial capabilities, and technological sophistication.

Protein plant factories: production and resource use efficiency of soybean proteins in vertical farming.

BACKGROUND: Controlled environment agriculture, particularly vertical farms (VF), also called plant factories, is often claimed as a solution for global food security due to its ability to produce crops unaffected by weather or pests. In principle, essential macronutrients of the human diet, like protein, could technically be produced in VF. This aspect becomes relevant in the era of protein transition, marked by an increasing consumer interest in plant-based protein and environmental challenges faced by conventional farming. However, the real question is: what does the cultivation of protein crops in VF imply in terms of resource use? To address this, a study was conducted using a VF experiment focusing on two soybean cultivars. RESULTS: With a variable plant density to optimize area use, and because of the ability to have more crop cycles per year, protein yield per square metre of crop was about eight times higher than in the open field. Assuming soy as the only protein source in the diet, the resources needed to get total yearly protein requirement of a reference adult would be 20 m2 of crop area, 2.4 m3 of water and 16 MWh of electricity, versus 164 m2, 111 m3 and 0.009 MWh in the field. CONCLUSIONS: The study's results inform the debate on protein production and the efficiency of VF compared to conventional methods. With current electricity prices, it is unlikely to justify production of simple protein crops in VF or promote it as a solution to meet global protein needs. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

The Environmental Sustainability of Plant-Based Dietary Patterns: A Scoping Review.

BACKGROUND: A large part of the existential threat associated with climate change is the result of current human feeding patterns. Over the last decade, research evaluating the diet-related environmental impacts of plant-based diets has emerged, and a synthesis of the available data is now due. OBJECTIVES: The objectives of the study were as follows: 1) to compile and summarize the literature on diet-related environmental impacts of plant-based dietary patterns; 2) to assess the nature of the data on impacts of plant-based dietary patterns on both environmental parameters and health (e.g., if land use is reduced for a particular diet, is cancer risk also reduced?); and 3) to determine where sufficient data exist for meta-analyses, in addition to identifying gaps within the literature. METHODS: Global peer-reviewed studies on the environmental impacts of plant-based diets were searched in Ovid MEDLINE, EMBASE, and Web of Science. After removing duplicates, the screening identified 1553 records. After 2 stages of independent review by 2 reviewers, 65 records met the inclusion criteria and were eligible to be used in synthesis. RESULTS: Evidence suggests that plant-based diets may offer lower greenhouse gas emissions (GHGEs), land use, and biodiversity loss than offered by standard diets; however, the impact on water and energy use may depend on the types of plant-based foods consumed. Further, the studies were consistent in demonstrating that plant-based dietary patterns that reduce diet-related mortality also promote environmental sustainability. CONCLUSIONS: Overall, there was agreement across the studies regarding the impact of plant-based dietary patterns on GHGE, land used, and biodiversity loss despite varied plant-based diets assessed.

Cradle-to-Gate and Use-Phase Carbon Footprint of a Commercial Plug-in Hybrid Electric Vehicle Lithium-Ion Battery.

Increased use of vehicle electrification to reduce greenhouse gas (GHG) emissions has led to the need for an accurate and comprehensive assessment of the carbon footprint of traction batteries. Unfortunately, there are few lifecycle assessments (LCAs) of commercial lithium-ion batteries available in the literature, and those that are available focus on the cradle-to-gate stage, often with little or no consideration of the use phase. To address this shortfall, we report both cradle-to-gate and use-phase GHG emissions for the 2020 Model Year Ford Explorer plug-in hybrid electric vehicle (PHEV) NMC622 battery. Using primary industry data for battery design and manufacturing, cradle-to-gate emissions are estimated to be 1.38 t CO2e (101 kg CO2e/kWh), with 78% from materials and parts production and 22% from cell, module, and pack manufacturing. Using mass-induced energy consumptions of 0.6 and 1.6 kWh/(100 km 100 kg) for charge-depleting and -sustaining modes, respectively, the mass-induced use-phase emission of the battery is estimated to be 1.04 t CO2e. We show that battery emissions during the cradle-to-gate and use phases are comparable and that both phases need to be considered. A holistic and harmonized LCA approach that includes battery use is required to reduce carbon footprint uncertainties and guide future battery designs.

Energy Criticality Avoidance-Based Delay Minimization Ant Colony Algorithm for Task Assignment in Mobile-Server-Assisted Mobile Edge Computing.

Mobile edge computing has been an important computing paradigm for providing delay-sensitive and computation-intensive services to mobile users. In this paper, we study the problem of the joint optimization of task assignment and energy management in a mobile-server-assisted edge computing network, where mobile servers can provide assisted task offloading services on behalf of the fixed servers at the network edge. The design objective is to minimize the system delay. As far as we know, our paper presents the first work that improves the quality of service of the whole system from a long-term aspect by prolonging the operational time of assisted mobile servers. We formulate the system delay minimization problem as a mixed-integer programming (MIP) problem. Due to the NP-hardness of this problem, we propose a dynamic energy criticality avoidance-based delay minimization ant colony algorithm (EACO), which strives for a balance between delay minimization for offloaded tasks and operational time maximization for mobile servers. We present a detailed algorithm design and deduce its computational complexity. We conduct extensive simulations, and the results demonstrate the high performance of the proposed algorithm compared to the benchmark algorithms.

PM2.5 can help adjust building's energy consumption.

Long- or short-term exposure to air pollution would distort human's cognitive function which has aroused widespread concern in interdisciplinary fields. It furtherly seems rational to assume that air pollution may affect energy use in public buildings. However, the overlooks of the potential impacts of air pollution on energy use would result in substantially higher energy saving cost. By matching the real-time energy consumption of public buildings to indoor and outdoor PM2.5, we construct a panel containing 193,226 data items. Based on this, we conduct the first preliminary exploration to try to reveal the impact of PM2.5 on energy use at the building-hourly level. Results show that the increase of energy intensity caused by PM2.5 is subtle, it indeed exists significantly. When indoor PM2.5 is 1 µg/m3, the marginal effect is minimum. After indoor PM2.5 exceeding 1 µg/m3, the marginal effect began to increase and the maximum is 0.3224 when PM2.5 is 1114 µg/m3. However, given the sorting and contrast effect, the practical relationship between indoor PM2.5 and energy use is possible inverted-U shaped. Furtherly, we find long term exposure to outdoor PM2.5 would not make people adapt to air pollution and instead cumulative the impact on energy use. Besides, centralized office could be an economical and feasible measure to achieve energy saving goal. Finally, we propose that it is promising for achieving the synergy between air pollution control and energy consumption reduction.

Modeling the impact of innovation in marine energy generation-related technologies on carbon dioxide emissions in South Korea.

South Korea has invested extensively in developing revolutionary marine and ocean technologies to accomplish renewable energy goals. Despite that, the available literature offers no insight into the environmental benefits of innovation in marine energy generation, distribution, or transmission-related technologies (IMET). This study examines the nexus between carbon dioxide emissions (CO2e) and IMET in South Korea (1990Q1-2018Q4). Control variables include international collaboration in green technology development (ICGD), gross domestic product (per capita) (GDPPC), expansionary commercial policy (ECP), and renewable energy use (REC). First, the findings validated the long-run relationship among ICGD, GDPPC, ECP, REC, IMET, and CO2e. Second, the findings asserted that increasing IMET assisted in the generation of low-carbon renewable energy, thereby contributing to the improvement of environmental quality. Third, the estimates revealed that an increase in GDPPC and ECP was positively associated with an upsurge in CO2e. Fourth, the data depicted that ICGD facilitated co-green technologies development, which de-escalated CO2e. Fifth, REC was negatively associated with a decrease in CO2e. Based on current estimates, this article recommended that governments implement policies that encourage companies and academia to participate in IMET to promote the green economy.

From pollution to prosperity: Investigating the Environmental Kuznets curve and pollution-haven hypothesis in sub-Saharan Africa's industrial sector.

Drivers of environmental change and policy processes are pushing the sub-Saharan African region to do more in the struggle against climate change as the region suffers most from climate change impact. To this end, this study investigates how the interaction effects of a sustainable financing model in energy use influence carbon emissions in Sub-Saharan African economies. It is based on the theory that energy consumption is determined by increased economic financing. Panel data analysis of thirteen countries from 1995 to 2019 is used to explore the interaction effect on CO2 emissions, taking a market-induced energy demand perspective. The study employed the fully modified ordinary least squares technique, removing all heterogeneity effects in a panel estimation. The econometric model was estimated with (and without) the interaction effect. The study finds support for the Pollution-Haven hypothesis and the Environmental Kuznets "inverted U-shaped" Curve Hypothesis in the region. It identifies a long-run relationship between the financial sector, economic activity, and CO2 emissions, with fossil fuel consumption in industrial activities increasing CO2 emissions by about 2.5 times. However, the study also reveals that the interactive effect of financial development can significantly reduce CO2 emissions, providing important implications for policymakers in Africa. The study suggests regulatory incentives to encourage banking credit intermediation for environmentally friendly energy sources. This research makes a valuable contribution to understanding the environmental impact of the financial sector in sub-Saharan Africa, an area that has received limited empirical attention. The findings highlight the relevance of the financial sector for policy formulation in addressing environmental issues in the region.

Assessing the spillover effects of research and development and renewable energy on CO2 emissions: international evidence.

The primary motivation of this paper is the lack of consensus on the impact of renewable energy (RE) and research and development (R&D) expenditure on CO2 emissions in the literature. Current literature has mostly ignored the spillover effect of R&D on CO2 emissions by increasing the intensity effect of technology, leading to biased results. Further, little is known about the impact of previous epidemics on CO2 emissions. This study fills these gaps by evaluating the spillover effects of RE and R&D on CO2 emissions in a global panel of 54 countries from 2003 to 2017. Using a two-way time- and spatial-fixed-effects panel analysis, we find both income-induced and scale effects of economic growth are present in our panel, though the scale effect is the dominant one. Our findings indicate that economic growth increases CO2 emissions at a decreasing rate, validating the Environmental Kuznets Curve hypothesis, and that urbanization and foreign trade worsen the environment. We also find that epidemic episodes before COVID-19 had a nonsignificant impact on CO2 emissions internationally. More importantly, our results confirm the presence of both the intensity and scale effects of R&D, with the intensity effect being the dominant one. We find overwhelming evidence that global R&D investment led to an overall (direct plus spillover) reduction of CO2 emissions, driven by its spillover effect, through two channels: RE and economic growth. Finally, we find that RE installations assist with reducing CO2 emissions internationally, though RE composition and state of R&D can lead to different findings. Our findings have significant policy implications for sustainable development. Our RE and R&D-spillover results support the policy recommendation of shifting to high-tech clean energy sources.

Effects of meteorin-like hormone on endocrine function of hypothalamo-hypophysial system and peripheral uncoupling proteins in rats.

BACKGROUND: Meteorin-like hormone (Metrnl) is a peptide secreted from the adipose tissue and modulates the whole-body energy metabolism. Metrnl release into the circulation is influenced by obesity, cold exposure, and exercise. Thyroid hormones also exert many of their effects on metabolism through uncoupling proteins (UCPs). This study aimed to determine effect of Metrnl on hypothalamo-hypophysier-thyroid axis and energy metabolism and reveal the possible involvement of UCPs in this process. METHODS AND RESULTS: Fourty male Sprague-Dawley rats were divided into 4 groups with 10 animals in each group: control, sham, 10 and 100 nM Metrnl. Hypothalamus, muscle, white adipose tissue (WAT) and brown adipose tissue (BAT) samples were collected to detect thyrotropin-releasing hormone (TRH), and UCP1 and UCP3 protein levels by western blot analysis. Serum thyroid-stimulating hormone (TSH), triiodothyronine (T3) and thyroxine (T4) hormone levels were determined by enzyme-linked immunosorbent assay. Central infusion of Metrnl caused significant increase in serum TSH, T3 and T4 levels compared to control (p < 0.05). After Metrnl treatment, there were significant increases in TRH in hypothalamus tissue, UCP1 in WAT and BAT; and UCP3 protein in the muscle tissue (p < 0.05). CONCLUSIONS: The findings that Metrnl induced increases in the peripheral UCPs and hypothalamus-pituitary-thyroid axis hormones implicate a role for this hormone in body energy homeostasis through UCP-mediated mechanisms.

Field measurements of indoor and community air quality in rural Beijing before, during, and after the COVID-19 lockdown.

The coronavirus (COVID-19) lockdown in China is thought to have reduced air pollution emissions due to reduced human mobility and economic activities. Few studies have assessed the impacts of COVID-19 on community and indoor air quality in environments with diverse socioeconomic and household energy use patterns. The main goal of this study was to evaluate whether indoor and community air pollution differed before, during, and after the COVID-19 lockdown in homes with different energy use patterns. Using calibrated real-time PM2.5 sensors, we measured indoor and community air quality in 147 homes from 30 villages in Beijing over 4 months including periods before, during, and after the COVID-19 lockdown. Community pollution was higher during the lockdown (61 ± 47 µg/m3 ) compared with before (45 ± 35 µg/m3 , p < 0.001) and after (47 ± 37 µg/m3 , p < 0.001) the lockdown. However, we did not observe significantly increased indoor PM2.5 during the COVID-19 lockdown. Indoor-generated PM2.5 in homes using clean energy for heating without smokers was the lowest compared with those using solid fuel with/without smokers, implying air pollutant emissions are reduced in homes using clean energy. Indoor air quality may not have been impacted by the COVID-19 lockdown in rural settings in China and appeared to be more impacted by the household energy choice and indoor smoking than the COVID-19 lockdown. As clean energy transitions occurred in rural households in northern China, our work highlights the importance of understanding multiple possible indoor sources to interpret the impacts of interventions, intended or otherwise.

Emission reduction effects of vertical environmental regulation: Capacity transfer or energy intensity reduction? Evidence from a quasi-natural experiment in China.

There is insufficient research on how to reduce the destructive effects of command-based environmental regulation through institutional design. The implementation of the National Key Monitoring Enterprises provides new evidence to assess the effects of vertical monitoring. This study integrates and matches three types of micro databases in China: industrial, pollution, and patent, and constructs firm-level panel data from 2004 to 2010. The empirical evidence shows that the policy reduces the energy use intensity of monitored enterprises by about 10.4% and sulfur dioxide emission intensity by about 23.9%. The mechanism test shows that this effect is achieved by means of energy structure optimization, process innovation, and end-of-pipe treatment, but the effect on total factor productivity is not significant. Among them, the positive impact is stronger for high-profit and emerging firms. Further, we quantify the policy-induced capacity transfer and technology spillovers from monitored enterprises to non-monitored enterprises. In terms of scale, the policy leads to a simultaneous increase in output and pollution emissions of unmonitored firms in the same industry. However, in terms of efficiency, the policy reduces the energy use intensity and pollution emission intensity of enterprises in the same industry.

COVID-19 pandemic ramifications on residential Smart homes energy use load profiles.

The COVID-19 pandemic has significantly affected people's behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre- and post-COVID-19 pandemic times. The weekend usage patterns look similar pre- and post-COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems.

Electricity consumption variation of public buildings in response to COVID-19 restriction and easing policies: A case study in Scotland, U.K.

A growing number of studies have showed energy demand changes during COVID-19; this study aims to further disclose the impact of the restriction and easing policies on the energy consumption of public buildings where occupants' usage and activities are regulated in response to the pandemic. This study analyzes half-hourly electricity consumption data of 35 public buildings covering 6 building types in the Perth and Kinross Council area in Scotland, U.K., over the span of 2020 and 2021. The results show that the restriction has a greater impact on the electricity reduction in the first year of the pandemic than that in the second year. In response to the restriction, the electricity use intensity of all public buildings reduces significantly (p < 0.001) except office buildings with no significant reduction (p > 0.05); secondary schools have the highest electricity consumption reduction (275.04 kwh/day), while museums have the lowest reduction (58.62 kwh/day). In addition, the electricity consumption and electricity use intensity of museum, library and school buildings are inversely proportional to the restriction intensity, while this is opposite for office buildings. Combing restriction intensity and mobility data, this research reveals the different impacts of the restriction policies on the electricity consumption of public buildings during the pandemic, which reflects people's changing attitudes and behaviors towards COVID-19. The results provide a reference basis for energy management to develop more realistic energy demand policies based on public building types and to optimize the electricity supply load and energy profile during the COVID-19 pandemic.