Multidimensional Energy Research Articles

The Impact of Demographic Transition on Energy Poverty in China: Potential Challenges and Opportunities

Energy poverty is a serious concern and an influential global determinant of subjective well-being (SWB). This paper seeks to explore the impact of demographic transition on energy poverty. Data for the study was obtained through panel data from 30 provinces of China from 2010 to 2022. The old dependency ratio is selected to address the shift in the total population. The negative population growth is anticipated to increase further and may not be easy to reverse. Demographic shifts also cause the gap to widen and alter the patterns of energy consumption. The energy poverty concept is measured through a multidimensional energy poverty index (MEPI) established on five key indicators: electricity consumption, clean cooking fuel like natural gas, telecommunication, heating, and cooling appliances. A Generalized Method of Moments (GMM) estimation technique is used to analyze the impact of the old dependency ratio (ODR) on energy poverty and a fixed effects model is performed to confirm the stability of the results. The outcome reveals that ODR and the demographic transition strongly contribute to worsening energy poverty. Effective policy implications regarding regional disparities among the elderly can change these challenges into opportunities and enhance clean energy access and infrastructure development across all regions.

Do Social Assistance Programs Alleviate Rural Households’ Energy Poverty? Evidence from China’s Basic Medical Insurance Scheme

Government social assistance programs have significantly alleviated poverty. However, to our knowledge, few studies have analyzed their effectiveness in mitigating energy poverty. This paper applies the Multidimensional Energy Poverty Index (MEPI) to measure the extent of rural households’ energy poverty in China. Using a two-way fixed effects model and quantile regression analysis, this study explores the long-term impact of China’s basic medical insurance system on rural households’ energy poverty. The findings indicate that basic medical insurance significantly reduces rural households’ energy poverty, with heterogeneous effects observed across different levels of energy poverty, household incomes, population sizes, and age distributions of household members. Enhancing farmers’ health conditions and reducing medical expenditure are key mechanisms through which basic medical insurance alleviates rural households’ energy poverty. Overall, these findings underscore the crucial role of social assistance programs in enhancing the quality of life for rural residents and contributing to global sustainable poverty governance.

Correlating enzymatic reactivity for different substrates using transferable data-driven collective variables

Machine learning (ML) is transforming the investigation of complex biological processes. In enzymatic catalysis, one significant challenge is identifying the reactive conformations (RC) of the enzyme:substrate complex where the substrate assumes a precise arrangement in the active site necessary to initiate a reaction. Traditional methods are hindered by the complexity of the multidimensional free energy landscape involved in the transition from nonreactive to reactive conformations. Here, we applied ML techniques to address this challenge, focusing on human pancreatic α-amylase, a crucial enzyme in type-II diabetes treatment. Using ML-based collective variables (CVs), we correlated the probability of being in a RC with the experimental catalytic activity of several malto-oligosaccharide substrates. Our findings demonstrate a remarkable transferability of these CVs across various compounds, significantly streamlining the modeling process and reducing both computational demand and manual intervention in setting up simulations for new substrates. This approach not only advances our understanding of enzymatic processes but also holds substantial potential for accelerating drug discovery by enabling rapid and accurate evaluation of drug efficacy across different generations of inhibitors.

Socio-Economic Impacts of Energy Poverty on Households in Ikorodu Communities, Lagos State, Nigeria

The study investigated the Ikorodu community's energy poverty status by adopting the Multidimensional Energy Poverty Index to assess each sub-community, as it centers on energy poverty. The study used both quantitative and qualitative assessments of data obtained from primary and secondary sources. The primary data was sourced from a questionnaire administered to households while secondary data was sourced mostly from the National Bureau of Statistics’ Nigeria Living Standard Survey (NLSS) dataset. Additional secondary data was obtained from the Lagos State socio-economic data survey which included the Ikorodu subset. The result showed that about half (42%) of the community was energy-poor while more than half (58%) were energy-non-poor. The study revealed energy poverty has a huge impact on the economic development of the studied communities, as there was a positive and significant correlation between energy poverty and educational, health, and economic activities. More specifically, energy poverty reduces social inclusion, diminishes the education level of the residents of the communities, lessens the quality of life and healthcare, and discourages business activities and the establishment of new businesses in the area. Given these findings, the study emphasizes the need for government intervention and public awareness to increase access to electricity through renewable energy sources. Additionally, it recommends promoting- clean and cost-effective energy alternatives to address the pressing issue of energy poverty within the community.

Nuclear Quantum Effects in Quantum Mechanical/Molecular Mechanical Free Energy Simulations of Ribonucleotide Reductase.

The enzyme ribonucleotide reductase plays a critical role in DNA synthesis and repair. Its mechanism requires long-range radical transfer through a series of proton-coupled electron transfer (PCET) steps. Nuclear quantum effects such as zero-point energy, proton delocalization, and hydrogen tunneling are known to be important in PCET. We present a strategy for efficiently incorporating nuclear quantum effects into multidimensional free energy surfaces and real-time dynamical simulations for condensed-phase systems such as enzymes. This strategy is based on the nuclear-electronic orbital (NEO) method, which treats specified protons quantum mechanically on the same level as the electrons. NEO density functional theory (NEO-DFT) is combined with the quantum mechanical/molecular mechanical finite temperature string method with umbrella sampling via a simple reweighting procedure. Application of this strategy to PCET between two tyrosines, Y731 and Y730, in ribonucleotide reductase illustrates that nuclear quantum effects could either raise or lower the free energy barrier, leading to a range of possible kinetic isotope effects. Real-time time-dependent DFT (RT-NEO-TDDFT) simulations highlight nuclear-electronic quantum dynamics. These approaches enable the incorporation of nuclear quantum effects into a wide range of chemically and biologically important processes.

Multidimensional energy poverty and its effects on household consumption and savings: Evidence from Nepal

This study examines the impact of multidimensional energy poverty (MDEP) on household consumption and savings, with a focus on potential differences by the gender of the household head. Using data from the Household Risk and Vulnerability Survey (HRVS) 2016–2018, a three-year panel dataset from Nepal covering 6000 households, we apply pooled OLS, dynamic panel fixed effects (FE), panel instrumental variable (IV), and Lewbel's (Lewbel, 2012) 2SLS methods. Our findings reveal that MDEP significantly reduces both household consumption and savings, with more pronounced effects on savings. The corresponding coefficients range from −0.376 to −0.092 for consumption and from – 0.722 to −3.213 for savings, suggesting that fully transitioning out of MDEP could increase household savings by 72.2 %–321.3 %. The effects of MDEP are consistent across households, regardless of the gender of the household head. This study underscores the importance of addressing MDEP to enhance household welfare and recommends that policymakers focus on expanding reliable and affordable energy access as part of broader economic development strategies to improve overall living standards in developing countries.

Pobreza Energética en Chorrera Mirador: Implementación y Monitoreo de un Sistema Híbrido Solar-Eólico

This work studies energy poverty in the community of Chorrera Mirador, located in Chimborazo, Ecuador. Energy poverty, defined as the inability to cover basic energy needs such as heating, cooking, and refrigeration, affects rural areas of Latin America. In Ecuador, this problem is exacerbated in rural areas, where more than half of the population suffers from it. The article proposes a methodology to measure energy poverty using the multidimensional energy poverty index (MEPI), which evaluates multiple conditions associated with this problem in households. The results reveal moderate energy poverty in the community, which justifies the implementation of a hybrid solar and wind renewable energy system (SHER) to mitigate it. The SHER was sized based on the daily energy demand and the solar and wind resources available in the area. A data collection system is included to monitor the voltage stability and power production of the system. The results demonstrate the functionality of the system and its ability to satisfy the energy demand of the community. The study concludes that the implementation of the SHER, together with the use of low-consumption lighting elements, contributes to mitigating energy poverty in the Chorrera Mirador community, improving the quality of life of its inhabitants. In addition, the data collection system allows for long-term analysis, which makes it easier to identify possible improvements and strategies to optimize its operation

Assessing energy vulnerability in Colombia using a multidimensional index

Energy vulnerability studies are conducted to identify and address the multidimensional causes of energy problems of a territory. Colombia faces substantial energy challenges, including sustained excess demand, slow supply expansion, rising tariffs, flow intermittency and power instability. It is a tropical developing country undergoing an energy transition and characterized by significant cultural, geographical, and demographic diversity. This article assesses the energy vulnerability of Colombia's 32 departments and its capital district through a Multidimensional Energy Vulnerability Index (MEVI). The MEVI is a measure ranging from 0 to 1 that evaluates energy vulnerability through 12 indicators across four dimensions: social, environmental, technical, and economic. To construct the index, a multivariate analysis using Cronbach's Alpha was conducted, and the min-max normalization method was employed. Additionally, a specific weighting system of the dimensions accompanied by an additive aggregation function was utilized to synthesize the various indicators into a unified index. Furthermore, a sensitivity analysis was performed to assess the robustness of the index, incorporating variations in key inputs such as the weighting scheme and data processing methods. The mean energy vulnerability score was 0.6, indicating that the departments of Colombia do not have extreme energy vulnerability. The territories with the highest energy vulnerability include the Departments of Vaupés, Guainía, Vichada, and Amazonas. In these cases, effective government policy is necessary to provide more energy security, which requires improvements across nearly all indicators involved in the calculation of the index. A discussion on the policies that could be implemented is presented in the document.

How do multidimensional energy justices work?: Specifying the role of anthropocentric and ecological justice in the acceptance of solar energy.

This study analyzed the acceptance of solar energy in terms of energy justice. The critical issue of energy supply, demand, and transition is a process of social redistribution of risks from old to new energy systems. The question of the appropriate distribution of risks for the energy system is closely related to energy justice. Previous studies are limited in empirically testing whether or not energy justice can contribute to the acceptance of new energy system. In addition, previous studies have heavily depended on energy justice in terms of anthropocentric type. Anthropocentric definitions of energy justice have focused primarily on the benefits and costs allocated only to humans. Such an anthropocentric view of justice lacks consideration of the value of various ecological beings. Therefore, this study aims to shed light on the role of not only four anthropocentric types of energy justices but also on for four ecological ones in the acceptance of solar energy. The analysis reveals that recognitive justice, generational justice, deep ecological justice, social ecological justice, and distributional justice positively influence the acceptance of solar energy, whereas procedural justice, restorative justice, and eco-socialist justice have no effect on it. In particular, this study found that recognitive justice moderates the effect of personal norms on acceptance of solar energy, whereas restorative justice moderates the effect of knowledge on it.

A Mode Evolution Metric to Extract Reaction Coordinates for Biomolecular Conformational Transitions.

The complex, multidimensional energy landscape of biomolecules makes the extraction of suitable, nonintuitive collective variables (CVs) that describe their conformational transitions challenging. At present, dimensionality reduction approaches and machine learning (ML) schemes are employed to obtain CVs from molecular dynamics (MD)/Monte Carlo (MC) trajectories or structural databanks for biomolecules. However, minimum sampling conditions to generate reliable CVs that accurately describe the underlying energy landscape remain unclear. Here, we address this issue by developing a Mode evolution Metric (MeM) to extract CVs that can pinpoint new states and describe local transitions in the vicinity of a reference minimum from nonequilibrated MD/MC trajectories. We present a general mathematical formulation of MeM for both statistical dimensionality reduction and machine learning approaches. Application of MeM to MC trajectories of model potential energy landscapes and MD trajectories of solvated alanine dipeptide reveals that the principal components which locate new states in the vicinity of a reference minimum emerge well before the trajectories locally equilibrate between the associated states. Finally, we demonstrate a possible application of MeM in designing efficient biased sampling schemes to construct accurate energy landscape slices that link transitions between states. MeM can help speed up the search for new minima around a biomolecular conformational state and enable the accurate estimation of thermodynamics for states lying on the energy landscape and the description of associated transitions.

Enhancement of carbonation, water purification and CO2 self-sequestration in hydrophobic piezo-photocatalytic carbonation coating for concrete

A eco-friendly carbonation coating (HBCC) with a piezo-photocatalysis was developed using gamma-dicalcium silicate and hydrophobic BiOI/BaTiO3 (HB), aiming at purifying pollutants by multi-dimensional energy (mechanical energy and visible light) and self-sequestrating CO2 produced by degrading pollutants. Based on the self-floating effect induced by the hydrophobicity of HB, the increase of catalyst content on the surface of HBCC was studied to promote the formation of a hydrophilic-hydrophobic interface. The selective adsorption of CO2 and H2O molecules by the hydrophilic-hydrophobic interface of HBCC was confirmed by simulations and experiments, which accelerates carbonation. Also, carbonation degree (37.1 %), bonding strength (40.1 %), and anti-corrosion performance (15.4 %) enhanced induced by accelerating carbonation was further confirmed. Additionally, HBBC exhibits the prominent degradation effect of Rhodamine b (90.8 %), methylene blue (86.6 %), and sulfamethoxazole (74.7 %) under ultrasound and visible light within 60 min. Meanwhile, CO2 emitted by piezo-photocatalytic degradation pollutants can be efficient sequestration by HBCC itself, and the carbonation can be enhanced to further improve its bonding strength. Finally, the enhancement mechanism of carbonation, water purification, and CO2 self-sequestration of HBBC was explored and ascertained.

Household Energy Poverty in the Context of Socioeconomic Status and Area of Residence: A Comparison of Central and Southern Punjab

Researchers have increasingly focused on the impact of energy poverty across various sectors of the economy. This paper aims to identify the determinants of household energy poverty in Central and Southern Punjab, Pakistan, utilizing the Pakistan Demographic and Health Survey Data from 2017-18. The analysis employs descriptive statistics and binary logistic regression to assess the influence of various socioeconomic and demographic factors on multidimensional energy poverty. The survey results indicate a disparity between the two regions, with just over 50 percent of respondents reporting energy poverty. The education level of the household head, wealth status, and place of residence are critical factors influencing multidimensional energy poverty. The findings highlight the substantial influence of socioeconomic factors on household energy poverty and underscore the necessity for effective policies to address these challenges.

Climate shocks, adaptive mechanisms and household energy transition in Uganda

Nearly 41% of the global populace depends on unclean fuels for cooking. As a result, about 4 million premature deaths connected to household air pollution are registered annually. Worryingly, over 2.1 billion people are estimated to continue using unclean fuels by 2030 if no strong policy actions are taken to alter the status quo. Climate parameters including; temperature, solar radiation, wind, and moisture have been widely touted as having an impact on multidimensional energy poverty, their effect on household energy consumption and subsequent transition to cleaner fuels is seldom investigated in Uganda. The purpose of this study is to investigate the effect of climate shocks, and adaptation mechanisms on household energy transition in Uganda. The study adopted a panel data methodology employing an ordered logit model with random effects to estimate the effect of climate shocks and adaptation mechanisms on household fuel transition from high to low-pollutant cooking fuels in Uganda. The findings revealed that climate shocks, adaptation mechanisms significantly affect household energy transition in Uganda. The study recommended that policies aimed at enhancing detection and report of early warning signs should be emphasized. Furthermore, investing in an insurance scheme especially for people living in climate shock prone areas can help households to cope up with shocks are eventually transition to clean cooking fuels.

Energy poverty and health in Turkey: Evidence from Longitudinal data

This study critically examines the effect of energy poverty on health in Turkey between 2018 and 2021 using the Income and Living Conditions Survey Longitudinal Micro Data Set. It considers the multidimensional structure of household energy poverty and its individual effects on health, resulting in several significant findings. Firstly, the multidimensional energy poverty index at the household level is obtained as a continuous variable using principal component analysis, considering subjective and objective indicators of energy poverty. Secondly, the impact of energy poverty on health at the individual level and the effect of several socioeconomic variables, including unobserved heterogeneity, are estimated with the random effects ordered logit model. Finally, commonly used measures of energy poverty in the literature and their health impacts are compared. The robustness analysis results show that the model's goodness of fit is highest when the multidimensional energy poverty index is constructed using principal component analysis. In addition, the analysis results show that unobserved heterogeneity across individuals significantly impacts health. These results indicate that decentralized policies should be implemented to increase policy effectiveness in combating energy poverty.

Energy Poverty and Women’s Economic Well-Being in Global South: Evidence from Burkina Faso

Although the relationship between household access to energy and economic well-being has received increasing attention in recent years, studies of this link have generally focused on unidimensional measures of fuel poverty. What is the link between multidimensional energy poverty and women’s economic well-being? Using data from the Continuous Multisectoral Survey on Household Living Conditions, this paper focuses on quantifying energy poverty and its effect on the economic well-being of households, particularly women, in Burkina Faso within a multidimensional framework. The results indicate that 84% of households are in a situation of multidimensional energy poverty. These energy-poor households are deprived, on average in 67.01% of the indicators. The results of the econometric estimations show that an increase in multidimensional energy deprivation is associated with a decrease in women’s economic well-being. Given that energy poverty reduces women’s economic well-being, they should be given priority in the implementation of energy policies.

Energy poverty and fertility intentions: An empirical analysis from household multidimensional perspectives

Fertility intentions determine fertility behaviors, and the decline in fertility intentions in China has directly led to a significant reduction in fertility rates in recent years. An analysis of the factors influencing fertility intentions can help China find solutions to increase fertility levels and reverse the decline. Using data from the 2015 Chinese General Social Survey, this study conducted Poisson regression analyses to investigate the relationship between energy poverty and fertility intentions from the perspective of energy poverty, and found that fertility intentions show a significant inverted U-shaped trend with the increase of multidimensional energy poverty. There is also significant cultural, urban‒rural and educational heterogeneity in the effect of energy poverty on fertility intentions. Multidimensional energy poverty acts on fertility intentions through three pathways: cultural effects, economic effects and health effects; therefore, at the policy level, fertility intentions can be increased by promoting some favorable traditional culture, increasing energy subsidies, and providing health check-ups for poverty-stricken families.

Energy deprivation to financial prosperity: Unveiling multidimensional energy Poverty's influence

The purpose of this research is to assess how energy poverty affects an individual's social wellbeing and financial constraints. The present research examines the effects of energy deprivation on a family's well-being, educational attainment, and economic advancement using survey data from PSLM (Pakistan Social and Living Standard Measurement). The investigation's empirical findings imply that a household's needs for energy are directly correlated with the fuel type they use and how little or expensively they rely on renewable energy. The consequent implications of energy dependence on family prosperity are significant. Energy-poor households have been shown to be more prone to experience respiratory illnesses, pay more for health care, drop out of school, and have less employment opportunities.

Multidimensional energy poverty in Colombia: A department-level review from 2018 to 2022

This article aims to measure energy poverty in Colombia in its thirty-two departments and its capital city from 2018 to 2022, using a composite approach. To achieve this, a Multidimensional Energy Poverty Index (MEPI) was designed, according to the methodology proposed by Nussbaumer et al. (2012; 2013) [1,2]. Twenty-eight variables were used, which were distributed across seven dimensions, and recorded by the National Quality of Life Survey (ECV, Spanish acronym), administered by the National Administrative Department of Statistics (DANE) of Colombia. In addition, a nested weighting method was used to assign weights within the index. Subjective weights were given to the dimensions, and an entropy method was used for each of the component variables. The results show that energy poverty has an increasing trend in Colombia throughout the period, especially in the municipal capitals. There are significant differences between urban and rural areas in all territories, and the departments located in the most remote areas of the country have a higher energy poverty. This is consistent with the low population density, as well as with off-grid areas. The results obtained will allow decision makers to conduct a preliminary evaluation of the management and effects of the specific public policy programs and plans that have been implemented in the different territories of the country.

Foreign direct investment, Green Technological Innovation and Energy Poverty: Empirical evidences from Sub-Saharan African countries

This study investigates the unconditional and conditional effects of Foreign Direct Investment (FDI) and Green Technology Innovation (GTI) on Energy Poverty (EP) in 11 Sub-Saharan African (SSA) countries from 2000 to 2020. Given that EP captures the share of the population without access to energy, it includes electricity, clean fuel and technology for cooking (CFTP), renewable energy consumption (RECP), and the multidimensional energy poverty index (MEPI) which is computed using the PCA method. Furthermore, this study considere the overall, urban and rural supsamples, and the data from the World Bank and OECD databases. This study employs the FGLS and the Driscoll- Kraay approaches. The findings reveal that FDI and GTI negatively affect both electricity poverty and CFT poverty, whereas these effects are significantly positives for both REC poverty and MEPI. This means that, in the long term, FDI and GTI allow the alleviation of both electricity and CFT poverty; conversely, FDI and GTI strengthen renewable energy and MEPI irrespectively of the residential area. However, FDI-EP nexus is significanty affected through GTI development. Moreover, FDI and GTI contribute to strengthening the rural-urban poverty gap in access to both electricity and CFT. In light of these findings, policy implications are presented.

Digital financial inclusion and household energy poverty: Evidence from China

This paper examines the impact of digital financial inclusion (DFI) on household energy poverty. We develop a simple theoretical model to explain the energy poverty alleviation effect of DFI. Using multidimensional household energy consumption survey data, we find that DFI reduces the incidence of household energy poverty by about 33.5 % and the intensity of energy poverty by 24.6 %, driven mainly by improvements in energy efficiency and an increase in household off-farm work, resulting in a stronger role in rural and low-income groups. However, the threshold model demonstrates that the Internet and digital tools are a prerequisite for this pro-poor energy effect to be realized. Notably, DFI, while exhibiting spatial spillover effects, exacerbate energy poverty in neighboring areas due to the siphoning effect.