Decrease In Energy Intensity Research Articles

Greener lightweight foam concrete using seaweed industrial by-product to replace natural sand with inorganic salt as a stabilizer

In recent years, the seaweed industry has expanded, resulting in higher volumes of seaweed industrial by-products (SWB). People commonly dispose SWB on land, which raises environmental concerns due to its hazardous chemical content. The use of waste materials as alternatives to natural sand has gained attention due to its potential to reduce environmental impact. Therefore, this study aimed to develop a greener lightweight foam concrete (LFC) by incorporating 0-30% SWB as a replacement for natural sand in fine aggregates and evaluate its performance. Furthermore, the study investigated the inclusion of inorganic salt concentrations ranging from 0 to 15% into the concrete mixture to improve performance. The production, sampling, and testing procedures followed the SNI 8640:2018 standards. Properties like density, water absorption, drying shrinkage, and compressive strength were analyzed for SWB percentage (0-30%), salt concentration (0-15%), foaming pressure (0.20, 0.39, and 0.59 MPa), and curing duration (7, 14, and 28 days). Viable specimens were further examined for microstructure, energy intensity, CO2 emission, and production cost. Specimen FS5 met standards with a density of 707.1 kg/m3, compressive strength of 2.12 MPa, water absorption of 25.45% (v/v), and drying shrinkage of 0.13%. The energy intensity, CO2 emission, and total cost of greener LFC were calculated to be 159.88 MJ/m3, 188.98 kg of CO2/m3, and IDR 682,130/m3, respectively. Ultimately, this work greatly contributes to the field of green manufacturing and environmental sustainability by successfully decreasing energy intensity, CO2 emissions, and environmental harm in LFC production processes.

Deciphering the complex interplay: Heterogeneous, threshold, and mediation effects of trade openness on CO2 emissions in Africa.

Despite having barely anything to do with the issue of CO2 emissions, Africa has been experiencing more severe climate change and its adverse effects than most other regions of the globe. However, the issue of CO2 emissions and its adverse effects has received relatively little attention in the African research arena. To this end, the present research assesses the effect of trade openness on the CO2 emissions utilizing panel data from 46 African countries spanning 2000 through 2022. To account for the possible heterogeneity and nonlinearity, the panel quantile regression and threshold methods were employed. Moreover, this study investigates the key mediating effects of the channel. The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. Besides the result from the double threshold model reveals a complex, nonlinear relationship between trade openness and CO2 emissions in Africa. Moreover, the findings divulge that openness to trade indirectly reduces CO2 emissions through the substitution and technology channels whereas it indirectly increases carbon dioxide production via the economic track. Therefore, it is vital to promote the use of renewable energy, effectively leverage the knowledge spillover effects of trade to decrease energy intensity and formulate pertinent policies aimed at curbing carbon emissions and addressing the imminent threat of climate change in Africa. Besides, the nonlinear and heterogeneous effects of trade openness on CO2 emissions suggest that policies and interventions related to the impact of trade openness on CO2 emissions should consider the current level of carbon dioxide emissions.

How does carbon emissions trading affect China’s energy intensity?

The carbon emissions trading policy should be an essential factor influencing the environment and the economy, and should have a crucial impact on energy intensity. This study analyzed data for 29 regions of China from 2005 to 2020, and applied the synthetic control method to assess the impact of carbon emissions trading on energy intensity. The results show that the carbon trading policy significantly reduced energy intensity in the pilot regions. Specifically, from 2013 to 2020, carbon emissions trading decreased energy intensity in Tianjin, Shanghai, Hubei, and Chongqing by 17.92%, 29.22%, 23.89%, and 16.33%. The results of the mechanism test show that carbon emissions trading reduce energy intensity through technology improvements and industrial structure upgrading.

Decomposition Analysis of CO2 Emissions in Greece from 1996 to 2020

To meet Greece’s commitments under the Kyoto Protocol (KP) and the UN Framework Convention on Climate Change (UNFCCC), it’s crucial to dissect the primary influencers of its greenhouse gas emissions. This study utilized the logarithmic mean Divisia index method in its additive form to delve into the main drivers behind carbon dioxide emissions in Greece from 1996 to 2020. The analysis revealed that the primary catalyst for the rise in CO2 emissions was the growth in GDP. Conversely, advancements in energy efficiency, as indicated by a decrease in energy intensity, played a significant role in reducing CO2 emissions. While population growth contributed to an increase in emissions, a decline in emissions intensity showcased a reduction in emissions per unit of output or consumption. The period from 1996 to 2020 witnessed a 38% change in emissions, demonstrating the effectiveness of Greece’s environmental policies. These findings highlight the pressing need for a sustained focus on enhancing renewable energy sources (RES) penetration and ensuring comprehensive attention across all sectors to further reduce emissions.

A review of evolving climate and energy economy trends to enhance the dynamic life cycle assessment of buildings

The changing global climate is impacting life cycle effects of all sectors, including the building sector. To effectively decrease the construction sector's 40 % share of global annual energy use and carbon emissions, it's crucial to integrate these changes into life cycle assessments (LCA) to inform current and future energy policies, since buildings have lifespans exceeding 100 years. Current research lacks methods and data to embed future weather and energy shifts into LCA. This paper quantifies these future changes and discusses their integration into building LCA. Using industry reports and scholarly articles, we calculated global energy trends and weather patterns for 2030, 2050, and 2080. The projected energy use changes across United States economic sectors were also analyzed. Projections indicate a 41–59 % decline in fossil fuel use by 2050, with renewable energy increasing from 11 % to 41 %. Concurrently, global temperatures may rise by 2–5 °C, signaling major weather shifts. These shifts will translate into an economy-wide energy intensity decrease, showing an expected drop of 8 %. A Dynamic LCA (DLCA) framework is also discussed to include these shifts into LCA, to help not only researchers and practitioners involved in the LCA of buildings but also energy policy makers in effectively mitigating climate change.

Near-, medium- and long-term impacts of climate change on the thermal energy consumption of buildings in Finland under RCP climate scenarios

The building sector is critical in climate change mitigation by reducing its energy consumption. At the same time, warming climate requires adaptation measures from buildings, making it necessary to study the future thermal energy demand of buildings. This paper studies the impact of climate change on the thermal energy demand of buildings in a heating dominated climate of Finland, under “representative concentration pathway” (RCP) climate scenarios in near- (2030), medium- (2050) and long-term (2080) horizon. Additionally, the impact of the thermal performance level of the buildings is investigated. The thermal energy demand calculation is based on overarching standards from the European “energy performance of buildings” directive. The weather scenarios present both typical and extreme weather years, applied through morphing and future weather data from the Finnish Meteorological Institute. The results show that annual thermal energy demand in Finland in 2080 can decrease up to 74.6kWh/m2. In addition, the decrease in heating demand will be higher than the increase in cooling demand. Cooling can become the dominant peak in long-term evaluations, especially in South Finland (Vantaa) with passive buildings under RCP8.5 climate scenario. Renovation is the most efficient action to decrease energy intensity, the earliest it is done the better.

Social and economic driving forces of recent CO2 emissions in three major BRICS economies

The study examines the driving factors of total energy-related and power-related (electricity-heat) CO2 emissions for China, India and Brazil, three BRICS countries with vital economic and demographic dynamics. The paper applies decoupling and decomposition analysis in order to investigate the influence of those factors that are prominent in the contemporary literature as well as factors reflecting important social and demographic dynamics which affect the ecological footprint of society. Household size and number of households are introduced into the relevant literature for the first time to reflect demographic factors with substantially different trends from population size, the predominant factor in the existing literature. This novelty together with the simultaneous application of decoupling and decomposition analysis adds importance to the findings of the study, which covers the period of 2000–2018. The results show that increasing income and population significantly enlarge the energy-related CO2 emissions. Household size, number of households and income effects are crucial in the increase of power-related CO2 emissions. The crucial factor for the decrease of energy-related CO2 emissions is the decreasing energy intensity, while for power-related CO2 emissions it is the emission factor effect reflecting the recent shift towards less carbon intensive energy types.

Opportunity or trap - the policy effect of China’s energy quota trading

ABSTRACT This paper assesses the policy effect of the energy quota trading (EQT) policy from the perspectives of energy consumption, economic growth, and energy intensity, based on the panel data of 30 provinces in China from 2006 to 2019. The energy intensity has been decomposed into technical effect and structural effect using the LMDI model. The triple difference method, the corresponding parallel dynamic trend test and the placebo test are employed in this study. The result suggests that the EQT policy is capable of suppressing the growth of energy consumption, and will not dampen economic growth. Moreover, the policy facilitates the decrease of energy intensity in China. The EQT policy has spurred energy technology innovation, improved energy efficiency, and exerted about innovative compensation effects. However, the initial allocation of energy quota is free, thus leading to the structural effect of enterprises converging to high-energy-consumption industries. Compared with the white certificate policy, the EQT policy has some defects in the regulatory mechanism and operating rules. It is imperative for the policymakers to formulate guiding policies when considering the policy shocks of the above low industrialization area on the rapidly developing country.

Economy of Scale of Energy Intensity in Aquifer Storage and Recovery (ASR)

More water utilities are adopting aquifer storage and recovery (ASR) to balance long-term water supply and demand. Due to large implementation and operation costs, ASR projects need to be optimized, particularly for energy use, which is a major operating expense. This study examines the relationships among energy use, recharge, and recovery at two ASR projects in the western United States. The major finding is an economy of scale for recovery processes, but not for gravity-fed recharge processes. The economy of scale found is as follows: the energy intensity recovered decreases with volume. This suggests it is more energy-efficient to recover large volumes of water in one interval instead of recovering smaller volumes at more frequent intervals. The H2Oaks recovery process experienced a 78% decrease in energy intensity from 0 to 50,000 m3 recovered, while the Sand Hollow site experienced a 43% decrease in energy intensity from 0 to 50,000 m3 recovered. Statistical analyses of the recovery process showed p values lower than 0.0001, R2 values between 0.43 and 0.57, and a RMSE value between 0.55 and 2.1, indicating the presence of a moderate correlation between energy and volume. This economy of scale has been observed in multiple instances in water and wastewater treatment. This finding not only has applications to ASR but also to all recovery or recharge wells, whether or not they are paired with each other. Furthermore, this study confirms the need for more reliable and accessible energy data to fully understand the implications of the energy–water nexus.

Coal efficiency, carbon reduction, and future policy perspective in Pakistan’s economic growth: a decomposition and decoupling approach

Pakistan is moving toward the large-scale use of coal. Coal plays a dominant role in Pakistan’s energy mix and is estimated to reach 30% by 2030. The purpose of this study is to analyze coal imports and indigenous reserves in relation to CO2 emissions. In particular, this study constructs the logarithmic mean Divisia index (LMDI) method to see the impact of the factors, decoupling index for the economic relationship, and pollution from coal-fired power plants from 1986 to 2019. The empirical results show that 1) coal consumption and imports are interrelated, while coal production has had the lowest production level since 1986; 2) the energy intensity impact plays a medium role in decreasing coal utilization, followed by the coal share effect; however, the aggregated impact accounts for 0.023% of the total coal use; 3) the economic and population activity effects progressively increase with coal consumption by 0.25% and 0.35%, respectively, with the annual average growth; 4) only “three” decoupling states were observed: expansive coupling, expansive negative decoupling, and weak decoupling. Expansive negative decoupling occurred due to high energy share and energy intensity. Expansive coupling occurred only in 2001 due to rapid growth in coal proportion and a sluggish decrease in energy intensity, and weak decoupling showed a decoupling association between economic growth and coal utilization; and 5) the various coal compositions, such as moisture, volatile matter, fixed carbon, ash, and sulfur, can be evaded by 1.82, 4.83, 5.16, 1.43, and 0.39 Mt currently. Finally, environmental analysis recognized that implementing clean coal technologies significantly saves fuel and, consequently, reduces emissions. This study also discusses further policies.

Drivers of global energy export dependency: A decomposition analysis

Exploring energy export dependency under the carbon neutrality target is crucial for energy security and low-carbon transition. Currently, few studies have examined drivers of energy export dependency; furthermore, most of them failed to capture the impact of technology on energy change and were unable to explain the causal factors of energy intensity decline. This study analyzed the trends and drivers of energy export dependency in 40 major countries from 2000 to 2019 through a decomposition approach, and explained the decline of energy intensity caused by technological progress. The empirical results indicate that energy prices and energy export importance are the key drivers of the increase in energy export dependency in OECD countries, while technological progress can effectively reduce the energy export dependency of non-OECD countries by decreasing energy intensity. In addition, OECD countries pay attention to capital-energy substitution capacity, while non-OECD countries attach importance to the improvement of technical efficiency. These findings provide a scientific reference for energy transition and sustainable development in various countries.

The Impact of Digital Business on Energy Efficiency in EU Countries

Digital business plays a crucial role in driving energy efficiency and sustainability by enabling innovative solutions such as smart grid technologies, data analytics for energy optimization, and remote monitoring and control systems. Through digitalization, businesses can streamline processes, minimize energy waste, and make informed decisions that lead to more efficient resource utilization and reduced environmental impact. This paper aims at analyzing the character of digital business’ impact on energy efficiency to outline the relevant instruments to unleash EU countries’ potential for attaining sustainable development. The study applies the panel-corrected standard errors technique to check the effect of digital business on energy efficiency for the EU countries in 2011–2020. The findings show that digital business has a significant negative effect on energy intensity, implying that increased digital business leads to decreased energy intensity. Additionally, digital business practices positively contribute to reducing CO2 emissions and promoting renewable energy, although the impact on final energy consumption varies across different indicators. The findings underscore the significance of integrating digital business practices to improve energy efficiency, lower energy intensity, and advance the adoption of renewable energy sources within the EU. Policymakers and businesses should prioritize the adoption of digital technologies and e-commerce strategies to facilitate sustainable energy transitions and accomplish environmental objectives.

Assessing the influence of energy transition on economic-social growth: the case of China.

In recent years, because of the one-sided interpretation of the nexus between the green & low-carbon energy transition and the high-quality economic-social growth, some over-idealized due-oriented judgments have led to failures in theories or deviations from practices. It is necessary and typical to select the panel data of 30 provinces in China from 2010 to 2020 to demonstrate that nexus, since China plays a different role in both climate change and global energy security. This paper defines and measures both the high-quality economic-social growth and the green & low-carbon energy transition efficiency. After analyzing the structure characteristics of energy transition, it also discusses the impact of the transition efficiency on the high-quality growth. The results indicate that the inflection point from quantitative to qualitative change in the regional high-quality growth has not yet arrived, while the developed regions and the developing regions are still grappling with pronounced problems of imbalance and insufficiency. As far as now, the energy transition efficiency in the energy resource centers is much higher than that in the energy load centers. The provinces with a characteristic of energy supply-demand equilibrium have seamlessly shifted from the Introduction stage of green & low-carbon development to the Growth stage. Both the decrease in energy intensity and the increase in renewable share are able to promote high-quality economic-social development obviously; however, the reduction of per capita carbon emission cannot yield the expected positive externality in a short run.

The Effect of Energy Consumption, Income, and Population Growth on CO2 Emissions: Evidence from NARDL and Machine Learning Models

With population and income growth, the need for energy has increased in developing and emerging economies, which has inevitably led to an increase in carbon dioxide emissions (CO2e). This paper investigates the impact of energy consumption on CO2e influenced by population growth, energy consumption per capita, and income. In particular, this paper investigates whether or not an increase in energy consumption, energy intensity, energy consumption per capita, population growth, and income impacts CO2e in China, India, and the USA. The study applied the non-linear Autoregressive distributed lag (NARDL) and machine learning techniques. We found a significant impact of energy consumption per capita on the CO2 emissions in China, India, and USA. Furthermore, the results revealed that, when income increased, CO2 emissions increased in India, but decreased in the USA. The results confirmed that population growth increases CO2 emissions only in India. The results revealed that a decrease in energy intensity significantly improves the environmental quality in China and India. Finally, we forecasted the CO2e trend from 2017 to 2025. The results revealed an upcoming increase in CO2e levels in China and India. Conversely, the forecasted results demonstrated a downward trend of CO2e emissions in the USA.

Does green manufacturing technology innovation decrease energy intensity for sustainable development?

Considering that the global manufacturing sector is partially to blame for climate change, and in light of the ongoing effort to achieve carbon neutrality, green manufacturing technology innovation seems to be the sure way to alleviate climate change and achieve sustainable development. By employing a cross-sectional autoregressive distributed lag (CS-ARDL) methodology to a panel dataset comprising 17 manufacturing sectors from 42 economies between 2000 and 2014, our study reveals the effect of green manufacturing technology innovation (GMTI) on energy intensity (EI). The findings show that: (1) GMTI decreased EI, and robustness tests indicate that the results are robust. (2) GMTI decreased EI in both the short- and long terms. Specifically, the long-term effect exceeds the short-term effect. (3) Heterogeneity analysis indicates that the effect of GMTI varies between regions. That is, GMTI decreased EI in developed economies in both the short and long term, while GMTI decreased EI only in the long term in developing economies. (4) Furthermore, the GMTI types showed that: (i) incremental GMTI had a more significant impact on EI in the short term compared to creative GMTI, whereas (ii) creative GMTI had more impact on EI in the long term than incremental GMTI. Consequently, relevant policy actions are proposed according to the results of our study to ensure that manufacturing sectors are progressing in the right direction to achieve sustainable economic development.

Decomposition effects of energy and co2 intensities in the Nigerian economy: A logarithmic mean weight divisia index (LMDI) analysis.

This paper investigates CO2 intensity changes from energy use in the Nigerian economy for a period of 39 years (1981-2019) using the Logarithmic Mean weight Divisia Index (LMDI). The respective contribution and the impacts of different factors such as activity effects, conversion efficiency, intensity of energy, fuel mix, among others on the aggregate carbon emission changes in the economy has been examined bearing in mind the poor electricity supply experienced over the years. The investigation was undertaken in four periods and the outcomes revealed that energy use and CO2 emission have increased to some extent. The analysis shows that carbon emissions decreased most between 1981 and 1989 as a result of a decrease in energy intensity and substitution/fuel mix changes. There was considerable increase in intensities from 1990 upwards, thereby neutralising the benefits experienced in the first period. Increased energy intensity, inadequate electricity supply as well as a switch over to high carbon-emitting fuels were principal factors that fuelled the increase. Given the trends in the decomposition, it is important to promote cleaner fuels and improve energy efficiency in order to decrease Nigeria’s energy intensity and carbon emissions overall contributions in the coming years.

‘Going global’ and pollution in home country: Evidence from Chinese industrial firms

AbstractThe relationship between international investment and the environment is always concerned around the world, but the literature mainly focuses on the impact of foreign direct investment (FDI) (especially from developed countries to developing countries). Currently, many developing countries have regarded outward foreign direct investment (OFDI) as a critical task of economic development and encourage firms to ‘Going global’. After OFDI, how do firms' pollution emissions change? In this study, we employ the data of Chinese industrial firms to empirically answer this question. In particular, we combine inverse probability weighted matching with a difference‐in‐difference approach to identify the causal effect of OFDI on firm‐level pollution emissions. Our result indicates that OFDI leads to the reduction in both emission intensity and emission levels. This pollution reduction is driven by improving abatement technology and decreasing energy intensity. It potentially implies that OFDI reduces pollution emissions mainly through the ‘reverse technology spillover’ effect rather than ‘pollution transfer’ effect. In addition, pollution reductions caused by OFDI are prominent for local production OFDI and resource exploitation OFDI, OFDI to high‐income countries as well as capital‐intensive industries. Overall, this study not only provides an initial evidence for the relationship between OFDI and the environment at the firm level but also provides enlightenments for international investment and sustainable development.

Mapping and Influencing the Mechanism of CO2 Emissions from Building Operations Integrated Multi-Source Remote Sensing Data

Urbanization has led to rapid growth in energy consumption and CO2 emissions in the building sector. Building operation emissions (BCEs) are a major part of emissions in the building life cycle. Existing studies have attempted to estimate fine-scale BCEs using remote sensing data. However, there is still a lack of research on estimating long-term BCEs by integrating multi-source remote sensing data and applications in different regions. We selected the Beijing–Tianjin–Hebei (BTH) urban agglomeration and the National Capital Region of Japan (NCRJ) as research areas for this study. We also built multiple linear regression (MLR) models between prefecture-level BCEs and multi-source remote sensing data. The prefecture-level BCEs were downscaled to grid scale at a 1 km2 resolution. The estimation results verify the method’s difference and accuracy at different development stages. The multi-scale BCEs showed a continuous growth trend in the BTH urban agglomeration and a significant downward trend in the NCRJ. The decrease in energy intensity and population density were the main factors contributing to the negative growth of BCEs, whereas GDP per capita and urban expansion significantly promoted it. Through our methods and analyses, we contribute to the study of estimating greenhouse gas emissions with remote sensing and exploring the environmental impact of urban growth.

Comprehensive assessment of energy supply-side and demand-side coordination on pathways to carbon neutrality of the Yangtze River Delta in China

The Yangtze River Delta region is one of the key areas of energy transition for China's carbon neutrality. The pathways to carbon neutrality are diverse in the regional level due to the different conditions on the energy supply and demand side. How to construct comprehensive assessment index system and evaluate regional pathways to carbon neutrality is an urgent problem to be solved. To fill this gap, this paper evaluates the carbon neutrality pathways of supply-side and demand-side coordination in the Yangtze River Delta region using the Low Emissions Analysis Platform with five scenarios (64 sub-scenarios): Business as usual, energy intensity decrease, energy structure reform, power supply technology innovation and policies mix. The simulation results indicate that: (1) 22 of the 64 sub-scenarios can achieve carbon neutrality by 2060. (2) In energy intensity decrease scenario, an annual 6% reduction in energy intensity could achieve carbon neutrality before 2060. (3) The policies mix scenario can lead to 21 sub-scenarios with pathways to achieve carbon neutrality when the average annual energy intensity decreases by 4% or more. Additionally, the end-use sectors electrification level should reach 64.19% at least by 2060. (4) There can be 14 sub-scenarios to achieve zero carbon emissions in the power plant sector, but annual energy intensity should be reduced by at least 4%. Applying Analytic Hierarchy Process analysis, the article evaluated the 22 sub-scenarios with the index of regional pathways to carbon neutrality. The result shows that the mixed policies of energy intensity reduction, energy structure reformation and power technology innovation can promote the coordination of supply-side and demand-side. This study can provide reference for policymakers to formulate effective policies to realize carbon neutrality.

The impact and transmission mechanism of green credit policy on energy efficiency: new evidence from China

Green credit policy is the primary means for financial institutions to fulfill their environmental responsibilities. It is an issue worthy of attention whether green credit policy can achieve the effect of energy conservation, efficiency improvement, pollution reduction, and carbon reduction. This study uses the difference-in-difference method to test the impact of green credit policy on energy efficiency. The results show that green credit policy led to a significant decrease in energy intensity of green credit-restricted sectors while impeding the advancement of green total factor energy efficiency. The heterogeneity results show that the energy efficiency of large-scale, light textile manufacturing, resource processing industries, and clean industries are more significantly affected. Green credit policy can achieve energy conservation and has a linkage effect on pollution and carbon reduction. Although the constraint effect of green credit policy has effectively suppressed energy intensity, it also leads some industries to face a vicious cycle of "enhanced financing constraints-weakened innovation impetus," which in turn makes it challenging to improve green total factor energy efficiency. The above findings confirm the effectiveness of green credit policy in energy conservation and emission reduction. Also, they indicate the necessity of further improvement of the green financial policy system.