Sector CO2 Emissions Research Articles

Reviewing of the net-zero energy buildings and housings in Japan

Abstract The buildings and construction sectors play a pivotal role in combating climate change. Globally, they account for 30% of the final energy consumption and 27% of total energy sector CO2 emissions. Buildings currently consume up to 40% of the world’s total energy, and it is projected to increase to 50% by 2030. The world faces a significant challenge in addressing these issues related to global energy production. From the Paris Agreement in 2015 to the United Nations Climate Change Conference in Glasgow (COP26),Japan has committed to developing and implementing robust greenhouse gas (GHG) emission reduction measures using its resources. They have declared their intention to achieve carbon neutrality by 2050, improving the energy efficiency of structures. This involves measures such as regulating electricity usage, imposing restrictions on design specifications concerning the built environment and raw materials and promoting the use of sustainable energy sources to minimize the environmental impact of buildings. These efforts have given rise to the concept of net-zero energy buildings (ZEB) and net-zero energy housing (ZEH). This paper aims to provide a comprehensive review of ZEB/ZEH in a general context and to assess its feasibility and practicality within the specific context of Japan.

Time and frequency-based effect of energy-related R&D investments on power sector CO2 emissions: evidence from leading R&D investing countries by WLMC approach

Time and frequency-based effect of energy-related R&D investments on power sector CO2 emissions: evidence from leading R&D investing countries by WLMC approach

Restructuring effects of industrial and energy structures on sectoral CO2 emission peak trajectories in China

Economic sectors are pivotal in achieving China's dual carbon goals; nevertheless, the combined impact of industrial and energy consumption structures on sectors' peak pathways remains unresolved. We extend the optimization of separate industrial and energy structures to a multi-objective dynamic input-output optimization model. Findings indicate the following. (1) China's energy-related CO2 emissions are projected to peak in 2028, reaching a volume of 10.06-10.25 Gt. The contribution of industrial structure upgrading to this peak is three times greater than that of energy structure transformation. (2) Approximately 40% of sectors can delay their peaks until after 2030 without impeding China's overall peaking before 2030. (3) Compared with the single objective of minimizing CO2 emissions, China can not only achieve its carbon peak earlier but also enhance its average annual gross domestic product (GDP) growth rates by more than 0.26 percentage points and increase the non-fossil energy use's share by at least 2.78%.

Advancing cost-optimal residential decarbonisation pathways: An examination of heat pumps and thermal efficiency

In Ireland, residential energy policy has been influenced by thermal inefficiency, high electricity prices and energy poverty. These factors have driven the fabric-first approach, where buildings must undergo extensive thermal retrofitting to qualify for heat pump subsidies. The cost-effectiveness of this approach has not been properly scrutinised to date. This paper addresses this knowledge gap by exploring the cost-effectiveness of the fabric-first approach and other decarbonisation strategies for the residential sector and broader energy system. The study develops scenarios by modifying the Heat Loss Indicator (HLI) threshold, which evaluates the fabric and ventilation heat loss per unit of floor area and is used to determine heat pump subsidy eligibility. The paper also considers scenarios that permit installing sub-optimal performing heat pumps that do not achieve peak performance levels in dwellings with higher HLIs. The analysis uses the TIMES-Ireland Model (TIM), a model of the whole energy system that reflects the interdependence of mitigation pathways across different energy sectors. Our study shows that Ireland's fabric-first approach requires 22 times more thermal retrofits to meet climate targets than alternative pathways. The alternative pathways based on the latest heat pump performance data are more cost-effective, showing that higher heat pump HLI thresholds can reduce the average sectoral marginal CO2 emission price by 60% compared to the current fabric-first approach. The cost savings indicate that shifting to an HLI threshold of 2.3 W/K/m2 is close to optimal, while cost savings are minimal when moving from an HLI of 2.3 to 3 W/K/m2. Furthermore, electricity prices and household awareness are essential to the cost-optimal transition to residential heat pumps.

Impacts of forest plantation programs on sectoral CO2 emissions regionally in New Zealand

Investing in projects that support environmental benefits, such as tree harvesting, has the potential to reduce air pollution levels in the atmosphere in the future. However, this kind of investment may increase the current level of emissions. Therefore, it is necessary to estimate how much the policy affects the current level of CO2 emissions. This makes sure the policy doesn’t increase the level of CO2 emissions. This study aims to analyze the effect of the One Billion Trees program on CO2 emissions in New Zealand by employing the 2020 input–output table analysis. This investigation examines the direct and indirect effects of policy on both the demand and supply sides across six regions of New Zealand. The results of this study for the first year of plantation suggest that the policy increases the level of CO2 emissions in all regions, especially in the Waikato region. The direct and indirect impact of the policy leads to 64 kt of CO2 emissions on the demand side and 270 kt of CO2 emissions on the supply side. These lead to 0.19 and 0.74% of total CO2 emissions being attributed to investment shocks. Continuing the policy is recommended, as it has a low effect on CO2 emissions. However, it is crucial to prioritize the use of low-carbon machinery that uses fossil fuels during the plantation process.

Navigating sustainability in the US: A comprehensive analysis of green energy, eco-innovation, and economic policy uncertainty on sectoral CO2 emissions

The United States is the world's second-largest polluter, generating 4.7 billion metric tons of CO2 in 2020. To combat it, the US is targeting a precise goal of 50–52 percent decrease in net CO2 emissions from 2005 levels by 2030. Hence, it is vital to determine the critical factors contributing to Sustainable Development Goals (SDGs). With this motivation, this study examines dynamic link between green energy transition, eco-innovation, economic policy uncertainty, energy use, economic growth, and sectoral CO2 emissions (SCO2) in the United States from 1980 to 2020 by using novel Quantile-On-Quantile Regression (QQR) and Granger causality in quantile approaches. The results show that the quantiles of the green energy transition are positively related to all SCO2 quantiles. While eco-innovation and SCO2 are marginally favorable in the lower to higher quantiles, positive slope coefficients showcase the effect of economic policy uncertainty on SCO2 in the 0.2–0.95 quantiles. Similarly, SCO2 and the energy use showed positive and negative results across quantiles, whereas QQR slope coefficients between SCO2 and economic growth are positive and negative throughout the quantiles. Suggests that investment in green energy and eco-innovation also reduces economic policy uncertainty by delivering energy for all sectors is vital if SDG-7 is executed by 2030.

Indonesia's contribution to global carbon flows: Which sectors are most responsible for the emissions embodied in trade?

Motivated by recent developments in global carbon policies, such as the carbon border adjustment mechanism (CBAM) in Europe and carbon pricing in Indonesia, this paper elaborates on CO2 emissions embodied in products entering and leaving Indonesia and identifies carbon-intensive sectors responsible for carbon leakage. This was performed by using global multi-regional input-output analysis and consumption-based accounting (CBA) - production-based accounting (PBA) ratio. In 2016, the annual CO2 emissions embodied in Indonesia's exports and imports were 114 and 95 Mt. CO2, respectively. Considering final demand only, these values reduce to 32 and 22 Mt. CO2 or 0.9 and 0.6 % of total CO2 emissions in global trade, respectively. The electrical and machinery sector makes up the most CO2 emissions in Indonesian exports. In terms of per USD, metal products and petroleum, chemical and non-metallic mineral products are among the most carbon-intensive sectors, thus likely to be affected by the CBAM policy. Furthermore, Indonesia's emissions under CBA were slightly lower than PBA, indicating that minor carbon leakage occurred in 2016, but this is subject to uncertainty. Assessing the relative CO2 emissions of various economic sectors is suitable for manufacturing goods whose processes are typically dominated by fossil combustion. However, this is not the case for the agriculture sector as its carbon footprint values are underestimated due to the exclusion of land use, land use change, and forestry emissions. Overall, our findings can serve as a baseline to further explore how a transition towards a low-carbon economy in Indonesia could improve global-trade carbon balances.

An innovative data-feature-driven approach for CO2 emission predictive analytics: A perspective from seasonality and nonlinearity characteristics

This study enhances data support for CO2 emission reduction strategies across the U.S., targeting the commercial, industrial, residential, and electric power sectors. Despite the availability of numerous predictive models for sector-specific CO2 emission forecasts, a gap remains for a versatile model adept at managing time series data with varied characteristics. We introduce a novel, highly generalizable forecasting model that merges Conformable Fractional Accumulation, seasonal dummy variables, and the time power item to address randomness, seasonality, and nonlinearity in predictions. Our model outshines prevailing competitors, including statistical (AR and ARIMA), machine learning (LSTM, BPNN, and GRU), and grey models (SGM (1,1) and GM (1,1)), in comparative tests. It achieves MAPE values below 5% and 10% for training and testing phases, respectively, across all sectors, surpassing the inconsistent results from benchmark models. Furthermore, the stability and reliability of our model are validated through a systematic robustness verification framework. Notably, leveraging this model's superior predictive performance, we forecast future sectoral CO2 emissions. A detailed analysis of sector-specific influencing factors provides actionable insights for crafting targeted decarbonization policies and plans.

Financial regulations and sustainability: The role of energy price and climate policy uncertainty

Russia ranks among the top five countries worldwide in terms of carbon emissions, with the energy, transportation, and manufacturing sectors as the major contributors. This poses a significant threat to both current and future generations. Russia faces challenges in achieving Sustainable Development Goal 13, necessitating the implementation of more innovative policies to promote environmental sustainability. Considering this alarming situation, this study investigates the role of financial regulations, energy price uncertainty, and climate policy uncertainty in reshaping sectoral CO2 emissions in Russia. This study utilizes a time-varying bootstrap rolling-window causality (BRW) approach using quarterly data from 1990 to 2021. The stability test for parameters indicates instability, suggesting that the full sample causality test may yield incorrect inferences. Thus, the BRW approach is employed for valid inferences. Our findings confirm the time-varying negative impact of financial regulations on CO2 emissions from energy, manufacturing, and transportation sectors. Additionally, findings confirm time-varying positive impact of energy prices and climate policy uncertainty on CO2 emissions from the energy, manufacturing, and transportation sectors. Strong financial regulations and stable energy and climate policies are crucial for achieving sustainability, highlighting significant policy implications for policymakers and stakeholders.

Role of energy transition in easing energy security risk and decreasing CO2 emissions: Disaggregated level evidence from the USA by quantile-based models

Consistent with the increasing environmental interest, the clean energy transition is highly critical to achieving decarbonization targets. Also, energy security has become an important topic under the shadow of the energy crisis,. Accordingly, countries have been trying to stimulate clean energy use to preserve the environment and ensure energy security. So, considering the leading role of economic size and volume of energy use, the study examines the USA to define whether energy transition helps decrease energy security risk (ESR) and curb CO2 emissions. So, the study applies a disaggregated level analysis by performing quantile-based models for the period from 2001/Q1 through 2022/Q4. The results demonstrate that (i) the energy transition index decreases environmental ESR at higher quantiles and reliability ESR at lower and middle quantiles, whereas it is not beneficial in declining economic and geopolitical ESR; (ii) energy transition curbs CO2 emissions in building and transport sectors at lower quantiles, whereas it does not help decrease CO2 emissions in industrial and power sectors; (iii) energy transition is mostly ineffective on ESR, whereas it is highly effective in curbing CO2 emissions in all sectors except for transport across various quantiles as time passes; (iv) the results differ according to the aggregated and disaggregated levels; (v) the results are consistent across main and alternative models. Hence, the study highlights the dominant effect of energy transition in curbing sectoral CO2 emissions rather than easing ESR. Accordingly, the study discusses various policy implications for the USA.

Marginal effect of electricity generation on CO2 emissions: Disaggregated level evidence from China by KRLS method and high-frequency daily data

The effect of energy use on carbon dioxide (CO2) emissions has been frequently studied in the literature. These studies have mainly concluded that countries should decline (increase) the use of fossil fuel (clean) energy. However, the literature suffers from a significant shortcoming as it does not focus on the marginal effect of a 1 % increase for each energy generation source on sectoral CO2 emissions. Therefore, a detailed analysis is conducted in this study to examine the relationship between electricity generation (EG) and CO2 emissions at a disaggregated level. The focus is on China, the world's leading country in terms of CO2 emissions and energy use. Thus, the study considers source-based EG and sector-based CO2 emissions, uses high-frequency daily data between January 1, 2019, and December 31, 2022, and applies the kernel-based regularized least squares (KRLS) method. The outcomes show that (i) the effects of EG sources on sectoral CO2 emissions follow a nonlinear structure, suggesting that the marginal effect varies by sector, EG sources, and estimation models (either incremental or degressive). Therefore, there are certain externalities among alternative EG sources for the effects of CO2 emissions in the sectors; (ii) the statistically significant effects of EG sources on CO2 emissions vary by sector and constructed models, showing that some EG sources are much more important for CO2 emissions in some sectors. For this reason, not all EG sources have the same importance for sectoral CO2 emissions; (iii) the KRLS method has a higher estimation ability of CO2 emissions, reaching ∼99.8 %, which provides novel outcomes and allows researchers to argue various policy options based on the obtained results. The study thus highlights varying marginal impacts of EG sources on sectoral CO2 emissions. The changing marginal influence is a crucial point that should be considered by Chinese policymakers when formulating energy-related environmental policies.

An Asymmetric Approach to Evaluate Sectoral CO2 Emissions in Turkey

The increase in population and economic growth are significant factors that contribute to the deterioration of the environment, primarily through the emission of carbon pollutants. Therefore, the overuse of natural resources, degradation of natural ecosystems, and the increasing release of harmful gases poses a threat to our ability to protect the environment for future generations. Although there is a global agreement on the need for clean and carbon-free energy systems to achieve sustainable development, emerging countries persist in giving more priority to economic objectives rather than environmental preservation. The objective of this research was to explore strategies to mitigate sector-specific emissions and environmental deterioration in Turkey, where the enforcement of environmental regulations has proven to be inadequate. The connections between emissions from different sectors, the value contributed to the economy, the income per person, and the growth of human capital were examined in the research. The study's findings indicated that implementing policies to increase production and develop human capital are effective in the short term for reducing carbon emissions in the services sector. Over time, policies that priorities raising income levels and building up human capital have been proven to be successful. Analyses of strategies to reduce agricultural emissions reveal that implementing short-term investments in human capital and long-term revenue increases are successful policies to reduce emission levels in the industry. Regarding the industry, past levels of emissions in the immediate future exert a constraint on managing the present period's emission levels. Given the asymmetrical impacts, it is evident that people whose quality of life improves through investments in human capital are more likely to prioritize environmental sustainability and adopt practices that reduce emissions in production. Thus, it is evident that the enhancement of human capital may serve as a significant policy tool across all industries.

Dynamic effect of disaggregated level electricity generation on residential carbon emissions: Daily inference from the largest EU economies

This study examines the dynamic effects of electricity generation (EG) on CO2 emissions from the residential sector. The study focuses on the EU-4 countries (Germany, Spain, France, and Italy), considers residential CO2 emissions as the dependent variable, and includes disaggregated level fossil and renewable EG as explanatory variables. In this context, the study runs nonlinear quantile-on-quantile (QQ) regression and Granger causality in quantiles (GQ) as the main models with daily data from January 2, 2019, to March 10, 2023, while quantile regression (QR) is used for robustness check. The findings present that in terms of CO2 emissions: (i) EG from coal, natural gas, and oil has a stimulating effect at higher quantiles in all countries; (ii) EG from hydro has an increasing effect at higher quantiles, while it has a decreasing effect at lower and middle quantiles in all countries except France; (iii) EG from solar has a dampening effect at higher quantiles in all countries except France; (iv) EG from wind has a declining effect at higher quantiles in both Spain and France; (v) both fossil and renewable energy EG have a causal effect on residential sector CO2 emissions at the disaggregated level except at some quantiles. Overall, the effect size and the causal effect of EG on CO2 emissions change for quantiles, countries, and EG sources. Therefore, the study proposes to rely on the specific EG sources for Germany and Italy (solar energy), Spain, and France (wind energy) to mitigate climate change by reducing residential CO2 emissions.

Role of Environmental Policy Stringency on Sectoral CO2 Emissions in EU-5 Countries: Disaggregated Level Evidence by Novel Quantile-Based Approaches

Consistent with the increasing awareness of environmental problems, countries have applied various measures to combat climate change by preventing environmental degradation of the environment. In this context, a set of measures in different areas and sectors have been taken. Although it is possible to consider each of them, instead, using a more comprehensive index, such as the Environmental Policy Stringency Index, can be appropriate in examining the effects of environmental measures in curbing emissions. Accordingly, this research examines the effect of Environmental Policy Stringency Index on sectoral carbon dioxide (CO2) emissions in the European Union Five countries (namely, Germany, Spain, France, United Kingdom, and Italy) by using data for the period 1990/Q2-2020/Q4, performing novel quantile-based approaches. The outcomes show that at higher quantiles, Environmental Policy Stringency Index provides (a) a decrease in building sector CO2 emissions in France, the United Kingdom, and Italy; (b) a decline in industrial combustion sector CO2 emissions in France and Italy; (c) a curb power sector CO2 emissions in Germany, Spain, and France; (d) a decrease in transport sector CO2 emission in Germany and France; (e) there are causalities from Environmental Policy Stringency Index to sectoral CO2 emissions across quantiles except for some ones; (f) the outcomes are verified as robust. The outcomes prove the differentiating effects of Environmental Policy Stringency Index across sectors under the empirical examinations, quantiles, and countries. Thus, the study discusses various policy endeavors, such as consideration of the varying structure of environmental measures, application of nonlinear approaches, and focusing on some sectors to go fast in curbing sectoral CO2 emissions.

Convergence of sectoral CO2 emissions across Australian states and territories

ABSTRACT We examine convergence in sectoral CO2 emissions across Australian states and territories. We apply the Phillips-Sul club convergence methodology to investigate club convergence for nine sectors across eight Australian regions over the period 1990–2017. Our results indicate multiple convergence clubs for the total of all sectors and the eight sectors under investigation. However, we find no evidence of full club convergence in any one sector highlighting that Australian states and territories converge to multiple equilibria depending on the sector under investigation. These results lend support to the need for tailored policies unique to a particular cluster of regions that will target the reduction of CO2 emissions in specific sectors.

How are electricity generation effective on carbon neutrality in the global south? Evidence from sectoral CO2 emissions by daily data

In light of the efforts to ensure carbon neutrality by combating climate-related problems, the study investigates the effectiveness of electricity generation (EG) from the main renewable sources (hydro-HEG, solar-SEG, and wind-WEG). In this context, the study examines the countries of the Global South (i.e., Brazil, China, and India), considers EG at a disaggregated level and sectoral CO2 emissions, applies nonlinear methods, and uses daily data between January 2, 2019 and December 31, 2022. The results demonstrate that (i) disaggregated EG sources have a stronger (weaker) time and frequency dependency on sectoral CO2 emissions in China (Brazil and India); (ii) HEG has a stimulating impact on sectoral CO2 emissions in all countries; (iii) SEG has an increasing impact on sectoral CO2 emissions in Brazil and China, while it provides a decrease in sectoral CO2 emissions in India; (iv) WEG upsurges sectoral CO2 emissions in China, while it achieves a CO2 reduction in Brazil and India; (v) disaggregated level EG has a causal impact on sectoral CO2 emissions across all quantiles except some lower, middle, and higher quantiles. The study adds scientific value to existing knowledge by analyzing for the first time which EG sources are effective in reducing daily CO2 emissions in the Global South. Based on the outcomes, the study demonstrates that WEG is the best EG source for Brazil, that SEG and WEG are optimal EG sources for India, and that China cannot benefit from the EG sources considered. In this way, the study provides fresh insights for the countries of the Global South and underlines the crucial role of renewable EG in ensuring carbon neutrality.

Exploring the relationship between economic diversification and energy-related CO2 emissions in a petroleum-producing country

Purpose This study aims to quantify sectoral energy and carbon intensity, revisit the validity of the Environmental Kuznets Curve (EKC) and explore the relationship between economic diversification and CO2 emissions in Bahrain. Design/methodology/approach Three stages were followed to understand the linkages between sectoral economic growth, energy consumption and CO2 emissions in Bahrain. Sectoral energy and carbon intensity were calculated, time series data trends were analyzed and two econometric models were built and analyzed using the autoregressive distributed lag method and time series data for the period 1980–2019. Findings The results of the analysis suggest that energy and carbon intensity in Bahrain’s industrial sector is higher than those of its services and agricultural sectors. The EKC was found to be invalid for Bahrain, where economic growth is still coupled with CO2 emissions. Whereas CO2 emissions have increased with growth in the manufacturing, and real estate subsectors, the emissions have decreased with growth in the hospitability, transportation and communications subsectors. These results indicate that economic diversification, specifically of the services sector, is aligned with Bahrain’s carbon neutrality target. However, less energy-intensive industries, such as recycling-based industries, are needed to counter the environmental impacts of economic growth. Originality/value The impacts of economic diversification on energy consumption and CO2 emissions in the Gulf Cooperation Council petroleum countries have rarely been explored. Findings from this study contribute to informing economic and environment-related policymaking in Bahrain.

Reducing transport sector CO2 emissions patterns: Environmental technologies and renewable energy

The research explores the impact of environmental technologies and renewable energy on carbon dioxide (CO2) emissions from the EU transportation sector (2007–2020). Utilizing panel corrected standard error and feasible generalized least squares methods, the study uncovers key drivers influencing declining CO2 emissions. The results reveal a significant and variable effect of environmental technologies and renewable energy on CO2 emissions in the EU transport sector, emphasizing the positive correlation between increased renewable energy adoption and emission reduction. This underscores the necessity for heightened EU investment in sustainable transport infrastructure and clean energy solutions, encompassing initiatives like electric vehicles, hydrogen fuel cells, and biofuels. The study further recommends promoting renewable energy sources for transport systems, aligning with the broader goals of the European Green Deal and the EU Climate Law. Additionally, the research provides essential insights into policy implications, emphasizing a multifaceted approach including comprehensive strategies for cleaner transportation, innovation, and education to accelerate the transition towards sustainable practices in the EU.

Forecasting the energy demand and CO2 emissions of industrial sectors in China's Beijing-Tianjin-Hebei region under energy transition.

As the world's greatest energy consumer, China's energy consumption and transition have become a focus of attention. The most significant location for regional integration in the north of China is the Beijing-Tianjin-Hebei region, where the industrial sector dominates its energy consumption. Forecasting the energy demand and structure of industrial sectors in China's Beijing-Tianjin-Hebei region may help to promote the energy transition and CO2 emission mitigation. This study conducts a model based on the year 2020 using the Long-Range Energy Alternatives Planning System (LEAP) software and sets two scenarios (baseline scenario and emission peak scenario) to forecast the future energy demand and CO2 emissions of industrial sectors in China's Beijing-Tianjin-Hebei region until the year 2035. Moreover, the industrial sectors are classified into traditional high-energy-consuming industries, emerging manufacturing industries, daily-related light industries, and other industries. The forecasting results show that (1) The industrial energy demand of the entire Beijing-Tianjin-Hebei region will grow from 234 Mtce in 2020 to 317 Mtce in 2035, and the corresponding energy structure will shift from coal-based to electricity-based; (2) at the provincial level, all three provinces will experience an increase in industrial energy demand between 2020 and 2035, with Hebei experiencing the fastest average annual growth rate of 2.18% and the largest share of over 80%, and Beijing experiencing the highest average annual electrification rate of 70%; (3) at the industrial sector level, the electricity and natural gas will gradually replace other energy sources as the main energy source for industry. The most representative industrial sub-sector in Beijing, Tianjin, and Hebei provinces are all traditional high-energy-consuming industries, which will account for more than 90% of the total energy demand in both Tianjin and Hebei by 2035.

The Function of Geopolitical Risk on Carbon Neutrality Under the Shadow of Russia-Ukraine Conflict: Evidence from Russia's Sectoral CO2 Emissions by High-Frequency Data and Quantile-Based Methods

The Function of Geopolitical Risk on Carbon Neutrality Under the Shadow of Russia-Ukraine Conflict: Evidence from Russia's Sectoral CO2 Emissions by High-Frequency Data and Quantile-Based Methods