An estimation of energy and GHG emission intensity caused by energy consumption in Korea: An energy IO approach

The paper examines the energy transition using Poland as a case study. The model was estimated based on annual data for Poland for the period of 1990–2024 (n = 35). The estimation was carried out using the OLS method with HAC correction, and the statistical significance of parameters was assessed using statistical tests. Based on econometric analysis, the impact was examined throughout the entire research period, with additional analysis of the structural break dummy for 2015. It was verified whether this impact had changed since 2015 compared to the earlier period. The data were used to calculate indicators, arranged in three groups: (1) capacity availability indicators (for the availability of the overall power system and for the renewable energy sources (RES)); (2) indicator of emission intensity (the indicator was defined as the ratio of total greenhouse gases emission to real GDP); (3) indicator of the economy’s energy intensity (the indicator was defined as primary energy consumption per unit of GDP). Annual summaries of these indicators constituted the input data for econometric modelling. The aim of the empirical analysis was to deepen the identification of mechanisms shaping greenhouse gas emission intensity by incorporating into the model indicators of generation capacity availability and measures of the economy’s energy intensity. The data collection based on constructed greenhouse gas emission intensity and energy intensity indicators of the economy enables the analysis of the increase in emission intensity regardless of the scale of the economy, in the system of power availability for the entire energy system, as well as for renewable energy sources. This approach makes it possible to move away from the analysis of absolute volumes toward a structural perspective that better reflects the real production capabilities of the power system as well as the efficiency of energy use in the economy. The results indicate that economic energy intensity is the dominant determinant of greenhouse gas emission intensity in Poland during the research period. The econometric analysis estimates show a positive and statistically significant relationship between energy intensity and emissions intensity, whereas generation capacity availability indicators—both for the total power system and for renewable energy sources—do not exhibit statistically significant effects. However, it was found that this impact was not constant throughout the entire period (β is 0.455 for pre-2015 and 0.325 for post-2015). Sensitivity analysis based on point elasticities reveals that a 1% increase in energy intensity of GDP leads to an increase in greenhouse gas emission intensity (by approximately 1.18% pre-2015 and 0.85% post-2015), whereas analogous changes in total capacity availability and RES availability are associated with substantially smaller effects (0.10% and 0.20%, respectively). These findings suggest that improvements in economy-wide energy efficiency played a more decisive role in reducing emissions intensity than short-term variations in generation capacity availability.

This research aims to evaluate the relationship between greenhouse gas emissions and economic growth [measured by GDP (gross domestics product) and GDP per capital] in Vietnam. The authors used the data compiled from the WB (word bank) database and time series estimation method. The results from models show that the factors affecting the intensity of CO2 emissions in Vietnam are statistically significant, at 1%, 5% and 10%, with the impact level of emission intensity (with a lag of 2 ) at -0.48; economic growth rate at 29180.49 (with a lag of 1); and the square of economic growth rate at - 14588.66 (with a lag of 1), with the model's explanatory level of 56.54%. In addition, the coefficient of the quadratic function is negative, illustrated by a downward curve in the graph representing the relationship between economic growth and emissions, reflecting correctly the environmental Kuznet curve. At the same time, the figures of Granger Causality Tests reveal that there is a causal relationship between the economic growth rate and the intensity of CO2 greenhouse gas emissions in Vietnam during the research period, with a significance level of 5. %. Economic growth exacerbates the intensity of greenhouse gas (CO2) emissions, and this increase has a return effect on growth (positive effect). However, with the square of economic growth rate doubling, this relationship will tend to be negative. On the basis of the analysis results, the study also proposes some policy implications which reduce the intensity of greenhouse gas emissions and aim to promote green growth in Vietnam: (1) reducing emission sources in economic fields: industry, agriculture, services; (2) reducing the use of fossil energy which should be replaced by Renewable energy (energy from wind and solar); (3) applying modern science and technology in production and economic activities; (4) completing the legal framework to encourage economic sectors and businesses to use natural resources effectively; (5) The Government should enact policies to encourage all economic sectors to apply modern technology in production.

Adjusting transportation structure to reduce the intensity of greenhouse gas emissions is an effective way to address climate change issues. This paper selects six transport sectors and constructs a hybrid input-output model to study the impact of transportation restructuring on the intensity of CO2 and non-CO2 greenhouse gas emissions in each sector during different periods. The results show that the effect of transportation restructuring on greenhouse gas emissions is manifested differently in different time periods. After 2008, transportation restructuring had a significant effect on reducing the intensity of greenhouse gas emissions in all sectors. However, the impact of transportation restructuring on the intensity of non-CO2 greenhouse gas emissions is limited. It is also found that the railway transport sector has been a low-impact transport sector in terms of greenhouse gas emissions since 2004, which provides insights for the optimization of China’s transportation structure.

Environmental pollution and climate change have become nontraditional global security threats. As China's economy grows, the country faces an increasing number of challenges associated with improving atmospheric quality and reducing greenhouse gas emissions. Based on China's dynamic noncompetitive input-output tables and data on energy consumption and emissions from 1994 to 2016, a hybrid input-output model is constructed to identify high-energy-consuming sectors and to quantify the impact of industrial restructuring on the intensity of air pollutant and greenhouse gas emissions from these sectors. The empirical results indicate that the impact of industrial restructuring on the intensity of air pollutant and greenhouse gas emissions from high-energy-consuming sectors was nonlinear and has undergone a "promotion reduction" shift. This study also found that the impact of industrial restructuring is more significant on the intensity of greenhouse gas emissions than on the intensity of air pollutant emissions; furthermore, the reduction in greenhouse gas emission intensity achieved by industrial restructuring after 2008 began to show results. Based on the findings of this study, we make recommendations such as the need for the Chinese government to continue to promote supply-side structural reforms in the energy sector.

Low-carbon production of iron and steel: Technology options, economic assessment, and policy

The environmental sustainability of food production systems, including net greenhouse gas (GHG) emissions, is of increasing importance. In Norwegian pork production, animal performance is high in terms of reproduction, growth, and health. The development and use of an IPCC methodology-based model for estimating GHG emissions from pork production could be helpful in identifying the effects of progress in genetics and management. The objective was to investigate whether an IPCC methodology-based model was able to reflect the effects of the progress in genetics and management in pork production on the GHG emissions per kg carcass weight (CW). It is hypothesized that this progress has led to low GHG emissions intensities in Norwegian pork compared to global levels and that expected improvements will give a lasting reduction in GHG emissions intensities. A model ‘HolosNorPork’ for estimating net farm gate GHG emissions intensities was developed, including allocation procedures, at the pig production unit level. The model was run with pig production data from in average 632 farms from 2014 to 2019. The estimates include emissions of enteric and manure storage methane, manure storage nitrous oxide emissions, as well as GHG emissions from production and transportation of purchased feeds, and direct and indirect GHG emissions caused by energy use in pig-barns. The model was able to estimate the effects on net GHG emissions intensities from pork production on the basis of production characteristics. The estimated net GHG emissions intensity was found to have decreased from on average 2.49 to 2.34 kg CO2 eq. kg−1 CW over the investigated period. For 2019 the net GHG emission for the one-third lower performing farms was estimated to 2.56 kg CO2 eq. kg−1 CW, whereas for the one-third medium and one-third best performing farms the estimates were 2.36 and 2.16 kg CO2 eq. kg−1 CW, respectively. The net GHG emissions intensity for pork carcasses from boars was estimated to be 2.07 kg CO2 eq. kg−1 CW. For the health regimes investigated, Conventional and Specific-Pathogen Free (SPF), the estimated GHG emissions intensities for 2019 were 2.37 and 2.24 kg CO2 eq. kg−1 CW, respectively. The effects on net GHG emissions intensities of breeding and management measures were estimated to be profound, and this progress in pig production systems contributes to an on-going strengthening of pork as a sustainable source for human food supply.

Life-cycle analysis on energy consumption and GHG emission intensities of alternative vehicle fuels in China

This article explores therelationship among farm‐level productivity growth, scale, and greenhouse gas (GHG) emission intensity during a time period of significant agricultural policy change affecting Ireland's dairy industry. Specifically, we focus on the 2015 EU milk quota abolition, which initiated major dairy expansion in Ireland. We use a representative sample of Irish dairy farms from 2000 to 2017, that includes data on farm specific GHG emissions. Based on this detailed farm level panel data set, we estimate productivity with a control function approach. We then apply fixed effects and dynamic panel data methods to explore the implications of productivity and scale on GHG emission intensity. Our findings indicate that increased productivity is negatively associated with GHG emission intensity, which changes with distinct milk quota abolition phases. Overall, our findings are important for understanding the relationship between policy reforms and GHG emissions in agriculture, and how to improve agricultural mitigation strategies.

Disputes around trade inequality have been growing over the last 2 decades, with different countries claiming inequality in different terms including monetary deficits, resource appropriation and degradation, and environmental emission transfer. Despite prior input-output-based studies analyzing multidimensional trade consequences at the sector level, there is a lack of bottom-up studies that uncover the complexity of trade imbalances at the product level. This paper quantifies four types of flows, monetary, resource, embodied energy use, and embodied greenhouse gas (GHG) emissions, resulting from aluminum trade for the four economies with the highest aluminum trade, that is, the United States, China, Japan, and Australia. Results show that the United States has a negative balance in monetary flows but a positive balance in resource flows, embodied energy use, and GHG emissions. China has a positive balance in monetary and resource flows but a negative balance in embodied energy use and GHG emissions. Japan has a positive balance in all flows, while Australia has a negative balance in all flows. These heterogeneous gains and losses along the global leaders of aluminum trade arise largely from their different trade structures and the heterogeneities of price, energy use, and GHG emission intensities of aluminum products; for example, Japan mainly imports unwrought aluminum, and its quantity is 3 times that of the exported semis and finished aluminum-containing products that have similar energy and GHG emission intensities but 20 times higher prices, while Australia mainly exports bauxite and alumina that have the lowest prices, the quantity of which is 25 times that of imported semis and finished products. This study suggests that resource-related trade inequalities are not uniform across economic and environmental impacts and that trade policies must be carefully considered from various dimensions.

Statistical analysis of greenhouse gas emissions of South Korean residential buildings

Supply chain optimization of sugarcane first generation and eucalyptus second generation ethanol production in Brazil

Life-cycle fossil energy consumption and greenhouse gas emission intensity of dominant secondary energy pathways of China in 2010

A whole farm systems analysis of greenhouse gas emissions of 60 Tasmanian dairy farms

The agricultural sector is currently confronted with the challenge to reduce greenhouse gas (GHG) emissions, whilst maintaining or increasing production. Energy‐saving technologies are often proposed as a partial solution, but the evidence on their ability to reduce GHG emissions remains mixed. Production economics provides methodological tools to analyse the nexus of agricultural production, energy use and GHG emissions. Convexity is predominantly maintained in agricultural production economics, despite various theoretical and empirical reasons to question it. Employing non‐convex and convex frontier frameworks, this contribution evaluates energy productivity change (the ratio of aggregate output change to energy use change) and GHG emission intensity change (the ratio of GHG emission change to polluting input change) using Hicks‐Moorsteen productivity formulations. We consider GHG emissions as by‐products of the production process by using a multi‐equation model. Given our empirical specification, non‐convex and convex Hicks‐Moorsteen indices can coincide under certain circumstances, which leads to a series of theoretical equivalence results. The empirical application focuses on 1,510 observations of Dutch dairy farms for the period of 2010–2019. The results show a positive association between energy productivity change and GHG emission intensity change, which calls into question the potential of on‐farm, energy‐efficiency‐increasing measures to reduce GHG emission intensity.

Greenhouse gas emissions and production cost footprints in Australian gold mines