Changes In Carbon Dioxide Emissions Research Articles

Methodology for selecting assessment periods of Logarithmic Mean Divisia Index decomposition techniques

Logarithmic Mean Divisia Index Decomposition Analysis (IDA-LMDI) is a widely used statistical technique in the engineering, economics, energy, and environmental sciences. The main application of the IDA-LMDI method is to identify the drivers that explain the change in carbon dioxide emissions of a country or region over a given time span. Therefore, proper selection of each time period is fundamental to ensure that its implemented accurately and meaningful results are obtained. In the literature, decomposition periods have been defined based on a single-, n-, or one-year period. However, in all these cases, the duration of each period was fixed and depended on arbitrary criteria. The adoption of fixed periods did not capture specific changing trends in the time series under analysis. Therefore, this study presents a new methodology for defining the number of periods and their extent to obtain unbiased drivers using the IDA-LMDI technique. The period selection was defined according to the mean square error of all feasible combinations. We illustrated the application of this method in two cases. First, an illustrative example was successfully validated using multivariate linear regression. Second, we obtained the Kaya factors of the Organisation for Economic Co-operation and Development countries of Europe. The results were compared with the decomposition results provided by the International Energy Agency on 10–7 year fixed periods. The results showed that the application of fixed periods in IDA-LMDI dismissed critical drivers that could only be captured with the proper selection of each period under analysis. Therefore, the proposed methodology will aid in accurate information analysis and decision making in energy policy and other applications. The proposed method has a broad application and could be applied to any decomposition method in the Divisia family.

The Impacts Of COVID-19 Pandemic on Greenhouse Gas Emissions and Climate Change

The outbreak of COVID-19 in 2020 has brought enormous damage to human life and health and socioeconomic development. Yet, the influence of COVID-19 outbreak on the environment within the context of global warming has not been fully understood. Detailed and accurate explanation for the relationship between COVID-19 and economy, carbon emissions, and methane emissions remains a challenge. This study aims to highlight the significant impact of the COVID-19 pandemic on greenhouse gas emissions and climate change through a systematic literature review and comprehensive analysis of data from the U.S., China, Canada, and 27 European countries. To clarify the impact of COVID-19 on climate, the study outlines changes in carbon dioxide emissions by comparing data from pre-pandemic, during-pandemic, and post-pandemic (projected) scenarios. The correlation among carbon dioxide, temperature, GDP, and Population in countries is further examined with different levels of development using Pearson's Linear Correlation analysis and significance test. This study will potentially provide insights into future preparation and management of the impact of global emergency disaster emergencies.

Impact of land consolidation on agricultural decarbonization: Estimation of changes in carbon dioxide emissions due to farm transport

Areas used for agriculture are a large source of carbon emissions, but there is great potential for reducing them. Land consolidation, through the comprehensive reorganization of the spatial arrangement of farms, can reduce emissions as a result of reducing fuel consumption. The subjects of this study are the veracity of this statement and the scope of variation in the potential reduction of carbon emissions. The analysis covered six land consolidation projects in Poland and Turkey, for several agricultural models that differ in the level of fuel consumption.Changes in agricultural road layout resulting from the implementation of land consolidation projects and changes in the number of farm plots and their spatial distribution were considered. The study considered several different levels and structures of fuel consumption on farms. The applied methodology is based on analysis of changes in distance to fields resulting from land consolidation projects, which are then expressed as changes in fuel consumption.The obtained emission reduction results for the studied land consolidation projects were diverse and range from 0.3 to 170 kg CO2/ha/year. The reduction in fuel consumption on farms at the level of individual villages reached a maximum of 32 %, while the average value of this reduction in the entire surveyed set was 12.5 %.The proposed approach increases the accuracy of existing methods for estimating the long-term balance of carbon emissions and carbon accumulation related to the implementation of land consolidation projects. The observed emission reduction values can be considered a significant economic and ecological effect because the effects of these projects persist for at least several decades.

Investigation of the intensity of carbon dioxide emissions by steppe soil when introducing fallow lands into circulation

The paper reflects the results of studying the temporal variability of carbon dioxide fluxes by the soils of deposits when they are introduced into agricultural circulation. The purpose of the research is to study the change in carbon dioxide emissions by the soils of fallow lands in the conditions of the steppe of Western Siberia. In 2022, research was conducted in the Omsk Region at key sites. The soils of the site are solodic, malodorous medium low-sodium columnar heavy loamy meadow-chernozem; cortical columnar heavy loamy saline meadow-chernozem, fine-grained low-humus heavy loamy meadow malt. Seasonal changes in carbon dioxide fluxes by soils on deposits when introduced into circulation using agrotechnical technology are significant (Figure 2) with a maximum in July (67.7 g CO2/m2/day) and a minimum in September (16.7 g CO2/m2/day); on deposits with combined technology, respectively, 54.4 and 14.1 g CO2/m2/day. Agrotechnical technology contributed to a greater emission of carbon dioxide from the soils of the deposit than combined. The system of agrotechnical techniques when introducing fallow soils into agricultural circulation has a significant impact on the release of carbon dioxide by the soil surface. Of the soil level of the deposit without treatment, it was 162% with agrotechnical technology (tillage), and with combined (tillage + herbicide application) 133%.

Global and regional changes in carbon dioxide emissions: 1970–2019

We introduce new frameworks to study spatio-temporal patterns in carbon dioxide emissions, demographic trends and economic patterns across 50 countries over the past 50 years. Our analysis is broken up into four sections. First, we introduce a new method to classify countries into one of three characteristic emissions classes based on a one, two or three-segment piecewise linear model. We reveal that most countries are best represented by a piecewise linear model with one change point. Next, we perform a decade-by-decade study of carbon dioxide trajectories. There, we demonstrate notable changes in cluster structures in each decade. We then study the spatial propagation of emissions over time, highlighting a peak in spatial dispersion in 2000, beyond which there has been a gradual decline in spatial emissions variance over space. Finally, we use carbon dioxide, GDP, and population data and apply dimensionality reduction and clustering to group countries based on similarity in their real and carbon economies.

The Impact of Energy Tax on Carbon Emission Mitigation: An Integrated Analysis Using CGE and SDA

By originally integrating the structural decomposition analysis (SDA) into a computable general equilibrium (CGE) model, this paper simulates and analyzes the impact and mechanism of energy taxes on carbon emissions. Changes in carbon dioxide emissions, energy consumption structure, and other macroeconomic variables are investigated under different pre-set scenarios. The conclusion shows that the imposition of an ad valorem energy tax will indeed impact the production and consumption of enterprises. A higher tax rate leads to more pronounced reductions in carbon dioxide emissions. The carbon intensity effect is the dominant factor driving national carbon emissions and carbon emission intensity decline. Although the production structure effect and final demand effect play a role, their influences are relatively weak. While levying energy taxes, subsidies for personal income tax or corporate production tax can achieve double dividends. The progress of energy utilization technology is capable of increasing unit energy output and easing the negative impact of energy tax collection, and the gross national product may rise rather than fall. Under this circumstance, the production structure effect will play a greater role because the total demand coefficients of various industries for energy industry products will further decline. Only by levying energy taxes on coal and oil, exempting energy taxes on natural gas, or using energy tax revenue to subsidize investment in the natural gas industry can the government optimize the energy consumption structure. Subsidies will boost final demand for the natural gas mining and processing industry and increase the consumption share of natural gas, a cleaner energy source than coal and oil, which is critical in the current energy transition process.

Change in Carbon Dioxide Emissions in Japan:The Synthetic Control Method

Change in Carbon Dioxide Emissions in Japan:The Synthetic Control Method

Drivers of the change in carbon dioxide emissions under the progress of urbanization in 30 provinces in China: A decomposition analysis

China's extensive and growing carbon dioxide (CO2) emissions are linked to rapid economic development and advancing urbanization, posing serious concerns in the context of climate change. Decomposition analysis has been widely performed to identify the drivers of China's CO2 emissions. However, to date, no researchers have examined the drivers of the change in CO2 emissions under the progress of urbanization across all of its provinces. Using provincial statistical data and six key factors influencing CO2 emissions (carbon intensity, energy intensity, resident consumption, consumption inhibition, population urbanization, and population size), we applied the logarithmic mean Divisia index decomposition method to examine how urbanization affect CO2 emission changes across 30 provinces during 1990–2016. We elucidated that while urbanization's effects on CO2 emissions increased in China as a whole during this period, they were regionally differentiated. The energy intensity effect was the main driver of reduced CO2 emissions, with carbon intensity exerting weaker effects in the 30 provinces, differentiated by their energy structures. The resident consumption effect, strongly linked to advancing urbanization, was the primary driver of increased CO2 emissions in all the provinces. While the consumption inhibition and population urbanization effects were positive at the national level, they were negative in highly urbanized provinces and in highly industrial provinces. These findings highlight the need to promote environmentally friendly consumption and to design regionally differentiated policies and optimized energy structures tailored to particular urbanization contexts. Moreover, they can provide valuable inputs for other developing countries undergoing continuous urbanization, contributing to efforts to balance economic development and environmental sustainability.

Effects of Carbon Mitigation on Co-pollutants at Industrial Facilities in Europe

In addition to global climate benefits, carbon mitigation improves local air quality by reducing emissions of hazardous co-pollutants. Using data on large industrial point sources in Europe, we estimate how changes in carbon dioxide emissions affect emissions of the three co-pollutants SOX, NOX, and PM10 for samples of 630 to 2,400 facilities for the years 2007 to 2015. We find substantial and statistically significant co-pollutant elasticities of about 1.0 for SOX, 0.9 for NOX, and 0.7 for PM10. These elasticities vary by economic activity, and are substantially higher for the production of energy. For climate policy-induced CO2 emission reductions we find elasticities in the energy sector of 1.2 to 1.8 for SOX, 1.1 to 1.5 for NOX, and 0.8 for PM10. Using these estimates to calculate monetary air quality co-benefits suggests that conventional European Environmental Agency estimates of carbon damages that omit co-benefits significantly underestimate the benefits of carbon mitigation.

FOREIGN DIRECT INVESMENT OUTFLOWS AND ENVIRONMENTAL POLLUTION: HIDDEN COINTEGRATION ANALYSIS FOR TURKEY

The relationship between foreign direct investment, which is a type of cross-border and long-term investment, and environmental quality is a current issue that is heavily debated. Foreign direct invesments can ensure economic growth and development of countries, while also causing a change in environmental quality. In the research conducted, it is seen that changes in carbon dioxide emissions with foreign direct capital inflows are mainly investigated from the point of view of the host countries. However, foreign direct invesment outflows may have an impact on the environmental quality of the home country. Because foreign direct invesment outflows can enable the transfer of more environmentally friendly techonogies to the country and strengthen management skills. The impact of foreign direct investment outflows on the home country's environmental pollution is shaped by many factors (scale, technique, and composition effects). In addition to these effects, it is necessary to pay attention to the regional and sectoral distribution of capital outflows. The main aim of this study is to examine the links between Turkey's foreign direct invesment outflows and carbon dioxide emissions for the period 1990-2018. For this reason, a unit root test was applied to variables whose natural logarithm was taken. Tests showed that all series are stable of the same degree. Engle&Granger(1987) and Granger&Yoon(2002) tests were used to determine the cointegration relationship between variables. The crouching error correction model(CECM) was applied to determine the causality relationship. According to the results of the analysis; i) In terms of the Engle&Granger(1987) test, there was no long-term relationship between variables. ii) According to the Granger&Yoon(2002) test, it was determined that there is a bidirectional hidden cointegration relationship between the positive shocks of carbon dioxide emissions and negative shocks of foreign direct invesment outflows. iii) There is a bidirectional asymmetric causality relationship between the positive shocks of carbon dioxide emissions and the negative shocks of foreign direct invesment outflows. iv) It is observed that 1% negative shocks in foreign direct invesment outflows reduce positive shocks in carbon dioxide emissions by 0,26%. As a result, since negative situations in foreign direct invesment outflows have an effect on improving the quality of the environment, the environmental dimension should be taken into account in the policies to be made.

Decoupling analysis between carbon dioxide emissions and the corresponding driving forces by Chinese power industry.

This study applied the Logarithmic Mean Divisia Index (LMDI) model to analyze changes in carbon dioxide emissions by Chinese power industry from 2003 to 2017. Besides, the Tapio decoupling analysis model is applied to explore the decoupling states between power industry carbon dioxide emissions and the corresponding influence factors. Several conclusions were obtained: (1) the power industry carbon dioxide emissions only displayed a slight downward trend during 2011-2012, 2013-2014, and 2014-2015; (2) the factors promoting the growth in power industry carbon dioxide emissions are energy consumption structure effect and total power generation effect. Power generation structural effect and fossil energy conversion efficiency effect inhibit the power industry carbon dioxide emissions from increasing, but they were far from offsetting the positive contribution value brought by total power generation effect; (3) changes in carbon dioxide emissions by the power industry were not sensitive to the change of fossil energy conversion efficiency and power production structure but were sensitive to the change of total power generation; (4) the contributions of technical effect were higher than those of structural effect on the decoupling index between impact factors and power industry carbon dioxide emissions.

An experimental investigation of the performance, emission and combustion stability of compression ignition engine powered by diesel and ammonia solution (NH4OH)

This study presents experimental examinations of a stationary single-cylinder compression ignition dual fuel engine for the combustion of diesel fuel with water ammonia solution. The effect of 25% water ammonia solution on the combustion, performance, emissions and stability of the dual fuel compression ignition engine was investigated, taking into account its different operating conditions. The experiments were carried out for three modes of engine operation with three loads (35%, 60% and 100%) and a change in the water ammonia solution energy fraction at 60% load, within the range from 0% to 17%. Co-combustion of diesel fuel with water ammonia solution in the test engine contributed to an increase in the ignition delay period and combustion duration, and to an increase in the heat release rate. Compared to the combustion of diesel fuel alone, combustion involving ammonia causes deterioration in the stability of the test engine operation, yet not exceeding the permissible stability indices for reciprocating combustion engines. Addition of water ammonia solution led to reduced nitrogen oxide emissions and increasing carbon monoxide and hydrocarbon emissions and did not result in significant changes in carbon dioxide emissions.

Impacts of wind erosion and seasonal changes on soil carbon dioxide emission in southwestern Iran

Wind erosion is one of the main drivers of soil loss in the world, which affects 20 million hectare land of Iran. Besides the soil loss, wind erosion contributes to carbon dioxide emission from the soil into the atmosphere. The objective of this study is to evaluate monthly and seasonal changes in carbon dioxide emission in four classes i.e., low, moderate, severe and very severe soil erosion and the interactions between air temperature and wind erosion in relation to carbon dioxide emission in the Bordekhun region, Boushehr Province, southwestern Iran. Wind erosion intensities were evaluated using IRIFR (Iran Research Institute of Forests and Ranges) model, in which four classes of soil erosion were identified. Afterward, we measured carbon dioxide emission on a monthly basis and for a period of one year using alkali traps in each class of soil erosion. Data on emission levels and erosion classes were analyzed as a factorial experiment in a completely randomized design with twelve replications in each treatment. The highest rate of emission occurred in July (4.490 g CO2/(m2·d)) in severely eroded lands and the least in January (0.086 g CO2/(m2·d)) in low eroded lands. Therefore, it is resulted that increasing erosion intensity causes an increase in soil carbon dioxide emission rate at severe erosion intensity. Moreover, the maximum amount of carbon dioxide emission happened in summer and the minimum in winter. Soil carbon dioxide emission was just related to air temperature without any relationship with soil moisture content; since changes of soil moisture in the wet and dry seasons were not high enough to affect soil microorganisms and respiration in dry areas. In general, there are complex and multiple relationships between various factors associated with soil erosion and carbon dioxide emission. Global warming causes events that lead to more erosion, which in turn increases greenhouse gas emission, and rising greenhouse gases will cause more global warming. The result of this study demonstrated the synergistic effect of wind erosion and global climate warming towards carbon dioxide emission into the atmosphere.

Estimating carbon dioxide emissions from electricity generation in the United States: How sectoral allocation may shift as the grid modernizes

The United States (U.S.) electric power sector historically comprises the largest portion of greenhouse gas (GHG) emissions from the world's second-largest GHG emitter. Consequently, carbon accounting methods employed for this economic sector play an important role in ensuring the accuracy of carbon accounts globally. For the U.S., the diverse purposes and methods of eight federal data products yield eight different estimates of U.S. electric-sector carbon dioxide emissions. Prior studies neither fully characterized these differences nor evaluated the data products' ability to capture changes in carbon dioxide emissions from certain now-minor sources of electricity that are projected to increase as the grid modernizes. Here we explore how shifts in electricity sources might impact current carbon accounting methods. We show that if no changes are made, four of the six data products could exclude (via omission or attribution) 1.1%–3.3% of carbon dioxide emissions from U.S. electricity generation in 2040. Maintaining comprehensive tracking of electric-sector emissions through the suggestions made herein can help enable efficient allocation of mitigation resources.

Addressing the Drivers of Carbon Emissions Embodied in Indian Exports: An Index Decomposition Analysis

This study identifies the determinants that have an observable impact over the change in carbon dioxide emissions embodied in the production of Indian exports by adopting an index decomposition analysis to address the contribution from four mutually non-exclusive factors which arise due to India’s increasing export performance during the 1995–2009 period on the change in total emissions embodied in exports. These four factors are scale effect, composition effect, emission regulation effect and production efficiency effect. The idea of bringing the last two effects is to capture the impact from technology factor due to international trade. This study found an increased emission embodiment in exports of 234.24 mega-tonnes by using input–output modelling with ‘emissions embodied in bilateral trade’ approach and then applies the Logarithmic Mean Divisia Index-I (LMDI-I)-based additive and multiplicative formulae following Ang and Zhang (2000) and Ang (2004) to conduct the decomposition exercise. This study finds the scale effect as the largest contributing factor increasing the emission levels by more than 184 per cent of the original increase, while the other three effects creating dampening impact over this scale-driven increase. Emission regulation effects created the maximum cleaning-up impact, especially during the 2002–2009 phase. JEL Codes: C67, F64, Q43, Q48, Q56

북한 육류 소비 행태 변화에 따른 이산화탄소 배출 변화량 예측

북한 육류 소비 행태 변화에 따른 이산화탄소 배출 변화량 예측

Differences in Changes in Carbon Dioxide Emissions among China’s Transportation Subsectors: A Structural Decomposition Analysis

ABSTRACT In recent years, one of the largest and most rapidly growing emitters of carbon dioxide (CO2) in China is the transportation industry. This article applies the structural decomposition analysis (SDA) method to identify the driving forces of CO2 emissions in four subsectors of the transportation industry in China and distinguishes the main final demand patterns that increase its emissions. Our results show that, first, during the study period, the expansion in demand was the largest contributor to the increase in CO2 emissions in the transportation industry, whereas the energy intensity effect played a dominant role in reducing emissions. In addition, CO2 emissions among four subsectors differed significantly not only in terms of changes in quantity but also the impacts of influencing factors. Moreover, most of the recent growth in CO2 emissions in China’s transportation industry has been driven by investment and exports. Because of the wide heterogeneity of changes in CO2 emissions among different transportation sectors, the particularities of each subsector should be taken into account in formulating pollution abatement policies in the transportation industry.

Economic growth and carbon dioxide emissions

The emissions of carbon dioxide (CO2) are an objective result of the civiliza-tional development of the world. Ensuring a steady decline in CO2emissions in the condi-tions of economic growth and social welfare requires a structural analysis of systemic de-pendencies. The purpose of the study is to investigate the contribution of different socio--economic factors to the changes in carbon dioxide emissions. A decomposition analysis is performed to examine the pace of CO2emission changes in relation to changes in: emissivi-ty of gross domestic product (GDP), productivity of man-hours, number of employees and working time per employee. Statistical data refer to the Polish economy in the period of 1990—2015.The results provided in this paper show that the economic growth in Poland had the most noticeable contribution to CO2emission changes. The solid growth of economy was ac-companied by decreasing emissivity of GDP. The increase in the labour supply, observed in some periods, contributed to the relative growth of that factor in pollutant emission changes. Considering the growing labour productivity, efforts to increase employment should be correlated with decreasing number of working hours per employee.

Forecasting CO2 emissions in Hebei, China, through moth-flame optimization based on the random forest and extreme learning machine.

The surge of carbon dioxide emission plays a dominant role in global warming and climate change, posing an enormous threat to the development of human being and a profound impact on the global ecosystem. Thus, it is essential to analyze the carbon dioxide emission change trend through an accurate prediction to inform reasonable energy-saving emission reduction measures and effectively control the carbon dioxide emission from the source. This paper proposed a hybrid model by combining the random forest and extreme learning machine together for the carbon dioxide emission forecasting in this paper; the random forest is applied for influential factors analysis and the extreme learning machine for the prediction. To improve the performance of the prediction model, moth-flame optimization is adopted to optimize initial weight and bias in extreme learning machine. A case study whose data is derived from Hebei Province, China, during the period 1995-2015 is conducted to verify the effectiveness of the proposed model. Results show that the novel model outperforms the compared parallel models in carbon dioxide emission prediction and has the potential to improve the accuracy of CO2 emission forecasting.

Will technology advances alleviate climate change? Dual effects of technology change on aggregate carbon dioxide emissions

The relationship between technology change and carbon dioxide emissions is complex. Existing research has emphasized technology progress in reducing carbon emission intensity but has ignored the impact of technology progress on economic growth, which leads to changes in carbon dioxide emissions. We argue that technology has relatively independent economic and environmental attributes. To provide evidence for this, we developed a method to distinguish the scale effect of technology change and its influence on economic scale from the intensity effect of technology change and its influence on carbon emission intensity. We applied this method to study the impact of technology change on carbon dioxide emissions in 95 countries between 1996 and 2007. We found that technology change indeed reduced aggregate carbon dioxide emissions, but the scale and intensity effects of technology change separately expressed positive and negative values. As a consequence, previous studies that only consider the intensity effect overestimate the impact of technology change on carbon dioxide emissions. Our findings yield important considerations for carbon dioxide emissions control in policy making.