Household CO2 Emissions Research Articles

An Overview of Household Energy Consumption and Carbon Dioxide Emissions in Iran

This review tends to obtain a deeper understanding of the methods used in household energy consumption and carbon dioxide (CO2) emissions in Iran. Issues relating to energy consumption and CO2 emissions are very complex. This complexity arises from the fact that energy demand and energy consumption in Iran are influenced by many factors, such as income, household size, age, and gender. In Iran, the relevant energy sources mostly include liquefied petroleum gas (LPG) and electricity, which are used for different sectors, such as transportation, industry, and residential. This overview looks at both the theories and empirical studies of household energy consumption and CO2 emissions in Iran. Since energy consumption typically results in air pollution, it is often used as an indicator of environmental degradation. Although Iran is recently faced to energy efficiency improvement from all sectors, household energy requirements have been significantly increased. In Iran, a prime motivator had been improving living standards. As Iran gradually turns into a consumer society, households have an enormous influence on the direct use of energy and related CO2 emissions as well as through indirect use, as embodied in goods and services. The findings of this study can help policymakers to focus on renewable energy projects in order to reduce energy consumption and mitigate CO2 emissions.

Factors driving the change of household CO2 emissions through 2040 in China: based on decomposition and scenario analyses.

With China's economic transformation into a consumption-driven model, household CO2 emissions (HCEs) become an increasingly essential part of China's CO2 emissions. However, how will the HCEs change in urban and rural areas and what are the driving forces of HCEs through 2040 are not clear. In this paper, we project nation-level HCEs up to 2040 by the scenario analysis, and analyze the drivers of HCEs during 1997-2040 by the decomposition analysis. We find that the HCEs kept a persistent growth during 1997-2017 as energy intensity reduction and energy structure optimization cannot offset the rapid growth of consumption and population. During 2017-2040, in the current policy scenario, the rural HCEs will decrease, while the peaking of the total HCEs and urban HCEs would not be achieved. In the sustainable development scenario, the total HCEs, urban HCEs and rural HCEs will peak before 2030 and afterward decrease, because the energy intensity will induce a 51% and 76% reduction in the total HCEs and urban HCEs, respectively. Moreover, the decrease in the share of coal consumption due to the development of non-fossil fuels and natural gas will cause a more than 25% reduction in HCEs in the sustainable development scenario.

Sustainability from household and infrastructure innovations

In this paper, we look at the impact of different possible changes and innovations in the national/regional infrastructure and of individual households on the reduction of their material ‘footprint’ and carbon emissions. We have developed an ‘agent-based model’ (ABM) that explores the impact of possible changes in regional infrastructure and in ‘household agent’ behaviour and lifestyles. We study households of the UK, Germany, Spain and Finland, and calculate the overall effects of the diffusion of such changes and innovations. The ‘lifestyle’ of households is divided into four different ‘Domains’—Living, Food, Mobility and Energy. For each change, the model shows the linked effects of adoption, and total household input requirements (materials, energy etc.), household and food wastes and CO2 emissions. This informs policy concerning which modifications will be most effective. We can also estimate approximately how much ‘clean’ electricity will be needed in each country for household needs and their electric vehicles.

Exploring the characteristics and drivers of indirect energy consumption of urban and rural households from a sectoral perspective

AbstractChina is actively taking measures to guide the household energy‐saving consumption pattern because the total household indirect energy consumption and CO2 emissions have rapidly multiplied from 2002 to 2017 with an annual growth rate of 5.95%, and 5.56%, respectively. This paper calculates indirect energy consumption and CO2 emissions by four energy sources (raw coal, crude oil, natural gas, and electricity), analyzes the energy structure, and conducts a structural decomposition analysis in urban and rural areas in China from 2002 to 2017. The results reveal that the indirect energy consumption and CO2 emissions of urban households was 3.84 and 3.80 times, respectively, that of rural households in 2017 with most contributions from the ‘Agriculture, Forestry, Animal Husbandry, and Fishery’, ‘Foods and Tobacco’, and ‘OTHERS’ sectors. The energy consumption structure has changed. The percentage of coal consumption falls from 66.87% to 57.62%. Electricity consumption, ranked second, increased substantially from 10.77% to 22.90%. The key sectors of the energy mix have been found to help energy conservation. The high indirect energy consumption sectors with higher indirect energy intensity are the key sectors, especially the ‘Processing of Petroleum, Coking and Processing of Nuclear Fuel’ and ‘Production and Supply of Electric Power and Heat Power’. The consumption structure effect is more obvious in urban areas than in rural areas. In the process of urbanization, its effect has little impact on urban indirect energy consumption. It implies that the focus is on optimizing consumption structure rather than reducing consumption scale. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.

Estimation of Direct and Indirect Household CO2 Emissions in 49 Japanese Cities with Consideration of Regional Conditions

We conducted a detailed estimation of direct and indirect CO2 emissions related to multi-person households in 49 Japanese cities. Direct energy consumption was decomposed into energy use in order to consider the relationship with regional conditions. The results showed that CO2 emissions from direct energy consumption were almost as large as indirect CO2 emissions induced by consuming products and services, suggesting that lifestyle improvements are important for both energy savings and reducing CO2 emissions relating to product and service consumption. In addition, CO2 emissions from direct energy consumption varied widely between cities, making them susceptible to regional conditions. We also calculated CO2 emissions from direct energy consumption and examined the regional conditions for individual forms of energy use. CO2 emissions were higher in cold regions and lower in larger cities. In Japan, large cities are often located in relatively warm areas, so we conducted an analysis to distinguish the effects of climatic conditions from those of urbanization. This analysis allowed us to clarify the effects of regional conditions on factors such as heating/cooling and the ratio of detached houses to apartments.

Impacts of household living consumption on energy use and carbon emissions in China based on the input–output model

China must urgently accelerate its decrease of energy use, optimize its energy structure, reduce CO2 emissions, and promote the early realization of an ecological civilization. Simultaneously, meeting the growing consumer demand is one of the reasons for the increase in energy use. This study investigates the impacts of household consumption on energy use and CO2 emissions from the perspective of the lifestyle of Chinese residents. On the basis of the input–output model of 30 provinces, we analyze the current situation of energy use and CO2 emissions in different regions (spatial scale) with economic development and income improvement (time scale), investigate the pulling effect of household consumption in different provinces on industrial sectors, examine the influencing factors of indirect CO2 emissions from food, clothing, housing, and transportation in key regions, and explore the policy implications of the transition to a low-carbon lifestyle in different provinces. Results show that the fuel structure of Chinese residents should be optimized further. Total household energy consumption and total CO2 emissions considerably increased. In 2012, total household energy consumption accounted for nearly 30% of total energy consumption, while indirect CO2 emissions accounted for 66.3% of total household emissions. With regard to the structures of indirect household energy consumption, the housing sector accounted for the largest proportion, reaching 23.4% in indirect energy consumption in 2012. The pulling effect of the housing sector on industrial sectors was also evident. The decomposition analysis showed that the rapid increase in indirect household CO2 emissions was primarily due to the increase in per capita living expenditure. The consumption structures in different provinces produced various impacts, and the energy intensity effect was identified as an important factor for reducing indirect household CO2 emissions.

How do age structure and urban form influence household CO2 emissions in road transport? Evidence from municipalities in Norway in 2009, 2011 and 2013

This article investigates the influence of age structure on CO2 emissions from household road transport by using an extended STIRPAT model plus data from 380 Norwegian municipalities for 2009, 2011 and 2013. After controlling for population, household income, age structures, household size, and different urban forms (urbanization, urban density, housing type, building density), the paper reveals that the age group responsible for the highest CO2 emissions is 50–69, followed by 20–34 and 35–49. Moreover, compared with other groups, the road transport activities of age group 35–49 are highly constrained by household income. The paper also shows that there is an inverted U-shape relationship between household CO2 road-related emissions and building densities. However, it indicates certain limitations on city planners when it comes to reducing household CO2 road-related emissions by bringing the downtown area closer. Moreover, the paper also identifies a so-called compensatory mechanism supporting the hypothesis that building densities have positive effects. Furthermore, the coefficient of low-density housing is positive and significant, implying that the private gardens of low-density housing might not be the reason for the hypothesized compensatory mechanism. However, this remains a question worth investigating.

A hybrid intelligent predicting model for exploring household CO2 emissions mitigation strategies derived from butterfly optimization algorithm

The warming on earth is having a profound impact on human survival. With the improvement of people’ living standard, the consumption of energy in residential sector has raised swiftly, leading to a rapid increase in corresponding CO2 emissions. To effectively mitigate household emissions, taking the Yangtze River Delta (YRD) region in China as a case study, this paper proposes a novel intelligent model combining driving forces exploration and prediction. The work first estimates the residential energy-related CO2 emissions precisely, and then the bivariate correlation analysis will be applied to analyze region discrepancy in main affecting factors of emissions based on 13 preliminary indicators. To obtain the principal information of above influencing factors as the input of prediction model, the kernel principal component analysis (KPCA) is introduced innovatively. Besides, butterfly optimization algorithm (BOA) is enhanced to better optimize the parameters of least square support vector machine (LSSVM). The new proposed hybrid model, hereafter called as EBOA-LSSVM, will be utilized to predict residential CO2 emissions in the YRD. Ultimate simulation results present the new model's prominent performance through comparing prediction accuracy with other models. Finally, this article provides some advice for policy makers to guide CO2 emissions reduction from residents department.

Effects of the polycentric spatial structures of Chinese city regions on CO2 concentrations

The environmental sustainability of polycentric spatial structures in urban planning must be evaluated to ensure the sustainable development of city regions. Given the mixed conclusions of previous studies, as well as the lack of information on reliable methods of assessment and quantifiable mechanisms, a three-year dataset for prefecture-level and above city regions in China and spatial econometric models were used to examine the relationship between regional polycentricity and CO2 concentrations. After robust testing, we confirmed that polycentric structures decrease the mean CO2 concentrations of city regions, significantly reducing CO2 concentrations in primary city centers and mildly increasing those in city subcenters. Further quantitative analyses of the mechanisms underlying these patterns revealed that the CO2-reduction effect of polycentric structures is due to the balancing of reductions in commuting duration, transference of industrial CO2 to neighboring areas, and an increase in household CO2 emissions.

Does Financial & Social Development are Important for Economic Growth? An International Scenario

Financial and Social Development plays pivotal role in the economic growth of nations. Developed countries have strong financial and social infrastructure. This study focuses on the social and financial development in relation to economic growth of developed, developing and frontier economies. Gross Domestic product (GDP) per capita used as dependent variable. Domestic credit, market capitalization, turnover ratio, household consumption, foreign direct investment, capital formation, Co2 Emission and trade openness are used as independent variables. government expenditures on education and current health expenditures are use as social variables. Unemployment and inflation rate also use as control variables. Pooled OLS (ordinary least squares), fixed effects and random effects models are used to check the relationship among variables from 2001-2017. Results show positive and significant relation between Gross Domestic product (GDP) Domestic credit, education expenditures and health expenditures in case of developing countries. Market capitalization, turnover ratio, foreign direct investment, and trade openness have a positive but insignificant relationship. Co2 Emission, inflation and unemployment rate have negative and insignificant relation with GDP per capita. In advanced countries Inflation rate trade openness and FDI have positive and significant relation with GDP per capita. Domestic credit, market capitalization, turnover ratio, household final consumption and Co2 Emission have a negative relation with GDP per capita. Education and health also have a negative and insignificant relation with GDP per capita. In Frontier economies there is a positive and insignificant relation of market capitalization, FDI, Co2 Emission and health expenditures with GDP per capita. capital formation, turnover ratio, household consumption, trade openness has negative and significant relation with per capita. Education expenditures have positive and significant relation with GDP per capita. Co2 have positive but insignificant relation. Inflation and unemployment rate have negative but insignificant relation with GDP per capita.

Do general pro-environmental behaviour, attitude, and knowledge contribute to energy savings and climate change mitigation in the residential sector?

Energy consumption in the residential sector has grown significantly over the last 30 years. In recent years, a large number of authors have analysed the determinants of behaviour related to climate change. However, in this paper, referring to the behaviour and consumption level, we focused on energy consumption and direct household CO2 emissions. Thus, the objective of this study was to evaluate the determinants of energy consumption and CO2 emissions in the Lithuanian residential sector. Energy consumption was evaluated referring to the residential bills based on the official energy prices; CO2 emission equivalent was calculated employing the emission factors for separate energy resources. The regression analysis revealed that attitudes were significant only in the case of energy consumption for heating, but not in the case of heating-related CO2, which depended solely on the housing area, the type of fuel, and home heating (centralized). Meanwhile, concerning electricity consumption and related CO2 emissions, the pro-environmental behaviour was one of the factors along with the type of house, the number of children, family size, and gender. Results indicated that a complex of different factors needed to be considered to increase energy savings and CO2 reduction inthe residential sector regarding heating and electricity consumption.

Investigating the Impacts of Energy Access Scenarios in the Nigerian Household Sector by 2030

Lack of access to modern forms of energy continues to hamper socio-economic development in Nigeria, and about 94% and 39% of the Nigerian population do not have access to clean cooking equipment and electricity, respectively. The United Nations Sustainable Energy for All initiative and Sustainable Development Goal number seven seek to provide universal modern energy for all by 2030. However, the implications of these global goals on Nigeria’s energy system have not been well researched in the literature. In this study, we applied the Long-Range Energy Alternatives Planning Systems model to analyse the impacts of different energy access scenarios by 2030 on household energy consumption, CO2 emissions and local air pollutant emissions. We also analysed different scenarios for biomass renewability in order to understand its impact on household net CO2 emissions. We found that achieving a 100% modern energy access by 2030 would reduce final energy demand by around 845 PJ, which is equivalent to a 52.4% reduction when compared to the baseline scenario. A 100% modern access would also significantly reduce local air pollutants, but increase CO2 emissions significantly by 16.7 MtCO2 compared to the baseline scenario. Our analysis shows that the benefits of modern energy access have been limited in Nigeria due to poor financing and low income levels of households. Therefore, we argue that for a 100% modern energy access in Nigeria by 2030, there is a need to explore local and foreign funding sources, and a serious need to couple energy access programs in the country with income-generating activities.

Uncovering the national and regional household carbon emissions in China using temporal and spatial decomposition analysis models

The household sector of China is responsible for 11.7% of national energy consumption and 12.6% of carbon dioxide (CO2) emissions in 2015. Thus, revealing the determinants of household CO2 emissions (HCE) is extremely important for national efforts towards emissions mitigation. In this context, this paper investigates the driving forces behind national and regional HCE changes employing a temporal Logarithmic Mean Divisia Index (LMDI) model. It also analyses interregional discrepancies in HCE using a spatial LMDI model. This study decomposes the changes or discrepancies of national and regional HCE from 2000 to 2015 into seven key factors. The temporal analysis indicates that household income is the predominant determinant explaining the increase of HCE, whereas energy intensity is the crucial determinant contributing to the mitigation of HCE. The spatial analysis reveals that the number of households and energy intensity are primary driving forces accountable for growing discrepancies in HCE, followed by household income, energy structure and carbon emission coefficient. The analysis also suggests that resourceful and economically developed regions generally have larger potential for mitigation of HCE. The study concludes with some policy recommendations based on the results.

Impact assessment of supply-side and demand-side policies on energy consumption and CO2 emissions from urban passenger transportation: The case of Istanbul

The transportation sector accounts for about a quarter of global energy consumption and energy-related carbon emissions. To design and realize sustainable urban transportation, it is vital to understand and analyze interactions between a set of dynamic factors that shape transportation patterns, behaviors, and impacts. To this end, this study aims to develop a systems dynamics (SD) model for Istanbul, Turkey to simulate its urban motorized passenger transport system for analyzing numerous policies under different scenarios and assessing their potential effects in reducing energy consumption and CO2 emissions in the upcoming years. The constructed SD model includes four subsystems: population, household disposable income, transport, and energy and CO2 emissions. Based on historical data (2000–2015) and model validation processes, the energy consumption and the associated CO2 emissions from motorized passenger transport are forecasted for the following scenarios. The first one is business as usual scenario (BAU) which is designed to show how energy use and the associated CO2 emissions would evolve over time with the current development plans. The second and third scenarios constitute supply management measures (SMM) which consider different levels of improvements in the fuel economy of the vehicle fleet and reduced carbon emission intensity in electricity generation through increased share of renewable energy use. The fourth and fifth scenarios consider travel demand management (TDM) policies that include different levels of transport cost increase, and trip length reduction. Finally, the last two scenarios include integrated scenarios that are composed of the SMM and TDM options. In detail, compared to the BAU scenario, integrated scenario considers (1) a 10% improvement in the fuel economy of the vehicles, (2) a 10% reduction in the emission intensity of electricity generation, (3) a 30% increase in the transportation cost, and (4) a 15% reduction in the trip lengths. Under the BAU scenario, the SD model shows that energy consumption per capita from passenger trips will increase from 183 L of oil equivalent in 2016 to 315 L of oil equivalent in 2025 while the associated CO2 emissions per capita will increase from 460 kg in 2016 to 807 kg in 2025. To combat this dramatic growth, the findings indicate that the ambitious integrated scenario achieves the lowest energy consumption and CO2 emissions by offering a 33.5% expected reduction in total energy consumption and a 32.8% expected reduction in total CO2 emissions.

The impact of income on household CO2 emissions in China based on a large sample survey

This study provides insights into the impact of income on HCEs from different regions of China. Our results indicate that per capita income had a strong positive effect on HCEs before the development needs are saturated. Understanding the trends and magnitude of income impact on HCEs is crucial in developing and refining climate change adaptation and mitigation policies, including local adaptation policy, economic policy and low carbon policy.

Energy consumption and carbon footprint accounting of urban and rural residents in Beijing through Consumer Lifestyle Approach

Household carbon emissions are major contributors to global emissions that is increasing recognized. In China, approximately 20 million rural populations transfer to the urban areas annually, which results in a lot of new infrastructure construction and consumer requirements. This paper quantifies the numbers and trends of urban and rural resident on energy use and carbon footprint in Beijing from 1996 to 2011 by analysis of Consumer Lifestyle Approach (CLA) and carbon footprint. It provides a better understanding of complete energy consumption and carbon emissions profile in Beijing. The results show that for the Beijing residents, when direct and indirect energy consumption and CO2 emissions are taken into account, the total household energy consumption proportion compared to the city increases from 22.7% to 59.2%, and the total household CO2 emissions proportion increases from 32.2% to 68.8% in the research period. In the urbanization process, total energy consumption and carbon emissions of Beijing urban residents are significantly higher than those of rural residents. However, the transformation of a rural Beijing resident into an urban Beijing resident would not create a large difference between urban and rural areas in the per-capita energy consumption and per-capita carbon footprint. Results are assessed with respect to the available scientific literature, as well as potential available technological and policy solutions. Since the implementation that different policy instruments can mitigate carbon emissions, governments are gradually combining policy measures for the same technology. The results in this paper may help promote alternative consumption strategies in household sector which could entail more reasonable resource distribution and effective reduction of both urban and rural environmental influences.

What are the impacts of demographic structure on CO2 emissions? A regional analysis in China via heterogeneous panel estimates

This study comprehensively investigated the impacts of demographic structure on CO2 emissions in China at the national level and the regional level for the first time. Panel cointegration modeling was employed to test the long-run relationships between CO2 emissions and six demographic structure variables, namely, dependency ratio, sex ratio, higher education ratio, industrial employment ratio, urbanization ratio, and average household size. The fully modified ordinary least squares method was then applied to estimate the long-run elasticity of CO2 emissions for the six demographic structure variables. The results suggested that long-run relationships between CO2 emissions and demographic structure existed at both the national level and the regional level. Dependency ratio was found to exert negative effects on CO2 emissions in China and its three sub-regions. Positive associations between sex ratio and CO2 emissions were revealed to exist in China and West China, and CO2 emissions elasticity for sex ratio was relatively high in West China. Higher education ratio had a positive effect on CO2 emissions in East China. Industrial employment ratio was found to positively correlate with CO2 emissions in China, East China, and Central China. Urbanization ratio was demonstrated to increase CO2 emissions at the national level and the regional level, and CO2 emissions elasticity for urbanization ratio decreased from West China to Central China, and then to East China. Negative correlations between average household size and CO2 emissions were detected at both the national level and the regional level. Based on the findings of this study, several practical recommendations were proposed, including optimizing age structure, promoting gender equality, advocating low-carbon lifestyles and low-carbon consumption patterns, promoting industrial upgrading and industrial structure optimization, building low-carbon cities and less carbon-intensive public infrastructure systems, and improving residential energy efficiency.

Assessment and determinants of per capita household CO2 emissions (PHCEs) based on capital city level in China

Household CO2 emissions were increasing due to rapid economic growth and different household lifestyle. We assessed per capita household CO2 emissions (PHCEs) based on different household consuming demands (including clothing, food, residence, transportation and service) by using provincial capital city level survey data in China. The results showed that: (1) there was a declining trend moving from eastward to westward as well as moving from northward to southward in the distribution of PHCEs. (2) PHCEs from residence demand were the largest which accounted for 44% of the total. (3) Correlation analysis and spatial analysis (Spatial Lag Model (SLM) and Spatial Error Model (SEM)) were used to evaluate the complex determinants of PHCEs. Per capita income (PI) and household size (HS) were analyzed as the key influencing factors. We concluded that PHCEs would increase by 0.2951% and decrease by 0.5114% for every 1% increase in PI and HS, respectively. According to the results, policy-makers should consider household consuming demand, income disparity and household size on the variations of PHCEs. The urgency was to improve technology and change household consuming lifestyle to reduce PHCEs.

Driving forces underlying sub-national carbon dioxide emissions within the household sector and implications for the Paris Agreement targets in Japan

This study investigated insights into reducing energy-related CO2 emissions in households by examining individual socio-economic drivers at a sub-national level. Specifically, the logarithmic mean Divisia index technique was used to decompose CO2 emission trends into six drivers in all 47 prefectures of Japan during the period from 1990 to 2015. Drivers included the change in the number of households (household effect), distribution of households (distribution effect), household size (size effect), per-capita household energy consumption (consumption effect), household energy choice (choice effect), and sectoral CO2 emission intensity (intensity effect). The results showed that, in contrast to size and the distribution effects, the number of households had a positive, significant effect on CO2 emissions, indicating that recent demographic trends are responsible for the increase in CO2 emissions observed in most of the prefectures during the study period. With regard to effects related to consumption and choice, CO2 emissions due to changes in lifestyle dropped in only seven prefectures and reductions due to changes in sectoral energy choice were seen in only two prefectures in 2015. The intensity effect boosted the emissions of these prefectures the most in 2015 because of the shutdown of nuclear power plants due to the Great East Japan Earthquake. Further, we identified those prefectures that needed to reduce their per-capita energy consumption level in order to attain the reduction targets for household CO2 emissions in 2030 from 2015, given projected changes in demographic trends and recent and projected emission intensities. In order to achieve reductions in total CO2 emissions in line with the Paris Agreement, it is important to prioritize national and local policy interventions for the transfer of new household energy technologies, upgrade household appliances, and encourage people to limit energy consumption in light of the differences in these key drivers in each prefecture.

Comparing Urban and Rural Household CO2 Emissions—Case from China’s Four Megacities: Beijing, Tianjin, Shanghai, and Chongqing

CO2 emissions caused by household consumption have become one of the main sources of greenhouse gas emissions. Studying household CO2 emissions (HCEs) is of great significance to energy conservation and emissions reduction. In this study, we quantitatively analyzed the direct and indirect CO2 emissions by urban and rural households in Beijing, Tianjin, Shanghai, and Chongqing. The results show that urban total HCEs are larger than rural total HCEs for the four megacities. Urban total per capita household CO2 emissions (PHCEs) are larger than rural total PHCEs in Beijing, Tianjin, and Chongqing, while rural total PHCEs in Shanghai are larger than urban total PHCEs. Electricity and hot water production and supply was the largest contributor of indirect HCEs for both rural and urban households. Beijing, Tianjin, Shanghai, and Chongqing outsourced a large amount of indirect CO2 emissions to their neighboring provinces.