Multiple household-related driving factors of residential direct carbon emissions (RDCE) in China at regional level have not yet been sufficiently addressed or quantified. In this paper, a logarithmic mean Divisia index (LMDI) decomposition analysis was employed to examine the factors (e.g., the number of households, per capita household income, household size, urbanization, energy intensity, energy structure and emission coefficient) impacting the changes in RDCE in Shanxi province of China from 1995 to 2014. The results showed that the increase in RDCE mainly attributed to the growing per capita household income and the increasing number of households. Additionally, the expansion of urbanization also contributed marginally to the increase in emissions. However, the shrinking household size was a main inhibitory factor and the decline in energy intensity was also responsible for the diminishing emissions. Based on the results, four emission reduction measures and strategies were identified: (i) using market economic mechanism to regulate household consumption behaviors towards environment protection and low carbon development, as well as encouraging the use of energy-efficiency domestic appliances and less energy-intensive lifestyles; (ii) setting strict divorce processes to lower divorce rates and encouraging people to live with their children and parents; (iii) realizing green transformation development of urbanization; (iv) promoting a shift to renewable and clean energy in people's daily life and power generation, e.g., wind, solar, hydro, nuclear and biogas.

In recent years, the occurrence of floods is one of the most important challenges facing in Hamadan city. In the absence/inefficiency of urban drainage systems, rainwater harvesting (RWH) systems as low-impact development (LID) methods can be considered as a measure to reduce the floods. In this study, three scenarios concerning the RWH from the roof surfaces are studied to evaluate the type of the harvested water on reducing flooding. In the first scenario, which indicates the current situation in the studied area, it is indicated that there is no harvest of the roof surfaces in the studied area. The second scenario is about the use of water harvested from the roof surfaces for household purposes. The third scenario also refers to the use of harvested water for irrigation of gardens. The simulation results of these three scenarios using the Soil Conservation Service (SCS) method in the Hydrologic Modeling System (HEC-HMS) model reveal that if the second scenario is implemented, the runoff volume decreases from 28 to 12% for the return period from 2 to 100 years. However, in the third scenario, this reduction in runoff volume will be 48 and 27% for return periods of 2 to 100 years, respectively. Therefore, the results of this study indicate that the use of harvested water can also affect the reduction on runoff volume.

Understanding the consumption-based accounting (CBA), production-based accounting (PBA), and emissions embodied in trade is an important prerequisite for designing climate mitigation policies. Environmentally extended input–output (EEIO) models have been developed to evaluate the linkages between economic activities and environmental impacts as well as the embodied emissions in goods and services that are traded between countries. In this study, an environmentally extended global multi-regional input–output (EE GMRIO) analysis is performed to calculate Turkey’s CBA emissions and import-based embodied emissions for the year 2015 using the Eora26 database, which is a simplified version of the Eora database adapted to 26 economic sectors. The key sectors and sectoral carbon intensities of countries are determined in terms of embodied emissions in imports for household consumption. Our results indicate that Turkey was a net importer of greenhouse gas (GHG) emissions in 2015 and about 10% of total emissions of the final consumption in Turkey have occurred in other countries. The dominant contributing sectors to a nation’s GHG emissions can be quite different for the CBA and PBA approaches and the efforts to reduce GHG emissions requires a holistic approach. Import-based household emissions are assessed in terms of countries, sector and GHG intensities. Our results indicate that Turkey was a net importer of GHG emissions in 2015 with its approximately 10% of the total and 7.7% of household final consumption emissions having occurred in other countries. This also suggests that imported goods and services for household consumption have been produced in those countries with relatively low emission intensities. Considering Turkey’s emissions reduction targets, these results provide methodological benefits that will enhance national efforts by giving invaluable inputs about the emission intensity of imported and exported goods and better guidance to policy makers about future strategies for low-carbon manufacturing and shifting consumption patterns.

The postmodernism stance critiques the current discourse of modern consumption–based societies. These societies legitimize their embedded beliefs and actions based on their lifestyle reflected through their consumption patterns. Their consumption patterns relate to carbon footprints that are yet to be explored in the current body of knowledge at the macro level. The legitimacy of their lifestyle and consumption patterns rely on their conscious efforts in reducing carbon footprints. This study uses the environmental Kuznets curve model and explores the impact of household lifestyle and household consumption patterns on CO₂ emissions across different cultures and societies worldwide. 49 countries were taken to assess how different cultures define consumption patterns related to CO₂ emission. The results showed that the curvilinear relationship between consumption and CO₂ depends on the country’s national cultural orientation.

To assess the characteristics of household carbon emissions per capita (HCPC), this paper divided China’s provinces into 4 groups based on the decoupling relationship between household consumption and related emissions. This classification helped to analyze the correlation and reflected the decoupling status between carbon emissions and household consumption and explored the effect of consumption growth on carbon emissions. Then, according to logarithmic mean divisia index (LMDI) model, HCPC in China’s provinces was decomposed into four drivers including carbon coefficient, energy structure, energy consumption, and population structure effect. Through multi-regional (M-R) analysis, temporal evolution and spatial differences of these four drivers in both national and provincial level were studied. This comparison method introduced temporal and spatial decomposition results into the same framework, which may provide a new perspective for analyzing carbon emission trends. The results showed that (a) the HCPC in all 30 provinces increased significantly especially in Inner Mongolia, Tianjin, Xinjiang, Heilongjiang, and Beijing. Energy consumption effect was the leading factor promoting HCPC growth. Energy structure and population structure also promoted HCPC growth slightly, and carbon coefficient was the effect which had inhibitory effect on HCPC growth at regional level. (b) Spatial differences of HCPC between regions narrowed during this period. This is mainly due to the rapid growth of HCPC in region IV. Energy consumption effect was the dominant factor for the spatial differences. Based on the results, this paper proposed to adopt more effective measures to improve energy efficiency, develop clean energy, and optimize energy structure, especially in the provinces with faster growth in carbon emissions.

Resource endowment and economic development of different provinces in China vary greatly, resulting in large amount of CO₂ transfers. We need further exploration to help decision makers allocate emission responsibilities reasonably. We construct China’s embodied CO₂ transfer network (CTN) in 2012 from the perspective of provinces and sectors based on multi-regional input-output (MRIO) model and complex network analysis. The key CO₂ transfer nodes and paths, final demand decomposition, topological structure, clustering characteristics, and influencing factors are analyzed. The results show that the average CO₂ transfer length from one province (sector) to another is only 1.323 (1.584). The top three net CO₂ importers (45.39% of the total), located in developed eastern coastal area, mainly import CO₂ from energy-rich but underdeveloped provinces such as Heilongjiang. It presents a CO₂ transfer pattern from north to south and from west to east. CO₂ transfer in energy industry is mainly driven by urban household consumption. Non-adjacent provinces with distance greater than 750 km have no significant spillover effect and difference in technology level has the greatest impact on CTN. This work is important for differentiating the roles of provinces and sectors in CTN, guiding the allocation of carbon credits and controlling total CO₂ emissions.

In-depth study of the key sectors and supply chain paths driving coal consumption in China is valuable for effectively formulating coal reduction and replacement policies to achieve sustainable development. This study conducted a structural path analysis, based on the latest publicly available input–output tables and energy use data provided by the World Input–Output Database, to trace China’s coal consumption transmission throughout its entire supply chain. The results indicate that investment, exports, and household consumption are important factors in coal consumption. “Electricity, Gas and Water Supply” is a critical sector for, largely indirect, coal consumption. The path of “Electricity, Gas and Water Supply→ intermediate sectors→ Construction→ Investment” accounts for the bulk of coal consumption in China. The node path analysis shows that the 2-node transmission paths, starting from Construction and ending with “Other Non-Metallic Mineral” and “Basic Metals and Fabricated Metal” are important sources of coal consumption induced by investment demand. The 1-node path of “Basic Metals and Fabricated Metal” is an important path for coal consumption induced by export demand. The 1-node path of “Electricity, Gas and Water Supply” is an important path for coal consumption caused by household consumption demand. In order to effectively implement coal reduction and replacement policies, China should control coal consumption in these key sectors and channels and optimize intermediate input and energy use structures.

Household consumption has been identified to have an essential role in influencing ultimately the environmental pressures generated by human activities. This study assesses the indirect environmental footprint of the Spanish households applying a combination of consumer expenditure surveys with environmentally extended multi-regional input–output analysis. A total of fourteen environmental impact categories are studied from 2006 to 2015. All the impact categories present a similar trend, particularly affected by the economic crisis. The impacts decreased from 2008 to 2013 and finally slightly started rising again from 2014 to 2015. Results show that the dominant categories influencing the indirect environmental footprint in 2015 are (1) food and beverages, (2) housing, and (3) furnishings. From the intensity perspective, housing, transport, and food and beverages appear to be the most intensive consumption clusters in the Spanish household indirect environmental footprint. In relation to the indirect water impacts embodied in the Spanish households’ imports, the largest amount is from European countries and the highest virtual water (59%) corresponds to food and agriculture, in particular from wheat, fruit, vegetables, and dairy products. The findings obtained in relation to the sources generating indirect impacts from household consumption could aid the implementation of future mitigation policies.

This study explores the relationship between remittances received, education expenditure, energy use, income, poverty, and economic growth for a panel of the nine selected remittance-receiving countries (Bangladesh, China, Egypt, India, Indonesia, Mexico, Nigeria, Pakistan, and Philippines). World Development Indicator database is used for retrieving data from the period of 1990 to 2014. Panel cointegration technique is used to test the long-run relationship among studied variables. Furthermore, the autoregressive distributive lag (ARDL) model is applied to confirm the presence of a long-run and short-run relationship. The findings of the ARDL model indicate that remittances received positively influence economic growth, and there is a significant relationship between remittances received and economic growth during the long-run. Education expenditure, energy use, and income also positively and significantly impact economic growth during the long-run. In contrast, final household consumption used in this study as a proxy of poverty showed a significant negative effect on economic growth during the long-run, which indicates that increasing poverty will reduce economic growth; on the other hand, reducing poverty will boost economic growth in the selected countries during the long-run.

Urbanization in China has dramatically increased from 39.10 in 2002 to 58.52% in 2017. Studies have discussed the impacts of urbanization and its corresponding changes in consumption patterns on carbon dioxide emissions; however, little is known about their impacts on black carbon (BC). Therefore, we collected data on the BC emissions of various sectors to calculate the consumption-based BC emissions in China, and we used an input–output analysis (IOA) and structural decomposition analysis (SDA) to explore the impacts of urbanization and changes in consumption patterns on BC emissions from 2002 to 2017, focusing on sectoral BC emissions. The total BC emissions of various sectors first increased and then decreased. BC emissions increased from 1083.47 in 2002 to 2550.83 Gg in 2012. They were then reduced to 2478.63 Gg in 2017. Additionally, with the rise in the urbanization rate, household consumption BC emissions increased from 446.18 in 2002 to 1080.12 Gg in 2017. Urban consumption, rural consumption, and BC emission intensity were the three main contributing factors to household consumption BC emission changes. Transport, storage, postal, and telecommunications services (TSP); farming, forestry, animal husbandry, and fishery (FFA); and residential and other industries (RES) contributed the most to the urbanization-related BC emission increase. In particular, the TSP sector contributed the most to the BC emission increase because of the increasing TSP needs related to urbanization. Therefore, it is necessary to formulate mitigation policies for the TSP sector.