Household Carbon Footprints Research Articles

Japanese urban household carbon footprints during early-stage COVID-19 pandemic were consistent with those over the past decade

As urbanization accelerates worldwide, substantial energy and services are required to meet the demand from cities, making cities major contributors to adverse environmental consequences. To bridge the knowledge gap in the absence of fine-grained city-level climate protection measures due to data availability and accuracy, this study provides a detailed carbon emission inventory for analyzing the monthly fluctuations based on citizens’ daily consumption behaviors. Here, carbon emissions embodied in approximately 500 household consumption items were calculated in 47 prefectural-level cities in Japan from 2011 to June 2021. We analyzed the results considering the regional, seasonal, demand, and emission way-specific aspects, and compared the emission before and during the COVID-19 pandemic. Notably, the carbon footprints during the pandemic were consistent with the previous level despite downtrends in specific categories. This study provides an example of utilizing city-level emission data to improve household green consumption behavior as references for enriching city-level decarbonization paths.

Quantifying GHG emissions enabled by capital and labor: Economic and gender inequalities in France

AbstractMany studies have investigated the carbon footprint of households. They rely on consumption‐based responsibility and focus on how many emissions are embodied in a product. Here we open a new field by discussing the emissions that individuals enable by providing labor and capital to companies, using the framework of income‐based (downstream) responsibility. This perspective focuses on the emissions enabled by providing inputs to production processes, and is relevant for discussion of sustainable work and the carbon impact of investment and financial portfolios. We compute the downstream carbon intensity of primary inputs for 35 industries in France using the multi‐regional input–output database EXIOBASE. We provide a detailed picture of enabled emissions, disaggregating those by industry and primary inputs. On average, capital inputs are more carbon intensive than labor inputs. Finally, we couple downstream carbon intensities with an extensive national survey on wages to obtain a distribution of the income‐based emissions of employees. Income‐based emissions are much more unequally distributed than wages due to the huge variability of carbon intensity across industries: a truck driver enables far more emissions than a social‐care worker. Inequalities in emissions do not strongly interact with economic inequality. Yet they are gendered because women work disproportionately in low‐carbon‐intensive industries such as healthcare. As a result, women contribute less to GHG emissions than their wage share would seem to indicate.

Rural and Urban Household Carbon Footprint: A Comparative Study, West Bengal, India

Rural and Urban Household Carbon Footprint: A Comparative Study, West Bengal, India

Emissões de carbono das famílias brasileiras por meio da POF e da matriz de insumo-produto

Abstract This study aims to comprehensively assess the carbon footprint of Brazilian households using data from the 2008 and 2018 Household Budget Survey (POF). Employing a hybrid Life Cycle Assessment methodology, our analysis reveals noteworthy insights. In 2008, households within the lower income bracket emitted approximately 4.04 tCO2e/year, decreasing to 3.81 tCO2e/year by 2018. Conversely, higher-income households emitted significantly more, with emissions of around 28.73 tCO2e/year in 2008, decreasing to 25.94 tCO2e/year by 2018 - almost seven times the emissions of their lower-income counterparts. Intriguingly, although constituting merely 2.47% of all families in 2018, the wealthiest households were responsible for 8.31% of total emissions, while the poorest, representing 24.25%, contributed to 11.97% of emissions. The imperative for affluent families, who exert a disproportionate environmental impact, lies in reconsidering consumption habits and actively seeking low-emission alternatives to curtail their carbon footprint.

Spatio-Ethnic Household Carbon Footprints in China and the Social Equity Implications of Climate Mitigation Policy

Spatio-Ethnic Household Carbon Footprints in China and the Social Equity Implications of Climate Mitigation Policy

Toward sustainable development: Connecting systems thinking competency and carbon footprint knowledge

AbstractPrevious research on field of sustainable development has shown that individuals' systems thinking competency promotes and predicts their sustainability competency and pro‐environmental behavior well. Systems thinking competency also enables us to focus more on large‐scale climate change mitigation actions. Previous surveys indicated that Finns have changed their behavior for mitigating climate change, but this has been not reflected in decreased consumption‐based calculated carbon footprints because large‐scale mitigation measures have not materialized. The present study assessed Finns' systems thinking competency (n = 2006) and knowledge of how to reduce their household carbon footprint. The survey data collected were analyzed using explorative factor analysis, hierarchical regression analysis, t‐test, and analysis of variance. The results indicate that Finns view their own systems thinking competency related to climate change as not very high, and heir assessments vary widely. Moreover, their knowledge of how to reduce their household carbon footprint is somewhat low and is geared toward small‐scale mitigation actions. The results can be used to inform environmental policy and sustainability education priorities.

An integrated urban neighbourhood GHG mitigation analysis as a means to advance urban climate management

Worldwide, cities collaborate in the global effort to manage climate change mitigation. As cities are highly spatially and socially diverse entities, any city encompass a wide range of ‘GHG emissions lifestyles’ and therefore GHG mitigation strategies should reflect the urban diversity. Advancing sub-urban analysis can improve GHG mitigation by relating efforts and limited resources to the unique characteristics and functioning of different parts of the city. This paper emphasizes the need to relate the unique characteristics of key emissions categories at the residential neighbourhood level to its potential mitigation. It analyses the carbon footprint of households in residential neighbourhoods in the city of Tel Aviv-Jaffa, Israel, focusing on three major direct and indirect emissions categories: electricity, transportation, and food consumption. While the average city scale emissions found to be 4.6 ton of CO2e per capita, different neighbourhoods emissions ranged between 3.1 tons and 6.8 tons. Exploring the linkages to various explanatory, socio-spatial drivers found range of emissions related characteristics of different neighbourhoods. Finally, examining the potential contribution of implementing various GHG mitigation measures, revealed that the integration of technological, policy and behavioural measures may result with range of footprint reduction in different parts of the city due to the neighbourhoods' socio-spatial characteristics.

Characteristics, temporal trends, and driving factors of household carbon inequality in India

The distribution of carbon space across households needs attention towards unraveling its temporal dynamics and drivers for designing just and equitable mitigation policies. This study focuses on the Indian economy from 2003–04 to 2015–16 as it aims to understand the characteristics, temporal trends, and driving factors of inequality in household carbon footprints for rural and urban areas. Utilizing Environmentally extended Input-Output (EE-IO) data along with national household survey-based micro-economic details of the Indian economy, we estimate the direct and indirect CO2 emissions associated with the consumption of regional expenditure deciles for both years. We first quantify the inequality in the distribution of these emissions across household deciles using the Gini coefficient, Theil index, and carbon Palma ratio to analyze their patterns and temporal trends. Secondly, we investigate the drivers of household carbon inequality and its variation over time using decomposition by regional population sub-groups, consumption category sources, and expenditures as a determinant.For 2015–16, the urban richest decile emits 13.3 times more than the poorest one, while this disparity is around 7.5 times only for the rural regions of the Indian economy. Our results indicate that inequality of carbon space sharing among Indian households increased over the 12 years, more conspicuously in the case of rural households than for urban counterparts. The rural carbon Gini increased from 0.308 to 0.324, while the urban one showed a negligible change from 0.398 to 0.400. The dominant role of household consumption basket changes over time, particularly towards transportation needs, is observed in contributing to increments in both regions' carbon inequality. On the other hand, the expenditure inequality shows a more prominent increase over time in the case of urban areas, with its expenditure Gini rising by 0.23 points compared to 0.19 points increment for the rural case. The reasons underlying the striking regional trends in carbon and expenditure Gini indices are explored. Implications of our results are relevant in informing climate justice and mitigation concerns.

Quantifying households’ carbon footprint in cities using socioeconomic attributes: A case study for The Hague (Netherlands)

Cities consume almost 80 percent of world’s energy and account for 60 percent of all the emissions of carbon dioxide and significant amounts of other greenhouse gases (GHG). The ongoing rapid urbanization will further increase GHG emissions of cities. The quantification of the environmental impact generated in cities is an important step to curb the impact. In fact, quantifying the consumption activities taking place inside a city, if differentiated by socioeconomic and demographic groups, can provide important insights for sustainable-consumption policies. However, the lack of high-resolution data related to these activities makes it difficult to quantify urban GHG emissions (as well as other impacts). This paper presents a methodology that can quantify the carbon footprint of households in cities using consumption data from a national or European level, where the resource consumption is linked to socioeconomic attributes of a population. The methodology is applied to analyzing the environmental impact by household resource consumption in the city of The Hague in the Netherlands. The key insights reveal potential intervention areas regarding resource consumption categories and demographic groups that can be targeted to reduce GHG emissions due to consumption-driven activities in the city. • Demographic clustering to realize a socio-economic segmentation of the population. • Regression and data-driven models applied at district level to derive resource consumption. • Carbon emissions calculated by matching resource consumption with process-based LCI database. • Mobility, household waste and energy use account for 70% of carbon emissions in The Hague. • An estimated potential reduction of 30% carbon emissions in the mobility sector for The Hague.

Household Carbon footprint Assessment across an Urban Area, Tirunelveli of India

Household Carbon footprint Assessment across an Urban Area, Tirunelveli of India

Unequal age-based household carbon footprint in China

ABSTRACT Controlling household consumption is an essential means to achieve carbon neutrality in China, and population ageing has an important impact on its structure. Since older people exhibit different consumption patterns than younger people, an increase in the proportion of aged people affects overall consumption patterns. This paper adopts an input–output model to reflect the heterogeneity in the consumption structure and household carbon footprint of different age groups, followed by a simulation of the future household carbon footprint. The results find that in China, the total household carbon footprint shows an inverted U-shape with age, with the lowest total carbon footprint coming from aged households (age of household head 65 and above) and the highest total carbon footprint from middle-aged households (age of household head 45–54). The average household carbon footprint decreases with age, with aged households remaining the lowest. Aged households, however, have the highest share of the direct carbon footprint. Interestingly, urban households of all ages have a higher carbon footprint than rural households, with the largest difference being among aged households. The projection results show that based on demographic changes, although the average household carbon footprint of elderly households in China is low, as the number of elderly households increases, the total carbon footprint of elderly households will be sizable and need to be taken seriously. Key policy insights The total carbon footprint of elderly households will become more significant and sizable as the number of elderly households increases. Urban life is more carbon-intensive, and China’s urbanization is leading to an increase in the carbon footprint. Aged households require more attention in future climate policies. Targeted, consumption-based climate policies are necessary for carbon reduction in China and will have relevance in other countries with similar consumption structure and demographic trends, e.g. with ageing or rapidly urbanizing populations.

Evaluating carbon inequality by household type and income level across prefectures in Japan

Affected by income level, household type, and other socioeconomic factors, carbon inequality among households substantially differs across prefectures in Japan, thereby profoundly affecting the country's sustainable development. Therefore, it is necessary to explore the carbon footprint of different households on the basis of systematically grouped income levels and evaluate carbon inequality in all prefectures. Using the 2005 multi-regional input–output table of Japan, we identified detailed structures of household carbon footprint (HCF) across single- and multi-person households of different income levels in Japan's 47 prefectures. We elucidated carbon inequality across prefectures through the carbon footprint Gini coefficients of the aforementioned households. The results showed that substantial differences in HCF exist among prefectures, thus contributing to variances in carbon inequality levels. Multi-person households are currently the main contributors to Japan's HCF, but the contribution of single-person households has considerable potential to grow. Income level has the most direct influence on HCF, which considerably determines the amount and structure of household consumption. Changes in carbon inequality among prefectures indicate that the aggravation of income inequality widens the HCF gap among income groups—a situation inconducive to the reduction of per-household CF during climate mitigation.

Household carbon footprints inequality in China: Drivers, components and dynamics

The significant achievements in economic growth and urbanization in China have recently led to substantial increases of and great inequality in household carbon footprints (HCFs). To achieve efficiency and justice in emissions reduction, policymakers need to fully understand the sources of HCFs and identify the major causes of carbon inequality. By applying the Unconditional Quantile Regression (UQR) model and decomposition method to the Chinese household survey data, this paper investigates the distributional features of HCFs and their determinants. We find that HCFs are unevenly distributed due to differences in the volume and pattern of consumption, which are further determined by household characteristics and lifestyles. The intertemporal lifestyle changes have played a major role in the rise of HCFs inequality measured by various quantile emissions differentials. In addition, considerable increases in HCFs come from the high carbon emission groups, and most of the HCFs inequality stems from the 90–50 emissions differential. To transform the current carbon-intensive economy, policies are required to enhance environmental equity and encourage low-carbon lifestyles.

Non-farm employment promotes nutritious diet without increasing carbon footprint: Evidence from rural China

A nutritionally balanced, environmentally friendly diet is a prerequisite for the coordinated and sustainable development of human health and the environment. Acquiring a balanced and environmentally friendly diet remains a great global challenge, especially in rural areas in developing countries. As an important indicator for urbanization, non-farm employment has been proven effective in promoting food consumption and diversity in rural areas. However, it remains to be verified how non-farm employment impact food structure, nutrition levels and environmental impact, especially the relationship between sustainability dimension and diet quality improvement needs to be explored. Based on the food consumption data of 996 rural households in China in 2019, the impact of non-farm employment on household food consumption, structure, nutrition levels, and carbon footprint was estimated. It was found that the dietary nutrition structure in rural areas of China is still unbalanced, with ample room for improvement. Non-farm employment will accelerate the adjustment of family dietary structure and the improvement of nutrition level, especially for low-income families. Meanwhile, it will not cause significant increase of food-related carbon footprint. Promotion of rural households’ non-farm employment and publicity health and nutrition knowledge are important ways to strengthen food structure and nutrition promotion.

China's urban-rural inequality caused by carbon neutrality: A perspective from carbon footprint and decomposed social welfare

Urban-Rural Inequality (URI) is a critical issue that must be solved in carbon neutrality process. However, few studies made a detailed analysis of the URI mechanism. By defining household carbon footprint and decomposed social welfare impact (in the perspective of source-side and use-side impact), and innovatively linking them into a computable general equilibrium model, this paper analyzes the effects of carbon neutrality on URI. The results show that rural residents have a lower carbon footprint, but a higher intensity, which explains why the welfare loss on the use side of rural households is more significant than urban households. Almost all carbon pricing strategies will increase URI without considering carbon revenue recycling. The recycling mechanisms based on population and power consumption are more conducive to narrowing the URI through the source-side welfare impact and help to achieve carbon equity.

Urban and rural carbon footprints in developing countries

A good understanding of household carbon emissions is an important part of forming climate mitigation strategies to achieve the goals set out in the Paris Agreement. Numerous studies have been carried out on emissions from household consumption and the inequality between urban and rural areas in high-income developed countries, but there is a lack of in-depth analysis of such differences in developing countries. Our research details household carbon footprints (CFs) of four urban and four rural income categories for 90 developing countries, by linking global expenditure data to the environmentally extended multi-regional input–output approach. We show that there are large inequalities between urban and rural areas in developing countries. The average per capita CF in urban areas tends to be larger than that of rural inhabitants ranging from twice as large to nine times larger. We find that electricity consumption and transport are the largest contributors to the total CF in all expenditure groups. High-income rural households have an average per capita CF of 12.38 t CO2 which is 25% higher than the equivalent urban high-income group, which deviates from the literature looking at a subset of cases. Our study contributes to the existing research on CFs by providing knowledge on the consumption patterns and related carbon emissions of urban and rural populations in these understudied parts of the world.

Do more efficient buildings lead to lower household energy consumption for cooling? Evidence from Guangzhou, China

Over the last decade, residential energy consumption has become a major contributor to global energy use and carbon emissions, and its contributions, especially in developing regions, are accelerating more rapidly than those of the industrial sector. The energy efficiency of the building stock has shown great potential for reducing household energy consumption through advanced measures on the envelopes of buildings, such as the use of advanced construction materials and improvements in building structures. Thus, policies have been implemented to improve energy efficiency and reduce carbon emissions from buildings. This paper analyses survey data from Guangzhou, a megacity with a subtropical climate in South China, to estimate the effects of energy efficiency on the energy consumption of residential buildings. We apply an econometric approach to examine the effects of energy efficiency, and we employ instrumental variables to address problems of endogeneity. The results show that greener buildings, in terms of advanced building materials and structures oriented towards high energy efficiency, reduce the carbon footprints of households. Additionally, households with low income levels and those with environmentally friendly energy consumption behaviour are likely to benefit from living in energy efficient buildings more than other households. Finally, suggestions on ways to improve energy policy and methods to reduce household energy consumption and carbon (CO2) emissions are presented.

Unequal household carbon footprints in the peak-and-decline pattern of U.S. greenhouse gas emissions

Greenhouse gas (GHG) emissions in the U.S. peaked and declined in the first decade of the 21st century, largely attributed to the increased use of natural gas and renewable energy replacing coal. However, if and to what extent household consumption also played a role in this trend is still debated. Finding demand-side options is necessary to hedge against the risks of technology solutions failing to materialize. To fill this gap, this study analyzes the change in GHG emissions driven by U.S. household consumption, explores the drivers of this change and the contribution of different income groups. To this end, this study combined the U.S. consumer expenditure survey with an environmentally-extended multi-regional input-output framework to analyze changes in GHG emissions induced by household consumption between 2001 and 2015. This study further analyzed how much population, consumption volume and consumption patterns drove emission changes by quintile income groups. The results show that changes in household consumption contributed approximately one-third of the national emission decline. The decline in GHG emissions from U.S. households was mainly associated with a decrease in the consumption of carbon-intensive products, including gasoline, electricity, and animal-based food products. The top quintile income households were the main contributors to the emission increase before the peak, while the third and fourth income quintiles became emission mitigation leaders after 2010. Carbon inequality increased during the 2001–2006 period, mainly driven by increased wealth and consumption of high-income households, and was relatively stable after the peak. Emissions from certain consumption categories of the top quintile group are significantly higher than the bottom four quintiles with increasing trends, especially leisure-related services and goods, which require more attention in future policymaking for emission reduction.

Uncovering the differences of household carbon footprints and driving forces between China and Japan

Household carbon footprint is closely related with economic development level. Thus, to reveal the characteristic of household carbon footprint and its driving forces for countries under different development stage, this paper compared household carbon footprint and driving forces of developing China and developed Japan using input-output method and structural decomposition analysis method. Results show that China's household carbon footprint increased rapidly from 939 megatons (Mt) in 1997–3363 Mt in 2015, and then gradually decreased, while Japan's household carbon footprint fluctuated between 700–1000 Mt. In terms of per capita indirect household carbon footprint, it increased fast in China, but was still only less than 1/4 of that in Japan in 2018. Another finding is that food carbon footprint will decrease, while housing carbon footprint will increase with economic development. Transportation & communication can be a potential source for reducing such carbon footprints. In terms of driving forces of household carbon footprint, consumption expenditure was the major positive driving force and technology was a major negative driving force in China, while Japan was mainly driven by technology. It is suggested to pay attention to control the per capita household carbon footprint of fast developing countries, particularly transportation & communication consumption.

Socioeconomics determinants of household carbon footprint in Iskandar Malaysia

Understanding the complex links between socioeconomic variables and carbon emissions can reveal household spending and lifestyle patterns. This study oversees those issues and examines consumption patterns and their related variables such as climate change understanding, attitudes, and knowledge, in order to better comprehend the complicated linkages. This study revealed that eight socioeconomic elements influence a household's carbon footprint: (i) household income (β = 0.476, p < 0.05), (ii) green attitudes (β = −0.196, p < 0.05), (iii) residential space (β = 0.157, p < 0.05), (iv), education levels (β = 0.131, p < 0.05), (v) household's tenure status by ownership (β = 0.130, p < 0.05), (vi) household's age (β = 0.112, p < 0.05), (vii) size of household (β = 0.101, p < 0.05), and, (viii) female-headed household (β = −0.077, p < 0.05). Approximately 83.6% of respondents are mindful of climate change, but only 2.6% correctly define it as a long-term shift in weather patterns. The study found that 82% of households are willing to change their consumption habits and lifestyle to reduce their household's carbon footprint. In order to achieve a low carbon society, our research advocate a multipronged approach and policy action is crucial based on the results. Further, robust climate change educational and awareness programmes is decisive at the multilevel and scale in Malaysia to achieve its carbon emissions reduction target by 2050.