Household Emissions Research Articles

COVID-19 lockdown was insufficient to bring India’s PM2.5 levels below national standards

Abstract The COVID-19 pandemic lockdown provided an unprecedented opportunity to examine changes in India’s air quality following abrupt reductions in anthropogenic emissions, particularly from transportation, industry, and construction. While many studies reported substantial pollution declines during the lockdown, most focused exclusively on this period, neglecting the subsequent “unlock” phase, the influence of transboundary pollution, and the need to distinguish between emission-driven and meteorology-driven changes in PM2.5. Our study addresses these gaps by isolating the contributions of meteorological variability and activity restrictions on PM2.5 across the entire lockdown and unlock phases (February 24-June 30, 2020) using a high-resolution modelling framework and satellite-derived PM2.5 data. We found that PM2.5 concentrations decreased by 29% post-lockdown compared to a 21% decrease over the same period in preceding years, with satellite data indicating reductions of 31% and 22%, respectively. However, only 8-9% of these reductions were directly attributable to emission controls, underscoring the dominant role of meteorology. The most pronounced PM2.5 declines occurred in the Indo-Gangetic Plain during the unlock phase. Despite the initial improvements, strict curbs on transportation, industry, and construction alone proved insufficient to bring PM2.5 levels below the National Ambient Air Quality Standards. A crucial finding is that persistent emissions from the residential sector, which were not curtailed during the lockdown, significantly limited the overall reduction in PM2.5. Without concerted efforts to address household emissions, including the adoption of cleaner fuels (e.g., through programs like the Pradhan Mantri Ujjwala Yojana) and improved waste management to prevent garbage burning, India will not achieve sustained compliance with national standards. These insights highlight the urgent need for integrated, regionally tailored, long-term strategies that simultaneously target household sources alongside other key sectors. Implementing comprehensive measures could yield substantial, enduring gains in India’s air quality, forging a clearer path toward healthier, more sustainable environments.

Do Regional Differences Matter? Spatiotemporal Evolution and Convergence of Household Carbon Emissions in China

Understanding how household carbon emissions vary across time and regions is essential for promoting low-carbon lifestyles and advancing sustainability, yet this dimension remains underexplored—especially in large, diverse economies like China. This study addresses that gap by analyzing household carbon emissions across 29 Chinese provinces from 2000 to 2022, focusing on regional differences and convergence patterns. Using spatial and convergence models, we find persistent clustering—where provinces with high or low emissions group together—though these patterns shift gradually. Emissions have generally risen nationwide, with convergence trends emerging in the east, central, south, and north, while the west and northeast show inconsistent dynamics. Notably, emissions in one province are influenced by those in neighboring provinces, particularly in central China, due to close economic and energy ties. Industrial structure slows convergence at the national level, whereas stronger economic development, better education, and higher industrialization contribute to narrowing regional disparities—especially in southern China. These findings offer new insights for designing region-specific strategies that align household emissions management with China’s broader climate and sustainability goals.

Single-Person Household and Greenhouse Gas Emission: Evidence from South Korea

Abstract This study examines the relationship between single-person households and greenhouse gas (GHG) emissions in South Korea, with a particular focus on emissions originating from the residential sector, categorized by electricity, gas, and heating usage. Utilizing municipal-level panel data from 2015 to 2022, we apply a two-way fixed-effects instrumental variable estimation to analyze the impact of single-person households on per capita GHG emissions. Our findings indicate that an increase in the proportion of single-person households in metropolitan areas significantly reduces per capita GHG emissions. Heterogeneity analysis further reveals that this relationship is influenced by factors such as energy sources, age, gender, and housing type. Notably, single-person households residing in small-sized dwellings exhibit substantial reductions in emissions, highlighting the role of economies of scale in shared residential spaces. These findings suggest that promoting energy-efficient housing for single-person households in urban areas can contribute to GHG emissions reduction, with targeted interventions for different demographic groups enhancing sustainability efforts.

Targeting carbon reduction in UK households: A new segmentation model using financial transaction data

AbstractDesigning effective and targeted policies to reduce household emissions needs to consider variability in household consumption patterns, preferences, and financial capacities. This paper introduces a new segmentation model of household carbon footprints that uses financial transaction data from over 700,000 customers of a major high‐street bank. Our approach considers socioeconomic, consumer‐preference, and spatial factors to identify 10 distinct household typologies. We focus on targeted retrofit as a practical application, identifying three high‐impact household types with the capacity to invest—“Suburban Home Improvers,” “Car and Tech Enthusiasts,” and “Affluent Families”—and suggest targeted policy and communication opportunities. Our segmentation supports a new data‐driven policy design that considers both the technical potential and diverse behavioral factors affecting decarbonization decisions.

Household transportation lifecycle greenhouse gas emission prediction

Household transportation lifecycle greenhouse gas emission prediction

Factors Affecting CO2 Emissions from Direct Energy Household Consumption in Vietnam

The energy sector is pivotal in Vietnam’s commitment to achieving net-zero emissions by 2050. This study employs a combination of Structural Decomposition Analysis (SDA) and decoupling approaches based on data from Vietnam’s energy statistics and the Vietnam Living Standards Survey (VHLSS) for 2016, 2018, and 2020. The primary aim is to elucidate the effects of direct energy consumption by household groups on CO2 emissions, examine factors affecting emissions, and clarify the relationship between CO2 emissions from household energy consumption and economic growth in Vietnam. Research results underscore that household groups make considerable use of electricity and Liquefied Petroleum Gas (LPG), simultaneously reducing the proportion of firewood, rice husk, sawdust, agricultural by-products and other fuels. The decrease in energy intensity emerges as the primary factor in lowering household emissions, while population growth and economic efficiency exert the opposite effect. Additionally, the research reveals disparities in emissions between urban and rural areas, similarly among household groups within the given location. Despite maintaining a robust decoupling status between emissions from household consumption and economic growth, unsustainable risks persist, particularly with the increase in electricity demand. The study also highlights the uneven impact of the COVID-19 epidemic on CO2 emissions across household groups. Drawing upon these findings, several recommendations are proposed to control CO2 emissions from direct energy household consumption to facilitate the most effective household decarbonisation process while ensuring sustainable economic growth in Vietnam.

Wildfires and their respiratory impact

Wildfires and their respiratory impact

Household level fuelwood use and carbon dioxide emissions in Delanta district, Northeastern Ethiopia

IntroductionEthiopian rural households primarily rely on fuelwood as their main energy Q7 source, yet the country lacks precise data on fuelwood harvesting and its economic significance. Consequently, there is limited understanding of CO2 emissions resulting from fuelwood use.MethodsThis study aimed to estimate the annual amount of fuelwood collected and the associated CO2 and carbon (C) emissions. Using simple random sampling for household selection, data were analyzed with Excel and Stata.ResultsThe results reveal that fuelwood dependency is a major driver of deforestation and CO2 emissions, with households consuming approximately 2,725 kg of firewood and 26 kg of charcoal annually. Each household also extracts an average of 3,909.3 kg of firewood and 516.5 kg of charcoal annually for sale. Among sampled households, fuelwood constitutes 904,261 kg of energy, with 51% used for household consumption and 96% allocated for income generation. The inefficient burning of this fuel results in significant emissions, adding 974,000 kg of CO2 or 265,600 kg of carbon annually to the household carbon footprint. On average, each household emits 7,740 kg of CO2 and 1,960 kg of carbon per year.DiscussionThe study emphasizes that, while fuelwood plays a critical role in household energy and income, its unsustainable use accelerates emissions and deforestation. To mitigate these effects, the adoption of alternative energy sources like electricity and forest conservation through local plantations is essential for climate resilience.

Urban–Rural Disparities in Greenhouse Gas Emissions: Fuel Consumption in Moldovan Households and Implications for Energy Policies

Climate change, driven by greenhouse gas (GHG) emissions, poses a critical global challenge, with household energy use as a significant contributor. In the Republic of Moldova, stark urban–rural disparities in fuel consumption and emissions necessitate targeted research to inform effective energy policies. This study analyzes GHG emissions from household fuel consumption, focusing on the differences between urban and rural areas, using a quantitative approach guided by the Intergovernmental Panel on Climate Change (IPCC) methodologies. The findings reveal that rural areas, heavily reliant on traditional fuels like firewood, contribute disproportionately to emissions compared to urban areas, where modern energy sources such as natural gas dominate. Nationally, the research provides critical data to shape energy transition strategies, promoting renewable energy adoption and energy efficiency in rural areas. Internationally, it offers a valuable case study on household emission dynamics in developing countries, contributing to the global understanding of energy use patterns and their environmental impacts. Recommendations include enhancing access to cleaner energy, modernizing infrastructure, and encouraging sustainable practices to align with Moldova’s commitment to GHG reduction goals and serve as a model for similar contexts worldwide.

Distribution and ecological risks of pharmaceuticals and personal care products with different anthropogenic pressures in typical watersheds in China.

Distribution and ecological risks of pharmaceuticals and personal care products with different anthropogenic pressures in typical watersheds in China.

Deciphering the point source carbon footprint puzzle: Land use dynamics and socio-economic drivers

Deciphering the point source carbon footprint puzzle: Land use dynamics and socio-economic drivers

Analyzing how the timing and magnitude of electricity consumption drive variations in household electricity-associated emissions on a high-VRE grid

Abstract Electrifying the residential sector is critical for national climate change adaptation and mitigation strategies, but increases in electricity demand could drive-up emissions from the power sector. However, the emissions associated with electricity consumption can vary depending on the timing of the demand, especially on grids with high penetrations of variable renewable energy. In this study, we analyze smart meter data from 2019 for over 100 000 homes in Southern California and use hourly average emissions factors from the California Independent System Operator, a high-solar grid, to analyze household CO2 emissions across spatial, temporal, and demographic variables. We calculate two metrics, the annual household electricity-associated emissions (annual-HEE), and the household average emissions factor (HAEF). These metrics help to identify appropriate strategies to reduce electricity-associated emissions (i.e. reducing demand vs leveraging demand-side flexibility) which requires consideration of the magnitude and timing of demand. We also isolate the portion of emissions caused by AC, a flexible load, to illustrate how a load with significant variation between customers results in a large range of emissions outcomes. We then evaluate the distribution of annual-HEE and HAEF across households and census tracts and use a multi-variable regression analysis to identify the characteristics of users and patterns of consumption that cause disproportionate annual-HEE. We find that in 2019 the top 20% of households, ranked by annual-HEE, were responsible for more emissions than the bottom 60%. We also find the most emissions-intense households have an HAEF that is 1.7 times higher than the least emissions-intense households, and that this spread increases for the AC load. In this analysis, we focus on Southern California, a demographically and climatically diverse region, but as smart meter records become more accessible, the methods and frameworks can be applied to other regions and grids to better understand the emissions associated with residential electricity consumption.

Exploring the Contribution Roles from Municipal Cities in the Rise in Household CO2 Emissions in China: From a Local Scale Analysis in the Global Context

A major source of carbon dioxide emissions (CO2) arises from the household sector. Recent studies have reported increasing household CO2 emissions (HCO2) in many countries. Cities represent a key administrative level in China and can be managed to mitigate HCO2 if spatial and temporal variations in HCO2 are understood at fine scales. Here, we applied panel data analysis to map HCO2 at a pixel scale of 1 km in China using remotely sensed time series nighttime light data, grid population density data, and provincial energy consumption statistics from 2000 to 2020. Spatial and temporal variations in HCO2 were observed with four growth modes, including high growth (HG), low growth (LG), negative growth (NG), and high negative growth (HNG), for different periods, i.e., 2000–2010, 2010–2020, and 2000–2020. We proposed a local scale analysis of HCO2 growth patterns within a global context to assess the contribution roles of 372 municipal cities to the changes in the national total HCO2 (T-HCO2). The results indicated that T-HCO2 has tripled in the last two decades, but the roles of the contribution to the increase varied among cities. The local scale analysis revealed that more cities contributed to the rise in T-HCO2 through HG and LG than those that suppressed it through NG and HNG. The majority of the cities displayed contributions to the rise in T-HCO2 through two or more of the growth modes, confirming a significant variation in HCO2 across locations, even within a city. This study provides a new approach to understanding the roles cities play in the long-term dynamics of T-HCO2. We recommend increased efforts to encourage HCO2 mitigation in cities that have contributed to the rise in T-HCO2 to help neutralize carbon emissions at the national level.

Examining changes in household carbon footprints across generations in the UK using decomposition analysis

AbstractTo meet climate targets, consumption‐based household emissions need to fall rapidly. An important but still poorly understood question is whether generational change could contribute to decreases in emissions. It is sometimes assumed that younger generations such as Millennials and Generation Z are more concerned about climate change and have greener lifestyles than previous generations of the Silent Generation, Baby boomers, and Generation X, but carbon footprinting analysis typically focuses on age groups rather than comparing generations over time. This paper provides a first assessment of the change in consumption‐based carbon footprints of the Silent, Baby boomer, Generation X, and Millennial generations within the United Kingdom between 2001 and 2020 and a comparison of the footprints of different generational groups. The analysis is based on environmentally extended input–output analysis, using the Living Costs and Food Survey and emission data from the UK multi‐regional input–output database. We find some evidence for the hypothesis that younger generations have smaller footprints than older generations as Generation X and Millennial households have smaller carbon footprints compared to the generation before them at a similar life stage. We find that factors such as decarbonization, household occupancy, total expenditure, and changing consumption patterns contribute to the UK's changing carbon consumption emissions between 2001 and 2020, and the importance of these factors varies for different generational groups. However, future research that uses a longer time series is required to assess generational differences in carbon footprints over the whole lifespan of several generations.

Does a more compact urban center layout matter in reducing household carbon emissions? Evidence from Chinese cities

Does a more compact urban center layout matter in reducing household carbon emissions? Evidence from Chinese cities

Energy consumption, structural transformation and related carbon dioxide emissions of rural households on the Tibetan plateau

Energy consumption, structural transformation and related carbon dioxide emissions of rural households on the Tibetan plateau

Analysing the Indicators and the Associated Recommendations of Household Emission Calculators

Analysing the Indicators and the Associated Recommendations of Household Emission Calculators

Will the miniaturization of household size promote household carbon emissions in China? Analysis based on CFPS data

As the proportion of household carbon emissions to global carbon emissions continues to increase, reducing carbon emissions from household consumption has become an important way to achieve the goals of carbon peaking and carbon neutrality. How the trend of miniaturization of household size will affect household carbon emissions is a matter of concern. This paper uses a sample of 9,090 households from the China Family Panel Studies (CFPS) database in 2018 to empirically study the impact of changes in household size on household carbon emissions, from the perspective of household consumption structure and urban-rural areas. The research results indicate that the miniaturization of household size will increase household carbon emissions, the impact of household size on indirect HCEs is greater than on direct HCEs. The impact of household size on indirect HCEs is heterogeneous in consumption structure and the impact of household size on indirect HCEs from housing, transportation is greater than that of other consumption items. The impact of household size on urban household carbon emissions is greater than that in rural areas. The upgrading of household consumption structure and the miniaturization of household size promote the increase of HCEs jointly. Therefore, this paper proposes that under the trend of household miniaturization, energy-saving and emission reduction policies should focus on reducing indirect households carbon emissions, optimizing household structure and household consumption structure, enhancing environmental awareness among family members, establishing and improving the green consumption system, and building environment-friendly households.

Exploring urban spatial heterogeneity and socio-environmental attributes of household greenhouse gas emissions

Understanding urban spatial heterogeneity of greenhouse gas (GHG) emissions from sectoral household consumption is crucial to facilitate moves towards low-carbon cities. In this study, we use Xiamen city of China as a case study to reveal the emission characteristics of household GHG as well as spatial heterogeneity. We conducted a face-to-face questionnaire survey and calculated GHG emissions of districts from household energy consumption, food consumption, transportation, housing, household waste and wastewater treatment. The GHG emissions and the amount of urban residential household consumption shows obvious spatial heterogeneity across districts. Total GHG emissions of Xiamen city were 8.39 Mt. CO2e, and average household and per capita of GHG emissions were 8.11 and 2.72 tCO2e, respectively. While total GHG emissions vary from 0.41 to 2.45 Mt. CO2e across six districts and range from 0.16 to 3.39 Mt. CO2e among six sectors. Household GHG emissions differ from 7.08 to 9.40 tCO2e, while the per capita emissions range between 2.41 to 3.14 tCO2e among districts. Results also showed that more urbanized areas with higher population density have larger total urban residential GHG emissions, whereas household emissions were comparatively lower in these areas. In contrast, our study did not show an (inverted-) U relationship or linear relationship between emissions and population, nor between emissions and income level. Household energy use is the largest sector emitting GHGs. These findings will be useful to underpin policy making towards low-carbon cities.

Better social infrastructure matters: Impacts of perceptional and behavioral smartization on food-related household emissions and wastes

Japan has been implementing policies to reduce greenhouse gas emissions (NDC goal) and food-related wastes (Food Recycling Act). However, these policies were mainly targeting commercial stakeholders instead of households. In this paper, we proposed a smart food transition framework with multiple dimensions, conducted a large sample size survey (5500 households in Japan) with consumer attitudes towards smart food services and smart eating habits, and investigated what may affect food-related household greenhouse gas emissions and food waste through a detailed assessment of both direct and indirect emissions. We found that, in the context of a better social infrastructure (e.g., better telecommunications infrastructure or higher penetration of SNS) where households can have a higher level of welfare and better access to smart food services, additional food waste would be generated, but not necessarily food-related greenhouse gas emissions. This is possible to be improved by perceptional changes and behavioral changes (e.g., more tolerance of using commercially prepared dishes, more willingness to use inventory management APPs). Our paper emphasized the importance of appropriate guidance in such perceptional changes and behavioral changes, together with detailed directions, for more decent household lives in the future of Japan.