Household Emissions Research Articles

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.

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

Point source carbon emissions account for approximately 80 % of total emissions. Investigating the influence of land use and socio-economic indicators on these emissions is crucial for achieving sustainable development goals. Existing research faces challenges such as focusing on specific regions, mixing variables that may exhibit multicollinearity, and lacking sufficient land use information. This study takes China, the largest emitting country, as a case study, utilizing geospatial big data to subdivide land use into 11 categories based on emission sectors. The impacts of land use and socio-economic indicators on different emission sectors are discussed from the perspectives of bivariate and spatial statistical analysis, with spatial hotspots identified. Hierarchical regression is used to evaluate the explanatory power of the indicators and to establish models, and potential carbon reduction strategies are further explored. Key findings reveal: (1) Significant multicollinearity between land use and socio-economic indicators was demonstrated, with land use explaining 57.1 % of emissions compared to 37.4 % explained by socio-economic indicators. The spatial consistency between land use and emissions exceeds 80 %, and the spatiotemporal variability is relatively low, making land use a more advantageous factor in explaining point source carbon emissions. (2) Agricultural mechanization increases emission intensity, but this efficient farming method helps convert surplus plowland, the largest influencing factor (Coefficient = 0.717), into carbon sinks, thereby controlling agricultural emissions. (3) Land intensification helps control industrial land, the main factor influencing industrial emissions (Coefficient = 0.392). It also contributes to the efficient use of carbon reduction technologies and industrial supporting land. (4) Mixed commercial and residential land has the greatest impact on commercial, service, and household emissions. However, its relationship with the economy (Correlation = 0.479) is stronger than its relationship with emissions (Correlation = 0.182), making it more applicable to cities that serve as economic growth hubs.

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

In recent years, compact urban development and carbon emissions reduction have been considered essential approaches for achieving sustainable development goals worldwide. Existing research has focused on the correlation between urban spatial structure and carbon emissions with inconsistent results. This study explores the correlation between urban compactness and household CO₂ emissions. Two indices of urban compactness and four categories of household CO₂ emissions are constructed. We utilize Spatial Durbin Models (SDM) and Spatial Autoregressive Models (SAC) on panel data from over 284 cities at the prefecture level and above in China, spanning 2008–2018. The results indicate that, except for heating consumption, household CO₂ emissions exhibit positive associations with two urban compactness indices. These findings suggest that a city with evenly developed urban cores within a relatively smaller urban area may have better household CO₂ emissions efficiency both locally and regionally. Our study contributes to the existing literature on the sustainability of compact city development with new evidence emphasizing a condensed but balanced urban structure.

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

The use of solid fuels presents a dual challenge for rural household energy systems: transitioning to cleaner energy sources while reducing carbon dioxide (CO2) emissions. Particularly in the Tibetan Plateau (TP), which is highly sensitive to global climate change, addressing rural household energy consumption, structural changes, and related CO2 emissions is crucial for implementing targeted measures. Based on household-level survey data, this study analyzes the quantitative and structural changes in energy consumption patterns among rural households on the TP from 2001 to 2021, as well as their related CO2 emissions. The results indicate that: (1) Yak dung is the primary fuel for rural households on the TP and a major contributor to direct household emissions. (2) While cooking has shifted considerably towards a modern clean energy structure, heating continues to rely on solid fuels such as firewood, yak dung, and coal. (3) Commercial energy used by high-income groups for agriculture, transportation, and other purposes has resulted in an overall increase in total household energy consumption and related CO2 emissions. Policymakers must implement more effective measures to accelerate the transition to cleaner, modern energy sources for heating and cooking purposes.

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.

Causal relationship between household consumption transition and CO2 emission in China: a dynamic panel model.

The mitigation of carbon dioxide (CO2) generated from household consumption, accounting for 52% of China's total greenhouse gas emissions, plays a pivotal role in China's pursuit of reaching a carbon peak by 2030. The study used three waves of nationally representative longitudinal data, energy statistics data, and input-output table to estimate household CO2 emissions (HCEs) in China at the micro-scale. The dynamic relationship between household consumption pattern transition and HCEs per capita was explored by applying maximum likelihood and structural equation modeling (ML-SEM) with panel data. The results indicate that per capita HCE level in a given year appears to be positively associated with HCE level for the same household in the previous year. A U-shaped relationship between consumption pattern transition and HCEs per capita was confirmed, as well as the reinforcement effect of income on the impacts of consumption pattern transition. The increase in consumption propensity, household income, share of wage-income, household asset values, and house space results in higher HCEs per capita. The family size and dependency ratio have a negative relationship with HCEs, whereas households that are female-oriented and more Internet-dependent tend to produce more CO2. Exploring the consumption transition of households is crucial for reducing CO2 emissions at the household level in China.

Quantifying functional group compositions of household fuel-burning emissions

Abstract. Globally, billions of people burn fuels indoors for cooking and heating, which contributes to millions of chronic illnesses and premature deaths annually. Additionally, residential burning contributes significantly to black carbon emissions, which have the highest global warming impacts after carbon dioxide and methane. In this study, we use Fourier transform infrared spectroscopy (FTIR) to analyze fine-particulate emissions collected on Teflon membrane filters from 15 cookstove types and 5 fuel types. Emissions from three fuel types (charcoal, kerosene, and red oak wood) were found to have enough FTIR spectral response for functional group (FG) analysis. We present distinct spectral profiles for particulate emissions of these three fuel types. We highlight the influential FGs constituting organic carbon (OC) using a multivariate statistical method and show that OC estimates by collocated FTIR and thermal–optical transmittance (TOT) are highly correlated, with a coefficient determination of 82.5 %. As FTIR analysis is fast and non-destructive and provides complementary FG information, the analysis method demonstrated herein can substantially reduce the need for thermal–optical measurements for source emissions.

Household carbon dioxide emissions Engel Curve dynamics

AbstractHousehold carbon dioxide emissions depend on the household's attributes and location. Wealthier suburbanites drive more and consume more energy at home. In recent years, affluent individuals have been more likely to purchase electric vehicles and install solar panels. Using several datasets from California, we observe that these shifts in consumer behavior have flattened household Carbon Emissions Engel Curves in the transportation sector and the electricity sector. Based on voting data from a 2018 proposition to repeal a fuel tax in California, we document that communities tend to support higher fuel taxes when their vehicle fleet is more fuel‐efficient.

Quantifying the greenhouse gas emissions of New Zealand households’ food purchases: An analysis by sociodemographic variables

New Zealand has committed to a 50% reduction in greenhouse gas emissions (GHGEs) from 2005 levels by 2030. Dietary changes within New Zealand could simultaneously improve population health and contribute towards the nation’s emissions reduction target, as agricultural emissions are estimated to account for half of New Zealand’s GHGEs(1). This research aimed to quantify the GHGEs associated with household purchases of major food groups in New Zealand and identify the sociodemographic characteristics that are associated with per capita household dietary emissions. Household dietary emissions were estimated using the NielsenIQ Homescan(R) consumer panel — a large sample of households within New Zealand who report purchasing data of take-home food and beverages. The sample is nationally representative in terms of broad geographical regions and selected key demographic characteristics. Carbon emission estimates were assigned to 1,908,485 total food and beverage purchases from 1,775 households over one year (2019) using a process-based life cycle assessment (LCA) dataset initially constructed in the United Kingdom (UK) and adapted for New Zealand(2). This LCA dataset contains estimates of greenhouse gas emissions generated over the life cycle of the production of food products from the following stages: farming and processing, transit packaging, consumer packaging, transport, warehouse and distribution, refrigeration, and overheads. Greenhouse gas emissions are expressed in kg of carbon dioxide equivalents per kg of food product over a 100-year time horizon. Total emissions from purchases of major food groups were then estimated. Multiple linear regression was used to examine the relationships between household variables and per capita dietary emissions. Overall purchases of red and processed meat (35%) and dairy products (19%) were responsible for the greatest proportion of emissions. The age group of the primary household shopper as well as household size were predictors of per capita dietary emissions — households with primary shoppers > 65 years had, on average, 33% (95% CI: 20% to 49%) higher per capita dietary emissions, compared to households with primary shoppers 34 years; and every additional household member was associated with, on average, 11% (95% CI: 9% to 13%) lower per capita dietary emissions. We have shown in this large representative sample of New Zealand households that purchases of just two food groups — red and processed meat, and dairy — were responsible for approximately half of dietary greenhouse gas emissions. Larger households had lower per capita dietary greenhouse gas emissions, and older shoppers had relatively higher greenhouse gas emissions. Whilst similar associations have been reported elsewhere more research is needed to confirm these latter findings. With enhanced understanding of the observed association between age of a household’s primary shopper and per capita dietary emissions, interventions may be devised that encourage shoppers to purchase lower-emitting foods, particularly less meat and dairy.

Understanding the Impact of the Key Determinants of Change in Household Emissions in The European Union: Index Decomposition Analysis

Sektörel faaliyetler ve hanehalkı faaliyetleri, insan faaliyetlerinden kaynaklanan sera gazı emisyonlarının ana etkenleridir. Yine de hanehalkı emisyonları sıklıkla göz ardı edilmekte ve uyumlu bir çaba gösterilememektedir. Ancak küresel iklim azaltımına ve net sıfır hedefine ulaşmak için hanehalkı emisyonlarının azaltılması gerekmektedir. Bu çalışmada emisyon azaltımında öncü olan Avrupa Birliği'ndeki 27 ülkede hanehalklarının faaliyetlerinden kaynaklanan emisyonlardaki değişimin incelenmesi amaçlanmıştır. Logaritmik Ortalama Divisia Endeksi (LMDI) yöntemi, çalışmada dört ana etkiye (emisyon yoğunluğu, enerji yoğunluğu, tüketim, nüfus) ayırılan hanehalkı emisyonlarındaki değişimi analiz etmek için kullanılmaktadır. Elde edilen bulgular, AB-27 ülkelerinin çoğunda, emisyon yoğunluğu ve enerji yoğunluğu faktörlerinin emisyonları azaltıcı etkide bulunduğunu, harcama etkisi ve nüfus etkisi faktörlerinin ise emisyonları artıran ve hanehalklarının emisyon azaltım performansını olumsuz etkileyen iki temel etken olduğunu göstermektedir. Hanehalkının kişi başına nihai tüketiminin emisyonları artırdığı böyle bir durumda, tüketici davranışını yönlendirmeye odaklanan müdahaleler tercih edilebilir. Sonuç olarak sürdürülebilir tüketim alışkanlıklarını teşvik eden, düşük karbonlu ürünlere erişimi teşvik eden programların ve benzeri politikaların AB-27 ülkeleri için uygun politika uygulamaları olacağı sonucuna varılmıştır.

The greenhouse gas emissions from meat sheep production contribute double of household consumption in a Eurasian meadow steppe

With the rapid development of the economy, household activities have emerged as an important source of greenhouse gas (GHG) emissions, making them a crucial focal point for research in the pursuit of sustainable development and carbon emission reduction. Hulunber, as a typical steppe region in eastern Eurasia, is representative of studying the GHG emissions from household ranches, which are the basic production units in this region. In this paper, based on survey data of 2018 and 2019, we quantified and assessed GHG emissions from household ranches by combining life cycle assessment (LCA) and structural equation modeling (SEM) approaches, with LCA to define household ranches system boundary and SEM to determine the key driving factors of emissions. The results showed that GHG emissions of meat sheep live weight was 23.54 kg CO2-eq/kg. The major contributor to household GHG emissions was enteric methane (55.23 %), followed by coal use (20.80 %) and manure management systems (9.16 %), and other contributing factors (14.81 %). The SEM results indicated that the GHG emissions from household ranches were derived primarily by economic level, while the economic level was significantly affected by income. This study also found a significant positive and linear correlation between household GHG emissions and the number of meat sheep (R2 = 0.89, P < 0.001). The GHG emissions from meat sheep production (67.52 %) were double times greater than household livelihood consumption (32.48 %). These findings emphasized the importance of reducing emissions from meat sheep production and adjusting the energy mix of household livelihood, contributing to the establishment of a low-carbon household livelihood operation.

Navigating Success in Carbon Offset Projects: A Deep Dive into the Determinants Using Topic Modeling

Carbon offset projects play a crucial role in tackling the global challenge of climate change. However, there is limited understanding of the factors contributing to the success of a carbon offset project. In this study, we utilize the latent Dirichlet allocation method to extract topics from the descriptions of carbon offset projects sourced from the Gold Standard Foundation. Our findings reveal that projects encompassing both safety and efficient energy solutions for households command higher prices. These results imply that an effective carbon offset project should mitigate individual household emissions while enhancing safety. Our research carries significant implications for stakeholders involved in carbon offset projects and can serve as a foundation for policy formulation and standard regulations.

Are cities ready for low‐carbon inclusive strategies? Household energy management under heterogeneous socioeconomic conditions

AbstractEnergy is an indispensable resource for economic development and the well‐being of society. Due to heterogeneity in socioeconomic conditions, households consume direct energy and produce emissions differently. Analysing energy emissions from heterogeneous socioeconomic groups helps to identify foci for intervention and create policies for sustainable cities. This study aimed to measure household emissions in Varanasi city and investigate the impact of heterogeneous socioeconomic variables on household emissions. Varanasi represents a million‐plus rapidly urbanising city. Analysis of variance (ANOVA) and non‐parametric regression revealed the relationship between end‐use energy emissions and socioeconomic variables for five income classes. Biomass‐based fuels constituted a significant proportion of energy (about 16%–20%) in low‐ to middle‐income groups, however, electricity consumption dominated in upper‐middle‐ and high‐income groups. A fuel‐stacking pattern was found, particularly in cooking activities. LPG was critical to replace solid biomass‐based fuels. To meet the present needs and absorb the impact of a growing population, energy policies and infrastructure should focus on accessibility and efficiency. An inclusive low‐carbon policy with a specialised focus on socioeconomic differences is needed for energy sustainability.

Research on energy consumption in household sector: a comprehensive review based on bibliometric analysis

Households are an important sector in carrying out human development activities, accounting for more than 30% of the total global energy consumption. The continued growth of household energy consumption (HEC) and carbon emissions is threatening economic and environmental sustainability. This review focuses on the research in the field of HEC and conducts a bibliometric analysis of research articles from the Web of Science Core Collection since 2000. The results show that: 1) HEC research has undergone rapid development since 2014, and interdisciplinary fusion and collaborative research have become dominant trends. 2) Keyword co-occurrence analysis clearly identifies the current urgent themes, including energy demand and its determinants, environmental impact factors and assessments, and energy-saving technologies and emission reduction measures. 3) The analysis of citations reveals that economic models, such as input-output models and life cycle assessment, are frequently employed in the field of HEC. Based on a summary of household energy-saving and emissions reduction work, this paper critically discusses the limitations of existing measures such as smart home technology, sustainable energy systems, and behavioral interventions. The main directions for promoting household energy-saving development in the future are identified: including improving the security and customer engagement of smart home technology, focusing on the availability and stability of sustainable energy, and paying more attention to low-income and aging households in behavioral intervention measures. One of the important obstacles facing research is how to reduce energy management efficiency and usage costs through technology and policy.

Synergistic effects of regional environmental governance on alleviating energy poverty and promoting household decarbonization

Alleviating energy poverty and lowering carbon emissions are two crucial goals that can help achieve sustainable regional development. However, to make this a reality, it is vital to understand the relationship between environmental governance and these goals, especially at the household level. This study utilizes microdata from the 2012–2020 China Family Panel Studies (CFPS) to construct models. We examine the synergies between reducing household energy poverty and emissions mitigation under regional policies, aiming to solve the long-standing energy poverty problem and reduce carbon emissions. Our findings emphasize that China's environmental governance exhibits significant synergies by concurrently addressing household energy security and promoting carbon reductions through integrated policy approaches. The efficacy and synergy depend critically on optimizing energy consumption structure, decreasing carbon intensity, and enabling technological advancement. These insights highlight the importance of top-level government design in balancing energy security and emissions reductions. Recommendations include establishing a robust governance framework to coordinate energy and climate goals while integrating climate and ecological governance regulations. The income-differentiated analysis provides valuable guidance for policymakers seeking to alleviate energy poverty and strengthen decarbonization, underscoring the importance of targeted interventions for disadvantaged households.