Household Greenhouse Gas Emissions Research Articles

Residential energy efficiency retrofits: How program design affects participation and outcomes

Better methods of characterizing and addressing heterogeneity in preferences and decision making are needed to stimulate reductions in household greenhouse gas emissions. Four residential energy efficiency programs were delivered consecutively in the Region of Waterloo, Canada, between 1999 and 2011, and each offered a unique combination of information, financial reward structure, and price. A natural quasi-experimental intervention design was employed to assess differences in outcomes across these program structures. Participation at the initial (evaluation by an energy advisor) and follow-up (verification of retrofit) stages, and the material characteristics (e.g., energy performance) were measured and compared between the groups of houses included in each program at each stage. The programs appealed to people with different types of material concerns; each phase of the program was associated with houses with a different mix of material characteristics and depths of recommended and achieved changes. While a performance-based reward attracted fewer houses at each stage than a larger list-based reward, older houses with poorer energy performance were included at each stage. The findings support experimentation with program designs to target sub-populations of housing stock; future program designs should experiment more carefully and with larger performance-based rewards and test parallels with potential carbon market structures.

An Exploration of the Relationship between Socioeconomic and Well‐Being Variables and Household Greenhouse Gas Emissions

SummaryThis research reports on a multivariate analysis that examined the relationship between direct greenhouse gas (GHG) emissions and socioeconomic and well‐being variables for 1,920 respondents living in Halifax Regional Municipality, Nova Scotia, Canada, using results from the Halifax Space‐Time Activity Research Project. The unique data set allows us to estimate direct GHG emissions with an unprecedented level of specificity based on household energy use survey data and geographic positioning system–verified personal travel data. Of the variables analyzed, household size, income, community zone, age, and marital status are all statistically significant predictors of direct GHG emissions. Birthplace, ethnicity, educational attainment, perceptions of health, life satisfaction, job satisfaction, happiness, volunteering, or community belonging did not seem to matter. In addition, we examined whether those reporting energy‐efficient behaviors had lower GHG emissions. No significant differences were discovered among the groups analyzed, supporting a growing body of research indicating a disconnect between environmental attitudes and behaviors and environmental impact. Among the predictor variables, those reporting to be married, young, low income, and living in households with more people have correspondingly lower direct GHG emissions than other categories in respective groupings. Our finding that respondents with lifestyles that generate higher GHG emissions did not report to be healthier, happier, or more connected to their communities suggest that individuals can experience similar degrees of well‐being regardless of the amount of GHG emissions associated with his or her respective lifestyle.

Greenhouse Gas Emissions Accounting of Urban Residential Consumption: A Household Survey Based Approach

Devising policies for a low carbon city requires a careful understanding of the characteristics of urban residential lifestyle and consumption. The production-based accounting approach based on top-down statistical data has a limited ability to reflect the total greenhouse gas (GHG) emissions from residential consumption. In this paper, we present a survey-based GHG emissions accounting methodology for urban residential consumption, and apply it in Xiamen City, a rapidly urbanizing coastal city in southeast China. Based on this, the main influencing factors determining residential GHG emissions at the household and community scale are identified, and the typical profiles of low, medium and high GHG emission households and communities are identified. Up to 70% of household GHG emissions are from regional and national activities that support household consumption including the supply of energy and building materials, while 17% are from urban level basic services and supplies such as sewage treatment and solid waste management, and only 13% are direct emissions from household consumption. Housing area and household size are the two main factors determining GHG emissions from residential consumption at the household scale, while average housing area and building height were the main factors at the community scale. Our results show a large disparity in GHG emissions profiles among different households, with high GHG emissions households emitting about five times more than low GHG emissions households. Emissions from high GHG emissions communities are about twice as high as from low GHG emissions communities. Our findings can contribute to better tailored and targeted policies aimed at reducing household GHG emissions, and developing low GHG emissions residential communities in China.

The bare necessities: How much household carbon do we really need?

The consumption patterns of Western nations are generally deemed to be unsustainable. Yet there is little attempt to restrain either material throughput or income growth. Nonetheless, in the face of the need to make ‘deep’ cuts in carbon emissions (for instance), consumption restraint may be a perfectly legitimate response. This paper explores the potential for a Reduced Consumption Scenario in the UK constructed by assuming that households achieve a specific ‘minimum income standard’ which is deemed to provide a decent life for each household type. The minimum income standards are taken from a recent study for the Joseph Rowntree Foundation and include not only subsistence commodities such as food, warmth and shelter but also the means to participate effectively in society. The Joseph Rowntree Foundation study produced detailed household expenditure budgets for these income standards. The paper uses an environmentally extended Quasi-Multi-Regional Input–Output model to estimate the greenhouse gas (GHG) emissions required in the production and distribution of all goods and services purchased according to these budgets. Our results show that average household GHG emissions in the UK would be around 37% lower in the Reduced Consumption Scenario than they are currently. We explore several implications of these findings including: the need to change social norms around consumption, the need for investment to improve the thermal performance of homes and the need to develop new transport infrastructures. We also address the potential to reduce emissions below the level achieved in this Scenario and discuss the implications for policy.

More or Better? A Model for Changes in Household Greenhouse Gas Emissions due to Higher Income

SummaryHouseholds exert an important influence on total greenhouse gas (GHG) emissions. Therefore, their consumption behavior is of interest in evaluations of climate policy options and projections of future emission paths. While most evaluations of household consumption and its emissions are based on expenditure only, we use a household consumption model based on functional units (e.g., kg food, person kilometers, living square meters). The goal of this article is to assess changes in consumption with increasing affluence level of households and to compare the allocation of GHG emissions to monetary versus functional units. We find that (1) the model based on functional units provides good bottom‐up estimates for greenhouse emissions of Swiss households; (2) quality (price per functional unit) increases with income for many consumption categories, and therefore using functional instead of monetary units leads to a lower increase of greenhouse gas emissions with income; (3) the relevance of GHG emissions from goods and mobility will increase. We conclude that using household models based on monetary units only overestimates the impact of marginal consumption and neglects the potential of decoupling income and environmental impact by consuming better instead of more. For sustainable consumption, research and policy should aim at preventing goods of higher quality from having higher environmental impact in order to benefit from the increasing quality orientation with rising income.

Richer and healthier, but not Greener? Choices concerning household energy use in India

India is among the world lowest per capita greenhouse gas (GHG) emitters, but rapid increases are expected. At the same time, World Health Organization (WHO) estimates show that 424,000 die prematurely in Indian households each year from air pollution exposure due to solid fuel use. We analyze GHG emissions and health through three policy scenarios for household energy, using projections for population, income and urbanization. In policy scenarios called Business as Usual (BAU), Improved Health, and Green Future, projected per capita household GHG emissions in 2026 increase by 169%, 164% and 139%, respectively, compared to 2001, whereas household mortality rates decrease by 45%, 67% and 45%, respectively. Due to income growth and urbanization, an increase in GHG emissions is likely inevitable, but can be slowed. For health, in contrast, improvements are expected and can be expanded.

Mājsaimniecību Ietekme uz Klimatu Latvijā: Oglekļa Pēdas Rādītājs

Mājsaimniecību Ietekme uz Klimatu Latvijā: Oglekļa Pēdas Rādītājs People more and more recognize climate change as one of the main environmental problems and the term ‘carbon footprint’ (CF) has become popular and is now in widespread use. In this paper, the CF concept has been applied to analyse average per capita household Greenhouse Gas (GHG) emissions in Latvia. We explore household CF in housing (heating and electricity consumption), transport, food and goods and service sectors, which are the main household environmental pressure areas. This paper provides an understanding of both direct and indirect (embodied) GHG emissions. Results from the study suggest that the average Latvian exceeds its global fair share of GHG emissions - the average per capita GHG in 2006 was 4.35 t CO2e. The highest household emissions arise from housing (37%), mobility (26%) and food consumption (25%), goods and services together account only for 12% of total household GHG emissions. This study, however, does not cover capital investments in infrastructure (roads, public buildings etc.) which could increase total emission by almost a ton. The study emphasizes that attention must be paid to the lifestyles, infrastructure and institutions that result in considerable amounts of carbon being locked up in the household activities through which people meet their everyday needs. The findings also indicate that policies should be targeted at the segments in society responsible for the highest carbon footprints, ie. housing, food and mobility.

The importance of goods and services consumption in household greenhouse gas calculators.

Despite the fact that lifestyles, in particular goods and services consumption, play a key role for global inequity and unsustainability of greenhouse gas emissions, these issues are often inadequately addressed in information and education materials such as household greenhouse gas calculators. Often, only limited individual responsibility for climate change can be concluded, and this is restricted to the reader's immediate surroundings such as the household and the private car, while goods and services consumption are almost always ignored. As a consequence, recommendations for reducing personal emissions concentrate on the relatively minor aspect of electricity and fuel use, while missing the more important issue of reducing goods and services consumption as an efficient way to abate climate change. These shortcomings are illustrated using the example of a recently published household greenhouse gas emissions questionnaire. An example for a comprehensive greenhouse gas calculator is also presented.