Consumer Lifestyle Approach Research Articles

How washing behaviors influence GHG emissions in textile use phase: a PLS-SEM analysis of household washing behaviors in Shanghai

PurposeThis paper explores what factors influence household textile washing behaviour and how these factors relate to greenhouse gas emissions during the textile use stage.Design/methodology/approachA questionnaire survey related to textile summer washing and care behavior was conducted among households in 16 administrative districts of Shanghai. This study used the modified Consumer Lifestyle Approach framework of the washing and care ecosystem. The research hypotheses were established by selecting related factors from four aspects: household demographic characteristics, economy and consumption characteristics, washing machines and detergents characteristics.FindingsFirst, we have demonstrated how some course factors do not significantly affect greenhouse emissions. None of the demographics, detergent-related activities, economy and consumption constructs significantly affect greenhouse emissions. Second, we have identified that washing machine and related activities has a direct positive effect on GHG emissions. The washing machine is not only the de facto carrier of all washing activities but also the core of washing activities. Washing machine is crucial in reducing greenhouse emissions and adjusting consumer behaviors.Originality/valueThis paper conducts a study related to the washing and care behavior of households in Shanghai. The paper examines the factors influencing household washing behavior and the relationship between these factors and greenhouse gas emissions during the textile use phase.

Smart cities and urban household carbon emissions: A perspective on smart city development policy in China

Smart cities have the potential to achieve the goal of carbon neutrality, but empirical evidence regarding the effect of smart city policies on carbon emissions is limited. In this novel study, we investigate the effect of China's smart city policy on household daily consumption and carbon emissions. The empirical analysis is based on a difference-in-differences regression, in which the dependent variable is the household indirect carbon emissions estimated based on the consumer lifestyle approach and a dataset of 201 Chinese cities between 2010 and 2018. The main findings are as follows. First, the smart city policy significantly reduces household indirect carbon emissions, and the reduction is greater when the policy pilot region includes the whole city rather than only certain subareas. Second, the mechanisms through which the smart city influences household indirect carbon emissions are mainly the reductions in transportation- and education-related emissions resulting from developments in smart technology. Third, the above effects last for years, and they are regionally heterogeneous and more significant in the cities of eastern China. The findings in this paper suggest that smart cities can potentially achieve city sustainability by promoting greener consumption behavior.

Estimation and Influencing Factor Analysis of Carbon Emissions From the Entire Production Cycle for Household consumption: Evidence From the Urban Communities in Beijing, China

Household carbon emissions (HCEs) in urban communities are significant sources of China’s total carbon emissions and contribute to global warming and climate change dramatically. This study aims to estimate the HCEs and investigate their influential factors based on a total of 185 household survey data collected from three typical types of urban communities in Beijing: traditional communities, unit communities, and commercial housing communities with the application of the consumer lifestyle approach analysis and econometrics model. The results show that unit communities contribute to the highest direct carbon emissions and the commercial housing communities produce the most indirect carbon emissions, with the traditional communities emitting the lowest carbon emissions both directly and indirectly. The highest direct carbon emissions of households are found in unit communities at 723.79 kgCO2 per month, followed by commercial communities at 580.01 kgCO2, and finally the traditional communities with 526.44 kgCO2 direct carbon emissions monthly. And the highest monthly indirect carbon emissions of households are found in commercial communities at 707.70 kgCO2, followed by unit communities at 669.38 kgCO2, and finally with 554.85 kgCO2 indirect carbon emissions monthly in traditional communities. It concludes that the community type affects HCE characteristics and their driving factors significantly. Household income, household population, and the ownership of cars increase HCE in more than one type of community. Scientific research work-related population, community environment satisfaction, housing area have positive effects, while community convenience has negative impacts on HCEs in one certain type of community. Policy implications tailored to general and specific community types are proposed as the guidance of carbon reduction and community transformation finally. This study contributes to the understanding of the impact of community attributes on HCEs and proposes some methods for microregional carbon emission reduction and the ecological transformation of urban communities.

Effect of Broadband Infrastructure on Rural Household CO2 Emissions in China: A Quasi-Natural Experiment of a “Broadband Village”

This paper explores how broadband infrastructure affects rural household carbon dioxide emissions (HCE). Based on the Environmental Kuznets curve hypothesis, a quasi-natural experiment of a “Broadband Village” (B&V) in China is conducted. Panel data from 9,790 rural households were collected as part of the China Family Finance Survey (CHFS). The consumer lifestyle approach was used to calculate HCE and a Difference-in-Differences (DID) model was used to analyze the impact of a B and V pilot project on rural HCE. The results of DID model showed that B and V significantly increases rural HCE, with an influencing coefficient 1.7. Subsequently, Threshold Model was utilized to examine the nonlinear relationship between household broadband penetration and rural HCE. The results revealed the threshold effect between rural household broadband penetration and rural HCE. Namely, the growth effect of B and V to rural HCE would be much weaker, if rural household broadband penetration goes above a threshold level, 31.32%. Our analysis provides important insights for policymakers to formulate digital village and income redistribution policies to support rural carbon dioxide (CO2) emissions reductions.

The Carbon Cost of an Educated Future: A Consumer Lifestyle Approach

Demographic and economic growth will account for most of the anticipated growth in greenhouse gas (GHG) emissions in the next century. Education is associated with development, and the world population in the near future is likelyto be significantly better educated than today. Previous studies ofhousehold energy demand and associated emissions have not directly considered the consequences of a more educated population. In this study, I estimate the energy intensity of consumption dollars and the total impact of households according to their demographic characteristics, with particular attention to differences in spending habits by education and the environmental consequences. I find that education results in fewer emissions per household, holding other household characteristics constant. Each year of education is associated with an average effect in CO2-equivalent (CO2e) emission of -466kg/yr.After controlling for household characteristics, the effect of a year of education is -163.1kg per year. Educated households spend less on home energy and transportation by car, two of the most important sources of household level atmospheric GHG production. They spend relatively more on investment goods, public transport, and other activities which have a low environmental footprint.

Analysis of Household Energy Use and CO2 Emission using Environmental Kuznets Curve

This study examined the environmental Kuznet’s curve based on the household energy use and pollution of carbon dioxide in Nigeria as a means of identifying efficient energy for a sustainable environment. Secondary data sets obtained from National Bureau of Statistics on the General Household Survey (2010-11, 2012-13, 2015-16 and 2018-19) were utilized. The study employed descriptive statistics, Consumer Lifestyle Approach and the Econometric specification for income-pollution models. The result showed that the use of diesel and kerosene were declining over the years while Liquefied Petroleum Gas (LPG), electricity and petrol recorded an increasing pattern. However, charcoal and fuelwood usage experienced some decline for the first three years of the survey and rose in 2019. The results also revealed that the total of 105674, 76329, 70006 and 47586 kg of carbon dioxide were emitted monthly based on the four data sets used respectively. With a total of 296064 and 303037 kg for rural and urban households respectively and on the average a household emits a total of 19 kg of carbon dioxide. With regards to the pollution-income relationship, the coefficients of income(y), (y2) and (y3) were all negative, although significant at 1% levels. Indicating that the Kuznets hypothesis was partially applicable to the Nigerian households, while educational level and sex were found to be negative but significant at 1% levels. On the contrary, the family size was positive and significant at 1% level but age of the household head was insignificant determinant of carbon dioxide emission. The paper recommended that the Nigeria government should improve electricity supply, LPG and the income of the households.

Empirical research on household carbon emissions characteristics and key impact factors in mining areas

The coal-rich mining areas are a key area to deal with climate change in China, and it is of great significance to study household carbon emissions in these areas. Based on the micro family activity survey data of 3 towns and 9 townships in the Gujiao mining area in Shanxi Province, this study took the Consumer Lifestyle Approach (CLA) as the research paradigm, used descriptive statistics and multiple regression analysis to process the data, and found that household carbon emissions characteristics were closely associated with specific resource endowment, household income level, education level and social development. Specifically, the residential behaviors and travel behaviors are the direct impact on household carbon emission characteristics. The residential behaviors have a significant positive correlation with household carbon emissions, in which residential electricity consumption accounted for nearly 41%. In the travel behaviors, private cars are the largest contributors to the carbon emissions from transportation, approaching 79%, followed by bus travel (13%) and motorcycle travel (8%). Then, aiming at the indirect effects of household carbon emissions, this study also set up three scenarios, and found that education level and policy regulation can effectively reduce carbon emissions, and family scale increases carbon emissions. According to the empirical results of this study, local governments should focus closely on two aspects: strengthening household energy conservation and emission reduction awareness and improving public infrastructure construction in the future.

Factors Controlling Urban and Rural Indirect Carbon Dioxide Emissions in Household Consumption: A Case Study in Beijing

Residential carbon dioxide emissions can be divided into a direct component caused by consumers via direct energy usage and an indirect component caused by consumers buying and using products to meet their needs, with a higher proportion caused by the latter. Based on Beijing panel data for 1993–2012, an economic boom period in China, indirect carbon dioxide emissions were separately calculated for urban and rural households using the consumer lifestyle approach (CLA) model. Then, an extended stochastic impact by regression on population, affluence, and technology (STIRPAT) model was used to analyze the influence from two aspects, social economy, and land use, with high precision. Results indicate that indirect CO2 emissions in Beijing households display a rising trend in urban areas but a slight decrease in rural areas. Technology influences and forest land are, respectively, the most important aspects of the social economy and land use. Higher population and urbanization resulted in enhanced emissions in both urban and rural areas. The Engel coefficient presented a negative correlation with indirect CO2 emissions for both rural and urban areas. Compared with urban areas, the per capita net income of rural areas restrained consumption. The consumption structure of urban residents was more biased toward the tertiary industry than that of rural residents. Although technical progress has proceeded, it cannot offset urban residents’ indirect CO2 emissions caused by the large amount and rapid growth of consumption. Regarding land use, urban construction land net primary productivity (NPP) was high and not an important factor contributing to indirect CO2 emissions. Forest and lawn primarily served a recreational function and exhibited a positive impact. Water and cultivated land offered insufficient production and thus had a negative influence. For rural residents, lawn and cultivated land production is self-sufficient. Forests offer a carbon sequence effect, and construction land expansion increased the proportion of developed area, offering a scale effect that resulted in reduced carbon emissions. Based on the results, alternative carbon emission reduction policies have been proposed for each tested influence aspect to reduce emissions, including policies for optimizing industrialization quality, constructing a medium-density city, increasing space efficiency, encouraging sustainable consumption behavior, and increasing the efficiency of energy utilization.

Indirect carbon emissions of urban households in China: Patterns, determinants and inequality

Abstract The urban household sector is considered to be an essential source of climate change. In order to obtain detailed information concerning the description of household consumption activities, this paper combined consumer lifestyle approach and input-output analysis to estimate indirect carbon emissions of urban household from 2002 to 2012. Besides, we further analysed the driving forces and inequality of indirect carbon emissions. The results showed that the total indirect carbon emissions during the study period increased rapidly, rising from 894.08 MtCO2 to 1957.03 MtCO2. ¬ More than 58% of carbon emissions were from 40% of the high income population. The highest income group, 10% of total urban households, deduced 21% of urban indirect carbon emissions. The per capita carbon emissions of different households showed a remarkable disparity, and the per capita carbon emissions of high income groups decreased from 2011 to 2012. The effective mitigation efforts should focus on reducing carbon intensity and shifting consumption structure. For high inequality consumption activities caused by rich households, rich urban households should consume less goods and services from this consumption activities. For high inequality consumption activities caused by low income households, the redistribution of income from rich to poor and low carbon intensity lifestyles may be better options to reduce carbon emissions and inequalities of urban households.

Household carbon emission characteristics and adaptive strategies for low carbon community planning

Urban communities are important sector for energy saving and emission reduction. Characterization of household carbon emission is critical to the planning of low-carbon communities. Taking data from five communities in Nanjing, China as the empirical research object, this study explores the relationship between household consumer activities and direct carbon emission of household energy consumption based on the Consumer Lifestyle Approach. Using regression analysis, we identify the characteristics of the emission and the four most significant impact factors. Adaptive low carbon strategies are further suggested as how to influence consumer activities by planning of urban communities.

Energy consumption and carbon footprint accounting of urban and rural residents in Beijing through Consumer Lifestyle Approach

Household carbon emissions are major contributors to global emissions that is increasing recognized. In China, approximately 20 million rural populations transfer to the urban areas annually, which results in a lot of new infrastructure construction and consumer requirements. This paper quantifies the numbers and trends of urban and rural resident on energy use and carbon footprint in Beijing from 1996 to 2011 by analysis of Consumer Lifestyle Approach (CLA) and carbon footprint. It provides a better understanding of complete energy consumption and carbon emissions profile in Beijing. The results show that for the Beijing residents, when direct and indirect energy consumption and CO2 emissions are taken into account, the total household energy consumption proportion compared to the city increases from 22.7% to 59.2%, and the total household CO2 emissions proportion increases from 32.2% to 68.8% in the research period. In the urbanization process, total energy consumption and carbon emissions of Beijing urban residents are significantly higher than those of rural residents. However, the transformation of a rural Beijing resident into an urban Beijing resident would not create a large difference between urban and rural areas in the per-capita energy consumption and per-capita carbon footprint. Results are assessed with respect to the available scientific literature, as well as potential available technological and policy solutions. Since the implementation that different policy instruments can mitigate carbon emissions, governments are gradually combining policy measures for the same technology. The results in this paper may help promote alternative consumption strategies in household sector which could entail more reasonable resource distribution and effective reduction of both urban and rural environmental influences.

The Scale, Structure and Influencing Factors of Total Carbon Emissions from Households in 30 Provinces of China—Based on the Extended STIRPAT Model

Household carbon emissions are important components of total carbon emissions. The consumer side of energy-saving emissions reduction is an essential factor in reducing carbon emissions. In this paper, the carbon emissions coefficient method and Consumer Lifestyle Approach (CLA) were used to calculate the total carbon emissions of households in 30 provinces of China from 2006 to 2015, and based on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the factors influencing the total carbon emissions of households were analyzed. The results indicated that, first, over the past ten years, the energy and products carbon emissions from China’s households have demonstrated a rapid growth trend and that regional distributions present obvious differences. Second, China’s energy carbon emissions due to household consumption primarily derived from the residents’ consumption of electricity and coal; China’s products household carbon emissions primarily derived from residents’ consumption of the high carbon emission categories: residences, food, transportation and communications. Third, in terms of influencing factors, the number of households in China plays a significant role in the total carbon emissions of China’s households. The ratio of children 0–14 years old and gender ratio (female = 100) are two factors that reflect the demographic structure, have significant effects on the total carbon emissions of China’s households, and are all positive. Gross Domestic Product (GDP) per capita plays a role in boosting the total carbon emissions of China’s households. The effect of the carbon emission intensity on total household carbon emissions is positive. The industrial structure (the proportion of secondary industries’ added value to the regional GDP) has curbed the growth of total carbon emissions from China’s household consumption. The results of this study provide data to support the assessment of the total carbon emissions of China’s households and provide a reasonable reference that the government can use to formulate energy-saving and emission-reduction measures.

Incorporating carbon emissions from landfills and wastewater treatment into a household emission inventory for systematically analysing household behaviour

Abstract In this paper, taking Nanchang, China, as an example, we first systematically divided household behaviour into three components: entrance (eight lifestyles), kernel (energy uses and private vehicles) and outlet, which was a concern of few scholars and contained the carbon emissions (CEs) of domestic wastewater treatment and landfills. The CEs of entrance were calculated by consumer lifestyle approach and others by Intergovernmental Panel on Climate Change (IPCC). The results showed all the CEs of entrance, kernel and outlet had increasing trend from 1998 to 2014. They were 172.65 × 104, 22.19 × 104 and 9.18 × 104 t CO2 in 1998 and increased to 283.10 × 104, 78.83 × 104 and 23.03 × 104 t CO2 in 2006 and to 458.43 × 104, 206.82 × 104 and 33.55 × 104 t CO2 in 2014. Their shares were 66%–85%, 11%–30% and 4–6%, respectively. Although the CE shares of wastewater treatment and landfills are currently modest, they will become increasingly greater in the future. Thus, it is significant to construct this new accounting frame, especially for analysing sustainable household consumption behaviour. Finally, some attributes of the new frame are clarified, and related policy implications are put forward.

Household CO<sub>2</sub> emissions: An assessment based a large sample survey in China

Household consumption and energy usage have increased with the improved per capita income and advancing living standard. CO2 emissions are also increasing from the household sector including direct CO2 emissions from energy usage and indirect CO2 emissions from household consumption. For example, household appliances, electronic products and private cars are increasingly widespread, which brings higher CO2 emissions from households. At the Copenhagen Climate Change Conference, China, as the largest developing country and largest total emitting country in the world, promised to reduce its carbon emission intensity (CO2 emissions per GDP) in the year 2020 by 40%–45% compared to 2005. China also promised to achieve its carbon emissions peak value around 2030 at Paris Climate Change Conference. The analysis of determinants of household CO2 emissions is a significant way to give effective low-carbon measures for governments and energy policy-makers. Based on survey data of household CO2 emissions (HCEs) in Mainland China, we calculated HCEs at the per household and per capita levels, and evaluated the carbon emissions structure level both in urban and rural areas in eight research regions by using IPCC Reference Approach and Input-Output Analysis and Consumer Lifestyle Approach. Our conclusions are as follows: (1) China’s HCEs are very low both from per household and per capita perspectives, at 8.05 t CO2/household and 2.47 t CO2/person, respectively. (2) There are great differences on HCEs between urban and rural areas in China. HCEs per household in urban and rural areas are 9.54 and 6.43 t CO2, respectively. HCEs per household in urban areas are 1.48 times as much as in rural areas. HCEs per capita in urban and rural areas are 3.25 and 1.78 t CO2, respectively. HCEs per capita in urban areas are 1.82 times as much as in rural areas. (3) There are great regional differences in HCEs. Southwest China has the lowest HCEs both per household and per capita, which are 6.89 t CO2/household and 2.06 t CO2/person, respectively. Shanxi-Shaanxi- Inner Mongolia Area has the greatest per household HCEs, which are 9.52 t CO2/household. Northeast China has the greatest per capita HCEs, which are 3.15 t CO2/person. (4) There are great differences in HCEs between direct and indirect forms of emissions. Comparing HCEs per household from direct energy usage and indirect household consumption, direct HCEs accounted for 23.51%, 15.80% and 35.88% in the all of China, urban areas, and rural areas, respectively. Indirect household consumption contributed to the balances of HCEs. (5) There are great differences in HCEs between different carbon emissions sources. Comparing HCEs from the point of carbon emissions, health care, heating, coal, food and electricity were the main contributors to HCEs both in the whole region, and both urban and rural areas. The results revealed the current situation and the development trend of HCEs both in urban areas and rural areas in China, as well as an analysis of both regional and urban/rural differences in HCEs. Our results show that different consuming behaviors played different roles in rising HCEs. Low-carbon policies, including enhancing the residents’ awareness on energy saving and carbon emission reduction, encouraging multi-generation members to live together and mastering green and low-carbon construction systems, were provided, which also gave data support and scientific evidence for achieving 40%–45% reduction targets in 2020 and the peak value targets around 2030.

Household carbon inequality in urban China, its sources and determinants

Designing mitigation policies for households requires knowledge of household carbon distributions. This study surveys the household carbon inequality in urban China and analyzes its sources and determinants using weighted household survey data. Different from existing literatures studying carbon inequality on the international or regional level, we focus on the household aspect and first survey its characteristics by some comparisons. By ascribing household carbon emissions calculated by the Consumer Lifestyle Approach to several consumption categories with the method of Gini coefficient decomposition, we find that residential consumption with high carbon intensity is the most important source of household carbon inequality in urban China. Food consumption and the consumption of educational, cultural and recreational services are the next largest sources because of the consumed quantities or carbon intensity. The application of Shapley decomposition shows the determinants of household carbon inequality in urban China and their contributions, which are household demographic characteristics (59.74%), household employment and income (24.31%), household burdens (8.00%), and household assets and financial plans (7.95%). The policy implications of these results are also discussed.

Direct and indirect energy consumption of rural households in China

Nowadays, energy consumption of rural household in China has been changing. Thus, it is necessary to explore the direct and indirect energy consumption of rural households, which may present an overview of rural households’ energy consumption. In this paper, the consumer lifestyle approach method is utilized to estimate the indirect energy consumption of rural household during 1998–2011. Over the study period, the direct energy consumption gradually increased, while the indirect energy consumption decreased. In 2008, the direct energy consumption exceeded the indirect one. In 2011, per capita indirect energy consumption of rural resident decreased 36 % compared to 1998. The reduction in per capita indirect energy consumption for high-income resident was the fastest. Per capita indirect energy consumption of eastern rural resident was higher than that of other regions. Per capita indirect energy consumption of Shanghai rural resident was the biggest in 1998. However, per capita indirect energy consumption of Beijing rural resident became the biggest in 2011. The center of gravity for per capita indirect energy consumption is an overall movement toward the northwest.

Indirect carbon emissions in household consumption: evidence from the urban and rural area in China

Abstract Resident energy consumption can be divided into direct and indirect parts, and the indirect part is often considered to be much more important than direct part by some scholars. In this paper, on the basis of Consumer Lifestyle Approach (CLA) and the estimation of Net Primary Productivity (NPP), Energy Ecological Footprint (EEF) of indirect energy consumption is calculated using statistical data of Chinese urban and rural areas from 1999 to 2010. And then, improved STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model is used to empirically study the influences of urbanization level, economic level, Engel coefficient, energy intensity and industry structure on indirect energy consumption. Given the consideration of potential multicollinearity, the model is estimated using partial least square (PLS) regression. The results indicate that, for urban residents, the EEF of indirect energy use is on the rise. It is positively influenced by urbanization level, per capita income and the ratio of tertiary industry, but negatively influenced by Engel coefficient and energy intensity. For rural residents, the EEF is declining. It is positively influenced by Engel coefficient, energy intensity and tertiary industry proportion, while negatively influenced by urbanization level and per capita income. Combining these empirical findings and China's specific circumstances, some policy recommendations are made.

Consumer Lifestyle Approach to Quantify CO<sub>2</sub> Emissions Caused by Domestic Washing Clothes

Consumer Lifestyle Approach to Quantify CO<sub>2</sub> Emissions Caused by Domestic Washing Clothes

Why don't consumers go internet shopping in Korea? Segmentation of consumer lifestyle approach

Due to the rapid increase of internet users, internet shopping malls in Korea are growing at a very rapid rate, though a structural vulnerability is also being revealed. About 55.8% of internet users in Korea use internet shopping malls. Therefore, to enlarge the sizes of internet shopping markets, it is paramount to attract shoppers who do not currently shop on the internet. In this regard, this study analysed the characteristics of internet shoppers and non-internet shoppers from diverse aspects based on surveys conducted on 4298 subjects residing across Korea, using 28 consumer lifestyle measurement items. The results of the analysis indicated that non-internet shoppers are married, earning relatively high incomes, and have little experience in accessing the internet. A Chi-square Automatic Interaction Detection (CHAID) analysis was conducted, and the result indicated that internet shoppers pursued the product/service information from internet shopping, but non-internet shoppers did not want to use credit cards during internet shopping. Based on the above mentioned study results, it was attempted to present detail strategies for internet shopping mall businesses to attract non-internet shoppers to internet shopping markets.

Suivi de la régénération tendineuse après prélèvement du demi-tendineux pour ligamentoplastie du ligament croisé antérieur

Based on the application of a Consumer Lifestyle Approach (CLA), this paper quantifies the direct and indirect impact of lifestyle of urban and rural residents on China's energy use and the related CO2 emissions during the period 1999–2002. The results show that approximately 26 per cent of total energy consumption and 30 per cent of CO2 emission every year are a consequence of residents’ lifestyles, and the economic activities to support these demands. For urban residents the indirect impact on energy consumption is 2.44 times greater than the direct impact. Residence; home energy use; food; and education, cultural and recreation services are the most energy-intensive and carbon-emission-intensive activities. For rural residents, the direct impact on energy consumption is 1.86 times that of the indirect, and home energy use; food; education, and cultural recreation services; and personal travel are the most energy-intensive and carbon-emission-intensive activities. This paper provides quantitative evidence for energy conservation and environmental protection focused policies. China's security for energy supply is singled out as a serious issue for government policy-makers, and we suggest that government should harmonize the relationships between stakeholders to determine rational strategies.