Enlarged carbon footprint inequality considering household time use pattern

Examining household carbon emissions through a supply chain perspective reveals the climate impact of consumption behaviors and variations across societal structures and features. Despite the evident and expanding environmental inequality, strategies for its mitigation and prioritization remain debated. This study investigates the origins of carbon emission inequalities from household consumption, using Japan as a case study, a society characterized by aging demographics and comparatively equal income redistribution. By quantitatively analyzing household carbon footprints, we observe a U-shaped distribution in emissions as income levels increase. Notably, the carbon footprint sizes are strikingly similar between the lowest and highest income groups, yet inequalities emerge in education and investments in future generations. Integrating these findings, this study further conducts a scenario analysis to project shifts in future low-carbon lifestyles, indicating that middle-income groups are more prone to achieving personal-level decarbonization. This projection is vital in understanding how to effectively address carbon footprint inequalities, especially considering the entrenched preferences in wealthier demographics for investing in future generations.


Introduction
Global warming has given rise to various negative externalities, primarily driven by anthropogenic activities (Edenhofer 2015, Yue and Gao 2018, Yang et al 2022).Over the past two decades, there has been an upsurge in household consumption, as global supply chain-related trade has fostered economic growth and improved living standards for residents (Jiang andGreen 2017, Bank 2019).In fact, as the primary final demand sector, household consumption accounts for more than 60% of goods produced and services provided (Long et al 2021, Ministry of Economy 2022), prompting numerous calls to action for lifestyle changes that foster more sustainable practices and stimulate greener production, ultimately creating a virtuous cycle (Shigetomi et al 2021).
Consequently, household decarbonization has been recognized as a pivotal opportunity for climate targets (UNFCCC 2015, Rogelj et al 2016), which renders sustainable lifestyles essential.
Households comprise individuals with diverse consumption behaviors, influenced by factors such as wealth, personality, education level, ethnicity, and cultural background.Although it is necessary to deepen our understanding of consumption patterns across various categories, capturing the complexity of consumers' characteristics and living habits remains a challenge, and household lifestyles can be multi-dimensional.Previous research has explored the efficient decarbonization of household consumption through policy constraints ( et al 2022).Nevertheless, before implementing these measures, fundamental questions about residents' consumption behavior, including what they do, where, when, and how long they engage in activities, as well as the types and amounts of resources they utilize, need to be addressed (Yu et al 2020).In other words, the allocation of time use and lifestyle choices within households are connected to environmental issues.
Similar to energy, time is also a scarce resource utilized by individuals to cultivate diverse lifestyles for fulfilling varied demands.Hence, incorporating time allocation and its distinctions among different groups into the understanding of household lifestyles jointly is pivotal (Brenc ˇic ˇand Young 2009, Druckman et al 2012, Jalas and Juntunen 2015, Wiedenhofer et al 2018, Yu et al 2019).Moreover, considering that the production of household goods and services requires the input of resources and energy (Brenc ˇic ˇand Young 2009), investigating time use in daily life can elucidate the impact of time squeezes versus prosperity on carbon footprints (De Lauretis et al 2017, Wiedenhofer et al 2018, Jiang et al 2022).Besides, diverse levels of household engagement in a spectrum of activities, as end-users of energy and resources, give rise to an unequal distribution of ultimate emissions.The determinants of this distribution include essential living demands, as well as other more discretionary purposes (Rybski et al 2017, Adachi 2019, FAO 2020).For instance, necessities such as food, shelter, healthcare, and education contrast with non-essential pursuits like hobbies, raising pets, or studying at private schools.
In other previous attempts, potential timesaving technologies for household decarbonization have been discussed by tracing lifestyle changes (Druckman et al 2012, Jalas and Juntunen 2015, De Lauretis et al 2017).For example, Smetschka et al (2019) investigated how time matters in daily emissions in Austria from the view of embodied emission.Notwithstanding these concerted efforts emphasizing the imperative of incorporating the time dimension into household decarbonization measurements, challenges persist.A primary concern is the accurate quantification of the carbon footprints of consumed goods, including durable items.Due to data constraints at times, analyses of time use often do not delve into targeted populations, such as individuals belonging to distinct income strata (Smetschka et al 2019, Yu et al 2019).Concurrently, there is a pressing need for a more elaborate examination of inter-group inequalities, particularly regarding how economic factors exert influence on time management and carbon footprints.
Meanwhile, the inequality in consumption patterns and climate among households is recognized as one of the major threats to contemporary standards of living, peace, and democracy (D'Alessandro et al 2020, Oswald et al 2020).Data from the United Nations Development Programme indicates that in 2016, 22% of global income was received by the top 1% of the global population, in stark contrast to the bottom 50% which only received 10% of income.Furthermore, projections suggest that by 2050, the top 1% population could reach 39% of global income (UN 2015).Apart from unequal social resource allocation, inequality is pointed out to be linked with contributions and sufferings in terms of climate change (Hubacek et al 2017a), with the top 10% of global income earners being responsible for 36% of world carbon emissions, whereas only 4% is generated by the poorest 12% (Hubacek et al 2017b).Importantly, disparities in wealth affect household lifestyles, which also overweight other demographic features that contribute to marked differences between groups.
Building on previous work (Long et al 2022), which explored carbon footprint differentiation within the Japanese residential sector due to income divergences and in/out-of-time allocation, this study distinguishes itself by delving into detailed drivers of such inequality and further divided in/out-ofhome time into 18 activities.Specifically, by linking the Environmental Extended Input-output Model (EEIO) with household monetary consumption, we analyze the carbon footprints from the consumption of 504 items covering basic living demands to discretionary activities.Updated datasets are adopted to estimate the carbon footprint in terms of CO 2 equivalent as well as emission intensity.Then, household carbon footprints are connected with daily activities by minute to investigate the time-based emission intensity.Unlike previous research, the role of education and future-generation investments in the exacerbation of these disparities is revealed.Additionally, future decarbonization pathways at the individual level are projected to gauge the extent to which an increased adoption rate of low-carbon lifestyles would contribute to achieving the 1.5

The framework of household carbon footprint evaluation
We apply the EEIO to estimate the household carbon emission intensity.Originating from the economic input-output (IO) model, EEIO is considered an extension of IO by connecting environmental impact to monetary flows.The basic equation of an economy is described as: where X is the vector of output, I is the identity matrix, A is the input coefficient matrix, and F is the vector of final demand, consisting of consumption, investment, and export.To note, due to the lack of sufficient data on imported products, the Leontief Matrix is transformed to type, which indicates only the domestic products is considered.Here, M indicates the imports column matrix, which is calculated by equation ( 2) to represent the import portion of the direct requirement coefficient: where e i and m i indicate the export and import of item i, therefore, (x i − e i + m i ) is known as the total supply to the domestic market.Then, using the diagonal matrix M to express the import coefficient, the carbon footprint intensity of domestic producer goods is shown as here, d and e indicate the direct and indirect carbon footprint intensity of per unit production, respectively.And solving equation (3), the embodied carbon footprint intensity is shown as: Connected with household monetary consumption, the embodied carbon footprint generated by household consumption can be expressed as: where Therefore, the following allocation is conducted to distinguish the energy-related emissions considering Japanese residents' living habits.All the household consumed items are classified into different activities by considering the using purpose.Semi-durable goods such as electricity, and natural gas are classified as follows.First, electricity consumption is multi-purpose while using.The percentage of household electricity consumption for a different purpose is derived from the Handbook of Japan's & World Energy & Economic Statistics (EDMC 2019) released by the Institute of Energy Economics of Japan.Shown as in table 1, lighting, appliance, hot water supply, and heating are found as major terminal purposes.The hot water supply here is identified as showing activity considering its major purpose.Electricity consumed by kitchen use is classified as cooking.Cooling, heating, lighting, and other appliance use are allocated to all the items occurring at home.Not just electricity, other accommodation-related items that cannot be classified by daily activities are allocated to in-home activities.Natural gas, which includes both city gas and LNG, is allocated to showing and cooking activities.The allocation ratio is 76% (Hot water supply) and 24% (Kitchen), which is referred from the Agency for Natural Resources and Energy and previous research (SUZUKI and Tanabe 2016, Agency for Natural Resources and Energy 2020).Besides, in a Here, lighting and other appliance indicates lighting, electronic bidet, washing machine, clothes dryer, futon dryer etc.

Figure 1.
Sector allocation flowchart and process.Prior to allocation, a total of 504 sectors are present, encompassing both allocation sectors (which include durable or semi-durable goods that do not directly correspond to daily activities), in-home sectors (segments that accommodate the allocated carbon footprints), and other sectors.Following the allocation of 26 sectors to 281 in-home activity sectors, a cumulative total of 487 sectors emerged as a result of this process.
2015, 18% of household water usage was for cooking, and other purposes including toilet, showing, and washing4 are all allocated to personal stuff (In-home activities).Second, durable goods such as furniture, interior decorations, curtains, floor covering, and rents (for dwelling and land) are considered necessary to conduct in-home activities.Therefore, although that consumption can be directly connected to certain behaviors, the correlated consumption is allocated to all the in-home activities5 .The aforementioned activities are classified as activities in-home (relatively higher likelihood to occur at home) and outof-home (relatively higher likelihood to occur outside the home) to allocate their carbon footprints reasonably (see figures 1 and S1, supplementary data).

Unequal carbon footprints by household income-based groups
In this research endeavor, the disparity in carbon footprints across income groups is quantified through the utilization of the Gini index.The Gini index is a statistical metric that assesses the distribution of a certain parameter, often employed to gauge disparities within populations or income brackets.For this study, the Gini index is applied to the carbon footprints specific to each income group.The Gini index of income-group-specific carbon footprints is calculated based on: where x n indicates the carbon footprints among income groups (n = 5), µ = (x 1 + x 2 + x 3 + . . .x n ) /n, and α and β refer to absolute mean difference and relative mean difference, respectively.Households are divided into quantile groups based on the household yearly income, including Low (below 2440 000 JPY), Low-mid (2440 000-3590 000 JPY), Mid (3590 000-5000 000 JPY), Mid-high (5000 000-7310 000 JPY) and High (Above 7310 000 JPY).  S1.Importantly, we need to point out that the activities evaluated encapsulate overarching household demands, not mere individual consumables.For instance, 'Dining' comprises all constituents of eating, ranging from food items, and beverages, to related energy consumption and waste management.

Evaluating the impact of lifestyle changes on future carbon footprints
Figure 2(b) presents a waterfall chart of the activities contributing to carbon footprint gaps, showing that 'Personal stuff ' , 'Dining' , and 'Rest and relaxation' significantly drive the disparity between low-income and middle-income groups, with table S2 provides the estimation results of specific contributions of various daily activities.Conversely, 'Transport and moving' is identified as the main activity that narrows the gap between these two groups.For middleincome versus high-income households, the increment in footprints is largely due to personal mobility and education expenditures.
Furthermore, incorporating the data from tables S3 and S4, we assess the carbon footprint variations associated with household consumption types, shedding light on the role of basic living demand and other auxiliary demands.Figure 2(c) shows the carbon footprint variation from low to high-income groups by aggregating household consumptions into two types of demands, namely the basic living demand (e.g.sleep, personal stuff) and other demands (e.g.Schoolwork, child care).Interestingly, the carbon footprints related to basic living demand are equally distributed among income groups.On the contrary, figure 2(d) shows that auxiliary demands, such as leisure and social activities, are where disparities emerge.This suggests that carbon footprint inequality stems more from discretionary spending than from essential needs.
Delving into specifics, figure 3(a) identifies major contributors within the 'Dining' category, which include Energy use (20%), Cooked food (13.5%),Grain (8.7%), Vegetables (8.6%), and Eating out (8.2%).The high-income group's predilection for meat and frequent dining out, accentuates its footprint.Meanwhile, lower income groups manifest heightened carbon footprints from energy use and staple foods, underscoring a dietary shift with income escalation.In terms of transport, figure 3(b) shows that the high-income and middle-high-income groups have the highest carbon footprint from gasoline use, automobile purchases, and the utilization of public transport, reflecting increased mobility with higher income.Conversely, the low-income group demonstrates the lowest carbon footprint in these categories due to reduced utilization of both personal and public transportation.Notably, 'Personal stuff ' is the primary factor in enlarging the carbon footprint gap.In figure 3(c), the high-income group shows the highest carbon footprint in clothing, footwear, beauty products, and services than other groups.In contrast, the low-income group has the highest expenditure on hot water supply in terms of both electricity and gas use, suggesting higher utility costs or less energyefficient appliances.As income increases, there's a noticeable decrease in these expenses, likely reflecting more energy-efficient choices or lifestyle preferences for out-of-home services.

Time-based dimension observations enlarged inequality
In this segment of the study, an emphasis is placed on examining the role of time use in exacerbating carbon footprint inequalities.As Smetschka et al  Consequently, we measured the quantile income groups' carbon footprint intensity from the time dimension and mapped it with 18 types of daily activities, the results of which are displayed in figure 4 (estimation results can be referred to in table S5).Different from previous energy intensities such as CO 2 per unit of production or monetary scale, we use the income-based per-minute consumption to quantify the lifestyle formation and its inner correlation and try to discover the concealed inequality.Moreover, before jumping into the result, we should note that Japan is one of the most developed countries as well as one the most equal countries economically.According to the Ministry of Health, Labor and Welfare of Japan, the Gini index is found to stay at 0.31 after income redistribution, tax, and performance in kind (Providing public assistance, services or any other means other than by providing performance in money.) in 2014 and 2017 (MHLF 2017).Japan shows a relatively low level (around 0.3) in residential income Gini Index after social income retribution (MHLF 2017) and slightly unbalanced regional or age-based carbon footprints (Shigetomi et al 2014, Long et al 2019).
Activities with a Gini index greater than 0.35, as shown in figure 4(a), are mainly related to schoolwork, reflecting disparities in education-related consumption.Wealthier households tend to choose private schools, contributing to higher carbon footprints due to factors like extracurricular activities.Luxury goods in the 'Personal stuff ' category also exhibit inequality among income groups.However, it is important to note that luxury consumption is not the primary driver of environmental inequality; education choices play a more significant role.Carbon footprint disparities related to schoolwork are amplified among income groups.Figures 4(b) and (c) delve deeper into schoolwork, classified by education stages and types.Apart from carbon footprints from preschool education and sanitation, the Gini index remains above 0.5 from elementary education through college and university.Specifically, elementary education, which includes both public and private school fees, sees the Gini index peak at 0.57.This signifies that the carbon footprint inequality begins as early as the elementary phase and continues to escalate through university.To note, 'Other education' represents Japanese Senshu (Specialization) University, and 'shadow education' refers to feebased supplementary education outside of traditional school.
Figure 4(c) further dissects the carbon footprints from education by type.Interestingly, alongside private schooling, remedial school fees also contribute to the widening inequality, as wealthier households tend to spend more on education-related services such as entrance exam preparation for high schools and universities.This trend is common in various Asian countries and regions like mainland China, Korea, Japan, etc. where competition in education has spilled over from traditional schools to other educational institutions requiring additional payment (Yamamoto and Brinton 2010, Byun et al 2012, Cheng 2017).Consequently, correlated consumption has been found to enlarge social environmental inequality from the consumption perspective.However, it should be acknowledged that education, while contributing to disparities in carbon footprints within current circumstances, also plays a pivotal role in cultivating environmental awareness and sustainable consumption practices among the next generation (Zsóka et al 2013, Ardoin et al 2020).
In addition to using the Gini index to measure the degree of inequality, the carbon intensities in terms of time use are also presented, revealing trends in carbon footprints per unit of time, as presented in figure 4(d).Here, 12 of 18 household activities are observed with inequality enlargement by time unit intensity, which can generally demonstrate a wide social inequality is happening in Japan considering environmental impact by involving time dimension.Notably, with respect to 'Schoolwork' and 'Child care' , the highest-income group substantially exceeds the carbon footprint of the lowest-income group, and the utilization of the gCO 2 -per capita/min metric highlights the pivotal role of time in evaluating emission intensity.Consequently, this approach not only elucidates which activities yield higher carbon footprints but also identifies those with greater emission intensity, denoting higher carbon footprints per unit of time.
The per-time-unit carbon footprints for 18 activities differentiated by income are presented in figure S2, supplementary data.Per-time-unit carbon footprints vary across income groups (detailed data on per-time-unit and the deviation from the average carbon footprint across 18 daily activities are provided in tables S6 and S7).Low-income households have higher carbon footprints in leisure and personal errands due to limited access to energyefficient options and economic constraints.Middleincome groups show a more even distribution, with a focus on formal education.Middle-high-income groups make eco-friendly choices but have higher carbon footprints in leisure and social activities.High-income households prioritize sustainability but contribute more carbon emissions in education, reflecting resource-intensive practices and wealth disparities.Despite relatively balanced overall carbon footprints across incomes in Japan, wealthier households invest more in health and child-rearing activities, impacting carbon emissions.

Lifestyle decarbonization of middle-income groups is most promising in reaching climate targets
The Paris Agreement has underlined the ambitious 1.5 • C climate target.Based on prior research, to attain the goals of the Paris Agreement, annual per capita carbon footprint goals for the years 2030, 2040, and 2050 have been established at 3.2 tCO 2 e, 2.2 tCO 2 e, and 1.5 tCO 2 e, respectively (Lettenmeier et al 2019).Given the decarbonization potential of household lifestyle change, an assessment of its impact on future climate targets has been conducted as figure 5, with Panels figures 5(a)-(e) delineating the projected outcomes from 2025 to 2050 for different income groups.
Delving into the findings, different income groups showcase analogous decarbonization trends at varying rates of adoption of low-carbon lifestyles (see table S8).Upon dissecting the data, a consistent trend emerges across income groups: higher adoption rates of low-carbon lifestyles correlate with reduced individual carbon footprints.Moreover, we have demarcated the intersections corresponding to the adoption rates and the 1.5 • C global warming targets, signifying the levels of adoption required to align with these ambitious climate objectives.For example, both Panels figure 5(a) (Low-Income) and figure 5(e) (High-Income) suggest that to meet the per capita emission target of 3.2 t CO 2 by 2030, an adoption rate exceeding 30% is vital.In contrast, the Low-Middle, Middle, and Middle-High income brackets can achieve this with a mere 15% adoption rate.It is particularly noteworthy that for the Middle-High-Income households, this goal is most attainable.This trend holds through to 2040, with middle-income groups maintaining lower necessary adoption rates than their wealthier and poorer counterparts.
By 2050, to reach the stringent 1.5 tCO 2 e per capita target, all groups must surpass a 30% adoption rate.The projections indicate that lower-income groups face a tougher challenge in achieving the 1.5 • C target, even at higher adoption rates.This is partly due to the higher resource-intensive activities, like private education, which are prevalent among wealthier households.It also reflects the inherent difficulty in expecting significant lifestyle reductions in high-income groups.
Additionally, these projections have not accounted for potential future income fluctuations among these groups, and the per capita carbon footprint under the 1.5 • C target integrated here includes the introduction of carbon capture and storage technologies.The sensitivity of these targets to negative emission technologies is significant.Absent these technologies, the targets become markedly stringent: 2.5, 1.4, and 0.7 tCO 2 e for 2030, 2040, and 2050, respectively.

Discussion
Our study offers novel insights into the dynamics of household carbon footprints in Japan, accentuating the role of time-use patterns and daily activity structures across different income groups.By integrating comprehensive data on dining, transportation, personal items, and educational investments, our analysis deepens the understanding of carbon footprint disparities, advancing the existing literature in this field.
According to findings with observations from China (Zhang and Zhao 2014, Liang et al 2019) and the U.S. (Jorgenson et al 2017), household carbon footprints might increase with income.This is primarily attributable to the higher purchasing power of affluent households, which tends to lean towards the consumption of more expensive, sometimes even luxurious, products and services (Moran et al 2018, Fremstad andPaul 2019).However, the total household carbon footprints in Japan appear uniformly distributed, with distinct variations at the sectoral and activity-specific levels.A unique Ushaped trend was identified, whereby both the lowest and highest income groups exhibit elevated carbon footprints.In Japan's circumstances, a divergent pattern of household decarbonization is indicated.A primary factor that can explain this anomaly is Japan's robust income redistribution mechanisms, which have facilitated a degree of social equality and ensured a relatively consistent standard of living across income strata (Davis et al 2014, Yamamura 2014).This uniformity is reflected in the nearly equivalent carbon footprints from basic needs such as food, accommodation, and transportation across different income groups.
Notably, despite their constrained lifestyle, the lowest-income segment in Japan produces a carbon footprint comparable to higher-income groups.
To demonstrate this point, we can find that carbon footprints from basic living demands stay at a comparatively equal level.In other words, higherincome groups do not mean, at least not the only groups, who should take the largest responsibility for household decarbonization.Furthermore, which is different from the previous observation, the lowest income groups in Japan are emitting the same level as the higher income groups although they do not enjoy a decent lifestyle.Therefore, Japan's household carbon footprints are comparatively equally distributed among income groups.
Another aspect is to find out the reason behind the comparably high carbon footprint of the lowest income group.The lowest income groups in Japan manifest significant carbon footprints, particularly in the realms of dining (e.g. the relative consumption of grains, bread, and noodles) and personal stuff, predominantly energy use.Our observations pinpoint their substantial direct emissions associated with shelter energy consumption and other primary household activities.While the nuances of this trend require intricate detailing, the prevailing data underscores the urgency of developing targeted interventions for this income group.In the meantime, as dietary demand produces the largest carbon footprint in the total carbon footprints across multiple demand categories, future policies in Japan should prioritize decarbonization from residential meals.This involves a comprehensive view of the entire food supply chain, from sourcing raw materials to cooking.Emphasizing the significance of sustainable eating habits, it is also crucial to advocate for environmentally-friendly food production and distribution methods.For all income groups in Japan, the reduction of food waste and the adoption of high-efficiency cooking appliances stand out as pivotal measures for household decarbonization.
In this study, we found that the middleand middle-high-income groups as the current beacon of low-carbon footprint.Not only do they presently exhibit a minimal carbon footprint among the observed groups, but their potential for future reductions is exceptionally promising.Intriguingly, these groups possess the adaptability and financial flexibility to seamlessly transition towards sustainable lifestyles without necessitating drastic changes.Therefore, we posit that middle-income households are not merely passive actors in the fight against climate change; they could very well spearhead Japan's decarbonization efforts.
Another notable finding is the carbon footprint inequalities, especially among high-income households driven by the impact of educational investments.Since we introduce an integration of timeuse data with carbon footprints, the disproportionate emissions tied to education-related activities reveal how high-income households' educational investments amplify ecological inequalities.Our analysis elucidates that Japan's future decarbonization pathway and mitigation policy should be discussed separately from 'carbon footprint inequality mitigation' and 'carbon footprint volume mitigation' .It is salient to note that in the Japanese context, merely mitigating carbon footprint inequality does not directly translate to efficacious household decarbonization, especially when the most pronounced inequality contributor is tied to demands on next-generation education and elderly care.Entrenched lock-in effects regarding behavioral patterns in different income groups can pose barriers to decarbonization.This nuanced view sets the stage for future research to explore whether high-income households in countries with egalitarian education systems exhibit similar carbon footprint patterns in comparison to the Asia-Pacific region given its education culture of extracurricular tutoring.Such comparative studies could yield insights into the interplay between public education provision and household carbon emissions.
In conclusion, while it is possible to achieve household decarbonization by adjusting predominant lifestyles, narrowing the inequality gap among household segments remains a significant challenge.Therefore, as Japan maps out its future decarbonization strategies, a critical decision emerges: should the primary focus be on reducing inequality or total carbon footprints?For timely achievement of decarbonization targets, prioritizing middle-income groups appears promising, as lifestyle adaptations within these groups are both more feasible and affordable.

Figure 2 .
Figure 2. Per capita carbon footprints embodied in daily activities.(a): activity-based carbon footprints across income groups in Japan.(b): contributions of varied daily activities to carbon footprint disparities among income groups.(c), (d): proportional distribution of (c) basic demand and (d) other demand among different income groups.
(2019) (Smetschka et al 2019) and Druckman et al (2012) (Druckman et al 2012) have mentioned, how people arrange their time matters in their associated carbon footprints embodied in consumption, casting light on the genesis of inequality.In other words, the time dimension can provide clues for dealing with the unequal carbon footprint distribution since time is a limited resource akin to energy.

Figure 4 .
Figure 4. Dissecting Carbon Footprint Inequities among Various Income Groups.(a) Activities with a Gini index greater than 0.35.Items in Schoolwork, Personal stuff, and Child care are marked in red, yellow, and blue, respectively, considering their high occurrence frequency in the list.Detailed information on carbon footprints by (b) education stage and (c) education types, with stationary as the reference.For both sub-figures, the left y-axis measures the per capita carbon footprint per day, while the right y-axis signifies the Gini index.Distinctly colored bars represent the CF values of varying quantile income groups, whereas the black dotted line traces the variations in the Gini index.(d) Gini Indices of Activities Across Income Groups with and without Time-Use Normalization.

Figure 5 .
Figure 5. Assessing the Potential of Low-Carbon Lifestyle Changes for Achieving the 1.5 • C Climate Target.Carbon reduction pathways for (a) Low-Income, (b) Low-Middle-Income, (c) Middle-Income, (d) Middle-High-Income, and (e) High-Income groups under different low-carbon lifestyle adoption rates.

Table 1 .
Percentage of household electricity consumption for different purposes.

. Result 3.1. Neglectable carbon footprint gap among income groups in Japan
To understand the extent to which lifestyle changes can contribute to global climate warming mitigation efforts, this study leveraged insights from prior research (Akenji et al 2019) on the aggregated reduction impacts of low-carbon options in Japan under the temperature goals of the Paris Agreement.
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