Negligible impacts of early COVID-19 confinement on household carbon footprints in Japan

Extension of Japan's Prefectural Emission Accounting and Enrichment of Socioeconomic Data from 1990 to 2020

With the continuous increase in carbon dioxide emissions due to human activities and the resulting severe climate issues, there is global concern about energy conservation and emission reduction. However, detailed data on energy consumption and emissions at a fine-grained scale, particularly regarding spatial dimensions and sector-specific emissions, remains insufficient and in need of refinement and timely updates. In Japan, following the Fukushima nuclear disaster, there has been a significant shift from nuclear power generation to reliance on fossil fuels across various sectors, highlighting disparities in emissions data across different regions and industries. Our work extends the emissions time series for Japan's 47 prefectures, incorporating their socioeconomic characteristics over a broader time frame and with a more detailed sectoral classification. The emissions inventory, covering the period from 1990 to 2020, is based on the consumption of the three main fossil fuels across 32 sectors, with emissions carefully allocated for regional power generation. This dataset, presented in a unified format, is expanded to include longer time scales and more detailed socioeconomic data. It is anticipated to offer crucial insights for establishing regional emission reduction targets and identifying sectoral priorities for decarbonization.

Household carbon footprints of age groups in China and socioeconomic influencing factors

China has a large fastest-aging population, which would reshape household consumption patterns and influence global CO2 emissions. This study examines global CO2 emissions driven by household consumption (i.e., household carbon footprints, HCFs) of 34 age groups in China's 30 provinces and uncovers relevant socioeconomic influencing factors. Results show that China's population aging (i.e., the proportion of the elderly population) is conducive to global CO2 emission reduction during 2011-2014. This trend is mainly due to the relatively lower per capita HCFs of the elderly (1.7 t in 2014). In contrast, the per capita HCFs of the youth group are higher (3.3 t in 2014), mainly affected by the large expenditure on residence and transportation & communication. In addition, the HCFs of all age groups have increased during 2011-2014. Per capita expenditure is the most significant driver of this increase. The decline in CO2 emission intensity makes the largest contribution to reducing the HCFs of the youth group. For the aged group, expenditure structure change is the largest contributor to HCFs reduction. These findings reveal the differentiated impacts of China's household consumption by age on global CO2 emissions. This study lays the scientific foundation for deriving amelioration policies and achieving emission reduction targets in the process of population aging.

Mixed diets can meet nutrient requirements with lower carbon footprints

Achieving sustainable dietary change is essential for safeguarding human and environmental health. However, dietary recommendations based on broad food groups may not accurately reflect real-world realities because individuals select and consume dishes with multiple food items influenced by diverse context-specific factors. Therefore, here we explored the sustainability trade-offs of dietary choices at the dish level through an optimization modeling approach tested in Japan. We estimated the nutritional quality, price, and carbon footprint of major Japanese dishes and examined 16 dietary scenarios to identify options that meet the nutritional requirements and minimize carbon footprint. Overall, mixed diets contain more combinations of dishes that meet nutritional requirements with lower carbon footprints compared to more restrictive dietary scenarios. We argue that the approach developed here enables a better understanding of dietary trade-offs, complements existing methods, and helps identify sustainable diets by offering nuanced information at the national and sub-national levels.

The pandemic effect on GHG emission variation at the sub-national level and translation into policy opportunities

Greenhouse gas (GHG) emissions inventories are commonly compiled at country level to monitor national progress towards nationally or internationally agreed targets. While they can support national climate change mitigation strategies, accounting for the intra-national heterogeneity of a country can draw different conclusions directly linked to the socio-economic and environmental sub-national context. This means that more refined and accurate policies and mitigation strategies can be designed when supported by GHG inventories at sub-national scale. The differences between sub-national territorial emissive behavior can be revealed by subjecting different territories to the same stress factors. A complete GHG emissions inventory, based on the Intergovernmental Panel on Climate Change (IPCC) Guidelines, is compiled for three diverse administrative territories, in terms of scale, socio-economic contexts, and environmental conditions. By selecting three diverse sub-national contexts belonging to the same national territory - Italy - the analysis provides highly detailed information on the emissive status and behavior and delivers insights that national inventories fail to provide. The COVID-19 pandemic is considered as a stress factor; therefore, the reference years are 2019 and 2020 during which GHG emissions are detected. The study will test the capacity of sub-national GHG emission inventories, compiled by scaling the IPCC methodology to the sub-national level, to detect such differences through the lens of the pandemic. This allows obtaining detailed information and linking the pandemic effect to the GHG emissions of particular activities, which can inspire effective sub-national context-specific mitigation actions. Furthermore, we show that environmental and economic metrics are not as strictly coupled as they would appear at national level.

Japanese urban household carbon footprints during early-stage COVID-19 pandemic were consistent with those over the past decade

As urbanization accelerates worldwide, substantial energy and services are required to meet the demand from cities, making cities major contributors to adverse environmental consequences. To bridge the knowledge gap in the absence of fine-grained city-level climate protection measures due to data availability and accuracy, this study provides a detailed carbon emission inventory for analyzing the monthly fluctuations based on citizens' daily consumption behaviors. Here, carbon emissions embodied in approximately 500 household consumption items were calculated in 47 prefectural-level cities in Japan from 2011 to June 2021. We analyzed the results considering the regional, seasonal, demand, and emission way-specific aspects, and compared the emission before and during the COVID-19 pandemic. Notably, the carbon footprints during the pandemic were consistent with the previous level despite downtrends in specific categories. This study provides an example of utilizing city-level emission data to improve household green consumption behavior as references for enriching city-level decarbonization paths.

Towards carbon neutrality: what has been done and what needs to be done for carbon emission reduction?

Carbon emissions embodied in anthropogenic activities represent the major cause of global warming. Countries, regions, and cities have implemented comprehensive, multi-level and multi-scale measures to reduce emissions and move towards carbon neutrality. The demand for carbon emission reduction (CER) is made more challenging by different geographical locations, country-owned natural resources, and economic development stages. The main objectives of this paper are to conduct a bibliometric analysis to map the frontiers and directions of CER and to explore the paths and development models of CER from the perspective of spatio-temporal, multi-scale, multi-sectoral, and multi-responsible subjects. This study reveals that carbon emission evaluation and prediction, correlation and causal relationship analysis, and CER-related policy simulation and optimization are the most critical hotspots. Additionally, we point out the shortcomings of and future developments for the three study dimensions above. The bibliometric analysis also highlights the fact that a cooperative global value chain as well as amendable policies and mechanisms for CER will help with climate change mitigation and adaptation through the use of advanced carbon capture and storage technologies. We review the technical measures for and policy responses to CER adopted by different countries and industries at the theoretical and practical levels and provide new recommendations. Our work provides important information for climate actions in different countries and sectors and for developing more effective CER strategies and policies.

Personal GHG emissions accounting and the driving forces decomposition in the past 10 years

Personal greenhouse gas (P_GHG) emissions were crucial for achieving carbon peak and neutrality targets. The accounting methodology and driving forces identification of P_GHG emissions were helpful for the quantification and the reduction of the P_GHG emissions. In this study, the methodology of P_GHG emissions was developed from resource obtaining to waste disposal, and the variations of Shanghainese P_GHG emissions from 2010 to 2020 were evaluated, with the driving forces analysis based on Logarithmic Mean Divisia Index (LMDI) model. It showed that the emissions decreased from 3796.05 (2010) to 3046.87 kg carbon dioxides (CO₂) (2014) and then increased to 3411.35 kg CO₂ (2018). The emissions from consumptions accounted for around 62.1% of the total emissions, and that from waste disposal were around 3.1%, which were neglected in most previous studies. The P_GHG emissions decreased by around 0.53 kg CO₂ (2019) and 405.86 kg CO₂ (2020) compared to 2018 and 2019, respectively, which were mainly affected by the waste forced source separation policy and the COVID-19 pandemic. The income level and consumption GHG intensity were two key factors influencing the contractively of GHG emissions from consumption, with the contributing rate of 169.3% and − 188.1%, respectively. Energy consumption was the main factor contributing to the growth of the direct GHG emissions (296.4%), and the energy GHG emission factor was the main factor in suppressing it (− 92.2%). Green consumption, low carbon lifestyles, green levy programs, and energy structure optimization were suggested to reduce the P_GHG emissions.

● The boundary of P_GHG emissions developed from resource obtaining to waste disposal.

● Shanghainese P_GHG emissions varied from 3004.64 to 3796.05 kgCO₂ in 2010-2020.

● Around 405.86 kg CO₂ decreased with the reduced consumption by COVID-19 lockdown.

● Energy consumption was the main contributor to DP_GHG emissions (296.4%) increase.

● The GHG intensity was the main contributor to IP_GHG emissions reduction (− 188.1%).

Does protectionism improve environment of developing countries? A perspective of environmental efficiency assessment

Past studies related to embodied pollutant accounting reported that free trade has increased the environmental pollution of developing economies, because the developed countries "outsource" their pollutants to developing nations. The COVID-19 pandemic has stimulated the rise of the most serious protectionism after World War II. This study is aimed to discuss whether protectionism improve the environment in developing countries by developing a comprehensive evaluation model, which integrates multi-regional input-output (MRIO), data envelopment analysis (DEA), and scenario analysis. We revealed the role of protectionism from two perspectives: the single impact on pollutant emissions and the comprehensive impact on environmental efficiency. Specifically, the capital inputs, labor inputs, energy consumption, economic output, carbon dioxide, sulfur dioxide and nitrogen oxides emissions related to global trade activities were simulated based on the MRIO. And then, sector-level trade environmental efficiency was computed by intergrading the MRIO and DEA using a non-radial directional distance function. Finally, the environmental efficiency of both developing and developed countries under two scenarios with and without trade were estimated. The results confirmed that trade has increased the CO₂, SO₂ and NO_X emissions of developing economies by 12.9%, 9.8% and 12.3%, and has reduced that of developed economies by 6.0%, 29.4% and 21.2%, respectively. However, the results also uncovered that the environmental efficiency of developing and developed economies was dropped by 3% and 5%, respectively, under no-trade scenario. We contend that protectionism is not conducive to the sustainable development of developing countries because it lowers their environmental efficiency, although it may reduce their territorial pollutant emissions. For developed countries, the single impact of protectionism on pollutant emission reduction and the comprehensive impact on environmental efficiency are both negative.

A global overview of developments of urban and rural household GHG footprints from 2005 to 2015

Household greenhouse-gas footprints (HGFs) are an important source of global emissions but can vary widely between urban and rural areas. These differences are important during the ongoing rapid, global, urbanization process. We provide a global overview of HGFs considering this urban-rural divide. We include 16 global regions, representing 80% of HGFs and analyze the drivers of urban and rural HGFs between 2005 and 2015. We do this by linking multi-regional input-output (MRIO) tables with household consumption surveys (HCSs) from 43 regions. Urban HGFs from high-income regions continue to dominate, at 75% of total HGFs over 2010-2015. However, we find a significant increase of rural HGFs (at 1% yr^-1), reflecting a convergent trend between urban and rural HGFs. High-income regions were responsible for the majority of urban HGFs (USA: 27.8% and EU: 18.7% in 2015), primarily from transport and services, while rural HGFs were predominately driven in emerging regions (China: 24% and India: 21.8% in 2015) mainly driven by food and housing. We find that improving emission intensities do not offset the increase in HGFs from increasing consumption and population during the period. A broad transition of expenditure from food to housing in rural areas and to transport in urban areas highlights the importance of reducing the emission intensities of food, housing, and transportation. Counterintuitively, urbanization increased HGFs in emerging regions, resulting in a >1% increase in China, Indonesia, India and Mexico over the period, due to large migrations of people moving from rural to urban areas.