The transition patterns of rural household carbon footprint in China

Climate change and population aging are inevitably the two most significant global challenges. Senior population growth in China is accompanied by an increase in consumption-induced carbon emissions (CCEs). The study's contribution of a deeper understanding of the intertemporal relationship between senior characteristics and multi-category CCEs provides the theoretical foundation for the formulation of mitigation strategies. This study utilizes panel data obtained from the China Health and Retirement Longitudinal Study (CHARLS) surveys in 2013, 2015, and 2018 to compute the per capita CCEs for elderly adults across eight major consumption categories. It also exposes the dynamic influences of individual characteristics on CCEs by estimating the mixed effects model. Based on the findings, accommodation, transportation and communication, and food comprise the top three categories of CCEs. Furthermore, seniors' consumption preferences have gradually drifted from basic necessities to pleasurable experiences and healthcare services. Notably, seniors' characteristics (e.g., income, health, education, marital status, residential type, and the degree of urbanization) exert distinctively dynamic impacts on each type of CCEs over time. In pursuit of a greener aging society, this study proposes various implementation strategies for mitigating CCEs among different actors (the government, community, manufacturers, and older individuals) in light of the captured intricate mechanism. 

Towards a greener aging society: A dynamic and multilevel analysis of consumption carbon emissions among China's aging population

With the increasing contribution of household carbon footprint to the global carbon footprint, household carbon footprint as a critical component of future carbon reduction has become a research hotspot to mitigate global warming and maintain sustainable economic development. The Web of Science (WOS) database is the literature data source. The literature on household carbon footprint is analyzed with the help of the visualization software CiteSpace. The collected data are analyzed using bibliometric analysis tools for knowledge base analysis, cooperative network analysis, and knowledge evolution analysis to grasp the developmental pulse of household carbon footprint. The findings show that the co-citation analysis reveals that household carbon footprint research has a clear knowledge base and shows a clear trend over time. The classic literature lays the foundation for subsequent diversified and interdisciplinary articles. The subsequent research hotspots show apparent inheritance and development characteristics, with many diversified and interdisciplinary studies appearing after 2008. Based on the three-level cooperation network analysis, household carbon footprint research has a clear structure of research cooperation network. Cross-institution and cross-country articles collaborate frequently; most authors tend to co-author articles, and there are still a small number of authors who write independently, among which China, Chinese institutions, and Chinese authors make significant contributions. Developed countries represented by the U.S. have chosen cross-region cooperation at the macro level through multifaceted research. The co-word and journal overlay analyses reveal that household carbon footprint research encompasses various research topics. The apparent shift of keywords within each research phase directly proves that household carbon footprint research is gradually developing into an interdisciplinary and diversified homogeneous field. This paper analyzes the evolution of household carbon footprint in detail and composes the basic knowledge which can provide a reliable reference for subsequent scholars.

https://www.mdpi.com/2071-1050/15/7/6138/pdf?version=1680510097

A Bibliometric Review of Household Carbon Footprint during 2000–2022

This study aims to analyse the structure and characteristics of innovation networks from Horizon (2020) projects in fourteen Spanish cities, and to understand how these networks influence a city's success in being selected for the European Mission on Climate-neutral and smart cities by 2030. Utilizing social network analysis, the research uncovers patterns within these urban innovation networks, emphasizing attributes that advance climate neutrality efforts. Results indicate that cities with larger and more interconnected innovation networks, exhibiting balanced participation from diverse stakeholders, and predominantly led by the private sector and research institutions, are more likely to be successfully chosen for the Cities European Mission. This research provides a novel insight into the role of urban innovation systems in the journey towards decarbonization, accentuating the significant influence of European institutional structures in moulding these networks. By focusing on urban networks as a metric for assessing the progress towards climate neutrality, this study offers a fresh perspective that diverges from traditional regional or transnational analyses. The findings have substantial implications for policymakers and urban planners, underscoring the need for fostering robust innovation networks as a strategy to achieve climate neutrality. Additionally, the results pave the way for future research on optimizing resource allocation within urban innovation systems, ultimately contributing to the broader objectives of the European Green Deal. 

The role of Horizon (2020) in achieving climate-neutral urban objectives: A study of 14 Spanish cities innovation networks

Mitigating city carbon emissions in major emitting economies is vital for sustainable development. This study exploits the complex interactions among major sources of emissions to address two research gaps in city carbon neutrality: causal discovery and forecasting in high-emission economies through developing a novel two-stage algorithm. In the initial phase, the algorithm intricately unravels the causal dynamics of emissions from thousands of urban sources. Next, it employs a deciphered causal matrix to forecast city emission trends, leveraging insights from the prior analysis. It outperformed other advanced algorithms in tests using daily emission data from China, the European Union, and the United States. Evaluations, including prediction errors, Taylor diagrams, Diebold-Mariano tests, and ablation experiments, validate its superior ability in identifying inter-city carbon emission interactions and more accurately making 1-step and 5-step advanced predictions. This research confirms that analyzing interactions among major urban emission sources can effectively reveal the causal patterns of carbon emissions among cities and predict future trends. It also finds that while the causal network traits of urban emissions in leading carbon-emitting economies show consistency, distinct differences exist. Leveraging these insights, this study offers tailored policy implications for collaborative carbon emission reduction in cities within these economies. 

Unveiling causal dynamics and forecasting of urban carbon emissions in major emitting economies through multisource interaction

/pdf/quantifying-households-carbon-footprint-in-cities-using-1i7bcid0.pdf

Quantifying households’ carbon footprint in cities using socioeconomic attributes: A case study for The Hague (Netherlands)

Bioregenerative life support systems (BLSS) are vital for long-duration and remote space missions to increase mission sustainability. These systems break down human waste materials into nutrients and CO 2 for plants and other edible organisms, which in turn provide food, fresh water, and oxygen for astronauts. The central idea is to create a materially closed loop, which can significantly reduce mission mass and volume by cutting down or even eliminating disposable waste. In most BLSS studies only a fraction of the resources, such as food, are provided by the system itself, with the rest taken on board at departure or provided through resupply missions. However, for autonomous long-duration space missions without any possibility of resupply, a BLSS that generates all resources with minimal or no material loss, is essential. The goal of this study is to develop a stoichiometric model of a conceptually fully closed BLSS that provides all the metabolic needs of the crew and organisms. The MELiSSA concept of the European Space Agency is used as reference system, consisting of five interconnected compartments, each inhabited by different types of organisms. A detailed review of publicly available MELiSSA literature from 1989 to 2022 revealed that no existing stoichiometric model met the study’s requirements. Therefore, a new stoichiometric model was developed to describe the cycling of the elements C, H, O, and N through all five MELiSSA compartments and one auxiliary compartment. A compact set of chemical equations with fixed coefficients was established for this purpose. A spreadsheet model simulates the flow of all relevant compounds for a crew of six. By balancing the dimensions of the different compartments, a high degree of closure is attained at steady state, with 12 out of 14 compounds exhibiting zero loss, and oxygen and CO 2 displaying only minor losses between iterations. This is the first stoichiometric model of a MELiSSA-inspired BLSS that describes a continuous provision of 100% of the food and oxygen needs of the crew. The stoichiometry serves as the foundation of an agent-based model of the MELiSSA loop, as part of the Evolving Asteroid Starships (E|A|S) research project. 

pdf/stoichiometric-model-of-a-fully-closed-bioregenerative-life-2yqg2yz6rq.pdf

Stoichiometric model of a fully closed bioregenerative life support system for autonomous long-duration space missions

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Quantifying households’ carbon footprint in cities using socioeconomic attributes: A case study for The Hague (Netherlands)

Stoichiometric model of a fully closed bioregenerative life support system for autonomous long-duration space missions

It's in the social network: The Social Neighbourhood model to unravel local social structures for liveable and safe neighbourhoods