Urban Carbon Footprint Research Articles

Unveiling the nonlinear drivers of urban land resources on carbon emissions: The mediating role of industrial upgrading and technological innovation

As cities continue to develop, land resources play a pivotal role in the pursuit of sustainable urban development. However, the impact and mechanisms of land resources on reducing emissions remain unclear. Therefore, our study employs an ensemble learning model within a Monte Carlo Simulation framework to explore the nonlinear relationship between land resources and carbon emissions. Additionally, we utilize a fixed effects model to identify the mechanisms of impact. Specifically, industrial and residential land uses are identified as primary drivers of carbon emissions, contributing 17.04 % and 4.75 % of the total variance in emissions, respectively. In contrast, a standard deviation increase in land price leads to a reduction of 4.65 tons in per capita carbon emissions. In addition, industrial upgrading and innovation emerge as critical mediators in promoting carbon reduction. This research contributes to sustainable urban planning and policy-making, offering insights into how strategic land use planning reduces urban carbon footprints.

Comparison of Urban Environment Factors for Solar-Powered Vehicles

Abstract. Urban areas face significant environmental challenges, including high CO2 emissions largely attributed to the transportation sector. Introducing solar-powered vehicles (SPVs) presents a promising solution to reduce urban carbon footprints. However, in dense urban settings, the effectiveness of SPVs is often compromised by shading from buildings, which significantly diminishes solar power generation. This study explores the impact of shading on urban roads, aiming to identify roads with substantial shadow variations that affect solar energy harvesting. Using Geographic Information Systems (GIS) and hillshade analysis, the study examines how nearby buildings and road orientation influence shadow variability. The findings reveal considerable variability in shadow throughout the year, with significant fluctuations during transitional months like February, August, October, and November. These results highlight the importance of considering shadow patterns in urban planning and vehicle routing to optimise the use of solar energy in urban settings.

Energy-saving path planning navigation for solar-powered vehicles considering shadows

Globally, the adverse climate effects caused by greenhouse gas emissions are becoming increasingly apparent, and solutions to increase the use of eco-friendly transportation methods are urgently needed. Introducing solar-powered vehicles (SPVs), which are cars integrated with solar panels capable of generating power, presents a promising solution to reduce urban carbon footprints. However, the low adoption rate of SPVs implies that the benefits—such as environmental friendliness and ability to charge while driving—need to be more palpably experienced by consumers. To address this aspect, in this study, we aimed to develop a navigation system algorithm that guides users along routes that optimize energy consumption and solar energy production from the starting point to the destination. This was done with the objective of providing more tangible benefits from using SPVs. The study focused on the high-traffic urban center of Seoul, where determining solar power availability for a moving SPV is challenging, given the presence of shadows cast by roadside features such as buildings and trees. To achieve this, panoramic images from Google Street View were collected at 10 m intervals from all roads within the research area. From these images, sky and non-sky elements were separated. Subsequently, a hemispherical map was constructed and superimposed with the sun's path. The presence of shadows was determined by assessing whether the sun's path was obstructed by non-sky elements; if the path was unimpeded in the sky, no shadow was recorded. The shadow data obtained at each spot were efficiently stored in a database for quick retrieval and application based on specific locations and departure times. Using this shadow information, the navigation algorithm calculates power generation along a given route and considers the energy consumption of the SPV. Analysis led to the identification of an energy-saving route, which enabled the achievement of energy conservation and CO2 reduction benefits. Furthermore, a comprehensive sensitivity analysis was conducted to examine the impact of four critical parameters—module efficiency, solar panel area, vehicle speed, and departure time—on route selection and net energy consumption. The energy-saving path planning algorithm enhances the economic feasibility of solar charging for SPVs during travel; thus, this study can contribute significantly to the widespread adoption of SPVs, which play a definitive role in reducing transportation's carbon footprint.

Digital finance reduces urban carbon footprint pressure in 277 Chinese cities

As global warming's impact on humanity surpasses initial predictions, numerous countries confront heightened risks associated with escalating urban carbon footprints. Concurrently, digital finance has flourished, propelled by advancements in digital technology. This convergence underscores the urgency of exploring digital finance's role in mitigating urban carbon footprint pressures. This study analyzes data spanning 277 Chinese cities from 2011 to 2020, yielding several key findings: Firstly, we developed a dataset detailing the carbon footprint pressures in these cities, revealing that variations in these pressures predominantly correlate with economic growth. Secondly, our analysis indicates that digital finance has a significant impact on reducing urban carbon footprint pressures, through mechanisms such as reducing the number of physical bank branches and enhancing residents' environmental awareness. Thirdly, the study identifies that the efficacy of digital finance in reducing carbon footprint pressures varies according to factors like sunshine duration and geographic location. The insights from this research aim to contribute substantively to strategies for sustainable urban development.

Carbon Emission Analysis and Reporting in Urban Emissions: An Analysis of the Greenhouse Gas Inventories and Climate Action Plans in Sarıçam Municipality

The urban carbon footprint (UCF) is an important tool for assessing an organization’s ecological impacts and in guiding sustainability efforts. This calculation is usually measured in tons of carbon dioxide equivalent (CO2-eq). Calculations provide important data to determine strategies to reduce the carbon footprint and establish sustainability targets. Various standards and protocols guide UCF calculation, and many organizations aim to make these data transparent to their stakeholders and the public. This study aims to calculate the UCF of Sarıçam Municipality (SM) in the Adana Province of Türkiye. This study includes the greenhouse gas emission inventories resulting from all activities of the SM main service building, guest house, construction site service building, Cultural Center service building, and additional service buildings between 1 January 2022 and 31 December 2022. The calculations include generator fuel consumption, electricity consumption, the refrigerant gas leaks and refills resulting from these activities, the fuel consumed in vehicles owned by the company or whose fuel consumption is under company control, emissions originating from personal travel, emissions originating from customers and visitors, emissions originating from business travel, purchases, etc. Emissions from products purchased and emissions from waste transportation are included. The findings show that, in 2022, the total UCF of SM was equal to 10,862.46 tons of CO2-eq. The Paris Agreement aims to reduce the per capita emissions to approximately two tons of CO2-eq by 2030. The carbon footprint per employee within the municipality was calculated at 12.43 tons of CO2-eq, as derived from the analyzed data. The results reveal the importance of implementing sustainable practices and strategies within SM, such as energy efficiency measures, waste reduction, and the adoption of renewable energy sources, to mitigate its carbon footprint. This study plans to provide a basis for SM’s reduction efforts by keeping greenhouse gas emissions under control.

Comparing the determinants of household carbon footprints between rural and urban: evidence from China household survey data

PurposeUrbanization is driving the growth of China’s carbon footprint. It’s important to investigate what factors, how and to what extent, affect carbon footprints embedded in various categories of rural and urban households’ consumption.Design/methodology/approachWe employ an environmental extended input-output model to assess and compare the rural-urban household carbon footprints and perform a multivariant regression analysis to identify the varying relationships of the determinants on rural and urban household carbon footprints based on the panel data of Chinese households from 2012 to 2018.FindingsThe results show evidence of urbanity density effect on direct carbon footprints and countervailing effect on indirect carbon footprints. The old dependency ratio has no significant effect on rural family emissions but has a significantly negative effect on urban direct and indirect carbon footprints. A higher child dependency ratio is associated with less rural household carbon emissions while the opposite is true for urban households. Taking advantage of recycled fuel saves direct carbon emissions and this green lifestyle benefits urban households more by saving more carbon emissions. There is a positive relationship between consumption structure ratio and direct carbon footprints while a negative relationship with indirect carbon footprints and this impact is less significant for urban households. The higher the price level of water, electricity and fuel, the lower the rural household’s direct carbon footprints. Private car ownership consistently augments household carbon footprints across rural and urban areas.Originality/valueThis paper provides comprehensive findings to understand the relationships between an array of determinants and China’s rural-urban carbon emissions, empowering China’s contribution to the global effort on climate mitigation.

Reducing Carbon Emissions: An Analysis of Smart City Initiatives and the Carbon Reduction Test

The need to cut carbon emissions in cities have become more pressing in an age of unparalleled urbanization and climate change. Using both quantitative and qualitative analysis, this study looks at how smart city efforts affect the decrease of carbon emissions. Carbon Reduction Test results and comparative studies show that smart cities with a comprehensive approach—including renewable energy use, energy-efficient buildings, public transportation upgrades, green energy projects, waste management enhancements, and energy-efficient transportation—achieved significant carbon emission reductions. These results demonstrate the transformational potential of smart cities in supporting international sustainability efforts and the efficacy of diverse techniques in reducing the urban carbon footprint.

Desenvolvimento da consciência ecológica por meio de projeto e desenvolvimento urbano

Abstract: Growing environmental concerns and the rise of sustainable development have made planners shift focus from prioritizing economic and social benefits to incorporating ecological consciousness into urban planning. Ecological challenges, such as habitat degradation from unchecked urban expansion and insufficient green spaces, underscore gaps in ecological awareness among urban planners. Issues, like urban heat islands and water mismanagement, further exemplify the need for enhanced ecological planning. To address these challenges, the paper proposes several governance strategies. It advocates for comprehensive planning for ecological civilization cities, including green infrastructures and natural landscape restoration to mitigate environmental impacts. Enhancing ecological responsibility, through education and community engagement, is vital for fostering a culture of sustainability. Developing an ecological circular economy addresses resource inefficiency and waste problems, while promoting low-carbon transportation options aims to reduce urban carbon footprints. Guided by the concept of ecological consciousness, this analysis offers actionable paths for improving urban ecological governance.

Exploring the determinants of the evolution of urban and rural household carbon footprints inequality in China

Households are key actors in mitigating climate change and their carbon footprints are unequally distributed due to differences in the scale and patterns of consumption. This study separately estimates household carbon footprints inequality in urban and rural areas of China from 2012 to 2018 and identifies the factors contributing to the evolution of the inequality by applying environmentally extended multiregional input-output analysis, unconditional quantile regression and Oaxaca-Blinder decomposition. The results show that the largest emission growth occurred among the 50th–80th percentile of urban emitters and the highest rural emitters. The Gini coefficient of urban household carbon footprints decreased from 0.463 to 0.439, whereas that of rural household carbon footprints increased from 0.447 to 0.459. Notably, the changes of household characteristics exacerbated carbon inequality, with income growth, increased car ownership, and smaller household size being the three primary factors, while the changes in consumption preferences and technological advancements reduced carbon inequality. The latter are dominant in urban households and the former are dominant in rural households. To mitigate climate change and reduce inequality, the government should not only encourage high-emitting households to adopt greener low-carbon consumption and lifestyles, but also promote low-carbon technology innovation to reduce carbon intensity.

Characteristics and drivers of changes in the carbon footprint of urban tourism in the post-COVID-19 era: A case study of Xi'an

COVID-19 pandemic prevention and control measures provide valuable social experimental opportunities for exploring the factors that affect changes in the urban tourism carbon footprint (TCFu). The study uses the carbon emission coefficient and energy consumption coefficient to calculate the TCFu of the transport, accommodation, catering, and recreational activity sectors, taking Xi'an from 2014 to 2020 as a case study. It analyzes the characteristics of the carbon footprint changes and their drivers in each sector. The results show that compared to before the outbreak of the pandemic, in the period afterwards, the TCFu decreased by 60.46%. The carbon footprint of tourism transport decreased the most. Carbon intensity has a significant inhibitory effect on the TCFu growth, and as drivers, the consumption level and population size shifted from promoting to inhibiting the TCFu. It emphasizes the importance of developing low-carbon tourism transportation to reduce the TCFu, providing a scientific basis for promoting the green transformation of urban tourism.

Decreasing the urban carbon footprint with woody biomass biochar in the united states of america

Urban centers are places with a high human population concentration, and they can pose social, economic, and environmental challenges. These challenges are accentuated by the increased use of available open space for housing and industrial expansion, leading to elevated energy consumption, increased pollution, higher carbon emissions, and, consequently, adverse effects on human health. Many of these issues also contribute to the acceleration of climate change. There are several ways to decrease these problems through the expansion of greenspaces that conserve biodiversity, decrease air pollution, improve human well-being, and reduce human health risks, while also allowing people to enjoy the benefits of ecosystem services. This review is aimed at professionals who can manage urban landscapes - including adjacent forests, urban parks, tree beds, or home gardens that produce biomass that, together with other non-chemically treated wood waste, could be used to produce and use biochar. Biochar-amended soils provide the benefits of increased carbon sequestration, water retention, and soil productivity and can also decrease stormwater runoff. In addition, a small number of cities around the world have adopted biochar as a nature-based solution to decrease the impacts of climate change. We point out the opportunities and benefits of converting urban wood waste into biochar, how cities can improve their green environments, and, at the same time, produce energy from waste that would otherwise end in landfills with no use or value. Finally, based on previous assessments of wood waste in the United States of America, we estimate the biochar potential to sequester CO2.

Tracing urban carbon footprints differentiating supply chain complexity: A metropolis case

More complicated linkages between sectors are enhancing supply chain complexity. How carbon footprints (CFs) transfer through simple and complex supply chain paths (SSCPs and CSCPs) (differentiated according to production layers covered) and evolve driven by socioeconomic effects remain elusive. Targeting Shanghai with a population larger than 20 million and pillar industries including services, transportation, communication electronics, we identified the key supply chain paths for CFs to uncover their evolutionary characteristics and investigated the contributions of major socioeconomic drivers including supply chain complexity to CFs changes during 2007–2017 based on structural path analysis and structural decomposition analysis. Results indicate that total CFs increased from 165.0 to 191.2 Mt-CO2, then decreased to 177.4 Mt-CO2. CFs of CSCPs kept decreasing, accompanied by the declining proportion in total CFs (3.1%–1.5%). The downstream sectors of Transportation and Metals Smelting and Pressing driven by export were most observable in the supply chain. For SSCPs, the most important negative driver of CFs turned from emission intensity to industrial structure. The transition of supply chain complexity favored to CFs reduction in CSCPs, especially for those associated with export. The findings provide decision-makers with reference to sounder urban supply chain management for pertinent carbon emission control.

Sustainable lifestyle: Urban household carbon footprint accounting and policy implications for lifestyle-based decarbonization

Cities, as the primary hubs of economic activities and the end-points of goods and services consumption, bear significant responsibility for the majority of global greenhouse gas emissions. Consequently, there is a pressing need for more granular data at the subnational level to formulate effective and feasible measures in line with current decarbonization targets. In this study, we present the carbon footprint embodied in household consumption behavior of 11 major metropolitan areas in Japan. Furthermore, our study innovatively introduces a temporal perspective, employing time organization as an insightful indicator to delineate the disparities in carbon footprints that arise from varying carbon intensities of distinct activities. The results are given from the following three aspects: 1) structural comparison of urban household carbon footprints; 2) time-based activity differences and drivers; and 3) inequality analysis among different activity-based carbon footprints. Here, we found that eating contributes most substantially to the carbon footprint. Conversely, transportation activities manifest the greatest regional inequality in carbon footprints. These findings provide indispensable evidence for the development of city-specific net-zero-emission goals within Japan. Furthermore, they exemplify the value of incorporating a temporal dimension into household carbon footprint analyses, thereby providing a broader perspective for future investigations in this field.

Planning factors affecting carbon footprints of residents: Density, land use, and suburbanization

Energy-efficient urban development and carbon footprints (CFs) are often discussed in relation to climate change. The optimal level of urban density from a carbon reduction perspective at the city level has been much debated. However, considering possible trade-offs or co-benefits for CFs in the housing and travel sectors, it remains difficult to evaluate how intra-urban/residential densities and mixed land-use patterns relate to individual CFs at a community level in different seasons. The study objective was to demonstrate the changes in the CFs of residents in summer and winter according to spatiotemporal changes in urban forms, such as intra-urban/residential densities and mixed land-use patterns. Based on geographical data and CF survey results from Seoul and Gyeonggi in 2009 and 2018, four path analysis models were used to verify the spatiotemporal variances of the relationships between urban forms and the CFs of the housing/travel sectors (HCF/TCF). Path analysis with a set of mediation variables enables the evaluation of possible trade-offs, or co-benefits, when investigating the impacts of different measures of intra-urban densities and mixed land-use patterns on the CFs. Furthermore, the moderating effects of different cooling and heating patterns in different seasons on CFs were verified by comparing the four path analysis models in different spatiotemporal contexts. The results showed spatiotemporal changes in urban density and different impacts of urban and residential densities on the TCF. It was also revealed that a low percentage of residential land use in urbanized areas offsets the advantage of high density in reducing TCF and HCF. Seasonal differences were also observed in the effects of residential density and HCF. The results of this study help us understand the spatiotemporal characteristics of TCF and HCF in urban settings, which can assist efforts to achieve carbon neutrality goals.

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.

System dynamics life cycle-based carbon model for consumption changes in urban metabolism

Materials and energy consumed by urban systems are one of the main sources of greenhouse gas emissions. Measuring these flows and their associated emissions is necessary to estimate the impact of cities on climate change in the future. In this research we developed a dynamic model for measuring the carbon footprint of cities’ urban metabolism using an integrated socio-ecological systems approach. Illustrated with a case study in Montreal we modelled the urban carbon footprint between 2000 and 2018, and simulated on to 2030 under four scenarios: baseline, increasing adoption of plant-based diets (PBD), pavement/road material circularity (PMC), and a combined approach of the latter two. By simultaneously modelling Montreal's population growth the GHG per capita trend was compared to the anticipated 2030 global threshold of 2.9 t CO2e per person needed to meet the 1.5°C Paris Agreement target. All scenarios result in decreased per capita emissions from 15.0 t CO2e/capita in 2018, in part due to the increasing urban population. The baseline scenario estimates a decrease to 12.7 t CO2e by 2030; the PBD and PMC scenarios estimate respective reductions to 10.8 and 12.4 t CO2e/capita by 2030. The combined scenario estimates a greater reduction to 10.5 t CO2e/capita, but this is still 7.6 t CO2e/capita over the Paris Agreement target for 1.5°C global warming.

Urban and rural carbon footprints in developing countries

A good understanding of household carbon emissions is an important part of forming climate mitigation strategies to achieve the goals set out in the Paris Agreement. Numerous studies have been carried out on emissions from household consumption and the inequality between urban and rural areas in high-income developed countries, but there is a lack of in-depth analysis of such differences in developing countries. Our research details household carbon footprints (CFs) of four urban and four rural income categories for 90 developing countries, by linking global expenditure data to the environmentally extended multi-regional input–output approach. We show that there are large inequalities between urban and rural areas in developing countries. The average per capita CF in urban areas tends to be larger than that of rural inhabitants ranging from twice as large to nine times larger. We find that electricity consumption and transport are the largest contributors to the total CF in all expenditure groups. High-income rural households have an average per capita CF of 12.38 t CO2 which is 25% higher than the equivalent urban high-income group, which deviates from the literature looking at a subset of cases. Our study contributes to the existing research on CFs by providing knowledge on the consumption patterns and related carbon emissions of urban and rural populations in these understudied parts of the world.

Dynamic Threshold Effect of Directed Technical Change Suppress on Urban Carbon Footprint in China

Promoting technical change is an important driving force for promoting the sustainable development of urban economy and ecology; however, the technical change is not always neutral and technical change may has a certain direction. This paper uses the DEA-Malmquist index to measure the directed technical change of 280 cities in China from 2009 to 2019, and uses the DMSP/OLS night light data to characterize the urban economic development level. It uses the dynamic threshold regression model to analyze the impact of directed technical change on urban carbon footprint under different economic development levels. The results show that: (1) during the study period, the carbon footprint of Chinese cities has a positive spatial correlation, and the direction of technical change is towards capital-saving overall. (2) The impact of capital-saving technical change on urban carbon footprint presents a negative double-threshold characteristic in China, and the inhibition of capital-saving technical change on the urban carbon footprint becomes stronger with the increasing economic development level. (3) The inhibitory effect of capital-saving technical change on carbon footprint has regional heterogeneity, and the inhibitory effect of capital-saving technical change on carbon footprint is stronger in eastern China than other regions. (4) Industrial structure, energy structure and innovation efficiency are mediating variables of the inhibitory effect of capital-saving technical change on carbon footprint except for population density.

Recent advances in carbon footprint studies of urban ecosystems: overview, application, and future challenges

Urban ecosystems are complex systems with anthropogenic features that generate considerable CO2 emissions, which contributes to global climate change. Quantitative estimates of the carbon footprint of urban ecosystems are crucial for developing low-carbon development policies to mitigate climate change. Herein, we reviewed more than 195 urban carbon footprint and carbon footprint related studies, collated the recent progress in carbon footprint calculation methods and research applications of the urban ecosystem carbon footprint, analyzed the research applications of the carbon footprint of different cities, and focused on the need to study the urban ecosystem carbon footprint from a holistic perspective. Specifically, we aimed to: (i) compare the strengths and weaknesses of five existing carbon footprint calculation methods [life cycle assessment, input–output analysis, hybrid life cycle assessment, carbon footprint calculator, and Intergovernmental Panel on Climate Change (IPCC)]; (ii) analyze the status of current research on the carbon footprint of different urban subregions based on different features; and (iii) highlight new methods and areas of research on the carbon footprint of future urban ecosystems. Not all carbon footprint accounting methods are applicable to the carbon footprint determination of urban ecosystems; although the IPCC method is more widely used than the others, the hybrid life cycle assessment method is more accurate. With the emergence of new science and technology, quantitative methods to calculate the carbon footprint of urban ecosystems have evolved, becoming more accurate. Further development of new technologies, such as big data and artificial intelligence, to assess the carbon footprint of urban ecosystems is anticipated to help address the emerging challenges in urban ecosystem research effectively to achieve carbon neutrality and urban sustainability under global change.

Potential Contribution to Carbon Neutrality Strategy from Industrial Symbiosis: Evidence from a Local Coal-Aluminum-Electricity-Steel Industrial System

Urban sustainability is a critical target under the sustainable development goals (SDGs), especially considering the response of cities to most of the resource and carbon footprints of human beings. The circular economy (CE) strategy offers an innovative and important pathway for forwarding sustainable urban development in terms of resource saving and waste mitigation. A particularly important measure of the circular economy is the urban industrial symbiosis, which, as an imitation of the ecological system, is viewed as an effective way to achieve the sustainable and low-carbon transformation of industries and downtown areas. However, evidence of its comprehensive environmental benefit is less reported. With this circumstance, this paper aims at identifying the environmental benefits of urban industrial symbiosis, with a focus on urban carbon footprints (CFP). With this basis, we shall also discuss the promotion of urban industrial symbiosis as a critical component in support of the carbon neutrality strategy. A hybrid approach integrating a process-based inventory analysis and an input–output analysis (IOA) is developed to analyze urban CFPs. Results imply that considerable savings in resources and the reduction of CFPs could be achieved via the coal-aluminum-electricity-steel industrial symbiosis. In detail, the eight designed synergies, with the aluminum-electricity-steel plants as the hubs, could reduce CO2 by 1.09 Mt per year, which accounted for 3.63% of the total CFPs in the city in a business-as-usual (BAU) scenario in 2012. This could partly offset the increase of CO2 emissions due to the economy’s expansion and realize a second mitigation effect apart from the efficiency change in technologies. A crucial understanding of the function of industrial symbiosis in accelerating the sustainable transformation of cities could then be reached. Finally, further implications on policy when tackling the gaps in regional eco-industrial development are proposed and discussed.