Global Sustainable Development Research Articles

Urban synergistic carbon emissions reduction research: A perspective on spatial complexity and link prediction

Reducing urban carbon emissions (UCEs) holds paramount importance for global sustainable development. However, the complexity of interactions among urban spatial units has impeded further research on UCEs. This study investigates synergistic emission reduction between cities by analyzing the spatial complexity within the UCEs network. The future potential for synergistic carbon emissions reduction is predicted by the link prediction algorithm. A case study conducted in the Pearl River Basin of China demonstrates that the UCEs network has a complex spatial structure, and the synergistic capacity of emission reduction among cities is enhanced. The core cities in the UCEs network, including Dongguan, Shenzhen, and Guangzhou, have spillover effects that contribute to synergistic emission reduction. Community detection reveals that the common characteristics associated with UCEs become concentrated, thereby enhancing the synergy of joint efforts between cities. The link prediction algorithm indicates a high probability of strengthened carbon emission connections in the Pearl River Delta, alongside those between upstream cities, which shows potential in forecasting synergistic emission reductions. Our research framework offers a comprehensive analysis for synergistic emission reduction from the spatial complexity of UCEs network and link prediction. It acts as a worthwhile reference for developing differentiated policies on synergistic emission reduction.

Exploring the power of informal institutions: How does social trust affect corporate's greenwashing strategy

AbstractCorporate greenwashing seriously impedes global sustainable development. Despite the discussion on the factors influencing corporate greenwashing strategy, the impact of informal institutions, particularly social trust, remains underexplored. Based on institutional theory and the attention‐based view, this study examines the effect of social trust on corporate greenwashing strategy. Additionally, it also explores the mediating roles of managers' environmental attention and firms' green open innovation, as well as the moderating roles of government environmental regulation and market competition. Using a sample of 3,143 heavily polluting companies listed on China's A‐share market, the results show that social trust negatively impacts corporate greenwashing strategy. Managers' environmental attention and firms' green open innovation are the chain mediators through which social trust constrains firms' greenwashing strategy. Moreover, government environmental regulation strengthens the effect of social trust on corporate greenwashing, while market competition weakens the effect. The obtained conclusions provide an important guidance for curbing corporate greenwashing strategy and highlight the role of social trust.

Towards sustainable fruit production: Identifying challenges and optimization strategies

CONTEXTThe transition to sustainable fruit production is vital for global sustainability and agricultural development. However, implementing these insights into practice faces significant challenges. OBJECTIVESPomelo (Citrus maxima), a prominent citrus species in tropical and subtropical regions, has been cultivated to enhance farmer profitability but increasing yields often comes at the cost of environmental degradation. This study uses pomelo as a case study to assess key factors influencing pomelo production and establish optimal practices that meet consumption-based food while co-benefits for environmental and economic sustainability. METHODSA comprehensive study was conducted by combining 1155 farm surveys (from 2010, 2018, and 2022) with 31 field experiments. Life cycle assessment (LCA), classification and regression tree (CART) analysis, and scenario analysis were employed to develop pathways for sustainable pomelo production in Pinghe County, Fujian Province, China. RESULTS AND CONCLUSIONSResults show no significant differences in pomelo yield across the three years; however, pomelo production in 2022 demonstrated a 60 %–67 % lower in environmental footprints and a 64 %–76 % higher benefit-cost ratio (BCR) compared to 2010 and 2018. Tree age was identified as a critical factor influencing pomelo yield, with optimal yields observed in trees older than 12.5 years. The rate of phosphorus fertilizer application was a key determinant of the phosphorus footprint (PF), which was positively correlated with phosphorus fertilizer rates. Similarly, nitrogen fertilizer application significantly impacted both carbon and nitrogen footprints (CF and NF) as well as the BCR. CF and NF increased with higher nitrogen fertilizer rates, while BCR exhibited a negative correlation with nitrogen fertilizer application. Implementing Science and Technology Backyards (STB) followed by farmer training of slightly more than pomelo nutrient requirements practice (SNRP) or coordinate management by farmers and researchers of matching pomelo nutrients requirement practice (MNRP) had 50 %–91 % lower environmental footprints per ton of pomelo produced and 15 %–44 % higher BCR compared to current farming practices (FP) via reducing 46 %–77 % N, 49 %–92 % P2O5, and 42 %–73 % K2O per hectare. Moreover, adopting 100 % MNRP in pomelo production, along with sustainable fertilizer practices and the implementation of innovative fertilizers, could reduce greenhouse gas (GHG) emissions (0.76 Tg), reactive nitrogen (Nr) emissions (8.76 Gg), phosphorus (P) losses (0.84 Gg), and augment net ecosystem economic benefits (NEEB) (0.94 billion CNY) at the county scale. SIGNIFICANCEOur study provides evidence-based strategies for achieving sustainable pomelo production through multi-stakeholder collaboration of STB, government, enterprises, and smallholders.

Disparities in Environmental Behavior from Urban–Rural Perspectives: How Socioeconomic Status Structures Influence Residents’ Environmental Actions—Based on the 2021 China General Social Survey Data

This study explores the environmental behavior disparities between urban and rural residents in China due to socioeconomic status differences amidst social governance and institutional reform. Using OLS regression models on the 2021 China General Social Survey (CGSS) data, it analyzes the impact of socioeconomic status on environmental behaviors. This study reveals that urban residents generally exhibit better environmental behaviors than rural residents. Education and income are identified as critical drivers, with education raising environmental awareness and income driving participation in environmental activities. Urban residents benefit more from these factors. The policy recommendations are for the government to enhance rural education resources and improve education quality, ensuring that education poverty alleviation policies are effectively implemented to support rural development. Simultaneously, promoting rural economic growth and narrowing the urban–rural economic gap is crucial for improving rural environmental behavior and achieving urban–rural environmental harmony. Furthermore, the results call on the international community to focus on environmental governance systems, aiming to provide references for other developing countries in formulating environmental policies, thereby promoting the creation of a more just, eco-friendly, and sustainable global development framework.

Towards the Corporate Social Responsibility on Labour in the Era of New-Generation Free Trade Agreements: The Case of EVFTA

The article gives an in-depth understanding of the commitment to corporate social responsibility (CSR) on labour under the new generation of free trade agreements (FTAs) of the European Union (EU), and especially, the EU – Vietnam Free Trade Agreement (EVFTA). Following that, via the EU’s foreign and trade policies, this research clarifies the history as well as the evolution of the CSR commitments in the EU’s new generation FTAs. On that basis, this article also delves into the nature of CSR commitments related to labour in the EVFTA. Last but not least, the article reviews the current legislation of the EU and its member states as partners and suggests different policy implications that Vietnam and other developing nations might adopt to execute their CSR commitments in the context of global sustainable development.

Development of Ecological Low-Carbon Agriculture with Chinese Characteristics in the New Era: Features, Practical Issues, and Pathways

Agriculture is not only the source of carbon emissions, but also an important carbon sink. The development of low-carbon agriculture in China is closely related to achieving the national strategic goal of “dual carbon.” Reducing carbon emissions in China’s agricultural sector and accelerating the development of ecological low-carbon agriculture (ELA) are extremely important and urgent, both from the perspective of the long-term common welfare for mankind and from the perspective of maintaining the sustainable development of agriculture itself. However, ELA is still an emerging concept in China, and its connotation and characteristics are not yet clear. There is a lack of effective paths for orderly and scientific promotion of the development of ELA in China. Based on this, this paper focuses on the emerging concept of ELA and examines ELA with Chinese characteristics from the dimensions of connotation, features, practical issues, and pathways, aiming to provide guidance for the sustainable development of ELA in China. The research results indicate that there are regional development imbalances, low willingness of farmers to participate, insufficient technological reserves, and difficulties in realizing the value of ecological products in China’s ELA. It is necessary to improve the modern agricultural production and operation system, tap into the potential of agricultural emission reduction and carbon sequestration, build a technical system to support the development of ELA, and establish a sound mechanism for realizing the value of ecological products. By continuously improving the regional organizational capacity and performance of ELA, accelerating the advancement of ELA technology and demonstrating its regional promotion, and by establishing and continuously improving the support system for ELA, one can promote the sustainable development of ELA in China. In addition, the research findings of this paper can also provide reference for the ecological low-carbon development of the global agricultural sector, supporting the contribution of the agricultural sector to achieving high-quality global sustainable development goals.

Research on Sustainable Form Design of NEV Vehicle Based on Particle Swarm Algorithm Optimized Support Vector Regression

With the growing emphasis on eco-friendly and sustainable development concepts, new energy vehicles (NEVs) have emerged as a popular alternative to traditional fuel vehicles (FVs). Due to the absence of an internal combustion engine, electric vehicles (EVs) do not require a front air intake grille, allowing for a more minimalist and flexible design. Consequently, aligning EV styling with users’ visual cognition and emotional perception is a critical objective for automakers and designers. In this study, we establish the mapping relationship between users’ emotional cognition and NEV styling design based on experimental data. We introduce Particle Swarm Optimization Support Vector Regression (PSO-SVR) into the perceptual engineering (KE) research process to predict user emotions using Support Vector Regression (SVR). To optimize the three hyperparameters (penalty coefficient C, RBF kernel function parameter γ, and insensitivity loss coefficient ε) of the SVR model, we utilize the Particle Swarm Optimization (PSO) algorithm. The results indicate that the proposed PSO-SVR model outperforms traditional SVR and BPNN models in predicting NEV user emotions. This model effectively captures the nonlinear relationship between battery electric vehicle (BEV) morphological features and users’ emotional cognition, providing a novel method for enhancing NEV design. The results of this research are expected to drive design innovation and technological advancement in the new energy vehicle industry, contributing to the achievement of the ambitious goal of global eco-friendliness and sustainable development.

Enhancing water security: Statistical measurement and spatiotemporal analysis

Water security is essential for ensuring energy security, sustainable development, and human survival. However, due to a series of challenges, including rising water demand, environmental pollution, and water resource shortages, the global water security situation remains concerning and poses a threat to global sustainable development. To assess water security in China, this study uses data from 30 provinces in China from 2012 to 2021. A comprehensive evaluation method was applied to determine the level of water resource security in China. The Dagum Gini coefficient, Moran index, and spatial model were used to clarify regional differentiation characteristics and the driving factors. The results indicate that while China's water resource security is relatively low, it has shown steady improvement in recent years. Significant regional disparities exist in water resource security across China, with notable spatial characteristics, and socio-economic factors are the primary causes of these differences. Based on the above research, we put forward policy recommendations from the aspects of water resources management, public participation and inter-regional water resources cooperation, to provide reference for water resources security in developing countries.

Global sustainable development programs: Challenges to the achievement of the goals

In this interview the Head of the Chair of Sociology of Public Administration of the School of Sociology, Lomonosov Moscow State University, Vladimir P. Vasiliev, shares his assessments of the results and significance of the UN climate Conference held in November-December 2023 in the UAE (Dubai). He examines the current dynamics of the implementation of the Paris Climate Agreement, the key provisions of the reports of the World Health Organization and the International Energy Agency, and focuses on the discussions that unfolded at the conference on the use of fossil fuels and the transition to renewable energy sources. It is noted that the process of implementing the Sustainable Development Goals (SDGs) is currently facing a number of serious obstacles, both economic and socio-political in nature. Meanwhile, failure to implement the SDGs is fraught with a sharp aggravation of the problems of global inequality, food security and climate migration, especially dangerous for the most vulnerable groups of the population. It is noted that under these conditions, the Russian Federation is pursuing a long-term climate policy aimed at achieving a balance between anthropogenic greenhouse gas emissions and their absorption, in a way that is consistent with national interests and priorities of socio-economic development. Hopefully, scientists from Lomonosov Moscow State University will be able to contribute both to improving the environmental policy of the Russian Federation and to defining the global climate agenda. And for this, in turn, it is important to develop and strengthen the dialogue between the leading scientific schools of Moscow State University.

Modeling and simulation for the sustainable recovery of aromatics (BTX) from petrochemical industrial wastewater.

Petrochemical wastewater is a major industrial source of pollution that produces a variety of toxic organic and inorganic pollutants, naturally present or added during the process. These pollutants are a serious threat to the soil, water, environment, and human being due to their complex and hazardous nature. Glycols such as monoethylene glycol (MEG), diethylene glycol (DEG), triethylene glycol (TEG), and aromatics (BTX-benzene, toluene, and xylene) are the most common organic impurities present in petrochemical wastewater. The objective of this paper is to recover aromatics and water from petrochemical industrial wastewater. The reclamation process is used to remove inorganic impurities such as heavy metals Fe, Zn, Pb, Mn, Al, Ni, As, Cr, Cu, Cd, and K and salts. In the present work, 1% sodium bi-carbonate (NaHCO3) is used to precipitate the inorganic impurities present in the wastewater at 40°C atmospherically. Aspen Hysys simulation software is used for modeling and simulation for the treatment process using NRTL (non-random-two-liquid) thermodynamic model. The process generated from Aspen Hysys is validated with lab experiments. To support global sustainable development, this study is focused on reducing, reusing, and recycling separation techniques such as centrifuge separation and vacuum distillation have been used. The characterization of regenerated water was performed using ICP-OES (inductively coupled plasma-optical emission spectroscopy) to determine the reduction in heavy metals. It was found that > 99.5% of heavy metals were removed. The regeneration of these aromatics is necessary for economic and environmental reasons so that it can be reused to avoid its disposal in and contamination of natural environments.

Impact of heavy metal hazard perceptions on pollution control intentions: Empirical evidence from rice farmers in China

Heavy metal pollution presents significant challenges to global sustainable development. The treatment of such pollution predominantly relies on government policies, often neglecting farmers’ crucial role in the remediation process. Therefore, this study investigates the driving mechanisms behind farmers’ willingness to control heavy metal pollution in farmland. By analyzing survey data from 718 rice farmers in China, this study employs the Probit model to quantitatively assess the impact of farmers’ perceptions of heavy metal hazards on their inclination to control pollution in farmland. Additionally, it examines the heterogeneity of these impacts between cultivated rice for domestic consumption and rice for export. The findings reveal the following: (1) Approximately 70% of farmers recognize the harmful effects of heavy metals, but only 66.2% of them express willingness to engage in pollution control measures. (2) More awareness regarding heavy metal hazards corresponds to a stronger intention to control pollution. (3) In addition to hazard perception, households with village cadres demonstrate a significantly positive influence on pollution control intention. (4) There are notable disparities in farmers’ attitudes towards retained rice (for domestic consumption) and exported rice, with a greater willingness to implement pollution control measures for retained rice. As such, this study provides valuable insights for informing policy development to address the challenges associated with heavy metal pollution control’s complex and limited effects. The findings contribute to a better understanding of the Chinese context as a typical developing country, offering analytical cases that promote global sustainable development while leveraging Chinese wisdom.

Evaluating Collaborative Emission Reduction Efforts in Urban Road Passenger Transportation: insights from the City Scale

Road passenger transportation contributes significantly to carbon dioxide (CO2) and pollutant emissions, posing challenges for urban sustainability, particularly in rapidly urbanizing cities such as Fuzhou, which was recognized as a global sustainable development city for 2023. This study addresses the research gap by integrating road green factors, which refer to the ecological attributes of roads, such as green space, vegetation, and tree coverage that contribute to improving air quality and reducing pollution, into emission reduction strategies for city-scale road passenger transportation. This novel approach has not been extensively explored in the existing literature. The purpose of this study was to identify a rational pathway for emissions reduction by analyzing the economic, demographic, transportation infrastructure, road green space, and policy factor impacts on emissions. Employing a system dynamics (SD) model, this research evaluates the emissions from road passenger transportation in Fuzhou from 2010 to 2030 under various scenarios, including a baseline scenario (BS), controlled private cars travel demand (CPD), promotion of new energy vehicles (PVE), improvement in energy efficiency (IEE), increase in road capacity (IRC), and improvement in road green level (IRG). The principal results indicate that by optimizing the traffic structure and integrating other emission reduction measures, peak CO2 emissions can be achieved by 2024 under the three scenarios or by 2023 under the four scenarios. Furthermore, significant reductions in pollutants of 84.62% and 86.07% are projected, respectively. The study concluded that the economic benefits of CO2 emissions reductions consistently exceeded those of carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NOx) reductions, highlighting the importance of a holistic approach to emissions reduction strategies. Based on these findings, policy recommendations were proposed to guide the formulation of effective road passenger transportation policies aimed at achieving sustainable urban development.

Unveiling complementarities between mangrove restoration and global sustainable development goals

Indonesia, renowned as the most mangrove-rich nation, has committed to extensive mangrove restoration policies, but the effects of these policies have yet to be systematically evaluated. Our study conducts a comprehensive network analysis to investigate the synergies between mangrove restoration policy and global Sustainable Development Goals (SDGs) achievements by exploring their interactions. This investigation follows the ‘product space’ method in economics and creates the ‘Mangrove-SDG space’ to assess each metric pair's co-occurrence and comparative advantages with validated stability. Our analysis unveils a tripartite structure, encompassing socio-economic and environmental clusters, each significantly contributing to global sustainability and a distinctive mangrove cluster tied to land attributes. At the Goal level, mangrove loss showcases robust synergies with SDGs 12 (Responsible Consumption and Production) and 13 (Climate Change), and mangrove metrics such as tropical storm frequency and mangrove change, indicating strong interdependences between mangrove forests and SDGs. The result indicates that improved performance of climate change and responsible consumption can greatly enhance mangrove forests' performance in alleviating mangrove loss and reducing tropical storms. Moreover, our analysis underscores the central roles played by ‘bridge’ Goals. Indicator-level space details how they warrant prioritization because of their cascade synergistic enhancements across widely interconnected indicators, triggering systematic positive improvements. Turning to Indonesia, we advocate a strategic shift from solely expanding mangrove extent to focusing on four critical policy priorities: effective nitrogen management, enhancing Ramsar site efficiency, optimizing logistic performance, and addressing urban population conditions. These priorities are pivotal to seeking complementarities between Indonesia's international sustainability commitment and fostering mangrove restoration success.

Inhibit or promote: Spatial impacts of multifunctional farmland use transition on grain production from the perspective of major function-oriented zoning

Ensuring global sustainable development depends on achieving food security, a goal intrinsically linked to the farmland's grain production capacity. Despite its critical importance, the comprehensive spatial effects of multifunctional farmland use transition (MFFUT) on grain production, particularly from a production-living-ecology perspective, remain insufficiently explored. Addressing this gap, this study employs geospatial analysis techniques and spatial econometric models to examine the spatial impacts of MFFUT on grain production in the Huang-Huai-Hai Plain (HHHP), North China, from the perspective of Major Function-oriented Zoning (MFZ) during 2000–2020. The findings reveal an overall upward trend in grain production in HHHP, with main agricultural production zones emerging as significant grain bases. MFFUT considerably enhances local grain production while suppressing production in neighbouring areas. Specifically, Production Function Farmland Use Transition (PFFUT) and Living Function Farmland Use Transition (LFFUT) stimulate grain production in both local and neighbouring areas, whereas Ecological Function Farmland Use Transition (EFFUT) negatively impacts neighbouring areas while simultaneously bolstering local production. The heterogeneous analysis demonstrates that MFFUT promotes grain production in different MFZs but adversely affects neighbouring regions within main agricultural production zones. Further analysis indicates that PFFUT, LFFUT, and EFFUT considerably enhance grain production across various MFZs. However, PFFUT and LFFUT detrimentally affect neighbouring grain production in main agricultural production zones. This research provides valuable insights for policymakers to formulate optimised land use allocation schemes, implement differentiated land use measures, and safeguard food security.

Tobacco as a promising crop for low-carbon biorefinery

Energy crops play a vital role in meeting future energy and chemical demands while addressing climate change. However, the idealization of low-carbon workflows and careful consideration of cost-benefit equations are crucial for their more sustainable implementation. Here, we propose tobacco as a promising energy crop because of its exceptional water solubility, mainly attributed to a high proportion of water-soluble carbohydrates and nitrogen, less lignocellulose, and the presence of acids. We then designed a strategy that maximizes biomass conversion into bio-based products while minimizing energy and material inputs. By autoclaving tobacco leaves in water, we obtained a nutrient-rich medium capable of supporting the growth of microorganisms and the production of bioproducts without the need for extensive pretreatment, hydrolysis, or additional supplements. Additionally, cultivating tobacco on barren lands can generate sufficient biomass to produce approximately 573 billion gallons of ethanol per year. This approach also leads to a reduction of greenhouse gas emissions by approximately 76% compared to traditional corn stover during biorefinery processes. Therefore, our study presents a novel and direct strategy that could significantly contribute to the goal of reducing carbon emissions and global sustainable development compared to traditional methods.

China's progress in synergetic governance of climate change and multiple environmental issues.

Advancing the synergetic control of climate change and environmental crisis is crucial for achieving global sustainable development goals. This study evaluates synergetic governance levels over climate change and four environmental issues at the provincial level in China from 2009 to 2020. Our findings reveal significant progress in China's coordinated efforts to mitigate carbon emissions, reduce air pollutants, and conserve water resources. However, there remains room for improvement in managing solid waste and protecting ecological systems and overall progress in synergetic governance has slowed since 2015. Employing a random forest model, we identify socio-economic factors with great influence on synergetic climate change and environmental governance, such as energy intensity, service sector development, electronic equipment manufacturing, and transportation. Additionally, we reveal nonlinear relationships between some factors and performance of environmental subsystems, including both plateau effects (e.g. output in the smelting of ferrous metals) and U-shaped patterns (e.g. output in the manufacturing of metal products), possibly attributed to constraints in end-of-pipe treatment capacities and complexities in supply chain networks. Furthermore, through hierarchical clustering analysis, we classify provinces into four groups and provide tailored recommendations for policymakers to enhance synergetic governance levels in their respective regions. The framework established in this study also serves as a valuable reference for countries seeking to develop practical and context-specific solutions to mitigate climate and environmental risks.

Assessment of climatic influences on net primary productivity along elevation gradients in temperate ecoregions

Elevation gradients significantly influence net primary productivity (NPP), but the relationship between elevation, climate variables, and vegetation productivity remains underexplored, particularly in diverse ecological zones. This study quantifies the impact of elevation and climatic variables on NPP in northern Pakistan, hypothesizing that elevation modulates NPP through its influence on temperature and precipitation patterns. Using remote sensing data (MODIS ERA5) and advanced ecological models like the Eddy Covariance-Light Use Efficiency (EC-LUE) model and the Thornthwaite Memorial Model (TMM), we analyzed Gross Primary Productivity (GPP) dynamics across various vegetation types and elevations from 2001 to 2023. Our findings show a mean annual NPP of 323.46 g C m-2 a-1, with an annual increase of 5.73 g C m-2 a-1. Significant elevation-dependent variations were observed, especially in mid-elevation zones (401 to 1600 meters), where NPP increased at a rate of 0.174 g C m-2 a-1 per meter (R² = 0.808, p < 0.01). In contrast, higher elevations (2800-5200 meters) exhibited a decline in NPP, decreasing by -0.171 g C m-2 a-1 per meter (R² = 0.905, p < 0.001). Temperature and precipitation were key drivers, with precipitation positively correlating with NPP across all vegetation types, particularly in Evergreen Needleleaf and Broadleaf Trees. The EC-LUE model's GPP estimates closely matched MODIS data (R² = 0.82), demonstrating the model's reliability. These findings highlight the critical role of elevation and climatic factors in vegetation productivity and underscore the need for targeted ecological management and conservation strategies. The insights from this research are vital for global climate adaptation policies and sustainable development goals, contributing to ecological resilience and carbon sequestration efforts worldwide.

Reinforcement learning for occupant behavior modeling in public buildings: Why, what and how?

Effective control of energy consumption in public buildings holds paramount significance for global sustainable development. However, uncertainty in occupant behavior during operational phase often leads to a substantial discrepancy between the designed and actual energy consumption. While there is existing research on occupant behavior in public buildings utilizing stochastic modeling, statistical modeling, data mining, and agent-based modeling methods, the connotations and formation mechanisms have not been systematically revealed, rendering these developed models weak in applicability and reliability in practical scenarios. Reinforcement learning, which can perceive aspects of external environment and learn from stochastic interactions spontaneously, has been distinguished as a promising method for occupant behavior modeling. This research aims to develop a paradigm for reinforcement learning application in occupant behavior modeling in public buildings. Semi-structured interviews and literature review were combined to collect relevant information, while reasons for using reinforcement learning and applicable algorithms were discerned through qualitative analysis. Finally, detailed frameworks were proposed and validated through focus groups, offering a comprehensive guide that will serve as a reference for future research. This includes steps for collecting occupant-related data, selecting appropriate algorithms, and training and deploying reinforcement learning agents effectively. This research innovatively proposed a “panorama” of reinforcement learning for occupant behavior modeling in public buildings, laying a solid foundation for indoor environment and energy efficiency improvement in public building operations.

Disparities in public transport accessibility in London from 2011 to 2021

Addressing urban inequalities has become a pressing concern on both the global sustainable development agenda and for local policy. Improving public transport services is seen as an important area where local governments can exert influence and potentially help reduce inequalities. Existing measures of accessibility used to inform decision-making for public transport infrastructure in London show spatial disparities, yet there is a gap in understanding how these disparities vary across demographic groups and how they evolve over time—whether they are improving or worsening. In this study, we investigate the distribution of public transport accessibility based on ethnicity and income deprivation in London over the past decade. We used data from the Census 2011 and 2021 for area-level ethnicity characteristics, English Indices of Deprivation for income deprivation in 2011 and 2019, and public transport accessibility metrics from Transport for London for 2010 and 2023, all at the small area level using lower super output areas (LSOAs) in Greater London. We found that, on average, public transport accessibility in London has increased over the past decade, with 78% of LSOAs experiencing improvements. Public transport accessibility in London showed an unequal distribution in cross-sectional analyses. Lower income neighbourhoods had poorer accessibility to public transportation in 2011 and 2023 after controlling for car-ownership and population density. These disparities were particularly pronounced for underground accessibility. Temporal analyses revealed that existing inequalities with respect to income deprivation and ethnicity are generally not improving. While wealthier groups benefited most from London Underground service improvements; lower income groups benefited more from bus service improvements. We also found that car ownership levels declined in areas with substantial increases to public transport accessibility and major housing developments, but not in those with moderate improvements.

Measuring transport-associated urban inequalities: Where are we and where do we go from here?

ABSTRACT Reducing urban inequalities is at the forefront of the global sustainable development agenda, as well as national and local policies. While existing measures of inequality are mostly focused on income and wealth, it is widely recognised that non-monetary disparities such as in health, education, and housing play a crucial role in creating and reinforcing inequalities. Transport plays a central role in mitigating inequalities by enhancing access to employment, education, and essential services. It is also directly and indirectly related to disparities in housing, neighbourhoods, and health. Policymakers increasingly recognize the potential of transport policies in addressing inequalities; however, the effects of interventions need to be understood beyond the transport sector only and should consider wider impacts. In this review, we concentrate on three interlinked sectors – housing, land-use, and transportation – where local governments possess some capacity to influence the processes by which inequalities are created and exacerbated. Currently, empirical research on inequalities within these domains is fragmented. Models and datasets used for scenario testing, planning, and intervention evaluation are often disjointed, sector-focused, and rarely consider distributional effects. Our aim is to critically review the literature across different disciplines and perspectives and propose future interdisciplinary directions towards better measurement and modelling of transport-associated inequalities.