The climate benefits, co-benefits, and trade-offs of green infrastructure: A systematic literature review

Comparative analysis of visual-thermal perceptions and emotional responses in outdoor open spaces: Impacts of look-up vs. look-forward viewing perspectives

Horizontal and vertical viewing perspectives exert varying influences on the environmental perceptions and emotional states of college students. Despite this, scant research addresses the impact on this demographic. We selected typical campus open spaces for comprehensive physical parameter assessments, encompassing meteorological and spatial characteristics. A cohort of 36 healthy college students participated in a questionnaire survey designed to ascertain shifts in visual comfort, thermal comfort, and emotional responses when viewing landscapes in look-forward and look-up orientations. Key findings following both viewing modalities included: 1) a notable rise in mean visual comfort vote (MVCV), by 1.22 for look-forward and 1.01 for look-up, with a pronouncedly higher sunlight sensation vote (SSV) for the latter orientation; 2) a significant increase in thermal comfort vote (TCV), although the difference in increments between the two viewing angles was minimal; 3) Positive affect (PA) exhibited considerable improvement in both viewing conditions, while negative affect (NA) was markedly reduced in the look-up condition relative to look-forward viewing; 4) The SSV was predominantly influenced by the trunk ratio and canopy-to-trunk ratio, with substantial weights of 31.47% and 32.15%, respectively. Landscape element diversity emerged as the most critical factor affecting visual comfort vote (VCV) and aesthetic assessment score (AAS), with overwhelming weights of 70.67% and 63.15%, respectively. Moreover, the leaf ratio was identified as the chief determinant of emotional responses. Our results provide insights into the design of campus spaces for enhanced student well-being.

Urban greening in Dhaka: Assessing rooftop agriculture suitability using GIS and MCDM techniques

Dhaka ranks among the world's most densely populated cities, with built-up areas expanding to accommodate the demands of a growing population. The rapid urbanization has reduced green space and exacerbated urban heat and pollution in the city. In the quest for a greener and healthier urban environment, rooftop agriculture has emerged as a promising solution, offering opportunities for the restoration of the environment and safe food production. Despite its potential, limited studies have explored the viability of this alternative greening solution for Dhaka. Therefore, this study aims to assess the suitability of rooftops for agricultural activities employing Geographic Information System (GIS) and Multi-Criteria Decision Making (MCDM) techniques. First, seven criteria were selected based on the literature, such as building age, height, rooftop size, building utility, property value, sunlight, and water availability. Second, an expert opinion survey was conducted using the Best Worst Method (BWM) to calculate the criteria's weights. Finally, the suitability map for Dhaka was derived by combining the criteria layers and was subsequently validated. Rooftop area and property value were identified as the most and least important criteria. Approximately 9% (6.27 km2), 68% (46.59 km2), 22% (15.15 km2), and a negligible portion (0.1 km2) of Dhaka city has been classified as highly suitable, suitable, moderately suitable, and not suitable, respectively, for rooftop agriculture. By identifying and promoting the most suitable locations for rooftop agriculture and highlighting existing opportunities, this research will help to initiate and expand sustainable agriculture practices that can contribute to climate change adaptation and urban resilience.

Green infrastructure layout based on a dynamic operation feature of drainage systems

Increasingly frequent urban floods strain the traditional grey infrastructure, overwhelming the capacity of drainage networks and causing challenges in managing stormwater. The heavy precipitation leads to flooding and damage to drainage systems. Consequently, efficient mitigation strategies for flooding have been researched deeply. Green infrastructure (GI) has proved to be effective in responding the increasing risk of flood and alleviate pressure on drainage systems. However, as the primary infrastructure of stormwater management, there is still a lack of attention to the dynamic operation feature of urban sewer systems during precipitation events. To fill this gap, we proposed a novel approach that integrates hydraulic characteristics and the topological structure of a sewer network system. This approach aims to identify influential nodes, which contribute to the connectivity of the sewer network amidst dynamic changes in inflow during precipitation events. Furthermore, we adopted rain barrels to serve as exemplars of GI, and 14 GI layout schemes are produced based on the different ranks of influential nodes. Implementing GI measures on both poorly performing and well-performing nodes can yield distinct benefits in mitigating node flooding. This approach provides a new perspective for stormwater management, establishing effective synergy between GI and the drainage system.

Modeling benefits and tradeoffs of green infrastructure: Evaluating and extending parsimonious models for neighborhood stormwater planning

Green infrastructure is often proposed to complement conventional urban stormwater management systems that are stressed by extreme storms and expanding impervious surfaces. Established hydrological and hydraulic models inform stormwater engineering but are time- and data-intensive or aspatial, rendering them inadequate for rapid exploration of solutions. Simple spreadsheet models support quick site plan assessments but cannot adequately represent spatial interactions beyond a site. The present study builds on the Landscape Green Infrastructure Design (L-GrID) Model, a process-based spatial model that enables rapid development and exploration of green infrastructure scenarios to mitigate neighborhood flooding. We first explored how well L-GrID could replicate flooding reports in a neighborhood in Chicago, Illinois, USA, to evaluate its potential for green infrastructure planning. Although not meant for prediction, L-GrID was able to replicate the flooding reported and helped identify strategies for flood control. Once evaluated for this neighborhood, we extended the model to include water quality through the representation of dispersion and settling mechanisms for two pollutant surrogates-total nitrogen and total suspended solids. With the extended model, Landscape Green Infrastructure Design Model-Water Quality (L-GrID-WQ), we examined benefits, costs, and tradeoffs for different green infrastructure strategies. Bioswales were slightly more effective than other green infrastructure types in reducing flooding extent and downstream runoff and pollution, through increased infiltration and settling capacity. Permeable pavers followed in effectiveness and are suggested where spatial constraints may limit the installation of bioswales. Although green infrastructure supports both flooding and pollution control, small tradeoffs between these functions emerged across spatial layouts: strategies based on only curb-cuts better controlled pollution, while layouts that followed the path of water flow better controlled flooding. By illuminating such tradeoffs, L-GrID-WQ can support green infrastructure planning that prioritizes unique concerns in different areas of a landscape.

Review of emerging contaminants in green stormwater infrastructure: Antibiotic resistance genes, microplastics, tire wear particles, PFAS, and temperature

Green stormwater infrastructure is a growing management approach to capturing, infiltrating, and treating runoff at the source. However, there are several emerging contaminants for which green stormwater infrastructure has not been explicitly designed to mitigate and for which removal mechanisms are not yet well defined. This is an issue, as there is a growing understanding of the impact of emerging contaminants on human and environmental health. This paper presents a review of five emerging contaminants - antibiotic resistance genes, microplastics, tire wear particles, PFAS, and temperature - and seeks to improve our understanding of how green stormwater infrastructure is impacted by and can be designed to mitigate these emerging contaminants. To do so, we present a review of the source and transport of these contaminants to green stormwater infrastructure, specific treatment mechanisms within green infrastructure, and design considerations of green stormwater infrastructure that could lead to their removal. In addition, common removal mechanisms across these contaminants and limitations of green infrastructure for contaminant mitigation are discussed. Finally, we present future research directions that can help to advance the use of green infrastructure as a first line of defense for downstream water bodies against emerging contaminants of concern.

Modeling place-based nature-based solutions to promote urban carbon neutrality

Nature-based solutions (NbS) are recognized as widely available and cost-effective mechanisms for sequestering carbon and offsetting carbon emissions. Realistic NbS implementations for carbon neutrality need to be effective at the global level and also appropriate for the socio-economic and physical conditions prevailing at the local level. This paper presents a framework that can help stakeholders identify demands, locations, and types of NbS interventions that could maximize NbS benefits at the local scale. Key processes in the framework include (1) interpolating carbon emissions data at larger spatial scales to high-resolution cells, using land use and socio-economic data; (2) assessing NbS effects on carbon reduction and their location-related suitability, through qualitative literature review, and (3) spatially allocating and coupling multiple NbS interventions to land use cells. The system was tested in Stockholm, Sweden. The findings show that the urban center should be allocated with combinations of improving access to green spaces and streetscapes, while the rural and suburban areas should prioritize preserving and utilizing natural areas. Our proposed method framework can help planners better select target locations for intended risk/hazard-mitigating interventions.

Civil society involvement in the governance of green infrastructure: An analysis of policy recommendations from EU-funded projects

Green Infrastructures (GI) help build and develop climate resiliency and biodiversity. Moreover, the ecosystem services (ESS) that GI generates can be a source of social and economic value. Public policies to support GIs are necessary, but they cannot be successful without the involvement of relevant stakeholders. Because GI is a rather obscure concept for most non-specialists, their contribution to sustainability is not always apparent, and this makes it difficult to mobilize resources. This paper analyzes the policy recommendations of 36 projects focused on GI governance, funded by the European Union (EU) in the last decade or so. Using the Quadruple Helix (QH) approach, we find that GIs are perceived as a mostly governmental responsibility, with civil society and business engaged to a limited extent. We argue that non-governmental players should be more actively involved in decisions concerning GI to foster more sustainable development.

Multi-objective optimization methodology for green-gray coupled runoff control infrastructure adapting spatial heterogeneity of natural endowment and urban development

Cost-effective runoff control scheme drafting involves localization, multi-sector coordination, and configuration of multifunctional infrastructures. Numerous independent variables, parameters, weights, and objectives make runoff control optimization quantitatively arduous. This study innovatively proposed a multi-objective optimization methodology for green-gray coupled runoff control infrastructure adapting spatial heterogeneity of natural endowment and urban development. The quantitative methods of multi-objective evaluation, hydrological feature partition, and pressure-adapted multi-objective weight assignment were proposed. Remote sensing inversion of water quality, hydrological model simulation (using SWAT and SWMM software), landscape pattern index calculation, life cycle cost (LCC), life cycle assessment (LCA) on ecological impact, and NSGA-II optimization algorithm were applied. Wuhan, the most water-sensitive city in China, was studied as a case. Runoff control function (RCF), capital investment (CI), and ecological return on investment (EROI) served as optimized objectives. High, medium, and low built-up regions in Wuhan urban development planning district were extracted by topographic factors and landscape patterns, which comprised 28, 34, and 38% of the case area, respectively. Three corresponding hydrological models were then built to illustrate distinct runoff control cost-efficiency in each region. Pressure distributions on runoff control, economic constraints, and ecological resource scarcity were quantitatively evaluated. And four pressure zones were clustered, which occupied 36, 29, 16, and 19% of the case area, respectively. Then the zonal weighted optimization decision-making matrix (with 3 hydrological models and 5 wt) was established by overlaying the pressure zone and built-up zone. In high, medium, and low built-up regions, optimized solutions reduced annual runoff volume by 86, 82%, and 77%The average runoff investments per square meter of impervious underlying surface in high, medium, and low built-up regions were 34.2, 18.7, and 7.9 RMB yuan, respectively. Medium and low built-up regions may only need 55 and 23% of the high built-up region for the unitary impervious underlying surface to balance runoff control and ecological benefits. Runoff control and financial utilization efficiency enhance with hydrological differentiation zones. Thus, the optimization solutions are zonal adaptive, refined, comparable, replicable, and implementable.

Assessment of street forest characteristics in four African cities using google street view measurement: Potentials and implications

Accurate information on urban forests of tree sizes, health state, community structures, and spatial distribution is still limited in African cities. Using a Google Street View (GSV)-based tree-size measuring method developed by our team, this paper aims to evaluate street trees of four African metropolitan cities using GSV data. The study compiled a large dataset with 46,016 street trees in 3454 sites in Kampala, Nairobi, Bloemfontein, and Johannesburg. The data including tree size (diameter at breast height, DBH; tree height, TH; underbranch height, UBH; canopy size), tree floristic composition (apical dominance types, broadleaf-conifer-palm leaf, flowering or not), tree health (leaf color, diebacks, dead tree, and bracket-supporting percent), streetside development (lane number, roadside shops, parking vehicle, and pedestrian density), and geolocation (latitude, longitude). These data can be spatially visualized with the help of ArcGIS, and the large dataset favors reliable maps from the street-view level. Data statistics showed that four cities were dominated by broad-leaved, apical dominance, and flowering trees, with a low level of unhealthy leaves and a tiny percentage of dead. The arbor-shrubs-herb structure vegetation dominated all four cities. Kampala had the most slender trees (DBH = 23 cm, TH = 8.4 m), while Nairobi and Johannesburg had the thickest trees (DBH = 38 cm, TH = 8.5-8.6 m). Bare land rates were lowest at 23% in Bloemfontein and highest at 33% in Nairobi. Principal analysis and Pearson correlations showed that these tree variations were closely associated with street development and local land use configuration. By comparing the urban tree data in other regions of the world, we found that the trees in African cities are generally giant but have a lower density (the trees within a 100-m street segment). Our findings emphasized that GSV data is feasible enough for urban forest monitoring in Africa, and the database is helpful for urban landscape planning and management.

Co-Benefits of China's Carbon Emissions Trading Scheme: Impact Mechanism and Spillover Effect

Based on the panel data of 281 prefecture-level cities in China, from 2007 to 2017, we empirically explore the co-benefits of the carbon emissions trading scheme. We found that the carbon emissions trading scheme effectively achieved the coordinated control of carbon dioxide and air pollutants, by improving the green production level of the pilot areas, reducing the regional industrial output, and promoting the upgrading of the industrial structure. In terms of heterogeneity, the emissions trading scheme shows obvious urban location and level heterogeneity, in terms of coordinated control. The synergistic emission reduction effects of eastern and central cities are significantly better than those of cities in central and western regions and non-central cities. It has also had positive spillover effects on the surrounding cities of the pilot areas, but pollution levels in farther areas may have increased due to possible "pollution shelter problems".

Multi-stage planning of LID-GREI urban drainage systems in response to land-use changes

Long-term planning of urban drainage systems aimed at maintaining the sustainability of urban hydrology remains challenging. In this study, an innovative multi-stage planning framework involving two adaptation pathways for optimizing hybrid low impact development and grey infrastructure (LID-GREI) layouts in opposing chronological orders was explored. The Forward Planning and Backward Planning are adaptation pathways to increase LID in chronological order based on the initial development stage of an urban built-up area and reduce LID in reverse chronological order based on the final development stage, respectively. Two resilience indicators, which considered potential risk scenarios of extreme storms and pipeline failures, were used to evaluate the performance of optimized layouts when land-use changed and evolved over time. Compared these two pathways, Forward Planning made the optimized layouts more economical and resilient in most risk scenarios when land-use changed, while the layouts optimized by Backward Planning showed higher resilience only in the initial stage. Furthermore, a decentralized scheme in Forward Planning was chosen as the optimal solution when taking costs, reliability, resilience, and land-use changes into an overall consideration. Nevertheless, this kind of reverse optimization order offers a novel exploration in planning pathways for discovering the alternative optimization schemes. More comprehensive solutions can be provided to decision-makers. The findings will shed a light on the exploration of optimized layouts in terms of spatial configuration and resilience performance in response to land-use changes. This framework can be used to support long-term investment and planning in urban drainage systems for sustainable stormwater management.

Mapping the planet's critical natural assets

Sustaining the organisms, ecosystems and processes that underpin human wellbeing is necessary to achieve sustainable development. Here we define critical natural assets as the natural and semi-natural ecosystems that provide 90% of the total current magnitude of 14 types of nature's contributions to people (NCP), and we map the global locations of these critical natural assets at 2 km resolution. Critical natural assets for maintaining local-scale NCP (12 of the 14 NCP) account for 30% of total global land area and 24% of national territorial waters, while 44% of land area is required to also maintain two global-scale NCP (carbon storage and moisture recycling). These areas overlap substantially with cultural diversity (areas containing 96% of global languages) and biodiversity (covering area requirements for 73% of birds and 66% of mammals). At least 87% of the world's population live in the areas benefitting from critical natural assets for local-scale NCP, while only 16% live on the lands containing these assets. Many of the NCP mapped here are left out of international agreements focused on conserving species or mitigating climate change, yet this analysis shows that explicitly prioritizing critical natural assets and the NCP they provide could simultaneously advance development, climate and conservation goals.

Sustainable pathways towards climate and biodiversity goals in the UK: the importance of managing land-use synergies and trade-offs

Agricultural and environmental policies are being fundamentally reviewed and redesigned in the UK following its exit from the European Union. The UK government and the Devolved Administrations recognise that current land use is not sustainable and that there is now an unprecedented opportunity to define a better land strategy that responds fully to the interconnected challenges of climate change, biodiversity loss and sustainable development. This paper presents evidence from three pathways (current trends, sustainable medium ambition, and sustainable high ambition) to mid-century that were co-created with UK policymakers. The pathways were applied to a national integrated food and land-use model (the FABLE calculator) to explore potential synergies and trade-offs between achieving multiple sustainability targets under limited land availability and constraints to balance food supply and demand at national and global levels. Results show that under the Current Trends pathway all unprotected open natural land would be converted to urban, agriculture and afforested land, with the consequence that from 2030 onwards tree planting targets could not be met. In contrast, the two sustainable pathways illustrate how dietary change, agricultural productivity improvements and waste reduction can free up land for nature recovery and carbon sequestration. This enables a transition to a sustainable food and land-use system that provides a net carbon sink with up to 44% of land able to support biodiversity conservation. We highlight key trade-offs and synergies, which are important to consider for designing and implementing emerging national policies. These include the strong dependence of climate, food and biodiversity targets on dietary shifts, sustainable improvements in agricultural productivity, improved land-use design for protecting and restoring nature, and rapid reductions in food loss and waste.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11625-022-01242-8.

Rethinking urban park irrigation under climate change

Climate change is forcing cities to reassess their water management practices, particularly for water-intensive applications like park irrigation. If water scarcity requires governments to deviate from current park management norms and allocate less water towards parks, it is essential that park managers design spaces that maintain community wellbeing. We apply the hedonic pricing method and use detailed park management information to assess the value of parks in a region where local climatic conditions require extensive irrigation to keep turf green, and where climate change is further constraining water supplies. Here we show that the impacts of irrigation on the value of parks differ depending on the dwelling types of the nearby housing populations that they serve. In most cases, the convention that parks have to be irrigated to deliver ecosystem services to the public is supported. However, we find that non-irrigated park areas are also valued positively by nearby apartment dwellers. Accelerating rates of urbanization and shifts towards high-density living may support the development of more diverse park options that are less water-intensive. Increased visibility of these alternative park forms, which could include more areas of native vegetation that do not require irrigation, may subsequently influence public expectations for landscape design.

Using artificial intelligence to make sustainable development decisions considering VUCA: a systematic literature review and bibliometric analysis

Sustainable development emergent subfields have been rapidly evolving, and their popularity increased in recent years. Sustainable development is a broad concept having numerous sub-concepts including, but not limited to, circular economy, sustainability, renewable energy, green supply chain, reverse logistics, and waste management. This polymorphism makes decision-making in this field to be an abstruse task. In this perplexing circumstance, the presence of VUCA conditions makes decision-making even more challenging. By taking advantage of artificial intelligence tools and approaches, this paper aims to study with a concentration on sustainable development-related decision-making under VUCA phenomena elements using bibliometric and network analyses which can propose numerous novel insights into the most recent research trends in this area by analyzing the most influential and cited research articles, keywords, author collaboration network, institutions, and countries that finally provides results not previously fully comprehended or assessed by other studies on this topic. In this study, an extensive systematic literature review and bibliometric analysis are conducted using 534 research articles out of more than 3600. From the content analysis part, four clusters have been found. The decision parameters, presumptions, and research goal(s) for each model are pointed out too. The findings contribute to both conceptual and practical managerial aspects and provide a powerful roadmap for future research directions in this field, such as how real-life multidimensionality can be considered in sustainable development-related decision-making, or what are the effects of the VUCA in sustainable development considering the circular economy and waste management intersection.

Decision-Making Framework for GI Layout Considering Site Suitability and Weighted Multi-Function Effectiveness: A Case Study in Beijing Sub-Center

The effectiveness of runoff control infrastructure depends on infrastructure arrangement and the severity of the problem in the study area. Green infrastructure (GI) has been widely demonstrated as a practical approach to runoff reduction and ecological improvement. However, decision-makers usually consider the cost-efficacy of the GI layout scheme as a primary factor, leading to less consideration of GI’s environmental and ecological functions. Thus, a multifunctional decision-making framework for evaluating the suitability of GI infrastructure was established. First, the study area was described by regional pollution load intensity, slope, available space, and constructible area. Then, to assess the multifunctional performance of GI, a hierarchical evaluation framework comprising three objectives, seven indices, and sixteen sub-indices was established. Weights were assigned to different indices according to stakeholders’ preferences, including government managers, researchers, and residents. The proposed framework can be extended to other cities to detect GI preference.

Green, hybrid, or grey disaster risk reduction measures: What shapes public preferences for nature-based solutions?

Nature-based solutions (NbS) contrast with grey infrastructure measures to reduce risk from natural hazards. Using natural and sustainable measures (green) or combining green with grey elements (hybrid) can provide important co-benefits beyond risk reduction. Thanks to their co-benefits and flexibility across a range of possible climate change futures, NbS are sometimes referred to as 'win-win' or 'no-regret' measures. The success of NbS and associated projects often relies on the public for co-creation, co-implementation, and long-term sustainable use, monitoring, and management. However, the relative importance of NbS benefits is defined by the perceptions and underlying values of stakeholders with potentially divergent interests. It is unclear what measures at-risk individuals may prefer on the green-hybrid-grey spectrum and what shapes their preferences, including perceived benefits and potential regret. Identifying public (mis)perceptions, expectations, objectives, and what underlies these can inform communication and project framing, engagement, and ultimately increase public acceptance and continued uptake of NbS. We use citizen surveys at three distinct European sites where NbS are being planned and in-depth focus groups as a follow-up in the site at risk of landslides (Catterline, Scotland). Preferences and their drivers for measures on the green-hybrid-grey spectrum are assessed, focusing on public perceptions of NbS effectiveness, risk, and nature. We find that although wildlife habitat and aesthetics as co-benefits are important, reducing risk is of primary concern. Uncertainty in the strength and effectiveness of NbS, as one of 13 qualitative factors we identify, drives public preferences towards hybrid measures - seen as balancing green and grey trade-offs. Misperceptions and a demand for NbS information should be addressed with experiential learning, combined with transparent two-way communication of expectations. We urge caution and further research regarding emphasizing co-benefits and the 'natural' framing of NbS when risk reduction is the primary public objective.

Ecosystem Benefits Provision of Green Stormwater Infrastructure in Chinese Sponge Cities

The Sponge City Development (SCD) concept was initiated in 2012 to address severe urban flooding and water quality challenges in China. Green stormwater infrastructure (GSI) such as rain gardens have been adopted as critical stormwater management tools. Existing GSI research has focused primarily on their environmental performance, overlooking the human dimensions. The co-benefits of GSI have been particularly underinvestigated. We used social surveys (n = 607) and expert interviews (n = 11) to explore public perception of SCD and GSI in four pilot sponge cities, examining flood experience, stormwater concerns, GSI familiarity, institutional trust, and GSI benefit perception. The survey found high exposure to flooding, medium GSI familiarity, and strong institutional trust. The public showed greater concern on stormwater impacts on their quality-of-life than the water environment, rating the less-intended aesthetic and health values as the best-perceived benefits. Experience, familiarity, concern, trust, age, and city significantly affected GSI benefit perception. In contrast, the experts spoke more positively about the environmental benefits while indicating the inadequacy of public participation. The case of GSI in SCD offers broad implications for environmental governance and expert-public relationships in an era of rapid social, technological, and environmental change. Refining policies and regulations to incorporate social goals, bringing the public into the SCD process, and building up the GSI industry's capacity in planning, design, construction, and maintenance are critical to enhancing GSI benefits provision. Adopting the co-benefits approach will be essential to utilizing GSI as a place-making tool to create more sustainable and livable communities.

Statistical modelling of hydrological performance in a suite of green infrastructure practices

Statistical modelling procedures (feature selection in conjunction with multiple linear regressions) were applied to determine the performance of a suite of stormwater green infrastructures (GIs) installed at the Belknap Campus of the University of Louisville. Two separate multiple linear regression models (MLRMs) were developed and calibrated to estimate the reductions of the flow regime parameters (flow volume and peak flow rates) within the down-gradient combined sewer system (CSS). The developed MLRMs showed that wet-weather-related CSS flow was mitigated post implementation of the stormwater GIs. At the down-gradient combined sewer flow-monitoring site, the average reduction rates of flow volume and the peak flow were estimated to be 22 and 63% per rainfall event, respectively. Unlike the black-box nature of most machine-learning techniques, the MLRM has the advantage of showing the unique statistical relationship between the rainfall features and the investigated CSS flow parameters. The results from this study indicate that proper statistic modelling can be applied effectively to evaluate the hydrological performance of stormwater management practices when lacking instrumentation and having limited drainage or sewer information.

Does Air Pollution Impact Fiscal Sustainability? Evidence from Chinese Cities

Fiscal sustainability is an issue of great concern for governments globally and air pollution control has become an important factor affecting fiscal sustainability. This study aims to examine the impact of air pollution on fiscal sustainability in the short and long run. We conducted an empirical analysis based on air pollution and local government debt data on China’s prefecture-level cities in 2014–2019, using regression discontinuity design (RDD) and a panel data model. The results show that air pollution reduces the debt burden of governments in the short run. However, in the long run, addressing the negative impacts of air pollution adds to the debt burden of local governments, hindering fiscal sustainability. Fiscal freedom and the level of public services significantly moderate the negative impact of air pollution on fiscal sustainability. A higher level of fiscal freedom generally indicates a greater incentive for local governments to raise pollutant emission standards, strengthen the construction of green infrastructure, and subsidize green enterprises. Furthermore, a higher level of public services reflects better infrastructure and higher levels of investment in environmental protection, which help to reduce the negative impact of air pollution. The governments are suggested to take measures to effectively control air pollution, so as to enhance fiscal stability in the long run.