Search Results (979)

With growing environmental pressure and tightening resource constraints, artificial intelligence has become a key technical path for urban low-carbon transformation. This study aims to empirically examine whether and how AI-oriented pilot policies affect green economic efficiency (GEE) and identify its underlying mechanisms and boundary conditions. Taking China’s National New-Generation Artificial Intelligence Innovation Development Pilot Zone (NAIDPZ) as a quasi-natural experiment, we use a staggered difference-in-differences model to test the policy effect based on panel data of 267 Chinese prefecture-level cities from 2007 to 2023, with a series of robustness checks to ensure the reliability of the conclusion. We find that the NAIDPZ policy significantly improves urban GEE, with a stronger effect in inland, central, and non-resource-based cities. The composite NAIDPZ policy effect is associated with higher GEE, mainly through green technological innovation and industrial structure optimisation, while its impact is positively moderated by government attention and public environmental attention. These conclusions provide empirical reference for global governments to optimise artificial intelligence policies for low-carbon development. Full article

The low-carbon transformation of the manufacturing industry is a key path to balance climate goals and industrial competitiveness. This systematic review critically analyzes 145 studies from 2012 to 2025 to explore the low-carbon transformation. Findings show that low-carbon city pilots reduce manufacturing carbon intensity via fiscal and tech expenditures; industrial internet and additive manufacturing reshape low-carbon production, with digital and green process innovations driving emission reduction. Yet, bottlenecks exist: SMEs face digital adaptation and green financing constraints; excessive digitalization causes energy rebound; high-carbon industries’ deep decarbonization is hindered by unproven large-scale economic feasibility of low-carbon tech, alongside policy-technological disconnection, and green finance structural contradictions. This study proposes core solutions: dynamic policy adjustment mechanisms, multi-dimensional SME support systems, and technology–economy coupling evaluation models. It establishes research coordinates for academia, designs policy tools for decision-makers, and provides a technological framework for industrial deep decarbonization, offering global references for balancing climate goals and manufacturing competitiveness. Full article

Although urban resilience is a complex concept, several initiatives have made it more tangible. Urban public authorities and policymakers are of utmost importance, as they influence multiple neighbourhoods, stakeholders and aspects of urban resilience. Nevertheless, the role of individual facilities—such as sports fields—should not be overlooked. While their impacts are smaller in scale, they can significantly enhance local resilience and serve as inspirational pilots for broader initiatives. To assess resilience at the facility scale, an existing assessment framework was adapted, aligned with ESG (environmental, social and governance) criteria and climate action pillars and valuing ecosystem services. In the sports field case study, stormwater was reframed from a burden into a resource and integrated with other scheduled resilience-enhancing interventions: water conservation, installation of photovoltaic panels, enhanced tree shading, and circularity through sports equipment reuse. Together, these interventions strengthen urban sustainability, resilience, and climate adaptation while delivering ecological and social benefits. The stormwater drainage system was modelled to simulate naturalization actions. The assessment framework is described, and its application at both neighbourhood and facility scales is discussed. Comparisons between the existing and improved situations show clear resilience gains, and opportunities for extending these measures to the city scale are explored. Full article

Utilizing panel data from prefecture-level and above cities in China, this study conceptualizes the “Made in China 2025” pilot policy as a quasi-natural experiment and applies a multi-period difference-in-differences (DID) methodology to assess the policy’s impact on carbon emission efficiency. The findings reveal several key insights: (1) The “Made in China 2025” pilot policy significantly enhances carbon emission efficiency, a result robust to various checks, including placebo tests. (2) Heterogeneity analysis indicates that the policy markedly improves carbon emission efficiency in resource-based and larger cities, with less pronounced effects in non-resource-based and smaller cities. (3) Non-linear regression analysis suggests that the policy’s benefits are more substantial in cities with higher initial levels of carbon emission efficiency, whereas its positive impacts are less evident in cities with lower efficiency levels. (4) Spatial effect analysis demonstrates that the policy not only boosts local carbon emission efficiency but also exerts a significant demonstrative effect on neighboring cities. (5) Mechanism analysis reveals that the policy primarily enhances carbon emission efficiency through the promotion of green technological innovation and the facilitation of industrial upgrading, without invoking a reinforced environmental regulation mechanism during the study period. (6) Extension analysis indicates the presence of regional convergence in carbon emission efficiency. While the “Made in China 2025” pilot policy aids in elevating efficiency levels, it does not actively foster convergence. The outcomes of this study offer substantial theoretical underpinnings for the implementation of industrial policies and the formulation of urban low-carbon development strategies. Full article

External shocks and uncertainty have increased the need for urban economic resilience. As an institutionalized form of digital trade, China’s cross-border e-commerce (CBEC) Comprehensive Pilot Zones may strengthen cities’ adaptive capacity by lowering trade frictions and improving network connectivity. Using the staggered establishment of China’s CBEC Comprehensive Pilot Zones as a quasi-natural experiment, this study examines the causal and spatial effects of CBEC policy on urban economic resilience. Based on a balanced panel of 297 Chinese cities from 2011–2023, we construct a GDP-based counterfactual resilience index and estimate policy impacts with a multi-period difference-in-differences (DID) model, complemented by a spatial Durbin model (SDM). Results show that CBEC pilot zones significantly enhance urban economic resilience, with event-study estimates indicating that the effect emerges after implementation and strengthens over subsequent years. Mechanism tests suggest that the resilience gains operate through increased entrepreneurial vitality, deeper financial development, and higher green innovation output. Spatial estimates further reveal pronounced positive spillovers: policy-induced improvements in one city raise resilience in neighboring cities within the urban network. Heterogeneity analyses indicate stronger effects in large cities and in eastern and central regions, while effects are weaker in western cities. These findings highlight CBEC-oriented digital governance as an effective lever for building resilient urban economies and support cross-city coordination to amplify regional resilience dividends. Full article

Reducing agricultural emissions is vital for climate mitigation, yet evidence on green finance’s potential to facilitate agricultural decarbonization—particularly in China—remains scarce. Leveraging China’s Green Finance Reform and Innovation Pilot Zones as a quasi-natural experiment, this study employs a staggered difference-in-differences design and complementary Callaway-Sant’Anna estimates. Using a balanced panel of 282 prefecture-level and above cities spanning 2012–2022—a window covering five pre-policy years before the initial 2017 pilot rollout and sufficient post-policy years to capture dynamic effects for the 2017, 2019, and 2022 cohorts—this study assesses the policy impact on agricultural carbon emission intensity. The findings reveal that the pilot policy reduces emission intensity by approximately 9.2% on average. This result is robust across event-study analyses, placebo tests, PSM-DID, policy interference checks, and alternative outcome specifications. Channel-consistent evidence suggests that the effect operates through three mechanisms: greener credit allocation, stronger green technological innovation, and lower-carbon adjustment of the agricultural production structure. The effect is larger in eastern China, major grain-producing regions, and cities with higher levels of financial development, and exhibits a strengthening trend over time. By analyzing China’s city-based pilot approach, this study demonstrates how financial policy can support agricultural decarbonization in settings characterized by dispersed emitters, imperfect environmental monitoring, and strong food-security constraints. The findings extend beyond China to inform other developing economies seeking non-price-based pathways to greener agriculture. Full article

In response to global climate change, low-carbon transition in the industrial sector has become essential for emission reduction. Industrial parks, as concentrated centers of production, are major sources of urban energy use and carbon emissions. Whether park-based policy interventions can generate broader decarbonization effects remains unclear. This study conceptualizes China’s National Low-Carbon Industrial Park Pilot Policy (NLCIPP) as a meso-level systemic intervention and examines its impact on urban carbon intensity (UCI). Using panel data for 282 Chinese cities from 2006 to 2020, causal effects are identified through a multi-period DID framework combined with a synthetic DID approach. The results show that the NLCIPP significantly reduces UCI, indicating that energy-oriented interventions at the industrial park level can induce broader decarbonization outcomes. The policy effect mainly works via reduced energy consumption and enhanced green technological capability, while the contribution of industrial structural upgrading is relatively limited. Stronger impacts appear in central regions, cities with stricter environmental regulation, and non-resource-based cities, highlighting the context-dependent effectiveness of energy transition policies. These findings provide empirical evidence for designing effective industrial energy policies to promote low-carbon transition. Full article

Promoting digital governance is a key direction for the Chinese government’s governance reform. Based on panel data from 280 prefecture-level and above cities spanning 2008–2023, this study treats the “National Pilot Policy for Information Benefiting the People” as a quasi-natural experiment. Employing a difference-in-differences model, it examines the impact of government digital governance on urban innovation and its underlying mechanisms. Findings indicate that digital governance significantly enhances urban innovation, with conclusions remaining robust after rigorous stability tests and endogeneity treatments. Mechanism tests reveal that digital governance enhances urban innovation by cultivating innovation entities, improving the innovation environment, and optimizing the allocation of innovation elements. Further analysis indicates that the impact of digital governance on urban innovation is influenced by city location and development level. In eastern regions, areas with lower government fiscal pressure, and regions with higher levels of informatization, government digital transformation is more effective in boosting urban innovation. In addition, digital governance has significantly promoted sustainable and strategic innovation in cities and can influence innovation in neighboring areas through spillover effects. These findings can provide valuable insights for promoting urban innovation. Full article

Enhancing urban ecological resilience (UER) is crucial for mitigating soil erosion, improving land use efficiency, and preventing ecological degradation. The digital–real economy integration (DRI) plays a pivotal role in strengthening UER, offering a vital pathway for modernizing ecological governance systems and capabilities in the Yellow River Basin (YRB). Based on ecological resilience theory, this study establishes a three-dimensional evaluation framework centered on “resistance–recovery–adaptation”. Using panel data from 78 cities in the YRB from 2011 to 2023, we empirically examine the impact of DRI on UER. The results indicate that DRI significantly improves UER in the YRB, with notably strong positive effects on recovery and adaptation capacities, although there is no significant effect on resistance capacity. Mechanism analysis reveals that DRI promotes UER primarily through three channels: upgrading the industrial structure, strengthening government governance, and spurring green technological innovation. Heterogeneity analysis further shows that the positive impact of DRI on UER is more pronounced in downstream cities, urban agglomerations, non-resource-based cities, key environmental protection cities, green data center pilot cities, and informatization–industrialization integration pilot cities. Spatial analysis confirms DRI generating positive spatial spillover effects on the UER of neighboring cities. This study provides a theoretical basis for understanding the ecological governance potential of DRI and offers policy insights to support coordinated digital and green transformation in the YRB. Full article

Ulaanbaatar, the capital of Mongolia, operates one of the world’s largest district heating (DH) systems in the coldest national capital (heating degree-days ~5800). Despite serving over 60% of the city’s 1.6 million residents, the current 3rd generation DH system suffers from high thermal losses (~17–18%) and relies on coal-fired combined heat and power plants. Transitioning to 4th generation district heating (4GDH) with lower supply temperatures could reduce these losses while enabling future low-temperature renewable energy integration. A geographic information system (GIS)-based spatial heat load density (HLD) analysis uses operational data from the Ulaanbaatar District Heating Company, encompassing 13,500 buildings with a total connected capacity of 3924 MW. Grid-based spatial analysis was performed at two resolutions (1 km² and 2 km²). Threshold sensitivity analysis was conducted across HLD criteria of 1–5 MW/km². Results indicate that median HLD values exceed the European reference threshold of 3 MW/km², with log-normal distributions confirmed by Shapiro–Wilk tests. Three candidate pilot zones were identified. A hybrid temperature strategy (65/35 °C above −25 °C; 90/60 °C below) further contextualizes the findings. These results suggest spatially favorable conditions for 4GDH development, providing a quantitative foundation for subsequent techno-economic feasibility studies. Full article

In the context of global climate governance, green technology innovation is essential for urban sustainable development. To address the limitations of traditional linear econometric models, this study investigates the impact of the National Innovative City Pilot Policy on green innovation using a novel framework combining a Multi-period Difference-in-Differences model and Deep Learning Counterfactual Prediction. Analyzing panel data from 100 eastern Chinese cities between 2004 and 2023, the research reveals that the policy significantly and robustly enhances innovation levels in pilot cities. Furthermore, the policy operates through a dual-track synergistic governance mechanism, successfully combining government scientific and technological support with environmental regulation. Additionally, heterogeneity analysis reveals that the policy exerts a more pronounced driving effect on green innovation in small-to-medium-sized cities and regions with lower industrial upgrading levels. Finally, deep learning counterfactual trajectories demonstrate that the policy dividend exhibits a non-linear, long-term cumulative effect that expands over time—a dynamic that traditional linear models often underestimate. Ultimately, this study provides solid empirical evidence that a combined governance system of incentives and constraints effectively promotes innovation-driven, sustainable urban transitions. Full article

This paper proposes a replicable, city-oriented workflow to support the preliminary screening of photovoltaic (PV) opportunities in Bogotá, Colombia, by integrating (i) georeferenced spatial inventories (roofs/land), (ii) solar-resource modeling based on local meteorological stations and radiation models, and (iii) an optional 3D module (LiDAR/DSM) to refine shading and orientation losses when higher-resolution data are available. Rather than claiming a complete citywide quantification from exhaustive building-level inputs, the workflow is demonstrated through two institutional case studies (public schools) selected to represent contrasting urban morphologies. The results show how the approach consistently transforms spatial constraints and solar estimates into comparable technical and economic indicators for decision-making at the site level. Finally, a practical scale-up pathway is described to extend the same logic from pilots to citywide portfolios through batch processing of urban footprints and the progressive enrichment of inputs—from 2D GIS screening to targeted 3D refinement—while preserving transparency and traceability of assumptions. For the two case study sites, the workflow yielded preliminary PV capacities of 72.6 and 95.0 kWp, with year-1 generation of 90.2 and 115.0 MWh, respectively. The IRR values achieved were between 18.9 and 19.5%, the simple payback period was approximately five years, and the LCOE was between 0.051 and 0.053 USD/kWh. It should be noted that the generation was reported as a central estimate with ±25% tolerance to reflect interannual solar resource variability. Full article

This study analyzes the impact of China’s smart city pilot policy (CSCP) on green total factor energy efficiency (GTFEE) using panel data from 245 cities (2006–2021). Applying the multi-period difference-in-differences (DID) method, results show that CSCP significantly promotes GTFEE. CSCP improves urban GTFEE by about 6.18%. Meanwhile, CSCP contributes to the enhancement of GTFEE by stimulating green technological innovation and improving the efficiency of resource allocation. These impacts are particularly evident in cities characterized by higher levels of digitalization, peripherality, and being non-resource-based. The findings provide a framework for advancing urban green transitions and integrating smart and green development strategies, highlighting the importance of technology innovation in global energy governance. Full article

Vehicle-mounted sensing enables high-resolution urban monitoring but remains constrained by heterogeneous multimodal integration, intermittent connectivity, privacy-sensitive visual data, and the absence of enforceable multi-provider governance. This paper introduces a governance-aware private cloud architecture that treats provider isolation, role-based access control, and privacy-by-design as core architectural properties rather than application-layer add-ons. The layered, containerised microservice design supports asynchronous store-and-forward ingestion, modality-specific processing pipelines, and GPU-accelerated object detection for structured metadata extraction. A key innovation is ingestion-time visual abstraction, which structurally separates raw imagery from derived observations and enforces lifecycle-based retention policies, embedding data minimisation directly into the data flow. The fully open-source implementation is validated through a two-month multi-provider pilot with continuous multimodal collection. Results demonstrate stable ingestion without data loss, real-time visual inference (~200 ms per frame), strict provider-level isolation under concurrent access, and up to 95% storage reduction via metadata abstraction. The findings establish a replicable architectural paradigm for scalable, privacy-aware, multi-actor mobile sensing infrastructures suitable for metropolitan-scale smart city deployment. Full article

Against the backdrop of global climate change, enhancing urban adaptive capacity to climate shocks has become a critical issue for sustainable urban development. Based on this, this study treats the Climate-Adaptive City Pilot (CACP) policy in China as a quasi-natural experiment and employs a difference-in-differences (DID) approach to empirically evaluate its impact on urban ecological resilience, using panel data from Chinese prefecture-level cities from 2010 to 2023. Heterogeneity and mechanism analyses are further conducted to explore differential policy effects and underlying transmission channels. The results indicate that the Climate-Adaptive City Pilot policy significantly enhances urban ecological resilience, and this finding remains robust after a series of robustness checks, including winsorized regressions, propensity score matching, time placebo tests, and individual placebo tests. Further analysis reveals that the policy effects are more pronounced in cities with lower or higher levels of human capital development, as well as in cities with low to medium water resource endowments. Mechanism analysis suggests that resilient infrastructure investment and green technological innovation constitute the key pathways through which the pilot policy improves urban ecological resilience. From the perspective of urban ecological resilience, this study provides empirical evidence on the effectiveness of climate-adaptive city pilot policies and offers important policy implications for deepening the implementation of climate-adaptive city initiatives, designing context-sensitive adaptation strategies, and improving urban climate adaptation governance mechanisms. Full article