Urban Climate最新文献

{"title":"Gustatory perception and its influence on emotional and psychological responses under outdoor thermal stress","authors":"Xiaoxi Wang ,&nbsp;Pei Deng ,&nbsp;Xinyue Zhang ,&nbsp;Meiheng Zhai ,&nbsp;Guanning Shang ,&nbsp;Bo Hong","doi":"10.1016/j.uclim.2025.102416","DOIUrl":"10.1016/j.uclim.2025.102416","url":null,"abstract":"<div><div>We investigated the interaction between thermal and gustatory environments in three outdoor spaces in China's cold region: an open square (OS), a tree-shaded space (TS), and a landscape pavilion (LP). Three gustatory stimuli (<em>Lycopersicon esculentum</em> var. <em>cerasiforme</em> A. Gray, <em>Prunus persica</em> ‘<em>Compressa</em>’, and <em>Prunus avium</em> ‘Mei Zao’) and a control group (no stimulus) were used. The electroencephalograms (EEGs) of 72 subjects were monitored pre- and post-stimulation alongside meteorological data. Subjective questionnaire, state anxiety scale and restoration outcome scale were used to evaluate perceptual changes, emotional regulation, and psychological recovery. Factors influencing thermal-gustatory perception under varying physiological equivalent temperatures (PET) were analyzed. Results showed significant interactions between space and gustatory type on thermal sensation vote, gustatory sensation vote, and gustatory comfort vote (GCV), with GCV affecting thermal comfort vote. In OS, <em>L. esculentum</em> better alleviated anxiety than <em>P. avium</em>. In TS, <em>P. avium</em> was most effective for stress relief and cognitive enhancement, while <em>P. persica</em> in LP had the greatest psychological recovery impact. Gustatory stimuli's influence on β relative power increased and on θ relative power decreased from open to shaded spaces. Sour taste was optimal for relaxation in OS and LP, while crisp and slightly soft textures were preferred in TS and LP. As PET rose, thermal-gustatory interaction's effect on thermal perception strengthened, while its effect on gustatory perception initially reduced then augmented. All gustatory stimuli significantly affected EEG signals, with thermal-gustatory interaction most significant on psychological recovery at 31.79 °C ≤ PET &lt;47.49 °C.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102416"},"PeriodicalIF":6.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ambient environmental exposures while cycling on a vegetated trail versus the road","authors":"Kevin Lanza ,&nbsp;Brendan Allison ,&nbsp;Baojiang Chen ,&nbsp;Preston S. Wilson ,&nbsp;Ethan T. Hunt ,&nbsp;Kathryn G. Burford ,&nbsp;Yuzi Zhang ,&nbsp;Leigh Ann Ganzar ,&nbsp;Timothy H. Keitt","doi":"10.1016/j.uclim.2025.102429","DOIUrl":"10.1016/j.uclim.2025.102429","url":null,"abstract":"<div><div>Cycling can improve health, yet cyclists in cities may be exposed to hazardous conditions and have limited exposure to nature and its benefits. The purpose of this study was to measure and compare environmental exposures of urban cyclists on a vegetated, gravel trail route separated from cars and a fully paved route on local roads. In September 2021 in Austin, Texas, US, we cycled on the trail and road routes from 7:30–8:30 and 17:30–18:30 on one weekday and weekend day. While cycling, we wore sensors that measured fine particulate matter (PM2.5), total volatile organic compounds (VOCs), sounds, air temperature, relative humidity, light intensity, and geographic location. We used a neural network to distinguish anthropogenic and natural sounds. After time-matching all sensor data, we specified linear mixed effects models to test the association between route type and each environmental exposure, adjusting for afternoons and weekdays. We also used inverse distance weighting in GIS to map spatially continuous estimates of environmental exposures for each cycling trip. Compared to the road route, the trail was associated with higher levels of PM2.5, total VOCs, natural sounds, and relative humidity, and lower levels of anthropogenic sounds, temperature, and light intensity (<em>p</em> &lt; 0.05). Mapping illustrated differences in environmental exposures within and between routes by time of day and day of week. Assessing exposures on existing and planned cycling routes may help inform the design of health interventions (e.g., tree planting along routes) in the face of increasing climate-related hazards.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102429"},"PeriodicalIF":6.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the intricate dynamics of PM2.5 sulfate aerosols in the urban boundary layer: A pioneering two-year vertical profiling and machine learning-enhanced analysis in global Mega-City","authors":"Hongyi Li ,&nbsp;Ting Yang ,&nbsp;Yifan Song ,&nbsp;Ping Tian ,&nbsp;Jiancun He ,&nbsp;Yining Tan ,&nbsp;Yutong Tian ,&nbsp;Yele Sun ,&nbsp;Zifa Wang","doi":"10.1016/j.uclim.2025.102424","DOIUrl":"10.1016/j.uclim.2025.102424","url":null,"abstract":"<div><div>Sulfate (SO₄²⁻) aerosols, a predominant chemical constituent of fine particulate matter (PM_2.5), wield profound influences on urban atmospheric environments, climate dynamics, and public health. While advancements have been made in understanding the formation mechanisms of ground-level SO₄²⁻, the scarcity of long-term, continuous vertical measurements has limited our understanding of SO₄²⁻ production across the entire boundary layer. This study bridges this gap by integrating two-year vertical profiles of aerosol components, derived from ground-based remote sensing data, with an advanced, interpretable machine learning model. We quantified the contributions of meteorological parameters and chemical species to SO₄²⁻ concentrations within 150–1500 m altitudes. The contributions of meteorological parameters in the boundary layer (54.87 %-65.29 %) exceed those of chemical species (34.71 %-45.13 %), with relative humidity and temperature as the main driving factors. Regional transport driven by southwest winds also increases SO₄²⁻ concentrations. Hydrogen peroxide (H₂O₂) serves as the primary oxidizing agent, and the acid-buffering capability of ammonia must not be disregarded. A substantial rise in the proportion of summertime SO₄²⁻ in PM_2.5 has been observed, with its proportion in the upper boundary layer reaching 30.29 %. This phenomenon mainly results from intensified photochemical reactions in the afternoon, whereby SO₂ oxidation facilitated by ozone, H₂O₂, and nitrogen dioxide promotes SO₄²⁻ production in the upper boundary layer. Our findings highlight that ground-based remote sensing retrieval can interpret the long-term continuous vertical distribution of aerosol components, thus providing a new perspective on elucidating the complex formation mechanisms of aerosol components within the boundary layer.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102424"},"PeriodicalIF":6.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143835114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate sensitive designs for policy makers: How LES model resolution affects accuracy in capturing urban micro-scale weather during heatwaves","authors":"Leyla Sungur ,&nbsp;Wolfgang Babel ,&nbsp;Eva Späte ,&nbsp;Johann Schneider ,&nbsp;Christoph K. Thomas","doi":"10.1016/j.uclim.2025.102400","DOIUrl":"10.1016/j.uclim.2025.102400","url":null,"abstract":"<div><div>Climate sensitive designs have been implemented recently in science to fill the niche of developing scientific tools to help mitigating urban heat island effects. A model capable of identifying hot and cool spots and testing adaptation and mitigation strategies to form recommendations for policy makers is in high demand. We present a novel two-step validation approach using 1) absolute comparison and 2) space-time evaluation of model performance across resolutions and against observations ensemble-averaged for representative urban microclimate types. Two Large Eddy Simulation (LES) models with 5 m and 20 m resolution are evaluated against a 14-point measurement station network during an extreme heatwave in Germany. To show space time behavior relationship between model and measurements, multiresolution decomposition (MRD) was used to investigate air temperature, specific humidity, and wind speed across time scales ranging from 11.25 to 180 min. The MRD analysis revealed strong correlations between stations with similar microclimatic conditions. Increasing model resolution did not uniformly improve accuracy across all climate elements; wind speed showed the greatest benefit from higher resolution. Absolute comparisons between simulations and observations demonstrated well-represented diurnal cycles for 5 m wind speed, whereas scalar variables remained sensitive to land surface parameterization. The simulated specific humidity exhibited deviations from measurements and nighttime air temperature tended to be overestimated. Space-time behavior instead was generally well captured except for nighttime specific humidity. This study contributes to correctly identifying and quantifying urban heat effects during extremes and supports urban planners and decision-makers in evaluating modeling tools for spatial planning.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102400"},"PeriodicalIF":6.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An approach for analyzing unpredicted heat and precipitation events using spatiotemporal big data: A case study of Indian Western coastal cities","authors":"Rachana Patil ,&nbsp;Meenal Surawar","doi":"10.1016/j.uclim.2025.102414","DOIUrl":"10.1016/j.uclim.2025.102414","url":null,"abstract":"<div><div>Climate change-related impacts have recently increased. Extreme precipitation and heat events are gaining attention because of their catastrophic damage, unpredictability and large spatial reach. Assessing such catastrophic events in a densely populated country such as India is critical because it exposes a large population to risk. This study is based on the approach that can be adopted to examine such unpredictable events. The whole-to-part approach is adopted, considering the region as a whole and urban areas as a part. This will provide a large spatiotemporal contextual understanding of a region, that must be considered when recommending mitigation strategies at the urban scale. The unpredicted future risk owing to unpredicted heat and precipitation events in the summer and winter seasons is analyzed using Coupled Model Intercomparison Project Phase 6 multimodel climate projections for the near future period 2020–2039 and the far future period 2080–2099 under Shared Socioeconomic Pathways for the entire region. This will reveal the spatial distribution of the potential risk of heat and precipitation events, guiding the formulation of policies at the municipal level in line with the severity of the potential risk event in that area. Furthermore, an analysis is conducted on the tier 2 cities in this region to identify and outline the vulnerable areas. It is essential to consider the regional context when implementing policies in this vulnerable area. By adopting this approach, it becomes possible to prevent both financial losses in investments and potential risks to human lives that may arise from insufficiently accurate predictions of such exceptional events.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102414"},"PeriodicalIF":6.0,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the status of ecosystem regulating services in the urbanising Rainforest and Guinea savanna ecological regions of Nigeria using InVEST models","authors":"Rotimi Oluseyi Obateru ,&nbsp;Appollonia Aimiosino Okhimamhe ,&nbsp;Olutoyin Adeola Fashae ,&nbsp;Adeyemi Oludapo Olusola ,&nbsp;Deirdre Dragovich ,&nbsp;Christopher Conrad","doi":"10.1016/j.uclim.2025.102410","DOIUrl":"10.1016/j.uclim.2025.102410","url":null,"abstract":"<div><div>Maintaining an equilibrium between the rapid pace of urbanisation and the demand for urban ecological well-being amid climate change remains a global challenge. This study integrates machine learning and geospatial techniques with biophysical models to investigate the changes in ecosystem regulating services (ERS), such as carbon stock and climate regulation, in cities of the Rainforest (Akure and Owerri) and Guinea savanna (Makurdi and Minna) ecological regions of Nigeria in 2002 and 2022. Landsat images were processed using the random forest (RF) machine learning classifier, with the Normalised Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) serving as indicators of landscape changes. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) platform was deployed to assess carbon storage and sequestration, and cooling and heat mitigation (HMI) services. Urban and agricultural expansion was associated with a drastic depletion of ERS within a 5 km–10 km radius of the urban core, resulting in an 8.60 %–33.83 % decline in carbon stock and a 5 %–13 % decline in HMI across cities. Correlation and geographically weighted regression models revealed that in the Rainforest (Akure and Owerri), carbon sequestration and heat mitigation are more influenced by LST, with strong correlations in Akure (<em>r</em> = 0.499) and Owerri (<em>r</em> = 0.408). In the Guinea savanna, carbon sequestration pattern in Makurdi is influenced by LST (<em>r</em> = 0.419), while Minna shows a stronger influence of NDVI on both carbon stock and heat mitigation. This highlights the influence of urbanisation and ecological variations in providing urban ERS and underscores the importance of enhancing vegetation biomass through existing urban and rural afforestation frameworks and sustainable agricultural practices. These measures are crucial for improving carbon stock, enhancing the heat mitigation potential of urban areas, and mitigating the impacts of further climate change.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102410"},"PeriodicalIF":6.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143817617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atmospheric oxidation, sources, budget of nitrous acid in an emerging city of Central China: Based on seasonal perspectives","authors":"Nan Jiang ,&nbsp;Xibin Ma ,&nbsp;Ruixin Xu ,&nbsp;Yunfei Wei ,&nbsp;Ruiqin Zhang","doi":"10.1016/j.uclim.2025.102411","DOIUrl":"10.1016/j.uclim.2025.102411","url":null,"abstract":"<div><div>Nitrous acid (HONO) significantly affects atmospheric oxidation ability by generating hydroxyl radicals (·OH). A year-long observational study (2017–2018) was conducted in a central plain city with ammonia-rich conditions and high PM_2.5 pollution. The study monitored HONO concentrations across different seasons to assess the seasonal impacts of PM_2.5 and NH₃ on HONO formation via heterogeneous conversion. The HONO levels were highest in autumn and lowest in winter, with consistent diurnal variations peaking at 07:00 and reaching a nadir at 16:00. Homogeneous reactions contributed 22.6 % to 96.8 % to nocturnal HONO accumulation, with the highest average HONO/NO₂ ratio observed during summer nights (9.7 %) compared to other seasons (5.0 %–6.2 %). Heterogeneous conversion at night was regulated by relative humidity (RH). The presence of abundant NH₃ and PM_2.5 pollution appeared to enhance the conversion efficiency of NO₂. The net primary production rate of ·OH generated by diurnal HONO (P_·OH(HONO)) and O₃ (P_·OH(O₃)) was calculated for each season. The rate of P_·OH(HONO) / (P_·OH(HONO) + P_·OH(O₃)) varied across the seasons from 10.9 to 92.0 % (from highest to lowest as winter &gt; spring &gt; autumn &gt; summer). This study enhances the understanding of the contribution of HONO to atmospheric oxidation across different seasons, particularly in ammonia-rich and polluted environments, and underscores the need for targeted pollution control strategies that consider these interactions.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102411"},"PeriodicalIF":6.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban Heat Island research using remote sensing: A bibliometric review with special reference to India","authors":"Rhitwik Gupta ,&nbsp;Ashwani Kumar","doi":"10.1016/j.uclim.2025.102403","DOIUrl":"10.1016/j.uclim.2025.102403","url":null,"abstract":"<div><div>Climate change is one of the prime concerns in the contemporary world, mainly due to the global proliferation of urban areas. This leads to the Urban Heat Island (UHI) effect, where the temperature of the city core is warmer than its non-urban surroundings and is known to affect inhabitants' lives. To better understand the phenomenon, Remote Sensing has proved to be a valuable tool for studying the phenomenon, its physics and its implications. Due to India's exponential urbanisation, studying the UHI effect and developing tailored mitigation policies is critical. This review intends to assist researchers, policymakers, and institutions by aiding informed decision-making for future research trajectory and policy formulation through an extensive review of the research studies conducted on the UHI effect using Remote Sensing and subsequently comparing the research status of India vis-a-vis the world. By incorporating rigid inclusion and exclusion criteria consisting of various keywords, top citations, and publication year range of the past 15 years, i.e., 2009 to 2023, a total of 94 papers out of a pool of 576 articles were meticulously reviewed for bibliometric trends, technical specifications and methodologies. These papers were also scoped for proposed mitigation strategies, if any. The review finds that the number of papers published saw a two-fold growth after 2015, which was the year when the Paris Agreement was signed. Globally, this number declined in 2020 due to the COVID-19 pandemic, while in the case of India, this effect became evident in 2021. Within India, North and North-Eastern regions need more studies in this subject matter. A review of satellites and sensors employed in these papers revealed that none of the satellites used were Indian, indicating a gap in disseminating the technical database and the need to increase technical capacity for research purposes. Additionally, studies using remote sensing technologies to study the UHI effect do not explore or suggest any mitigation strategies, leaving a gap in this remote sensing-led UHI research area.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102403"},"PeriodicalIF":6.0,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143820261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of downscaling technology for land surface temperature: A case study of Shanghai, China","authors":"Shitao Song ,&nbsp;Jun Shi ,&nbsp;Dongli Fan ,&nbsp;Linli Cui ,&nbsp;Hequn Yang","doi":"10.1016/j.uclim.2025.102412","DOIUrl":"10.1016/j.uclim.2025.102412","url":null,"abstract":"<div><div>Rapidly urbanizing megacities face multiple challenges such as heat island effect and ecological degradation. High-precision land surface temperature (LST) data is critical for optimizing urban planning and environmental management. However, the spatial resolution of LST data obtained by satellite alone is low, which has certain limitations in urban-scale analysis. Based on ECMWF ERA5-Land reanalysis data, Landsat, Sentinel and other remote sensing data, as well as ground station observation data, this paper takes Shanghai, China as a case study, uses two machine learning algorithms, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost), and Multiple Linear Regression (MLR) method, to downscale and monitor LST with fine resolution. Results show that the three downscaling methods all have good fitting effects, with XGBoost emerging as a standout performer, with an impressive coefficient of determination (R²) of 0.97, a minimal root mean square error (RMSE) of 1.14 °C and a mean absolute error (MAE) of 1.85 °C. MODIS data is further upgraded from low resolution to higher resolution, and finally realizes multi-level downscaling from 1000 m to 30 m and 10 m, which greatly improves the monitoring accuracy of LST in urban areas, and supports the identification and evaluation of subtle spatial differences in heat island effect and microclimate characteristics. In addition, the results of this study have been successfully transferred to the Google Earth Engine (GEE) platform to achieve rapid update and analysis. This innovative application provides technical support for real-time and dynamic urban thermal environment monitoring, helping to optimize the management and decision-making of environmental resources.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102412"},"PeriodicalIF":6.0,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143808333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating the pollution abatement effect of artificial intelligence policy: Evidence from a quasi-natural experiment in China","authors":"Changfei Nie ,&nbsp;Zhanmei Huang ,&nbsp;Yuan Feng","doi":"10.1016/j.uclim.2025.102402","DOIUrl":"10.1016/j.uclim.2025.102402","url":null,"abstract":"<div><div>Artificial intelligence (AI) policy refers to a series of regulations, strategies and measures formulated by governments, international organizations or industry bodies to guide the research, development, deployment and application of AI. In recent years, the potential of AI policy in pollution abatement has received widespread attention. In this study, we use China's National New Generation Artificial Intelligence Innovation and Development Pilot Zone (AIIDPZ) policy as a quasi-natural experiment to evaluate the impact of AI policy on urban environmental pollution (EP). Specifically, we construct a staggered difference-in-differences (DID) model and find that the AIIDPZ policy help reduce EP. In terms of potential mechanisms, we find that the AIIDPZ policy mainly abate EP through increasing fiscal technology expenditure, improving the level of green technology innovation and promoting economic agglomeration. Heterogeneity test reveals that the pollution abatement effect is more significant in cities with high levels of EP, as well as eastern cities, southern cities, non-resource-based cities and gigabit cities. Our findings provide important references for policymakers to scientifically utilize AI policies to achieve sustainable development.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102402"},"PeriodicalIF":6.0,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143808387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}