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The phenomenon of seasonal hysteresis between urban heat islands (UHIs) and background surface temperature was reported in many studies, but a unifying explanation for the causes of its magnitude, shape and looping direction remained less clear, and the impacts of urban landscapes and background climate on such hysteresis were also the subject of enquiry. Here we performed a systematic study based on a long‐term offline simulation for surface energy budgets, surface air and skin temperature of the urban‐biosphere system in East China. It was carried out with an up‐to‐date land surface model — the CLM5‐LCZs (the Community Land Model version 5 (CLM5) coupled with a newly developed urban canopy model representing diverse urban landscapes with the local climate zones classification scheme). To isolate the causes of UHIs hysteresis, a simplified framework was constructed by combining a mathematical representation of grid/subgrid model outputs, the two‐resistance mechanism method and the time‐lagged cross correlation analysis. The results exhibited distinct hysteresis patterns of UHIs such as twisted, concave‐down, concave‐up and convex‐up curve across diverse background climates and urban landscapes. The basic shapes of hysteresis depict a gradual transition from concave/convex‐up to concave/convex‐down by characterized by a larger winter UHIs from a wetter and warmer climate to a drier and colder climate. Magnitude and seasonality of surface UHIs are separately dominated by the urban‐rural contrast of evapotranspiration and heat storage at daytime and nighttime, whereas across‐climate variations of daytime and nighttime surface UHIs hysteresis are regulated by the phase shift of convection efficiency and anthropogenic heat. Urban landscapes affect the hysteresis mainly by altering the amplitude rather than the shape of looping curves. Our work could provide a fuller picture of how to mitigate urban warming considering inter‐seasonal tradeoffs over a broader region. Plain Language Summary: The seasonality of urban heat islands (UHIs) has been investigated toward its characteristics and controls, of which analyses were conducted on several cities and left intra‐urban variations out of account. It was essential to understand whether the local seasonality‐arguments can be extended to broader geographic regions or lots of cities with different landscapes. In this study, an updated urban climate model describing intra‐urban heterogeneity better was utilized to simulate surface energy fluxes and UHIs. Based on the subgrid outputs of this model and the hypothesis of phase shift mechanism, we presented a simplified framework to isolate the contribution of time lags of different biophysical factors to the magnitude, shape and looping direction of UHIs hysteresis. These hysteretic characteristics are varied with background climates and urban landscapes. The time lags of evaporative cooling and heat storage corresponding to background surface temperature between urban and rural areas account for different hysteresis patterns at daytime and nighttime. Hysteretic typology for different urban classes or cities in diverse background climates is regulated by the time lead/lag of other secondary biophysical factors. The results could serve as a valuable reference for coping with the growing heat risk in cities. Key Points: The seasonality of surface and canopy urban heat island exhibited hysteresis‐like curves, whose looping patterns vary across background climate and urban featuresA simplified conceptual model to explain hysteretic behaviors was constructed based on a second‐order Fourier representation, the attribution method and a newly developed land surface modelThe urban‐biosphere time lags of evaporative cooling rates and storage heat, dominated such hysteresis at daytime and nighttime respectively [ABSTRACT FROM AUTHOR]

Few studies have investigated the spatial patterns of the air temperature urban heat island (AUHI) and its controlling factors. In this study, the data generated by an urban climate model were used to investigate the spatial variations of the AUHI across China and the underlying climate and ecological drivers. A total of 355 urban clusters were used. We performed an attribution analysis of the AUHI to elucidate the mechanisms underlying its formation. The results show that the midday AUHI is negatively correlated with climate wetness (humid: 0.34 K; semi-humid: 0.50 K; semi-arid: 0.73 K). The annual mean midnight AUHI does not show discernible spatial patterns, but is generally stronger than the midday AUHI. The urban–rural difference in convection efficiency is the largest contributor to the midday AUHI in the humid (0.32 ± 0.09 K) and the semi-arid (0.36 ± 0.11 K) climate zones. The release of anthropogenic heat from urban land is the dominant contributor to the midnight AUHI in all three climate zones. The rural vegetation density is the most important driver of the daytime and nighttime AUHI spatial variations. A spatial covariance analysis revealed that this vegetation influence is manifested mainly through its regulation of heat storage in rural land. [ABSTRACT FROM AUTHOR]

The frequent occurrence of extreme weather events has imparted significant pressure on urban ecosystem management. Evaluating the relationship between extreme climate risk (ECR) and urban ecological resilience (UER) is a key issue in achieving the green and sustainable development objectives of cities. This study measures UER in China from 2005 to 2020 using the entropy weight method–TOPSIS method, investigates the relationship between ECR and UER using the dynamic GMM model, and further explores the influencing mechanism. The results suggest that ECR has an inhibiting influence on UER. Additionally, the moderating mechanism investigation demonstrates that environmental regulation can mitigate the threat of ECR to UER to a certain extent, and with the regulation effect based on the government's environmental concern being better than that of the market pollution fee payment. The group test outcomes demonstrate that the discrepancies in regions and marketization lead to certain differences in the relationship between ECR and UER. Additional investigation indicates that ECR has an asymmetric relationship with UER at distinct quantiles. Our findings reflect the subtle associations between ECR and UER as a whole, and will help relevant organizations in formulating more precise and scientific policies to enhance urban ecological resilience. [ABSTRACT FROM AUTHOR]

This study aimed to utilize hybrid physics-based models that allow for a comprehensive evaluation of how solar–meteorological variables influence the fraction of absorbed photosynthetically active radiation (FAPAR). By integrating both physical and statistical approaches, these models provided a novel perspective on understanding the complex relationship between solar radiation and FAPAR dynamics. The integration of URE and CLC in studying ecosystem efficiency in the nations of China and India is crucial, owing to their interdependent nature. To achieve this, the coupled model intercomparison project phase 6 (CMIP6) was utilized, which involved interpolating data from the most recent five GCMs from the six-phase CMIP6. By integrating advanced modeling techniques with observational data, this innovative approach enabled a holistic assessment of the intricate connections between urban development, climate dynamics, and the productivity of surrounding ecosystems in these regions. The reported decline in FAPAR productivity in China and India highlights the growing concern over the impact of climate change on the health and resilience of vegetation. China experienced negative changes of −1.425, −0.414, and −0.018, while India reported negative changes of −2.463, 2.199, and 2.915 under different scenarios. Interestingly, despite these variations, both countries observed similar tidal variations in their seasonal bases, suggesting a consistent pattern in the fluctuations of vegetation productivity throughout the year. The authors of this study collected and analyzed extensive data on CLC and URE in order to investigate their impact on FAPAR fluctuations in China and India. The higher impact of URE compared to CLC in terms of effective contributions suggests that URE plays a crucial role in shaping the atmospheric physics of both China, accounting for 45.26%, and India, registering 33.95%. Conversely, the effects of CLC and PAR residual factor (PRF) were more pronounced in India compared to China, with impacts of 8.21% and 53.03% compared to 4.21% and 46.70%, respectively. [ABSTRACT FROM AUTHOR]

Climate change is an important issue for cities today and in the future. At present, China has a large population and complex climate conditions, and cities are also vulnerable to the adverse effects of climate change (Tian, Environ Sustain Dev 6: 153-155 2020). Three-dimensional greening can not only improve the green space system of a city but also have a far-reaching impact on the ecology, image, and economic benefits of a city. Therefore, the study of urban three-dimensional greening is an effective means to deal with climate change strategies. By exploring the influence of traditional greening and three-dimensional greening on Local Climate in Beilin District of Xi'an, Shaanxi Province, the mechanism of three-dimensional greening on urban ecological environment was discussed, and the ecological theory, urban three-dimensional greening theory, and urban local climate zone (LCZ) were referred to. Based on the methods of national climate monitoring, ENVI-met simulation, and field independent measurement, this paper selected a research sample site in the east section of Jianshe Road, Beilin District, Xi'an City, Shaanxi Province, China, and applied ENVI-met software to simulate the thermal stress relationship among building exterior surfaces, plants, and air in the street; quantified the overall ecology of the area; and used measuring instruments. The influence of different types of greening in the base on the site temperature, humidity, CO2 (carbon dioxide) concentration, wind speed, and other climate factors data was, respectively, measured and analyzed. The grid analysis was used to compare the traditional greening and three-dimensional greening, then the numerical differences of each impact factor were sorted out, and the effect of three-dimensional greening on the improvement of urban ecological environment was discussed by analyzing the climate factors with greater impact. The results show that (1) three-dimensional greening plus traditional greening is the most beneficial mode; (2) in the same environment, according to the parameter of 1.5 m from the ground in the model environment, it can be seen that the temperature of the space treated with three-dimensional greening of buildings is reduced by 3.5–3.6 ℃ compared with the control group, the relative humidity is different by 7–8%, the CO2 concentration is reduced by about 5%, and the spatial wind speed is relatively small. (3) When the urban green coverage rate is more than 40%, the improvement of temperature is more obvious, if it reaches 50%, the cool phenomenon in summer can be fundamentally changed. From the perspective of human perception, the PMV index increased by 0.27 on average. This paper discusses and analyzes the three-dimensional greening of urban streets in Beilin District, Xi'an City, Shaanxi Province, China, and studies its influence on urban ecology to different degrees. The conclusions are as follows: Different types of greening have different degrees of influence on urban climate. Meanwhile, the experimental results of this paper show that in cities like Xi'an, Shaanxi Province, China, where summer is hot, adding three-dimensional greening to traditional street greening can significantly improve the environmental microclimate, which is an effective means to cope with climate change, improve the site environment, and stabilize the urban ecosystem. [ABSTRACT FROM AUTHOR]

The urban climate has a critical influence on developing sustainable cities, and one important factor is the urban wind environment. Moreover, refining urban wind fields is required for the quantitative assessment of urban wind environments. Computational fluid dynamics (CFD) is a powerful tool for modeling the wind flow characteristics in urban areas. Although CFD has been widely used in various fields, its use for simulating urban wind fields has limitations because of the complexity of urban building models and the high computational workload. Accordingly, we consider the generalization parameters in the vertical and horizontal directions based on the CFD results and the building topology based on the state of the building nodes. We perform a two-dimensional generalization of building clusters, conduct spatial analysis in a geographic information system (GIS), and generate three-dimensional models. This generalization scheme is applied to Meiling Street in Jinjiang City, Fujian Province, China. The results indicate that the generalization decreases the number of buildings from 7003 to 3367 and the computation time from 11 h and 26 min to 10 h and 25 min. The computation efficiency is improved by 8.89%, with 1.85% changes in the average wind speed ratio. This scheme substantially improves the computational efficiency of urban wind field CFD simulations by reducing the geometric model's complexity without compromising the accuracy. This strategy is suitable for simulating large-scale urban wind fields. [ABSTRACT FROM AUTHOR]

Understanding the spatial and temporal variations of urban carbon dioxide fluxes ( F C O 2 ) and their influencing factors is crucial for solving urban climate problems and promoting the development of low-carbon cities. In this study, the carbon dioxide flux ( F C O 2 ) in Changsha City, China, was analyzed using the eddy covariance technique and flux footprint model. The results showed that the extent of the flux footprint within the observation site was mostly limited to 500 m. Diurnal variation of F C O 2 showed a regular pattern influenced by plant photosynthesis and traffic flow. Meanwhile, photosynthesis was directly regulated by photosynthetically active radiation and indirectly regulated by air temperature and water vapor pressure differences. The average value of F C O 2 was lower during the daytime than at night, indicating the high vegetation cover (43.5%) in the study area. In addition, there were spatial characteristics of F C O 2 in each wind direction due to different surface land use in the study area. Notably, a decreasing trend in carbon dioxide content was observed after the area covered by vegetation was 1.8 times the area of buildings and major roads combined. These findings guide climate management, urban planning, and sustainable development toward a low-carbon society. [ABSTRACT FROM AUTHOR]

The development and renewal of gas sensor technology have enabled more and more low-cost gas sensors to form a carbon monitoring network to meet the requirements of the city. In the context of China's commitment to achieving the "double carbon" target by 2060, this paper reviews the principles of four standard gas sensors and the application of several low-cost sensors in urban carbon monitoring networks, with the aim of providing a practical reference for the future deployment of carbon monitoring networks in Chinese cities. Moreover, the types, prices, and deployment of the sensors used in each project are summarized. Based on this review, non-dispersive infrared sensors have the best performance among the sensors and are commonly used in many cities. Lots of urban climate networks in cities were summarized by many reviews in the literature, but only a few sensors were studied, and they did not consider carbon dioxide (CO2) sensors. This review focuses on the dense CO2 urban monitoring network, and some case studies are also discussed, such as Seoul and San Francisco. To address the issue of how to better ensure the balance between cost and accuracy in the deployment of sensor networks, this paper proposes a method of simultaneously deploying medium-precision and high-precision fixed sensors and mobile sensors to form an urban carbon monitoring network. Finally, the prospects and recommendations, such as different ways to mitigate CO2 and develop an entire carbon monitoring system for future urban carbon monitoring in China, are also presented. [ABSTRACT FROM AUTHOR]

The urban expansion‐induced heat can exacerbate heat stress for urban dwellers, especially during heat waves. With a focus on the intra‐urban variability of urban heat islands (UHIs) and thermal comfort, the urban parameterization within the Community Land Model version 5 (CLM5) was modified incorporating the local climate zones (LCZs) framework, named CLM5‐LCZs, to simulate the urban climate during a heat wave (HW) event in the summer of 2013. The evaluation of model performance demonstrated that it did a reasonable job of simulating surface energy balance and thermal regimes in cities against observational fluxes from a flux tower measurement site and temperatures from automatic meteorological stations in Nanjing, China. Then we investigated the characteristics and causes of UHIs associated with local background climate, intra‐urban inhomogeneity and HW intensity in East China. The results exhibited that daytime and nighttime canopy urban heat island intensity (CUHII) were highest in the Compact Low Rise (LCZ3) and the Compact High Rise (LCZ1) areas, respectively, while surface urban heat island intensity (SUHII) peaked in the Large Low Rise (LCZ8) and the Compact High Rise (LCZ1) areas during daytime and nighttime, respectively. Urban dwellers were easier exposed to serious heat environment in LCZ3 and LCZ1 areas over the north subtropical climate zone. Contrasts of CUHII and SUHII among different urban classes could exceed 1.7°C and 5.4°C. The intra‐urban heterogeneity may alter the dominant factors controlling SUHII, which were also modulated by local climate and HW intensity. Unlike other controlling factors, the impact of local climate on the contribution from the urban‐rural contrast of convection efficiency was larger than urban features. Overall, CLM5‐LCZs displayed potential of implementing detailed simulations for inter‐ and intra‐city UHIs at a larger scale, and enhancing the capabilities in modeling urban climate and exploring the causes and controls of UHIs. Plain Language Summary: The Community Land Model Urban (CLMU) is the urban parameterization within the Community Land Model version 5 (CLM5) to simulate urban climate and human thermal comfort. The local climate zones (LCZs) framework has been utilized to facilitate communications and studies of urban climate knowledge, which was applied to update the CLMU by substituting the current urban density class representation in the model in this study. The modified model was evaluated by comparing its simulated results with observations to demonstrate its credibility. This work aimed to investigate: (a) the intra‐urban variability of urban heat islands (UHIs) and heat stress, (b) the impact of urban features on UHIs, (c) the response of UHIs, thermal comfort and controlling factors of UHIs to the occurrence of heat waves. It was useful to investigate the features, causes and controls of UHIs as well as the combined effects of between heat waves and UHIs for this model. The results indicated that temperature behaviors and thermal comfort levels varied with urban form and materials. This intra‐urban heterogeneity significantly affected quantitative contributions to surface UHIs from the urban‐rural contrast of various biogeophysical properties, which were regulated by local background climate and heat wave intensity. Key Points: The Community Land Model Urban (CLMU) was developed by incorporating the local climate zones (LCZs) frameworkThe intra‐urban variability of urban heat islands (UHIs) and urban thermal comfort modulated by background climate in the 2013 heatwave episode were exploredThe dominant factors of surface UHIs vary with intra‐urban heterogeneity and are also regulated by heat wave intensity and local climate [ABSTRACT FROM AUTHOR]

Urban areas mediate climate transformations and generate new forms of climate urbanism. Looking at climate action in the twelve fastest-growing cities in China with under one million people, this paper proposes a perspective on urban climate politics 'from elsewhere' that foregrounds the potential role of smaller urban areas in mediating climate transformations. The analysis reveals three climate action strategies that reflect practical, institutional, and personal spheres of climate transformations. Planning action in the personal sphere provides opportunities for urban transformations. A perspective 'from elsewhere' calls for greater attention to planning for diverse change strategies for climate transformation. [ABSTRACT FROM AUTHOR]

This paper studies climate change impacts on total factor productivity (TFP) in China using economic and climatic data for provincial capital cities and municipalities from 1998 to 2017. We employ a novel nonparametric quantile method to decompose historical temperature data into multiple temperature quantiles, which are then used in our regression analysis to avoid estimation bias caused by seasonal heterogeneity of temperatures across China. Specifically, we create three temperature quantiles for each city to represent their extremely high temperatures in summer, extremely low temperatures in winter, and mild temperatures in spring and fall. In general, we find that a warming climate has a significant negative impact on TFP in the long-run, while in the short term, only increases in extreme temperatures exert significant negative effects on TFP growth. However, the temperature effects on TFP vary substantially across coastal capital cities, inland capital cities, and municipalities due to their differences in geography, development levels, and political positions. Finally, our results are robust when spatial spillover, temporal lagging, and labor intensity effects are taken into account. [ABSTRACT FROM AUTHOR]

The Local Climate Zone (LCZ) classification scheme is a vital method of building a category dataset for high-resolution urban land. For the development of urban meteorology, air pollution and related disciplines, the high-resolution classification data of urban buildings are very important. This study aims to create LCZ datasets with detailed architectural characteristics for major cities and urban agglomerations in China, and obtain more accurate results. We constructed 120 m resolution land use datasets for 63 cities (mainly provincial capitals, municipalities directly under the Central Government, important prefecture-level cities and special administrative regions) and 4 urban agglomerations in China based on the local climate zone (LCZ) classification scheme using the World Urban Database and Access Portal Tools method (WUDAPT). Nearly 100,000 samples were used, of which 76,000 training samples were used to provide spectral signatures and 23,000 validation samples were used to ensure accuracy assessments. Compared with similar studies, the LCZ datasets in this paper were generally of good quality, with an overall accuracy of 71–93% (mean 82%), an accuracy for built classifications of 57–83% (mean 72%), and an accuracy for natural classifications of 70–99% (mean 90%). In addition, 35% of 63 Chinese cities have construction areas of more than 5%, and the plateaus northwest of Chengdu and Chongqing are covered with snow all year round. Therefore, based on the original LCZ classification system, the construction area (LZC H) and the snow cover (LCZ I) were newly added as the basic classifications of urban LCZ classification in China. Detailed architectural features of cities and urban agglomerations in China are provided by the LCZ datasets in this study. It can be applied to fine numerical models of the meteorological and atmospheric environment and improve the prediction accuracy. [ABSTRACT FROM AUTHOR]

Urban greening is the most effective way to regulate the microclimate environment and thermal discomfort. However, despite being an important type of vegetation, relatively few studies have investigated the effect of bamboo on microclimate characteristics and thermal comfort. In this study, the microclimate characteristics and the differences in the thermal comfort provided by common bamboo communities in East China were investigated in summer and winter, and the effects of canopy structure characteristics on microclimate and thermal comfort were analyzed. The results showed that there were significant differences in microclimate between bamboo communities and the control check in summer, but the differences in air temperature in winter were not obvious. In the daytime during summer, the maximum daily average temperature of the bamboo community decreased by 2.6 °C, and the maximum temperature–humidity index (THI) decreased by 1.1 °C. In the daytime during winter, the maximum daily average temperature increased by 0.5 °C and the maximum THI increased by 0.8 °C. Among the different bamboo communities, Sinobambusa tootsik var. laeta and Pseudosasa amabilis had better effects on improving microclimate and thermal comfort, while the effects of Phyllostachys nigra and Phyllostachys heterocycla 'Pubescens' were relatively small. Aspects of canopy structure, especially leaf area index and canopy coverage, had the greatest influence on the microclimate environment, while air temperature made the greatest contribution to thermal comfort. The goal of our study is to quantify the data to confirm the role of bamboo in improving urban climate problems and human comfort and to further select the appropriate bamboo species for urban green spaces and to utilize the ecological benefits of bamboo to optimize the human living environment. [ABSTRACT FROM AUTHOR]

Light climate environment (LCE) has a significant impact on human health, behavioral characteristics, and the safety of life and property due to the high albedo of snow on the ground cover type, which in turn affects the regional climate and socio-economic development, but less relevant studies have been found. In this study, the effect of snow on daytime and nighttime light levels was quantified using comparative field observations and controlled experiments in artificial climate chambers, combined with analysis of variance and model fitting. The results of the study found that there was a significant difference between the presence and absence of snow on both daytime and nighttime light levels. During daytime, the ambient light level on the ground with snow is 5.68 times higher than without snow, an improvement of 12,711.06 Lux. At night, with moonlight, the nighttime illuminance with and without snow is 0.213 Lux and 0.01 Lux, respectively. When there is no moonlight, the snow has no significant effect on the light level. In addition, significant differences in LCE intensity with different snow depths, snow densities and black carbon (BC) pollution. At the same background light intensity, the LCE intensity varies significantly with increasing snow depth, snow density and BC pollution. The results reveals the quantitative impact of snow on LCE, providing scientific support for regional natural light energy use, human health and safety, urban environmental management and economic development. [ABSTRACT FROM AUTHOR]

Given the interdependence of climate change (CLC) and urban expansion (URE) on ecosystem productivity in China and India, hybrid physics-based models were fitted in this study to evaluate the effects of these variables on photosynthetically active radiation (PAR). This was accomplished by interpolating the most recent five general circulation models (GCMs) from coupled model intercomparison project phase 6 (CMIP6) into the CMIP6 multi-ensemble model. The potential of PAR is projected to increase by 0.001 to 2.077% in China and by 0.002 to 6.737% in India, on a seasonal and annual basis, if the warming is kept at 1.5 °C from now until the end of this century. The effects of CLC and URE on the changes in PAR in China and India were investigated, and URE had a greater impact than CLC when compared to effective contributions, with 49.47% for China and 28.41% for India in the entire case scenario. In contrast, CLC and PAR residual factor (PRF) have a greater impact in India than in China, with effects of 13.79% and 57.79% compared to 0.89% and 49.64%, respectively. Preferences for exotic, high-productivity plant species, irrigation, CO2 fertilization, and nitrogen deposition are suggested as measures for replenishing PAR in both countries. [ABSTRACT FROM AUTHOR]

The concept of self-containment in new towns has been widely discussed from social and economic perspectives. However, localized interpretations within the context of China's development, particularly regarding climate adaptability and urban heat island (UHI) mitigation, are scarce. To fill this gap, our research analyzed self-containment from the perspectives of urban spatial scale and land use function. Focusing on Shanghai's five new towns, we empirically demonstrated how self-containment influenced the UHI effects from 2005 to 2020, employing the Geodetector method. The findings reveal that during the daytime, the intensity of UHI in new towns decreased, serving as vital connectivity nodes of UHI within the region. Conversely, during the nighttime, both the intensity and area of UHI showed an increasing trend. The research confirmed that expanding the urban scale and functional diversity are effective strategies for mitigating the UHI. Based on these findings, we offer practical suggestions for the development of new towns: Increase population size while ensuring coordination with development scale; enhance mixed-use functions in large-scale development projects like university towns and industrial parks; and be vigilant of potential functional decline in central areas and increasing thermal impact due to new town development. Overall, this study enriches our understanding of self-containment in Chinese new towns and provides valuable insights for mitigating UHI in other similar contexts. • Effective land use planning is essential to supplement new towns' self-containment for UHI mitigation. • Daytime enhancements in the thermal environment of new towns are offset by regional disturbances. • UHI effects in new towns are more pronounced during nighttime. • Enhancing both scale and functional diversity is pivotal for promoting sustainable growth in new towns. [ABSTRACT FROM AUTHOR]

Large‐scale human activity changes in megacities during Chinese New Year (CNY) are believed to significantly affect urban heat islands (UHIs). However, the urban‐rural gradient in UHI variations responsive to human activity changes in cities remains largely unclear. Using in‐situ surface air temperature obtained from a meteorological network that includes 3000‐plus stations, we show that the mean UHI intensity (UHII) in 31 Chinese capitals is 0.52 ± 0.23 K during the CNY holiday and 0.77 ± 0.29 K in the reference period, indicating a UHII reduction of 0.25 ± 0.20 K during the holiday. The reduced UHII decreased more from city core (0.54 K) to city periphery (0.071 K). We find that these UHII reductions were larger at night than during the day and were larger in northern subtropical and warm temperate climates than in other climates. These UHII reductions were mainly attributable to the decline in anthropogenic heat release. Plain Language Summary: Human activity changes during the Chinese New Year (CNY) holiday can lead to various impacts on urban climate and environment and particularly the urban heat island (UHI). However, the spatial pattern of UHI intensity (UHII) changes during the CNY holiday for cities within different background climates is still not clear. Based on in situ observations from 2017 to 2019, we find that the mean UHII during the CNY holiday is reduced by 33% (UHII of 0.52 ± 0.23 K in the CNY holiday vs. UHII of 0.77 ± 0.29 K in the reference period) over 31 capitals in China. During the CNY holiday, the UHII reduction reaches 57% (0.15 ± 0.11 K vs. 0.34 ± 0.16 K) in the day and 25% (0.90 ± 0.31 K vs. 1.20 ± 0.36 K) at night. The CNY‐holiday impact also differs greatly by climate zone and hour of day. The UHII reductions are more notable in northern subtropical and warm temperate climates than in other climates. These reductions are mainly caused by the substantial decrease in human activities during the CNY holiday. Our findings can help better understand urban climate changes during the CNY holiday. Key Points: The urban heat island intensity (UHII) decreases by −0.19 K in the day and −0.30 K at night during the Chinese New Year (CNY) holiday over 31 capitals in ChinaThe UHII reduction is more pronounced in city core (0.54 K) than in city periphery (0.071 K)The CNY‐holiday impacts on UHII differ greatly by climate zone and by hour of day [ABSTRACT FROM AUTHOR]

Traffic congestion is one of serious problems in cities; rainfalls would exacerbate traffic congestion, and thus result in huge economic losses. However, limited studies focused on how rainfalls influenced traffic congestion and its associated economic losses. Based on detailed hourly data, we estimated how traffic congestion index (TCI) changed with different rainfall intensities in the Beijing-Tianjin-Hebei (BTH) region, and we also explored their economic losses. The results illustrated that all cities presented the similar trend of daily traffic congestion, and morning peak occurred 2 h later on holidays than workdays. Rainfall had significant impacts on traffic congestion for most time windows, except midnight. Traffic congestion increased with rainfall intensities, but smaller cities were more vulnerable to rainfall intensity than megacities. Rainfalls led to 0.95 billion yuan of extra economic losses in 2019, 38% of which occurred under heavy rainfalls. Traffic congestion in 2019 caused a total economic cost of 30.08 billion yuan in the BTH region (0.4% of its GDP), including the recurrent cost and economic losses due to rainfalls; besides, the social cost and direct cost contributed the same share of 49.5%, with 1% from the environmental costs. Considering future urban development and climate change, it is beneficial to establish the climate-resilient transportation system for avoiding future serious traffic congestion as well as huge economic losses in future. [ABSTRACT FROM AUTHOR]

Rapid urban expansion and climate change have prompted further investigations into urban thermal climates and the development of local climate zone (LCZ) classification systems. LCZs, proposed 10 years ago, comprise a new and systematic classification of field sites for heat island studies to provide a reference for future LCZ research, so that scholars can understand what research has been done and identify future research trends. We analyzed LCZ studies in a database from 2012 to the present, and identified recurring themes using VOSviewer software, including LCZ mapping, measurement methods, thermal environments, and outdoor thermal comfort, among others. A systematic evaluation was performed using bibliometric analysis in the PRISMA framework—190 relevant studies were selected for subsequent analysis. Descriptive analysis showed that LCZ research has received increasing attention, particularly in China, where more than 60% of the LCZ studies were conducted. The results showed that the maximum number of articles on all themes was 57 articles on LCZ mapping, followed by studies of the thermal environment (UHI/SLT). It is hoped that this article will provide scholars in this area with an understanding of the research that has been conducted and the methods used, and provide insight into future research directions. [ABSTRACT FROM AUTHOR]

Climate disruption and rapid urbanization present numerous challenges to infrastructure and communities in Chinese cities, from flooding and coastal erosion, to drought and pollution. This review article focuses on the utilization of Blue‐Green Infrastructure (BGI)—a suite of nature‐based strategies combining hydrological functions (blue) with vegetated landscaping (green)—to provide climate resilience and urban multifunctionality in China's large, high‐density cities. Chinese cities are utilizing BGI in new construction, in neighborhood retrofits, and in revival of ancient nature‐based infrastructure. The literature gives most attention to BGI in China's Sponge City Initiative that addresses the pluvial flooding crisis. Quantitative monitoring of BGI shows progress in stormwater‐related functions and to a lesser extent with rainwater utilization to address water scarcity. Other studies document multifunctional aspects of BGI, including cooling and energy‐saving functions of urban trees and green roofs, and green space expansion with parks that serve as retention basins. However, significant challenges and potential remain. China's urban infrastructure, including BGI, needs stronger design to be robust under extreme conditions as climate disruption intensifies. There is potential for BGI to more fully address habitat fragmentation, extreme heat, sea‐level rise and other climate and urbanization hazards. Further research and pilot projects are needed to characterize and quantify the benefits of multifunctional BGI. More integrated planning across city sectors, with greater incorporation of ecological and social functions, will help Chinese cities achieve multiple goals: providing carbon‐neutral and climate‐resilient infrastructure, improving air and water quality, regenerating ecosystems, and enhancing urban quality of life. This article is categorized under:Energy and Urban Design > Climate and EnvironmentEnergy and Climate > Systems and InfrastructureEnergy and Urban Design > Systems and Infrastructure [ABSTRACT FROM AUTHOR]

Urban heat island (UHI) draws more attention as it affects not only the health of residents but also the energy consumption of buildings at the city scale. To achieve carbon neutrality goals, it is crucial to better understand the mechanism of the UHI influences on building energy consumption. The characteristics of urban heat island intensity (UHII) and the relationship between the UHII effect and building electricity and related coal consumption were analyzed, based on the long period of monitoring data with hourly weather data from 1 January to 31 December 2019. Results show that a strong correlation between the annual mean UHII and the median daily mean UHII exists. The synthetic diurnal UHII of most cities presents a U-shaped variation trend. In different building climate zones in China, namely, severe cold region (SCR), cold region (CR), hot summer cold winter region (HSCWR), hot summer and warm winter region (HSWWR), and mild region (MR), the influences of UHII on building energy consumption were analyzed. The existence of UHI reduces building energy consumption in 96.7% of SCR cities and 60.8% of CR cities, while in HSCWR, HSWWR, and MR cities, the percentage of cities where the building energy consumption is increased by UHI is 69.4%, 80%, and 63.6%, respectively. Urban climate strongly influences building energy consumption, indicating that it should be considered and analyzed in detail for making future urban development or carbon emission reduction strategies. [ABSTRACT FROM AUTHOR]

Urban vegetation plays a very important role in regulating urban climate and improving the urban environment. There is an urgent need to construct an effective index to quickly detect urban vegetation quality changes. In this study, a synthetic vegetation quality index (VQI) was proposed using a holistic approach based on the quality of vegetation itself and the spatial relationship with its surroundings, composed of four selected variables: normalized difference vegetation index (NDVI), patch aggregation index (AI), patch density (PD), and percentage of landscape (PLAND). Principal component analysis (PCA) was employed to calculate weights for each variable due to its objectivity. Then, taking Fuzhou City, southeast China as the case study, the scale effects of the VQI under different moving window sizes (500 m, 1 km, 2 km, ..., 5 km) and the spatiotemporal changes were explored. The results showed that a VQI with a window size of 3 km had the highest correlations with all the selected indicators. Meanwhile, the representativeness and the effectiveness of the VQI were validated by the percentage eigenvalues of PC1, as well as Pearson correlation analysis and bivariate spatial autocorrelation analysis. We also revealed that the proposed VQI had the greatest explanatory power for land surface temperature (LST) among all the factors in both studied years (2000 and 2016), with the VQI's interpretation of LST being 0–44% better than any individual indicator except for AI in 2000. Additionally, our work revealed that the location of vegetation has a great impact on the urban thermal environment. The VQI can assess urban vegetation quality effectively and quickly. [ABSTRACT FROM AUTHOR]

Cities face twin challenges of changing climate and urban heat island (UHI) effect, with the environmental implications of urbanization still unclear. This study employs the Weather Research and Forecasting (WRF) model to examine the impacts of urbanization in the Greater Bay Area (GBA) during warm and cold seasons in past (2000) and near-future (2030) scenarios [i.e., under shared socioeconomic pathways (SSP): SSP1-26, SSP2-45, and SSP5-85]. Datasets from the World Urban Database and Access Portal Tools (WUDAPT) were incorporated into the WRF model to improve the representation of urbanization effects on weather patterns. Our findings indicate that urban expansion significantly increases urban temperatures and decreases wind speed across selected climate change scenarios. The spatially averaged urban temperatures in the fine resolution domain for 2030 could rise by 0.9 °C (warm season) and 2.4 °C (cold season), respectively, and urban wind speed decreases by ∼ 3 m/s under the SSP5-85 scenario. In cold season, the UHI effect could last over 20 h, while urban area may experience cooler nighttime temperatures than rural areas in warm season. Moreover, the future scenario predicts higher daytime O 3 levels due to the warming effects of climate change and urbanization, but lower nighttime levels in warm season, attributed to intensified south-easterly sea breeze and background winds, when compared to the past scenario. This study highlights the importance of incorporating urbanization and climate change in future urban atmospheric environment studies, and underscores that urban climate change adaptation and mitigation should consider extra impacts on built-environment caused by urbanization. • Climate change and urbanization impacts on meteorological and O 3 fields were explored in GBA. • Urbanization and climate change are expected to raised temperatures by 0.9 °C in warm season over the study area. • Urbanization and climate change are expected to raised temperatures by 2.4 °C in cold season over the study area. • Urbanization is expected to reduce wind speed by 3 m/s and intensify sea breeze penetration over the study area. [ABSTRACT FROM AUTHOR]

China is experiencing the largest and fastest urbanization process in the world (Kneebone E., 2013). At the same time, its current rapid urbanization process is almost simultaneously accompanied by urban sprawl. Since the 1990s, the sprawl process of Chinese cities has begun to reach a climax (Shan Baoguo, 2018). As the largest developing country in the world, China is also one of the countries most vulnerable to the coercion of climate change. This research takes the four municipalities that are China's urban development orientation as typical representatives, and uses multiple indicators to measure urban sprawl and climate change in them. Finally, models are established to explore the impact of urban sprawl on climate warming. The results showed that all four cities experienced sprawl, but to varying degrees. Shanghai is very compact. Also, the climate warming is definitely, yet urban sprawl doesn't always contribute to its deterioration. The proportion of arable land had the least impact on global warming, but it was the only factor that could improve temperatures, albeit conditionally. Fragmented built-up land heating the climate is most critical. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) has a profound impact on urban climate and ecology, and is widely used to quantify surface urban heat islands. The spatial heterogeneity of LST is affected by natural and human factors, with seasonal differences. This study selected Dongguan, a rapidly urbanizing city in China, as an example to analyze the relationship between the spatial heterogeneity of LST in different seasons and influencing factors in six dimensions. Multi-source spatial data were combined, including Landsat images, meteorological data, digital elevation models, National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite nighttime light, and points of interest. The results show that spatial patterns of LST across different seasons were consistent, although there were local differences. Based on the GeoDetector model, the result indicated differences between separate effects and interactive effects, and identified the high temperature risk areas. [ABSTRACT FROM AUTHOR]

The significant reduction in human activities during COVID‐19 lockdown is anticipated to substantially influence urban climates, especially urban heat islands (UHIs). However, the UHI variations during lockdown periods remain to be quantified. Based on the MODIS daily land surface temperature and the in‐situ surface air temperature observations, we reveal a substantial decline in both surface and canopy UHIs over 300‐plus megacities in China during lockdown periods compared with reference periods. The surface UHI intensity (UHII) is reduced by 0.25 (one S.D. = 0.22) K in the daytime and by 0.23 (0.20) K at night during lockdown periods. The reductions in canopy UHII reach 0.42 (one S.D. = 0.26) K in the daytime and 0.39 (0.29) K at night. These reductions are mainly due to the near‐unprecedented drop in human activities induced by strict lockdown measures. Our results provide an improved understanding of the urban climate variations during the global pandemic. Plain Language Summary: The outbreak of COVID‐19 has destabilized the global economy and resulted in various impacts on the climate and environment. However, the changes in urban climate during lockdown periods, and particularly in urban heat islands (UHIs), remain largely not known. Using satellite and ground‐based measurements, we find that the surface UHI intensity (UHII) during lockdown periods is reduced by 25% in the daytime and by 20% at night. The reductions in canopy UHII are 36% and 42% during the daytime and nighttime, respectively. These reductions almost certainly result from the significant decrease in human activities induced by strict lockdown measures. Our results provide a fresh perspective of understanding urban climate changes during COVID‐19 lockdown periods. Key Points: Reduced human activities during COVID‐19 lockdown cause a significant decline in both surface and canopy urban heat islands (UHI) intensity over ChinaSurface (canopy) UHI intensity is reduced by 0.25 K (0.42 K) and 0.23 K (0.39 K) on average during the day and night, respectivelyImpacts of COVID‐19 lockdown UHI intensity depend on hour of day [ABSTRACT FROM AUTHOR]

Urbanization is known to cause 'Urban Heat Island' (UHI) and elevate storm runoff. However, how urbanization influences local atmospheric moisture under global warming is not well‐understood. By examining 140 paired urban‐rural weather station data (1980–2018), this study finds significant declines in atmospheric humidity or the 'Urban Dry Island' (UDI) in multiple large city clusters across a large climatic gradient in China. Global warming, UHI, and reduction in local evapotranspiration and water vapor supplies all contribute to the observed UDI. The magnitude and frequency of UDI are more pronounced in humid regions than arid regions due to differences in background climate and vegetation characteristics that affect both energy and water balances at land surfaces. Mitigating the negative effects of UDI and UHI should focus on restoring the evapotranspiration power of urban ecosystems. The present empirical analyses provide new evidence and mechanistic understanding of environmental change in urban ecosystems. Plain Language Summary: More than half of the world's population live in cities and the Earth is increasingly urbanized. Understanding near‐ground atmospheric humidity is important to better monitor urban climate, inform urban planning, and assess ecosystem (i.e., urban forests) and human health under environmental change. This study shows that urban cores have become drier, the so‐called 'Urban Dry Island' (UDI) effect, across a large climatic gradient in China, which has experienced dramatic urbanization in the past three decades. This atmospheric drying (UDI) effect is attributed to both global warming and 'Urban Heat Island' (UHI), but it is significantly exacerbated by urban sprawls due to the loss of vegetation and associated reduction in evapotranspiration and water vapor supply. This study offers insights into the ecohydrologic role of urban ecosystems in mitigating the negative effect of the UHI and UDI. Such knowledge would help design 'Low‐Impact Development' and 'Nature‐based Solutions' to address urban environmental problems. Key Points: 'Urban Dry Islands' (UDI) effects are detected across a large climatic gradientUrbanization exacerbates global warming and UHI effects on UDI through reducing evapotranspiration and water vapor availabilityThe magnitude and frequency of UDI are more pronounced in humid regions than arid regions due to differences in vegetation and climate [ABSTRACT FROM AUTHOR]

Urban spatial expansion is a critical aspect of urbanization, but it must occur in a manner that ensures the sustainable development of the urban climate. The primary objective of this study was to assess the population exposure risk of urban heat island (UHI) effect from the perspective of urban spatial expansion. Additionally, the population weighted urban heat island intensity (UHII) index (Ep) was proposed to compare the population exposure risk of UHI effects in different types of urban spatial expansion in China during the summer of 2005–2020. It was found that, in China, urban land increased by an area of 74,894 km2 (1.01-fold) from 2005 to 2020. Leapfrogging emerged as the predominant pattern of urban spatial expansion and was primarily driven by the conversion of cropland to urban land. It witnessed a significant increase in the area covered by UHIs of 107,119 km2 (1.20-fold), accompanied by a rise in the UHII of 0.12 °C in China. Notably, the UHII for infilling urban expansion was significantly higher at 2.03 °C, in contrast to 1.66 °C for edge expansion and 1.47 °C for leapfrogging. Correspondingly, the Ep was markedly larger under the infilling urban expansion (2.10 °C) in contrast to edge expansion (1.75 °C) and leapfrogging (1.67 °C). However, edge expansion dominated the newly developed urban land, contributing to 18.60 % of the Ep, which was still far less than the contribution of the pre-existing urban land to Ep (61.24 %). Importantly, the dominant driver of the increased Ep was the increasing UHII. This study established a connection between inevitable urban spatial expansion and the population exposure risk of UHI effect, providing a strong theoretical basis and practical guidance for the active adaptation and mitigation of urban environmental hazards in urban regions. • Assessing population exposure risk of UHI is crucial. • The population weighted UHII index was proposed. • Leapfrogging was the main pattern of urban spatial expansion. • The UHII and Ep for infilling urban expansion was significantly higher. • The dominant driver of the augmented Ep was the increasing UHII. [ABSTRACT FROM AUTHOR]

Resilience is an important aim of climate adaptation in urban development planning. Since 2015, sponge city (SC) pilot construction in China has highlighted the importance of urban water systems, but has paid insufficient attention to extreme and long-term climate change risks. This paper aims to provide a new method for evaluating the urban water system climate resilience (UWSCR), classify China cities in combination with climate hazards, conduct case studies on SC pilots, and propose ways to improve the UWSCR in SCs. Firstly, Taking heavy rain and drought as hazards, an evaluation index system of UWSCR is established, including engineering resilience (ENR), ecological resilience (ECR) and evolutionary resilience (EVR). A combination model based on the analytic hierarchy process and entropy weight method is used to measure the UWSCR of 27 SC pilot cities and 253 non-pilot cities at or above the prefecture level in China. Secondly, coordinating hazard index and UWSCR index, cities are divided into four types. The results show that the ENR and EVR of SC pilots exhibited an increasing trend from 2010 to 2020 and were greater than those of non-pilots. Among the four types, Resilient Cities and Low Risk Cities with high climate resilience (CR) were mainly distributed in the eastern and central regions of China. High Risk Cities and Vulnerable Cities with low CR were mostly distributed in the central and western regions. Among the cities of high CR, SC pilots accounted for 63.0% of the pilot samples, while non-pilots only accounted for 26.5% of the non-pilot samples. Finally, this paper analyzes the typical cases of SC pilots, and puts forward some suggestions, such as considering the UWSCR systematically and holistically, improving the ECR of UWSCR, making medium-term to long-term adaptation planning and providing differentiated policy support. The originality of this work is to identify four types of cities from the perspective of UWSCR and provide reference for improving the CR of SCs. [Display omitted] • Against climate change, security risks of urban water systems have intensified. • Sponge city pilot projects in China highlighted the importance of urban water system. • The climate resilience of urban water system in China was evaluated and classified. • The proportion of high-resilience cities in the sponge city pilot sample is high. • The evaluation of urban water system climate resilience can guide sponge city constructions. [ABSTRACT FROM AUTHOR]

• The urban heat island intensity (UHII) characteristics of small cities are different from those of larger cities. • The local climate zones (LCZs) types in small cities are different from those of larger cities. • The UHII of compact LCZs is higher than that of open LCZs. • Natural factors significantly reduce UHII, while built-up factors greatly increase the UHII. • The effect of natural factors on UHII is greater than that of build-up factors. Urban form has been confirmed to be a contributor to the Urban Heat Island (UHI) effect in metropolitan areas, but few studies have focused the relationship in fast-growing small cities through LCZs approach. How the Local Climate Zones (LCZs) distributes and whether the correlations between UHI intensity (UHII) and urban form differ between small cites and large cities remain to be studied. This study mapped LCZs and analyzed UHII in Yangling, a small city in China using the GIS-based method. The results showed: (1) 37 % of the study area contained "High" and "Very High" UHII, mainly in areas with high building density and expansive impervious surfaces. The maximum UHII in Yangling was below 40 °C, which was lower than that of many large cities. In addition, the high UHII areas scattered and formed a small-scale cluster in Yangling, which was different from large cities where high UHII formed large-scale agglomeration areas. (2) Unlike previous findings in megacities, the open Low-rise (LCZ6) was the most prevalent LCZ in Yangling. (3) The UHII of build-up LCZs (2.01 °C) was significantly higher than those of natural LCZ types (-0.61 °C), and the UHII of compact LCZs (LCZ1-3) was higher than that of open LCZs (LCZ4-6). (4) Natural factors were negatively correlated with UHII, whereas most build-up factors were positively correlated with UHII, and the effect of natural factors on UHII was greater than that of build-up factors. These findings will help urban climate researchers and planners better understand the relationship between urban form and UHII and apply this knowledge to build a more comfortable urban thermal environment. [ABSTRACT FROM AUTHOR]

Anthropogenic heat (AH) emissions have rapidly increased in recent decades and are now critical for studying urban thermal environments; however, AH datasets composed of multiple heat sources with fine and accurate spatiotemporal characteristics at large scales are lacking. This study obtained annual, monthly, and hourly AH of multiple heat sources in China for 2019 at 500 m resolution. We first corrected the top-down inventory method for China, which is based on official energy consumption data. Then, we considered features such as the national building height, weighted factory density, and weighted road density to better represent the spatial characteristics of multi-source AH. Based on the above data preparation, a stacking framework was employed to integrate multiple machine-learning algorithms to construct an efficient and accurate AH estimation model. Finally, besides the comparative validation, the results were further tested by participating in a short-term climate numerical simulation for both winter and summer. The resulting data showed a reasonable AH composition and the total amount and composition of AH varied notably from region to region. The spatial and temporal characteristics of the AH from different sources differed greatly and were more detailed and accurate than those reported in previous studies. Air temperature simulations in winter were improved by the AH dataset input, but the uncertainties of climate simulations also limit its validity in AH validation. Because of its large spatial extent and detailed spatiotemporal characteristics, the new dataset strongly supports urban climate research and sustainable development. [Display omitted] [ABSTRACT FROM AUTHOR]

• International eco-cities face unique governance challenges. • We examine Chinese international eco-cities from a multilevel governance perspective. • Multilevel governance provides possibilities for establishing bilateral cooperation. • Effectiveness of multilevel governance is conditioned by intermediary institutions. • Effectiveness also depends on maintaining the attention of national governments. International cooperation has become an important element of urban climate experimentation, particularly in developing countries. Using the Sino-German Eco-Park in Qingdao as a case study, we argue that while multilevel governance and international cooperation are often discussed separately, these two governance tendencies are in fact both important to China's urban climate experimentation. In particular, Chinese multilevel governance enables bilateral cooperation by (re)shaping the national vision at the local level and resolving potential conflicts or contradictions. It also allows local and foreign intermediaries to coordinate and match resources among different interests and actors. The effectiveness of multilevel governance in eco-city projects is conditioned by intermediary institutions' resources and capabilities. Effectiveness also depends on maintaining the attention of national governments to the eco-city projects. Thus, the cooperative form, the actors' attributes, and the resources mobilised by actors are three important factors that affect the outcomes of international eco-city projects. [ABSTRACT FROM AUTHOR]

• LCZ mapping is considered as remote sensing scene classification instead of pixel-based classification to fully exploit the urban environment context. • A convolutional neural network integrating residual learning and the Squeeze-and-Excitation block is proposed for LCZ mapping. • Image sizes of 32 × 32 to 64 × 64 corresponding to 320 × 320 to 640 × 640 m 2 areas are found suitable for LCZ mapping depending on the region. • LCZ maps are generated for fifteen cities in China. China, with the world's largest population, has gone through rapid development in the last forty years and now has over 800 million urban citizens. Although urbanization leads to great social and economic progress, they may be confronted with other issues, including extra heat and air pollution. Local climate zone (LCZ), a new concept developed for urban heat island research, provides a standard classification system for the urban environment. LCZs are defined by the context of the urban environment; the minimum diameter of an LCZ is expected to be 400–1,000 m so that it can have a valid effect on the urban climate. However, most existing methods (e.g., the WUDAPT method) regard this task as pixel-based classification, neglecting the spatial information. In this study, we argue that LCZ mapping should be considered as a scene classification task to fully exploit the environmental context. Fifteen cities covering 138 million population in three economic regions of China are selected as the study area. Sentinel-2 multispectral data with a 10 m spatial resolution are used to classify LCZs. A deep convolutional neural network composed of residual learning and the Squeeze-and-Excitation block, namely the LCZNet, is proposed. We obtained an overall accuracy of 88.61% by using a large image (48 × 48 corresponding to 480 × 480 m 2 ) as the representation of an LCZ, 7.5% higher than that using a small image representation (10 × 10) and nearly 20% higher than that obtained by the standard WUDAPT method. Image sizes from 32 × 32 to 64 × 64 were found suitable for LCZ mapping, while a deeper network achieved better classification with larger inputs. Compared with natural classes, urban classes benefited more from a large input size, as it can exploit the environment context of urban areas. The combined use of the training data from all three regions led to the best classification, but the transfer of LCZ models cannot achieve satisfactory results due to the domain shift. More advanced domain adaptation methods should be applied in this application. [ABSTRACT FROM AUTHOR]

The urban heat island intensity (UHII) is the temperature difference between urban areas and their rural surroundings. It is commonly attributed to changes in the underlying surface structure caused by urbanization. Air pollution caused by aerosol particles can affect the UHII through changing (1) the surface energy balance by the aerosol radiative effect (ARE) and (2) planetary-boundary-layer (PBL) stability and airflow intensity by modifying thermodynamic structure, which is referred to as the aerosol dynamic effect (ADE). By analyzing satellite data and ground-based observations collected from 2001 to 2010 at 35 cities in China and using the WRF-Chem model, we find that the impact of aerosols on UHII differs considerably: reducing the UHII in summer but increasing the UHII in winter. This seasonal contrast is proposed to be caused by the different strengths of the ARE and ADE between summer and winter. In summer, the ARE on UHII is dominant over the ADE, cooling down surface temperature more strongly in urban areas than in rural areas because of much higher aerosol loading, and offsets the urban heating, therefore weakening UHII. In winter, however, the ADE is more dominant, because aerosols stabilize the PBL more in the polluted condition, weakening the near-surface heat transport over urban areas in both vertical and horizontal directions. This means that the heat accumulated in urban areas is dispersed less effectively, and thus the UHII is enhanced. These findings shed new light on the impact of the interaction between urbanization-induced surface changes and air pollution on urban climate. [ABSTRACT FROM AUTHOR]

The land surface model SURFEX 7.3 was used to study climate effect of urban expansion located in oasis in arid area of Northwest China by surface and 2 m urban heat island (UHI) intensity and available energy ratio (B). We performed a true regional development scenario and three assumed scenario simulations in 1978, 1993, 2004, and 2014, respectively. The results show that 2 m UHI always displays positive twin peaks during whole day, while surface UHI only displays a positive single peak with several hours during daytime at four seasons in the four years. Moreover, 2 m UHI intensity during night is higher than that during daytime, indicating that UHI intensity is contributed more by "trap effect" from urban complex geometry or anthropogenic heat and that surface UHI according to land surface temperature cannot reflect UHI comprehensively. The oasis-urban development resulted in local warming and increasing of B , and compared with the original undeveloped environment, local climate in the study area was in a relatively balanced state in 1978 and 1993 due to the "heating effect" of urban area and the "cooling effect" of oasis, but the offsetting effect from oasis would become weaker after1993. [ABSTRACT FROM AUTHOR]

• Chinese cities are more resilient to heavy rainfall than to extreme heat. • Nationally, areas near the Hu Line are the least resilient to heavy rainfall. • The potential long-term negative impact of extreme weathers is up to seven months. • Areas dominated by the secondary sector need to address extreme weather impacts. • Developed economies are vulnerable to climate hazards despite having high defense. Given the unprecedented climate change, extreme weathers have become more intense and frequent, causing severe socio-economic impacts. Urban resilience is vital for mitigating extreme events, but little is known about its city-level response to such shocks in China. Here, we aim to investigate the persistent effects of extreme heat and heavy rainfall on Chinese cities, ultimately revealing urban resilience. We use monthly nighttime lights from 2013–2019 as a proxy for urban functioning. Our results suggest that cities are less resilient to extreme heat than to heavy rainfall, yet the adverse effects of heavy rainfall can persist for up to seven months. Importantly, we reveal for the first time that areas near the Hu Line are vulnerable to heavy rainfall (e.g., Beijing, Tianjin and Chongqing), and cities in the Yangtze River basin are most affected by extreme heat (up to 24.8 % loss of nighttime light intensity). There is an urgent need to address severe weather impacts in regions dominated by secondary sector, while developed economies are vulnerable to climate hazards, despite having high defense. Our findings identify urban climate risk hotspots and underlying impact mechanisms, providing valuable insights into climate mitigation policies and urban development strategies. [Display omitted] [ABSTRACT FROM AUTHOR]

Climate change has increasingly become a significant challenge to sustainable socio-economic development, and climate adaptation is a key issue that relevant research focuses on regional sustainable development models. By employing panel data between 2007 and 2020 from 284 Chinese prefecture-level cities, this study adopts quasi-experimental methods, including a difference-in-differences design and double dual machine learning model, to study the impact of climate adaptability on green regional sustainable development. Empirical results confirm that the pilot policy of building climate-resilient cities significantly improves urban green total-factor productivity. Difference-in-difference models (derived from entropy-weight and propensity score matching) and double dual learning models also support the improving effect of regional green total-factor productivity after policy intervention. The digital economy has strengthened the green development effect of pilot policies for building climate-adaptive cities. In addition, policy interventions to build climate-adaptive cities promote green urban development by optimizing industrial development structures and enhancing economic growth resilience. In addition, climate adaptability can also attract highly skilled talent and high-quality enterprises, facilitate science and technological progress in urban areas, and thus promoting the green development of cities in China. This study objectively evaluates the effects of climate policies and provides insights for global adaptation to climate change and optimization of public policies. • Urban climate adaptability effect on green sustainable development was examined. • A panel data of 284 Chinese prefecture-level cities was used for the analysis. • Techniques used were double dual machine learning and differences-in-differences. • Building climate-resilient cities improves urban green total-factor productivity. • Industrial structure and resource attraction mediate the studied effect. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) is one of the essential phenomena of the modern urban climate. In recent years, urbanization in China has gradually accelerated, and the heat island effect has also intensified as the urban impervious surface area and the number of buildings is increasing. Urban building density (UBD) is one of the main factors affecting UHI, but there is little discussion on the relationship between the two. This paper takes Hefei as the research area, combines UBD data estimated by Luojia1-01 night-time light (NTL) imagery as the research object with land surface temperature (LST) data obtained from Landsat8 images, and carries out spatial correlation analysis on 0.5 × 0.5 km to 2 × 2 km resolution for them, so as to explore the relationship between UBD and UHI. The results show the following: (1) Luojia1-01 data have a good ability to estimate UBD and have fewer errors when compared with the actual UBD data; (2) At the four spatial scales, UBD and LST present a significant positive correlation that increases with the enlargement of the spatial scale; and (3) Moreover, the fitting effect of the Geographically Weighted Regression (GWR) model is better than that of the ordinary least squares (OLS) regression model. [ABSTRACT FROM AUTHOR]

In China, urban climatic factors are seldom taken into account in urban planning and urban management due to the lack of basic data, as well as practical evaluation tool to bridge the gap between climatic data and urban planning. Comprehensive surveys were performed to determine residential environment factors, such as urban thermal comfort environment, urban air quality, urban wind environment and urban short-term heavy precipitation disasters, at community scale. A standard of urban climate environment map and an atlas of climate environment in the typical cities were then compiled to encourage urban environmental adaptation. The state council has approved the "China's National Plan on Climate Change (2014-2020)"[20] in 2014, with the goal of reducing CO SB 2 sb emissions per unit GDP by up to 45% by 2020, limiting the energy- and emission-intensive industries, promoting the utilization of new energy sources and improving adaptation to climate change. [Extracted from the article]

Studies on urban climatic mapping and local climate zones are urgently needed due to rapid urbanisation in China, to identify and predict serious air pollution problems and occurrence of urban heat islands, for sustainable urban planning. The study of wind environment, especially measurements of wind data on the urban scale, is important to the climate mapping and investigation of air pollution and heat island events. In this paper, we introduce a measurement method for the urban-scale wind environment, which combines measurements conducted at the stationary reference station with those at portable/mobile stations. Data collected from portable/mobile stations were normalised with respect to wind data measured at the stationary reference station. Three criteria for the selection of the stationary reference station were compared according to the land-use and distance to the portable/mobile stations. The background meteorological station was selected as the stationary reference station for data normalisation and was found to be the most appropriate. The normalisation method for wind data was used to analyse the measured wind data at portable/mobile stations. Clear differences were observed between measured and normalised average wind speeds. The normalised wind was used in the urban wind environment mapping. The objective of the mapping is to assess the ventilation potential of the urban canopy layer, to help the urban climate mapping and to inform future sustainable urban planning. [ABSTRACT FROM AUTHOR]

The city's local climate zone (LCZ) has been considered as a useful guiding tool for urban climate mapping and classification of urban canopy in cities. However, the LCZ classification methods and results are different in different cities in different countries and regions. Therefore, it is necessary to conduct a targeted research that would take into account local urban morphology and canopy characteristics. In the current work, a LCZ classification method is proposed. This would provide a useful guide for city planning and operation. In the newly proposed method, the LCZ types were first adjusted, according to the characteristics and urban morphology of Chinese cities, in relation to existence of high- and low-rise buildings and high density residential population and land cover of greeneries. Based on investigations of two LCZ classifications of the City of Xi'an, a coupling method was proposed. This method couples the World Urban Database and Access Portal Tools method based on remote sensing data with the classification method based on road network divided by land parcels. The proposed method was validated in this study against the actual land use and construction data that were surveyed in Xi'an, which showed acceptable accuracy. Our results have illustrated the feasibility of our proposed classification for urban LCZ mapping in China. [ABSTRACT FROM AUTHOR]

This study presents that increases in atmospheric CO 2 levels impact the ventilation and energy in buildings. The most significant impact of ventilation occurs during use, because of the indoor air quality. According to the 2014 IPCC report, observed atmospheric CO 2 levels increased at a rate of 1.9–2.1 ppm per year. This study measured CO 2 levels in a building in an urban area in Shanghai, China, and analyzed existing ventilation performance and energy simulation in relation to the impact of increased atmospheric CO 2 concentrations. As long as the atmospheric CO 2 level increased, the outdoor airflow rate had to increase also to maintain an acceptable indoor CO 2 level. The ventilation rate was also considered in relation to the surrounding environment. In Shanghai, the average value of CO 2 concentrations on an auto road was 550 ± 20 ppm and the average value on a pedestrian road was 435 ± 15 ppm. A building that was surrounded by high traffic roads needed 20–30% more outdoor airflow rate than a building surrounded by pedestrian roads. Accordingly, energy loads in buildings, for heating and cooling were also affected. In order to dilute indoor CO2 level, the thermal ventilation energy and the ventilation energy uniformly provided a 20% energy load increase during the 12 months, while each monthly energy load varied, depending on the season and/or month. By analyzing indoor CO 2 levels and the rise in atmospheric CO 2 levels, this study determined how these rises impacted the energy consumption of the building, and how to design a new outdoor airflow supply rate to adapt to a changed environmental condition. • How a rise in atmospheric CO 2 concentrations impacts energy consumption in a building. • How to design new outdoor airflow supply rates to adapt to ambient conditions. • Indoor air ventilation performance governed by urban factors and climate changes. • Outdoor air supply rate must be increased by 10% per 50 ppm of the CO2 level rise. [ABSTRACT FROM AUTHOR]

Background. China is considered as the largest and most rapidly urbanizing nation in the world. However, possible changes of urban thermal environment and comfort under the rapid urbanization in China still remain poorly understood at a national scale. Methods. Based on the data collected from 180 cities in 1990, 2005, and 2015 in China, the spatiotemporal patterns of urban thermal environment and comfort in summer and their relationships with urbanization variables were investigated in this study. Results. Our results indicate that urban thermal environment has changed greatly during the 25 years. Furthermore, the changes of urban climate in different regions are inconsistent. The Physiological Equivalent Temperature (PET) at most cities (81%) in China increased from 1990 to 2015, which suggested that urban thermal comfort in China was also deteriorating during the 25 years. However, while the PET of some cities in China began to decrease from 2005 to 2015, there were still 33% of cities that had positive trends, which mainly located in North region. Urbanization resulted in a significant influence on urban climate. Compared to southern cities, northern cities were more sensitive to urbanization impact. The most important contribution to increasing of PET for urbanization variables is gross domestic product, followed by urban population. The analysis results reveal changing patterns of urban thermal comfort in China during summer season. It can help urban government and managers improve urban thermal environment and comfort. [ABSTRACT FROM AUTHOR]

Abstract Climate change and urbanization strongly affect the variations of terrestrial net primary production (NPP), but the relative contributions of these two factors to NPP changes have not been determined yet (especially on a macroscale). In this study, spatial-temporal variations of NPP in China from 2000 to 2010 were estimated using the Carnegie−Ames−Stanford Approach model, and the effects induced by urbanization and climate change were quantified. The obtained results showed that during the study period, the NPP in China exhibited an annual increase of 0.03 Pg C accompanied by large spatial heterogeneities. During the whole study period, the urban area in China increased by 16.44 × 103 km2, and the corresponding NPP losses amounted to 11.60 × 10−3 Pg C. Urban expansion significantly offset the climate change-induced NPP increases and worsened NPP decreases (the offsetting ratio calculated for China was 5.42%, and its exact magnitudes varied by province). The largest NPP variations were observed over the regions with rapid urban expansion, whose contribution ratio was 32.20% for China and exceeded 30% for most provinces. Climate change contributed considerably to the NPP variations in both the newly urbanized (30.45%) and purely vegetated (46.92%) areas, but its contribution ratios were slightly lower than those of residual factors. Moreover, climate change strongly affected the NPP levels over the arid and semi-arid regions as well as over the Tibet Plateau; however, residual factors dominated the NPP variations over the central and southeast China. Our study highlights a significant role of urbanization in driving terrestrial NPP variations on a macroscale and provides a new perspective on disentangling the impacts of external factors on NPP values. Highlights • Urbanization offsets 5.42% of climate-induced NPP increases at a country scale. • Urbanization contributes 32.20% of NPP changes at whole China. • NPP variations in high-speed urban sprawl areas were led by Urbanization. • Climate change dominated the NPP variations in arid and semi-arid regions. • Residual factors ran the NPP changes in central and southeast China predominantly. [ABSTRACT FROM AUTHOR]

Climate change and urbanization collectively influence precipitation changes. However, their separate potential contributions to precipitation changes are not well understood due to their complex interactions. Hence, a "trajectory"‐based method was used to separate their potential contributions across national, regional and local scales in China. Precipitation changes in non‐urban regions can be regarded as representing the influence of climate change and can serve as a reference for isolating precipitation changes due to urbanization in urban areas. Our results revealed that climate change was the dominant factor for precipitation trends, while urbanization exhibited a relatively weak influence, especially for extreme precipitation at the national scale. At the regional scale, the impacts of urbanization on precipitation became more significant. About 20.2 and −30.6% of positive and negative trends in total precipitation originated from urbanization. At the local scale, the potential contribution of urbanization was strongly correlated with local environmental characteristics. Although there were differences in the potential contributions of climate change and urbanization at national, regional and local scales, climate change was the dominant factor for precipitation trends and urbanization acted as a regulator to drying or wetting due to precipitation under climate change. In general, urbanization causes a greater impact on total precipitation than on precipitation extremes. Due to this, attribution approach is static and broad‐based and does not render the level of confidence that is needed for scale‐aware attribution, future studies are needed to understand the physical mechanisms of impacts of local environment changes on precipitation trends at different geographical locations over China. [ABSTRACT FROM AUTHOR]

Urban buildings and parks play an important role in regulating urban climate and ecosystem services. Diurnal air temperature range (DTRa) of rocklike buildings is commonsensically regarded as higher due to no latent heat from evapotranspiration and its smaller thermal inertia compared to wet soil. Therefore, the building DTRa is supposed to be higher than that of parks due to its building fabric. However, we found an opposite phenomenon (smaller building DTRa than that of parks), and the underlying mechanisms explaining this phenomenon are unclear. Here we conducted, in Beijing (China), a long‐term observational campaign of standard meteorological variables and radiation/energy fluxes to provide a new valuable evidence (a part of external energy) to explain this phenomenon. The observations indicated external heat energies from horizontal advection and anthropogenic heat sources. We found a significantly lower building DTRa than that of parks (ΔDTRa =2.53±1.93 °C), with a maximum difference of 3.54±1.96 °C in autumn; which was mainly attributed to higher daily minimum air temperature. We also found the large differences in air temperature contribution between the buildings and the parks happened mainly at night. The external heat sources of the building contributed 16.71% to the nighttime air temperature, which was higher than that of the parks (8.39%). The more indoor and outdoor anthropogenic heat sources in the building footprints were the major cause of the slower decrease in Tmin. The comparison between buildings and parks can be extensively applied to analyzing the effects of urbanization on climate. Plain Language Summary: An effective mosaic of buildings and parks, as the two core elements of cities, plays an important role in regulating urban climate and providing ecosystem services. A comfortable urban environment is becoming the pivotal theme for the United Nations Sustainable Development Goals 2030 related to resilient and sustainable cities and to mitigate climate change. While the urbanization effect on the diurnal air temperature range (DTRa) is still being debated within the climate community, we, surprisingly, found a significantly lower DTRa of buildings than of parks, which contradicts our common knowledge. The observations showed that nocturnal radiation cooling did not result in a decrease of air temperature, largely due to external heat input (60.17±22.98 W/m2). Heat fluxes of both the building roofs from their large indoor heat sources and the mixed peripheral advection with anthropogenic heat discharges contributed to a higher minimum air temperature. In daytime, despite additional input from human‐induced energy, neighboring vegetation transpiration and building/tree shadows offset those heat fluxes and slowed down the air temperature increase. The findings provide new knowledge on urban heat island mitigation and climate change adaptation. Key Points: The diurnal air temperature range of buildings is significantly lower than that of parks (ΔDTRa = 2.53±1.93 °C)The lower diurnal air temperature range of buildings compared to parks is attributed to a higher daily minimum air temperatureThe contribution of external heat sources by buildings (16.71%) to the nighttime air temperature was twice that of the park (8.39%) [ABSTRACT FROM AUTHOR]

The urban heat island effect is a typical urban climate phenomenon, and the formation and intensity of these phenomena are closely related to the land cover type. Based on Landsat 8 remote sensing images of Shenzhen, China, this study uses a linear spectral mixture model to extract land coverage information, and then analyzes the effects of urban land coverage on the land surface temperature (LST) and heat budget components. The results show that the LST of Shenzhen decreases gradually from northwest to southeast and that the LST of urban impervious surfaces are significantly higher than those of vegetation-covered areas with a difference of 3–4 K, thus demonstrating a significant urban heat island effect. Impervious surfaces and urban vegetation both affect the LST and heat budget components of Shenzhen. The impervious area contributes more to the surface sensible heat, while urban vegetation contributes more to the surface latent heat. The research results show that a very small area of urban green land (vegetation fraction coverage less than 4–8%) exhibits a strong capacity for heat dissipation. In the practice of urban construction, avoiding concentrated impervious areas and increasing urban green land areas represent effective methods of alleviating the urban heat island effect. This study helps to better understand the optimization of urban landscapes and alleviation of the urban heat island effect. • Use linear spectral mixture model to extract land coverage in Shenzhen. • Analyze the effects of urban land coverage on the LST and heat budget components. • Understand the effect of land coverage patterns on urban thermal environment. [ABSTRACT FROM AUTHOR]

Multi-level governance (MLG) theory has become the main explanation for how climate action is realized in polycentric, multi-sector, multi-actor policy landscapes. In this paper, we examine processes of climate change governance in a given city in China, Rizhao, and evaluate how MLG arrangements operate. We do so by examining primary data collected through in-depth interviews with local stakeholders. Our results show that the focus on multi-level – and in particular transnational – interactions obscures the ways in which urban low carbon transitions happen in three ways. First, in spite of Rizhao being a well-known case in environmental politics, there is an absence of international actors and non-governmental organizations operating on the ground. Second, the emphasis on opportunities of local authorities to build political agendas through participation in global networks conceals how structures of power, political-economic coalitions, and technological practices are firmly fixed in a local context. Third, the case study illustrates the enduring authority of formal top-down channels of control in this political system. Based on these results, we caution against the uncritical application of MLG theory to environmental politics in settings where deliberative democracy is lacking and the full benefits of multi-level interactions are unlikely to be achieved. [ABSTRACT FROM AUTHOR]

• Climate change and urban growth combined caused surface runoff increases in an urban agglomeration. • At regional and city scales, climate change was the main driver of the runoff change. • At sub-city scale, urban growth might have the greatest effect on the runoff change. • Solutions at multiple scales are needed to surface runoff in mega-cities. Climate change and urban growth have been shown to alter hydrological processes, particularly surface runoff. While there is widespread evidence of the combined effects of climate change and urban expansion on surface runoff at the watershed scale, little is known about their combined effects at different scales in large-scale urban agglomerations. Using integrated spatial models, we simulated the combined effects of climate change and urban growth on surface runoff in the Beijing-Tianjin-Hebei urban agglomeration, China, in 2030. We found that the surface runoff increased under both climate change and urban growth scenarios but the relative contributions of these two factors to surface runoff change varied from the regional to the sub-city scale. At regional and city scales, climate change was the main control on surface runoff change, while urban growth had the most effect on surface runoff change in the main urban areas of some cities, i.e., the sub-city scale. The results indicate that one single factor does not give reliable information for managing surface runoff in megacities, as the effects of other factors are ignored. These findings highlight that integrated solutions must be tailored to the appropriate spatial scale to effectively regulate surface runoff change across large-scale urban agglomerations. [ABSTRACT FROM AUTHOR]