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The artificial impervious surface (AIS) counts among the most important components of the urban surface, and understanding how temperature changes with the AIS fraction (AISF) is crucial for urban ecology and sustainability. Considering the high heterogeneity among existing local studies, this study systematically analyzed the relationship between land surface temperature (LST) and AISF in 682 global cities. The LST-AISF relation was quantified by the coefficient (δLST, ΔLST/ΔAISF) of a linear regression model, which measures the LST change by 1 unit (1%) increase in AISF. The LST was acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) daily products during 2014-2016, while the AISF was calculated as the proportion of AIS in each MODIS pixel according to the high-resolution Global Artificial Imperious Area (GAIA) product in 2015. Major results can be summarized as follows: (a) LST shows an increasing trend along AISF gradients (positive δLST) in most cities, with annually average daytime and nighttime δLST of 0.0219 (0.0205, 0.0232) °C/% (values in parenthesis define the 95% confidence interval, hereinafter) and 0.0168 (0.0166, 0.0169) °C/%, respectively, for global cities. (b) Daytime δLST varies substantially among cities, with generally stronger values in tropical and temperate cities, but weaker or even negative values in arid cities; while at night, cities located in the cold climate zone tend to have larger δLST. (c) The LST-AISF relation is also season-dependent, characterized by a greater δLST in warm months, especially for cities located in temperate and cold climate zones. (d) Driver analyses indicate that changes in surface biophysical properties, including vegetation conditions and albedo, are main contributors to the spatiotemporal variation of daytime and nighttime δLST, respectively. These results help us to get a quantitative and systematic understanding of the climatic impacts of urbanization.

The urban heat island (UHI) effect exerts a great influence on the Earth’s environment and human health and has been the subject of considerable attention. Landscape patterns are among the most important factors relevant to surface UHIs (SUHIs); however, the relationship between SUHIs and landscape patterns is poorly understood over large areas. In this study, the surface UHI intensity (SUHII) is defined as the temperature difference between urban and suburban areas, and the landscape patterns are quantified by the urban-suburban differences in several typical landscape metrics (ΔLMs). Temperature and land-cover classification datasets based on satellite observations were applied to analyze the relationship between SUHII and ΔLMs in 332 cities/city agglomerations distributed in different climatic zones of China. The results indicate that SUHII and its correlations with ΔLMs are profoundly influenced by seasonal, diurnal, and climatic factors. The impacts of different land-cover types on SUHIs are different, and the landscape patterns of the built-up and vegetation (including forest, grassland, and cultivated land) classes have the most significant effects on SUHIs. The results of this study will help us to gain a deeper understanding of the relationship between the SUHI effect and landscape patterns.

Trees are among the most important urban land covers, and their effects on local thermal environments have been extensively evaluated by using the concept of urban trees’ cooling efficiency (CE), defined as the magnitude of land surface temperature (LST) reduction by per 1% increase in fractional tree cover (FTC). Existing studies provide quantitative knowledge of the CE at local and regional scales, but global-scale analyses are still lacking. Therefore, this study fills this research gap through investigating the spatiotemporal pattern of CE in 510 global cities. CE is quantified by the opposite value of the regression coefficient of FTC (i.e. CE =− ∂ LST/ ∂ FTC) in a multiple linear regression model, where LST is the dependent variable and FTC, surface elevation, and nighttime light intensity are the independent variables. Results show that daytime LST decreases greatly with increasing FTC in most cities, and the globally averaged annual daytime CE reaches 0.063 °C % −1 , while at night, the effect of urban trees on LST weakens a lot, with an annual average CE of only 0.007 °C % −1 across global cities. CE varies markedly among cities and tends to be higher in hot and dry cities, which can be attributed to the significant nonlinear relation between CE and climatic conditions, in that the increase in temperature and the decrease in humidity can enhance vapor pressure deficit and further promote the heat dissipation by plant transpiration. As expected, CE shows a distinct seasonal variation, generally characterized as being higher in summer and lower in winter. In addition, our results suggest that previous studies based on a bivariate linear regression model have overestimated CE, especially at night when trees’ activities are weak. This global-scale study provides new insights into the mitigation of urban thermal stress from the perspective of increasing urban greenery.

Satellite‐based thermal infrared (TIR) land surface temperature (LST) is hindered by cloud cover and is applicable solely under clear‐sky conditions for estimating surface urban heat island intensity (SUHII). Clear‐sky SUHII may not accurately represent all‐sky conditions, potentially introducing quantitative biases in assessing urban heat islands. However, the differences between clear‐sky and all‐sky SUHIIs and their spatiotemporal variations are still poorly understood. Our analysis of over 600 global cities demonstrates that clear‐sky SUHII is mostly higher than all‐sky SUHII, particularly in summer, daytime, and precipitation‐rich regions. Besides, clear‐sky SUHII typically exhibits stronger seasonal and diurnal contrasts than all‐sky SUHII, especially for cities located in humid regions. These discrepancies can be attributed mainly to the increased missing LST data caused by cloud enhancement in urban areas. Our findings highlight the tendency for clear‐sky observations to overestimate SUHII, providing valuable insights for standardizing the quantification of surface urban heat islands. Plain Language Summary Surface urban heat island intensity (SUHII) and its spatial and temporal variations are important for describing the urban thermal environment. SUHII is usually estimated from remotely sensed land surface temperature (LST), which is only available under clear‐sky conditions. The SUHII derived from clear‐sky observations may differ from the SUHII under all‐sky conditions. However, there is currently a lack of large‐scale quantitative assessments addressing the differences between clear‐sky and all‐sky SUHIIs. This study fills this research gap and indicates a substantial overestimation of SUHII in humid regions when using clear‐sky LST. This overestimation can be explained by the increased occurrence of missing LST data caused by the enhanced presence of clouds in urban areas. Our findings show the importance of utilizing all‐sky LST data in the examination of urban surface thermal environments, especially for cities situated in humid regions. Key Points Clear‐sky surface urban heat island intensity (SUHII) shows higher values and stronger spatiotemporal variations than all‐sky SUHII, notably in summer, daytime, and humid areas The annual daytime SUHII for tropical cities is, on average, overestimated by 30% when relying on clear‐sky land surface temperature (LST) observations Differences in clear‐sky and all‐sky SUHIIs can be explained by more missing LST data caused by increased clouds in urban areas

Accurately capturing the impact of urban trees on temperature can help optimize urban heat mitigation strategies. Recently, there has been widespread use of remotely sensed land surface temperature (Ts) to quantify the cooling efficiency (CE) of urban trees. However, remotely sensed Ts reflects emitted radiation from the surface of an object seen from the point of view of the thermal sensor, which is not a good proxy for the air temperature (Ta) perceived by humans. The extent to which the CEs derived from Ts reflect the true experiences of urban residents is debatable. Therefore, this study systematically compared the Ts-based CE (CETs) with the Ta-based CE (CETa) in 392 European urban clusters. CETs and CETa were defined as the reductions in Ts and Ta, respectively, for every 1% increase in fractional tree cover (FTC). The results show that the increase in FTC has a substantial impact on reducing Ts and Ta in most cities during daytime. However, at night, the response of Ts and Ta to increased FTC appears to be much weaker and ambiguous. On average, for European cities, daytime CETs reaches 0.075 ◦C %−1 , which is significantly higher (by an order of magnitude) than the corresponding CETa of 0.006 ◦C %−1 . In contrast, the average nighttime CETs and CETa for European cities are similar, both approximating zero. Overall, urban trees can lower daytime temperatures, but the magnitude of their cooling effect is notably amplified when using remotely sensed Ts estimates compared to in situ Ta measurements, which is important to consider for accurately constraining public health benefits. Our findings provide critical insights into the realistic efficiencies of alleviating urban heat through tree planting. : urban heat islands, green space, in situ measurements, ecosystem service, mitigation strategies, remote sensing

Urban color represents the visual skin of a city, embodying regional culture, historical memory, and the contemporary spirit. However, while the existing studies focus on pedestrian-level facade colors, the “fifth facade” from a bird’s-eye view has been largely overlooked. Moreover, color distortions in traditional remote sensing imagery hinder precise analysis. This study targeted 56 Chinese coastal cities, decoding the spatiotemporal patterns of their fifth facade color (FFC). Through developing an innovative natural color optimization algorithm, the oversaturation and color bias of Sentinel-2 imageries were addressed. Several color indicators, including dominant colors, hue–saturation–value, color richness, and color harmony, were developed to analyze the spatial variations of FFC. Results revealed that FFC in Chinese coastal cities is dominated by gray, black, and brown, reflecting the commonality of cement jungles. Among them, northern warm grays exude solidity, as in Weifang, while southern cool grays convey modern elegance, as in Shenzhen. Blue PVC rooftops (e.g., Tianjin) and red-brick villages (e.g., Quanzhou) serve as symbols of industrial function and cultural heritage. Economically advanced cities (e.g., Shanghai) lead in color richness, linking vitality to visual diversity, while high-harmony cities (e.g., Lianyungang) foster livability through coordinated colors. The study also warns of color pollution risks. Cities like Qingdao exposed planning imbalances through color clashes. This research pioneers a systematic and large-scale decoding of urban fifth facade color from a remote sensing perspective, quantitatively revealing the dilemma of “identical cities” in modernization development. The findings inject color rationality into urban planning and create readable and warm city images.

To contain the outbreak of COVID-19 in Wuhan, unprecedented interventions, including city lockdown and community closure, have been implemented. However, most of the current studies focused on evaluation of the city lockdown, but paid limited attention to the impacts of the community containment measures within the city. This research addressed this important issue from the perspective of urban planning, based on the epidemic and remote sensing data of 194 communities of Wuhan. We found that the number of confirmed cases of communities is highly related to urban planning factors, e.g. area percentage of buildings and density of neighboring markets. These factors are relevant to the residents' activity patterns, which therefore impact the mode of virus transmission. Our research confirmed the effectiveness of the community-oriented control strategies, provided a valuable reference for other cities that are suffering from the epidemic, and exhibited new thoughts into future urban planning.

Conclusions The developed Chang’E 7 LSWMA prototype demonstrates high precision in measuring water content and isotope values, which are the most important part of the measurement process, and the experimental results offer valuable guidance for in-situ measurement and data inversion. The LSWMA will perform the measurements after obtaining drilling (up to 1 m deep) or surface samples on the Moon. The estimated water content has also been affected by the processes of sampling, transportation and heating in addition to TDLAS. Therefore, the overall errors need to be analyzed and corrected. For isotopes measurement, the repetitions of experiments on the Moon’s PSR are limited due to power and temperature constraints. The memory effect error correction algorithm should be introduced to improve accuracy.

Solar irradiance received at the lunar surface is crucial for interpreting brightness temperatures detected by orbiters and for understanding the thermal, physical, and dielectric properties of the lunar regolith. We developed a real‐time effect solar irradiance (ESI) model that accounts for the influence of surface relief and terrain shading. This model was integrated with a standard thermal model to examine ESI fluctuations and their impacts on the diurnal physical temperature variations. To assess the effects of spatial resolution, we selected four locations with significant ESI disparities for simulation, then compared lunar surface temperatures at various spatial scales, ranging from 20 m to 25 km. Utilizing brightness temperature data obtained from the Chang'E‐2 (CE‐2) microwave radiometer (MRM), we integrated the shallow physical temperature profiles with the radiative transfer equation to simulate brightness temperatures and determine dielectric loss at different frequencies. In the Von Kármán crater, the received ESI exhibits a cyclical pattern of approximately 18 years and areas with rugged topography may exhibit larger ESI variations (∼7%). We found that the spatial resolution of ESI has a minimal effect on the physical and brightness temperatures at resolutions of 10 km or coarser. At the shallow layer, the average dielectric loss values are 0.0128–0.0170, 0.0083–0.0110, 0.0055–0.0073, and 0.0061–0.0081 for the CE‐2 frequencies of 3, 7.8, 19.35, and 37 GHz, respectively. The integration of real‐time ESI modeling, thermal dynamics, radiative transfer equations, and observational data enhances our comprehension of the physical temperature profile and thermal characteristics of shallow regolith. Plain Language Summary The combination of solar irradiance and temperature data sets detected by orbiters can help to explain the temperature variation and thermophysical properties of shallow lunar surface. This study develops a real‐time effect solar irradiance (ESI) model that takes into account the influence of lunar topography and integrates it with a thermal model to simulate physical temperature variations within the Von Kármán crater. We compared lunar surface physical temperature profiles at spatial resolutions of 20, 240, 500 m, 1, 5, 10, 15, and 25 km, each exhibiting distinct ESI characteristics, to assess the impact of spatial resolution. We then simulated the temperature data in the four frequencies consistent with Chang'E‐2 (CE‐2) microwave radiometer and obtained the average ranges of dielectric loss. At 3, 7.8, 19.35, and 37 GHz, the average dielectric loss ranges were determined to be 0.0128–0.0170, 0.0083–0.0110, 0.0055–0.0073, and 0.0061–0.0081, respectively. These findings provide valuable insights for analyzing lunar surface temperature and observed brightness temperature, as well as for inverting physical and dielectric properties of the shallow regolith (e.g., dielectric loss). Key Points Analyzing lunar shallow temperature variation with real‐time effect solar irradiance (ESI) model considering terrain influence Assessing the real‐time ESI impact on physical and brightness temperature curves at diverse spatial resolutions Estimating the dielectric loss of shallow regolith by coupling simulated brightness temperature data with observations

As a promising hydrogen carrier, formic acid (HCOOH) is renewable, safe and nontoxic. Although noble-metal-based catalysts have exhibited excellent activity in HCOOH dehydrogenation, developing non-noble-metal heterogeneous catalysts with high efficiency remains a great challenge. Here, we modulate oxygen coverage on the surface of Ti 3 C 2 T x MXenes to boost the catalytic activity toward HCOOH dehydrogenation. Impressively, Ti 3 C 2 T x MXenes after treating with air at 250 °C (Ti 3 C 2 T x -250) significantly increase the amount of surface oxygen atoms without the change of crystalline structure, exhibiting a mass activity of 365 mmol·g −1 ·h −1 with 100% of selectivity for H 2 at 80 °C, which is 2.2 and 2.0 times that of commercial Pd/C and Pt/C, respectively. Further mechanistic studies demonstrate that HCOO* is the intermediate in HCOOH dehydrogenation over Ti 3 C 2 T x MXenes with different coverages of surface oxygen atoms. Increasing the oxygen coverage on the surface of Ti 3 C 2 T x MXenes not only promotes the conversion from HCOO* to CO 2 * by lowering the energy barrier, but also weakens the adsorption energy of CO 2 and H 2 , thus accelerating the dehydrogenation of HCOOH. Developing non-noble-metal heterogeneous catalysts with high efficiency in HCOOH dehydrogenation is significant for the acquisition of hydrogen, but remains a great challenge. Here, the authors modulate oxygen coverage of Ti 3 C 2 T x MXenes to boost the catalytic activity toward HCOOH dehydrogenation.