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Forests are one of the most important sources of negative oxygen ions (NAIs). NAIs have been recognized as beneficial for both physical and mental well–being, and higher concentrations of NAIs have been associated with improved health. However, the environmental factors that predominantly influence NAI concentration and their relationship with NAIs remain uncertain. This study aims to investigate the dominant factors and their impact on NAI concentration by observing NAIs and various environmental factors in two different environments (natural forest and urban forest) in the Beijing region over a one–year period. Through our investigation, we aimed to identify the key factor as well as other influential variables affecting NAI concentration. Our analysis encompassed the examination of dynamic concentration changes over multiple time scales, revealing uniform trends in both forest types. Notably, natural forests consistently demonstrated higher NAI concentration across these time scales, attributable to greater vegetation density and the stability of the forest microenvironment. By utilizing regression, correlation analysis, and structural equation analysis, we determined that relative humidity (RH) has the most significant effect on NAI concentration. Notably, both NAI concentration and RH displayed similar patterns across multiple time scales. When considering hourly average daily variation, the lowest values for both NAI concentration and RH were observed at noon, followed by an increase that persisted throughout the night. Seasonal average variation showed that both NAI concentration and RH peaked in the summer, followed by autumn. In terms of daily average annual variation, summer exhibited more days with high NAI concentration and high RH, which can be attributed to the increased rainfall during that season. Rainy weather was found to contribute to higher NAI concentration and RH levels. Furthermore, our findings revealed that on a daily scale, high RH and high NAI concentration occurred more frequently under conditions of high air temperature and low wind speed. However, the air quality index demonstrated only a minor effect in urban forest, while net radiation exhibited no significant influence on NAI concentration and RH. The fitted equations and trends of the aforementioned environmental factors with NAI concentration and RH were found to be comparable. The path analysis further corroborates these conclusions. The findings of this study indicate that RH is the primary factor driving the fluctuations in NAI concentration across various time scales, including hourly, daily, and seasonal variations. The study revealed that wind speed indirectly impacts NAI concentration by modulating RH. In contrast, air temperature influences NAI concentration both indirectly through RH and directly. The environmental factors affecting NAI concentration in the two types of forests are similar, but the degrees vary; in urban forests, wind speed, air quality index, and RH are slightly higher, while in natural forests, air temperature is slightly higher. This discovery further enhances our understanding of the underlying mechanisms and dynamic changes in NAI concentration within urban forests and natural forests. Moreover, it confirms the reliability and effectiveness of using RH as an indicator to monitor changes in NAI concentration over time. [ABSTRACT FROM AUTHOR]

New particle formation contributes significantly to the number concentration of ultrafine particles (UFPs, d ≤ 100 nm) and has a great impact on human health and global climate. Iodine oxoacids (HIO x , including iodic acid, HIO 3 , and iodous acid, HIO 2) have been observed in pristine regions and proved to dominate new particle formation (NPF) at some sites. However, the knowledge of HIO x in polluted urban areas is rather limited. Here, we conducted a long-term measurements of gaseous iodine oxoacids and sulfuric acid in Beijing from January 2019 to October 2021 and also in Nanjing from March 2019 to February 2020 and investigated the contribution of HIO x to UFP number concentration in both urban environments. HIO 3 is highest in summer, up to 2.85 × 10 6 and 2.78 × 10 6 cm -3 in Beijing and Nanjing, respectively, and is lowest in winter by 96 % and 75 %, respectively. HIO 3 exhibits more prominent variation than H 2 SO 4 in both urban sites. HIO 3 concentration shows a clear diurnal pattern at both sites with a daily maximum at around noontime, similar to the atmospheric temperature, solar radiation, and ozone (O 3) levels. HIO 2 concentration has the same diurnal and seasonal trend as HIO 3 but is overall about an order of magnitude lower than HIO 3 concentration. Back trajectory analysis suggests that the sources for inland iodine species could be a mix of marine and terrestrial origins, with both having peak iodine emission in warm seasons. While the contribution of HIO 2 to particle growth is marginal in Beijing and Nanjing, our results demonstrate that HIO 3 enhances the particle survival probability of sub-3 nm particles by about 40 % (median) and occasionally by more than 100 % in NPF events, suggesting HIO x are significant contributor to UFPs in polluted urban areas. As the growth contribution from HIO 3 and H 2 SO 4 is similar on a per-molecule basis, we propose that the sum of HIO 3 and H 2 SO 4 could be used to estimate sub-3 nm particle growth of inorganic acid origin in polluted atmospheres with a significant amount of HIO x. [ABSTRACT FROM AUTHOR]

Based on the air quality monitoring data and meteorological data, the pollution characteristics of PM2.5 in southern Beijing and relationships between PM2.5 levels and meteorological features were analyzed. The results showed that during the investigation period, daily air quality was characterized as "excellent" and "favorable" (<75 µg m−3) on 77% of days in southern Beijing, and there were only two days with serious air pollution (>250 µg m−3). The PM2.5 concentration displayed obvious monthly variations with the highest concentration in November and the lowest concentration in August. When PM2.5 pollution episodes occurred (>75 µg m−3) in this area, the wind direction was often south and southeast with low wind speed (<3 m∙s−1), followed by southwest wind; in addition, the air temperature was low (<10 °C) and the relative humidity was high (>75%). The air quality of the study area was affected by the pollution transmission form the surrounding areas, especially the southeastern and the southern transmission paths. The PM2.5 concentration was positively correlated with SO2, NO2 and CO, and negatively correlated with O3. Therefore, to further improve the air quality in the study area, it is necessary to coordinate the control of PM2.5 and O3. [ABSTRACT FROM AUTHOR]

Construction of urban green and blue spaces (UGBS) has long been proved as an effective mitigation to urban heat island effect. Yet we spotted a rarity of studies evaluating UGBS's climatic effect difference in different land-uses, and a rarity of empirical evidence on better UGBS allocation for better cooling. In this study, we conducted field measurements of nighttime air temperature (Ta) and relative humidity (Rh) along an enclosed transect at the core area of Beijing, China, and evaluated the contributions of UGBS on local-scale climate. Land-cover types and land-use classification scheme Local Climate Zone (LCZ) were used to analyze measured Ta and Rh. Urban vegetation coverage is further intersected with LCZs to evaluate vegetation's cooling and humidifying effects in different land-uses. Results show that better correlations were generally detected with larger buffer zones when more land-cover and land-use conditions were included. UGBS exhibit significant cooling and humidifying effects, and better regression models were built when green and blue spaces were taken as a whole rather than independently. Coverage of LCZ 1 (compact high-rise), LCZ 2 (compact midrise) and LCZ G (water coverage) were found to more significantly contribute to local-scale climate. Increasing vegetation coverage in LCZ 2 and LCZ 3 is expected to facilitate better cooling and humidifying effect. Results of this study may provide insights for practitioners to allocate UGBS for better urban cooling. [ABSTRACT FROM AUTHOR]

This study aims to investigate the extreme temperature variations of asphalt pavement structures. First, this study established a thermal analysis model using finite element methods to investigate the temperature profile of asphalt pavements. Thereafter, the significant factors affecting the pavement temperature were determined using the grey correlation method. Finally, linear prediction models for maximum, minimum, and average temperatures of asphalt layers at any depth were developed. The results indicated that the pavement and air temperature change trends were similar, and that the temperature decreased with increasing depth. The maximum temperature occurred on the road surface during the daytime and moved from the asphalt layer to the base layer during the night. The maximum temperature difference on the road surface was 26.8 °C. The most significant factors affecting the asphalt pavement temperature were air temperature and solar radiation. The maximum, minimum, and average temperatures of the asphalt layers had good linear relationships with air temperature, solar radiation, and depth of concern, and the R2 of these predicted models were all greater than 0.94. In addition, a comparison between the predicted and actual measured pavement temperature of Beijing's RIOHTRACK road in 2019 found that the R2 between the measured and predicted values was greater than 0.90 and the root-mean-squared error was less than 5 °C. Using this model, the maximum, minimum, and average temperatures of the asphalt layer at any depth can be determined if the air temperature is known. These results will be beneficial for analyzing the stresses and strains resulting from temperature differences and calibrating the structural design methods for asphalt pavements. [ABSTRACT FROM AUTHOR]

Deepening the understanding of diurnal characteristics and driving mechanisms of surface urban heat islands (SUHIs) across different local climate zones (LCZs) and time scales is of great significance for guiding urban surface heat mitigation. However, a comprehensive investigation of SUHIs from the diurnal, local, multi-seasonal, and interactive perspectives remains a large gap. Here, we generalized major diurnal patterns of LCZ-based SUHI intensities (SUHIIs) throughout 2020 over the urban area of Beijing, China, based on diurnal temperature cycle modeling, block-level LCZ mapping, and hierarchical clustering. A geographical detector was then employed to explore the individual and interactive impacts of 10 morphological, socioeconomic, and meteorological factors on the multi-temporal spatial differentiations of SUHIIs. Results indicate six prevalent diurnal SUHII patterns with distinct features among built LCZ types. LCZs 4 and 5 (open high- and mid-rise buildings) predominantly display patterns one, two, and five, characterized by an afternoon increase and persistently higher values during the night. Conversely, LCZs 6, 8, and 9 (open, large, and sparsely built low-rise buildings) mainly exhibit patterns three, four, and six, with a decrease in SUHII during the afternoon and lower intensities at night. The maximum/minimum SUHIIs occur in the afternoon–evening/morning for patterns 1–3 but in the morning/afternoon for patterns 5–6. In all four seasons, the enhanced vegetation index (EVI) and gross domestic product (GDP) have the top two individual effects for daytime spatial differentiations of SUHIIs, while the air temperature (TEM) has the largest explanatory power for nighttime differentiations of SUHIIs. All factor interactions are categorized as two-factor or nonlinear enhancements, where nighttime interactions exhibit notably greater explanatory powers than daytime ones. The strongest interactions are EVI ∩ GDP (q = 0.80) during the day and TEM ∩ EVI (q = 0.86) at night. The findings of this study contribute to an improved interpretation of the diurnal continuous dynamics of local SUHIIs in response to various environmental conditions. [ABSTRACT FROM AUTHOR]

This paper introduces a fast urban microscale meteorological model with a horizontal resolution of O(10) m, named URBAN (Urban Rapid & Building-Aware Neighborhood), which is capable of rapid assessment of meteorological fields over key urban areas, including wind speed, air temperature, humidity and thermal comfort index, with the execution time less than 10 minutes consuming 1 CPU core. URBAN uses a fast wind diagnostic method to construct three-dimensional (3-D) wind fields surrounding complex building clusters with their geometry resolved explicitly To enhance the accuracy of wind reconstruction and the continuity of the initial wind field around irregular buildings, we propose a new parameterization method based on stream functions, which can accurately characterize the influences of complex urban building clusters on the three-dimensional wind field The model can provide various results for the meteorological service of large outdoor activities, including conventional meteorological elements (wind, temperature, humidity, radiation, etc.) and the Universal Thermal Comfort Index, which is derived from the relationship between physiological processes and environmental meteorological conditions. In this paper, URBAN is applied to develop an automatic analysis and forecast system of microscale meteorological elements over the central Beijing region in summer during a large outdoor event. By comparing with the half-hourly observations from three auto weather stations (AWSs) in the region, the root-mean-square errors (RMSEs) of the modeled 10-meter-height wind speed, 2-meter-height air temperature and humidity are 0.98 m s−1,1.37 °C and 7.37%, respectively. [ABSTRACT FROM AUTHOR]

As an essential structural indicator of buildings, sky view factor (SVF) is one of the most critical factors affecting the urban thermal environment. However, the relationship between SVF and the thermal environment at the neighborhood scale has not been adequately studied. Therefore, this paper investigates the relationship between SVF and air temperature in different building scenarios based on the Local Climate Zone (LCZ) classification framework. Firstly, the study is based on multi-source urban data and the Open Street Map (OSM) to map the local climate zones in Beijing. Then, a simulation model with different LCZs was constructed based on realistic scenarios using the microclimate simulation software ENVI-met, and the thermal environment was simulated in 24 h on a single day in summer. Finally, the SVF and air temperature relationship under different LCZ scenarios was calculated and analyzed. The results show that (1) the SVF values of LCZ 1, LCZ 2, and LCZ 5 show a more apparent positive correlation with air temperature than other categories, and the SVF values of LCZ 6–9 show a negative and then positive correlation with air temperature; (2) in the morning, the dense building areas show a weak correlation with air temperature, and the differences in air temperature corresponding to the SVF values in different zones are greater; (3) in the morning, the air temperature in the dense building areas showed a weak correlation, the difference between the SVF values and the air temperature in different intervals was different, and when the SVF was larger or smaller, the air temperature change was smaller and concentrated, and the correlation between the air temperature and the SVF in the open building areas was not obvious; (4) with 12:00 as the dividing line, the SVF and the air temperature in all categories showed a weak positive correlation after this time. This study can provide guidance on optimizing building layouts and mitigating the impacts of urban heat on human health. [ABSTRACT FROM AUTHOR]

New particle formation processes contribute significantly to the number concentration of ultrafine particles (UFP), and have great impacts on human health and global climate. Iodine oxoacids (HIO x , including iodic acid, HIO3 and iodous acid, HIO2) have been observed in pristine regions and proved to dominate NPF events at some sites. However, the knowledge of HIO x in polluted urban areas is rather limited. Here, we conducted a long-term comprehensive observation of gaseous iodine oxoacids and sulfuric acid in Beijing from January 2019 to October 2021 and also in Nanjing from March 2019 to February 2020, and investigated the contribution of HIO x to UFP number concentration in urban environments. HIO3 concentration is highest in summer, up to 2.85×106 cm-3 and 2.78×106 cm-3 in Beijing and Nanjing, respectively, and is lowest in winter, with a more prominent seasonal variation than H2SO4. HIO3 concentration shows a clear diurnal pattern at both sites with a daily maximum at around noontime, similar to the atmospheric temperature, radiation and ozone (O3) levels. HIO2 concentration has the same diurnal and seasonal trend as HIO3 but is overall about one order of magnitude lower than HIO3 concentration. Back trajectory analysis suggests that the sources for inland iodine species could be a mix of marine and terrestrial origins, both having peak iodine emission in warm seasons. While the contribution of HIO2 to particle growth is marginal in Beijing and Nanjing, our results demonstrate that HIO3 enhances the particle survival probability of sub-3 nm particles by about 40 % (median) and occasionally by more than 100 % in NPF events, suggesting HIO x are non-negligible contributor to UFPs in polluted urban areas. As the growth contribution from HIO3 and H2SO4 is similar on a per-molecule basis, we propose that the sum of HIO3 and H2SO4 could be used to estimate sub-3 nm particle growth of inorganic acid origin, in the polluted atmospheres with a significant amount of HIO x . [ABSTRACT FROM AUTHOR]

Background and aims: Studies concerning the impact of air temperature on esophagogastric variceal bleeding (EGVB) have yielded conflicting results. Our study aimed to evaluate the correlation between air temperature and EGVB. Methods: A time-stratified case-crossover study design was performed. Patients received emergency gastroscopic hemostasis for upper gastrointestinal bleeding between Jan 1, 2014, and Dec 31, 2018 in the Fifth Medical Center of PLA General Hospital were enrolled. Conditional logistic regression analysis was applied to determine the association between air temperature and EGVB for different lag structures. Results: A total of 4204 cirrhotic patients diagnosed with EGVB and received emergency gastroscopic hemostasis were enrolled. The mean number of daily EGVB cases peaked in October (2.65 ± 1.69) and fell to the lowest level in July (1.86 ± 1.38), and was 2.38 ± 1.58 in spring, 2.00 ± 1.46 in summer, 2.37 ± 1.58 in autumn, and 2.45 ± 1.58 in winter, respectively (P < 0.0001). In conditional logistic regression analysis, no significant correlations between air temperature and EGVB were observed and no significant difference were found when stratified by age, sex, etiology, liver cancer status, and grade of varices. Conclusion: Emergency admission for EGVB showed significant monthly and seasonal fluctuations, while in conditional logistic regression analysis, no association between minimum temperature and emergency admission for EGVB were observed. [ABSTRACT FROM AUTHOR]

Perfluorohexane sulfonic acid (PFHxS), one of the substitutes for perfluorooctane sulfonic acid (PFOS), has been widely discussed around the world. In this study, the atmospheric concentrations of PFHxS in Beijing in the summer and autumn of 2021 were monitored, and the gas–particle partitioning and wet and dry deposition characteristics were analyzed. The results show that the average total concentrations of PFHxS in Beijing in the summer and autumn were 1.61 pg/m3 and 1.41 pg/m3, respectively. The particulate fraction φ of PFHxS was about 48% during the research period, and there was a significant positive correlation between φ and air temperatures. The linear fitting relationship between log K p (gas–particle partition coefficient) and log P L (compound vapor pressure) showed that the absorption between the PFHxS molecule and particulate matter dominated the process of gas–particle partitioning. The total deposition flux of PFHxS was the largest in July and the smallest in October, with values of 55.2 and 23.7 ng/m2, respectively. During the study period, PFHxS in the atmosphere had no obvious health impacts on humans. However, with their extensive use, the possible harmful effects on children should be continuously investigated. [ABSTRACT FROM AUTHOR]

We compare apparent temperatures – that is a combination of 2 m air temperature, relative humidity and surface wind speed in four Earth System Models under the modest greenhouse emissions RCP4.5, the “business-as-usual" RCP8.5 and the stratospheric aerosol injection G4 geoengineering scenarios. Apparent temperatures come from both a 10 km resolution dynamically downscaled model (WRF), and a statistically bias corrected (ISIMIP) and downscaled simulation for the greater Beijing region. ISIMIP downscaling method tends to simulate apparent temperatures well at present in all seasons, and WRF produces warmer winters than does ISIMIP. WRF produces warmer winters and cooler summers than does ISIMIP in the future. These differences mean that estimates of numbers of days with extreme apparent temperatures vary systematically with downscaling method, as well as between climate models and scenarios. Air temperature changes dominate differences in apparent temperatures between future scenarios even more than they do at present because the reductions in humidity expected under solar geoengineering are overwhelmed by rising vapor pressure due to rising temperatures and the lower windspeeds expected in the region in all future scenarios. Urban centres see larger rises in extreme apparent temperatures than rural surroundings due to differences in land surface type, and since these are also the most densely populated, health impacts will be dominated by the larger rises in apparent temperatures in these urban areas. [ABSTRACT FROM AUTHOR]

High-rise residential estates are characterized by high floor area ratios, many floors, and similar green area ratios. Beijing is hot in summer, and shading is an important strategy to improve the outdoor thermal environment of residential estates in summer. With respect to the morphological characteristics of high-rise residential estates, three types of shading were summarized, and their relationships with air temperature were quantified and analyzed. The three types of shading are building–tree integrated shading, building shading, and tree shading. Two residential estates that can represent the morphological characteristics of high-rise residential estates in Beijing were selected for field measurements, and the cooling effects of the three types of shading were obtained by analyzing the measured data. In the same residential estate, the daytime air temperature difference between shaded and un-shaded areas can be 0.5 °C or more. It was found that building–tree integrated shading has the most significant cooling effect, with building shading and tree shading second. The cooling effect of shading decreases with time, with morning shading having the greatest effect, and afternoon shading having the least effect. [ABSTRACT FROM AUTHOR]

• Scalable thermoplastic polyurethane films containing nanoparticles are recently developed. • Innovative advanced films present superior optical performance. • New films contribute to reduction in daytime overheat. Radiative cooling, which does not entail any energy consumption, has received considerable attention as a promising, practical, and sustainable solution to heatwaves. This study investigated single layer nanoparticles–polymer films that reflected sunlight and emitted radiation through atmospheric windows. In this paper, the fundamental principles of Mie theory, the cooling power model, and the thermal balance model of metamaterial films were first introduced. Then, the influence of fabrication parameters (nanoparticle materials, mass fractions, and thicknesses) to the reflectivity in solar band was experimentally explained. An increase in the mass fraction enhanced the reflectivity corresponding to the stretching vibration regions of C H, N H, and O H, while an increase in the thickness improved the reflectivity at non-absorption bands. Laboratory measurements indicated that the combination of TiO 2 , a fluorescent brightener, and a far-infrared ceramic powder on 100 μm thermoplastic polyurethane film achieved excellent solar reflectivity of 92.2 % and infrared emissivity of 96.1 %. Experimental testing and Fluent simulation showed that the film achieved a substantial cooling capacity in both Beijing and Tianjin. Under a transparent atmospheric window, it exhibited a subambient temperature of 3.7 °C when the air temperature reached its peak. The maximum daytime and night-time subambient temperature were 13.4 °C and 14 °C respectively. [ABSTRACT FROM AUTHOR]

Urban land-use affects surface air temperature; however, the impact of urban land-use on surface air temperature, particularly the extent to which it affects the duration of extreme heat waves, remains uncertain and the mechanisms of diurnal differences need to be further explored. This paper presents study of daytime/nighttime extreme heat waves duration in Beijing under different land-use changes by adopting an index of cumulative hours of extreme heat waves exceeding the certain thresholds. The urban day/night extreme heat waves cumulative hourly interpolation models were established based on high-resolution urban land-use and socioeconomic data and were assessed to have good performance. The annual average cumulative hours of extreme heat waves increased by 95% (daytime) and 116% (nighttime) in 2016–2020 compared to 2011–2015. The cumulative hours for each land-use type ranked as follows: urban land > cropland > water > grassland > woodland. We found that the cumulative hours of extreme heat waves increased significantly with the proportion of urban land and decreased significantly with the proportion of forested land and water. This research provided important information for alleviating extreme heat waves in cities and for rational land planning. [ABSTRACT FROM AUTHOR]

• A high-resolution air temperature measurement was applied in Beijing CUHI research. • Discrepancies among LCZ properties impact the spatiotemporal pattern of CUHI. • The research reveals the effects of LCZ spatial pattern on regional air temperature. • Distinct mitigation strategies were put forward in four subareas in Beijing. Urban heat island (UHI) is a widely concerned urban climate which impacts billions of residents worldwide. Nevertheless, inadequate rigorous air temperature (T air) measurement has become an obstacle to UHI research and mitigation, especially in megacities like Beijing. In this study, we applied a 1-km hourly T air dataset interpolated from records of 521 stations in Beijing. The dataset enables us to analyze UHI patterns on a block scale and the impacts of landscapes combined with the local climate zones (LCZ) scheme. Our results indicate that: (1) T air and its temporal variation in each LCZ vary significantly, which are highly relevant to their morphology and thermal-radiative properties. (2) LCZ 1 and LCZ 2 have the highest nocturnal UHI intensities (UHII). Discrepancies among LCZs also cause various temporal variations in their UHII. (3) The spatial pattern of LCZs affects regional temperature. Area ratio and aggregation extent of LCZ 1&2 show significant positive correlations with regional temperature, while LCZ A&D&G have the opposite regularity. (4) Distinct mitigation strategies are put forward for each subarea in Beijing with various endowments of population and the LCZ structure. The study provides insight into Beijing UHI and plausible mitigation advice in megacities like Beijing. [ABSTRACT FROM AUTHOR]

The weekend effect of the canopy urban heat island (UHI) has been long recognized. However, how the UHI weekend effect (UWE) varies with the hour of day and season of year is still unclear; it remains largely unknown on how the UWE is regulated by various controls. To address these knowledge gaps, here we took Beijing, China as an example and investigated the detailed spatiotemporal UWE patterns and the major regulators with a 3‐year data set of in‐situ surface air temperatures. Our results indicate that the annual ΔIc (the UHI intensity difference on weekends and weekdays) is stronger at night (−0.13 ± 0.12 K; mean ± 1 STD) than during the day (−0.05 ± 0.10 K); at the seasonal scale, ΔIc reaches the strongest in winter (−0.14 K) and the weakest in summer (−0.05 K). The ΔIc is strongly regulated by anthropogenic heat flux (AHF), evidenced by a quasi‐synchronous diurnal pattern between ΔIc and ΔAHF (i.e., the AHF difference between weekends and weekdays). The nighttime ΔIc is intensely modulated by urban morphology, with a stronger modulation by the landscape shape index than by the distance of the station from the urban center. Weather conditions also modulate the ΔIc, with the ΔIc weakening with the increase of cloud coverage and wind speed level. We consider these findings deepen our understanding of the weekly rhythms of UHI as well as the underlying modulators. Key Points: A significant ΔIc (weekend‐weekday difference in canopy urban heat island) is observed in Beijing, ChinaΔIc is stronger at night than during the day and the two minima of diurnal ΔIc correspond well to morning and evening rush hoursVariations in weekday‐weekend contrasts in Ic and anthropogenic heat flux are synchronous yet ΔIc is also modulated by urban morphology and weather condition [ABSTRACT FROM AUTHOR]

To avoid a sharp rise in temperature in the cabin of parked vehicles exposed to solar radiation, experienced drivers leave some windows partly open when the vehicle is parked in the sunlight to achieve cooling through natural ventilation. However, the effectiveness of this measure to reduce the temperature under different weather conditions has not been verified. To this end, this study investigates the effect of open windows on the thermal environment of a vehicle under different environmental conditions. A field measurement, in which two identical vehicles with and without window gaps were used, was carried out in Daxing District, Beijing. The measurements were conducted for 15 days under different window gaps and ambient conditions. The results revealed that open windows resulted in a maximum temperature reduction of 6.7 °C in cabin air temperature under high temperature and high solar radiation, while only 0.6 °C can be reduced under low temperature and low solar radiation. The results also showed that when window gaps effectively reduce the air temperature, lower air temperature can be obtained with larger open-window areas. [ABSTRACT FROM AUTHOR]

Thermal condition of the surface soil layer was neglected due to much concern of the urban heat island effect, which has an important impact on cities. In this study, on-site measurements of surface soil layer temperatures were conducted between two east-west oriented buildings in the winter, spring and summer. Building shade was shown to reduce average surface soil layer temperatures to 0.33, 0.33 and 0.37°C in three seasons, respectively. The horizontal heat flux between the building and the soil was calculated and showed different intensities at various monitoring sites. Additionally, the building shade could reduce and stabilize the surface soil layer temperature. According to the analytic hierarchy process, among six energy factors only horizontal heat flux between the building and the soil was correlated significantly (p <0.05) to the different surface soil layer temperatures. This has a key or dominant role in affecting the difference in surface soil layer temperatures, which was influenced by the building shade. Moreover, the soil warming rate was reduced by the building shade (50% at most). The surface soil layer temperatures at various observation points were compared with the air temperature. The surface soil layer was found to have different roles between two sites in three seasons. [ABSTRACT FROM AUTHOR]

Despite the existing myriad of tools and models to assess atmospheric source–receptor relationships, their uncertainties remain largely unexplored and arguably stem from the scarcity of observations available for validation. Yet, Lagrangian models are increasingly used to determine the origin of precipitation and atmospheric heat by scrutinizing the changes in moisture and temperature along air parcel trajectories. Here, we present a unified framework for the process-based evaluation of atmospheric trajectories to infer source–receptor relationships of both moisture and heat. The framework comprises three steps: (i) diagnosing precipitation, surface evaporation, and sensible heat from the Lagrangian simulations and identifying the accuracy and reliability of flux detection criteria; (ii) establishing source–receptor relationships through the attribution of sources along multi-day backward trajectories; and (iii) performing a bias correction of source–receptor relationships. Applying this framework to simulations from the Lagrangian model FLEXPART, driven with ERA-Interim reanalysis data, allows us to quantify the errors and uncertainties associated with the resulting source–receptor relationships for three cities in different climates (Beijing, Denver, and Windhoek). Our results reveal large uncertainties inherent in the estimation of heat and precipitation origin with Lagrangian models, but they also demonstrate that a source and sink bias correction acts to reduce this uncertainty. The proposed framework paves the way for a cohesive assessment of the dependencies in source–receptor relationships. [ABSTRACT FROM AUTHOR]

Urban artificial water dissipation is a concomitant process of human water use in built‐up areas that can absorb heat through evapotranspiration, reduce air temperature, transfer surface water to the atmosphere, and participate in the urban water cycle. In the context of increased urbanization, the impact of artificial water dissipation on urban climates cannot be ignored. In this study, calculation models for artificial water dissipation from different underlying surface types (buildings, hardened ground, soil, and vegetation) were introduced into an urban canopy model and coupled with the weather research and forecasting (WRF) model for mesoscale weather simulations of the Beijing area. Observational datasets of temperature and humidity from automatic weather stations in Beijing were used for validation. Results showed that the coupled model could reproduce the temperature and humidity of urban weather stations in Beijing more accurately compared to simulations that did not employ an urban canopy model or that adopted a traditional urban canopy model. In the Beijing urban area, the latent heat flux of NON, urban canopy model, and artificial water dissipation into the UCM are approximately 0, 35, and 65 W/m2, respectively, and the anthropogenic latent heat is about 30 W/m2. Incorporating urban artificial water dissipation into the urban canopy model reduced the urban air temperature by 0.2°C and increased the specific humidity by 0.6 g/kg, alleviating urban heat island effects and increasing humidity. These findings indicate that artificial urban water dissipation plays an important role in urban weather and climate that should be considered by urban canopy models. In the future, this model can be coupled into WRF for more accurate mesoscale weather simulations. [ABSTRACT FROM AUTHOR]

Air-to-water heat pumps (AWHPs) utilize renewable energy and have found worldwide applications, with the seasonal coefficient of performance (SCOP) as a key index. Considering reliability and costs, short-term dynamic monitoring combined with regression analysis and extrapolation is used for predicting SCOP. Different regression models are being researched. A statistical analysis method is proposed to work out the optimal scheme. A series of prediction models with different independent variables, fitting methods and training dataset acquisition methods are discussed. Two indicators, the qualification rate R ±10% and the maximum relative error E max , are proposed for accuracy evaluation. For analysis a typical AWHP heating system in Beijing was monitored for 78d. Linear fitting performs better than quadratic polynomial fitting. For the consecutive-day method, the prediction deviation decreases with a longer test time and presents diminishing marginal benefits. A critical value of 10-day is identified and unrepresentative days should be avoided. For the typical-meteorological-day method, three days with an outdoor air temperature (T out) range covering over 50% days of the heating season and including the average T out of local winter are recommended. Satisfactory prediction results are realized, with R ±10% >97% and E max <14%, while using T out or the difference between water temperature and T out presents consistent accuracy. • Multiple regression models for evaluating AWHP's SCOP are reviewed. • A field test of a practical AWHP heating system is conducted with 78-day data. • A statistical analysis method is proposed to work out the optimal scheme. • Independent variable, fitting method and dataset acquisition method are discussed. • Typical-day data using linear fitting with Tout is feasible for prediction. [ABSTRACT FROM AUTHOR]

Typical urban and rural temperature records are essential for the estimation and comparison of urban heat island effects in different regions, and one of the key issues is how to identify the typical urban and rural stations. This study tried to analyze the similarity of air temperature sequences by using dynamic time warping algorithm (DTW) to improve the selection of typical stations. We examined the similarity of temperature sequences of 20 stations in Beijing, and the results indicated that DTW algorithm could identify the difference of temperature sequence, and clearly divide them into different groups according to their probability distributions. DTW algorithm could create more rigorous and reasonable classification for typical urban and rural stations in Beijing by comparing with remote sensing and cluster analysis method. We also found that some traditional rural stations did not represent temperature variation in rural areas because their surrounding environments have been highly modified by urbanization process in last decades, and this might lead to an underestimate of the urban climate effect by 1.24℃. The study suggests that DTW algorithm is a simple and efficient method for selecting appropriate temperature records and analyzing temperature sequences with a good potential in improving urban heat island estimation. [ABSTRACT FROM AUTHOR]

Information on the spatiotemporal characteristics of Beijing's urban–rural near-surface air temperature difference, known as the canopy layer urban heat island (UHI), is important for future urban climate management strategies. This paper investigates the variation of near-surface air temperatures within Beijing at a neighbourhood-scale resolution (∼ 100 m) during winter 2016 and summer 2017. We perform simulations using the urban climate component of the ADMS-Urban model with land surface parameters derived from both local climate zone classifications and OpenStreetMap land use information. Through sensitivity simulations, the relative impacts of surface properties and anthropogenic heat emissions on the temporal variation of Beijing's UHI are quantified. Measured UHI intensities between central Beijing (Institute of Atmospheric Physics) and a rural site (Pinggu) during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) campaigns, peak during the evening at ∼ 4.5 ∘ C in both seasons. In winter, the nocturnal UHI is dominated by anthropogenic heat emissions but is underestimated by the model. Higher-resolution anthropogenic heat emissions may capture the effects of local sources (e.g. residential buildings and adjacent major roads). In summer, evening UHI intensities are underestimated, especially during heatwaves. The inability to fully replicate the prolonged release of heat stored in the urban fabric may explain this. Observed negative daytime UHI intensities in summer are more successfully captured when surface moisture levels in central Beijing are increased. However, the spatial correlation between simulated air temperatures and satellite-derived land surface temperatures is stronger with a lower urban moisture scenario. This result suggests that near-surface air temperatures at the urban meteorological site are likely influenced by fine-scale green spaces that are unresolved by the available land cover data and demonstrates the expected differences between surface and air temperatures related to canopy layer advection. This study lays the foundations for future studies of heat-related health risks and UHI mitigation strategies across Beijing and other megacities. [ABSTRACT FROM AUTHOR]

• The urban forest was a C sink, which was dominated by changes in R e rather than GEP. • Annual GEP and R e were primarily controlled by summer SWC. • Summer T a impacted annual NEE through the suppression of R e , rather than GEP. • Drought decreased both GEP and R e , with greater reduction in R e relative to GEP. Afforestation projects in urban areas have generally prospered in China. Although urban forests play an important role in sequestering carbon (C) at local to regional scales, understanding the current role of C-sink strength in urban forests is generally absent. We used continuous eddy-covariance and hydrometeorological data from 2012 to 2020 acquired from an urban forest reserve in Beijing to assess the interannual variability (IAV) in C-fluxes, as well as their key controlling factors. Over the study period, the urban forest was mostly a C-sink, maintaining a mean net ecosystem exchange (NEE) of -195 ± 98 g C m−2 yr−1. Interannual variability in NEE was largely due to variation in ecosystem respiration (R e). Interannual variation in annual gross ecosystem production (GEP) and R e were controlled to a large extent by summer soil water content (SWC). Since the effects of SWC on GEP and R e partially offset their individual responses, IAV in annual NEE was seen as being less influenced by summer SWC. Annual NEE was constrained by changes in summer air temperature (T a). Residuals based on a R e -to- SWC regression exhibited significant decreases with increasing summer T a , appreciably more than the residuals based on GEP- to -SWC regressions. This underscored the importance of summer T a in impacting annual NEE through the suppression of R e , rather than through GEP. Our analysis also revealed that R e was more affected by drought than GEP. Long-lasting drought, greater than one month, was seen to impact GEP and R e more than short-term drought. Our study might imply that irrigation by elevating SWC was not be an effective strategy improving NEE of urban forest. Under anticipated climate change, drought and attendant high temperatures would impact C-fluxes more in the future. Land-surface models should adequately address the inhibitive characteristics of high temperatures on C-fluxes to improve simulations. [ABSTRACT FROM AUTHOR]

• We examined environmental controls on ecosystem RUEs in a young, urban plantation. • Upward trends in RUEs corresponded with increases in NDVI. • Duration and timing of drought played a significant role in regulating RUEs. • Ample mid-summer rainfall lessened the impact early, spring drought had on RUEs. Understanding the long-term trends and interannual variability in ecosystem resource use efficiencies (RUEs) and their controlling factors is central to the prediction of ecosystem response to climate change. However, knowledge in this area, particularly as it pertains to young urban plantations, remains largely absent. In this study, we used continuous eddy covariance and site-specific climatic data collected from a 12-year-old mixedwood plantation in Beijing, China, to assess (i) long-term trends, (ii) interannual variability, and (iii) key controlling factors of RUEs with respect to plantation use of carbon (i.e., CUE), water (WUE) and light (LUE). On average, annual CUE and WUE over the 2012–2020 growing seasons increased by about 5.2 and 7.6%. Trends in RUEs corresponded with increases in normalized difference vegetation index (NDVI) when the plantation transitioned from a carbon source to a sink. Analysis of controlling factors indicated that RUEs were regulated by NDVI and other environmental factors at varying degrees dependent on season. Interannual variability in (i) CUE was largely controlled by spring soil temperature, (ii) WUE by summer water vapor pressure deficit and spring soil water content (SWC), and (iii) LUE by photosynthetically active radiation, summer SWC and spring air temperature. Relative seasonal changes in paired RUEs were positively correlated, with soil water availability being the most limiting. Long-term summer drought was shown to evoke severe and persistent decline in same-year RUEs. Ample mid-summer rainfall lessened the impact of early spring drought on plantation performance. Our results emphasized the need to account for the combined effects of climatic controls and canopy-physiological characteristics in the management of young plantations. [ABSTRACT FROM AUTHOR]

Vegetation plays a critical role in climate regulation by cooling and humidifying urban regions. The climate regulation capacity of vegetation varies in different seasons, and its association with the coupling of temperature and humidity remains poorly understood. Here, we investigated the climate regulation potential of vegetation by establishing a set of indices, namely, cooling intensity (CI), cooling efficiency (CE), humidifying intensity (HI), and humidifying efficiency (HE), using continuous decadal field measurements (2013–2022) of temperature and humidity in vegetation and built-up areas in Beijing, China. Additionally, we examined the coupling effect and threshold of cooling and humidification using these indices. Climate regulation by vegetation was insignificant at night. However, the daytime results were as follows: (1) the maximum CI and CE were similar in four seasons, and their ratio was 2:3:2:1 in spring, summer, autumn, and winter, respectively; (2) the ratio of maximum HI was 4:10:7:3, whereas that of the maximum HE was 7:8:7:2 in spring, summer, autumn, and winter, respectively; and (3) the coupling of ambient temperature and humidity affected the climate regulation of vegetation. The CE and HE of vegetation increased significantly when the ambient temperature exceeded 15.1 °C and 8.5 °C, respectively. The CI and HI decreased with increasing humidity and were highest in a high temperature and low humidity ambient environment. Our study presents scientific insights into vegetation cooling and humidifying effects under different climate backgrounds and provides an enhanced understanding of the coping ability of vegetation in a severe heat island environment. • Climate regulation by urban vegetation was more significant during the day. • The cooling efficiency of vegetation increases at air temperature >15.1 °C. • The humidifying efficiency of vegetation increases at air temperature >8.5 °C. • High air temperature and low humidity enhance climate regulation by vegetation. [ABSTRACT FROM AUTHOR]

To investigate the variation of classroom environment during typical lecture hours, repeated field measurements and intervention experiments for indoor temperature were carried out in a typical class (95 min in duration, 0.32–0.39 person/m2 of occupants density) in a spring semester of a university in Beijing. Environmental data were recorded every 5 min, including indoor temperature, relative humidity and carbon dioxide (CO 2) concentration. Additionally, volatile organic compounds (VOCs) were sampled and indoor air quality (IAQ) were evaluated repeatedly. The results of field measurements showed the average air temperature in the classroom ranged from 21.2 ± 0.8 °C to 26.8 ± 0.7 °C, relative humidity ranged from 23.1 ± 1.8% to 57.5 ± 0.2%, and the average concentrations of CO 2 and total volatile organic compounds (TVOC) were 1,291–1,833 ppmv and 159-1,178 ppbm respectively. The subjective evaluations collected during intervention experiments showed that perceived odor intensity by visitors upon entering the room increased significantly, meanwhile the satisfaction and acceptability of air quality reduced considerably at the indoor temperature of 27 °C than that at 24 °C. Present results suggest when the indoor temperature rises, it is necessary to increase the outdoor air supply rate to ensure air freshness in classrooms. Subsequently, the calculated CO 2 emission rate by students increased by 0.54 L/h per person for every 1 °C rise in indoor temperature. Corresponding to the control target of indoor CO 2 concentration of 1,000 ppmv, the outdoor air ventilation rate required to eliminate occupant-generated pollution needs to be increased by 0.25 L/s per person. • The air quality in a classroom during typical lecture periods was investigated. • The CO 2 emission rate of college students was estimated using indoor CO 2 levels. • Perceived air quality was reduced significantly as indoor temperature increased. • Personal CO 2 emission rate increases by 0.54 L/h for 1 °C rise in temperature. • Higher outdoor air supply rate is recommended when indoor temperature rises. [ABSTRACT FROM AUTHOR]

Activities in urban parks contribute to greater socialization and a more active lifestyle, yet such health benefits could be mingled with health concerns – e.g., extreme thermal events or hazardous air quality, which received much less attention than the benefits. Particularly, there is a lack of empirical studies on behavioral changes under different thermal and air-quality conditions. To address the research gap, this study quantitatively measured the impact of thermal environmental parameters (air temperature, humidity, wind scale) and air quality parameters (PM 2.5 , PM 10 , NO 2 , SO 2 , O 3 , integrated air quality index (AQI)) on the daily attendance at Haidian Park – a neighborhood park – and Chaoyang Park – an urban recreational park – in Beijing covering consecutive days from April 1, 2020 to March 31, 2021. The analysis revealed the degrees to which urban park visits were influenced by temperature and air quality. Temperature had the greatest impact on the attendance, while the impact was asymmetric: The effect of low temperature showed more elasticity than that of high temperature. The influence of air quality was not as significant as that of the air temperature. The analysis also showed that such impacts of thermal and air-quality conditions on park visits were mediated by type of activities (the everyday-recreational continuum), days (weekday/weekend), and seasons. The findings provide useful implications for tackling the wicked problem of promoting outdoor activities in parks while controlling adverse effects of thermal and air-quality conditions. [ABSTRACT FROM AUTHOR]

Understanding the associations of indoor air temperature with building physical characteristics is essential for human comfort and energy saving. While traditional studies depended heavily on simulation tools, statistical approaches have recently provided higher flexibility and efficiency to explore factors associated with indoor air temperature. Under such background, this study systematically constructed building spatial design and occupancy features for 53 university classrooms in 4 teaching buildings in Beijing, China, and used statistical models to quantify their impacts on indoor air temperature. Both multiple linear regression (MLR) and random forest regression (RFR) were conducted for different time periods in a day, and the MLR coefficients and RFR feature importance were examined. 16 spatial design features and 5 occupancy features were identified as significant. Among spatial design features, floor number of the classroom had the most notable positive impacts throughout a day. Window-to-wall ratios from different orientations had distinctive influences and added up to make a huge difference. Impacts from classroom size and position, parent building's forms and envelopes were certain but less important. Among occupancy features, it was found for teaching buildings that the whole-buildings' occupancy had stronger impacts over the classrooms' one, and daily occupancy over temporal one, with building daily occupancy rate being the most influential. The results highlight the potential to adjust thermal environment through proper organization of spatial design and occupancy features addressing their rankings. The RFR models obtained adjusted R2 of above 98%, testifying the effectiveness of predicting indoor air temperature with well-selected building features. [Display omitted] • 16 spatial design and 5 occupancy features were related to indoor air temperature. • Impacts of these features were quantified and ranked using statistical models. • Floor number of the classroom was the most influential spatial design feature. • Building daily occupancy rate was the most influential occupancy feature. • The random forest regression models obtained notable performance. [ABSTRACT FROM AUTHOR]

Dense sensor networks are being built to collect urban climate information in global cities, yet the performance of network design has rarely been accessed. Existing studies have three major issues: 1) focusing on summertime and lack of seasonal variation, 2) overlooking meteorological variables other than air temperature, 3) not incorporating the current network into the future design. In this study, we proposed a cluster-based network design for monitoring meteorological variables within the urban canopy layer, and examined its applications in Beijing and Hong Kong by using weather simulation data as ground truth. The clustering analysis separates the city into groups with similar urban climate characteristics, and consequently one sensor is sufficient to collect representative meteorological information for each group. Results show a robust design strategy is to train the cluster model with multiple meteorological variables that contain seasonal variations. Utilizing the cluster-based design strategy, we optimize the current network by rearranging sensor locations. For the study period, the sampling error of meteorological variables by the rearranged network is 22.7% smaller in Beijing and 10.7% smaller in Hong Kong than that by the current network. With a sampling ratio of 6.3%, the expanded monitoring network has a mean bias of 0.58 °C (0.44 °C) for representing the air temperature variability across Beijing (Hong Kong). The proposed method is not sensitive to the cluster models, background climate, and resolution of the weather simulation data. The design strategy thus can be applied to other cities for establishing dense urban climate monitoring networks. • Three major issues in current urban climate monitoring network design are identified. • A cluster-based network design is proposed to overcome the existing issues. • Rearrange sensor locations can improve the network performance by more than 10%. • The cluster-based design is robust for cities under different background climate. [ABSTRACT FROM AUTHOR]

The unique climate in cold plateaus leads to long and cold winters, which result in the characteristics and creation of an indoor thermal environment different from that of plain areas. However, there is a lack of detailed research on and evaluation of indoor temperature distributions. This study took an office building in Lhasa as an example to study the indoor non-uniform temperature distributions with radiator and solar radiation. The indoor and outdoor thermal environment parameters were tested. Next, a numerical model was established and verified. On a typical winter weather day, although the average indoor air temperature and radiation temperature in Lhasa are higher than those in Beijing (both are cold areas), the temperature in both is lower than comfortable levels. The indoor vertical air temperature differences are below 3 °C, with a 5% dissatisfaction most of the time. Solar radiation and radiators seriously affect the uniformity of the indoor thermal environment. The radiation asymmetry in Lhasa is significant, and the maximum radiation temperature asymmetry can reach 8.73 °C. In addition, the setting of north-facing windows should be avoided as far as possible in Tibetan areas. Suitable design and evaluation standards should pay attention to the obvious phenomenon of uneven indoor temperature distribution. [ABSTRACT FROM AUTHOR]

Ground-based microwave radiometers (MWRPS) can provide continuous atmospheric temperature and relative humidity profiles for a weather prediction model. We investigated the impact of assimilation of ground-based microwave radiometers based on the rapid-refresh multiscale analysis and prediction system-short term (RMAPS-ST). In this study, five MWRP-retrieved profiles were assimilated for the precipitation enhancement that occurred in Beijing on 21 May 2020. To evaluate the influence of their assimilation, two experiments with and without the MWRPS assimilation were set. Compared to the control experiment, which only assimilated conventional observations and radar data, the MWRPS experiment, which assimilated conventional observations, the ground-based microwave radiometer profiles and the radar data, had a positive impact on the forecasts of the RMAPS-ST. The results show that in comparison with the control test, the MWRPS experiment reproduced the heat island phenomenon in the observation better. The MWRPS assimilation reduced the bias and RMSE of two-meter temperature and two-meter specific humidity forecasting in the 0–12 h of the forecast range. Furthermore, assimilating the MWRPS improved both the distribution and the intensity of the hourly rainfall forecast, as compared with that of the control experiment, with observations that predicted the process of the precipitation enhancement in the urban area of Beijing. [ABSTRACT FROM AUTHOR]

Previous studies have confirmed the inextricable connection between meteorological factors and air pollutants. This study presents the complex nonlinear relationship between meteorological variables and four major air pollutants under high-concentration air pollution in Beijing. The generalized additive model combined with marginal effects is used for quantitative analysis. After controlling the confounding factors such as long-term trends, seasonality and spatio-temporal deviation, the final fitting results exhibit that temperature, relative humidity and visibility are the most significant meteorological variables associating with PM2.5 concentration, and the marginal effect reaches 80%, −23% and 270%, respectively. Temperature and relative humidity are the most significant variables for SO2, and the marginal effect reaches 15% and 7%. The most significant variables for O3 are temperature and solar radiation, with marginal effect of up to 70% and 8%. Atmospheric pressure and temperature results in a positive effect on CO, and the marginal effect can reach 18% and 80%. All these indicate that local meteorological variables are a significant driving factor for air quality in Beijing. Other variables, such as wind speed, visibility, and precipitation, display some influence on air pollutants, but have less explanatory power in the model. Overall, our study provides a better understanding of the relationship between local meteorological variables and air quality, as well as an insight into how climate change affects air quality. [ABSTRACT FROM AUTHOR]

Ground-based microwave radiometer profilers (MWRPs) are widely used to provide high-temporal resolution atmospheric temperature and humidity profiles. The quality of the observed brightness temperature (TB) from MWRPs is key for retrieving accurate atmospheric profiles. In this study, TB simulations derived from a radiative transfer model (RTM) were used to assess the quality of TB observations. Two types of atmospheric profile data (conventional radiosonde and ERA5 reanalysis) were combined with the RTM to obtain TB simulations, then compared with corresponding observations from three MWRPs located in different places in North China to investigate the influence of input atmospheric profiles on TB simulations and evaluate the quality of TB observations from the three MWRPs. The comparisons of the matching samples under clear-sky conditions showed that TB simulations derived from both radiosonde and ERA5 profiles were very close to the TB observations from most of the MWRP channels; however, the correlation was lower and the bias was obvious at 51.26 GHz and 52.28 GHz, which indicates that the oxygen absorption component in the RTM needs to be improved for lower-frequency temperature channels. The difference in location of the radiosonde and MWRP sites affected the TB simulations for the water vapor channels, but had little impact on temperature channels that are insensitive to humidity. Comparisons of both simulations (ERA5 and Radiosonde) and the corresponding TB observations from the three sites indicated that the water vapor channels observation quality for the MWRP located in southern Beijing needs improvement. For the two types of profile data, ERA5 profiles have a more positive effect on TB simulations in the water vapor channels, such as enhanced consistence, reduced bias and standard deviation between simulations and observations for those MWRPs located away from the radiosonde station. Therefore, hourly ERA5 data are an optimal option in terms of compensating for limited radiosonde measurements and enhancing the monitoring quality of MWRP observations within 24 h. [ABSTRACT FROM AUTHOR]

[Display omitted] • This paper focused on stable urban heat island which is lack of attention in current studies. • This paper used morphological spatial pattern analysis to identify the key zones. • This paper obtained the causes and characteristics of the stable urban heat island. People residing near stable urban heat islands (UHIs) experience a high long-term heat exposure, and the health consequences of such islands may be more severe than those of an expanding UHI; however, these areas are hidden in the overall heat island and not focused on. We developed a novel approach to identify the locations and ranges of stable UHIs by considering multiple frequency urban heat islands (MFUHIs). The MFUHIs were identified through multi-temporal remote sensing data and morphological spatial pattern analysis (MSPA), and the approach was applied in the case area of Beijing, the capital city of China. Specifically, the MFUHIs in Beijing were classified according to the landscape characteristics, based on the field survey and remote sensing data. The landscape indicators included land-use types, biophysical parameters (normalised difference vegetation index (NDVI), proportion of water areas, and impervious surface area (ISA)) and 3-D metrics (building density and building heights), which were considered causative factors. The relationship between the land surface temperature and landscape indicators was examined using ordinary least-squares (OLS) regressions and the Area Weighted Contribution Index (AWCI). The results showed that the MFUHIs in Beijing have four key zones, in which the surface temperature is more than 9 ℃ higher than the average temperature of the urban area, and the air temperature is 3.3–8.5 ℃ higher than the built-up temperature in the non-UHI area. The OLS regression and spatial statistics of the landscape indicators and surface temperature indicated that the regions in which area where MFUHIs occur could be characterised by a relatively high degree of impervious surface coverage, lack of green space and water area, and presence of low-rise and high-density buildings. The average number of building-floors in MFUHIs was between 1.93 and 2.64, and the number of floors in the entire study area was less than 3.6. Moreover, the building-densities in the MFUHIs were 16.25% to 27.62% higher than that in the whole study area. According to the result of the AWCI and field survey, the MFUHIs were classified into transportation, historical block, commercial, and city village high-temperature centre. The main findings indicated that certain regions between the city centre and rural areas, in which sound planning is not implemented, are the hotspots of UHI mitigation and risk elimination regions. The proposed approach can help policymakers develop targeted mitigation strategies in urban planning. [ABSTRACT FROM AUTHOR]

Construction of urban parks has long been proved as an effective way to mitigate urban heat island effect, and better arrangement of green spaces in a city is expected to help regulate urban climate. To provide further empirical evidence and guidance for urban green spaces planning and design, field measurement of summertime air temperature and relative humidity was conducted in and out of 10 large urban parks in Beijing, China. Averaged daytime and nighttime park cool and wet island intensity were 1.09 ℃, 1.48 % and 3.63 ℃, 4.25 % respectively. Parks' influence on local-scale climate extended as far as over 1km during summer nights, and more effective cooling effects were provided within approximately one-park width. Among all influencing factors, park size plays dominant role in regulating nighttime local-scale climate in parks' adjacent area, while vegetation coverage around sampling points out of urban parks also has significant contributions, indicating that large urban parks and their surrounding urban greenery interact to affect neighborhood climate. Park size was the only factor found correlated with nocturnal park cool and wet island intensity. Results of this study provide additional information on large urban parks' local-scale climate effect and give insights to future urban green spaces planning and design practice. [ABSTRACT FROM AUTHOR]

Based on 139 nights of observational data of the Rayleigh lidar site in Beijing, China (40.5° N, 116.2° E), typical lower MIL cases and their temperature inversion evolution process were reported and compared with the SABER data from the same time. Meanwhile, the seasonal distribution of lower MIL cases over North China was also statistically analyzed. The average inversion temperature of the low MIL is 23.4 K, and the average layer thickness is 4.78 km with an average MIL bottom altitude of 68.2 km. Meanwhile, 65% of the MIL propagates vertically, most of which goes downward. These results show the temperature behavior properties of the lower MIL over North China, which may be helpful for us to further understand middle atmosphere chemical and dynamics processes. [ABSTRACT FROM AUTHOR]