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Under the condition of urban rail transit uncertainty of passenger demand and the high frequency of departure intervals, this study presents an innovative real-time urban rail transit (URT) train service scheduling control framework. In the context of a bidirectional urban rail transit line, a high-fidelity urban rail transit simulation environment was constructed. Within this environment, an advantage actor–critic (A2C) reinforcement learning approach was utilized to train a suitable strategy aimed at minimizing both passenger waiting costs and transit authority operational expenses. Subject to specific constraints, the strategy is designed to generate real-time train schedule based on the representation of traffic state using station congestion levels and train positions. Experimental results on Lines 3 and S7 of Nanjing Metro demonstrated the agent's effectiveness in achieving high-performance schedules across various scenarios. This research integrates deep reinforcement learning into the optimization of dynamic traffic systems, showing great potential for enhancing the efficiency and resilience of urban transport systems. [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]

Aims/Introduction: The triglyceride‐glucose (TyG) index is a simple and reliable indicator of insulin resistance, and is associated with the development and poor outcomes of cardiovascular disease. Subclinical left ventricular dysfunction (SLVD) is frequently detected in approximately one‐third of diabetes patients, but it has not been established whether the TyG index correlates with SLVD. We carried out this research to evaluate the relationship between the TyG index and SLVD in type 2 diabetes mellitus patients. Materials and Methods: This was a cross‐sectional and observational study of 183 type 2 diabetes mellitus inpatients at Nanjing Drum Tower Hospital, Nanjing, China. The TyG index and homeostasis model assessment 2 estimates for insulin resistance (HOMA2‐IR) were calculated from biochemical measurements, and speckle‐tracking echocardiography was carried out. According to global longitudinal strain (GLS) by echocardiography, participants were categorized into the SLVD (GLS <18%) group or the non‐SLVD (GLS ≥18%) group. Results: In comparison with non‐SLVD participants, SLVD participants had higher insulin resistance, as reflected by elevated TyG and HOMA2‐IR indices, as well as a higher body mass index, waist circumference and triglyceride level (P < 0.05 for each). When grouped by TyG index tertiles, an elevated TyG index was correlated with other cardiometabolic risk factors, as well as a decrease in GLS. In the multivariate logistic regression analyses, the TyG index was an independent risk factor for SLVD in type 2 diabetes mellitus patients (odds ratio 2.047, 95% confidence interval 1.07–3.914, P = 0.03), whereas HOMA2‐IR was not. Conclusions: The TyG index is independently associated with SLVD in type 2 diabetes mellitus patients and is a more reliable indicator of SLVD than HOMA2‐IR. [ABSTRACT FROM AUTHOR]

Objectives: To examine the association between health literacy (HL) and health-related quality of life (HRQoL) among primary and high school students in Nanjing, China.Methods: A cross-sectional study was conducted among randomly selected primary (graders 4-6), junior (graders 7-9) and senior (graders 10-12) high school students in 2018 in Nanjing Municipality of China. HRQoL, the outcome variable, was assessed with the validated Chinese version of Child Health Utility 9D (CHU9D) and used as continuous variable, while HL, our independent variable, was measured with the validated Chinese Students' Health literacy Assessment Scale and treated as categorical variable ("adequate" or "inadequate") in the analysis. Mixed-effects linear regression models were introduced to calculate mean difference and 95% confidence interval (CI) for examining the association between HL and HRQoL.Results: Totally, 4388 of 4498 students completed the survey. Among these responders, the mean score of CHU9D was 0.78 ± 0.17, and the proportion of participants with adequate HL was 85.8% (95% CI = 84.7%, 86.8%). After adjustment for potential confounders and class-level clustering effects, participants who had adequate HL were observed having, on average, an elevated HRQoL score of 0.08 (95% CI = 0.06, 0.11) units compared to their counterparts with inadequate HL. Such a positive HL-HRQoL association was also identified among each stratum of participants' age, gender and residence.Conclusions: HL was positively associated with HRQoL score among primary and high school students in China. It has public health implications that HRQoL may be improved through school-based health literacy intervention among children and adolescents in China. [ABSTRACT FROM AUTHOR]

As one of the effective ways to study urban climate and environmental problems, the performance of numerical model could be improved in urban areas by enhancing the description of urban morphology. One of the largest challenges faced by researchers is the lack of real urban canopy parameters (UCPs) to represent urban morphological characteristics. In this study, the urban morphological parameters were estimated and a high‐resolution urban morphological parameter data set for the main cities in China was developed. The results show that the distribution of urban morphological parameters is of regional characteristics and cities in China are mainly dominated by low‐rise buildings. Chinese cities can be broadly divided into two types based on the probability distribution of building height: single‐peak and double‐peak. The number of low‐rise buildings in single‐peak cities is much larger than that of double‐peak cities, which contributes to the difference between the two types of cities. The equivalent street width of northern cities in China is higher than that of southern cities, and the equivalent building width is almost the same. However, the default UCPs of the Weather Research and Forecasting (WRF) model distort the morphology of Chinese cities. The sensitivity of the WRF model to urban morphological parameters was also investigated in Nanjing. Overall, our results indicate that urban morphological parameters have a significant influence on the energy balance process in cities and improve the performance of the WRF model in simulating the air temperature and canopy wind speed. Plain Language Summary: The urban morphological parameters are important for simulation in urban areas using numerical models. In this study, we develop a data set of the urban morphological parameters for the main cities in China. The regional characteristics of urban morphological parameters in China are summarized, and we find that Chinese cities can be divided into two types: single‐peak cities and double‐peak cities. The sensitivity of the urban canopy parameterization schemes of Weather Research and Forecasting (WRF) to the new data set is also investigated. The urban morphological parameters can significantly improve the performance of WRF in simulations of wind speed and temperature in urban areas compared with the default values in WRF. Key Points: A data set of the urban morphological parameters for the main cities in China is developedThe regional characteristics of urban morphological parameters in China are summarizedThe urban morphological parameters can improve the performance of Weather Research and Forecasting in simulations in urban areas compared with the default values [ABSTRACT FROM AUTHOR]

Urban heat islands (UHIs) are caused by a multitude of changes induced by urbanization. However, the relative importance of biophysical and atmospheric factors in controlling the UHI intensity remains elusive. In this study, we quantify the magnitude of surface UHIs (SUHIs), or surface urban cool islands (SUCIs), and elucidate their biophysical and atmospheric drivers on the basis of observational data collected from one urban site and two rural grassland sites in and near the city of Nanjing, China. Results show that during the daytime a strong SUCI effect is observed when the short grassland site is used as the reference site whereas a moderate SUHI effect is observed when the tall grassland is used as the reference site. We find that the former is mostly caused by the lower aerodynamic resistance for convective heat transfer at the urban site and the latter is primarily caused by the higher surface resistance for evapotranspiration at the urban site. At night, SUHIs are observed when either the short or the tall grassland site is used as the reference site and are predominantly caused by the stronger release of heat storage at the urban site. In general, the magnitude of SUHI is much weaker, and even becomes SUCI during daytime, with the short grassland site being the reference site because of its larger aerodynamic resistance. The study highlights that the magnitude of SUHIs and SUCIs is mostly controlled by urban–rural differences of biophysical factors, with urban–rural differences of atmospheric conditions playing a minor role. [ABSTRACT FROM AUTHOR]

This study aims to estimate travel behaviors by dividing individual travelers into several groups based on their personal characteristics. The individual grouping was achieved using the cluster analysis with the aid of the statistical analysis system (SAS) software. The trips to the central business district (CBD) in Nanjing City of China were taken as a case study. Two travel mode choices were investigated: the transit (bus and metro) and car. Travelers’ personal information and travel information were collected through a reveal preference (RP) survey and a stated preference (SP) survey. The personal information include gender, occupation, income, and car ownership, while the travel information include the mode choice, walking time, waiting time, in-vehicle time, fare, comfort, etc. There were 524 valid respondents in the RP/SP survey. These 524 individuals were categorized into three groups using cluster analysis based on their personal information. It was found that people from the three groups had very different characteristics, indicating the cluster analysis worked well. In addition, six travel scenarios were designed for each respondent to ask their travel mode choice. Then, the travel mode choices were estimated using a discrete choice model and compared with the mode choices in the RP/SP survey for each group. It was found that the accuracy rate of the mode choice estimation using individual grouping were remarkably higher than that without grouping, indicating that the individual grouping improved the travel behavior estimation. [ABSTRACT FROM AUTHOR]

This study aims to estimate dynamics in mode choice decisions at different traffic states and transit congestion levels. Specifically, dynamics were examined over time of explanatory variables such as in-vehicle time and comfort of transit. The trips to the central business district (CBD) in Nanjing City of China were taken as a case study. Three travel modes were investigated: bus, metro, and car. Travelers’ socioeconomic characteristics and alternative specific attributes were collected through a reveal preference (RP) survey. A multinomial logit (MNL) model was proposed using RP Data1 from the questionnaire survey. It was found that in-vehicle time of cars and buses varied with traffic states. In addition, congestion level was divided by passengers per carriage to obtain the comfort of transit. Then, the mode choice decisions at different traffic states or congestion levels were estimated using a MNL model to analyze the dynamics. MNL analysis on the mode choice decisions revealed that those who own cars prefer auto trips. The income influence was also confirmed that individuals with high income prefer driving. The predicted mode choice decisions were compared with the actual choices to evaluate the model. Some possible reasons were explored to examine the mispredictions. Last, a comparison among different departure time with reference to their utilities of choosing modes revealed that traffic state and congestion level of transit took a significant effect on mode choice decisions. The proposed model had important implications to study travel behavior to improve the service of transit although some limitations in the model, such as only one mode determining rule, one transportation environment. The result of this prediction, however, can be viewed along with the results of other studies to obtain a development of dynamic travel behavior. [ABSTRACT FROM AUTHOR]

An offline single-layer urban canopy model (SLUCM) was driven by the surface energy balance observations in winter in Nanjing, China, to evaluate the capability of the model to simulate the urban surface energy balance. The results of the evaluation suggest that the simulated daytime net radiation is approximately 20% lower than the observed and display relatively high systematic error, which is due to the relatively poor capacity of the model to simulate the daytime longwave radiation (which is underestimated by approximately 35%). By contrast, the simulated sensible heat flux shows mainly unsystematic error. Moreover, the one-at-a-time method is used to conduct a sensitivity analysis of the model parameters. The sensitivity analysis demonstrates that the major factors affecting the surface energy balance are the albedo, the thermal conductivity, and the roof and wall volumetric heat capacity. The influences of the shape of the street canyon and the average height of buildings are relatively weaker. The effects of the albedo on the fluxes are nearly linear. The effects of the thermal parameters are approximately logarithmic. Furthermore, the simulated sensible heat flux in the SLUCM is insensitive to the morphological parameters of the buildings. [ABSTRACT FROM AUTHOR]

Building-integrated photovoltaic (BIPV) windows are an effective way to increase distributed PV capacity in the urban environment. However, the effects of BIPV windows on an annual scale have not been rigorously studied. In this study, we compared their performances with different window-to-wall ratios, canyon aspect ratios, and orientations in three Chinese cities. Our results show that in Beijing, BIPV windows with the southward orientation have the highest potential for power generation of 44.7 kWh/(m2·yr), which is 1.5 times the potential in Shenzhen and Nanjing. Compared to clear windows, BIPV windows are advantageous when the window coverage is greater than 50 % in a shallow canyon. The highest electricity saving ratios are found in Beijing (29.7 %), followed by Shenzhen (26.3 %) and Nanjing (23.3 %). However, the electricity saving ratio decreases by over 10 % in deep canyons. Under future climate forcing, the saving potential of BIPV windows increases slightly in Nanjing and remain stable in Shenzhen and Beijing. The study also found that BIPV windows could increase canyon air temperatures by over 0.2 °C during winter days but slightly cool the canyon in summer. The findings guide BIPV application in the built environment and cast light on the construction of low-carbon neighbourhoods. • BIPV windows generate 1.5 times more power in Beijing than in Shenzhen and Nanjing. • Highest electricity savings in studied neighbourhoods: 26.3% SZ, 23.3% NJ, 29.7% BJ. • BIPV windows slightly improve the outdoor thermal comfort in street canyons. • BIPV windows are energy-efficient for glass curtain walls with high solar access. • Energy saving potential remain stable or slightly increases by 2050s. [ABSTRACT FROM AUTHOR]

With global warming and rapid urban growth, cities get warmer, which poses additional stress on human thermal comfort and health. Complex three-dimensional (3D) urban forms change radiation fluxes and shade patterns in cities, but most studies that link urban form to thermal exposure have traditionally investigated the horizontal, two-dimensional composition and configuration of urban landscapes. Supported by high-precision airborne LiDAR data and IKONOS satellite data, this study calculates 3D urban landscape metrics for central Nanjing, China, including vegetation above ground biomass (AGB), building volume (V B), standard deviation of building and vegetation heights (HSD B , HSD V), the building normalized compactness radio (nCR), sky view factor (SVF), surface roughness (SR), and shadow patterns (SP). Diurnal hourly mean radiant temperature (T mrt) is simulated using the UMEP (Urban Multi-scale Environmental Predictor) tool forced with fixed-point observation data for a typical hot summer day. Correlation and multiple regression analyses are conducted to investigate the relationship between the 3D form metrics and T mrt and to identify key factors that influence the thermal environment. T mrt varies spatially and diurnally and is strongly related to SP during the day, revealing the importance of solar access for modulating the thermal environment. AGB is negatively, but SVF, SP , and building nCR are positively correlated with daytime T mrt. At night, T mrt is more homogeneous across space and mainly impacted by the urban fabric's ability to lose heat. Open areas cool faster than areas with low SVF and complex urban forms with high building nCR. Findings from this study have great scientific and practical significance for optimizing urban landscape patterns from a human-centered heat exposure perspective and will guide planning and design strategies to promote thermally comfortable urban environments. • 3-Dimensional urban landscape pattern metrics were derived from Lidar Point Clouds. • Mean radiant temperature was simulated using meteorological observations as forcing. • Above ground biomass is negatively correlated with daytime mean radiant temperature. • Sky View Factor, shadow patterns, building compactness are positively correlated. • Open areas cool faster at night than dense, complex urban forms. [ABSTRACT FROM AUTHOR]