随着我国城市化进程的快速发展,建设用地扩张引发的城市下垫面属性变化对城市热环境产生了日益严重的负面影响.以探究城市建成区平面形态与城市热环境的相关关系为研究目标,以西安市城六区为研究对象,基于Landsat遥感影像提取2002—2021年间的城市建成区边界并得出其平面形态的量化参数,同时通过地表温度反演计算出对应年份地表温度的各项指标,而后对两者进行相关性分析,结果表明地表温度最大值与建成区平面形态的面积、周长具有高显著性的相关关系,最终分别对两组数据通过曲线拟合建立数学模型并得出其具体的函数方程,为城市热环境的优化设计提供参考.

Increasing urban heat island and global warming have aroused serious thermal environmental problems and even harm people's thermal health. Because of the importance in people's daily life, a commercial pedestrianized block represents a symbol of a city or metropolis; therefore, focusing the attention on the thermal environment in such regions is very necessary. Most of the researches on the urban thermal environment are calculated by remote sensing data; limited by the low spatial resolution of remote sensing image, it may not obviously reflect the true thermal environment of the research site, especially in some microscale regions. Based on this, the new software ENVI-met is developed to research the thermal environment and forecast people's thermal sensation in a microscale region. Therefore, the objective of this study aims at conducting field measurement and numerical simulation to assess the thermal environment of a typical commercial pedestrianized space in southern China and assess the different urban design parameters in ameliorating the urban heat island effect. Our final results demonstrate a quantitative evidence for establishing a comprehensive standard for improving the thermal environment in a microscale region, and this study also can be a supplementary in the research field about improving thermal health.

Many Chinese are living in the traditional buildings, especially in rural regions. Cave dwelling settlement is a significant living residential form in China. Because of the special thermal adaptive behavior, residents in such regions will have a different thermal sensation in winter. In order to assess the local's thermal behavior, we conduct the field measurement, numerical simulation and questionnaire survey in a caving dwelling settlement in winter, and the index-PET (physiological equivalent temperature) is evaluated for assessing the outdoor thermal conditions in the research site. The final results show that the neutral temperature of local traditional dweller is 16.5 degrees C PET, lower than existing standard, also proves that local residents are more tolerant than the residents in urban regions. At last, we strongly make an appeal to put forward the different assessing standard of thermal comfort in rural and urban zone, even the two different sites are in the same climate zone, thus help to improve energy efficiency in rural regions of China.

The site selection of a logistics park is an indispensable part of its planning and construction. Conventional site-selection methods mainly focus on qualitative analysis and lack evaluation criteria for the reliability of selection results. In this study, the probability method was used to analyze the site selection and planning theory of a logistics park. By using the EM algorithm and GeNie software, a Bayesian network model was constructed to explore the internal causal and logical relationships among the influencing factors, quantify the significance of each influencing factor, and construct a scientific and reasonable logistics-park site-selection planning evaluation index system. The K-means clustering method was adopted to establish the logistics-park-location model, and MATLAB was used to iteratively calculate the established model. The gray fuzzy risk assessment model was also optimized based on the Bayesian network method. Moreover, the combination of qualitative analysis and quantitative calculation was used to obtain the corresponding location risk coefficient and evaluation risk probability, and the site-selection risk-level assessment of the logistics park was completed. The results show that the site-selection model based on the Bayesian method can fully consider the influence of city scale, economic and social development, urban logistics volume, and traffic location in the selection process; realize the quantitative evaluation of logistics-park-location results; reduce the impact of human subjective factors and objective data ambiguity on site selection; and effectively improve the site selection of logistics parks. Ten prefecture-level cities in Shaanxi Province were selected as candidate sites to verify the feasibility of the site-selection model. The site-selection risk coefficient of Xi'an logistics park was 4.030 1, which indicates a low risk level. According to the overall risk probability, the reliability of determining the low risk level was 65.50%. Thus, the results confirmed that the risk coefficient of constructing logistic parks in Xi'an is low, which is scientifically feasible. Moreover, the risk-assessment result of the Xi'an port has relatively high reliability.
© 2020, Editorial Department of China Journal of Highway and Transport. All right reserved.

在城镇及乡村建筑设计之初,气候经验与现代化样式自然成为民居建筑设计的基本依据与遵循标准,西北五省地区也不例外。调研结果显示,在西北五省地区新建与改建的乡村民居住宅中,室内居住热环境与建筑节能效果并不明显,不太符合环保节能与绿色发展的要求。因此,如何在保证经济性与热舒适性的同时,最大限度地降低建筑能耗,便成了乡村民居被动式设计策略选择上的一大问题。文中结合当地气候数据,利用Climate Consultant气候分析软件对焓湿图、当地温度与太阳辐射量进行分析对比,得出适用于当地建筑的被动式设计策略,并通过Design Builder对其进行模拟验证。结果表明,合理设置建筑窗墙比与阳光间、外围护结构传热系数参数以及增设南侧窗户遮阳,可有效降低乡村民居建筑能耗。同时针对不同被动式建筑设计策略与组合式被动式设计策略对降低建筑能耗效果的对比,为当地在改建或新建民居选择设计方案时提供参考与借鉴。

PM2.5 and PM10, could increase the risk for cardiovascular and respiratory diseases in the general public and severely limit the sustainable development in urban areas. Land use regression models are effective in predicting the spatial distribution of atmospheric pollutants, and have been widely used in many cities in Europe, North America and China. To reveal the spatial distribution characteristics of PM2.5 and PM10, in Xi'an during the heating seasons, the authors established two regression prediction models using PM2.5 and PM10, concentrations from 181 monitoring stations and 87 independent variables. The model results are as follows: for PM2.5, R-2 = 0.713 and RMSE = 8.355 mu g/m(3); for PM10, R-2 = 0.681 and RMSE = 14.842 mu g/m(3). In addition to the traditional independent variables such as area of green space and road length, the models also include the numbers of pollutant discharging enterprises, restaurants, and bus stations. The prediction results reveal the spatial distribution characteristics of PM2.5 and PM10, in the heating seasons of Xi'an. These results also indicate that the spatial distribution of pollutants is closely related to the layout of industrial land and the location of enterprises that generate air pollution emissions. Green space can mitigate pollution, and the contribution of traffic emission is less than that of industrial emission. To our knowledge, this study is the first to apply land use regression models to the Fenwei Plain, a heavily polluted area in China. It provides a scientific foundation for urban planning, land use regulation, air pollution control, and public health policy making. It also establishes a basic model for population exposure assessment, and promotes the sustainability of urban environments.

Global climate change and urban heat islands have generated heat stress in summer, which does harm to people's health. The outdoor public commercial pedestrianized zone has an important role in people's daily lives, and the utilization of this space is evaluated by their outdoor thermal comfort and health. Using microclimatic monitoring and numerical simulation in a commercial pedestrianized zone in Tai Zhou, China, this study investigates people's outdoor thermal comfort in extreme summer heat. The final results provide a comprehensive system for assessing how to improve outdoor human thermal health. Under the guidance of this system, local managers can select the most effective strategy to improve the outdoor thermal environment.

物流园区选址是其规划建设中不可或缺的部分,传统的选址方法以定性分析为主,缺乏对选址结果可靠性的评判标准,为此,引入贝叶斯概率方法开展了物流园区选址规划理论研究。借助EM算法和GeNie软件,构建了贝叶斯网络模型,挖掘出各影响因素间存在的内在因果和逻辑关系,量化各影响因素的显著性,构建科学合理的物流园区选址规划评价指标体系;采用K-means聚类方法建立了物流园区选址模型,使用MATLAB软件对建立的模型进行迭代计算,并引入贝叶斯判别方法对聚类结果进行了可靠性分析;基于贝叶斯网络方法优化了灰色模糊风险评估模型,结合了定性分析和定量计算,得出相应的选址风险系数与评估风险概率,完成了物流园区的选址风险等级评估。研究结果表明:基于贝叶斯方法建立的物流园区选址模型能够充分考虑城市规模、经济社会发展、城市物流量及交通区位等多因素的影响,实现了对物流园区选址结果的量化评价,降低了人为主观因素和客观数据的模糊性对物流园区选址方案的影响,有效提高了物流园区选址规划的科学性和可靠性。以陕西省10个地级市为候选地点验证该选址模型的可行性,结果显示:西安建设物流园区的选址风险系数为4.030 1,处于低风险水平,依据总体风险概率确定低风险水平的可靠性为65.50%,证实了在西安建设物流园区（西安港）风险系数较低,科学可行,且西安港风险评估结论具有较高的可靠性。

本文针对日本中小城市在人口老龄化、产业空间转移等因素的影响下出现的城市收缩现象,从城市生态学的角度出发,提出以可持续交通系统、可再生能源系统结合优化城市景观的生态城市设计策略,解决城市收缩问题,提出应对我国中小城市收缩现