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Review

Research Progress of Urban Wind and Thermal Environment Based on CiteSpace and China National Knowledge Infrastructure Database

by
Heng Liu
1,
Xinyu Liu
1,
Lufeng Nie
1,
Xiaochun Hong
2 and
Xiang Ji
1,3,*
1
School of Architecture and Design, China University of Mining and Technology, Xuzhou 221116, China
2
School of Building Science and Engineering, Yangzhou University, Yangzhou 225000, China
3
Jiangsu Collaborative Innovation Center for Building Energy Saving and Construction Technology, Jiangsu Vocational Institute of Architectural Technology, Xuzhou 221000, China
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(20), 13108; https://doi.org/10.3390/su142013108
Submission received: 31 August 2022 / Revised: 26 September 2022 / Accepted: 7 October 2022 / Published: 13 October 2022
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Abstract

:
The urban wind–thermal environment affects the sustainable development of the urban ecological environment. In recent years, China has frequently suffered from storms, hurricanes, floods, and other disasters that damage the urban ecology. The urban wind and thermal environment involves many components; therefore, it is necessary to systematically review the current research progress in China. This paper uses CiteSpace software to analyze researchers, institutions, keywords, and research hotspots. By summarizing the knowledge structure, temporal and spatial distribution, evolution trends, and frontiers and hotspots of urban wind and thermal environment research, it is found that (1) the urban wind and thermal environment has gradually become a research hotspot in the field of the urban ecological environment; (2) the cooperative relationship between authors generally presents the characteristics of “large dispersion, small aggregation”, and the inter-institutional cooperation in this field is close and forms part of the interdisciplinary cooperation; (3) the research content involves a variety of disciplines and provides a good platform for interdisciplinary research, and the focus of the research has gradually shifted from the macro urban layout to the micro urban local environment; and (4) in order to obtain a more targeted understanding of the mechanisms of the urban wind–thermal environment, technical methods and regulatory means should be used to study the target at different scales and levels. In the future, multidisciplinary communication should be strengthened, qualitative and quantitative research should be performed with the help of mature technical methods in various disciplines, and the scale classification of research objects should be refined to improve the theoretical methods and evaluation system of each scale.

1. Introduction

The rapid urbanization process has greatly affected the urban ecological environment, among which global warming, extreme climatic events, and other urban climate environmental factors continue to intensity, affecting the living environment of human beings [1]. The urban thermal environment and wind environment are important components of the urban environment, and they interact with each other and are closely related, so they are often considered simultaneously in related fields [2,3]. On the one hand, the urban thermal environment and wind environment interact and influence each other. The study of their coupling mechanism is conducive to better revealing the formation and change mechanism of the urban environmental climate, and then lay the foundation for urban climate control [4]. On the other hand, the urban wind–thermal environment, as a factor affecting the comfort of the urban ecological environment, is related to human safety and health. The deterioration of the urban wind–thermal environment may aggravate the urban heat island and air pollution [5,6,7], increase the energy consumption of indoor refrigeration and mechanical ventilation [8], and lead to heat-related health conditions and even death [9,10]. In addition, a good wind and heat environment can reduce building energy consumption, improve human comfort, and contribute to the physical and mental health of residents [11,12,13], so it has gradually received attention in recent years. Urban ecological environment research involves many disciplines, including atmospheric science, ecology, surveying and mapping science, resource science, environmental science, urban planning, etc., and a vast and complex research system has been formed among various disciplines. For example, the urban climate in atmospheric science, water quality, and sanitation in ecology, remote sensing detection technology in surveying and mapping science, soil conditions in resource science, surface temperature in environmental science and other factors are closely related to the urban ecological environment [14,15,16]. Although there have been a large number of research results on the urban wind and heat environment in our country, there are many differences in research purpose, significance and methods due to the different knowledge backgrounds and concerns of different researchers in different disciplines [17]. At present, there are few studies in the field of the urban wind and thermal environment using bibliometric methods. After comparing the international and national literature databases, it was found that most of the literature in the field of the urban wind and thermal environment in China is included in the China National Knowledge Infrastructure (CNKI). Therefore, based on CNKI, this paper uses the CiteSpace (Citation Space) tool and bibliometric methods to analyze and summarize the domestic research status, solidify the existing research basis, deepen the research ability, and summarize and predict the urban wind and thermal environment.

2. Data Collection and Research Methods

2.1. Data Source and Processing

In order to ensure the professionalism and completeness of the research content, journal articles in Chinese databases were selected during the literature retrieval. Firstly, an advanced search was conducted on the CNKI database to select Chinese journals with SCI and EI sources, Chinese core journals and CSSCI journals from the CNKI database. Secondly, the CNKI database was searched with the themes of “urban wind environment”, “urban thermal environment”, “urban wind and thermal environment”, “city” or containing “thermal comfort”. Furthermore, the literature retrieval period of 20 May 2002 to 20 May 2022 was selected. Finally, the selected literature was further screened accurately, and the missing information of the author and the year, news, invitations for manuscripts, popular science propaganda, interviews, conference notices, and documents not related to the theme were excluded. A total of 521 Chinese articles were retrieved, and 512 Chinese articles were excluded.
All documents are exported in Refworks format as “TXT” text, which contains data information such as author, research institution, title, publication time, abstract and keywords.

2.2. Research Tools and Methods

This study used CNKI visual data analysis and CiteSpace 5.8.R3 to conduct co-occurrence, clustering, and emergence analysis of the annual number of publications, authors, research institutions, and keywords. Different conditions (Table 1) were set to generate different knowledge graphs. Selection Criteria: Top N Per Slice, select Top 50 for each node; Pruning: The Pathfinder algorithm is selected and the Pruningsliced network is sliced.

3. Data Statistics and Visual Analysis

3.1. Analysis of the Number of Publications

The included literature was statistically analyzed according to the publication time. A total of 512 studies related to the urban wind and thermal environment were included in the CNKI database from 2002 to 2022, and the average annual number of publications was 24 (Figure 1). The highest number of articles published was 58, in 2021. From 2002 to 2022, the annual number of published articles showed an overall upward trend. In general, China has paid more and more attention to the research field of the urban wind and thermal environment, and it has experienced three stages: the formation stage (2002–2007), growth stage (2008–2013), and development stage (2014–2022). From 2002 to 2007, the number of articles published was small, and began to rise from 2008, with a small climax in 2011. However, after a small decline in 2013, it began to show a rapid development trend, and reached the peak in 2021 (58 articles).
This trend cannot be separated from our policy direction to guide urban environmental problems. In 2007, the Chinese government formulated China’s National Plan to Address Climate Change and issued China’s Special Action on Science and Technology to Address Climate Change, indicating that China began to take action against urban environmental problems. In April 2016, China was invited to sign the Paris Agreement, and the ratification by the Standing Committee of the National People’s Congress of China’s accession to the Paris Agreement on Climate Change proves the urgency of the need for action on urban climate change. In September 2020, China clearly proposed the goal of the “carbon peak” in 2030 and “carbon neutrality” in 2060, which greatly promoted the accelerated development of urban wind and thermal environment research. The following October, the Central Committee of the Communist Party of China and The State Council issued the “Opinions on the Complete, Accurate and Comprehensive Implementation of the New Development Concept to achieve peak carbon and carbon neutrality”. In the power, transportation, construction, metallurgy, chemical, petrochemical, and other sectors, efforts have been made to promote urban wind and thermal environment remediation and development. This trend is also closely related to China’s rapid economic growth. After the reform and opening up in 1978, the country actively promoted the opening policy. Coastal provinces and cities established special economic zones and economic development zones [18]. Since then, China’s GDP has skyrocketed [19]. In July 2008, in response to the international financial crisis, our country implemented the “moderately loose” economic policy to promote the sustainable development of the economy, which then intensified the speed of urbanization. There are also significant ecological effects. The structure, process, and function of the urban ecosystem are affected or changed irreversibly by the process of urbanization. The urbanization process has caused the loss of cultivated land resources, the scarcity of water resources, the pressure of energy, the serious pollution of the urban environment and the expansion of urban regional ecological occupation, as well as other resource and ecological environment problems [20]. Therefore, an increasing number of scholars have focused on urban ecological problems such as the urban wind and thermal environment.

3.2. Researchers, Research Institutions and Their Cooperation Networks

3.2.1. Distribution of Main Researchers

The analysis of 512 studies shows that the top 13 scholars have produced more than 4 papers per person (Table 2). Among these researchers, Liu Jing has published 11 related papers, and is the scholar with the largest number of publications. His papers are mostly published in core journals such as Architectural Science and the Journal of Harbin Institute of Technology. The second most published scholar is Liu Yonghong, who has published eight related papers.

3.2.2. Researcher Cooperation Network

The number of core authors in this research field was calculated, and the minimum number of publications by core authors was N = 0.749 × ηmax1/2 (η Max is the number of publications by the most productive authors) [21]. With η Max = 11, N ≈ 2 can be obtained, and there are 147 core authors, accounting for 43.36% of all authors. In order to obtain an in-depth understanding of the cooperation between different authors, this study used CiteSpace to generate the author co-occurrence knowledge graph (Figure 2), and we highlighted scholars with more than two original papers. There are 341 author nodes involved, 345 lines between authors, and the density is 0.006. As can be clearly seen from the figure, the cooperative relationship structure among the authors of different teams is generally scattered, and some of them form a network of small groups. It can be seen that the internal ties and cooperation of each research team are relatively close, represented by Liu Jing, Liu Lin, Liu Hongyong, etc. Combined with the most frequently cited journal papers listed in Table 3, 8 of the 10 most frequently cited journal papers were published by multiple scholars, which is obviously more conducive to the publication of high-level journal papers due to group cooperation. As can be seen from Table 3, frequently cited papers focus on the urban wind and thermal environment, urban form and spatial pattern, and other macroscopic scales [22,23], and take human needs as the main evaluation criteria [24,25], while relatively few studies are conducted on the medium and micro scale of streets and buildings.

3.2.3. Distribution of Research Institutions and Statistics of Published Journals

The knowledge graph of co-occurrence of institutions is shown in Figure 3. A total of 276 institutions are involved, the number of connections is 206, the density is 0.0054, and the co-occurrence frequency of institutions is 552. It can be clearly seen from Figure 3 that the State Key Laboratory of Subtropical Building Science of South China University of Technology is closely connected with other institutions, and the number of cooperations and publications is also relatively large. In addition, 11 institutions published more than seven articles (Figure 4), among which the University of Chinese Academy of Sciences published the largest number of articles (17). Eight of these institutions are universities. In addition, there are state key laboratories and research institutes within universities. Tianjin Jianzhu University presented the first research in this field in 2002. The remaining institutions studied the field from 2003 to 2016.
The selected 512 papers were ranked by their source journals to obtain the top 10 journals (Figure 5). The research fields are concentrated, mainly in urban and rural planning, surveying, and mapping science, the ecological environment, architectural science, and other disciplines. The journal with the most publications was Architectural Science (46 articles), whose main research topic was the thermal comfort of meso-level urban design. The second was the Journal of Ecology (32 articles), which mainly focuses on the interaction between urban layout form and the wind–thermal environment at the macro urban planning level.

3.3. Research Hotspots and Trend Analysis

3.3.1. Keyword Co-Occurrence Analysis

Keywords represent highly summarized and condensed research content. The higher the frequency, the more attention received by the research content that it represents. The keyword co-occurrence map of the research literature related to the urban wind and thermal environment is shown in Figure 6, which contains 303 nodes and 527 lines in total, with a cumulative frequency of 991 times and a network density of 0.0115. The number of lines is larger than the number of nodes, and the lines between keywords in the figure are intricate, indicating that the keywords are closely related [26]. Regarding keywords with frequency ≥10 and their centrality (Table 4), it can be found that in addition to the basic keywords the main keywords closely related to them include “surface temperature” (67 times), “urban heat island” (49 times), “remote sensing” (41 times), “numerical simulation” (30 times), etc. From the chart, we can observe that the research on the urban wind and heat environment is mainly focused on the urban heat island and land surface temperature. Remote sensing and numerical simulation are the main measurement and simulation methods used to study the urban wind and heat environment.
Mediation centrality refers to the mediation ability of a node to connect other nodes in the entire network graph. Nodes whose mediation centrality exceeds 0.1 are called critical nodes. The higher the centrality of the mediation, the more important the node is in the structure. The centrality of “thermal environment” is relatively large, which is 0.43, and it is the first key node in the atlas. The centrality of “thermal comfort”, “surface temperature” and “urban heat island” amounts to 0.23, 0.21, and 0.21, respectively, indicating that they second-level important nodes. It can be seen that these keywords are not only the focus of the research, but also an important medium to connect with other research topics.
As shown in Figure 6, the research on the urban wind and thermal environment in the past 20 years has covered many aspects, such as research disciplines, research objects, research questions, technical methods, and data sources, etc., and the color of the connections between highlighted keywords can reveal the main problems, main research objects, and research methods in each stage. In the formation stage (2002–2007), research on the urban wind and heat environment mainly focused on the “urban heat island”, “surface temperature” and other urban ecological aspects, and focused on the problems of the urban thermal environment and thermal comfort; measurement methods such as remote sensing are mostly used. With the help of remote sensing technology, Chen Yunhao et al. proposed the thermal landscape view for the first time to study the spatial pattern of the urban thermal environment and created an evaluation system for the spatial pattern of the thermal landscape [23]. However, the relevant literature at this stage was not rich enough and the progress was relatively slow. In the growth stage (2008–2013), especially in Beijing, Shanghai, Guangzhou, and other large cities, high-density population aggregation brought great pressure to the cities, leading to the intensification of ecological and environmental problems. Various scholars present a problem-oriented focus in the study of the urban wind–thermal environment; in addition to systematically and constantly improving the rules and regulations of the technology, more and more researchers have come to depend on these concepts. Where available, computer numerical simulation has become the main means of research, beginning in 2006, when plans to develop the national general land use planning outline to optimize the land use structure were put forward. The realization of land stock utilization led to the prominence of “urban design”, “land use”, and other keywords, and the literature at this stage began to increase gradually. In the development stage (2014–2022), the research on the urban wind and thermal environment paid more attention to and explored the wind environment; it did not only focus on the urban pattern and landscape planning itself, but also paid more attention to human comfort needs in the urban microclimate, such as single buildings, urban public spaces, and even underground space [21,22,23]. For the differentiation of the urban wind and heat environment, there is also targeted research on influencing factors and evaluation systems, coupled with the continuous innovation of information technology, and the popularization of computers. In this stage, the research on the urban wind and heat environment grew rapidly.

3.3.2. Keyword Cluster Analysis

On the basis of the keyword co-occurrence map, the LSI (Shallow Semantic index) algorithm is used for keyword clustering analysis, which can highlight research hotspots more clearly (Table 5, Figure 7). The Q value (clustering module value) = 0.6176; a Q value > 0.3 indicates a significant clustering structure; the S value (cluster average contour value) = 0.7666; an S value > 0.5 indicates that the clustering results are reasonable; and an S value > 0.7 indicates that the clustering is efficient and convincing [26]. The results indicate that the map can reflect the research hotspots in the field well. In the cluster analysis, size (capacity) > 10 indicates a good clustering effect, and silhouette (homogeneity) is greater than 0.7, so it is considered that the closeness between the members of the cluster unit is good. Therefore, a total of nine meaningful clusters were screened out in this analysis. They are #0 surface temperature, #1 numerical simulation, #2 residential district, #3 urban heat island, #4 urban street valley, #5 urban form, #6 urban green space, #7 historical district, and #8 spatial pattern. The color of each cluster area represents the year in which the most literature related to the cluster topic appeared. There are many overlapping clusters in the map, indicating that these clusters are closely related; that is, the research content is different, but the main research content is concentrated.

3.3.3. Keyword Saliency Map

By transforming the keyword co-occurrence map and detecting the emergent words (Figure 8), we can clearly find the frontiers and iterations of the research field related to the urban wind and thermal environment in recent years. In the emergent bar after the emergent word, the red color represents the active research of the emergent word in this period, among which the relatively active emergent words include Shanghai, thermal landscape, urban street valley, heat island intensity, numerical simulation, and microclimate. Among them, the most prominent keywords are not among the above keywords, but they are “vegetation index” (2.91) and “microclimate” (2.91). It can be seen that their duration is relatively long, and the microclimate has been particularly prominent in recent years.

4. Discussion

4.1. Temporal and Spatial Distribution of Studies Related to Urban Wind–Thermal Environment

From the point of view of the number of publications, its change can reflect the development status of a field and the future research trend. First, in the past 20 years, the research literature on the urban wind and thermal environment has been on the rise in CNKI. It can be seen that the number of researchers related to the urban wind and thermal environment has increased, and the attention to it has gradually increased. The urban wind and thermal environment has gradually become a research hotspot in the field of the urban ecological environment. Secondly, there are significant differences in the growth stages of the published articles in the field of the urban wind and thermal environment, which can be roughly divided into three stages: the formation stage (2002–2007), growth stage (2008–2013), and development stage (2014–2022), indicating that the research has stage characteristics, and the feedback at the practical level promotes progress at the theoretical level. Third, the amount of literature on the urban wind and heat environment started to grow rapidly after 2014, which is highly correlated with the introduction of the low-carbon energy-saving policy, indicating that this field is closely connected to the actual demands within China.
From the perspective of the literature distribution, most of the studies on the urban wind and thermal environment are published in journals in the fields of ecological and environmental science, landscape architecture, and geographical science, and the number of journal publications in the fields of architecture and urban underground space is relatively small. Tang Mingfang analyzed the climatic characteristics of the mountain environment and its influence on the urban thermal environment [27]; Liu Shuhua et al. found, through simulation, that greening can greatly reduce the urban temperature and wind speed [28], and Jiangxuedong concluded that local circulation and other influences on the thermal landscape pattern were large, based on the coastal environment characteristics of the Pearl River Delta [29]. Focusing on the Shanghai city center, six different types of urban river and water body were evaluated, and it was found that the river can effectively lower the temperature in the summer, increase humidity, and regulate the urban climate [30]. These are important characteristics of the urban wind–thermal environment, mainly concentrated in the natural environment, such as mountain lakes, with influences on urban self-factors. The research process of the urban wind–thermal environment field is not only the process of optimizing the urban physical environment, but also the process of exploring the interaction and influence between the urban building layout and form and the wind–thermal environment. The research issues cover the land surface temperature, heat island effect, and so on. Bao Ruiqing mentioned that the urban land surface temperature is closely related to the urban spatial distribution structure, and there is a great difference in the thermal environment between vegetation land and construction land [31]. Liu Jingji quantified the relationship between urban form, such as the type, height, density, and layout of building groups, and heat island intensity [32] based on local climate zoning. Feng Zhangxian quantified the influence of the interaction between the roughness of the underlying surface, building height, and the density of the regional windward surface in the urban form and urban wind environment on the land surface temperature [33]. On the other hand, his research focused on the urban spatial pattern and urban form. In regional planning, accurate assessment of the wind–thermal environment is carried out by analyzing the macro-scale wind–thermal environment conditions [34]. In architectural design, the key aspect of the wind–thermal environment influence factors, including the building surface and volume [35], as in the micro-scale building monomer and combination of the group, is the main factors of the urban spatial pattern. The architecture of the influence of the natural environment, serving as a guide for the wind to absorb heat and so on, also makes this an important factor of the urban wind–thermal environment. Therefore, distinguishing the spatial scale is more conducive to accurately proposing targeted solutions. In addition, the building form directly affects the surrounding local wind and thermal environment, which is also directly related to the human body’s wind and thermal comfort. The complex building shape and combination forms the phenomenon of aerodynamic interference between buildings prominent, and there is a high-wind-speed area at the level of pedestrians, which affects the comfort of pedestrians and even endangers their safety [36]. Therefore, it is necessary to study the wind and thermal environment at the “building scale”.
From the distribution of authors, there are 339 authors among the relevant literature, 15 of whom have published more than five articles, accounting for 15.20% of the total number of articles. The author with the highest number of articles is Liu Jing, with a total of 11 articles, showing the characteristics of “large dispersion and small aggregation”. Three large research teams represented by Liu Jing, Liu Yonghong, and Liu Binyi have been formed in this field in China. Authors are loosely distributed, and cooperation between different teams is weak. A total of 276 institutions were involved in the included literature, and 11 institutions published more than seven articles, among which the University of the Chinese Academy of Sciences published the most articles, and the School of Architecture of Tianjin University carried out the earliest research in this field. In general, the working institutions in this field are closely linked, and cross-disciplinary cooperation is formed among multiple institutions.

4.2. Research Hotspots and Frontier Analysis of Urban Wind–Thermal Environment

The research hotspots in each stage also reflect the changing trends and problems in this field. “City” and “wind and heat environment” are the key terms running through the entirety of urban environment research, which covers research under the framework of the urban environment system, involving urban planning, architecture, landscape, mountains and lakes, and other aspects of the field. After removing the search keywords, such as “thermal environment”, “wind environment”, and “thermal comfort”, the keywords can be divided into four categories for analysis according to the research elements: research object, research discipline, research question, and technology method (Table 6). From the perspective of research disciplines, the urban planning discipline was originally devoted to the study of the urban wind–thermal environment. Since 2010, the research content of the landscape architecture discipline has gradually become involved in this field. In the following years, a large number of studies have emerged, and the research topic of the urban wind–thermal environment has been extended from the city as the main body to landscape architecture. From the perspective of the research object, from the spatial pattern initially mentioned in 2002, to the urban street valley in 2007, to the urban green space in 2010, and to the urban park and landscape pattern since 2014, the research object has gradually shifted its focus from the macro urban layout to the medium- and micro-scale urban environment. From the point of view of research questions, they have shifted from the initial solar radiation and urban heat island to the urban microclimate and microclimate. Research questions, objects, methods, and fields are related to each other by scale (Figure 9). Researchers have begun to focus on the local wind and thermal environment and the climate characteristics of cities and carry out refined research on landscape design and the public space environment [37,38].
On the one hand, based on the number of publications described above, we can see that the number of publications in the first and second stages is small, but the types of keywords are very diverse, which reflects the lack of depth of research in this field by scholars in this stage. The classification of research objects in the third stage has become more detailed, especially with the development of technology and the application and popularization of computers. Regarding the research method, it can be found that the computer simulation method is mainly used to carry out quantitative data acquisition and sub-simulation analysis for more refined research objects. On the other hand, with the deepening of the research and the expansion of the research scope, it can be found that the research objects and content from the first stage to the third stage became more focused. The changing trend of high-frequency keywords reflects the more frequent research on microenvironmental problems closely related to the human body.
Four conclusions can be obtained through the above knowledge map and analysis: (1) The urban wind and thermal environment is an important part of the urban ecological environment, and the focus of the urban climate environment. The research on this topic, from multiple perspectives and fields, is conducive to alleviating urban climate and environmental problems and implementing low-carbon policies and dual-carbon goals. (2) The disciplines of atmospheric science, surveying and mapping science, resource science, environmental science, urban planning, and other fields have laid a good theoretical foundation and presented research methods to obtain rich research results, and the interdisciplinary discipline provides a new perspective for the research. (3) The study of the urban wind and thermal environment has gradually moved from the macro scale to the more specific medium and micro scale. (4) The research on the urban wind and heat environment in the past two decades has mainly adopted the design guidance of landscape, spatial pattern, and urban form to improve the urban surface temperature and urban heat island effect. (5) Many authors have combined measurement and simulation in terms of technical methods. In summary, this paper reviews the research on the urban wind and thermal environment in terms of two aspects: object-scale classification research from a multidisciplinary perspective, and thematic research including technical means and regulatory mechanisms.

4.3. Research on Object-Scale Classification from a Multidisciplinary Perspective

The research objects of urban wind and thermal environment research are characterized by spatial scale differentiation. Different disciplines and fields have different research focuses and research scales. The disciplines of meteorology, surveying and mapping, resources, and environment mainly study the surface temperature [39] and urban canopy wind [40,41] based on meteorological and remote sensing data. Planning, architecture, landscape architecture, and other disciplines pay more attention to the coupling relationship between the urban wind environment and thermal environment in terms of urban form and architectural form. Based on the existing research results, this study divided the scale of the urban wind and thermal environment as follows (Table 7). From the perspective of urban planning and architecture, the scale of the urban wind and thermal environment can be divided into three categories: macro, meso, and micro. The macro scale refers to the urban or regional scope, covering hundreds of kilometers in the urban area; the meso scale refers to the scope of blocks or buildings, covering tens of kilometers in diameter; and the micro scale refers to single buildings, city squares or green parks, covering hundreds of meters up to the present [34].

4.3.1. Macro Scale

Despite the differences in disciplinary background, the urban wind–thermal environment research in the early years studied the urban environment, urban form, spatial pattern, and other objects in view of the urban heat island effect, urban ventilation corridors, solar radiation, and urbanization, and the research in such disciplinary fields was carried out at the urban regional scale. Chen Yunhao drew upon the research methods of landscape ecology and used RS and GIS computer methods to study and establish an evaluation system of the thermal landscape spatial pattern in cities [42]. Shen Zhongjian, who has a background in environmental and resource science, analyzed the temperature data of Xiamen City from the perspective of the local climate zone and found that there was significant spatial autocorrelation between heat island intensity and land use nature, and the intensity of the heat island varied greatly with different spatial patterns [43]. With the aid of remote sensing image analysis of the urban area under the condition of different wind speeds and the function layout coupling the time and space distribution law of the urban heat island effect, and from the geographic location, spatial structure and land surface temperature, they summarized the three levels of the Tianjin heat island space–time distribution characteristics, through improving the urban air duct in the urban wind–thermal environment coupling optimization adjustment strategy [44].
In general, researchers within the fields of environmental and resource science, physical geography and mapping and meteorology study the urban wind and thermal environment at a macroscopic scale, especially with the help of remote sensing and other scientific methods. However, the comparative analysis of different scale regions, such as the spatial pattern and landscape ecology of specific regions, is relatively lacking. At the same time, the evaluation method from the multi-scale perspective has the limitation of no dissimilation.

4.3.2. Mesoscale

Meso-scale studies focus on local climate and environmental issues such as ventilation and the thermal comfort of urban buildings, urban street valleys, urban villages, and residential areas. This mainly includes research on the influencing factors of the local wind and thermal environment, the coupling relationship between spatial form and microclimate elements and research on the integration and reconstruction strategy of block spatial form under the influence of the urban macroclimate. Shi Man, by testing the surface temperature at night, found that the local heat island effect was influenced by the land cover type and human factors such as heat and construction [45]. Bao JuanJuan discussed the relationship between the thermal environment and summer outdoor thermal comfort, and the quantitative planning was summarized based on the measured index, spatial form, and detailed design of three factors, as well as the relationship with the physiological equivalent temperature [46]. Feng Wei proposed an optimization strategy to improve the quality of the wind environment of the block by studying how the spatial forms of urban blocks with high and low degrees of enclosure change the internal rules of the wind environment of the block [47]. Zeng Suoping conducted CFD simulation on 20 types of residential modules in four types of typical residential groups and analyzed the coupling relationship between ventilation efficiency and layout [48].
From the above research content, we can easily find that the disciplines of ecological environment and urban planning place a greater emphasis on meso-scale research. In addition, due to the location, layout and form of buildings, vegetation and water at this scale, the near-stratum urban wind can produce great changes, which are different from those caused by the urban canopy wind. Compared with the macro scale, research at the meso scale is more inclined to study the urban wind and then study the changes in the local thermal environment and thermal comfort.

4.3.3. Micro Scale

Micro-scale research focuses on urban green space, urban parks, and urban squares, as well as the local microclimate. Urban green space reasonably influences the urban thermal environment and can effectively improve the human body’s thermal comfort conditions [49]. Urban green space, especially green spaces situated near busy roads, is covered with various types of plants; in the inhibition of the traffic’s environmental impact (impact on microclimatic conditions, the absorption of different pollutants, reduced wind speed, etc.) green space can play an important role [50]. In addition, urban parks and green spaces can actively promote human health by restoring the environment and relieving mental stress [51]. A city square is a public space in which people’s daily activities are carried out, and effective ventilation in city squares is very important for residents’ living comfort and health [52].
In general, disciplines such as architecture and landscape pay more attention to the microclimate at the architectural scale when studying the urban wind and thermal environment. In addition, the influencing factors of the urban wind and thermal environment interact with the green space, squares, and buildings in the local scope, for example the orientation of the street, the scale of green configuration, the composition of the square and the degree of openness. Further research on the above factors can explore the weight influence and coupling relationships among driving factors affecting the local microclimate.

4.4. Thematic Research

At present, the research in the field of the urban wind and thermal environment includes atmospheric science, ecology, surveying and mapping science, resource science, environmental science, urban planning, architecture, and other disciplines, and the technical methods and regulatory mechanisms in different fields are also different. The atmospheric sciences place a greater emphasis on the construction of the theoretical basis, while the environmental sciences place a greater emphasis on the exploration and development of technology. There are frequent exchanges between them and good interdisciplinary cooperation and interaction. However, in the practical work, the former is often not understanding of practical problems; and the latter shows a lack of awareness of the wind–heat mechanism of interaction between cities. One of the largest areas contributing to national carbon emissions is the construction field, in which it is crucial to achieve energy conservation and emissions reduction; regulation of the urban wind–thermal environment wind must be considered in building design and construction, architectural design, and technology. According to Yu Chengguo, the combination of theory and technology is used to create a good urban wind and thermal environment. However, some technical means are somewhat insufficient for the cross-application of architectural disciplines, and there are certain technical barriers and academic barriers. Therefore, collaborative research involving the two levels of technical methods and theoretical mechanisms is particularly important [10].

4.4.1. Technical Means

(1)
Technical means of urban wind environment
The technical methods to study the wind environment are constantly evolving with the changes in technology. The first is the meteorological data observation method. The study of the urban wind environment requires wind condition assessment. Due to the limited technical level in the early stage, the prevailing wind direction and annual wind speed were determined only from meteorological data and wind rises. Later, with the gradual increase in the complexity of the roughness of the urban underlying surface, the alienation of thermal properties and the obvious difference between the urban wind in the near surface [53], as well as the continuous development of the meteorological discipline itself, the understanding of wind conditions obtained from the limited meteorological observation stations was improved. In particular, the observation period for the interpolation statistics of spatio-temporal high-resolution encrypted observation data offers improvements. The second is the remote sensing monitoring method. Due to the improvement of remote sensing monitoring systems, combined with the comprehensive analysis of computer GIS [54], such methods can capture the local complex and variable wind field affected by geographical location, topography, and buildings [55]. The third is the numerical simulation method, which uses CFD software to simulate the urban physical environment. In addition, there are two technical methods that have been used throughout the research process of the urban wind environment. The first is the most direct and effective field test method that can obtain first-hand actual data. Shuzo conducted long-term measurements on a high-rise building in Tokyo and its surrounding wind environment, which was used as a reference factor to evaluate the wind environment in this area [56]. The other wind tunnel test method is the most commonly used method in wind environment research. Its essence is to simulate the actual wind field by creating an actual scale model and testing the relevant data with instruments [57].
(2)
Technical means of urban thermal environment
The urban thermal environment itself is also affected by urban wind to a certain extent. In addition to some technical means of studying the wind environment, there are some other methods to solve the problems of the urban heat island, surface temperature and thermal comfort. The first is the meteorological observation method, which uses the spatio-temporal variations in meteorological station data to compare and deduce the situation of the urban heat island [58,59,60]. The second is the flow observation method, which can effectively study the local climate of the city through flow detection on different routes with an on-board temperature measurement instrument [61,62]. The third is the remote sensing inversion method. Due to the development and progress of remote sensing satellites, land use information data obtained by satellites can be used to quantitatively analyze the change characteristics and influence relationship of the land surface temperature and heat island effect [63]. The fourth is the fixed-point observation method, which uses small meteorological observation instruments to directly obtain meteorological values such as wind speed, thermal humidity, and air quality. On the one hand, it can be used to compare data differences in different regions of the city [64], and on the other hand, it can analyze meteorological changes in different periods [65] to achieve horizontal and vertical comparisons [66]. The fifth is the numerical simulation method, which adopts the Weather Research and Forecast Model (WRF) model to fit the actual observations for the macroscopic and meso scale and describes and evaluates various complex climate phenomena [67]. For the urban thermal environment at the meso–micro scale, the key research is focused on thermal comfort. Thermal environment simulation software, such as Fluent, Airpak, Phoenics, and ENVI-Met, is usually used for simulation, and measures to optimize the urban thermal environment can be discussed from a theoretical perspective [36,68]. Generally speaking, the first three methods are often used to study the urban thermal environment at the macro and meso scales. Compared with the first three methods, the fixed-point observation method has the advantage of a more direct and convenient acquisition. However, due to the limitations of manpower and equipment, the fixed-point observation method and numerical simulation method are more suitable for measuring the thermal comfort index at the micro and meso scales.
To summarize, there is a coupling effect between the wind–thermal environment and the technical methods used to study the urban thermal environment, which have a certain similarity, including meteorological observations, actual measurements and data acquisition using remote sensing technology, which ensure the authenticity and scientific research. For the computer simulation of the data sources, these methods have laid a solid foundation. The integration and development of different disciplines and various technologies constitute a set of relatively mature urban wind and thermal environment research techniques supported by meteorological observation and actual measurement, combined with computer numerical simulation and so on.

4.4.2. Regulation Mechanism

(1)
Evaluation method
To realize regulation, it is necessary to understand the formation mechanism of the urban wind–thermal environment, and the evaluation method of the urban wind–thermal environment is an important means to reveal its mechanism [69]. However, as a multi-scale concept, the research content of urban wind–thermal environment research is different at different spatial levels, and the evaluation emphasis is also different. The macro and meso-scale evaluation focuses on the urban atmosphere research of the urban heat island and canopy wind, while the mid-micro scale comprises the urban microenvironment research on thermal comfort and the microclimate. In the study of the urban atmosphere, environmental values such as air temperature, relative humidity, wind speed, wind direction, radiation, and atmospheric particles are obtained through measurement capture, remote sensing inversion, and numerical simulation to simulate the specific composition of the underlying surface of the city and quantify the objective change law of the urban wind–thermal environment [69]. A series of evaluation systems that take temperature and humidity, heat, and air quality as indicators and adapt to different wind and thermal environments are summarized. In the study of the microclimate, the coupling relationship between the underlying surface attributes, such as building layout, building form, and urban water greening, under the influence of the atmospheric environment and microclimate are more often considered. Since the impact on the human body is more direct, thermal comfort has become an important evaluation criterion. The evaluation methods include the black box model [70] and heat balance model [71].
(2)
Means of regulation
There are certain differences in the regulatory means of wind–thermal environment research at different scales, but the objective is to optimize climate indicators to meet the requirements of environmental safety and human comfort, and to determine its mechanism and influencing factors before proposing corresponding regulatory means. At the macro scale, the land use structure should be optimized [72], urban ventilation corridors should be planned and constructed [73], etc. At the micro scale, the urban building layout and form should be optimized, land cover types such as green planting water should be increased, and anthropogenic heat should be reduced. In order to strengthen the pertinence of the regulation means, we should study the target at different scales and levels.

4.5. Future Research Directions of Urban Wind–Thermal Environment

Based on the above research on the hotspots and progress of the literature related to the urban wind and thermal environment, this study believes that future research in this field should focus on the following aspects: (1) Under the medium scale, involving residential units, the city streets of the urban thermal environment are usually subjected to isolated wind assessments, and on a larger scale of urban morphology and spatial layout, there is a certain contradiction between the landscape design and construction and the selection of micro-scale improvement strategies [74], and the different scales of the urban wind–thermal environment cannot be generalized. Small- and medium-sized spatial environment changes, such as building blocks and plots, have a great impact on the urban local wind and thermal environment. In fact, the macro scale is based on the role of the small- and medium-sized wind and thermal environment, so it is necessary to conduct research on the small- and medium-sized urban wind and thermal environment. (2) There is a lack of complete knowledge and technical systems regarding how to conduct an appropriate analysis of the wind and thermal environment, how to evaluate the wind field effect and thermal comfort of the scheme for the design of plots with different regions, scales, and ground cover types and especially how to formulate optimization measures for potential problems. Thus, in a future study, it is necessary to adopt geographical spatial data, computer simulation, and questionnaire surveys, alongside measured data to determine the classification of space, geography, and scale from the city, ecological building, construction, and other different scales to obtain a complete theoretical classification model considering technology within all groups of the knowledge system targeted at various scales in an in-depth study.

5. Conclusions and Prospects

This paper systematically reviews the research trends related to the urban wind and thermal environment, explains the research hotspots, frontiers and development trends in this field, and provides a certain reference for the future direction of interdisciplinary cooperation and exchange research. The results show that (1) the research content in this field mainly focuses on the interaction between natural environments such as mountains and lakes and the urban pattern; (2) the cooperative relationships among authors in this field generally show the characteristics of “large dispersion, small aggregation”; (3) the inter-agency cooperation in this field is close and partly interdisciplinary. In addition, the urban wind and thermal environment was first studied from the perspective of urban planning. In the context of environmental science, there are many quantitative analysis processes and strong data support, but there is no systematic planning and architectural spatial form design consideration. In the future, more attention should be paid to the scale classification of research objects, the coupling of the medium- and micro-scale environment, and the multi-field and interdisciplinary application of research methods and other technologies. With the help of the existing research tools and methods of various disciplines, including quantitative analysis methods such as computer simulation, physical experiments, and data measurement, in-depth and detailed quantitative research may be carried out on the basis of the establishment of physical models in the research of architecture, landscape architecture and other related backgrounds, and the prototype and its rules can be summarized. If related tools can be used in the future to build a set of quantitative models that integrate the temporal, spatial, and climatic environments, this can better promote the coordinated development of urban and rural planning, architecture, landscape architecture, and other disciplines. In general, although the analysis and summary of this paper is relatively complete, there are some deficiencies. The literature included in this study is relatively narrow. This review only searched literature in the CNKI database, which prevented the study from covering a wider range of research. The authors will continue to supplement and improve these aspects in future research.

Author Contributions

Conceptualization, H.L. and X.J.; methodology, H.L.; software, H.L.; validation, H.L., X.L., L.N., X.H. and X.J.; formal analysis, H.L.; investigation, H.L.; resources, H.L., X.L., L.N., X.H. and X.J.; data curation, H.L.; writing—original draft preparation, H.L.; writing—review and editing, X.J., X.L., L.N. and X.H.; visualization, H.L.; supervision, X.J.; project administration, X.J.; funding acquisition, X.J. All authors have read and agreed to the published version of the manuscript.

Funding

The 2021 Special Fund of Jiangsu Collaborative Innovation Center of Building Energy Conservation and Construction Technology, grant number SJXTBS2108; multi-factor coupling mechanism and regulation method of heat and humid environment in underground atrium space of the National Natural Science Foundation of China, grant number 51778611; and the Assistance Program for Future Outstanding Talents of China University of Mining and Technology Research on the Optimal Design of Wind Environment at the Entrance and Exit of Underground Public Space—Taking Xuzhou City as an Example, grant number 2022WLJCRCZL314.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

We would like to express our gratitude to those who helped us while writing this article. Our most profound appreciation goes to Gao Wang from the China University of Mining and Technology in China, for his encouragement and inspiration.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Khan, M.A.; Tahir, A.; Khurshid, N.; Husnain, M.I.U.; Ahmed, M.; Boughanmi, H. Economic Effects of Climate Change-Induced Loss of Agricultural Production by 2050: A Case Study of Pakistan. Sustainability 2020, 12, 1216. [Google Scholar] [CrossRef] [Green Version]
  2. Zaki, S.A.; Toh, H.J.; Yakub, F.; Mohd Saudi, A.S.; Ardila-Rey, J.A.; Muhammad-Sukki, F. Effects of Roadside Trees and Road Orientation on Thermal Environment in a Tropical City. Sustainability 2020, 12, 1053. [Google Scholar] [CrossRef] [Green Version]
  3. Yang, G.; Xuan, Y.; Zhou, Z. Influence of Building Density on Outdoor Thermal Environment of Residential Area in Cities with Different Climatic Zones in China—Taking Guangzhou, Wuhan, Beijing, and Harbin as Examples. Buildings 2022, 12, 370. [Google Scholar] [CrossRef]
  4. Ru, S. Based on the Thermal Comfort of the Commercial Building Underground Atrium Research; China Mining University: Xuzhou, China, 2020. [Google Scholar]
  5. Oke, T.R. Boundary Layer Climate; Methuen: London, UK, 1987. [Google Scholar]
  6. Liu, Y.; Li, Q.; Yang, L.; Mu, K.; Zhang, M.; Liu, J. Urban heat island effects of various urban morphologies under regional climate conditions. Total Environ. 2020, 743, 140589. [Google Scholar] [CrossRef] [PubMed]
  7. Wang, Y.; Guo, Z.; Han, J. The relationship between urban heat island and air pollutants and them with influencing factors in the Yangtze River Delta, China. Ecol. Indic. 2021, 129, 107976. [Google Scholar] [CrossRef]
  8. Santamouris, M. On the energy impact of urban heat island and global warming on buildings. Energy Build. 2014, 82, 100–113. [Google Scholar] [CrossRef]
  9. Wong, L.P.; Alias, H.; Aghamohammadi, N.; Aghazadeh, S.; Sulaiman, N.M.N. Urban heat island experience, control measures and health impact: A survey among working community in the city of Kuala Lumpur. Sustain. Cities Soc. 2017, 35, 660–668. [Google Scholar] [CrossRef]
  10. Taylor, J.; Wilkinson, P.; Davies, M.; Armstrong, B.; Chalabi, Z.; Mavrogianni, A.; Symonds, P.; Oikonomou, E.; Bohnenstengel, S.I. Mapping the effects of urban heat island, housing, and age on excess heat-related mortality in London. Urban Clim. 2015, 14, 517–528. [Google Scholar] [CrossRef]
  11. Chen, F. Building Wind Environment: Research on Wind Environment in Hot Summer and Cold Winter Climate Zone and Design of Building Energy Conservation; China Architecture and Building Press: Beijing, China, 2009. [Google Scholar]
  12. Wang, Y.; Qian, C. Analysis on the influence of building wind environment on human comfort. Urban Archit. 2019, 16, 115–116. [Google Scholar]
  13. Guan, B.; Ma, G. Architectural Design and Wind Environment. Archit. J. 1995, 11, 44–48. [Google Scholar]
  14. Yanos, M.H. Analysis of Rainfall Variability in the Province of Quirino. J. Environ. Sci. Econ. 2022, 1, 44–50. [Google Scholar] [CrossRef]
  15. Adebanjo, S.A.; Morufu Adeoye, O. Transparency and Global Initiatives in the Face of Natural Resource Depletion in Sub-Saharan Africa. J. Environ. Sci. Econ. 2022, 1, 13–24. [Google Scholar] [CrossRef]
  16. Aidonojie, P.; Idahosa, M.E.; Agbale, O.P.; Oyedeji, A.I. The Environmental Conservation, Legal and Ethical Issues Concerning Herbal Products in Nigeria. J. Environ. Sci. Econ. 2022, 1, 26–32. [Google Scholar] [CrossRef]
  17. Zhongnan, Y.E. Review and prospect of urban wind environment research in China. Planner 2015, 31 (Suppl. S1), 236–241. [Google Scholar]
  18. Huang, J.; Wu, M.; Bao, Q. Special economic zone, Contract system and Comparative advantage. Manag. World 2013, 11, 28–38. [Google Scholar] [CrossRef]
  19. Pesce, M.; Tamai, I.; Guo, D.; Critto, A.; Brombal, D.; Wang, X.; Cheng, H.; Marcomini, A. Circular Economy in China: Translating Principles into Practice. Sustainability 2020, 12, 832. [Google Scholar] [CrossRef] [Green Version]
  20. Li, S.; Zhao, Z.; Wang, Y. The process of urbanization and its mechanism of resource and eco-environment effect in China. Prog. Geogr. 2009, 28, 63–70. [Google Scholar]
  21. Qiu, J. Measurement and Evaluation; Wuhan University Press: Wuhan, China, 2020. [Google Scholar]
  22. Ding, W.; Hu, Y.; Dou, P. Study on the correlation between urban morphology and urban microclimate. Archit. J. 2012, 7, 16–21. [Google Scholar]
  23. Chen, Y.; Li, X.; Shi, P.; He, C. Spatial pattern analysis of urban thermal environment in Shanghai. Geogr. Sci. 2002, 3, 317–323. [Google Scholar]
  24. Tong, H.; Liu, H.; Sang, J.; Hu, F. The Effect of Urban Anthropogenic Heat on the Thermal Environment of Beijing. Clim. Environ. Res. 2004, 3, 409–421. [Google Scholar]
  25. Liu, B.; Mei, W.; Kuang, W. Analysis on the relationship between spatial microclimate elements and population behavior in landscape architecture in Shanghai urban residential area. Chin. Gard. 2016, 32, 5–9. [Google Scholar]
  26. Chen, Y.; Chen, C.; Hu, Z. Principles and Applications of Citation Spatial Analysis: A Practical Guide to CiteSpace; Science Press: Beijing, China, 2014. [Google Scholar]
  27. Tang, M.; Wang, D.; Zheng, K. Mountain Urban Greening and Thermal Environment. J. Chongqing Jianzhu Univ. 2006, 2, 1–3. [Google Scholar]
  28. Fan, L.; Liu, S.; Liu, H.; Sang, J. The effect of green belt on urban atmospheric environment and air quality. Clim. Environ. Res. 2006, 1, 85–93. [Google Scholar]
  29. Jiang, X.; Xia, B. Spatial pattern dynamics of thermal environment in urban agglomerations in the Pearl River Delta. Acta Ecol. Sin. 2007, 4, 1461–1470. [Google Scholar]
  30. Yang, K.; Tang, M.; Liu, Y.; Wu, A.; Fan, Q. Analysis of microclimate effects around rivers and water bodies in downtown Shanghai. J. East China Norm. Univ. (Nat. Sci. Ed.) 2004, 3, 105–114. [Google Scholar]
  31. Bao, R. The Relationship between Surface Temperature and Urban Spatial Distribution Structure and Its Prediction Model. Chin. Gard. 2020, 36, 69–74. [Google Scholar]
  32. Liu, J.; Shen, L.; Huang, Y.; Deng, X. Spatial differentiation characteristics of nocturnal heat island intensity in Beijing based on local climate zoning. Geogr. Geoinformatics Sci. 2020, 36, 39–45, 64. [Google Scholar]
  33. Feng, Z.; Wang, S.; Jin, S.; Yang, J. Effects of urban morphology and wind environment on surface temperature in Changchun. Acta Geogr. Sin. 2019, 74, 902–911. [Google Scholar]
  34. Zeng, Z.; Ren, Y. Research on urban wind environment based on three spatial scales. Urban Dev. Res. 2017, 24, 35–42. [Google Scholar]
  35. Fan, Y.; Zhong, H.; He, Y.; Cui, G.; Zhang, Q. Research on building hierarchy renewal strategy of existing settlements from the perspective of improving the quality of outdoor thermal environment. Archit. J. 2022, 2, 46–51. [Google Scholar]
  36. Hu, X.; Gu, K.; Geng, S.; Wei, D. Simulation of Thermal Environment and Thermal Comfort of Human Body Based on ENVI-met Software: A Case Study of Green Roof of Anhui Academy of Construction Sciences. Environ. Occup. Med. 2021, 38, 694–700. [Google Scholar]
  37. Han, G.; Wang, Y.; Cheng, X. Dynamic Evaluation Method of Landscape Perception Effect in Urban Park:Based on The Superposition of Landscape Vision and Thermal Comfort. Chin. Gard. 2021, 37, 38–43. [Google Scholar]
  38. Jin, Y.; Jin, H.; Kang, J.; Wong, N.H. Experimental study on thermal environment and thermal comfort in public space in urban settlements in severe cold areas. Build. Sci. 2021, 37, 29–37. [Google Scholar]
  39. Zhang, X.; Zhao, Y.; Ma, F.; Liu, N.; Zhang, Y.; Chu, X.; Wu, W. Analysis of urban park cooling effect on urban thermal environment in Yinchuan City based on remote sensing data. Bull. Soil Water Conserv. 2021, 41, 338–347. [Google Scholar]
  40. Bao, J.; Huang, Q.; Zhang, A.; Zhang, X. Study on Outdoor Thermal comfort of former Concession blocks in Tianjin in summer. South. Archit. 2021, 5, 108–118. [Google Scholar]
  41. Shen, Z.; Zeng, J. Spatial relationship between heat island intensity and related surface factors in Xiamen. Geogr. Sci. 2020, 40, 842–852. [Google Scholar]
  42. Feng, W.; Fei, M.; Zhen, M.; Feng, S. Numerical simulation of wind environment and urban optimization design strategy of typical neighborhood in Xi’an. Mod. Urban Res. 2019, 8, 35–40. [Google Scholar]
  43. Zeng, S.; Tian, J.; Zeng, J. Coupling Optimization Method of Wind and Heat Environment in Tianjin Central Urban Area from the Perspective of Low Carbon and Low Heat. Planner 2019, 35, 32–39. [Google Scholar]
  44. Zeng, S.; Tian, J.; Zeng, J. Study on ventilation efficiency and optimal layout of typical settlement modules based on CFD simulation. Archit. J. 2019, 2, 24–30. [Google Scholar]
  45. Shi, M.; Chen, J.; Wu, D.; Qin, B.; Li, S. Remote sensing monitoring and analysis of surface thermal environment at urban block scale. Infrared Technol. 2019, 41, 84–91. [Google Scholar]
  46. Xiang, W.; An, J.; Wang, X.; Wang, Z. Parametric method of urban canopy wind profile in atmospheric emergency response simulation. Clim. Environ. Res. 2013, 18, 187–194. [Google Scholar]
  47. Xin, J.; He, Q.; Wei, H.; Liu, D.; Zhou, G.; Yang, H.; Shao, D. Observation and study on vertical variation of boundary stratigraphic wind above Shanghai World Expo Park. Plateau Meteorol. 2009, 28, 127–135. [Google Scholar]
  48. Chen, Y.; Shi, P.; Li, X. Research on Urban Spatial Thermal Environment in Shanghai Based on Remote Sensing and GIS. J. Geomat. 2002, 2, 139–144. [Google Scholar]
  49. Reza, J.; Nazanin, N. Urban green space and health: The role of thermal comfort on the health benefits from the urban green space; a review study. Build. Environ. 2021, 202, 108039. [Google Scholar]
  50. Stojanovic, N.; Tesic, M.; Petrovic, J. The effect of roadside green spaces on wind speed reduction in the urban environment. Fresenius Environ. Bull. 2021, 29, 10465–10473. [Google Scholar]
  51. Wang, S. Mechanism of Perceived Restorative Impact of Xuzhou City Park under the Background of Epidemic[J/OL]. Southern Architecture:1–9. Available online: http://kns.cnki.net/kcms/detail/44.1263.tu.20220518.1954.002.html (accessed on 18 July 2022).
  52. Wei, Y.; Wowo, D. Effects of urban square entry layouts on spatial ventilation under different surrounding building conditions. Build. Simul. 2021, 14, 377–390. [Google Scholar]
  53. Xing, P.; Fang, X.; Zhang, N.; Cheng, C.; Wang, X.; Liu, Y.; Du, W.; Yang, R.; Dang, B. Construction and application of urban near-ground high-resolution fast wind field model. Meteorology 2019, 45, 978–988. [Google Scholar]
  54. Wang, W.; Li, F.; Wang, W.; Wang, Q. Construction of urban air duct based on quantitative analysis of ventilation potential and wind characteristics. J. Zhejiang Univ. (Eng. Sci.) 2019, 53, 470–481. [Google Scholar]
  55. Fang, X.; Li, L.; Liu, W.; Ren, C.; Wang, J.; Cheng, C.; Yu, Y.; Zhang, S.; Du, W.; Liu, Y. Research and practice progress of urban ventilation corridors in China. J. Ecol. 2021, 40, 4088–4098. [Google Scholar]
  56. Shuzo, M.; Yaushige, M. Study on acceptable criteria for assessing wind environment at ground level based on residents’ diaries. J. Wind. Eng. Ind. Aerodyn. 1986, 24, 1–18. [Google Scholar]
  57. Du, G. Numerical Simulation Study of Wind Environment in Several Typical Layouts of Residential Areas; Hunan University: Changsha, China, 2009. [Google Scholar]
  58. He, P.; Li, H. Analysis of heat island effect in small and medium-sized cities on Yunnan-Guizhou Plateau. Meteorol. Sci. Technol. 2002, 5, 288–291. [Google Scholar]
  59. Ji, L.; Li, Q.; Zhang, S.; Ma, J.; Wang, Z.; Chen, X.; Si, Y.; Ran, J. Effects of urbanization process on temperature change in the suburbs of Beibei, Chongqing. Meteorol. Sci. Technol. 2015, 43, 320–325. [Google Scholar]
  60. Zhang, W.; Wu, S.; Hao, L.; Wang, Q.; Hu, L. Characteristic analysis of the change characteristics of Xi’an urban heat island effect. Shaanxi Meteorol. 2019, 1, 18–21. [Google Scholar]
  61. Liu, J.; Lin, X.; Liu, Y.; Sun, Z. Research on urban heat island in Xi’an winter. J. Sol. Energy 2007, 8, 912–917. [Google Scholar]
  62. Wang, Z.; Lu, J.; Yang, K. Study on summer heat island effect in Huayan New Town, Chongqing. J. Sol. Energy 2012, 33, 953–957. [Google Scholar]
  63. Liu, D.; Liu, J.; Jiang, H. Spatio-temporal variation of heat island effect in Harbin Based on Landsat image. Surv. Mapp. Spat. Geogr. Inf. 2020, 43, 5–7, 13. [Google Scholar]
  64. He, Y.; Zhang, Y.; Liu, Y.; Ma, Y.; Li, Y.; Dou, J.; Guo, P. Spatial distribution characteristics of urban climate level in Kunming. Geogr. Sci. 2002, 6, 724–729. [Google Scholar]
  65. Zhang, Y.; He, Y.; Ma, Y.; Liu, Y.; Li, Y.; Dou, J.; Guo, P. Three-dimensional distribution characteristics of urban heat island effect in Kunming. Plateau Meteorol. 2002, 6, 604–609. [Google Scholar]
  66. Li, G.; Zhang, J.; Cheng, H.; Zhao, L.; Tian, H. Urban heat island effect under the background of global warming and urbanization. Adv. Meteorol. Sci. Technol. 2012, 2, 45–49. [Google Scholar]
  67. Miao, G.; Zhang, L.; Shu, H. Numerical simulation of the winter atmospheric boundary layer of Lanzhou using WRF. Meteorol. Sci. 2007, 2, 169–175. [Google Scholar]
  68. Lu, L.; Yang, X. Urban Renewal Research Based on ENVI-met Software Microclimate Simulation and Thermal Comfort Experience: A Case Study of North Xin’an Area of Shijingshan Mountain, Beijing. Urban Dev. Res. 2018, 25, 147–152. [Google Scholar]
  69. Sun, T.; Xiao, R.; Cai, Y.; Wang, Y.; Wu, C. Research progress and development trend of quantitative evaluation technology of urban thermal environment. Chin. J. Appl. Ecol. 2016, 27, 2717–2728. [Google Scholar]
  70. Yaglou, C.P.; Minard, D. Control of heat casualties at military training centers. Am. Med. Assoc. Arch. Ind. Health 1957, 16, 302–316. [Google Scholar]
  71. Wang, H.; Hu, S. Analysis on applicability of PMV thermal comfort model. Build. Sci. 2009, 25, 108–114. [Google Scholar]
  72. Yue, W.; Xu, L. Study on the Thermal Environment Effects of Urban Land Use Types and Patterns: A Case Study of Downtown Shanghai. Sci. Geogr. 2007, 2, 243–248. [Google Scholar]
  73. Xue, W. On the construction strategy of ventilation corridor in urban center. Ind. Archit. 2021, 51, 257. [Google Scholar]
  74. Du, S.; Zhang, X.; Jin, X.; Zhou, X.; Shi, X. A review of multi-scale modelling, assessment, and improvement methods of the urban thermal and wind environment. Build. Environ. 2022, 213, 108860. [Google Scholar] [CrossRef]
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Figure 1. Publication time distribution of literature related to urban wind–thermal environment in China.
Figure 1. Publication time distribution of literature related to urban wind–thermal environment in China.
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Figure 2. Author co-occurrence knowledge graph.
Figure 2. Author co-occurrence knowledge graph.
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Figure 3. Knowledge graph of institutional co-occurrence.
Figure 3. Knowledge graph of institutional co-occurrence.
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Figure 4. Distribution of main research institutions related to urban wind and thermal environment.
Figure 4. Distribution of main research institutions related to urban wind and thermal environment.
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Figure 5. Main sources of research papers on urban wind–thermal environment.
Figure 5. Main sources of research papers on urban wind–thermal environment.
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Figure 6. Keyword co-occurrence knowledge graph.
Figure 6. Keyword co-occurrence knowledge graph.
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Figure 7. Keyword clustering knowledge graph.
Figure 7. Keyword clustering knowledge graph.
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Figure 8. Keyword salience knowledge graph.
Figure 8. Keyword salience knowledge graph.
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Figure 9. Content–scale relationship of urban wind–thermal environment research.
Figure 9. Content–scale relationship of urban wind–thermal environment research.
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Table
Table 1. CiteSpace conditions.
Table 1. CiteSpace conditions.
Time PartitionThe Node Type
20 May 2002–20 May 2022
(Slice every two years for a time)		The author
Research institutions
Keywords
Table
Table 2. Distribution of authors related to urban wind–thermal environment.
Table 2. Distribution of authors related to urban wind–thermal environment.
RankScholarsNumber of Papers (Papers)The Year of the First OccurrenceComposition Ratio (%)
1Jing Liu1120062.15%
2Hong-yong Liu720111.37%
3Bin-yi Liu720081.37%
4Yong-wei Wang620161.17%
5Lin Liu620081.17%
6Jun Yang620141.17%
7Jian Zeng520060.98%
8Qing-lin Meng520070.98%
9Li-hua Zhao520140.98%
10Zhi-Feng Wu520060.98%
11Jia-Ping Liu520190.98%
12Hong Jin520020.98%
13George520090.98%
14Yun-hao Chen520190.98%
Table
Table 3. Frequently cited journal papers on urban wind–thermal environment.
Table 3. Frequently cited journal papers on urban wind–thermal environment.
NumberAuthorPaper TitleNumber of Citations
1Wen-ze Yue, etc.Study on ecological environment effect of urban land use based on remote sensing image328
2Wo-wo Ding, etc.The relationship between urban form and urban microclimate303
3Yun-hao Chen, etc.Spatial pattern analysis of urban thermal environment in Shanghai243
4Ren Chao, etc.Study on urban ventilation corridor and its planning and application230
5Tong Hua, etc.Effects of anthropogenic heat on thermal environment in Beijing194
6Han-qiu XuAnalysis of urban heat island effect based on changes of urban land surface parameters172
7Yun-hao Chen, etc.Study on urban spatial thermal environment of Shanghai based on remote sensing and GIS165
8Wen-ze Yue, etc.Study on the thermal environmental effects of urban land use types and patterns: A case study of downtown Shanghai142
9Jing-yuan Zhao, etc.Numerical Simulation of urban street Valley thermal environment and planning and design countermeasures135
10Bin-yi Liu, etc.Analysis on the relationship between spatial microclimate elements and crowd behavior of residential landscape gardens in Shanghai128
Table
Table 4. The centrality and frequency of keywords related to urban wind–thermal environment.
Table 4. The centrality and frequency of keywords related to urban wind–thermal environment.
NumberKeywordCentralityCo-Occurrence FrequencyNumberKeywordCentralityCo-Occurrence Frequency
1Thermal environment0.438610Landscape pattern0.0516
2The surface temperature0.216711Urban planning0.0816
3Urban heat island0.214912Microclimate0.0816
4Remote sensing0.144113Urban green space0.0712
5The numerical simulation0.083014Urban form0.0511
6Heat island effect0.132815Land utilization0.0610
7The wind environment0.152516Impervious surface0.0210
8Thermal comfort0.232417Urban design0.0610
9Landscape architecture0.022218Urbanization0.0310
Table
Table 5. Keyword clustering information table.
Table 5. Keyword clustering information table.
NumberKeywordCentralityCo-Occurrence FrequencyNumberKeywordCentralityCo-Occurrence Frequency
1Thermal environment0.438610Landscape pattern0.0516
2The surface temperature0.216711Urban planning0.0816
3Urban heat island0.214912Microclimate0.0816
4Remote sensing0.144113Urban green space0.0712
5The numerical simulation0.083014Urban form0.0511
6Heat island effect0.132815Land utilization0.0610
7The wind environment0.152516Impervious surface0.0210
8Thermal comfort0.232417Urban design0.0610
9Landscape architecture0.022218Urbanization0.0310
Table
Table 6. Research hotspots in each stage.
Table 6. Research hotspots in each stage.
StageThe Year of the First OccurrenceResearch SubjectResearch ObjectResearch QuestionMethods
The First Stage2002—Spatial patternSolar radiationRemote sensing
2003Urban planningUrban designResidential district—Numerical modeling
2004—Urban environmentUrban heat island—
2005———CFD
2006—Surface temperatureLand utilization—
2007—Urban street canyon——
The Second Stage2008—Underlying surfaceHeat island effect
Microclimate		—
2010Landscape architectureUrban green spaceUrbanization—
2011—Impervious surfaceHeat island intensity—
2012—Urban form——
The Third Stage2013 Urban villages——
2014—City parkLandscape patternUrban climate—
2016———Simulation
2017——Microclimate—
Table
Table 7. Study scale division of urban wind–thermal environment.
Table 7. Study scale division of urban wind–thermal environment.
PerspectiveMacro ScaleMeso ScaleMicro Scale
Other Disciplinary PerspectivesVerticalContentUrban boundary layerUrban canopy layerBlocks of layer
Sustainability 14 13108 i001Sustainability 14 13108 i002
HorizontalRegional scaleMesoscaleMicro scale
The extent of a city or regionThe extent of a block or buildingSingle building, city square or park green space
Architectural Planning PerspectiveRangeThe diameter covers hundreds of kilometersThe diameter covers tens of kilometersThe diameter covers several hundred meters
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Liu, H.; Liu, X.; Nie, L.; Hong, X.; Ji, X. Research Progress of Urban Wind and Thermal Environment Based on CiteSpace and China National Knowledge Infrastructure Database. Sustainability 2022, 14, 13108. https://doi.org/10.3390/su142013108

AMA Style

Liu H, Liu X, Nie L, Hong X, Ji X. Research Progress of Urban Wind and Thermal Environment Based on CiteSpace and China National Knowledge Infrastructure Database. Sustainability. 2022; 14(20):13108. https://doi.org/10.3390/su142013108

Chicago/Turabian Style

Liu, Heng, Xinyu Liu, Lufeng Nie, Xiaochun Hong, and Xiang Ji. 2022. "Research Progress of Urban Wind and Thermal Environment Based on CiteSpace and China National Knowledge Infrastructure Database" Sustainability 14, no. 20: 13108. https://doi.org/10.3390/su142013108

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