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Characteristics, Progress and Trends of Urban Microclimate Research: A Systematic Literature Review and Bibliometric Analysis

Characteristics, Progress and Trends of Urban Microclimate Research: A Systematic Literature... buildings Review Characteristics, Progress and Trends of Urban Microclimate Research: A Systematic Literature Review and Bibliometric Analysis 1 1 1 , 2 , Yichen Zhou , Na An and Jiawei Yao * College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China; 1954034@tongji.edu.cn (Y.Z.); anna2010255@tongji.edu.cn (N.A.) Key Laboratory of Spatial Intelligent Planning Technology, Ministry of Natural Resources, Shanghai 200092, China * Correspondence: jiawei.yao@tongji.edu.cn; Tel.: +86-138-1651-5004 Abstract: Climate change has been a hot topic in recent years. However, the urban microclimate is more valuable for research because it directly affects people’s living environments and can be adjusted by technological means to enhance the resilience of cities in the face of climate change and disasters. This paper analyses the literature distribution characteristics, development stages, and research trends of urban microclimate research based on the literature on “urban microclimate” collected in the Web of Science core database since 1990, using CiteSpace and VOSviewer bibliometric software. It is found that the literature distribution of the urban microclimate is characterized by continuous growth, is interdisciplinary, and can be divided into four stages: nascent exploration, model quantification, diversified development and ecological synergy. Based on the knowledge mapping analysis of keyword clustering, annual overlap, and keyword highlighting, it can be predicted that the research on foreign urban land patch development has three hot trends—multi-scale modelling, multi-factor impact, and multi-policy guidance. The study’s findings help recognize the literature distribution characteristics and evolutionary lineage of urban microclimate research and provide suggestions for Citation: Zhou, Y.; An, N.; Yao, J. Characteristics, Progress and Trends future urban microclimate research. of Urban Microclimate Research: A Systematic Literature Review and Keywords: bibliometrics; citespace; development stages; distribution characteristics; research trends; Bibliometric Analysis. Buildings 2022, urban microclimate; vosviewer 12, 877. https://doi.org/10.3390/ buildings12070877 Academic Editors: Baojie He, 1. Introduction Ayyoob Sharifi, Chi Feng and Jun Yang Climate risks have and will continue to affect national security, economic security, human health, infrastructure, and ecosystem stability [1]. The Global Risks Report 2022, Received: 13 May 2022 published by the World Economic Forum, lists climate change as one of the ten most press- Accepted: 20 June 2022 ing global risks [2]. The United Nations Intergovernmental Panel on Climate Change (IPCC) Published: 22 June 2022 Sixth Assessment Report, Climate Change 2022: Impacts, Adaptation and Vulnerability, Publisher’s Note: MDPI stays neutral states that humanity is pushing the limits of climate carrying capacity and points to the with regard to jurisdictional claims in urgency of climate transition in the next decade [3]. Therefore, urban climate research is of published maps and institutional affil- great importance for healthy urban development. iations. The study of urban climate began in 1818 with Lake Howard’s “The Climate of Lon- don”, which first identified the temperature difference between urban and rural areas, i.e., the urban heat island effect, and studied the factors influencing the city’s climate [4]. Most current research on urban climate change focuses on macro-scale climate change patterns Copyright: © 2022 by the authors. such as national scales and climate zones, while climate research on the complex and Licensee MDPI, Basel, Switzerland. variable near-surface micro spaces has a later origin and slightly less research. Compared This article is an open access article with macro climate change, urban microclimate has a more direct impact on people’s living distributed under the terms and environments. People can regulate the urban microclimate through technical means and conditions of the Creative Commons then enhance the self-recovery ability of cities in the face of climate change and disasters, Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ and if we enlarge the concept of resilient cities, the concept of microclimate becomes more 4.0/). critical [5,6]. Buildings 2022, 12, 877. https://doi.org/10.3390/buildings12070877 https://www.mdpi.com/journal/buildings Buildings 2022, 12, 877 2 of 17 The research plan uses WOS, the largest Database of English documents, as the raw material and combines the advantages of Citespace and VosViewer for visualization and clustering analysis. Compared with traditional bibliometric methods, the visual analysis of scientific knowledge graphs is more intuitive and readable [7]. Urban microclimate originated in 1947 [8], and 2131 articles were searched in the Web of Science database under TS = (urban microclimate) OR TS = (city microclimate). The language of the literature was limited to English, the type of literature was limited to articles, and the search date was 4 May 2022. Searched with (TS = (urban microclimate) OR TS = (city microclimate)) AND TS = (review) AND ALL = (citespace), the type of literature was Article, the language was English, the result was 0, and the search time was 9 April 2022. There are 51 reviews, and no citespace based search studies are available. Most current microclimate studies focus on the quantification of microclimates [9], such as the calculation of thermal comfort equations [10], meteorological data moni- toring [11], computer simulations [12], and subjective thermal environment question- naires [13,14]. The concept of urban microclimate first referred to the influence of some climatic factors in the ground boundary layer by local features [10] and then also shifted to focus on urban scale differences [15], urban climate characteristics [16], and urban environmental elements [17]. Although there are some review studies on urban microcli- mate research, previous studies are mostly clustered analyses, and we have not yet seen time series-based development stage classification and multi-method research hotspot prediction [6]. 2. Data and Methods This paper adopts data analysis, software measurement, and scientific mapping meth- ods to understand further the evolutionary characteristics and hot issues of urban microcli- mate research. It uses visual analysis of CiteSpace and VOSviewer bibliometric analysis software to conduct scientific knowledge mapping analysis of urban microclimate literature to clarify potential knowledge connections among the literature [18]. A science mapping can highlight potentially significant patterns, trends, and theories of scientific change that can guide the exploration and interpretation of visual, intellectual structures and dynamic patterns [19]. Compared to other mapping software, CiteSpace and VOSviewer have a higher frequency of use and broader dissemination as commonly used bibliometric map- ping software [20]. CiteSpace can detect and visualize emerging trends and radical changes in scientific disciplines over time [21]. VOSviewer is a bibliometric analysis software jointly developed by Leiden University scholars Nees Jan van Eck and Ludo Waltman for drawing knowledge maps. It can be used for co-word, co-citation, and literature coupling analysis. It can display research results visually and has unique advantages in clustering technology and map displays [22]. Compared to Scopus, Google Scholar and PubMed, Web of Science is the world’s largest and most comprehensive scholarly information resource covering a wide range of disciplines, including the most influential core academic journals in various research fields such as natural sciences, engineering and technology, and biomedicine. Therefore, this paper uses the Web of Science core collection (hereafter referred to as WOS) as the data source, and the search period was 9 April 2022, with a years limit of 1990–2022. The search mode of “subject” + “document type” was used, and the search terms were: TS = (urban microclimate) OR TS = (city microclimate), and the document language was limited to “English”, the type was restricted to “articles” to ensure the scientific validity and accuracy of the research, and a total of 2070 relevant documents were obtained. Centrality metrics provide a computational method for finding pivotal points be- tween different specialties or tipping points in an evolving network [23]. It measures the percentage of the number of shortest paths in a network to which a given node belongs. Nodes with high-betweenness centrality tend to be found in paths connecting different clusters. This feature has been used in community-finding algorithms to identify and separate clusters [24]. Higher strength refers to a sharp increase in the number of term occurrences in this period, which is the frontier of research in this phase [23]. Kleinberg’s Buildings 2022, 12, x FOR PEER REVIEW 3 of 18 Buildings 2022, 12, x FOR PEER REVIEW 3 of 18 clusters. This feature has been used in community-finding algorithms to identify and sep- clusters. This feature has been used in community-finding algorithms to identify and sep- Buildings 2022, 12, 877 3 of 17 arate clusters [24]. Higher strength refers to a sharp increase in the number of term occur- arate clusters [24]. Higher strength refers to a sharp increase in the number of term occur- rences in this period, which is the frontier of research in this phase [23]. Kleinberg’s (2002) rences in this period, which is the frontier of research in this phase [23]. Kleinberg’s (2002) burst-detection algorithm can be adapted for detecting sharp increases of interest in a spe- burst-detection algorithm can be adapted for detecting sharp increases of interest in a spe- (2002) burst-detection algorithm can be adapted for detecting sharp increases of interest cialty [25]. In CiteSpace, a current research front is identified based on such burst terms cialty [25]. In CiteSpace, a current research front is identified based on such burst terms in a specialty [25]. In CiteSpace, a current research front is identified based on such burst extracted from keywords [23]. extracted from keywords [23]. terms extracted from keywords [23]. 3. Results 3. Results 3. Results 3.1. Current Status of Urban Microclimate Research 3.1. Current Status of Urban Microclimate Research 3.1. Current Status of Urban Microclimate Research 3.1.1. Research Scale and Impact Analysis 3.1.1. Research Scale and Impact Analysis 3.1.1. Research Scale and Impact Analysis The number of publications in this field has increased (Figure 1). The number of an- The The number number of of publ publications ications in in this thisfi field eld has hasincre increased ased (F (Figur igure e 1). The number 1). The number of an- of nual publications before 2005 was small (basically less than 10 publications per year), and annual nual pu publications blications bebef fore 20 ore 05 2005 wa was s smsmall all (bas (basically ically less less than 1 than 0 p 10 ub publications lications per ye perar) year), , and urban microclimate research was still in the exploration stage; from 2000 to the present, and urban mic urban micr roclim oclimate ate rese resear arch was s ch wastistill ll inin the ex the explor ploraa tion s tion stage; tage; fr from om 20 2000 00 to to the the p prr esent, esent, the number of publications has shown an exponential increase, and urban microclimate the number of publications has shown an exponential increase, and urban microclimate the number of publications has shown an exponential increase, and urban microclimate research has received significant attention since the 21st century and has become one of research has received significant attention since the 21st century and has become one of the research has received significant attention since the 21st century and has become one of the current research hot topics. As of 9 April 2022, 49 articles have been published, and current research hot topics. As of 9 April 2022, 49 articles have been published, and the the current research hot topics. As of 9 April 2022, 49 articles have been published, and the number of articles is expected to climb in 2022. number of articles is expected to climb in 2022. the number of articles is expected to climb in 2022. Figure 1. Number of published articles on urban microclimate. Figure 1. Number of published articles on urban microclimate. Figure 1. Number of published articles on urban microclimate. 3.1.2. Interdisciplinary and Publication Analysis 3.1.2. Interdisciplinary and Publication Analysis 3.1.2. Interdisciplinary and Publication Analysis In terms of disciplinary distribution, urban microclimate research is mainly concen- In terms of disciplinary distribution, urban microclimate research is mainly concen- In terms of disciplinary distribution, urban microclimate research is mainly concen- trated in Environmental Science (13.24%) and Construction Building Technology trated in Environmental Science (13.24%) and Construction Building Technology (11.04%), trated in Environmental Science (13.24%) and Construction Building Technology (11.04%), reflecting the multidisciplinary and comprehensive nature of urban microcli- reflecting the multidisciplinary and comprehensive nature of urban microclimate research (11.04%), reflecting the multidisciplinary and comprehensive nature of urban microcli- mate research (Figure 2). (Figure 2). mate research (Figure 2). Disciplines Disciplines Environmental Sciences 13.24% Construction Building Technology 11.04% Environmental Sciences 13.24% Energy Fuels 7.93% Construction Building Technology 11.04% Engineering Civil 7.61% Energy Fuels 7.93% Green Sustainable Science Technology 6.76% Engineering Civil 7.61% Meteorology Atmospheric Sciences 6.54% Green Sustainable Science Technology 6.76% Environmental Studies 6.10% Meteorology Atmospheric Sciences 6.54% Engineering Environmental 4.73% Environmental Studies 6.10% Urban Studies 3.95% Engineering Environmental 4.73% Ecology 2.88% Urban Studies 3.95% 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 14.00% Ecology 2.88% Percentage 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 14.00% Percentage Figure 2. Percentage of urban microclimate papers by discipline (top 10). Buildings 2022, 12, x FOR PEER REVIEW 4 of 18 Figure 2. Percentage of urban microclimate papers by discipline (top 10). Buildings 2022, 12, x FOR PEER REVIEW 4 of 18 Regarding source publications, there are 527, with Building and Environment and Sus- Buildings 2022, 12, 877 4 of 17 tainable Cities and Society posting the most articles, accounting for 8.72% and 6.58%, respec- Figure 2. Percentage of urban microclimate papers by discipline (top 10). tively. The top 10 publications focused on urban and architectural research and environ- mental sustainability (Figure 3). Regarding source publications, there are 527, with Building and Environment and Regarding source publications, there are 527, with Building and Environment and Sus- Sustainable Cities and Society posting the most articles, accounting for 8.72% and 6.58%, tainable Cities and Society posting the most articles, accounting for 8.72% and 6.58%, respec- Publications respectively. The top 10 publications focused on urban and architectural research and tively. The top 10 publications focused on urban and architectural research and environ- BUILDING AND ENVIRONMENT 8.72% environmental sustainability (Figure 3). mental sustainability (Figure 3). SUSTAINABLE CITIES AND SOCIETY 6.58% Publications ENERGY AND BUILDINGS 5.68% SUSTAIN B A U BI ILD LIT IN YG AND ENVIRONMENT 5.64% 8.72% SUSTAINABLE CITIES AND SOCIETY 6.58% URBAN CLIMATE 3.51% ENERGY AND BUILDINGS 5.68% URBAN FORESTRY URBAN GREENING 3.13% SUSTAINABILITY 5.64% INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2.46% 3.51% URBAN CLIMATE SCIENCE OF THE TOTAL ENVIRONMENT 1.89% URBAN FORESTRY URBAN GREENING 3.13% LANDSCAPE AND URBAN PLANNING 1.89% INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2.46% ATMOSPHERE 1.89% SCIENCE OF THE TOTAL ENVIRONMENT 1.89% 0.00% 1.00% 2.00% 3.00% 4.00% 5.00% 6.00% 7.00% 8.00% 9.00% 10.00% Percentage LANDSCAPE AND URBAN PLANNING 1.89% ATMOSPHERE 1.89% Figure 3. Percentage of urban microclimate papers published in journals (top 10). 0.00% 1.00% 2.00% 3.00% 4.00% 5.00% 6.00% 7.00% 8.00% 9.00% 10.00% Percentage Figure 3. Percentage of urban microclimate papers published in journals (top 10). 3.1.3. Country Di Figure 3. stribPerce ution ntag Ana e of u lys ris ban m icroclimate papers published in journals (top 10). 3.1.3. Country Distribution Analysis National time zonal mapping helps us find the most worthy references and to further 3.1.3. Country Distribution Analysis National time zonal mapping helps us find the most worthy references and to further select and classify the literature. In terms of the number of publications (radius size) (Fig- National time zonal mapping helps us find the most worthy references and to further select and classify the literature. In terms of the number of publications (radius size) ure 4), China has the highest number of articles (430) in country distribution, followed by select and classify the literature. In terms of the number of publications (radius size) (Fig- (Figure 4), China has the highest number of articles (430) in country distribution, followed the United States (359). The U.S. (1991) was the first to study urban microclimate, while ure 4), China has the highest number of articles (430) in country distribution, followed by by the United States (359). The U.S. (1991) was the first to study urban microclimate, China did not start until 2005. Centrality measures the importance of a node in the net- the United States (359). The U.S. (1991) was the first to study urban microclimate, while while China did not start until 2005. Centrality measures the importance of a node in work; a more critical node means a higher centrality, indicating that the country has pub- China did not start until 2005. Centrality measures the importance of a node in the net- the network; a more critical node means a higher centrality, indicating that the country lished more citations and is more influential in the period. In terms of centrality (more work; a more critical node means a higher centrality, indicating that the country has pub- has published more citations and is more influential in the period. In terms of centrality circles or colors), France (0.46) is much higher than other countries, followed by the U.S. lished more citations and is more influential in the period. In terms of centrality (more (more circles or colors), France (0.46) is much higher than other countries, followed by the circles or colors), France (0.46) is much higher than other countries, followed by the U.S. (0.41) and Canada (0.33). Although China started later, the number of publications has U.S. (0.41) and Canada (0.33). Although China started later, the number of publications (0.41) and Canada (0.33). Although China started later, the number of publications has shown explo has shown explosive sive grow grth, probably because owth, probably because the urb the urban an microclimat microclimate e issue issue has bee has been n gradu- shown explosive growth, probably because the urban microclimate issue has been gradu- ally no gradually ticed d noticed ue to due the h to the ighhigh-speed -speed urburban an development. development. ally noticed due to the high-speed urban development. Figure 4. National time zonal mapping for urban microclimate studies. Figure 4. National time zonal mapping for urban microclimate studies. Figure 4. National time zonal mapping for urban microclimate studies. Buildings 2022, 12, x FOR PEER REVIEW 5 of 18 Buildings 2022, 12, 877 5 of 17 3.2. Development Stages of Urban Microclimate Research 3.2. Development Stages of Urban Microclimate Research CiteSpace’s keyword clustering analysis, centrality, and emergent detection can iden- CiteSpace’s keyword clustering analysis, centrality, and emergent detection can iden- tify research frontiers to predict research trends. Using CiteSpace to map keyword time tify research frontiers to predict research trends. Using CiteSpace to map keyword time regions and temporal partitioning of highly cited literature can help analyze the evolu- regions and temporal partitioning of highly cited literature can help analyze the evolu- tionary path of research hotspots. Combined with co-citation analysis, it can help identify tionary path of research hotspots. Combined with co-citation analysis, it can help identify turning points in research and critical literature in each period [19]. turning points in research and critical literature in each period [19]. This paper uses CiteSpace to analyze the time-zoned mapping of urban microclimate This paper uses CiteSpace to analyze the time-zoned mapping of urban microclimate research literature (Figure 5) and divides the research into four stages; the main research research literature (Figure 5) and divides the research into four stages; the main research progress and characteristics are reviewed in stages. There are numerous urban microcli- progress and characteristics are reviewed in stages. There are numerous urban microclimate mate research hotspots (Table 1), and their research hotspots have apparent characteristics research hotspots (Table 1), and their research hotspots have apparent characteristics of the of the times and are significantly influenced by the social context and policy focus. For times and are significantly influenced by the social context and policy focus. For example, example, the fourth Conference of the Parties to the United Nations Framework Conven- the fourth Conference of the Parties to the United Nations Framework Convention on tion on Climate Change was held in 1998, and the Paris Agreement was signed and for- Climate Change was held in 1998, and the Paris Agreement was signed and formally mally implemented in 2016, which may serve as additional factors for phase division. implemented in 2016, which may serve as additional factors for phase division. Figure 5. Temporal partition mapping of urban microclimate research keywords. Figure 5. Temporal partition mapping of urban microclimate research keywords. Table 1. A burst of high-frequency keywords in urban microclimate research. Table 1. A burst of high-frequency keywords in urban microclimate research. Phase Year Frequency Keyword Burst Phase Year Frequency Keyword Burst 1993 419 Temperature 8.29 1993 419 Temperature 8.29 1993 308 Heat island 1993 308 Heat island 1990–1997 1993 219 Model 1990–1997 1993 219 Model 1996 294 Vegetation 1996 294 Vegetation 1997 46 Albedo 1997 46 Albedo 1998 282 Environment 4.03 1998 282 Environment 4.03 1998 167 Performance 1998 167 Performance 1999 62 Pattern 2000 62 Land use 7.58 1998–2005 1999 62 Pattern 2001 331 Thermal comfort 1998–2005 2000 62 Land use 7.58 2003 69 land surface temperature 2001 331 Thermal comfort 2005 136 Hot 2003 69 land surface temperature 2005 136 Hot 2006–2015 2006 231 Outdoor thermal comfort Buildings 2022, 12, 877 6 of 17 Table 1. Cont. Phase Year Frequency Keyword Burst 2006 231 Outdoor thermal comfort 2006 124 Urbanization 3.19 2007 127 Energy 2007 126 ENVI-met 2009 63 Green space 2011 126 Mitigation 2006–2015 2011 102 Street canyon 2014 51 Strategy 2015 75 Mean radiant temperature 2014 87 Expansion 2014 58 Urban Expansion 2016 55 Green infrastructure 3.50 2016 51 Ecosystem service 2016 to date 2017 45 Ventilation 2018 30 Mitigation strategy 2019 23 Aspect ratio 4.16 Higher burst refers to a sharp increase in the number of term occurrences in this period, which is the frontier of research in this phase [21]. 3.2.1. The Nascent Exploratory Phase (1990–1997): The Rise of Multidisciplinary and Urban Studies High-frequency keywords of early studies include temperature, heat island, and vegetation (Table 1), indicating that urban microclimate studies have mainly focused on multidisciplinary integrated studies and correlation analysis of urban constituents. However, the identification of the framework and connotation of microclimate composition has not yet emerged. Regarding multidisciplinary synthesis: Graves et al. used microclimate as one of the temperature indicator factors in the high root zone to study the effect of high-temperature zones on plant seedlings [22]. Gorbushina et al. used microclimate variability as an observ- able indicator of the biological activity of black fungi to study its role in morphology [26]. Regarding urban climate factors, Akbari et al. studied the feasibility of vegetation and high albedo materials in modifying the urban microclimate [27]. They found that increasing the vegetation cover by 30% with 20% albedo in dwellings in areas such as Toronto and Vancouver could reduce energy consumption by about 10% to 20%. Nichol conducted a microclimate study of the tropical city of Singapore for microclimate monitoring studies of high-rise housing and found a high correlation between satellite heat sensing data and biomass indices, with high similarity to actual temperatures [28]. In general, the literature published at this stage is small, and the attention of the academic community is low, mainly focusing on multidisciplinary microclimate aux- iliary research and microclimate research in small areas within cities (e.g., indoor en- vironments such as houses). The exploration of urban microclimate research systems has not yet emerged, which can be regarded as the nascent exploratory phase of urban microclimate research. 3.2.2. Model Quantification Phase (1998–2005): Application of Numerical Quantification and Model Evaluation The high-frequency keywords in this phase include environment, climate, and thermal comfort (Table 1), with environmental emergence at 4.03 and land use at 7.58, which were research hotspots. This stage mainly focuses on the research of urban microclimate model quantification. A typical representative is an ENVI-met model, simulation software developed by Bruse et al. to study surface–plant–air interactions in urban environments, which has become the most widely used tool in microclimate studies [29]. The research in this phase focuses on exploring urban microclimate perturbations, their influencing effects, and model construction. Buildings 2022, 12, 877 7 of 17 The research focuses on numerical assessment studies at the macro level on the one hand and studies the influence relationship with microclimate from different means and factors. Carlson et al. used satellite image data to obtain microclimate variables such as surface temperature, vegetation rate, ISA, and E.T, and used Chester County as an example to construct regression analysis models and predict future parameter changes [30]. Adolphe studied the relationship between urban building form and urban microclimate and used environmental form evaluation indicators to construct a simplified urban spatial model [31]. On the other hand, factors such as human perception are incorporated into micro- climate model construction. Matzarakis et al. proposed the physiologically equivalent temperature (PET), considering the correlation with human thermal–physiological percep- tion [32]. Steemers used microclimate as a research object to invert the energy consumption of buildings with different densities and analyze the urban morphology correlation, em- phasizing the value of outdoor comfort research [33]. Dimoudi et al. attempted to quantify the effect of vegetation on microclimate in urban environments and found that increased vegetation had a significant effect on temperature reduction [34]. de La Flor et al. proposed an “urban canyon” computational model that considers human thermal fitness to improve the urban microclimate and save the thermal performance of buildings [35]. At this stage, the number of publications on urban microclimate started to increase, and the academic community’s attention grew. The microclimate research process is complete with numerical modelling methods, but the coupling of microclimate with other factors is still unclear about the value of microclimate volume. 3.2.3. Diversified Development Phase (2006–2015): System Maturity and Expansion of Research Breadth Urban substratum changes bring a harsh climate environment, increased anthro- pogenic heat emission, and the spread of pollution from urban activities [36]. This stage of urban microclimate pays attention to urban heat islands, thermal comfort and other climate change mitigation studies based on the previous stage, where the high-frequency words include outdoor thermal comfort, urbanization and energy. From the total citations of the literature, this stage of research mainly focuses on urban planning or design, urban microclimate, and outdoor thermal comfort and gradually focuses on the actual measurement and testing of outdoor thermal comfort from the PET theory proposed in the previous stage, and combines quantitative findings to guide urban design. Subsequently, the research scope is further expanded, and the research object is no longer limited to a single model or a specific landscape, a disciplinary and social extension of the previous stage that only focused on microclimate-related factors. In terms of macro-simulation and micro-perception, Ali-Toudert et al. studied the effect of urban street aspect ratio and orientation on urban microclimates, evaluated the effect of PET on the climate of urban streets, and found that the street with south–north orientation and aspect ratio 2 had a better thermal environment compared with other combinations [37]. Yu, C et al. explored the effect of green space on microclimate regulation, selected two parks in Singapore as examples, conducted simulation verification with TAS and ENVI-MET, and found that green space could reduce the built environment temperature by 1.3 C and cooling load by 10% [38]. The RUROS project conducted by Nikolopoulou et al., which collected subjective human perception questionnaires from five European countries, concluded that urban microclimate is closely related to thermal comfort and that temperature and solar radiation are two essential factors influencing thermal comfort [16]. Harlan et al. used a model to estimate the summertime U.S. outdoor human thermal comfort index (HTCI) [39]. They found that community microclimate temperature has a strong negative relationship with HTCI and that lower socio-economic status and minority groups in residential areas with weak coping are more vulnerable to the adverse effects of the microclimate. Buildings 2022, 12, 877 8 of 17 In terms of the influence of urban design elements on the thermal environment, Huang et al. took Nanjing as an example and calculated the cooling effect of four urban ground cover types, which showed a cooling effect of 0.2 ~ 2.9 C for all urban blue-green spaces compared to bare concrete surfaces [40]. Shashua-Bar et al., also focusing on outdoor landscape cooling strategies in dry heat regions, selected six cooling combinations of trees, lawns, or shade nets and found that the cooling effect of grasses was most significant when they were in the shade of trees or shaded by shade nets [41]. Santamouris et al. analyzed the effect of reflective street pavement on microclimate and concluded that reflective pavement reduced ambient summer temperatures by up to 1.9 C and park surface temperatures by up to 12 C [42]. Kong et al. studied the relationship between urban cold island effects (UCIs) and microclimate in Nanjing green parks, where a 10% increase in vegetation area reduced surface temperatures by approximately 0.83 C [43]. Techniques and factors for microclimate studies have also been gradually expanded. Popular et al. used CFD simulations to predict the meteorology of the city of Rotterdam, including wind flow and heat transfer by conduction, convection and radiation and con- firmed that the average deviation between simulated and experimental data was 7.9%, confirming the potential of CFD to predict urban microclimate accurately [44]. The influ- ence of individual humans on the microclimate has also been considered. Bocker et al. were the first to systematically include behavioral activities considering thermal comfort to study the influence of climate on daily human behavior and critical activities such as walking and cycling [45]. They found that climate has a profound effect on travel. The number of publications in this period showed rapid growth compared with the previous period (Figure 1), and the number of co-cited literature increased significantly compared with the previous period (Figure 5). Microclimate-related research and meth- ods gradually matured and focused on the coupling research between microclimate and other objects, expanding the value volume of microclimate, providing in-depth theoretical support, mature technical methods, and high application value research directions. 3.2.4. Eco-Synergy Phase (2016 to Date): Focus on Eco-Synergy with Multiple Types of Elements This phase focuses on urban microclimate research under interdisciplinary and multi- perspectives, and the main keywords are green infrastructure, ecosystem services, and ventilation. In addition to the wide application of new technologies and models, the relationship between urban landscape and ecology is given unprecedented attention, and the focus is on the social benefits of the urban microclimate and the innovation of research applications. Among urban landscape benefit studies, Livesley et al. investigated the cooling benefits of urban forests on the local microclimate, including air quality, improved water quality, and biochemical cycling [46]. Wang et al. found significant effects of direct sunlight hours and mean radiation temperature on urban thermal comfort, using urban settlements in Toronto as an example [15]. Berardi simulated the impact of green roof retrofitting on an outdoor microclimate in the context of high settlement density, confirming the potential of green roofs as an urban heat island mitigation strategy [47]. Salata et al. used a university campus in Rome as an example to study different mitigation strategies for urban microclimate change. In contrast, an appropriate combination of cold roofs, urban vegetation and cold pavement can result in mean and maximum reductions of 2.5 and 3.5 in MOCI (Mediterranean Outdoor Comfort Index) [48]. Among climate adaptation benefits, Gunawardena et al. analyzed the impact of urban blue-green spaces on urban climate, and both were able to significantly mitigate the thermal effects of cities and enhance climate adaptation [49]. Among the applications, Shamshiri et al. deeply integrated microclimate with the agricultural sector to build advanced microclimate control and energy optimization models [50]. Cureau et al. focused on microclimate at the hyperlocal scale (refers to higher spatial resolution situations, usually on the meter scale) and monitored microclimate indicators from a human perspective in all aspects and multiple domains [28]. Buildings 2022, 12, x FOR PEER REVIEW 9 of 18 hyperlocal scale (refers to higher spatial resolution situations, usually on the meter scale) Buildings 2022, 12, 877 9 of 17 and monitored microclimate indicators from a human perspective in all aspects and mul- tiple domains [28]. Building types are also considered in the urban content; Yang et al. investigated the thermal microclimate of two building types, residential and office, and Building types are also considered in the urban content; Yang et al. investigated the thermal found that office buildings are less sensitive to thermal pressure [51]. It is concluded that microclimate of two building types, residential and office, and found that office buildings the spatial and temporal variability of the urban heat island effect at the local scale can are less sensitive to thermal pressure [51]. It is concluded that the spatial and temporal have different effects on building energy efficiency. variability of the urban heat island effect at the local scale can have different effects on The urban microclimate continued to develop rapidly during this period, and its re- building energy efficiency. search scope and methods were further expanded. Research results continued to increase, The urban microclimate continued to develop rapidly during this period, and its with research on elements, scale and development strategies of urban microclimate, research scope and methods were further expanded. Research results continued to in- closely following ecological issues, and more in-depth interdisciplinary directions gradu- crease, with research on elements, scale and development strategies of urban microclimate, ally emerged, forming a diversified research direction. closely following ecological issues, and more in-depth interdisciplinary directions gradually emerged, forming a diversified research direction. 4. Hot Spots and Trends in Urban Microclimate Research 4.1. Distribution of Research Hotspots Based on Keyword Clustering 4. Hot Spots and Trends in Urban Microclimate Research 4.1. Distribution of Research Hotspots Based on Keyword Clustering Word frequency analysis of literature keywords is commonly used in bibliometrics to reveal the distribution of research hotspots [19]. The graphical analysis of VOSviewer Word frequency analysis of literature keywords is commonly used in bibliometrics to can reflect the relationship between each important node, topic and keyword more visu- reveal the distribution of research hotspots [19]. The graphical analysis of VOSviewer can ally [52]. First, set the statistic value of word frequency to the threshold of 30, then select reflect the relationship between each important node, topic and keyword more visually [52]. the top 110 high-frequency keywords to draw the urban microclimate research keyword First, set the statistic value of word frequency to the threshold of 30, then select the top 110 co-occurrence network mapping (Figure 6) and annual overlap mapping (Figure 7). Sev- high-frequency keywords to draw the urban microclimate research keyword co-occurrence eral keywords with high word frequency were temperature, climate, vegetation, outdoor network mapping (Figure 6) and annual overlap mapping (Figure 7). Several keywords thermal comfort, and urban heat island. with high word frequency were temperature, climate, vegetation, outdoor thermal comfort, and urban heat island. Figure 6. Keyword co-occurrence network mapping for urban microclimate research. Figure 6. Keyword co-occurrence network mapping for urban microclimate research. Buildings 2022, 12, x FOR PEER REVIEW 10 of 18 Buildings 2022, 12, 877 10 of 17 Figure 7. Annual overlap mapping of urban microclimate studies. Figure 7. Annual overlap mapping of urban microclimate studies. In the keyword co-occurrence network view (Figure 6), the four-word nodes of temper- In the keyword co-occurrence network view (Figure 6), the four-word nodes of tem- ature, vegetation, model, and energy are the largest and the most frequent. Around these perature, vegetation, model, and energy are the largest and the most frequent. Around four core concepts, other high-frequency keywords based on co-occurrence relationships these four core concepts, other high-frequency keywords based on co-occurrence relation- present four main research clusters: (1) Green: Focus on urban microclimate and urban ships present four main research clusters: (1) Green: Focus on urban microclimate and environment, urban space, and other research. The high-frequency words include climate, urban environment, urban space, and other research. The high-frequency words include outdoor thermal comfort, environment and adaptation. From the word frequency, the climate, outdoor thermal comfort, environment and adaptation. From the word fre- research objects focus on urban geometry, hot, environment, and summer, the purpose of quency, the research objects focus on urban geometry, hot, environment, and summer, the the research is mainly concerned with adaptation, orientation, and perception, and the purpose of the research is mainly concerned with adaptation, orientation, and perception, research methods involve design and ENVI-met simulation; (2) Red: Research exploring the relationshipand the between re the search natural metho andd urban s involve desig environments. n and High-fr ENVequency I-met simula words tion; include (2) Red: Research urban heat exp island, loring climate the re change lationship and b urbanization. etween the nat The ustudy ral and object urban env is related ironto msurface ents. High-frequency temperature, ecosystem services, and green infrastructure regarding word frequency. It words include urban heat island, climate change and urbanization. The study object is focuses on health, mitigation, and land use. The research methods mainly involve covering related to surface temperature, ecosystem services, and green infrastructure regarding and remote sensing; (3) Blue: The study of urban microclimate modelling. High-frequency word frequency. It focuses on health, mitigation, and land use. The research methods words include simulation, street canyon, and air quality. The main objects of interest are mainly involve covering and remote sensing; (3) Blue: The study of urban microclimate density, pollution, and ventilation in terms of word frequency. The research methods are modelling. High-frequency words include simulation, street canyon, and air quality. The mainly CFD methods and prediction; (4) Yellow: In the study of urban energy consumption, main objects of interest are density, pollution, and ventilation in terms of word frequency. its high-frequency words are consumption and albedo. The main objects of concern are the The research methods are mainly CFD methods and prediction; (4) Yellow: In the study green roof and shade trees. of urban energy consumption, its high-frequency words are consumption and albedo. The From the year analysis (Figure 7), the high-frequency words that appeared earlier main objects of concern are the green roof and shade trees. (before 2010) include temperature, climate, vegetation and urbanization. Early urban micro- From the year analysis (Figure 7), the high-frequency words that appeared earlier climate research focused on integrated research with other disciplines such as environment, (before 2010) include temperature, climate, vegetation and urbanization. Early urban mi- and then outdoor thermal comfort, simulation, and surface temperature were proposed, croclimate research focused on integrated research with other disciplines such as environ- and the research objects and contents were further refined. Since 2016, the high-frequency ment, and then outdoor thermal comfort, simulation, and surface temperature were pro- words have been consumption, radiation, ventilation, ecosystem and CFD. Compared with posed, and the research objects and contents were further refined. Since 2016, the high- the previous stages, the research perspective is more macroscopic, and new concepts and frequency words have been consumption, radiation, ventilation, ecosystem and CFD. technologies are gradually applied. Compared with the previous stages, the research perspective is more macroscopic, and new concepts and technologies are gradually applied. 4.2. Evolution of Research Hotspots Based on Annual Overlap Buildings 2022, 12, x FOR PEER REVIEW 11 of 18 The Time view function in CiteSpace enables the visual analysis of evolutionary paths [23], which helps discover the turning time points of research and the critical litera- ture of the corresponding period. The timeline view reflects the distribution of keywords with high centrality over different years. The size of the circles in Figure 8 reflects the high level of keyword centrality. Nodes with higher centrality have a more significant influ- ence. If the keywords in a time zone are intensive, there are more research results in this period. The timeline view can also analyze the relationship among different clusters. In this paper, we use CiteSpace’s keyword analysis, set the time slice to 1 year, and Buildings 2022, 12, 877 11 of 17 plot the time-zoned axes of research in different periods (Figure 8) to analyze the relation- ship between each cluster and analyze the importance of different categories in different periods. Ten categories of relevant research hotspots were obtained, namely #0 human 4.2. Evolution of Research Hotspots Based on Annual Overlap thermal comfort, #1 thermal performance, #2 heatwave, #3 outdoor thermal comfort, #4 The Time view function in CiteSpace enables the visual analysis of evolutionary green infrastructure, and #5 urban trees, #6 grills, #7 urban morphology, #8 green CTTC paths [23], which helps discover the turning time points of research and the critical literature (cluster thermal time constant) model, #9 atmospheric pollution. The topics include heat, of the corresponding period. The timeline view reflects the distribution of keywords with heat balance equations, environment, ecology, urban geometry, modelling, and meteorol- high centrality over different years. The size of the circles in Figure 8 reflects the high level ogy. Human thermal comfort is the cluster with the most prolonged duration, the highest of keyword centrality. Nodes with higher centrality have a more significant influence. If keyword cen the keywords tral in ita y an time d th zone e most s are intensive, ignifican ther t ine flar uence o e moren r other c esearch lrus esults ters, which in this period. is the focus The timeline view can also analyze the relationship among different clusters. of urban microclimate research. Figure 8. Time-zoned axial mapping of urban microclimate studies (top ten categories). Figure 8. Time-zoned axial mapping of urban microclimate studies (top ten categories). In this paper, we use CiteSpace’s keyword analysis, set the time slice to 1 year, and plot 4.3. Research Hotspot Prediction Based on Keyword Emergence the time-zoned axes of research in different periods (Figure 8) to analyze the relationship between each cluster and analyze the importance of different categories in different periods. Keyword burst detection can detect changes in the frequency of keywords over a Ten categories of relevant research hotspots were obtained, namely #0 human thermal certain period and derive promising research directions [18]. In the study from 1990 to comfort, #1 thermal performance, #2 heatwave, #3 outdoor thermal comfort, #4 green 2021, the 24 burst keywords with the highest frequency were selected for study (Table 2). infrastructure, and #5 urban trees, #6 grills, #7 urban morphology, #8 green CTTC (cluster Before 2006, the main focus was on urban design and land planning. From 2006 to 2016, thermal time constant) model, #9 atmospheric pollution. The topics include heat, heat the research was extended towards landscape, temperature, hot, dry climate, and param- balance equations, environment, ecology, urban geometry, modelling, and meteorology. eterization, and from 2016 to date, related research has focused more on morphology and Human thermal comfort is the cluster with the most prolonged duration, the highest keyword centrality and the most significant influence on other clusters, which is the focus materials. of urban microclimate research. 4.3. Research Hotspot Prediction Based on Keyword Emergence Keyword burst detection can detect changes in the frequency of keywords over a certain period and derive promising research directions [18]. In the study from 1990 to 2021, the 24 burst keywords with the highest frequency were selected for study (Table 2). Before 2006, the main focus was on urban design and land planning. From 2006 to 2016, the research was extended towards landscape, temperature, hot, dry climate, and param- eterization, and from 2016 to date, related research has focused more on morphology and materials. This paper further analyses the keywords that appeared in the last five years (2017– 2022) and the strength and timing of their appearance to mitigate the lag in the bibliometric results and more accurately analyze the research trends in urban microclimate. As shown in Table 3, coating, atmosphere boundary layer, Mediterranean climate, shading and energy efficiency are new topics in recent years. Buildings 2022, 12, x FOR PEER REVIEW 12 of 18 Table 2. Top 24 most cited keywords in urban microclimate research in1990–2021. Buildings 2022, 12, 877 12 of 17 Keywords Strength Start End 1990----------------------------------------------------------2021 Buildings 2022, 12, x FOR PEER REVIEW 12 of 18 Urban design 5.2354 1992 2017 Landscape 4.4904 2006 2014 Table 2. Top 24 most cited keywords in urban microclimate research in 1990–2021. Community 4.2531 2006 2017 Table 2. Top 24 most cited keywords in urban microclimate research in1990–2021. Parameterization 4.093 2008 2014 Keywords Tempera Strengthture 8Start.2872 2008 End 2013 1990———————————————————-2021 Keywords Strength Start End 1990----------------------------------------------------------2021 Air pollution 4.2191 2008 2012 Urban design Urban desi 5.2354 gn 5.2 1992 354 1992 2017 2017 Thermal performance 3.1075 2009 2011 Landscape Landsca 4.4904pe 4.4 2006904 2006 20142014 Urban planning 4.0628 2011 2014 Community Communi 4.2531ty 4.2 2006531 2006 20172017 Impervious surface 3.5086 2011 2016 ParameterizationParameterizat 4.093ion 4.2008093 2008 20142014 Land use 7.5759 2012 2017 Temperature Tempera 8.2872ture 8.2 2008872 2008 20132013 Green roof 4.3646 2013 2017 Air pollution Air poll4.2191 ution 4.2 2008 191 2008 2012 2012 Thermal performance ThermaEvapot l performa ransp 3.1075iratince on 3 3.1 2009.8 075 072 2009 2013 2011 2011 2015 Urban planning The hot Urban p , dry cl l4.0628 anning imate 44 .0 2011 .8 628 018 2011 2013 2014 2014 2016 Impervious surfaceImpervious surfa 3.5086ce 3.5 2011 086 2011 2016 2016 Urbanization 3.1877 2014 2015 Land use Land use 7.5759 7.5 2012 759 2012 2017 2017 GI 3.3411 2015 2017 Green roof Green roof 4.3646 4.3 2013 646 2013 2017 2017 Biodiversity 3.1095 2016 2017 EvapotranspirationEvapotransp 3.8072iration 3.8 2013072 2013 20152015 Cool material 4.0713 2017 2018 The hot, dry climate The hot, dry cl 4.8018 imate 4.8 2013 018 2013 2016 2016 Thermal sensation 3.5097 2018 2019 Urbanization Urbaniza 3.1877tion 3.1 2014877 2014 20152015 Urban heat 3.5198 2019 2021 GI 3.3411 2015 2017 GI 3.3411 2015 2017 Equivalent temperature 3.3522 2019 2019 Biodiversity 3.1095 2016 2017 Biodiversity 3.1095 2016 2017 Energy performance 3.7053 2019 2019 Cool material 4.0713 2017 2018 Cool material 4.0713 2017 2018 Aspect ratio 4.1644 2019 2021 Thermal sensation 3.5097 2018 2019 Thermal sensation 3.5097 2018 2019 Urban park 3.9219 2020 2021 Urban heat 3.5198 2019 2021 Urban heat 3.5198 2019 2021 The blue line indicates the period from 1990 to 2021, with each small segment representing one year; Equivalent temperature 3.3522 2019 2019 Equivalent temperature 3.3522 2019 2019 the red thickened line indicates the period of the sudden growth of the corresponding keyword, Energy performance 3.7053 2019 2019 Energy performance 3.7053 2019 2019 with the red appearing and ending positions representing its starting and ending years, and the Aspect ratio 4.1644 2019 2021 Aspect ratio 4 longer the red .1644 2019 line represents 2021 , the longer the sudden growth of the keyword is maintained. Urban park 3.9219 2020 2021 Urban park 3.9219 2020 2021 This paper further analyses the keywords that appeared in the last five years (2017– The blue line indicates the period from 1990 to 2021, with each small segment representing one year; The blue line indicates the period from 1990 to 2021, with each small segment representing one year; the red the red thickened line indicates the period of the sudden growth of the corresponding keyword, 2022) and the strength and timing of their appearance to mitigate the lag in the biblio- thickened line indicates the period of the sudden growth of the corresponding keyword, with the red appearing with the red appearing and ending positions representing its starting and ending years, and the and ending positions metric r repr esults and more esenting its startacc ingu and rate ending ly analy years, ze thand e rese the arc longer h trends the rin ur ed lin ban microc e represents, limate the longer . As longer the red line represents, the longer the sudden growth of the keyword is maintained. the sudden growth of the keyword is maintained. shown in Table 3, coating, atmosphere boundary layer, Mediterranean climate, shading and energy efficiency are new topics in recent years. This paper further analyses the keywords that appeared in the last five years (2017– Table 3. Keywords highlighting strength and timing of urban microclimate research in 2017–2022. 2022) and the strength and timing of their appearance to mitigate the lag in the biblio- Table 3. Keywords highlighting strength and timing of urban microclimate research in 2017–2022. metric results and more accurately analyze the research trends in urban microclimate. As Keywords Strength Begin End 2017————————2022 Keywords St shown in Table 3, corengt ath ing , atmosphere bBegin oundary layeEnd r, Mediterr2017 an-- ean c------ lim----- at-- e, --s-- h-- adin---2g 022 and energy efficiency are new topics in recent years. Coating 2.0568 2017 2019 Coating 2.0568 2017 2019 Atmosphere boundary layer 1.9597 2017 2018 Atmosphere boundary layer 1.9597 2017 2018 Table 3. Keywords highlighting strength and timing of urban microclimate research in 2017–2022. Mediterranean climate 2.0746 2017 2018 Mediterranean climate 2.0746 2017 2018 Shading 2.8963 2018 2019 KSehywords St ading 2re.ngt8963 h Begin 2018 End 2019 2017------------------------2022 Energy efficiency 2.2226 2020 2022 Energy effCoatinig 2 ciency .20.568 2226 2017 2020 2019 2022 The blue line indicates the period from 2017 to 2022, with each small segment representing one year; the red Atmosphere boundary layer The blue line in1 dicate .9597 s the period from 2017 2017 to 2022, with 2018 each small segment representing one year; thickened line indicates the period of the sudden growth of the corresponding keyword, with the red appearing the red thickened line indicates the period of the sudden growth of the corresponding keyword, Mediterranean climate 2.0746 2017 2018 and ending positions representing its starting and ending years, and the longer the red line represents, the longer with the red appearing and ending positions representing its starting and ending years, and the Shading 2.8963 2018 2019 the sudden growth of the keyword is maintained. longer the red line represents, the longer the sudden growth of the keyword is maintained. Energy efficiency 2.2226 2020 2022 The blue line indicates the period from 2017 to 2022, with each small segment representing one year; CiteSpace provides two metrics, module value (Q value) and average profile value CiteSpace provides two metrics, module value (Q value) and average profile value (S value), the red thickened line indicates the period of the sudden growth of the corresponding keyword, based on the clarity of network structure and clustering, which can be used to judge the effectiveness (S value), based on the clarity of network structure and clustering, which can be used to with the red appearing and ending positions representing its starting and ending years, and the of mapping. In general, Q values are generally in the interval [0, 1), Q > 0.3 means that the delineated longer the red line represents, the longer the sudden growth of the keyword is maintained. judge the effectiveness of mapping. In general, Q values are generally in the interval [0, 1), association structure is significant, and the clustering is efficient and convincing when the S value is Q > 0.3 means that the delineated association structure is significant, and the clustering is CiteSpace provides two metrics, module value (Q value) and average profile value (S value), efficient and convincing when the S value is 0.7. The co-occurrence network relationship is based on the clarity of network structure and clustering, which can be used to judge the effectiveness of mapping. In general, Q values are generally in the interval [0, 1), Q > 0.3 means that the delineated simplified into clusters and labelled, and the top 10 clusters are listed with cluster module association structure is significant, and the clustering is efficient and convincing when the S value is value (Q value) of 0.8013 > 0.3 and average profile value (S value) of 0.9239 > 0.7, indicating that the clusters lie in the confidence interval and the clustering quality is high. Table 4 and Figure 9 show a more in-depth analysis of the specifics contained in each cluster name. Buildings 2022, 12, 877 13 of 17 Table 4. Keyword clustering of urban microclimate research in the last five years. Cluster Name Size Profile Value Year Main Keywords urban ecosystems; land surface temperature; air 0. Urban ecology 35 0.913 2018 temperature; ecosystem services; indicators; physical health; global climate regulation 1. NDVI (Normalized surface urban heat island; physical activity; citizen science; 30 0.936 2018 Difference Vegetation Index) biological invasion; convective heat flux agent-based model; ventilation path; twining plants; small 2. Particulate matter 30 0.882 2018 urban planting design; geographic information system (gis); single planting cool pavement; microclimate model; thermal behavior; physiological equivalent temperature index; 3. Thermal comfort 29 0.857 2018 micrometeorological measurements; hedonic modelling; outdoor microclimate map turbulence; urban canyon; weather research and 4. Heat mitigation 26 0.918 2018 forecasting model; low-rise housing; humid tropics region; office buildings; height-to-width ratio; passive design mitigation; integrated environmental assessment; 5. ENVI-met 25 0.953 2018 residential district; direct shortwave radiation scattering; wind speed reduction; plant geometry; plant physiology tree species; air relative humidity; reduced soil water 6. Urban trees 23 0.886 2018 availability; antioxidants; surface-energy balance; light; latent heat flux; sap flow dynamics thermal adaptation; form indices; cooling energy 7. EnergyPlus 23 0.879 2018 consumption; generic residential districts; OpenFOAM building energy simulation; computational fluid dynamics; 8. Thermal network model 23 0.946 2017 vertical greenery system; CoMFA human heat balance model; lumped thermal parameter Buildings 2022, 12, x FOR PEER REVIEW 14 of 18 green walls; urban agriculture; urbanization; Teb; urban 9. Irrigation 21 0.872 2017 water cycle; subtropical monsoon climate; vertical farming Figure 9. Cluster mapping of urban microclimate research keywords 2017–2022. Figure 9. Cluster mapping of urban microclimate research keywords 2017–2022. Those with greater frequency (>200 times) are temperature, urban heat island, ther- mal comfort, vegetation, and environment. Those with more vital centrality (greater than or equal to 0.15) are energy-saving, cooling load, biometeorological assessment, roof, cover, and heat stress. 5. General Forecast of Trends in Research Characteristics 5.1. Multi-Scale Urban Climate Simulation Study Computer simulations can integrate the effects of different meteorological conditions on cities, buildings and humans, and play an essential role in urban microclimate assess- ment [53]. However, most studies have focused on micro-scale outdoor human thermal comfort using ENVI-met, and more multi-scale model coupling is needed at the urban level [54], e.g., the high-resolution urban climate model PALM-4U [55], and the urban multi-scale environmental predictor UMEP [56]. Future research could combine models at different scales with climate zones, and there are already nesting ENVI-met into local climate zones LCZ [57], WUDAPT [58], mesoscale models (e.g., WRF), or larger scale model domains [57], intending to achieve more scientific strategic plans for cities to im- plement climate change. Buildings 2022, 12, 877 14 of 17 Those with greater frequency (>200 times) are temperature, urban heat island, thermal comfort, vegetation, and environment. Those with more vital centrality (greater than or equal to 0.15) are energy-saving, cooling load, biometeorological assessment, roof, cover, and heat stress. 5. General Forecast of Trends in Research Characteristics 5.1. Multi-Scale Urban Climate Simulation Study Computer simulations can integrate the effects of different meteorological conditions on cities, buildings and humans, and play an essential role in urban microclimate assess- ment [53]. However, most studies have focused on micro-scale outdoor human thermal comfort using ENVI-met, and more multi-scale model coupling is needed at the urban level [54], e.g., the high-resolution urban climate model PALM-4U [55], and the urban multi-scale environmental predictor UMEP [56]. Future research could combine models at different scales with climate zones, and there are already nesting ENVI-met into local climate zones LCZ [57], WUDAPT [58], mesoscale models (e.g., WRF), or larger scale model domains [57], intending to achieve more scientific strategic plans for cities to implement climate change. 5.2. Multi-Factor Urban Microclimate Impact Study An urban microclimate is influenced by various factors such as physical and social factors, and scholars have used methods such as fluid dynamics (CFD) [12] and weather research and forecasting (WRF) [59] to study factors such as wind speed and direction [60], building materials [61], temperature [62] and humidity [63] to determine urban micro- climate parameters. Since the influencing factors of urban microclimates involve many aspects, there are still many research blind spots in the existing literature, which need to be further sorted out and comparatively studied to build a more systematic urban microclimate model, and then form a systematic scientific cycle system. 5.3. Multi-Policy Urban Microclimate Guidance Study Compared with “smart cities” and “low-carbon cities”, there is a lack of clear policy guidance on the urban microclimate [64], and the improvement of urban environmental comfort by microclimate optimization has not been considered. In the future, the role of the urban microclimate can be highlighted in the ambient air quality standards or green building guidelines. 6. Conclusions In this paper, we use WOS online analysis with bibliometric data analysis of CiteSpace and VOSviewer to study the literature related to the urban microclimate from 1990 to 2021, and visualize and analyze the characteristics of literature distribution, research development stages and research hotspot trends in different periods, disciplines and country situations and conclude the following: (1) The urban microclimate research literature volume shows prominent multidisci- plinary and comprehensive characteristics. The overall number of publications shows an increasing trend, and four leading research clusters are formed: theoretical research on the urban environment and urban space, research on the natural environment and urban environment, research on urban microclimate modelling, and research on urban energy consumption; (2) Urban microclimate research can be divided into four stages: nascent exploration, model quantification, diversified development, and ecological synergy. In terms of lit- erature and discipline distribution, research hotspots and focus, they show the “rise of multidisciplinary and urban studies”, “application of numerical quantification and model evaluation”, “maturation of system and expansion of research breadth”, and “focus on eco-synergy with multiple types of elements”; Buildings 2022, 12, 877 15 of 17 (3) The knowledge mapping characteristics of research hotspots based on keyword clustering, annual overlap, and keyword highlighting show that urban microclimate re- search has three hotspot trends—multi-scale urban climate simulation research, multi- element urban microclimate impact research, and multi-policy urban microclimate guid- ance research. Urban microclimate research has achieved specific results since 1990, but there are still problems such as incomplete policies and insufficient elements. The academic community needs more innovations in urban microclimate theory and practice to construct a theoretical system of the urban microclimate and solve the urban microclimate’s complex and diverse practical problems. Author Contributions: Conceptualization and writing, Y.Z.; methodology and visualization, N.A.; audit and funding acquisition, J.Y. All authors have read and agreed to the published version of the manuscript. Funding: National Natural Science Foundation of China under Grant NO. 51908410; the Shanghai Municipal Science and Technology Major Project under Grant NO. 2021SHZDZX0100; the Funda- mental Research Funds for the Central Universities. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest. References 1. Lin, J.; Brown, R. Integrating Microclimate into Landscape Architecture for Outdoor Thermal Comfort: A Systematic Review. Land 2021, 10, 196. 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Characteristics, Progress and Trends of Urban Microclimate Research: A Systematic Literature Review and Bibliometric Analysis

Buildings , Volume 12 (7) – Jun 22, 2022

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buildings Review Characteristics, Progress and Trends of Urban Microclimate Research: A Systematic Literature Review and Bibliometric Analysis 1 1 1 , 2 , Yichen Zhou , Na An and Jiawei Yao * College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China; 1954034@tongji.edu.cn (Y.Z.); anna2010255@tongji.edu.cn (N.A.) Key Laboratory of Spatial Intelligent Planning Technology, Ministry of Natural Resources, Shanghai 200092, China * Correspondence: jiawei.yao@tongji.edu.cn; Tel.: +86-138-1651-5004 Abstract: Climate change has been a hot topic in recent years. However, the urban microclimate is more valuable for research because it directly affects people’s living environments and can be adjusted by technological means to enhance the resilience of cities in the face of climate change and disasters. This paper analyses the literature distribution characteristics, development stages, and research trends of urban microclimate research based on the literature on “urban microclimate” collected in the Web of Science core database since 1990, using CiteSpace and VOSviewer bibliometric software. It is found that the literature distribution of the urban microclimate is characterized by continuous growth, is interdisciplinary, and can be divided into four stages: nascent exploration, model quantification, diversified development and ecological synergy. Based on the knowledge mapping analysis of keyword clustering, annual overlap, and keyword highlighting, it can be predicted that the research on foreign urban land patch development has three hot trends—multi-scale modelling, multi-factor impact, and multi-policy guidance. The study’s findings help recognize the literature distribution characteristics and evolutionary lineage of urban microclimate research and provide suggestions for Citation: Zhou, Y.; An, N.; Yao, J. Characteristics, Progress and Trends future urban microclimate research. of Urban Microclimate Research: A Systematic Literature Review and Keywords: bibliometrics; citespace; development stages; distribution characteristics; research trends; Bibliometric Analysis. Buildings 2022, urban microclimate; vosviewer 12, 877. https://doi.org/10.3390/ buildings12070877 Academic Editors: Baojie He, 1. Introduction Ayyoob Sharifi, Chi Feng and Jun Yang Climate risks have and will continue to affect national security, economic security, human health, infrastructure, and ecosystem stability [1]. The Global Risks Report 2022, Received: 13 May 2022 published by the World Economic Forum, lists climate change as one of the ten most press- Accepted: 20 June 2022 ing global risks [2]. The United Nations Intergovernmental Panel on Climate Change (IPCC) Published: 22 June 2022 Sixth Assessment Report, Climate Change 2022: Impacts, Adaptation and Vulnerability, Publisher’s Note: MDPI stays neutral states that humanity is pushing the limits of climate carrying capacity and points to the with regard to jurisdictional claims in urgency of climate transition in the next decade [3]. Therefore, urban climate research is of published maps and institutional affil- great importance for healthy urban development. iations. The study of urban climate began in 1818 with Lake Howard’s “The Climate of Lon- don”, which first identified the temperature difference between urban and rural areas, i.e., the urban heat island effect, and studied the factors influencing the city’s climate [4]. Most current research on urban climate change focuses on macro-scale climate change patterns Copyright: © 2022 by the authors. such as national scales and climate zones, while climate research on the complex and Licensee MDPI, Basel, Switzerland. variable near-surface micro spaces has a later origin and slightly less research. Compared This article is an open access article with macro climate change, urban microclimate has a more direct impact on people’s living distributed under the terms and environments. People can regulate the urban microclimate through technical means and conditions of the Creative Commons then enhance the self-recovery ability of cities in the face of climate change and disasters, Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ and if we enlarge the concept of resilient cities, the concept of microclimate becomes more 4.0/). critical [5,6]. Buildings 2022, 12, 877. https://doi.org/10.3390/buildings12070877 https://www.mdpi.com/journal/buildings Buildings 2022, 12, 877 2 of 17 The research plan uses WOS, the largest Database of English documents, as the raw material and combines the advantages of Citespace and VosViewer for visualization and clustering analysis. Compared with traditional bibliometric methods, the visual analysis of scientific knowledge graphs is more intuitive and readable [7]. Urban microclimate originated in 1947 [8], and 2131 articles were searched in the Web of Science database under TS = (urban microclimate) OR TS = (city microclimate). The language of the literature was limited to English, the type of literature was limited to articles, and the search date was 4 May 2022. Searched with (TS = (urban microclimate) OR TS = (city microclimate)) AND TS = (review) AND ALL = (citespace), the type of literature was Article, the language was English, the result was 0, and the search time was 9 April 2022. There are 51 reviews, and no citespace based search studies are available. Most current microclimate studies focus on the quantification of microclimates [9], such as the calculation of thermal comfort equations [10], meteorological data moni- toring [11], computer simulations [12], and subjective thermal environment question- naires [13,14]. The concept of urban microclimate first referred to the influence of some climatic factors in the ground boundary layer by local features [10] and then also shifted to focus on urban scale differences [15], urban climate characteristics [16], and urban environmental elements [17]. Although there are some review studies on urban microcli- mate research, previous studies are mostly clustered analyses, and we have not yet seen time series-based development stage classification and multi-method research hotspot prediction [6]. 2. Data and Methods This paper adopts data analysis, software measurement, and scientific mapping meth- ods to understand further the evolutionary characteristics and hot issues of urban microcli- mate research. It uses visual analysis of CiteSpace and VOSviewer bibliometric analysis software to conduct scientific knowledge mapping analysis of urban microclimate literature to clarify potential knowledge connections among the literature [18]. A science mapping can highlight potentially significant patterns, trends, and theories of scientific change that can guide the exploration and interpretation of visual, intellectual structures and dynamic patterns [19]. Compared to other mapping software, CiteSpace and VOSviewer have a higher frequency of use and broader dissemination as commonly used bibliometric map- ping software [20]. CiteSpace can detect and visualize emerging trends and radical changes in scientific disciplines over time [21]. VOSviewer is a bibliometric analysis software jointly developed by Leiden University scholars Nees Jan van Eck and Ludo Waltman for drawing knowledge maps. It can be used for co-word, co-citation, and literature coupling analysis. It can display research results visually and has unique advantages in clustering technology and map displays [22]. Compared to Scopus, Google Scholar and PubMed, Web of Science is the world’s largest and most comprehensive scholarly information resource covering a wide range of disciplines, including the most influential core academic journals in various research fields such as natural sciences, engineering and technology, and biomedicine. Therefore, this paper uses the Web of Science core collection (hereafter referred to as WOS) as the data source, and the search period was 9 April 2022, with a years limit of 1990–2022. The search mode of “subject” + “document type” was used, and the search terms were: TS = (urban microclimate) OR TS = (city microclimate), and the document language was limited to “English”, the type was restricted to “articles” to ensure the scientific validity and accuracy of the research, and a total of 2070 relevant documents were obtained. Centrality metrics provide a computational method for finding pivotal points be- tween different specialties or tipping points in an evolving network [23]. It measures the percentage of the number of shortest paths in a network to which a given node belongs. Nodes with high-betweenness centrality tend to be found in paths connecting different clusters. This feature has been used in community-finding algorithms to identify and separate clusters [24]. Higher strength refers to a sharp increase in the number of term occurrences in this period, which is the frontier of research in this phase [23]. Kleinberg’s Buildings 2022, 12, x FOR PEER REVIEW 3 of 18 Buildings 2022, 12, x FOR PEER REVIEW 3 of 18 clusters. This feature has been used in community-finding algorithms to identify and sep- clusters. This feature has been used in community-finding algorithms to identify and sep- Buildings 2022, 12, 877 3 of 17 arate clusters [24]. Higher strength refers to a sharp increase in the number of term occur- arate clusters [24]. Higher strength refers to a sharp increase in the number of term occur- rences in this period, which is the frontier of research in this phase [23]. Kleinberg’s (2002) rences in this period, which is the frontier of research in this phase [23]. Kleinberg’s (2002) burst-detection algorithm can be adapted for detecting sharp increases of interest in a spe- burst-detection algorithm can be adapted for detecting sharp increases of interest in a spe- (2002) burst-detection algorithm can be adapted for detecting sharp increases of interest cialty [25]. In CiteSpace, a current research front is identified based on such burst terms cialty [25]. In CiteSpace, a current research front is identified based on such burst terms in a specialty [25]. In CiteSpace, a current research front is identified based on such burst extracted from keywords [23]. extracted from keywords [23]. terms extracted from keywords [23]. 3. Results 3. Results 3. Results 3.1. Current Status of Urban Microclimate Research 3.1. Current Status of Urban Microclimate Research 3.1. Current Status of Urban Microclimate Research 3.1.1. Research Scale and Impact Analysis 3.1.1. Research Scale and Impact Analysis 3.1.1. Research Scale and Impact Analysis The number of publications in this field has increased (Figure 1). The number of an- The The number number of of publ publications ications in in this thisfi field eld has hasincre increased ased (F (Figur igure e 1). The number 1). The number of an- of nual publications before 2005 was small (basically less than 10 publications per year), and annual nual pu publications blications bebef fore 20 ore 05 2005 wa was s smsmall all (bas (basically ically less less than 1 than 0 p 10 ub publications lications per ye perar) year), , and urban microclimate research was still in the exploration stage; from 2000 to the present, and urban mic urban micr roclim oclimate ate rese resear arch was s ch wastistill ll inin the ex the explor ploraa tion s tion stage; tage; fr from om 20 2000 00 to to the the p prr esent, esent, the number of publications has shown an exponential increase, and urban microclimate the number of publications has shown an exponential increase, and urban microclimate the number of publications has shown an exponential increase, and urban microclimate research has received significant attention since the 21st century and has become one of research has received significant attention since the 21st century and has become one of the research has received significant attention since the 21st century and has become one of the current research hot topics. As of 9 April 2022, 49 articles have been published, and current research hot topics. As of 9 April 2022, 49 articles have been published, and the the current research hot topics. As of 9 April 2022, 49 articles have been published, and the number of articles is expected to climb in 2022. number of articles is expected to climb in 2022. the number of articles is expected to climb in 2022. Figure 1. Number of published articles on urban microclimate. Figure 1. Number of published articles on urban microclimate. Figure 1. Number of published articles on urban microclimate. 3.1.2. Interdisciplinary and Publication Analysis 3.1.2. Interdisciplinary and Publication Analysis 3.1.2. Interdisciplinary and Publication Analysis In terms of disciplinary distribution, urban microclimate research is mainly concen- In terms of disciplinary distribution, urban microclimate research is mainly concen- In terms of disciplinary distribution, urban microclimate research is mainly concen- trated in Environmental Science (13.24%) and Construction Building Technology trated in Environmental Science (13.24%) and Construction Building Technology (11.04%), trated in Environmental Science (13.24%) and Construction Building Technology (11.04%), reflecting the multidisciplinary and comprehensive nature of urban microcli- reflecting the multidisciplinary and comprehensive nature of urban microclimate research (11.04%), reflecting the multidisciplinary and comprehensive nature of urban microcli- mate research (Figure 2). (Figure 2). mate research (Figure 2). Disciplines Disciplines Environmental Sciences 13.24% Construction Building Technology 11.04% Environmental Sciences 13.24% Energy Fuels 7.93% Construction Building Technology 11.04% Engineering Civil 7.61% Energy Fuels 7.93% Green Sustainable Science Technology 6.76% Engineering Civil 7.61% Meteorology Atmospheric Sciences 6.54% Green Sustainable Science Technology 6.76% Environmental Studies 6.10% Meteorology Atmospheric Sciences 6.54% Engineering Environmental 4.73% Environmental Studies 6.10% Urban Studies 3.95% Engineering Environmental 4.73% Ecology 2.88% Urban Studies 3.95% 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 14.00% Ecology 2.88% Percentage 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 14.00% Percentage Figure 2. Percentage of urban microclimate papers by discipline (top 10). Buildings 2022, 12, x FOR PEER REVIEW 4 of 18 Figure 2. Percentage of urban microclimate papers by discipline (top 10). Buildings 2022, 12, x FOR PEER REVIEW 4 of 18 Regarding source publications, there are 527, with Building and Environment and Sus- Buildings 2022, 12, 877 4 of 17 tainable Cities and Society posting the most articles, accounting for 8.72% and 6.58%, respec- Figure 2. Percentage of urban microclimate papers by discipline (top 10). tively. The top 10 publications focused on urban and architectural research and environ- mental sustainability (Figure 3). Regarding source publications, there are 527, with Building and Environment and Regarding source publications, there are 527, with Building and Environment and Sus- Sustainable Cities and Society posting the most articles, accounting for 8.72% and 6.58%, tainable Cities and Society posting the most articles, accounting for 8.72% and 6.58%, respec- Publications respectively. The top 10 publications focused on urban and architectural research and tively. The top 10 publications focused on urban and architectural research and environ- BUILDING AND ENVIRONMENT 8.72% environmental sustainability (Figure 3). mental sustainability (Figure 3). SUSTAINABLE CITIES AND SOCIETY 6.58% Publications ENERGY AND BUILDINGS 5.68% SUSTAIN B A U BI ILD LIT IN YG AND ENVIRONMENT 5.64% 8.72% SUSTAINABLE CITIES AND SOCIETY 6.58% URBAN CLIMATE 3.51% ENERGY AND BUILDINGS 5.68% URBAN FORESTRY URBAN GREENING 3.13% SUSTAINABILITY 5.64% INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2.46% 3.51% URBAN CLIMATE SCIENCE OF THE TOTAL ENVIRONMENT 1.89% URBAN FORESTRY URBAN GREENING 3.13% LANDSCAPE AND URBAN PLANNING 1.89% INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 2.46% ATMOSPHERE 1.89% SCIENCE OF THE TOTAL ENVIRONMENT 1.89% 0.00% 1.00% 2.00% 3.00% 4.00% 5.00% 6.00% 7.00% 8.00% 9.00% 10.00% Percentage LANDSCAPE AND URBAN PLANNING 1.89% ATMOSPHERE 1.89% Figure 3. Percentage of urban microclimate papers published in journals (top 10). 0.00% 1.00% 2.00% 3.00% 4.00% 5.00% 6.00% 7.00% 8.00% 9.00% 10.00% Percentage Figure 3. Percentage of urban microclimate papers published in journals (top 10). 3.1.3. Country Di Figure 3. stribPerce ution ntag Ana e of u lys ris ban m icroclimate papers published in journals (top 10). 3.1.3. Country Distribution Analysis National time zonal mapping helps us find the most worthy references and to further 3.1.3. Country Distribution Analysis National time zonal mapping helps us find the most worthy references and to further select and classify the literature. In terms of the number of publications (radius size) (Fig- National time zonal mapping helps us find the most worthy references and to further select and classify the literature. In terms of the number of publications (radius size) ure 4), China has the highest number of articles (430) in country distribution, followed by select and classify the literature. In terms of the number of publications (radius size) (Fig- (Figure 4), China has the highest number of articles (430) in country distribution, followed the United States (359). The U.S. (1991) was the first to study urban microclimate, while ure 4), China has the highest number of articles (430) in country distribution, followed by by the United States (359). The U.S. (1991) was the first to study urban microclimate, China did not start until 2005. Centrality measures the importance of a node in the net- the United States (359). The U.S. (1991) was the first to study urban microclimate, while while China did not start until 2005. Centrality measures the importance of a node in work; a more critical node means a higher centrality, indicating that the country has pub- China did not start until 2005. Centrality measures the importance of a node in the net- the network; a more critical node means a higher centrality, indicating that the country lished more citations and is more influential in the period. In terms of centrality (more work; a more critical node means a higher centrality, indicating that the country has pub- has published more citations and is more influential in the period. In terms of centrality circles or colors), France (0.46) is much higher than other countries, followed by the U.S. lished more citations and is more influential in the period. In terms of centrality (more (more circles or colors), France (0.46) is much higher than other countries, followed by the circles or colors), France (0.46) is much higher than other countries, followed by the U.S. (0.41) and Canada (0.33). Although China started later, the number of publications has U.S. (0.41) and Canada (0.33). Although China started later, the number of publications (0.41) and Canada (0.33). Although China started later, the number of publications has shown explo has shown explosive sive grow grth, probably because owth, probably because the urb the urban an microclimat microclimate e issue issue has bee has been n gradu- shown explosive growth, probably because the urban microclimate issue has been gradu- ally no gradually ticed d noticed ue to due the h to the ighhigh-speed -speed urburban an development. development. ally noticed due to the high-speed urban development. Figure 4. National time zonal mapping for urban microclimate studies. Figure 4. National time zonal mapping for urban microclimate studies. Figure 4. National time zonal mapping for urban microclimate studies. Buildings 2022, 12, x FOR PEER REVIEW 5 of 18 Buildings 2022, 12, 877 5 of 17 3.2. Development Stages of Urban Microclimate Research 3.2. Development Stages of Urban Microclimate Research CiteSpace’s keyword clustering analysis, centrality, and emergent detection can iden- CiteSpace’s keyword clustering analysis, centrality, and emergent detection can iden- tify research frontiers to predict research trends. Using CiteSpace to map keyword time tify research frontiers to predict research trends. Using CiteSpace to map keyword time regions and temporal partitioning of highly cited literature can help analyze the evolu- regions and temporal partitioning of highly cited literature can help analyze the evolu- tionary path of research hotspots. Combined with co-citation analysis, it can help identify tionary path of research hotspots. Combined with co-citation analysis, it can help identify turning points in research and critical literature in each period [19]. turning points in research and critical literature in each period [19]. This paper uses CiteSpace to analyze the time-zoned mapping of urban microclimate This paper uses CiteSpace to analyze the time-zoned mapping of urban microclimate research literature (Figure 5) and divides the research into four stages; the main research research literature (Figure 5) and divides the research into four stages; the main research progress and characteristics are reviewed in stages. There are numerous urban microcli- progress and characteristics are reviewed in stages. There are numerous urban microclimate mate research hotspots (Table 1), and their research hotspots have apparent characteristics research hotspots (Table 1), and their research hotspots have apparent characteristics of the of the times and are significantly influenced by the social context and policy focus. For times and are significantly influenced by the social context and policy focus. For example, example, the fourth Conference of the Parties to the United Nations Framework Conven- the fourth Conference of the Parties to the United Nations Framework Convention on tion on Climate Change was held in 1998, and the Paris Agreement was signed and for- Climate Change was held in 1998, and the Paris Agreement was signed and formally mally implemented in 2016, which may serve as additional factors for phase division. implemented in 2016, which may serve as additional factors for phase division. Figure 5. Temporal partition mapping of urban microclimate research keywords. Figure 5. Temporal partition mapping of urban microclimate research keywords. Table 1. A burst of high-frequency keywords in urban microclimate research. Table 1. A burst of high-frequency keywords in urban microclimate research. Phase Year Frequency Keyword Burst Phase Year Frequency Keyword Burst 1993 419 Temperature 8.29 1993 419 Temperature 8.29 1993 308 Heat island 1993 308 Heat island 1990–1997 1993 219 Model 1990–1997 1993 219 Model 1996 294 Vegetation 1996 294 Vegetation 1997 46 Albedo 1997 46 Albedo 1998 282 Environment 4.03 1998 282 Environment 4.03 1998 167 Performance 1998 167 Performance 1999 62 Pattern 2000 62 Land use 7.58 1998–2005 1999 62 Pattern 2001 331 Thermal comfort 1998–2005 2000 62 Land use 7.58 2003 69 land surface temperature 2001 331 Thermal comfort 2005 136 Hot 2003 69 land surface temperature 2005 136 Hot 2006–2015 2006 231 Outdoor thermal comfort Buildings 2022, 12, 877 6 of 17 Table 1. Cont. Phase Year Frequency Keyword Burst 2006 231 Outdoor thermal comfort 2006 124 Urbanization 3.19 2007 127 Energy 2007 126 ENVI-met 2009 63 Green space 2011 126 Mitigation 2006–2015 2011 102 Street canyon 2014 51 Strategy 2015 75 Mean radiant temperature 2014 87 Expansion 2014 58 Urban Expansion 2016 55 Green infrastructure 3.50 2016 51 Ecosystem service 2016 to date 2017 45 Ventilation 2018 30 Mitigation strategy 2019 23 Aspect ratio 4.16 Higher burst refers to a sharp increase in the number of term occurrences in this period, which is the frontier of research in this phase [21]. 3.2.1. The Nascent Exploratory Phase (1990–1997): The Rise of Multidisciplinary and Urban Studies High-frequency keywords of early studies include temperature, heat island, and vegetation (Table 1), indicating that urban microclimate studies have mainly focused on multidisciplinary integrated studies and correlation analysis of urban constituents. However, the identification of the framework and connotation of microclimate composition has not yet emerged. Regarding multidisciplinary synthesis: Graves et al. used microclimate as one of the temperature indicator factors in the high root zone to study the effect of high-temperature zones on plant seedlings [22]. Gorbushina et al. used microclimate variability as an observ- able indicator of the biological activity of black fungi to study its role in morphology [26]. Regarding urban climate factors, Akbari et al. studied the feasibility of vegetation and high albedo materials in modifying the urban microclimate [27]. They found that increasing the vegetation cover by 30% with 20% albedo in dwellings in areas such as Toronto and Vancouver could reduce energy consumption by about 10% to 20%. Nichol conducted a microclimate study of the tropical city of Singapore for microclimate monitoring studies of high-rise housing and found a high correlation between satellite heat sensing data and biomass indices, with high similarity to actual temperatures [28]. In general, the literature published at this stage is small, and the attention of the academic community is low, mainly focusing on multidisciplinary microclimate aux- iliary research and microclimate research in small areas within cities (e.g., indoor en- vironments such as houses). The exploration of urban microclimate research systems has not yet emerged, which can be regarded as the nascent exploratory phase of urban microclimate research. 3.2.2. Model Quantification Phase (1998–2005): Application of Numerical Quantification and Model Evaluation The high-frequency keywords in this phase include environment, climate, and thermal comfort (Table 1), with environmental emergence at 4.03 and land use at 7.58, which were research hotspots. This stage mainly focuses on the research of urban microclimate model quantification. A typical representative is an ENVI-met model, simulation software developed by Bruse et al. to study surface–plant–air interactions in urban environments, which has become the most widely used tool in microclimate studies [29]. The research in this phase focuses on exploring urban microclimate perturbations, their influencing effects, and model construction. Buildings 2022, 12, 877 7 of 17 The research focuses on numerical assessment studies at the macro level on the one hand and studies the influence relationship with microclimate from different means and factors. Carlson et al. used satellite image data to obtain microclimate variables such as surface temperature, vegetation rate, ISA, and E.T, and used Chester County as an example to construct regression analysis models and predict future parameter changes [30]. Adolphe studied the relationship between urban building form and urban microclimate and used environmental form evaluation indicators to construct a simplified urban spatial model [31]. On the other hand, factors such as human perception are incorporated into micro- climate model construction. Matzarakis et al. proposed the physiologically equivalent temperature (PET), considering the correlation with human thermal–physiological percep- tion [32]. Steemers used microclimate as a research object to invert the energy consumption of buildings with different densities and analyze the urban morphology correlation, em- phasizing the value of outdoor comfort research [33]. Dimoudi et al. attempted to quantify the effect of vegetation on microclimate in urban environments and found that increased vegetation had a significant effect on temperature reduction [34]. de La Flor et al. proposed an “urban canyon” computational model that considers human thermal fitness to improve the urban microclimate and save the thermal performance of buildings [35]. At this stage, the number of publications on urban microclimate started to increase, and the academic community’s attention grew. The microclimate research process is complete with numerical modelling methods, but the coupling of microclimate with other factors is still unclear about the value of microclimate volume. 3.2.3. Diversified Development Phase (2006–2015): System Maturity and Expansion of Research Breadth Urban substratum changes bring a harsh climate environment, increased anthro- pogenic heat emission, and the spread of pollution from urban activities [36]. This stage of urban microclimate pays attention to urban heat islands, thermal comfort and other climate change mitigation studies based on the previous stage, where the high-frequency words include outdoor thermal comfort, urbanization and energy. From the total citations of the literature, this stage of research mainly focuses on urban planning or design, urban microclimate, and outdoor thermal comfort and gradually focuses on the actual measurement and testing of outdoor thermal comfort from the PET theory proposed in the previous stage, and combines quantitative findings to guide urban design. Subsequently, the research scope is further expanded, and the research object is no longer limited to a single model or a specific landscape, a disciplinary and social extension of the previous stage that only focused on microclimate-related factors. In terms of macro-simulation and micro-perception, Ali-Toudert et al. studied the effect of urban street aspect ratio and orientation on urban microclimates, evaluated the effect of PET on the climate of urban streets, and found that the street with south–north orientation and aspect ratio 2 had a better thermal environment compared with other combinations [37]. Yu, C et al. explored the effect of green space on microclimate regulation, selected two parks in Singapore as examples, conducted simulation verification with TAS and ENVI-MET, and found that green space could reduce the built environment temperature by 1.3 C and cooling load by 10% [38]. The RUROS project conducted by Nikolopoulou et al., which collected subjective human perception questionnaires from five European countries, concluded that urban microclimate is closely related to thermal comfort and that temperature and solar radiation are two essential factors influencing thermal comfort [16]. Harlan et al. used a model to estimate the summertime U.S. outdoor human thermal comfort index (HTCI) [39]. They found that community microclimate temperature has a strong negative relationship with HTCI and that lower socio-economic status and minority groups in residential areas with weak coping are more vulnerable to the adverse effects of the microclimate. Buildings 2022, 12, 877 8 of 17 In terms of the influence of urban design elements on the thermal environment, Huang et al. took Nanjing as an example and calculated the cooling effect of four urban ground cover types, which showed a cooling effect of 0.2 ~ 2.9 C for all urban blue-green spaces compared to bare concrete surfaces [40]. Shashua-Bar et al., also focusing on outdoor landscape cooling strategies in dry heat regions, selected six cooling combinations of trees, lawns, or shade nets and found that the cooling effect of grasses was most significant when they were in the shade of trees or shaded by shade nets [41]. Santamouris et al. analyzed the effect of reflective street pavement on microclimate and concluded that reflective pavement reduced ambient summer temperatures by up to 1.9 C and park surface temperatures by up to 12 C [42]. Kong et al. studied the relationship between urban cold island effects (UCIs) and microclimate in Nanjing green parks, where a 10% increase in vegetation area reduced surface temperatures by approximately 0.83 C [43]. Techniques and factors for microclimate studies have also been gradually expanded. Popular et al. used CFD simulations to predict the meteorology of the city of Rotterdam, including wind flow and heat transfer by conduction, convection and radiation and con- firmed that the average deviation between simulated and experimental data was 7.9%, confirming the potential of CFD to predict urban microclimate accurately [44]. The influ- ence of individual humans on the microclimate has also been considered. Bocker et al. were the first to systematically include behavioral activities considering thermal comfort to study the influence of climate on daily human behavior and critical activities such as walking and cycling [45]. They found that climate has a profound effect on travel. The number of publications in this period showed rapid growth compared with the previous period (Figure 1), and the number of co-cited literature increased significantly compared with the previous period (Figure 5). Microclimate-related research and meth- ods gradually matured and focused on the coupling research between microclimate and other objects, expanding the value volume of microclimate, providing in-depth theoretical support, mature technical methods, and high application value research directions. 3.2.4. Eco-Synergy Phase (2016 to Date): Focus on Eco-Synergy with Multiple Types of Elements This phase focuses on urban microclimate research under interdisciplinary and multi- perspectives, and the main keywords are green infrastructure, ecosystem services, and ventilation. In addition to the wide application of new technologies and models, the relationship between urban landscape and ecology is given unprecedented attention, and the focus is on the social benefits of the urban microclimate and the innovation of research applications. Among urban landscape benefit studies, Livesley et al. investigated the cooling benefits of urban forests on the local microclimate, including air quality, improved water quality, and biochemical cycling [46]. Wang et al. found significant effects of direct sunlight hours and mean radiation temperature on urban thermal comfort, using urban settlements in Toronto as an example [15]. Berardi simulated the impact of green roof retrofitting on an outdoor microclimate in the context of high settlement density, confirming the potential of green roofs as an urban heat island mitigation strategy [47]. Salata et al. used a university campus in Rome as an example to study different mitigation strategies for urban microclimate change. In contrast, an appropriate combination of cold roofs, urban vegetation and cold pavement can result in mean and maximum reductions of 2.5 and 3.5 in MOCI (Mediterranean Outdoor Comfort Index) [48]. Among climate adaptation benefits, Gunawardena et al. analyzed the impact of urban blue-green spaces on urban climate, and both were able to significantly mitigate the thermal effects of cities and enhance climate adaptation [49]. Among the applications, Shamshiri et al. deeply integrated microclimate with the agricultural sector to build advanced microclimate control and energy optimization models [50]. Cureau et al. focused on microclimate at the hyperlocal scale (refers to higher spatial resolution situations, usually on the meter scale) and monitored microclimate indicators from a human perspective in all aspects and multiple domains [28]. Buildings 2022, 12, x FOR PEER REVIEW 9 of 18 hyperlocal scale (refers to higher spatial resolution situations, usually on the meter scale) Buildings 2022, 12, 877 9 of 17 and monitored microclimate indicators from a human perspective in all aspects and mul- tiple domains [28]. Building types are also considered in the urban content; Yang et al. investigated the thermal microclimate of two building types, residential and office, and Building types are also considered in the urban content; Yang et al. investigated the thermal found that office buildings are less sensitive to thermal pressure [51]. It is concluded that microclimate of two building types, residential and office, and found that office buildings the spatial and temporal variability of the urban heat island effect at the local scale can are less sensitive to thermal pressure [51]. It is concluded that the spatial and temporal have different effects on building energy efficiency. variability of the urban heat island effect at the local scale can have different effects on The urban microclimate continued to develop rapidly during this period, and its re- building energy efficiency. search scope and methods were further expanded. Research results continued to increase, The urban microclimate continued to develop rapidly during this period, and its with research on elements, scale and development strategies of urban microclimate, research scope and methods were further expanded. Research results continued to in- closely following ecological issues, and more in-depth interdisciplinary directions gradu- crease, with research on elements, scale and development strategies of urban microclimate, ally emerged, forming a diversified research direction. closely following ecological issues, and more in-depth interdisciplinary directions gradually emerged, forming a diversified research direction. 4. Hot Spots and Trends in Urban Microclimate Research 4.1. Distribution of Research Hotspots Based on Keyword Clustering 4. Hot Spots and Trends in Urban Microclimate Research 4.1. Distribution of Research Hotspots Based on Keyword Clustering Word frequency analysis of literature keywords is commonly used in bibliometrics to reveal the distribution of research hotspots [19]. The graphical analysis of VOSviewer Word frequency analysis of literature keywords is commonly used in bibliometrics to can reflect the relationship between each important node, topic and keyword more visu- reveal the distribution of research hotspots [19]. The graphical analysis of VOSviewer can ally [52]. First, set the statistic value of word frequency to the threshold of 30, then select reflect the relationship between each important node, topic and keyword more visually [52]. the top 110 high-frequency keywords to draw the urban microclimate research keyword First, set the statistic value of word frequency to the threshold of 30, then select the top 110 co-occurrence network mapping (Figure 6) and annual overlap mapping (Figure 7). Sev- high-frequency keywords to draw the urban microclimate research keyword co-occurrence eral keywords with high word frequency were temperature, climate, vegetation, outdoor network mapping (Figure 6) and annual overlap mapping (Figure 7). Several keywords thermal comfort, and urban heat island. with high word frequency were temperature, climate, vegetation, outdoor thermal comfort, and urban heat island. Figure 6. Keyword co-occurrence network mapping for urban microclimate research. Figure 6. Keyword co-occurrence network mapping for urban microclimate research. Buildings 2022, 12, x FOR PEER REVIEW 10 of 18 Buildings 2022, 12, 877 10 of 17 Figure 7. Annual overlap mapping of urban microclimate studies. Figure 7. Annual overlap mapping of urban microclimate studies. In the keyword co-occurrence network view (Figure 6), the four-word nodes of temper- In the keyword co-occurrence network view (Figure 6), the four-word nodes of tem- ature, vegetation, model, and energy are the largest and the most frequent. Around these perature, vegetation, model, and energy are the largest and the most frequent. Around four core concepts, other high-frequency keywords based on co-occurrence relationships these four core concepts, other high-frequency keywords based on co-occurrence relation- present four main research clusters: (1) Green: Focus on urban microclimate and urban ships present four main research clusters: (1) Green: Focus on urban microclimate and environment, urban space, and other research. The high-frequency words include climate, urban environment, urban space, and other research. The high-frequency words include outdoor thermal comfort, environment and adaptation. From the word frequency, the climate, outdoor thermal comfort, environment and adaptation. From the word fre- research objects focus on urban geometry, hot, environment, and summer, the purpose of quency, the research objects focus on urban geometry, hot, environment, and summer, the the research is mainly concerned with adaptation, orientation, and perception, and the purpose of the research is mainly concerned with adaptation, orientation, and perception, research methods involve design and ENVI-met simulation; (2) Red: Research exploring the relationshipand the between re the search natural metho andd urban s involve desig environments. n and High-fr ENVequency I-met simula words tion; include (2) Red: Research urban heat exp island, loring climate the re change lationship and b urbanization. etween the nat The ustudy ral and object urban env is related ironto msurface ents. High-frequency temperature, ecosystem services, and green infrastructure regarding word frequency. It words include urban heat island, climate change and urbanization. The study object is focuses on health, mitigation, and land use. The research methods mainly involve covering related to surface temperature, ecosystem services, and green infrastructure regarding and remote sensing; (3) Blue: The study of urban microclimate modelling. High-frequency word frequency. It focuses on health, mitigation, and land use. The research methods words include simulation, street canyon, and air quality. The main objects of interest are mainly involve covering and remote sensing; (3) Blue: The study of urban microclimate density, pollution, and ventilation in terms of word frequency. The research methods are modelling. High-frequency words include simulation, street canyon, and air quality. The mainly CFD methods and prediction; (4) Yellow: In the study of urban energy consumption, main objects of interest are density, pollution, and ventilation in terms of word frequency. its high-frequency words are consumption and albedo. The main objects of concern are the The research methods are mainly CFD methods and prediction; (4) Yellow: In the study green roof and shade trees. of urban energy consumption, its high-frequency words are consumption and albedo. The From the year analysis (Figure 7), the high-frequency words that appeared earlier main objects of concern are the green roof and shade trees. (before 2010) include temperature, climate, vegetation and urbanization. Early urban micro- From the year analysis (Figure 7), the high-frequency words that appeared earlier climate research focused on integrated research with other disciplines such as environment, (before 2010) include temperature, climate, vegetation and urbanization. Early urban mi- and then outdoor thermal comfort, simulation, and surface temperature were proposed, croclimate research focused on integrated research with other disciplines such as environ- and the research objects and contents were further refined. Since 2016, the high-frequency ment, and then outdoor thermal comfort, simulation, and surface temperature were pro- words have been consumption, radiation, ventilation, ecosystem and CFD. Compared with posed, and the research objects and contents were further refined. Since 2016, the high- the previous stages, the research perspective is more macroscopic, and new concepts and frequency words have been consumption, radiation, ventilation, ecosystem and CFD. technologies are gradually applied. Compared with the previous stages, the research perspective is more macroscopic, and new concepts and technologies are gradually applied. 4.2. Evolution of Research Hotspots Based on Annual Overlap Buildings 2022, 12, x FOR PEER REVIEW 11 of 18 The Time view function in CiteSpace enables the visual analysis of evolutionary paths [23], which helps discover the turning time points of research and the critical litera- ture of the corresponding period. The timeline view reflects the distribution of keywords with high centrality over different years. The size of the circles in Figure 8 reflects the high level of keyword centrality. Nodes with higher centrality have a more significant influ- ence. If the keywords in a time zone are intensive, there are more research results in this period. The timeline view can also analyze the relationship among different clusters. In this paper, we use CiteSpace’s keyword analysis, set the time slice to 1 year, and Buildings 2022, 12, 877 11 of 17 plot the time-zoned axes of research in different periods (Figure 8) to analyze the relation- ship between each cluster and analyze the importance of different categories in different periods. Ten categories of relevant research hotspots were obtained, namely #0 human 4.2. Evolution of Research Hotspots Based on Annual Overlap thermal comfort, #1 thermal performance, #2 heatwave, #3 outdoor thermal comfort, #4 The Time view function in CiteSpace enables the visual analysis of evolutionary green infrastructure, and #5 urban trees, #6 grills, #7 urban morphology, #8 green CTTC paths [23], which helps discover the turning time points of research and the critical literature (cluster thermal time constant) model, #9 atmospheric pollution. The topics include heat, of the corresponding period. The timeline view reflects the distribution of keywords with heat balance equations, environment, ecology, urban geometry, modelling, and meteorol- high centrality over different years. The size of the circles in Figure 8 reflects the high level ogy. Human thermal comfort is the cluster with the most prolonged duration, the highest of keyword centrality. Nodes with higher centrality have a more significant influence. If keyword cen the keywords tral in ita y an time d th zone e most s are intensive, ignifican ther t ine flar uence o e moren r other c esearch lrus esults ters, which in this period. is the focus The timeline view can also analyze the relationship among different clusters. of urban microclimate research. Figure 8. Time-zoned axial mapping of urban microclimate studies (top ten categories). Figure 8. Time-zoned axial mapping of urban microclimate studies (top ten categories). In this paper, we use CiteSpace’s keyword analysis, set the time slice to 1 year, and plot 4.3. Research Hotspot Prediction Based on Keyword Emergence the time-zoned axes of research in different periods (Figure 8) to analyze the relationship between each cluster and analyze the importance of different categories in different periods. Keyword burst detection can detect changes in the frequency of keywords over a Ten categories of relevant research hotspots were obtained, namely #0 human thermal certain period and derive promising research directions [18]. In the study from 1990 to comfort, #1 thermal performance, #2 heatwave, #3 outdoor thermal comfort, #4 green 2021, the 24 burst keywords with the highest frequency were selected for study (Table 2). infrastructure, and #5 urban trees, #6 grills, #7 urban morphology, #8 green CTTC (cluster Before 2006, the main focus was on urban design and land planning. From 2006 to 2016, thermal time constant) model, #9 atmospheric pollution. The topics include heat, heat the research was extended towards landscape, temperature, hot, dry climate, and param- balance equations, environment, ecology, urban geometry, modelling, and meteorology. eterization, and from 2016 to date, related research has focused more on morphology and Human thermal comfort is the cluster with the most prolonged duration, the highest keyword centrality and the most significant influence on other clusters, which is the focus materials. of urban microclimate research. 4.3. Research Hotspot Prediction Based on Keyword Emergence Keyword burst detection can detect changes in the frequency of keywords over a certain period and derive promising research directions [18]. In the study from 1990 to 2021, the 24 burst keywords with the highest frequency were selected for study (Table 2). Before 2006, the main focus was on urban design and land planning. From 2006 to 2016, the research was extended towards landscape, temperature, hot, dry climate, and param- eterization, and from 2016 to date, related research has focused more on morphology and materials. This paper further analyses the keywords that appeared in the last five years (2017– 2022) and the strength and timing of their appearance to mitigate the lag in the bibliometric results and more accurately analyze the research trends in urban microclimate. As shown in Table 3, coating, atmosphere boundary layer, Mediterranean climate, shading and energy efficiency are new topics in recent years. Buildings 2022, 12, x FOR PEER REVIEW 12 of 18 Table 2. Top 24 most cited keywords in urban microclimate research in1990–2021. Buildings 2022, 12, 877 12 of 17 Keywords Strength Start End 1990----------------------------------------------------------2021 Buildings 2022, 12, x FOR PEER REVIEW 12 of 18 Urban design 5.2354 1992 2017 Landscape 4.4904 2006 2014 Table 2. Top 24 most cited keywords in urban microclimate research in 1990–2021. Community 4.2531 2006 2017 Table 2. Top 24 most cited keywords in urban microclimate research in1990–2021. Parameterization 4.093 2008 2014 Keywords Tempera Strengthture 8Start.2872 2008 End 2013 1990———————————————————-2021 Keywords Strength Start End 1990----------------------------------------------------------2021 Air pollution 4.2191 2008 2012 Urban design Urban desi 5.2354 gn 5.2 1992 354 1992 2017 2017 Thermal performance 3.1075 2009 2011 Landscape Landsca 4.4904pe 4.4 2006904 2006 20142014 Urban planning 4.0628 2011 2014 Community Communi 4.2531ty 4.2 2006531 2006 20172017 Impervious surface 3.5086 2011 2016 ParameterizationParameterizat 4.093ion 4.2008093 2008 20142014 Land use 7.5759 2012 2017 Temperature Tempera 8.2872ture 8.2 2008872 2008 20132013 Green roof 4.3646 2013 2017 Air pollution Air poll4.2191 ution 4.2 2008 191 2008 2012 2012 Thermal performance ThermaEvapot l performa ransp 3.1075iratince on 3 3.1 2009.8 075 072 2009 2013 2011 2011 2015 Urban planning The hot Urban p , dry cl l4.0628 anning imate 44 .0 2011 .8 628 018 2011 2013 2014 2014 2016 Impervious surfaceImpervious surfa 3.5086ce 3.5 2011 086 2011 2016 2016 Urbanization 3.1877 2014 2015 Land use Land use 7.5759 7.5 2012 759 2012 2017 2017 GI 3.3411 2015 2017 Green roof Green roof 4.3646 4.3 2013 646 2013 2017 2017 Biodiversity 3.1095 2016 2017 EvapotranspirationEvapotransp 3.8072iration 3.8 2013072 2013 20152015 Cool material 4.0713 2017 2018 The hot, dry climate The hot, dry cl 4.8018 imate 4.8 2013 018 2013 2016 2016 Thermal sensation 3.5097 2018 2019 Urbanization Urbaniza 3.1877tion 3.1 2014877 2014 20152015 Urban heat 3.5198 2019 2021 GI 3.3411 2015 2017 GI 3.3411 2015 2017 Equivalent temperature 3.3522 2019 2019 Biodiversity 3.1095 2016 2017 Biodiversity 3.1095 2016 2017 Energy performance 3.7053 2019 2019 Cool material 4.0713 2017 2018 Cool material 4.0713 2017 2018 Aspect ratio 4.1644 2019 2021 Thermal sensation 3.5097 2018 2019 Thermal sensation 3.5097 2018 2019 Urban park 3.9219 2020 2021 Urban heat 3.5198 2019 2021 Urban heat 3.5198 2019 2021 The blue line indicates the period from 1990 to 2021, with each small segment representing one year; Equivalent temperature 3.3522 2019 2019 Equivalent temperature 3.3522 2019 2019 the red thickened line indicates the period of the sudden growth of the corresponding keyword, Energy performance 3.7053 2019 2019 Energy performance 3.7053 2019 2019 with the red appearing and ending positions representing its starting and ending years, and the Aspect ratio 4.1644 2019 2021 Aspect ratio 4 longer the red .1644 2019 line represents 2021 , the longer the sudden growth of the keyword is maintained. Urban park 3.9219 2020 2021 Urban park 3.9219 2020 2021 This paper further analyses the keywords that appeared in the last five years (2017– The blue line indicates the period from 1990 to 2021, with each small segment representing one year; The blue line indicates the period from 1990 to 2021, with each small segment representing one year; the red the red thickened line indicates the period of the sudden growth of the corresponding keyword, 2022) and the strength and timing of their appearance to mitigate the lag in the biblio- thickened line indicates the period of the sudden growth of the corresponding keyword, with the red appearing with the red appearing and ending positions representing its starting and ending years, and the and ending positions metric r repr esults and more esenting its startacc ingu and rate ending ly analy years, ze thand e rese the arc longer h trends the rin ur ed lin ban microc e represents, limate the longer . As longer the red line represents, the longer the sudden growth of the keyword is maintained. the sudden growth of the keyword is maintained. shown in Table 3, coating, atmosphere boundary layer, Mediterranean climate, shading and energy efficiency are new topics in recent years. This paper further analyses the keywords that appeared in the last five years (2017– Table 3. Keywords highlighting strength and timing of urban microclimate research in 2017–2022. 2022) and the strength and timing of their appearance to mitigate the lag in the biblio- Table 3. Keywords highlighting strength and timing of urban microclimate research in 2017–2022. metric results and more accurately analyze the research trends in urban microclimate. As Keywords Strength Begin End 2017————————2022 Keywords St shown in Table 3, corengt ath ing , atmosphere bBegin oundary layeEnd r, Mediterr2017 an-- ean c------ lim----- at-- e, --s-- h-- adin---2g 022 and energy efficiency are new topics in recent years. Coating 2.0568 2017 2019 Coating 2.0568 2017 2019 Atmosphere boundary layer 1.9597 2017 2018 Atmosphere boundary layer 1.9597 2017 2018 Table 3. Keywords highlighting strength and timing of urban microclimate research in 2017–2022. Mediterranean climate 2.0746 2017 2018 Mediterranean climate 2.0746 2017 2018 Shading 2.8963 2018 2019 KSehywords St ading 2re.ngt8963 h Begin 2018 End 2019 2017------------------------2022 Energy efficiency 2.2226 2020 2022 Energy effCoatinig 2 ciency .20.568 2226 2017 2020 2019 2022 The blue line indicates the period from 2017 to 2022, with each small segment representing one year; the red Atmosphere boundary layer The blue line in1 dicate .9597 s the period from 2017 2017 to 2022, with 2018 each small segment representing one year; thickened line indicates the period of the sudden growth of the corresponding keyword, with the red appearing the red thickened line indicates the period of the sudden growth of the corresponding keyword, Mediterranean climate 2.0746 2017 2018 and ending positions representing its starting and ending years, and the longer the red line represents, the longer with the red appearing and ending positions representing its starting and ending years, and the Shading 2.8963 2018 2019 the sudden growth of the keyword is maintained. longer the red line represents, the longer the sudden growth of the keyword is maintained. Energy efficiency 2.2226 2020 2022 The blue line indicates the period from 2017 to 2022, with each small segment representing one year; CiteSpace provides two metrics, module value (Q value) and average profile value CiteSpace provides two metrics, module value (Q value) and average profile value (S value), the red thickened line indicates the period of the sudden growth of the corresponding keyword, based on the clarity of network structure and clustering, which can be used to judge the effectiveness (S value), based on the clarity of network structure and clustering, which can be used to with the red appearing and ending positions representing its starting and ending years, and the of mapping. In general, Q values are generally in the interval [0, 1), Q > 0.3 means that the delineated longer the red line represents, the longer the sudden growth of the keyword is maintained. judge the effectiveness of mapping. In general, Q values are generally in the interval [0, 1), association structure is significant, and the clustering is efficient and convincing when the S value is Q > 0.3 means that the delineated association structure is significant, and the clustering is CiteSpace provides two metrics, module value (Q value) and average profile value (S value), efficient and convincing when the S value is 0.7. The co-occurrence network relationship is based on the clarity of network structure and clustering, which can be used to judge the effectiveness of mapping. In general, Q values are generally in the interval [0, 1), Q > 0.3 means that the delineated simplified into clusters and labelled, and the top 10 clusters are listed with cluster module association structure is significant, and the clustering is efficient and convincing when the S value is value (Q value) of 0.8013 > 0.3 and average profile value (S value) of 0.9239 > 0.7, indicating that the clusters lie in the confidence interval and the clustering quality is high. Table 4 and Figure 9 show a more in-depth analysis of the specifics contained in each cluster name. Buildings 2022, 12, 877 13 of 17 Table 4. Keyword clustering of urban microclimate research in the last five years. Cluster Name Size Profile Value Year Main Keywords urban ecosystems; land surface temperature; air 0. Urban ecology 35 0.913 2018 temperature; ecosystem services; indicators; physical health; global climate regulation 1. NDVI (Normalized surface urban heat island; physical activity; citizen science; 30 0.936 2018 Difference Vegetation Index) biological invasion; convective heat flux agent-based model; ventilation path; twining plants; small 2. Particulate matter 30 0.882 2018 urban planting design; geographic information system (gis); single planting cool pavement; microclimate model; thermal behavior; physiological equivalent temperature index; 3. Thermal comfort 29 0.857 2018 micrometeorological measurements; hedonic modelling; outdoor microclimate map turbulence; urban canyon; weather research and 4. Heat mitigation 26 0.918 2018 forecasting model; low-rise housing; humid tropics region; office buildings; height-to-width ratio; passive design mitigation; integrated environmental assessment; 5. ENVI-met 25 0.953 2018 residential district; direct shortwave radiation scattering; wind speed reduction; plant geometry; plant physiology tree species; air relative humidity; reduced soil water 6. Urban trees 23 0.886 2018 availability; antioxidants; surface-energy balance; light; latent heat flux; sap flow dynamics thermal adaptation; form indices; cooling energy 7. EnergyPlus 23 0.879 2018 consumption; generic residential districts; OpenFOAM building energy simulation; computational fluid dynamics; 8. Thermal network model 23 0.946 2017 vertical greenery system; CoMFA human heat balance model; lumped thermal parameter Buildings 2022, 12, x FOR PEER REVIEW 14 of 18 green walls; urban agriculture; urbanization; Teb; urban 9. Irrigation 21 0.872 2017 water cycle; subtropical monsoon climate; vertical farming Figure 9. Cluster mapping of urban microclimate research keywords 2017–2022. Figure 9. Cluster mapping of urban microclimate research keywords 2017–2022. Those with greater frequency (>200 times) are temperature, urban heat island, ther- mal comfort, vegetation, and environment. Those with more vital centrality (greater than or equal to 0.15) are energy-saving, cooling load, biometeorological assessment, roof, cover, and heat stress. 5. General Forecast of Trends in Research Characteristics 5.1. Multi-Scale Urban Climate Simulation Study Computer simulations can integrate the effects of different meteorological conditions on cities, buildings and humans, and play an essential role in urban microclimate assess- ment [53]. However, most studies have focused on micro-scale outdoor human thermal comfort using ENVI-met, and more multi-scale model coupling is needed at the urban level [54], e.g., the high-resolution urban climate model PALM-4U [55], and the urban multi-scale environmental predictor UMEP [56]. Future research could combine models at different scales with climate zones, and there are already nesting ENVI-met into local climate zones LCZ [57], WUDAPT [58], mesoscale models (e.g., WRF), or larger scale model domains [57], intending to achieve more scientific strategic plans for cities to im- plement climate change. Buildings 2022, 12, 877 14 of 17 Those with greater frequency (>200 times) are temperature, urban heat island, thermal comfort, vegetation, and environment. Those with more vital centrality (greater than or equal to 0.15) are energy-saving, cooling load, biometeorological assessment, roof, cover, and heat stress. 5. General Forecast of Trends in Research Characteristics 5.1. Multi-Scale Urban Climate Simulation Study Computer simulations can integrate the effects of different meteorological conditions on cities, buildings and humans, and play an essential role in urban microclimate assess- ment [53]. However, most studies have focused on micro-scale outdoor human thermal comfort using ENVI-met, and more multi-scale model coupling is needed at the urban level [54], e.g., the high-resolution urban climate model PALM-4U [55], and the urban multi-scale environmental predictor UMEP [56]. Future research could combine models at different scales with climate zones, and there are already nesting ENVI-met into local climate zones LCZ [57], WUDAPT [58], mesoscale models (e.g., WRF), or larger scale model domains [57], intending to achieve more scientific strategic plans for cities to implement climate change. 5.2. Multi-Factor Urban Microclimate Impact Study An urban microclimate is influenced by various factors such as physical and social factors, and scholars have used methods such as fluid dynamics (CFD) [12] and weather research and forecasting (WRF) [59] to study factors such as wind speed and direction [60], building materials [61], temperature [62] and humidity [63] to determine urban micro- climate parameters. Since the influencing factors of urban microclimates involve many aspects, there are still many research blind spots in the existing literature, which need to be further sorted out and comparatively studied to build a more systematic urban microclimate model, and then form a systematic scientific cycle system. 5.3. Multi-Policy Urban Microclimate Guidance Study Compared with “smart cities” and “low-carbon cities”, there is a lack of clear policy guidance on the urban microclimate [64], and the improvement of urban environmental comfort by microclimate optimization has not been considered. In the future, the role of the urban microclimate can be highlighted in the ambient air quality standards or green building guidelines. 6. Conclusions In this paper, we use WOS online analysis with bibliometric data analysis of CiteSpace and VOSviewer to study the literature related to the urban microclimate from 1990 to 2021, and visualize and analyze the characteristics of literature distribution, research development stages and research hotspot trends in different periods, disciplines and country situations and conclude the following: (1) The urban microclimate research literature volume shows prominent multidisci- plinary and comprehensive characteristics. The overall number of publications shows an increasing trend, and four leading research clusters are formed: theoretical research on the urban environment and urban space, research on the natural environment and urban environment, research on urban microclimate modelling, and research on urban energy consumption; (2) Urban microclimate research can be divided into four stages: nascent exploration, model quantification, diversified development, and ecological synergy. In terms of lit- erature and discipline distribution, research hotspots and focus, they show the “rise of multidisciplinary and urban studies”, “application of numerical quantification and model evaluation”, “maturation of system and expansion of research breadth”, and “focus on eco-synergy with multiple types of elements”; Buildings 2022, 12, 877 15 of 17 (3) The knowledge mapping characteristics of research hotspots based on keyword clustering, annual overlap, and keyword highlighting show that urban microclimate re- search has three hotspot trends—multi-scale urban climate simulation research, multi- element urban microclimate impact research, and multi-policy urban microclimate guid- ance research. Urban microclimate research has achieved specific results since 1990, but there are still problems such as incomplete policies and insufficient elements. The academic community needs more innovations in urban microclimate theory and practice to construct a theoretical system of the urban microclimate and solve the urban microclimate’s complex and diverse practical problems. Author Contributions: Conceptualization and writing, Y.Z.; methodology and visualization, N.A.; audit and funding acquisition, J.Y. All authors have read and agreed to the published version of the manuscript. Funding: National Natural Science Foundation of China under Grant NO. 51908410; the Shanghai Municipal Science and Technology Major Project under Grant NO. 2021SHZDZX0100; the Funda- mental Research Funds for the Central Universities. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest. References 1. Lin, J.; Brown, R. Integrating Microclimate into Landscape Architecture for Outdoor Thermal Comfort: A Systematic Review. Land 2021, 10, 196. 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Journal

BuildingsMultidisciplinary Digital Publishing Institute

Published: Jun 22, 2022

Keywords: bibliometrics; citespace; development stages; distribution characteristics; research trends; urban microclimate; vosviewer

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