Towards Digitalized Urban Planning and Design of Low-Carbon Cities: Evolution and Application Review of Assessment Tools

Abstract

Facing the challenges of global climate change, the construction of low-carbon cities has become an inevitable pathway, where carbon emission assessment is a critical part to the transition towards digitalized urban planning and design of low-carbon cities. However, comprehensive review on carbon assessment tools applied to urban planning and design is absent. As a response, this paper selected and reviewed typical digital assessment tools of carbon emissions at both the city and district/neighborhood scales, and summarized their measuring dimensions and reference data. Currently, tools based on energy system planning and operational energy simulation dominate the field, while tools for carbon emission and carbon sink estimations based on land use types or materials are rapidly developing due to the increasing refinement of carbon emission assessments and shifts of decarbonization policies. At present, these tools are primarily used in energy planning and design, governmental decision-making, and building structural design and material choice, and their application in urban planning and design practice, especially in the early stages, remains limited. Hence, this study further underscored the limitations and potential development directions of existing carbon emission assessment tools by case studying low-carbon practices worldwide that have not utilized digital assessment tools—in the future, improving tools' flexibility and adaptability for diverse scenarios, building comprehensive databases, incorporating the calculation of operational carbon, embedded carbon, and carbon sinks, and aligning with the needs for multi-dimensional, multi-criteria, and full-process assessments should be put into more efforts.

● Summarizes five categories of carbon emission assessment tools at both city and district/neighborhood scales

● Summarizes the application scenarios, advantages and disadvantages, measuring dimensions, and reference data of the tools

● Points out the limitations of the tools and proposes the future development trend towards multi-disciplinary, multi-criteria, full-process, and intelligent estimations

Graphical abstract

Keywords

Low Carbon Cities / Carbon Emission / Carbon Emission Assessment Tools / Urban Planning and Design / Digitalization / Carbon Sink

1 Introduction

With the promotion of carbon neutrality and carbon peaking goals, the construction of low-carbon cities and related quantitative assessments have become hot topics in the field of urban planning and design^[1][2]. One important driver for promoting low-carbon concepts is global climate change. The Intergovernmental Panel on Climate Change (IPCC) points out that the net emissions of anthropogenic greenhouse gases have continued to rise over the past decade, with the average annual emissions higher than any previous decade^[3]. Without additional climate change mitigation policies, global warming could lead to a temperature increase of 3.5℃ by 2100^[4]. Therefore, advancing the implementation of low carbon policies is of utmost urgency.

Currently, the focus of low-carbon urban construction at home and abroad has shifted from macro-level conceptual introduction and review towards the analysis of specific issues and the application of digital technologies at the micro level^[5]~[7]. As the first step of carbon reduction actions, precise quantitative assessment of carbon emissions has increasingly been incorporated into urban planning and design. Analyzing the impact of urban spatial planning on carbon emissions and estimating the effectiveness of carbon-neutral action plans can help determine carbon reduction objectives and provide guidance for policy-making and planning design^[8]. Emerging frameworks and tools for carbon emission assessment applicable at varied scales^[9] enable digital carbon assessment for planning strategies and design schemes, progressively promoting the cross-integration of energy planning and urban planning design^[10]~[12].

However, existing reviews on carbon assessment tools have several limitations. First, these reviews primarily focus on energy system planning and design, as well as life cycle assessments of buildings. Under climate policies, carbon emission has become a new quantitative indicator in urban planning and design practice. Since carbon assessment tools serving early-stage planning and design have been developed and applied in practice in recent years^[13][14], there is a lack of comprehensive reviews on carbon assessment tools for urban planning strategies and design schemes^[15][16]. Second, existing reviews often focus on a single scale or discipline, lacking cross-scale and interdisciplinary systematic analysis^[13][14][17] from a macro-level comprehensive perspective that could better guide planners and designers in selecting appropriate carbon assessment tools based on specific usage scenarios and stages. Third, although the development of assessment tools sees a diversification trend, these tools are still less used in planning and design practice, the reasons behind which are worth exploring; in addition, the research on the application limitations and future development directions of different sorts of carbon assessment tools remains insufficient^[18]~[20].

To address the aforementioned limitations, this paper systematically categorizes, reviews, and compares the functional features, assessment dimensions, and applicable scenarios of existing assessment tools for digitalized low-carbon urban planning and design, and discusses their application shortcomings in planning and design practice. Finally, the paper summarizes the development trends of various assessment tools and points out potential development directions to provide references for future research and practice of low-carbon planning and design.

2 Research Methods

Typical carbon assessment tools as the research subjects in this study were selected through the literature screening and validation by Google Scholar. Google Scholar offers extensive coverage, including both Chinese and English literature in the Architecture category from core-collection journals (e.g., SCI, A&HCI) and non-core collection journals, as well as conference papers.

First, initial searching was conducted by using both Chinese and English keywords, including "carbon assessment tools," "carbon emission evaluation," "low carbon urban planning," "low carbon urban design," "low-carbon city," "urban energy planning," "carbon-neutral city," "碳评估工具," "低碳评估指标体系," "碳评估工具综述," "零碳城市," "零碳规划," "减碳技术, " and "碳中和城市规划." This study retrieved literature published after January 1, 1980 to December 31, 2023. And then frequently mentioned carbon assessment tools were selected from the search results. Citation counts and frequency of mentions reflect, to a certain extent, the gained attention and application of the tools. Meanwhile, the relatively new tools that were less mentioned in the retrieved literature were compared with conventionally typical tools, to select the relatively mature, highly innovative ones that can represent recent development trends. Finally, the obtained tools were preliminarily categorized, and tools with well-documented official descriptions in each category were retained for the final analysis.

3 Research Results

3.1 Overview of Assessment Tools

A total of 19 assessment tools were finally selected for the study, which are categorized into two major types by scale and function (Tab.1). 1) Urban-scale tools that mainly aid in the formulation of larger-scale planning policies, by predicting carbon emissions, financial costs, and environmental impacts under different energy planning and master planning policy measures or various scenarios based on macroeconomic data and energy consumption data. 2) District-/neighborhood-scale tools that are mainly used to evaluate planning and design schemes at smaller scales^[21] by predicting carbon emissions based on information such as building form and attributes, and climatic data.

The development and evolution of carbon assessment tools are closely related to the development of low-carbon policies and associated demands (Fig.1). Carbon assessment tools at both city and district/neighborhood scales have been initially developed since the 1980s, witnessing a significant increase in number over the past decade, especially the district-/neighborhood-scale assessment tools. This reflects the trend of refined low-carbon assessments and the shift in decarbonization policy focus—from reducing energy demand and the carbon intensity of energy systems towards decreasing embodied carbon emissions and promoting ecological restoration to enhance carbon sinks^[22].

3.2 City-Scale Carbon Assessment Tools

City-scale carbon assessment tools can be roughly classified into three categories by function: energy system and policy analysis, urban climate policy analysis, and carbon emission prediction based on land use types.

1) Tools for energy system and policy analysis. These tools are used to assess carbon emissions under different energy planning strategies and scenarios, predicting funding, costs, and the impact of environmental changes, primarily in areas of energy system, electricity, heating and cooling, etc.

2) Tools for urban climate policy analysis. These tools are of high comprehensiveness and typically used for cross-sectoral planning in construction, transportation, industry, etc.; although the numerical values used in calculations are relatively coarse, they can provide an overall picture to help decision-makers choose effective climate intervention measures.

3) Tools for carbon emission prediction based on land use types. These tools predict a city's carbon emissions under different development scenarios based on the changes of land use types of real plots, reflecting high-precision geographic spatial distribution characteristics and interactions by analyzing energy consumption data of different land use types. In recent years, many researchers have started exploring more refined carbon emission prediction methods^[23], but which are still in early stages and require users having a high level of expertise (academic researchers mainly).

In summary, city-scale carbon assessment tools guide government policy-making by predicting carbon emissions. With the increasing trend of refined assessment of carbon emissions, predictions based on macro statistical data are relatively mature, whereas those upon local urban spatial characteristics requiring further efforts.

3.3 District-/neighborhood-Scale Carbon Assessment Tools

Over the past decade, carbon assessment tools at the district-/neighborhood-scale have become a focus of attention for universities and research institutions^[10]. They combine energy system analysis and energy demand prediction to evaluate the carbon emissions and environmental performance of planning and design schemes^[11][12][24]. Such tools can generally be divided into two categories: operational energy consumption simulation, and embodied carbon and carbon sink estimation.

1) Tools for operational energy consumption simulation. These tools are often developed in earlier years, and mainly used to predict the operational energy consumption of buildings and districts based on climate data and building forms and attributes. Some of such tools can assist early-stage design schemes from multiple sustainable dimensions (including carbon assessment), while others focus on predicting energy consumption and optimizing energy systems at the district/neighborhood scale and support high-precision real-time prediction of operational carbon emissions, considering urban morphological factors in energy consumption calculations.

2) Tools for embodied carbon and carbon sink estimation. Although a few operational energy consumption simulation tools (such as umi^[25] and CESAR^[26]) also support embodied carbon assessment, they can simply quantify the embodied energy consumption generated by building construction and renovation, yet without considering landscapes and other urban environmental factors. As full-life-cycle assessment of urban construction has been paid more and more attention^[23], emerging carbon assessment tools increasing target assessing embodied carbon from operational carbon. They can predict embodied carbon and carbon sinks of projects at various scales based on data of land use types and materials^[19][27], offering a more comprehensive perspective for the environmental impacts of large-scale urban planning and design projects. Among them, Urban Decarb^[28] can conveniently perform comparative analysis of the differences of carbon emissions and costs between various design schemes, and are suitable for diverse types of design projects. The Carbon Conscience tool developed by Sasaki^[29] can calculate the embodied carbon generated by buildings and landscapes separately, supporting not only the estimation of carbon emissions and environmental impacts per unit under given land use scenarios at the early planning stages but also the calculation of carbon emissions and carbon sinks by building types, structures, materials, etc., at later design stages.

In summary, there is still a lack of comprehensive assessment tools at the district/neighborhood scale that consider both operational carbon and embodied carbon, while also integrating data of climate, energy systems, land use types, and materials.

3.4 Measuring Dimensions and Reference Data

Based on the energy demands, carbon emissions, and sustainable development elements of different sectors in cities, the study summarizes the 12 and 9 measuring dimensions of the city-scale and district-/neighborhood-scale carbon assessment tools, respectively (Tab.2).

For the city-scale tools, building, industrial and manufacturing, commercial and business, and transportation are the main sectors of urban carbon emissions^[19], which also constitute common dimensions among the carbon assessment tools. Other major dimensions include electricity, sewage treatment, and solid waste management.

City-scale carbon assessment tools quantitatively evaluate the above dimensions mainly based on macro energy consumption data in economy and land use. Both such types of data have long updating cycles and low accessibility that would fundamentally affect the accuracy and applicability of assessment results.

1) Economic energy consumption data are typically sourced from annual government statistical reports, and often updated every 2 or 3 years, resulting in a certain lag in data acquisition^[30][31]. So for the globally universal tools, such as LEAP^[32] and CURB^[30], timely data acquisition and updates across global cities poses a significant challenge. To ensure data accuracy, these tools require users to input data from various sectors of the case city. On the contrary, tools developed for a specific country or region, such as ALasSken^[31], are easier to access and update data from the government, and they are usually equipped with built-in databases that do not require additional data input from the user. Additionally, tools like LEAP allow users to develop extra functional programs based on cities' realities and specific assessment needs, enhancing the applicability of assessment tools.

2) Land use energy consumption data consist of land use type data and carbon emission coefficient for land use types. Land use type data also come from government agencies and are annually updated. However, carbon emission coefficients must be precisely measured based on the specific land use situations of the given city, which is crucial for the accuracy of carbon emission predictions.

At the district/neighborhood scale, simulation tools for operational energy consumption are mainly used to predict energy demand and usually combined with microclimate and thermal comfort assessments. Some tools can support energy system analysis and renewable energy assessments. Tools for early stages of planning and design also include other sustainable analysis modules (such as daylighting), providing designers with a more comprehensive lenses. In contrast, the embodied carbon and carbon sink estimation tools measure narrower dimensions, primarily focusing on buildings and landscapes, with less consideration of transportation, infrastructure, etc.

The tools for operation energy consumption simulation mainly refer to building form and attributes data and climate data, and the ones for embodied carbon and carbon sink estimation primarily refer to data of the land use types, materials, and structures of buildings, landscapes, and infrastructure (Tab.3).

1) Climate data and building form and attributes data are accessible from meteorological statistics websites, OpenStreetMap, and official databases of cities^[33]. Usually these data are input by users; in cases where the data do not align with the reality, designers need to validate and adjust by collecting data from additional sources such as satellite images, so as to improve data accuracy. The tools mainly for energy system optimization and demand-supply analysis (e.g., CEA^[34], CitySim^[35], CESAR^[26], etc.) can utilize the information of building energy supply system types and user behavior data to conduct high-accuracy energy consumption calculation and prediction. These data can be extracted from OpenStreetMap, but which usually does not cover all the urban areas of a given city, requiring the supplement with census data for some tools^[26].

2) There is no directly available data of land use type, site area, materials, site management, etc., for the embodied carbon and carbon sink estimation tools, which requires an integration of multidisciplinary knowledge with existing research and practical experiences. Meanwhile, databases need to be continuously updated with new knowledge and experience to meet the diverse project needs. For example, Carbon Conscience has established separate specialized building and landscape datasets^[36]—the building dataset references existing tools for full-life cycle assessment of buildings, while the landscape dataset is derived from relevant academic research papers. In the absence of direct reference data, drawing on data sources from first-hand academic research effectively improves the accuracy of embodied carbon and carbon sink estimations.

4 Discussion

4.1 Application Limitations of Carbon Assessment Tools

Carbon assessment tools have developed rapidly with a variety of measuring dimensions, but their application in specific planning decisions and design practices is still limited. Compared with district-/neighborhood-scale tools, city-scale carbon assessment tools see relatively mature applications, primarily for energy planning and climate planning decision-making, with less application in the early stages of planning and design. Therefore, this study collects and compares authentic cases of low carbon practices that do not utilize assessment tools, in order to identify the shortcomings of existing assessment tools.

Due to the significant disparity between countries and cities, it is challenging to develop universal standards and strategies of carbon emission assessment. This often necessitates the creation of context-specific assessment frameworks and standards^[37], leading to the limited application of existing city-scale tools in urban planning decision-making. Cities in China and abroad have constructed their own assessment frameworks and implementation methods of low-carbon construction. For example, Tianjin, as one of China's low-carbon pilot cities, proposed its low-carbon assessment framework and indicators for urban planning with both carbon reduction and carbon sink goals^[38], and explored a carbon reduction roadmap integrated with its existing territorial spatial planning framework^[39]. Similarly, Malaysian cities have proposed their own frameworks and assessment systems of low-carbon city, to bridge the gap between government policies and the green city rating tools available in the market, so as to better guide cities in implementing carbon reduction measures^[40]. However, the inability to obtain accurate data from other case cities makes these tools fail to be employed in broader regions.

At the district/neighborhood scale, carbon emissions are typically assessed alongside indicators such as microclimate/thermal comfort and daylight potential. Multi-dimensional assessment tools like Ladybug Tools^[33] have already been effectively utilized at early stages of planning and design. Additionally, tools for embodied carbon and carbon sink estimation have become increasingly mature in the context of building materials and structural design, but their application in comprehensive urban planning and design is just beginning and gradually being incorporated into practice projects, such as Carbon Conscience^[29].

The following limitations of district-/neighborhood-scale assessment tools are worth discussing.

First, most planning and design practices still do not consider carbon emission as a key factor yet; instead, treating it only as one of the evaluation options after the completion of design scheme.

Second, most tools focus on a single aspect of carbon emissions (operational carbon, or buildings' embodied carbon). However, urban planning and design requires an overall consideration on carbon emissions and carbon sinks from multiple urban systems, such as buildings, landscapes, and transportation; also, combined use of multiple tools would easily ignore the correlations between data. Therefore, a holistic approach to the assessment is necessary to help identify trends of correlations between various components. For example, the Lihu New City Planning Project in Wuxi improved existing assessment models and constructed a new carbon-neutral assessment system, which can simultaneously assess carbon emissions and carbon sinks^[41]; in the case of the planning of Jinan Western New District, a planning scheme assessment was conducted on the accessibility of road network and the carbon emission potential of transportation^[42]. These cases mark the gap of multi-dimensional carbon emission assessments for spatial planning and design among current assessment tools.

Third, most of the existing tools focus on qualifying carbon emission, and cannot offer design optimization suggestions, low-carbon strategies, and recommended implementation methods based on the assessment results. However, practical technical roadmaps and pathways in critical to its implementation. For example, the and practical cases of seven communities, including the Xietu community and other six communities in Shanghai developed their low-carbon renewal strategies and implementation paths by using traditional methods such as status surveys, carbon emission baseline assessments, and data analysis^[43].

Finally, the district-/neighborhood-scale tools generally lack the full-process awareness and the monitoring and verification of carbon emissions during project management and operation. Some cities are currently exploring this. For instance, the Shanghai Digital Jianghai Industrial Park has constructed an overall control mechanism: by building a digital twin platform for intelligent carbon reduction, carbon emission data can be collected and fed back from aspects of building energy use, transportation, carbon sinks, etc., forming a technical framework of carbon reduction in urban neighborhoods covering the full-process from planning, construction to management and operation^[44].

In summary, both city- and district-/neighborhood-scale carbon assessment tools should improve their comprehensiveness and flexibility to make them suitable for more diverse scenarios and to assist planning and design practices more accurately and efficiently.

4.2 Trends of Carbon Assessment Tool Development

Based on the above comparative analysis, this paper summarizes the future development trends of assessment tools for digitalized low-carbon urban planning and design as follows.

First, enhancing tools' practicality by promoting the interdisciplinary integration, to provide optimized, cohesive design solutions for carbon emission issues. At both the city and district/neighborhood scales, future efforts could delve into the development of comprehensive digital assessment tools that integrate knowledge from architecture, planning, landscape, transportation, structural engineering, MEP (mechanical electrical, and plumbing), and sustainability.

Second, database construction is the key to improving the application breadth and result precision of carbon assessment tools. For city-scale tools, the open access to data from multiple sources can facilitate the database building that contain assessment standards and strategies for different countries and cities, thereby increasing the tools' flexibility and competitiveness and minimizing the waste of resources and time caused by duplicated development. Although the district-/neighborhood-scale tools share some energy and material data, establishing comprehensive and continuously updated databases remains challenging. In addition, studies using cross-scale data for refined assessments at both scales offer a new perspective for carbon assessment. For example, city-scale tools are used in bottom-up digital carbon assessments of micro sites based on land use data^[45]; using city-scale data (e.g., census data), district-/neighborhood-scale tools are employed in site-specific carbon assessments through a combination with GIS^[26][34].

Third, the research on multi-criteria low-carbon assessment needs to be deepened. The use of multi-criteria assessment methods—such as considering the complexity of circular economy and carbon tracking, and the dynamics of carbon sinks influenced by climate change and vegetation growth cycle—can maximize the simulation performance of carbon emissions of authentic projects.

Fourth, improving the economic feasibility and convenience of carbon assessment tools. In the application of carbon assessment tools, calculating the payback period and costs will help investors balance different factors to ensure that the selected solution meets the low-carbon and energy-saving requirements and is economically viable. In addition, visualized forms and displays can help investors and designers better understand the carbon emissions between different design schemes, facilitating option comparison and decision-making.

Fifth, with the advancement and widespread application of artificial intelligence (AI) technology, carbon assessment tools will also usher in the iterative innovation of intelligence in digital future. With the help of AI algorithms, large amounts of data can be processed quickly, greatly enhancing the efficiency of calculations related to energy simulation. AI can also be utilized for environmental predictions, such as forecasting climate changes by training past climate data, to better help decision makers formulate and implement low-carbon policies.

4.3 Research Limitations

This study collected carbon tools through literature screening on Google Scholar. This may have led to the exclusion of some emerging carbon assessment tools, especially those that are less mentioned in the literature but have recently arisen owning to the advent of AI. Also, in studying global low-carbon urban planning and design cases, the methods of literature review and information searching were mainly used, where a systematic approach to comprehensively examine the application cases of carbon assessment tools needs more efforts in future research.

5 Conclusions

This study systematically categorized and compared the characteristics and application of the carbon assessment tools for digitalized low-carbon urban planning and design. Overall, the application of these tools at multiple stages of planning and design is of great significance to the construction of low-carbon cities. At the policy-making stage, carbon assessment tools can predict the city's carbon emissions under different development scenarios, visions, and measures, helping decision-making on carbon reduction options. At the early stages of planning and design, many assessment tools can measure the carbon emissions of conceptual design schemes from the beginning of the project, including embodied carbon, and life-cycle carbon sinks and operational carbon. At the mid-to-late stages, many carbon assessment tools can quickly and accurately simulate the carbon emissions of design schemes. At the post-construction stage, some carbon assessment tools can continuously track the operational carbon of the project, providing constructive suggestions for future design optimization. In the future, carbon assessment tools will see advance in global applicability, multidisciplinary coverage, full life-cycle calculation, economic balance, and data visualization. The combination of AI and other intelligent technologies will greatly increase the efficiency of carbon assessment in practice and enable carbon assessment tools to better support urban planning and design practices.

References

[1] Wang, Y. , Bian, T. , & Huang, X. (2021) Research on time–space differences in the prediction of carbon peaking of China's comprehensive economic zones. Landscape Architecture Frontiers, 9 (6), 24– 43.

[2] Hewlett, M. (2014) Eco-low carbon urban planning methodology. Landscape Architecture Frontiers, 2 (3), 70– 75.

[3] Intergovernmental Panel on Climate Change (IPCC). (2022). Summary for Policymakers. Climate Change 2022: Mitigation of Climate Change. Working Group III Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 1–48). Cambridge University Press.

[4] Intergovernmental Panel on Climate Change (IPCC). (2023). 2023: Sections. Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (pp. 35–115). IPCC.

[5] Yang, L. , & Li, Y. (2013) Low-carbon city in China. Sustainable Cities and Society, (9), 62– 66.

[6] Jiang, W. , & Kang, W. (2019) A review on the low-carbon city study: Development and trends. Chinese Journal of Urban and Environmental Studies, 7 (2), 1950006.

[7] Mauree, D. , Naboni, E. , Coccolo, S. , Perera, A. T. D. , Nik, V. M. , & Scartezzini, J.-L. (2019) A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities. Renewable and Sustainable Energy Reviews, (112), 733– 746.

[8] Wang, S. , Gao, S. , Huang, Y. , & Shi, C. (2020) Spatiotemporal evolution of urban carbon emission performance in China and prediction of future trends. Journal of Geographical Sciences, 30 (5), 757– 774.

[9] Lai, S. , Lu, J. , Luo, X. , & Ge, J. (2022) Carbon emission evaluation model and carbon reduction strategies for newly urbanized areas. Sustainable Production and Consumption, (31), 13– 25.

[10] Huang, Z. , Yu, H. , Peng, Z. , & Zhao, M. (2015) Methods and tools for community energy planning: A review. Renewable and Sustainable Energy Reviews, (42), 1335– 1348.

[11] Markovic, D. , Cvetkovic, D. , & Masic, B. (2011) Survey of software tools for energy efficiency in a community. Renewable and Sustainable Energy Reviews, 15 (9), 4897– 4903.

[12] Torabi Moghadam, S. , Delmastro, C. , Corgnati, S. P. , & Lombardi, P. (2017) Urban energy planning procedure for sustainable development in the built environment: A review of available spatial approaches. Journal of Cleaner Production, (165), 811– 827.

[13] Ng, S. T. , Chen, Y. , & Wong, J. M. W. (2013) Variability of building environmental assessment tools on evaluating carbon emissions. Environmental Impact Assessment Review, (38), 131– 141.

[14] Fenner, A. E. , Kibert, C. J. , Woo, J. , Morque, S. , Razkenari, M. , Hakim, H. , & Lu, X. (2018) The carbon footprint of buildings: A review of methodologies and applications. Renewable and Sustainable Energy Reviews, (94), 1142– 1152.

[15] Li, L. (2021) Integrating climate change impact in new building design process: A review of building life cycle carbon emission assessment methodologies. Cleaner Engineering and Technology, (5), 100286.

[16] Chau, C. K. , Leung, T. M. , & Ng, W. Y. (2015) A review on Life Cycle Assessment, Life Cycle Energy Assessment and Life Cycle Carbon Emissions Assessment on buildings. Applied Energy, (143), 395– 413.

[17] Albuquerque, F. D. B. , Maraqa, M. A. , Chowdhury, R. , Mauga, T. , & Alzard, M. (2020) Greenhouse gas emissions associated with road transport projects: Current status, benchmarking, and assessment tools. Transportation Research Procedia, (48), 2018– 2030.

[18] Gao, H. , Wang, X. , Wu, K. , Zheng, Y. , Wang, Q. , Shi, W. , & He, M. (2023) A review of building carbon emission accounting and prediction models. Buildings, 13 (7), 1617– .

[19] Udara Willhelm Abeydeera, L. H. , Wadu Mesthrige, J. , & Samarasinghalage, T. I. (2019) Global research on carbon emissions: A scientometric review. Sustainability, 11 (14), 3972– .

[20] O'Regan, A. C. , & Nyhan, M. M. (2023) Towards sustainable and net-zero cities: A review of environmental modelling and monitoring tools for optimizing emissions reduction strategies for improved air quality in urban areas. Environmental Research, (231), 116242.

[21] Chan, E., Conejos, S., & Wang, M. (2017). Low Carbon Urban Design: Potentials and Opportunities (pp. 75–88). In: S. Dhakal & M. Ruth (Eds.), Creating Low Carbon Cities. Springer.

[22] Arup. (2022). Reduce, restore, remove: A call to action.

[23] Chen, L. , Msigwa, G. , Yang, M. , Osman, A. I. , Fawzy, S. , Rooney, D. W. , & Yap, P.-S. (2022) Strategies to achieve a carbon neutral society: A review. Environmental Chemistry Letters, 20 (4), 2277– 2310.

[24] Gao, S. , & Zhang, H. (2020) Urban planning for low-carbon sustainable development. Sustainable Computing: Informatics and Systems, (28), 100398– .

[25] Fonseca, J. A. , & Schlueter, A. (2015) Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts. Applied Energy, (142), 247– 265.

[26] Wang, D. , Landolt, J. , Mavromatidis, G. , Orehounig, K. , & Carmeliet, J. (2018) CESAR: A bottom-up building stock modelling tool for Switzerland to address sustainable energy transformation strategies. Energy & Buildings, (169), 9– 26.

[27] Han, Y. , Zhang, S. , & Yin, L. (2019) Quantifying the carbon storage capacity and its spatial distribution patterns of green spaces in a metropolitan area: A case study of Seoul, South Korea. Landscape Architecture Frontiers, 7 (2), 55– 65.

[28] Henning Larsen. (2023, April 20). Urban Decarb: New Digital Tool Brings Carbon into Focus on the Urban Scale.

[29] Sasaki. (2021). Introducing the carbon conscience App.

[30] The World Bank. (2016, September 22). The CURB tool: Climate action for urban sustainability.

[31] Carbonneutralfinland. (2023). Municipalities' greenhouse gas emission scenario tool has been updated – agricultural actions included.

[32] Stockholm Environment Institute. (2022). LEAP: The Low Emissions Analysis Platform [Software version: 2020.1.107]. Somerville, MA, USA.

[33] Natanian, J. , & Auer, T. (2020) Beyond nearly zero energy urban design: A holistic microclimatic energy and environmental quality evaluation workflow. Sustainable Cities and Society, (56), 102094.

[34] Chair of Architecture and Building Systems, ETH Zurich. (n. d.). City Energy Analyst (CEA).

[35] Mutani, G., Coccolo, S., Kaempf, J., & Bilardo, M. (2018). CitySim Guide: Urban Energy Modelling by Mutani, Guglielmina. Createspace Independent Publishing Platform.

[36] One-Click LCA. (2023). One-Click LCA for construction and manufacturing.

[37] Yu, D. , Zhou, X. , Qi, H. , & Qian, F. (2023) Low-carbon city planning based on collaborative analysis of supply and demand scenarios. City and Built Environment, 1 (1), 7– .

[38] Lu, L. , Tian, Y. , Zhang, L. , & Liu, Y. (2011) Study on low-carbon assessment indicator system of urban planning of Tianjin. City Planning Review, 35 (S1), 26– 31.

[39] Lin, C. , Zhu, W. , Zhang, Y. , & Wu, C. (2022) Methods and practice of territorial spatial planning toward the goal of "peak carbon emissions and carbon neutrality": The case study of Tianjin. Urban Planning Forum, (S2), 229– 234.

[40] Ministry of Energy, Green Technology and Water (KeTTHA), & GreenTech Malaysia. (2017). Low Carbon Cities Framework (Version 2).

[41] Wu, Z. , Zhao, Z. , Gan, W. , Zhou, S. , Dong, W. , & Wang, M. (2023) Achieving carbon neutrality through urban planning and design. International Journal of Environmental Research and Public Health, 20 (3), 2420– .

[42] An, Q. , Sheng, S. , Zhang, H. , Xiao, H. , & Dong, J. (2019) Research on the construction of carbon emission evaluation system of low-carbon-oriented urban planning scheme: Taking the West New District of Jinan City as example. Geology, Ecology, and Landscapes, 3 (3), 187– 196.

[43] Yu, X. , He, J. , Zhu, D. , & Wang, D. (2022) Path and practice of low-carbon urban renewal: A case study of seven communities in Shanghai. Urban Planning Forum, (4), 111– 119.

[44] Wu, H. , Lin, C. , Chen, Y. , & Weng, T. (2022) Technical framework and implementation strategy for carbon reduction in urban districts based on whole process management and control: The case of Shanghai Jianghai Digital Industrial Park. Urban Planning Forum, (S2), 59– 65.

[45] Yao, Y. , Sun, Z. , Li, L. , Cheng, T. , Chen, D. , Zhou, G. , Liu, C. , Kou, S. , Chen, Z. , & Guan, Q. (2023) CarbonVCA: A cadastral parcel-scale carbon emission forecasting framework for peak carbon emissions. Cities, (138), 104354– .

[46] EnergyPLAN. (2022). EnergyPLAN—Advanced analysis of smart energy systems.

[47] C40 Cities Climate Leadership Group. (2020). Vertically-integrated climate action tools.

[48] Zhou, Y. , Chen, M. , Tang, Z. , & Mei, Z. (2021) Urbanization, land use change, and carbon emissions: Quantitative assessments for city-level carbon emissions in Beijing–Tianjin–Hebei region. Sustainable Cities and Society, (66), 102701– .

[49] Autodesk. (2024). Autodesk Forma: Cloud-based software for early-stage planning and design.

[50] Nault, E. , Waibel, C. , Carmeliet, J. , & Andersen, M. (2018) Development and test application of the UrbanSOLve decision-support prototype for early-stage neighborhood design. Building and Environment, (137), 58– 72.

[51] Building Transparency. (2023). Tally.

[52] Climate Positive Design. (n. d.). Measure + improve our carbon impact.

RIGHTS & PERMISSIONS

© Higher Education Press 2024