A Strategic Multidirectional Approach for Picking Indicator Systems of Sustainability in Urban Areas
Abstract
:1. Introduction
- (i)
- Creating appropriate methods for assessing urban settings overall depends on the interlinkages between the sustainability triad. The interdependence of social, environmental, and economic issues makes it tricky to create issue-specific indicators relevant to decision-making contexts. To entirely realize the relevance of indicator interactions and the synergy between dominant fields in a particular decision–framework system, further investigation needs to be performed.
- (ii)
- A mismatch can be detected between the objectives and expectations of all those engaged in the urban sustainable development procedure and the process itself. When the metrics for sustainability and interest are not equal, there is less confidence in employing one kind of signal over another.
- (iii)
- The effectiveness of indicators is directly impacted by the settings in which they are used. Many tools and indicator frameworks that function at the building, neighborhood, city, region, national, and international levels serve a range of geographic scales and provide data pertinent to their reference scale [21,22]. Indicators at the city or metropolitan level typically focus on broad issues that affect the urban area, such as economic productivity, environmental value, and social equality. National or worldwide indicators of urban sustainability address wider concerns and trends that extend beyond specific city boundaries, providing a more comprehensive view [2,12]. When the inquiry is expanded to the local level, a number of connected problems concerning the arrangement of various components occur [23,24]. The interoperability indicators create on multiple geographic analytic scales turn out to be challenging.
- (iv)
- Evaluation is determined by the quantity and the quality of accessible data across several geographical dimensions. Smaller analytical contexts create more challenges for data collection since accessible data are typically aggregated. This problem might make it more difficult to holistically assess sustainability. Metropolitan areas may have varying levels of data accessibility; although some may have large databases, others may not have well-documented data. Because of these distinctions, evaluations may be skewed to favor decisional settings with greater access to data, excluding a number of locations from the comparison [6].
- RQ1: What are the key measures used to assess the condition of sustainability at the urban scale?
- RQ2: Given the available indicators for measuring urban sustainability, how can we link them in a sustainability assessment exercise at the local urban scale with the needs of those involved in the design process?
2. Materials and Methods
2.1. Methods and Tools for Tracking the Indicator Suite of Sustainability
- (1)
- The first category includes instruments for product-related evaluations that examine the creation and usage of products and services. Environmental laws and regulations are influenced by evaluating a product’s resource consumption and environmental impact throughout its lifespan.
- (2)
- The second type includes integrated assessment tools that provide scenarios for project implementation or policy changes. To reduce externalities, terms such as “Environmental Impact Assessment” and “Strategic Environmental Assessment” are commonly used to examine how development projects or strategic decisions may affect the environment.
- (3)
- The third one is about urban sustainability indices and indicators, which are becoming more commonly recognized as effective instruments for evaluation [31].
2.2. Methods
2.2.1. Top-Down Systematic Literature Review
- The formulation of research questions: the identification of the main questions that need to be researched in connection to urban sustainability [44]. These questions are precisely tailored to align with the objectives of the study.
- Database building and literature sources’ identification: databases relevant to the field are selected to facilitate a comprehensive literature search. A selection of keywords is made to find research articles that support the objectives of the study. Examples of these keywords are “sustainability indicators”, “urban sustainability assessment”, and “urban indicator systems”. The initial collection of articles gleaned from the literature is then sifted using relevant inclusion and/or exclusion criteria, most often based on the existence or absence of a sustainability indicator list and the adaption of the indicators to an urban framework.
- Information gathering: the next step is the collection of key data from the selection of literature sources. This includes the article’s year of publication, title, primary goal, sustainability categories taken into consideration, variables/indicators employed, and, for each indicator, the kind of methodology used (e.g., qualitative or quantitative), measurement method/unit, and spatial scale [45,46,47,48,49,50].
2.2.2. Bottom-Up Approach
- Examine pilot case-specific documents for thorough information, highlighting significant lines with keywords that convey contextual factors and/or intervention characteristics. The resources under investigation have to be focused on a compelling analytical pilot case that will function as a prototype for further study. By identifying the indicators to assume based on valuation approaches within the same analysis environment, the pilot case aids in the customization of the analytical framework.
- Identify the important variables required for establishing a set of sustainability indicators across a number of dimensions using the highlighted keywords.
- By exploring these key variables, one can gain insight into a variety of sustainability-related topics (categories), including the technological, typological, social, and environmental aspects that are monitored in the analysis document.
Pilot Case
3. Results
3.1. Top-Down Analyis
3.2. Bottom-Up Analysis
3.3. Comparing and Validating Sustainability Metrics
- (i)
- These metrics offer an evaluation of metropolitan areas’ overall environmental quality in terms of resource sustainability and ecosystem health. As an illustration, temperature-related indicators that shed light on the condition of the air environment have been added. This category also includes land use indicators, which help to evaluate the environmental effects of various land uses by providing data on the geographical distribution of built and undeveloped areas relative to the entire region under study.
- (ii)
- These indicators provide insight into cultural variety, social dynamics, and people’s overall well-being in an urban setting. A variety of important factors are included in this group of indicators, such as the caliber and the accessibility of educational institutions, the accessibility of health care, and the level of safety, as determined by crime rates. Furthermore, metrics like the quantity of green space in the city and proximity to public transit and services shed light on the accessibility of these areas and their impacts on the connectivity and well-being of city dwellers. The socio-cultural compatibility category also encompasses metrics pertaining to the regeneration project, which offer insights into attitudes towards the project among the local population. The indicators of building technologies that shed light on their potential effects on the environment are also included here.
- (iii)
- This category covers employment-related factors, such as unemployment rates, job openings, and the development of jobs locally. Indicators of the residential market, rental prices, and typical expenses for water supply, heating, and cooling services are also included in this area. This category contains indicators pertaining to the redevelopment project that quantify the costs of interventions such as investments and provide details on building upkeep, such as the price and frequency of such upkeep.
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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No. | Year | Authors | Scale of Analysis | Categories | Indicator Set |
---|---|---|---|---|---|
I | 2023 | Samuel M., et al. | City | Access to City | n.a. |
Credit facilities | |||||
Consumption patterns | |||||
Economic prosperity | |||||
Environment | |||||
Environmental knowledge | |||||
Equity/justice | |||||
Hospital network services | |||||
Livable communities | |||||
Place shaping | |||||
Population | |||||
Quality of life | |||||
Building resilience | |||||
Safety | |||||
Social | |||||
II | 2023 | Yue Z., et al. | Global scale | SDG11.6.2 | PM2.5 concentrations |
III | 2023 | Zhou-Qian G., et al. | River | Land dataset | |
Natural environmental data | |||||
Socioeconomic data | |||||
Pressure on urban expansion | Built-up land expansion intensity | ||||
Proportion of built-up land | |||||
Land use composite index | |||||
Pressure on the food supply | Proportion of agricultural land | ||||
Decrease rate of agricultural land | |||||
Pressure on ecological degradation | Ecological service value | ||||
Ecological carrying capacity | |||||
Pressure on landscape pattern | Shannon’s diversity index | ||||
Landscape disturbance index | |||||
Landscape vulnerability index | |||||
IV | 2023 | Fusaro L., et al. | City | ES supply and demand | O3 and PM10 removal |
V | 2023 | Qu J., et al. | City | Water resource system | Water quantity |
Water quality | |||||
Water efficiency | |||||
Socioeconomic system | Economic development level | ||||
Social development level | |||||
VI | 2023 | Keshtkar M., et al. | Biome | Environment | Bio-physical data |
Socioeconomic system | Socioeconomic data | ||||
VII | 2023 | Raquel Calapez A., et al. | Urban | Ecosystem services | Provisioning |
Regulating | |||||
Cultural | |||||
VIII | 2023 | Zhou Y., et al. | Greater Bay Area | Urban ecological network | Water conservation |
Habitat quality | |||||
Soil conservation | |||||
Carbon fixation | |||||
IX | 2023 | Cheng M., et al. | Country | Urban areas | Nighttime data |
Urban greenness | Enhanced vegetation index | ||||
X | 2023 | Abu-Rayash A. and Dincer I. | City | Environment | |
Economy | |||||
Society | |||||
Governance | |||||
Energy | |||||
Infrastructure | |||||
Transportation | |||||
Health | |||||
XI | 2023 | Mylonakou M., et al. | City | Public satisfaction with transport | Access to mobility services |
Active mobility | |||||
Affordability | |||||
Quality of public space | |||||
Air pollution emissions | |||||
Energy efficiency | |||||
Greenhouse gas emissions | |||||
Commuting travel time | |||||
Congestion and delays | |||||
Road deaths | |||||
Security | |||||
Traffic safety active mode | |||||
XII | 2022 | Prieto-Curiel R., et al. | City | Urban | Building footprint density |
XIII | 2023 | Zafar Z., et al. | Megacity | Vegetation | Enhanced vegetation index |
XIV | 2023 | Anwar Uddin Md., et al. | City | Density | Population density |
Commercial density | |||||
Employment density | |||||
Diversity of land use | Land use diversity | ||||
Destination accessibility | Land use mixedness | ||||
Length of walkable/cyclable paths | |||||
Intersection density | |||||
Design | Parkin utilization | ||||
Open/green spaces | |||||
XV | 2022 | Pukowiec-Kurda K. | City | Urban ecosystem | Number of ecosystem services provided by forests |
Percentage of forests | |||||
Number of ecosystem services provided by wetlands | |||||
Percentage of wetland | |||||
Percentage of recreational area | |||||
Number of ecosystem services provided by recreational area | |||||
XVI | 2022 | Zhang H., et al. | City | Economic scale | GDP per capita |
Disposable income of urban residents per capita | |||||
Net income of rural residents per capita | |||||
Economic structure | Primary industry output | ||||
Secondary industry output | |||||
Financial income per capita | |||||
Economic vitality | Retail sales of consumer goods per capita | ||||
Residential savings deposit balance per capita | |||||
XVII | 2022 | Valencia A., et al. | Metropolitan area | Environmental aspects | Carbon footprint |
Water footprint | |||||
Sea level rise | |||||
Social aspects | Food consumption index | ||||
Unemployment index | |||||
Crime rate index | |||||
Economic aspects | Crop production index | ||||
Water reuse potential | |||||
XVIII | 2021 | Effat H. A., et al. | City | Shelter degradation | Habitat quality |
Overcrowding | |||||
Social degradation | Rate of illiteracy | ||||
School enrolment | |||||
Social status | |||||
Quality of society | |||||
Environmental degradation | Population growth | ||||
Pollution | |||||
High-voltage pressure area | |||||
Economic degradation | Average price of residential land | ||||
Utilities | |||||
Road density | |||||
XIX | 2022 | Han Z., et al. | Province | Provisioning ecosystem services | Food supply |
Supporting ecosystem services | Habitat quality | ||||
Soil conservation | |||||
Regulating ecosystem services | Carbon sequestration and oxygen production | ||||
Water conservation | |||||
Cultural services | Landscape esthetics | ||||
XX | 2022 | Cardenas-Mamani and Perrotti D. | n.a. | Ecosystem services | Provisioning |
Regulation and maintenance |
Source/Information for the Definition of A Variable | Description of the Rationale of Each Variable | Type of Variable | Unit of Measure |
---|---|---|---|
Location: Vernier, Switzerland | |||
Original Project | |||
Georges Addor, Dominique Julliard, Louis Payot, and Jacques Bolliger | 1. Are the architects a reason for the project having an element of identity? | Categorical/ordinal | Yes or no |
Renovation Project | |||
Jaccaud Spicher Architectes Associés | 2. It is the project an “example” of the traditional architecture of the place? | Categorical/ordinal | Yes or no |
Academic Research Project | |||
Directed by Franz Graf and Giulia Marino (TSAM) | 3. It is the project a masterpiece? | Categorical/ordinal | Yes or no |
Timeline | |||
1971 original|2021 renovation | |||
Research Project 2008|2011 | |||
Renovation: | |||
Design Phase 2010|2017 | |||
Construction: 2017|2021 | |||
Typology | |||
Upcycling | 4. Does the upcycling involve the residents? | Categorical/ordinal | Yes or no |
5. Are the architects specialists in upcycling? | Categorical/ordinal | Yes or no | |
6. Is the project appropriate for upcycling? | Categorical/ordinal | Yes or no | |
Technology | |||
Concrete PreFab | 7. Is this type of construction usual in the area? | Categorical/ordinal | Yes or no |
Clients | |||
Anlagestiftung Pensimo, Bellerive Immobilien, Comité Central Du Lignon, Immobilien Anlagestiftung Turidomus, Imoka Immobilien Anlagestiftung, La Fondation HBM Camille Martin, La Rente Immobilière, and Marconi Investment | 8. Are the clients private or public? | Categorical/ordinal | Yes or no |
Indicator Set | |||||||
---|---|---|---|---|---|---|---|
No. | Indicator/Data | No. | Indicator/Data | No. | Indicator/Data | No. | Indicator/Data |
1 | Gross internal floor area | 22 | Land density of suburb | 43 | Shape of the building and information about its main dimensions (height, length) | 64 | Maintenance costs of the building |
2 | Green surfaces | 23 | Inhabitants of suburb | 44 | Distance from university, school, train station, city center, and parks | 65 | Commercial rental values for this typology |
3 | Built area | 24 | Land density of the Cantone | 45 | Analysis of urban standards | 66 | Dwellings for non-self-sufficient people |
4 | Built density | 25 | Inhabitants of the Cantone | 46 | Pervious surfaces | 67 | Access to the building |
5 | Residents | 26 | Original construction typology | 47 | Impervious surfaces | 68 | Access to nearby spaces |
6 | Composition of households | 27 | Time of maintenance | 48 | Garden surfaces | 69 | Per capita housing surface |
7 | Population density | 28 | Is the building preserved? | 49 | Facilities (schools, shops, medical center, church, and cultural and sports areas) | 70 | Public aggregation areas |
8 | Age of inhabitant | 29 | Where is the project located? | 50 | Average summer temperature perceived internally and average summer temperature measured externally | 71 | Distance from the underground, train station, and bus services |
9 | Number of houses | 30 | Is it a prestigious location? | 51 | Average winter temperature perceived internally and average winter temperature measured externally | 72 | Distance from the university, postal offices, hospital, schools, and supermarket |
10 | Commercial activities | 31 | Elements of the building that are going to be renovated | 52 | Air pollution | 73 | Distance from car–bike sharing points |
11 | Parking lots | 32 | Type of housing tenure | 53 | Construction technologies for minimizing natural risk | 74 | |
12 | Number of garages | 33 | Market value of residential buildings | 54 | Sources of renewable energy | 75 | Average cost of water supply |
13 | Building typology | 34 | Rental value of residential buildings | 55 | Systems for water recycling | 76 | Investment costs of the entire renovation of the building |
14 | Residential typology | 35 | Average period of possession for residents | 56 | Frequency of ordinary and extra-ordinary maintenance interventions in the last 5 years | 77 | Maintenance costs of the building |
15 | Average climate temperature | 36 | Average income of residents | 57 | CO2 quantity produced by the green areas and construction elements of buildings | 78 | Commercial rental values for this typology |
16 | Humidity | 37 | Average income of suburb | 58 | Transmittance of walls and window frames | 79 | Number of dwellings for non-self-sufficient people |
17 | Wind conditions | 38 | Average income of Cantone | 59 | Transmittance of rooftop and midline ceiling | 80 | Number of access points in the building |
18 | Rain precipitation | 39 | Type of education | 60 | Are any materials being reused? | 81 | Number of access points to nearby spaces |
19 | Local radiation | 40 | Employment status of residents | 61 | Average cost of heating and cooling | ||
20 | Exposure of the apartments | 41 | Average age of residents | 62 | Average cost of water supply | ||
21 | Land density | 42 | Information about criminality | 63 | Investment costs of the entire renovation project of the building |
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Guarini, M.R.; Sica, F.; Tajani, F.; Sabatelli, E.; Anelli, D. A Strategic Multidirectional Approach for Picking Indicator Systems of Sustainability in Urban Areas. Urban Sci. 2024, 8, 107. https://doi.org/10.3390/urbansci8030107
Guarini MR, Sica F, Tajani F, Sabatelli E, Anelli D. A Strategic Multidirectional Approach for Picking Indicator Systems of Sustainability in Urban Areas. Urban Science. 2024; 8(3):107. https://doi.org/10.3390/urbansci8030107
Chicago/Turabian StyleGuarini, Maria Rosaria, Francesco Sica, Francesco Tajani, Emma Sabatelli, and Debora Anelli. 2024. "A Strategic Multidirectional Approach for Picking Indicator Systems of Sustainability in Urban Areas" Urban Science 8, no. 3: 107. https://doi.org/10.3390/urbansci8030107
APA StyleGuarini, M. R., Sica, F., Tajani, F., Sabatelli, E., & Anelli, D. (2024). A Strategic Multidirectional Approach for Picking Indicator Systems of Sustainability in Urban Areas. Urban Science, 8(3), 107. https://doi.org/10.3390/urbansci8030107