The Role of Non-Climate Data in Equitable Climate Adaptation Planning: Lessons from Small French and American Cities
Abstract
:1. Introduction and Background
2. Methodology
2.1. Climate Adaptation Plans
2.2. Conceptualization of Vulnerability
2.3. Conceptualization of Equity and Inclusion
2.4. Data Analysis
- How is the concept of human vulnerability defined and what information is used to assess it?
- How climate justice is addressed in climate adaptation goals across various sectors, and what information is used to formulate the goals?
- What groups of stakeholders are involved in the co-production of information used in vulnerability assessment and the co-development of local climate adaptation plans?
3. Results and Discussion
3.1. Assessment of Human Vulnerability
3.2. Consideration of Justice in Climate Adaptation Goals
3.3. Stakeholders’ Role in Knowledge Development
4. Conclusions
- (a)
- Municipalities need flexible, user-friendly, and reliable tools for comprehensive vulnerability assessment, mapping, and monitoring, informed by the up-to-date body of knowledge and best practices around the world, and relevant to their geographical context. Many currently existing products are based on outdated literature and offer rigid step-by-step guidelines, rather than interactive analytical tools. Cities need the best common standards, which are currently lacking, but not necessarily common data sources or guidelines.
- (b)
- Centralized approaches to data monitoring for climate adaptation planning often fail to provide information at relevant temporal and spatial scales. Produced by different agencies and groups of experts, these databases are often hard to integrate and downscale. Decentralized interdisciplinary monitoring networks equipped with digital applications allowing local citizens to engage in knowledge production may offer promising alternatives.
- (c)
- Climate-adaptation design tools for local governments should prioritize climate justice in all adaptation contexts and sectors. GIS-based online mapping tools and mobile applications are very helpful in visualization and analysis of spatial correlations between income, race, environmental justice issues, and various dimensions of vulnerability to climate impacts, helping to inform difficult conversations about resource allocations in climate adaptation planning.
- (d)
- Long-term funding programs are necessary to provide financial and other resources and incentives for stakeholders’ collaboration and community engagement in local knowledge co-production. Funding agencies should prioritize active local and regional partnerships involving academic institutions, schools, advocacy groups, local businesses, and especially citizens and organizations representing the most vulnerable communities. Funding programs that prioritize mainstreaming climate adaptations into neighborhood revitalization, food-security, community wellness, environmental education, and citizen-science projects should be designed to support long-term partnerships among all local actors.
- (e)
- Climate education networks, local working groups, and other boundary organizations connecting experts and non-experts would play an increasingly important role in merging community-based education, scientific research, climate action, and co-design of digital technologies, tools, and data for local climate adaptation planning.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Municipality | Source | Impacts of Climate Change Addressed | |||||||
---|---|---|---|---|---|---|---|---|---|
Coastal Changes | Severe Storms | Extreme Heat | Extreme Cold | Flooding | Drought | Wildfires | Seasonal Shifts | ||
U.S. climate adaptation plans | |||||||||
Albany, NY | [35] | X | X | X | X | X | |||
Alger County, MI | [36] | X | X | X | X | X | X | X | X |
Boulder County, CO | [37] | X | X | X | X | X | |||
Chula Vista, CA | [38] | X | X | X | X | X | X | ||
Corte Madera, CA | [39] | X | X | X | X | X | X | ||
Flagstaff, AZ | [40,41] | X | X | X | X | X | X | ||
Georgetown, ME | [42] | X | X | X | |||||
Groton, CT | [43] | X | X | X | X | X | X | ||
Iowa City, IA | [44,45] | X | X | X | X | X | |||
Keene, NH | [46,47] | X | X | X | X | X | X | ||
Laguna Woods, CA | [48] | X | X | X | X | X | |||
Marquette, MI | [49] | X | X | X | X | X | X | ||
Marquette County, MI | [50] | X | X | X | X | X | X | X | X |
Marshfield, MA | [51] | X | X | X | X | X | X | ||
North Kingston, RI | [52] | X | X | X | X | X | X | ||
Punta Gorda, FL | [53,54] | X | X | X | X | ||||
Salem, MA | [55] | X | X | X | X | ||||
Santa Cruz, CA | [56,57] | X | X | X | X | X | X | ||
Sarasota, FL | [58,59] | X | X | X | X | ||||
Taos County, NM | [60] | X | X | X | X | X | X | ||
Tybee Island, GA | [61] | X | X | X | |||||
Tompkins County, NY | [62] | X | X | X | X | ||||
Watsonville, CA | [63] | X | X | X | X | X | X | ||
French climate adaptation plans | |||||||||
Brest métropole, Bretagne | [64,65] | X | X | X | X | X | |||
Clermont Auvergne Métropole, Auvergne-Rhône-Alpes | [66,67,68,69] | X | X | X | X | ||||
Cordais et Causse (4 C), Occitanie | [70,71,72] | X | X | ||||||
Golfe du Morbihan, Bretagne | [73] | X | X | X | |||||
La ivière du Levant, Guadeloupe | [74] | X | X | X | |||||
Le Grand Chalon, Bourgogne-Franche-Comté | [75,76] | X | X | X | |||||
Niortais, Nouvelle-Aquitaine | [77,78] | X | X | X | |||||
Pays de Barr, Grand Est | [79,80,81] | X | X | X | X | ||||
Pays Dieppois—Terroir de Caux (PDTC), Normandie | [82,83,84,85] | X | X | X | |||||
Pays Voironnais, Auvergne-Rhône-Alpes | [86] | X | X | X | X | ||||
Perpignan Méditerranée Métropole, Occitanie | [87] | X | X | X | X | ||||
Saint Omer—CAPSO, Hauts-de-France | [88,89,90] | X | X | X | |||||
St-Quentin-en-Yvelines—CASQY, Ile de France | [91,92] | X | |||||||
Sud-Estuaire, Pays de la Loire | [93,94,95,96] | X | |||||||
Sundgau, Grand Est | [97,98,99] | X | X | X | |||||
Vallée de Chamonix-Mont-Blanc, Auvergne-Rhône-Alpes | [100,101] | X | |||||||
Var Esterel Méditerranée, Provence-Alpes-Côte d’Azur | [102,103] | X | X | X | X |
Area of Interest | Information Used in Climate Adaptation Plans |
---|---|
| |
As a synonym of exposure (omit sensitivity and adaptive capacity) | Climate change trends, climate change scenarios, risk analysis |
As a combination of exposure, sensitivity, and adaptative capacity (pre-IPCC-SREX) | Climate change trends, climate change scenarios, risk analysis, demographic, health, and socio-economic data |
As a combination of sensitivity and adaptive capacity to projected climate risks (post-IPCC-SREX) | Demographic, socio-economic, health statistics and risk analysis based on climate change trends and scenarios |
As a combination of exposure and sensitivity (omit adaptive capacity) | Climate change trends, climate change scenarios, risk analysis, demographic data |
As a combination of exposure and adaptive capacity (omit sensitivity) | Climate change trends, climate change scenarios, risk analysis, socio-economic data |
| |
Green and blue infrastructure | Climate, ecological and environmental data |
Housing | Housing inventory and plans |
Energy security | Energy access, cost, and future projections |
Public transportation | Transportation networks and plans |
Utilities | Utilities infrastructure and plans |
Emergency services | Emergency infrastructure and plans |
Food security | Food access, safety, and security data and projections |
Water quality | Water quality data and scenarios |
Air quality | Air quality data and scenarios |
Community education | Information about education attainment and community education resources |
Insurance | Insurance access data and scenarios |
Community health | Health statistics trends, data about access to health care, and projections |
| |
Local citizens | Stories, survey, and focus group input, art, traditional knowledge, citizen science |
Environmental and climate advocacy groups | Environmental and climate data, case studies, stories, non-scientific articles, blogs |
Social justice advocacy groups | Environmental and climate data, case studies, stories, non-scientific articles, blogs |
Local government officials | Policy connection, litigation, public mobilization, public funding |
City planners | Urban, land-use, environmental spatial data, case studies, ordinances, litigation |
Members of state or federal/national agencies | Guidelines, toolkits, case studies, science/policy connection, public funding, training materials |
Academic institutions | Guidelines, toolkits, scholarly literature, spatial data, scenarios, public lectures |
Local businesses | Surveys and focus group input, private funding |
External consulting firms | Climate, geoscience, and environmental data, risk analysis, impact scenarios |
Area of Interest | U.S. Plans | French Plans |
---|---|---|
| ||
As a synonym of exposure (omit sensitivity and adaptive capacity) | 5 (22%) | 6 (35%) |
As a combination of exposure, sensitivity, and adaptive capacity(pre-IPCC-SREX) | 9 (38%) | 3 (18%) |
As a combination of sensitivity and adaptive capacity to projected climate risks (post-IPCC-SREX) | 2 (9%) | 0 (0%) |
As a combination of exposure and sensitivity (omit adaptive capacity) | 2 (9%) | 0 (0%) |
As a combination of exposure and adaptive capacity (omit sensitivity) | 5 (22%) | 8 (47%) |
| ||
Green and blue infrastructure | 11 (48%) | 4 (24%) |
Housing | 8 (35%) | 14 (82%) |
Energy security | 6 (20%) | 10 (59%) |
Public transportation | 8 (35%) | 6 (35%) |
Utilities | 5 (22%) | 2 (12%) |
Emergency services | 12 (52%) | 7 (41%) |
Food security | 4 (17%) | 13 (76%) |
Water quality | 4 (17%) | 5 (29%) |
Air quality | 3 (13%) | 1 (6%) |
Community education | 11 (48%) | 9 (53%) |
Insurance | 2 (9%) | 0 (0%) |
Community health | 7 (30%) | 7 (41%) |
| ||
Local citizens | 18 (78%) | 9 (53%) |
Environmental and climate advocacy groups | 16 (70%) | 8 (47%) |
Social justice advocacy groups | 6 (26%) | 2 (12%) |
Local government officials | 22 (96%) | 16 (94%) |
City planners | 21 (91%) | 17(100%) |
Members of state or federal/national agencies | 12 (52%) | 8 (47%) |
Academic institutions | 15 (65%) | 3 (18%) |
Local businesses | 14 (61%) | 13 (76%) |
External consulting firms | 13 (57%) | 5 (29%) |
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Share and Cite
Lioubimtseva, E.; da Cunha, C. The Role of Non-Climate Data in Equitable Climate Adaptation Planning: Lessons from Small French and American Cities. Sustainability 2023, 15, 1556. https://doi.org/10.3390/su15021556
Lioubimtseva E, da Cunha C. The Role of Non-Climate Data in Equitable Climate Adaptation Planning: Lessons from Small French and American Cities. Sustainability. 2023; 15(2):1556. https://doi.org/10.3390/su15021556
Chicago/Turabian StyleLioubimtseva, Elena, and Charlotte da Cunha. 2023. "The Role of Non-Climate Data in Equitable Climate Adaptation Planning: Lessons from Small French and American Cities" Sustainability 15, no. 2: 1556. https://doi.org/10.3390/su15021556
APA StyleLioubimtseva, E., & da Cunha, C. (2023). The Role of Non-Climate Data in Equitable Climate Adaptation Planning: Lessons from Small French and American Cities. Sustainability, 15(2), 1556. https://doi.org/10.3390/su15021556