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Abstract
This article investigates the potential impact of sustainable energy action plans (SEAPs) on local development through a two-step methodology involving participatory planning and quantitative analysis. The first phase relies on a participatory system mapping (PSM) approach and generates a causal structure at the basis of the urban model. In the second phase, we transform the qualitative map into a system dynamic model which evaluates the effect of the SEAP on social, economic and environmental indicators. This methodology was applied to the case of Cascina Municipality (Italy). Through scenario analysis, we show that some indirect feedback can harm the achievement of the 20% emission reduction target. This process allows the local authority and stakeholders to evaluate the impact of emission reduction policies on CO2 emissions and local development, thereby generating collective learning on the systemic implications of the plan. We show that this method can enhance the ambition of emission mitigation efforts by small towns.
Acknowledgements
The authors would like to thank Alessandra Anacleto and all the participants at the initial workshop organised by the Municipality of Cascina. In particular, Alessio Antonelli, former Mayor of Cascina, and all the members of the local Government Council, Marco Ricci and Sergio Mottola who contributed their knowledge and experience during the initial stages of this research project. In addition, we are very grateful to the many participants at the Workshop INOGOV (Innovative urban governance for mitigation and adaptation: Mapping, exploring and interrogation), 35th International Conference of the System Dynamics Society and the 7th International Sustainability Transitions for helpful comments. We are also immensely grateful to Emanuele Campiglio, Davide Fiaschi, Tiziano Razzolini, Jordi Roja and Ashok Thomas for their comments on earlier versions of the manuscript. We finally thank five anonymous reviewers for their comments which improved the manuscript.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Supplemental data
Supplemental data for this article can be accessed here.
Notes
1 See, for instance, Responder projects, which aim to promote sustainable consumption by assessing potential contradictions with economic growth – taking into account aspects of green growth, non-growth and de-growth. For further information, refer to http://www.scp-responder.eu/.
2 See for instance Shepherd (Citation2014) on transport systems, Brailsford et al. (Citation2004) and Viana et al. (Citation2014) on health care, Feng, Chen, and Zhang (Citation2013) and Bianchi and Tomaselli (Citation2015) on energy and environment and local strategic management.
3 After this seminal work, several models and applications were developed, the most relevant being Sanders and Sanders (Citation2004), Swanson (Citation2003), Duran-Encalada and Paucar-Caceres (Citation2008) and Hennessy et al. (Citation2011).
4 Delponte, Pittaluga, and Schenone (Citation2017) present a detailed SD model for supporting the monitoring and evaluation phases of the SEAP in the city of Genoa (Italy). While this contribution considers several sectors, it focuses on the impact of the plan on its specific targets, that is, energy savings and CO2 emission reductions.
5 Especially from Empoli, Pisa and Pontedera.
6 Given the size of the town and the consequent limits of the administrative structure, local administrators were not prepared to draw up such a specific energy plan. For this reason, they decided to entrust the development of the BEI and SEAP to external auditors – namely, GreenGea. For further details see http://www.greengeasnc.it/
7 For more information see http://edgar.jrc.ec.europa.eu/overview.php?v=$CO_2$ts1990-2014.
8 In particular, we emphasise the presence of the Councillor for Urban Planning and Transport (representing some publicly owned corporations – namely the school transport provider, Amico Bus, and the transport company of northern Tuscany, CTT); the Councillor for Agriculture and Environmental Policies (representing some publicly owned corporations – namely Toscana Energia SPA and AEP, energy agencies, respectively, at regional and provincial levels, the waste management companies RETIAMBIENTE SPA and GEOFOR PATRIMONIO SRL, the Cascina aqueduct and sewer authority, CERBAIE S.P.A); the Councillor for Finance; the Councillor for Trade and Local Development (representing some publicly owned corporations – namely ECOFOR SERVICE SPA, the agency for planning, monitoring and control of industrial plants) and Polo Tecnologico SPA).
9 GreenGea. For further details see http://www.greengeasnc.it/GreenGea/Home.html
10 describe each action and its expected contribution in CO2 emissions reduction. Outside these three groups, there is action 10 – that is, the development of the model discussed in this paper, action 11 – a specific survey, and action 16 – a change in regulation governing land use.
11 For a detailed description of the model, see Bernardo (Citation2016).
12 For a discussion of this topic, see for instance Hong et al. (Citation2016), Team (Citation2011), Barbu, Griffiths, and Morton (Citation2013).
13 Note that a significant share of total SEAP funding comes from Regional, National or European authorities.
14 Italian National Institute of Statistics: http://demo.istat.it/archive.html
15 The Italian Automobile Club http://www.aci.it/laci/studi-e-ricerche/dati-e-statistiche/open-data.html
17 Regional Institute for Economic Planning of Tuscany - http://www.irpet.it/en/index.php
18 Ministry of Economy and Finance.
19 Italian National Agency for New Technologies, Energy and Sustainable Economic Development.
20 GSE is the state-owned company which promotes and supports renewable energy sources (RES) in Italy. It fosters sustainable development by providing support for renewable electricity (RES-E) generation and by taking action to build awareness of environmentally efficient energy uses. Moreover, it is part of the National Statistics System (SISTAN).
21 For convenience, we cite the most recent version of this technical report while we also used previous versions for data collection.
23 The average rate of change is extensively used in cases where one variable is directly connected to another, such that the change in one causes a positive or negative variation to the other.
24 The simulation period starts in 2008 (period zero in the figures) and is run for 13 years.
25 All the indices are built taking 2008 as the base year, that is, X2008=100 for any variable x.