Cycle lanes and green infrastructures may be expensive at first, but they involve long-term profits enhancing the quality of human life. This paper focuses on an easily replicable methodology for a cost-benefit analysis to estimate the economic value of benefits provided by cycling mobility and urban forestation in the city of Pisa. Open-source tools easily adaptable to local contexts and supported by a lot of experimentations and user guides were selected: HEAT (Health Economic Assessment Tool), a web tool designed by World Health Organization to quantify the monetary value of reduced mortality due to regular cycling, and i-Tree Eco, a software developed by the USDA Forest Service to assess the economic benefits provided by ES (Ecosystem Services) of urban trees. These tools provide an economic appraisal to verify and validate the suitability of political and economic choices and/or estimate the number of resources required in the long term.

A Methodology to Investigate the Human Health and Environmental Benefits by the Improvement of Urban Mobility and Ecosystem Services: A Case Study in Pisa

Frosini G.;Santini L.;Cinelli F.
2021-01-01

Abstract

Cycle lanes and green infrastructures may be expensive at first, but they involve long-term profits enhancing the quality of human life. This paper focuses on an easily replicable methodology for a cost-benefit analysis to estimate the economic value of benefits provided by cycling mobility and urban forestation in the city of Pisa. Open-source tools easily adaptable to local contexts and supported by a lot of experimentations and user guides were selected: HEAT (Health Economic Assessment Tool), a web tool designed by World Health Organization to quantify the monetary value of reduced mortality due to regular cycling, and i-Tree Eco, a software developed by the USDA Forest Service to assess the economic benefits provided by ES (Ecosystem Services) of urban trees. These tools provide an economic appraisal to verify and validate the suitability of political and economic choices and/or estimate the number of resources required in the long term.
2021
Frosini, G.; Santini, L.; Cinelli, F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1104894
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