Evaluating Health Co-Benefits of Climate Change Mitigation in Urban Mobility

Abstract

There is growing recognition that implementation of low-carbon policies in urban passenger transport has near-term health co-benefits through increased physical activity and improved air quality. Nevertheless, co-benefits and related cost reductions are often not taken into account in decision processes, likely because they are not easy to capture. In an interdisciplinary multi-model approach we address this gap, investigating the co-benefits resulting from increased physical activity and improved air quality due to climate mitigation policies for three urban areas. Additionally we take a (macro-)economic perspective, since that is the ultimate interest of policy-makers. Methodologically, we link a transport modelling tool, a transport emission model, an emission dispersion model, a health model and a macroeconomic Computable General Equilibrium (CGE) model to analyze three climate change mitigation scenarios. We show that higher levels of physical exercise and reduced exposure to pollutants due to mitigation measures substantially decrease morbidity and mortality. Expenditures are mainly born by the public sector but are mostly offset by the emerging co-benefits. Our macroeconomic results indicate a strong positive welfare effect, yet with slightly negative GDP and employment effects. We conclude that considering economic co-benefits of climate change mitigation policies in urban mobility can be put forward as a forceful argument for policy makers to take action.

Keywords: air pollution; climate change mitigation; health co-benefits; interdisciplinary approach; physical activity; urban mobility.

Figure 1

Interdisciplinary multi-model approach for calculating climate change effects and health co-benefits.

Figure 2

Modal share of trips [%] (a) and transport performance (passenger-km) (b) for the three cities for the Baseline (Base), Green Mobility (GM) and Green Exercise (GE) Scenario.

Figure 3

Annual mean concentrations of PM_2.5 (μg/m³) for Vienna (baseline and scenarios).

Figure 4

Changes in CO₂ equivalent emissions (1000 t) for the three scenarios (all urban areas) relative to the baseline.

Figure 5

Changes in atraumatic mortality per 100,000 inhabitants due to increased physical activity and cardiovascular disease mortality changes due to NO₂ decreases.

Figure 6

Changes in Disability-Adjusted Life Years (DALYs) per 100,000 inhabitants for the pollutants NO₂, PM_2.5 and PM₁₀.

Figure 7

Changes in private investment and operating costs relative to the baseline for all three cities and scenarios (M € p.a.).

Figure 8

Changes in public investment and operating costs relative to the baseline for all three cities and scenarios (M € p.a.).

Figure 9

Summary of costs and benefits in private and public investment and operating costs relative to the baseline for all three cities and scenarios (M € p.a.).

Figure 10

Changes in Gross Domestic Product (GDP), welfare and unemployment for the three scenarios. Error bars indicate welfare effects when additionally accounting for intangible benefits (upper range: using VSL approach with 1.65 million € per life [60]; lower range: using VOLY approach with 43,000 €/VOLY [58]).

Figure 11

Decomposing the effects of climate mitigation measures on GDP, welfare and employment (illustrative for the Green Exercise scenario).

Figure 12

Summary of co-benefits due to CO₂equ reduction, reduced death cases (through physical activity and improved air quality) and reduced health costs. The size of the green bubbles correspond to the numbers in white which represent the cost savings due to mortality and morbidity decreases for each scenario in 1000 €/100,000 inhabitants.