Why local air pollution is more than daily peaks: modelling policies in a city in order to avoid premature deaths

Abstract

We use a predator-prey representation of an urban system to analyse how policy interventions can prevent the adverse effects of air pollution on people's health. The number of residents is treated as prey variable, and particulate matter that consists of particles with a diameter of up to 10 micrometres (PM10) as predator variable. This representation allows integration of population trends and the effects of environmental interventions on the average level of PM10 concentration (which establishes a baseline for the potential health burden for residents). For the case of Graz, Austria, we illustrate the insights generated regarding the interdependency of market-based and technological pollution controls, and propose an indicator that assesses the cost of delayed interventions by counting additional premature deaths caused by polluted environments.

Keywords: Air pollution; Environmental policy interventions; Predator–prey model.

Fig. 1

Population levels in Austria’s provincial capitals plus the Larger Graz Area (Graz & GU) 2017 and as %-change of residents between 1991 and 2017. Source: Statistics Austria, own illustration

Fig. 2

Stocks and flows diagram of the urban (predator–prey) system of mutually dependent population and pollution development (see Eqs. 6a and 6b)

Fig. 3

The state space for residents and population a for the base case parameter values (top left; see Table 1), b the “very green” scenario 2 (top right), c the “less green” scenario 3 (bottom left) and d the “deterioration” scenario 4 (bottom right); the point cloud represent historical data for the city of Graz since 2002, which follow a downward trend in PM10 concentration (from upper left to lower right)