Handling pollution issues is one of the main challenges that cities have to face nowadays. The reason is twofold. On the one hand the urban areas are the main sources of emission of pollutants, which indeed are mainly related with anthropogenic factors. On the other hand, cities, being the areas with higher densities of inhabitants, are the areas where the impact of pollution on human health is more important. The main effects of high values of pollutants on human health regard respiratory apparatus, cardiovascular system and neurological system. Evidence shows that there are connections between the spread of viruses and environmental pollution. Thus, urban monitoring of pollutants is crucial, since it is the preliminary and necessary step to elaborate and then perform actions aimed at reducing pollution in order to safeguard citizens’ health. This study proposes a method to design a low-cost urban air quality monitoring system that can be implemented in any small-to-medium-sized smart city. We focus on the monitoring of atmospheric particulate matter (PM10 and PM2.5) since this is one of the main sources of pollution and it is the one with strongest impact on human health. The proposed method uses a combination of the AHP multi-criteria decision-making technique and of a cellular automaton model for the identification of the most suitable positions for the monitoring sensors. Furthermore, the data infrastructure architecture of the monitoring system is defined.
Designing Air Quality Monitoring Systems in Smart Cities
Sdringola P.;
2022-01-01
Abstract
Handling pollution issues is one of the main challenges that cities have to face nowadays. The reason is twofold. On the one hand the urban areas are the main sources of emission of pollutants, which indeed are mainly related with anthropogenic factors. On the other hand, cities, being the areas with higher densities of inhabitants, are the areas where the impact of pollution on human health is more important. The main effects of high values of pollutants on human health regard respiratory apparatus, cardiovascular system and neurological system. Evidence shows that there are connections between the spread of viruses and environmental pollution. Thus, urban monitoring of pollutants is crucial, since it is the preliminary and necessary step to elaborate and then perform actions aimed at reducing pollution in order to safeguard citizens’ health. This study proposes a method to design a low-cost urban air quality monitoring system that can be implemented in any small-to-medium-sized smart city. We focus on the monitoring of atmospheric particulate matter (PM10 and PM2.5) since this is one of the main sources of pollution and it is the one with strongest impact on human health. The proposed method uses a combination of the AHP multi-criteria decision-making technique and of a cellular automaton model for the identification of the most suitable positions for the monitoring sensors. Furthermore, the data infrastructure architecture of the monitoring system is defined.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
