Abstract
Traffic-related atmospheric emissions of greenhouse gases (GHG) and toxic air pollutants (AP) are a serious environmental problem that affects climate change and air quality in megacities. About 80 % of air pollution in São Paulo comes from vehicles. This work aimed to develop a methodology using a traffic demand model for GHG and AP inventories of vehicular emissions and demonstrate its applicability to the Metropolitan Area of São Paulo (MASP) as a part of regional air quality and climate change modelling. These high-resolution emission inventories also allow identifying hot spots of air pollution and poor air quality with a spatial resolution of 0.5 km and temporal resolution of 1 h. With this, we also intend to develop an approach for the validation of the emission model through low cost sensor measurements. These sensors will be placed through the MASP close to the identified vehicle emission hot spots to continuously measure over one-year duration to address a novel question on how the low-cost sensors data can be applied for improving the model performance and air quality monitoring. This paper integrates two approaches: the vehicle emission and air quality modeling and the use of low-cost sensors for model validation and develop novel approaches for high-resolution spatial mapping. This work provided a basis for establishing sound climate change policies in other areas such as public health and urban planning. These high-resolution emission inventories also allowed identifying hot spots of air pollution and poor air quality with a spatial resolution of 0.5 km and temporal resolution of 1 h. Data from sensors NOTS were compared with reference data obtained from the Osasco monitoring network website and data from devices at other nearby air quality monitoring stations. This comparison made it possible to determine the errors for adjusting the calibration model in the field.The calibration of the NOTS platforms considered the co-location between the NOTS devices and the CETESB monitor platform.