Predicting fine-scale daily NO over Mexico City using an ensemble modeling approach.

In recent years, there has been growing interest in developing air pollution prediction models to reduce exposure measurement error in epidemiologic studies. However, efforts for localized, fine-scale prediction models have been predominantly focused in the United States and Europe. Furthermore, the availability of new satellite instruments such as the TROPOsopheric Monitoring Instrument (TROPOMI) provides novel opportunities for modeling efforts.

Short-term NO exposure and cognitive and mental health: A panel study based on a citizen science project in Barcelona, Spain.

Background: The association between short-term exposure to air pollution and cognitive and mental health has not been thoroughly investigated so far.

Objectives: We conducted a panel study co-designed with citizens to assess whether air pollution can affect attention, perceived stress, mood and sleep quality.

Methods: From September 2020 to March 2021, we followed 288 adults (mean age = 37.

A new method for deriving trace gas emission inventories from satellite observations: The case of SO over China.

A method is developed that allows the construction of spatial emission inventories. The method is applied for anthropogenic SO over China (0.25°×0.

Air-quality modelling in the Lake Baikal region.

In this paper, we assess the status of the air quality in the Lake Baikal region which is strongly influenced by the presence of anthropogenic pollution sources. We combined the local data, with global databases, remote sensing imagery and modelling tools. This approach allows to inventorise the air-polluting sources and to quantify the air-quality concentration levels in the Lake Baikal region to a reasonable level, despite the fact that local data are scarcely available.