Summer 2020 Fine Particulate Matter Research Data

Monitoring particulate matter levels in urban environments is essential for understanding environmental health and public safety. These records track the concentration of PM2.5 in Milan's atmosphere during the summer of 2020, utilising laser-scattering sensor technology to provide hourly mean values. The collection facilitates the study of air pollution phenomena and assists in the development of predictive models to safeguard city residents. By capturing high-frequency fluctuations in air quality, it provides a detailed foundation for researching urban environmental conditions during the warmer months.

The information is contained within a single CSV file named aq_milan_summer_2020.csv, with a file size of approximately 38.49 kB. It consists of 1,398 valid records across two columns. The data structure is highly uniform, with a 100% validity rate and no missing or mismatched entries reported for either the temporal markers or the particulate measurements. It is provided as a static record with an expected annual update frequency for subsequent seasons.

This resource is ideal for building time-series forecasting models aimed at predicting air quality fluctuations within a 24-hour window. It is well-suited for environmental research and the creation of interpretable visualisations that explain pollution trends to the general public. Additionally, analysts can use these hourly means to study the impact of summer weather patterns on urban air quality or to benchmark the performance of low-cost laser-scattering sensors against professional-grade monitoring equipment.

The geographic scope is focused specifically on Milan, Italy, at a fixed sensor location (45.4582861 North, 9.1675597 East). Temporally, the records capture a continuous series from 24 July 2020 through to 20 September 2020. The measurements provide a high-resolution view of the city's air during this specific seasonal window, reflecting the atmospheric conditions of the late summer period in a major European metropolitan area.

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Environmental scientists can leverage these records to study urban pollution cycles and the effectiveness of local air quality regulations. Data scientists may utilise the structured time-series data to train and test forecasting algorithms for predictive maintenance or public alert systems. Furthermore, educators and local government officials can use the findings to develop informative resources for citizens regarding city-wide air health and the science behind particulate matter.

Original Data Source: Summer 2020 Fine Particulate Matter Research Data