Raw Air Quality and Meteorological Data from February 11th, 2024 Pollution Event

This dataset contains pollutants concentration and meteorological data collected by several stations during a significant pollution event that occurred on February 11th, 2024. The data were gathered from air quality monitoring stations and meteorological stations located at various points, measuring a variety of pollutants and atmospheric parameters.

Dataset Content:
- Monitored pollutants: SO2, NO2, PM 2.5, and PM 10.
- Meteorological variables: Wind Direction and Speed.

Stations involved:
- Air Quality. In Ciudad Madero the station AQS-MR (AQS2036303358325010004B002B, in Altamira AQS-ACI (AQS2036303358325010004D002B), in Tampico AQS-PT (AQS2036303358325010004F002B) located in Puente Tampico and AQS-TA near to the airport (AQS20363033583250100040002E).
- Meteorological stations: ICIUDA228 [22.257, -97.823], ITAMPI7 [22.287, -97.894], ICIUDA207 [22.273, -97.841], ITAMPI4 [22.245, -97.863], ITAMPI9 [22.303, -97.883], IMIRAM24 [22.324, -97.872], IMIRAM25 [22.341, -97.887], IALTAM36 [22.404, -97.938], IALTAM35 [22.521, -98.127], and IALTAM33 [22.394, -97.895].

Data collection frequency:
In the case of the weather, every 5 minutes, resulting in a total of 288 data points per day for each station. And in the case of the air quality, is every minute, resulting in a total of 1440 data points per day for each station.

Event context:
After citizen reports about rotten egg-like smell in the vicinity of the local oil refinery in the Tampico-Madero-Altamira conurbation on February 11th, 2024, the local media showed vapor emissions from a chimney in the refinery. The authorities later confirmed that an electrical failure turned off a burner in one of the refinery processes, which in turn, lead to the turning on of the emergency washing system of the chimney, which at the end, caused the perceived emissions. The first citizen report of the smell was registered about 14:00 hr. This dataset covers the period before and after the reported emissions, following the evolution of the criteria pollutants ( SO2, NO2, PM2.5 and PM10) as well as the meteorological conditions that lead to the spatial diffusion of the emissions in the conurbation. This dataset offers a valuable resource for analyzing the impact of environmental conditions on air quality and public health due to specific events like this.