# Air pollution data: A dataset gathered through a crowd sensing platform

## TL;DR

This paper presents a detailed air pollution dataset collected using a crowd sensing platform in Skopje, offering insights into urban air and noise pollution.

## Contribution

The dataset introduces high-resolution, real-time air and noise pollution data collected over several years in multiple urban locations.

## Key findings

- The dataset includes pollutants like PM2.5, PM10, NO2, O3, and CO along with meteorological parameters.
- It provides insights into pollution trends and supports data-driven urban planning and policy development.
- The data spans from early 2018 to December 2024 with high spatial and temporal resolution.

## Abstract

This paper introduces an extensive dataset on air pollution monitoring, collected through a crowd sensing IoT platform. The dataset contains real-time measurements of various pollutants, including PM2.5, PM10, NO2, O3, and CO, enriched with meteorological parameters such as temperature, humidity, and atmospheric pressure. Additionally, it includes noise level measurements, offering insights into urban noise pollution. The data, collected across multiple urban locations in Skopje, North Macedonia, spans from early 2018 to December 2024, providing both high spatial and temporal resolution. This dataset is a valuable resource for studying pollution trends, forecasting pollution levels, identifying pollution sources, and assessing the impact of urban planning on air quality. All in all, it supports research aimed at improving air quality and public health through data-driven decision-making and policy development.