Work

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

Year: 2025

Type: data-paper

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 PM 2.5 , PM 10 , NO 2 , O 3 , 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.

Source: Data in Brief

DOI: 10.1016/j.dib.2025.111683

Authors: Slave Temkov, Pance Cavkovski, Petre Lameski, Eftim Zdravevski, Michael A. Herzog, Vladimir Trajkovik

Institutions: Ss. Cyril and Methodius University in Skopje, Hochschule Magdeburg-Stendal

Language: English

Topic: Air Quality Monitoring and Forecasting

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $1,220