The Dataset of Daily Air Quality for the Years 2013-2023 in Italy

2026-02-11

AI Summary

This study addresses the longstanding scarcity of comprehensive, high-quality, and readily accessible integrated air quality and climate datasets in Italy, which has hindered public health and policy research. To bridge this gap, the authors construct and publicly release the GRINS AQCLIM dataset, which harmonizes daily-scale measurements of air pollutants and climate variables from over 700 monitoring stations across Italy spanning 2013–2023. By integrating raw data from the European Environment Agency and the Copernicus Programme through a rigorous multi-stage quality control pipeline—including automated correction, manual validation, anomaly detection, and temporal alignment—the dataset provides the first nationally representative, decade-long, standardized, and stringently quality-controlled daily-resolution environmental record for Italy. This resource substantially enhances regional environmental data availability and robustly supports interdisciplinary research and evidence-based policymaking.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Data Mining & Knowledge Management: Intelligent Query Processing
• Machine Learning: Efficient ML / Green AI

Application Category

• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Web Mining and Content Analysis: Web data integration and cleaning
• Security and Privacy: Data transparency and provenance

Abstract

Air quality and climate are major issues in Italian society and lie at the intersection of many research fields, including public health and policy planning. There is an increasing need for readily available, easily accessible, ready-to-use and well-documented datasets on air quality and climate. In this paper, we present the GRINS AQCLIM dataset, created under the GRINS project framework covering the Italian domain for an extensive time period. It includes daily statistics (e.g., minimum, quartiles, mean, median and maximum) for a collection of air pollutant concentrations and climate variables at the locations of the 700+ available monitoring stations. Input data are retrieved from the European Environmental Agency and Copernicus Programme and were subjected to multiple processing steps to ensure their reliability and quality. These steps include automatic procedures for fixing raw files, manual inspection of stations information, the detection and removal of anomalies, and the temporal harmonisation on a daily basis. Datasets are hosted on Zenodo under open-access principles.

Problem

• air quality
• climate data
• dataset availability
• environmental monitoring
• public health

Innovation

• air quality dataset
• data harmonization
• anomaly detection
• open-access data
• daily statistics