A scalable framework for harmonizing, standardization, and correcting crowd-sourced low-cost sensor PM2.5 data across Europe
The article introduces a scalable framework designed to harmonize, standardize, and correct crowd-sourced low-cost sensor PM2.5 data across Europe. By addressing inconsistencies in data quality and calibration among various sensors, the framework enhances the reliability of citizen-generated air quality data. This advancement supports more accurate environmental monitoring and informed policymaking.
Related links
Related content
PublicationDaily high-resolution surface PM2.5 estimation over Europe by ML-based downscaling of the CAMS regional forecast
The article presents the S-MESH (Satellite and ML-based Estimation of Surface air quality at High resolution) framework for estimating daily PM2.5 concentrations…
PublicationData, dialogue and infrastructure: the benefits of eight years of Samen Meten
The article summarises eight years of the Samen Meten initiative by the Dutch National Institute for Public Health and the Environment (RIVM),…
PublicationData fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention
The article presents a novel method for integrating diverse environmental sensor data to improve spatial predictions. The authors propose an adaptive distance…