A methodological framework for estimating ambient PM_2.5 particulate matter concentrations in the UK

Scientific evidence sustains PM_2.5 particles' inhalation may generate harmful impacts on human beings' health; therefore, their monitoring in ambient air is of paramount relevance in terms of public health. Due to the limited number of fixed stations within the air quality monitoring networks, development of methodological frameworks to model ambient air PM_2.5 particles is primordial to providing additional information on PM_2.5 exposure and its trends. In this sense, this work aims to offer a global easily-applicable tool to estimate ambient air PM_2.5 as a function of meteorological conditions using a multivariate analysis. Daily PM_2.5 data measured by 84 fixed monitoring stations and meteorological data from ERA5 (ECMWF Reanalysis v5) reanalysis daily based data between 2000 and 2021 across the United Kingdom were attended to develop the suggested approach. Data from January 2017 to December 2020 were employed to build a mathematical expression that related the dependent variable (PM_2.5) to predictor ones (sea-level pressure, planetary boundary layer height, temperature, precipitation, wind direction and speed), while 2021 data tested the model. Evaluation indicators evidenced a good performance of model (maximum values of RMSE, MAE and MAPE: 1.80 µg/m³, 3.24 µg/m³, and 20.63%, respectively), compiling the current legislation's requirements for modelling ambient air PM_2.5 concentrations. A retrospective analysis of meteorological features allowed estimating ambient air PM_2.5 concentrations from 2000 to 2021. The highest PM_2.5 concentrations relapsed in the Mid- and Southlands, while Northlands sustained the lowest concentrations.