Understanding Spatial Variability of NO2 in Urban Areas Using Spatial Modelling and Data Fusion Approaches

Abstract

Small-scale spatial variability in NO2 concentrations is analysed with the help of pollution maps. Maps of NO2 estimated by the Airviro dispersion model and land use regression (LUR) model are fused with measured NO2 concentrations from low-cost sensors (LCS), reference sensors and diffusion tubes. In this study, geostatistical universal kriging was employed for fusing (integrating) model estimations with measured NO2 concentrations. The results showed that the data fusion approach was capable of estimating realistic NO2 concentration maps that inherited spatial patterns of the pollutant from the model estimations and adjusted the modelled values using the measured concentrations. Maps produced by the fusion of NO2-LCS with NO2-LUR produced better results, with r-value 0.96 and RMSE 9.09. Data fusion adds value to both measured and estimated concentrations: the measured data are improved by predicting spatiotemporal gaps, whereas the modelled data are improved by constraining them with observed data. Hotspots of NO2 were shown in the city centre, eastern parts of the city towards the motorway (M1) and on some major roads. Air quality standards were exceeded at several locations in Sheffield, where annual mean NO2 levels were higher than 40 µg/m3. Road traffic was considered to be the dominant emission source of NO2 in Sheffield.

Changes in Air Quality Associated with Mobility Trends and Meteorological Conditions during COVID-19 Lockdown in Northern England, UK

“…Some studies have successfully used geolocation mobility data provided by Google and Apple as proxies of traffic to investigate movement and risk perception [35] and changes in air quality [36,37] during COVID-19 lockdown. Munir et al [38] in a study in Sheffield, UK highlighted the role of traffic in driving NO 2 emissions. These studies demonstrated the importance of meteorological conditions and mobility characteristics in controlling the levels of air pollution.…”

Spatio-temporal dynamics of aerosol distribution in an urban environment recorded in situ by means of a bike based monitoring system

“…Due to the limited number of recording stations, this study (Górka and Lewicka-Szczebak, 2013) only shows general trends that are not comparable with the higher resolution of this study. The same is valid for the study of Muni et al (2021), in which NO 2 concentrations were interpolated via the city of Sheffield, United Kingdom. The final interpolation results in statements about the influence of the topography and distance from the city center.…”

Identification of Neighborhood Hotspots via the Cumulative Hazard Index: Results From a Community‐Partnered Low‐Cost Sensor Deployment

“…Air pollution studies have routinely used various interpolation techniques to estimate concentrations in unsampled areas (Gressent et al., 2020 ; Munir et al., 2021 ). Interpolation involves applying mathematical processes to the measured concentrations to estimate values across a continuous spatial field.…”