Description and applications of a mobile system performing on-road aerosol remote sensing and in situ measurements

Abstract

The majority of ground-based aerosols observations are limited to fixed locations, narrowing the knowledge on their spatial variability. In order to overcome this issue, a compact Mobile Aerosol Monitoring System (MAMS) was developed to explore the aerosol vertical and spatial variability. This mobile laboratory is equipped with a micropulse lidar, a sun photometer and an aerosol spectrometer. It is distinguished from other transportable platforms through its ability to perform on-road measurements and its unique feature lies in the sun photometer's capacity for tracking the sun during motion. The system presents a great flexibility, being able to respond quickly in case of sudden aerosol events such as pollution episodes, dust, fire or volcano outbreaks. On-road mapping of aerosol physical parameters such as attenuated aerosol backscatter, aerosol optical depth, particle number and mass concentration and size distribution is achieved through the MAMS. The performance of remote sensing instruments on-board has been evaluated through intercomparison with instruments in reference networks (i.e. AERONET and EARLINET), showing that the system is capable of providing high quality data. This also illustrates the application of such a system for instrument intercomparison field campaigns. Applications of the mobile system have been exemplified through two case studies in northern France. MODIS AOD data was compared to ground-based mobile sun photometer data. A good correlation was observed with R2 of 0.76, showing the usefulness of the mobile system for validation of satellite-derived products. The performance of BSC-DREAM8b dust model has been tested by comparison of results from simulations for the lidar–sun-photometer derived extinction coefficient and mass concentration profiles. The comparison indicated that observations and the model are in good agreement in describing the vertical variability of dust layers. Moreover, on-road measurements of PM10 were compared with modelled PM10 concentrations and with ATMO Hauts-de-France and AIRPARIF air quality in situ measurements, presenting an excellent agreement in horizontal spatial representativity of PM10. This proves a possible application of mobile platforms for evaluating the chemistry-models performances.