The second ACTRIS inter-comparison (2016) for Aerosol Chemical Speciation Monitors (ACSM) : Calibration protocols and instrument performance evaluations

AbstractThis work describes results obtained from the 2016 Aerosol Chemical Speciation Monitor (ACSM) intercomparison exercise performed at the Aerosol Chemical Monitor Calibration Center (ACMCC, France). Fifteen quadrupole ACSMs (Q_ACSM) from the European Research Infrastructure for the observation of Aerosols, Clouds and Trace gases (ACTRIS) network were calibrated using a new procedure that acquires calibration data under the same operating conditions as those used during sampling and hence gets information representative of instrument performance. The new calibration procedure notably resulted in a decrease in the spread of the measured sulfate mass concentrations, improving the reproducibility of inorganic species measurements between ACSMs as well as the consistency with co-located independent instruments. Tested calibration procedures also allowed for the investigation of artifacts in individual instruments, such as the overestimation of m/z 44 from organic aerosol. This effect was quantified by the m/z (mass-to-charge) 44 to nitrate ratio measured during ammonium nitrate calibrations, with values ranging from 0.03 to 0.26, showing that it can be significant for some instruments. The fragmentation table correction previously proposed to account for this artifact was applied to the measurements acquired during this study. For some instruments (those with high artifacts), this fragmentation table adjustment led to an ?overcorrection? of the f44 (m/z 44/Org) signal. This correction based on measurements made with pure NH4NO3, assumes that the magnitude of the artifact is independent of chemical composition. Using data acquired at different NH4NO3 mixing ratios (from solutions of NH4NO3 and (NH4)2SO4) we observe that the magnitude of the artifact varies as a function of composition. Here we applied an updated correction, dependent on the ambient NO3 mass fraction, which resulted in an improved agreement in organic signal among instruments. This work illustrates the benefits of integrating new calibration procedures and artifact corrections, but also highlights the benefits of these intercomparison exercises to continue to improve our knowledge of how these instruments operate, and assist us in interpreting atmospheric chemistry.Peer reviewe

European aerosol phenomenology - 8 : Harmonised source apportionment of organic aerosol using 22 Year-long ACSM/AMS datasets

Organic aerosol (OA) is a key component of total submicron particulate matter (PM1), and comprehensive knowledge of OA sources across Europe is crucial to mitigate PM1 levels. Europe has a well-established air quality research infrastructure from which yearlong datasets using 21 aerosol chemical speciation monitors (ACSMs) and 1 aerosol mass spectrometer (AMS) were gathered during 2013-2019. It includes 9 non-urban and 13 urban sites. This study developed a state-of-the-art source apportionment protocol to analyse long-term OA mass spectrum data by applying the most advanced source apportionment strategies (i.e., rolling PMF, ME-2, and bootstrap). This harmonised protocol was followed strictly for all 22 datasets, making the source apportionment results more comparable. In addition, it enables quantification of the most common OA components such as hydrocarbon-like OA (HOA), biomass burning OA (BBOA), cooking-like OA (COA), more oxidised-oxygenated OA (MO-OOA), and less oxidised-oxygenated OA (LO-OOA). Other components such as coal combustion OA (CCOA), solid fuel OA (SFOA: mainly mixture of coal and peat combustion), cigarette smoke OA (CSOA), sea salt (mostly inorganic but part of the OA mass spectrum), coffee OA, and ship industry OA could also be separated at a few specific sites. Oxygenated OA (OOA) components make up most of the submicron OA mass (average = 71.1%, range from 43.7 to 100%). Solid fuel combustion-related OA components (i.e., BBOA, CCOA, and SFOA) are still considerable with in total 16.0% yearly contribution to the OA, yet mainly during winter months (21.4%). Overall, this comprehensive protocol works effectively across all sites governed by different sources and generates robust and consistent source apportionment results. Our work presents a comprehensive overview of OA sources in Europe with a unique combination of high time resolution (30-240 min) and long-term data coverage (9-36 months), providing essential information to improve/validate air quality, health impact, and climate models.Peer reviewe

Independent Retrieval of Aerosol Type From Lidar

This paper presents an algorithm for aerosol typing from multiwavelength lidar data, based on Artificial Neural Networks. The aerosol model used to simulate optical properties for the training of the network is described. The algorithm is tested on real observations from ESA-CALIPSO database

Variability of Biomass Burning Aerosols Layers and Near Ground

The aim of this study is to characterize aerosols from both chemical and optical point of view and to explore the conditions to sense the same particles in elevated layers and at the ground. Three days of continuous measurements using a multi-wavelength depolarization lidar(RALI) and a C-ToF-AMS aerosol mass spectrometer are analyzed. The presence of smoke particles was assessed in low level layers from RALI measurements. Chemical composition of submicronic volatile/semi-volatile aerosols at ground level was monitored by the CTOF AMS Several episodes of biomass burning aerosols have been identified by both techniques due to the presence of specific markers (f60, linear particle depolarization ratio, Ängström exponent)

Independent Retrieval of Aerosol Type From Lidar

This paper presents an algorithm for aerosol typing from multiwavelength lidar data, based on Artificial Neural Networks. The aerosol model used to simulate optical properties for the training of the network is described. The algorithm is tested on real observations from ESA-CALIPSO database

Variability of Biomass Burning Aerosols Layers and Near Ground

The aim of this study is to characterize aerosols from both chemical and optical point of view and to explore the conditions to sense the same particles in elevated layers and at the ground. Three days of continuous measurements using a multi-wavelength depolarization lidar(RALI) and a C-ToF-AMS aerosol mass spectrometer are analyzed. The presence of smoke particles was assessed in low level layers from RALI measurements. Chemical composition of submicronic volatile/semi-volatile aerosols at ground level was monitored by the CTOF AMS Several episodes of biomass burning aerosols have been identified by both techniques due to the presence of specific markers (f60, linear particle depolarization ratio, Ängström exponent)

Strengths and limitations of the NATALI code for aerosol typing from multiwavelength Raman lidar observations

A Python code was developed to automatically retrieve the aerosol type (and its predominant component in the mixture) from EARLINET’s 3 backscatter and 2 extinction data. The typing relies on Artificial Neural Networks which are trained to identify the most probable aerosol type from a set of mean-layer intensive optical parameters. This paper presents the use and limitations of the code with respect to the quality of the inputed lidar profiles, as well as with the assumptions made in the aerosol model

Strengths and limitations of the NATALI code for aerosol typing from multiwavelength Raman lidar observations

A Python code was developed to automatically retrieve the aerosol type (and its predominant component in the mixture) from EARLINET’s 3 backscatter and 2 extinction data. The typing relies on Artificial Neural Networks which are trained to identify the most probable aerosol type from a set of mean-layer intensive optical parameters. This paper presents the use and limitations of the code with respect to the quality of the inputed lidar profiles, as well as with the assumptions made in the aerosol model

Biomass burning aerosols characterization from ground based and profiling measurements

The study goal is to assess the chemical and optical properties of aerosols present in the lofted layers and at the ground. The biomass burning aerosols were evaluated in low level layers from multi-wavelength lidar measurements, while chemical composition at ground was assessed using an Aerosol Chemical Speciation Monitor (ACSM) and an Aethalometer. Classification of aerosol type and specific organic markers were used to explore the potential to sense the particles from the same origin at ground base and on profiles

Biomass burning aerosols characterization from ground based and profiling measurements

The study goal is to assess the chemical and optical properties of aerosols present in the lofted layers and at the ground. The biomass burning aerosols were evaluated in low level layers from multi-wavelength lidar measurements, while chemical composition at ground was assessed using an Aerosol Chemical Speciation Monitor (ACSM) and an Aethalometer. Classification of aerosol type and specific organic markers were used to explore the potential to sense the particles from the same origin at ground base and on profiles