Aerosol classification using sun photometer and lidar data within a machine learning algorithm-a possible nowcasting application

2021 ◽  
Author(s):  
Joelle Buxmann ◽  
Martin Osborne ◽  
Mike Protts ◽  
Debbie O'Sullivan
Keyword(s):  
Machine Learning ◽  
Biomass Burning ◽  
Machine Learning Algorithms ◽  
Supervised Machine Learning ◽  
Training Set ◽  
Angstrom Exponent ◽  
Ångström Exponent ◽  
Aerosol Classification ◽  
Aerosol Types ◽  
Ångstrom Exponent

<p>The Met Office operates a ground based operational network of nine polarisation Raman lidars (aerosol profiling instruments) and sun photometers (column integrated information). An aerosol classification scheme using supervised machine learning has been developed. The concept of Mahalanobis (~normalized) distance to identify the aerosol type  from individual Aerosol Robotic Network (AERONET) measurements including Extinction Angstrom Exponent, Absorption Angstrom Exponent, Single Scattering Albedo and Index of refraction is used for a subset of AERONET stations around the globe of known main aerosol types (training set). The aerosol types  include maritime, urban industrial, biomass burning and dust. We build a predictive model from this training set using K nearest neighbour machine learning algorithms. The relation of particle polarisation ratio and lidar ratio from the Raman lidar is used as a sanity check.  We apply the model to 3- 4 years of AERONET and profiling data across the UK, with instruments evenly distributed across the country, from Camborne in Cornwall to Lerwick in the Shetland Islands. We are showing more detailed data of a dust event in May 2016, dust/biomass burning aerosol mix from October 2017 (hurricane Ophelia) and more recent aerosol transported from the Canadian wild fires in September 2020. AERONET Level 2.0  data is compared to level 1.5 in order to determine the implications for the aerosol classification. Level 1.5 data are cloud-screened, but not quality assured and may not have the final calibration applied. Level 2.0  data have pre- and post-field calibration applied, are cloud-screened, and quality-assured data. As level 2.0 data is usually only available after 1-2 years (after a new calibration has been performed), it is important to understand the  usefulness of more readily available level 1.5 (cloud screened) data.</p><p>The aim is to build a real time aerosol classification application that can be used in Nowcasting.</p>

scholarly journals Detection of Saharan dust and biomass burning events using near real-time intensive aerosol optical properties in the northwestern Mediterranean

2016 ◽  
Author(s):  
M. Ealo ◽  
A. Alastuey ◽  
A. Ripoll ◽  
N. Pérez ◽  
M. C. Minguillón ◽  
...  
Keyword(s):  
Optical Properties ◽  
Biomass Burning ◽  
Mineral Dust ◽  
Organic Aerosol ◽  
Saharan Dust ◽  
Aerosol Optical Properties ◽  
Angstrom Exponent ◽  
Ångström Exponent ◽  
Dust Events ◽  
Ångstrom Exponent

Abstract. The study of Saharan dust events (SDE) and biomass burning (BB) emissions are both topic of great scientific interest since they are frequent and important polluting scenarios affecting air quality and climate. The main aim of this work is evaluating the feasibility of using near real-time in situ aerosol optical measurements for the detection of these atmospheric events in the Western Mediterranean Basin (WMB). With this aim, intensive aerosol optical properties (SAE: scattering Ångström exponent, AAE: absorption Ångström exponent, SSAAE: single scattering albedo Ångström exponent, and g: asymmetry parameter) were derived from multi-wavelength aerosol light scattering, hemispheric backscattering and absorption measurements performed at regional (Montseny; MSY, 720 m a.s.l.) and continental (Montsec; MSA, 1570 m a.s.l.) background sites in the WMB. A sensitivity study aiming at calibrating the measured intensive optical properties for SDE and BB detection is presented and discussed. The detection of Saharan dust events (SDE) by means of the SSAAE parameter and Ångström matrix depended on the altitude of the measurement station, and on SDE intensity. At MSA (mountain-top site) SSAAE detected around 85% of SDE compared with 50% at MSY station, where pollution episodes dominated by fine anthropogenic particles frequently masked the effect of mineral dust on optical properties during less intense SDE. Furthermore, an interesting feature of SSAAE was its capability to detect the presence of mineral dust after the end of SDE. Thus, resuspension processes driven by summer regional atmospheric circulations and dry conditions after SDE favored the accumulation of mineral dust at regional level having important consequences for air quality. On average, SAE, AAE and g ranged between -0.7 and 1, 1.3 and 2.5, and 0.5 and 0.75, respectively, during SDE. Based on the Aethalometer model, biomass burning (BB) contribution to equivalent black carbon (BC) accounted for 36% and 40% at MSY and MSA respectively. Linear relationships were found between AAE and %BCbb, with AAE values reaching around 1.5 when %BCbb was higher than 50%. BB contribution to organic matter (OM) at MSY was around 30%. Thus FF combustion sources showed important contributions to both BC and OM in the region under study. Results for OM source apportionment showed good agreement with simultaneous biomass burning organic aerosol (BBOA) and hydrocarbon-like organic aerosol (HOA) calculated from Positive Matrix Factorization (PMF) applied to simultaneous Aerosol Mass Spectrometer (ACSM) measurements. A wildfire episode was identified at MSY, showing AAE values up to 2 when daily BB contributions to BC and OM were 73% and 78% respectively.

scholarly journals Multiyear Typology of Long-Range Transported Aerosols over Europe

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 482 ◽  
Author(s):  
Victor Nicolae ◽  
Camelia Talianu ◽  
Simona Andrei ◽  
Bogdan Antonescu ◽  
Dragoș Ene ◽  
...  
Keyword(s):  
Mean Values ◽  
Continental Scale ◽  
Angstrom Exponent ◽  
Circulation Types ◽  
Ångström Exponent ◽  
Lidar Ratio ◽  
The One ◽  
Aerosol Types ◽  
532 Nm ◽  
Ångstrom Exponent

In this study, AERONET (Aerosol Robotic Network) and EARLINET (European Aerosol Research Lidar Network) data from 17 collocated lidar and sun photometer stations were used to characterize the optical properties of aerosol and their types for the 2008–2018 period in various regions of Europe. The analysis was done on six cluster domains defined using circulation types around each station and their common circulation features. As concluded from the lidar photometer measurements, the typical aerosol particles observed during 2008–2018 over Europe were medium-sized, medium absorbing particles with low spectral dependence. The highest mean values for the lidar ratio at 532 nm were recorded over Northeastern Europe and were associated with Smoke particles, while the lowest mean values for the Angstrom exponent were identified over the Southwest cluster and were associated with Dust and Marine particles. Smoke (37%) and Continental (25%) aerosol types were the predominant aerosol types in Europe, followed by Continental Polluted (17%), Dust (10%), and Marine/Cloud (10%) types. The seasonal variability was insignificant at the continental scale, showing a small increase in the percentage of Smoke during spring and a small increase of Dust during autumn. The aerosol optical depth (AOD) slightly decreased with time, while the Angstrom exponent oscillated between “hot and smoky” years (2011–2015) on the one hand and “dusty” years (2008–2010) and “wet” years (2017–2018) on the other hand. The high variability from year to year showed that aerosol transport in the troposphere became more and more important in the overall balance of the columnar aerosol load.

scholarly journals Optical properties of different aerosol types: seven years of combined Raman-elastic backscatter lidar measurements in Thessaloniki, Greece

2010 ◽  
Vol 3 (3) ◽  
pp. 569-578 ◽  
Author(s):  
E. Giannakaki ◽  
D. S. Balis ◽  
V. Amiridis ◽  
C. Zerefos
Keyword(s):  
Saharan Dust ◽  
Downward Movement ◽  
Angstrom Exponent ◽  
Lidar Measurements ◽  
Ångström Exponent ◽  
Lidar Ratio ◽  
Local Path ◽  
Aerosol Types ◽  
Lidar Observations ◽  
Ångstrom Exponent

Abstract. We present our combined Raman/elastic backscatter lidar observations which were carried out at the EARLINET station of Thessaloniki, Greece, during the period 2001–2007. The largest optical depths are observed for Saharan dust and smoke aerosol particles. For local and continental polluted aerosols the measurements indicate high aerosol loads. However, measurements associated with the local path indicate enhanced aerosol load within the Planetary Boundary Layer. The lowest value of aerosol optical depth is observed for continental aerosols, from West directions with less free tropospheric contribution. The largest lidar ratios, of the order of 70 sr, are found for biomass burning aerosols. A significant and distinct correlation between lidar ratio and backscatter related Ångström exponent values were estimated for different aerosol categories. Scatter plot between lidar ratio values and Ångström exponent values for local and continental polluted aerosols does not show a significant correlation, with a large variation in both parameters possibly due to variable absorption characteristics of these aerosols. Finally for continental aerosols with west and northwest directions that follow downward movement when arriving at our site constantly low lidar ratios almost independent of size are found.

scholarly journals Optical properties of different aerosol types: seven years of combined Raman- elastic backscatter lidar measurements in Thessaloniki, Greece

2009 ◽  
Vol 2 (6) ◽  
pp. 3027-3054
Author(s):  
E. Giannakaki ◽  
D. S. Balis ◽  
V. Amiridis ◽  
C. Zerefos
Keyword(s):  
Saharan Dust ◽  
Scatter Plot ◽  
Angstrom Exponent ◽  
Lidar Measurements ◽  
Ångström Exponent ◽  
Lidar Ratio ◽  
Local Path ◽  
Aerosol Types ◽  
Lidar Observations ◽  
Ångstrom Exponent

Abstract. We present our combined Raman/elastic backscatter lidar observations which were carried out at the EARLINET station of Thessaloniki, Greece, during the period 2001–2007. The largest optical depths are observed for Saharan dust and smoke aerosol loads. For "local" and "continental polluted" aerosols the measurements indicate moderate aerosol loads. However, measurements associated with the "local" path show lower values of free tropospheric contribution (37% versus 46% for "continental polluted") and thus, enhanced aerosol load within the Planetary Boundary Layer. The lowest value of aerosol optical depth is observed for "continental clean" aerosols. The largest lidar ratios, of the order of 70 sr are found for biomass burning aerosols. A significant and distinct correlation between lidar ratio and backscatter related Ångström exponent values was estimated for well defined aerosol categories, which provides a statistical measure of the lidar ratio's dependency on aerosol-size, which is a useful tool for elastic lidar systems. Scatter plot between lidar ratio values and Ångström exponent values for "local" and "continental polluted" aerosols does not show a significant correlation, with a large variation in both parameters possibly due to variable absorption characteristics of these aerosols. Finally for "clean continental" aerosols we found constantly low lidar ratios almost independent of size.

scholarly journals Light absorption of brown carbon in eastern China based on 3-year multi-wavelength aerosol optical property observations at the SORPES station and an improved Absorption Ångstrom exponent segregation method

2018 ◽  
Author(s):  
Jiaping Wang ◽  
Wei Nie ◽  
Yafang Cheng ◽  
Yicheng Shen ◽  
Xuguang Chi ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Light Absorption ◽  
Mie Theory ◽  
Brown Carbon ◽  
Angstrom Exponent ◽  
Lagrangian Modeling ◽  
Ångström Exponent ◽  
Multi Wavelength ◽  
Ångstrom Exponent

Abstract. Brown carbon (BrC), a certain group of organic carbon (OC) with strong absorption from the visible to ultraviolet (UV) wavelengths, makes considerable contribution to light absorption on both global and regional scales. High concentration and proportion of OC has been reported in China, but studies of BrC absorption based on long-term observations are rather limited in this region. In this study, we reported 3-year results of light absorption of BrC based on continuous measurement at the Station for Observation Regional Processes of the Earth System (SORPES) in the Yangtze River Delta, China combined with Mie-theory calculation. Light absorption of BrC was obtained using an improved Absorption Ångstrom exponent (AAE) segregation method to calculate AAE of pure and non-absorbing coated black carbon (BC) at each time step based on Mie-theory simulation and measurement of multi-wavelength aerosol light absorption. By using this improved method, the variation of AAE over time is taken into consideration, making it applicable for long-term analysis. The yearly average light absorption of BrC (babs_BrC) at 370 nm was 4.3 Mm−1 at the SORPES station. The contribution of BrC to total aerosol absorption (PBrC) at 370 nm ranged from 6 % to 18 % (10th and 90th percentiles, respectively), and reached up to ~ 28 % in biomass burning-dominant season and winter. Both babs_BrC and PBrC exhibited clear seasonal cycles with two peaks in later spring/early summer (May–June, babs_BrC ~ 4 Mm−1, PBrC ~ 11 %) and winter (December, babs_BrC ~ 12 Mm−1, PBrC ~ 17 %), respectively. Lagrangian modeling and chemical signature observed at the site suggested that open biomass burning and residential emissions were the dominate sources influencing BrC in the two seasons.

scholarly journals Light absorption of brown carbon in eastern China based on 3-year multi-wavelength aerosol optical property observations and an improved absorption Ångström exponent segregation method

2018 ◽  
Vol 18 (12) ◽  
pp. 9061-9074 ◽  
Author(s):  
Jiaping Wang ◽  
Wei Nie ◽  
Yafang Cheng ◽  
Yicheng Shen ◽  
Xuguang Chi ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Light Absorption ◽  
Mie Theory ◽  
Time Step ◽  
Brown Carbon ◽  
Angstrom Exponent ◽  
Lagrangian Modeling ◽  
Ångström Exponent ◽  
Ångstrom Exponent

Abstract. Brown carbon (BrC), a certain group of organic carbon (OC) with strong absorption from the visible (VIS) to ultraviolet (UV) wavelengths, makes a considerable contribution to light absorption on both global and regional scales. A high concentration and proportion of OC has been reported in China, but studies of BrC absorption based on long-term observations are rather limited in this region. In this study, we reported 3-year results of light absorption of BrC based on continuous measurement at the Station for Observing Regional Processes of the Earth System (SORPES) in the Yangtze River Delta, China, combined with Mie theory calculation. Light absorption of BrC was obtained using an improved absorption Ångström exponent (AAE) segregation method. The AAE of non-absorbing coated black carbon (BC) at each time step is calculated based on Mie theory simulation, together with single particle soot photometer (SP2) and aethalometer observations. By using this improved method, the variation of the AAE over time is taken into consideration, making it applicable for long-term analysis. The annual average light absorption coefficient of BrC (babs_BrC) at 370 nm was 6.3 Mm−1 at the SORPES station. The contribution of BrC to total aerosol absorption (PBrC) at 370 nm ranged from 10.4 to 23.9 % (10th and 90th percentiles, respectively), and reached up to ∼ 33 % in the open-biomass-burning-dominant season and winter. Both babs_BrC and PBrC exhibited clear seasonal cycles with two peaks in later spring/early summer (May–June, babs_BrC ∼ 6 Mm−1, PBrC ∼ 17 %) and winter (December, babs_BrC ∼ 15 Mm−1, PBrC ∼ 22 %), respectively. Lagrangian modeling and the chemical signature observed at the site suggested that open biomass burning and residential coal/biofuel burning were the dominant sources influencing BrC in the two seasons, respectively.

scholarly journals Classifying aerosol type using in situ surface spectral aerosol optical properties

2017 ◽  
Vol 17 (19) ◽  
pp. 12097-12120 ◽  
Author(s):  
Lauren Schmeisser ◽  
Elisabeth Andrews ◽  
John A. Ogren ◽  
Patrick Sheridan ◽  
Anne Jefferson ◽  
...  
Keyword(s):  
Optical Properties ◽  
Carbonaceous Aerosol ◽  
Spatiotemporal Variability ◽  
Classification Methods ◽  
Aerosol Optical Properties ◽  
Angstrom Exponent ◽  
Ångström Exponent ◽  
Aerosol Classification ◽  
Ångstrom Exponent ◽  
Aerosol Type

Abstract. Knowledge of aerosol size and composition is important for determining radiative forcing effects of aerosols, identifying aerosol sources and improving aerosol satellite retrieval algorithms. The ability to extrapolate aerosol size and composition, or type, from intensive aerosol optical properties can help expand the current knowledge of spatiotemporal variability in aerosol type globally, particularly where chemical composition measurements do not exist concurrently with optical property measurements. This study uses medians of the scattering Ångström exponent (SAE), absorption Ångström exponent (AAE) and single scattering albedo (SSA) from 24 stations within the NOAA/ESRL Federated Aerosol Monitoring Network to infer aerosol type using previously published aerosol classification schemes.Three methods are implemented to obtain a best estimate of dominant aerosol type at each station using aerosol optical properties. The first method plots station medians into an AAE vs. SAE plot space, so that a unique combination of intensive properties corresponds with an aerosol type. The second typing method expands on the first by introducing a multivariate cluster analysis, which aims to group stations with similar optical characteristics and thus similar dominant aerosol type. The third and final classification method pairs 3-day backward air mass trajectories with median aerosol optical properties to explore the relationship between trajectory origin (proxy for likely aerosol type) and aerosol intensive parameters, while allowing for multiple dominant aerosol types at each station.The three aerosol classification methods have some common, and thus robust, results. In general, estimating dominant aerosol type using optical properties is best suited for site locations with a stable and homogenous aerosol population, particularly continental polluted (carbonaceous aerosol), marine polluted (carbonaceous aerosol mixed with sea salt) and continental dust/biomass sites (dust and carbonaceous aerosol); however, current classification schemes perform poorly when predicting dominant aerosol type at remote marine and Arctic sites and at stations with more complex locations and topography where variable aerosol populations are not well represented by median optical properties. Although the aerosol classification methods presented here provide new ways to reduce ambiguity in typing schemes, there is more work needed to find aerosol typing methods that are useful for a larger range of geographic locations and aerosol populations.

scholarly journals Aerosol climatology: dependence of the Angstrom exponent on wavelength over four AERONET sites

2007 ◽  
Vol 7 (3) ◽  
pp. 7347-7397 ◽  
Author(s):  
D. G. Kaskaoutis ◽  
H. D. Kambezidis ◽  
N. Hatzianastassiou ◽  
P. G. Kosmopoulos ◽  
K. V. S. Badarinath
Keyword(s):  
Second Order ◽  
Spectral Variation ◽  
Angstrom Exponent ◽  
Coarse Mode ◽  
Polynomial Fit ◽  
Ångström Exponent ◽  
Order Polynomial ◽  
Fine Mode ◽  
Aerosol Types ◽  
Ångstrom Exponent

Abstract. The Ångström exponent, α, is often used as a qualitative indicator of aerosol particle size. In this study, aerosol optical depth (AOD) and Ångström exponent (α) data were analyzed to obtain information about the adequacy of the simple use of the Ångström exponent for characterizing aerosols, and for exploring possibilities for a more efficient characterization of aerosols. This was made possible by taking advantage of the spectral variation of α, the so-called curvature. The data were taken from four selected AERONET stations, which are representative of four aerosol types, i.e. biomass burning, pollution, desert dust and maritime. Using the least-squares method, the Ångström-α was calculated in the spectral interval 340–870 nm, along with the coefficients α1 and α2 of the second order polynomial fit to the plotted logarithm of AOD versus the logarithm of wavelength, and the second derivative of α. The results show that the spectral curvature can provide important additional information about the different aerosol types, and can be effectively used to discriminate between them, since the fine-mode particles exhibit negative curvature, while the coarse-mode aerosols positive. In addition, the curvature has always to be taken into account in the computations of Ångström exponent values in the spectral intervals 380–440 nm and 675–870 nm, since fine-mode aerosols exhibit larger α675–870 than α380–440 values, and vice-versa for coarse-mode particles. A second-order polynomial fit simulates the spectral dependence of the AODs very well, while the associated constant term varies proportionally to the aerosol type. The correlation between the coefficients α1 and α2 of the second-order polynomial fit and the Ångström exponent α, and the atmospheric turbidity, is further investigated. The obtained results reveal important features, which can be used for better discriminating between different aerosol types.

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