A uniform classification of aerosol signature size distributions based on regression-guided and observational cluster analysis

Bismarck-Osten, Clemens von; Weber, Stephan

doi:10.1016/j.atmosenv.2014.02.050

Cited by 11 publications

(4 citation statements)

References 30 publications

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“…For the time period studied (24 January-12 March 2020), 874 h of available data (averaged from 10 s intervals -76 % coverage) from the OPC and 732 h from the SMPS (66 % coverage) were exposed to k-means clustering. k-means clustering is a method successfully used in many studies for particle source differentiation (Beddows et al, 2015;Brines et al, 2015, Von Bismarck-Osten andWeber, 2014;Giorio et al, 2015;Wegner et al, 2012) and has been shown to have better performance compared to other clustering techniques (Beddows et al, 2009;Salimi et al, 2014). The technique was found to produce clusters with the highest similarity between their elements and the highest separation against the other clusters formed (Hennig, 2007).…”

Section: K-means Clusteringmentioning

confidence: 99%

“…Measurements in ambient conditions also lead to discrepancies with researchgrade instruments, which often measure in controlled environments that are air conditioned (U.S. Environmental Protection Agency, 2016). The reproducibility and variability of the outputs from sensors of the same type can also be problematic (Austin et al, 2015;Sousan et al, 2016;Wang et al, 2015). Therefore, the need for constant and careful calibration is repeatedly highlighted for many studies that evaluate the potential of low-cost sensors (Rai et al, 2017;Spinelle et al, 2015Spinelle et al, , 2017.…”

Section: Introductionmentioning

confidence: 99%

“…The present study investigates the ability of low-cost sensors to provide measurements that can be used to identify the sources of pollution at a background site in Birmingham, UK, using clustering of particle size profiles. This method was successfully used in a number of previous studies, though with the use of measurements from research-grade instruments (Beddows et al, 2009(Beddows et al, , 2015Von Bismarck-Osten and Weber, 2014;Dall'Osto et al, 2011Sabaliauskas et al, 2013). To support the clustering method, chemical composition data from both research-grade and low-cost sensor instruments were used, as well as meteorological data from a closely located measurement station.…”

Section: Introductionmentioning

confidence: 99%

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Assessing the sources of particles at an urban background site using both regulatory instruments and low-cost sensors – a comparative study

et al. 2021

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Abstract. Measurement and source apportionment of atmospheric pollutants are crucial for the assessment of air quality and the implementation of policies for their improvement. In most cases, such measurements use expensive regulatory-grade instruments, which makes it difficult to achieve wide spatial coverage. Low-cost sensors may provide a more affordable alternative, but their capability and reliability in separating distinct sources of particles have not been tested extensively yet. The present study examines the ability of a low-cost optical particle counter (OPC) to identify the sources of particles and conditions that affect particle concentrations at an urban background site in Birmingham, UK. To help evaluate the results, the same analysis is performed on data from a regulatory-grade instrument (SMPS, scanning mobility particle sizer) and compared to the outcomes from the OPC analysis. The analysis of the low-cost sensor data manages to separate periods and atmospheric conditions according to the level of pollution at the site. It also successfully identifies a number of sources for the observed particles, which were also identified using the regulatory-grade instruments. The low-cost sensor, due to the particle size range measured (0.35 to 40 µm), performed rather well in differentiating sources of particles with sizes greater than 1 µm, though its ability to distinguish their diurnal variation, as well as to separate sources of smaller particles, at the site was limited. The current level of source identification demonstrated makes the technique useful for background site studies, where larger particles with smaller temporal variations are of significant importance. This study highlights the current capability of low-cost sensors in source identification and differentiation using clustering approaches. Future directions towards particulate matter source apportionment using low-cost OPCs are highlighted.

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Section: K-means Clusteringmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessing the sources of particles at an urban background site using both regulatory instruments and low-cost sensors – a comparative study

et al. 2021

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“…Aerosol size distribution, an important indicator of aerosol origins, is often used to establish aerosol models (Logan et al., 2013; Omar et al., 2005; Shettle & Fenn, 1979; von Bismarck‐Osten & Weber, 2014). The aerosol size distribution is generally described according to an earlier theory of lognormal distribution (Davies, 1974) and each component has unique parameters, such as modal radius and standard deviation.…”

Section: Introductionmentioning

confidence: 99%

Global Gridded Aerosol Models Established for Atmospheric Correction Over Inland and Nearshore Coastal Waters

Zhao

Feng

2023

JGR Atmospheres

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The use of standard aerosol models for atmospheric correction over inland and nearshore coastal waters generates large uncertainties due to their inability to appropriately characterize aerosols in those regions. To address this problem, we developed new aerosol models using data acquired from 1,475 Aerosol Robotic Network (AERONET) sites distributed in inland and coastal regions throughout the globe. We established spatially gridded (5°×5°) aerosol models on a climatological monthly scale, with a total of 3,207 new aerosol models developed for 310 grid cells worldwide. The monthly aerosol model for each grid was derived using mean monthly values of microphysical aerosol properties from AERONET data. The optical properties (i.e., single scattering albedo (SSA) and Ångström coefficient) of our global gridded aerosol models demonstrated considerable spatial and seasonal dynamics and deviated substantially from the aerosol models currently utilized by the National Aeronautics and Space Administration. We built associated lookup tables for all aerosol models and incorporated them into two atmospheric correction algorithms: the combined near‐infrared (NIR) and shortwave infrared (SWIR) algorithm (NIR‐SWIR) and the Atmospheric Correction algorithm for inLand and Nearshore Coastal waters (ACLANC). For both algorithms, the accuracies of atmospherically corrected satellite remote sensing reflectance (Rrs) improved markedly when the new aerosol models were used, and improvements were noted across all spectral bands and across all six inland and nearshore water bodies used in this study. Our new aerosol models can be easily applied to all ocean color satellite missions to obtain accurate Rrs products for inland and coastal waters worldwide.

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Using ambient noise measurements to model urban particle number size distributions at a traffic site

Löbig

Weber

2017

Atmospheric Pollution Research

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A uniform classification of aerosol signature size distributions based on regression-guided and observational cluster analysis

Cited by 11 publications

References 30 publications

Assessing the sources of particles at an urban background site using both regulatory instruments and low-cost sensors – a comparative study

Assessing the sources of particles at an urban background site using both regulatory instruments and low-cost sensors – a comparative study

Global Gridded Aerosol Models Established for Atmospheric Correction Over Inland and Nearshore Coastal Waters

Using ambient noise measurements to model urban particle number size distributions at a traffic site

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