scholarly journals Aerosol type classification analysis using EARLINET multiwavelength and depolarization lidar observations

2020 ◽  
Author(s):  
Maria Mylonaki ◽  
Elina Giannakaki ◽  
Alexandros Papayannis ◽  
Christina-Anna Papanikolaou ◽  
Mika Komppula ◽  
...  
Keyword(s):  
Lower Percentage ◽  
Optical Parameters ◽  
Full Data ◽  
Data Set ◽  
Classification Analysis ◽  
Source Regions ◽  
Aerosol Classification ◽  
Aerosol Source ◽  
Type Classification ◽  
Aerosol Type

Abstract. We introduce an automated aerosol type classification method, called Source Classification ANalysis (SCAN). SCAN is based on predefined and characterized aerosol source regions, the time that the air parcel spends above each geographical region and a number of additional criteria. The output of SCAN is compared with two independent aerosol classification methods, which use the intensive optical parameters from lidar data: (1) Mahalanobis distance automatic aerosol type classification (MD) and (2) Neural Network Aerosol Typing Algorithm (NATALI). In this paper, data from the European Aerosol Research Lidar Network (EARLINET) have been used. A total of 97 free tropospheric (FT) aerosol layers from 4 typical EARLINET stations (i.e., Bucharest, Kuopio, Leipzig and Potenza) in the period 2014–2018 were classified based on a 3β+2α+1δ lidar configuration. We found that SCAN, being an optical property independent method, is not affected by the overlapping optical values of different aerosol types. Furthermore, SCAN has no limitations concerning its ability to classify different aerosol mixtures. Additionally, it is a valuable tool to classify aerosol layers, based on even to single (elastic) lidar signals, in case of lidar stations which cannot provide a full data set (3β+2α+1δ) of aerosol optical properties, therefore it can work independently of the capabilities of a lidar system. Finally, our results show that NATALI has the lower percentage of unclassified layers (4 %), while MD has the percentage of unclassified layers (50 %) and the lower percentage of cases classified as aerosol mixtures (5 %).

scholarly journals Aerosol type classification analysis using EARLINET multiwavelength and depolarization lidar observations

2021 ◽  
Vol 21 (3) ◽  
pp. 2211-2227
Author(s):  
Maria Mylonaki ◽  
Elina Giannakaki ◽  
Alexandros Papayannis ◽  
Christina-Anna Papanikolaou ◽  
Mika Komppula ◽  
...  
Keyword(s):  
Optical Properties ◽  
Lower Percentage ◽  
Optical Parameters ◽  
Full Data ◽  
Data Set ◽  
Classification Analysis ◽  
Tropospheric Aerosol ◽  
Aerosol Classification ◽  
Type Classification ◽  
Aerosol Type

Abstract. We introduce an automated aerosol type classification method, called Source Classification Analysis (SCAN). SCAN is based on predefined and characterized aerosol source regions, the time that the air parcel spends above each geographical region, and a number of additional criteria. The output of SCAN is compared with two independent aerosol classification methods, which use the intensive optical parameters from lidar data: (1) the Mahalanobis distance automatic aerosol type classification (MD) and (2) a neural network aerosol typing algorithm (NATALI). In this paper, data from the European Aerosol Research Lidar Network (EARLINET) have been used. A total of 97 free tropospheric aerosol layers from four typical EARLINET stations (i.e., Bucharest, Kuopio, Leipzig, and Potenza) in the period 2014–2018 were classified based on a 3β+2α+1δ lidar configuration. We found that SCAN, as a method independent of optical properties, is not affected by overlapping optical values of different aerosol types. Furthermore, SCAN has no limitations concerning its ability to classify different aerosol mixtures. Additionally, it is a valuable tool to classify aerosol layers based on even single (elastic) lidar signals in the case of lidar stations that cannot provide a full data set (3β+2α+1δ) of aerosol optical properties; therefore, it can work independently of the capabilities of a lidar system. Finally, our results show that NATALI has a lower percentage of unclassified layers (4 %), while MD has a higher percentage of unclassified layers (50 %) and a lower percentage of cases classified as aerosol mixtures (5 %).

scholarly journals Application of spectral analysis techniques to the intercomparison of aerosol data – Part 4: Synthesized analysis of multisensor satellite and ground-based AOD measurements using combined maximum covariance analysis

2014 ◽  
Vol 7 (8) ◽  
pp. 2531-2549 ◽  
Author(s):  
J. Li ◽  
B. E. Carlson ◽  
A. A. Lacis
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Satellite Data ◽  
Covariance Analysis ◽  
Data Sets ◽  
Data Set ◽  
Maximum Covariance Analysis ◽  
Source Regions ◽  
Cross Covariance ◽  
Aerosol Source

Abstract. In this paper, we introduce the usage of a newly developed spectral decomposition technique – combined maximum covariance analysis (CMCA) – in the spatiotemporal comparison of four satellite data sets and ground-based observations of aerosol optical depth (AOD). This technique is based on commonly used principal component analysis (PCA) and maximum covariance analysis (MCA). By decomposing the cross-covariance matrix between the joint satellite data field and Aerosol Robotic Network (AERONET) station data, both parallel comparison across different satellite data sets and the evaluation of the satellite data against the AERONET measurements are simultaneously realized. We show that this new method not only confirms the seasonal and interannual variability of aerosol optical depth, aerosol-source regions and events represented by different satellite data sets, but also identifies the strengths and weaknesses of each data set in capturing the variability associated with sources, events or aerosol types. Furthermore, by examining the spread of the spatial modes of different satellite fields, regions with the largest uncertainties in aerosol observation are identified. We also present two regional case studies that respectively demonstrate the capability of the CMCA technique in assessing the representation of an extreme event in different data sets, and in evaluating the performance of different data sets on seasonal and interannual timescales. Global results indicate that different data sets agree qualitatively for major aerosol-source regions. Discrepancies are mostly found over the Sahel, India, eastern and southeastern Asia. Results for eastern Europe suggest that the intense wildfire event in Russia during summer 2010 was less well-represented by SeaWiFS (Sea-viewing Wide Field-of-view Sensor) and OMI (Ozone Monitoring Instrument), which might be due to misclassification of smoke plumes as clouds. Analysis for the Indian subcontinent shows that here SeaWiFS agrees best with AERONET in terms of seasonality for both the Gangetic Basin and southern India, while on interannual timescales it has the poorest agreement.

scholarly journals Aerosol Typing Based on Multiwavelength Lidar Observations and Meteorological Model Data

2020 ◽  
Vol 237 ◽  
pp. 08003
Author(s):  
Maria Mylonaki ◽  
Elina Giannakaki ◽  
Alexandros Papayannis ◽  
Elena Floca ◽  
Mika Komppula
Keyword(s):  
Typical Case ◽  
Classification Methods ◽  
Model Data ◽  
Meteorological Model ◽  
Aerosol Classification ◽  
Lidar Observations ◽  
Type Classification ◽  
Aerosol Characterization ◽  
Aerosol Type

Three different aerosol classification methods have been used to characterize lidar observations: Mahalanobis distance automatic aerosol type classification, Neural Network Aerosol Typing Algorithm (NATALI) and Source and Analysis (SCAN) aerosol classification. The data selection has been made through the EARLINET database depending on the 3b+2a+1δ optical property availability. One hundred aerosol layers from four EARLINET stations (Bucharest, Kuopio, Leipzig and Potenza) have been classified. We present a typical case study of aerosol characterization observed by the MUSA system over Potenza on the 11th of April 2016 (20:30-21:30 UTC).

scholarly journals Back in Time for Breakfast: An Analysis of the Changing Breakfast Cereal Aisle

Nutrients ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 489
Author(s):  
Emilie Croisier ◽  
Jaimee Hughes ◽  
Stephanie Duncombe ◽  
Sara Grafenauer
Keyword(s):  
Dietary Fibre ◽  
Saturated Fat ◽  
Health Claims ◽  
Whole Grain ◽  
Breakfast Cereal ◽  
Full Data ◽  
Data Set ◽  
Time Points ◽  
Total Fat ◽  
Over Time

Breakfast cereal improves overall diet quality yet is under constant scrutiny with assertions that the category has not improved over time. This study aimed to comprehensively analyse the category of breakfast cereals, the nutritional values, and health claims across eight distinct sub-categories at four time points (2013, 2015, 2018, and 2020). An audit of products from four major supermarkets in metropolitan Sydney (Aldi, Coles, IGA, and Woolworths) collected ingredient lists, nutrition information, claims and Health Star Rating (HSR) for biscuits and bites; brans; bubbles, puffs, and flakes; granola and clusters; hot cereal flavoured; hot cereal plain; muesli; breakfast biscuits. The median (IQR) were calculated for energy, protein, fat, saturated fat, carbohydrate, sugars, dietary fibre, and sodium for comparisons over time points by nutrient. Data from 2013 was compared with 2020 (by sub-category and then for a sub-section of common products available at each time point). Product numbers between 2013 (n = 283) and 2020 (n = 543) almost doubled, led by granola and clusters. Whole grain cereals ≥ 8 g/serve made up 67% of products (↑114%). While there were positive changes in nutrient composition over time within the full data set, the most notable changes were in the nutrition composition of cereals marketed as the same product in both years (n = 134); with decreases in mean carbohydrate (2%), sugar (10%) and sodium (16%) (p < 0.000), while protein and total fat increased significantly (p = 0.036; p = 0.021). Claims regarding Dietary Fibre and Whole Grain doubled since 2013. Analysis of sub-categories of breakfast cereal assisted in identifying some changes over time, but products common to both timeframes provided a clearer analysis of change within the breakfast category, following introduction of HSR. Whole grain products were lower in the two target nutrients, sodium and sugars, and well-chosen products represent a better choice within this category.

scholarly journals Aerosol classification from airborne HSRL and comparisons with the CALIPSO vertical feature mask

2013 ◽  
Vol 6 (1) ◽  
pp. 1815-1858 ◽  
Author(s):  
S. P. Burton ◽  
R. A. Ferrare ◽  
M. A. Vaughan ◽  
A. H. Omar ◽  
R. R. Rogers ◽  
...  
Keyword(s):  
High Spectral Resolution ◽  
Dependent Observations ◽  
Aerosol Retrieval ◽  
Direct Measurements ◽  
Aerosol Classification ◽  
Lidar Ratio ◽  
Langley Research Center ◽  
High Spectral Resolution Lidar ◽  
Aerosol Types ◽  
Aerosol Type

Abstract. Aerosol classification products from the NASA Langley Research Center (LaRC) airborne High Spectral Resolution Lidar (HSRL-1) on the NASA B200 aircraft are compared with coincident V3.01 aerosol classification products from the CALIOP instrument on the CALIPSO satellite. For CALIOP, aerosol classification is a key input to the aerosol retrieval, and must be inferred using aerosol loading-dependent observations and location information. In contrast, HSRL-1 makes direct measurements of aerosol intensive properties, including the lidar ratio, that provide information on aerosol type. In this study, comparisons are made for 109 underflights of the CALIOP orbit track. We find that 62% of the CALIOP marine layers and 54% of the polluted continental layers agree with HSRL-1 classification results. In addition, 80% of the CALIOP desert dust layers are classified as either dust or dusty mix by HSRL-1. However, agreement is less for CALIOP smoke (13%) and polluted dust (35%) layers. Specific case studies are examined, giving insight into the performance of the CALIOP aerosol type algorithm. In particular, we find that the CALIOP polluted dust type is overused due to an attenuation-related depolarization bias. Furthermore, the polluted dust type frequently includes mixtures of dust plus marine aerosol. Finally, we find that CALIOP's identification of internal boundaries between different aerosol types in contact with each other frequently do not reflect the actual transitions between aerosol types accurately. Based on these findings, we give recommendations which may help to improve the CALIOP aerosol type algorithms.

scholarly journals Serum sodium changes in marathon participants who use NSAIDs

2018 ◽  
Vol 4 (1) ◽  
pp. e000364 ◽  
Author(s):  
Steven Whatmough ◽  
Stephen Mears ◽  
Courtney Kipps
Keyword(s):  
Serum Sodium ◽  
Fluid Intake ◽  
Large City ◽  
Control Group ◽  
Full Data ◽  
Data Set ◽  
Nsaid Group ◽  
Total Body ◽  
Average Serum ◽  
Internal And External Factors

IntroductionThe primary mechanism through which the development of exercise-associated hyponatraemia (EAH) occurs is excessive fluid intake. However, many internal and external factors have a role in the maintenance of total body water and non-steroidal anti-inflammatory medications (NSAIDs) have been implicated as a risk factor for the development of EAH. This study aimed to compare serum sodium concentrations ([Na]) in participants taking an NSAID before or during a marathon (NSAID group) and those not taking an NSAID (control group).MethodsParticipants in a large city marathon were recruited during race registration to participate in this study. Blood samples and body mass measurements took place on the morning of the marathon and immediately post marathon. Blood was analysed for [Na]. Data collected via questionnaires included athlete demographics, NSAID use and estimated fluid intake.ResultsWe obtained a full data set for 28 participants. Of these 28 participants, 16 took an NSAID on the day of the marathon. The average serum [Na] decreased by 2.1 mmol/L in the NSAID group, while it increased by 2.3 mmol/L in the control group NSAID group (p=0.0039). Estimated fluid intake was inversely correlated with both post-marathon serum [Na] and ∆ serum [Na] (r=−0.532, p=0.004 and r=−0.405 p=0.032, respectively).ConclusionSerum [Na] levels in participants who used an NSAID decreased over the course of the marathon while it increased in those who did not use an NSAID. Excessive fluid intake during a marathon was associated with a lower post-marathon serum [Na].

scholarly journals Lyman Break Galaxies at Redshiftz∼ 3: Survey Description and Full Data Set

2003 ◽  
Vol 592 (2) ◽  
pp. 728-754 ◽  
Author(s):  
Charles C. Steidel ◽  
Kurt L. Adelberger ◽  
Alice E. Shapley ◽  
Max Pettini ◽  
Mark Dickinson ◽  
...  
Keyword(s):  
Full Data ◽  
Data Set ◽  
Lyman Break Galaxies

Electoral Performance by Post-Rebel Parties

2018 ◽  
Vol 54 (3) ◽  
pp. 415-453 ◽  
Author(s):  
Carrie Manning ◽  
Ian Smith
Keyword(s):  
Legislative Elections ◽  
Full Data ◽  
Data Set ◽  
Factors Affecting ◽  
Future Performance ◽  
Organizational Experience ◽  
Varying Length ◽  
New Research ◽  
Electoral Performance ◽  
Positive Effect

This article explores the factors affecting post-rebel party electoral performance. We present new research tracking the participation of these groups in national legislative elections from 1990 to 2016. Our full data set covers 77 parties and 286 elections in 37 countries. It includes parties formed after conflicts of varying length and intensity, with different incompatibilities, in every region of the world, and in countries with disparate political histories. Our analysis suggests that post-rebel parties’ early electoral performance strongly affects future performance, and that competition – crowd-out by older rival parties – and pre-war organizational experience in politics have a significant positive effect, particularly for those parties that are consistently winning more than about 10 per cent of seats. But especially for parties that consistently win very low seat shares, organizational characteristics yield increasingly to environmental factors, most importantly the presence of rival parties and the barriers to representation presented by electoral rules.

scholarly journals Association of RASSF1A, DCR2, and CASP8 Methylation with Survival in Neuroblastoma: A Pooled Analysis Using Reconstructed Individual Patient Data

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Waleed M. Hassan ◽  
Mohamed S. Bakry ◽  
Timo Siepmann ◽  
Ben Illigens
Keyword(s):  
Overall Survival ◽  
Individual Patient Data ◽  
Wide Spectrum ◽  
Pooled Analysis ◽  
Patient Data ◽  
Epigenetic Alterations ◽  
Full Data ◽  
Data Set ◽  
Kaplan Meier ◽  
Registration Number

Neuroblastoma (NB) is a heterogeneous tumor affecting children. It shows a wide spectrum of clinical outcomes; therefore, development of risk stratification is critical to provide optimum treatment. Since epigenetic alterations such as DNA methylation have emerged as an important feature of both development and progression in NB, in this study, we aimed to quantify the effect of methylation of three distinct genes (RASSF1A, DCR2, and CASP8) on overall survival in NB patients. We performed a systematic review using PubMed, Embase, and Cochrane libraries. Individual patient data was retrieved from extracted Kaplan–Meier curves. Data from studies was then merged, and analysis was done on the full data set. Seven studies met the inclusion criteria. Methylation of the three genes had worse overall survival than the unmethylated arms. Five-year survival for the methylated arm of RASSF1A, DCR2, and CASP8 was 63.19% (95% CI 56.55-70.60), 57.78% (95% CI 47.63-70.08), and 56.39% (95% CI 49.53-64.19), respectively, while for the unmethylated arm, it was 93.10% (95% CI 87.40–99.1), 84.84% (95% CI 80.04-89.92), and 83.68% (95% CI 80.28-87.22), respectively. In conclusion, our results indicate that in NB patients, RASSF1A, DCR2, and CASP8 methylation is associated with poor prognosis. Large prospective studies will be necessary to confirm definitive correlation between methylation of these genes and survival taking into account all other known risk factors. (PROSPERO registration number CRD42017082264).

Azimuth estimation capabilities of the ARCESS regional seismic array

1993 ◽  
Vol 83 (4) ◽  
pp. 1213-1231
Author(s):  
Dorthe B. Carr
Keyword(s):  
Time Window ◽  
Source Region ◽  
Event Data ◽  
Small Aperture ◽  
Data Set ◽  
Low Frequencies ◽  
Source Regions ◽  
The Mean ◽  
Local Geology ◽  
Regional Arrays

Abstract The effect of local geology and noise conditions on the performance of a small regional array is investigated by comparing the regional Pn backazimuth estimation capabilities of the ARCESS array in northern Norway to the NORESS array. A broadband frequency-wavenumber estimator was used to calculate backazimuths from the Pn arrival for each of 203 regional events recorded at ARCESS while varying element spacing, frequency band, and time window. Most of the errors in backazimuth are less than 20° when appropriate parameter combinations are used, and mean backazimuth errors are close to zero. The best results are obtained using a 13-element configuration that has a 1.4 km aperture and a maximum station spacing of about 600 m. With the 13-element configuration and the data filtered to include frequencies between 3 and 10 Hz, the mean errors for the 203 event data set are less than 0.9°, and S.D. are as small as 16.9°. There are differences seen in the backazimuth estimation capabilities of ARCESS and NORESS with specific parameter combinations. The larger aperture configurations (10- and 17-elements) have smaller means at ARCESS, although the precision is about the same. The estimates using unfiltered data at ARCESS are poor, because of local noise conditions that increase the level of background noise at low frequencies. Overall the precision is better at NORESS, but both regional arrays have the best results using the 13-element configuration and filtering the data in the middle frequency range (3 to 10 Hz). Other factors investigated include SNR and source region. Backazimuth estimation statistics improve if only events with 5 dB of SNR are included in the data set at both ARCESS and NORESS. The mean errors move closer to zero and standard deviations decrease. The differences between the two arrays are not as pronounced. There are some path effects from different source regions around the ARCESS array. However, combinations of small aperture configurations and middle (3 to 10 Hz) frequency bands work well for events over the entire distance range of 30 to 1200 km. ARCESS and NORESS have similar backazimuth estimation capabilities even though there are differences in the local geology and noise conditions. Because a 13-element configuration produces reliable results for both arrays, it would be reasonable to reduce the number of elements in a regional array. This in turn will reduce the costs associated with building and deploying small regional arrays.

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