scholarly journals Differences in aerosol absorption Ångström exponents between correction algorithms for particle soot absorption photometer measured on South African Highveld

2014 ◽  
Vol 7 (9) ◽  
pp. 9733-9769
Author(s):  
J. Backman ◽  
A. Virkkula ◽  
V. Vakkari ◽  
J. P. Beukes ◽  
P. Van Zyl ◽  
...  
Keyword(s):  
South African ◽  
Urban Pollution ◽  
Absolute Amount ◽  
Data Set ◽  
Aerosol Absorption ◽  
Remote Sites ◽  
Biomass Burning Aerosol ◽  
The Difference ◽  
Absorption Photometer ◽  
Absorption Measurements

Abstract. Absorption Ångstrom exponents (AAE) calculated from filter-based absorption measurements are often used to give information on the origin of the ambient aerosol, for example to distinguish between urban pollution and biomass burning aerosol. Filter-based absorption measurements are a widely used method and are commonly used at aerosol monitoring stations globally. Several correction algorithms are used to account for the artifacts associated with filter-based absorption techniques. These algorithms are of profound importance when determining the absolute amount of absorption by the aerosol. However, this study shows that there are significant differences between the AAEs calculated from these corrections. The study also shows that the difference between AAEs calculated using different corrections can lead to conflicting conclusions on the type of aerosol for the same data set. In this work the AAEs were calculated from data measured with a three-wavelength Particle Soot Absorption Photometer (PSAP) at Elandsfontein on deployed on the South African Highveld for 23 months. The sample air of the PSAP was diluted to prolong filter change intervals. The dilution-corrected PSAP showed a good agreement with a non-diluted MAAP. Thus, the study also shows that the applicability of the PSAP can be extended to remote sites are not often visited or suffer from high levels of pollution.

scholarly journals Differences in aerosol absorption Ångström exponents between correction algorithms for a particle soot absorption photometer measured on the South African Highveld

2014 ◽  
Vol 7 (12) ◽  
pp. 4285-4298 ◽  
Author(s):  
J. Backman ◽  
A. Virkkula ◽  
V. Vakkari ◽  
J. P. Beukes ◽  
P. G. Van Zyl ◽  
...  
Keyword(s):  
South African ◽  
Urban Pollution ◽  
Absolute Amount ◽  
The South ◽  
Data Set ◽  
Aerosol Absorption ◽  
The Difference ◽  
A Site ◽  
Absorption Photometer ◽  
Absorption Measurements

Abstract. Absorption Ångström exponents (AAEs) calculated from filter-based absorption measurements are often used to give information on the origin of the ambient aerosol, for example, to distinguish between urban pollution and biomass burning aerosol. Filter-based absorption measurements are widely used and are common at aerosol monitoring stations globally. Several correction algorithms are used to account for artefacts associated with filter-based absorption techniques. These algorithms are of profound importance when determining the absolute amount of absorption by the aerosol. However, this study shows that there are substantial differences between the AAEs calculated from these corrections. Depending on the used correction, AAEs can change by as much as 46%. The study also highlights that the difference between AAEs calculated using different corrections can lead to conflicting conclusions on the type of aerosol when using the same data set. The AAE ranged between 1.17 for non-corrected data to 1.96 for the correction that gave the greatest values. Furthermore, the study implies that the AAEs reported for a site depend on at which filter transmittance the filter is changed. In this work, the AAEs were calculated from data measured with a three-wavelength particle soot absorption photometer (PSAP) at Elandsfontein on the South African Highveld for 23 months. The sample air of the PSAP was diluted to prolong filter change intervals, by a factor of 15. The correlation coefficient between the dilution-corrected PSAP and a non-diluted Multi-Angle Absorption Photometer (MAAP) was 0.9. Thus, the study also shows that the applicability of the PSAP can be extended to remote sites that are not often visited or suffer from high levels of pollution.

scholarly journals Evaluating biases in filter-based aerosol absorption measurements using photoacoustic spectroscopy

2019 ◽  
Vol 12 (6) ◽  
pp. 3417-3434 ◽  
Author(s):  
Nicholas W. Davies ◽  
Cathryn Fox ◽  
Kate Szpek ◽  
Michael I. Cotterell ◽  
Jonathan W. Taylor ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Photoacoustic Spectroscopy ◽  
Strong Dependence ◽  
Single Scattering ◽  
Aerosol Absorption ◽  
Aerosol Mass ◽  
Correction Scheme ◽  
Measurement Biases ◽  
Absorption Photometer ◽  
Absorption Measurements

Abstract. Biases in absorption coefficients measured using a filter-based absorption photometer (Tricolor Absorption Photometer, or TAP) at wavelengths of 467, 528 and 652 nm are evaluated by comparing to measurements made using photoacoustic spectroscopy (PAS). We report comparisons for ambient sampling covering a range of aerosol types including urban, fresh biomass burning and aged biomass burning. Data are also used to evaluate the performance of three different TAP correction schemes. We found that photoacoustic and filter-based measurements were well correlated, but filter-based measurements generally overestimated absorption by up to 45 %. Biases varied with wavelength and depended on the correction scheme applied. Optimal agreement to PAS data was achieved by processing the filter-based measurements using the recently developed correction scheme of Müller et al. (2014), which consistently reduced biases to 0 %–18 % at all wavelengths. The biases were found to be a function of the ratio of organic aerosol mass to light-absorbing carbon mass, although applying the Müller et al. (2014) correction scheme to filter-based absorption measurements reduced the biases and the strength of this correlation significantly. Filter-based absorption measurement biases led to aerosol single-scattering albedos that were biased low by values in the range 0.00–0.07 and absorption Ångström exponents (AAEs) that were in error by ± (0.03–0.54). The discrepancy between the filter-based and PAS absorption measurements is lower than reported in some earlier studies and points to a strong dependence of filter-based measurement accuracy on aerosol source type.

scholarly journals Evaluating biases in filter-based aerosol absorption measurements using photoacoustic spectroscopy

2019 ◽  
Author(s):  
Nicholas W. Davies ◽  
Cathryn Fox ◽  
Kate Szpek ◽  
Michael I. Cotterell ◽  
Jonathan W. Taylor ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Photoacoustic Spectroscopy ◽  
Strong Dependence ◽  
Single Scattering ◽  
Aerosol Absorption ◽  
Aerosol Mass ◽  
Correction Scheme ◽  
Measurement Biases ◽  
Absorption Photometer ◽  
Absorption Measurements

Abstract. Biases in absorption coefficients measured using a filter-based absorption photometer (Tricolor Absorption Photometer, or TAP) at wavelengths of 467, 528 and 652 nm are evaluated by comparing to measurements made using photoacoustic spectroscopy (PAS). We report comparisons for ambient sampling covering a range of aerosol types including urban, fresh biomass burning and aged biomass burning. Data are also used to evaluate the performance of three different TAP correction schemes. We found that photoacoustic and filter-based measurements were well correlated, but filter-based measurements generally overestimated absorption by up to 45 %. Biases varied with wavelength and depended on the correction scheme applied. Optimal agreement to PAS data was achieved by processing the filter-based measurements using the recently developed correction scheme of Müller et al. (2014), which consistently reduced biases to 0–17 % at all wavelengths. The biases were found to be a function of the ratio of organic aerosol mass to light-absorbing carbon mass although applying the Müller et al. (2014) correction scheme to filter-based absorption measurements reduced the biases and the strength of this correlation significantly. Filter-based absorption measurement biases led to aerosol single-scattering albedos that were biased low by up to 0.07 and absorption Ångström exponents (AAE) that were in error by ±0.54. The discrepancy between the filter-based and PAS absorption measurements is lower than reported in some earlier studies, and points to a strong dependence of filter-based measurement accuracy on aerosol source type.

scholarly journals Determination of Aethalometer multiple-scattering enhancement parameters and impact on source apportionment during the winter 2017–2018 EMEP/ACTRIS/COLOSSAL campaign in Milan

2020 ◽  
Author(s):  
Vera Bernardoni ◽  
Luca Ferrero ◽  
Ezio Bolzacchini ◽  
Alice Corina Forello ◽  
Asta Gregorič ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Multiple Scattering ◽  
Filter Material ◽  
Wavelength Dependence ◽  
Optical Source ◽  
Attenuation Coefficients ◽  
Aerosol Absorption ◽  
The Difference ◽  
Absorption Photometer

Abstract. In the frame of the EMEP/ACTRIS/COLOSSAL campaign in Milan during winter 2018, equivalent black carbon measurements using the Aethalometer 31 (AE31), the Aethalometer 33 (AE33), and the Multi-Angle Absorption Photometer (MAAP) were carried out together with levoglucosan analyses on 12-h resolved PM2.5 samples collected in parallel. From AE31 and AE33 data, the loading-corrected aerosol attenuation coefficients (bATN) were calculated at 7 wavelengths (λs, where λ = 370, 470, 520, 590, 660, 880, 950 nm). Aerosol absorption coefficient at 637 nm (babs_MAAP) was determined by MAAP measurements. Furthermore, babs was also measured at 4 wavelengths (405, 532, 635, 780 nm) on the 12-h resolved PM2.5 samples by a polar photometer (PP_UniMI). After comparing PP_UniMI and MAAP results, we exploited PP_UniMI data to evaluate the filter multiple-scattering enhancement parameter at different wavelengths for AE31 and AE33. We obtained instrument- and wavelength-dependent multiple-scattering parameters by linear regression of the Aethalometer bATN against the babs measured by PP_UniMI. We found significant filter material, and hence instrumental, dependence of the multiple-scattering enhancement parameter with the difference up to 30 % between the AE31 and the AE33 tapes. The wavelength dependence and day/night variations were small – the difference between the smallest and largest value was up to 6 %. Data from the different instruments were used as input to the so-called “Aethalometer model” for optical source apportionment and instrument-dependence of the results was investigated. Inconsistencies among the source apportionment were found fixing the AE31 and AE33 multiple-scattering enhancement parameters to their usual values. Opposite, optimised multiple-scattering enhancement parameters led to 5 % agreement among the approaches. Also, the component-apportionment “MWAA model” was applied to the dataset. It resulted less sensitive to the instrument and the number of wavelengths, whereas significant differences in the determination of the absorption Ångström exponent for brown carbon were found (up to 22 %).

Difference Fourier Analysis of Glucose Embedded and Frozen Hydrated Purple Membrane

1982 ◽  
Vol 40 ◽  
pp. 74-75
Author(s):  
Jules S. Jaffe ◽  
Robert M. Glaeser
Keyword(s):  
Purple Membrane ◽  
Data Set ◽  
High Resolution Data ◽  
X Ray ◽  
X Ray Crystallography ◽  
Fourier Techniques ◽  
Versus Protein ◽  
The Difference ◽  
Difference Fourier ◽  
Ideal Method

Although difference Fourier techniques are standard in X-ray crystallography it has only been very recently that electron crystallographers have been able to take advantage of this method. We have combined a high resolution data set for frozen glucose embedded Purple Membrane (PM) with a data set collected from PM prepared in the frozen hydrated state in order to visualize any differences in structure due to the different methods of preparation. The increased contrast between protein-ice versus protein-glucose may prove to be an advantage of the frozen hydrated technique for visualizing those parts of bacteriorhodopsin that are embedded in glucose. In addition, surface groups of the protein may be disordered in glucose and ordered in the frozen state. The sensitivity of the difference Fourier technique to small changes in structure provides an ideal method for testing this hypothesis.

Event detection of different English data sources based on transfer learning

2021 ◽  
pp. 1-11
Author(s):  
Yanan Huang ◽  
Yuji Miao ◽  
Zhenjing Da
Keyword(s):  
Transfer Learning ◽  
Event Detection ◽  
Visual Analysis ◽  
Learning Algorithm ◽  
Data Sources ◽  
Data Set ◽  
Data Source ◽  
Single Data Source ◽  
The Difference ◽  
Single Data

The methods of multi-modal English event detection under a single data source and isomorphic event detection of different English data sources based on transfer learning still need to be improved. In order to improve the efficiency of English and data source time detection, based on the transfer learning algorithm, this paper proposes multi-modal event detection under a single data source and isomorphic event detection based on transfer learning for different data sources. Moreover, by stacking multiple classification models, this paper makes each feature merge with each other, and conducts confrontation training through the difference between the two classifiers to further make the distribution of different source data similar. In addition, in order to verify the algorithm proposed in this paper, a multi-source English event detection data set is collected through a data collection method. Finally, this paper uses the data set to verify the method proposed in this paper and compare it with the current most mainstream transfer learning methods. Through experimental analysis, convergence analysis, visual analysis and parameter evaluation, the effectiveness of the algorithm proposed in this paper is demonstrated.

Magnetotelluric static shift: Estimation and removal using the cokriging method

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. F25-F34 ◽  
Author(s):  
Benoit Tournerie ◽  
Michel Chouteau ◽  
Denis Marcotte
Keyword(s):  
Apparent Resistivity ◽  
A Priori ◽  
Shift Factor ◽  
Static Shift ◽  
Geostatistical Model ◽  
Data Set ◽  
Resistivity Sounding ◽  
The Difference ◽  
Cross Variogram

We present and test a new method to correct for the static shift affecting magnetotelluric (MT) apparent resistivity sounding curves. We use geostatistical analysis of apparent resistivity and phase data for selected periods. For each period, we first estimate and model the experimental variograms and cross variogram between phase and apparent resistivity. We then use the geostatistical model to estimate, by cokriging, the corrected apparent resistivities using the measured phases and apparent resistivities. The static shift factor is obtained as the difference between the logarithm of the corrected and measured apparent resistivities. We retain as final static shift estimates the ones for the period displaying the best correlation with the estimates at all periods. We present a 3D synthetic case study showing that the static shift is retrieved quite precisely when the static shift factors are uniformly distributed around zero. If the static shift distribution has a nonzero mean, we obtained best results when an apparent resistivity data subset can be identified a priori as unaffected by static shift and cokriging is done using only this subset. The method has been successfully tested on the synthetic COPROD-2S2 2D MT data set and on a 3D-survey data set from Las Cañadas Caldera (Tenerife, Canary Islands) severely affected by static shift.

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