scholarly journals Pollen observations at four EARLINET stations during the ACTRIS-COVID-19 campaign

2021 ◽  
Author(s):  
Xiaoxia Shang ◽  
Holger Baars ◽  
Iwona S. Stachlewska ◽  
Ina Mattis ◽  
Mika Komppula
Keyword(s):  
Least Square ◽  
Automatic Data ◽  
Case Examples ◽  
Pollen Types ◽  
Aerosol Classification ◽  
Atmospheric Pollen ◽  
Novel Method ◽  
Linear Least Square ◽  
532 Nm ◽  
Depolarization Ratios

Abstract. Lidar observations were analysed to characterize atmospheric pollen at four EARLINET (European Aerosol Research Lidar Network) stations (Hohenpeißenberg, Germany; Kuopio, Finland, Leipzig, Germany; and Warsaw, Poland) during the ACTRIS-COVID-19 campaign in May 2020. The re-analysis lidar data products, after the centralized and automatic data processing with the Single Calculus Chain (SCC), were used in this study, focusing on particle backscatter coefficients at 355 nm and 532 nm, and particle linear depolarization ratios (PDRs) at 532 nm. A novel method for the characterization of the pure pollen depolarization ratio was presented, based on the non-linear least square regression fitting using lidar-derived backscatter-related Ångström exponents (BAEs) and PDRs. Under the assumption that the BAE between 355 and 532 nm should be zero (± 0.5) for pure pollen, the pollen depolarization ratios were estimated: for Kuopio and Warsaw stations, the pollen depolarization ratios at 532 nm were of 0.24 (0.19–0.28) during the birch dominant pollen periods; whereas for Hohenpeiβenberg and Leipzig stations, the pollen depolarization ratios of 0.21 (0.15–0.27) and 0.20 (0.15–0.25) were observed for periods of mixture of birch and grass pollen. The method was also applied for the aerosol classification, using two case examples from the campaign periods: the different pollen types (or pollen mixtures) were identified at Warsaw station, and dust and pollen were classified at Hohenpeißenberg station.

scholarly journals Characterization of atmospheric pollen with active remote sensing

2021 ◽  
Author(s):  
◽  
Stephanie Bohlmann ◽  
Keyword(s):  
Lower Troposphere ◽  
Wavelength Dependence ◽  
Forest Site ◽  
Depolarization Ratio ◽  
Additional Information ◽  
Lidar Measurements ◽  
Atmospheric Pollen ◽  
Pollen Distribution ◽  
532 Nm ◽  
Depolarization Ratios

Atmospheric pollen is a well-known health threat causing allergy-related diseases. As a biogenic aerosol, pollen also affects the climate by directly absorbing and scattering solar radiation and by acting as cloud condensation or ice nuclei. A good understanding of pollen distribution and transport mechanisms is needed to evaluate the environmental and health impacts of pollen. However, pollen observations are usually performed close to ground and vertical information, which could be used to evaluate and improve pollen transport models, is widely missing. In this thesis, the applicability of lidar measurements to detect pollen in the atmosphere is investigated. For this purpose, measurements of the multiwavelength Raman polarization lidar PollyXT at the rural forest site in Vehmasmäki (Kuopio), Eastern Finland have been utilized. The depolarization ratio was identified to be the most valuable optical property for the detection of atmospheric pollen, as nonspherical pollen like pine and spruce pollen causes high depolarization ratios. However, detected depolarization ratios coincide with typical values for dusty mixtures and additional information such as backward trajectories need to be considered to ensure the absence of other depolarizing aerosols like dust. To separate pollen from background aerosol, a method to estimate the optical properties of pure pollen using lidar measurements was developed. Under the assumption that the Ångström exponent of pure pollen is zero, the depolarization ratio of pure pollen can be estimated. Depolarization ratios for birch and pine pollen at 355 and 532 nm were determined and suggested a wavelength dependence of the depolarization ratio. To further investigate this wavelength dependence, the possibility to use depolarization measurements of Halo Doppler lidars (1565 nm) was explored. In the lower troposphere, Halo Doppler lidars can provide reasonable depolarization values with comparable quality to PollyXT measurements. Finally, measurements of PollyXT and a Halo StreamLine Doppler lidar were used to determine the depolarization ratio at three wavelengths. A wavelength dependence of the particle depolarization ratio with maximum depolarization at 532 nm was found. This could be a characteristic feature of non-spherical pollen and the key to distinguish pollen from other depolarizing aerosol types.

GPS-DERIVED SECULAR VELOCITY FIELD AROUND SANGIHE ISLAND AND ITS IMPLICATION TO THE MOLUCCA SEA SEISMICITY

GEOMATIKA ◽  
2020 ◽  
Vol 26 (2) ◽  
pp. 107
Author(s):  
Leni Sophia Heliani ◽  
Cecep Pratama ◽  
Parseno Parseno ◽  
Nurrohmat Widjajanti ◽  
Dwi Lestari
Keyword(s):  
Surface Displacement ◽  
Active Regions ◽  
Least Square ◽  
The Other ◽  
Gps Data ◽  
West Side ◽  
Active Deformation ◽  
Secular Motion ◽  
Small Change ◽  
Linear Least Square

<p><em>Sangihe-Moluccas region is the most active seismicity in Indonesia. Between 2015 to 2018 there is four M6 class earthquake occurred close to the Sangihe-Moluccas region. These seismic active regions representing active deformation which is recorded on installed GPS for both campaign and continuous station. However, the origin of those frequent earthquakes has not been well understood especially related to GPS-derived secular motion. Therefore, we intend to estimate the secular motion inside and around Sangihe island. On the other hand, we also evaluate the effect of seismicity on GPS sites. Since our GPS data were conducted on yearly basis, we used an empirical global model of surface displacement due to coseismic activity. We calculate the offset that may be contained in the GPS site during its period</em><em>. </em><em>We remove the offset and estimate again the secular motion using linear least square. Hence, in comparison with the secular motion without considering the seismicity, we observe small change but systematically shifting the motion. We concluded the seismicity in the Molucca sea from 2015 to 2018 systematically change the secular motion around Sangihe Island at the sub-mm level. Finally, we obtained the secular motion toward each other between the east and west side within 1 to 5.5 cm/year displacement. </em></p>

scholarly journals An Indoor Visible Light Positioning System Using Tilted LEDs with High Accuracy

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 920
Author(s):  
Neha Chaudhary ◽  
Othman Isam Younus ◽  
Luis Nero Alves ◽  
Zabih Ghassemlooy ◽  
Stanislav Zvanovec ◽  
...  
Keyword(s):  
Visible Light ◽  
Polynomial Regression ◽  
Power Level ◽  
Least Square ◽  
Line Of Sight ◽  
Received Power ◽  
Strength Based ◽  
Complex Linear ◽  
Linear Least Square ◽  
First Time

The accuracy of the received signal strength-based visible light positioning (VLP) system in indoor applications is constrained by the tilt angles of transmitters (Txs) and receivers as well as multipath reflections. In this paper, for the first time, we show that tilting the Tx can be beneficial in VLP systems considering both line of sight (LoS) and non-line of sight transmission paths. With the Txs oriented towards the center of the receiving plane (i.e., the pointing center F), the received power level is maximized due to the LoS components on F. We also show that the proposed scheme offers a significant accuracy improvement of up to ~66% compared with a typical non-tilted Tx VLP at a dedicated location within a room using a low complex linear least square algorithm with polynomial regression. The effect of tilting the Tx on the lighting uniformity is also investigated and results proved that the uniformity achieved complies with the European Standard EN 12464-1. Furthermore, we show that the accuracy of VLP can be further enhanced with a minimum positioning error of 8 mm by changing the height of F.

High-Accuracy Fundamental Frequency Detection in Power System

2011 ◽  
Vol 383-390 ◽  
pp. 4962-4966
Author(s):  
Ling Li ◽  
Guo Bin Jin ◽  
Shao Ping Huang ◽  
Xiao Peng
Keyword(s):  
Power System ◽  
Fundamental Frequency ◽  
Frequency Measurement ◽  
Least Square ◽  
Signal Model ◽  
Least Square Estimation ◽  
Signal Process ◽  
Frequency Detection ◽  
Novel Method ◽  
Subspace Estimation

A novel method on frequency measurement based on improved TLS-ESPRIT (total least square estimation of signal parameters via rotational invariance techniques) is proposed in this paper with the research on fundamental frequency measurement in power system. TLS-ESPRIT is belong to subspace estimation in modern signal process. Noise is included in signal model, so it is independent on noise. But the same multi-poles cannot be taken when signal is in noise and based on TLS-ESPRIT. Multiple poles restoring is presented to take the true poles accurately. It is revealed that fundamental frequency is detected accurately in harmonics, interharmonics, noise and frequency fluctuations and better anti-noise ability in particular better adaptiveness on time varying signal in amplitude by simulation results.

scholarly journals Characteristics and Application of the NHPP Log-Logistic Reliability Model

2018 ◽  
Vol 8 (1) ◽  
pp. 44
Author(s):  
Lutfiah Ismail Al turk
Keyword(s):  
Evaluation Criteria ◽  
Real Data ◽  
Least Square ◽  
Estimation Methods ◽  
Data Sets ◽  
Reliability Model ◽  
Reliability Engineering ◽  
Reliability Models ◽  
Time Domain Data ◽  
Linear Least Square

In this paper, a Nonhomogeneous Poisson Process (NHPP) reliability model based on the two-parameter Log-Logistic (LL) distribution is considered. The essential model&rsquo;s characteristics are derived and represented graphically. The parameters of the model are estimated by the Maximum Likelihood (ML) and Non-linear Least Square (NLS) estimation methods for the case of time domain data. An application to show the flexibility of the considered model are conducted based on five real data sets and using three evaluation criteria. We hope this model will help as an alternative model to other useful reliability models for describing real data in reliability engineering area.

scholarly journals Airborne pollen observations using a multi-wavelength Raman polarization lidar in Finland: characterization of pure pollen types

2020 ◽  
Author(s):  
Xiaoxia Shang ◽  
Elina Giannakaki ◽  
Stephanie Bohlmann ◽  
Maria Filioglou ◽  
Annika Saarto ◽  
...  
Keyword(s):  
Optical Properties ◽  
Airborne Pollen ◽  
Pollen Grains ◽  
Wavelength Dependence ◽  
Depolarization Ratio ◽  
Mean Values ◽  
Pollen Types ◽  
Pine Pollen ◽  
Significant Wavelength ◽  
532 Nm

Abstract. We present a novel algorithm for characterizing the optical properties of pure pollen particles, based on the depolarization values obtained in lidar measurements. The algorithm was first tested and validated through a simulator, and then applied to the lidar observations during a four-month pollen campaign from May to August 2016 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio (62°44′ N, 27°33′ E), in Eastern Finland. Twenty types of pollen were observed and identified from concurrent measurements with Burkard sampler; Birch (Betula), pine (Pinus), spruce (Picea) and nettle (Urtica) pollen were most abundant, contributing more than 90 % of total pollen load, regarding number concentrations. Mean values of lidar-derived optical properties in the pollen layer were retrieved for four intense pollination periods (IPPs). Lidar ratios at both 355 and 532 nm ranged from 55 to 70 sr for all pollen types, without significant wavelength-dependence. Enhanced depolarization ratio was found when there were pollen grains in the atmosphere, and even higher depolarization ratio (with mean values of 25 % or 14 %) was observed with presence of the more non-spherical spruce or pine pollen. The depolarization ratio at 532 nm of pure pollen particles was assessed, resulting to 24 ± 3 % and 36 ± 5 % for birch and pine pollen, respectively. Pollen optical properties at 1064 nm and 355 nm were also estimated. The backscatter-related Ångström exponent between 532 and 1064 nm was assessed as ~ 0.8 (~ 0.5) for pure birch (pine) pollen, thus the longer wavelength would be better choice to trace pollen in the air. The pollen depolarization ratio at 355 nm of 17 % and 30 % were found for birch and pine pollen, respectively. The depolarization values show a wavelength dependence for pollen. This can be the key parameter for pollen detection and characterization.

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