scholarly journals INVESTIGATION OF THE AIR QUALITY CHANGE EFFECT ON GNSS SIGNALS

2017 ◽  
Vol IV-4/W4 ◽  
pp. 229-233
Author(s):  
G. Gurbuz ◽  
K. S. Gormus ◽  
U. Altan
Keyword(s):  
Air Pollution ◽  
Power Plants ◽  
Thermal Power ◽  
Mapping Function ◽  
Satellite System ◽  
Study Data ◽  
Air Pollutant ◽  
Zenith Delay ◽  
Turkish State ◽  
Global Navigation Satellite

Air pollution is the most important environmental problem in Zonguldak city center. Since bituminous coal is used for domestic heating in houses and generating electricity in thermal power plants, particulate matter (PM<sub>10</sub>) is the leading air pollutant. Previous studies have shown that the water vapor in the troposphere is responsible for the tropospheric zenith delay in Global Navigation Satellite System (GNSS) measurements. In this study, data obtained from the ZONG GNSS station from Türkiye Ulusal Sabit GNSS Ağı (TUSAGA-Active network) in the central district of Zonguldak province, processed with GIPSY-OASIS II and GAMIT/GlobK software using the VMF1 mapping function, which is developed previously and considered to be the most accurate model. The resulting values were examined separately in terms of software. The meteorological parameters obtained from the Turkish State Meteorological Service and the air pollution values obtained from the Ministry of Environment and Urban Planning were analyzed and the zenith delay values were compared. When wet zenith delays of different days with different amounts of PM<sub>10</sub> concentrations were examined in succession and under the same meteorological conditions, differences in the range of 20&amp;ndash;40&amp;thinsp;mm on ZTD were observed.

scholarly journals Water Vapor Retrievals from Spectral Direct Irradiance Measured with an EKO MS-711 Spectroradiometer—Intercomparison with Other Techniques

2021 ◽  
Vol 13 (3) ◽  
pp. 350
Author(s):  
Rosa Delia García ◽  
Emilio Cuevas ◽  
Victoria Eugenia Cachorro ◽  
Omaira E. García ◽  
África Barreto ◽  
...  
Keyword(s):  
Water Vapor ◽  
Power Plants ◽  
Precipitable Water ◽  
Satellite System ◽  
Infrared Spectrometry ◽  
Radiative Balance ◽  
Direct Normal Irradiance ◽  
Routine Basis ◽  
Solar Power Plants ◽  
Global Navigation Satellite

Precipitable water vapor retrievals are of major importance for assessing and understanding atmospheric radiative balance and solar radiation resources. On that basis, this study presents the first PWV values measured with a novel EKO MS-711 grating spectroradiometer from direct normal irradiance in the spectral range between 930 and 960 nm at the Izaña Observatory (IZO, Spain) between April and December 2019. The expanded uncertainty of PWV (UPWV) was theoretically evaluated using the Monte-Carlo method, obtaining an averaged value of 0.37 ± 0.11 mm. The estimated uncertainty presents a clear dependence on PWV. For PWV ≤ 5 mm (62% of the data), the mean UPWV is 0.31 ± 0.07 mm, while for PWV > 5 mm (38% of the data) is 0.47 ± 0.08 mm. In addition, the EKO PWV retrievals were comprehensively compared against the PWV measurements from several reference techniques available at IZO, including meteorological radiosondes, Global Navigation Satellite System (GNSS), CIMEL-AERONET sun photometer and Fourier Transform Infrared spectrometry (FTIR). The EKO PWV values closely align with the above mentioned different techniques, providing a mean bias and standard deviation of −0.30 ± 0.89 mm, 0.02 ± 0.68 mm, −0.57 ± 0.68 mm, and 0.33 ± 0.59 mm, with respect to the RS92, GNSS, FTIR and CIMEL-AERONET, respectively. According to the theoretical analysis, MB decreases when comparing values for PWV > 5 mm, leading to a PWV MB between −0.45 mm (EKO vs. FTIR), and 0.11 mm (EKO vs. CIMEL-AERONET). These results confirm that the EKO MS-711 spectroradiometer is precise enough to provide reliable PWV data on a routine basis and, as a result, can complement existing ground-based PWV observations. The implementation of PWV measurements in a spectroradiometer increases the capabilities of these types of instruments to simultaneously obtain key parameters used in certain applications such as monitoring solar power plants performance.

scholarly journals Analysis and Comparison of GPS Precipitable Water Estimates between Two Nearby Stations on Tahiti Island

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5578
Author(s):  
Fangzhao Zhang ◽  
Jean-Pierre Barriot ◽  
Guochang Xu ◽  
Marania Hopuare
Keyword(s):  
Mapping Function ◽  
Precipitable Water ◽  
Satellite System ◽  
Tropospheric Delay ◽  
Horizontal Distance ◽  
International Gnss Service ◽  
Weighted Mean Temperature ◽  
The Difference ◽  
Global Navigation Satellite ◽  
The Impact

Since Bevis first proposed Global Positioning System (GPS) meteorology in 1992, the precipitable water (PW) estimates retrieved from Global Navigation Satellite System (GNSS) networks with high accuracy have been widely used in many meteorological applications. The proper estimation of GNSS PW can be affected by the GNSS processing strategy as well as the local geographical properties of GNSS sites. To better understand the impact of these factors, we compare PW estimates from two nearby permanent GPS stations (THTI and FAA1) in the tropical Tahiti Island, a basalt shield volcano located in the South Pacific, with a mean slope of 8% and a diameter of 30 km. The altitude difference between the two stations is 86.14 m, and their horizontal distance difference is 2.56 km. In this paper, Bernese GNSS Software Version 5.2 with precise point positioning (PPP) and Vienna mapping function 1 (VMF1) was applied to estimate the zenith tropospheric delay (ZTD), which was compared with the International GNSS Service (IGS) Final products. The meteorological parameters sourced from the European Center for Medium-Range Weather Forecasts (ECMWF) and the local weighted mean temperature ( T m ) model were used to estimate the GPS PW for three years (May 2016 to April 2019). The results show that the differences of PW between two nearby GPS stations is nearly a constant with value 1.73 mm. In our case, this difference is mainly driven by insolation differences, the difference in altitude and the wind being only second factors.

scholarly journals Comparative analysis of blind tropospheric correction models in Ghana

2021 ◽  
Vol 11 (1) ◽  
pp. 14-26
Author(s):  
S. Osah ◽  
A. A. Acheampong ◽  
C. Fosu ◽  
I. Dadzie
Keyword(s):  
Prediction Models ◽  
Mapping Function ◽  
Satellite System ◽  
Tropospheric Delay ◽  
Model Bias ◽  
Significance Level ◽  
Significant Difference ◽  
Global Navigation Satellite ◽  
The Impact ◽  
Delay Prediction

Abstract The impact of the earth’s atmospheric layers, particularly the troposphere on Global Navigation satellite system (GNSS) signals has become a major concern in GNSS accurate positioning, navigation, surveillance and timing applications. For precise GNSS applications, tropospheric delay has to be mitigated as accurately as possible using tropospheric delay prediction models. However, the choice of a particular prediction model can signifi-cantly impair the positioning accuracy particularly when the model does not suit the user’s environment. A performance assessment of these prediction models for a suitable one is very important. In this paper, an assessment study of the performances of five blind tropospheric delay prediction models, the UNB3m, EGNOS, GTrop, GPT2w and GPT3 models was conducted in Ghana over six selected Continuously Operating Reference Stations (CORS) using the 1˚x1˚ gridded Vienna Mapping Function 3 (VMF3) zenith tropospheric delay (ZTD) product as a reference. The gridded VMF3-ZTD which is generated for every six hours on the 1˚x1˚ grids was bilinearly interpolated both space and time and transferred from the grid heights to the respective heights of the CORS locations. The results show that the GPT3 model performed better in estimating the ZTD with an overall mean (bias: 2.05 cm; RMS: 2.53 cm), followed by GPT2w model (bias: 2.32cm; RMS: 2.76cm) and GTrop model (bias: 2.41cm; 2.82cm). UNB3m model (bias: 6.23 cm; RMS: 6.43 cm) and EGNOS model (bias: 6.70 cm; RMS: 6.89 cm) performed poorly. A multiple comparison test (MCT) was further performed on the RMSE of each model to check if there is significant difference at 5% significant level. The results show that the GPT3, GPT2w and GTrop models are significantly indifferent at 5% significance level indicating that either of these models can be employed to mitigate the ZTD in the study area, nevertheless, the choice of GPT3 model will be more preferable.

scholarly journals A satellite-based method for modeling ionospheric slant TEC from GNSS observations: algorithm and validation

GPS Solutions ◽  
2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Wen Li ◽  
Zishen Li ◽  
Ningbo Wang ◽  
Ang Liu ◽  
Kai Zhou ◽  
...  
Keyword(s):  
Mapping Function ◽  
Satellite System ◽  
Ionospheric Delay ◽  
Electron Content ◽  
Observation Data ◽  
Total Electron ◽  
Observation Network ◽  
Different Seasons ◽  
Global Navigation Satellite ◽  
Validation Tests

AbstractTotal Electron Content (TEC) modeling is critical for Global Navigation Satellite System (GNSS) users to mitigate ionospheric delay errors. The mapping function is usually used for Vertical TEC ionospheric correction models for slant and vertical TEC conversion. But the mapping function cannot characterize TEC variation in different azimuths between the user and satellites. The ionospheric modeling error resulting from the mapping function tends to be bigger in middle and low latitudes. Therefore, a new algorithm for ionospheric Slant TEC (STEC) modeling with Satellite-based Ionospheric Model (SIM) is proposed in this contribution. Validation tests are carried out with GNSS observation data from the Crustal Movement Observation Network of China during different solar activities and in different seasons. The performance of SIM is compared with that of several commonly-used Global Ionospheric Map (GIM) and Regional Ionospheric Map (RIM) products. The results show that the STEC bias and STD of SIM are within 1.0 TECU and about 2.0 TECU, respectively, and SIM can correct over 90% STEC RMS errors, outperforming the GIM and RIM products. Consequently, the SIM algorithm can be a new option for high-accuracy ionospheric delay correction in regional and local GNSS networks.

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