Stations In Region Research Articles

An Improved Deep Learning Approach Considering Spatiotemporal Heterogeneity for PM2.5 Prediction: A Case Study of Xinjiang, China

Prediction of fine particulate matter with particle size less than 2.5 µm (PM2.5) is an important component of atmospheric pollution warning and control management. In this study, we propose a deep learning model, namely, a spatiotemporal weighted neural network (STWNN), to address the challenge of poor long-term PM2.5 prediction in areas with sparse and uneven stations. The model, which is based on convolutional neural network–bidirectional long short-term memory (CNN–Bi-LSTM) and attention mechanisms and uses a geospatial data-driven approach, considers the spatiotemporal heterogeneity effec It is correct.ts of PM2.5. This approach effectively overcomes instability caused by sparse station data in forecasting daily average PM2.5 concentrations over the next week. The effectiveness of the STWNN model was evaluated using the Xinjiang Uygur Autonomous Region as the study area. Experimental results demonstrate that the STWNN exhibits higher performance (RMSE = 10.29, MAE = 6.4, R2 = 0.96, and IA = 0.81) than other models in overall prediction and seasonal clustering. Furthermore, the SHapley Additive exPlanations (SHAP) method was introduced to calculate the contribution and spatiotemporal variation of feature variables after the STWNN prediction model. The SHAP results indicate that the STWNN has significant potential in improving the performance of long-term PM2.5 prediction at the regional station level. Analyzing spatiotemporal differences in key feature variables that influence PM2.5 provides a scientific foundation for long-term pollution control and supports emergency response planning for heavy pollution events.

The dominant pests (Coleoptera) of cereal crops, and population forecast for this

Goal. Create a forecast of the development of harmful organisms in cereal crops, to determine the economic feasibility of applying plant protection measures.
 Methods. Analysis of the phytosanitary state of cereal crops in Ukraine, where the main attention is paid to the dominant pest species. Analysis of the areas of distribution of these pests, population dynamics, their phenology and the state of populations in the context of natural and climatic zones (Steppe, Forest-steppe and Polissya). To assess the phytosanitary state of crops, and its dynamic changes, the following are used: — the results of phytosanitary monitoring of crops (according to generally accepted methods), which were carried out directly by the staff of the forecast laboratory of the Institute of Plant Protection of NAAS; — current reports of researchers from other laboratories of the Institute of Plant Protection of NAAS from the places of business trips; — materials of decadal reports of regional plant protection stations, as well as signaling and forecasting points; — information on the phytosanitary situation from regional state research stations and institutes of NAAS.
 Results. A study of the phytosanitary state of cereal crops on the territory of Ukraine was carried out, the dominant species of pests were identified, materials were prepared regarding the peculiarities of the phytosanitary state in the conditions of the year, and a long-term (annual) forecast of the development of pests for the next year was drawn up, based on the appropriate analysis of the data obtained.
 Conclusions. In recent years, climate change in Ukraine has manifested itself through an increase in the average annual temperature, and an increase in the sum of effective temperatures. A decrease in the zone of sufficient soil moisture was noted, its line shifted to the north. Under the influence of abiotic factors, pests constantly change the boundaries of their habitat and zones of damage, therefore reliable protection of crops is impossible without constant monitoring, constant clarification of the species composition of phytophages, and phytosanitary forecast. Improved methodological approaches for assessing the phytosanitary state of acrocyanoses and the promptness of obtaining relevant data will allow agricultural producers to make timely decisions on the economic feasibility of using certain plant protection products.

The communication and measurement architecture of BDS-3 global operations and services

This study introduces the third-generation BeiDou Navigation Satellite System (BDS-3) system’s creative global operation and service architecture based on regional stations and Ka-band inter-satellite links (ISLs). The architecture’s contributions to BDS-3 include not only combined orbit determination and time synchronization but also autonomous orbit determination and time synchronization, global operations and services. The BDS-3 on-orbit operation results are being presented in the paper to verify the designed capabilities. Compared with BDS-2, the orbit determination accuracy is improving from 0.6 m to 0.15 m, and the time synchronization accuracy is improving from 6.67 ns to 1.16 ns. Under autonomous orbit determination and time synchronization, the 30-day orbit maintenance accuracy reaches 16 m, and the time synchronization accuracy reaches 3.74 ns. The success rate of data transmission reaches 99%, and the delay is better than 12.9 s. In the future, laser ISLs will be used to enhance the system structure and further improve global operation and service capabilities.

Comparison between GPS network analysis with undifferenced and double differenced integer ambiguity resolution: A practical perspective

Global Navigation Satellite System (GNSS) network analysis benefits from precise point positioning with undifferenced (UD) or double differenced (DD) integer ambiguity resolution (IAR). Position time series with UD-IAR and a practical DD-IAR are compared for a mixture network consisting of 57 global and 82 regional stations with 4-year observations. The sparse global stations are more affected by different IAR methods than the regional stations of Crustal Movement Observation Network of China (CMONOC). The most significant differences between UD-IAR and the practical DD-IAR are observed in velocity estimations, with averages of 0.15 and 0.30 mm/yr for the horizontal and vertical components, respectively. UD-IAR can achieve smaller root mean square at 70–83 % of the daily solutions than the practical DD-IAR for global stations. Nevertheless, moderate differences of frame parameters and annual variations are introduced by different IAR methods. The IAR is also proved to be one of the potential origins for Global Positioning System (GPS) draconitic signals and white noise at high frequency.

ОЦЕНКА СОДЕРЖАНИЯ ОЗОНА В АТМОСФЕРЕ НА СТАНЦИИ ЛИСТВЯНКА БАЙКАЛЬСКОЙ ПРИРОДНОЙ ТЕРРИТОРИИ ПО НАЗЕМНЫМ ДАННЫМ И ПО ДАННЫМ РЕАНАЛИЗА

The machine learning model used to predict ozone concentrations at the Listvyanka monitoring station in the Baikal region is described. The model was trained and verified using automatic ground-based gas analyzer ozone measurements. Random forest and boosting machine learning models were used. According to the ERA5 reanalysis, the mean absolute error of ozone values exceeds 16 ppb, and the mean percentage error is 80%. The respective errors in the ozone values calculated using machine learning models are 6.7 ppb and 29%. The results of forecasting are the most sensitive to the season, air temperature, and vegetation. The ozone values for 2017-2022 were simulated and analyzed using the trained model and reanalysis data.

Eksistensi Radio Melalui Konvergensi Siaran di Era Digital

Radio is a communication medium that must now be able to compete with new media which is currently increasingly massive. The aim of this research is to find out how national private broadcast radio in West Java is able to maintain its existence and the strategies it implements to continue to exist amidst competition with digital information platforms that currently exist. Research respondents were managers of local radio stations in West Java, especially those in Bandung, Cimahi, Sukabumi and Cirebon. This research uses qualitative methods by describing the result of questioners and interviewing and then processing them in the form of descriptive narratives and pie diagram. The results of this research are that almost all private broadcast radio stations in the West Java region that were respondents implemented a convergence strategy to maintain their existence and made changes to their broadcast model management. Some of the convergence strategies implemented are broadcasting via digital streaming, creating more interesting broadcast program content with an audio-visual style such as podcasts, choosing broadcasters who have popularity and character, upgrading broadcast equipment, having social media as a branding and content publication medium, and upload content to YouTube media. This convergence strategy is also carried out to increase interest and the number of advertisers so that they can continue to choose radio as a medium for marketing the products and services offered more widely and in a contemporary style.

Urban microclimate differences in continental zone of China

In modern cities, the block geometry and land cover feature directly affect the heat transfer between ground surface and atmosphere, resulting in significant differences of local microclimate. Clarifying this difference will help to accurately predict regional building energy demand and optimize regional layout design. However, existing microclimate research mainly focuses on tropical, arid, and temperate climate regions, leaving continental areas virtually unexplored. To address this problem and clarify the interactions of the urban blocks and microclimate, the combination of the local climate zone (LCZ) scheme and fixed-point weather station monitoring is employed to investigate the variation characteristics of the thermal and humidity conditions of typical urban blocks in continental zone of China. Firstly, sixty-seven typical urban blocks with self-built, national and regional meteorological stations are selected as the object of study, and classified into twelve LCZ categories, according to their inherent features. Secondly, the spatial and temporal variation patterns of the thermal environment indexes of the twelve LCZ types are analyzed and compared. Additionally, correlation analyses and regression fittings are performed between the thermal environment indexes and the urban morphological parameters. The results indicate significant differences in thermal environment indexes among different LCZ types. The mean temperature of built types is 0.72 °C higher than land cover types. The temperature and humidity exhibit a parabolic relationship with height of roughness elements and building surface fraction respectively, while the humidity has strong negatively correlations with the impervious surface fraction and the height of roughness elements.

Reliable Earthquake Source Parameters Using Distributed Acoustic Sensing Data Derived from Coda Envelopes

Abstract A challenge in fully using distributed acoustic sensing (DAS) data collected from fiber-optic sensors is correcting the signals to provide quantitative true ground motion. Such corrections require considering coupling and instrument response issues. In this study, we show via comparison with geophone and broadband seismometer data that we can use coda envelope calibration techniques to obtain absolute moment magnitudes and source spectra from DAS data. Here, we use DAS and nodal geophones deployed as part of a geothermal monitoring experiment at Brady Hot Springs, Nevada, and on a 20 km long dark fiber of the ESnet’s Dark Fiber Testbed–a U.S. Department of Energy user facility, in Sacramento, California. Several DAS line segments with colocated geophone stations were used to compare the amplitude variation using narrowband S-wave coda envelopes. The DAS coda envelope decay at each point showed remarkable similarity with coda envelopes from different events in each narrow frequency range examined. The coda envelopes are used to determine Mw magnitudes and source spectra from regional stations without any major scatter. Because coda waves arrive from a range of directions, the azimuthal sensitivity of DAS is somewhat ameliorated. We show that the openly available seismic coda calibration software toolkit can be used for straightforward and faster processing of large DAS datasets for source parameters and subsurface imaging.

Statistical Characteristics of Spread F in the Northeastern Edge of the Qinghai-Tibet Plateau during 2017–2022

Spread F (SF) in the ionosphere can be observed frequently in mid-latitude regions. It is suggested that atmospheric gravity waves play a significant role for the seeding of mid-latitude SF. Previous research suggested that the source of travelling ionospheric disturbances (TIDs) over China is in the southeastern and northeastern edge of the Qinghai-Tibet Plateau, however, until now there have been no ground-based observations of the ionosphere in this region. Recently, an advanced digital ionosonde was installed at Zhangye station (39.2°N, 100.54°E, Dip Lat 29.6°N) in the northeastern edge of the Qinghai-Tibet Plateau. It is an opportunity to verify the effect of gravity waves on the formation of mid-latitude SF by comparing it with observations in other regions of the Chinese sector. In this study, statistical analysis of SF recorded at Zhangye station during 2017–2022 was carried out. Results show that diurnal, seasonal and solar cycle characteristics of the occurrence rate of SF are similar with previous studies. At Zhangye station, the maximum occurrence rate of SF is during the post-midnight period in summer and winter. The occurrence rate of SF events have a negative relationship with solar activity. There is no obvious relationship between the occurrence rate of SF and geomagnetic activity. Comparing observations of other stations in the mid-latitude region, we found that the occurrence rates of SF (the annual maximum rates are from 33.83% to 53.29%) are much higher at Zhangye station. Further studies show that ionospheric disturbances can be observed frequently at Zhangye station, especially in autumn and winter. Gravity waves/TIDs in the northeast of the Qinghai-Tibet Plateau are suggested to explain the abnormal higher occurrence rate of SF at Zhangye station.

Technical and technological support for the involvement of fallow lands in agriculture

Sustainable development of agricultural production is a key factor in ensuring food security and growth of the country's export potential. One of the main reserves for the development of the agro-industrial complex is the involvement of fallow lands in agricultural industry, which is associated with the problem of technical and technological support for these works. The purpose of the work is to intensify the process of involving fallow lands in agriculture by developing a program of technical and technological support for this type of works, aimed at creating and accelerated implementation of a system of specialized machines. The authors systematized technologies and complexes of technical means, used in the involvement of fallow lands in crop production, depending on the stages of wild species overgrowth. For active involvement of fallow lands in agriculture, it is proposed to create a network of regional machine-technological stations equipped with modern domestic specialized equipment, providing services in removal of woody and shrubby vegetation and in initial tillage to agricultural producers in regions. The program assumes the development and organization of mass production of modern equipment for the involvement of fallow lands in agriculture, as well as implementation of a set of support measures aimed at accelerated technical equipment of machine-technological stations. Such an approach should make it possible for small and medium-sized agricultural producers to use financially affordable machinery services to involve fallow lands in agriculture, eliminating the need for its acquisition and maintenance, hiring and training of additional stuff. The implementation of the proposed program should allow agricultural producers to involve fallow lands in agricultural production with minimal costs, at the same time ensuring high growth rates of acreage and agricultural production volumes.

Самоочищение атмосферного воздуха от пылевых частиц в условиях прибрежного морского климата

The intensity of air pollution depends on the characteristics of pollution sources, distance from the sea, terrain, density of residential buildings and the presence of a green zone. The influence of climatic conditions on the distribution of suspended particulate matter in the atmospheric surface layer of Vladivostok was studied. The aim of the study was to determine the particle size distribution of suspended particulate matter in the atmospheric surface layer and to assess the conditions for self-purification of urban air under the influence of the coastal maritime climate. The assessment of the urban air pollution with suspended particulate matter was carried out in two areas with different levels of pollution. The human breathing zone was examined. The temperature, humidity, air pressure, wind direction and speed at sampling points were determined. We used monitoring of meteorological data (dew point, wind gusts, clouds, fog) from the nearest regional meteorological stations. Statistical processing included the “Canonical Analysis” module. In the polluted area of the city the atmospheric circulation (direction, speed and gusts of wind) greatly affect the distribution of fine-dispersed particles (2.5–10.0 µm) that are hazardous to health. The impact of temperature and humidity conditions is reduced in power. The temperature and humidity regime, atmospheric pressure, cloudiness with frequent fog affect the ultrafine dust spectrum in the slightly polluted island area of the city. The above factors contribute to the enhancement of the nanoparticle nucleation process. Self-purification of the air surface layer from dust particles in both polluted and slightly polluted areas of Vladivostok is associated with the southerly winds. The monsoon maritime climate defines the air purifying in the region. The temperature and humidity regime actively affects the dust disperse composition in both sampling sites. In the island area of the city it determines the content of particles up to 10 µm; in the continental area – fractions of 0.1–50.0 µm.

Investigating the compatibility of an irrigation decision support system with water rights and allocation in a selected irrigation network

AbstractIt is necessary to use different planning models, including decision support systems (DSSs), to allocate water resources. For this purpose, in this study, an irrigation decision support system (IDSS) was developed to improve irrigation management in the farming fields of Mahabad Plain located to the south‐east of Lake Urmia. Next, the compatibility of the IDSS with the conditions of the Mahabad irrigation and drainage network, water and soil resources, meteorological data and soil moisture (SM) were investigated. The statistical indices of coefficient of determination (R2), root mean square error (RMSE), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency (EF) and Wilmot agreement (d) were used to evaluate the adaptability of the IDSS. The results showed that the IDSS has reasonable compatibility with soil and water resources, crop yield and meteorological data. Irrigation scheduling provided by the IDSS led to a 13.9% reduction in water consumption and a 6.7% increase in crop yield. The IDSS estimated minimum and maximum temperature and sunshine hours to a satisfactory degree and relative humidity with an acceptable degree (NRMSE = 0.72–0.77) compared to regional synoptic station data. The performance of the IDSS in simulating SM is ranked from good to well (NRMSE = 0.75–0.83). The results indicate that the IDSS has a sufficient performance in estimating meteorological and soil moisture data with R2 = 0.90, RMSE = 4.65, NRMSE = 0.78, EF = 0.76 and d = 0.80. In addition, the IDSS provides the optimal irrigation schedule by considering the ability to deliver water from the irrigation and drainage network to the third‐grade canal and agricultural fields as the upstream condition.

Tracking Seismic Velocity Perturbations at Ridgecrest Using Ballistic Correlation Functions

Abstract We present results based on data of a dense nodal array composed of 147 stations, deployed in 2022 near the epicenter of the 2019 Mw 7.1 Ridgecrest earthquake to investigate characteristics of the seismic wavefields. Through array analyses, we identified two primary components. First, we observed far-field P waves dominating the 0.5–1.2 Hz frequency range, which are likely primarily generated by wind-driven oceanic swell activity. Second, we detected near-field body waves resulting from anthropogenic activities in the frequency range 2–8 Hz. We examined noise correlation functions derived from data of the dense deployment and regional stations to explore fault-zone seismic velocity changes using ballistic arrivals, with a focus on velocity perturbation shortly before and after the Ridgecrest earthquake sequence. Our findings exhibit distinct behavior compared to results obtained through standard coda-wave interferometry. Particularly, we observed a decrease in P-wave travel time on certain station pairs prior to the 2019 earthquake sequence. Supported by detailed investigation of the local seismic wavefields, we interpret the decreasing P-wave travel time as likely caused by a velocity increase away from the fault, possibly related to fluid migration. However, additional information is necessary to verify this hypothesis.

Improved monthly streamflow prediction using integrated multivariate adaptive regression spline with K-means clustering: implementation of reanalyzed remote sensing data

This study investigates monthly streamflow modeling at Kale and Durucasu stations in the Black Sea Region of Turkey using remote sensing data. The analysis incorporates key meteorological variables, including air temperature, relative humidity, soil wetness, wind speed, and precipitation. The study also investigates the accuracy of multivariate adaptive regression (MARS) with Kmeans clustering (MARS-Kmeans) by comparing it with single MARS, M5 model tree (M5Tree), random forest regression (RF), multilayer perceptron neural network (MLP). In the first modeling stage, principal component regression is applied to diverse input combinations, both with and without lagged streamflow (Q), resulting in twenty-three and twenty input combinations, respectively. Results demonstrate the critical role of including lagged Q for improved model accuracy, as models without lagged Q exhibit significant performance degradation. The second stage involves a comparative analysis of the MARS-Kmeans model with other machine-learning models, utilizing the best-input combination. MARS-Kmeans, incorporating three clusters, consistently outperforms other models, showcasing superior accuracy in predicting monthly streamflow.

Shake to the Beat: Exploring the Seismic Signals and Stadium Response of Concerts and Music Fans

Abstract Large music festivals and stadium concerts are known to produce unique vibration signals that resemble harmonic tremor, particularly at frequencies around 1–10 Hz. This study investigates the seismic signals of a Taylor Swift concert performed on 5 August 2023 (UTC) as part of a series at SoFi Stadium in Inglewood, California, with an audience of ∼70,000. Signals were recorded on regional seismic network stations located within ∼9 km of the stadium, as well as on strong-motion sensors placed near and inside the stadium prior to the concert series. We automatically identified the seismic signals from spectrograms using a Hough transform approach and characterized their start times, durations, frequency content, particle motions, radiated energy, and equivalent magnitudes. These characteristics allowed us to associate the signals with individual songs and explore the nature of the seismic source. The signal frequencies matched the song beat rates well, whereas the signal and song durations were less similar. Radiated energy was determined to be a more physically relevant measure of strength than magnitude, given the tremor-like nature of the signals. The structural response of the stadium showed nearly equal shaking intensities in the vertical and horizontal directions at frequencies that match the seismic signals recorded outside the stadium. In addition, we conducted a brief experiment to further evaluate whether the harmonic tremor signals could be generated by the speaker system and instruments, audience motions, or something else. All evidence considered, we interpret the signal source as primarily crowd motion in response to the music. The particle motions of the strongest harmonics are consistent with Rayleigh waves influenced by scattered body waves and likely reflect how the crowd is moving. Results from three other musical performances at SoFi in summer 2023 were similar, although differences in the signals may relate to the musical genre and variations in audience motions.

Temperature Inversion and Particulate Matter Concentration in the Low Troposphere of Cergy-Pontoise (Parisian Region)

This study aims to elucidate the influence of meteorological conditions on particle levels in Cergy-Pontoise. It explores the temporal variability of PM10 pollution days by associating them with the vertical temperature profile derived from conventional radiosondes from 2013 to 2022 (regional station). The results indicate that nearly 80% of exceedance days were associated with thermal inversions, primarily observed in winter and typically lasting 1 to 3 days. Analysis of winter thermal inversion characteristics suggests that those linked to pollution primarily occur near the ground, with higher intensity in December (12.1 °C) and lower in February (10.3 °C). Persistent inversions (extended nocturnal by diurnal inversion) account for 91.4% of the total inversions associated with high concentrations. Captive balloon soundings and temperature measurements at different altitudes were conducted during the winter of 2022/2023 to clarify thermal inversion in the Oise Valley at the center of Cergy-Pontoise. The results highlight three nocturnal wind circulation mechanisms in the valley, including downslope flow, circulation influenced by an urban heat island, and mechanical air evacuation under an inversion layer towards the less steep East side of the valley. Analysis of PM with the temperature gradient in the Oise Valley shows a significant correlation, suggesting an increase in concentrations during locally detected inversions and a decrease during atmospheric disturbance.

Comprehensive seismic evidence for the inducing mechanism of extremely shallow 2019 Changning Ms 6.0 earthquake by solution salt mining, Sichuan Basin, China

Abstract In the Changning region of the Sichuan Basin, China, which has experienced decades-long injection of freshwater for commercial salt mining, a Ms 6.0 earthquake occurred in June 2019, along with four Ms >5 aftershocks. Using data from local and regional seismic stations, we determine accurate locations for this earthquake sequence, velocity structures, and excess pore fluid pressures of the source region. Our results show that the Ms 6.0 earthquake is extremely shallow (~1.6 km below mean sea level) and is associated with low Vs and high Vp/Vs values and excess fluid pressures, indicating a fluid-induced earthquake. The mainshock was likely the shallowest M >6.0 induced earthquake, and it was triggered by the combined effect of pore pressure increase from the diffusion of injected fluids, differential formation subsidence from salt caverns, and highly fractured slip-prone rocks enriched in quartz and silica content. Following Coulomb stress transfer from the mainshock, the sequence ruptured in a cascading manner involving preexisting oblique faults of varying dips.

Episootological features of tularemia in the Donetsk region

Objective: to evaluate epizootic monitoring of tularemia in the Donetsk region.Materials and methods: methods of retrospective, statistical, and comparative analysis were used. The sources of infection were investigated using serological and biological methods. The data of industry statistical reporting on form No. 40-annual of the department of especially dangerous infections of the Donetsk regional Sanitary and Epidemiological Station (since 2013 — SSESU, since 2015 — Republican Center for Sanitary and Epidemiological Surveillance of the State Sanitary and Epidemiological Service of the Ministry of Health of the DPR) were used. 20 "Maps of epizootological and epidemiological examination of the focus of zoonotic disease" (F.391/y) were studied.Results: since 1987, the number of enzootic territories in the Donetsk region has increased annually: from 2 settlements in 1987 to 79 (in 4 cities and 16 districts) in 2023. With the beginning of active hostilities, the epidemic process of tularemia in Donbass has sharply intensified. Antibody titers (1:80 and 1:160) for tularemia were detected in environmental samples: in the North Steppe zone — 6.2%, Donetsk-Kryazhnaya — 10.4%, Primorsko-steppe — 15.8%. In the study of mouse-like rodents, 6 cultures of Francisella tularensis holarctica biovar II era R were isolated, resistance of the strain to ampicillin, cefotaxime, erythromycin, clindamycin, polymyxin was established; sensitivity to gentamicin, fluoroquinolones, rifampicin, doxycycline, levomycetin.Conclusions: the activation of epizootic processes of tularemia in the DPR is associated with the conduct of hostilities. High titers of antibodies to tularemia in environmental samples are noted in the south of the Donetsk region.

THE EFFECT OF SEASONAL VARIATION ON GNSS ZENITH TROPOSPHERIC DELAY

Abstract. The Global Navigation Satellite System (GNSS) signal experiences delays caused by the atmosphere, leading to the lengthening of the geometric path of the ray, commonly referred to as tropospheric delay. This delay is a significant source of error in GNSS positioning, contributing to a bias in the height component of several centimeters, even when meteorological data are simultaneously recorded and used in tropospheric models. In this study, considering seasonal variations, we investigated the impact of tropospheric delay on the GNSS height component. GNSS stations, part of the Turkish RTK CORS Network known as TUSAGA-Active (Turkish National Permanent GNSS Network Active), covered different heights over the 2014–2019 period. Daily coordinates of GNSS stations and tropospheric zenith delay were obtained through the GAMIT/GLOBK software solution.In the study, temperature, pressure, and relative humidity data of meteorological stations at different heights were converted to mean sea level. By using these values, interpolation estimates were made for the continuous GNSS stations in the same region with the IDW method. The most significant delay in GNSS signals occurs in July and August. This effect, which causes periodic changes in the zenith delay, varies inversely with the station's height. With the increase in the amount of water vapor in the atmosphere in parallel with the rise in the temperature in the summer months, it is seen that the stations at a low height are more exposed to the tropospheric effect than the stations at higher heights. In addition, GNSS stations' reduced meteorological values (temperature, pressure and relative humidity) show that the zenith delay values changed directly proportional to the temperature and inversely proportional to the pressure and relative humidity.

Satellite or ground-based measurements for air pollutants (PM2.5, PM10, SO2, NO2, O3) data and their health hazards: which is most accurate and why?

Air pollution is growing at alarming rates on regional and global levels, with significant consequences for human health, ecosystems, and change in climatic conditions. The present 12 weeks (4 October 2021, to 26 December 2021) study revealed the different ambient air quality parameters, i.e., PM2.5, PM10, SO2, NO2, and O3 over four different sampling stations of Delhi-NCR region (Dwarka, Knowledge park III, Sector 125, and Vivek Vihar), India, by using satellite remote sensing data (MERRA-2, OMI, and Aura Satellite) and different ground-based instruments. The ground-based observation revealed the mean concentration of PM2.5 in Dwarka, Knowledge park III, Sector 125, and Vivek Vihar as 279 µg m-3, 274 µg m-3, 294 µg m-3, and 365 µg m-3, respectively. The ground-based instrumental concentration of PM2.5 was greater than that of satellite observations, while as for SO2 and NO2, the mean concentration of satellite-based monitoring was higher as compared to other contaminants. Negative and positive correlations were observed among particulate matter, trace gases, and various meteorological parameters. The wind direction proved to be one of the prominent parameter to alter the variation of these pollutants. The current study provides a perception into an observable behavior of particulate matter, trace gases, their variation with meteorological parameters, their health hazards, and the gap between the measurements of satellite remote sensing and ground-based measurements.