Measurement Stations Research Articles

Development of Hydroacoustic Localization Algorithms for AUV Based on the Error-Corrected WMChan-Taylor Algorithm

Autonomous underwater vehicles (AUVs) are susceptible to non-line-of-sight (NLOS) errors and noise bias at receiving stations during the application of hydroacoustic localization systems, leading to a degradation in positioning accuracy. To address this problem, this paper optimizes the Chan-Taylor algorithm. Initially, we propose the Weighted Modified Chan-Taylor (WMChan-Talor) algorithm, which introduces dynamic weights into the Chan algorithm to correct noise variance at measurement stations, thereby improving the accuracy of AUV positioning. Computer simulations validate the effectiveness of the WMChan-Taylor algorithm in enhancing positioning accuracy. To further address the accuracy degradation caused by noise deviations across different receiving stations, we introduce an error-corrected WMChan-Taylor algorithm. This algorithm utilizes a standard residual function to eliminate significant delays caused by large errors at receiving stations and applies standard residual weighting to improve the combined positioning solution. The performance of the error-corrected WMChan-Taylor algorithm is demonstrated through both computer and semi-physical simulation experiments, confirming its capability to isolate noisier stations and thus enhance overall positioning accuracy.

Accuracy Assessment of UAV LiDAR Compared to Traditional Total Station for Geospatial Data Collection in Land Surveying Contexts

Abstract. Accurate surveying of vegetated areas presents significant challenges due to obstructions that obscure visibility and compromise the precision of measurements. This paper introduces a methodology employing the DJI Zenmuse L2 Light Detection and Ranging (LiDAR) sensor, which is mounted on a Matrice 350 RTK drone. The DJI Zenmuse L2 sensor excels at capturing detailed terrain data under heavy foliage, capable of collecting 1.2 million points per second and offering five returns, thus enhancing the sensor's ability to detect multiple surface responses from a single laser pulse. In a case study conducted near a creek heavily obscured by tree coverage, traditional aerial imaging techniques are found insufficient for capturing critical topographic features, such as the creek banks. Employing LiDAR, the study aims to map these obscured features effectively. The collected data is processed using DJI Terra software, which supports the accurate projection and analysis of the LiDAR data. To validate the accuracy of the data collected from the LiDAR sensor, traditional survey methods are deployed to ground truth the data and provide an accuracy assessment. Ground control points (GCPs) are established using a GNSS receiver to provide geodetic coordinates, which then assist in setting up a total station. This total station measures vertical and horizontal angles, as well as the slope distance from the instrument to positions underneath the tree coverage on the ground. These measurements serve as checkpoints to validate the accuracy of the LiDAR data, thus ensuring the reliability of the survey. This paper discusses the potential of integrating LiDAR data with traditional surveying data, which is expected to enhance the ability of surveyors to map environmental features efficiently and accurately in complex and vegetated terrains. Through detailed procedural descriptions and expected outcomes, the study aims to provide valuable insights into the strategic application of geospatial technologies to overcome common surveying challenges.

On the Variability in the Temporal Stability Pattern of Soil Moisture Under Mediterranean Conditions

In recent decades, there has been increasing interest in studying the variability in soil water properties and, specifically, the spatiotemporal variability in the soil water content. This is motivated by the notable theoretical and applied research interests in soil moisture dynamics and their implications for many natural processes. This study aimed to study whether there are variations in the spatial pattern of the temporal stability of soil moisture over time and to analyze the possible influences of certain hydroclimatic (soil water content, precipitation, and evapotranspiration) and soil factors (texture, bulk density, and organic matter content) on these variations. This study was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS, Spain) under Mediterranean conditions, with daily surface moisture data (0–5 cm depth) obtained from 20 stations for the 2006-2023 period. The results showed differences between the average pattern obtained with the 18-year data series and that obtained with the data series for each year. In more than half of the years studied, the representative station differed from that derived from the average pattern. The mean annual precipitation and summer precipitation characteristics seem to be the main factors influencing the variability in the spatial pattern of the temporal stability of soil moisture.

Spatial Variation of Airborne Pollen Concentrations Locally around Brussels City, Belgium, during a Field Campaign in 2022–2023, Using the Automatic Sensor Beenose

As a growing part of the world population is suffering from pollen-induced allergies, increasing the number of pollen monitoring stations and developing new dedicated measurement networks has become a necessity. To this purpose, Beenose, a new automatic and relatively low-cost sensor, was developed to characterize and quantify the pollinic content of the air using multiangle light scattering. A field campaign was conducted at four locations around Brussels, Belgium, during summer 2022 and winter–spring 2023. First, the consistency was assessed between the automatic sensor and a collocated reference Hirst-type trap deployed at Ixelles, south-east of Brussels. Daily average total pollen concentrations provided by the two instruments showed a mean error of about 15%. Daily average pollen concentrations were also checked for a selection of pollen species and revealed Pearson and Spearman correlation coefficients ranging from 0.71 to 0.93. Subsequently, a study on the spatial variability of the pollen content around Brussels was conducted with Beenose sensors. The temporal evolution of daily average total pollen concentrations recorded at four sites were compared and showed strong variations from one location to another, up to a factor 10 over no more than a few kilometers apart. This variation is a consequence of multiple factors such as the local vegetation, the wind directions, the altitude of the measurement station, and the topology of the city. It is therefore highly necessary to multiply the number of measurement stations per city for a better evaluation of human exposure to pollen allergens and for more enhanced pollen allergy management.

Intermediate complexity atmospheric modeling in complex terrain: is it right?

Dynamic downscaling of atmospheric forcing data to the hectometer resolution has shown increases in accuracy for landsurface models, but at great computational cost. Here we present a validation of a novel intermediate complexity atmospheric model, HICAR, developed for hectometer scale applications. HICAR can run more than 500x faster than conventional atmospheric models, while containing many of the same physics parameterizations. Station measurements of air temperature, wind speed, and radiation, in combination with data from a scanning Doppler wind LiDAR, are compared to 50 m resolution HICAR output during late spring. We examine the model’s performance over bare ground and melting snow. The model shows a smaller root mean squared error in 2 m air temperature than the driving model, and approximates the 3D flow features present around ridges and along slopes. Timing and magnitude of changes in shortwave and longwave radiation also show agreement with measurements. Nocturnal cooling during clear nights is overestimated at the snow covered site. Additionally, the thermal wind parameterization employed by the model typically produces excessively strong surface winds, driven in part by this excessive nocturnal cooling over snow. These findings highlight the utility of HICAR as a tool for dynamically downscaling forcing datasets, and expose the need for improvements to the snow model used in HICAR.

A New Automated Algorithm for Optimization of Measurements for Achieving the Required Accuracy of a Geodetic Network

The optimization of measurements in a geodetic network (second-order design) has been investigated in the past; however, the practical usability of the outcomes of most of such studies is doubtful. Hence, we have proposed a new automated optimization algorithm, taking into account the practical aspects of total station measurements. The algorithm consists of four parallel partial algorithms, of which one is subsequently automatically selected—the one meeting the geodetic network accuracy requirements with the lowest number of necessary measurements. We tested the algorithm (and individual partial algorithms) on four geodetic networks designed to resemble real-world networks with 50–500 modifications to each of those networks in individual tests. The results indicate that (i) the results achieved by the combined algorithm are close to the optimal results and (ii) none of the four partial algorithms universally performs the best, implying that the combination of the four partial algorithms is necessary for achieving the best possible results of geodetic network optimization.

Terrestrial laser scanning in the construction of a numerical model geometry related to underground post-mining facility

Abstract The procedure of building a quasi-3D geometry of a numerical model of an underground post-mining facility is presented in the article. For this purpose, measurements were made, based on the terrestrial laser scanning (TLS) technology, of a fragment of St. John adit, which is part of the underground tourist route “Geopark” St. Johannes Mine in Krobica in Lower Silesia in Poland, in the neighborhood of Krobica, Gierczyn and Przecznica – the places located in the vicinity of the well-known health resort Świeradów Zdrój. TLS, as one of the most advanced mining surveying technologies, enables accurate mapping of even the most complex geometries of underground mining facilities. This opens wide possibilities in the construction of more accurate numerical models of the behavior of the rock mass around such underground objects. As a result, more reliable calculation results are obtained, which are the basis for designing mining support protection, for example, with rock bolting. This translates into an improvement in the safety of underground excavations, in the conditions of exploitation in mining as well as in historical post-mining excavations made available to tourists. In the construction of the geometry of numerical model, software such as Trimble RealWorks was used to orientate individual “point clouds” from measurement stations. CloudCompare software was also used to generate cross sections to the adit axis, and AutoCad software was used for processing and spatial orientation of a selected characteristic cross section. Using the latest version of the FLAC 3D v.9.0 software, the excavation cross-section geometry obtained from measurements was mapped to and discretized (i.e., meshed), giving it a third dimension at the same time.

Estimate of the Surface Evaporation from the Tharthar Lake (Buhayrat Tharthar) in Iraq, Based on Remote Sensing Data and Techniques of Geographic Information Systems GIS

Tharthar is the largest water reservoir in Iraq. It is Giving the circumstances of drought and water crisis in Iraq, which is considered a semi-arid region, along with significantly feverish temperatures, especially in the summer. It is expected that evaporation rates will increase. Therefore, it was necessary to determine the water loss due to evaporation from Lake Tharthar. Due to the lack of ground measurement stations providing such data, the study relied on remote sensing data, specifically satellite imagery from Landsat 8 and Landsat 9. These images were used to extract temperature values for Lake Tharthar for the hydrological year extending from October 2022 to September 2023. This was done in conjunction with geographic information system (GIS) software and using ArcMap to calculate the annual evaporation rate and volume of the lake. Spatial modeling of evaporation was conducted for each month using the modified Lambert equation, adapted from the Penman-Cridle equation, which is most suitable for the climatic conditions of Iraq. Using this methodology saved time, effort, and cost, and yielded satisfactory results compared to field measurements of nearby water bodies. Temperature and evaporation rates were calculated at the level of each image pixel (30×30 meters). The research concluded many important findings, including that the total annual evaporation from the lake is estimated at 1881.16 millimeters (2.930 billion cubic meters per year). Accordingly, the annual loss per square kilometer from Lake Tharthar is estimated at 188 million cubic meters. This means that when Lake Tharthar reaches its maximum capacity, expanding the area to 2710 square kilometers, the evaporation loss will increase to 5.089 billion cubic meters per year. This necessitates relevant authorities to take necessary measures to reduce the annual evaporation loss from the lake surface. The study recommends adopting this method in cases where data is not available for locations lacking weather stations or when there is a data shortage.

The Influence of Vibrations Induced by Blasting Works in an Open-Pit Mine and Seismic Events in an Underground Mine on Building Structures—A Case Study

Monitoring induced vibrations caused by blasting works is becoming an increasingly common form of preventive activity conducted in open-pit mines. Measurement stations also record other events unrelated to blasting works. This article presents a comparison of the intensity of vibrations induced by blasting works in an open-pit mine and mining tremors in an underground mine. The recorded data and conducted analyses of vibration intensity and frequency structure also allowed for a comparison of the impact of vibrations on a building structure. Calculations and analyses, conducted in accordance with the procedures provided in the standard PN-B-02170:2016-12 and the rules for applying the Mining Seismic Intensity Scale MSIS-2017, demonstrated a stronger impact on the building from induced vibrations in an underground mine located 10 km away compared to vibrations induced by blasting operations conducted in an open-pit mine, which is approximately 600 m away from the building. The presented material constitutes a unique set of data that can be used to introduce any necessary corrections in the methodology of analyzing vibrations regarding their harmfulness to building structures. The velocity value of vibrations correlated with frequency alone, without taking into account the vibration duration, can lead to incorrect interpretation.

Intermediate ions as indicator for local new particle formation

Abstract. Atmospheric aerosol particles have a considerable influence on climate via both aerosol–radiation and aerosol–cloud interactions. A major fraction of global aerosol particles, in terms of their number concentration, is due to atmospheric new particle formation (NPF) that involves both neutral and charged clusters and particles. NPF is the major source of atmospheric intermediate ions, i.e., charged particles with mobility diameters between approx. 2 and 7 nm. We investigate ion concentrations between 1.7 and 3.1 nm at the SMEAR II (Station for Measuring Forest Ecosystem–Atmosphere Relations II) measurement station in Hyytiälä, Finland. Both negative and positive ion number size distributions measured by a Neutral cluster and Air Ion Spectrometer (NAIS) are used. Our aim is to find the best diameter size range of ions for identifying and evaluating the intensity of local intermediate ion formation (LIIF). Intermediate ion formation (IIF) refers to the formation of intermediate ions through NPF, while local means that the growth of such ions from smaller clusters has occurred in close proximity (e.g., within 500 m to 1 km) to the measurement site, i.e., locally. We find that the ions in the mobility diameter size range of 2.0–2.3 nm are the best suited for detection of LIIF. The ion concentrations in this size range indicate the elevated rates of IIF, and the potential distances the growing ions have traveled are smaller than those for larger ions. In addition, in Hyytiälä, the negative ion concentrations are more sensitive to IIF than the positive ion concentrations due to the higher difference in concentrations between periods of IIF and the background. Therefore, we recommend the concentrations of ions with diameters 2.0–2.3 nm as the best choice for identifying and evaluating the intensity of LIIF.

On the added value of satellite AOD for the investigation of ground-level PM2.5 variability

To assess and mitigate PM2.5 pollution, it is imperative to accurately characterize its spatiotemporal variability and distribution. As station measurements are spatially selective, additional data sources such as satellite observations or chemical transport models (CTMs) are indispensable for providing essential complementary information. With the increasing accessibility of high-quality reanalysis datasets on air pollutants from CTMs, the use of satellite-based observations with their limited spatial and temporal availability is more and more put into question. Model simulations present a clear advantage concerning spatiotemporal continuity. However, how reliable are these model simulations and how does the information they provide differ from satellite-derived data? By applying a random forest (RF) approach we derive PM2.5 concentrations for Germany based on observations of aerosol optical depth (AOD) and a variety of other atmospheric parameters and systematically compare the satellite-derived PM2.5 dataset to results from the CAMS regional model system. We discern the differences in the information they provide to demonstrate the added value of the satellite AOD-derived data for the investigation of long-term PM2.5 variability. The development in PM2.5 variability is analyzed on a yearly and seasonal base over the time period from 2018 to 2022, including the COVID-19 lockdown in spring 2020. We can demonstrate a better accuracy of the RF-based AOD model compared to CAMS reanalysis data with R2 values of 0.71 and 0.57, respectively. Moreover, we find that the AOD-based data provides more detail in spatial gradients and can better depict local and short-term events of enhanced PM2.5 pollution.

The application of a high-density street-level air temperature observation network (HiSAN): Spatial and temporal variations of thermal and wind condition in different climatic condition types

Different patterns of urban development will result in different characteristics of the urban heat island effect (UHI). In order to explore the impacts of urban environment characteristics, wind conditions, and climatic condition types on UHI over different periods, this study adopted Tainan City as the study site, and utilized the surface roughness length and wind prediction, to evaluate the correlation between wind conditions and UHI, as well as the thermal environment affected by different environmental. The UHI characteristics were evaluated by using 100 measurement stations (HiSAN) located in different urban environments. The results revealed the expansion of the daily temperature range was associated with an increase in the eastwest UHI centroid point movement; wind conditions affected north-south shifts of UHI centroid point. The built environments was positively correlate with daytime (0.24) and nighttime (0.68) temperatures. Daytime water bodies notably cool surroundings (correlation -0.52), and green spaces enhance nighttime cooling (correlation -0.64). Wind speed negatively correlates with UHI deviation values during the daytime (-0.17) and nighttime (-0.58). The study highlights the impact of wind speeds and temperature ranges on UHI movement, emphasizing effective ventilation's role in urban cooling and quantifying the importance of water and green space in mitigating UHI.

The observed evolution of sub‐daily to multi‐day heavy precipitation in Switzerland

AbstractHeavy precipitation is a major natural hazard in the Alps. Understanding the possible changes due to climate change is a prerequisite for effective climate adaptation and protection. In this study, we revisit the long‐term (1901–2023) evolution of daily and multi‐day heavy precipitation intensity and frequency, discuss trends for sub‐daily to multi‐day events in the recent period 1981–2023 and investigate elevation dependencies in the complex topography of Switzerland. We analyze station measurements from MeteoSwiss' dense operational network covering the whole country and a wide range of elevation levels. We find that daily maximum precipitation and the frequency of precipitation events exceeding the 99th all‐day percentile have increased since 1901 with a peak in the 1980s and decreases thereafter. For the recent period 1981–2023, positive trends in summer heavy precipitation intensity are detected for short (10‐min to 3‐h) events, but no changes are found for the frequency of these moderate extreme events. For longer (1‐ to 5‐day) events on the other hand, decreases in intensity and frequency are found, especially for the winter half‐year. We hypothesize that the opposing trends on the centennial (1901–2023) vs. decadal (1981–2023) time scales are caused by the interaction between thermodynamics, reflecting the primary influence of human‐induced climate change, and the internal variability of atmospheric dynamics. Moreover, we observe a small negative elevation dependency of the daily long‐term trends up to 2300 m above sea level. For the 1981–2023 trends, no strong elevation dependencies are found for sub‐daily events. For daily events, we find small opposing negative summer and positive winter elevation dependencies for both intensities and frequencies. The reason for these tendencies remains unclear. Our results underscore the need to further investigate the interplay between climate change, internal variability of large‐scale dynamics and elevation to better understand heavy precipitation variability in the complex Alpine terrain.

Geometric Error Identification of Gantry-Type CNC Machine Tool Based on Multi-Station Synchronization Laser Tracers

Laser tracers are a three-dimensional coordinate measurement system that are widely used in industrial measurement. We propose a geometric error identification method based on multi-station synchronization laser tracers to enable the rapid and high-precision measurement of geometric errors for gantry-type computer numerical control (CNC) machine tools. This method also improves on the existing measurement efficiency issues in the single-base station measurement method and multi-base station time-sharing measurement method. We consider a three-axis gantry-type CNC machine tool, and the geometric error mathematical model is derived and established based on the combination of screw theory and a topological analysis of the machine kinematic chain. The four-station laser tracers position and measurement points are realized based on the multi-point positioning principle. A self-calibration algorithm is proposed for the coordinate calibration process of a laser tracer using the Levenberg–Marquardt nonlinear least squares method, and the geometric error is solved using Taylor’s first-order linearization iteration. The experimental results show that the geometric error calculated based on this modeling method is comparable to the results from the Etalon laser tracer. For a volume of 800 mm × 1000 mm × 350 mm, the maximum differences of the linear, angular, and spatial position errors were 2.0 μm, 2.7 μrad, and 12.0 μm, respectively, which verifies the accuracy of the proposed algorithm. This research proposes a modeling method for the precise measurement of errors in machine tools, and the applied nature of this study also makes it relevant both to researchers and those in the industrial sector.

Mechanistic microclimate models and plant pest risk modelling

AbstractClimatic conditions are key determining factors of whether plant pests flourish. Models of pest response to temperature are integral to pest risk assessment and management, helping to inform surveillance and control measures. The widespread use of meteorological data as predictors in these models compromises their reliability as these measurements are not thermally coupled to the conditions experienced by pest organisms or their body temperatures. Here, we present how mechanistic microclimate models can be used to estimate the conditions experienced by pest organisms to provide significant benefits to pest risk modelling. These well-established physical models capture how landscape, vegetation and climate interact to determine the conditions to which pests are exposed. Assessments of pest risk derived from microclimate conditions are likely to significantly diverge from those derived from weather station measurements. The magnitude of this divergence will vary across a landscape, over time and according to pest habitats and behaviour due to the complex mechanisms that determine microclimate conditions and their effect on pest biology. Whereas the application of microclimate models was once restricted to relatively homogeneous habitats, these models can now be applied readily to generate hourly time series across extensive and varied landscapes. We outline the benefits and challenges of more routine application of microclimate models to pest risk modelling. Mechanistic microclimate models provide a heuristic tool that helps discriminate between physical, mathematical and biological causes of model failure. Their use can also help understand how pest ecology, behaviour and physiology mediate the relationship between climate and pest response.

Very high frequency radiation emitted by negative narrow bipolar events occurred over malacca strait

In this paper, Very-High Frequency (VHF) radiation pulses associated with 11 negative Narrow Bipolar Events (NBEs) produced by a tropical storm over Malacca Strait are examined. The lightning data were recorded from a measurement station (ST) which consisted of a fast antenna (FA) and three VHF sensors (two 5 m perpendicular baselines interferometer). The average rise time (RT), average zero-crossing time (ZCT), average pulse duration (PD), and range of peak currents of the negative NBEs were 1.4 ± 0.4 μs, 2.7 ± 1.0 μs, 12.0 ± 6.9 μs, and −10 to −64 kA, respectively. The key finding is that all VHF radiation pulses have been found to precede the negative NBEs with an average lead time of 0.7 ± 0.3 μs. An interferometer map for one negative NBE (labelled as NBE10) detected at 35.7 km from ST has shown a characteristic of mixed propagation direction of fast streamers. The first VHF radiation source was detected at 12.4 ± 0.4 km above sea level. The total length and estimated velocity of the main propagation of the VHF radiation sources were 2.2 ± 0.7 km and between 1.4 × 108 and 2.8 × 108 ms−1, respectively. Moreover, based on the Himawari satellite image, the maximum extent of the cloud top height was estimated to be around 20.9 km over sea level (over Malacca Strait). All the VHF radiation sources associated with NBE10 were suggested to be detected above the main negative charge region (6 km altitude that corresponds to −10 °C). Thus, it could be suggested that NBE10 was initiated most likely in the environment of the ice crystals alone, based on the first altitude of the VHF radiation source and maximum extent of cloud top height.

A Study on Three-Dimensional Modelling of the Baitul Ilmi Mosque's Itera Using Terrestrial Laser Scanner Technology

As advancements in three-dimensional (3D) modeling continue to progress, the demand for precise and efficient measurement techniques has led to significant innovations in the methods and tools used for creating 3D models. Among these, the utilization of Terrestrial Laser Scanners (TLS) has become increasingly popular. This study focuses on the integration of TLS and total station technologies for 3D modeling of a mosque. The total station was employed to conduct five sets of perfectly bonded closed polygon measurements, each consisting of five polygon points, from which three marker points were derived. Concurrently, the TLS was used to perform a comprehensive scan of the mosque from 17 different positions. The data obtained from the TLS scan provided a detailed 3D model, while the total station measurements served as control points to ensure the model's global coordinate accuracy. The processing of the closed polygon data was executed using the Bowditch method, and the TLS data was registered using the cloud-to-cloud method. This approach yielded an overall quality assessment, including a bundle error of 0.008 m, an overlap of 27%, a strength of 65%, and a cloud-to-cloud discrepancy of 0.008 m. The integration of point clouds with total station coordinates resulted in an error margin of 0.160 m. Geometric validation of the model was conducted by comparing its dimensions to measurements obtained using a measuring tape, which yielded a Root Mean Square Error (RMSE) of 0.045 m.

Assessment Wind Energy in the Central Region of Thailand

This study evaluates the wind energy potential in the central region of Thailand by using data from seven wind measurement stations (Ayutthaya, Bangna, Chainat, Kamphaeng Saen, Lopburi, Nakhon Sawan, and Pathum Thani) and two wind turbines, namely AN Bonus 1300/62 and Vestas Wind System A/S. The analysis was conducted using the Wind Atlas Analysis and Application Program (WAsP) to examine the collected wind speed data over three years from the seven stations. The objective was to identify the top three areas with the highest annual energy production (AEP). Additionally, the study included an economic analysis using various metrics, such as the present value of costs (PVC), benefit-cost ratio (BCR), payback period (PBP), and levelized cost of electricity (LCOE). The results indicate that the AN Bonus 1300/62 model provides higher values in areas with high wind speeds and relatively high electricity demand, whereas the Vestas V52 model is suitable for areas with low wind speeds and lower investment requirements. Based on these findings, the authors recommend prioritizing wind energy development in the provinces of Ayutthaya, Nakhon Sawan, and Lopburi using the AN Bonus 1300/62 model, as these areas have high wind speeds and relatively high electricity demand. Overall, this research provides valuable insights for policymakers and investors, enabling them to make informed decisions regarding renewable energy investments in Thailand.

Development and machine learning-based calibration of low-cost multiparametric stations for the measurement of CO2 and CH4 in air

The pressing issue of atmospheric pollution has prompted the exploration of affordable methods for measuring and monitoring air contaminants as complementary techniques to standard methods, able to produce high-density data in time and space. The main challenge of this low-cost approach regards the in-field accuracy and reliability of the sensors. This study presents the development of low-cost stations for high-time resolution measurements of CO2 and CH4 concentrations calibrated via an in-field machine learning-based method. The calibration models were built based on measurements parallelly performed with the low-cost sensors and a CRDS analyzer for CO2 and CH4 as reference instrument, accounting for air temperature and relative humidity as external variables.To ensure versatility across locations, diversified datasets were collected, consisting of measurements performed in various environments and seasons. The calibration models, trained with 70 % for modeling, 15 % for validation, and 15 % for testing, demonstrated robustness with CO2 and CH4 predictions achieving R2 values from 0.8781 to 0.9827 and 0.7312 to 0.9410, and mean absolute errors ranging from 3.76 to 1.95 ppm and 0.03 to 0.01 ppm, for CO2 and CH4, respectively. These promising results pave the way for extending these stations to monitor additional air contaminants, like PM, NOx, and CO through the same calibration process, integrating them with remote data transmission modules to facilitate real-time access, control, and processing for end-users.

Steel Arch and Rock Bolt Support in Terms of the Gateroad Stability Maintaining behind the Longwall Face

The longwall system is an extraction system commonly used in coal mining in many countries, including Poland. One of the methods for reducing extraction costs is the dual use of the gateroad. In the first instance, the gateroad serves as the tailgate, and during the exploitation of the second coal panel, it functions as the headgate. Such a situation requires maintenance of the roadway behind the longwall face, which is typically challenging, due to significant stress-related loads on the support and its substantial deformation. The support design for this kind of roadway should take into consideration the dual impact of exploitation pressure and the caved zone influence behind the longwall face. This article presents the results of in-situ research conducted on two roadways behind the longwall face. In both roadways, the effectiveness of specially designed steel arch frames and rock bolt patterns were examined to minimize roadway deformations and maintain their functionality. The research project was comprised of several stages. Initially, mining and laboratory studies were conducted to determine the geomechanical parameters of the rocks. Subsequently, excavation stability and functionality forecasts were performed based on the authors’ empirical indicators. Then, numerical analyses were carried out to design support schemes (steel arches and rock bolt) in both roadways. A fully automated monitoring system with programmed data loggers was designed to check the behaviour of a specific rock mass and the support elements. The load on the steel arch support was measured with the help of load cells, while the load on the rock bolt support was carried out with the help of measurement bolts. Behind the longwall face, the loads on the wooden cribs set from the goaf side were also monitored. Additionally, the measurement station was equipped with extensometers to monitor the movement of roof layers and stress meters to determine changes in rock mass stress. Laser scanning or traditional surveying methods were also used to verify the support schemes through roadway convergence measurements. The obtained results allowed us to draw conclusions regarding the optimization of support schemes and to give recommendations for the practical application of specific reinforcements in excavations maintained behind the longwall face.