Meteorological Monitoring System Research Articles

The study on the Internet of Things implication in improving the punctuality of air transportation in bad weather

Air travel is a popular choice for people who seek to travel outside in the present. It greatly promotes communication and economic development. However, flight delays can have seriously disappointing effects on various aspects. For passengers, they not only need a long time to wait and additional expenses, but they also experience more psychological stress. And airlines face economic losses, reduced customer satisfaction, and disruptions in flight scheduling, which further affect operational efficiency. Therefore, this paper aims to explore potential methods that are combined with the Internet of Things to improve the punctuality of air transportation in order to ease the hard situation of flight delays caused by bad weather. And based on the previous related papers, the author of this paper thinks a kind of meteorological monitoring and early warning system can be built based on the Internet of Things to improve real-time weather monitoring and flight scheduling, as well as ground service optimization. Hence, people can improve the punctuality of air transportation by optimizing resource utilization and cost management so that the whole industry can bring significant economic benefits to airline companies and improved travel experiences to passengers.

Self-powered wireless sensor node enabled by ultra-high-output swinging hybrid generator toward real-time and in-situ marine meteorological observations

With the intensification of global ocean exploration, there is an increasing need for extensive and dispersed wireless sensor networks (WSNs) to meet the requirements of real-time, in-situ, and high-spatial-temporal-density marine meteorological observations. Nevertheless, providing a reliable power source and ensuring the ongoing maintenance of these WSNs pose significant challenges. Here, an innovative self-powered wireless sensor node is developed to address these challenges, featuring an ultra-high-output triboelectric-electromagnetic hybrid generator (T-EHG) with a swinging mechanism. The T-EHG, which combines triboelectric (TENG) and electromagnetic (EMG) generation, assisted by a universal power management system (UPMS), efficiently converts wave energy into a consistent voltage output between 1.5 V to 3.3 V. Additionally, the self-powered WSNs integrated with T-EHG, UPMS circuits, meteorological sensors, and microcontroller units (MCUs) with LoRa wireless transmission functionality are capable of executing data collection and transmission operations every 10 s under simulated wave conditions. These systems can achieve a maximum wireless transmission range of 1.5 km. Notably, a marine meteorological monitoring system utilizes these autonomous sensor nodes, along with base stations, cloud servers, and terminal devices to effectively implement real-time, on-site measurements of temperature, humidity, and air pressure within the monitored zone. This research underscores the substantial practical utility and extensive application prospects of these advanced self-powered WSNs for marine meteorological surveillance.

Elastic Self-Recovering Hybrid Nanogenerator for Water Wave Energy Harvesting and Marine Environmental Monitoring.

To achieve large-scale development of triboelectric nanogenerators (TENGs) for water wave energy harvesting and powering the colossal sensors widely distributed in the ocean, facile and scalable TENGs with high output are urgently required. Here, an elastic self-recovering hybrid nanogenerator (ES-HNG) is proposed for water wave energy harvesting and marine environmental monitoring. The elastic skeletal support of the ES-HNG is manufactured using three-dimensional (3D) printing technology, which is more conducive to the large-scale integration of the ES-HNG. Moreover, the combination of a TENG and an electromagnetic generator (EMG) optimizes the utilization of device space, leading to enhanced energy harvesting efficiency. Experimental results demonstrate that the TENG achieves a peak power output of 42.68 mW, and the EMG reaches a peak power output of 4.40 mW. Furthermore, various marine environment monitoring sensors, such as a self-powered wireless meteorological monitoring system, a wireless alarm system, and a water quality monitoring pen, have been successfully powered by the sophisticated ES-HNG. This work introduces an ES-HNG for water wave energy harvesting, which demonstrates potential in marine environment monitoring and offers a new solution for the sustainable development of the marine internet of things.

Wind Aggregation Enhanced Triboelectric-Electromagnetic Hybrid Generator with Slit Effect.

It is of great significance to establish a low-cost, high-efficiency, self-powered micrometeorological monitoring system for agriculture, animal husbandry, and transportation. However, each additional detection element in the meteorological monitoring system increases the power consumption of the whole system by about 0.7 W. As a renewable energy technology, a triboelectric nanogenerator has the advantages of low price and self-powered sensing. To reduce the power consumption of the micrometeorological monitoring system, this work introduces an innovative solution: the wind-gathering enhanced triboelectric-electromagnetic hybrid generator (WGE-TEHG). Coupling the thin-film vibrating triboelectric nanogenerator (TENG) and electromagnetic generator (EMG), the TENG is used to monitor wind direction and the EMG is used to monitor wind speed and provide energy needed by the system. In particular, the TENG can be used as a self-powered sensor to reduce the power consumption of the sensing system. Besides, the TENG is used to produce slit effect to enhance the output performance of EMG. The experimental results show that the WGE-TEHG can build a self-powered natural environment micrometeorological sensing system. It can monitor the wind direction, wind speed, temperature, and relative humidity. This research has great application value for the self-powered sensing implementation of a hybrid TENG and EMG.

Highly Durable Compact Sleeve Triboelectric–Electromagnetic Hybrid Nanogenerator for Broadband Triggered Energy Harvesting and Active Wind Speed Sensing

AbstractTriboelectric nanogenerator (TENG) has great potential in harvesting low‐frequency environmental mechanical energy, but the unavoidable friction between tribo‐layers limits the frequency range and efficiency of energy harvesting. Herein, a lower friction and high‐performance triboelectric–electromagnetic hybrid nanogenerator (TE‐HNG) is proposed to harvest broadband rotation energy. The compact sleeve multi‐unit TENG and electromagnetic generator are integrated to achieve respective complementary in electrical output and energy harvesting frequencies. The charge‐supplement type TENG with a single arched fluorinated ethylene propylene film design can not only supplement the charge dissipation of the Nylon surface in time but also ensure the stable output of TENG. The influences of the rotation speed on the electrical output and optimal load of TENG are systematically studied. As a self‐powered active wind speed sensor, the TE‐HNG device can detect the wind speed as low as 1 m s−1, which indicates that the TE‐HNG can harvest broadband wind energy (≈1 m s−1). Triggered by the wind, the TE‐HNG device can not only power the temperature/humidity sensor to work steadily and continuously but also realize the full‐automatic and self‐powered operation of the environmental meteorological monitoring system by combining the energy management and wireless transmission module.

Air Quality in Lombardy, Italy: An Overview of the Environmental Monitoring System of ARPA Lombardia

In this paper, we describe the structure and the features of the air quality and meteorological monitoring system adopted in the Lombardy region in Northern Italy. We are interested in describing which data the Regional Agency for Environmental Protection (ARPA Lombardia) must collect, how this process takes place and how they are disseminated to the public for institutional communication and research purposes. ARPA monitors the atmospheric conditions through a dense ground monitoring network composed mainly by permanent stations, but also by mobile samplers. We describe in a detailed fashion the structure of the network: how many stations the network consists of, their locations, which pollutants and weather events are monitored and with what frequency. Our main objective is to present to an international audience the case study of ARPA Lombardia and the main available public data, explicitly stating the sources of information and how to find them, and encouraging international researchers to deal with the subject. In spite of the significant and extensive efforts made to counteract the phenomenon of air pollution, the air quality recorded in the region is very poor, and the local authorities are struggling to comply with international regulations on the concentration of pollutants in the air, making Lombardy a relevant international case. In addition, we present in a synthetic and descriptive way, without any modeling ambition, some data observed in the last years in Lombardy regarding meteorology and the main pollutants (oxides and particulate matters). The empirical descriptive results have been obtained by analyzing sample data provided by ARPA Lombardia through the same sources described in the sections dedicated to the Agency. From the graphical analysis, it is noticeable that at aggregate (regional) level, the concentrations are affected by significant decreasing trends, but at a rather contained speed. This is particularly true for the concentrations of oxides (NO2 and NOX) in urban and industrial areas. However, particulate matters and ozone show a high persistence in the average concentrations, interrupted only by the alternation of climatic seasons. The data also show that the meteorology of the region does not seem favorable for the improvement of air quality, as the region is characterized by low precipitation, and wind almost everywhere is not very intense. This situation could be induced by the unfavorable geography of the area, which prevents adequate air recycling and facilitates the stagnation of pollutants. We suggest that any public policy intervention aimed at improving the air quality situation in the region should take into account this empirical evidence in the impact assessment phase.

A GA-BP Neural Network Regression Model for Predicting Soil Moisture in Slope Ecological Protection

In this study, based on a highway project in Zhejiang, China, the meteorological factors and soil moisture of high side slopes were monitored in real time by a meteorological data monitoring system, and the correlation between soil moisture and meteorological factors was investigated using the obtained data of soil moisture and total solar radiation, atmospheric temperature, soil temperature, relative humidity, and wind speed. Based on the correlation and the influence of meteorological factors on soil moisture lag, a back propagation (BP) neural network regression model optimized with genetic algorithm (GA) was proposed for the first time and applied to soil moisture prediction of high side slopes. The results showed that the BP neural network regression model and the GA-BP neural network regression model were used for soil moisture prediction in two cases without and with lags, respectively, and both prediction methods showed a more significant improvement in prediction accuracy considering their lags compared with those without lags; the GA-BP neural network regression model outperformed the BP neural network regression model in terms of accuracy. V-fold cross-validation eliminated the effect of random errors, indicating that the model can be applied to soil moisture prediction for ecological conservation. Using the soil moisture prediction results as the basis for screening ecological slope protection vegetation is of great significance to the safety and reliability of road construction.

Development of a low-cost and low-power air quality and weather monitoring system

Due to the recent pandemic, air quality monitoring has seen a resurgence of interest, however, commercial equipment for environmental monitoring needs a considerable economic effort. In this project, a prototype of a meteorological and air quality monitoring system is developed and implemented. The validation of the system was conducted by comparing the energy consumption with the Gila station, a version used previously. The system is composed of a sensor node, a gateway, and an application server. Communication between the sensor node and the gateway is through the LoRaWAN low-power protocol and The Things Network (TTN) service is used for IoT integration. The system monitored meteorological and air quality variables using low-cost components and with low energy consumption and prolong its autonomous life thanks to an energy harvesting system.

Regional-level risk factors for severe hand-foot-and-mouth disease: an ecological study from mainland China

BackgroundSevere hand-foot-and-mouth disease (HFMD) is a life-threatening contagious disease among young children and infants. Although enterovirus A71 has been well acknowledged to be the dominant cause of severe HFMD, there still remain other unidentified risk factors for severe HFMD. Previous studies mainly focused on identifying the individual-level risk factors from a clinical perspective, while rare studies aimed to clarify the association between regional-level risk factors and severe HFMD, which may be more important from a public health perspective.MethodsWe retrieved the clinical HFMD counts between 2008 and 2014 from the Chinese Center for Disease Control and Prevention, which were used to calculated the case-severity rate in 143 prefectural-level cities in mainland China. For each of those 143 cities, we further obtained city-specific characteristics from the China City Statistical Yearbook (social and economic variables) and the national meteorological monitoring system (meteorological variables). A Poisson regression model was then used to estimate the associations between city-specific characteristics (reduced by the principal component analysis to avoid multicollinearity) and the case-severity rate of HFMD. The above analysis was further stratified by age and gender to examine potential modifying effects and vulnerable sub-populations.ResultsWe found that the case-severity rate of HFMD varied dramatically between cities, ranging from 0 to 8.09%. Cities with high case-severity rates were mainly clustered in Central China. By relating the case-severity rate to city-specific characteristics, we found that both the principal component characterized by a high level of social and economic development (RR = 0.823, 95%CI 0.739, 0.916) and another that characterized by warm and humid climate (RR = 0.771, 95%CI 0.619, 0.960) were negatively associated with the case-severity rate of HFMD. These estimations were consistent across age and gender sub-populations.ConclusionExcept for the type of infected pathogen, the case-severity rate of HFMD was closely related to city development and meteorological factor. These findings suggest that social and environmental factors may also play an important role in the progress of severe HFMD.

Typhoon Inversion Method Combined With the YanMeng Wind Field and a Meteorological Monitoring System for Transmission Lines

Extreme weather like typhoon leaves significantly terrible influence on the stability of power grid in the coastal area. A high-voltage transmission line includes hundreds of towers and usually stretches hundreds of kilometers. It is not economical to install typhoon monitoring system throughout the transmission line. This paper proposes a typhoon inversion method (TIM) for transmission line which utilizes engineering wind field model and only requires monitoring data from a few towers. The developed method is called YanMeng wind field (YM) with directional mutation genetic algorithm (DMGA) for transmission lines, or YM-DMGA method. DMGA utilizes real-time monitoring data, and improves simulation accuracy of average wind speed by dynamically optimizing two critical parameters <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$B$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$z_{0}$ </tex-math></inline-formula> in wind field model, which is a great improvement over the traditional YM model relying on historical data. The TIM is mainly composed of three parts, the meteorological monitoring system (MMS), the YM-DMGA model, and the software system. The TIM collects real-time measured wind data of particular monitoring stations through the MMS. Meanwhile, wind data of the whole transmission line is simulated using the YM-DMGA and displayed by the software system. Then the method proposed is verified to be effective in three aspects. First of all, the YM-DMGA method has great enhancement in accuracy, for the coefficient of determination <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R_{square}$ </tex-math></inline-formula> increases from 0.811 to 0.986. Secondly, DMGA in the method has quicker convergent speed than typical GA, with fitness converged in the 269 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> epoch, earlier than that for typical GA, 656 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> epoch. Lastly, DMGA has better optimal fitness value of 0.6239, bigger than that of typical GA, 0.5891. At the end of the paper, an application of the method to an 110kV double-circuit transmission line is presented to reveal the risk under the impact of the super typhoon Rammasun.

Two-Dimensional CMOS MEMS Thermal Flow Sensor With High Sensitivity and Improved Accuracy

In this paper, we report a two-dimensional (2D) Thermoresistive Micro Calorimetric Flow (TMCF) sensor by using a $0.35~\mu \text{m}$ 2P4M CMOS MEMS technology. For the airflow, the fabricated and the open-space packaged 2D flow sensor system achieved the highest normalized sensitivity of 32 mV/W/(m/s) with respect to input heating power and gain. To overcome the sensor output drifting issue due to the locally redistributed fluid flow near the bonding wires, a digital signal conditioning algorithm using the inverse distance weighting (IDW) method, instead of the conventional fitting method with sine and cosine function, was proposed. Accordingly, the calibrated 2D flow sensor showed an improved velocity accuracy of ±4% and the angle accuracy of ±3° for an input airflow from 0 to 20 m/s. Therefore, the developed highly sensitive 2D TMCF sensor will be a promising device for the airflow measurement in the smart buildings and the meteorological monitoring system. [2019-0259]

Simulation and partition evapotranspiration for the representative landform-soil-vegetation formations in Horqin Sandy Land, China

Quantifying evapotranspiration (ET) and its components are particularly crucial to reveal the eco-hydrological processes in arid and semi-arid regions, such as the Horqin Sandy Land in China, but is lacking in existing literature. This study applied the Shuttleworth-Wallace (S-W) model to simulate and partition the ET at the representative landform-soil-vegetation formations (i.e., mobile dune, semi-fixed dune, and fixed dune) in Horqin Sandy Land based on the in situ data sampled by the meteorological monitoring system. Eddy covariance technology was used to validate the performance of the model. The results showed that the performance of the S-W model for clear days was better than that for cloudy or rainy days, and the S-W model would underestimate ET in rainy days. During 2017 growing season, ET showed as mobile dune (308 mm) semi-fixed dune (84 mm) > fixed dune (75 mm), accounting for 57.1%, 25.2%, and 21.3% of ET, respectively. With the increase of canopy coverage, the effect of leaf area index (LAI) on E/ET increased; conversely, the effect of soil moisture decreased. There were significant differences in the variation of ET in the dry and wet periods. During the dry period, the desert vegetation maintained low water consumption and showed obvious “midday break.” Compared with transpiration from canopy, evaporation from soil was more sensitive to precipitation.

Evaluation of five various technologies of PV panels for Si production using Sahara sand silica source

The Sahara Solar Breeder (SSB) project is a joint Japanese-Algerian universities project to utilise the plentiful sand and solar energy in the Sahara desert. In the context of the SSB project, a Sahara Solar Energy Research Center was created at the University of Saida in Algeria. This centre is equipped with the meteorological monitoring system, the outside photovoltaic panels evaluation systems and the underground temperature measurement system. In this paper, a description of these types of equipment of this centre is presented. Also, some important data such as irradiance, temperature, energy, I–V curves and underground temperature measurement are presented and analysed. Finally, a discussion on the usefulness of these data for the SSB project will be discussed.&#x0D; Keywords: Sahara Solar Breeder project, solar irradiation, air temperature, underground temperature, PV module, I–V curve

ANALYSIS OF RAINFALL IN THE KAZAKHSTAN

Before building the storm sewer networks the analysis of precipitation is very important. The issues of assessing the reliability of the information on the annual amounts of precipitation in the meteorological monitoring system of the KazHydroMet State Hydrometeorological Service of Kazakhstan are considered. An assessment is made of the homogeneity of the spatial correlation function, as the basis of the cartographic modeling of the statistical parameters of annual precipitation amounts. A special study aimed at studying the processes of cyclical fluctuations in the temporal variability of annual and summer precipitation amounts for stations representing all regions of the country. The data of daily precipitation of Kazakhstan in the period 1936-2017 were processed. When processing data, an open-source computer program R was used. The results will be useful for designers and researchers. A statistically significant increase in the maximum daily precipitation of 2–4 mm per 10 years was recorded at the Arkalyk, Aksay, Atyrau, Ushtobe, Bektauat and Karabalyk meteorological stations. At some stations in the Akmola and Pavlodar regions, as well as in the south and southeast of the republic, a statistically significant reduction of 2-6 days per 10 years was observed for the maximum duration of the period without precipitation.

Simulation of evapotranspiration for the mobile and semi-mobile dunes in the Horqin Sandy Land using the Shuttleworth-Wallace model.

Terrestrial evapotranspiration (ET) plays a crucial role in climate regulation and the maintenance of regional water balance. Quantitative estimation of ET and its partitioning are important for revealing the eco-hydrological processes in arid and semi-arid areas. Using the in situ data sampled by the meteorological monitoring system, the Shuttleworth-Wallace (S-W) model was applied to simulate and partition ET in the mobile and semi-mobile dunes of the Horqin sandy land during the growing season in 2017. The eddy covariance system was used to verify the simulated ET. The results were as follows: the simulated ET (308 mm) was very close to the eddy covariance observed ET (296 mm) during the whole growing season, indicating the applicability of the S-W model for ET estimation in this area. The ET rate at the vigorous growth stage (192 mm) was larger than those at the late and early growth stages (71 and 45 mm, respectively) which accounted for 62.3%, 23.1%, and 14.6% of the total, respectively. The simulated ET was close to the eddy covariance observed ET at the daily time-scale. The simulation performance of the S-W model for clear days was better than for cloudy or rainy days. The simulated ET rate was always smaller than the eddy covariance observed ET in the cloudy or rainy days. According to the model, the evaporation (E) from soil was 176 mm and the transpiration (T) from plants was 132 mm, accounting for 57.1% and 42.9% of the ET, respectively, suggesting that water use efficiency of the sand dune was low. The characteristics of ET varied substantially under the sustained drought and precipitation events. Compared to T from plants, E from soil was more sensitive to precipitation.

Research on achieving a meteorological monitoring system to increase efficiency in the execution and operation of solar installations and to reduce environmental pollution

Environmental protection alongside the economic and social cohesion are key pillars in the sustainable development of a country. In this context, the strategy of development of industries in Romania should promote modern technologies with as reduced environmental impact as possible. Therefore, determining how dispersion of the pollutants and identify weather events that cause the stagnation of pollutants in the atmosphere are a necessity in the industrial areas. On the other hand, the increased photovoltaic conversion efficiency by increasing the use of solar radiation, both in terms of execution as well as the operation of photovoltaic installations can be achieved as a result of detailed analysis of parameters and meteorological phenomena that define the area where the photovoltaic park will be located. Thus, this article presents a weather system consisting of six weather stations and a computer for keeping the data acquired. Each weather station acquires from where is assembled, information on the following variables: ambient temperature, solar radiation intensity, humidity, barometric pressure, altitude, wind speed, wind direction and rainfall.

Photovoltaic System Energy Performance Analysis Using Meteorological Monitoring Data

Nowadays, domestic photovoltaic system market has been expanded and the governmental dissemination policy has been continued. There is only PV system output performance analysis which is called Performance Ratio(PR) analysis. However, there exists many parameters that can affect PV system output. This papers shows the PV system energy performance analysis using meteorological monitoring data. The meteorological monitoring system was installed in the H university and we analyzed the PV system which installed in the H university. We also investigated other three PV systems which located less than 3 kilometers from H university. We evaluated total 4 PV systems through the field survey data, design drawing data and power generation data. Finally, we compared the actual measuring data with the simulation data using PVSYST software.

Sistem Monitoring Meteorologi Menggunakan Mikrokontroler Berbasis Web

Indonesia is an area of tropical islands with a tropical wet (humid tropic) which has two seasons of the dry season that occurred in May to October and the rainy season in November to April. In meteorological data monitoring system many of the facilities used include using thingspeak that can be accessed online and realtime wherever and whenever connected to the internet. The purpose of this research is to make monitoring system of meteorological sensor data in realtime by using data logger which is stored in thingspeak server using Android platform, Windows, iOS. The input of this research comes from meteorological sensor which is then processed using a microcontroller in the form of serial data so that it can be sent to the network which will be connected to thingspeak.com. On the Android platform the application is used thingsview, while on IOS using TS Connect application and on Windows using googlechrome, mozzila firefox or browser available on the PC client. The website address used on the Windows platform is https://thingspeak.com/channels/358620. Monitoring results have values corresponding to the data logger. The unsuitable value of the monitoring result is caused by the error that occurs on the sensor.

Implementation of the system approach in the development of radar meteorological monitoring system

The principles of building existing radar meteorological networks are analyzed. The necessity of a systematic approach to the construction of a radar system for meteorological monitoring is substantiated. The methodology of applying a systematic approach to the construction of a radar meteorological monitoring system is formulated. The results of the simulation of the radar system for meteorological monitoring are presented.

Meteorological effects of the 20 March 2015 solar eclipse over the United Kingdom

On 20 March 2015 a deep partial eclipse of the Sun, the most significant since the 11 August 1999 total solar eclipse, occurred over the UK. No comparably deep UK solar eclipse will occur until 2026 (e.g. Williams 1996, Espenak 1987). It is well known that solar eclipses cause transient meteorological effects, the most obvious of which is a drop in temperature, but – because total or major partial solar eclipses are fairly rare from any one point on the Earth’s surface and many areas are not well instrumented - there are relatively few systematic studies covering a wide region. The UK has one of the densest networks of weather stations compared with many other parts of the world. This applies to both amateur and professional station networks. Therefore the 2015 event was a unique opportunity to gather and analyse meteorological data. This has already been done for the main Met Office network of Meteorological Monitoring System sites (Hanna et al. 2016, Clark 2016), so here I present the results of a similar exercise based on amateur weather stations. I compare the meteorological effects of the 2015 eclipse over the UK with the 11 August 1999 eclipse for which I carried out a previous study (Hanna 2000).