Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data

At present,water pollution has become an important factor affecting and restricting national and regional economic development.Total phosphorus is one of the main sources of water pollution and eutrophication,so the prediction of total phosphorus in water quality has good research significance.This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform.By constructing the attribute object mapping relationship,the correlation between the two indicators was analyzed and used to predict the future data.Firstly,the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers were calculated after cleaning,and the correlation between them was analyzed.Secondly,the correlation coefficients of different times and frequencies were used to predict the values for the next five days,and the data trend was predicted by python visualization.Finally,the real value was compared with the predicted value data,and the results showed that the correlation between total phosphorus and turbidity was useful in predicting the water quality.

Importance of Proficiency Testing in Water Quality Monitoring

The monitoring data is undoubtedly important to the water quality monitor- ing department. The proficiency testing is an important way to improve the monitor- ing capacity and enhance the quality management of laboratories. It plays an impor- tant role in ensuring the accuracy, integrity and comparability of monitoring data. In this paper, the positive role of proficiency testing in the water quality monitoring was analyzed. In addition, how to improve the water quality monitoring capacity and the quality management level of laboratories through the proficiency testing was also discussed.

Introduction to the airborne marine surveillance platform and its application to water quality monitoring in China

China Marine Surveillance Force was equipped with modern aerial equipments for marine lawexecute with the advantage of functioning agilely at a large scale of surveillance coverage, providing powerful all-round safeguard, which is of benefit to the harmonious and sustainable development of coastal economy. Onboard the planes, three kinds of remote sensing sensors have been installed, including a marine airborne multi-spectrum scanner （MAMS）, an optical-electronic platform, and an airborne hyper-spectral system AISA＋. The specifications of remote sensing platforms were introduced briefly first, then examples of water quality monitoring by airborne remote sensing were presented, including the monitoring in coastal suspended material, oil-spill and abnormal warm water, etc.

Characteristics analyzing and parametric modeling of the arc sound in CO_2 GMAW for on-line quality monitoring

For on-line monitoring of welding quality, the characteristics of the arc sound signals in short circuit CO2 GMAW were analyzed in the time and frequency domains. The arc sound presents a series of ringing-like oscillations that occur at the end of short circuit i. e. the moment of arc re-ignition, and distributes mainly in the frequency band below 10 kHz. A concept of the arc tone channel and its equivalent electrical model were suggested, which is considered a time-dependent distributed parametric system of which the transmission properties depend upon the geometric and physical characteristics of the arc and surroundings, and is excited by the sound source results from the change of arc energy so that results in arc sound. The linear prediction coding （ LPC ） model is an estimation of the tone channel. The radial basis function （ RBF ） neural networks were built for on-line pattern recognition of the gas-lack in welding, in which the input vectors were formed with the LPC coefficients. The test results proved that the LPC model of arc sound and the RBF networks are feasible in on-line quality monitoring.

Design and Analysis of a Water Quality Monitoring Data Service Platform

Water is one of the basic resources for human survival.Water pollution monitoring and protection have been becoming a major problem for many countries all over the world.Most traditional water quality monitoring systems,however,generally focus only on water quality data collection,ignoring data analysis and data mining.In addition,some dirty data and data loss may occur due to power failures or transmission failures,further affecting data analysis and its application.In order to meet these needs,by using Internet of things,cloud computing,and big data technologies,we designed and implemented a water quality monitoring data intelligent service platform in C#and PHP language.The platform includes monitoring point addition,monitoring point map labeling,monitoring data uploading,monitoring data processing,early warning of exceeding the standard of monitoring indicators,and other functions modules.Using this platform,we can realize the automatic collection of water quality monitoring data,data cleaning,data analysis,intelligent early warning and early warning information push,and other functions.For better security and convenience,we deployed the system in the Tencent Cloud and tested it.The testing results showed that the data analysis platform could run well and will provide decision support for water resource protection.

Visualization Research and Application of Water Quality Monitoring Data Based on ECharts

Water resources are one of the basic resources for human survival,and water protection has been becoming a major problem for countries around the world.However,most of the traditional water quality monitoring research work is still concerned with the collection of water quality indicators,and ignored the analysis of water quality monitoring data and its value.In this paper,by adopting Laravel and AdminTE framework,we introduced how to design and implement a water quality data visualization platform based on Baidu ECharts.Through the deployed water quality sensor,the collected water quality indicator data is transmitted to the big data processing platform that deployed on Tencent Cloud in real time through the 4G network.The collected monitoring data is analyzed,and the processing result is visualized by Baidu ECharts.The test results showed that the designed system could run well and will provide decision support for water resource protection.

Air Pollution Concentration Approach to Potential Area Selection of the Air Quality Monitoring Station in Nakhon Ratchasima Municipality, Thailand

The purpose of the study is to generate traffic air information system） to determine a proper zone of AQMS （air analyzed were carbon monoxide （CO）, and nitrogen oxides （NOx） pollution map using mathematical model and GIS （geographic quality monitoring station） in municipality area. The pollutants which can be harmful to people living in the area. The three steps of mapping process were performed under the GIS environment using the existing vehicle emission rates and pollutant dispersion model. First, traffic volume, road network, and the emission rates of road segments varying with types of vehicle were collected from existing data. Second, the pollutant concentrations were calculated by use of CALINE4, a tool with Gaussian dispersion model. The model parameters include emission rate, wind directions and speeds, ambient temperature and observed pollutant concentration, and atmospheric stability during all seasons from the January 1, 2010 to May 31,2011 with regardless the rainy season. This resulted in concentrations at many receptor points along links of the road network. Third, distributions of pollution concentrations were generated by means of the spatial interpolation of those from receptors. The results of pollution raster-based maps are used for determining frequency of violence and combined pollution map. The resulting frequency of violence and intensity concentration will be further integrated to determine a potential area of AQMS. Finally, achieving pollution potential area of AQMS can be located as helpful basic data for efficient traffic and transportation planning.

A Study on Water Quality Monitoring in Urban Watercourse of Xinli River in Binzhou City

This paper aims to explore the pH,COD,ammonia nitrogen,total nitrogen,total phosphorus and other indices regarding Xinli River water in Binzhou City.The results show that the pH of the water quality index is between 7.3 and 7.8,slightly alkaline;the COD content of Xinli River is about 140-163 mg/L,and the COD pollution is serious in some water sections;the ammonia nitrogen content of Xinli River is 0.2-2.17 mg/L,the total nitrogen content is about 0.799-1.3 mg/L,the total phosphorus content is about 0.54-0.92 mg/L,suggesting that the water eutrophication is very serious.Due to the large amount of domestic sewage discharged into Xinli River without treatment,slow circulation of river water and other factors,the eutrophication is serious in the urban watercourse.

Optimization of Air Quality Monitoring Network Using GIS Based Interpolation Techniques

This paper proposes a simple method of optimizing Air Quality Monitoring Network (AQMN) using Geographical Information System (GIS), interpolation techniques and historical data. Existing air quality stations are systematically eliminated and the missing data are filled in using the most appropriate interpolation technique. The interpolated data are then compared with the observed data. Pre-defined performance measures root mean square error (RMSE), mean absolute percentage error (MAPE) and correlation coefficient (r) were used to check the accuracy of the interpolated data. An algorithm was developed in GIS environment and the process was simulated for several sets of measurements conducted in different locations in Riyadh, Saudi Arabia. This methodology proves to be useful to the decision makers to find optimal numbers of stations that are needed without compromising the coverage of the concentrations across the study area.

A power-quality monitoring and assessment system for high-speed railways based on train-network-data center integration

In recent years,with the rapid development of high-speed railways(HSRs),power interruptions or disturbances in traction power supply systems have become increasingly dangerous.However,it is often impossible to detect these faults immediately through single-point monitoring or collecting data after accidents.To coordinate the power quality data of both traction power supply systems(TPSSs)and high-speed trains(HSTs),a monitoring and assessing system is proposed to access the power quality issues on HSRs.By integrating train monitoring,traction substation monitoring and data center,this monitoring system not only realizes the real-time monitoring of operational behaviors for both TPSSs and HSTs,but also conducts a comprehensive assessment of operational quality for train-network systems.Based on a large number of monitoring data,the field measurements show that this real-time monitoring system is effective for monitoring and evaluating a traction-network system.

Study on Division Method of Quality Monitoring Control Area Based on Comprehensive Cultivated Land Attribute

The quality change of cultivated land resources requires the scientific deployment of monitoring areas.In this study,Yuzhou City is taken as an example to divide the quality monitoring control areas through the study of natural quality,utilization level,income level,and utilization characteristics,etc.Compared with the traditional administrative unit division or cultivated land quality division method,the regional homogeneity of this study is stronger,and there are quality differences between regions.It provides precondition and precision guarantee for the monitoring of cultivated land quality.

Analysis of Teaching Quality Monitoring in ISO9000 Quality Management System

With the development of the times, all kinds of competition, higher education gradually grow into the community center from the margins of society; the quality of higher education is becoming a major issue of concern. Monitoring and protecting the quality of higher education is now the main topic of higher education reform and development. Quality is the lifeline of university development, improving the quality of teaching is the eternal theme of higher education, and undergraduate education is the main and basic higher education. Therefore, improving the quality of undergraduate teaching is essential to enhance the quality of teaching in Higher Education.

Design of a Web Crawler for Water Quality Monitoring Data and Data Visualization

Many countries are paying more and more attention to the protection of water resources at present,and how to protect water resources has received extensive attention from society.Water quality monitoring is the key work to water resources protection.How to efficiently collect and analyze water quality monitoring data is an important aspect of water resources protection.In this paper,python programming tools and regular expressions were used to design a web crawler for the acquisition of water quality monitoring data from Global Freshwater Quality Database(GEMStat)sites,and the multi-thread parallelism was added to improve the efficiency in the process of downloading and parsing.In order to analyze and process the crawled water quality data,Pandas and Pyecharts are used to visualize the water quality data to show the intrinsic correlation and spatiotemporal relationship of the data.

Air Quality Monitoring and Its Implication on the Environmental Licensing Process in Brazil

In the state of Sao Paulo, Brazil, public policies regarding the air quality aimed at the welfare of the population are strongly dependent on monitoring conducted by the Sao Paulo State Environmental Company (CETESB), which can be influenced by faulty monitors and equipment support and cuts in power supply, among others. A research conducted from 1998 to 2008 indicated that a significant portion of the air quality automatic stations in the state of Sao Paulo did not meet the criterion of representativeness of measurements of PM10, NO2, O3, CO and SO2 concentrations which resulted in the classification of some municipalities as the nonattainment area, a situation evidenced for PM10 and O3 parameters. The network unavailability for each parameter was estimated and compared with the monitoring networks operated in Canada and the UK. This paper discusses the implications of the lack of representativeness of measurements in the environmental licensing process of pollution sources from 2008, when by the effect of state law, municipalities have been qualified according to their air quality nonattainment level.

Composition analysis of colored dissolved organic matter in Taihu Lake based on three dimension excitation-emission fuorescence matrix and PARAFAC model, and the potential application in water quality monitoring

Taihu Lake is one of the five biggest lakes in China. Surface water samples from 26 sampling sites of Taihu Lake were collected. Furthermore wet chemical analysis （CODCr and BOD5） and measurement of three dimensional excitation-emission matrix （3DEEM） spectra in the laboratory have been conducted. Using parallel factor analysis （PARAFAC） model, three components of colored dissolved organic matter （CDOM） have been identified successfully, based on the analysis of 3DEEM data. The characteristics of the three components also have been described by comparing them to some components of CDOM, identified in earlier researches. Meanwhile, spatial variations of concentration for the three components in Taihu Lake have been analyzed, and the result indicates that the concentration of component 1 depends more on the situation of wastewater pollution and can be used as the indicator of wastewater pollution. The relationship between the concentrations of the three components and results of the wet chemical analysis show that none of the three components can be used as indicators of gross organic matter in water. However, the concentrations of all the three components have obvious linear relationships with the BOD5 value, especially for component 1 （r = 0.72878）. Finally, the potential applications of the composition analysis based on 3DEEM and PARAFAC model in water quality monitoring have been illuminated.

Quality monitoring of real-time GNSS precise positioning service system

The Real-Time Global Navigation Satellite System(GNSS)Precise Positioning Service(RTPPS)is recognized as the most promising system by providing precise satellite orbit and clock correc-tions for users to achieve centimeter-level positioning with a stand-alone receiver in real-time.Although the products are available with high accuracy almost all the time,they may occasionally suffer from unexpected significant biases,which consequently degrades the positioning perfor-mance.Therefore,quality monitoring at the system-level has become more and more crucial for providing a reliable GNSS service.In this paper,we propose a method for the monitoring of realtime satellite orbit and clock products using a monitoring station network based on the Quality Control(QC)theory.The satellites with possible biases are first detected based on the outliers identified by Precise Point Positioning(PPP)in the monitoring station network.Then,the corresponding orbit and clock parameters with temporal constraints are introduced and esti-mated through the sequential Least Square(LS)estimator and the corresponding Instantaneous User Range Errors(IUREs)can be determined.A quality indicator is calculated based on the IUREs in the monitoring network and compared with a pre-defined threshold.The quality monitoring method is experimentally evaluated by monitoring the real-time orbit and clock products generated by GeoForschungsZentrum(GFZ),Potsdam.The results confirm that the problematic satellites can be detected accurately and effectively with missed detection rate 4×10^(-6) and false alarm rate 1:2×10^(-5).Considering the quality alarms,the PPP results in terms of RMS of positioning differences with respect to the International GNSS Service(IGS)weekly solution in the north,east and up directions can be improved by 12%,10%and 27%,respectively.

Design and Realization of a Novel Hybrid-Drive Robotic Fish for Aquaculture Water Quality Monitoring

Thunniform swimmers(tuna)have a swinging narrow sequence stalk and a moon-shaped tail fin,which performs poorly at slow speed,higher acceleration and turning maneuverability.In most cases,faster speed and higher maneuverability are mutually rejection for most marine creatures and their robotic opponents.This paper presents a novel hybrid tuna-like swimming robot for aquaculture water quality monitoring,which interleaves faster speed and higher maneuverability.The robotic prototype emphasizes on streamlining and enhanced maneuverability mechanism designs in conjunction with a narrow caudal propeller to the tail.The innovative design endows the robot to easily execute the multi-mode swimming gait,including forward swimming,turning,diving/surfacing.The capabilities of our robot are validated through a series of indoor swimming pool and field breeding ponds.The robotic fish can achieve a maximum speed up to about 1.16 m/s and a minimum turning radius less than 0.46 Body Lengths(BL)and its maximum turning speed can reach 78.6∘/s.Due to its high speed,maneuverability and relatively small size,the robotic fish shed light on intelligent monitoring in complex aquatic environments.

Hot metal quality monitoring system based on big data and machine learning

The system of hot metal quality monitoring was established based on big data and machine learning using the real-time production data of a steel enterprise in China.A working method that combines big data technology with process theory was proposed for the characteristics of blast furnace production data.After the data have been comprehensively processed,the independent variables that affect the target parameters are selected by using the method of multivariate feature selection.The use of this method not only ensures the interpretability of the input variables,but also improves the accuracy of the machine learning process and is more easily accepted by enterprises.For timely guidance on production,specific evaluation rules are established for the key quality that affects the quality of hot metal on the basis of completed predictions work and uses computer technology to build a quality monitoring system for hot metal.The online results show that the hot metal quality monitoring system established by relying on big data and machine learning operates stably on site,and has good guiding significance for production.

Investigating the Air Quality Parameters in Louisiana’s Industrial Corridor: A Baton Rouge Case Study

In a local context, sustainable development entails utilizing the current resources—material and immaterial, measurable and immeasurable, popular and unpopular—of the community in a manner that avoids overexploitation and ensures intergenerational equity. This approach prioritizes the safety and health of local citizens, placing communal productivity above corporate profitability. This research aims to assess air quality surrounding 28 chemical industry sites in Baton Rouge, Louisiana, to understand the environmental and health impacts of industrial pollutants, with a focus on environmental justice. Air quality pollutants, including PM2.5, PM10, O3, NO2, CO, and SO2, were monitored for 75 days during the Summer, using the BreezoMeter app. Python, Mapize, and QGIS software technologies were utilized for data analysis and visualization. Findings indicate a reduction in NO2 and CO levels, compared to existing literature. However, the persistent challenge of particulate matter suggests areas for further environmental management efforts. Additionally, the research suggests a significant disparity in air pollution exposure, probably affecting marginalized communities. Although the nature of the study might not fully capture annual pollution trends, the findings highlight the urgent need for the chemical industry to adopt efficient production methods and for policymakers to enhance air quality standards and enforcement, particularly in pollution-sensitive areas. The disproportionate impact of air pollution on vulnerable communities calls for a more inclusive approach to environmental justice, ensuring equitable distribution of clean air benefits and community involvement in pollution management decisions.

Air quality nearby road traffic tunnel portals: BTEX monitoring

A monitoring campaign of BTEX （benzene, toluene, ethylbenzene, o- m- and p-xylene） was carried out nearby two tunnel portals in the urban area of Naples with the aim to verify air quality in this kind of urban sites. Sampling was carried out using the active adsorption technique. Sampling time was 1 h. Ambient temperature and traffic flow measurements were carried out during each sampling operation. The results indicate that average benzene concentrations at both sites exceed the limit value of 10 μg/Nm^3 established by the European Community （EC） （Dir. 2000/69）. Concentration levels of other BTEX are relatively high as well. A correlation between BTEX concentration and two wheeler vehicle flow was observed.