scholarly journals Study on Acidity and Neutralizing Ability of Ions in the Chemical Composition of Rainwater

2021 ◽  
Vol 37 (2) ◽  
Author(s):  
Han Thi Ngan ◽  
Hoang Xuan Co ◽  
Pham Thi Thu Ha ◽  
Nguyen Manh Khai
Keyword(s):  
Chemical Composition ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Acid Neutralization ◽  
Ph Distribution ◽  
Main Contributor ◽  
Rainwater Quality

The acidity in rainwater is mainly controlled by the presence of H2SO4, HNO3 in combination with the ability to neutralize cations in rainwater. pH is an important value in the evaluation of acidity in rainwater. The research used a series of rainwater quality monitoring data from 2005 to 2018 in Vietnam. The research showed that the average pH distribution at 23 stations ranged from 5.83 ± 0.62. The rains with pH <5.6 appear in all years at the research stations. Considering the ability of acid neutralizing to various ions shows that Ca2+ is the main contributor to acid neutralization processes in rainwater, followed by Mg2 +, NH4+, and K+. While Ca2+ always play the highest acid neutralizing role at all stations; Depending on each station, Mg2+ and NH4+  ions play a role in neutralizing acidity in rainwater. The research also shows a match between the trend of H+ concentration and the tendency of cations to contribute to acid neutralization in rainwater.  

Monitoring of Flooding Water under Coal Mine Based on Improved Fuzzy Clustering

2014 ◽  
Vol 580-583 ◽  
pp. 2713-2716
Author(s):  
Meng Ya Nie ◽  
Meng Ran Zhou ◽  
Xue Qiang Fu
Keyword(s):  
Fuzzy Clustering ◽  
Coal Mine ◽  
Clustering Algorithm ◽  
Water Quality Monitoring ◽  
Underground Water ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Swarm Optimization ◽  
Mine Flooding ◽  
Monitoring Data Processing

Due to the complicated coal mine flooding water quality monitoring data, in order to extract the effective data from vast amounts of data, this article used the fuzzy clustering to analyze the monitoring data processing. This study makes a brief analysis of monitoring data structure, then analyzes the shortcomings of fuzzy C mean clustering algorithm (FCM),which also proposes fuzzy C-means algorithm based on particle swarm optimization (PSO-FCM). Finally samples of the underground water data are used to carry out the instance simulation. The experiment results showed that in dealing with data samples. The algorithm had some advantages and it was worthy of research.

Air Quality Data Management System Based on VB.NET

2014 ◽  
Vol 955-959 ◽  
pp. 1147-1150
Author(s):  
A Gu Da Mu Liu ◽  
Peng Yang ◽  
Wen Sheng Lv ◽  
Jie Liu
Keyword(s):  
Air Quality ◽  
Data Management ◽  
Management System ◽  
System Development ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Data Management System ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
Air Quality Data

In order to achieve the automatic management of air quality monitoring data, the air quality data management system has been developed using VB.NET platform and Oracle as background database. It is also combined with the situation of the air quality in Beijing and based on the air quality monitoring data. The paper analyzes the system from 6 aspects, including technology selection, system architecture, system data flow diagram, system development environment, system functions and system features. Finally this paper explains the significance of the system development and application prospects.

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