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Temporal Changes in Water Quality Parameters of Two Sections of the Ancient Canal: A Case of a Reach for Yangnong Chemical Plant
Huang Yongzeng,
Huang Jinbai,
Zhou Yaming,
Zhen Ziqiang,
Zhou Qin
Issue:
Volume 6, Issue 3, June 2018
Pages:
71-76
Received:
11 June 2018
Accepted:
25 June 2018
Published:
13 July 2018
Abstract: The water quality of the Ancient Canal has changed significantly due to the continuous urbanization of Yangzhou City. The main objective of this study was to reveal the temporal changes of conventional water quality parameters in a specific section of the Ancient Canal that flows through the Yangnong Chemical Plant. Two sections (Sec. 1 and Sec. 2) located upstream and downstream of this chemical plant, respectively, were chosen for observation of water quality parameters, including temperature (WT), pH, dissolved oxygen concentration (DO), electrical conductivity (EC) and total dissolved solids (TDS) content. The correlation coefficient method (CC), single factor index method (SFI) and variation coefficient method (VC) were used to analyze the data obtained from October 2015 to September 2016. The results indicated that (1) WT of Sec. 2 was higher than Sec.1 by an average of 0.8°C. In addition, the pH increased and decreased occasionally and with no obvious trend. The mean DO of Sec. 2 was 1.80 mg/L lower than that of Sec. 1. The EC and TDS of Sec. 2 were higher than those of Sec. 1; a relatively high correlation existed between the observed results of each corresponding parameter between Sec. 1 and Sec. 2. Overall, the water quality of Sec. 2 was worse than that of Sec. 1 over the study period; VC of the DO was the maximum, while the VC of the pH was the minimum. The results provide a partial basis for further studies on water quality of the Ancient Canal and urban river of Yangzhou City.
Abstract: The water quality of the Ancient Canal has changed significantly due to the continuous urbanization of Yangzhou City. The main objective of this study was to reveal the temporal changes of conventional water quality parameters in a specific section of the Ancient Canal that flows through the Yangnong Chemical Plant. Two sections (Sec. 1 and Sec. 2)...
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Topic Modeling of Environmental Data on Social Networks Based on ED-LDA
Lei Feng,
Jose López,
Li Feng,
Sheng Zhang,
Bormin Huang,
Fang Fang,
Chongming Li
Issue:
Volume 6, Issue 3, June 2018
Pages:
77-83
Received:
24 April 2018
Accepted:
21 June 2018
Published:
23 July 2018
Abstract: The rapid development in information technology and web technology has facilitated an extreme increase in the collection and storage of digital data. With the development of environmental online monitoring science and internet technology development, more and more environmental data are stored on the Internet and shared by people on social networks. Therefore, there is a growing interest in automatically identifying environmental factors and environmental big data mining that contribute to public environmental risks, such as mining water quality problem, air pollution problem, soil problem on internet. Better understanding of these factors and analysis data will enable more precise prediction of the location and time of high risk events for environmental management. These environmental data from social networks by using WebCrawler in Twitter, Early work research on environmental data analysis focused more on specific filed analysis for traditional data without consider data relationships and data structure on social networks. The traditional environmental data analysis methods have been studied well, but no algorithms are designed for analysis environmental data on social networks. In this paper, this research propose a novel probabilistic generative model based on LDA, it called ED-LDA algorithm model that algorithm model not only consider the traditional environmental data analysis method, but also include the environmental data relationship and structure to help us find out the useful information and analysis to mine the relationship between users and their posted environmental data on social network to better understand data meaning for environmental management. This research present a Gibbs sampling implementation for inference of our model, and find out the environmental data topic on twitters. Besides our model can be used to many other environmental context files. The experimental result shows that Comparing with the traditional LDA clustering algorithm ED-LDA method can effectively mine and classify environmental data. This method can be a powerful computational approach for clustering environmental data on internet.
Abstract: The rapid development in information technology and web technology has facilitated an extreme increase in the collection and storage of digital data. With the development of environmental online monitoring science and internet technology development, more and more environmental data are stored on the Internet and shared by people on social networks...
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Equilibrium, Kinetic and Adsorption Mechanisms of Chromium (VI) on Characterized Activated Carbon Synthesized from Phosphoric Acid Activation of Coconut Shells
Hakeem Seidu,
Dapeng Li,
Jing Zhou
Issue:
Volume 6, Issue 3, June 2018
Pages:
84-94
Received:
15 May 2018
Accepted:
6 June 2018
Published:
25 July 2018
Abstract: Over the years, water pollution due primarily to the discharge of toxic heavy metals from industrial activities has served as a major challenge in our quest to provide clean drinking water to millions of people across the world. Numerous cheap and environmentally friendly methods and technologies have been developed for the treatment of wastewater contaminated with heavy metals. Key among these technologies is the use of adsorbent as it is the most economical and efficient. In this present study, coconut shells were used to develop microporous adsorbent (activated carbon) through chemical activation by phosphoric acid (H3PO4). An analysis of the effect of various process parameters such as pH, temperature, initial metal ion concentration, adsorbent dose and contact time was conducted through batch adsorption of hexavalent chromium [Cr (VI)] on prepared AC sample. Initial Cr (VI) concentration was investigated through a range of 10 – 50 mg/L with the study showing an optimum concentration for AC of 20 mg/L for percentage removal (93.3%) but adsorption capacity (Qe) was highest for 50 mg/L (4.512 mg/g). The optimum conditions for adsorbent dose, contact time and temperature were determined as 6 g/L, 100 minutes and 30°C respectively for the prepared AC. Maximum adsorption was recorded for pH (2) at 88.2 5% (removal) and 4.41 mg/g (adsorption capacity) for AC. The experimental data obtained were modelled using various isotherms, including adsorption equilibrium isotherms, adsorption kinetic study and adsorption mechanisms with positive correlations (better fit) obtained for Freundlich isotherm, D-R isotherm (slightly), pseudo-second-order kinetic and Boyd models.
Abstract: Over the years, water pollution due primarily to the discharge of toxic heavy metals from industrial activities has served as a major challenge in our quest to provide clean drinking water to millions of people across the world. Numerous cheap and environmentally friendly methods and technologies have been developed for the treatment of wastewater ...
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Chemical and Biochemical Evaluation of Marine Pollution by Polychlorinated Biphenyls and Pesticides in Two Regions Along the Egyptian Mediterranean Sea
Mohamed Atia Sheradah,
Amany Ahamed El-Sikaily,
Nehad Mohamed Abd El Moneam,
Nabila Elsayed Abd El Maguid,
Marwa Gaber Zaki
Issue:
Volume 6, Issue 3, June 2018
Pages:
95-109
Received:
1 August 2018
Accepted:
3 September 2018
Published:
26 September 2018
Abstract: The main objective of this paper is to understand the importance of biochemical biomarkers in assessing marine pollution by Polychlorinated biphenyls (PCBs) and Pesticides. Methods: The oxidative stress and antioxidant response as well as ultrastructural changes of both liver and muscle tissues of Siganusrivulatus collected from El-Mex Bay as a polluted region and Marsa Matrouh as a control region far from land-based sources of pollution have been investigated by using standard methods. In general, the results cleared out that El-Mex Bay was much more polluted by polychlorinated biphenyls (PCBs) and pesticides compared to Matrouh area. The concentration range of total polychlorinated biphenyls (PCBs) and pesticides in sediment samples collected from Matrouh coast was 16.29-32.58 ng/g, dry weight and 107.62-149.11ng/g, dry weight, respectively. On contrast, the range in sediment samples collected from El- Mex Bay was 217.12-255.33 ng/g, dry weight and 663.73-778.7ng/g, dry weight, respectively. Biomarkers studies revealed that the induction of antioxidant systems in response to oxidative stress and the increase in lipid peroxidation in fish collected from the polluted area were good indicators for the pollution load" in the present study. On the meantime, the present study revealed that ultrastructural changes serve as a biomarker of stress in aquatic environment. Moreover, the results suggested that chemical pollution, on the other hand, is capable of inducing morphological alteration in liver of fish collected from polluted area.
Abstract: The main objective of this paper is to understand the importance of biochemical biomarkers in assessing marine pollution by Polychlorinated biphenyls (PCBs) and Pesticides. Methods: The oxidative stress and antioxidant response as well as ultrastructural changes of both liver and muscle tissues of Siganusrivulatus collected from El-Mex Bay as a pol...
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Visibility Graph Network Analysis of Air Quality Data
Xinghua Fan,
Qi Zhang,
Li Wang,
Jiuli Yin
Issue:
Volume 6, Issue 3, June 2018
Pages:
110-115
Received:
17 October 2018
Accepted:
Published:
18 October 2018
Abstract: As air quality is closely related to human life and physical and mental health, the data of air quality has become a concern of the entire society. This study analyzes the characteristics of air quality data from a visibility graph networks point of view. The authors select eight monitoring stations in Beijing as samples. The time series of air quality data is mapped to a complex network based on the visibility graph algorithm. First, the authors study the topological structure of the networks for all the monitoring stations. Comparison results show that all constructed networks have similar structures in terms of the average path length, the network diameter, average clustering coefficient, density and the average degrees. Then the authors study the evolution of the visibility graph network for Huairou Town station for a long period of time. On the one hand, the value of the node degree indicates that the most important dates for air quality are the end of April, the beginning of May and the first three weeks of winter. On the other hand, the small-world properties of the networks reveals that the air quality data for the year 2014 is more stable without extreme fluctuations. This finding is consistent with the conclusion that air quality is largely affected by the weather while human activities play a more and more important role.
Abstract: As air quality is closely related to human life and physical and mental health, the data of air quality has become a concern of the entire society. This study analyzes the characteristics of air quality data from a visibility graph networks point of view. The authors select eight monitoring stations in Beijing as samples. The time series of air qua...
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