Evaluation of Regional Water Resources Carrying Capacity in Yan'an Based on Principal Component Analysis

2013 ◽  
Vol 864-867 ◽  
pp. 2331-2334
Author(s):  
Xiao Jun Liu ◽  
Jia Wang
Keyword(s):  
Principal Component Analysis ◽  
Water Resources ◽  
Sewage Treatment ◽  
Temporal Distribution ◽  
Principal Component ◽  
Environmental Water ◽  
Component Analysis ◽  
Treatment Rate ◽  
Factors Affecting ◽  
Development And Utilization

Yan'an is the center of political, economic, cultural and military in Shanbei, and is also a city of water resources extremely shortage. This paper by using the principal component analysis to select 13 indicators and establish the indicators system, two main ingredients reflect Yan'an WRCC, thus evaluate Yan'an WRCC in 2006 - 2011 timing data. Results show that: rate of urbanization, ecological and environmental water use rate, per capita GDP, rate of water resources development and utilization and sewage treatment rate are the main factors affecting Yan'an WRCC; 2006-2011 Yan'an in the temporal distribution of WRCC overall downward trend, the development and utilization of water resources potential in Yan'an weaker. Finally put forward reasonable suggestions aim at future sustainable development and utilization of water resources in Yan'an.

Fault Detection and Monitoring Using Multiscale Principal Component Analysis at a Sewage Treatment Plant

2014 ◽  
Vol 70 (3) ◽  
Author(s):  
Siti Nur Suhaila Mirin ◽  
Norhaliza Abdul Wahab
Keyword(s):  
Principal Component Analysis ◽  
Fault Detection ◽  
Sewage Treatment ◽  
Sewage Treatment Plant ◽  
Treatment Plant ◽  
Principal Component ◽  
Component Analysis ◽  
False Alarms ◽  
Sewage Treatment Plants ◽  
Hotelling’S T2

Safety, environmental regulations, the cost of maintenance and the operation of sewage treatment plants are some of the many reasons researchers have carried out countless research studies into fault detection and monitoring over the years. Conventional principal component analysis (PCA) in particular has been used in the field of fault detection, where the technique is able to separate useful information from multivariate data. However, conventional PCA can only be used on data that has a constant mean, which is rare in sewage treatment plants. Consequently, the success of combining wavelet and conventional PCA has attracted many researchers to apply it to fault detection where the wavelet is capable of separating data into several time scales. The separated data will be approximated to a constant mean. In addition, the conventional PCA only captures the correlation across the data, unlike multiscale PCA (MSPCA) which captures the correlation within the data and across the data. Therefore, in this work, MSPCA is introduced to improve the performance of PCA in fault detection. The objective of this paper is to reduce false alarms that exist in PCA fault detection and monitoring. Data from the Bunus sewage treatment plant (Bunus STP) is used and analysed using conventional PCA with Hotelling’s T2 and the squared prediction error (SPE). MSPCA with Hotelling’s T2 and SPE is used to improve the efficiency of fault detection and monitoring performance in conventional PCA. Therefore, MSPCA is successful in improving conventional PCA in fault detection and monitoring by reducing false alarms. 

scholarly journals Evaluation Methods of Water Environment Safety and Their Application to the Three Northeast Provinces of China

2019 ◽  
Vol 11 (18) ◽  
pp. 5135 ◽  
Author(s):  
Li ◽  
Sun ◽  
Yuan ◽  
Liu
Keyword(s):  
Principal Component Analysis ◽  
Water Resources ◽  
Chemical Oxygen Demand ◽  
Water Environment ◽  
Oxygen Demand ◽  
Principal Component ◽  
Component Analysis ◽  
Analysis Method ◽  
Industry Output ◽  
Per Capita

Focusing on the topic of water environment safety of China, this paper has selected the three northeast provinces of China as the research object due to their representativeness in economic development and resource security. By using the Entropy Weight Method, the Grey Correlation Analysis Method, and the Principal Component Analysis Method, this paper has first constructed a water environment safety evaluation system with 17 indicators from the economic, environmental, and ecological aspects. Furthermore, this paper has screened the initially selected indicators by the Principal Component Analysis Method and finally determined 11 indicators as the evaluation indicators. After indicator screening, this paper has adopted the improved Fuzzy Comprehensive Evaluation Method to evaluate the water environment safety of the three northeast provinces of China and obtained the change in water environment safety of different provinces from 2009 to 2017. The results show that the overall water environment safety of the region had improved first but worsened afterward, and that in terms of water safety level, Jilin Province ranked first, followed by Heilongjiang Province and Liaoning Province. The three factors that have the greatest impact on the water environment safety of the three provinces are: Liaoning—Chemical Oxygen Demand (score: 17.10), Per Capita Disposable Income (score: 13.50), and Secondary Industry Output (score: 11.50); Heilongjiang—Chemical Oxygen Demand (score: 18.64), Per Capita Water Resources (score: 12.75), and Concentration of Inhalable Particles (score: 10.89); Jilin—Per Capita Water Resources (score: 15.75), Chemical Oxygen Demand (score: 14.87), and Service Industry Output (score: 11.55). Based on analysis of the evaluation results, this paper has proposed corresponding policy recommendations to improve the water environment safety and promote sustainable development in the northeast provinces of China.

scholarly journals Diversity of entomopathogenic fungi associated with Mediterranean fruit fly (Ceratitis capitata (Diptera: Tephritidae)) in Moroccan Argan forests and nearby area: impact of soil factors on their distribution

BMC Ecology ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ayoub Hallouti ◽  
Mohamed Ait Hamza ◽  
Abdelaziz Zahidi ◽  
Rachid Ait Hammou ◽  
Rachid Bouharroud ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Entomopathogenic Fungi ◽  
Ceratitis Capitata ◽  
Chemical Properties ◽  
Principal Component ◽  
Fruit Fly ◽  
Component Analysis ◽  
Organic Content ◽  
Pathogenicity Test ◽  
Factors Affecting

Abstract Background Studying the ecology of biocontrol-agents is a prerequisite to effectively control medfly (Ceratitis capitata (Diptera: Tephritidae)) with entomopathogenic fungi. In this context, factors affecting the occurrence and distribution of medfly-associated entomopathogenic-fungi were studied. Soil samples (22) were collected from natural and cultivated areas of Souss-region Morocco. Results A total of 260 fungal isolates belonging to 22 species and 10 genera were obtained by using medfly pupae as bait. Medfly-associated fungi were detected in all studied soils and pupae infection percentages ranged from 3.33% to 48%. Two genera, Fusarium and Beauveria were the most frequent with 83 isolates (32%) and 50 isolates (19.23%) respectively. Pathogenicity test of isolated species against medfly pupae showed high mortality rates up to 91% for some strains. Principal component analysis (PCA) demonstrated a strong influence of origin, physical, and chemical properties of soil on the abundance of these fungi. In general, medfly-associated fungi were more abundant in soils with moderate pH (7.5 to 8) having high sand and organic content. High relative humidity negatively influenced the abundance of these fungi. Both factors directly affected the fungal infection percentages in pupae. The response of fungi to these parameters varied among species. According to principal component analysis (PCA), the soils of argan fields and forests were more suitable for the development of medfly-associated fungi than citrus orchards. Conclusions These results guide identifying suitable soils for the effective application of entomopathogenic fungi as biological control agents. In summary, isolated indigenous strains seem to be a promising option to control C. capitata.

The Establishment of Principal Component Analysis Assessment Model for Drinking Water Quality of City Resource

2014 ◽  
Vol 675-677 ◽  
pp. 960-963
Author(s):  
Li Feng Sun ◽  
Qing Jie Qi ◽  
Xiao Liang Zhao ◽  
Rui Feng Li
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Drinking Water ◽  
Water Resources ◽  
Principal Component ◽  
Water Source ◽  
Component Analysis ◽  
Assessment Model ◽  
Affecting Factors

In order to effectively control pollution of sources of drinking water, improve the environmental quality of drinking water and guarantee the sanitation of drinking water, it is very important to assess water source quality. Main factors of drinking water were identified. Then principal component analysis was used to establish assessment model of drinking water, which could ensure that under the condition that the primitive data information was in the smallest loss, a small number of variables were used to replace the integrated multi-dimensional variables to simplify the data structure. The weightings of principal component were determinated as theirs pollution ratios. This paper was based on the theoretical study of principal component analysis, used the monitoring data on water quality of the main water resources in 2013 to evaluate and analyze the water quality of water resources. Analysis content included the main affecting factors, cause of pollution and the degree of pollution.The resulted showed that: the main affecting factors on water quality of Fo Si water source was CODMn, TP, fluoride.

scholarly journals Spatio-temporal distribution of microalgae producing chlorophyll and carotenoid pigments in Bali Strait, Indonesia

2018 ◽  
Vol 20 (1) ◽  
pp. 61-67
Author(s):  
ANNA FAUZIAH ◽  
DIETRIECH G BENGEN ◽  
MUJIZAT KAWAROE ◽  
HEFNI EFFENDI ◽  
MAJARIANA KRISANTI
Keyword(s):  
Principal Component Analysis ◽  
Water Resources ◽  
Chlorophyll A ◽  
Correspondence Analysis ◽  
Temporal Distribution ◽  
Principal Component ◽  
Carotenoid Pigments ◽  
Chlorophyll B ◽  
Chaetoceros Gracilis ◽  
Spatio Temporal

Fauziah A, Bengen DG, Kawaroe M, Effendi H, Krisanti M. 2019. Spatio-temporal distribution of microalgae producing chlorophyll and carotenoid pigments in Bali Strait, Indonesia. Biodiversitas 20: 61-67. The Bali Strait waters become a place for various development activities that connect Java Island and Bali Island so that it is thought to have an impact in the life of microalgae that play an important role in the wealth of their water resources. This study aims to explore the spatiotemporal distribution of marine microalgae, which has the potential to produce chlorophyll and carotenoid pigments, as well as their relationship with the environmental characteristics of the Bali Strait waters. The research was conducted at the 5 stations in the morning, midday and afternoon. The data obtained were analyzed using Principal component analysis (PCA) and Correspondence analysis (CA). The results showed that chlorophyll-a, chlorophyll-b and carotenoid were mostly contained by the species Chaetoceros gracilis, Tripos lunula at station 5 (Pang-pang Bay) in the morning, midday and afternoon, and contained by the species Fragilariopsis cylindrus, Thalassiothrix fravenfeldii at station 3 (Ketapang-Gilimanuk ferriage) in the midday and afternoon. Spatially, salinity, ammonia, nitrate, and chlorophyll-a have significantly different values between stations, while temporally the content of chlorophyll-b and carotenoid are influenced by time (in the morning, midday and afternoon).

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