scholarly journals Environmental Impact Assessment of Taza City’s Wastewater: Application through Principal Component Analysis

Scientifica ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Ibrahim Touzani ◽  
Mohammed Machkor ◽  
Otmane Boudouch ◽  
Imane El Machrafi ◽  
Rachid Flouchi ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Urban Expansion ◽  
Physicochemical Characterization ◽  
Oxygen Demand ◽  
Principal Component ◽  
Component Analysis ◽  
Wastewater Discharge ◽  
One Year ◽  
Sewerage Network ◽  
Highly Loaded

Taza City is among the Moroccan cities which is in full urban expansion, with a daily wastewater discharge volume estimated at 16534 m3/d in 2020, and expected to reach 20056 m3/d by 2030. These waters, collected in a combined sewerage network, are directly released into the natural environment without any treatment. Indeed, a large part of this water is discharged into Oued Defali, the main tributary of Oued Larbâa. In order to manage and better understand these discharges impact on the streams crossing this city, wastewater sampling campaigns were carried out for one year from May 2018 to April 2019 at domestic (S1) and industrial (S2) sites. The wastewater physicochemical characterization revealed that these discharges are highly loaded with organic matter in terms of chemical oxygen demand (S1 avg = 1231.44 mg/l and S2 avg = 933.03 mg/l), biochemical oxygen demand (S1 avg = 511.87 mg/l and S2 avg = 464.35 mg/l), and suspended matter (S1 avg = 744.11 mg/l and S2 avg = 578.13 mg/l). The use of principal component analysis (PCA) has allowed us to collect as much information as possible from the database of the physicochemical analyses performed for the studied parameters.

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 STUDI AWAL RAJA AMPAT SEBAGAI MARINE ECO ARCHEO PARK: ANALISIS KUALITAS PERAIRAN DI KAWASAN SELAT DAMPIR

Jurnal Segara ◽  
2018 ◽  
Vol 14 (1) ◽  
Author(s):  
Agustin Rustam ◽  
Ira Dillenia ◽  
Rainer A Troa ◽  
Dietriech G Bengen
Keyword(s):  
Principal Component Analysis ◽  
Oxygen Demand ◽  
Principal Component ◽  
Component Analysis ◽  
Biological Oxygen Demand ◽  
Coral Triangle ◽  
Purposive Sampling

Selat Dampir yang berada di daerah Raja Ampat merupakan salah satu gugusan pulau-pulau kecil yang berada di ujung kepala burung pulau Papua bagian dari kawasan Coral Triangle Initiative (CTI) yang memiliki biodiversitas tinggi. Selain itu di lokasi ini terdapat situs arkeologi maritim, sehingga kawasan ini merupakan kawasan yang cocok sebagai kawasan marine eco archeo park. Perlu dilakukan penelitian awal keberadaan lokasi ini seperti kualitas perairan yang dilakukan pada tanggal 7 – 13  Mei 2014. Pengambilan data kualitas perairan dilakukan secara purposive sampling dengan menggunakan alat multiparameter secara in situ dan analisis sampel air di laboratorium. Parameter yang diukur yaitu salinitas, pH, turbiditas, padatan tersuspensi (TSS), Biological Oxygen Demand (BOD5), nitrat, tembaga dan nikel. Analisis data dilakukan secara deskriptif dan menggunakan analisis PCA (Principal Component Analysis). Hasil yang didapat untuk semua parameter masih sesuai dengan KMNLH no 51 tahun 2004, hanya nilai tembaga pada saat pengukuran tidak sesuai, walaupun secara keseluruhan perairan Selat  Dampir pada saat pengukuran masih dalam kondisi baik sebagai daerah taman nasional dan wisata bahari. Berdasarkan analisis PCA didapatkan parameter yang berperan kuat di lokasi adalah BOD5, pH, TSS dan kecerahan. Diperlukan penelitian lebih lanjut terkait lokasi penelitian sebagi situs maritim dan daerah wisata bahari di daerah konservasi dalam mewujudkan marine eco archeo park berbasis ekosistem lestari.

scholarly journals PARAMETER FISIKA, KIMIA, DAN BIOLOGI PENCIRI HABITAT IKAN BELIDA (Chitala lopis)

2017 ◽  
Vol 15 (1) ◽  
pp. 13
Author(s):  
Arif Wibowo ◽  
Mas Tri Djoko Sunarno ◽  
Safran Makmur
Keyword(s):  
Principal Component Analysis ◽  
Discriminant Analysis ◽  
Dissolved Oxygen ◽  
Air Temperature ◽  
Oxygen Demand ◽  
Principal Component ◽  
Environmental Parameters ◽  
Component Analysis ◽  
Biological Oxygen Demand ◽  
Total Dissolved Solid

Penelitian mengenai parameter fisika, kimia, dan biologi penciri habitat ikan belida (Chitala lopis) dilakukan tahun 2005 - 2006 di perairan umum daratan di Sumatera, Kalimantan, dan Jawa. Tujuan nya adalah untuk mendapatkan informasi parameter lingkungan yang menjadi karakteristik habitat ikan belida dari berbagai badan air di Jawa, Sumatera, dan Kalimantan. Metode survei dan kegiatan laboratorium digunakan dalam penelitian ini. Parameter lingkungan yang diamati meliputi suhu udara, suhu air, Total Dissolved Solid (TDS), Daya Hantar Listrik (DHL), klorofil-a, kecepatan arus, Biological Oxygen Demand (BOD), oksigen terlarut, pH, alkalinitas, CO2 bebas, kedalaman air, dan kecerahan pada 116 lokasi pengambilan yang ditentukan secara sengaja di Sungai Tulang Bawang (Provinsi Lampung), Sungai Kampar, Sungai Siak (Provinsi Riau), Sungai Musi (Provinsi Sumatera Selatan), Sungai Citarum (Provinsi Jawa Barat), Sungai Kapuas (Provinsi Kalimantan Barat), dan Waduk Riam Kanan (Provinsi Kalimantan Selatan). Analisis data menggunakan pendekatan analisis multivariabel regresi berganda Metode Backward yang didasarkan pada Analisis Komponen Utama (Principal Component Analysis) dan pembeda (Discriminant Analysis), serta korespondensi analisis (correspondency analysis). Hasil penelitian menunjukkan habitat ikan belida dapat dibedakan menjadi tiga tipe, yaitu tipe yang menyerupai sungai utama, waduk, dan anak sungai. Pembeda utama sekaligus parameter lingkungan utama adalah parameter TDS yang paling besar, dan selanjutnya parameterparameter DHL, suhu udara, klorofil-a, kecepatan arus, BOD, Oksigen terlarut, pH, alkalinitas, dan CO2 bebas menyumbang yang paling sedikit. Kehadiran plankton genus Ulothrix dan Mytilina secara tidak langsung teridentifikasi sebagai penciri habitat spesifik ikan belida. Research on physical, chemical, and biological parameters indicating specific habitat of clown knife fish (Chitala lopis) was carried out at 2005 - 2006 in inlands waters of Sumatera, Borneo, and Java. This study purposed to obtain information of environmental parameters indicating habitat characteristic of the knife fish in various inland waters bodies in Sumatera, Borneo, and Java. Survey method and laboratory activities were employed in this research. Environmental parameters observed were air temperature, water temperature, Total Dissolved Solid (TDS), conductivity, water velocity, Biological Oxygen Demand (BOD), dissolved oxygen, pH, alkalinity, free C02, water depth, and water transparancy taken on 116 sampling stations distributing in Tulang Bawang River (Lampung Province), Kampar and Siak River (Riau Province), Musi River (South Sumatera Province), Kapuas River (West Kalimantan Province), Riam Kanan Reservoar (South Kalimantan Province), and Citarum River (West Java Province). Data analysis used multivariate approach of multiple regression of Backward Method such as Principal Component Analysis, Discriminant Analysis, and Corre spondency Analysis. The results showed that the clown knife fish habitats could be divided by three types of specific habitat, namely water bodies similar with main rivers, reservoir, and tributaries. Parameter of TDS indicated the primary differentization as well as habitat characteristics of the clown knife fish.Whilst the parameters of conductivity, air temperature, chlorophyill-a, water current, BOD, dissolved oxygen, pH, alcalinity, and free CO2 contributed less significance. The existence of plankton from genus Ulothrix and Mytilina was identified indirectly as the specific habitat of the clown knife fish.

scholarly journals Efficiency of electroflocculation in the treatment of water contaminated by organic waste

2020 ◽  
Vol 15 (2) ◽  
pp. 1
Author(s):  
Aline Nunes Andrade ◽  
Rodrigo Vieira Blasques ◽  
Paulo Cesar Mendes Villis ◽  
Darlan Ferreira Silva ◽  
Wolia Costa Gomes
Keyword(s):  
Water Pollution ◽  
Principal Component Analysis ◽  
Organic Waste ◽  
Oxygen Demand ◽  
Principal Component ◽  
Component Analysis ◽  
Effluent Treatment ◽  
Aluminum Electrode ◽  
Statistical Tool ◽  
Rivers And Lakes

 Population growth has led to occupation and housing near rivers and lakes. This contributes to the increase of water pollution. The industrial laundry sector, for example, consumes a large quantity for its processes and pollutes water bodies due to the improper disposal of its effluents which contain numerous harmful compounds. This study employed electroflocculation in effluent treatment and evaluated its efficiency by analyzing turbidity, chemical oxygen demand, and pH levels. It used aluminum and zinc plates as sacrificial electrodes and principal component analysis (PCA) as a statistical tool. A maximum electroflocculation time of 40 min was utilized in order to obtain efficient results from the study. The experiment showed significant improvement in the water quality in the physicochemical aspects, primarily concerning the reduction of organic matter in the effluent. The efficiency of this treatment increased with higher current; however, both the aluminum and zinc plates reacted differently to pH, COD, and turbidity. Two principal components were generated to explain 86.90% of the data variance in the experiment. The principal component analysis indicated that the aluminum electrode showed the best correlation (|>0.5|) for pH, COD, and turbidity in the effluent treatment.

Assessment of Aquatic Ecological Health: A Case Study of Lake Rewalsar, Himachal Pradesh

2020 ◽  
Vol 7 (01) ◽  
Author(s):  
RAMA KUMARI ◽  
PARMANAND KUMAR
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Water Quality Index ◽  
Quality Index ◽  
Management Strategies ◽  
Oxygen Demand ◽  
Principal Component ◽  
Component Analysis ◽  
Different Seasons

The present study was conducted for two years to analyze the water quality of the sacred lake Rewalsar. Water quality of different seasons was evaluated by water quality index. Various statistical techniques, such as correlation, principal component analysis were applied. Based on Water Quality Index, water quality of the lake was in the range of 33-80 in different seasons. Cluster analysis of similarity indicates the relationship intensity between the seasons as cluster ranged 80-100% during the study period. In the principal component analysis maximum variables (Conductivity, Alkalinity, Biochemical Oxygen Demand, Nitrates, Phosphates, and Chloride) shows maximum influence during the summer and monsoon. The outcome revealed that the major driving factors of water quality deterioration are the runoff of effluent from the domestic area and offering food materials to the fishes. So, it is necessary to implement effective management strategies for the conservation of the Rewalsarlake.

scholarly journals A Characterization of Metrics for Comparing Satellite-Based and Ground-Measured Global Horizontal Irradiance Data: A Principal Component Analysis Application

2020 ◽  
Vol 12 (6) ◽  
pp. 2454 ◽  
Author(s):  
Maria. C. Bueso ◽  
José Miguel Paredes-Parra ◽  
Antonio Mateo-Aroca ◽  
Angel Molina-García
Keyword(s):  
Principal Component Analysis ◽  
Power Systems ◽  
Power Plants ◽  
Principal Component ◽  
Component Analysis ◽  
Data Sources ◽  
Time Data ◽  
Irradiance Data ◽  
One Year

The increasing integration of photovoltaic (PV) power plants into power systems demands a high accuracy of yield prediction and measurement. With this aim, different global horizontal irradiance (GHI) estimations based on new-generation geostationary satellites have been recently proposed, providing a growing number of solutions and databases, mostly available online, in addition to the many ground-based irradiance data installations currently available. According to the specific literature, there is a lack of agreement in validation strategies for a bankable, satellite-derived irradiance dataset. Moreover, different irradiance data sources are compared in recent contributions based on a diversity of arbitrary metrics. Under this framework, this paper describes a characterization of metrics based on a principal component analysis (PCA) application to classify such metrics, aiming to provide non-redundant and complementary information. Therefore, different groups of metrics are identified by applying the PCA process, allowing us to compare, in a more extensive way, different irradiance data sources and exploring and identifying their differences. The methodology has been evaluated using satellite-based and ground-measured GHI data collected for one year in seven different Spanish locations, with a one-hour sample time. Data characterization, results, and a discussion about the suitability of the proposed methodology are also included in the paper.

scholarly journals Evaluation of Water Quality and Benthic Macrointervebrates Fauna Relationship Using Principal Component Analysis (PCA): A Case Study of Cameron Highlands Malaysia

2016 ◽  
Vol 5 (1) ◽  
pp. 187 ◽  
Author(s):  
Kok Weng Tan ◽  
Weng Chee Beh
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Dissolved Oxygen ◽  
Oxygen Demand ◽  
Principal Component ◽  
Component Analysis ◽  
Ammonia Nitrogen ◽  
Average Density ◽  
Class Iii ◽  
Cameron Highlands

<p class="ber"><span lang="EN-GB">This study applies the Principal Component Analysis (PCA) to evaluate and interpret the relationship between water quality and benthic macro-invertebrates fauna data obtained from <span class="longtext">Pauh River, Cameron Highlands. Samples were collected once every two months (in February, April, June, August and October 2013) with six chosen sampling stations. Six water quality parameters namely </span></span><span lang="EN-GB">dissolved oxygen (DO), pH, biological oxygen demand (BOD<sub>5</sub>), chemical oxygen demand (COD), ammonia-nitrogen (NH<sub>3</sub>-N), total suspended solid (TSS) and heavy metals contents <span class="longtext"><span>were analyzed according to American Public Health Association (APHA), </span></span>Standard Methods for Examination of Water and Wastewater<span class="longtext"><span> (1998)</span>. <span>Macro-invertebrates were also sampled using Surber sampler and were identified until their family level. Water Quality Index (WQI) values for all stations were class II except for the station 6 which was recorded as class III. Both the diversity and biotic indices showed decreasing value from the upstream (Station 1) to downstream (Station 6). </span></span>A total 28 to 31 taxa have been found in Station 1, 2, 3 and 5 (upstream to middle stream). However, only 7 taxa found at station 6 (downstream). Total 31 taxa with an average density 368.28 ind/m<sup>2</sup> were found in Station 4 which was highest number of taxa among the monitoring stations. <span class="longtext"><span>The </span></span><span>principal component analysis (PCA) was applied on the dataset, which explained 72.15 % of the total variance </span>of the variables<span>. Three components were extracted in this study. First component was classified as benthic macroinvertebrates which tolerated to low water quality condition and high loading of organic matters. The benthic macro-invertebrates families loaded in second component were sensitive to water environment such as NH<sub>3</sub>-N, dissolved oxygen (DO), organic matter and stream flow. The benthic macroinvertebrate families loaded in third component were recognized as species which might not tolerate low concentration of dissolved oxygen.  </span></span></p>

scholarly journals Evaluation of Water Quality of Kaveri River in Tiruchirappalli District, Tamil Nadu by Principal Component Analysis

2016 ◽  
Vol 11 (1) ◽  
pp. 89-95 ◽  
Author(s):  
Monikandon Sukumaran ◽  
Kesavan Devarayan
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Tamil Nadu ◽  
Oxygen Demand ◽  
Principal Component ◽  
Component Analysis ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Linear Relationships

Principal component analysis is a unique technique for reducing the dimensionality of the data. In this study, ten water quality parameters of the river Kaveri observed at five different stations of Tiruchirappalli for six years were collected and subjected to principal component analysis. A computational program was prepared in order to process and understand the data as a cluster. At first necessary data for compiling the program were listed and then fed to the program. Then the outputs were analyzed and possible linear and non-linear relationships between the water quality parameters and the timeline. It is understood that biological oxygen demand and fecal coli had a linear relationship. Further, the results suggested for group of factors that influence the water quality in a particular year.

scholarly journals Principal Component Analysis of Urban Expansion Drivers in Greater Lagos, Nigeria

2017 ◽  
Vol 1 (1) ◽  
pp. 156-168
Author(s):  
O. E. Abiodun ◽  
J. B. Olaleye ◽  
J. O. Olusina ◽  
O. g> Omogunloye
Keyword(s):  
Principal Component Analysis ◽  
Environmental Changes ◽  
Urban Expansion ◽  
Principal Component ◽  
Component Analysis ◽  
Land Policy ◽  
Sustainable Urban Development ◽  
Landsat Images ◽  
Water Vegetation

Urban expansion has been identified as a major cause of global climatic and environmental changes. Accurate and up-to-date information about urban expansion in terms of the drivers responsible for this expansion are important for long term planning and sustainable urban development. Lagos is one of the cities that have undergone rapid urban enlargement in the last few decades and, many factors have been adduced to contribute to its sprawling. Therefore, this study aims at using the Principal Component Analysis (PCA) for identifying the principal drivers of urban expansion in greater Lagos. In this study, a set of fourteen (14) drivers of expansion are considered in a multinucleic structure. A sequence of Landsat images of the study area for 1984, 2001, 2006 and 2013 was acquired and processed to six land use classes: dense, moderate urban, water, vegetation, wetland and mangrove. The study area was partitioned into 25 regular cells of 20km by 25km each from where proximate driver values were obtained. The effectiveness of each driver was tested using PCA. The results show that Land Availability accounted for 37.836% of total variance. This result of this study may form the basis for a renewed attention on land policy in the study area as a way to enhance sustainable development.

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