Reducing the dimension of water quality parameters in source water: An assessment through multivariate analysis on the data from 441 supply systems
In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Co...
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| Autor*in: |
Chowdhury, Shakhawat [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
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| Übergeordnetes Werk: |
Enthalten in: Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality - Ren, Chunhui ELSEVIER, 2022, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:274 ; year:2020 ; day:15 ; month:11 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.jenvman.2020.111202 |
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ELV051503913 |
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| 520 | |a In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. | ||
| 520 | |a In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. | ||
| 650 | 7 | |a Factor analysis |2 Elsevier | |
| 650 | 7 | |a Source water quality |2 Elsevier | |
| 650 | 7 | |a Water quality parameters |2 Elsevier | |
| 650 | 7 | |a Data reduction |2 Elsevier | |
| 650 | 7 | |a Principal component analysis |2 Elsevier | |
| 700 | 1 | |a Husain, Tahir |4 oth | |
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10.1016/j.jenvman.2020.111202 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001534.pica (DE-627)ELV051503913 (ELSEVIER)S0301-4797(20)31127-0 DE-627 ger DE-627 rakwb eng 300 VZ 70.00 bkl 71.00 bkl Chowdhury, Shakhawat verfasserin aut Reducing the dimension of water quality parameters in source water: An assessment through multivariate analysis on the data from 441 supply systems 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. Factor analysis Elsevier Source water quality Elsevier Water quality parameters Elsevier Data reduction Elsevier Principal component analysis Elsevier Husain, Tahir oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:274 year:2020 day:15 month:11 pages:0 https://doi.org/10.1016/j.jenvman.2020.111202 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 274 2020 15 1115 0 |
| spelling |
10.1016/j.jenvman.2020.111202 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001534.pica (DE-627)ELV051503913 (ELSEVIER)S0301-4797(20)31127-0 DE-627 ger DE-627 rakwb eng 300 VZ 70.00 bkl 71.00 bkl Chowdhury, Shakhawat verfasserin aut Reducing the dimension of water quality parameters in source water: An assessment through multivariate analysis on the data from 441 supply systems 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. Factor analysis Elsevier Source water quality Elsevier Water quality parameters Elsevier Data reduction Elsevier Principal component analysis Elsevier Husain, Tahir oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:274 year:2020 day:15 month:11 pages:0 https://doi.org/10.1016/j.jenvman.2020.111202 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 274 2020 15 1115 0 |
| allfields_unstemmed |
10.1016/j.jenvman.2020.111202 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001534.pica (DE-627)ELV051503913 (ELSEVIER)S0301-4797(20)31127-0 DE-627 ger DE-627 rakwb eng 300 VZ 70.00 bkl 71.00 bkl Chowdhury, Shakhawat verfasserin aut Reducing the dimension of water quality parameters in source water: An assessment through multivariate analysis on the data from 441 supply systems 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. Factor analysis Elsevier Source water quality Elsevier Water quality parameters Elsevier Data reduction Elsevier Principal component analysis Elsevier Husain, Tahir oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:274 year:2020 day:15 month:11 pages:0 https://doi.org/10.1016/j.jenvman.2020.111202 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 274 2020 15 1115 0 |
| allfieldsGer |
10.1016/j.jenvman.2020.111202 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001534.pica (DE-627)ELV051503913 (ELSEVIER)S0301-4797(20)31127-0 DE-627 ger DE-627 rakwb eng 300 VZ 70.00 bkl 71.00 bkl Chowdhury, Shakhawat verfasserin aut Reducing the dimension of water quality parameters in source water: An assessment through multivariate analysis on the data from 441 supply systems 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. Factor analysis Elsevier Source water quality Elsevier Water quality parameters Elsevier Data reduction Elsevier Principal component analysis Elsevier Husain, Tahir oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:274 year:2020 day:15 month:11 pages:0 https://doi.org/10.1016/j.jenvman.2020.111202 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 274 2020 15 1115 0 |
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10.1016/j.jenvman.2020.111202 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001534.pica (DE-627)ELV051503913 (ELSEVIER)S0301-4797(20)31127-0 DE-627 ger DE-627 rakwb eng 300 VZ 70.00 bkl 71.00 bkl Chowdhury, Shakhawat verfasserin aut Reducing the dimension of water quality parameters in source water: An assessment through multivariate analysis on the data from 441 supply systems 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. Factor analysis Elsevier Source water quality Elsevier Water quality parameters Elsevier Data reduction Elsevier Principal component analysis Elsevier Husain, Tahir oth Enthalten in Elsevier Ren, Chunhui ELSEVIER Cohort, signaling, and early-career dynamics: The hidden significance of class in black-white earnings inequality 2022 Amsterdam [u.a.] (DE-627)ELV008002754 volume:274 year:2020 day:15 month:11 pages:0 https://doi.org/10.1016/j.jenvman.2020.111202 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 70.00 Sozialwissenschaften allgemein: Allgemeines VZ 71.00 Soziologie: Allgemeines VZ AR 274 2020 15 1115 0 |
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Reducing the dimension of water quality parameters in source water: An assessment through multivariate analysis on the data from 441 supply systems |
| abstract |
In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. |
| abstractGer |
In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. |
| abstract_unstemmed |
In this research, multivariate statistical analysis was performed on twenty water quality parameters (WQP) collected on tri-monthly basis (four times/year) from 441 drinking water sources in Newfoundland and Labrador (NL), Canada for 18 years (1999–2016). The WQP included alkalinity (Alk), color (Col), conductivity (Cond), hardness (Hard), pH, total dissolved solids (TDS), turbidity (Turb), bromide (Br), calcium (Ca), chloride (Cl), fluoride (F), potassium (K), sodium (Na), sulfate (SO4), dissolved organic carbon (DOC), ammonia (NH3), nitrate (NO3), Kjeldahl nitrogen (N), total phosphorus (P) and magnesium (Mg). The assessment was conducted on surface water (SWS) and groundwater (GWS) sources separately. In SWS and GWS, number of samples analyzed for each WQP were in the ranges of 3434–6057 and 1915–1919 respectively. Averages of DOC and pH showed increasing trends (SWS: DOC = 0.0722 mg/L/year; pH = 0.0375 units/year; GWS: DOC = 0.0491 mg/L/year; pH = 0.0441 units/year) while the other WQP showed variable characteristics, which could increase treatment cost and deteriorate tap water quality. Strong correlations were observed for Ca-Hard (r = 0.97–0.98), TDS-Cond (r = 0.91–0.99) and Na–Cl (r = 0.87–0.96). In SWS, Alk had stronger correlations with Cond, Hard, pH, TDS, Ca and Mg (r = 0.62–0.94) than GWS (r = 0.56–0.63). Principal Component Analysis revealed separate clusters for DOC-Col, Na–Cl, TDS-Cond, Ca-Alk and Mg-Hard, indicating that these WQP moved together. In SWS and GWS, six principal components were significant (eigenvalue ≥ 1.0), and explained 74.8% and 72.9% of overall variances respectively. In Factor Analysis, six varifactors explained 73.4% and 70.5% of total variances in SWS and GWS respectively. For SWS and GWS, eleven and ten WQP, respectively explained these variances, indicating 45% and 50% data reduction respectively. The findings can assist in controlling water quality through monitoring reduced number of WQP, which is likely to minimize the monitoring cost. |
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Reducing the dimension of water quality parameters in source water: An assessment through multivariate analysis on the data from 441 supply systems |
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https://doi.org/10.1016/j.jenvman.2020.111202 |
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Husain, Tahir |
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10.1016/j.jenvman.2020.111202 |
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