Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 4
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

The purpose of the work was to determine the relationship between the of the water quality parameters in an artificial reservoir used as cooling ponds. Multivariate methods, cluster analysis and factor analysis were applied to analyze eighteen physico-chemical parameters such as air and water temperature, dissolved oxygen concentration, visibility of the Secchi disk, concentrations of total nitrogen, ammonium, nitrate, nitrite, total phosphorus, phosphate, concentrations of calcium, magnesium, chlorides, sulfates and total dissolved salts, pH, chemical oxygen demand and electric conductivity from 2002-2017 to investigated cooling water discharge. Hierarchical cluster analysis (CA) allowed identified five different clusters that reflect the different water quality characteristics of the water system. Similar results were obtained in exploratory factor analysis, five factors were obtained with 65.96% total variance. However, confirmatory factor analysis showed that four latent variables: salinity, temperature, eutrophication, and ammonia provide better fit to the data than a five-factor structure. Correlations between latent variables temperature, eutrophication and ammonia show a significant effect of temperature on the transformation of nitrogen and phosphorus compounds.
Go to article

Bibliography

  1. Arsonists, G.B., Stow, C.A., Steinberg, L.J., Kenney M.A., Lathro, R.C., McBride, S.J. & Reckhow, K.H. (2006). Exploring ecological patterns with structural equation modeling and Bayesian analysis. Ecological Modelling, 192, pp. 385–409. DOI:10.1016/j.ecolmodel.2005.07.028
  2. Baran, A., Tarnowski M., Urbański K., Klimkowicz-Pawlas A. & Spałek I. (2017). Concentration, sources and risk assessment of PAHs in bottom sediments, Environmental Science and Pollution Research, 24, pp. 23180–23195. DOI 10.1007/s11356-017-9944-y
  3. Bloemkolk, J.W., van der Schaaf, R.J. (1996). Design alternatives for the use of cooling water in the process industry: minimization of the environmental impact from cooling systems. Journal of Cleaner Production 4(1), pp. 21-27.
  4. Boyacioglu, H. & Boyacioglu, H. (2018). Application of environmetric methods to investigate control factors on water quality on water quality. Archives of Environmental Protection. 43 (3) pp. 17–23. DOI: 10.1515/aep-2017-0026
  5. Boyacioglu, H. & Boyacioglu, H. (2018) Environmental Determinants of Surface Water Quality Based on Environmetric Methods. Environment and Ecology Research. 6(2), pp. 120-124. DOI: 10.13189/eer.2018.060204
  6. Choiński, A. & Ptak, M. (2013). Variability of thermals and water levels in Konin lakes as a result of the activity of the «Konin» and «Pątnów» power plants. Науковий вісник Східноєвропейського національного університету імені Лесі Українки РОЗДІЛ І. Фізична і конструктивна географія. 16 (265), pp. 31-40 (in Polish). http://www.esnuir.eenu.edu.ua/bitstream/123456789/11181/1/5.pdf
  7. Conclusions from the forecast analysis for the energy production sector – annex no. 2 to Poland's energy policy until 2040 (PEP 2040 – ver 2.1), Ministry of Energy Warsaw 2019 (in Polish). https://www.gov.pl/attachment/cff9e33d-426a-4673-a92b-eb4fb0bf4a04
  8. Doria, M.F, Pidgeon, N. & Hunter, P.(2005). Pe.2005.0245rception of tap water risks and quality: a structural equation model approach. Water Science & Technology, 52 (8) pp. 143–149. DOI:10.2166/wst.2005.0245
  9. Dragan, D. & Topolŝek, D. (2014). Introduction to Structural Equation Modeling: Review, Methodology and Practical Applications. The International Conference on Logistics & Sustainable Transport, 19–21 June 2014 Celje, Slovenia
  10. Dyer, K., Holmes, P., Roast S.,. Taylor, C.J.L. & Wicher, A. (2017). Challenges in the management and regulation of large cooling water discharges. Estuarine, Coastal and Shelf Science, 190, pp. 23-30. DOI: 10.1016/j.ecss.2017.03.027
  11. European Environment Agency, (2018). Water abstraction by sector, EU, European Environment Agency https://www.eea.europa.eu/data-and-maps/daviz/water-abstraction-by-sector-eu-2/download.table
  12. Fan, Y., Chen, J., Shirkey, G., John, R., Susie, R. Wu., S.R., Park, H. & Shao, C. (2016). Applications of structural equation modeling (SEM) in ecological studies: an updated review. Ecological Processes 5, 19. DOI 10.1186/s13717-016-0063-3
  13. Fox J., Nie Z. & ,Byrnes, J. (2020). Package ‘sem’. https://cran.r-project.org/web/packages/sem/sem.pdf
  14. Gao, C., Yan, J., Yang, S. & Tan G. (2011). Applying Factor Analysis to Water Quality Assessment: A Study Case of Wenyu River [In] S. Li (Ed.): Nonlinear Mathematics for Uncertainty and its Applications, 2011, Springer-Verlag Berlin Heidelberg , pp. 541–547. ISBN 978-3-642-22832-2. DOI 10.1007/978-3-642-22833-9
  15. Helena, B., Pardo, R., Vega, M., Barrado, E., Fernandez, J.M.& Fernandez, L. (2000). Temporal evolution of groundwater analysis. Water Research 34 (3), pp. 807-16. DOI: 10.1016/S0043-1354(99)00225-0
  16. Hossain, M.G., Selim Reza, A.H.M. & Lutfun-Nessa, M. (2013). Factor and cluster analysis of water quality data of the groundwater wells of Kushtia, Bangladesh: Implication for arsenic enrichment and mobilization. Journal of the Geological Society of India, 81, pp. 377–384. DOI: 10.1007/s12594-013-0048-0
  17. Jabłońska-Czapla, M., Szopa, S., Zerzucha, P., Łyko, A. & Michalski, R. (2015). Chemometric and environmental assessment of arsenic, antimony, and chromium speciation form ocurrence in a water reservoir subjected to thermal anthropopressure. Environmental Science and Pollution Research 22, pp.15731–15744. DOI: 10.1007/s11356-015-4769-z
  18. Jabłońska, M., Kostecki, M., Szopa, S., Łyko, A. & Michalski, R. (2012). Speciation of Inorganic Arsenic and Chromium Forms in Selected Water Reservoirs of Upper Silesia. Ochrona Środowiska, 34(3), pp. 25–32. (in Polish)
  19. Jancewicz, A., Dmitruk, U., Sosnicki, L. & Tomczuk, U. (2012). Influence of Land Development in the Drainage Area on Bottom Sediment Quality in Some Dam Reservoirs. Ochrona Środowiska 34(4), pp. 29–34.(In Polish)
  20. Johnson, R.A. & Wichern, D.W. (2007). Applied Multivariate Statistical Analysis, Pearson Education, Inc. 6th ed. ISBN 0-13-187715-1
  21. Johst M. & Rothsteinn B., (2014). Reduction of cooling water consumption due to photovoltaic and wind electricity feed-in. Renewable and Sustainable Energy Reviews 35, 311–317 DOI: 10.1016/j.rser.2014.04.029
  22. Jolliffe I.T. (2002). Principal Component Analysis, Second Edition Springer Verlag. ISBN 0-387-05442-2
  23. Kannel P.R., Lee S., Kanel S.R. & Khan S.P. (2007). Chemometric application in classification and assessment of monitoring locations of an urban river system, Analytica Chimica Acta 582, pp. 390–399. DOI: 10.1016/j.aca.2006.09.006
  24. Kim, S.E., Seo, I.W. & Choi S.Y. (2017). Assessment of water quality variation of a monitoring network using exploratory factor analysis and empirical orthogonal function. Environmental Modelling & Software 94, pp. 21-35. DOI: 10.1016/j.envsoft.2017.03.035
  25. Koczorowska, R. (2001). The impact of a fuel-energy complex on selected ]elements of water balance [In] German, K. & Balon, J. (Eds) Przemiany środowiska przyrodniczego Polski a jego funkcjonowanie, IGiGP UJ, Kraków, ss. 814., pp. 158-163. (in Polish) https://denali.geo.uj.edu.pl/publikacje,000025?&page=start&menu=3&nr=000025_018&brf=summary#000025_018
  26. Korkmaz, S., Goksuluk, D. & Zararsiz, G. (2020). Package ‘bestNormalize’ https://cran.r-project.org/web/packages/MVN/MVN.pdf
  27. Kostecki, M. (2005) Specificity of the thermal conditions of the "Rybnik" water reservoir as an effect of heated waterseated discharge, Problemy Ekologii 9 (3) 151-161 (in Polish)
  28. Kostecki, M. & Kowalski, E. (2007). Spatial arrangement of heavy metals in the dam-reservoir sediments in the conditions of anthropomixion, Archives of Environmental Protection, 3, pp. 67–81.
  29. Kostecki, M. (2007). Bioaccumulation of heavy metals in selected elements of trophic chain of anthropogenic reservoirs in the aspect of environmental protection and economical function. Institute of Environmental Engineering of the Polish Academy of Sciences, Works & Studies, 71, pp. 87. (in Polish)
  30. Kowalska-Musiał M. & Ziółkowska, A. (2013). Factor analysis in investigating relation structure in relation marketing. Zeszyt Naukowy Wyższej Szkoły Zarządzania i Bankowości w Krakowie. (in Polish)
  31. Kowalski, E., Mazierski, J. (2008). Effects of cooling water discharges from a power plant on reservoir water quality. Oceanological and Hydrobiological Studies International Journal of Oceanography and Hydrobiology, 37, pp. 107- 118. DOI: 10.2478/v10009-008-0001-5
  32. Kumar, J.I.N. (2009). Assessment of spatial and temporal fluctuations in water quality of a tropical permanent estuarine system - Tapi, West Coast India. Applied Ecology and Environmental Research 7(3), pp. 267-276. DOI: 10.15666/aeer/0703_267276
  33. Liu, C.W., Lin, K.H. & Kuo, Y.M., (2003). Application of factor analysis in the assessment of groundwater quality in a blackfoot disease area in Taiwan. The Science of the Total Environment 313, pp. 77–89. DOI: 10.1016/S0048-9697(02)00683-6
  34. Loska,K., Korus, I. & Wiechuła, D. (2009). Arsenic speciation in Rybnik reservoir. Architecture Civil Engineering Environmen, 2(3) pp. 109-116.
  35. Loska, K. , Wiechuła, D. , Pęciak, G. (2003a) Contamination of the arsenic in the bottom sediment of the Rybnik Reservoir. Problemy Ekologii 7 (1), pp. 29-32 (in Polish))
  36. Loska, K., Korus, I., Pelczar J., Wiechuła D. (2005) Analysis of spatial distribution of arsenic in bottom sediments of the Rybnik Reservoir. Gospodarka Wodna 65(3), pp. 104-107. (in Polish)
  37. Loska,.K., Wiechuła, D. (2003b). Application of principal component analysis for the
  38. estimation of source of heavy metal contamination in surface sediments from the Rybnik Reservoir. Chemosphere 51, pp. 723–733. DOI: 10.1016/S0045-6535(03)00187-5
  39. Loska K., Wiechuła D., Cebula J. (2000) Changes in the Forms of Metal Occurrence in Bottom Sediment under Conditions of Artificial Hypolimnetic Aeration of Rybnik Reservoir, Southern Poland. Polish Journal of Environmental Studies 9(6), pp. 523-530.
  40. Loska K., Cebula J., Pelczar J., Wiechuła D. & Kwapuliński J. (1997). Use of enrichment, and contamination factors together with geoaccumulation indexes to evaluate the content of Cd, Cu, and Ni in the Rybnik water reservoir in Poland. Water, Air, & Soil Pollution, 93, pp. 347–365. DOI: 10.1023/A:1022121615949
  41. Loska, K., Wiechula D., Pelczar J. & Kwapulinski J. (1994) Occurrence of heavy metals in bottom sediments of a heated reservoir [the Rybnik Reservoir, southern Poland]. Acta Hydrobiologica. 36(3), pp. 281-295
  42. Loska K., Wiechuła D., Cebula J. & Kwapulinski J (2001) Occurrence of sodium, potassium and calcium in the Rybnik Reservoir. Ochrona Powietrza i Problemy Odpadów, vol. 35 (6), pp. 229–234. (in Polish)
  43. Marsh, H. W., Muthén, B., Asparouhov, T., Lüdtke, O., Robitzsch, A., Morin, A. J. S., & Trautwein, U. (2009). Exploratory structural equation modeling, integrating CFA and EFA: Application to students' evaluations of university teaching. Structural Equation Modeling, 16(3), 439-476. DOI:10.1080/10705510903008220
  44. Masduqi, A., Endah, N., Soedjono, E. S., Hadi, W. (2010) Structural equation modeling for assessing of the sustainability of rural water supply systems. Water Science & Technology: Water Supply—WSTWS | 10.5 pp. 815 – 823. DOI: 10.2166/ws.2010.339
  45. Mustapha, A. & Aris, A.Z. (2012). Multivariate Statistical Analysis and Environmental Modeling of Heavy Metals Pollution by Industries. Polish Journal of Environmental Studies 5, pp.1359-1367.
  46. OpenStreetMap Foundation (OSMF) https://www.openstreetmap.org/copyright/en
  47. Petersen, W., Bertino, L., Callies, U. & Zorita E. (2001). Process identification by principal component analysis of river water-quality data, Ecological Modelling 138, pp. 193 – 213.
  48. Peterson R.A. (2020). Package ‘bestNormalize’
  49. https://cran.r-project.org/web/packages/bestNormalize/bestNormalize.pdf
  50. R Core Team, (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
  51. Rajagopal, S., Venugopalan, V.P. & Jenner H.A., (2012). Cooling Water Systems: Efficiency vis-à-vis Environment. [In] Rajagopal, S., Jenner, H.A. & Venugopalan V.P. (Eds) Operational and Environmental Consequences of Large Industrial Cooling Water Systems, pp. 455-461
  52. Reference Document on the application of Best Available Techniques to Industrial Cooling Systems. European Commission, December 2001. http://eippcb.jrc.ec.europa.eu/reference/BREF/cvs_bref_1201.pdf
  53. Revelle W. (2020) Package ‘psych’ https://cran.r-project.org/web/packages/psych/psych.pdf
  54. Rodrigues, P.M.S.M, Rodrigues, R.M.M., Costa, B.H.F., Tavares Martins, A.A.A.L., Estaves da Silva, J.C.G. (2010) Multivariate analysis of the water quality variation in the Serra da Estrela (Portugal) Natural Park as a consequence of road deicing with salt, Chemometrics and Intelligent Laboratory Systems 102, pp. 130–135. DOI: 10.1016/j.chemolab.2010.04.014
  55. Ryberg, K. R. (2017) Structural Equation Model of Total Phosphorus Loads in the Red River of the North Basin, USA and Canada. Journal of Environmental Quality. 46 pp. 1072-1080. DOI: 10.2134/jeq2017.04.0131
  56. Rzętała, M. (2008). Operation of water reservoirs and the course of limnic processes in diverse conditions anthropopression on the example of the Upper Silesian region. Katowice: University of Silesia Publishing House.(in Polish)
  57. Simeonov, V. Stratis, J.A. Samara, C., Zachariadis,G., Voutsa, D., Anthemidis, A., Sofoniou, M., Th. Kouimtzis, Th. (2003) Assessment of the surface water quality in Northern Greece, Water Research 37, pp. 4119–4124. DOI: 10.1016/S0043-1354(03)00398-1
  58. Singh, K.P., Malik, A., Mohan, D., Sinha, S., (2004) Multivariate statistical techniques for the evaluation of spatial and temporal variations in water quality of Gomti River (India) - a case study. Water Research 38, pp. 3980-3992. DOI: 10.1016/j.watres.2004.06.011
  59. Standard Methods for the Examination of Water and Wastewater (2017) 23rd Edition American Public Health Association, American Water Works Association, and Water Environment Federation. ISBN: 978-0-87553-287-5
  60. Statistical Yearbook of Republic of Poland, Warsaw, 2018. (in Polish)
  61. Vega, M., Pardo, R., Barrado, E. & Debán L. (1998). Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis, Water Research 32 pp. 3581-3592. DOI: 10.1016/S0043-1354(98)00138-9
  62. Viswanath, N.C., Kumar, P.G.D. & Ammad K.K. (2015). Statistical Analysis of Quality of Water in Various Water Shed for Kozhikode City, Kerala, India, Aquatic Procedia 4 pp. 1078 – 1085. DOI: 10.1016/j.aqpro.2015.02.136
  63. Wang, S.-W., Liu, C.-W. & Jang, C.-S. (2003). Factors responsible for high arsenic concentrations in two groundwater catchments in Taiwan. Applied Geochemistry, 22, pp. 460–47. DOI: 10.1016/j.apgeochem.2006.11.011
  64. Wiechuła, D., Loska, K. & Korus, I. (2005). Lead partitioning in the bottom sediment of Rybnik reservoir (southern Poland). Water, Air, & Soil Pollution 164, pp. 315–327.
  65. Widziewicz, K. & Loska, K. (2012) Multivariate statistical analyses on arsenic occurrence in Rybnik reservoir. Archives of Environmental Protection 38(2) pp.12-23. DOI: 10.2478/v10265-012-0014-8
  66. Wu, E.M.-Y., Tsai, C.C., Cheng, J.F., Kuo, S.L., Lu, W.T. (2014) The Application of Water Quality Monitoring Data in a Reservoir Watershed Using AMOS Confirmatory Factor Analyses, Environmental Modeling & Assessment 19, pp. 325–333. DOI 10.1007/s10666-014-9407-5
  67. Zemełka, G. & Szalinska, E. (2017). Heavy Metal Contamination of Sediments from Recreational Reservoirs of Urban Areas and its Environmental Risk Assessment, Engineering and Protection of Environment, 20(1), pp.131-145. DOI: 10.17512/ios.2017.1.10
Go to article

Authors and Affiliations

Jerzy Mazierski
1
Maciej Kostecki
1
ORCID: ORCID

  1. Institute of Environmental Engineering, Polish Academy of Sciences, Poland
Download PDF Download RIS Download Bibtex

Abstract

The results of investigation on the amount and chemical composition of biogas emitted from bottom sediments of polluted Dzierżno Duże dam reservoir have been presented. The bottom sediments could be a resource of considerable quantity of biogas, e.g. methane. The dilution of methane in water is similar to that of oxygen. The presence of methane dissolved in the water deteriorates environmental conditions. The quantity of biogas depending on temperature ranged from 2 to 12 dm3/m2*d. The biggest singular grow exist in the water temperature 10-15°C. Chemical composition for biogas is dependent on the temperature. Along with the water temperature growth from 7 to 24°C, participation of methane in the biogas increased from 73% to 85%, and the participation of nitrogen from 3.9% to 22.47%. The participation of carbon dioxide decreased from 22% to 4.5%. The heterogeneous process of biogas emission arc running in the kinetic and diffusion area is dependent on temperature. In the low temperature the progress of the process is controlled by the speed of biochemical reaction. The progress of the diffusion process grows in a high temperature, and in the range of 15-24° C the processes is controlled by diffusion of substrates and products of reaction.
Go to article

Authors and Affiliations

Maciej Kostecki
Jerzy Mazierski
Eligiusz Kowalski
Download PDF Download RIS Download Bibtex

Abstract

Improving the effects of hydrolysis on waste activated sludge (WAS) prior to anaerobic digestion is of primary importance. Several technologies have been developed and partially implemented in practice. In this paper, perhaps the simplest of these methods, alkaline solubilization, has been investigated and the results of hydrolysis are presented. An increase to only pH 8 can distinctively increase the soluble chemical oxygen demand (SCOD), and produce an anaerobic condition effect favorable to volatile fatty acids (VFA) production. Further increases of pH, up to pH 10, leads to further improvements in hydrolysis effects. It is suggested that an increase to pH 9 is sufficient and feasible for technical operations, given the use of moderate anti-corrosive construction material. This recommendation is also made having taken in consideration the option of using hydrodynamic disintegration after the initial WAS hydrolysis process. This paper presents the effects of following alkaline solubilization with hydrodynamic disintegration on SCOD

Go to article

Authors and Affiliations

Jan Suschka
Eligiusz Kowalski
Jerzy Mazierski
Klaudiusz Grübel

This page uses 'cookies'. Learn more