Performance evaluation of a hybrid-passive landfill leachate treatment system using multivariate statistical techniques

Journal Article · Thu Jan 15 00:00:00 EST 2015 · Waste Management

DOI:https://doi.org/10.1016/J.WASMAN.2014.10.011· OSTI ID:22443607

Wallace, Jack ^[1]; Champagne, Pascale ^[1]; Monnier, Anne-Charlotte ^[2]

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1. Department of Civil Engineering, Queen’s University, Ellis Hall, 58 University Avenue, Kingston, Ontario K7L 3N6 (Canada)
2. National Institute for Applied Sciences – Lyon, 20 Avenue Albert Einstein, 69621 Villeurbanne Cedex (France)

Highlights: • Performance of a hybrid passive landfill leachate treatment system was evaluated. • 33 Water chemistry parameters were sampled for 21 months and statistically analyzed. • Parameters were strongly linked and explained most (>40%) of the variation in data. • Alkalinity, ammonia, COD, heavy metals, and iron were criteria for performance. • Eight other parameters were key in modeling system dynamics and criteria. - Abstract: A pilot-scale hybrid-passive treatment system operated at the Merrick Landfill in North Bay, Ontario, Canada, treats municipal landfill leachate and provides for subsequent natural attenuation. Collected leachate is directed to a hybrid-passive treatment system, followed by controlled release to a natural attenuation zone before entering the nearby Little Sturgeon River. The study presents a comprehensive evaluation of the performance of the system using multivariate statistical techniques to determine the interactions between parameters, major pollutants in the leachate, and the biological and chemical processes occurring in the system. Five parameters (ammonia, alkalinity, chemical oxygen demand (COD), “heavy” metals of interest, with atomic weights above calcium, and iron) were set as criteria for the evaluation of system performance based on their toxicity to aquatic ecosystems and importance in treatment with respect to discharge regulations. System data for a full range of water quality parameters over a 21-month period were analyzed using principal components analysis (PCA), as well as principal components (PC) and partial least squares (PLS) regressions. PCA indicated a high degree of association for most parameters with the first PC, which explained a high percentage (>40%) of the variation in the data, suggesting strong statistical relationships among most of the parameters in the system. Regression analyses identified 8 parameters (set as independent variables) that were most frequently retained for modeling the five criteria parameters (set as dependent variables), on a statistically significant level: conductivity, dissolved oxygen (DO), nitrite (NO{sub 2}{sup −}), organic nitrogen (N), oxidation reduction potential (ORP), pH, sulfate and total volatile solids (TVS). The criteria parameters and the significant explanatory parameters were most important in modeling the dynamics of the passive treatment system during the study period. Such techniques and procedures were found to be highly valuable and could be applied to other sites to determine parameters of interest in similar naturalized engineered systems.

• OSTI ID: 22443607
• Journal Information: Waste Management, Vol. 35; Other Information: Copyright (c) 2014 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.; Country of input: International Atomic Energy Agency (IAEA); ISSN 0956-053X
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
AMMONIA
AQUATIC ECOSYSTEMS
CALCIUM
CHEMICAL OXYGEN DEMAND
DISSOLVED GASES
HEAVY METALS
IRON
LEACHATES
LEAST SQUARE FIT
MASS NUMBER
MULTIVARIATE ANALYSIS
NATURAL ATTENUATION
NITRITES
NITROGEN
ONTARIO
OXIDATION
PH VALUE
POLLUTANTS
REDUCTION
REGRESSION ANALYSIS
SANITARY LANDFILLS
SULFATES
TOXICITY
VOLATILE MATTER
WASTE PROCESSING
WATER CHEMISTRY
WATER QUALITY