Modelling Landfill Gas Generation And A Review Of Models For Leachate Production

Author : Richa Vijay Karanjekar
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (842 download)

DOWNLOAD NOW!

Download or read book An Improved Model for Predicting Methane Emissions from Landfills Based on Rainfall, Ambient Temperature and Waste Composition written by Richa Vijay Karanjekar and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurately estimating the emissions of methane (CH4) and carbon dioxide (CO2) in a landfill is important for quantifying its greenhouse gas (GHG) emissions and power generation potential. Previous studies have shown that variation in waste composition, rainfall and ambient temperature of a landfill significantly influences its methane generation potential. Current methane generation models, namely U.S. Environmental Protection Agency's (EPA) Landfill Gas Generation Model (LandGEM) and Intergovernmental Panel on Climate Change's (IPCC) methane generation model, are overly simplified and do not account for the variations in waste composition, rainfall and ambient temperature. The goal of this research was to improve our ability to estimate methane generation rates from landfills worldwide, which can be used by any country/city, with any anticipated waste composition, or climatic conditions. The proposed Capturing Landfill Emissions for Energy Needs (CLEEN) model allows methane generation to be estimated for any landfill, with basic information about waste composition, annual rainfall, and ambient temperature. A statistical experimental design was used for determining the first order methane generation constants (k values) for laboratory scale landfills, with varying waste composition, temperature, and rainfall conditions. The experimental design was developed using incomplete block design, where the waste composition served as a blocking variable and combinations of temperature and rainfall were the primary predictor variables. 27 lab scale landfills reactors were simulated with varying waste compositions (ranging from 0 to 100 %); average rainfall rates of 2, 8, and 15 mm/day; and temperatures of 20, 30, and 37C. These rainfall rates encompass average precipitation rates for most locations worldwide, with the exception of deserts. Refuse components considered were the major biodegradable wastes, food, paper, yard/wood, and textile, as well as inert inorganic waste. Methane generationfrom laboratory scale simulated landfills was monitored for a period of 180 to 400 days until the methane generation rates dropped to a low constant value. Based on the simulated landfill data, a comprehensive regression equation was developed for predicting the methane generation rate constant, (k) using waste composition, rainfall and temperature as predictor variables. Finally, the regression equation was incorporated into the CLEEN model and scale-up factors were evaluated for studying the applicability of the model for field scale studies. It was observed from the simulated landfill data that the methane generation curves from reactors with high amounts of textile waste and food waste showed multiple peaks and did not follow a typical first-order decay curve. Methane generation curves from reactors with yard waste and paper waste followed a classic first order decay curve. Overall, the mixture of waste components helped in supplying nutrients hence the combined waste followed a first order decay curve. Multiple Linear Regression (MLR) analysis was used on the lab scale data to estimate the effect of waste composition, rainfall and ambient temperature on the first-order decay constant (k). The best model selected using the backward elimination method, best subsets method and stepwise regression method had an adjusted R2 of 0.7538. From the MLR model it was observed that increasing the ambient temperature increased the rate of degradation. Likewise, increasing the amount of textile waste and yard waste increased the rate of degradation. It was observed that the rate of degradation was affected by the combined effect of food waste and rainfall. A change in the amount of paper waste affected the overall rate of degradation; however, that effect was not significant at 90% confidence level. The comprehensive regression equation was able to predict methane generation rates for rainfall from 2 mm/day to 12 mm/day, and ambient temperature between 20oC to 37oC, and was limited to 0 to 60% of food waste, 0 to 60% of textile waste, and 0-100% for paper and yard waste. The Capturing Landfill Emissions for Energy Needs (CLEEN) model was developed by incorporating the comprehensive regression equation into first-order decay based model for estimating methane generation rates from landfills. Methane recovery and methane oxidation factors were also incorporated in the CLEEN model, to estimate the methane emissions from the landfill surfaces. A scale-up factor was computed to adapt the lab based regression equation to actual landfill scale methane generation using the City of Denton's landfill emissions data, which was found to be 0.012. This study will possibly allow better estimation of the methane generation rate constant k based on waste composition, rainfall and ambient temperature. CLEEN model will also allow k values to be adjusted as recycling and composting increase, without developing new country-specific ks. Overall, this study will develop a model for better predictions of methane generation rates from any landfill worldwide.