Preliminary regression models for estimating first-order rate constants for removal of BOD and COD from landfill leachate

The increasing production of municipal solid waste (MSW) has direct consequences on leachate generation and its contamination of the environment. Leachate contains organic and inorganic pollutants that have been extensively studied in the last four decades. Most BOD and COD leachate models in the past have been based on data from single or regionally specific landfills. In this study, preliminary models for first-order rate constants for BOD and COD removal from leachate were developed. The models represent a first step to estimate BOD and COD concentrations over time for any conventional municipal solid waste landfill, given information about the landfill’s precipitation rate, temperature, and percents of different types of waste. Data was collected from 27 lab-scale anaerobic reactors, with temperatures of, 70, 85, and 100 °F; average rainfall rates of, 2, 6, and 12 mm/day; and waste compositions, food, paper, yard, textile, and inorganics, varying from 0 to 100%, according to a statistical experimental design. Leachate was collected regularly and analyzed for BOD and COD. Multiple linear regression (MLR) equations were developed for estimating first-order rate constants for BOD and COD. Scale-up factors were calculated to convert lab-scale reaction rates to field-scale rates. Future work will include development of additional scale-up factors and model validation. The best models developed in this study showed that increasing rainfall and temperature leads to higher BOD and COD concentrations. The kCOD model indicated that only paper and textile waste were significant at a 90% confidence level in estimating COD concentration, while paper, yard, and food waste were significant in the kBOD model.