MODELLING REMEDIATION OF POLYCYCLIC AROMATIC HYDROCARBON (PAH) CONTAMINATED SOIL THROUGH COMPOSTING WITH COP-COMPOST MODEL 

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The fate of microorganisms during the composting process

Actinomycetes are a group of filamentous organisms that are often found in blue-grey powder-like colonies. Both actinomycetes and fungi are relatively slow growing organisms that are less tolerant of low oxygen concentrations and high temperatures compared to the bacteria. The microbial populations and the temperature in the compost often follow a specific pattern dictated by the degradation of compounds in the organic matter. The composting process can be divided into four phases.

Evolution of organic matter (OM) during composting

The theoretical evolution of the temperature within the compost during composting makes it possible to define four successive phases, related to the activity of the various microbial populations.

The mesophilic phase

Easily biodegradable OM involves a strong microbial activity generating a strong production of heat and a fast rise of the temperature in the middle of the compost. The present micro-organisms are primarily bacteria, no-actinomycetes, as well as fungi (Vergé-Leviel, 2001).

The thermophilic phase

Very quickly the temperature reaches values 60°C even 75°C. Only the heat-resisting micro-organisms can survive these high temperatures. This phase is characterized by the presence of actinomycetes and thermophilous nonfilamentous bacteria. The mushrooms disappear beyond 60°C or survive in the form of spores. During this phase, a big part of OM is lost under the form of carbon dioxide CO2 and a draining of the compost related to the evaporation of water occurs. The phase of fermentation corresponds primarily to the degradation of the easily biodegradable molecules: glucides, proteins, lipids (Vergé-Leviel, 2001).

The cooling phase

The reduction in the quantity of easily degradable OM causes a deceleration of the microbial activity involving a cooling of compost. The mesophilic micro-organisms colonize the composting system again.

The maturation phase

During this last phase, the processes of humification dominate, as well as the slow degradation of the resistant compounds. This phase is characterized by the colonization of the compost by mushrooms when lignin and the cellulose become the dominant substrates. Among colonizing fungi, the filamentous fungi of the white, brown and soft rots are known for their role in the degradation of lignin and another xenobiotic related molecules (PAHs, chlorophenols…) (Vergé-Leviel, 2001). During this phase, the diversity of the metabolic micro-organisms augments. This phase lasts until the use of the composts.

Bioremediation of contaminated soil by composting

Soil pollution by petroleum products which contain high concentration of PAHs is a widespread problem. Polycyclic aromatic hydrocarbons (PAHs) are hydrocarbons that contain at least two fused benzene rings in linear, angular, or cluster arrangements. PAHs in the molecular weight range between naphthalene (128.16) and coronene (300.36) are of environmental concern (Ashok and Saxena, 1995). Many PAHs are stable and persistent in the environment and toxic. PAHs are common by products formed either by thermal alteration of buried organic matter (petrogenic) or by incomplete combustion of organic matter (pyrogenic) (Suess, 1976; Sims and Overcash, 1983; Nikolaou et al., 1984).
PAHs also exhibit extraordinary structural diversity. The number of possible PAH isomer is large and it expands rapidly as the number of rings and alkylations increase. However, not all the possible PAHs exist because of the low conformational stability of larger ring numbers, especially for linearly fused PAHs (Harvey, 1997).
Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous contaminants found in most of the processes of incomplete combustion of wood and fossil fuels (Jones and Voogt, 1999). Major sources of petrogenic PAHs also include crude oil and its refined products, coal, and oil shale (Harvey, 1997; Page et al., 1999).
During pyrolysis and pyrosynthesis, cracking of complex organic molecules into smaller and unstable fragments (pyrolysis) results in the formation of free radicals with short average lifetimes. The highly reactive free radicals produce more stable and highly condensed aromatic ring systems through recombination reactions (pyrosynthesis) (Ballentine et al., 1996; Mastral and Callen, 2000).

Potential bioremediation of PAH-contaminated soils by composting

The Earlier studies showed that higher molecular weight PAHs remained in the soil after 16 weeks and 11 months of pilot-scale and full-scale land farming, respectively (Atagana, 2003; Atagana, 2004a). The past decade, bioremediation techniques have been developed and improved to clean up soils polluted with hazardous chemicals (Skladany and Metting, 1992; Alexander, 1994; Romantschuk et al., 2000). A promising approach to reduce PAH pollution is the utilization of the natural potential of microorganisms to utilize hydrocarbons since the bioremediation techniques are cheaper than the other alternatives (soil washing, solidification and stabilization, incineration, thermal treatment or advanced oxidation processes) used for cleaning up of contaminated sites (Clarinet, 2007).
Contaminated soil can be bioremediated by addition of nutrients (bio-stimulation), addition of microbial inocula (bioaugmentation), aeration and turning, or by a combination of these practices (Alexander, 1994). Also, the addition of organic matter to the hydrocarbon contaminated soil can be beneficial, as it is a source of co-substrates, nutrients and microorganisms, and ameliorates the structure and water-retention capacity of the soil (Alexander, 1994). When fresh organic substrates are incubated with a contaminated soil, a thermophilic phase is likely to occur and the process is called composting. Earlier composting experiments using hydrocarbon-contaminated soil co-composted with cow manure and mixed vegetable waste showed that more than 90% of the hydrocarbons including some of the recalcitrant components were removed (Atagana et al., 2003). Co-composting hydrocarbon-contaminated soil with poultry manure showed that PAHs could be removed from the soil by composting (Atagana, 2004b).
The composting process used to stabilise organic materials can be considered as a bioremediation process (Bollag & Bollag 1995). Numerous studies have shown that composting has an enormous potential for bioremediation through sustaining microbial populations of a wide range of microorganisms, which are able to degrade a variety of organic contaminants at the laboratory and/or field scales (Antizar-Ladislao et al., 2005; Moretto et al., 2005; Semples et al., 2001; Lau et al., 2003). Composting has been proven to degrade PAHs, in rates that exceed 80% in some cases and require treatment time shorter than land-farming (Amir et al., 2005).
Composting strategies for soils contaminated with organic pollutants in general has been recently reviewed by Semple et al. (2001). The number of studies on composting of petroleum- contaminated soil and petroleum-based oil wastes is increasing (e.g. Beaudin et al., 1996, 1999; Al-Daher et al., 1998; Kirchmann and Ewnetu, 1998; Milne et al., 1998; Jørgensen et al., 2000; Chaw and Stoklas, 2001; Namkoong et al., 2002). Elevated temperatures stimulate hydrocarbon degradation (Atlas, 1975), and enhance the contaminant availability by increased solubility and mass transfer (Pignatello and Xing, 1996).

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Calibration and evaluation of the model

The model requires inputs of the initial carbon quantity in each fraction of organic matter, the microbial biomass (X), the kinetic parameters for the organic fractions (Ki=1~5) and the microbial biomass X (µ max, Tmin, Topt, Tmax and mB) and the limiting factors (KS, YH2O, Y). Overall, the model consists of 13 parameters. The experimental temperatures of each composting experiment were used in the model (Fig.2.3 gave temperature for P1 and R1 composts). The initial quantity of microbial biomass was supposed to be small enough and similar for all simulations (with the value of 0.05 g C 100 g-1 initial TOC).
From the total of 12 mixtures (R1 to R6 and P1 to P6), eight were randomly selected (four feedstock mixtures from R1-R6 and four from P1-P6) to constitute the calibration dataset. These mixtures were used to estimate the parameters of the model. The calibration dataset consisted of mixtures R1, R3, R5, R6, P1, P2, P3 and P5. The four remaining mixtures, R2, R4, P4 and P6, constituted the validation dataset. They were not used for model calibration but were kept for validation.

Description of the COP_Compost model

The two modules (OC and OP) of the COP-Compost model can be used separately or coupled (Fig.3.1, Table 3.1). The model has been programmed in Matlab® language (The Mathwork, USA). All equations in the two modules are described in Appendix 1.

Organic C module

Briefly, OC is divided into five pools (Ci, i=1-5) with decreasing degradability. Following first order kinetics with specific hydrolysis constants, these organic pools were hydrolyzed into one organic pool, CS, defined as the substrate available for microbial growth. These five pools could be determined using the Van Soest fractionation method (AFNOR, 2005): OC soluble in neutral detergent (SOL) and the hemicellulose-like (HEM), the cellulose-like (CEL) and lignin-like (LIC) fractions. The SOL fraction was further divided into two pools with fast (SOL-F) and slow (SOL-S) degradability (Francou et al., 2008). The available substrate (CS) was defined as being the hot water soluble fraction of total OC (H2O). Microbial biomass growth and its assimilation of the available substrate were modeled using Monod kinetics, modulated by the temperature growth-limiting function proposed by Rosso et al. (1993). The microbial biomass gradually died off, and the dead cells were recycled into either the SOL-S pool (characterized by a slow hydrolysis rate) or the H2O pool of available substrate.

Table of contents :

CHAPTER 1 LITERATURE REVIEW
1.1 Presentation of composting
1.1.1 Temperature
1.1.2 Areation (ventilation)
1.1.3 Free Air Space (FAS)
1.1.4 Moisture content
1.1.5 C/N ratio
1.1.6 pH value
1.1.7 The fate of microorganisms during the composting process
1.2 Evolution of organic matter (OM) during composting
1.2.1 The mesophilic phase
1.2.2 The thermophilic phase
1.2.3 The cooling phase
1.2.4 The maturation phase
1.3 Bioremediation of contaminated soil by composting
1.3.1 Contaminated soil by PAHs
1.3.2. Potential bioremediation of PAH-contaminated soils by composting
1.3.3 Evolution of PAHs during composting
1.4 Modelling the dynamics of OM and OP during the composting
1.4.1 Summary of environmental conditions
1.4.2 Summary of OM models
1.4.3 Summary of OP models
1.5 Objectives of the thesis
1.6 References
PART I: MODELING ORGANIC CARBON AND ORGANIC POLLUTANT DYNAMICS DURING COMPOSTING OF ORGANIC WASTES
CHAPTER 2: MODELLING OF ORGANIC MATTER DYNAMIC DURING THE COMPOSTING PROCESS
2.1 Abstract
2.2 Introduction
2.3 Materials and Methods
2.3.1 The model
2.3.2 Data acquisition for the model calibration
2.3.3 Calibration and evaluation of the model
2.4 Results and Discussion
2.4.1 Estimation of model parameters
2.4.2 Evaluation of calibrated model
2.4.3 Sensitivity analysis
2.5 Conclusion
2.6 Acknowledgements
CHAPTER 3: A MODEL COUPLING ORGANIC CARBON AND ORGANIC POLLUTANT DYNAMICS DURING COMPOSTING
3.1 Abstract
3.2 Introduction
3.3 Description of the COP_Compost model
3.3.1 Organic C module
3.3.2 Organic pollutant module
3.3.3 Model coupling OC and OP modules
3.4 Data acquisition for model calibration and evaluation
3.4.1 Data acquisition for calibration and evaluation of the OC module
3.4.2 Data acquisition for OP module calibration
3.4.3 Data acquisition for the coupling between OC and OP modules
3.5 Model calibration and evaluation
3.5.1 Calibration and evaluation of the OC module
3.5.2 Calibration and evaluation of the OP module
3.6 Results and discussion
3.6.1 Calibration of the OC module
3.6.2 Evaluation of the OC module
3.6.3 Calibration of the OPs module
3.7 Conclusions
3.8 Acknowledgements
3.9 References
CHAPTER 4: SENSITIVITY ANALYSIS OF COP_COMPOST MODEL FOR THE DEGRADATION OF ORGANIC MICROPOLLUTANTS DURING COMPOSTING PROCESS
4.1 Abstract
4.2 Introduction
4.3 Materials and methods
4.3.1 Presentation of COP_Compost model
4.3.2 Software / Interface (MATLAB & Excel)
4.3.3 Experimental Data for model calibration and evaluation
4.3.4 Model calibration for OP module
4.3.5 Sensitivity analysis
4.4 Results and discussion
4.4.1 Calibration of OP module
4.5 Sensitivity analysis
4.5.1 Sensitivity of pyrene and simazine to all parameters
4.5.2 Sensitivity to initial conditions
4.6 Conclusion
4.7 Acknowledgements
4.8 References
PART II: APPLICATION OF COP_COMPOST MODEL TO BIOREMEDIATION OF PAH CONTAMINATED SOIL TROUGH COMPOST
CHAPTER 5: REMEDIATION OF POLYCYCLIC AROMATIC HYDROCARBON (PAH) CONTAMINATED SOIL THROUGH COMPOSTING WITH FRESH ORGANIC WASTES
5.1 Abstract
5.2 Introduction
5.3 Materials and methods
5.3.1 Experimental design
5.3.2 Contaminated soil
5.3.3 Mixture of wastes
5.3.4 Initial soil/waste mixtures
5.3.5 Specific added microorganisms
5.3.6 Bioreactors
5.3.7 Temperature and moisture
5.3.8 Sample collection
5.3.9 Organic matter analysis
5.3.10 PAHs analysis
5.3.11 PAH sorption
5.3.12 PLFA analysis
5.3.13 Statistical analysis
5.4 Results & Discussion
5.4.1 Dry mass
5.4.2 Organic matter analysis
5.4.3 Fate of PAHs
5.5 Conclusion
5.6 Acknowledgements
5.7 References
CHAPTER 6: MODELLING REMEDIATION OF POLYCYCLIC AROMATIC HYDROCARBON (PAH) CONTAMINATED SOIL THROUGH COMPOSTING WITH COP-COMPOST MODEL 
6.1 Materials and Methods
6.1.1 Contaminated soil
6.1.2 Mixture of wastes
6.1.3 Initial soil/waste mixtures
6.1.4 Bioreactors
6.1.5 Temperature and moisture
6.1.6 Sample collection
6.1.7 Organic matter analysis
6.1.8 PAHs analysis
6.1.9 PAH sorption
6.1.10 Statistical analysis
6.1.11 COP_Compost model
6.1.12 Model application
6.2 Data acquisition for model simulation
6.2.1 Organic matter analysis
6.2.2 Organic micro-pollutant analysis
6.3 Results and discussion
6.3.1 OM simulation
6.3.2 OP simulation
6.3.2.2 Simulations with coupling model
PART III: GENERAL CONCLUSION AND PERSPECTIVES
APPENDIX: EQUATIONS OF THE COP-COMPOST MODEL

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