Comprehensive Modeling of Agrochemicals Biodegradation in Soil a Multidisciplinary Approach to Make Informed Choices to Protect Human Health and the Environment
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Comprehensive modeling of agrochemicals biodegradation in soil A multidisciplinary approach to make informed choices to protect human health and the environment Daniele la Cecilia School of Civil Engineering Faculty of Engineering The University of Sydney 2019 A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy Supervisor: Ass. Prof. Federico Maggi Auxiliary Supervisor: Prof. Chengwang Lei Abstract Numerical models are relied upon by risk assessors to predict the dynamics of potentially haz- ardous pesticides in soil. Those models may account for fundamental processes affecting pes- ticide dynamics, such as environmental and edaphic conditions, water flow, degradation, and sorption. However, those models lack the ability to account for complex biogeochemical and ecological feedbacks, and thus create challenges in achieving robust predictions. In particular, no attention has been paid on the coupled mechanistic description of microbial dynamics and soil organic matter cycling and the implications on agrochemicals biodegradation and soil and groundwater quality. This thesis aims to provide this description by developing a comprehen- sive framework through a multidisciplinary approach. Microbiological regulation of pesticide dynamics was investigated by coupling theoretical and numerical approaches with experiments carried out in our environmental laboratory or sourced from the literature. We propose the use of reaction networks to highlight the possibly multiple pesticide degradation pathways and the feedbacks with macronutrient cycles. Biochemically-similar pathways are mediated by a spe- cific microbial functional group, which represents the microbial community carrying out par- ticular functions; these functions are biodegradation of pesticides and metabolism of carbon-, nitrogen-, and phosphorus-containing molecules. We describe biochemical reactions by means of Michaelis-Menten-Monod (MMM) kinetics. Indeed, MMM parameters fully encompass the microbial life strategies including rapid growth, high affinity for substrates, or high substrate consumption efficiency. Michaelis-Menten terms allow us to include microbial competition for substrates, growth inhibition, and the memory-associated catabolite repression herein pre- sented, which all can alter agrochemicals biodegradation effectiveness and macronutrients cy- cling. Because each biogeochemical process is mechanistically characterized in our approach, its uncertainty amd relevance can be quantified by means of sensitivity analyses. The latter are therefore crucial to explore the range of likely outcomes under a suite of scenarios, thus allowing risk managers to make informed decisions. We numerically show that a relatively small variability in MMM kinetic parameters and soil hydraulic parameters can result in large variability in agrochemicals environmental concentration. These results are in line with moni- toring campaigns worldwide reporting agrochemicals accumulation in soil and water resources, despite currently-enforced first-order kinetic models predict quick and complete biodegrada- tion. The proposed high-level process coupling introduced using a multidisciplinary approach is urged to develop sustainable plans in accordance with Nature-based strategies to cope with environmental changes and provide robust evidence to make informed choices. Statement Originality I, Daniele la Cecilia, hereby certify that to best of my knowledge, the intellectual content and writing embodied in this thesis are my own work and that any collaborations which contributed to this doctoral studies have been appropriately described and acknowledged. I also certify that this thesis has not been submitted anywhere else for any degree or other purposes. Name: Daniele Surname: la Cecilia Signature Date 25/02/2019 iv Authorship Attribution Statement Chapter 1 of this thesis reflects views of the author. Chapter 2 Sections 2.2 and 2.5 of this thesis was submitted as a special issue1 to Mathematics and Computers in Simulation. I carried out the literature review and wrote the manuscript. Chapter 3 of this thesis presents laboratory experiments carried out by the author, which results have not been published in any format anywhere else. Chapter 4 of this thesis was published as research articles2;3;4 in Journal of Environmental Management, Journal of Contaminant Hydrology, and Environmental Pollution, respectively. I contributed to develop the reaction networks and I carried out the calibrations, analyzed the data, and wrote the manuscripts. Chapter 5 of this thesis was published as research articles3;5 in Journal of Contaminant Hydrology and Water Research. I carried out the numerical simulations, analyzed the data, and wrote the manuscripts. The source code of the BRTSim-v2 solver used to conduct the simulations was developed by the co-author, Ass. Prof. Maggi. Chapter 6 of this thesis was published as research article6 in Advances in Water Resources, conference paper7 in International Congress on Modelling and Simulation, and conference abstract8 in Computational Methods in Water Resources and submitted as special issue1 in Mathematics and Computers in Simulation. In 6;8 I contributed by explaining the results of the sensitivity analyses and writing both the manuscript and the conference abstract. The source code of the BRTSim-v2 solver used to conduct the simulations was developed by the co-author, Ass. Prof. Maggi, while the source code used to conduct the sensitivity analyses was developed by the author, Prof. Porta. In 1;7 I carried out the numerical simulations, analyzed the data, and wrote both the manuscript and the conference paper. The source code of the BRTSim-v2 solver used to conduct the simulations was developed by the co-author, Ass. Prof. Maggi, while the source code used to conduct the sensitivity analyses was developed by myself. Chapter 7 of this thesis was published as research article9 in Soil Biology & Biochemistry.I developed the kinetic framework, carried out the numerical simulations, analyzed the data, and wrote the manuscript. The source code of the BRTSim-v2 solver used to conduct the simulations was developed by the co-author, Ass. Prof. Maggi. List of publications: 1 la Cecilia, D. and Maggi. F (Under Review). Influential sources of uncertainty in glyphosate biochemical degradation in soil. Mathematics and Computers in Simulation. Manuscript Num- ber: MATCOM-D-18-00335. 2 la Cecilia, D. and Maggi, F. (2016). Kinetics of Atrazine, Deisopropylatrazine, and Deethylatrazine soil biodecomposers. Journal of Environmental Management, 183, pp. 673- 686, 10.1016/j.jenvman.2016.09.012. 3 la Cecilia, D. and Maggi, F. (2017). In-situ atrazine biodegradation dynamics in wheat (Triticum) crops under variable hydrologic regime. Journal of Contaminant Hydrology, 203, pp. 104-121, http://dx.doi.org/10.1016/j.jconhyd.2017.05.004. vi 4 la Cecilia, D. and Maggi, F. (2018). Analysis of glyphosate degradation in a soil micro- cosm. Environmental Pollution. 233, pp. 201-207, https://doi.org/10.1016/j.envpol.2017.10.017. 5 la Cecilia, D., Tang, F.H., Coleman, N.V., Conoley, C., Vervoort, R.W., and Maggi, F. (2018). Glyphosate dispersion, degradation, and aquifer contamination in vineyards and wheat fields in the Po Valley, Italy. Water Research, 146, pp. 37-54, 10.1016/j.watres.2018.09.008. 6 Porta, G., la Cecilia, D., Guadagnini, A., and Maggi, F. (2018). Implications of uncertain biogeochemical parameters on a complex reaction network of atrazine biodegradation in soil. Advances in Water Resources, 121, pp. 494-498, 10.1016/j.advwatres.2018.08.002. 7 la Cecilia, D. and Maggi, F. (2017). Stochastic sensitivity analysis of glyphosate bio- chemical degradation. In Syme, G., Hatton MacDonald, D., Fulton, B. and Piantadosi, J. (eds) MODSIM2017, 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2017, pp. 257 - 263, isbn 978-0-9872143-7-9, https://www.mssanz.org.au/modsim2017/B3/lacecilia.pdf. 8 la Cecilia, D, Porta, G., Riva, M., Vervoort, RW., Coleman, NV, Tang, FH, and Maggi, F. (2018). Propagation of ecohydrological uncertainty in a complex biogeochemical network of Glyphosate dispersion and degradation. Computational Methods in Water Resources (CMWR) XXII. Bridging gaps between data, models, and predictions, p. 154. 9 la Cecilia, D., Riley, WJ, and Maggi, F. (2019). Biochemical modeling of microbial memory effects and catabolite repression on soil organic carbon compounds, Soil Biology & Biochemistry, 128, pp. 1 - 12, 10.1016/j.soilbio.2018.10.003. vii Hereby, I (Daniele la Cecilia) confirm that I am the first and the corresponding author of the publications listed above, and that I have acknowledged the first and the corresponding author (Ass. Prof. Giovanni Michele Porta) of the research outputs delivered as a result of collaborative projects with the Politecnico di Milano. Title: Mr. Surname: la Cecilia Name: Daniele Signature Date 25/02/2019 As supervisor for the candidature upon which this thesis is based, I can confirm that the authorship attribution statement above is correct. Title: A/Prof Surname: Maggi Name: Federico Signature Date 25 February 2019 viii Acknowledgments The scientific advancements achieved during the past 3 years have been embodied in this the- sis. Many more words shall be written to pursue the overall aim to understand how Nature responds and copes with pollutants and man-made environmental changes. This thesis outlines experimental and numerical frameworks