TOWARDS A THEORY OF CONSTRUCTED WETLAND FUNCTIONING AND WITH THE HELP OF MATHEMATICAL MODELS

Transcription

1 SWS 2112 European Chapter Meeting Aarhus University, Denmark TOWARDS A THEORY OF CONSTRUCTED WETLAND FUNCTIONING AND WITH THE HELP OF MATHEMATICAL MODELS Roger Samsó & Joan García 20 June 2012

2 Constructed wetlands Distribution system Inlet zone Macrophytes Outlet zone Exit pipe Collection pipe Horizontal subsurface flow constructed wetland. Fixed biofilm-reactor From Brix and Schierup (1989) Knowledge mostly empiric and there is a lack of conceptual framework or theory on their functioning and corresponding mathematical formulation

3 Constructed wetlands Schematic illustration of wetlands processes From Kumar and Zhao (2012) In this presentation we will focus on bacteria communities/groups

4 Constructed wetlands 1. What are these bacteria? Do they belong to heterogeneous communities? 2. Do bacteria communities reach a steady state? 3. Do spatial variations of bacteria distribution occur? 4. Are they in the same location? In years?

5 Experimental evidences to answer these questions Classical approach Electron acceptors Mollecular microbiology FISH Gaseous end and intermediate products Culture microbiology PCR Physiological profiling

6 1. What are these bacteria? Do they belong to heterogenous groups? Evidences from gaseous or volatile intermediate and end products, or electron acceptors Organic matter was degraded aerobically by means of oxygen delivered directly from the atmosphere and anaerobically by methanogenic bacteria Brix (1990)

7 1. What are these bacteria? Do they belong to heterogeneous groups? Evidences from gaseous or volatile intermediate and end products, or electron acceptors The emission of N 2 O and CH 4 was found to be relatively high Teiter and Mander (2005)

8 1. What are these bacteria? Do they belong to heterogeneous groups? Evidences from gaseous or volatile intermediate and end products, or electron acceptors SO 4 2-, mg/l SO 4 2-, mg/l Influent C2-June C2-August 2 Location 3 Effluent 1 Influent C2-July C2-December 2 Location 3 Effluent Organic matter is removed from the wetlands by a combination of five possible mechanisms: sulphate reduction, denitrification, diffusion of air at the air and water interface (aerobic respiration), oxygen transport through macrophytes García et al. (2004) (aerobic respiration) and methanogenesis

9 1. What are these bacteria? Do they belong to heterogeneous groups? Evidences from molecular microbiology methods (FISH, PCR and community-level physiological profiling) Community studies have revealed in general a high diversity of bacterial strains in CWs comparable to that of other treatment technologies and natural ecosystems (Sims et al., 2012; Criado and Bécares, 2005; Calheiros Feng et al. (2012) et al., 2010)

10 2. Do bacteria groups reach a steady state? Scarce evidences from molecular microbiology methods (FISH, PCR and community-level physiological profiling) Weber and Legge (2011) The results found here can be described as intuitive from an ecological perspective and have relevance with respect to CW optimization and engineering

11 3. Do spatial variations of bacteria distribution occur? Scarce evidences from molecular microbiology methods (FISH, PCR and community-level physiological profiling) Depth was found to have a greater influence on the distribution of microbial communities than distance from the inlet, as indicated by the statistical analysis Krasnits et al. (2011) (Overloaded wetland: 11 gbod/m 2.day)

12 4. Are they in the same location? In years? Community studies have evaluated mainly static bacterial communities Ramond et al. (2012) and Weber and Legge (2011) have observed periods of 75 to 100 days to reach steady state in terms of diversity Calheiros et al. (2012) did not observed a clear effect of seasonality on communities Sims et al. (2012) detected more nitrifiers in summer than in winter coupled with a higher nitrification activity

13 Models Dynamics of bacterial communities can be simulated by means mechanistic models which initially were implemented in CWs to predict effluent concentrations Describing pollutant transformation and elimination processes, coupled to the hydraulic behaviour of the CW s flow field, models allow understanding the parallel reactions and interactions occurring in wetlands One notable limitation of previous simulation studies lies in their static or quasi-static nature. This means that in these studies only pictures of the state of a wetland at specific points in time were produced

14 TOWARDS A THEORY OF WETLAND FUNCTIONING GEMMAWET MODEL

15 The theory is based on a mathematical model. The model has to allow predictions and inferences of the real system in which it is applied, but in the long term. Features of the theory Theory development Is an effective theory which describes certain observed phenoma but whithout the implication of all processes involved The model says how the wetland behaves, we say why and build the theory The model is not unique, there may be others that match observed results

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17 Main equations Flow in saturated porous medium reaction Reactive transport Diffussion-dispersion advection Bacterial growth growth lysis Substrate consumption CWM1

18 Biokinetic submodel: CWM1 (Langergraber et al., 2009) 16 components XH Heterotrophic bacteria XA Nitrifiers XFB Fermenting bacteria XAMB Methanogens XASRB Sulphate reducing bacteria XSOB Sulphide oxidising bacteria DO 2 particulated fractions of COD 3 dissolved fractions of COD NH4-N and NO-N SO4-S and SH2S-S 17 processes Hydrolisis Growth Lysis

19 Langergraber et al. (2009) Process kinetics

20 2D Domain Mesh of more Approximate solution of the equations of the problem using FEM

21 COMSOL Multiphysics

22 Longitudinal section Simulations from several moths to 2 years Pristine conditions with regards to microorganisms in t=0 Scales can t be compared in all cases CW length= 10.3 m, CW depth= 0.6 m. Constant flow (2 m 3 /day) and constant influent properties (250 mgcod/l, 57 mg NH 3 -N/L, etc). Load= 4 gbod/m 2.day.

23 How it works? SF (Soluble fermentable COD) Influent: 170 mg COD.L -1 SF XFB (Fermenting bacteria) XFB + (XH) SA SA (Acetate as COD) Influent : 27 mg DQO.L -1

24 Do bacteria communities reach a steady state? Concentration (mg/l) Effluent concentrations SSO4 COD 0 Time (days)

25 Do bacteria communities reach a steady state? 20 seconds = 4 months SA (Acetate as COD) XASRB 20 seconds = 2 years SA (Acetate as COD)

26 Do bacteria communities reach a steady state? 20 seconds = 1.5 years Methanogenic bacteria (XAMB) Sulphate reducing bacteria (XASRB) Acetate as COD (SA)

27 Do spatial variations of bacteria distribution occur? Heterotrophic bacteria(xh) 2 years Fermenting bacteria (XFB) 2 years Metanogenic bacteria (XAMB) 2 years Sulphate reducing bacteria (XASRB) 2 years

28 Are they in the same location? In years? Fermenting bacteria (XFB) 5 years Methanogenic bacteria (XAMB) XH 5 years Sulphate reducing bacteria (XASRB) 5 years Porosity 5 years

29 Tips & Tricks of the model Logistic growth

30 Tips & Tricks of the model Porosity reduction 1 month 1 year 2 years

31 The ideal cartridge Clogged zone Active zone From Knowles et al. (2011)

32 The ideal cartridge Clogged zone Active zone From Knowles et al. (2011)

33 The ideal cartridge Clogged zone Active zone From Knowles et al. (2011)

34 Achievements Biomass growth is limited by available space and intrinsic biofilm limitations This has opened the door to perform long term simulations Also this has allow to develop a clogging model that permits to reproduce hydraulic conductivity behaviour, which couples with the hydrologic submodel (now hydraulic conductivity is constant)

35 Conclusions Each pore of the granular media can be viewed as a microreactor in which bacterial growth is limited by substrates, intrinsic biofilm limitations and space. CWs behave like an ideal cartridge in which active bacterial reactions occur in different places in time. The results of the model coupled with field studied will give new insights and perspectives on wetland performance

36 SWS 2112 European Chapter Meeting Aarhus University, Denmark THANK YOU SH2S Roger Samsó & Joan García 20 June 2012

37 20 seconds = 2 years Porosity SF SF SA

38 20 seconds = 2 years SNO SNH SO

39 20 seconds = 2 years SSO4 SH2S

40 20 seconds = 2 years Tips & Tricks Filtration and washout XS XI XS+XI