Application of the BioClog model for landfill leachate clogging of gravel-packed columns

2005 ◽  
Vol 42 (6) ◽  
pp. 1600-1614 ◽  
Author(s):  
A J Cooke ◽  
R K Rowe ◽  
J VanGulck ◽  
B E Rittmann
Keyword(s):  
Landfill Leachate ◽  
Volatile Fatty Acids ◽  
Transport Model ◽  
Packed Columns ◽  
Chemical Transport Model ◽  
Inorganic Solids ◽  
Leachate Collection ◽  
Suspended Biomass ◽  
Reactive Chemical Transport ◽  
Multiple Species

A numerical, multiple-species, reactive chemical transport model (BioClog) developed to predict clogging in landfill leachate collection systems is used to interpret results from experiments conducted with gravel-packed columns permeated with landfill leachate. The model predicts changes to the microbial community and leachate chemistry, including the concentrations of volatile fatty acids, suspended biomass, dissolved calcium, and suspended inorganic solids. The calculated quantity and composition of the clog matter (biomass and mineral), along with the associated decrease in porosity, are compared to the measured values. The modelled clogging is in reasonable agreement with that observed in the gravel column experiments. By identifying and quantitatively linking many microbiological, chemical, and transport mechanisms, the model helps elucidate the phenomena controlling the rate and extent of clogging.Key words: clogging, landfills, leachate collection systems, biofilms, mineral precipitation.

Modelling species fate and porous media effects for landfill leachate flow

2005 ◽  
Vol 42 (4) ◽  
pp. 1116-1132 ◽  
Author(s):  
A J Cooke ◽  
R K Rowe ◽  
B E Rittmann
Keyword(s):  
Porous Media ◽  
Landfill Leachate ◽  
Reactive Transport ◽  
Volatile Fatty Acids ◽  
Transport Model ◽  
Calcium Carbonate Precipitation ◽  
Transport Modelling ◽  
Inorganic Particles ◽  
The Media ◽  
Multiple Species

A numerical, multiple-species, reactive transport model, coupled to models of kinetic biodegradation, precipitation, and particle attachment and detachment for predicting landfill leachate-induced clogging in porous media for one-dimensional flow systems, is described. The finite-element method is used for transport modelling, with reactions incorporated into point-source or sink terms. The species modelled include three volatile fatty acids, active and inert suspended biomass, dissolved calcium, and inorganic particles. The clog matter consists of active biofilm, inert biofilm, and inorganic solids. A biofilm model is used to simulate the growth and decay of active biomass and removal of substrate. Precipitate accumulation and calcium removal are simulated by a model of calcium carbonate precipitation. Interphase movement between clog matter and fluid includes the processes of attachment and detachment. A geometric representation of the porous media allows porosity and specific surface to be estimated from the thickness of the accumulated clog matter. The porosity of the media can thus change spatially and temporally. The behaviour of the model is demonstrated with a hypothetical example.Key words: clogging, landfills, leachate collection systems, modelling, biofilms, mineral precipitation.

2D modelling of clogging in landfill leachate collection systems

2008 ◽  
Vol 45 (10) ◽  
pp. 1393-1409 ◽  
Author(s):  
A. J. Cooke ◽  
R. Kerry Rowe
Keyword(s):  
Finite Element ◽  
Hydraulic Conductivity ◽  
Landfill Leachate ◽  
Transport Model ◽  
Point Sources ◽  
Time Step ◽  
Leachate Collection ◽  
Aspect Ratios ◽  
The Media ◽  
Multiple Species

A 2D model for predicting clogging of a landfill leachate collection system and subsequent leachate surface position (mounding) is described. A transient finite element fluid flow model is combined with a reactive, multiple-species finite element transport model. The transport model considers biological growth and biodegradation, precipitation, and particle attachment and detachment. It uses a geometrical relationship to establish porosity from the computed thickness of the accumulated clog matter and a relationship between the porosity and hydraulic conductivity of elements in the system. The model represents the flow path within the drainage layer in profile. An iterative method is used to solve for the new hydraulic heads, surface and internal nodal positions, and redistributed clog properties (clog quantity, porosity, hydraulic conductivity) for each element and for each time step. The porosity (and consequently hydraulic conductivity) of the media can therefore change spatially and temporally. The mesh is regenerated automatically each time step (including the addition or subtraction of nodes) taking into account allowable element aspect ratios, the interfaces between differing hydrostratigraphic layers, and static point sources and openings. An integrated alternate solution for very thin mounds is included. The application of the model is demonstrated using a hypothetical field case.

scholarly journals A tropospheric chemistry reanalysis for the years 2005–2012 based on an assimilation of OMI, MLS, TES and MOPITT satellite data

2015 ◽  
Vol 15 (6) ◽  
pp. 8687-8770
Author(s):  
K. Miyazaki ◽  
H. J. Eskes ◽  
K. Sudo
Keyword(s):  
Transport Model ◽  
Lower Troposphere ◽  
Tropospheric Chemistry ◽  
Atmospheric Environment ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Observational Estimate ◽  
Multiple Species ◽  
Chemical Fields

Abstract. We present the results from an eight-year tropospheric chemistry reanalysis for the period 2005–2012 obtained by assimilating multiple retrieval data sets from the OMI, MLS, TES, and MOPITT satellite instruments. The reanalysis calculation was conducted using a global chemical transport model and an ensemble Kalman filter technique that simultaneously optimises the chemical concentrations of various species and emissions of several precursors. The optimisation of both the concentration and the emission fields is an efficient method to correct the entire tropospheric profile and its year-to-year variations, and to adjust various tracers chemically linked to the species assimilated. Comparisons against independent aircraft, satellite, and ozonesonde observations demonstrate the quality of the analysed O3, NO2, and CO concentrations on regional and global scales and for both seasonal and year-to-year variations from the lower troposphere to the lower stratosphere. The data assimilation statistics imply persistent reduction of model error and improved representation of emission variability, but also show that discontinuities in the availability of the measurements lead to a degradation of the reanalysis. The decrease in the number of assimilated measurements increased the ozonesonde minus analysis difference after 2010 and caused spurious variations in the estimated emissions. The Northern/Southern Hemisphere OH ratio was modified considerably due to the multiple species assimilation and became closer to an observational estimate, which played an important role in propagating observational information among various chemical fields and affected the emission estimates. The consistent concentration and emission products provide unique information on year-to-year variations of the atmospheric environment.

Parameter estimation for modelling clogging of granular medium permeated with leachate

2008 ◽  
Vol 45 (6) ◽  
pp. 812-823 ◽  
Author(s):  
Jamie F. VanGulck ◽  
R. Kerry Rowe
Keyword(s):  
Water Quality ◽  
Volatile Fatty Acids ◽  
Transport Model ◽  
Kinetic Constants ◽  
Inverse Modelling ◽  
Mineral Matter ◽  
Column Experiments ◽  
Chemical Transport Model ◽  
Degrading Bacteria ◽  
Synthetic Leachate

A numerical model called BioClog is used to backcalculate biological activity rate constants using measured values of water quality and clog chemical characteristics from well-controlled laboratory column experiments that contained a granular-sized material permeated with synthetic and real leachates. BioClog is a multispecies, reactive chemical transport model capable of predicting clogging of a porous media caused by the accumulation of biofilms, chemical precipitates, and entrained particles. Monod kinetic constants for acetate- and butyrate-degrading bacteria were obtained through inverse modelling of granular-sized material permeated with synthetic leachate. The model predicted the changes in concentrations of volatile fatty acids and dissolved calcium and it predicted the changes in clog composition from a juvenile clog containing biofilm to a mature clog containing biofilm with mineral matter. The kinetic constants were then applied to predict spatial and temporal water quality and clog composition for a granular-sized material permeated with real leachate. The kinetic constants deduced through inverse modelling of the synthetic leachate column experiments provided reasonable predictions of the behaviour of the columns permeated with real leachate.

scholarly journals A tropospheric chemistry reanalysis for the years 2005–2012 based on an assimilation of OMI, MLS, TES, and MOPITT satellite data

2015 ◽  
Vol 15 (14) ◽  
pp. 8315-8348 ◽  
Author(s):  
K. Miyazaki ◽  
H. J. Eskes ◽  
K. Sudo
Keyword(s):  
Transport Model ◽  
Lower Troposphere ◽  
Tropospheric Chemistry ◽  
Atmospheric Environment ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Multiple Data ◽  
Multiple Data Sets ◽  
Observational Estimate ◽  
Multiple Species

Abstract. We present the results from an 8-year tropospheric chemistry reanalysis for the period 2005–2012 obtained by assimilating multiple data sets from the OMI, MLS, TES, and MOPITT satellite instruments. The reanalysis calculation was conducted using a global chemical transport model and an ensemble Kalman filter technique that simultaneously optimises the chemical concentrations of various species and emissions of several precursors. The optimisation of both the concentration and the emission fields is an efficient method to correct the entire tropospheric profile and its year-to-year variations, and to adjust various tracers chemically linked to the species assimilated. Comparisons against independent aircraft, satellite, and ozonesonde observations demonstrate the quality of the analysed O3, NO2, and CO concentrations on regional and global scales and for both seasonal and year-to-year variations from the lower troposphere to the lower stratosphere. The data assimilation statistics imply persistent reduction of model error and improved representation of emission variability, but they also show that discontinuities in the availability of the measurements lead to a degradation of the reanalysis. The decrease in the number of assimilated measurements increased the ozonesonde-minus-analysis difference after 2010 and caused spurious variations in the estimated emissions. The Northern/Southern Hemisphere OH ratio was modified considerably due to the multiple-species assimilation and became closer to an observational estimate, which played an important role in propagating observational information among various chemical fields and affected the emission estimates. The consistent concentration and emission products provide unique information on year-to-year variations in the atmospheric environment.

scholarly journals Urban Air Quality Modeling Using Low-Cost Sensor Network and Data Assimilation in the Aburrá Valley, Colombia

Atmosphere ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 91
Author(s):  
Santiago Lopez-Restrepo ◽  
Andres Yarce ◽  
Nicolás Pinel ◽  
O.L. Quintero ◽  
Arjo Segers ◽  
...  
Keyword(s):  
Air Quality ◽  
Data Assimilation ◽  
Transport Model ◽  
Cost Model ◽  
Low Cost ◽  
Model Performance ◽  
Monitoring Network ◽  
Correlation Factor ◽  
Chemical Transport Model ◽  
High Quality

The use of low air quality networks has been increasing in recent years to study urban pollution dynamics. Here we show the evaluation of the operational Aburrá Valley’s low-cost network against the official monitoring network. The results show that the PM2.5 low-cost measurements are very close to those observed by the official network. Additionally, the low-cost allows a higher spatial representation of the concentrations across the valley. We integrate low-cost observations with the chemical transport model Long Term Ozone Simulation-European Operational Smog (LOTOS-EUROS) using data assimilation. Two different configurations of the low-cost network were assimilated: using the whole low-cost network (255 sensors), and a high-quality selection using just the sensors with a correlation factor greater than 0.8 with respect to the official network (115 sensors). The official stations were also assimilated to compare the more dense low-cost network’s impact on the model performance. Both simulations assimilating the low-cost model outperform the model without assimilation and assimilating the official network. The capability to issue warnings for pollution events is also improved by assimilating the low-cost network with respect to the other simulations. Finally, the simulation using the high-quality configuration has lower error values than using the complete low-cost network, showing that it is essential to consider the quality and location and not just the total number of sensors. Our results suggest that with the current advance in low-cost sensors, it is possible to improve model performance with low-cost network data assimilation.

scholarly journals Sunset–sunrise difference in solar occultation ozone measurements (SAGE II, HALOE, and ACE–FTS) and its relationship to tidal vertical winds

2015 ◽  
Vol 15 (2) ◽  
pp. 829-843 ◽  
Author(s):  
T. Sakazaki ◽  
M. Shiotani ◽  
M. Suzuki ◽  
D. Kinnison ◽  
J. M. Zawodny ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Seasonal Variations ◽  
Climate Model ◽  
Transport Model ◽  
Stratospheric Aerosol ◽  
Data Sets ◽  
Chemical Transport Model ◽  
Latitude Range ◽  
Solar Occultation ◽  
Vertical Winds

Abstract. This paper contains a comprehensive investigation of the sunset–sunrise difference (SSD, i.e., the sunset-minus-sunrise value) of the ozone mixing ratio in the latitude range of 10° S–10° N. SSD values were determined from solar occultation measurements based on data obtained from the Stratospheric Aerosol and Gas Experiment (SAGE) II, the Halogen Occultation Experiment (HALOE), and the Atmospheric Chemistry Experiment–Fourier transform spectrometer (ACE–FTS). The SSD was negative at altitudes of 20–30 km (−0.1 ppmv at 25 km) and positive at 30–50 km (+0.2 ppmv at 40–45 km) for HALOE and ACE–FTS data. SAGE II data also showed a qualitatively similar result, although the SSD in the upper stratosphere was 2 times larger than those derived from the other data sets. On the basis of an analysis of data from the Superconducting Submillimeter-Wave Limb-Emission Sounder (SMILES) and a nudged chemical transport model (the specified dynamics version of the Whole Atmosphere Community Climate Model: SD–WACCM), we conclude that the SSD can be explained by diurnal variations in the ozone concentration, particularly those caused by vertical transport by the atmospheric tidal winds. All data sets showed significant seasonal variations in the SSD; the SSD in the upper stratosphere is greatest from December through February, while that in the lower stratosphere reaches a maximum twice: during the periods March–April and September–October. Based on an analysis of SD–WACCM results, we found that these seasonal variations follow those associated with the tidal vertical winds.

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