949 resultados para Concentration-time response modelling
Resumo:
Mountain regions worldwide are particularly sensitive to on-going climate change. Specifically in the Alps in Switzerland, the temperature has increased twice as fast than in the rest of the Northern hemisphere. Water temperature closely follows the annual air temperature cycle, severely impacting streams and freshwater ecosystems. In the last 20 years, brown trout (Salmo trutta L) catch has declined by approximately 40-50% in many rivers in Switzerland. Increasing water temperature has been suggested as one of the most likely cause of this decline. Temperature has a direct effect on trout population dynamics through developmental and disease control but can also indirectly impact dynamics via food-web interactions such as resource availability. We developed a spatially explicit modelling framework that allows spatial and temporal projections of trout biomass using the Aare river catchment as a model system, in order to assess the spatial and seasonal patterns of trout biomass variation. Given that biomass has a seasonal variation depending on trout life history stage, we developed seasonal biomass variation models for three periods of the year (Autumn-Winter, Spring and Summer). Because stream water temperature is a critical parameter for brown trout development, we first calibrated a model to predict water temperature as a function of air temperature to be able to further apply climate change scenarios. We then built a model of trout biomass variation by linking water temperature to trout biomass measurements collected by electro-fishing in 21 stations from 2009 to 2011. The different modelling components of our framework had overall a good predictive ability and we could show a seasonal effect of water temperature affecting trout biomass variation. Our statistical framework uses a minimum set of input variables that make it easily transferable to other study areas or fish species but could be improved by including effects of the biotic environment and the evolution of demographical parameters over time. However, our framework still remains informative to spatially highlight where potential changes of water temperature could affect trout biomass. (C) 2015 Elsevier B.V. All rights reserved.-
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Fine sediment delivery to and storage in stream channel reaches can disrupt aquatic habitats, impact river hydromorphology, and transfer adsorbed nutrients and pollutants from catchment slopes to the fluvial system. This paper presents a modelling toot for simulating the time-dependent response of the fine sediment system in catchments, using an integrated approach that incorporates both land phase and in-stream processes of sediment generation, storage and transfer. The performance of the model is demonstrated by applying it to simulate in-stream suspended sediment concentrations in two lowland catchments in southern England, the Enborne and the Lambourn, which exhibit contrasting hydrological and sediment responses due to differences in substrate permeability. The sediment model performs well in the Enborne catchment, where direct runoff events are frequent and peak suspended sediment concentrations can exceed 600 mg l(-1). The general trends in the in-stream concentrations in the Lambourn catchment are also reproduced by the model, although the observed concentrations are low (rarely exceeding 50 mg l(-1)) and the background variability in the concentrations is not fully characterized by the model. Direct runoff events are rare in this highly permeable catchment, resulting in a weak coupling between the sediment delivery system and the catchment hydrology. The generic performance of the model is also assessed using a generalized sensitivity analysis based on the parameter bounds identified in the catchment applications. Results indicate that the hydrological parameters contributing to the sediment response include those controlling (1) the partitioning of runoff between surface and soil zone flows and (2) the fractional loss of direct runoff volume prior to channel delivery. The principal sediment processes controlling model behaviour in the simulations are the transport capacity of direct runoff and the in-stream generation, storage and release of the fine sediment fraction. The in-stream processes appear to be important in maintaining the suspended sediment concentrations during low flows in the River Enborne and throughout much of the year in the River Lambourn. Copyright (c) 2007 John Wiley & Sons, Ltd.
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This paper exploits a structural time series approach to model the time pattern of multiple and resurgent food scares and their direct and cross-product impacts on consumer response. A structural time series Almost Ideal Demand System (STS-AIDS) is embedded in a vector error correction framework to allow for dynamic effects (VEC-STS-AIDS). Italian aggregate household data on meat demand is used to assess the time-varying impact of a resurgent BSE crisis (1996 and 2000) and the 1999 Dioxin crisis. The VEC-STS-AIDS model monitors the short-run impacts and performs satisfactorily in terms of residuals diagnostics, overcoming the major problems encountered by the customary vector error correction approach.
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We compare future changes in global mean temperature in response to different future scenarios which, for the first time, arise from emission-driven rather than concentration-driven perturbed parameter ensemble of a global climate model (GCM). These new GCM simulations sample uncertainties in atmospheric feedbacks, land carbon cycle, ocean physics and aerosol sulphur cycle processes. We find broader ranges of projected temperature responses arising when considering emission rather than concentration-driven simulations (with 10–90th percentile ranges of 1.7 K for the aggressive mitigation scenario, up to 3.9 K for the high-end, business as usual scenario). A small minority of simulations resulting from combinations of strong atmospheric feedbacks and carbon cycle responses show temperature increases in excess of 9 K (RCP8.5) and even under aggressive mitigation (RCP2.6) temperatures in excess of 4 K. While the simulations point to much larger temperature ranges for emission-driven experiments, they do not change existing expectations (based on previous concentration-driven experiments) on the timescales over which different sources of uncertainty are important. The new simulations sample a range of future atmospheric concentrations for each emission scenario. Both in the case of SRES A1B and the Representative Concentration Pathways (RCPs), the concentration scenarios used to drive GCM ensembles, lies towards the lower end of our simulated distribution. This design decision (a legacy of previous assessments) is likely to lead concentration-driven experiments to under-sample strong feedback responses in future projections. Our ensemble of emission-driven simulations span the global temperature response of the CMIP5 emission-driven simulations, except at the low end. Combinations of low climate sensitivity and low carbon cycle feedbacks lead to a number of CMIP5 responses to lie below our ensemble range. The ensemble simulates a number of high-end responses which lie above the CMIP5 carbon cycle range. These high-end simulations can be linked to sampling a number of stronger carbon cycle feedbacks and to sampling climate sensitivities above 4.5 K. This latter aspect highlights the priority in identifying real-world climate-sensitivity constraints which, if achieved, would lead to reductions on the upper bound of projected global mean temperature change. The ensembles of simulations presented here provides a framework to explore relationships between present-day observables and future changes, while the large spread of future-projected changes highlights the ongoing need for such work.
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High soil phosphorus (P) concentration is frequently shown to reduce root colonization by arbuscular mycorrhizal (AM) fungi, but the influence of P on the diversity of colonizing AM fungi is uncertain. We used terminal restriction fragment length polymorphism (T-RFLP) of 18S rDNA and cloning to assess diversity of AM fungi colonizing maize (Zea mays), soybean (Glycene max) and field violet (Viola arvensis) at three time points in one season along a P gradient of 10280mgl1 in the field. Percentage AM colonization changed between sampling time points but was not reduced by high soil P except in maize. There was no significant difference in AM diversity between sampling time points. Diversity was reduced at concentrations of P > 25mgl1, particularly in maize and soybean. Both cloning and T-RFLP indicated differences between AM communities in the different host species. Host species was more important than soil P in determining the AM community, except at the highest P concentration. Our results show that the impact of soil P on the diversity of AM fungi colonizing plants was broadly similar, despite the fact that different plants contained different communities. However, subtle differences in the response of the AM community in each host were evident.
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Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.
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Alkyl esters of p–hydroxybenzoic acid (parabens) are widely used as preservatives in personal care products, foods and pharmaceuticals. Their oestrogenic activity, their measurement in human breast tissue and their ability to drive proliferation of oestrogen-responsive human breast cancer cells has opened a debate on their potential to influence breast cancer development. Since proliferation is not the only hallmark of cancer cells, we have investigated the effects of exposure to parabens at concentrations of maximal proliferative response on migratory and invasive properties using three oestrogen-responsive human breast cancer cell lines (MCF-7, T-47-D, ZR-75-1). Cells were maintained short-term (1 week) or long-term (20±2 weeks) in phenol-red-free medium containing 5% charcoal-stripped serum with no addition, 10-8M 17-oestradiol, 1-5x10-4M methylparaben, 10-5M n-propylparaben or 10-5M n-butylparaben. Long-term exposure (20±2 weeks) of MCF-7 cells to methylparaben, n-propylparaben or n-butylparaben increased migration as measured using a scratch assay, time-lapse microscopy and xCELLigence technology: invasive properties were found to increase in matrix degradation assays and migration through matrigel on xCELLigence. Western immunoblotting showed an associated downregulation of E-cadherin and -catenin in the long-term paraben-exposed cells which could be consistent with a mechanism involving epithelial to mesenchymal transition. Increased migratory activity was demonstrated also in long-term paraben-exposed T-47-D and ZR-75-1 cells using a scratch assay and time-lapse microscopy. This is the first report that in vitro, parabens can influence not only proliferation but also migratory and invasive properties of human breast cancer cells.
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A fast simple climate modelling approach is developed for predicting and helping to understand general circulation model (GCM) simulations. We show that the simple model reproduces the GCM results accurately, for global mean surface air temperature change and global-mean heat uptake projections from 9 GCMs in the fifth coupled model inter-comparison project (CMIP5). This implies that understanding gained from idealised CO2 step experiments is applicable to policy-relevant scenario projections. Our approach is conceptually simple. It works by using the climate response to a CO2 step change taken directly from a GCM experiment. With radiative forcing from non-CO2 constituents obtained by adapting the Forster and Taylor method, we use our method to estimate results for CMIP5 representative concentration pathway (RCP) experiments for cases not run by the GCMs. We estimate differences between pairs of RCPs rather than RCP anomalies relative to the pre-industrial state. This gives better results because it makes greater use of available GCM projections. The GCMs exhibit differences in radiative forcing, which we incorporate in the simple model. We analyse the thus-completed ensemble of RCP projections. The ensemble mean changes between 1986–2005 and 2080–2099 for global temperature (heat uptake) are, for RCP8.5: 3.8 K (2.3 × 1024 J); for RCP6.0: 2.3 K (1.6 × 1024 J); for RCP4.5: 2.0 K (1.6 × 1024 J); for RCP2.6: 1.1 K (1.3 × 1024 J). The relative spread (standard deviation/ensemble mean) for these scenarios is around 0.2 and 0.15 for temperature and heat uptake respectively. We quantify the relative effect of mitigation action, through reduced emissions, via the time-dependent ratios (change in RCPx)/(change in RCP8.5), using changes with respect to pre-industrial conditions. We find that the effects of mitigation on global-mean temperature change and heat uptake are very similar across these different GCMs.
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Four rumen-fistulated Holstein heifers (134 +/- 1 kg initial BW) were used in a 4 x 4 Latin square design to determine the effects of delaying daily feed delivery time on intake, ruminal fermentation, behavior, and stress response. Each 3-wk experimental period was preceded by 1 wk in which all animals were fed at 0800 h. Feed bunks were cleaned at 0745 h and feed offered at 0800 h (T0, no delay), 0900 (T1), 1000 (T2), and 1100 (T3) from d1 to 21 with measurements taken during wk 1 and 3. Heifers were able to see each other at all times. Concentrate and barley straw were offered in separate compartments of the feed bunks, once daily and for ad libitum intake. Ruminal pH and saliva cortisol concentrations were measured at 0, 4, 8, and 12 h postfeeding on d 3 and 17 of each experimental period. Fecal glucocorticoid metabolites were measured on d 17. Increasing length of delay in daily feed delivery time resulted in a quadratic response in concentrate DMI (low in T1 and T2; P = 0.002), whereas straw DMI was greatest in T1 and T3 (cubic P = 0.03). Treatments affected the distribution of DMI within the day with a linear decrease observed between 0800 and 1200 h but a linear increase during nighttimes (2000 to 0800 h), whereas T1 and T2 had reduced DMI between 1200 and 1600 h (quadratic P = 0.04). Water consumption (L/d) was not affected but decreased linearly when expressed as liters per kilogram of DMI (P = 0.01). Meal length was greatest and eating rate slowest in T1 and T2 (quadratic P <= 0.001). Size of the first meal after feed delivery was reduced in T1 on d 1 (cubic P = 0.05) and decreased linearly on d 2 (P = 0.01) after change. Concentrate eating and drinking time (shortest in T1) and straw eating time (longest in T1) followed a cubic trend (P = 0.02). Time spent lying down was shortest and ruminating in standing position longest in T1 and T2. Delay of feeding time resulted in greater daily maximum salivary cortisol concentration (quadratic P = 0.04), which was greatest at 0 h in T1 and at 12 h after feeding in T2 (P < 0.05). Daily mean fecal glucocorticoid metabolites were greatest in T1 and T3 (cubic P = 0.04). Ruminal pH showed a treatment effect at wk 1 because of increased values in T1 and T3 (cubic P = 0.01). Delaying feed delivery time was not detrimental for rumen function because a stress response was triggered, which led to reduced concentrate intake, eating rate, and size of first meal, and increased straw intake. Increased salivary cortisol suggests that animal welfare is compromised.
Resumo:
Partial or full life-cycle tests are needed to assess the potential of endocrine-disrupting compounds (EDCs) to adversely affect development and reproduction of fish. Small fish species such as zebrafish, Danio rerio, are under consideration as model organisms for appropriate test protocols. The present study examines how reproductive effects resulting from exposure of zebrafish to the synthetic estrogen 17alpha-ethinylestradiol (EE2) vary with concentration (0.05 to 10 ng EE2 L(-1), nominal), and with timing/duration of exposure (partial life-cycle, full life-cycle, and two-generation exposure). Partial life-cycle exposure of the parental (F1) generation until completion of gonad differentiation (0-75 d postfertilization, dpf) impaired juvenile growth, time to sexual maturity, adult fecundity (egg production/female/day), and adult fertilization success at 1.1 ng EE2 L(-1) and higher. Lifelong exposure of the F1 generation until 177 dpf resulted in lowest observed effect concentrations (LOECs) for time to sexual maturity, fecundity, and fertilization success identical to those of the developmental test (0-75 dpf), but the slope of the concentration-response curve was steeper. Reproduction of zebrafish was completely inhibited at 9.3 ng EE2 L(-1), and this was essentially irreversible as a 3-mo depuration restored fertilization success to only a very low rate. Accordingly, elevated endogenous vitellogenin (VTG) synthesis and degenerative changes in gonad morphology persisted in depurated zebrafish. Full life-cycle exposure of the filial (F2) generation until 162 dpf impaired growth, delayed onset of spawning and reduced fecundity and fertilization success at 2.0 ng EE2 L(-1). In conclusion, results show that the impact of estrogenic agents on zebrafish sexual development and reproductive functions as well as the reversibility of effects, varies with exposure concentration (reversibility at < or = 1.1 ng EE2 L(-1) and irreversibility at 9.3 ng EE2 L(-1)), and between partial and full life-cycle exposure (exposure to 10 ng EE2 L(-1) during critical period exerted no permanent effect on sexual differentiation, but life-cycle exposure did).
Resumo:
Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.
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The marine laboratories in Plymouth have sampled at two principle sites in the Western English Channel for over a century in open-shelf (station E1; 50° 02'N, 4° 22'W) and coastal (station L4; 50° 15'N, 4° 13'W) waters. These stations are seasonally stratified from late-April until September, and the variable biological response is regulated by subtle variations in temperature, light, nutrients and meteorology. Station L4 is characterized by summer nutrient depletion, although intense summer precipitation, increasing riverine input to the system, results in pulses of increased nitrate concentration and surface freshening. The winter nutrient concentrations at E1 are consistent with an open-shelf site. Both stations have a spring and autumn phytoplankton bloom; at station E1, the autumn bloom tends to dominate in terms of chlorophyll concentration. The last two decades have seen a warming of around 0.6°C per decade, and this is superimposed on several periods of warming and cooling over the past century. In general, over the Western English Channel domain, the end of the 20th century was around 0.5°C warmer than the first half of the century. The warming magnitude and trend is consistent with other stations across the north-west European Shelf and occurred during a period of reduced wind stress and increased levels of insolation (+20%); these are both correlated with the larger scale climatic forcing of the North Atlantic Oscillation.
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This paper reports for the first time upon the effects of increasing CO2 concentrations on a natural phytoplankton assemblage in a tropical estuary (the Godavari River Estuary in India). Two short-term (5-day) bottle experiments were conducted (with and without nutrient addition) during the pre-monsoon season when the partial pressure of CO2 in the surface water is quite low. The results reveal that the concentrations of total chlorophyll, the phytoplankton growth rate, the concentrations of particulate organic matter, the photosynthetic oxygen evolution rates, and the total bacterial count were higher under elevated CO2 treatments, as compared to ambient conditions (control). delta13C of particulate organic matter (POM) varied inversely with respect to CO2, indicating a clear signature of higher CO2 influx under the elevated CO2 levels. Whereas, delta13CPOM in the controls indicated the existence of an active bicarbonate transport system under limited CO2 supply. A considerable change in phytoplankton community structure was noticed, with marker pigment analysis by HPLC revealing that cyanobacteria were dominant over diatoms as CO2 concentrations increased. A mass balance calculation indicated that insufficient nutrients (N, P and Si) might have inhibited diatomgrowth compared to cyanobacteria, regardless of increased CO2 supply. The present study suggests that CO2 concentration and nutrient supply could have significant effects on phytoplankton physiology and community composition for natural phytoplankton communities in this region. However, this work was conducted during a non-discharge period (nutrient-limited conditions) and the responses of phytoplankton to increasing CO2 might not necessarily be the same during other seasons with high physicochemical variability. Further investigation is therefore needed.
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As part of the Coupled Model Intercomparison Project, integrations with a common design have been undertaken with eleven different climate models to compare the response of the Atlantic thermohaline circulation ( THC) to time-dependent climate change caused by increasing atmospheric CO2 concentration. Over 140 years, during which the CO2 concentration quadruples, the circulation strength declines gradually in all models, by between 10 and 50%. No model shows a rapid or complete collapse, despite the fairly rapid increase and high final concentration of CO2. The models having the strongest overturning in the control climate tend to show the largest THC reductions. In all models, the THC weakening is caused more by changes in surface heat flux than by changes in surface water flux. No model shows a cooling anywhere, because the greenhouse warming is dominant.
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Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.