Verification of the "first flush" phenomenon in mine water from coal mines in the Upper Silesian Coal Basin, Poland

Case studies of Grodziec and Siersza mines in the Upper Silesian Coal Basin confirm that mine water accumulating in and over-flowing from abandoned coal mines is subject to a "first flush" phenomenon. The accumulated products of sulphide oxidation are dissolved in the rising mine water and flushed out at concentrations several times those observed during mine operation. Following the first overflow, sulphate concentration and hydrogen ion activity decay exponentially. In the case of workings in Siersza, decay constants of -0.003 to -0.005 day(-1) are observed, corresponding to flushing times of 480 to 820 days, some 10-20 times the period required for the workings to flood. Quantities of leachable sulphur in the abandoned workings of 0.02-0.03% are adequate to explain the observed concentrations of sulphate in the first flush, and this figure is tentatively supported by laboratory analyses.     

Ensemble-based data assimilation and targeted observation of a chemical tracer in a sea breeze model

We study the use of ensemble-based Kalman filtering of chemical observations for constraining forecast uncertainties and for selecting targeted observations. Using a coupled model of two-dimensional sea breeze dynamics and chemical tracer transport, we perform three numerical experiments. First, we investigate the chemical tracer forecast uncertainties associated with meteorological initial condition and forcing error. We find that the ensemble variance and error builds during the transition between land and sea breeze phases of the circulation. Second, we investigate the effects on the forecast variance and error of assimilating tracer concentration observations extracted from a truth simulation for a network of surface locations. We find that assimilation reduces the variance and error in both the observed variable (chemical tracer concentrations) and unobserved meteorological variables (vorticity and buoyancy). Finally, we investigate the potential value to the forecast of targeted observations. We calculate an observation impact factor that maximizes the total decrease in model uncertainty summed over all state variables. We find that locations of optimal targeted observations remain similar before and after assimilation of regular network observations.     

Modelling the closure-related geochemical evolution of groundwater at a former uranium mine

A newly developed reactive transport model was used to evaluate the potential effects of mine closure on the geochemical evolution in the aquifer downgradient from a mine site. The simulations were conducted for the K?nigstein uranium mine located in Saxony, Germany. During decades of operation, uranium at the former mine site had been extracted by in situ acid leaching of the ore underground, while the mine was maintained in a dewatered condition. One option for decommissioning is to allow the groundwater level to rise to its natural level, flooding the mine workings. As a result, pore water containing high concentrations of dissolved metals, radionuclides, and sulfate may be released. Additional contamination may arise due to the dissolution of minerals contained in the aquifer downgradient of the mine. On the other hand, dissolved metals may be attenuated by reactions within the aquifer. The geochemical processes and interactions involved are highly non-linear and their impact on the quality of the groundwater and surface water downstream of the mine is not always intuitive. The multicomponent reactive transport model MIN3P, which can describe mineral dissolution-precipitation reactions, aqueous complexation, and oxidation-reduction reactions, is shown to be a powerful tool for investigating these processes. The predictive capabilities of the model are, however, limited by the availability of key geochemical parameters such as the presence and quantities of primary and secondary mineral phases. Under these conditions, the model can provide valuable insight by means of sensitivity analyses.     

The use of wind fields in a land use regression model to predict air pollution concentrations for health exposure studies

A methodology is developed to include wind flow effects in land use regression (LUR) models for predicting nitrogen dioxide (NO₂) concentrations for health exposure studies. NO₂ is widely used in health studies as an indicator of traffic-generated air pollution in urban areas. Incorporation of high-resolution interpolated observed wind direction from a network of 38 weather stations in a LUR model improved NO₂ concentration estimates in densely populated, high traffic and industrial/business areas in Toronto-Hamilton urban airshed (THUA) of Ontario, Canada. These small-area variations in air pollution concentrations that are probably more important for health exposure studies may not be detected by sparse continuous air pollution monitoring network or conventional interpolation methods. Observed wind fields were also compared with wind fields generated by Global Environmental Multiscale-High resolution Model Application Project (GEM-HiMAP) to explore the feasibility of using regional weather forecasting model simulated wind fields in LUR models when observed data are either sparse or not available. While GEM-HiMAP predicted wind fields well at large scales, it was unable to resolve wind flow patterns at smaller scales. These results suggest caution and careful evaluation of regional weather forecasting model simulated wind fields before incorporating into human exposure models for health studies. This study has demonstrated that wind fields may be integrated into the land use regression framework. Such integration has a discernable influence on both the overall model prediction and perhaps more importantly for health effects assessment on the relative spatial distribution of traffic pollution throughout the THUA. Methodology developed in this study may be applied in other large urban areas across the world.     

A reaction-based paradigm to model reactive chemical transport in groundwater with general kinetic and equilibrium reactions

This paper presents a reaction-based water quality transport model in subsurface flow systems. Transport of chemical species with a variety of chemical and physical processes is mathematically described by M partial differential equations (PDEs). Decomposition via Gauss-Jordan column reduction of the reaction network transforms M species reactive transport equations into two sets of equations: a set of thermodynamic equilibrium equations representing N(E) equilibrium reactions and a set of reactive transport equations of M-N(E) kinetic-variables involving no equilibrium reactions (a kinetic-variable is a linear combination of species). The elimination of equilibrium reactions from reactive transport equations allows robust and efficient numerical integration. The model solves the PDEs of kinetic-variables rather than individual chemical species, which reduces the number of reactive transport equations and simplifies the reaction terms in the equations. A variety of numerical methods are investigated for solving the coupled transport and reaction equations. Simulation comparisons with exact solutions were performed to verify numerical accuracy and assess the effectiveness of various numerical strategies to deal with different application circumstances. Two validation examples involving simulations of uranium transport in soil columns are presented to evaluate the ability of the model to simulate reactive transport with complex reaction networks involving both kinetic and equilibrium reactions.     

Biogeochemical characterisation of a coal tar distillate plume

The distillation of acidified coal tars for up to 50 years has given rise to a phenol plume approximately 500 m long, 50 m deep and containing up to 15 g l(-1) dissolved organic carbon (DOC) in the Triassic Sandstones aquifer. A conceptual biogeochemical model based on chemical and microbiological analysis of groundwater samples has been developed as a preliminary to more detailed studies of the controls on natural attenuation. While the development of redox zones and the production of methane and carbon dioxide provide evidence of natural attenuation, it appears that degradation is slow. The existence of sulphate in the plume indicates that this electron acceptor has not been depleted and that consequently methanogenesis is probably limited. Based on a simple estimate of sulphate input concentration, a half-life of about 15 years has been estimated for sulphate reduction. Geochemical modelling predicts that increased alkalinity within the plume has not led to carbonate precipitation, and thus within the limits of accuracy of the measurement, alkalinity may reflect the degree of biodegradation. This implies a loss of around 18% of the DOC over a 30-year period. Despite limited degradation, microbial studies show that there are diverse microbial communities in the aquifer with the potential for both anaerobic and aerobic biodegradation. Microbial activity was found to be greatest at the leading edge of the plume where DOC concentrations are 60 mg l(-1) or less, but activity could still be observed in more contaminated samples even though cells could not be cultured. The study suggests that degradation may be limited by the high phenol concentrations within the core of the plume, but that once diluted by dispersion, natural attenuation may proceed. More detailed studies to confirm these initial findings are identified and form the basis of associated papers.     

Development and verification of a screening model for surface spreading of petroleum

Overflows and leakage from aboveground storage tanks and pipelines carrying crude oil and petroleum products occur frequently. The spilled hydrocarbons pose environmental threats by contaminating the surrounding soil and the underlying ground water. Predicting the fate and transport of these chemicals is required for environmental risk assessment and for remedial measure design. The present paper discusses the formulation and application of the Oil Surface Flow Screening Model (OILSFSM) for predicting the surface flow of oil by taking into account infiltration and evaporation. Surface flow is simulated using a semi-analytical model based on the lubrication theory approximation of viscous flow. Infiltration is simulated using a version of the Green and Ampt infiltration model, which is modified to account for oil properties. Evaporation of volatile compounds is simulated using a compositional model that accounts for the changes in the fraction of each compound in the spilled oil. The coupling between surface flow, infiltration and evaporation is achieved by incorporating the infiltration and evaporation fluxes into the global continuity equation of the spilled oil. The model was verified against numerical models for infiltration and analytical models for surface flow. The verification study demonstrates the applicability of the model.     

A computational technique for turbulent flow of wastewater sludge.

A computational fluid dynamics (CFD) technique applied to the turbulent flow of wastewater sludge in horizontal, smooth-wall, circular pipes is presented. The technique uses the Crank-Nicolson finite difference method in conjunction with the variable secant method, an algorithm for determining the pressure gradient of the flow. A simple algebraic turbulence model is used. A Bingham-plastic rheological model is used to describe the shear stress/shear rate relationship for the wastewater sludge. The method computes velocity gradient and head loss, given a fixed volumetric flow, pipe size, and solids concentration. Solids concentrations ranging from 3 to 10% (by weight) and nominal pipe sizes from 0.15 m (6 in.) to 0.36 m (14 in.) are studied. Comparison of the CFD results for water to established values serves to validate the numerical method. The head loss results are presented in terms of a head loss ratio, R(hl), which is the ratio of sludge head loss to water head loss. An empirical equation relating R(hl) to pipe velocity and solids concentration, derived from the results of the CFD calculations, is presented. The results are compared with published values of Rhl for solids concentrations of 3 and 6%. A new expression for the Fanning friction factor for wastewater sludge flow is also presented.     

Analysis of a deep well recharge experiment by calibrating a reactive transport model with field data

This paper describes the modeling of the hydrogeochemical effects of deep well recharge of oxic water into an anoxic pyrite-bearing aquifer. Kinetic expressions have been used for mineral dissolution-precipitation rates and organic matter oxidation. Hydrological and chemical parameters of the model were calibrated to field measurements. The results showed that oxidation of pyrite (FeS(2)) and, to a lesser extent, organic matter dominate the changes in quality of the recharged water during its passage through the aquifer. The recharge leads to the consumption of oxygen and nitrate and the formation of sulfate and ferrihydrite. Complexation reactions, cation exchange and precipitation and dissolution of calcite, siderite and rhodochrosite were also identified through the modeling. Despite problems of non-uniqueness of the calibrated parameters, the model was used successfully to depict the geochemical processes occurring in the aquifer. Non-uniqueness can be avoided by constraining the model as much as possible to measurements and/or data from literature, although they cannot be considered always as fixed values and should be considered as stochastic variables instead.     

Modelling aerosol number distributions from a vehicle exhaust with an aerosol CFD model

Vehicular traffic contributes significantly to the aerosol number concentrations at the local scale by emitting primary soot particles and forming secondary nucleated nanoparticles. Because of their potential health effects, more attention is paid to the traffic induced aerosol number distributions.The aim of this work is to explain the phenomenology leading to the formation and the evolution of the aerosol number distributions in the vicinity of a vehicle exhaust using numerical modelling. The emissions are representative of those of a light-duty diesel truck without a diesel particle filter. The atmospheric flow is modelled with a computational fluid dynamics (CFD) code to describe the dispersion of pollutants at the local scale. The CFD code, coupled to a modal aerosol model (MAM) describing the aerosol dynamics, is used to model the tailpipe plume of a vehicle with emissions corresponding to urban driving conditions. On the basis of available measurements in Schauer et al. (1999), three surrogate species are chosen to treat the semi-volatile organic compounds in the emissions.The model simulates the formation of the aerosol distribution in the exhaust plume of a vehicle as follows. After emission to the atmosphere, particles are formed by nucleation of sulphuric acid and water vapour depending strongly on the thermodynamic state of the atmosphere and on the dilution conditions. The semi-volatile organic compounds are critical for the rapid growth of nanoparticles through condensation. The semi-volatile organic compounds are also important for the evolution of primary soot particles and can contribute substantially to their chemical composition.The most influential parameters for particle formation are the sulphur fuel content, the semi-volatile organic emissions and also the mass and initial diameter of the soot particles emitted. The model is able to take into account the complex competition between nucleation, condensation and dilution, as well as the interactions among the different aerosol modes. This type of model is a useful tool to better understand the dynamics leading to the formation of traffic induced aerosol distributions. However, some key issues such as the turbulence in the exhaust plume and in the wake of the car, the magnitude and chemical composition of semi-volatile organic emissions and the possible nucleation of organic species need to be investigated further to improve our understanding of ultrafine particle formation.     

Calibration and validation of an integrated nitrate transport model within a well capture zone

Groundwater contamination by nitrate was investigated in an agricultural area in southern Quebec, Canada, where a municipal well is the local source of drinking water. A network of 38 piezometers was installed within the capture zone of the municipal well to monitor water table levels and nitrate concentrations in the aquifer. Nitrate concentrations were also measured in the municipal well. A Water flow and Nitrate transport Global Model (WNGM) was developed to simulate the impact of agricultural activities on nitrate concentrations in both the aquifer and municipal well. The WNGM first uses the Agriflux model to simulate vertical water and nitrate fluxes below the root zone for each of the seventy agricultural fields located within the capture zone of the municipal well. The WNGM then uses the HydroGeoSphere model to simulate three-dimensional variably-saturated groundwater flow and nitrate transport in the aquifer using water and nitrate fluxes computed with the Agriflux model as the top boundary conditions. The WNGM model was calibrated by reproducing water levels measured from 2005 to 2007 in the network of piezometers and nitrate concentrations measured in the municipal well from 1997 to 2007. The nitrate concentrations measured in the network of piezometers, however, showed greater variability than in the municipal well and could not be reproduced by the calibrated model. After calibration, the model was validated by successfully reproducing the decrease of nitrate concentrations observed in the municipal well in 2006 and 2007. Although it cannot predict nitrate concentrations in individual piezometers, the calibrated and validated WNGM can be used to assess the impact of changes in agricultural practices on global nitrate concentrations in the aquifer and in the municipal well.     

Testing the capability of the chemistry transport model LOTOS-EUROS to forecast PM10 levels in the Netherlands

Since particulate matter has a direct and adverse impact on public health, a good air quality forecast is important. Several European countries presently use statistical forecasting models, which have their limitations, especially for PM10. An alternative approach is to use a chemistry transport model. Here, the ability of the chemical transport model LOTOS-EUROS to forecast PM10 concentrations in the Netherlands was investigated. LOTOS-EUROS models several PM10 components individually. For sulphate, nitrate and ammonium aerosol the evaluation against observations shows that the modelled annual mean concentrations are within 20% of the measured concentration and that the temporal correlation is reasonably good (R > 0.6). For sea salt the model tended to overestimate the measured concentrations. For elemental carbon the correspondence with black smoke observations was reasonable. However, total PM10 is seriously underestimated, due to unmodelled components (secondary organic aerosols, mineral dust) and missing sources. Therefore, a simple bias correction for four seasons was derived based on the years 2004–2006. The model was compared with the Dutch operational statistical model PROPART and ground-level observations. With bias correction, LOTOS-EUROS performed better than PROPART regarding the timing of events. The major flaw of LOTOS-EUROS was that high values (>50 μg m^?3) were still underestimated. Another advantage of LOTOS-EUROS over the statistical model was the more detailed information in space and time, which facilitates communication of the forecast to the general public.     

Sensitivity of modelled sulphate and nitrate aerosol to cloud,pH and ammonia emissions

A Lagrangian dispersion model has been used to predict daily sulphate aerosol in 2006 at five UK rural measurement sites and hourly nitrate aerosol in April 2003 at Harwell (UK). The sensitivity of aqueous phase sulphate production to the meteorological input has been investigated. Large differences were found between cloud fraction and cloud liquid water output from the regional and mesoscale Met Office Unified Model. The impact on the sulphate aerosol was relatively small, with the mesoscale meteorology giving better results.Sulphate aerosol production in the aqueous phase was found to be very sensitive to modelled cloud pH. As the cloud becomes acidic sulphate production is greatly limited, conversely if the cloud is basic large amounts of sulphate aerosol are produced. A fixed model pH of 5.8 was found to produce better results than allowing the model to calculate pH which resulted in large over-predictions of measured sulphate aerosol in some episodes.Nitrate aerosol was not sensitive to cloud variables or pH, but showed a slight increase with 30% more ammonia emissions, and a slight decrease with 30% less ammonia.Sulphate production in model runs with fixed pH was not sensitive to changing ammonia emissions, however the sulphate production with modelled pH was very sensitive to plus or minus 30% ammonia. This work suggests that good modelling of ammonia is essential to correct estimation of aqueous phase sulphate aerosol if cloud pH is modelled. It is concluded that modelling to estimate the effect of reduced ammonia emission scenarios on future ambient aerosol levels should also take into account the neutralising effect of ammonia in cloud and hence the effect on aqueous phase production of sulphate.     

Overestimation of urban nitrogen dioxide by passive diffusion tubes: a comparative exposure and model study

A detailed comparative trial of passive diffusion tubes (PDT) for measurement of NO₂ in urban air has been undertaken in Edinburgh, UK. Acrylic, foil-wrapped and quartz tubes were exposed in parallel for 1-week and 4-week periods at three urban sites equipped with continuous analysers for NO, NO_x and O₃. Standard acrylic PDTs significantly overestimated NO₂ concentrations relative to chemiluminescence analysers, by an average of 27% over all sites for 1-week exposures. No significant difference was observed between standard and foil-wrapped acrylic tubes (both UV blocking). The mean ratio between quartz (UV transmitting) tubes and chemiluminescence analysers was 1.06. Quartz PDT data suggest a tendency for in situ photolysis to offset (but in a non-quantifiable way) the effect of chemical overestimation. The 4-week exposures yielded systematically lower NO₂ concentration than average NO₂ from four sequential 1-week exposures over the same period. The reduction in the apparent NO₂ sampling rate with time mostlikely arises from in situ photolysis of trapped NO₂. Hourly NO₂, NO and O₃ data for 20 1-week exposures were used as input to a numerical model of diffusion tube operation incorporating chemical reaction between co-diffusing NO and O₃ within the tube. The mean calculated overestimation of 22% for NO₂ from the PDT model simulations is close to the average difference between acrylic PDT and analyser NO₂ concentrations (24% for the same exposure periods), showing that within-tube chemistry can account for observed discrepancies in NO₂ measurement between the two techniques. Overestimation by PDT generally increased as average NO₂/NO_x ratios decreased. Accurate quantitative correction of PDT measurements is not possible. Nevertheless, PDT NO₂ concentrations were correlated with both analyser NO₂ and NO_x suggesting that acrylic PDTs retain a qualitative measure of NO₂ and NO_x variation at a particular urban location.     

Coastal hydrogeological system of Mar Piccolo (Taranto,Italy)

The Mar Piccolo basin is an internal sea basin located along the Ionian coast (Southern Italy), and it is surrounded primarily by fractured carbonate karstic environment. Because of the karstic features, the main continental water inflow is from groundwater discharge. The Mar Piccolo basin represents a peculiar and sensitive environment and a social emergency because of sea water and sediment pollution. This pollution appears to be caused by the overlapping effects of dangerous anthropogenic activities, including heavy industries and commercial and navy dockyards. The paper aims to define the contribution of subaerial and submarine coastal springs to the hydrological dynamic equilibrium of this internal sea basin. A general approach was defined, including a hydrogeological basin border assessment to detect inflowing springs, detailed geological and hydrogeological conceptualisation, in situ submarine and subaerial spring measurements, and flow numerical modelling. Multiple sources of data were obtained to define a relevant geodatabase, and it contained information on approximately 2000 wells, located in the study area (1600 km²). The conceptualisation of the hydrogeological basin, which is 978 km² wide, was supported by a 3D geological model that interpolated 716 stratigraphic logs. The variability in hydraulic conductivity was determined using hundreds of pumping tests. Five surveys were performed to acquire hydro-geochemical data and spring flow-yield measurements; the isotope groundwater age was assessed and used for model validation. The mean annual volume exchanged by the hydrogeological basin was assessed equal to 106.93 10⁶ m³. The numerical modelling permitted an assessment of the mean monthly yield of each spring outflow (surveyed or not), travel time, and main path flow.     

A partially coupled, fraction-by-fraction modelling approach to the subsurface migration of gasoline spills

The subsurface spreading behaviour of gasoline, as well as several other common soil- and groundwater pollutants (e.g. diesel, creosote), is complicated by the fact that it is a mixture of hundreds of different constituents, behaving differently with respect to e.g. dissolution, volatilisation, adsorption and biodegradation. Especially for scenarios where the non-aqueous phase liquid (NAPL) phase is highly mobile, such as for sudden spills in connection with accidents, it is necessary to simultaneously analyse the migration of the NAPL and its individual components in order to assess risks and environmental impacts. Although a few fully coupled, multi-phase, multi-constituent models exist, such models are highly complex and may be time consuming to use. A new, somewhat simplified methodology for modelling the subsurface migration of gasoline while taking its multi-constituent nature into account is therefore introduced here. Constituents with similar properties are grouped together into eight fractions. The migration of each fraction in the aqueous and gaseous phases as well as adsorption is modelled separately using a single-constituent multi-phase flow model, while the movement of the free-phase gasoline is essentially the same for all fractions. The modelling is done stepwise to allow updating of the free-phase gasoline composition at certain time intervals. The output is the concentration of the eight different fractions in the aqueous, gaseous, free gasoline and solid phases with time. The approach is evaluated by comparing it to a fully coupled multi-phase, multi-constituent numerical simulator in the modelling of a typical accident-type spill scenario, based on a tanker accident in northern Sweden. Here the PCFF method produces results similar to those of the more sophisticated, fully coupled model. The benefit of the method is that it is easy to use and can be applied to any single-constituent multi-phase numerical simulator, which in turn may have different strengths in incorporating various processes. The results demonstrate that the different fractions have significantly different migration behaviours and although the methodology involves some simplifications, it is a considerable improvement compared to modelling the gasoline constituents completely individually or as one single mixture.     

Sulphate aerosol size distributions at Mumbai,India, during the INDOEX-FFP (1998)

Sulphate size distributions were measured at the coastal station of Mumbai (formerly Bombay) through 1998, during the Indian ocean experiment (INDOEX) first field phase (FFP), to fill current gaps in size-resolved aerosol chemical composition data. The paper examines meteorological, seasonal and source-contribution effects on sulphate aerosol and discusses potential effects of sulphate on regional climate. Sulphate size-distributions were largely trimodal with a condensation mode (mass median aerodynamic diameter or MMAD 0.6 μm), a droplet mode (MMAD 1.9–2.4 μm) and a coarse mode (MMAD 5 μm). Condensation mode sulphate mass-fractions were highest in winter, consistent with the high meteorological potential for gas-to-particle conversion along with low relative humidity (RH). The droplet mode concentrations and MMADs were larger in the pre-monsoon and winter than in monsoon, implying sulphate predominance in larger sized particles within this mode. In these seasons the high RH, and consequently greater aerosol water in the droplet mode, would favour aerosol-phase partitioning and reactions of SO₂. Coarse mode sulphate concentrations were lowest in the monsoon, when continental contribution to sulphate was low and washout was efficient. In winter and pre-monsoon, coarse mode sulphate concentrations were somewhat higher, likely from SO₂ gas-to-particle conversion. Low daytime sulphate concentrations with a large coarse fraction, along with largely onshore winds, indicated marine aerosol predominance. High nighttime sulphate concentrations and a coincident large fine fraction indicated contributions from anthropogenic/industrial sources or from gas-to-particle conversion. Monthly mean sulphate concentrations increased with increasing SO₂ concentrations, RH and easterly wind direction, indicating the importance of gas-to-particle conversion and industrial sources located to the east. Atmospheric chemistry effects on sulphate size distributions in Mumbai, indicated by this data, must be further examined.