A method for mapping the air pollution in cities with the combined use of measured and calculated concentrations

The aim of this paper is to develop the technique for mapping the air pollution in cities using measured and computed concentrations. It is based on the combined use of deterministic and stochastic modelling. Two different approaches are applied to extrapolate the measurements to the regular grid points covering the city. The first uses the method of the principal components, and the second is based on optimal interpolation or 'kriging' of meteorological fields. The results of the application of this model for the mapping of air pollution in the city of Pskov, Russia, are given.     

An overview of uncertainties in modelling groundwater solute transport

Model predictions are uncertain because of uncertainties on future and/or anthropogenic stresses, parameter values and conceptual models. The first two groups of problems can be addressed through rather systematic methods (scenario analysis, error transmission techniques, automatic calibration algorithms, etc.). However, conceptual uncertainties are rarely given adequate attention. The objective of this paper is to synthesize conceptual difficulties associated with transport. These include: (1) processes that are significant at small scales may not be relevant at large scales; (2) inversely, new processes (e.g., dispersion) emerge in response to increase in scale and the way to represent them may depend on the assumed model structure; (3) the observed shapes of both breakthrough curves and pollutant plumes are not well represented by the classical transport equation; (4) porosities and dispersivities derived from field tracer tests often exhibit a directional dependence; etc. Though not directly related to solute transport, scale effects on hydraulic conductivity may also affect solute transport modelling. When these anomalies are examined, it is concluded that they are directly or indirectly caused by heterogeneity. Current approaches for dealing with heterogeneity can be divided into stochastic and deterministic. Stochastic methods have been successful in explaining qualitatively some anomalies of solute transport, but they appear to be far from reaching a stage at which they can be used routinely for solving realistic field problems. On the other hand, when applied with care, deterministic methods have been successfully used in actual problems. Yet, it can be argued that they fail to account for small-scale variability of concentrations so that they would become ineffective when dealing with nonlinear processes, such as chemical reactions. Relevance of on-going research for overcoming these difficulties is discussed.     

Challenges in quantifying biosphere-atmosphere exchange of nitrogen species

Recent research in nitrogen exchange with the atmosphere has separated research communities according to N form. The integrated perspective needed to quantify the net effect of N on greenhouse-gas balance is being addressed by the NitroEurope Integrated Project (NEU). Recent advances have depended on improved methodologies, while ongoing challenges include gas-aerosol interactions, organic nitrogen and N(2) fluxes. The NEU strategy applies a 3-tier Flux Network together with a Manipulation Network of global-change experiments, linked by common protocols to facilitate model application. Substantial progress has been made in modelling N fluxes, especially for N(2)O, NO and bi-directional NH(3) exchange. Landscape analysis represents an emerging challenge to address the spatial interactions between farms, fields, ecosystems, catchments and air dispersion/deposition. European up-scaling of N fluxes is highly uncertain and a key priority is for better data on agricultural practices. Finally, attention is needed to develop N flux verification procedures to assess compliance with international protocols.     

Water quality modelling of Lis River, Portugal

The aim of the study was to predict the impact of flow conditions, discharges and tributaries on the water quality of Lis River using QUAL2Kw model. Calibration of the model was performed, based on data obtained in field surveys carried out in July 2004 and November 2006. Generally the model fitted quite well the experimental data. The results indicated a decrease of water quality in the downstream area of Lis River, after the confluence of Lena, Milagres and Amor tributaries, as a result of discharges of wastewaters containing degradable organics, nutrients and pathogenic organisms from cattle-raising wastewaters, domestic effluents and agricultural runoff. The water quality criteria were exceeded in these areas for dissolved oxygen, biochemical oxygen demand, total nitrogen and faecal coliforms. Water quality modelling in different scenarios showed that the impact of tributaries on the quality of Lis River water was quite negligible and mainly depends on discharges, which are responsible by an increase of almost 45, 13 and 44 % of ultimate carbonaceous biochemical oxygen demand (CBOD_u), ammonium nitrogen and faecal coliforms, for winter simulation, and 23, 33 and 36 % for summer simulation, respectively, when compared to the real case scenario.     

Estimating catchment nutrient flow with the HBV-NP model: sensitivity to input data

The dynamic catchment model HBV-N has been further developed by adding routines for phosphorus transport and is now called the HBV-NP model. The model was shown to satisfactorily simulate nutrient dynamics in the R?nne? catchment (1,900 km2). Its sensitivity to input data was tested, and results demonstrated the increased sensitivity to the selection of input data on a subcatchment scale when compared with the catchment scale. Selection of soil and land use databases was found to be critical in some subcatchments but did not have a significant impact on a catchment scale. Although acceptable on a catchment scale, using templates and generalization, with regards to emissions from point sources and rural households, significantly decreased model performance in certain subcatchments when compared with using more detailed local information. A division into 64 subcatchments resulted in similar model performance at the catchment outlet when compared with a lumped approach. Adjusting the imported matrixes of the regional leaching of nitrogen, from agricultural land, against mean subcatchment water percolation did not have a significant impact on the model performance.     

Integrated analysis of the effects of agricultural management on nitrogen fluxes at landscape scale

The integrated modelling system INITIATOR was applied to a landscape in the northern part of the Netherlands to assess current nitrogen fluxes to air and water and the impact of various agricultural measures on these fluxes, using spatially explicit input data on animal numbers, land use, agricultural management, meteorology and soil. Average model results on NH₃ deposition and N concentrations in surface water appear to be comparable to observations, but the deviation can be large at local scale, despite the use of high resolution data. Evaluated measures include: air scrubbers reducing NH₃ emissions from poultry and pig housing systems, low protein feeding, reduced fertilizer amounts and low-emission stables for cattle. Low protein feeding and restrictive fertilizer application had the largest effect on both N inputs and N losses, resulting in N deposition reductions on Natura 2000 sites of 10% and 12%, respectively.     

Methods for quantifying variability and uncertainty in AP-42 emission factors: case studies for natural gas-fueled engines

Quantitative methods for characterizing variability and uncertainty were applied to case studies of oxides of nitrogen and total organic carbon emission factors for lean-burn natural gas-fueled internal combustion engines. Parametric probability distributions were fit to represent inter-engine variability in specific emission factors. Bootstrap simulation was used to quantify uncertainty in the fitted cumulative distribution function and in the mean emission factor. Some methodological challenges were encountered in analyzing the data. For example, in one instance, five data points were available, with each data point representing a different market share. Therefore, an approach was developed in which parametric distributions were fitted to population-weighted data. The uncertainty in mean emission factors ranges from as little as approximately +/-10% to as much as -90 to +180%. The wide range of uncertainty in some emission factors emphasizes the importance of recognizing and accounting for uncertainty in emissions estimates. The skewness in some uncertainty estimates illustrates the importance of using numerical simulation approaches that do not impose restrictive symmetry assumptions on the confidence interval for the mean. In this paper, the quantitative method, the analysis results, and key findings are presented.     

Monte Carlo analysis of field water flow comparing uni- and bimodal effective hydraulic parameters for structured soil

Soil structure critically affects the hydrological behaviour of soils. In this paper, we examined the impact of areal heterogeneity of hydraulic properties of a structured soil on soil ensemble behaviour for various soil water flow processes with different top boundary conditions (redistribution and drainage plus evaporation and infiltration). Using a numerical solution of the Richards' equation in a stochastic framework, the ensemble characteristics and flow dynamics were studied for drying and wetting processes observed during a time interval of ten days when a series of relatively intense rainfall events occurred. The effects of using unimodal and bimodal interpretative models of hydraulic properties on the ensemble hydrological behaviour of the soil were illustrated by comparing predictions to mean water contents measured over time in several sites at field scale. Although the differences between unimodal and bimodal fitting are not significant in terms of goodness of fit, the differences in process predictions are considerable with the bimodal soil simulating water content measurements much better than unimodal soil. We also investigated the relative contribution of the soil variability of each parameter on the variance of the water contents obtained as the main output of the stochastic simulations. The variability of the structural parameter, weighting the two pore space fractions in the bimodal interpretative model, has the largest contribution to water content variance. The contribution of each parameter depends only partly on the coefficient of variation, much more on the sensitivity of the model to the parameters and on the flow process being observed. We observed that the contribution of the retention parameters to uncertainty increases during drainage processes; the opposite occurs with the hydraulic conductivity parameters.     

The variability of processes involved in transgene dispersal—case studies from Brassica and related genera

Background, aim, and scope

We strive to predict consequences of genetically modified plants (GMPs) being cultivated openly in the environment, as human and animal health, biodiversity, agricultural practise and farmers’ economy could be affected. Therefore, it is unfortunate that the risk assessment of GMPs is burdened by uncertainty. One of the reasons for the uncertainty is that the GMPs are interacting with the ecosystems at the release site thereby creating variability. This variability, e.g. in gene flow, makes consequence analysis difficult. The review illustrates the great uncertainty of results from gene-flow analysis.

Main features

Many independent experiments were performed on the individual processes in gene flow. The results comprise information both from laboratory, growth chambers and field trials, and they were generated using molecular or phenotypic markers and analysis of fitness parameters. Monitoring of the extent of spontaneous introgression in natural populations was also performed. Modelling was used as an additional tool to identify key parameters in gene flow.

Results

The GM plant may affect the environment directly or indirectly by dispersal of the transgene. Magnitude of the transgene dispersal will depend on the GM crop, the agricultural practise and the environment of the release site. From case-to-case these three factors provide a variability that is reflected in widely different likelihoods of transgene dispersal and fitness of introgressed plants. In the present review, this is illustrated through a bunch of examples mostly from our own research on oilseed rape, Brassica napus. In the Brassica cases, the variability affected all five main steps in the process of gene dispersal. The modelling performed suggests that in Brassica, differences in fitness among plant genome classes could be a dominant factor in the establishment and survival of introgressed populations.

Discussion

Up to now, experimental analyses have mainly focused on studying the many individual processes of gene flow. This can be criticised, as these experiments are normally carried out in widely different environments and with different genotypes, and thus providing bits and pieces difficult to assemble. Only few gene-flow studies have been performed in natural populations and over several plant generations, though this could give a more coherent and holistic view.

Conclusion

The variability inherent in the processes of gene flow in Brassica is apparent and remedies are wished for. One possibility is to expose the study species to additional experiments and monitoring, but this is costly and will likely not cover all possible scenarios. Another remedy is modelling gene flow. Modelling is a valuable tool in identifying key factors in the gene-flow process for which more knowledge is needed, and identifying parameters and processes which are relatively insensitive to change and therefore require less attention in future collections of data. But the interdependence between models and experimental data is extensive, as models depend on experimental data for their development or testing.

Recommendations

More and more transgenic varieties are being grown worldwide harbouring genes that might potentially affect the environment (e.g. drought tolerance, salt tolerance, disease tolerance, pharmaceutical genes). This calls for a thorough risk assessment. However, in Brassica, the limited and uncertain knowledge on gene flow is an obstacle to this. Modelling of gene flow should be optimised, and modelling outputs verified in targeted field studies and at the landscape level. Last but not least, it is important to remember that transgene flow in itself is not necessarily a thread, but it is the consequences of gene flow that may jeopardise the ecosystems and the agricultural production. This emphasises the importance of consequence analysis of genetically modified plants.     

Modelling the spatial distribution of ammonia emissions in the UK

Ammonia emissions (NH3) are characterised by a high spatial variability at a local scale. When modelling the spatial distribution of NH3 emissions, it is important to provide robust emission estimates, since the model output is used to assess potential environmental impacts, e.g. exceedance of critical loads. The aim of this study was to provide a new, updated spatial NH3 emission inventory for the UK for the year 2000, based on an improved modelling approach and the use of updated input datasets. The AENEID model distributes NH3 emissions from a range of agricultural activities, such as grazing and housing of livestock, storage and spreading of manures, and fertilizer application, at a 1-km grid resolution over the most suitable landcover types. The results of the emission calculation for the year 2000 are analysed and the methodology is compared with a previous spatial emission inventory for 1996.     

Methods for Quantifying Variability and Uncertainty in AP-42 Emission Factors: Case Studies for Natural Gas-Fueled Engines

Abstract

Quantitative methods for characterizing variability and uncertainty were applied to case studies of oxides of nitrogen and total organic carbon emission factors for lean-burn natural gas-fueled internal combustion engines. Parametric probability distributions were fit to represent inter-engine variability in specific emission factors. Bootstrap simulation was used to quantify uncertainty in the fitted cumulative distribution function and in the mean emission factor. Some methodological challenges were encountered in analyzing the data. For example, in one instance, five data points were available, with each data point representing a different market share. Therefore, an approach was developed in which parametric distributions were fitted to population-weighted data. The uncertainty in mean emission factors ranges from as little as ~±10% to as much as -90 to 21+180%. The wide range of uncertainty in some emission factors emphasizes the importance of recognizing and accounting for uncertainty in emissions estimates. The skewness in some uncertainty estimates illustrates the importance of using numerical simulation approaches that do not impose restrictive symmetry assumptions on the confidence interval for the mean. In this paper, the quantitative method, the analysis results, and key findings are presented.     

NitroScape: a model to integrate nitrogen transfers and transformations in rural landscapes

Modelling nitrogen transfer and transformation at the landscape scale is relevant to estimate the mobility of the reactive forms of nitrogen (N_r) and the associated threats to the environment. Here we describe the development of a spatially and temporally explicit model to integrate N_r transfer and transformation at the landscape scale. The model couples four existing models, to simulate atmospheric, farm, agro-ecosystem and hydrological N_r fluxes and transformations within a landscape. Simulations were carried out on a theoretical landscape consisting of pig-crop farms interspersed with unmanaged ecosystems. Simulation results illustrated the effect of spatial interactions between landscape elements on N_r fluxes and losses to the environment. More than 10% of the total N₂O emissions were due to indirect emissions. The nitrogen budgets and transformations of the unmanaged ecosystems varied considerably, depending on their location within the landscape. The model represents a new tool for assessing the effect of changes in landscape structure on N_r fluxes.     

小流域N、P污染负荷的构成比重研究

对浙江省宁海县颜公河流域N、P污染物负荷的构成比重进行了研究，提出了农业非点源污染造成水体污染的严重性。采用美国农业部的AnnAGNPS模型模拟计算流域中农业面源污染的N、P负荷，并对模型模拟计算的可靠性进行了验证。     

A sensitivity analysis of adsorption and degradation parameters in the modeling of pesticide transport in soils

The increasing use of deterministic models in predicting the movement of pesticides in soils, has focused attention on the evaluation of major parameters which represent attenuation factors of organics in the subsurface. These parameters are the degradation rate constant and the adsorption constant for the pesticide. In view of the large in situ variability of these parameters and of the difficulty in obtaining accurate field data, there is a high degree of uncertainty associated with the results obtained from deterministic models. A sensitivity analysis is performed here to quantify the impact of such variation in each of these input parameters on the output results of an unsaturated zone transport model (PRZM). Results show that variations in these parameters about their respective mean values greatly affect the predicted concentration distributions, obtained after three years, of the pesticide aldicarb in all the soil profile. A 15–22% variation in the degradation constant, or a 24% variation in the adsorption constant, lead to a 100% uncertainty in the various simulation results defined as the cumulative quantity of aldicarb or the dissolved aldicarb concentration leached below the root zone (or the unsaturated zone) of the soil. Such a deterministic model presents a high degree of sensitivity to these input parameters. Accurate field data are then needed to obtain reliable model results in predicting pesticide movement inthe unsaturated zone.     

Long-term effects of soil heterogeneity on cadmium behaviour in soil

A deterministic model for long-term behaviour of contaminants in the rootzone is developed that includes sorption, leaching, and plant uptake. The model is applied to cadmium accumulation in a sandy soil and uptake of cadmium by barley. Sensitivity analysis showed that the sensitivity of the leaching rate to changes in soil chemical and soil physical parameters decreases as a function of time, and becomes zero when steady state is reached. In contrast, accumulation of cadmium in soil and the plant uptake rate of barley are increasingly sensitive to soil chemical and soil physical parameters as time preceeds. To analyse cadmium behaviour in a field that is heterogeneous with respect to soil physical properties, the interstitial flow velocity was assumed to be a random, lognormally distributed variate. Using Monte Carlo simulation, the average plant uptake rate appeared to be much higher in the stochastic analysis than in the deterministic approach. Steady state is reached after a very long period of time. For a lognormally distributed proton activity, causing heterogeneity with respect to the sorption capacity of the soil, the model predicted similar deviations from the deterministic approach. It is concluded that reference values for groundwater and crop quality are exceeded earlier in a heterogeneous field than in a homogenous soil profile. Moreover, when average values suggest an acceptable situation, variability of the leaching rate and the plant uptake rate can still cause exceedance of reference values in part of the field. Therefore, it is reasoned that environmental quality standards should take soil heterogeneity into account.     

Process Based Modelling of Phosphorus Losses from Arable Land

Improved understanding of temporal and spatial Phosphorus (P) discharge variations is needed for improved modelling and prioritisation of abatement strategies that take into account local conditions . This study is aimed at developing modelling of agricultural Phosphorus losses with improved spatial and temporal resolution, and to compare the accuracy of a detailed process-based model with a rainfall-runoff coefficient-based model. The process-based SWAT model (Soil and Water Assessment Tool) was implemented for five river basins in central Sweden, and results compared with the rainfall-runoff coefficient-based model WATSHMAN (Watershed Management System) for one of these river basins. Parameter settings and attribute values were adapted to Scandinavian soil conditions, crops and management practices. Model performance regarding flow dynamics was overall satisfactory. Comparable results were achieved at several scales. The modelled P load was of high accuracy for the days when monitoring data were available for validation, generally once a month. Modelled monthly P load did not fit as well with averaged monthly monitoring load values, mainly since monthly monitoring often partly or entirely misses the peak flows. The comparison of SWAT and WATSHMAN gave slightly better results for the process-based model (SWAT). Better spatial resolution for input data such as Soil-P content and agricultural management practices will be required to reach modelling results that enable identification of measures adapted to local conditions.     

Modelling of diffusion-limited retardation of contaminants in hydraulically and lithologically nonuniform media

A new reactive transport modelling approach and examples of its application are presented, dealing with the impact of sorption/desorption kinetics on the spreading of solutes, e.g. organic contaminants, in groundwater. Slow sorption/desorption is known from the literature to be strongly responsible for the retardation of organic contaminants. The modelling concept applied in this paper quantifies sorption/desorption kinetics by an intra-particle diffusion approach. According to this idea, solute uptake by or release from the aquifer material is modelled at small scale by a "slow" diffusion process where the diffusion coefficient is reduced as compared to the aqueous diffusion coefficient due to (i) the size and shape of intra-particle pores and (ii) retarded transport of solutes within intra-particle pores governed by a nonlinear sorption isotherm. This process-based concept has the advantage of requiring only measurable model parameters, thus avoiding fitting parameters like first-order rate coefficients.In addition, the approach presented here allows for modelling of slow sorption/desorption in lithologically nonuniform media. Therefore, it accounts for well-known experimental findings indicating that sorptive properties depend on (i) the grain size distribution of the aquifer material and (ii) the lithological composition (e.g. percentage of quartz, sandstone, limestone, etc.) of each grain size fraction. The small-scale physico-chemical model describing sorption/desorption is coupled to a large-scale model of groundwater flow and solute transport. Consequently, hydraulic heterogeneities may also be considered by the overall model. This coupling is regarded as an essential prerequisite for simulating field-scale scenarios which will be addressed by a forthcoming publication.This paper focuses on mathematical model formulation, implementation of the numerical code and lab-scale model applications highlighting the sorption and desorption behavior of an organic contaminant (Phenanthrene) with regard to three lithocomponents exhibiting different sorptive properties. In particular, it is shown that breakthrough curves (BTCs) for lithologically nonuniform media cannot be obtained via simple arithmetic averaging of breakthrough curves for lithologically uniform media. In addition, as no analytical solutions are available for model validation purposes, simulation results are compared to measurements from lab-scale column experiments. The model results indicate that the new code can be regarded as a valuable tool for predicting long-term contaminant uptake or release, which may last for several hundreds of years for some lithocomponents. In particular, breakthrough curves simulated by pure forward modelling reproduce experimental data much better than a calibrated standard first-order kinetics reactive transport model, thus indicating that the new approach is of high quality and may be advantageously used for supporting the design of remediation strategies at contaminated sites where some lithocomponents and/or grain size classes may provide a long-term pollutant source.     

Assessing the risk of N leaching from forest soils across a steep N deposition gradient in Sweden

Nitrogen leaching from boreal and temporal forests, where normally most of the nitrogen is retained, has the potential to increase acidification of soil and water and eutrophication of the Baltic Sea. In parts of Sweden, where the nitrogen deposition has been intermediate to high during recent decades, there are indications that the soils are close to nitrogen saturation. In this study, four different approaches were used to assess the risk of nitrogen leaching from forest soils in different parts of Sweden. Nitrate concentrations in soil water and C:N ratios in the humus layer where interpreted, together with model results from mass balance calculations and detailed dynamic modelling. All four approaches pointed at a risk of nitrogen leaching from forest soils in southern Sweden. However, there was a substantial variation on a local scale. Basing the assessment on four different approaches makes the assessment robust.     

Flow and transport in unsaturated fractured rock: effects of multiscale heterogeneity of hydrogeologic properties

The heterogeneity of hydrogeologic properties at different scales may have different effects on flow and transport processes in a subsurface system. A model for the unsaturated zone of Yucca Mountain, Nevada, is developed to represent complex heterogeneity at two different scales: (1) layer scale corresponding to geologic layering and (2) local scale. The layer-scale hydrogeologic properties are obtained using inverse modeling, based on the available measurements collected from the Yucca Mountain site. Calibration results show a significant lateral and vertical variability in matrix and fracture properties. Hydrogeologic property distributions in a two-dimensional, vertical cross-section of the site are generated by combining the average layer-scale matrix and fracture properties with local-scale perturbations generated using a stochastic simulation method. The unsaturated water flow and conservative (nonsorbing) tracer transport through the cross-section are simulated for different sets of matrix and fracture property fields. Comparison of simulation results indicates that the local-scale heterogeneity of matrix and fracture properties has a considerable effect on unsaturated flow processes, leading to fast flow paths in fractures and the matrix. These paths shorten the travel time of a conservative tracer from the source (repository) horizon in the unsaturated zone to the water table for small fractions of total released tracer mass. As a result, the local-scale heterogeneity also has a noticeable effect on global tracer transport processes, characterized by an average breakthrough curve at the water table, especially at the early arrival time of tracer mass. However, the effect is not significant at the later time after 20% tracer mass reaches the water table. The simulation results also verify that matrix diffusion plays an important role in overall solute transport processes in the unsaturated zone at Yucca Mountain.