Testing model accuracy measures according to the EU directives—examples using the chemical transport model REM-CALGRID

The paper presents a comprehensive model evaluation focusing on the meaning and shortcomings of accuracy measures used to determine model quality according to European Union (EU) directives on air quality. European wide simulations employing the chemical transport model REM-CALGRID for the year 2002 were compared with O₃, NO₂, SO₂ and PM₁₀ observations of the German measurement network.The EU model quality objective, which is based on maximum relative errors, tends to penalise (i) the overestimation of very low measured concentrations in the case of annual averages and (ii) the underestimation of extremely high measured concentrations in the case of short-term values. As a more robust alternative, a model accuracy measure is presented, which corresponds to the allowed number of exceedances of the corresponding short-term air quality limit values.The influence of the spatial heterogeneity of the observations in relation to the spatial resolution of the model is investigated by spatial averaging of observation data. Because of this heterogeneity, any model with a 25 km resolution would fail to simulate about 20% of all NO₂ and SO₂ stations and 5–10% of all O₃ and PM₁₀ stations in Germany according to the EU model quality objectives for short-term averages.     

The application of the RAINS model for Greece

In order to comply in 2010 with the emission ceilings proposed by European commission under the convention on transboundary air pollution, Greece has to develop and implement a cohesive strategy affecting all the sectors of the economy. The RAINS model was used for the evaluation of the environmental and economic impacts arising from the use of a number of control technologies under alternative energy scenarios. To this purpose a number of modifications regarding the input databases of RAINS were made. The analysis clearly reveals that the reduction of SO₂ emissions can be achieved in a lower cost compared to the reduction of NO_x emissions. Moreover, the complementarity of CO₂ abatement policies and the SO₂/NO_x abatement policies is also accented.     

Experimental design strategy for the Weibull dose response model

The objective of this research was to determine optimum design point allocation for estimation of relative yield losses from ozone pollution when the true and fitted yield-ozone dose response relationship follows the Weibull. The optimum design is dependent on the values of the Weibull model parameters. A transformation was developed which allowed the optimum design (by the determinant criterion) for one parametric situation to be translated to any other, and permitted the search for optimum designs to be restricted to one set of Weibull parameters. Optimum designs were determined for the case where the Weibull parameters are assumed known, and effects of deviating from the optimum designs were investigated. Several alternative design strategies were considered for protecting against incorrectly guessing the Weibull model parameters when their true values are not known.     

Baltic sub-basin turnover times examined using the Rossby Centre Ocean model

Not least when judging the possible effects of climate change it proves necessary to estimate the water-renewal rates of limited marine areas subject to pronounced external influences. In connection with the SWECLIM programme this has been undertaken for two ecologically sensitive sub-basins of the Baltic, viz. the Gulf of Riga and Gdansk Bay. For this purpose two methodologically different approaches have been employed, based on mass-balance budgets and analysis of Lagrangian trajectories, respectively. When compared to the results obtained using the Lagrangian technique, the box-model approach proved to be adequate for the Gulf of Riga representing a morphologically highly constrained basin, whereas it demonstrated certain shortcomings when applied to the more open topographic conditions characterizing Gdansk Bay.     

A pesticide emission model (PEM) Part II: model evaluation

In the first part of the paper, the development of a numerical pesticide emission model (PEM) is described for predicting the volatilization of pesticides applied to agricultural soils and crops through soil incorporation, surface spraying, or in the furrow at the time of planting. In this paper the results of three steps toward the evaluation of PEM are reported. The evaluation involves: (i) verifying the numerical algorithms and computer code through comparison of PEM simulations with an available analytical solution of the advection/diffusion equation for semi-volatile solutes in soil; (ii) comparing hourly heat, moisture and emission fluxes of trifluralin and triallate modeled by PEM with fluxes measured using the relaxed eddy-accumulation technique; and (iii) comparison of the PEM predictions of persistence half-life for 29 pesticides with the ranges of persistence found in the literature. The overall conclusion from this limited evaluation study is that PEM is a useful model for estimating the volatilization rates of pesticides from agricultural soils and crops. The lack of reliable estimates of chemical and photochemical degradation rates of pesticide on foliage, however, introduces large uncertainties in the estimates from any model of the volatilization of pesticide that impacts the canopy.     

A model describing the complexing effect in the leaching of aluminum from cooking utensils

A simple model describing the complexing effect in the leaching of aluminum from cooking utensils is presented in this paper. Some experimental results obtained by previous workers may be explained by this model, which demonstrates that the complexing effect takes a very important role in the process of aluminum liberated from cooking utensils. Increased concentrations of complexing ions (organic acids, fluoride ion, OH-, etc.) significantly enhance the release of aluminum. The speciation of aluminum in simulated food solution is also investigated. The model suggests that in the pH range of most food (pH 4-8) aluminum present is predominantly in the form of organic Al-complexes, which is harmful to the human body.     

A multi media load model for the Baltic Sea

The background of this work is the international decision process with regard to the selection of chemicals to be assessed with priority. In order to stress the precautionary principle, mass flows were analysed rather than concentrations, threshold values, etc., as preferred by the chemical legislation (which still excludes the marine area). Lindane, hexachlorobenzene (HCB), trichloroacetic acid and its sodium salt, medium-chained chlorinated paraffins and tributyltin (TBT) were selected due to their great relevance for the marine area. Trichloroacetic acid is an interesting model compound on account of its accidental formation by degradation of volatile chlorinated hydrocarbons and during chlorination processes. In addition, a hypothetical compound was modelled, representing a highly water-soluble substance with low vapour pressure. The balancing area is the Baltic Sea and its catchment area. In order to model the substance flows, the 'Input/Output-load model' has been developed. The model quantifies the shift and the distribution of a yearly load of the substance investigated from the terrestrial-limnic into the marine compartment (Baltic Sea). Water-soluble substances, which are usually considered to be of no concern, may enter the sea in great amounts and, if not degradable, remain there. It turned out to be necessary to take into account remobilisation, unintended formation and point as well as line-sources.     

A pesticide emission model (PEM) Part I: model development

The application of pesticides to cultivated soil and crops is a major source of pesticides that are found in the atmosphere and which are transported and deposited to land and water surfaces over distances that range from local to global scales. In this first part of a two-part paper, a pesticide emission model (PEM) is proposed for estimating the exchange with the atmosphere of pesticides applied to soils and crops. The basis of PEM is a one-dimensional numerical solution of the dynamic equations describing the advection and diffusion of heat, moisture and pesticide within the soil column and exchange with the atmosphere through heat transfer, evapotranspiration and volatilization. The soil model is coupled with an atmospheric surface layer and a simple canopy model that includes: the interception of sprayed pesticide by the crop foliage; the partitioning of pesticide within a wet or dry canopy; and, the volatilization of pesticide to the atmosphere or the wash-off to the soil by precipitation. The finite-element technique used for solving the model equations is mass conservative and multi-year periods of simulation are possible while maintaining a proper mass balance of pesticide in the soil. The model is solved using 1200 s time-steps and 49 variably spaced levels in the soil to a depth of 2 m, with the highest vertical resolution (0.002 m spacing) near the soil surface. Similarity theory is used to parameterize the fluxes of heat, moisture and pesticide through the atmospheric surface layer with hourly meteorology being provided by either climate station observations or a meteorological model. In the second part to this paper, the results of an evaluation of PEM are reported.     

The forecasting model research of rural energy transformation in Henan Province based on STIRPAT model

Environmental Science and Pollution Research - In order to find the model of rural energy transformation in Henan Province. In this paper, Tapio decoupling model is employed to investigate the...     

Shifted power-law relationship between NO2 concentration and the distance from a highway: A new dispersion model based on the wind profile model

In this paper, a shifted power-law model, based on the wind profile model, had been supposed to simulate concentration gradient of nitrogen dioxide (NO₂) with distance from a highway. Field experiments were performed for NO₂ gradients from a highway in Shanghai by using passive samplers. The shifted power-law model was fitted well with experimental results of field experiments both in this study and in the literature. The results not only verified the validity of shifted power-law relationship between NO₂ concentration and the distance from a highway, but also partially demonstrated that there were some significant similarities between wind profile and air pollutants concentration profile near highway. With known concentration of chosen reference point and appropriate value of the parameter k, the model could be practically applied for predicting the NO₂ distributions near a highway. The methods of determining the parameter k were also discussed for further detailed studies.     

Development of an empirical model to estimate real-world fine particulate matter emission factors: the traffic air quality model

The purpose of the study was to quantify the impact of traffic conditions, such as free flow and congestion, on local air quality. The Borman Expressway (I-80/94) in Northwest Indiana is considered a test bed for this research because of the high volume of class 9 truck traffic traveling on it, as well as the existing and continuing installation of the Intelligent Transportation System (ITS) to improve traffic management along the highway stretch. An empirical traffic air quality (TAQ) model was developed to estimate the fine particulate matter (PM2.5) emission factors (grams per kilometer) based solely on the measured traffic parameters, namely, average speed, average acceleration, and class 9 truck density. The TAQ model has shown better predictions that matched the measured emission factor values more than the U.S. Environmental Protection Agency (EPA)-PART5 model. During congestion (defined as flow-speeds < 50 km/hr [30 mi/hr]), the TAQ model, on average, overpredicted the measured values only by a factor of 1.2, in comparison to a fourfold underprediction using the EPA-PART5 model. On the other hand, during free flow (defined as flow-speeds > 80 km/hr [50 mi/hr]), the TAQ model was conservative in that it overpredicted the measured values by 1.5-fold.     

A statistical model for predicting PM2.5 for the western United States

ABSTRACT

A new statistical model for predicting daily ground level fine scale particulate matter (PM_2.5) concentrations at monitoring sites in the western United States was developed and tested operationally during the 2016 and 2017 wildfire seasons. The model is site-specific, using a multiple linear regression schema that relies on the previous day’s PM_2.5 value, along with fire and smoke related variables from satellite observations. Fire variables include fire radiative power (FRP) and the National Fire Danger Rating System Energy Release Component index. Smoke variables, in addition to ground monitored PM_2.5, include aerosol optical depth (AOD) and smoke plume perimeters from the National Oceanic and Atmospheric Administration’s Hazard Mapping System. The overall statistical model was inspired by a similar system developed for British Columbia (BC) by the BC Center for Disease Control, but it has been heavily modified and adapted to work in the United States. On average, our statistical model was able to explain 78% of the variance in daily ground level PM_2.5. A novel method for implementation of this model as an operational forecast system was also developed and was tested and used during the 2016 and 2017 wildfire seasons. This method focused on producing a continuously-updating prediction that incorporated the latest information available throughout the day, including both updated remote sensing data and real-time PM_2.5 observations. The diurnal pattern of performance of this model shows that even a few hours of data early in the morning can substantially improve model performance.

Implications: Wildfire smoke events produce significant air quality impacts across the western United States each year impacting millions. We present and evaluate a statistical model for making updating predictions of fine particulate (PM_2.5) levels during smoke events. These predictions run hourly and are being used by smoke incident specialists assigned to wildfire operations, and may be of interest to public health officials, air quality regulators, and the public. Predictions based on this model will be available on the web for the 2019 western U.S. wildfire season this summer.     

Two-generation toxicity study on the copepod model species Tigriopus japonicus

Previous studies on the intertidal copepod Tigriopus japonicus have demonstrated that it is a suitable model species for the assessment of acute toxicities of marine pollutants. In order to standardize T. japonicus for use in environmental risk assessment involving whole life cycle exposure, we tested nine pollutants for their effects on growth and reproduction during a two-generation life cycle exposure test. Nauplii (F 0) were exposed to a range of concentrations of each chemical in a static renewal culture system. Broods of the second generation (F1) were subsequently exposed to the same concentrations for one full life cycle. Of the seven traits (nauplius phase, development time, survival, sex ratio, number of clutch, nauplii per clutch and fecundity), only the length of the nauplius phase and development time showed a greater sensitivity to chemical exposure. Between the two sensitive traits, the period of the nauplius phase was more sensitive than cohort generation time. Biocides significantly increased the maturation period of nauplii as well as copepodids in F 0 generation. In this study, it was demonstrated that T. japonicus could also be used in reproduction and life cycle tests and it provides an opportunity for testing the chronic and subchronic toxic effects of marine pollutants. Further validation and harmonization in a multi-centric study involving other laboratories of the region will strengthen its use as a supplement to existing model species.     

Data assimilation in the atmospheric dispersion model for nuclear accident assessments

Uncertainty factors in atmospheric dispersion models may influence the reliability of model prediction. The ability of a model in assimilating measurement data will be helpful to improve model prediction. In this paper, data assimilation based on ensemble Kalman filter (EnKF) is introduced to a Monte Carlo atmospheric dispersion model (MCADM) designed for assessment of consequences after an accident release of radionuclides. Twin experiment has been performed in which simulated ground-level dose rates have been assimilated. Uncertainties in the source term and turbulence intensity of wind field are considered, respectively. Methodologies and preliminary results of the application are described. It is shown that it is possible to reduce the discrepancy between the model forecast and the true situation by data assimilation. About 80% of error caused by the uncertainty in the source term is reduced, and the value for that caused by uncertainty in the turbulence intensity is about 50%.     

Performance of the partition-limited model on predicting ryegrass uptake of polycyclic aromatic hydrocarbons

Accurate modeling of the uptake and accumulation behavior of organic contaminants like polycyclic aromatic hydrocarbons (PAHs) in plants is essential to assess crop contamination and subsequent human exposure. In this study, the performance of a partition-limited model on predicting ryegrass uptake of PAHs (acenaphthene, fluorene, phenanthrene and pyrene) from water was evaluated and the major factors were examined. It was found that model predictions of PAH concentrations in roots and shoots of ryegrass were all within an order of magnitude of the observed values with the differences between estimated and measured concentrations less than 42.1% for roots and 78.4% for shoots. Since the model considered soil/water-plant pathway only, it was inevitable that simulated concentrations in shoots suffered a bigger error than those in roots due to the influence of foliar uptake, the other important pathway for PAHs. If the impact of foliar uptake was excluded, the accuracy of simulated shoot concentrations would be greatly enhanced, with the maximum prediction error reduced from 78.4% to 47.1% for pyrene. Other factors aside from foliar uptake were also examined, including aqueous PAH concentrations, uptake time, plant composition and chemical properties. These factors were found to influence the model performance generally through acting on the quasi-equilibrium factor (alpha(pt)). Results from this study substantiated the utility of this partition-limited model for vegetation-uptake assessment, and then provided some testimony valuable for the modification of a model with a better performance.     

Measuring the integrated risk of China’s carbon financial market based on the copula model

Measuring the risks of the carbon financial market is of great significance for investment decision-making, risk supervision, and the healthy development of the carbon trading market. Different from previous studies based on traditional VaR (value at risk), this study measures the integrated risk of China’s carbon market based on the Copula-EVT (Extreme Value Theory) -VaR model which can explore the unique strength of the copula and EVT-VaR models, of which the copula model is applied to capture the dependence between the different risk factors of carbon price volatility and macroeconomic fluctuation, while the EVT-VaR is used to explore the risk value. The empirical results show that the traditional VaR that only considers a single risk factor from carbon price volatility is likely to overestimate the risk. In addition, compared with other methods that do not consider the interdependence between risk factors, using the copula function to measure the carbon market integration risk is more effective, and backtesting also confirms this conclusion. This paper provides a specific reference for carbon emission companies to participate in the carbon market. It provides a theoretical basis for the supervision of the risk management of the carbon market.

     

Approximation of a radial diffusion model with a multiple-rate model for hetero-disperse particle mixtures

An innovative method is proposed for approximation of the set of radial diffusion equations governing mass exchange between aqueous bulk phase and intra-particle phase for a hetero-disperse mixture of particles such as those occurring in suspension in surface water, in riverine/estuarine sediment beds, in soils and in aquifer materials. For this purpose the temporal variation of concentration at several uniformly distributed points within a normalized representative particle with spherical, cylindrical or planar shape is fitted with a 2-domain linear reversible mass exchange model. The approximation method is then superposed in order to generalize the model to a hetero-disperse mixture of particles. The method can reduce the computational effort needed in solving the intra-particle mass exchange of a hetero-disperse mixture of particles significantly and also the error due to the approximation is shown to be relatively small. The method is applied to describe desorption batch experiment of 1,2-dichlorobenzene from four different soils with known particle size distributions and it could produce good agreement with experimental data.     

A model for the behaviour of Cs in watershed scenarios

A mathematical model of the radiocesium transfer in a lake and its catchment is presented in an attempt to improve previous approaches. The experimental data base of the Esthwaite Water location, U.K., prepared in the international program on VAlidation of Model Predictions (VAMP) of IAEA/CEC, was used as a test scenario. Radiocesium enters the lake via: (1) a quick pulse of atmospheric deposition for 1–2 days; and (2) a lasting but smaller contribution from the catchment carried by the water runoff and the dragged sediments. An auxiliary model of the catchment was used to quantify these two source terms.The temporal evolution of the ¹³⁷Cs concentration in this lake after the contamination by the Chernobyl accident is modelled using a compartmental approach following the Codell model. The desorption/adsorption dynamics between water and sediments are considered both in the drainage water in the lake boundary layer. The most important processes transferring contamination out of the lake water are adsorption of radioactivity by suspended sediments and their sedimentation; these processes are modelled through a distribution coefficient and through an aerial removal rate. Summer stratification is modelled introducing some auxiliary hypotheses.When using a priori probability distributions for the parameters based both on experimental evidence and on information from the literature the model simulates the observed radiocesium concentrations with an expected underprediction bias of 30% in the integrated concentrations in water. The concentration in sediments is inside the observed range in most of the runs. After the calibration of the model to the best fits observed with parameters inside their expected ranges, the bias decreases to −6% in the epilimnion, 8% in the hypolimnion and −4.4% in sediments, with an unexplained variance of ±3.2%, ±3% and ±1%, respectively.     

Toward verifying fossil fuel CO2 emissions with the CMAQ model: Motivation,model description and initial simulation

Motivated by the question of whether and how a state-of-the-art regional chemical transport model (CTM) can facilitate characterization of CO₂ spatiotemporal variability and verify CO₂ fossil-fuel emissions, we for the first time applied the Community Multiscale Air Quality (CMAQ) model to simulate CO₂. This paper presents methods, input data, and initial results for CO₂ simulation using CMAQ over the contiguous United States in October 2007. Modeling experiments have been performed to understand the roles of fossil-fuel emissions, biosphere–atmosphere exchange, and meteorology in regulating the spatial distribution of CO₂ near the surface over the contiguous United States. Three sets of net ecosystem exchange (NEE) fluxes were used as input to assess the impact of uncertainty of NEE on CO₂ concentrations simulated by CMAQ. Observational data from six tall tower sites across the country were used to evaluate model performance. In particular, at the Boulder Atmospheric Observatory (BAO), a tall tower site that receives urban emissions from Denver, CO, the CMAQ model using hourly varying, high-resolution CO₂ fossil-fuel emissions from the Vulcan inventory and CarbonTracker optimized NEE reproduced the observed diurnal profile of CO₂ reasonably well but with a low bias in the early morning. The spatial distribution of CO₂ was found to correlate with NOx, SO₂, and CO, because of their similar fossil-fuel emission sources and common transport processes. These initial results from CMAQ demonstrate the potential of using a regional CTM to help interpret CO₂ observations and understand CO₂ variability in space and time. The ability to simulate a full suite of air pollutants in CMAQ will also facilitate investigations of their use as tracers for CO₂ source attribution. This work serves as a proof of concept and the foundation for more comprehensive examinations of CO₂ spatiotemporal variability and various uncertainties in the future.

Implications: Atmospheric CO₂ has long been modeled and studied on continental to global scales to understand the global carbon cycle. This work demonstrates the potential of modeling and studying CO₂ variability at fine spatiotemporal scales with CMAQ, which has been applied extensively, to study traditionally regulated air pollutants. The abundant observational records of these air pollutants and successful experience in studying and reducing their emissions may be useful for verifying CO₂ emissions. Although there remains much more to further investigate, this work opens up a discussion on whether and how to study CO₂ as an air pollutant.     

Description of sorbing tracers transport in fractured media using the lattice model approach

The transport of contaminants in fractured media is a complex phenomenon with a great environmental impact. It has been described with several models, most of them based on complex partial differential equations, that are difficult to apply when equilibrium and nonequilibrium dynamics are considered in complex boundaries. With the aim of overcoming this limitation, a combination of two lattice Bathnagar, Gross and Krook (BGK) models, derived from the lattice Boltzmann model, is proposed in this paper. The fractured medium is assumed to be a single fissure in a porous rock matrix. The proposed approach permits us to deal with two processes with different length scales: advection-dispersion in the fissure and diffusion within the rock matrix. In addition to the mentioned phenomena, sorption reactions are also considered. The combined model has been tested using the experimental breakthrough curves obtained by Garnier et al. (Garnier, J.M., Crampon, N., Préaux, C., Porel, G., Vreulx, M., 1985. Tra?age par 13C, 2H, I- et uranine dans la nappe de la craie sénonienne en écoulement radial convergent (Béthune, France). J. Hidrol. 78, 379-392.) giving acceptable results. A study on the influence of the lattice BGK models parameters controlling sorption and matrix diffusion on the breakthrough curves shape is included.