In the present work WRF model is used to generate meteorological fields for the HYSPLIT dispersion model. Sensitivity and validation of the WRF model, is conducted by utilizing different combinations of physical parameterization schemes. For this purpose, eight different configurations are examined. Assessment of the predictions of the WRF model is carried out by computing the statistical parameters including correlation coefficient (CC) and root mean square error (RMSE). As an example of the results of the WRF model utilizing proper physical configuration at Bousher syoptic station at 03/01/2005 leads to CC=0.82007 and RMSE=1.91783 for wind speed parameter. Once the proper configuration of the WRF model is obtained, dispersion simulations and annual effective dose for adult age group are carried out by WRF-HYSPLIT coupled model under normal conditions for Bushehr power plant. Simulated annual effective dose for adult age group by the coupled model for the years 2014, 2015 and 2016 are 5.8E-08 Sv/yr, 6.7E-08 Sv/yr and 1.1E-07 Sv/yr respectively. Results show that simulation and prediction of effective dose with coupled WRF-HYSPLIT model are in good agreement with observations and indicates the validity of the simulations. The ratio of predicted annual effective dose to dose limit (1E-04 Sv/yr) for normal operation is obtained less than 0.2 percent (

In this paper, we present an application of evolved neural networks using a real coded genetic algorithm for simulations of monthly groundwater levels in a coastal aquifer located in the Shabestar Plain, Iran. After initializing the model with groundwater elevations observed at a given time, the developed hybrid genetic algorithm-back propagation (GA-BP) should be able to reproduce groundwater level variations using the external input variables, including rainfall, average discharge, temperature, evaporation and annual time series. To achieve this purpose, the hybrid GA-BP algorithm is first calibrated on a training dataset to perform monthly predictions of future groundwater levels using past observed groundwater levels and additional inputs. Simulations are then produced on another data set by iteratively feeding back the predicted groundwater levels, along with real external data. This modelling algorithm has been compared with the individual back propagation model (ANN-BP), which demonstrates the capability of the hybrid GA-BP model. The later provides better results in estimation of groundwater levels compared to the individual one. The study suggests that such a network can be used as a viable alternative to physical-based models in order to simulate the responses of the aquifer under plausible future scenarios, or to reconstruct long periods of missing observations provided past data for the influencing variables is available.

Predicting the transfer of contaminants in soils is often hampered by lacking validation of mathematical models. Here, we applied Hydrus-2D software to three agricultural soils for simulating the 1900–2005 changes of zinc and lead concentration profiles derived from industrial atmospheric deposition, to validate the tested models with plausible assumptions on past metal inputs to reach the 2005 situation. The models were set with data from previous studies on the geochemical background, estimated temporal metal deposition, and the 2005 metal distributions. Different hypotheses of chemical reactions of metals with the soil solution were examined: 100% equilibrium or partial equilibrium, parameterized following kinetic chemical extractions. Finally, a two-site model with kinetic constant values adjusted at 1% of EDTA extraction parameters satisfactory predicted changes in metal concentration profiles for two arable soils. For a grassland soil however, this model showed limited applicability by ignoring the role of earthworm activity in metal incorporation.

Plastic particles smaller than 1 μm are considered to be highly dangerous pollutants due to their ability to penetrate living cells. Model experiments on the toxicity of plastics should be correlated with actual concentrations of plastics in natural water. We simulated the natural destruction of polystyrene, polyvinyl chloride, and poly(methyl methacrylate) in experiments on the abrasion of plastics with small stones. The plastics were dyed in mass with a fluorescent dye, which made it possible to distinguish plastic particles from stone fragments. We found that less than 1% of polystyrene and polyvinyl chloride were converted to submicron size particles. In the case of more rigid poly(methyl methacrylate), the fraction of such particles reaches 11%. The concentration of particles with a diameter less than 1 μm in the model experiments was from 0.7 (polystyrene) to 13 mg/L (poly(methyl methacrylate)), and when transferring the obtained data to real reservoirs, these values should be reduced by several orders of magnitude. These data explain the difficulties associated with the search for nanoplastics in natural waters. The toxicity of such particles to hydrobionts in model experiments was detected for concentrations greater than 1 mg/L, which is unrealistic in nature. Detectable and toxic amounts of nano- and submicron plastic particles in living organisms can be expected only in the case of filter-feeding organisms, such as molluscs, krill, sponges, etc.

Ambient ozone (O₃) concentrations have shown an upward trend in China and its health hazards have also been recognized in recent years. High-resolution exposure data based on statistical models are needed. Our study aimed to build high-performance random forest (RF) models based on training data from 2013 to 2017 in the Beijing-Tianjin-Hebei (BTH) region in China at a 0.01 ° × 0.01 ° resolution, and estimated daily maximum 8h average O₃ (O₃-8hmax) concentration, daily average O₃ (O₃-mean) concentration, and daily maximum 1h O₃ (O₃-1hmax) concentration from 2010 to 2017. Model features included meteorological variables, chemical transport model output variables, geographic variables, and population data. The test-R² of sample-based O₃-8hmax, O₃-mean and O₃-1hmax models were all greater than 0.80, while the R² of site-based and date-based model were 0.68–0.87. From 2010 to 2017, O₃-8hmax, O₃-mean, and O₃-1hmax concentrations in the BTH region increased by 4.18 μg/m³, 0.11 μg/m³, and 4.71 μg/m³, especially in more developed regions. Due to the influence of weather conditions, which showed high contribution to the model, the long-term spatial distribution of O₃ concentrations indicated a similar pattern as altitude, where high concentration levels were distributed in regions with higher altitude.

Recent gas discoveries in the eastern Mediterranean Sea led to multiple operations with substantial economic interest, and with them there is a risk of oil spills and their potential environmental impacts. To examine the potential spatial distribution of this threat, we created seasonal maps of the probability of oil spill pollution reaching an area in the Israeli coastal and exclusive economic zones, given knowledge of its initial sources. We performed simulations of virtual oil spills using realistic atmospheric and oceanic conditions. The resulting maps show dominance of the alongshore northerly current, which causes the high probability areas to be stretched parallel to the coast, increasing contamination probability downstream of source points. The seasonal westerly wind forcing determines how wide the high probability areas are, and may also restrict these to a small coastal region near source points. Seasonal variability in probability distribution, oil state, and pollution time is also discussed.

To assess risks of chemically-dispersed oil to marine organisms, oil concentrations in the water were simulated using a hypothetical spill accident in Tokyo Bay. Simulated oil concentrations were then compared with the short-term no-observed effect concentration (NOEC), 0.01mg/L, obtained through toxicity tests using marine diatoms, amphipod and fish. Area of oil concentrations higher than the NOEC were compared with respect to use and non-use of dispersant. Results of the simulation show relatively faster dispersion near the mouth of the bay compared to its inner sections which is basically related to its stronger water currents. Interestingly, in the inner bay, a large area of chemically-dispersed oil has concentrations higher than the NOEC. It seems emulsifying oil by dispersant increases oil concentrations, which could lead to higher toxicity to aquatic organisms. When stronger winds occur, however, the difference in toxic areas between use and non-use of dispersant is quite small.

Increasing the precision of nitrogen (N) fertiliser management in cropping systems is integral to increasing the environmental and economic sustainability of cropping. In a simulation study, we found that natural variability in year-to-year climate had a major effect on optimum N fertiliser rates for sugarcane in the Tully region of north-eastern Australia, where N discharges pose high risks to Great Barrier Reef ecosystems. There were interactions between climate and other factors affecting crop growth that made optimum N rates field-specific. The regional average optimum N fertiliser rate was substantially lower than current industry guidelines. Likewise, simulated N losses to the environment at optimum N fertiliser rates were substantially lower than the simulated losses at current industry fertiliser guidelines. Dissolved N discharged from rivers is related to fertiliser applications. If the reductions in N applications identified in the study occurred in the Tully region, the reduction in dissolved N discharges from rivers in the region would almost meet current water quality improvement targets. Whilst there were many assumptions made in this exploratory study, and there are many steps between the study and a practically implemented dynamic N fertiliser recommendation system, the potential environmental benefits justify field validation and further development of the concepts identified in the study.