Geoinformation modeling of soil pollution processes by lead compounds in highway geosystems
Abstract
In this paper, we have worked out a method of geoinformation modeling of soil pollution by heavy metals in highway geosystems. Permanent process of contamination and redistribution of pollutants in highway geosystems causes difficulties in determining the degree of soil pollution and the speed of this process. This problem can be solved when using the method of geoinformation modeling of pollution by heavy metals compounds of soil. The method allows you to set the spatial parameters of the contamination field and the speed of the contamination process. The goal of the work is to test the method on the examples of lead compounds in the soils of the mixed forest zone.
The methodology uses geoinformation and mathematical models. These models describe the behavior of lead compounds when forming the contamination field. These are models of spatial distribution of heavy metals in the atmospheric air, soil, «soil-plant system».
Results: working out the provisions of the methodology took place at the test area. This area has plain fluvio-glacial and fluvial relief, close to the surface of the groundwater, the presence of wetlands, the soils are preferably of light mechanical composition with acid reaction and fulvatic type of humus, that are typical for the mixed forest zone. The modeling process is divided into two stages: 1. determining the amount of lead compounds brought in over a period of time and 2. determination of the number of lead compounds that have been removed from soil or removed from migration flows the same time period.
At each stage, models and tools supported obtaining, storing data, analyzing and displaying results of modeling. During the modeling process, we determined the total number of lead compounds coming per unit of time into the geosystem. First of all, we have identified the number of lead compounds entering the atmospheric surface from vehicles as the main source of emissions. We used an atmospheric impurity scattering model and obtained a mapping of the distribution of lead compounds in the near-earth layers of atmospheric air at dangerous wind speeds. In the next step, we determined the amount of lead compounds that reach the soil surface. The constructed surface, reflecting the spatial characteristics and intensities of the primary contamination field, became the basis for modeling the “soil cleaning processes”, following the main migration scenarios: lateral, radial and biogenic migration processes. For next step of modeling, we used a method that calculates soil loss (and, accordingly, lead compounds) from the site due to erosion processes. The number of lead compounds recovered from soils during lateral migration was determined. The results showed that in the test site geosystems, natural factors create conditions for the slow lateral migration. Closed negative landforms were geosystems with the highest probability of accumulation. The next step was to determine the migration intensity of soluble forms of lead in soils during radial migration. We determined that due to the liming, these soils show a "very low" intensity of metal migration and, accordingly, a "low" risk of contamination of plants. Preferably this relates to the accumulation of soluble lead compounds in concentrator plants.
In the next step, the amount of lead compounds that were transferred from soil to plants within the farmland was calculated.
Scientific novelty: as a result of the step-by-step implementation of the methodology of modeling, a series of digital maps were created and areas with different levels of soil contamination (or self-cleaning) speed were determined. We have identified areas that can be self-cleaning under conditions typical of the mixed forest zone with the existing level of anthropogenic loading. We have identified areas that are potentially dangerous for agricultural production by lead contamination.
Practical importance. This method can be applied to any heavy metal and other physical and geographical conditions. It allows to implement modeling in projects of ecological management, to determine the optimum level of anthropogenic load within highway geosystems.
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References
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