Characteristics And Rules Of Heavy Metal Pollution On Roadside Soil And Crop Along Highway

The highway traffic is the main source of heavy metal pollution. Due to limited cropland area, it is very common to plant crops along the highways. So, in view of agricultural products safety, the heavy metal pollution by the highway traffic to the soils and crops along the highways is widely concerned by scientist and public. Lots of evidence has demonstrated that the soils and crops along the highway were contaminated at various degrees by heavy metals such as Pb, Cd, Cr and Zn etc. However, the traits and laws of the pollution were unclearly documented. The soils along the highway have lower heavy metal content while the crops, such as rice, wheat, vegetables and fruits, contain Pb, Cd, Cr and Zn over the national guidance limits. The heavy metal which is higher in soils is not necessarily higher in crops and which is lower in soils is higher in crops. These uncertainties may be mainly contributed to the uncertainties about the polluting pathways of the heavy metals, biological availability and its influence factors of heavy metal in soils. The express highway will impact agro-environment more seriously due to its main part in future traffic. Therefore, to study the distribution traits, accumulative laws and influence factors of heavy metals in agricultural soils and crops can provide scientific evidence and theoretical basis for the environmental protection and cultivation planning along the express highway.This study took the Shanghai-Nanjing and Beijing-Shanghai express highways which have the heaviest traffic flows as research objects. In 2008-2009, six typical sections with different traffic flows were selected for collection of the bilateral soils and crops (rice and wheat) along the highway. The total and available contents of heavy metals (Pb, Cd, Cr, Zn and Cu) in soil and the contents of heavy metal in grains of rice and wheat were measured. The distribution traits and influence factors of the heavy metal were analyzed. At the same time, by pot experiment and stable Pb isotope tracing method, source origin (atmosphere or soil) of the heavy metal in rice and wheat, and the proportion of the heavy metal from atmosphere or soils in different organs were analyzed. Based on the field monitoring and simulation experiment, the content of heavy metal in roadside agricultural soils and crops were simulated by the artificial neural network method. From the simulation, the prediction model of heavy metal contents in soils and crops were built. The main conclusions in our study were as follows:Along the six sections, the bilateral soil, rice and wheat were contaminated by heavy metal with the furthest border reaching 330 m. The Pb, Cd, Cr, Zn and Cu contents in soils were higher than the control but no more than the maximum allowable conentrations. These heavy metals in rice and wheat were also higher than control. The Pb, Cd and Zn contents in some plant samples were higher than the national guidance limit with higher over limit ratio existed in Pb and Cd.There existed obvious spatial distribution differences in heavy metal contents of roadside soils and crops. Along with the increased distance from highways, the Cd, Cr, Zn and Cu contents in soils decreased while Pb increased first and then decreased. And the five heavy metals in grains of rice and wheat all increased first and then decreased along with, the increased distance from highway. There were differences between the high value area of heavy metal content in soils and in crops. The area where the heavy metal was higher in soils hasn’t had necessarily higher heavy metal in crops.The heavy metals in rice and wheat along the express highway came from different pathways among which the atmosphere pathway couldn’t be neglected. Results from pot experiment and stable Pb isotope showed that part of Pb, Cd and Zn accumulated in rice were derived from the atmosphere via foliar uptake, while Cr and Cu were mainly from the soil via root uptake. In rice leaves, about 20% Pb,35% Cd and 60% Zn were from atmosphere. In rice grains, about 46% Pb and 41% Cd were derived from the atmosphere via foliar uptake. In rice stem,49% Zn were also derived from the atmosphere via foliar. The ratios of atmosphere-originated Pb, Cd and Zn in rice leaves, stem and grains decreased along with the increased distance from the highway. As for wheat, part of Cd and Zn in wheat came from atmosphere via foliar uptake, while Pb, Cr and Cu mainly came from the soil via root uptake. In wheat leaves, about 22% Cd and 29% Zn were from atmosphere. In wheat grains, about 21% Cd and 20% Zn were from the atmosphere. In wheat stem, Pb, Cd, Cr, Zn and Cu mainly came from absorption and transportation by roots. The ratios of atmosphere-originated Cd and Zn in rice leaves and grains decreased along with the increased distance from the highway.The traffic density had significant effect on the accumulation of heavy metals in soils. The accumulation of heavy metals in rice and wheat grains were affected by the traffic desenty, wind direction, soil pH and organic matter contents, and the total and available heavy metals contents. Accumulation coefficients of Pb, Cd, Zn and Cu in soils along the six sections had significant positive correlation with the traffic density. The influence of wind direction, soil pH and soil organic matter were releativly lower. The traffic fluxes were significantly positively correlated with the accumulation coefficients of Pb and Cd in rice and the accumulation coefficients of Cd and Zn in wheat grains. The accumulation of heavy metals in roadside rice and wheat was affected by the traffic density, wind direction, soil properties, and available contents. The most important factors for each heavy metals were different.The BP neural network has a strong ability of self-learning, self-organizing and self-adapting and a high function of nonlinear function mapping. So it will have high fitting precision and good generalization ability to apply the Bp neural network to the prediction and evaluation of the heavy metals distribution and content in soils and crops along with the express highway. And the BP neural network can fit and generate on the Pb, Cd, Zn and Cu content in soils, Pb and Cd contents in rice grains and Pb, Cd and Zn contents in wheat grains.