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Ecological risk assessment on heavy metals in soils: Use of soil diffuse reflectance mid-infrared Fourier-transform spectroscopy

View Article: PubMed Central - PubMed

ABSTRACT

The bioavailability of heavy metals in soil is controlled by their concentrations and soil properties. Diffuse reflectance mid-infrared Fourier-transform spectroscopy (DRIFTS) is capable of detecting specific organic and inorganic bonds in metal complexes and minerals and therefore, has been employed to predict soil composition and heavy metal contents. The present study explored the potential of DRIFTS for estimating soil heavy metal bioavailability. Soil and corresponding wheat grain samples from the Yangtze River Delta region were analyzed by DRIFTS and chemical methods. Statistical regression analyses were conducted to correlate the soil spectral information to the concentrations of Cd, Cr, Cu, Zn, Pb, Ni, Hg and Fe in wheat grains. The principal components in the spectra influencing soil heavy metal bioavailability were identified and used in prediction model construction. The established soil DRIFTS-based prediction models were applied to estimate the heavy metal concentrations in wheat grains in the mid-Yangtze River Delta area. The predicted heavy metal concentrations of wheat grain were highly consistent with the measured levels by chemical analysis, showing a significant correlation (r2 > 0.72) with acceptable root mean square error RMSE. In conclusion, DRIFTS is a promising technique for assessing the bioavailability of soil heavy metals and related ecological risk.

No MeSH data available.


Spatial distribution of ecological risks assessment of Cd in arable soils.Cd* denotes the predicted Cd concentration of wheat grain. The grade division was based on the Chinese Maximum Permissible Concentration of Cd, for which five grades are classified. The “Grade IV” (color denoted by orange) means that the corresponding sites should be early-warned as “Not suitable for planting wheat”, and “Grade V” (color denoted by red) should be early-warned as “obviously unsafe for wheat production”. The map was created by software ArcGIS 9.3.
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f3: Spatial distribution of ecological risks assessment of Cd in arable soils.Cd* denotes the predicted Cd concentration of wheat grain. The grade division was based on the Chinese Maximum Permissible Concentration of Cd, for which five grades are classified. The “Grade IV” (color denoted by orange) means that the corresponding sites should be early-warned as “Not suitable for planting wheat”, and “Grade V” (color denoted by red) should be early-warned as “obviously unsafe for wheat production”. The map was created by software ArcGIS 9.3.

Mentions: The established models in the Table 1 can be used to predict the concentrations of heavy metals in wheat by scanning the soil with a MIR device. In reference with the food safety standards for heavy metals in wheat grain, the most outstanding and significant application of the models is to assess the risk (and issue early warning) of the bioavailability of heavy metals in soil. The present study developed and tested such an approach by introducing the Chinese food safety standards for heavy metals in wheat grain36 and the models in Table 1 to the prediction and assessment of heavy metal concentrations in wheat grain. Taking Cd as an example, the soil DRIFTS spectral information was applies in the wheat grain heavy metal concentration prediction model (Table 1) to assess the ecological risk of Cd in soils (154 soil samples) of the Yangtze River Delta region. The results are presented in Fig. 3. The established approach divided the soils into five grades corresponding to the categorized concentration levels of Cd in wheat grain. The detailed process was narrated in Supporting Information. According to the assessment results, the soils in the Suzhou-Wuxi region (Middle Yangtze River Delta area) were not safe in terms of Cd level for wheat production. The Suzhou-Wuxi local area was then grouped into “Grade V”, meaning “obviously unsafe for wheat production”. In fact, the Suzhou-Wuxi region is a concentrated manufacture industry zone. The natural environment has been suffering from severe heavy metal pollution. Previous investigations had recognized that Cd pollution in the region was related to industrial emissions2830.


Ecological risk assessment on heavy metals in soils: Use of soil diffuse reflectance mid-infrared Fourier-transform spectroscopy
Spatial distribution of ecological risks assessment of Cd in arable soils.Cd* denotes the predicted Cd concentration of wheat grain. The grade division was based on the Chinese Maximum Permissible Concentration of Cd, for which five grades are classified. The “Grade IV” (color denoted by orange) means that the corresponding sites should be early-warned as “Not suitable for planting wheat”, and “Grade V” (color denoted by red) should be early-warned as “obviously unsafe for wheat production”. The map was created by software ArcGIS 9.3.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5304163&req=5

f3: Spatial distribution of ecological risks assessment of Cd in arable soils.Cd* denotes the predicted Cd concentration of wheat grain. The grade division was based on the Chinese Maximum Permissible Concentration of Cd, for which five grades are classified. The “Grade IV” (color denoted by orange) means that the corresponding sites should be early-warned as “Not suitable for planting wheat”, and “Grade V” (color denoted by red) should be early-warned as “obviously unsafe for wheat production”. The map was created by software ArcGIS 9.3.
Mentions: The established models in the Table 1 can be used to predict the concentrations of heavy metals in wheat by scanning the soil with a MIR device. In reference with the food safety standards for heavy metals in wheat grain, the most outstanding and significant application of the models is to assess the risk (and issue early warning) of the bioavailability of heavy metals in soil. The present study developed and tested such an approach by introducing the Chinese food safety standards for heavy metals in wheat grain36 and the models in Table 1 to the prediction and assessment of heavy metal concentrations in wheat grain. Taking Cd as an example, the soil DRIFTS spectral information was applies in the wheat grain heavy metal concentration prediction model (Table 1) to assess the ecological risk of Cd in soils (154 soil samples) of the Yangtze River Delta region. The results are presented in Fig. 3. The established approach divided the soils into five grades corresponding to the categorized concentration levels of Cd in wheat grain. The detailed process was narrated in Supporting Information. According to the assessment results, the soils in the Suzhou-Wuxi region (Middle Yangtze River Delta area) were not safe in terms of Cd level for wheat production. The Suzhou-Wuxi local area was then grouped into “Grade V”, meaning “obviously unsafe for wheat production”. In fact, the Suzhou-Wuxi region is a concentrated manufacture industry zone. The natural environment has been suffering from severe heavy metal pollution. Previous investigations had recognized that Cd pollution in the region was related to industrial emissions2830.

View Article: PubMed Central - PubMed

ABSTRACT

The bioavailability of heavy metals in soil is controlled by their concentrations and soil properties. Diffuse reflectance mid-infrared Fourier-transform spectroscopy (DRIFTS) is capable of detecting specific organic and inorganic bonds in metal complexes and minerals and therefore, has been employed to predict soil composition and heavy metal contents. The present study explored the potential of DRIFTS for estimating soil heavy metal bioavailability. Soil and corresponding wheat grain samples from the Yangtze River Delta region were analyzed by DRIFTS and chemical methods. Statistical regression analyses were conducted to correlate the soil spectral information to the concentrations of Cd, Cr, Cu, Zn, Pb, Ni, Hg and Fe in wheat grains. The principal components in the spectra influencing soil heavy metal bioavailability were identified and used in prediction model construction. The established soil DRIFTS-based prediction models were applied to estimate the heavy metal concentrations in wheat grains in the mid-Yangtze River Delta area. The predicted heavy metal concentrations of wheat grain were highly consistent with the measured levels by chemical analysis, showing a significant correlation (r2 > 0.72) with acceptable root mean square error RMSE. In conclusion, DRIFTS is a promising technique for assessing the bioavailability of soil heavy metals and related ecological risk.

No MeSH data available.