As the awareness of environment andimproved , the has got the people’s attention. Green food is an kind of nutritious food which is safe, non-polluting and high-quality. Green food comes from good ecological environment. The environment quality of the producing area is one of factors to impact , so the guarantee on the soil quality is essential to the sustainable development of green food.In this paper, 91 samples have been collected in Daxing District in Beijing. According to environment standard of the green food area (NY/T391-2000),content monitoring was done of soil heavy metals (Cr, Ni, Cu, Zn, As, Hg, Pb),soil nutrients(pH, organic matter, alkali-hydrolyzable N, available K, available P). The spatial variability and Kriging interpolation have been done using the combined with . In addition, the heavy metal and nutrient content were assessed by the method of pollution index and fuzzy comprehensive evaluation. The spatial analysis and Kriging interpolation of the indexes have been done similarly. The evaluation results helped the drawing of the spatial distribution map in which the heavy metal pollution and nutrient level can be revealed. The results could provide support for the development of high-efficiency agriculture.(1) The results of geostatistical analysis showed that, eight heavy metals had the stable content and they had middle-variability. the semivarigram for Cr, Ni, Cu, As, Hg well fitted by exponential model, the semivarigram for Zn, Pb well fitted by spherical and gaussian models. From the model curves, we knew that Zn in the study area has a constant variation and could not been interpolated. The spatial variability of Ni, Hg, Pb was produced by random factors, the variability of Cd was controlled mainly by structural factors, random and structure factors effected Cr, Cu, As at the same time.(2) The distribution map of the heavy metals showed that, in the area Dapiying and Fengheying in Caiyu which connected with Tongzhou District, the content of Cr, Ni, Cu, As, Cd, Pb was higher than other areas. The probable reason was sewage irrigation .The polluted river–Fenghe flowed through here. The content of Hg in Huangcun was much higher which was brought by people’s living garbage. In addition to Cd, the content of the other six heavy metals was less than the limit value in NY/T391-2000.The development of green food in this soil was feasible.(3) The distribution map of the heavy metal indexes showed that, with the exception of Cd, the single pollution indexes of Cr, Ni, Cu, As, Pb, Hg were less than 1, Daxing District was clean. The index of Cd was more than 1 in the area of Caiyu southeast,Xihongmen north and Lixian east. It showed that the soil in these areas was polluted by Cd , the area was no longer suitable for the development of green food. The integrated pollution index of heavy metals proved that safe soil in Daxing District reached 893.33 km2, accounting for 89.1 percent of the total area. The areas belonged alert level was 109.57km2, accounting for 10.9%. The index distribution map of Cd was similar to the integrated pollution index ,which proved Cd was the primary pollution factor in the region.(4) The spatial variability analysis of nutrient showed that, organic matter, alkali-hydrolyzable N, available K, available P and IFI(Integrated Fertility Index)had medium variability except that pH had weak variability. The variation coefficient of these elements was small and close to each other, which proved they were stable in soil. The semivarigram for pH, organic matter, alkali-hydrolyzable N, available K well fitted by exponential model, but available P was spherical models.From the model curves,we knew that the spatial variability of pH, organic matter, alkali-hydrolyzable N, available K was produced by random and structural factors, the variability of IFI was controlled mainly by random factors. Their range were also more than 3 km and they had correlation to a degree.(5) The distribution map of soil nutrient showed that, the soil in Daxing District was neutral subalkalic. Soil organic matter levels was high and general quality, accounting for 47.9% and 52.1% of the total area respectively. The level of N belonged to general grade, accounting for 94.1% of total area. K levels in the whole district was general, the content was 80～120 mg ? kg-1 . 82.0% of soil was ok for the P content. 17.9% was pretty good. The value of IFI belonged to the3 grade and 4 grade. The soil of grade 1 were small, sharing less than 1% of the total area.(6) Comparison and test results showed that, Kriging interpolation could make the data more normal. The errors between interpolation and measured results was less than 10%,so the mapping was meaningful and it could provide the suggestion for the development of green food in Daxing District in Beijing.
Frequent Buyer Deals!
Buy 4 Get 1 Free
Customer Care Center
Exclusive Order Taking Hotline
- The Stability and Decentralized Stabilization Control for Generalized System
- Pyridine-2, 6-bis（oxazolino） （pybox） is a C2-symmetri…
- Semi-Active Flutter Suppression of a Wing Using Magnetorheological Dampers
- Ecological Study on the Soil Animal Community at the Natural Reserve of FuNiu Mountain
- Study on the Improvement of the Damage of ODD Laser Diode
- Modern Esthetic Education and the Development of Students’ Sensibility
- Dichloroacetic Acid(DCA)-induced DNA Strand Breaks and Modulation of Glutathione in HepG2 Cell
- Biblical Archetypes in D.H. Lawrence’s Novels
- The Study of the Existential “Freedom” Theme in Fowles’s Early Novels
- Rheumatism of Joint Pain’s the Grade of TCM Symptom,Nail Fold Microcirculation and Hemorheology
AHP Capital structure China commercial bank Commercial banks core competence corporate governance countermeasure countermeasures credit risk Development Development Strategy economic growth evaluation Factor Analysis FDI Foreign Direct Investment game theory human capital Index system industrial structure Innovation Internal Control Listed companies Listed Company management marketing marketing strategy Model performance Performance evaluation Performance Management Project Management Real Estate research Risk risk management strategy Supply chain Supply chain management sustainable development SWOT analysis system urbanization value chain