AU2020100440A4 - The high-risk area identification method and differential processing method for land agricultural product producing areas - Google Patents
The high-risk area identification method and differential processing method for land agricultural product producing areas Download PDFInfo
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Abstract
Abstract The invention discloses a method for identifying a high-risk region of a land agricultural product producing area and a differential processing method. Basic data parameters for identifying the high risk region of the land agricultural product producing area are obtained based on combined cross analysis of multivariate factors, and differential multi-layer superposition analysis is carried out on the multivariate factor data parameters by using a geographic information system method to realize rapid and accurate identification of the high-risk region in the agricultural product producing area. 12As 9 Hg El Pb 0 Cr * Cd Z-H 1.4 t *~0.4 Root vegetables Fruit vegetables Leaf vegetables Average Figure 1 ~A ~ZiPb ~Cr A --Cd-.* Ig 10.00 -- 1.00 Root vegetables Fruit vegetables Leaf vegetables Figure 2 ~ Z As PTb ~Cr --- A-- Cd --- Hg 70 - 0.14 S60 - 0.12 30 - 0.00 20 -0.04 Sand soil Cated sand Loam Sub-clay Clay 00
Description
The high-risk area identification method and differential processing method for land agricultural product producing areas
Technical field
The invention relates to the technical field of agricultural and forestry planting and environmental treatment, in particular to a high-risk area identification technology for land agricultural product producing areas and a related treatment method.
Background art
Agricultural products are the source of human survival, and the quality of the environment directly affects the quality of agricultural products. Pollutants in agricultural products come .0 from the environment. Solving the problem of environmental quality and safety is the key to improve the quality and safety level of agricultural products. The premise of improving the quality and safety of agricultural products is to find out the boundaries and extent of high-risk areas in agricultural production areas.
In recent years, with the aggravation of industrial point source pollution and agricultural non.5 point source pollution, the content of certain elements or compounds in the soil increases, exceeding the purification capacity (capacity) of the soil environment, resulting in the degradation of soil environmental quality and the occurrence of phenomena affecting human (or organism) health and ecological risks. From April 2005 to December 2013, China carried out the first national soil pollution survey. The survey covered the land within China
Ό (excluding the Hong Kong Special Administrative Region, Macao Special Administrative Region and Taiwan). The survey sites covered all cultivated land, some woodland, grassland, unused land and construction land. The actual survey area was about 6.3 million square kilometers. The over-standard rate in the national soil is 16.1%, and the pollution type is mainly inorganic pollutants, with the number of over-standard points accounting for 82.8% of 15 all over-standard points. However, the traditional methods of in-laboratory analysis and onsite manual inspection can no longer meet the needs of people's life, government decisionmaking and social development. Rapid and accurate identification of high-risk areas in major agricultural production areas has become a hot front topic.
Summary of the Invention
The technical problem to be solved by the invention is to provide a high-risk area identification method and a differential treatment method for land agricultural product producing areas.
In order to solve the above technical problems, the technical scheme adopted by the present invention is as follows.
The invention relates to a method for identifying high-risk areas of land agricultural product producing areas and a differential processing method. The method obtains basic data parameters for identifying high-risk areas of land agricultural product producing areas based on combined cross analysis of multivariate factors, and performs differential multi-layer superposition analysis on the multivariate factor data parameters by using geographic information system means to realize rapid and accurate identification of high-risk areas in agricultural product producing areas. The multivariable factors include: source and
2020100440 23 Mar 2020 distribution factors of pollutants in the region, soil type factors of appearance and water system distribution in the region, sensitive population factors in the region, soil texture types and vertical configuration factors of soil in the region, plant species and distribution factors in the region, land use type factors in the region, population density factors in the region, and one or more combinations.
As a preferred technical scheme of the present invention, the geographic information system means include ArcGIS and MapGIS.
As a preferred technical scheme of the present invention, the analysis method for pollutant source distribution factors in the region is as follows:
.0 (1) Multi-source big data integration analysis: aiming at the target area, collecting pollution discharge permits through government departments, capturing pollution site locations through enterprise lists, pollutant attributes and pollutant high-concentration emission time, capturing major news events, socio-economic status and development trend data through the network, and retrieving multi-source big data from Chinese and foreign databases and documents fall .5 into the same geographic information distribution map of the area;
(2) spatial source tracing analysis of pollution sources: uniform sampling, purposive sampling and convenient rapid in-situ inspection are carried out under the methods of sample point distribution equalization detection and equalization treatment; According to the different impacts of different pollutants on the local environment, corresponding to the subsequent Ό pollutant reduction, contaminated soil remediation or differential treatment of selective utilization.
As a preferred technical scheme of the invention, in step 2, a soil quick-acting nutrient rapid detection spectrometer is adopted for the collected soil sample, and nitrate nitrogen, ammonium nitrogen, water-soluble phosphorus and Olsen-P large-amount elements of the 15 quick-acting phosphorus are detected and measured in 20 minutes; The toxic and harmful heavy metal elements such As As, Hg, Pb, Cd and Cr are rapidly detected on site for 30 minutes by using an in-situ rapid atomic spectrum detector.
As a preferred technical scheme of the invention, in step 2, high nitrogen and phosphorus accumulation affects water bodies, groundwater or surface water, causing eutrophication of 30 water bodies, and agricultural non-point source pollution prevention and control is carried out; For the soil polluted by heavy metals, the lightly polluted soil shall be classified and utilized, and the moderately and severely polluted soil shall be comprehensively repaired.
As a preferred technical scheme of the present invention, the analysis method for the soil type factors of the topography and water system distribution in the region is to classify and analyze the topography and water system distribution in the region, and to classify the distribution types of different elements for different types of plots in dry land, irrigated land, paddy field, mountain land and forest land.
As a preferred technical scheme of the present invention, the analysis method for sensitive crowd factors in the area is as follows:
Firstly, combining with the local industrial development planning, large-scale livestock and poultry farms, high input and high multiple cropping index planting areas, and the
2020100440 23 Mar 2020 distribution areas of sensitive pollution discharge factors in non-ferrous metal smelting industrial and mining enterprises, the corresponding types of pollutants discharged, the intensity and concentration of emissions from each source are investigated clearly, thus enlightening the future distribution of land use types and the design planning of the whole 5 region. In the analysis process, high-efficiency mixed time-space retrieval technology is used to reduce large data redundancy, improve data quality and reliability, and improve data mining analysis efficiency and accuracy. On this basis, based on the overlapping of the source of pollution with sensitive groups such as the elderly and children on the dietary structure of crops, the types of agricultural products consumed daily, the parameters of .0 exposure routes and multiple parameters, the agricultural planting structure is further superimposed, and a series of risk data of heavy metal intake of agricultural products, drinking water intake, respiratory intake and skin contact of the population in the target area are analyzed.
As a preferred technical scheme of the invention, the analysis method for the soil texture type .5 and soil vertical configuration factors in the region comprises the following steps of: dividing the high-risk distribution of agricultural production areas formed by different soil textures, types and vertical soil configurations, and dividing the difference of enrichment coefficients of heavy metals in soils of different texture types.
As a preferred technical scheme of the present invention, the analysis method for species and Ό distribution factors in the region is as follows:
(1) Based on the different enrichment coefficients of pollutants for different crops, the following analytical strategies are determined: high-risk areas are taken as remediation targets instead of high-concentration areas; Different crops have different characteristics in risk assessment of agricultural product producing areas, and corresponding to different regional risk control methods, different planting structures are adjusted accordingly, instead of removing all patches or high-concentration contaminated soil completely, so as to avoid ultra-high time and human, financial and material costs; On the basis of clarifying which types of crops have strong or weak enrichment capacity for which heavy metal elements, the risk distribution of various heavy metal elements ingested through agricultural products is 30 judged; Furthermore, according to the absorption and accumulation characteristics of different crops for heavy metal elements and the spatial distribution of heavy metal content in soil, suitable planting areas are selected to avoid environmental risks in the planting process of agricultural products.
(2) Based on the high-risk identification of agricultural production areas, the high-risk position distribution analysis of different crops through calculation is carried out. In order to control the application amount and cost of passivating agent, heavy metal passivating agent is applied in the critical period of crop growth. Remote sensing images are used to identify the fruit setting period, filling period and other key periods of crop growth. Inefficient passivating treatment in the early stage of crop growth is avoided, and heavy metal passivating agent is selected to control the activity of heavy metals in the fruit setting period or filling period.
As a preferred technical scheme of the invention, in step (1), for the high-risk areas of vegetable Cd non-carcinogenic elements, Chinese cabbage of cruciferous plants is easy to enrich Cd, pepper is easy to enrich Pb and Cd, tomatoes and celery are not easy to enrich 45 heavy metals, and safe planting areas with low Pb and Cd contents in soil are correspondingly
2020100440 23 Mar 2020 selected; Carcinogenic risk mainly comes from As, and the coefficient of As is set high when calculating the coefficient. According to the absorption and accumulation characteristics of heavy metals by different crops and the spatial distribution of heavy metals in soil, suitable planting areas are determined to avoid environmental risks in the process of planting agricultural products.
The technical scheme has the beneficial effects that the invention discloses a technical method for identifying high-risk regions of agricultural product producing areas on land other than fishery and other aquatic products, and the method can identify and divide the spatial distribution of high-risk regions of inorganic pollutants such as heavy metals, nitrogen, .0 phosphorus and the like from farmland in land to farmland of agricultural product producing areas at different regional scales such as counties, cities, provinces, watersheds and the like.
Using geographic information system (such as ArcGIS, MapGIS, etc.) to overlay and analyze different layers, the source distribution of pollutants, local landform and water system distribution, soil type, texture and soil body configuration, planting area, land use type, .5 population density and sensitive population in the region are analyzed in detail. Provide strong scientific and technological support for fast and accurate identification of high-risk areas in major agricultural production areas.
Brief description of drawings
Fig. 1 is a difference diagram of heavy metal enrichment coefficients of different types of Ό vegetables.
Fig. 2 is a difference chart of heavy metal element output fluxes of different types of vegetables.
Fig. 3 is a comparison chart of the total amount of heavy metals in soils with different textures.
Fig. 4 is a comparison chart of enrichment coefficients of heavy metal elements in different soil textures.
Fig. 5 is a comparative diagram of enrichment coefficients of heavy metal elements for different soil types.
Detailed description of the preferred embodiment
The following examples illustrate the present invention in detail. Various raw materials and various equipment used in the invention are conventional commercial products and can be directly obtained through market purchase.
In the following description of the embodiments, for purposes of explanation and not limitation, specific details such as specific system structures and techniques are set forth in 35 order to provide a thorough understanding of the embodiments of the present application.
However, it will be apparent to one skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of this application with unnecessary details.
2020100440 23 Mar 2020
It should be understood that when used in this specification and the appended claims, the term comprising indicates the presence of the described features, integers, steps, operations, elements, and/or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term and/or as used in the specification of this application and the appended claims refers to any and all possible combinations of one or more of the items listed in association, and includes such combinations.
As used in the specification of this application and the appended claims, the term if' may be interpreted as when or once or in response to determination or in response to .0 detection depending on the context. Similarly, the phrase if determined or if [described condition or event] is detected may be interpreted as meaning once determined or in response to determination or once [described condition or event] is detected or in response to detection of [described condition or event] depending on the context.
In addition, in the description of the specification of this application and the appended claims, .5 the terms first, second, third and the like are used for distinguishing description only and cannot be understood as indicating or implying relative importance.
Reference to one embodiment or some embodiments or the like described in the specification of this application means that a specific feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of this Ό application. Thus, the statements in one embodiment, in some embodiments, in other embodiments, in other embodiments, and the like appearing in different places in this specification do not necessarily all refer to the same embodiment, but rather mean one or more but not all embodiments, unless otherwise specifically emphasized in other ways. The terms including, including, having, and variations thereof all mean including, but not 15 limited to, unless otherwise specifically emphasized.
Example 1: Analysis of Source Distribution of Pollutants in the Region;
(1) The multi-source big data integration technology aims at a certain region and collects large data such as pollutant discharge permits, pollutant site locations captured by enterprise lists, pollutant attributes and the time of pollutant high concentration discharge through government departments. As well as a series of multi-source big data, such as network capture of major news events, social and economic status and development trend data, and Chinese and foreign database literature retrieval, fall into the same geographic information distribution map of the region.
(2) Uniform sampling, purposive sampling and convenient rapid in-situ inspection are carried 35 out by adopting a pollution source spatial source tracing method under the sampling point distribution equilibrium detection and homogenization treatment method. The collected soil samples are detected by a soil available nutrient rapid detection spectrometer, and a large number of elements such as nitrate nitrogen, ammonium nitrogen, water-soluble phosphorus, available phosphorus (Olsen-P) and the like are detected within 20 minutes; The toxic and 40 harmful heavy metal elements such As As, Hg, Pb, Cd, Cr, etc. are rapidly detected on site for 30 minutes by using an in-situ rapid atomic spectrum detector.
2020100440 23 Mar 2020
According to the different impacts of different pollutants on the local environment, subsequent pollutant reduction, remediation of contaminated soil or selective utilization are required. For example, the accumulation of high nitrogen and phosphorus affects water body, groundwater or surface water, resulting in eutrophication of water body, which requires prevention and control of agricultural non-point source pollution. Soil contaminated by heavy metals will eventually enter the food chain through crops planted on farmland and affect human health. Slightly contaminated soil needs land classification and utilization, and moderately and severely contaminated soil needs comprehensive remediation.
Example 2: Analysis of Geomorphology and Water System Distribution in the Region .0 Especially in hilly and mountainous areas, there are areas where mining land intersects with river valleys, and mountain runoff, farmland and water systems intersect, which are high-risk areas for heavy metals.(For example, in the land of fish and rice in the south, 40% of farmland in Hunan exceeds the standard, and Jiangxi is also very serious).Dryland, irrigated land, paddy field, mountain land, forest land and so on, each of them focuses on the .5 distribution type division of different elements. For example, Cd: the red area has a relatively high distribution concentration (average 400-500, while the general environmental standard is 0. several), while the green area has a relatively low distribution concentration. In areas with high Pb distribution, the source discharge of Cr is not too much.
Example 3: Analysis of Identification Distribution of Sensitive Factors in Region;
Ό (1) In combination with the local industrial development plan, the distribution areas of sensitive pollution discharge factors in areas such as large-scale livestock and poultry farms, high input and high multiple cropping index planting areas, non-ferrous metal smelting industrial and mining enterprises, etc. should be investigated clearly to find out the types of pollutants that may be discharged, and the intensity and concentration of emissions from each source. These will also reveal the future distribution of land use types and the design planning of the whole area. The high-efficiency hybrid time and space retrieval technology is applied to reduce large data redundancy, improve data quality and reliability, and improve data mining analysis efficiency and accuracy.
(2) The source of pollution can be overlapped with the dietary structure of sensitive groups (such as the elderly and children) on crops, the types of agricultural products they consume every day, the parameters of exposure routes, and the overlapping of agricultural planting structures, so as to analyze a series of risks such as heavy metals intake, drinking water intake, respiration intake, skin contact, etc. by the population in the local area. One county, for example, has 164 mineral smelting enterprises and over 400 small and large workshops.
Characteristics of mining and dressing enterprises: waste water is mainly discharged; characteristics of smelting enterprises: atmospheric transmission, with a relatively wide range, spreads to polluted areas along the wind direction to affect the surrounding poor agricultural products. It provides good instructions for later identification of high-risk areas.
Example 4: Analysis of Distribution of Agricultural Planting Types in the Region (Figures 140 2) (1) Different crops have different enrichment coefficients for pollutants. Therefore, high-risk areas should be targeted for remediation, rather than high-concentration areas. Use your money to the best of your ability. The risk assessment of different crops on agricultural
2020100440 23 Mar 2020 production areas is also different, and the risk control methods in these areas are also different. Different planting structures can be adjusted, instead of removing all the patches or high-concentration contaminated soil completely, otherwise it will take a long time and a high cost. Some plots in Hunan have exceeded the standard 100 times. Therefore, it is absolutely not advisable to restore it to the restoration within the Soil Environmental Quality Standard.
Through the research of this team, it is clear which types of crops have strong or weak enrichment ability for which heavy metal elements, and the distribution of risks of ingesting various heavy metal elements (such as Cd, Pb, etc.) through agricultural products can be .0 judged. For example, high-risk areas for Cd (non-carcinogenic elements) in vegetables, cabbage in cruciferous plants are easy to enrich Cd, and pepper is easy to enrich Pb and Cd. Therefore, safe planting areas with low contents of Pb and Cd in soil should be selected. The risk of cancer mainly comes from As. When calculating the coefficient, the coefficient of As is quite high. But tomatoes and celery are not easy to accumulate heavy metals. Therefore, we .5 can choose suitable planting areas according to the absorption and accumulation characteristics of heavy metals by different crops and the spatial distribution of heavy metals in soil to avoid environmental risks in the process of agricultural product planting.
The team's research shows that the output fluxes of heavy metals among different types of vegetables show great differences (except Hg), so residents have different intake of different Ό types of vegetables. The output fluxes of As, Cr and Cd elements are mainly root vegetables, while the output fluxes of Pb elements are mainly leaf vegetables, and the output fluxes of all elements of fruit vegetables are the lowest among all kinds of vegetables.
(2) The application of heavy metal passivator in the critical period of crop growth (such as fruit setting period or filling period) can identify this critical period through remote sensing 15 image. If we apply heavy metal passivator at the early stage of crop growth, the best we can do is to reduce the migration of heavy metals to the stem of the crop. Heavy metal enrichment does not directly affect food safety, so it has less impact on human health. However, in the fruit setting or filling stage, heavy metals will migrate to the edible parts of crops along the stems. Therefore, the fruit setting or filling stage is the key period in which the activity of 30 heavy metals is controlled. If you want to control the application amount and cost of passivating agent, you should choose to apply it during the growth period of crop seeds or fruits. Through high-risk identification of agricultural production areas, we analyzed the distribution of high-risk locations of different crop types and calculated results. For example, areas marked red are high-risk areas that have been preliminarily identified by us.
Example 5: Analysis of Soil Texture, Types and Vertical Soil Configuration Distribution in the Region
Different soil textures, types and vertical soil configurations also have great influence on the high-risk distribution of agricultural production areas. For example, the leaching risk of sandy soil is much higher than that of clay soil, while the soil body of full-body sandy soil in 40 vertical soil body configuration has higher leaching risk than the soil body stuck under sand.
However, the enrichment coefficients of heavy metals in soils of different textures and types are also very different (as shown in Figures 3, 4 and 5).
Example 6, Hebei Plain Analysis Example
2020100440 23 Mar 2020
Taking Hebei plain area as an example, the risks of soil total Cd, atmospheric dry and wet deposition Cd input flux, irrigation water Cd input flux, fertilizer Cd input flux and soil total Cd were analyzed and identified respectively. Provide strong scientific support for fast and accurate identification of high-risk areas in major agricultural production areas.
The above-mentioned embodiments are only used to illustrate the technical scheme of the present invention, not to limit it; Although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those skilled in the art that it can still modify the technical scheme described in the foregoing embodiments or replace some of its technical features equally. However, these modifications or substitutions .0 do not cause the essence of the corresponding technical scheme to depart from the spirit and scope of the technical scheme of each embodiment of the present invention, and should be included in the protection scope of the present invention.
Claims (10)
- (1) Based on the different enrichment coefficients of pollutants for different crops, the following analytical strategies are determined: high-risk areas are taken as remediation targets instead of high-concentration areas; Different crops have different characteristics in risk assessment of agricultural product producing areas, and corresponding to different regional risk control methods, different planting structures are adjusted accordingly, instead of removing all patches or high-concentration contaminated soil completely, so as to avoid ultra-high time and human, financial and material costs; On the basis of clarifying which types of crops have strong or weak enrichment capacity for which heavy metal elements, the risk distribution of various heavy metal elements ingested through agricultural products is judged; Furthermore, according to the absorption and accumulation characteristics of2020100440 23 Mar 2020 different crops for heavy metal elements and the spatial distribution of heavy metal content in soil, suitable planting areas are selected to avoid environmental risks in the planting process of agricultural products.(1) Multi-source big data integration analysis: aiming at the target area, collecting pollution discharge permits through government departments, capturing pollution site locations through enterprise lists, pollutant attributes and pollutant high-concentration emission time, capturing major news events, socio-economic status and development trend data through the network, and retrieving multi-source big data from Chinese and foreign databases and documents fall into the same geographic information distribution map of the area;1 .The high-risk area identification method and differential processing method for land agricultural product producing areas, characterized in that: the method obtains basic data parameters for identifying high-risk areas of land agricultural products producing areas based on combined cross analysis of multivariate factors, and performs differential multi-layer superposition analysis on the multivariate factor data parameters by using geographic information system means to realize rapid and accurate identification of high-risk areas in agricultural products producing areas; The multivariable factors include: source and distribution factors of pollutants in the region, soil type factors of appearance and water system distribution in the region, sensitive population factors in the region, soil texture types and vertical configuration factors of soil in the region, plant species and distribution factors in the region, land use type factors in the region, population density factors in the region, and one or more combinations.
- (2) Based on the high-risk identification of agricultural production areas, the high-risk position distribution analysis of different crops through calculation is carried out. In order to control the application amount and cost of passivating agent, heavy metal passivating agent is applied in the critical period of crop growth. Remote sensing images are used to identify the fruit setting period, filling period and other key periods of crop growth. Inefficient passivating treatment in the early stage of crop growth is avoided, and heavy metal passivating agent is selected to control the activity of heavy metals in the fruit setting period or filling period.(2) spatial source tracing analysis of pollution sources: uniform sampling, purposive sampling and convenient rapid in-situ inspection are carried out under the methods of sample point distribution equalization detection and equalization treatment; According to the different impacts of different pollutants on the local environment, corresponding to the subsequent pollutant reduction, contaminated soil remediation or differential treatment of selective utilization.2. The high-risk area identification method and differential processing method for land agricultural product producing areas according to claim 1, characterized in that: the geographic information system means include ArcGIS and MapGIS.
- 3. The high-risk area identification method and differential processing method for land agricultural product producing areas according to claim 1, characterized in that: the analysis method for pollutant source distribution factors in the area is as follows:
- 4. The high-risk area identification method and differential processing method for land agricultural product producing areas according to claim 3, characterized in that: in step 2, soil samples collected are detected by a soil available nutrient rapid detection spectrometer, and results of nitrate nitrogen, ammonium nitrogen, water soluble phosphorus and available phosphorus Olsen-P massive elements are detected within 20 minutes; The toxic and harmful heavy metal elements such As As, Hg, Pb, Cd and Cr are rapidly detected on site for 30 minutes by using an in-situ rapid atomic spectrum detector.
- 5. The high-risk area identification method and differential processing method for land agricultural product producing areas according to claim 3, characterized in that: in step 2, the accumulation of high nitrogen and phosphorus affects water body, groundwater or surface water, causing eutrophication of water body, and agricultural non-point source pollution prevention and control is carried out;For the soil polluted by heavy metals, the lightly2020100440 23 Mar 2020 polluted soil shall be classified and utilized, and the moderately and severely polluted soil shall be comprehensively repaired.
- 6. The high-risk area identification method and differential processing method for land agricultural product producing areas according to claim 1, characterized in that: the analysis method for the soil type factors of the topography and water system distribution in the area is to classify and analyze the landform and water system distribution in the area, and to classify the distribution types of different elements for different types of plots in dry land, irrigated land, paddy field, mountain land and forest land.
- 7. The high-risk area identification method and differential processing method for land agricultural product producing areas according to claim 1, characterized in that: the analysis method for sensitive crowd factors in the area is as follows:Firstly, combining with the local industrial development planning, large-scale livestock and poultry farms, high input and high multiple cropping index planting areas, and the distribution areas of sensitive pollution discharge factors in non-ferrous metal smelting industrial and mining enterprises, the corresponding types of pollutants discharged, the intensity and concentration of emissions from each source are investigated clearly, thus enlightening the future distribution of land use types and the design planning of the whole region.In the analysis process, high-efficiency mixed time-space retrieval technology is used to reduce large data redundancy, improve data quality and reliability, and improve data mining analysis efficiency and accuracy. On this basis, based on the overlapping of the source of pollution with sensitive groups such as the elderly and children's dietary structure on crops, types of agricultural products consumed daily, exposure pathway parameters and multiple parameters, the agricultural planting structure situation is further superimposed, and a series of risk data on heavy metal intake of agricultural products, drinking water intake, respiratory intake and skin contact of the population in the target area are analyzed.
- 8. The high-risk area identification method and differential processing method for land agricultural product producing areas according to claim 1, characterized in that: the analysis method for soil texture types and soil vertical configuration factors in the areas is to divide the high-risk distribution of agricultural product producing areas formed by different soil textures, types and vertical soil configurations, and divide the difference in enrichment coefficients of heavy metals for soils of different texture types.
- 9. The high-risk area identification method and differential processing method for land agricultural product producing areas according to claim 1, characterized in that: the analysis method for species and distribution factors in the region is as follows:
- 10. The high-risk area identification method and differential processing method for land agricultural product producing areas according to claim 9, characterized in that: in step 1, for high-risk areas of vegetable Cd non-carcinogenic elements, Chinese cabbage of cruciferous plants is easy to enrich Cd, peppers are easy to enrich Pb and Cd, tomatoes and celery are not easy to enrich heavy metals, and safe planting areas with low Pb and Cd contents in soil are correspondingly selected; Carcinogenic risk mainly comes from As, and the coefficient of As is set high when calculating the coefficient. According to the absorption and accumulation characteristics of heavy metals by different crops and the spatial distribution of heavy metals in soil, suitable planting areas are determined to avoid environmental risks in the process of planting agricultural products.
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