CN101968439B - Method for monitoring petroleum pollution in soil by utilizing community aboveground biomass indexes - Google Patents
Method for monitoring petroleum pollution in soil by utilizing community aboveground biomass indexes Download PDFInfo
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- CN101968439B CN101968439B CN 201010506511 CN201010506511A CN101968439B CN 101968439 B CN101968439 B CN 101968439B CN 201010506511 CN201010506511 CN 201010506511 CN 201010506511 A CN201010506511 A CN 201010506511A CN 101968439 B CN101968439 B CN 101968439B
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Abstract
The invention relates to a method for monitoring petroleum pollution in soil by utilizing community aboveground biomass indexes, belonging to the field of environmental pollution monitoring. The invention is realized by the following technical scheme: (1) establishing a plant/vegetation characteristic parameter forecasting model of total petroleum hydrocarbon content in the soil, which comprises the following steps: selecting a sampling point, measuring the plant/vegetation characteristic parameters of the sampling point, sampling the soil and measuring the total petroleum hydrocarbon content, and determining an optimal forecasting model of the total petroleum hydrocarbon content in the soil; and (2) computing the total petroleum hydrocarbon content in the soil of the monitoring point by utilizing the optimal forecasting model TPH=806.514-134.763ln(TBio), wherein TPH is the total petroleum hydrocarbon content in the soil, and the TBio is the total community aboveground biomass in the quadrat of which the area is 1m*1m. Compared with the traditional chemical analysis method of soil and plants, the invention has the advantages of simple and easy realization and low cost, can save a large amount of labor, financial resources and time and can realize the purpose of quickly monitoring the petroleum pollution in a large area.
Description
Technical field
The invention belongs to the environmental pollution monitoring field, be specifically related to utilize the oil pollution of soil in plant/vegetation characteristics parameter monitoring terrestrial ecosystems.
Background technology
Because global Petroleum Production, transportation, processing and utilization, oil pollution has become a general and serious environmental problem.After oil gets into terrestrial ecosystems, not only can produce considerable influence, and petroleum pollution can pass through food chain enrichment step by step in animal and plant body, finally get into human body, harm humans health composition, the 26S Proteasome Structure and Function of terrestrial ecosystems.
In the crude oil total production that the whole world is annual more than 30 hundred million tons, more than 3/4ths by the land field produces.The crude oil that China produces also major part comes from onshore oil field.Therefore, environmental monitoring how to carry out the terrestrial ecosystems oil pollution is effectively efficiently carried out the degraded and the repair of oil pollution for the diffusion of prevention oil pollution, and to administer oil pollution significant comprehensively.
At present, conventional soil, phytochemistry analysis are carried out in the environmental monitoring of land oil pollution more.But adopt soil and phytochemistry analytical approach monitoring land oil pollution; Particularly large-area pollution monitoring often needs a large amount of samplings, and sample analysis mensuration needs the testing tool of many costlinesses/precision; Test procedure is comparatively complicated, therefore is a consumption power, consumption wealth, work consuming time.
The change of phytomorph characteristic is the Critical policies that plant adapts to varying environment and resource.With the aerial part is example; Plant leaf blade is big, relatively more responsive to the environmental change organ of plasticity; Environment coerce the height that also usually limits plant, and colony's indexs such as the leaf area index of group, cover degree, ground biomass also can be made a response to environment-stress.The mensuration of these indexs is all comparatively easy, cost is also comparatively cheap.Therefore; The present invention is directed to the reed is the ecosystem of sociales, indexs such as reed ground biomass, the total ground biomass of the interior group of sample prescription in the screening individual plant reed number of blade, reed width of blade, reed length of blade, reed density, apparent leaf area index, reed height, reed cover degree, group's total cover-degree, the sample prescription.With these indexs is independent variable, and soil petroleum hydrocarbon content is that dependent variable is carried out regretional analysis, seeks the optimum prediction model of soil oil pollution.
Summary of the invention
The purpose of this invention is to provide a kind of method of utilizing the oil pollution of group ground biomass index monitoring soil, with overcome traditional soil and phytochemistry analytical approach monitoring soil oil pollution consumption power, consume wealth, deficiency consuming time.
The object of the invention is realized through following technical scheme:
1) set up soil total petroleum hydrocarbons content plant/vegetation characteristics parametric prediction model, may further comprise the steps:
(a) select sampled point: on the vegetation around the oil well, select 30 sampled points; The sample prescription that it is 1m * 1m that each sampled point is provided with 3 areas; Each sampling point apart from the distance of oil well between 30-130m; Sampled point does not suffer artificial interference, and vegetation is trampleed on, and sampled point does not exist non-oil pollution to coerce;
(b) measure sampled point plant/vegetation characteristics parameter: in 3 1m of each sampled point * 1m sample prescription, measure respectively and calculate each plant/vegetation characteristics parameter; Selected parameter comprises the total ground biomass of reed ground biomass and the interior group of 1m * 1m sample prescription in the individual plant reed number of blade, reed width of blade, reed length of blade, reed density, apparent leaf area index, reed height, reed cover degree, group's total cover-degree, the 1m * 1m sample prescription; Calculate the mean value of each plant of 3 sample prescriptions of each sampled point/vegetation characteristics parameter, as each plant of each sampled point/vegetation characteristics parameter value;
(c) soil sample and total petroleum hydrocarbons content are measured: in 3 sample prescriptions of each sampled point, respectively get the soil that the degree of depth is 0-30cm; The heavy 450-550g of soil sample amount; Adopt each sample prescription soil total petroleum hydrocarbons content of infrared spectrophotometric determination then; The mean value of 3 sample prescription soil total petroleum hydrocarbons contents of calculating sampling point obtains sampled point soil total petroleum hydrocarbons content, and the unit of soil total petroleum hydrocarbons content is mg/kg;
(d) confirm soil total petroleum hydrocarbons content optimum prediction model: adopt linearity, logarithm, inverse, secondary, three times, power, S type curve, exponential Function Model that the relation of each sampled point plant/vegetation characteristics parameter value and soil total petroleum hydrocarbons content is carried out match respectively; Confirm that the optimum prediction model is TPH=806.514-134.763ln (TBio), wherein TPH is the soil total petroleum hydrocarbons content, and the unit of soil total petroleum hydrocarbons content is mg/kg; TBio is that area is the total ground biomass of group in 1m * 1m sample prescription, and the unit of the total ground biomass of group is g/m
2
2) utilize optimum prediction Model Calculation monitoring point soil total petroleum hydrocarbons content: obtain after the soil total petroleum hydrocarbons content forecast model; Only the sample prescription that representative area is 1m * 1m is chosen in the monitoring point in the open air; Obtain the total ground biomass of group in the sample prescription then; And, calculate monitoring point soil total petroleum hydrocarbons content through forecast model TPH=806.514-134.763ln (TBio).
Beneficial effect of the present invention is: simple, with low cost with respect to traditional soil and phytochemistry analytical approach, and great amount of manpower, financial resources and time can be practiced thrift, and the large tracts of land fast monitored of oil pollution can be realized.
Description of drawings
Fig. 1 is total ground biomass of sampled point group and a soil total petroleum hydrocarbons content graph of relation in the described a kind of method of utilizing the oil pollution of group ground biomass index monitoring soil of the embodiment of the invention.
Embodiment
The described a kind of method of utilizing group's ground biomass index monitoring soil oil pollution of the embodiment of the invention may further comprise the steps:
1) set up soil total petroleum hydrocarbons content plant/vegetation characteristics parametric prediction model, may further comprise the steps:
(a) select sampled point: on the vegetation around the oil well, select 30 sampled points; The sample prescription that it is 1m * 1m that each sampled point is provided with 3 areas; Each sampling point apart from the distance of oil well between 30-130m; Sampled point does not suffer artificial interference, and vegetation is trampleed on, and sampled point does not exist non-oil pollution to coerce;
(b) measure sampled point plant/vegetation characteristics parameter: in 3 1m of each sampled point * 1m sample prescription, measure respectively and calculate each plant/vegetation characteristics parameter; Selected parameter comprises the total ground biomass of reed ground biomass and the interior group of 1m * 1m sample prescription in the individual plant reed number of blade, reed width of blade, reed length of blade, reed density, apparent leaf area index, reed height, reed cover degree, group's total cover-degree, the 1m * 1m sample prescription; Calculate the mean value of each plant of 3 sample prescriptions of each sampled point/vegetation characteristics parameter, as each plant of each sampled point/vegetation characteristics parameter value;
(c) soil sample and total petroleum hydrocarbons content are measured: in 3 sample prescriptions of each sampled point, respectively get the soil that the degree of depth is 0-30cm; The heavy 450-550g of soil sample amount; Adopt each sample prescription soil total petroleum hydrocarbons content of infrared spectrophotometric determination then; The mean value of 3 sample prescription soil total petroleum hydrocarbons contents of calculating sampling point obtains sampled point soil total petroleum hydrocarbons content, and the unit of soil total petroleum hydrocarbons content is mg/kg;
(d) confirm soil total petroleum hydrocarbons content optimum prediction model: adopt linearity, logarithm, inverse, secondary, three times, power, S type curve, exponential Function Model that the relation of each sampled point plant/vegetation characteristics parameter value and soil total petroleum hydrocarbons content is carried out match respectively; Confirm that the optimum prediction model is TPH=806.514-134.763ln (TBio), wherein TPH is the soil total petroleum hydrocarbons content, and the unit of soil total petroleum hydrocarbons content is mg/kg; TBio is that area is the total ground biomass of group in 1m * 1m sample prescription, and the unit of the total ground biomass of group is g/m
2
2) utilize optimum prediction Model Calculation monitoring point soil total petroleum hydrocarbons content: obtain after the soil total petroleum hydrocarbons content forecast model; Only the sample prescription that representative area is 1m * 1m is chosen in the monitoring point in the open air; Obtain the total ground biomass of group in the sample prescription then; And, calculate monitoring point soil total petroleum hydrocarbons content through forecast model TPH=806.514-134.763ln (TBio).
In the above-mentioned method of utilizing group's ground biomass index to monitor the soil oil pollution, being directed against with the reed is the ecosystem of sociales; Screened 10 kinds of indexs such as reed ground biomass in the individual plant reed number of blade, reed width of blade, reed length of blade, reed density, apparent leaf area index, reed height, reed cover degree, group's total cover-degree, the 1m * 1m sample prescription, the total ground biomass of the interior group of 1m * 1m sample prescription, wherein the assay method of each characteristic parameter index and calculating are as follows:
The individual plant reed number of blade (Leaf Number Per Reed, LeafNo): in 1m * 1m sample prescription, select 30 strain reeds at random, write down the number of blade of each strain reed, ask its mean value, be the individual plant reed number of blade of this sample prescription.
(Leaf Width ofReed, LeafW): in 1m * 1m sample prescription, select 10 strain reeds at random, measure the width of each all blade of strain reed, ask its mean value, be the reed width of blade of this sample prescription, the unit of reed width of blade is cm to the reed width of blade.
(Leaf Length of Reed, LeafL): in 1m * 1m sample prescription, select 10 strain reeds at random, measure the length of each all blade of strain reed, ask its mean value, be the reed length of blade of this sample prescription, the unit of reed length of blade is cm to the reed length of blade.
Reed density (Reed Density, RDen): statistics 1m * 1m (=1m
2) quantity of reed plant in the sample prescription, being the reed density of this sample prescription, the unit of reed density is strain/m
2
(Apparent Leaf Area Index, ALAI): the apparent leaf area index=individual plant reed number of blade * reed width of blade * reed length of blade * reed density, the unit of apparent leaf area index is cm to apparent leaf area index
2/ m
2
(Reed Height, RHei): in 1m * 1m sample prescription, select 30 strain reeds at random, measure the height of each strain reed, ask its mean value, be the reed height of this sample prescription, the unit of reed height is cm to the reed height.
(Reed Cover, RCov): adopt eye estimating method to measure reed cover degree in 1m * 1m sample prescription, the unit of reed cover degree is % to the reed cover degree.
(Total Cover of Vegetation, TCov): adopt eye estimating method to measure group's total cover-degree in 1m * 1m sample prescription, the unit of group's total cover-degree is % to group's total cover-degree.
Reed ground biomass (Aboveground Biomass ofReed in a 1m * 1mQuadrat in 1m * 1m sample prescription; RBio): the aerial part of all reeds in results 25cm * 25cm area in 1m * 1m sample prescription; Indoorly in 80 ℃ of baking ovens, dry by the fire 48h; Claim its weight and multiply by 16 that be reed ground biomass in 1m * 1m sample prescription, the unit of reed ground biomass is g/m with centesimal balance
2
Total ground biomass (the Total Aboveground Biomass of Vegetationin a 1m * 1m Quadrat of group in 1m * 1m sample prescription; TBio): adopt harvest method to measure the ground biomass (with the mensuration of reed ground biomass in the sample prescription) of each plant in the sample prescription; Ask its summation; Be the total ground biomass of group in the sample prescription, the unit of the total ground biomass of group is g/m
2
In the above-mentioned method of utilizing the oil pollution of group ground biomass index monitoring soil; When confirming the optimum prediction model, adopt function models such as linearity, logarithm, inverse, secondary, three times, power, S type curve, index that the relation of each plant/vegetation characteristics parameter and soil total petroleum hydrocarbons content has been carried out match respectively.Fitting result is seen table 1.
Each function model of table 1 is to the fitting result (n=30) of plant individual/COMMUNITY CHARACTERISTICS parameter
Wherein, the optimum prediction model of each plant/vegetation characteristics parameter is seen table 2.Relatively each forecast model can confirm that TPH=806.514-134.763ln (TBio) is the optimum prediction model, and its model is as shown in Figure 1.Wherein TPH is the soil total petroleum hydrocarbons content, and the unit of soil total petroleum hydrocarbons content is mg/kg; TBio is the total ground biomass of group in 1m * 1m sample prescription, and the unit of the total ground biomass of group is g/m
2The R of this forecast model
2Up to 0.701, the p value shows that also much smaller than 0.01 the degree of reliability of this model prediction is higher.
Each plant individual of table 2/COMMUNITY CHARACTERISTICS parameters optimal forecast model and check (n=30)
The present invention is with respect to traditional soil and phytochemistry analytical approach, and is simple, with low cost, can practice thrift great amount of manpower, financial resources and time, and can realize the large tracts of land fast monitored of oil pollution.
Claims (1)
1. a method of utilizing group's ground biomass index monitoring soil oil pollution is characterized in that, may further comprise the steps:
1) set up soil total petroleum hydrocarbons content plant/vegetation characteristics parametric prediction model, may further comprise the steps:
(a) select sampled point: on the vegetation around the oil well, select several sampled points; The sample prescription that it is 1m * 1m that each sampled point is provided with 3 areas; Each sampling point apart from the distance of oil well between 30-130m; Sampled point does not suffer artificial interference, and vegetation is trampleed on, and sampled point does not exist non-oil pollution to coerce;
(b) measure sampled point plant/vegetation characteristics parameter: in 3 1m of each sampled point * 1m sample prescription, measure respectively and calculate each plant/vegetation characteristics parameter; Selected parameter comprises the total ground biomass of reed ground biomass and the interior group of 1m * 1m sample prescription in the individual plant reed number of blade, reed width of blade, reed length of blade, reed density, apparent leaf area index, reed height, reed cover degree, group's total cover-degree, the 1m * 1m sample prescription; Calculate the mean value of each plant of 3 sample prescriptions of each sampled point/vegetation characteristics parameter, as each plant of each sampled point/vegetation characteristics parameter value;
(c) soil sample and total petroleum hydrocarbons content are measured: in 3 sample prescriptions of each sampled point, respectively get the soil that the degree of depth is 0-30cm; The heavy 450-550g of soil sample amount; Adopt each sample prescription soil total petroleum hydrocarbons content of infrared spectrophotometric determination then; The mean value of 3 sample prescription soil total petroleum hydrocarbons contents of calculating sampling point obtains sampled point soil total petroleum hydrocarbons content, and the unit of soil total petroleum hydrocarbons content is mg/kg;
(d) confirm soil total petroleum hydrocarbons content optimum prediction model: adopt linearity, logarithm, inverse, secondary, three times, power, S type curve, exponential Function Model that the relation of each sampled point plant/vegetation characteristics parameter value and soil total petroleum hydrocarbons content is carried out match respectively; Confirm that the optimum prediction model is TPH=806.514-134.763ln (TBio), wherein TPH is the soil total petroleum hydrocarbons content, and the unit of soil total petroleum hydrocarbons content is mg/kg; TBio is that area is the total ground biomass of group in 1m * 1m sample prescription, and the unit of the total ground biomass of group is g/m
2
2) utilize optimum prediction Model Calculation monitoring point soil total petroleum hydrocarbons content: obtain after the soil total petroleum hydrocarbons content forecast model; Only the sample prescription that representative area is 1m * 1m is chosen in the monitoring point in the open air; Obtain the total ground biomass of group in the sample prescription then; And, calculate monitoring point soil total petroleum hydrocarbons content through forecast model TPH=806.514-134.763ln (TBio).
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| CN106404448A (en) * | 2016-10-27 | 2017-02-15 | 辽宁石油化工大学 | Systematized sampling method of petroleum hydrocarbon contaminated site soil |
| CN109030069A (en) * | 2018-06-19 | 2018-12-18 | 中国林业科学研究院 | A kind of comprehensive sampling method of Alpine sandy land root system |
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| 8种花卉植物种子萌发对石油烃污染土壤的响应;彭胜巍等;《环境科学学报》;20090430;第29卷(第4期);786-790 * |
| 土壤环境污染的生物监测及其应用;邓晓等;《华南热带农业大学学报》;20061231;第12卷(第4期);50-53 * |
| 彭胜巍等.8种花卉植物种子萌发对石油烃污染土壤的响应.《环境科学学报》.2009,第29卷(第4期),786-690. |
| 邓晓等.土壤环境污染的生物监测及其应用.《华南热带农业大学学报》.2006,第12卷(第4期),第50-53页. |
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