CN108596481A - A kind of reduction of greenhouse gas discharge Default Risk method and system - Google Patents
A kind of reduction of greenhouse gas discharge Default Risk method and system Download PDFInfo
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Abstract
The invention discloses a kind of reduction of greenhouse gas discharge Default Risk method and system.This method includes：The discharge capacity for determining food Life cycle greenhouse gases is denoted as greenhouse gas emission data；It determines food production economic well-being of workers and staff amount, is denoted as economic well-being of workers and staff data；According to greenhouse gas emission data, the probability density function of greenhouse gas emission data is determined；According to food production economic well-being of workers and staff data, the probability density function of economic well-being of workers and staff data is determined；According to the probability density function of the probability density function of greenhouse gas emission data and economic well-being of workers and staff data, the joint probability density function of greenhouse gas emission and economic well-being of workers and staff is determined；The default risk of food Life cycle greenhouse gas emissions is determined according to joint probability density function.Reduction of greenhouse gas discharge Default Risk method and system provided by the invention can reflect the correlativity between greenhouse gas emission and economic well-being of workers and staff, keep the estimation to the emission reduction of greenhouse gases more accurate.
Description
Technical field
The present invention relates to amblent air temperature fields, more particularly to a kind of reduction of greenhouse gas discharge Default Risk method and are
System.
Background technology
As global warming trend is increasingly sharpened, more and more countries and regions start to greenhouse gas emission into
Row control, the current reduction of greenhouse gas discharge target in China are greenhouse gas emission intensity targets, i.e.,：The greenhouse of the year two thousand twenty per GDP
Whether gas emissions are 82% in 2015, and be more than in the prior art state-set standard for greenhouse gas emissions
Judge, can not reflect the relationship between greenhouse gas emission and economic well-being of workers and staff, this makes to reduction of greenhouse gas discharge assessment not
Accurately.
Invention content
The object of the present invention is to provide a kind of reduction of greenhouse gas discharge Default Risk method and system, this method and system
It can reflect the correlativity between greenhouse gas emission and economic well-being of workers and staff, keep the estimation to the emission reduction of greenhouse gases more accurate
Really.
To achieve the above object, the present invention provides following schemes：
A kind of food reduction of greenhouse gas discharge Default Risk method, the method includes：
The discharge capacity for determining food Life cycle greenhouse gases is denoted as greenhouse gas emission data；
It determines food production economic well-being of workers and staff amount, is denoted as economic well-being of workers and staff data；
According to the greenhouse gas emission data, the probability density function of the greenhouse gas emission data is determined；
According to the food production economic well-being of workers and staff data, the probability density function of economic well-being of workers and staff data is determined；
According to the probability density letter of the probability density function of the greenhouse gas emission data and the economic well-being of workers and staff data
Number, determines the joint probability density function of the greenhouse gas emission and economic well-being of workers and staff；
The promise breaking wind of the food Life cycle greenhouse gas emissions is determined according to the joint probability density function
Danger.
Optionally, the discharge capacity of the determining food Life cycle greenhouse gases, specifically includes：
According to
Calculate the discharge capacity ψ of food Life cycle greenhouse gasesLCA, wherein GiIt is given birth to for unit area the i-th class crops
Order the greenhouse gas emissions in period, SijFor the cultivated area of the i-th class crops in j-th of region, OiFor the i-th class crops institute
The discharge capacity of the unit material used for agriculture production process percent of greenhouse gases of consumption, gkFor unit area kth class energy crop Life Cycle
The greenhouse gas emissions of phase, skjFor the cultivated area of kth class energy crop in j-th of region, okFor kth class energy crop institute
The discharge capacity of the unit material used for agriculture production process percent of greenhouse gases of consumption, pljFor in the domestic birds and animals feeding process of unit quantity
Feed dosage, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, EFlFor the ammonia of a ruminant domestic animal
Annual emissions, o'lFor the greenhouse gas emission in the unit material used for agriculture production process of l class domestic birds and animals live boxes consumption
Amount, θ are that unit weight feed converts into crops life cycle greenhouse gas emissions, and a is the number of species of crops, and b is area
The quantity in domain, c are the number of species of energy crop, and d is the quantity of domestic birds and animals.
Optionally, described according to greenhouse gas emission data, determine the probability density letter of the greenhouse gas emission data
Number, specifically includes：
The quality of the emissions data is evaluated using more criterion evaluation methods；
The credit rating of the emissions data is assessed using fuzzy mathematics theory；
Monte Carlo simulation is carried out to the emissions data according to the credit rating of the emissions data, obtains emissions data
Probability density function.
Optionally, the determining food production economic well-being of workers and staff amount, specifically includes：
According toCalculate food
Object production economy income amount ψGDP, wherein UiFor the i-th class cereal or the unit price of vegetables, ukFor the unit price of kth class bioenergy, u 'l
For l classes meat, the unit price of egg or milk, YijFor the yield of the i-th class cereal or vegetables in j-th of region, ykjFor j-th of region
The yield of middle kth class bioenergy, y 'ljFor the yield of l classes meat, egg or milk in j-th of region, DiFor the i-th class unit plane
Chemical fertilizer expense consumed in the crops of product or quantity, dkFor the chemical fertilizer expense consumed in kth class energy crop, d 'lFor l classes
The chemical fertilizer Meteorological of feed conversion crop, E needed for the poultry or livestock of Board LotiFor the i-th class unit area or quantity agriculture
Energy expenditure consumed in crop, ekFor the energy expenditure consumed in kth class unit area or amount of energy crop, e 'lFor l
Energy expenditure consumed in class and poultry or livestock, ZirThe chemical fertilizer expense and the energy are removed for the i-th class unit area crops
The outer Master Cost consumed of source expense, zkr'The chemical fertilizer expense and the energy cost are removed for kth class unit area energy crop
With outer consumed Master Cost, SijFor the cultivated area of the i-th class crops in j-th of region, skjFor kth in j-th of region
The cultivated area of class energy crop, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, a is the kind of crops
Class quantity, b are the quantity in region, and c is the number of species of energy crop, and d is the quantity of domestic birds and animals.
Optionally, described according to the food production economic well-being of workers and staff data, determine that the probability of the economic well-being of workers and staff data is close
Function is spent, is specifically included：
The quality of the economic well-being of workers and staff data is evaluated using more criterion evaluation methods；
The credit rating of the economic well-being of workers and staff data is assessed using fuzzy mathematics theory；
Monte Carlo simulation is carried out to the economic well-being of workers and staff data according to the credit rating of the economic well-being of workers and staff data, is obtained
The probability density function of economic well-being of workers and staff data.
Optionally, the probability of the probability density function and the economic well-being of workers and staff according to the greenhouse gas emission data
Density function determines the joint probability density function of the greenhouse gas emission and economic well-being of workers and staff, specifically includes：
The greenhouse gas emission is examined to obtain institute with the correlation of the Joint Distribution of economic well-being of workers and staff using Cupla functions
State the joint probability distribution function of greenhouse gas emission and economic well-being of workers and staff；
According to the joint probability distribution function of the greenhouse gas emission and economic well-being of workers and staff, the greenhouse gas emission data
Probability density function and the economic well-being of workers and staff probability density function, determine the connection of the greenhouse gas emission and economic well-being of workers and staff
Close probability density function.
Optionally, described that the food Life cycle greenhouse gas emission is determined according to the joint probability density function
The default risk of amount, specifically includes：
Obtain greenhouse gas emission intensity overall control index；
According to R=∫ ∫H≥LfX,Y(x, y) dxdy calculates greenhouse gas emission Default Probability R, whereinL is institute
State greenhouse gas emission intensity overall control index.
The present invention also provides a kind of food reduction of greenhouse gas discharge default risks to determine system, the system comprises：
Greenhouse gas emissions determination unit, the discharge capacity for determining food Life cycle greenhouse gases, is denoted as temperature
Room gas emissions data；
Economic well-being of workers and staff amount determination unit is denoted as economic well-being of workers and staff data for determining food production economic well-being of workers and staff amount；
First probability density function determination unit, for according to the greenhouse gas emission data, determining the greenhouse gas
The probability density function of body emissions data；
Second probability density function determination unit, for according to the food production economic well-being of workers and staff data, determining economic receive
The probability density function of beneficial data；
Joint probability density function determination unit, for according to the probability density functions of the greenhouse gas emission data and
The probability density function of the economic well-being of workers and staff data determines the joint probability density letter of the greenhouse gas emission and economic well-being of workers and staff
Number；
Default risk determination unit, for determining the food Life cycle temperature according to the joint probability density function
The default risk of room gas emissions.
Optionally, the room gas emissions determination unit, specifically includes：
Room gas emissions determination subelement is used for basis
Calculate the discharge capacity ψ of food Life cycle greenhouse gasesLCA, wherein GiIt is given birth to for unit area the i-th class crops
Order the greenhouse gas emissions in period, SijFor the cultivated area of the i-th class crops in j-th of region, OiFor the i-th class crops institute
The discharge capacity of the unit material used for agriculture production process percent of greenhouse gases of consumption, gkFor unit area kth class energy crop Life Cycle
The greenhouse gas emissions of phase, skjFor the cultivated area of kth class energy crop in j-th of region, okFor kth class energy crop institute
The discharge capacity of the unit material used for agriculture production process percent of greenhouse gases of consumption, pljFor in the domestic birds and animals feeding process of unit quantity
Feed dosage, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, EFlFor the ammonia of a ruminant domestic animal
Annual emissions, o'lFor the greenhouse gas emission in the unit material used for agriculture production process of l class domestic birds and animals live boxes consumption
Amount, θ are that unit weight feed converts into crops life cycle greenhouse gas emissions, and a is the number of species of crops, and b is area
The quantity in domain, c are the number of species of energy crop, and d is the quantity of domestic birds and animals；
The economic well-being of workers and staff amount determination unit, specifically includes：
Economic well-being of workers and staff amount determination subelement is used for basis
Calculate food life
Produce economic well-being of workers and staff amount ψGDP, wherein UiFor the i-th class cereal or the unit price of vegetables, ukFor the unit price of kth class bioenergy, u 'lIt is
The unit price of l classes meat, egg or milk, YijFor the yield of the i-th class cereal or vegetables in j-th of region, ykjFor kth in j-th of region
The yield of class bioenergy, y 'ljFor the yield of l classes meat, egg or milk in j-th of region, DiFor the i-th class unit area or number
Chemical fertilizer expense consumed in the crops of amount, dkFor the chemical fertilizer expense consumed in kth class energy crop, d 'lFor l class units
The chemical fertilizer Meteorological of feed conversion crop, E needed for the poultry or livestock of amountiFor the i-th class unit area or quantity crops institute
The energy expenditure of consumption, ekFor the energy expenditure consumed in kth class unit area or amount of energy crop, e 'lFor l classes and family
Energy expenditure consumed in fowl or domestic animal, ZirThe chemical fertilizer expense and the energy expenditure are removed for the i-th class unit area crops
Outer consumed Master Cost, zkr'For kth class unit area energy crop in addition to the chemical fertilizer expense and the energy expenditure institute
The Master Cost of consumption, SijFor the cultivated area of the i-th class crops in j-th of region, skjFor the kth class energy in j-th of region
The cultivated area of crop, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, a is the species number of crops
Amount, b are the quantity in region, and c is the number of species of energy crop, and d is the quantity of domestic birds and animals.
Optionally, the first probability density function determination unit, specifically includes：
Emissions data quality evaluation subelement, the quality for evaluating the emissions data using more criterion evaluation methods；
Second credit rating assesses subelement, the quality etc. for assessing the emissions data using fuzzy mathematics theory
Grade；
First probability density function determination subelement is used for the credit rating according to the emissions data to the discharge number
According to Monte Carlo simulation is carried out, the probability density function of emissions data is obtained；
The second probability density function determination unit, specifically includes：
Economic well-being of workers and staff data quality accessment subelement, for evaluating the economic well-being of workers and staff data using more criterion evaluation methods
Quality；
Second credit rating assesses subelement, the quality for assessing the economic well-being of workers and staff data using fuzzy mathematics theory
Grade；
Second probability density function determination subelement is used for the credit rating according to the economic well-being of workers and staff data to the warp
Avail data of helping carries out Monte Carlo simulation, obtains the probability density function of economic well-being of workers and staff data；
The joint probability density function determination unit, specifically includes：
Joint probability distribution function determination subelement, for examining the greenhouse gas emission and warp using Cupla functions
The correlation of the Joint Distribution for income of helping, obtains the joint probability distribution function of the greenhouse gas emission and economic well-being of workers and staff；
Joint probability density function determination subelement, for general according to the greenhouse gas emission and combining for economic well-being of workers and staff
Rate distribution function, the greenhouse gas emission data probability density function and the economic well-being of workers and staff probability density function, really
The joint probability density function of the fixed greenhouse gas emission and economic well-being of workers and staff；
Default risk determination unit, specifically includes：
Con trolling index obtains subelement, for obtaining greenhouse gas emission intensity overall control index；
Default risk determination subelement, for according to R=∫ ∫H≥LfX,YIt is general that (x, y) dxdy calculates greenhouse gas emission promise breaking
Rate R, whereinL is the greenhouse gas emission intensity overall control index.
According to specific embodiment provided by the invention, the invention discloses following technique effects：Greenhouse provided by the invention
Gas abatement Default Risk method and system carry out food greenhouse gas emissions, food production economic well-being of workers and staff respectively
Accounting and Data Quality Analysis, probability density function, the food of food greenhouse gas emissions are determined using Monte Carlo simulation
Production economy income probability density function, by the way that greenhouse gas emissions and economic well-being of workers and staff are carried out joint risk analysis, instead
The relationship of the fluctuating change and reduction of greenhouse gas discharge realization of goal of future city resident's food reinforcement is reflected, and using promise breaking
Risk analysis method predicts default risk, realizes more accurately pre- to the default risk of food reduction of greenhouse gas discharge
It surveys.
Description of the drawings
It in order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will be to institute in embodiment
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the present invention
Example, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 is food reduction of greenhouse gas discharge Default Risk method flow diagram of the embodiment of the present invention；
Fig. 2 is that food reduction of greenhouse gas discharge default risk of the embodiment of the present invention determines system structure diagram.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The object of the present invention is to provide a kind of reduction of greenhouse gas discharge Default Risk method and system, this method and system
It can reflect the correlativity between greenhouse gas emission and economic well-being of workers and staff, keep the estimation to the emission reduction of greenhouse gases more accurate
Really.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, below in conjunction with the accompanying drawings and specific real
Applying mode, the present invention is described in further detail.
Fig. 1 is food reduction of greenhouse gas discharge Default Risk method flow diagram of the embodiment of the present invention, as shown in Figure 1, food
Object reduction of greenhouse gas discharge Default Risk method is as follows：
Step 101：The discharge capacity for determining food Life cycle greenhouse gases is denoted as greenhouse gas emission data；
Step 102：It determines food production economic well-being of workers and staff amount, is denoted as economic well-being of workers and staff data；
Step 103：According to the greenhouse gas emission data, the probability density letter of the greenhouse gas emission data is determined
Number；
Step 104：According to the food production economic well-being of workers and staff data, the probability density function of economic well-being of workers and staff data is determined；
Step 105：According to the general of the probability density function of the greenhouse gas emission data and the economic well-being of workers and staff data
Rate density function determines the joint probability density function of the greenhouse gas emission and economic well-being of workers and staff；
Step 106：The food Life cycle greenhouse gas emissions are determined according to the joint probability density function
Default risk.
Wherein, step 101 specifically includes：
According to
Calculate the discharge capacity ψ of food Life cycle greenhouse gasesLCA, wherein GiIt is given birth to for unit area the i-th class crops
Order the greenhouse gas emissions in period, SijFor the cultivated area of the i-th class crops in j-th of region, OiFor the i-th class crops institute
The discharge capacity of the unit material used for agriculture production process percent of greenhouse gases of consumption, gkFor unit area kth class energy crop Life Cycle
The greenhouse gas emissions of phase, skjFor the cultivated area of kth class energy crop in j-th of region, okFor kth class energy crop institute
The discharge capacity of the unit material used for agriculture production process percent of greenhouse gases of consumption, pljFor in the domestic birds and animals feeding process of unit quantity
Feed dosage, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, EFlFor the ammonia of a ruminant domestic animal
Annual emissions, o'lFor the greenhouse gas emission in the unit material used for agriculture production process of l class domestic birds and animals live boxes consumption
Amount, θ are that unit weight feed converts into crops life cycle greenhouse gas emissions, and a is the number of species of crops, and b is area
The quantity in domain, c are the number of species of energy crop, and d is the quantity of domestic birds and animals.
Emission analysis to food life cycle greenhouse gases includes following process, and specific calculation formula is as shown in table 1：
A) rice terrace greenhouse gases (GHG) discharge；
B) farm machinery GHG is discharged；
C) the GHG discharges in material used for agriculture production process；
D) ruminant GHG direct emissions；
E) poultry/poultry live box consumption feed converts into crops GHG discharges；
F) fertilized soil GHG is discharged.
1 food life cycle GHG of table discharges accounting method
Influence of the different greenhouse gases for climate warming simultaneously differs.In order to characterize above-mentioned influence degree, IPCC is public
The cloth reduced value of different greenhouse gases and CO2 greenhouse effects, is indicated (i.e. with global warming potential：Global warming
Potential, abbreviation GWP).Specifically, the global warming potential of the CO2 under 100 years levels is the global warming of 1, CH4
The global warming potential that potentiality is 25, N2O is 298.Therefore, because the greenhouse effects caused by GHG discharges can pass through the complete of GHG
Ball heats potentiality and discharge capacity is calculated：
Wherein, GWI represents the food life cycle Global climate change potentiality under certain function unit；MiRepresent certain work(
The amount of the i-th class GHG discharges under energy unit；GWPiRepresent the Global climate change potentiality of the i-th class GHG.
Step 102 specifically includes：According to
Calculate food life
Produce economic well-being of workers and staff amount ψGDP, wherein UiFor the i-th class cereal or the unit price of vegetables, ukFor the unit price of kth class bioenergy, u 'lIt is
The unit price of l classes meat, egg or milk, YijFor the yield of the i-th class cereal or vegetables in j-th of region, ykjFor kth in j-th of region
The yield of class bioenergy, y 'ljFor the yield of l classes meat, egg or milk in j-th of region, DiFor the i-th class unit area or number
Chemical fertilizer expense consumed in the crops of amount, dkFor the chemical fertilizer expense consumed in kth class energy crop, d 'lFor l class units
The chemical fertilizer Meteorological of feed conversion crop, E needed for the poultry or livestock of amountiFor the i-th class unit area or quantity crops institute
The energy expenditure of consumption, ekFor the energy expenditure consumed in kth class unit area or amount of energy crop, e 'lFor l classes and family
Energy expenditure consumed in fowl or domestic animal, ZirThe chemical fertilizer expense and the energy expenditure are removed for the i-th class unit area crops
Outer consumed Master Cost, zkr'For kth class unit area energy crop in addition to the chemical fertilizer expense and the energy expenditure institute
The Master Cost of consumption, SijFor the cultivated area of the i-th class crops in j-th of region, skjFor the kth class energy in j-th of region
The cultivated area of crop, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, a is the species number of crops
Amount, b are the quantity in region, and c is the number of species of energy crop, and d is the quantity of domestic birds and animals.
Step 103 specifically includes：
The quality of the emissions data is evaluated using more criterion evaluation methods；
The credit rating of the emissions data is assessed using fuzzy mathematics theory；
Monte Carlo simulation is carried out to the emissions data according to the credit rating of the emissions data, obtains emissions data
Probability density function.
Step 104 specifically includes：
The quality of the economic well-being of workers and staff data is evaluated using more criterion evaluation methods；
The credit rating of the economic well-being of workers and staff data is assessed using fuzzy mathematics theory；
Monte Carlo simulation is carried out to the economic well-being of workers and staff data according to the credit rating of the economic well-being of workers and staff data, is obtained
The probability density function of economic well-being of workers and staff data.
The present invention is used when determining the probability density function of the greenhouse gas emission data, economic well-being of workers and staff data
The method that Data Quality Analysis (DQI), fuzzy mathematics theory and Monte Carlo simulation are combined, Data Quality Analysis are a kind of
More criterion evaluation methods, the error for assessing data.Data Quality Analysis is by comprehensive assessment data in source, acquisition side
Formula, representative, the time limit, the features of 6 aspects such as geo-relevance and technology correlation assess the quality of data.Wherein, often
A factor by a numerical value come characterize data the case where, such as indicated with 1~5 numerical value.Wherein 1 represents the quality of data most
Poor (maximum uncertainty), 5 represent the quality of data preferably (minimum uncertainty).Based on quality testing method, number
It can be by quality testing matrix according to quality.Set Pair Analysis is a kind of systematic analytic method.The main thought of Set Pair Analysis is
By " same ", " different ", three kinds of negation relationship, establish two set Pair Analysis.In our current research, " same " and negation are considered
The relationship being to determine, and " different " is considered as uncertain relationship, can assess its data matter by the method for fuzzy mathematics
Measure grade.Details are as follows for specific method：
Assuming that set A is quality testing matrix, set B is rank, then the evaluations matrix of set A is usedIt indicates.Pair Analysis between set A and set B can use following formula
To characterize.
Wherein,K=1,2 ..., 6；B is the grade of the quality of data；It is set AkWith the Pair Analysis of B；
WithIt is the fuzzy coefficient of " different " index, whereinJ is that phase negation coefficient usually takes -1；N presenting sets pair
Total quantity；Sk0BeNumber of elements identical with grade B in set；Fk1It representsIn set with grade B+1
Identical number of elements；Fk2It representsNumber of elements identical with grade B+2 in set；Pk3It representsSet
In be more than grade B+2 number of elements.
Above formula can quantitatively compare identical, the different and opposite relationship between the quality of data and opinion rating.WhenWithWhen numerical value between value [0,1], the size of the numerical value can reflect identical or opposite degree.The result of above formula is bigger
The possibility for representing the set close to grade B is bigger.Therefore quality testing can determine the range of data fluctuations variation, such as
Shown in table 2.
2 quality testing transformation coefficient of table
By the Monte Carlo simulation of certain sample size, the probability density function of data can be generated, which can be with
For analyzing the variation range of data.Monte Carlo simulation can be according to the probability density function of different distribution simulation data.
By taking β is distributed as an example, the probability density function of data is as follows：
Wherein, α and β represents the form parameter of distribution function, and a and b represent the interval value chosen.Probability density function is set
Believe section [e.g., (5%, 95%)], can reflect the distributed area of data.
Step 105 specifically includes：
The greenhouse gas emission is examined to obtain institute with the correlation of the Joint Distribution of economic well-being of workers and staff using Cupla functions
State the joint probability distribution function of greenhouse gas emission and economic well-being of workers and staff；
According to the joint probability distribution function of the greenhouse gas emission and economic well-being of workers and staff, the greenhouse gas emission data
Probability density function and the economic well-being of workers and staff probability density function, determine the connection of the greenhouse gas emission and economic well-being of workers and staff
Close probability density function.
(such as two relevant stochastic variable X and Y：Agricultural product greenhouse gas emission and economic well-being of workers and staff), it is respective
Cumulative distribution function (Cumulative Distribution Functions, abbreviation CDF) can be expressed as FX(X ＜ x) and FY
(Y ＜ y).So, the joint probability distribution function C (u, v) of existence anduniquess between the two, passes through C (u, v)=FX,Y(x, y)=
[FX(x),FY(y)] it indicates, wherein FX,Y(x, y) represents variable X and the joint CDF functions of Y, and u and v respectively represent the tired of X and Y
Product distribution function.So, the joint probability density function of two stochastic variables is (i.e.：fX,Y(x, y)) it can be characterized as：
fX,Y(x, y)=c (FX(x),FY(y))fX(x)fY(y)
In order to preferably capture the tail-dependence coefficient of correlated variables Joint Distribution, a plurality of types of Copula functions can provide
Correlation test.For example, environmental area often using the Copula functions of Archimedean races (such as：Gumbel
Copula, Frankcopula and Clayton copula).By assessing the rank correlation coefficient of Copula functions (i.e.：θ) come
The suitability of verification method.Specifically, in order to choose, more to meet both food greenhouse gas emission and economic well-being of workers and staff related
Property Copula functions, select the historical data composition ordered series of numbers u of food greenhouse gas emissions and economic well-being of workers and staff1And v1.With
Spearman related coefficients are (i.e.：ρn) analysis and assessment correlation between the two.Choose the closest ρ of θnCopula functions come
Embody both food greenhouse gas emission and economic well-being of workers and staff correlative character.
Gumbel copula Joint Distributions models can be characterized as
Clayton Copula Joint Distributions models can be characterized as
Frank Copula Joint Distributions models can be characterized as formula
Wherein：N is sample size；RiIt is set u1In some element u1iIn set u1In sequence；SiIt is set v1In some
Element v1iIn set v1In sequence.
Step 106 specifically includes：
Obtain greenhouse gas emission intensity overall control index；
According to R=∫ ∫H≥LfX,Y(x, y) dxdy calculates greenhouse gas emission Default Probability R, whereinL is institute
State greenhouse gas emission intensity overall control index.
The default risk of greenhouse gas emission intensity can be characterized by the probability that exceeded event occurs, i.e.,：Future food
Object GHG discharges intensity is (i.e.：) it is more than the probability that country or local GHG discharge intensity Target of Total Pollutant Amount Control, with ginseng
Number RGHGTo indicate.
R=P (H >=L)=∫ ∫H≥LfX,Y(x, y) dxdy, wherein R represents future food GHG discharge intensity default risks；L
Represent country/place GHG discharge intensity Target of Total Pollutant Amount Control.
Reduction of greenhouse gas discharge Default Risk method provided by the invention is to food greenhouse gas emissions, food production
Economic well-being of workers and staff carries out accounting and Data Quality Analysis respectively, and the general of food greenhouse gas emissions is determined using Monte Carlo simulation
Rate density function, food production economic well-being of workers and staff probability density function, by carrying out greenhouse gas emissions and economic well-being of workers and staff
Joint risk analysis reflects fluctuating change and the reduction of greenhouse gas discharge realization of goal of future city resident's food reinforcement
Relationship, and default risk is predicted using Default Risk method, it realizes to food reduction of greenhouse gas discharge promise breaking wind
Danger more accurately prediction.
The present invention also provides a kind of food reduction of greenhouse gas discharge default risks to determine that system, Fig. 2 are the embodiment of the present invention
Food reduction of greenhouse gas discharge default risk determines system structure diagram, as shown in Fig. 2, the system comprises：
Greenhouse gas emissions determination unit 201, the discharge capacity for determining food Life cycle greenhouse gases, is denoted as
Greenhouse gas emission data；
Economic well-being of workers and staff amount determination unit 202 is denoted as economic well-being of workers and staff data for determining food production economic well-being of workers and staff amount；
First probability density function determination unit 203, for according to the greenhouse gas emission data, determining the greenhouse
The probability density function of gas emissions data；
Second probability density function determination unit 204, for according to the food production economic well-being of workers and staff data, determining economic
The probability density function of avail data；
Joint probability density function determination unit 205, for the probability density letter according to the greenhouse gas emission data
The probability density function of number and the economic well-being of workers and staff data, determines that the joint probability of the greenhouse gas emission and economic well-being of workers and staff is close
Spend function；
Default risk determination unit 206, for determining the full Life Cycle of the food according to the joint probability density function
The default risk of phase greenhouse gas emissions.
Wherein, the room gas emissions determination unit 201, specifically includes：
Room gas emissions determination subelement is used for basis
Calculate the discharge capacity ψ of food Life cycle greenhouse gasesLCA, wherein GiIt is given birth to for unit area the i-th class crops
Order the greenhouse gas emissions in period, SijFor the cultivated area of the i-th class crops in j-th of region, OiFor the i-th class crops institute
The discharge capacity of the unit material used for agriculture production process percent of greenhouse gases of consumption, gkFor unit area kth class energy crop Life Cycle
The greenhouse gas emissions of phase, skjFor the cultivated area of kth class energy crop in j-th of region, okFor kth class energy crop institute
The discharge capacity of the unit material used for agriculture production process percent of greenhouse gases of consumption, pljFor in the domestic birds and animals feeding process of unit quantity
Feed dosage, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, EFlFor the ammonia of a ruminant domestic animal
Annual emissions, o'lFor the greenhouse gas emission in the unit material used for agriculture production process of l class domestic birds and animals live boxes consumption
Amount, θ are that unit weight feed converts into crops life cycle greenhouse gas emissions, and a is the number of species of crops, and b is area
The quantity in domain, c are the number of species of energy crop, and d is the quantity of domestic birds and animals；
The economic well-being of workers and staff amount determination unit 202, specifically includes：
Economic well-being of workers and staff amount determination subelement is used for basis
Calculate food life
Produce economic well-being of workers and staff amount ψGDP, wherein UiFor the i-th class cereal or the unit price of vegetables, ukFor the unit price of kth class bioenergy, u 'lIt is
The unit price of l classes meat, egg or milk, YijFor the yield of the i-th class cereal or vegetables in j-th of region, ykjFor kth in j-th of region
The yield of class bioenergy, y 'ljFor the yield of l classes meat, egg or milk in j-th of region, DiFor the i-th class unit area or number
Chemical fertilizer expense consumed in the crops of amount, dkFor the chemical fertilizer expense consumed in kth class energy crop, d 'lFor l class units
The chemical fertilizer Meteorological of feed conversion crop, E needed for the poultry or livestock of amountiFor the i-th class unit area or quantity crops institute
The energy expenditure of consumption, ekFor the energy expenditure consumed in kth class unit area or amount of energy crop, e 'lFor l classes and family
Energy expenditure consumed in fowl or domestic animal, ZirThe chemical fertilizer expense and the energy expenditure are removed for the i-th class unit area crops
Outer consumed Master Cost, zkr'For kth class unit area energy crop in addition to the chemical fertilizer expense and the energy expenditure institute
The Master Cost of consumption, SijFor the cultivated area of the i-th class crops in j-th of region, skjFor the kth class energy in j-th of region
The cultivated area of crop, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, a is the species number of crops
Amount, b are the quantity in region, and c is the number of species of energy crop, and d is the quantity of domestic birds and animals.
The first probability density function determination unit 203, specifically includes：
Emissions data quality evaluation subelement, the quality for evaluating the emissions data using more criterion evaluation methods；
Second credit rating assesses subelement, the quality etc. for assessing the emissions data using fuzzy mathematics theory
Grade；
First probability density function determination subelement is used for the credit rating according to the emissions data to the discharge number
According to Monte Carlo simulation is carried out, the probability density function of emissions data is obtained；
The second probability density function determination unit 204, specifically includes：
Economic well-being of workers and staff data quality accessment subelement, for evaluating the economic well-being of workers and staff data using more criterion evaluation methods
Quality；
Second credit rating assesses subelement, the quality for assessing the economic well-being of workers and staff data using fuzzy mathematics theory
Grade；
Second probability density function determination subelement is used for the credit rating according to the economic well-being of workers and staff data to the warp
Avail data of helping carries out Monte Carlo simulation, obtains the probability density function of economic well-being of workers and staff data；
The joint probability density function determination unit 205, specifically includes：
Joint probability distribution function determination subelement, for examining the greenhouse gas emission and warp using Cupla functions
The correlation of the Joint Distribution for income of helping, obtains the joint probability distribution function of the greenhouse gas emission and economic well-being of workers and staff；
Joint probability density function determination subelement, for general according to the greenhouse gas emission and combining for economic well-being of workers and staff
Rate distribution function, the greenhouse gas emission data probability density function and the economic well-being of workers and staff probability density function, really
The joint probability density function of the fixed greenhouse gas emission and economic well-being of workers and staff；
Default risk determination unit 206, specifically includes：
Con trolling index obtains subelement, for obtaining greenhouse gas emission intensity overall control index；
Default risk determination subelement, for according to R=∫ ∫H≥LfX,YIt is general that (x, y) dxdy calculates greenhouse gas emission promise breaking
Rate R, whereinL is the greenhouse gas emission intensity overall control index.
Reduction of greenhouse gas discharge default risk provided by the invention determines system to food greenhouse gas emissions, food production
Economic well-being of workers and staff carries out accounting and Data Quality Analysis respectively, and the general of food greenhouse gas emissions is determined using Monte Carlo simulation
Rate density function, food production economic well-being of workers and staff probability density function, by carrying out greenhouse gas emissions and economic well-being of workers and staff
Joint risk analysis reflects fluctuating change and the reduction of greenhouse gas discharge realization of goal of future city resident's food reinforcement
Relationship, and default risk is predicted using Default Risk method, it realizes to food reduction of greenhouse gas discharge promise breaking wind
Danger more accurately prediction.
Each embodiment is described by the way of progressive in this specification, the highlights of each of the examples are with other
The difference of embodiment, just to refer each other for identical similar portion between each embodiment.For system disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so description is fairly simple, related place is said referring to method part
It is bright.
Principle and implementation of the present invention are described for specific case used herein, and above example is said
The bright method and its core concept for being merely used to help understand the present invention；Meanwhile for those of ordinary skill in the art, foundation
The thought of the present invention, there will be changes in the specific implementation manner and application range.In conclusion the content of the present specification is not
It is interpreted as limitation of the present invention.
Claims (10)
1. a kind of food reduction of greenhouse gas discharge Default Risk method, which is characterized in that the method includes：
The discharge capacity for determining food Life cycle greenhouse gases is denoted as greenhouse gas emission data；
It determines food production economic well-being of workers and staff amount, is denoted as economic well-being of workers and staff data；
According to the greenhouse gas emission data, the probability density function of the greenhouse gas emission data is determined；
According to the food production economic well-being of workers and staff data, the probability density function of economic well-being of workers and staff data is determined；
According to the probability density function of the probability density function of the greenhouse gas emission data and the economic well-being of workers and staff data, really
The joint probability density function of the fixed greenhouse gas emission and economic well-being of workers and staff；
The default risk of the food Life cycle greenhouse gas emissions is determined according to the joint probability density function.
2. food reduction of greenhouse gas discharge Default Risk method according to claim 1, which is characterized in that the determination
The discharge capacity of food Life cycle greenhouse gases, specifically includes：
According to
Calculate the discharge capacity ψ of food Life cycle greenhouse gasesLCA, wherein GiFor unit area the i-th class crops life cycle
Greenhouse gas emissions, SijFor the cultivated area of the i-th class crops in j-th of region, OiIt is consumed by the i-th class crops
The discharge capacity of unit material used for agriculture production process percent of greenhouse gases, gkFor the temperature of unit area kth class energy crop life cycle
Room gas emissions, skjFor the cultivated area of kth class energy crop in j-th of region, okIt is consumed by kth class energy crop
The discharge capacity of unit material used for agriculture production process percent of greenhouse gases, pljFor the feed in the domestic birds and animals feeding process of unit quantity
Dosage, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, EFlFor the ammonia year discharge of a ruminant domestic animal
Amount, o'lFor the greenhouse gas emissions in the unit material used for agriculture production process of l class domestic birds and animals live boxes consumption, θ is single
Position weight feed converts into crops life cycle greenhouse gas emissions, and a is the number of species of crops, and b is the quantity in region,
C is the number of species of energy crop, and d is the quantity of domestic birds and animals.
3. food reduction of greenhouse gas discharge Default Risk method according to claim 1, which is characterized in that the basis
Greenhouse gas emission data determine the probability density function of the greenhouse gas emission data, specifically include：
The quality of the emissions data is evaluated using more criterion evaluation methods；
The credit rating of the emissions data is assessed using fuzzy mathematics theory；
Monte Carlo simulation is carried out to the emissions data according to the credit rating of the emissions data, obtains the general of emissions data
Rate density function.
4. food reduction of greenhouse gas discharge Default Risk method according to claim 1, which is characterized in that the determination
Food production economic well-being of workers and staff amount, specifically includes：
According toCalculate food life
Produce economic well-being of workers and staff amount ψGDP, wherein UiFor the i-th class cereal or the unit price of vegetables, ukFor the unit price of kth class bioenergy, u 'lIt is
The unit price of l classes meat, egg or milk, YijFor the yield of the i-th class cereal or vegetables in j-th of region, ykjFor kth in j-th of region
The yield of class bioenergy, y 'ljFor the yield of l classes meat, egg or milk in j-th of region, DiFor the i-th class unit area or number
Chemical fertilizer expense consumed in the crops of amount, dkFor the chemical fertilizer expense consumed in kth class energy crop, d 'lFor l class units
The chemical fertilizer Meteorological of feed conversion crop, E needed for the poultry or livestock of amountiFor the i-th class unit area or quantity crops institute
The energy expenditure of consumption, ekFor the energy expenditure consumed in kth class unit area or amount of energy crop, el' it is l classes and family
Energy expenditure consumed in fowl or domestic animal, ZirThe chemical fertilizer expense and the energy expenditure are removed for the i-th class unit area crops
Outer consumed Master Cost, zkr'For kth class unit area energy crop in addition to the chemical fertilizer expense and the energy expenditure institute
The Master Cost of consumption, SijFor the cultivated area of the i-th class crops in j-th of region, skjFor the kth class energy in j-th of region
The cultivated area of crop, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, a is the species number of crops
Amount, b are the quantity in region, and c is the number of species of energy crop, and d is the quantity of domestic birds and animals.
5. food reduction of greenhouse gas discharge Default Risk method according to claim 1, which is characterized in that the basis
The food production economic well-being of workers and staff data determine the probability density function of the economic well-being of workers and staff data, specifically include：
The quality of the economic well-being of workers and staff data is evaluated using more criterion evaluation methods；
The credit rating of the economic well-being of workers and staff data is assessed using fuzzy mathematics theory；
Monte Carlo simulation is carried out to the economic well-being of workers and staff data according to the credit rating of the economic well-being of workers and staff data, obtains economy
The probability density function of avail data.
6. food reduction of greenhouse gas discharge Default Risk method according to claim 1, which is characterized in that the basis
The probability density function of the probability density function and the economic well-being of workers and staff of the greenhouse gas emission data determines the greenhouse gas
Body discharges the joint probability density function with economic well-being of workers and staff, specifically includes：
The greenhouse gas emission is examined to obtain the temperature with the correlation of the Joint Distribution of economic well-being of workers and staff using Cupla functions
The joint probability distribution function of room gas discharge and economic well-being of workers and staff；
According to the joint probability distribution function of the greenhouse gas emission and economic well-being of workers and staff, the greenhouse gas emission data it is general
The probability density function of rate density function and the economic well-being of workers and staff determines that the greenhouse gas emission and combining for economic well-being of workers and staff are general
Rate density function.
7. food reduction of greenhouse gas discharge Default Risk method according to claim 1, which is characterized in that the basis
The joint probability density function determines the default risk of the food Life cycle greenhouse gas emissions, specifically includes：
Obtain greenhouse gas emission intensity overall control index；
According to R=∫ ∫H≥LfX,Y(x, y) dxdy calculates greenhouse gas emission Default Probability R, whereinL is the greenhouse
Gas discharges intensity overall control index.
8. a kind of food reduction of greenhouse gas discharge default risk determines system, which is characterized in that the system comprises：
Greenhouse gas emissions determination unit, the discharge capacity for determining food Life cycle greenhouse gases are denoted as greenhouse gas
Body emissions data；
Economic well-being of workers and staff amount determination unit is denoted as economic well-being of workers and staff data for determining food production economic well-being of workers and staff amount；
First probability density function determination unit, for according to the greenhouse gas emission data, determining the greenhouse gases row
Put the probability density function of data；
Second probability density function determination unit, for according to the food production economic well-being of workers and staff data, determining economic well-being of workers and staff number
According to probability density function；
Joint probability density function determination unit, for according to the probability density function of the greenhouse gas emission data and described
The probability density function of economic well-being of workers and staff data determines the joint probability density function of the greenhouse gas emission and economic well-being of workers and staff；
Default risk determination unit, for determining food Life cycle greenhouse gas according to the joint probability density function
The default risk of body discharge capacity.
9. food reduction of greenhouse gas discharge default risk according to claim 8 determines system, which is characterized in that
The room gas emissions determination unit, specifically includes：
Room gas emissions determination subelement is used for basis
Calculate the discharge capacity ψ of food Life cycle greenhouse gasesLCA, wherein GiFor unit area the i-th class crops life cycle
Greenhouse gas emissions, SijFor the cultivated area of the i-th class crops in j-th of region, OiIt is consumed by the i-th class crops
The discharge capacity of unit material used for agriculture production process percent of greenhouse gases, gkFor the temperature of unit area kth class energy crop life cycle
Room gas emissions, skjFor the cultivated area of kth class energy crop in j-th of region, okIt is consumed by kth class energy crop
The discharge capacity of unit material used for agriculture production process percent of greenhouse gases, pljFor the feed in the domestic birds and animals feeding process of unit quantity
Dosage, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, EFlFor the ammonia year discharge of a ruminant domestic animal
Amount, o'lFor the greenhouse gas emissions in the unit material used for agriculture production process of l class domestic birds and animals live boxes consumption, θ is single
Position weight feed converts into crops life cycle greenhouse gas emissions, and a is the number of species of crops, and b is the quantity in region,
C is the number of species of energy crop, and d is the quantity of domestic birds and animals；
The economic well-being of workers and staff amount determination unit, specifically includes：
Economic well-being of workers and staff amount determination subelement is used for basis
Calculate food production warp
Income amount of helping ψGDP, wherein UiFor the i-th class cereal or the unit price of vegetables, ukFor the unit price of kth class bioenergy, u 'lFor l classes
The unit price of meat, egg or milk, YijFor the yield of the i-th class cereal or vegetables in j-th of region, ykjFor kth class in j-th of region
The yield of bioenergy, y 'ljFor the yield of l classes meat, egg or milk in j-th of region, DiFor the i-th class unit area or quantity
Crops consumed in chemical fertilizer expense, dkFor the chemical fertilizer expense consumed in kth class energy crop, d 'lFor l class Board Lots
Poultry or livestock needed for feed conversion crop chemical fertilizer Meteorological, EiIt is consumed by the i-th class unit area or quantity crops
Energy expenditure, ekFor the energy expenditure consumed in kth class unit area or amount of energy crop, e 'lFor l classes and poultry
Or the energy expenditure consumed in domestic animal, ZirIt is the i-th class unit area crops in addition to the chemical fertilizer expense and the energy expenditure
The Master Cost consumed, zkr'Disappeared in addition to the chemical fertilizer expense and the energy expenditure by kth class unit area energy crop
The Master Cost of consumption, SijFor the cultivated area of the i-th class crops in j-th of region, skjMake for the kth class energy in j-th of region
The cultivated area of object, mljFor the cultivation quantity that l class domestic birds and animals in j-th of region are raised, a is the number of species of crops, b
For the quantity in region, c is the number of species of energy crop, and d is the quantity of domestic birds and animals.
10. food reduction of greenhouse gas discharge default risk according to claim 8 determines system, which is characterized in that
The first probability density function determination unit, specifically includes：
Emissions data quality evaluation subelement, the quality for evaluating the emissions data using more criterion evaluation methods；
Second credit rating assesses subelement, the credit rating for assessing the emissions data using fuzzy mathematics theory；
First probability density function determination subelement, for according to the credit rating of the emissions data to the emissions data into
Row Monte Carlo simulation obtains the probability density function of emissions data；
The second probability density function determination unit, specifically includes：
Economic well-being of workers and staff data quality accessment subelement, the matter for evaluating the economic well-being of workers and staff data using more criterion evaluation methods
Amount；
Second credit rating assesses subelement, the quality etc. for assessing the economic well-being of workers and staff data using fuzzy mathematics theory
Grade；
Second probability density function determination subelement, for being received to the economy according to the credit rating of the economic well-being of workers and staff data
Beneficial data carry out Monte Carlo simulation, obtain the probability density function of economic well-being of workers and staff data；
The joint probability density function determination unit, specifically includes：
Joint probability distribution function determination subelement, for examining the greenhouse gas emission to be received with economic using Cupla functions
The correlation of the Joint Distribution of benefit, obtains the joint probability distribution function of the greenhouse gas emission and economic well-being of workers and staff；
Joint probability density function determination subelement, for according to the joint probability of the greenhouse gas emission and economic well-being of workers and staff point
Cloth function, the greenhouse gas emission data probability density function and the economic well-being of workers and staff probability density function, determine institute
State the joint probability density function of greenhouse gas emission and economic well-being of workers and staff；
Default risk determination unit, specifically includes：
Con trolling index obtains subelement, for obtaining greenhouse gas emission intensity overall control index；
Default risk determination subelement, for according to R=∫ ∫H≥LfX,Y(x, y) dxdy calculates greenhouse gas emission Default Probability R,
Wherein,L is the greenhouse gas emission intensity overall control index.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109242340A (en) * | 2018-09-29 | 2019-01-18 | 国网辽宁省电力有限公司电力科学研究院 | A kind of thermal storage electric boiler consumption system monitoring data evaluation system and its evaluation method |
| CN111079087A (en) * | 2019-12-09 | 2020-04-28 | 中国农业科学院农业资源与农业区划研究所 | Method for measuring and calculating greenhouse gas emission in live pig breeding industry |
-
2018
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109242340A (en) * | 2018-09-29 | 2019-01-18 | 国网辽宁省电力有限公司电力科学研究院 | A kind of thermal storage electric boiler consumption system monitoring data evaluation system and its evaluation method |
| CN109242340B (en) * | 2018-09-29 | 2021-08-27 | 国网辽宁省电力有限公司电力科学研究院 | Monitoring data evaluation system and evaluation method for heat storage electric boiler digestion system |
| CN111079087A (en) * | 2019-12-09 | 2020-04-28 | 中国农业科学院农业资源与农业区划研究所 | Method for measuring and calculating greenhouse gas emission in live pig breeding industry |
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