CN112364483B - Water footprint analysis method and device - Google Patents
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Abstract
The invention provides a water footprint analysis method, which comprises the following steps of firstly, determining each water consumption process of a product or service in a full life cycle; establishing a water footprint accounting model according to the water consumption flow and the water consumption type; and determining the influence degree of each water consumption flow on the water footprint by comprehensively using a qualitative and quantitative analysis method according to the water footprint accounting model and the water consumption type and the water consumption amount in each water consumption flow, and adjusting the water consumption amount of the water consumption flow according to the influence degree so as to reduce the water footprint of the product or service. The method can obtain the influence degree of each link on the water track quantity of the whole process, further help enterprises to better save water, realize the influence degree of each link in the life cycle of products and services on the whole water, and have higher scientificity, effectiveness and practicability.
Description
Technical Field
The invention relates to the field of water resources, in particular to a water footprint analysis method and a water footprint analysis device.
Background
Water resources serve as important basic natural resources of human society, and the position of the water resources in the development of economic society is very important. Water footprint (water fountain) refers to the invisible consumption of water by the public during the consumption of products and services in daily life. The water consumed by a product or service in a production process is the water footprint of that product. For example, a 100 gram apple has a water footprint of 70 litres, a cup of coffee has a water footprint of 140 litres and a hamburger has a water footprint of 2400 litres.
Along with the process of industrialization of China, the problems of water resources are more and more, the situation of regulating the supply and the use of the water resources is urgent day by day, and the research on water footprint has important significance for regulating and standardizing the use of the water resources. The water footprint is an important means for solving the problem of water resource environment, and the water footprint is also used as a new water resource management evaluation tool. The type and quantity of water resources involved in a product or service process are difficult to determine, and how to measure the water consumption in the process to reduce the water footprint of a product or service becomes one of the fundamental problems of saving water resources.
For example, chinese patent document CN103226791A discloses a method for measuring and calculating regional grain production water footprint, which performs comprehensive irrigation rating of regional grain crops and economic crops by using obtained seeding area, irrigation rating, grain yield, irrigation water consumption, cultivated land area, irrigation area, multiple cropping index, precipitation, crop growth period data, and the like of crops, calculates irrigation water consumption and blue water resource usage by using comprehensive irrigation rating allocation method, calculates regional grain production water footprint by using total amount of green water resource, determines the composition thereof, and provides policy reference for research of grain production water problem. Similarly, the document is also referred to as Chinese patent document CN107133881A.
Chinese patent document CN107239615A discloses a hydropower station water purification footprint evaluation calculation method, which considers the net loss amount of water resources, considers the water resource consumption generated by evaporation, eliminates the interference of evaporation of the existing water amount in the natural state of the river before the hydropower station is constructed, and provides a new evaluation index for hydropower station development project site selection and environmental impact evaluation.
Chinese patent document CN110751422A discloses a method for quantifying the water footprint of coal produced by coal mine enterprises, which comprises the steps of firstly collecting coal mine enterprise data, then calculating the water footprint of the coal mine enterprises according to the collected coal mine enterprise data, calculating the annual average yield and the water footprint of three types of coal mines, and predicting the water footprint data of the national coal.
Chinese patent document CN110298575A discloses a water footprint sustainability evaluation method, which calculates the difference between the regional sustainable water resource quantity and the regional production water footprint, obtains regional water resource overload, calculates the difference between the regional consumption water footprint and the regional production water footprint, obtains regional water resource trade braille, calculates the difference between the regional sustainable water resource quantity and the regional consumption water footprint, obtains regional water resource braille, and evaluates the water footprint sustainability according to the overload and the braille.
However, there is no analysis technique in the prior art for measuring water consumption during water consumption and establishing a water footprint accounting model to reduce the water footprint.
Disclosure of Invention
In view of the technical problems in the prior art, the present invention aims to provide a water footprint analysis method and apparatus capable of measuring the water consumption during water consumption to reduce the water footprint of a product or service.
According to an aspect of the present invention, there is provided a water footprint analysis method, characterized by comprising:
determining the respective water consumption processes of a product or service in a full life cycle;
establishing a water footprint accounting model according to the water consumption flow and the water consumption type;
and determining the influence degree of each water consumption flow on the water footprint according to the water footprint accounting model and the water consumption type and the water consumption amount in each water consumption flow, and adjusting the water consumption amount of the water consumption flow according to the influence degree so as to reduce the water footprint of the product or service.
Optionally, the water consumption process comprises a direct water consumption process and an indirect water consumption process, and the water consumption types comprise blue water, green water and grey water.
Optionally, the building of the water footprint accounting model according to the water consumption flow and the water consumption type comprises:
determining blue water, green water and grey water classifications of water consumption in each process;
obtaining a grey water footprint accounting coefficient according to the national pollutant comprehensive emission standard;
determining an accounting coefficient of the indirect water footprint according to the relation between the raw materials and the product;
the total water footprint of the product = direct water footprint + indirect water footprint, and a product water footprint accounting model is obtained; wherein, the direct water footprint = blue water consumption + green water consumption + grey water consumption in the direct water consumption flow, and the indirect water footprint = blue water consumption + green water consumption + grey water consumption in the indirect water consumption flow.
Optionally, determining the extent of influence of each of the water-consumption routines on the water footprint comprises:
and obtaining the influence degree of each water consumption process on the water footprint by adopting a qualitative analysis or quantitative analysis method.
Optionally, the method further comprises:
and according to the water consumption of each process in the production process of the product or service, carrying out random sampling simulation by taking the actually produced data as the upper and lower boundaries to obtain a plurality of groups of simulation sample data.
Optionally, determining the influence degree of each water consumption process on the water footprint according to the water footprint accounting model and the water consumption type and the water consumption amount in each water consumption process, including:
forming a plurality of groups of track matrixes according to the water footprints of the water consumption processes of the products or services and the simulation sample data;
substituting the water footprint accounting model to obtain the water footprint value of each track;
dividing the difference between every two lines of data results by the process data variation to obtain a basic effect;
and averaging the basic effects obtained by the tracks to obtain the influence degree of the water footprint of each process on the whole water footprint consumption.
Optionally, determining the influence degree of each water consumption process on the water footprint according to the water footprint accounting model and the water consumption type and the water consumption amount in each water consumption process, including:
respectively forming a matrix A and a matrix B according to the water footprint of each water consumption process of the product or service and the simulation sample data;
each column of the matrix B replaces the corresponding column of the matrix A in turn to obtain a plurality of groups of matrixes, and each row of data of the matrix is substituted into the water footprint accounting model respectively to obtain the water footprint value of each row;
calculated according to the following formula:
wherein, V xi (E X~i (Y|X i ) Represents the water footprint data variance of each process except for itself, n is the number of rows in the matrix, WF (B) i ) Water footprint for i rows in matrix B, WF (AB) i ) Is a matrix AB i Water footprint of line Zhou, WF (A) i ) Is the water footprint of i rows in matrix A;
according to the formulaObtaining an overall water footprint average value, wherein n is the number of matrix rows, WF Ai Water footprint, WF, for row i in matrix A Bi The water footprints of i rows in the matrix B; thenI.e. the uncertainty value of the water footprint of each link, S i Is an uncertainty value, V, of flow i xi For the variance of the water footprint data for flow i except for itself, V (Y) represents the overall water footprint levelMean value;
and obtaining the influence degree of the water footprint of each flow on the whole water footprint consumption according to the numerical value.
The embodiment of the invention also provides a water footprint analysis device, which comprises:
a process determining unit for determining each water-consuming process of a product or service in a full lifecycle;
the model establishing unit is used for establishing a water footprint accounting model according to the water consumption flow and the water consumption type;
and the sequencing unit is used for determining the influence degree of each water consumption flow on the water footprint according to the water footprint accounting model and the water consumption type and the water consumption amount in each water consumption flow, and adjusting the water consumption amount of the water consumption flow according to the influence degree so as to reduce the water footprint of the product or service.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program to realize the steps of the water footprint analysis method.
An embodiment of the present invention further provides a computer readable medium, on which a computer program is stored, wherein the program is executed by a processor to implement the steps of the water footprint analysis method.
In the present invention, the product or service refers to a product which is consumed by water resources, such as coal chemical products or agricultural products, or a service, such as hotel management, car washing service, and the like. The life cycle is generally referred to as its duration, such as the period from planting an apple to cultivating the apple until the apple is ripe and picked or even transported for consumption.
The technical scheme of the invention has the following advantages:
the water footprint analysis method of the invention determines each water consumption process of a product or service in the whole life cycle; establishing a water footprint accounting model according to the water consumption flow and the water consumption type; and comprehensively using a qualitative and quantitative analysis method to determine the influence degree of each water consumption flow on the water footprint according to the water footprint accounting model and the water consumption type and the water consumption amount in each water consumption flow, and adjusting the water consumption amount of the water consumption flow according to the influence degree to reduce the water footprint of the product or service. The method can obtain the influence degree of each link on the water track quantity of the whole process, further help enterprises to better save water, realize the influence degree of each link in the life cycle of products and services on the whole water, and have higher scientificity, effectiveness and practicability.
Drawings
In order to more clearly illustrate the detailed description of the present invention or the technical solutions in the prior art, the detailed description of the detailed description or the prior art with reference to the drawings is provided below. Wherein:
FIG. 1 is a flowchart showing a specific example of a water footprint analysis method in embodiment 1 of the present invention;
FIG. 2 is a flowchart illustrating the production of an exemplary product in example 1 of the present invention;
FIG. 3 is a flowchart of a method of using qualitative or quantitative analysis in example 1 of the present invention;
fig. 4 is a flow chart for obtaining the influence degree of each water consumption flow on the water footprint in embodiment 1 of the present invention;
FIG. 5 is a schematic block diagram showing a specific example of a water footprint analysis apparatus in embodiment 2 of the present invention;
fig. 6 is a schematic diagram of a hardware structure of an electronic device that executes the water footprint analysis method in embodiment 3 of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it is obvious that the described embodiments are illustrative and the present invention is not limited to the specific embodiments. The person skilled in the art realizes that the features mentioned in the following description of the different embodiments of the invention can be combined with each other as long as they do not conflict with each other.
Example 1
The embodiment provides a water footprint analysis method, which is used for measuring water consumed in the production process of a product or service, analyzing the water footprint of the product or service and guiding the optimization of links with more water consumption in the production process of the product or service, so as to achieve the purpose of saving water resources.
The water footprint analysis method in this embodiment, as shown in fig. 1, includes the following steps:
s1, determining each water consumption process of a product or service in a full life cycle. Determining water consumption processes in the production process of the product according to national 'clean production standards' and production standards of various products, wherein the water consumption processes comprise a direct water consumption process and an indirect water consumption process, the direct water consumption process refers to the process of producing the specific product, and the direct water footprint refers to water consumed in the process of producing the specific product. The indirect water consumption process refers to the processes of raw materials, auxiliary materials and energy production and exploitation, and the indirect water footprint refers to the water consumed in the processes of raw materials, auxiliary materials and energy production and exploitation. The use and consumption of water resources comprise blue water, green water and grey water, wherein the blue water refers to surface water and underground water used in the production process of products, the green water refers to water resources contained in plants or consumed by plant transpiration, and the grey water refers to water resources consumed when the pollutant content in the waste water is diluted to natural body concentration. The direct water footprint and the indirect water footprint comprise blue water, green water and grey water. Namely, the direct water footprint refers to a green-blue grey water footprint consumed in the production process of the product, and the indirect water footprint refers to a green-blue grey water footprint consumed in the production and exploitation processes of raw materials, auxiliary materials and energy, so that not only is the actual water consumption considered, but also the influence of sewage on the environment is considered.
To analyze the water footprint of a product, a product production flow diagram is first determined. Taking a coal-to-methanol product as an example, the raw material is coal, the coal production and coal washing are indirect water footprint processes, and the coal gasification methanol production and comprehensive water consumption are direct water footprint processes. The flow chart is shown in FIG. 2.
S2, establishing a water footprint accounting model according to the water consumption flow and the water consumption type, wherein the water footprint accounting model comprises the following steps:
firstly, determining the blue water, green water and grey water classifications of the water consumption of each process. The blue water, green water and grey water classifications of the water consumption of each process can be determined based on a water footprint evaluation manual.
And secondly, obtaining a grey water footprint accounting coefficient according to the national pollutant comprehensive emission standard. Blue water and green water refer to water resources consumed in specific production and can be directly added; grey water is the water consumption required by diluting pollutants in discharged sewage to a certain standard, so the calculation is converted according to national pollutant standards.
Thirdly, determining an accounting coefficient of the indirect water footprint according to the relation between the raw materials and the product; when the raw materials are manufactured into products, a certain conversion ratio exists, for example, 1.5t of coal can be manufactured into 1t of methanol, so that the raw materials need to be converted according to the ratio. And for the direct water footprint, the direct water footprint is directly consumed in the production of the product, so the coefficient is not required to be calculated.
Fourthly, the total water footprint of the product = the direct water footprint + the indirect water footprint, and a product water footprint accounting model is obtained; wherein, the direct water footprint = blue water consumption + green water consumption + grey water consumption in the direct water consumption flow, and the indirect water footprint = blue water consumption + green water consumption + grey water consumption in the indirect water consumption flow.
And S3, because of one product or service, the actually obtained water consumption information of each flow is less, in order to ensure the accuracy of subsequent operation, sample data is increased in a difference mode, and random data simulation is carried out by using the water consumption data in the production process and relevant national standards to obtain more simulation samples. The method specifically comprises the following steps:
according to water consumption (n groups of data) of each process in the production process of the product, random sampling simulation is carried out by taking actually produced data as upper and lower boundaries to obtain 2n groups of water footprint data, and inaccurate data in the simulation data are removed and corrected according to a manual interpretation method to obtain a plurality of groups of simulation sample data.
And S4, determining the influence degree of each water consumption flow on the water footprint according to the water footprint accounting model and the water consumption type and the water consumption amount in each water consumption flow, and adjusting the water consumption amount of the water consumption flow according to the influence degree so as to reduce the water footprint of the product or service.
In this embodiment, the influence degree of each water consumption process on the water footprint is obtained by respectively adopting a qualitative analysis method or a quantitative analysis method, and a flow chart is shown with reference to fig. 3.
In this embodiment, the first mode adopted is a qualitative analysis method, and the influence degree of each water consumption process on the water footprint is obtained. The specific process is shown in fig. 4, and comprises the following steps:
and S4-1, forming a plurality of groups of track matrixes according to the water footprints of the water consumption processes of the products or the services and the simulation sample data. And forming a (2 n-1) group track matrix according to the water footprint consumption and the random sampling simulation data of the production process of the product, wherein n is a positive integer and the same applies below.
S4-2, substituting the water footprint accounting model to obtain a water footprint value of each track;
s4-3, dividing the difference of every two lines of data results by the variable quantity of the flow data to obtain a basic effect;
and S4-4, averaging the basic effects of each process obtained by the (2 n-1) tracks to obtain the influence degree of each process water footprint on the whole water footprint consumption.
And generating (2 n-1) track matrixes, namely converting the 2n rows of data by one variable each time under the condition of keeping other variable data unchanged until each data is changed once, so as to obtain one track. Each track matrix consists of 2n groups of data, the data are sequentially substituted into the water footprint accounting model to obtain the water footprint value of each row of data,expressing the fundamental effect of each element, the mean value mu of each variable EEi is determined i Shows the sensitivity, wherein EE i Representing the basic effect of flow i; WF (xi +1, j) represents the water foot quantity of the (i + 1) th row in the j-th track, WF (xi,j) Representing the water footfall in row (i) of the jth track; delta is equal to one-half (track number-1).
Mean value mu of each variable EEi i Representing sensitivity, variance σ i As the degree of interaction between the variables. And generating a sensitivity evaluation coordinate graph by taking the mean value of the basic effect as an abscissa and the variance as the abscissa, and visually representing the uncertainty degree of the water footprints of all the processes and the influence degree of all the processes.
After the influence degree is calculated, the flows with larger influence degree can be selected, and the water consumption in the flows is adjusted, so that the aim of saving water resources can be fulfilled, and an operable implementation mode is provided for saving water.
As another mode, a quantitative analysis method is adopted to obtain the influence degree of each water consumption process on the water footprint. The specific process is as follows:
firstly, respectively forming a matrix A and a matrix B according to the water footprint of each water consumption process of the product or service and the simulation sample data.
Secondly, each row of the matrix B replaces the corresponding row of the matrix A in turn to obtain a plurality of groups of matrixes; each column of the matrix B replaces the corresponding column of the matrix A in turn to obtain (AB) 1 、AB 2 ……AB N ) And a plurality of groups of matrixes are used, and each row of the matrixes are respectively substituted into the water footprint accounting model to obtain the water footprint value of each row.
Again, it is calculated according to the following formula:
wherein, V xi (E X~i (Y|X i ) Represents the water footprint data variance of each flow except for itself; n is the number of rows of the matrix; WF (B) i ) Water footprints of i rows in the matrix B; WF (AB) i ) Is a matrix AB i The water footprint of row i in; WF (A) i ) Is the water footprint of row i in matrix a.
Then, it is calculated according to the following formula:
v (Y) represents the overall water footprint average; n is the number of matrix rows; WF (WF) Ai Is the water footprint of i rows in matrix A; WF Bi Is the water footprint of row i in matrix B.
ThenAn uncertainty value for the water footprint for each link; s. the i Is the uncertainty value of procedure i; vxi is the water footprint data variance of the process i except the process i; (E) X~I (Y|X I ) Represents the average water footprint consumption for flow i; v (Y) represents the overall water footprint average.
And finally, obtaining the influence degree of the water footprint of each flow on the whole water footprint consumption according to the numerical value.
The matrix transformation method has the advantage that the influence degree of each process on the whole can be obtained quantitatively, so that the influence degree of each water consumption process on the water footprint can be known clearly through the quantized values.
The method in the embodiment is a multi-scale product life cycle water footprint uncertainty evaluation method, and comprises the steps of constructing a life cycle-based product water footprint accounting model, classifying blue water, green water and grey water of a water consumption process of a product life cycle, and obtaining a plurality of groups of data samples through random sampling simulation; and constructing each flow of the life cycle by using a meta-effect analysis and matrix transformation uncertainty analysis method to analyze the water footprint. And obtaining the influence degree of each link on the water trace amount of the whole process, thereby helping enterprises to better save water. The scheme can realize the influence degree of each link in the life cycle of products and services on the whole water consumption, and has higher scientificity, effectiveness and practicability.
Example 2
The embodiment of the invention also provides a water footprint analysis device, which comprises:
a process determining unit 01 for determining each water-consuming process of a product or service in a full life cycle; see example 1, step S1 for details.
The model establishing unit 02 is used for establishing a water footprint accounting model according to the water consumption flow and the water consumption type; see example 1, step S2 for details.
And the sequencing unit 03 is configured to determine the influence degree of each water consumption process on the water footprint according to the water footprint accounting model and the water consumption type and water consumption amount in each water consumption process, and adjust the water consumption amount of the water consumption process according to the influence degree to reduce the water footprint of the product or service. The water consumption process comprises a direct water consumption process and an indirect water consumption process, and the water consumption types comprise blue water, green water and grey water. The unit obtains the influence degree of each water consumption process on the water footprint by adopting a qualitative analysis or quantitative analysis method. See example 1, step S4 for details.
Wherein, the model building unit 02 includes:
the classification subunit is used for determining blue water, green water and grey water classifications of the water consumption of each process;
the first nuclear operator unit is used for obtaining a grey water footprint nuclear calculation coefficient according to the national pollutant comprehensive emission standard;
the second nuclear operator unit is used for determining a nuclear coefficient of the indirect water footprint according to the relation between the raw material and the product;
a model calculation subunit, wherein the total water footprint of the product = direct water footprint + indirect water footprint, and a product water footprint accounting model is obtained; wherein, the direct water footprint = blue water consumption + green water consumption + grey water consumption in the direct water consumption flow, and the indirect water footprint = blue water consumption + green water consumption + grey water consumption in the indirect water consumption flow.
On the basis, the system also comprises a sample generating unit which is used for carrying out random sampling simulation by taking actually produced data as an upper boundary and a lower boundary according to water consumption of each process in the production process of products or services to obtain a plurality of groups of simulation sample data.
Wherein, the sequencing unit 03 comprises a qualitative analysis subunit including:
the qualitative analysis first subunit is used for forming a plurality of groups of track matrixes according to the water footprints of the water consumption processes of the products or services and the simulation sample data;
the qualitative analysis second subunit is used for substituting the water footprint accounting model to obtain a water footprint value of each track;
a qualitative analysis third subunit, configured to divide a difference between every two rows of data results by the process data variation to obtain a basic effect;
and the qualitative analysis fourth subunit is used for averaging the basic effects obtained by the track to obtain the influence degree of the water footprint of each process on the whole water footprint consumption.
Wherein, the sequencing unit 03 comprises a quantitative analysis subunit including:
a first subunit of quantitative analysis, which is used for respectively forming a matrix A and a matrix B according to the water footprint of each water consumption process of the product or service and the simulation sample data,
the quantitative analysis second subunit is used for replacing the corresponding column of the matrix A in sequence for each column of the matrix B to obtain a plurality of groups of matrixes, and each row of data of the matrix is respectively substituted for the water footprint accounting model to obtain the water footprint value of each row;
a third subunit of quantitative analysis, configured to calculate, according to a formula: obtaining the water footprint data variance of each step except the step itself; wherein, V xi (E X~i (Y|X i ) Represents the water footprint data variance of each flow except for itself; (E) X~I (Y|X I ) Represents the water footprint consumption average for flow i). (ii) a n is the number of rows of the matrix; WF (B) i ) The water footprints of i rows in the matrix B; WF (AB) i ) Is a matrix AB i The water footprint of the middle i row; WF (A) i ) Is the water footprint of row i in matrix a.
A quantitative analysis fourth subunit for calculating according to the following formula:
v (Y) represents the overall water footprint average; n is the number of matrix rows; WF (WF) Ai Is the water footprint of i rows in matrix A; WF (WF) Bi The water footprint of row i in matrix B.
According toCalculating an uncertainty value for the water footprint of each link; s i Is the uncertainty value of procedure i; v xi The water footprint data variance of the process i except the process itself is obtained; (E) X~I (Y|X I ) Represents the average water footprint consumption for flow i; v (Y) represents the overall water footprint average.Namely the uncertainty value of the water footprint of each link.
And the fifth subunit carries out quantitative analysis to obtain the influence degree of the water footprint of each flow on the overall water footprint consumption according to the numerical value.
The water footprint analysis device in the embodiment comprises a flow determining unit 01, a model establishing unit 02 and a sequencing unit 03, wherein the product water footprint accounting model based on the life cycle is established, blue water, green water and grey water are classified in the water consumption flow of the life cycle of the product, and a plurality of groups of data samples are obtained through random sampling simulation; and constructing each flow of the life cycle by using a meta-effect analysis and matrix transformation uncertainty analysis method to carry out water footprint analysis, and obtaining the influence degree of each link on the water footprint quantity of the whole flow, thereby helping enterprises to better save water. The scheme can realize the influence degree of each link in the life cycle of products and services on the whole water consumption, and has higher scientificity, effectiveness and practicability.
Example 3
Fig. 6 is a schematic diagram of a hardware structure of an electronic device for performing a water footprint analysis method according to an embodiment of the present invention, as shown in fig. 6, the device includes one or more processors 610 and a memory 620, and one processor 610 is taken as an example in fig. 6.
The apparatus for performing the above method may further include: an input device 630 and an output device 640.
The processor 610, the memory 620, the input device 630, and the output device 640 may be connected by a bus or other means, such as the bus connection in fig. 6.
The memory 620, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the processing methods of list item operations in the embodiments of the present application. The processor 610 executes various functional applications of the server and data processing by executing non-transitory software programs, instructions and modules stored in the memory 620, namely, implements the method in the above-described method embodiments.
The memory 620 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the processing apparatus operated by the list items, and the like. Further, the memory 620 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 620 optionally includes memory located remotely from the processor 610, which may be connected to the processing device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input means 630 may receive input numeric or character information and generate key signal inputs related to function control. The output device 640 may include a display device such as a display screen.
The one or more modules are stored in the memory 620 and, when executed by the one or more processors 610, perform the methods illustrated in fig. 1-4.
The product can execute the method provided by the embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method. Details of the technique not described in detail in the present embodiment may be specifically referred to the related description in the embodiments shown in fig. 1 to 3.
The embodiment of the invention also provides a non-transitory computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions can execute the processing method of the list item operation in any method embodiment. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a Random Access Memory (RAM).
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1-7 are implemented when the program is executed by the processor.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications derived therefrom are intended to be within the scope of the invention.
Claims (7)
1. A water footprint analysis method, comprising:
determining the respective water consumption processes of a product or service in a full life cycle;
establishing a water footprint accounting model according to the water consumption flow and the water consumption type;
determining the influence degree of each water consumption flow on the water footprint according to the water footprint accounting model and the water consumption type and the water consumption amount in each water consumption flow, and adjusting the water consumption amount of the water consumption flow according to the influence degree so as to reduce the water footprint of the product or service;
determining the influence degree of each water consumption process on the water footprint according to the water footprint accounting model and the water consumption type and the water consumption amount in each water consumption process comprises the following steps:
according to water consumption of each process in the production process of products or services, random sampling simulation is carried out by taking actually produced data as upper and lower boundaries to obtain a plurality of groups of simulation sample data; respectively forming a matrix A and a matrix B according to the water footprint of each water consumption process of the product or service and the simulation sample data; each column of the matrix B replaces the corresponding column of the matrix A in turn to obtain a plurality of groups of matrixes, and each row of data of the matrix is substituted into the water footprint accounting model respectively to obtain the water footprint value of each row; calculated according to the following formula:
wherein, V xi (E X~i (YX i ) Represents the water footprint data variance of each process except for itself, n is the number of rows in the matrix, WF (B) i ) Water footprint for i rows in matrix B, WF (AB) i ) Is a matrix AB i Water footprint of line Zhou, WF (A) i ) Is the water footprint of i rows in matrix A;
according to the formulaObtaining the average value of the overall water footprint, wherein n is the number of matrix lines and WF (A) i ) For the water footprint of row i in matrix A, WF (B) i ) The water footprints of i rows in the matrix B; thenI.e. the uncertainty value of the water footprint of each link, S i Is an uncertainty value, V, of flow i xi Is the water footprint data variance of the process i except for itself, E X-i (YX i ) Representing the average water footprint consumption value of the flow i, and V (Y) representing the average water footprint value of the whole body;
and obtaining the influence degree of the water footprint of each flow on the whole water footprint consumption according to the numerical value.
2. The method of claim 1, wherein the water consumption process comprises a direct water consumption process and an indirect water consumption process, and the water consumption types comprise blue water, green water, grey water.
3. The method of claim 1, wherein building a water footprint accounting model based on water consumption flow and water consumption type comprises:
determining blue water, green water and grey water classifications of water consumption in each process;
obtaining a grey water footprint accounting coefficient according to the national pollutant comprehensive emission standard;
determining an accounting coefficient of the indirect water footprint according to the relation between the raw materials and the product;
the total water footprint of the product = direct water footprint + indirect water footprint, and a product water footprint accounting model is obtained; wherein, the direct water footprint = blue water consumption + green water consumption + grey water consumption in the direct water consumption flow, and the indirect water footprint = blue water consumption + green water consumption + grey water consumption in the indirect water consumption flow.
4. The method of claim 1, 2 or 3, wherein determining the extent to which each of the water-consuming processes affects the water footprint comprises:
and obtaining the influence degree of each water consumption process on the water footprint by adopting a qualitative analysis or quantitative analysis method.
5. A water footprint analysis device, comprising:
a process determining unit for determining each water-consuming process of a product or service in a full lifecycle;
the model building unit is used for building a water footprint accounting model according to the water consumption flow and the water consumption type;
the sequencing unit is used for determining the influence degree of each water consumption flow on the water footprint according to the water footprint accounting model and the water consumption type and the water consumption amount in each water consumption flow, and adjusting the water consumption amount of the water consumption flow according to the influence degree so as to reduce the water footprint of the product or service;
the sorting unit is further configured to; according to water consumption of each process in the production process of products or services, random sampling simulation is carried out by taking actually produced data as upper and lower boundaries to obtain a plurality of groups of simulation sample data; respectively forming a matrix A and a matrix B according to the water footprint of each water consumption process of the product or service and the simulation sample data; each column of the matrix B replaces the corresponding column of the matrix A in turn to obtain a plurality of groups of matrixes, and each row of data of the matrix is substituted into the water footprint accounting model respectively to obtain the water footprint value of each row; calculated according to the following formula:
wherein, V xi (E X~i (YX i ) Represents the water footprint data variance of each process except for itself, n is the number of rows in the matrix, WF (B) i ) Water footprint for i rows in matrix B, WF (AB) i ) As a matrix AB i Water footprint of line Zhou, WF (A) i ) Water footprints of i rows in the matrix A;
according to the formulaObtaining the average value of the overall water footprint, wherein n is the number of matrix lines and WF (A) i ) For the water footprint of row i in matrix A, WF (B) i ) The water footprints of i rows in the matrix B; then theI.e. the uncertainty value of the water footprint of each link, S i Is an uncertainty value, V, of flow i xi Is the water footprint data variance of the process i except for itself, E X-i (YX i ) Representing the average water footprint consumption for flow i, and V (Y) representing the average water footprint for the whole;
and obtaining the influence degree of the water footprint of each flow on the whole water footprint consumption according to the numerical value.
6. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of any of claims 1-4 when executing the program.
7. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.
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Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103226350A (en) * | 2013-04-22 | 2013-07-31 | 北京工业大学 | Metering and on-line control method of cement production water footprint |
CN110532501A (en) * | 2019-08-09 | 2019-12-03 | 东华大学 | Textile product printing and dyeing workshop section's water footprints accounting method based on modularity theory |
CN111639294A (en) * | 2020-06-01 | 2020-09-08 | 云南大学 | Water resource loss compensation method based on hydropower station water purification footprint |
-
2020
- 2020-10-14 CN CN202011098838.0A patent/CN112364483B/en active Active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103226350A (en) * | 2013-04-22 | 2013-07-31 | 北京工业大学 | Metering and on-line control method of cement production water footprint |
CN110532501A (en) * | 2019-08-09 | 2019-12-03 | 东华大学 | Textile product printing and dyeing workshop section's water footprints accounting method based on modularity theory |
CN111639294A (en) * | 2020-06-01 | 2020-09-08 | 云南大学 | Water resource loss compensation method based on hydropower station water purification footprint |
Non-Patent Citations (5)
Title |
---|
Optimizing the economics and the carbon and water footprints of bioethanol supply chains;Andrea Bernardi et al;《Modeling and Analysis》;20120612;第1-17页 * |
Water footprint and scenario analysis in the transformation of Chongming into an international eco-island;Pengzhou Luo et al;《Resources, Conservation & Recycling》;20181230;第1-10页 * |
产品生命周期可得性水足迹计算方法;章菁等;《环境科学研究》;20180305;第31卷(第05期);第967-974页 * |
旅游水足迹评价初探;黄郸等;《生态科学》;20150929;第34卷(第05期);第211-218页 * |
资源循环复杂物质流系统的Petri网建模方法研究;陈海涛等;《中国环境管理》;20161025(第05期);第85-89页 * |
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