Uncertainty analysis method based on Monte Carlo simulation electro-catalytic membrane environmental influence accounting

Abstract

The invention discloses an uncertainty analysis method for simulating electro-catalytic membrane environmental influence accounting based on Monte Carlo, and relates to the field of environmental evaluation of electro-catalytic membranes. The invention aims to solve the problems of complicated operation, time consumption and labor consumption in the traditional method. On the basis of a Monte Carlo random sampling method, the total environmental influence load evaluation model of the electro-catalytic membrane is adopted, the influence of resources and energy on environmental influence indexes in the life cycle process of the electro-catalytic membrane is obtained, key factors are screened out through sensitivity analysis, uncertainty analysis is conducted through Monte Carlo simulation, and the evaluation result of the environmental influence indexes in the life cycle process of the electro-catalytic membrane is obtained. And the uncertainty range of the environmental influence of the electro-catalytic membrane is obtained. The method can quantitatively and objectively analyze the environmental influence of each index in the life cycle process of the electro-catalytic membrane, judges the main environmental influence and the uncertainty range of the electro-catalytic membrane, and is accurate in evaluation, convenient to operate, small in subjective influence and wide in application prospect. The method has certain mathematical significance and physical significance, is high in reliability, can be popularized to other models, and has certain practical value.

Description

Technical Field

[0001] The present invention relates to the field of environmental assessment of electrocatalytic membranes, and in particular to an uncertainty analysis method for environmental impact assessment of electrocatalytic membranes based on Monte Carlo simulation. Background Art

[0002] Electrocatalytic membrane is a promising emerging water treatment technology that cleverly couples membrane filtration with a variety of electrical phenomena, including electrochemical oxidation, electroadsorption, electrophoresis, etc. It can fully utilize the micro-nano space confinement effect within the membrane pores to enrich pollutants and free radicals, thereby efficiently removing new pollutants that traditional water treatment processes cannot cope with. It has the advantages of low consumption, high efficiency, strong robustness, integration and portability.

[0003] At present, there are few targeted studies on the environmental impact accounting of electrocatalytic membranes. At the same time, the development of electrocatalytic membranes is still in the laboratory stage, with a high degree of freedom and room for improvement. The above situation causes the results of the environmental impact analysis of electrocatalytic membranes to have strong uncertainty. Therefore, it is necessary to analyze and quantify the uncertainty of the environmental impact assessment of electrocatalytic membranes. Summary of the invention

[0004] The present invention provides an uncertainty analysis method for the environmental impact of electrocatalytic membranes based on Monte Carlo simulation to solve the problems of complex operation, time-consuming and labor-intensive in traditional methods. Based on the Monte Carlo random sampling method, the present invention comprehensively analyzes the uncertainty factors in the environmental impact assessment process of electrocatalytic membranes removing new pollutants. It can quantify the environmental impact of electrocatalytic membranes during the entire life cycle of water treatment, quantitatively deal with the uncertainty factors and size of environmental impacts, and propose improvement measures.

[0005] The uncertainty analysis method of the present invention based on Monte Carlo simulation of the environmental impact of electrocatalytic membranes, the analysis system is implemented based on the total environmental impact load evaluation model of the electrocatalytic membranes, specifically as follows:

[0006] (1) Collecting the resource and energy inventory during the life cycle of the electrocatalytic membrane and establishing a corresponding relationship model between different life cycle stages of the electrocatalytic membrane and the resource and energy inventory; the electrocatalytic membrane life cycle stages include material preparation and assembly stage, electric filtration operation stage, cleaning and maintenance stage, and waste disposal stage;

[0007] (2) Determine the environmental impact indicators during the life cycle of electrocatalytic membranes, including global warming potential, terrestrial acidification, freshwater eutrophication, human toxicity, mineral resource depletion, and stratospheric ozone depletion;

[0008] (3) Constructing a total environmental impact load evaluation model for the electrocatalytic membrane; the total environmental impact load evaluation model for the electrocatalytic membrane is:

[0009]

[0010] Where Y j is the jth environmental impact indicator in step (2); X i is the amount of the i-th resource or energy invested in the electrocatalytic membrane life cycle stage in the electrocatalytic membrane life cycle assessment model in step (1); C ij Yes X i Corresponding to Y j Characterization factors of environmental impacts;

[0011] (4) Input the corresponding relationship model between each life cycle stage of the electrocatalytic membrane and the resource and energy inventory and the total environmental impact load evaluation model of the electrocatalytic membrane into OpenLCA or eFootprint software to calculate the total environmental impact load of the electrocatalytic membrane;

[0012] (5) Environmental impact assessment of the electrocatalytic membrane: Based on the total environmental impact load of the electrocatalytic membrane, determine the stage in the life cycle of the electrocatalytic membrane that has the greatest environmental impact;

[0013] (6) performing a single factor sensitivity analysis on the environmental impact of the electrocatalytic membrane life cycle determined in step (5) to screen out key factors;

[0014] (7) Determine the variation range and probability distribution of the key factors screened out in step (6), use Monte Carlo to generate random input data in Python, sample the input data 1000-100000 times, and then obtain the output results based on the total environmental impact load evaluation model of the electrocatalytic membrane.

[0015] Furthermore, the resource and energy list of the electrocatalytic membrane is as follows:

[0016] Resource list: raw materials, chemical reagents, stainless steel, plastics, electrolytes, cleaning water, influent, treated effluent, solid waste and wastewater;

[0017] Energy list: electricity for material preparation and assembly, electricity for pollutant degradation, electricity for cleaning and maintenance, and electricity for water pump operation.

[0018] Furthermore, the model for establishing the corresponding relationship between the life cycle stages of the electrocatalytic membrane and the resource and energy inventory is as follows:

[0019]

[0020]

[0021] Furthermore, the power consumption of the water pump for conveying liquid can be calculated by the following formula:

[0022] E pump=Q×TMP×t÷3600÷η pump

[0023] Where Q is the flow rate of the electrocatalytic membrane, unit: m 3 / h, TMP is the transmembrane pressure difference, t is the running time, η pump is the energy efficiency of the pump.

[0024] Furthermore, the power consumption for degrading pollutants is calculated by the following formula:

[0025] E degradation =10 -3 ×U×I÷Q÷(C f -C P )

[0026] Where U and I are the voltage and current applied to the electrocatalytic membrane, respectively, and Q is the flow rate of the electrocatalytic membrane, in units of m 3 / h,C f and C p They are the pollutant concentrations in the inlet and outlet water, respectively, in mg / L.

[0027] Furthermore, the step (4) of inputting the correspondence model between the life cycle stage of the electrocatalytic membrane and the resource and energy inventory and the total environmental impact load evaluation model of the electrocatalytic membrane into the OpenLCA or eFootprint software to calculate the total environmental impact load of the electrocatalytic membrane; is to embed the total environmental impact load evaluation model of the electrocatalytic membrane into the OpenLCA or eFootprint software, respectively input the resource and energy inventory under the life cycle stage in the correspondence model between the life cycle stage of the electrocatalytic membrane and the resource and energy inventory, and calculate the total environmental impact load of the electrocatalytic membrane under different life cycle stages of the electrocatalytic membrane.

[0028] Furthermore, the key factors described in step (6) are electrolyte concentration, grid carbon intensity, degradation power consumption, membrane permeation flux and membrane life. Explanation of key factors: Electrolyte concentration will directly affect the amount of electrolyte used in the resource list, grid carbon intensity is the GWP characterization factor corresponding to electric energy, and the permeation flux and life of the electrocatalytic membrane will affect the total mass of micropollutants removed by the membrane during its life cycle, thereby affecting the resources and energy consumed to remove 1g of micropollutants. Specifically, changes in permeation flux and life will affect the amount of all resources and energy in the material preparation and assembly stage, cleaning and maintenance stage, and waste disposal stage.

[0029] Furthermore, the variation range and probability distribution of the key factors are as follows:

[0030] The electrolyte concentration varies within a range of ±10%, with a probability distribution of uniform distribution; the carbon intensity of the power grid varies within a range of ±10, with a probability distribution of uniform distribution; the degradation power consumption varies within a range of ±5%, with a probability distribution of uniform distribution; the membrane permeation flux varies within a range of ±15%, with a probability distribution of uniform distribution; the membrane life varies within a range of ±20%, with a probability distribution of uniform distribution.

[0031] Furthermore, the life cycle stage of the electrocatalytic membrane that has the greatest impact on the life cycle environment is the electrofiltration operation stage.

[0032] Furthermore, the output results of the total environmental impact load assessment model of the electrocatalytic membrane were analyzed: it was found that the key factors causing uncertainty in the environmental impact assessment of the electrocatalytic membrane are electrolyte concentration and grid carbon intensity.

[0033] The present invention has the following beneficial effects:

[0034] The present invention uses the Monte Carlo uncertainty analysis method to evaluate the environmental impact of the electrocatalytic membrane, which can quantitatively and objectively analyze the contribution of various factors to the uncertainty of the environmental impact results during the life cycle of the electrocatalytic membrane, and determine the factors that have the greatest impact on the environmental impact results of the electrocatalytic membrane. The evaluation is accurate, the operation is convenient, the subjective influence is small, and the application prospects are broad. Since previous studies have not involved the study of electrocatalytic membranes, there are very few studies that use the Monte Carlo method to perform uncertainty analysis on the environmental impact evaluation of electrocatalytic membranes. In addition to the pre-screening link of single-factor sensitivity analysis, the method of the present invention can avoid the problems of complex operation, time-consuming and labor-intensive in traditional methods. The results of the uncertainty analysis of the environmental impact evaluation of electrocatalytic membranes using Monte Carlo random sampling have certain mathematical and physical meanings, high reliability, can be extended to other models, and have certain practical value. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is a flow chart of the uncertainty analysis method in Example 1 of the present invention;

[0036] Figure 2 A tornado diagram showing the sensitivity analysis result in Example 1 of the present invention;

[0037] Figure 3 This is a result diagram of the Monte Carlo simulation in Example 1 of the present invention. DETAILED DESCRIPTION

[0038] In order to make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the spirit of the contents disclosed by the present invention will be described in detail below. After understanding the embodiments of the contents of the present invention, any technician in the relevant technical field can change and modify them according to the techniques taught by the contents of the present invention without departing from the spirit and scope of the contents of the present invention.

[0039] The exemplary embodiments of the present invention and the description thereof are used to explain the present invention but are not intended to limit the present invention.

[0040] Example

[0041] like Figure 1 As shown in the figure, a life cycle inventory of electrocatalytic membrane for removal of micropollutants was compiled according to the system boundaries, the literature and experimental data were investigated, and the main input data and output data of each process of electrocatalytic membrane for removal of micropollutants were collected. The input data included titanium dioxide powder, hydrogen, electrolyte, stainless steel, deionized water, electricity, etc., and the output included the products of each process of electrocatalytic membrane for removal of micropollutants and pollutants such as wastewater and solid waste.

[0042] Taking "removing 1 gram of pollutants" as the functional unit, the system boundary is determined to include four stages, namely material preparation and assembly stage, electrofiltration operation stage, cleaning and maintenance stage, and waste disposal stage. The energy and material lists of each stage process are collected to evaluate the life cycle environmental impact of electrocatalytic membrane removal of micropollutants.

[0043] The method for evaluating the environmental impact of the life cycle of removing micropollutants by electrocatalytic membrane of the present invention comprises the following specific steps:

[0044] Step 1: List the life cycle resources and energy list of the titanium oxide electrocatalytic membrane for removing micro-pollutants perfluorooctanoic acid (PFOA). The life cycle list includes four stages (material preparation and assembly stage, electric filtration operation stage, cleaning and maintenance stage, and waste disposal stage). The core data list after quantification and sorting of the correspondence between the four stages of this embodiment and the life cycle resources and energy list is shown in Table 1 below:

[0045] Table 1 Total energy material list for removal of micropollutant PFOA by electrocatalytic membrane

[0046]

[0047] The data in Table 1 can be replaced as follows:

[0048] During the membrane material preparation stage, the electrocatalytic membrane can also be prepared by other methods, such as physical vapor deposition, chemical deposition, etc.

[0049] During the membrane assembly stage, other inert materials may also be used for the counter electrode, such as titanium mesh, carbon electrode, metal oxide electrode, etc.

[0050] During the electrofiltration operation stage, other chemicals may also be selected as supporting electrolytes, such as disodium hydrogen phosphate, sodium bicarbonate, sodium sulfate, potassium sulfate, sodium chloride, potassium chloride, etc.

[0051] During the waste disposal stage, solid waste can also be disposed of by other methods, such as recycling, reuse, incineration, etc.

[0052] Step 2: Quantitatively evaluate the life cycle environmental impact of the titanium dioxide electrocatalytic membrane in removing the micropollutant PFOA; according to the characteristics of the electrocatalytic membrane in removing micropollutants, select the type of environmental impact involved and classify the influencing factors, as shown in Table 2.

[0053] Table 2 Environmental impact types

[0054]

[0055] Step 3. According to the selected environmental impact type, in order to measure the relative size of various environmental impacts in each stage of micropollutant removal, the collected list is input into the OpenLCA software to obtain the life cycle environmental impact results of the electrocatalytic membrane micropollutant removal process, as shown in Table 3.

[0056] Table 3 Life cycle environmental impact results of titanium dioxide electrocatalytic membrane for removal of micropollutant PFOA

[0057] Stage process GWP TA FE MRS SOD ME Preparation and Assembly 2.71E+00 2.14E-02 1.41E-03 4.85E-02 1.13E-06 9.95E-05 Electric filtration operation 1.70E+01 9.55E-02 1.18E-02 2.36E-01 6.67E-06 4.89E-04 Cleaning and maintenance 6.31E-03 2.10E-05 3.81E-06 4.22E-05 5.00E-09 3.14E-07 Waste Disposal 3.19E-03 1.92E-05 1.32E-05 3.11E-05 7.09E-09 3.11E-05 total 1.97E+01 1.17E-01 1.32E-02 2.85E-01 7.81E-06 6.20E-04

[0058] Step 4: Environmental impact assessment of electrocatalytic membranes

[0059] According to the life cycle environmental impact results in Table 3, by comparing the environmental impact composition and differences of different stages, it can be seen that the environmental impact of the electrofiltration operation stage is the largest, and the contribution to the overall environmental impact is more than 75%. The reason for this result is that the electrocatalytic membrane system needs to add a large amount of potassium dihydrogen phosphate as a supporting electrolyte, and the environmental impact of potassium dihydrogen phosphate per unit mass is also much higher than other electrolytes (such as sodium chloride and sodium sulfate, etc.). At the same time, the degradation of pollutants also requires a lot of electricity. Therefore, in order to reduce the environmental impact of the electrocatalytic membrane process, greener electrolyte types or lower concentrations of electrolytes can be used as much as possible on the basis of guaranteeing the target. At the same time, the electricity consumed by the degradation of pollutants should be reduced as much as possible. This can be achieved by improving current efficiency and reducing competition for side reactions. The second largest contributor to the environmental impact is the membrane material preparation stage or the membrane assembly stage. For the membrane material preparation stage, the current technical level is still in the laboratory preparation stage, so the power consumption is large, but in the future, the power consumption can be reduced by increasing the single preparation amount and optimizing the heating equipment. A large amount of stainless steel is used in the assembly process of membrane components, which consumes steel metal. Therefore, this stage of the process has a greater impact on the consumption of mineral resources.

[0060] Step 5: Conduct single factor sensitivity analysis on the selected representative environmental indicators.

[0061] According to the uncertainty and importance of the parameters, a. electrolyte concentration b. grid carbon intensity c. degradation power consumption d. membrane permeation flux e. membrane life f. membrane preparation power consumption g. electrode life are initially selected as the main parameters for focus, and the numerical changes of all parameters are set to ±10%. Then, the resulting GWP change value is calculated according to the total environmental impact load assessment model of the electrocatalytic membrane, so as to determine the sensitivity of the parameters and sort them from high to low, such as Figure 2 shown.

[0062] Step 6: Determine the five variables with the highest input sensitivity as key parameters, as well as their range of variation and probability distribution type. Based on the sorting results of step 5, the top five key parameters are: a. electrolyte concentration b. grid carbon intensity c. degradation power consumption d. membrane permeation flux e. membrane life. Determine the range of variation and probability distribution of these parameters, as shown in the following table.

[0063] Table 4 Input parameters and distribution of Monte Carlo simulation

[0064] Parameter name symbol Value unit Range of variation Distribution Type Electrolyte concentration C 100 mM ±10％ Even distribution Grid carbon intensity CI 705 <![CDATA[gCO2e k·Wh -1 ]]> ±10 Even distribution Degradation of power consumption E 5.77 <![CDATA[kWh·g -1 ]]> ±5％ Even distribution Membrane permeation flux J 720 <![CDATA[LMH·bar -1 ]]> ±15％ Even distribution Membrane life T 115969 h ±20％ Even distribution

[0065] Step 7: Based on the determined range of variation and probability distribution, random input data is generated using Monte Carlo in Python, sampling 1,000-100,000 times, and the output results are generated based on the total environmental impact load evaluation model of the electrocatalytic membrane. Figure 3 shown.

[0066] Step 8. Analyze the output results: find out the factors that cause great uncertainty in the environmental impact assessment of electrocatalytic membranes and the main environmental impact factors. Figure 3 The results show that when the sampling frequency is 10,000 times, the median global warming potential GWP result is 19.07 kgCO2e·g -1 , the 95% confidence interval is [18.07, 21.34]. Combined with Table 3, it can be seen that the contribution of the electrofiltration operation stage to various environmental impacts is the largest, and the contribution to the impact on GWP is also the largest. Therefore, the key stage of the environmental impact of electrocatalytic membrane is the electrofiltration operation stage. Figure 2 The results show that electrolyte concentration and grid carbon intensity are the two most sensitive parameters to the environmental impact assessment results. The electrolyte concentration can be reduced by selecting water quality with higher conductivity and the advancement of electrocatalytic membrane technology, while the grid carbon intensity can be reduced by connecting the electrocatalytic membrane to the green grid and using renewable clean energy. For degradation power consumption, it can be reduced by optimizing the selection of electrode materials, the design of the reactor, and the optimization of operating conditions.

Claims

1. Uncertainty analysis method for calculating environmental impact of electrocatalytic membrane based on Monte Carlo simulation, characterized by The analysis system is implemented based on the total environmental impact load evaluation model of the electrocatalytic membrane, as follows: (1) Collecting the resource and energy inventory during the life cycle of the electrocatalytic membrane and establishing a corresponding relationship model between different life cycle stages of the electrocatalytic membrane and the resource and energy inventory; the electrocatalytic membrane life cycle stages include material preparation and assembly stage, electric filtration operation stage, cleaning and maintenance stage, and waste disposal stage; (2) Determine the environmental impact indicators during the life cycle of electrocatalytic membranes, including global warming potential, terrestrial acidification, freshwater eutrophication, human toxicity, mineral resource depletion, and stratospheric ozone depletion; (3) Constructing a total environmental impact load evaluation model for the electrocatalytic membrane; the total environmental impact load evaluation model for the electrocatalytic membrane is: Where Y j is the jth environmental impact indicator in step (2); X i is the amount of the i-th resource or energy invested in the electrocatalytic membrane life cycle stage in the electrocatalytic membrane life cycle assessment model in step (1); C ij Yes X i Corresponding to Y j Characterization factors of environmental impacts; (4) Input the corresponding relationship model between each life cycle stage of the electrocatalytic membrane and the resource and energy inventory and the total environmental impact load evaluation model of the electrocatalytic membrane into OpenLCA or eFootprint software to calculate the total environmental impact load of the electrocatalytic membrane; (5) Environmental impact assessment of the electrocatalytic membrane: Based on the total environmental impact load of the electrocatalytic membrane, determine the stage in the life cycle of the electrocatalytic membrane that has the greatest environmental impact; (6) performing a single factor sensitivity analysis on the environmental impact of the electrocatalytic membrane life cycle determined in step (5) to screen out key factors; (7) Determine the variation range and probability distribution of the key factors screened out in step (6), use Monte Carlo to generate random input data in Python, sample the input data 1000-100000 times, and then obtain the output results based on the total environmental impact load evaluation model of the electrocatalytic membrane.

2. The uncertainty analysis method for calculating the environmental impact of electrocatalytic membranes based on Monte Carlo simulation according to claim 1 is characterized in that The resource and energy list of the electrocatalytic membrane is as follows: Resource list: raw materials, chemical reagents, stainless steel, plastics, electrolytes, cleaning water, influent, treated effluent, solid waste and wastewater; Energy list: electricity for material preparation and assembly, electricity for pollutant degradation, electricity for cleaning and maintenance, and electricity for water pump operation.

3. The uncertainty analysis method for calculating the environmental impact of electrocatalytic membranes based on Monte Carlo simulation according to claim 1 is characterized in that The model for establishing the corresponding relationship between the life cycle stages of the electrocatalytic membrane and the resource and energy inventory is as follows:

4. The uncertainty analysis method for calculating the environmental impact of electrocatalytic membranes based on Monte Carlo simulation according to claim 3 is characterized in that The electric energy consumption of the water pump for conveying liquid can be calculated by the following formula: AND pump =Q×TMP×t÷3600÷η pump Where Q is the flow rate of the electrocatalytic membrane, unit: m 3 / h, TMP is the transmembrane pressure difference, t is the running time, η pump is the energy efficiency of the pump.

5. The uncertainty analysis method for calculating the environmental impact of electrocatalytic membranes based on Monte Carlo simulation according to claim 3 is characterized in that The energy consumption for pollutant degradation is calculated by the following formula: E degradation =10 -3 ×U×I÷Q÷(C f -C P ) Where U and I are the voltage and current applied to the electrocatalytic membrane, respectively, and Q is the flow rate of the electrocatalytic membrane, in units of m 3 / h,C f and C p They are the pollutant concentrations in the inlet and outlet water, respectively, in mg / L.

6. The uncertainty analysis method for calculating the environmental impact of electrocatalytic membranes based on Monte Carlo simulation according to claim 1 is characterized in that The correspondence model between the life cycle stages of the electrocatalytic membrane and the resource and energy inventory and the total environmental impact load evaluation model of the electrocatalytic membrane described in step (4) are input into OpenLCA or eFootprint software to calculate the total environmental impact load of the electrocatalytic membrane; The total environmental impact load evaluation model of the electrocatalytic membrane is embedded in the OpenLCA or eFootprint software, and the resource and energy lists at different life cycle stages of the electrocatalytic membrane are respectively input into the corresponding relationship model between the different life cycle stages of the electrocatalytic membrane and the resource and energy lists, and the total environmental impact load of the electrocatalytic membrane at different life cycle stages of the electrocatalytic membrane is calculated.

7. The uncertainty analysis method for calculating the environmental impact of electrocatalytic membranes based on Monte Carlo simulation according to claim 1 is characterized in that The key factors described in step (6) are electrolyte concentration, grid carbon intensity, degradation power consumption, membrane permeation flux and membrane life.

8. The uncertainty analysis method for calculating the environmental impact of electrocatalytic membranes based on Monte Carlo simulation according to claim 1 or 7, characterized in that The variation range and probability distribution of the key factors are as follows: The electrolyte concentration varies within a range of ±10%, with a probability distribution of uniform distribution; the carbon intensity of the power grid varies within a range of ±10%, with a probability distribution of uniform distribution; the degradation power consumption varies within a range of ±5%, with a probability distribution of uniform distribution; the membrane permeation flux varies within a range of ±15%, with a probability distribution of uniform distribution; the membrane life varies within a range of ±20%, with a probability distribution of uniform distribution.

9. The uncertainty analysis method for calculating the environmental impact of electrocatalytic membranes based on Monte Carlo simulation according to claim 1 is characterized in that The life cycle stage of the electrocatalytic membrane that has the greatest impact on the life cycle environment is the electrofiltration operation stage.

10. The uncertainty analysis method for calculating the environmental impact of electrocatalytic membranes based on Monte Carlo simulation according to claim 1 is characterized in that The output results of the total environmental impact load assessment model of electrocatalytic membranes were analyzed: it was found that the key factors causing uncertainty in the environmental impact assessment of electrocatalytic membranes are electrolyte concentration and grid carbon intensity.

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