An environmental health effect evaluation method, system, terminal and storage medium

Abstract

The application discloses an environmental health effect evaluation method, system, terminal and storage medium, and the method comprises the following steps: acquiring an atmospheric particulate emission inventory, and classifying and processing the atmospheric particulate emission inventory according to production department types to obtain a production-side emission inventory; coupling a reverse concomitant mode in an air quality model with a health evaluation model to obtain a coupling model; inputting the production-side emission inventory into the coupling model to obtain a production-side environmental effect evaluation result; acquiring an environmental extension input-output model, and inputting the production-side environmental effect evaluation result into the environmental extension input-output model to obtain a consumption-side environmental effect evaluation result. The application can accurately evaluate the influence of products on environmental health effects in the whole life process of production and consumption by constructing a consumption-side emission inventory, coupling a reverse concomitant mode in an air quality model with a health evaluation model to obtain a coupling model.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of environmental data evaluation, and particularly relates to an environmental health effect evaluation method and system, a terminal and a computer readable storage medium. BACKGROUND

[0002] Atmospheric particulate matter enters the human body through the respiratory tract, causing harm to the heart and lung function, and thus having a negative impact on human health. Products need to go through packaging, transportation, sales and other processes in the whole life cycle before being consumed by consumers. The environmental health impact caused by the emission of atmospheric particulate matter during this process is borne by the residents of the production area. Therefore, studying the pollutant emissions in the whole process from production to consumption helps to attribute the environmental and health responsibilities borne by consumers, and promotes humans to take corresponding air pollution prevention and control measures and economic regulation and control policies to maintain the health of the population.

[0003] However, the calculation of the environmental health impact of products in the whole process from production to consumption in the prior art requires a large amount of computing resources, and also cannot guarantee the accuracy of the result of the impact of atmospheric particulate matter on human health, so that consumers cannot attribute the responsibility to the areas or objects that have an impact on the environment and health, and the health of the population cannot be guaranteed.

[0004] Therefore, the prior art still needs to be improved and developed. SUMMARY

[0005] The main purpose of the present application is to provide an environmental health effect evaluation method and system, a terminal and a computer readable storage medium, which aims to solve the problem that the calculation of the impact of atmospheric particulate matter on human health in the prior art is complex, requires a large amount of computing resources, and the accuracy of the calculation result is not high, so that consumers cannot attribute the responsibility to the areas or objects that have an impact on the environment and health, and the health of the population cannot be guaranteed.

[0006] To achieve the above-mentioned purpose, the present application provides an environmental health effect evaluation method, which comprises the following steps:

[0007] An atmospheric particulate matter emission inventory is obtained, and the atmospheric particulate matter emission inventory is classified and processed according to the production department type to obtain a production side emission inventory;

[0008] The inverse concomitant mode in the air quality model is coupled with the health evaluation model to obtain a coupled model;

[0009] The production side emission inventory is input into the coupled model to obtain a production side environmental effect evaluation result;

[0010] An environmental extension input-output model is acquired, and the production-side environmental effect evaluation result is input into the environmental extension input-output model to obtain a consumption-side environmental effect evaluation result.

[0011] Optionally, the environmental health effect evaluation method, wherein the atmospheric particulate matter emission inventory is acquired, and the atmospheric particulate matter emission inventory is classified according to production department types to obtain a production-side emission inventory, and the method specifically comprises the following steps:

[0012] A target region is determined, and an atmospheric particulate matter emission inventory corresponding to the target region is acquired;

[0013] An input-output table of the target region is acquired, and production department types in the input-output table are determined;

[0014] The atmospheric particulate matter emission inventory is classified according to the production department types to obtain the production-side emission inventory.

[0015] Optionally, the environmental health effect evaluation method, wherein the inverse concomitant mode in the air quality model is coupled with the health evaluation model to obtain a coupling model, and the method specifically comprises the following steps:

[0016] A preset region is determined, and the preset region is subjected to grid division processing to obtain a grid-based preset region;

[0017] Historical meteorological data in the grid-based preset region are acquired, and the historical meteorological data are input into the air quality model to obtain particulate matter concentrations in the grid-based preset region;

[0018] The particulate matter concentrations are input into the health evaluation model to obtain a first environmental effect evaluation result, and the inverse concomitant mode and the health evaluation model are coupled and trained according to a corresponding relationship between the particulate matter concentrations and the first environmental effect evaluation result to obtain the coupling model.

[0019] Optionally, the environmental health effect evaluation method, wherein an expression of the health evaluation model is as follows:

[0020]

[0021] z x,y =max(0,C x,y -cf);

[0022] wherein GEMM(z) is the number of premature deaths caused by particulate matter concentration exposure, Z is the particulate matter concentration, θ is a fitting parameter of the health evaluation model and a risk proportion model, (x, y) is a grid unit of the grid-based preset region in the health evaluation model, T is a preset time, and T(z x，y) is the corresponding particulate matter concentration in the grid cell within the preset time, z x，y is the corresponding particulate matter concentration in the grid cell after the concentration threshold judgment, and α, μ, v are adjustment parameters of the health assessment model, C x，y is the annual average particulate matter concentration of the grid cell, cf is the particulate matter concentration threshold set by the health assessment model, and max represents data greater than the particulate matter concentration threshold.

[0023] Optionally, the environmental health effect assessment method, wherein the expression of the coupling model is:

[0024]

[0025] wherein J is the coupling model; M 0,x,y is the baseline mortality rate of the grid cell, P x，y is the population number of the grid cell, is the population attributable fraction.

[0026] Optionally, the environmental health effect assessment method, wherein the health assessment model is coupled with the inverse concomitant mode according to the corresponding relationship between the particulate matter concentration and the first environmental effect assessment result, and the coupling model is obtained by coupling training, and then the method further comprises:

[0027] derivative calculation according to the coupling model and the particulate matter concentration to obtain the sensitivity of the coupling model to the particulate matter concentration;

[0028] wherein the expression of the sensitivity is:

[0029]

[0030] wherein, is the sensitivity of the grid cell; is the derivative calculation; J is the coupling model; c x，y is the annual average particulate matter concentration of the grid cell; M 0，x，y is the baseline mortality rate of the grid cell; P x，y is the population number of the grid cell; θ is the fitting parameter of the health assessment model and the risk proportion model; T(z x，y ) is the corresponding particulate matter concentration in the grid cell within the preset time; is the derivative of the total number of time steps of the health assessment model; T'(z x，y ) is the derivative of T(z) when z=z x，y .

[0031] Optionally, the environment health effect evaluation method, wherein the environment extended input-output model is obtained, and the production side environment effect evaluation result is input into the environment extended input-output model to obtain a consumption side environment effect evaluation result, and the method specifically comprises:

[0032] The environment extended input-output model is obtained, and the consumption department type of the consumption side is obtained, the consumption department type and the production side environment effect evaluation result are input into the environment extended input-output model, and a total output matrix is output;

[0033] The production side emission inventory is input into the environment extended input-output model to obtain a production side consumption matrix, and dot product processing is performed according to the total output matrix and the production side consumption matrix to obtain the consumption side environment effect evaluation result.

[0034] In addition, to achieve the above object, the present application further provides an environment health effect evaluation system, wherein the environment health effect evaluation system comprises:

[0035] A production side emission inventory construction module is configured to obtain an atmospheric particulate matter emission inventory, and perform classification processing on the atmospheric particulate matter emission inventory according to the production department type to obtain a production side emission inventory;

[0036] A coupling model construction module is configured to couple a reverse concomitant mode in an air quality model with a health evaluation model to obtain a coupling model;

[0037] A production side evaluation result generation module is configured to input the production side emission inventory into the coupling model to obtain a production side environment effect evaluation result;

[0038] A consumption side evaluation result generation module is configured to obtain an environment extended input-output model, and input the production side environment effect evaluation result into the environment extended input-output model to obtain a consumption side environment effect evaluation result.

[0039] In addition, to achieve the above object, the present application further provides a terminal, wherein the terminal comprises a memory, a processor, and an environment health effect evaluation program stored in the memory and executable on the processor, and the environment health effect evaluation program, when executed by the processor, implements the steps of the environment health effect evaluation method.

[0040] In addition, to achieve the above object, the present application further provides a computer readable storage medium, wherein the computer readable storage medium stores an environment health effect evaluation program, and the environment health effect evaluation program, when executed by a processor, implements the steps of the environment health effect evaluation method.

[0041] In the present application, an atmospheric particulate matter emission inventory is obtained, and the atmospheric particulate matter emission inventory is classified according to the production department type to obtain a production side emission inventory; a reverse concomitant model in an air quality model is coupled with a health assessment model to obtain a coupling model; the production side emission inventory is input into the coupling model to obtain a production side environmental effect evaluation result; an environmental extension input-output model is obtained, and the production side environmental effect evaluation result is input into the environmental extension input-output model to obtain a consumption side environmental effect evaluation result. The present application couples the reverse concomitant model in the air quality model with the health assessment model to obtain the coupling model, obtains the production side emission inventory by obtaining the atmospheric particulate matter emission inventory, inputs the production side emission inventory into the coupling model to obtain the influence of the production side on the environmental health effect, further inputs the production side environmental effect evaluation result into the environmental extension input-output model to obtain the influence of the consumption side on the environmental health effect, without a large amount of computing resources, and also saves the precise evaluation of the environmental effect of the product in the whole production and consumption process, improves the feasibility of the fine reduction scheme design and the health effect evaluation of the atmospheric particulate matter in the actual business, is beneficial to the responsibility attribution of the environment and health borne by the consumer, and is beneficial to promoting the human to take corresponding atmospheric pollution prevention measures and economic control policies to maintain the health of the population. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 is a flow chart of a preferred embodiment of the environmental health effect evaluation method of the present application;

[0043] Figure 2 is a running flow schematic diagram of a preferred embodiment of the environmental health effect evaluation method of the present application;

[0044] Figure 3 is a structure diagram of a preferred embodiment of the environmental health effect evaluation system of the present application;

[0045] Figure 4 is a structure diagram of a preferred embodiment of the terminal of the present application. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical scheme and advantages of the present application more clear and definite, the present application is further described in detail below with reference to the drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0047] Atmospheric particulate matter enters the human body through the respiratory tract, causing harm to the heart and lung function, and thus having a negative impact on human health. Products need to go through packaging, transportation, sales and other processes in the whole life cycle before being consumed by consumers. The environmental health impact of atmospheric particulate matter emissions during this process is borne by the residents of the production area. Therefore, studying the pollutant emissions of products from production to consumption can help attribute the environmental and health responsibilities borne by consumers, and promote humans to take corresponding atmospheric pollution prevention measures and economic control policies to maintain the health of the population.

[0048] In the numerical simulation of atmospheric particulate matter, global or regional air quality numerical models are often used for simulation, such as CMAQ (Community Multiscale Air Quality model) and GEOS-Chem (Goddard Earth Observing System with Chemistry). These models are numerical models developed specifically for fine simulation of atmospheric pollutants, which can provide high temporal and spatial resolution particulate matter concentration information and are widely used in the field of numerical simulation of atmospheric particulate matter.

[0049] The main methods for evaluating the atmospheric pollutant emissions generated from the production to the consumption of products are life cycle assessment and input-output method. Life cycle assessment mainly investigates the environmental impact of each link in the product life cycle; while the input-output method is based on the input-output table published by the state and scientific research institutions and the corresponding regional pollutant emission inventory. Through the input-output model, the emission inventory from production to consumption is calculated, and then the atmospheric pollutant emissions generated in the whole production to consumption process of the commodity are obtained.

[0050] For the environmental health effect assessment of atmospheric particulate matter, the current mainstream methods include Global Exposure Mortality Model (GEMM) and Integrated-Exposure Response (IER). The main evaluation index of these models is the number of premature deaths, i.e. the number of deaths caused by atmospheric particulate matter pollution before reaching the expected lifespan.

[0051] Currently, the main method for evaluating the environmental health effects of atmospheric particulate matter on the consumption side is to use life cycle method or input-output method to construct the atmospheric particulate matter emission inventory of product consumption side, and input it into the regional air quality numerical model (such as CMAQ, GEOS-Chem) for simulation, and then input the simulated concentration into the health effect assessment model GEMM or IER model to obtain the number of premature deaths.

[0052] However, there are some deficiencies in practical applications. Due to the large number of nonlinear equations of physical transmission and chemical reactions of particulate matters in the air quality numerical model, the simulation of atmospheric particulate matters requires a large amount of computing resources. Due to the limitation of computing resources, the time and spatial accuracy of atmospheric particulate matter simulation cannot be achieved in practical applications. In addition, the existing method has important limitations for evaluating the optimization scheme of atmospheric particulate matters. In order to design an environmental health effect optimization scheme for the whole process of product from production to consumption, it is necessary to reuse the regional air quality model for simulation calculation, and the huge amount of calculation greatly limits the design and evaluation of the environmental effect optimization scheme of the product from production to consumption.

[0053] With the in-depth development of the evaluation of the health effects of atmospheric particulate matters, the demand for fine evaluation and optimization scheme design gradually increases. Although the regional air quality model combined with input-output and health evaluation model has made certain progress in simulating atmospheric particulate matter concentration, consumer environmental responsibility and health effects, etc., under the condition of limited computing resources and budget, it is impossible to achieve high-quality simulation results with time and spatial resolution. Therefore, the above method has certain limitations in fine evaluation of particulate matter health effects and optimization scheme.

[0054] In order to overcome the foregoing technical problems, the present application provides an environmental health effect evaluation method based on reverse adjoint and input-output model. The method couples the health evaluation model (such as GEMM and IER) with the reverse adjoint model of the air quality model, such as CMAQ-Adjoint (The adjoint of the Community Multiscale Air Quality model, the reverse adjoint model of the Community Multiscale Air Quality model) and GC-Adjoint (The adjoint of the Goddard Earth Observing System with Chemistry, the reverse adjoint model of the Goddard Earth Chemistry Observation System).

[0055] Unlike the forward simulation of traditional air quality models, the backward adjoint model sets an objective function, solves the adjoint equations after the forward simulation of the air quality model, and calculates the gradient of the objective function (i.e., the sensitivity of the objective function to the input parameters) and the associated premature death of the population for each time step, spatial grid and pollutant emission sector according to the solution of the adjoint equations. Subsequently, the environmental health effects of the entire process from the production side to the consumption side are evaluated by connecting the production sector and the consumption sector using the input-output model. The advantage of the present application is that, since the backward adjoint model only needs to perform one forward and one backward simulation, the sensitivity of particulate matter generation obtained can be repeatedly used for the optimization design of pollutant emission reduction in the production and consumption sectors, which effectively shortens the running time and calculation cost of the model. In addition, the backward adjoint model has superior spatial distribution of sensitivity, which can more comprehensively capture the difficulty and ease of particulate matter generation in various regions, and realize high-resolution and high-accuracy environmental health effect evaluation of atmospheric particulate matter.

[0056] The environmental health effect evaluation method described in the preferred embodiment of the present application, as shown in Figure 1 The environmental health effect evaluation method comprises the following steps:

[0057] Step S10, obtaining an atmospheric particulate matter emission inventory, and classifying the atmospheric particulate matter emission inventory according to production sector types to obtain a production side emission inventory.

[0058] Specifically, a target region is determined, and an atmospheric particulate matter emission inventory corresponding to the target region is obtained; an input-output table of the target region is obtained, and the production sector types in the input-output table are determined; the atmospheric particulate matter emission inventory is classified according to the production sector types to obtain the production side emission inventory.

[0059] As shown in Figure 2 The present application mainly includes three core modules: production side emission inventory construction, environmental health effect calculation and consumption side environmental health effect inventory construction. On the production side, a production side emission inventory based on input-output sector classification is reconstructed using a global or regional emission inventory. Taking the PKU-FUEL-global emission inventory as an example, the resolution is 10km x 10km. The inventory includes various emission sectors (such as power generation, industry, transportation and agriculture), fuel types (such as coal, oil, natural gas and biomass) and atmospheric pollutants (such as primary particulate matter, SO2, NO X, CO, OC, BC, etc.). The production side sector classification is taken as an example of the China Multi-Regional Input-Output Table (MRIO), and the production side sectors include 42 production sectors such as agricultural products and services, coal mining products, oil and gas exploration products, etc. The emission sectors, fuel types and air pollutant types in the PKU-FUEL emission inventory are reclassified according to the production sectors of the input-output table, so as to obtain the production side emission inventory.

[0060] Step S20, coupling the adjoint mode in the air quality model with the health assessment model to obtain a coupled model, wherein the health assessment model in the application can be GEMM model or IER model; the adjoint mode can be CMAQ-Adjoint mode or GC-Adjoint mode.

[0061] As shown in Figure 2 , the core of the application is the coupling of the adjoint mode of the air quality model and the health assessment model. The coupled model is used to quantify the contribution of different regions, time and air pollutants to premature death.

[0062] The adjoint mode contains two main modules: a forward simulation module and an adjoint module. Taking region A as an example, the simulation region of the adjoint mode is also set to region A (the region settings of forward simulation and adjoint are the same), which is defined by 124 x 184 horizontal grid cells with a resolution of 36 km and 13 vertical layers. A preset time range is set as the base simulation year, and a forward simulation is performed for 1 year. The forward simulation is divided into two steps. First, the meteorological simulation of the selected region (region A) is performed using the meteorological module-WRF in WRF-CMAQ (air quality forecast model system), and finally the meteorological field data (including temperature, humidity, wind speed, wind direction, air pressure, precipitation and other meteorological parameters) of the region is obtained. Then, the meteorological field data and the corresponding air pollutant emission inventory are input into the CMAQ model, and the nonlinear equations of physical and atmospheric chemical reactions contained in the CMAQ model are solved to finally obtain the particulate matter concentration field of the region. After the forward simulation is completed, the adjoint module of the air quality model is used to set the objective function J (the function takes the particulate matter concentration output by the air quality model as the independent variable), and the partial derivative of the input parameter c (the particulate matter precursor in the emission inventory) with respect to the particulate matter concentration field data output by the model , that is, the sensitivity of the objective function J to the input parameter c.

[0063] Specifically, a preset area is determined, grid division processing is performed on the preset area to obtain a grid preset area, historical meteorological data in the grid preset area is acquired, and the historical meteorological data is input into the air quality model to obtain particulate matter concentration in the grid preset area; the particulate matter concentration is input into the health assessment model to obtain a first environmental effect assessment result, and the inverse concomitant mode and the health assessment model are coupled and trained according to a corresponding relationship between the particulate matter concentration and the first environmental effect assessment result to obtain the coupled model.

[0064] Taking the inverse concomitant mode CMAQ-Adjoint and the health assessment model GEMM as examples, the basic principle of the coupled model used in the present application is as follows:

[0065] The health model GEMM: GEMM is one of the most popular models for assessing premature deaths of a population exposed to atmospheric particulate matter, and the model takes the number of premature deaths of a population as a characterization index, and the expression of the health assessment model is:

[0066]

[0067] z x,y =max(0,C x，y -cf);

[0068] Wherein, GEMM(z) is the number of premature deaths caused by particulate matter concentration exposure, Z is the particulate matter concentration, θ is the fitting parameter of the health assessment model and the risk proportion model, (x, y) is the grid unit of the grid preset area in the health assessment model, Y is the preset time, T(z x，y ) is the corresponding particulate matter concentration in the grid unit within the preset time, z x，y is the corresponding particulate matter concentration of the grid unit after concentration threshold judgment, α, μ, v are all adjustment parameters of the health assessment model, C x，y is the annual average particulate matter concentration of the grid unit, cf is the particulate matter concentration threshold set by the health assessment model, and max represents the data greater than the particulate matter concentration threshold.

[0069] The coupled model J based on the inverse concomitant mode is defined as the total number of premature deaths caused by the population-weighted PM 2.5 concentration exposure in China, and the coupled model J realizes the coupling of the health assessment model and the inverse concomitant mode, and the expression of the coupled model is:

[0070]

[0071] Wherein, J is the coupled model; M 0,x,y is the baseline mortality rate of the grid unit, P x,ya population number of the grid cell, a population attribution score calculated by a calculation equation of a GEMM-health assessment model.

[0072] Step S30, inputting the production side emission inventory into the coupling model to obtain a production side environmental effect assessment result.

[0073] As Figure 2 shown, the constructed production side emission inventory is imported into a reverse adjoint model coupled with a health assessment model to calculate the exposure health effect of the production side emission particulate matter on the population (taking the premature death number of the population as a representation index).

[0074] Further, after obtaining the coupling model, a partial derivative calculation is performed according to the coupling model and the particulate matter concentration to obtain the sensitivity of the coupling model to the particulate matter concentration.

[0075] Adjoint forcing term: in the reverse adjoint model, the adjoint forcing term of the objective function J still needs to be set. The adjoint forcing term directly calculates the partial derivative of the objective function to the input parameter, that is, the sensitivity of the model to the input parameter. The expression of the sensitivity is:

[0076]

[0077] wherein, is the sensitivity of the grid cell; is the partial derivative calculation; J is the coupling model; c x，y is the annual average particulate matter concentration of the grid cell; M 0,x,y is the baseline mortality rate of the grid cell; P x,y is the population number of the grid cell; θ is a fitting parameter of the health assessment model and the risk proportion model; T(z x，y ) is the corresponding particulate matter concentration of the grid cell in a preset time; is the derivative of the total number of time steps of the health assessment model; T'(z x，y ) is the derivative of T(z) at z=z x，y .

[0078] Step S40, obtaining an environmental extension input-output model and inputting the production side environmental effect assessment result into the environmental extension input-output model to obtain a consumption side environmental effect assessment result.

[0079] As Figure 3 shown, the present application calculates the premature death number of the population caused by the particulate matter based on the consumption side by inputting the production side environmental effect assessment result into the input-output model.

[0080] Specifically, the environment extended input-output model is acquired, and a consumption department type on a consumption side is acquired, the consumption department type and the production side environment effect evaluation result are input into the environment extended input-output model, and a total output matrix is output; the production side emission list is input into the environment extended input-output model, a production side consumption matrix is obtained, and dot product processing is performed according to the total output matrix and the production side consumption matrix, and the consumption side environment effect evaluation result is obtained.

[0081] In the present application, an environment extended input-output model (EEIOA) is adopted: the EEIOA is an extended form of an input-output model (IOA, Input-Output Analysis, environmental input-output analysis, which is a quantitative economic analysis method for studying trade-induced pollution factor transfer among departments of a country or region based on an input-output table), and is used for evaluating environment and health effects from a production side to a consumption side, wherein an expression of the environment extended input-output model is as follows:

[0082] X=(I-A) -1 Y;

[0083] E=f(I-A) -1 Y;

[0084] wherein X is a total output matrix, I is a unit matrix, A is a standardized matrix of intermediate coefficients (wherein columns in the matrix correspond to inputs required for producing one unit of output of each department of another region in a given region), (I-A) -1 is a Leontief inverse matrix, Y is a final consumption matrix, E is pollution emission amount contained among consumption departments, and f is pollution emission intensity of each department on a production side.

[0085] Taking MRIO (multi-regional input-output data) as an example, the dimension of the emission inventory based on the production side (i.e., f in the formula) is (31*42, 1), wherein 31 represents 31 regions, and 42 represents 42 production departments in the MRIO. I is a unit matrix, and the dimension is (31*42, 31*42); A is a direct consumption matrix, and the dimension is (31*42, 31*42), which is obtained by dividing the intermediate flow matrix (dimension (31*42, 31*42)) in the MRIO by the total input (dimension (31*42, 1)); the dimension of the Leontief inverse matrix obtained through the calculation is (31*42, 31*42). The final consumption matrix contains 5 consumption departments in the MRIO, namely rural resident consumption, urban resident consumption, government consumption, total fixed capital formation and inventory increase, and the dimension is (31*42, 31*5). Finally, the dimension of the inventory based on the consumption side is (31*42, 31*42, 31*42, 5), wherein the first dimension is the production side, the second dimension is the intermediate use department, and the third dimension is the consumption side. The intermediate use department represents that there can be other departments such as energy and mineral departments to provide support between the production department and the consumption department.

[0086] In summary, the specific calculation process of the environmental health effect of particulate matter exposure on the consumption side is as follows: first, the particulate matter emission inventory based on the production side is recompiled (the emission departments of the original emission inventory are aligned and classified with the production departments in the input-output table one by one), and is transmitted to the model J coupled with the backtracking mode and the health assessment model. Then, the backtracking mode is set to accompany the forcing term, so as to calculate the sensitivity and the number of premature deaths caused by atmospheric particulate matter emissions based on the production side (i.e., the environmental effect evaluation result on the production side). Finally, the result is introduced into the environmental extension input-output model to obtain the number of premature deaths caused by each department and the particulate matter precursor on the consumption side (i.e., the environmental effect evaluation result on the consumption side), that is, the environmental health effect that consumers should be responsible for due to product consumption. In summary, the model of coupling the backtracking mode of the air quality model with the health assessment model and the EEIOA are used to finely evaluate the environmental health effect of atmospheric particulate matter on the product consumption side, so as to realize the research on the pollutant emissions in the whole process from production to consumption of the product, and help to attribute the environmental and health responsibilities of consumers to the product, and promote human beings to take corresponding atmospheric pollution prevention measures and economic regulation and control policies to maintain the health of the population.

[0087] Technical effects:

[0088] 1.The present application proposes an environmental health effect evaluation method based on inverse companion analysis and input-output model, which realizes the evaluation of the environmental health effect of products from the production side to the consumption side, greatly shortens the calculation time required for evaluation, saves a large amount of computing resources, and improves the feasibility of the fine reduction scheme design and health effect evaluation of atmospheric particulate matter in actual business. In addition, it also improves the discrimination accuracy of the areas prone to particulate matter generation and realizes the fine identification of the potential hotspot areas of atmospheric particulate matter.

[0089] 2.The present application solves the problem that the current product consumption side atmospheric particulate matter health effect evaluation technology is not mature, the fine degree is not high, the simulation process is time-consuming, and the health effect optimization scheme design cannot be well carried out.

[0090] 3.The present application solves the problem that the existing technology cannot well capture the sensitivity of particulate matter generation in each region, and thus cannot accurately identify the potential hotspot areas of particulate matter generation.

[0091] Further, as shown in Figure 4 Based on the above environmental health effect evaluation method, the present application also correspondingly provides an environmental health effect evaluation system, wherein the environmental health effect evaluation system comprises:

[0092] A production side emission inventory construction module 51 is configured to obtain an atmospheric particulate matter emission inventory, and classify and process the atmospheric particulate matter emission inventory according to production department types to obtain a production side emission inventory.

[0093] A coupling model construction module 52 is configured to couple an inverse companion mode in an air quality model with a health evaluation model to obtain a coupling model.

[0094] A production side evaluation result generation module 53 is configured to input the production side emission inventory into the coupling model to obtain a production side environmental effect evaluation result.

[0095] A consumption side evaluation result generation module 54 is configured to obtain an environmental extension input-output model, and input the production side environmental effect evaluation result into the environmental extension input-output model to obtain a consumption side environmental effect evaluation result.

[0096] Further, as shown in Figure 4 Based on the above environmental health effect evaluation method and system, the present application also correspondingly provides a terminal, which comprises a processor 10, a memory 20 and a display 30. Figure 4 Only part of the components of the terminal are shown, but it should be understood that all the shown components are not required to be implemented, and more or less components can be alternatively implemented.

[0097] The memory 20 can be an internal storage unit of the terminal in some embodiments, such as a hard disk or a memory of the terminal. The memory 20 can also be an external storage device of the terminal in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal. Further, the memory 20 can include both the internal storage unit and the external storage device of the terminal. The memory 20 is used to store application software installed on the terminal and various types of data, such as program codes of the installed terminal, etc. The memory 20 can also be used to temporarily store data that has been output or will be output. In an embodiment, the memory 20 stores an environmental health effect assessment program 40, which can be executed by the processor 10 to implement the environmental health effect assessment method in the present application.

[0098] The processor 10 can be a central processing unit (CPU), a microprocessor or other data processing chip in some embodiments, which is used to run program codes stored in the memory 20 or process data, such as executing the environmental health effect assessment method, etc.

[0099] The display 30 can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, etc. in some embodiments. The display 30 is used to display information of the terminal and to display a visualized user interface. The components 10-30 of the terminal communicate with each other through a system bus.

[0100] In an embodiment, the following steps are implemented when the processor 10 executes the environmental health effect assessment program 40 in the memory 20:

[0101] An atmospheric particulate matter emission inventory is obtained, and the atmospheric particulate matter emission inventory is classified by production department type to obtain a production-side emission inventory;

[0102] A reverse adjoint model in an air quality model is coupled with a health assessment model to obtain a coupled model;

[0103] The production-side emission inventory is input into the coupled model to obtain a production-side environmental effect assessment result;

[0104] An environmental extended input-output model is obtained, and the production-side environmental effect assessment result is input into the environmental extended input-output model to obtain a consumption-side environmental effect assessment result.

[0105] The method comprises the following steps:

[0106] determining a target region and obtaining an atmospheric particulate emission inventory corresponding to the target region;

[0107] obtaining an input-output table of the target region and determining a production department type in the input-output table;

[0108] classifying the atmospheric particulate emission inventory according to the production department type to obtain the production-side emission inventory.

[0109] The method comprises the following steps:

[0110] determining a preset region, performing grid division processing on the preset region to obtain a grid-based preset region;

[0111] obtaining historical meteorological data in the grid-based preset region and inputting the historical meteorological data into the air quality model to obtain particulate concentrations in the grid-based preset region;

[0112] inputting the particulate concentrations into the health assessment model to obtain a first environmental effect assessment result, and coupling training the reverse concomitant mode and the health assessment model according to a corresponding relationship between the particulate concentrations and the first environmental effect assessment result to obtain the coupling model.

[0113] The expression of the health assessment model is:

[0114]

[0115] z x，y =max(0,C x，y -cf);

[0116] wherein GEMM(z) is the number of premature deaths caused by particulate concentration exposure, Z is the particulate concentration, θ is the fitting parameter of the health assessment model and the risk proportion model, (x, y) is the grid unit of the grid-based preset region in the health assessment model, T is the preset time, T(z x，y ) is the corresponding particulate concentration in the grid unit within the preset time, z x，y is the particulate concentration corresponding to the grid unit after concentration threshold judgment, and α, μ, v are adjustment parameters of the health assessment model, G x，yis the annual average particulate matter concentration of the grid cell, cf is a particulate matter concentration threshold set by the health assessment model, and max represents data greater than the particulate matter concentration threshold.

[0117] wherein the expression of the coupling model is:

[0118]

[0119] wherein J is the coupling model; M 0，x，y is the baseline mortality rate of the grid cell, P x,y is the population number of the grid cell, is the population attributable fraction.

[0120] wherein the particulate matter concentration is input into the health assessment model to obtain a first environmental effect assessment result, and the inverse concomitant mode and the health assessment model are coupled and trained according to the corresponding relationship between the particulate matter concentration and the first environmental effect assessment result to obtain the coupling model, and then further comprising:

[0121] sensitivity of the coupling model to the particulate matter concentration is obtained by performing partial derivative calculation according to the coupling model and the particulate matter concentration;

[0122] wherein the expression of the sensitivity is:

[0123]

[0124] wherein, is the sensitivity of the grid cell; is the partial derivative calculation; J is the coupling model; c x,y is the annual average particulate matter concentration of the grid cell; M 0,x,y is the baseline mortality rate of the grid cell; R x，y is the population number of the grid cell; θ is a fitting parameter of the health assessment model and the risk proportion model; T(z x，y ) is the corresponding particulate matter concentration of the grid cell in a preset time; is the derivative of the total number of time steps of the health assessment model; T'(z x，y ) is the derivative of T(z) at z=z x，y .

[0125] wherein the environmental extension input-output model is obtained, and the production-side environmental effect assessment result is input into the environmental extension input-output model to obtain a consumption-side environmental effect assessment result, and specifically comprising:

[0126] obtaining the environment extension input-output model, and obtaining the consumption department type, inputting the consumption department type and the production side environment effect evaluation result into the environment extension input-output model, and outputting a total output matrix;

[0127] inputting the production side emission list into the environment extension input-output model to obtain a production side consumption matrix, and performing dot product processing according to the total output matrix and the production side consumption matrix to obtain the consumption side environment effect evaluation result.

[0128] The application further provides a computer readable storage medium, wherein the computer readable storage medium stores an environment health effect evaluation program, and the environment health effect evaluation program is executed by a processor to realize the steps of the environment health effect evaluation method.

[0129] In summary, the application provides an environment health effect evaluation method and related equipment, and the method comprises the following steps: obtaining an atmospheric particulate matter emission list, and classifying the atmospheric particulate matter emission list according to production department types to obtain a production side emission list; coupling a reverse concomitant mode in an air quality model with a health evaluation model to obtain a coupling model; inputting the production side emission list into the coupling model to obtain a production side environment effect evaluation result; obtaining an environment extension input-output model, and inputting the production side environment effect evaluation result into the environment extension input-output model to obtain a consumption side environment effect evaluation result. The application couples the reverse concomitant mode in the air quality model with the health evaluation model to obtain the coupling model, obtains the production side emission list by obtaining the atmospheric particulate matter emission list, inputs the production side emission list into the coupling model to obtain the influence of the production side on the environment health effect, further inputs the production side environment effect evaluation result into the environment extension input-output model to obtain the influence of the consumption side on the environment health effect, so that the application does not need a large amount of computing resources, saves the precise evaluation of the environment effect of products in the whole production and consumption process, improves the feasibility of the fine reduction scheme design and health effect evaluation of the atmospheric particulate matter in actual business, is beneficial to the responsibility attribution of the environment and health borne by the products by consumers, and is beneficial to promoting the human beings to take corresponding atmospheric pollution prevention measures and economic regulation and control policies to maintain the health of the population.

[0130] It should be noted that, in the present document, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element preceded by "comprises a" does not, without more constraints, foreclose the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0131] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing relevant hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer readable computer readable storage medium, and the program can include the processes of the above-mentioned method embodiments when executed. The computer readable storage medium can be a memory, a magnetic disc, an optical disc, etc.

[0132] It should be understood that the application is not limited to the above examples, and those skilled in the art can make improvements or changes according to the above description, and all these improvements and changes shall fall within the protection scope of the appended claims of the present application.

Claims

1. A method of assessing the environmental health effect, characterized by, The environment health effect evaluation method comprises: an air quality model, and obtaining a production-side emission inventory by classifying the air particulate matter emission inventory according to production department types; coupling a reverse concomitant mode in the air quality model with a health evaluation model to obtain a coupling model; The coupling of the reverse concomitant mode in the air quality model with the health evaluation model to obtain the coupling model specifically comprises: determining a preset region, performing grid division processing on the preset region to obtain a grid-based preset region; obtaining historical meteorological data in the grid-based preset region and inputting the historical meteorological data into the air quality model to obtain particulate matter concentration in the grid-based preset region; inputting the particulate matter concentration into the health evaluation model to obtain a first environment effect evaluation result, and coupling training the reverse concomitant mode and the health evaluation model according to a corresponding relationship between the particulate matter concentration and the first environment effect evaluation result to obtain the coupling model; inputting the production-side emission inventory into the coupling model to obtain a production-side environment effect evaluation result; obtaining an environment extended input-output model and inputting the production-side environment effect evaluation result into the environment extended input-output model to obtain a consumption-side environment effect evaluation result; The obtaining of the environment extended input-output model and the inputting of the production-side environment effect evaluation result into the environment extended input-output model to obtain the consumption-side environment effect evaluation result specifically comprises: obtaining the environment extended input-output model and obtaining a consumption department type of the consumption side, inputting the consumption department type and the production-side environment effect evaluation result into the environment extended input-output model, and outputting a total output matrix; inputting the production-side emission inventory into the environment extended input-output model to obtain a production-side consumption matrix, and performing dot product processing according to the total output matrix and the production-side consumption matrix to obtain the consumption-side environment effect evaluation result.

2. The environmental health effect assessment method according to claim 1, characterized in that, The obtaining of the air particulate matter emission inventory and the classification processing of the air particulate matter emission inventory according to production department types to obtain the production-side emission inventory specifically comprises: determining a target region and obtaining an air particulate matter emission inventory corresponding to the target region; obtaining an input-output table of the target region and determining production department types in the input-output table; classifying the air particulate matter emission inventory according to the production department types to obtain the production-side emission inventory.

3. The environmental health effect assessment method according to claim 1, wherein, The expression of the health evaluation model is: GEMM(z) = e θT (z x，y ); z x，y = max(0, C x,y -cf); Wherein, GEMM(z) is the premature death number caused by particulate matter concentration exposure, Z is the particulate matter concentration, θ is the fitting parameter of the health assessment model and the risk proportion model, (x, y) is the grid unit of the preset area in the health assessment model, T is the preset time, T(z x,y ) is the corresponding particulate matter concentration in the grid unit within the preset time, z x,y is the corresponding particulate matter concentration of the grid unit after the concentration threshold judgment, ɑ, μ, v are all the adjustment parameters of the health assessment model, C x，y is the annual average particulate matter concentration of the grid unit, cf is the particulate matter concentration threshold set by the health assessment model, and max represents the data greater than the particulate matter concentration threshold.

4. The environmental health effect assessment method according to claim 3, wherein The expression of the coupling model is: where J is the coupling model; M 0，x，y is the baseline mortality rate for the grid cell, P x，y is the population number for the grid cell, is the population attributable fraction.

5. The environmental health effect assessment method of claim 1, wherein, The inputting of the particulate matter concentration into the health evaluation model to obtain a first environment effect evaluation result, and the coupling training of the reverse concomitant mode and the health evaluation model according to a corresponding relationship between the particulate matter concentration and the first environment effect evaluation result to obtain the coupling model further comprises: performing partial derivative calculation according to the coupling model and the particulate matter concentration to obtain sensitivity of the coupling model to the particulate matter concentration; wherein the expression of the sensitivity is: wherein, is the sensitivity of the grid cell; is the partial derivative calculation; J is the coupling model; c x，y is the annual average particulate matter concentration of the grid cell; M 0，x，y is the baseline mortality rate of the grid cell; P x,y is the population of the grid cell; θ is the fitting parameter of the health assessment model and the risk proportion model; T(z x，y ) is the corresponding particulate matter concentration in the grid cell within a preset time; is the derivative of the total number of time steps of the health assessment model; T'(z x，y ) is the derivative of T(z) at z = z x，y .

6. An environmental health effect assessment system, characterized by, The environmental health effect assessment system based on the environmental health effect assessment method of any one of claims 1-5, the environmental health effect assessment system comprising: a production side emission inventory construction module configured to obtain an atmospheric particulate matter emission inventory and classify the atmospheric particulate matter emission inventory according to production department types to obtain a production side emission inventory; a coupling model construction module configured to couple a reverse concomitant model in an air quality model with a health assessment model to obtain a coupling model; a production side assessment result generation module configured to input the production side emission inventory into the coupling model to obtain a production side environmental effect assessment result; a consumption side assessment result generation module configured to obtain an environmental extended input-output model and input the production side environmental effect assessment result into the environmental extended input-output model to obtain a consumption side environmental effect assessment result.

7. A terminal, characterized by comprising: The terminal comprises a memory, a processor, and an environmental health effect assessment program stored on the memory and executable on the processor, and the environmental health effect assessment program, when executed by the processor, implements the steps of the environmental health effect assessment method of any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores an environmental health effect assessment program, and the environmental health effect assessment program, when executed by a processor, implements the steps of the environmental health effect assessment method of any one of claims 1-5.

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