Method for estimating atmospheric heavy metal environmental capacity

Abstract

The present application provides a kind of estimation method of atmospheric heavy metal environmental capacity, comprising: obtaining the basic terrain meteorological data of target area to be estimated;Determine the atmospheric heavy metal emission scheme;Using air quality model to obtain the daily grid heavy metal concentration of target area in simulation year;Non-carcinogenic risk quotient and carcinogenic risk quotient are calculated, by comparing with 1, judge whether it needs to adjust atmospheric heavy metal emission scheme, until non-carcinogenic risk quotient or carcinogenic risk quotient is less than 1, obtain the atmospheric heavy metal environmental capacity of emission source arrangement position.The present application expands the pollutant species from fine particulate matter and its precursor to atmospheric heavy metal, advances the constraint based on pollutant concentration to the constraint of human health, and obtains reasonable environmental capacity result by using iterative calculation.The present application improves the goal of atmospheric environmental pollution prevention and control work from improving air quality to reducing the risk of human health, and provides technical support for the coordinated emission reduction of multiple pollutants.

Description

Technical Field

[0001] This invention belongs to the field of air pollution control technology, specifically relating to a method for estimating the atmospheric heavy metal environmental capacity. Background Technology

[0002] Fine particulate matter in ambient air carries a large number of toxic and harmful substances, such as carbon dioxide, polycyclic aromatic hydrocarbons, heavy metals, and bacteria and viruses. Heavy metals, as a significant toxic component, can enter the human body through respiration and accumulate, harming organ function and even causing irreversible damage. Heavy metals present in the atmosphere include lead, cadmium, chromium, arsenic, nickel, and cobalt. The estimation of atmospheric heavy metal environmental capacity is the basis for formulating atmospheric heavy metal emission reduction measures.

[0003] Current methods for calculating environmental capacity primarily use the requirement that pollutant concentrations meet standards as a constraint. Widely used methods include the A-value method, linear optimization methods, and model simulation methods. Model simulation methods are further divided into model algorithms based on physicochemical process analysis and iterative simulation optimization methods.

[0004] A-value method: Based on the principle of box model, it assumes that the environmental capacity is directly proportional to the self-purification capacity of the atmospheric environment and the area of ​​the region. It only considers natural factors and does not reflect the characteristics of emission sources or chemical transformation processes. It is suitable for determining the atmospheric environmental capacity under ideal conditions, but not for the environmental capacity under the constraints of fine particulate matter, ozone and other standards. Its advantage is that it is simple and convenient.

[0005] Linear optimization methods: These methods calculate atmospheric environmental capacity based on linear optimization theory, linking pollution sources and their diffusion processes with control points. Using the concentration compliance of target control points as a constraint, the maximum allowable emissions from pollution sources are determined through multi-source models and mathematical programming. Linear optimization methods are primarily applicable to smaller-scale areas, reflecting the "emission-receptor" response relationship and allowing for optimized allocation of atmospheric environmental capacity. However, this method is limited by the linear assumption and cannot handle secondary air pollution problems with nonlinear characteristics.

[0006] Iterative simulation optimization method: Based on dynamic spatial transport matrices, industry contribution matrices, and precursor contribution matrices, a multi-objective nonlinear optimization model is established to obtain multiple optimized emission reduction schemes. Through iterative simulation, the pollutant emissions corresponding to achieving air quality standards are obtained, which is the atmospheric environmental capacity. This method can take into account the influence of natural factors such as meteorology and topography, as well as anthropogenic factors such as pollution sources on atmospheric environmental capacity, effectively overcoming the shortcomings of traditional methods. It can reflect complex atmospheric physicochemical processes. However, this method is based on the ideal assumption that the spatial and industry distribution characteristics of pollution source emissions do not change significantly, and it cannot optimize the allocation of atmospheric environmental capacity. Furthermore, it is technically complex and computationally intensive.

[0007] The model algorithm based on physicochemical process analysis considers atmospheric environmental capacity as the maximum allowable emission level to meet fine particulate matter (PM2.5) standards. It calculates the atmospheric environmental capacity of PM2.5 and its precursors based on PM2.5 compliance using air quality models. This method divides atmospheric environmental capacity into two indispensable components: dynamic capacity and static capacity. The dynamic capacity considers the combined effects of actual pollutant concentrations and given pollutant concentration constraints on processes such as transport, diffusion, deposition, and chemical transformation; its calculation result represents the maximum dynamic allowable emission level.

[0008] Existing environmental capacity calculation methods mainly focus on fine particulate matter and its precursors, and only require that the concentrations of pollutants such as fine particulate matter, sulfur dioxide, nitrogen oxides, or inhalable particulate matter meet the standards. Currently, there are no environmental capacity estimation methods that take atmospheric heavy metals as the calculation object, nor do they consider the health effects on the population attributable to atmospheric heavy metal concentrations. Summary of the Invention

[0009] In view of the shortcomings of existing technologies, the present invention provides a method for estimating the atmospheric heavy metal environmental capacity, which can effectively solve the above problems.

[0010] The technical solution adopted in this invention is as follows:

[0011] This invention provides a method for estimating the atmospheric heavy metal environmental capacity, comprising the following steps:

[0012] Step S1: Obtain basic topographic and meteorological data of the target area to be estimated;

[0013] Step S2: Perform 3D meshing on the target area, dividing it into N layers in the vertical z-axis from bottom to top. The coordinates of any grid point i in the 3D mesh are represented as: (x i ,y i ,z i ), z i =1,2,…,N,z i =1 represents the layer closest to the ground;

[0014] The basic topographic and meteorological data are input into the mesoscale meteorological model WRF, which outputs the meteorological data of the target area for each time period t and each grid i in the simulated year.

[0015] Step S3, determine the atmospheric heavy metal emission scheme, including: atmospheric heavy metal emission source ES hm The number of deployments, each atmospheric heavy metal emission source ES hm The location of the layout and each atmospheric heavy metal emission source ES hm Atmospheric heavy metal emissions E hm and emission time; where, let the number of arrangements be M, and the arrangement location be represented as (xj ,y j ,z j ), j = 1, 2, ..., M;

[0016] Step S4: Input the atmospheric heavy metal emission scheme and the meteorological data obtained in step S2 into the air quality model; the air quality model, under the influence of the meteorological data, simulates the atmospheric heavy metal propagation mode to obtain the daily grid-by-grid i heavy metal concentration c of the target area in the simulated year. hm (x i ,y i ,z i );

[0017] Step S5, for z i =1 for each grid (x) i ,y i 1) Calculate the average daily heavy metal concentration for each grid cell during the simulated year. i ,y i ,1) Annual average atmospheric heavy metal concentration

[0018] Step S6, based on each grid (x i ,y i ,1) Annual average atmospheric heavy metal concentration The total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration was calculated. i ,y i ) and the total carcinogenic risk index CR(x) i ,y i );

[0019] Step S7, calculate the total non-carcinogenic risk index HI(x) i ,y i The non-carcinogenic risk quotient Q is obtained by comparing it with the non-carcinogenic risk threshold 1 attributed to atmospheric heavy metal concentration. HI (x i ,y i ); The total carcinogenic risk index CR(x) i ,y i () and the carcinogenic risk threshold of 1×10 attributable to atmospheric heavy metal concentration -4 In comparison, the carcinogenic risk quotient Q was obtained. CR (x i ,y i );

[0020] Step S8, determine whether all atmospheric heavy metal emission sources ES are currently present. hm (x j ,y j ,z jIf all atmospheric heavy metal emission sources ES that are not currently marked as having completed capacity assessments are to be marked as having completed capacity assessments, proceed to step S10; otherwise, for each atmospheric heavy metal emission source ES that is not currently marked as having completed capacity assessments, proceed to step S10. hm (x j ,y j ,z j ), obtain its value in z i = Non-carcinogenic risk quotient Q of a 1-layer projected grid HI (x j ,y j ) and the carcinogenic risk quotient Q CR (x j ,y j If Q HI (x j ,y j ) < 1 or Q CR (x j ,y j If ) < 1, then the atmospheric heavy metal emission source ES is determined. hm (x j ,y j ,z j Atmospheric heavy metal emissions E hm (x j ,y j ,z j ), which is the grid (x) it arranges. j ,y j ,z j Atmospheric heavy metal environmental capacity Q hm (x j ,y j ,z j ), and mark the capacity assessment as complete; if Q HI (x j ,y j )≥1 or Q CR (x j ,y j If )≥1, then proceed to step S9;

[0021] Step S9, for all unmarked atmospheric heavy metal emission sources ES that have completed capacity assessments. hm (x j ,y j ,z j According to the established emission source reduction strategy, the atmospheric heavy metal emissions are adjusted to obtain the reduced atmospheric heavy metal emissions E. hm-Q (x j ,y j ,z j ), using the reduced atmospheric heavy metal emissions E hm-Q (x j ,y j,z j Update the atmospheric heavy metal emissions in step S3, and then return to step S3;

[0022] Step S10: Output the ES of each atmospheric heavy metal emission source obtained at this time. hm (x j ,y j ,z j The atmospheric heavy metal environmental capacity Q at the location of the ) hm (x j ,y j ,z j ), and completed the estimation of atmospheric heavy metal environmental capacity.

[0023] Preferably, the basic topographic and meteorological data includes the topography, underlying surface data, and initial meteorological boundary data of the target area.

[0024] Preferably, the terrain of the target area is a high-resolution horizontal terrain of the target area; the underlying surface data includes the land use type and building height of the target area.

[0025] Preferably, the mesoscale meteorological model WRF outputs the meteorological data of the target area for each time period t and each grid i in the simulated year, including: the east-west component of the horizontal wind u(x) i ,y i ,z i ), the north-south component of horizontal wind v(x) i ,y i ,z i Vertical wind speed w(x) i ,y i ,z i ), temperature T(x i ,y i ,z i ), boundary layer height h(x) i ,y i ), Precipitation prec(x) i ,y i ), relative humidity RH(x) i ,y i ,z i ), water vapor mixing ratio Q vapor (x i ,y i ,z i ) and cloud-water mixing ratio Q cloud (x i ,y i ,z i ).

[0026] Preferably, in step S5, formula (1) is used to obtain each grid (xi ,y i ,1) Annual average atmospheric heavy metal concentration

[0027]

[0028] in: This represents the k-th day of the simulated year in grid (x). i ,y i The heavy metal concentrations of ,1); k=1,2,...,K, where K is the number of days in the simulated year.

[0029] Preferably, in step S6, the total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration is obtained in the following manner. i ,y i ):

[0030] Step A1: Using formulas (2) and (3), the non-carcinogenic daily exposure dose (ADD) of heavy metals entering the human body via the skin adhesion pathway in the target area during the simulated year is statistically calculated. dermal-nocar (x i ,y i (EC) and the non-carcinogenic daily exposure dose of heavy metals entering the body through the respiratory route. inh-nocar (x i ,y i ):

[0031]

[0032] Where: SA is the exposed skin surface area, AF is the skin adhesion, ABS is the skin absorption coefficient, BW is the average body weight, EF is the number of days of exposure per year, ED is the number of years of exposure, and AT is the number of days of exposure per year. nocar AT is the average non-carcinogenic exposure days, CF is the conversion factor, ET is the daily exposure time, and AT is the average non-carcinogenic exposure days. inh-nocar It is the average number of non-carcinogenic exposure days via the respiratory route;

[0033] Step A2: Using formulas (4) and (5), the non-carcinogenic risk index HQ under the skin adhesion exposure route is obtained. dermal-nocar (x i ,y i ) and the non-carcinogenic risk index HQ under respiratory exposure route inh-nocar (x i ,y i ):

[0034]

[0035] Among them: RfD dermal This is the oral reference dose, GLABS is the gastrointestinal absorption rate, and RfC is...inh This is the respiratory reference dose;

[0036] Step A3, using formula (6), obtain the total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration. i ,y i ):

[0037] HI(x i ,y i ) = HQ dermal-nocar (x i ,y i )+HQ inh-nocar (x i ,y i (6)

[0038] This yields the total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration. i ,y i ).

[0039] Preferably, in step S6, the total carcinogenic risk index CR(x) attributable to atmospheric heavy metal concentration is obtained in the following manner. i ,y i );

[0040] Step B1: Using formulas (7) and (8), the average daily carcinogenic exposure dose (ADD) of heavy metals entering the human body via the skin adhesion pathway in the target area during the simulated year is statistically calculated. dermal-car (x i ,y i (EC) and the carcinogenic daily exposure dose of heavy metals entering the body through the respiratory route. inh-car (x i ,y i ):

[0041]

[0042] Where: SA is the exposed skin surface area, AF is the skin adhesion, ABS is the skin absorption coefficient, BW is the average body weight, EF is the number of days of exposure per year, ED is the number of years of exposure, and AT is the number of days of exposure per year. car It is the average number of days of carcinogenic exposure, CF is the conversion factor, ET is the daily exposure time, and AT is the average number of days of carcinogenic exposure. inh-car It is the average number of days of carcinogenic exposure via the respiratory route;

[0043] Step B2: Using formulas (9) and (10), the carcinogenic risk index CR under the skin adhesion exposure pathway is obtained. dermal-car (x i ,y i ) and the carcinogenic risk index CR under respiratory exposure route inh-car (xi ,y i ):

[0044] CR dermal-car (x i ,y i ) = ADD dermal-car (x i ,y i )×(SF0 / GLABS) (9)

[0045] CR inh-car (x i ,y i ) = EC inh-car (x i ,y i )×IUR (10)

[0046] Where: SF0 is the carcinogenic slope coefficient of heavy metals, GLABS is the gastrointestinal absorption rate, and IUR is the inhalation reference dose;

[0047] Step B3, using formula (11), obtain the total carcinogenic risk index CR(x) attributable to atmospheric heavy metal concentration. i ,y i );

[0048] CR(x i ,y i ) = CR dermal-nocar (x i ,y i )+CR inh-nocar (x i ,y i (11)

[0049] This leads to the total carcinogenic risk index CR(x) attributable to atmospheric heavy metal concentration. i ,y i ).

[0050] Preferably, step S7 specifically includes:

[0051] Using formulas (12) and (13), the non-carcinogenic risk quotient Q is obtained respectively. HI (x i ,y i ) and the carcinogenic risk quotient Q CR (x i ,y i ):

[0052] Q HI (x i ,y i )=HI(x i ,y i ) / 1 (12)

[0053] Q CR (x i ,y i )=CR(x i ,y i ) / (1×10 -4 (13)

[0054] This step is now complete.

[0055] Preferably, in step S9, when setting the emission source reduction strategy, the atmospheric heavy metal concentration reduction Δc is obtained using formula (14). hm (x i ,y i ):

[0056]

[0057] The decrease in atmospheric heavy metal concentration Δc hm (x i ,y i ) as a source of atmospheric heavy metal emissions hm (x j ,y j ,z j Based on the reduction criteria, set emission source reduction strategies.

[0058] Preferably, based on the decrease in atmospheric heavy metal concentration Δc hm (x i ,y i Identify atmospheric heavy metal emission sources (ES) hm (x j ,y j ,z j The amount of heavy metal emissions that need to be reduced in the atmosphere ΔE hm (x j ,y j ,z j Using formula (15), the reduced atmospheric heavy metal emissions E are obtained. hm-Q (x j ,y j ,z j ):

[0059] E hm-Q (x j ,y j ,z j ) = E hm (x j ,y j ,z j )-ΔE hm (x j ,y j ,zj (15)

[0060] This step is now complete.

[0061] The method for estimating atmospheric heavy metal environmental capacity provided by this invention has the following advantages:

[0062] This invention provides a method for estimating the environmental capacity of atmospheric heavy metals. Compared with existing environmental capacity estimation methods, this method expands the types of pollutants from fine particulate matter and its precursors to atmospheric heavy metals, advances the constraints based on pollutant concentration to constraints based on public health, and uses iterative calculations to obtain reasonable environmental capacity results. This invention fills the gap in atmospheric heavy metal environmental capacity estimation methods, upgrades the constraints of environmental capacity estimation methods, elevates the goal of atmospheric environmental pollution prevention and control from improving air quality to reducing public health risks, and provides technical support for the coordinated emission reduction of multiple pollutants. Attached Figure Description

[0063] Figure 1 A flowchart of a method for estimating atmospheric heavy metal environmental capacity provided by the present invention. Detailed Implementation

[0064] To make the technical problems solved, the technical solutions, and the beneficial effects of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the invention.

[0065] This invention provides a method for estimating the atmospheric heavy metal environmental capacity, addressing the aforementioned problems in existing technologies. This invention provides technical support for determining the upper limit of atmospheric heavy metal carrying capacity, controlling heavy metal emissions, formulating heavy metal emission reduction plans, and promoting air quality improvement.

[0066] See Figure 1 This invention provides a method for estimating the atmospheric heavy metal environmental capacity, comprising the following steps:

[0067] Step S1: Obtain basic topographic and meteorological data of the target area to be estimated;

[0068] In this step, the basic topographic and meteorological data includes the topography, underlying surface data, and initial meteorological boundary data of the target area. The topography of the target area is a high-resolution horizontal topography of the target area; the underlying surface data includes, but is not limited to, land use types and building heights of the target area.

[0069] Step S2: Perform three-dimensional meshing on the target area and divide it into N layers in the vertical z direction from bottom to top. The coordinates of any grid point i in the three-dimensional mesh are represented as (xi,yi,zi), where zi = 1, 2, ..., N, and zi = 1 is the layer closest to the ground. As an application, the vertical z direction can be divided into no less than 20 layers starting from the ground and moving upwards.

[0070] The basic topographic and meteorological data are input into the mesoscale meteorological model WRF, which outputs the meteorological data of the target area for each time period t and each grid i in the simulated year.

[0071] For example, the mesoscale meteorological model WRF outputs the meteorological data of the target area for each time period t and each grid i in the simulated year, including: the east-west component of the horizontal wind u(x) i ,y i ,z i ), the north-south component of horizontal wind v(x) i ,y i ,z i Vertical wind speed w(x) i ,y i ,z i ), temperature T(x i ,y i ,z i ), boundary layer height h(x) i ,y i ), Precipitation prec(x) i ,y i ), relative humidity RH(x) i ,y i ,z i ), water vapor mixing ratio Q vapor (x i ,y i ,z i ) and cloud-water mixing ratio Q cloud (x i ,y i ,z i ).

[0072] Step S3, determine the atmospheric heavy metal emission scheme, including: atmospheric heavy metal emission source ES hm The number of deployments, each atmospheric heavy metal emission source ES hm The location of the layout and each atmospheric heavy metal emission source ES hm Atmospheric heavy metal emissions E hm and emission time; where, let the number of arrangements be M, and the arrangement location be represented as (x j ,y j ,z j), j = 1, 2, ..., M;

[0073] Step S4: Input the atmospheric heavy metal emission scheme and the meteorological data obtained in step S2 into the air quality model; the air quality model, under the influence of the meteorological data, simulates the atmospheric heavy metal propagation mode to obtain the daily grid-by-grid i heavy metal concentration c of the target area in the simulated year. hm (x i ,y i ,z i );

[0074] As one implementation method, the air quality model can take the following form:

[0075]

[0076] Where: C hm It represents the heavy metal concentration, ΔH is the difference between tropospheric height and topographic height, t is time, θ and φ are latitude and longitude, R is the Earth's radius, and K is the Earth's radius. θ K φ K σ These are the meridional, zonal, and vertical turbulent diffusion coefficients, u and v are the horizontal wind speeds, W is the vertical wind speed, P is the chemical conversion rate, S is the source emission rate, and R is the vertical emission rate. d It is dry settlement, W ash It is the amount of wet cleaning.

[0077] Step S5, for z i =1 for each grid (x) i ,y i 1) Calculate the average daily heavy metal concentration for each grid cell during the simulated year. i ,y i ,1) Annual average atmospheric heavy metal concentration

[0078] Specifically, using formula (1), we obtain the value of each grid (x). i ,y i ,1) Annual average atmospheric heavy metal concentration :

[0079]

[0080] in: This represents the k-th day of the simulated year in grid (x). i ,y i The heavy metal concentrations of ,1); k=1,2,...,K, where K is the number of days in the simulated year.

[0081] Step S6, based on each grid (x i ,yi ,1) Annual average atmospheric heavy metal concentration The total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration was calculated. i ,y i ) and the total carcinogenic risk index CR(x) i ,y i );

[0082] Specifically, the total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentrations was obtained using the following method. i ,y i ):

[0083] Step A1: Using formulas (2) and (3), the non-carcinogenic daily exposure dose (ADD) of heavy metals entering the human body via the skin adhesion pathway in the target area during the simulated year is statistically calculated. dermal-nocar (x i ,y i (EC) and the non-carcinogenic daily exposure dose of heavy metals entering the body through the respiratory route. inh-nocar (x i ,y i ):

[0084]

[0085] Where: SA is the exposed skin surface area, AF is the skin adhesion, ABS is the skin absorption coefficient, BW is the average body weight, EF is the number of days of exposure per year, ED is the number of years of exposure, and AT is the number of days of exposure per year. nocar AT is the average non-carcinogenic exposure days, CF is the conversion factor, ET is the daily exposure time, and AT is the average non-carcinogenic exposure days. inh-nocar It is the average number of non-carcinogenic exposure days via the respiratory route;

[0086] Step A2: Using formulas (4) and (5), the non-carcinogenic risk index HQ under the skin adhesion exposure route is obtained. dermal-nocar (x i ,y i ) and the non-carcinogenic risk index HQ under respiratory exposure route inh-nocar (x i ,y i ):

[0087]

[0088] Among them: RfD dermal This is the oral reference dose, GLABS is the gastrointestinal absorption rate, and RfC is... inh This is the respiratory reference dose;

[0089] Step A3, using formula (6), obtain the total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration. i ,y i ):

[0090] HI(x i ,y i ) = HQ dermal-nocar (x i ,y i )+HQ inh-nocar (x i ,y i (6)

[0091] This yields the total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration. i ,y i ).

[0092] The total carcinogenic risk index CR(x) attributable to atmospheric heavy metal concentration was obtained using the following method. i ,y i );

[0093] Step B1: Using formulas (7) and (8), the average daily carcinogenic exposure dose (ADD) of heavy metals entering the human body via the skin adhesion pathway in the target area during the simulated year is statistically calculated. dermal-car (x i ,y i (EC) and the carcinogenic daily exposure dose of heavy metals entering the body through the respiratory route. inh-car (x i ,y i ):

[0094]

[0095] Where: SA is the exposed skin surface area, AF is the skin adhesion, ABS is the skin absorption coefficient, BW is the average body weight, EF is the number of days of exposure per year, ED is the number of years of exposure, and AT is the number of days of exposure per year. car It is the average number of days of carcinogenic exposure, CF is the conversion factor, ET is the daily exposure time, and AT is the average number of days of carcinogenic exposure. inh-car It is the average number of days of carcinogenic exposure via the respiratory route;

[0096] Step B2: Using formulas (9) and (10), the carcinogenic risk index CR under the skin adhesion exposure pathway is obtained. dermal-car (x i ,y i ) and the carcinogenic risk index CR under respiratory exposure route inh-car (x i ,y i ):

[0097] CRdermal-car (x i ,y i ) = ADD dermal-car (x i ,y i )×(SF0 / GLABS) (9)

[0098] CR inh-car (x i ,y i ) = EC inh-car (x i ,y i )×IUR (10)

[0099] Where: SF0 is the carcinogenic slope coefficient of heavy metals, GLABS is the gastrointestinal absorption rate, and IUR is the inhalation reference dose;

[0100] Step B3, using formula (11), obtain the total carcinogenic risk index CR(x) attributable to atmospheric heavy metal concentration. i ,y i );

[0101] CR(x i ,y i ) = CR dermal-nocar (x i ,y i )+CR inh-nocar (x i ,y i (11)

[0102] This leads to the total carcinogenic risk index CR(x) attributable to atmospheric heavy metal concentration. i ,y i ).

[0103] Step S7, calculate the total non-carcinogenic risk index HI(x) i ,y i The non-carcinogenic risk quotient Q is obtained by comparing it with the non-carcinogenic risk threshold 1 attributed to atmospheric heavy metal concentration. HI (x i ,y i ); The total carcinogenic risk index CR(x) i ,y i () and the carcinogenic risk threshold of 1×10 attributable to atmospheric heavy metal concentration -4 In comparison, the carcinogenic risk quotient Q was obtained. CR (x i ,y i );

[0104] Step S7 is as follows:

[0105] Using formulas (12) and (13), the non-carcinogenic risk quotient Q is obtained respectively. HI (x i ,y i ) and the carcinogenic risk quotient Q CR (x i ,y i ):

[0106] Q HI (x i ,y i )=HI(x i ,y i ) / 1 (12)

[0107] Q CR (x i ,y i )=CR(x i ,y i ) / (1×10 -4 (13)

[0108] This step is now complete.

[0109] Step S8, determine whether all atmospheric heavy metal emission sources ES are currently present. hm (x j ,y j ,z j If all atmospheric heavy metal emission sources ES that are not currently marked as having completed capacity assessments are to be marked as having completed capacity assessments, proceed to step S10; otherwise, for each atmospheric heavy metal emission source ES that is not currently marked as having completed capacity assessments, proceed to step S10. hm (x j ,y j ,z j ), obtain its value in z i = Non-carcinogenic risk quotient Q of a 1-layer projected grid HI (x j ,y j ) and the carcinogenic risk quotient Q CR (x j ,y j If Q HI (x j ,y j ) < 1 or Q CR (x j ,y j If the value is less than 1, it indicates that the non-carcinogenic and carcinogenic risks attributable to atmospheric heavy metal concentrations are less than the threshold constraint, and the atmospheric heavy metal emission source ES is determined to be... hm (x j ,y j ,z j Atmospheric heavy metal emissions E hm (x j ,yj ,z j ), which is the grid (x) it arranges. j ,y j ,z j Atmospheric heavy metal environmental capacity Q hm (x j ,y j ,z j ), and mark the capacity assessment as complete; if Q HI (x j ,y j )≥1 or Q CR (x j ,y j A value ≥ 1 indicates that the non-carcinogenic and carcinogenic risks attributable to atmospheric heavy metal concentrations are greater than the threshold constraint, thus determining the current atmospheric heavy metal emission source ES. hm (x j ,y j ,z j Atmospheric heavy metal emissions E hm (x j ,y j ,z j ) is not a grid (x j ,y j ,z j Atmospheric heavy metal environmental capacity Q hm (x j ,y j ,z j It is necessary to formulate an ESC (Environmental Safety System) for atmospheric heavy metal emission sources. hm (x j ,y j ,z j If the emission reduction plan is implemented, then step S9 is executed;

[0110] Step S9, for all unmarked atmospheric heavy metal emission sources ES that have completed capacity assessments. hm (x j ,y j ,z j According to the established emission source reduction strategy, the atmospheric heavy metal emissions are adjusted to obtain the reduced atmospheric heavy metal emissions E. hm-Q (x j ,y j ,z j ), using the reduced atmospheric heavy metal emissions E hm-Q (x j ,y j ,z j Update the atmospheric heavy metal emissions in step S3, and then return to step S3;

[0111] In this step, when setting the emission source reduction strategy, the atmospheric heavy metal concentration reduction Δc is obtained using formula (14). hm (x i ,y i ):

[0112]

[0113] The decrease in atmospheric heavy metal concentration Δc hm (x i ,y i ) as a source of atmospheric heavy metal emissions hm (x j ,y j ,z j Based on the reduction criteria, set emission source reduction strategies.

[0114] Specifically, based on the decrease in atmospheric heavy metal concentration Δc hm (x i ,y i Identify atmospheric heavy metal emission sources (ES) hm (x j ,y j ,z j The amount of heavy metal emissions that need to be reduced in the atmosphere ΔE hm (x j ,y j ,z j Using formula (15), the reduced atmospheric heavy metal emissions E are obtained. hm-Q (x j ,y j ,z j ):

[0115] E hm-Q (x j ,y j ,z j ) = E hm (x j ,y j ,z j )-ΔE hm (x j ,y j ,z j (15)

[0116] This step is now complete.

[0117] In practical applications, this invention does not limit how to formulate emission source reduction strategies. For example, the emission source reduction principle can be: prioritize the reduction of Δc. hm (x i ,y i ) and E hm (xj ,y j ,z j E) of atmospheric heavy metal emissions from regions with relatively large emissions and significant contributions to the transmission to other regions hm (x j ,y j ,z j The reduction method can be: in each iteration of the calculation, based on the atmospheric heavy metal emission amount ΔE hm (x j ,y j ,z j The reduction will be carried out step by step at a rate of 1%.

[0118] Step S10: Output the ES of each atmospheric heavy metal emission source obtained at this time. hm (x j ,y j ,z j The atmospheric heavy metal environmental capacity Q at the location of the ) hm (x j ,y j ,z j ), and completed the estimation of atmospheric heavy metal environmental capacity.

[0119] In practical applications, when estimating the atmospheric heavy metal environmental capacity based on population health risk constraints, supercomputing clusters can be used to complete the estimation task.

[0120] This invention provides a method for estimating the environmental capacity of atmospheric heavy metals. Compared with existing environmental capacity estimation methods, this method expands the types of pollutants from fine particulate matter and its precursors to atmospheric heavy metals, advances the constraints based on pollutant concentration to constraints based on public health, and uses iterative calculations to obtain reasonable environmental capacity results. This invention fills the gap in atmospheric heavy metal environmental capacity estimation methods, upgrades the constraints of environmental capacity estimation methods, elevates the goal of atmospheric environmental pollution prevention and control from improving air quality to reducing public health risks, and provides technical support for the coordinated emission reduction of multiple pollutants.

[0121] This invention can serve the national air pollution prevention and control field, providing a scientific basis for determining the upper limit of atmospheric environmental carrying capacity, effectively formulating prevention and control measures, optimizing the allocation of environmental capacity in time and space, and promoting the continuous improvement of air quality and the continuous reduction of public health risks.

[0122] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for estimating the atmospheric heavy metal environmental capacity, characterized in that, Includes the following steps: Step S1: Obtain basic topographic and meteorological data of the target area to be estimated; Step S2: Perform 3D meshing on the target area, dividing it into N layers in the vertical z-axis from bottom to top. The coordinates of any grid point i in the 3D mesh are represented as: (x i ,y i ,z i ), z i =1,2,…,N,z i =1 represents the layer closest to the ground; The basic topographic and meteorological data are input into the mesoscale meteorological model WRF, which outputs the meteorological data of the target area for each time period t and each grid i in the simulated year. Step S3, determine the atmospheric heavy metal emission scheme, including: atmospheric heavy metal emission source ES hm The number of deployments, each atmospheric heavy metal emission source ES hm The location of the layout and each atmospheric heavy metal emission source ES hm Atmospheric heavy metal emissions E hm and emission time; where, let the number of arrangements be M, and the arrangement location be represented as (x j ,y j ,z j ), j = 1, 2, ..., M; Step S4: Input the atmospheric heavy metal emission scheme and the meteorological data obtained in step S2 into the air quality model; the air quality model, under the influence of the meteorological data, simulates the atmospheric heavy metal propagation mode to obtain the daily grid-by-grid i heavy metal concentration c of the target area in the simulated year. hm (x i ,y i ,z i ); Step S5, for z i =1 for each grid (x) i ,y i 1) Calculate the average daily heavy metal concentration for each grid cell during the simulated year. i ,y i ,1) Annual average atmospheric heavy metal concentration Step S6, based on each grid (x i ,y i ,1) Annual average atmospheric heavy metal concentration The total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration was calculated. i ,y i ) and the total carcinogenic risk index CR(x) i ,y i ); Step S7, calculate the total non-carcinogenic risk index HI(x) i ,y i The non-carcinogenic risk quotient Q is obtained by comparing it with the non-carcinogenic risk threshold 1 attributed to atmospheric heavy metal concentration. HI (x i ,y i ); The total carcinogenic risk index CR(x) i ,y i () and the carcinogenic risk threshold of 1×10 attributable to atmospheric heavy metal concentration -4 In comparison, the carcinogenic risk quotient Q was obtained. CR (x i ,y i ); Step S8, determine whether all atmospheric heavy metal emission sources ES are currently present. hm (x j ,y j ,z j If all atmospheric heavy metal emission sources ES that are not currently marked as having completed capacity assessments are to be marked as having completed capacity assessments, proceed to step S10; otherwise, for each atmospheric heavy metal emission source ES that is not currently marked as having completed capacity assessments, proceed to step S10. hm (x j ,y j ,z j ), obtain its value in z i = Non-carcinogenic risk quotient Q of a 1-layer projected grid HI (x j ,y j ) and the carcinogenic risk quotient Q CR (x j ,y j If Q HI (x j ,y j ) < 1 or Q CR (x j ,y j If ) < 1, then the atmospheric heavy metal emission source ES is determined. hm (x j ,y j ,z j Atmospheric heavy metal emissions E hm (x j ,y j ,z j ), which is the grid (x) it arranges. j ,y j ,z j Atmospheric heavy metal environmental capacity Q hm (x j ,y j ,z j ), and mark the capacity assessment as complete; if Q HI (x j ,y j )≥1 or Q CR (x j ,y j If )≥1, then proceed to step S9; Step S9, for all unmarked atmospheric heavy metal emission sources ES that have completed capacity assessments. hm (x j ,y j ,z j According to the established emission source reduction strategy, the atmospheric heavy metal emissions are adjusted to obtain the reduced atmospheric heavy metal emissions E. hm-Q (x j ,y j ,z j ), using the reduced atmospheric heavy metal emissions E hm-Q (x j ,y j ,z j Update the atmospheric heavy metal emissions in step S3, and then return to step S3; Step S10: Output the ES of each atmospheric heavy metal emission source obtained at this time. hm (x j ,y j ,z j The atmospheric heavy metal environmental capacity Q at the location of the ) hm (x j ,y j ,z j ), and completed the estimation of atmospheric heavy metal environmental capacity.

2. The method for estimating atmospheric heavy metal environmental capacity according to claim 1, characterized in that, The basic topographic and meteorological data includes the topography, underlying surface data, and initial meteorological boundary data of the target area.

3. The method for estimating atmospheric heavy metal environmental capacity according to claim 2, characterized in that, The terrain of the target area is a high-resolution horizontal terrain of the target area; the underlying surface data includes the land use type and building height of the target area.

4. The method for estimating atmospheric heavy metal environmental capacity according to claim 1, characterized in that, The mesoscale meteorological model WRF outputs the meteorological data of the target area for each time period t and each grid i in the simulated year, including: the east-west component of horizontal wind u(x) i ,y i ,z i ), the north-south component of horizontal wind v(x) i ,y i ,z i Vertical wind speed w(x) i ,y i ,z i ), temperature T(x i ,y i ,z i ), boundary layer height h(x) i ,y i ), Precipitation prec(x) i ,y i ), relative humidity RH(x) i ,y i ,z i ), water vapor mixing ratio Q vapor (x i ,y i ,z i ) and cloud-water mixing ratio Q cloud (x i ,y i ,z i ).

5. The method for estimating atmospheric heavy metal environmental capacity according to claim 1, characterized in that, In step S5, formula (1) is used to obtain the value of each grid (x). i ,y i ,1) Annual average atmospheric heavy metal concentration in: This represents the k-th day of the simulated year in grid (x). i ,y i The heavy metal concentrations of ,1); k=1,2,...,K, where K is the number of days in the simulated year.

6. The method for estimating atmospheric heavy metal environmental capacity according to claim 1, characterized in that, In step S6, the total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration is obtained using the following method. i ,y i ): Step A1: Using formulas (2) and (3), the non-carcinogenic daily exposure dose (ADD) of heavy metals entering the human body via the skin adhesion pathway in the target area during the simulated year is statistically calculated. dermal-nocar (x i ,y i (EC) and the non-carcinogenic daily exposure dose of heavy metals entering the body through the respiratory route. inh-nocar (x i ,y i ): Where: SA is the exposed skin surface area, AF is the skin adhesion, ABS is the skin absorption coefficient, BW is the average body weight, EF is the number of days of exposure per year, ED is the number of years of exposure, and AT is the number of days of exposure per year. nocar AT is the average non-carcinogenic exposure days, CF is the conversion factor, ET is the daily exposure time, and AT is the average non-carcinogenic exposure days. inh-nocar It is the average number of non-carcinogenic exposure days via the respiratory route; Step A2: Using formulas (4) and (5), the non-carcinogenic risk index HQ under the skin adhesion exposure route is obtained. dermal-nocar (x i ,y i ) and the non-carcinogenic risk index HQ under respiratory exposure route inh-nocar (x i ,y i ): Among them: RfD dermal This is the oral reference dose, GLABS is the gastrointestinal absorption rate, and RfC is... inh This is the respiratory reference dose; Step A3, using formula (6), obtain the total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration. i ,y i ): HI(x i ,and i )=HQ dermal-nocar (x i ,and i )+HQ inh-nocar (x i ,and i ) (6) This yields the total non-carcinogenic risk index HI(x) attributable to atmospheric heavy metal concentration. i ,y i ).

7. The method for estimating atmospheric heavy metal environmental capacity according to claim 1, characterized in that, In step S6, the total carcinogenic risk index CR(x) attributable to atmospheric heavy metal concentration is obtained using the following method. i ,y i ); Step B1: Using formulas (7) and (8), the average daily carcinogenic exposure dose (ADD) of heavy metals entering the human body via the skin adhesion pathway in the target area during the simulated year is statistically calculated. dermal-car (x i ,y i (EC) and the carcinogenic daily exposure dose of heavy metals entering the body through the respiratory route. inh-car (x i ,y i ): Where: SA is the exposed skin surface area, AF is the skin adhesion, ABS is the skin absorption coefficient, BW is the average body weight, EF is the number of days of exposure per year, ED is the number of years of exposure, and AT is the number of days of exposure per year. car It is the average number of days of carcinogenic exposure, CF is the conversion factor, ET is the daily exposure time, and AT is the average number of days of carcinogenic exposure. inh-car It is the average number of days of carcinogenic exposure via the respiratory route; Step B2: Using formulas (9) and (10), the carcinogenic risk index CR under the skin adhesion exposure pathway is obtained. dermal-car (x i ,y i ) and the carcinogenic risk index CR under respiratory exposure route inh-car (x i ,y i ): CR dermal-car (x i ,y i )=ADD dermal-car (x i ,y i )×(SF0 / GLABS) (9) CR inh-car (x i ,y i )=EC inh-car (x i ,y i )×IUR (10) Where: SF0 is the carcinogenic slope coefficient of heavy metals, GLABS is the gastrointestinal absorption rate, and IUR is the inhalation reference dose; Step B3, using formula (11), obtain the total carcinogenic risk index CR(x) attributable to atmospheric heavy metal concentration. i ,y i ); CR(x i ,y i )=CR dermal-nocar (x i ,y i )+CR inh-nocar (x i ,y i ) (11) This yields the total carcinogenic risk index CR(x) attributable to atmospheric heavy metal concentration. i ,y i ).

8. The method for estimating atmospheric heavy metal environmental capacity according to claim 1, characterized in that, Step S7 is as follows: Using formulas (12) and (13), the non-carcinogenic risk quotient Q is obtained respectively. HI (x i ,y i ) and the carcinogenic risk quotient Q CR (x i ,y i ): Q HI (x i ,y i )=HI(x i ,y i ) / 1 (12) Q CR (x i ,y i )=CR(x i ,y i ) / (1×10 -4 ) (13) This step is now complete.

9. The method for estimating atmospheric heavy metal environmental capacity according to claim 1, characterized in that, In step S9, when setting the emission source reduction strategy, the atmospheric heavy metal concentration reduction Δc is obtained using formula (14). hm (x i ,y i ): The decrease in atmospheric heavy metal concentration Δc hm (x i ,y i ) as a source of atmospheric heavy metal emissions hm (x j ,y j ,z j Based on the reduction criteria, set emission source reduction strategies.

10. The method for estimating atmospheric heavy metal environmental capacity according to claim 9, characterized in that, Based on the decrease in atmospheric heavy metal concentration Δc hm (x i ,y i Identify atmospheric heavy metal emission sources (ES) hm (x j ,y j ,z j The amount of heavy metal emissions that need to be reduced in the atmosphere ΔE hm (x j ,y j ,z j Using formula (15), the reduced atmospheric heavy metal emissions E are obtained. hm-Q (x j ,y j ,z j ): E hm-Q (x j ,y j ,z j )=E hm (x j ,y j ,z j )-ΔE hm (x j ,y j ,z j ) (15) This step is now complete.

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