Estimation method of atmospheric heavy metal environmental capacity

Abstract

The invention provides a method for estimating atmospheric heavy metal environmental capacity. The method comprises the following steps: acquiring basic topographic and meteorological data of a to-be-estimated target area; determining an atmospheric heavy metal emission scheme; obtaining the day-by-day grid-by-grid heavy metal concentration of the target area in the simulation year by adopting an air quality model; and calculating to obtain a non-carcinogenic risk quotient value and a carcinogenic risk quotient value, comparing with 1 to judge whether an atmospheric heavy metal emission scheme needs to be adjusted, and obtaining the atmospheric heavy metal environmental capacity of the emission source arrangement position until the non-carcinogenic risk quotient value or the carcinogenic risk quotient value is less than 1. According to the method, pollutant types are expanded from fine particulate matters and precursors thereof to atmospheric heavy metals, constraint based on pollutant concentration is promoted to constraint of crowd health, and a reasonable environmental capacity result is obtained by utilizing iterative calculation. According to the invention, the goal of atmospheric environmental pollution prevention and control work is improved from improvement of air quality to reduction of crowd health risks, and technical support is provided for cooperative emission reduction work of various pollutants.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of air pollution prevention and control, and particularly relates to a method for estimating the environmental capacity of heavy metals in the atmosphere. BACKGROUND

[0002] A large amount of toxic and harmful substances, such as black carbon, polycyclic aromatic hydrocarbons, heavy metals and bacteria viruses, are attached to fine particulate matters in the ambient air. As an important toxic and harmful component, heavy metals can enter the human body through the respiratory tract and deposit, endangering the function of human organs and even causing irreversible damage to the human body. Heavy metals existing in the atmosphere include lead, cadmium, chromium, arsenic, nickel, cobalt and the like. The estimation result of the environmental capacity of heavy metals in the atmosphere is the basis for formulating measures for reducing the emission of heavy metals in the atmosphere.

[0003] The current environmental capacity calculation method mainly takes the compliance of pollutant concentration as a constraint condition, and the widely used environmental capacity calculation methods mainly include A-value method, linear optimization method, model simulation method and the like. The model simulation method is further divided into a model algorithm based on the analysis of physical and chemical processes and an iterative simulation optimization method.

[0004] The A-value method is based on the principle of the box model, assumes that the environmental capacity is in direct proportion to the atmospheric environmental self-purification capacity and the area of the region, only considers natural factors, does not reflect the characteristics of the emission source and the chemical conversion process, is suitable for the atmospheric environmental capacity under ideal conditions, and is not suitable for the environmental capacity under the compliance constraints of fine particulate matters and ozone, and has the advantages of simplicity and convenience.

[0005] The linear optimization method is based on the linear optimization theory to calculate the atmospheric environmental capacity, links the pollution sources and their diffusion processes with the control points, takes the compliance of the concentration of the target control point as a constraint, and determines the maximum allowable emission of the pollution source through a multi-source model and a mathematical programming method. The linear optimization method is mainly suitable for small-scale regions, can reflect the response relationship between "emission-receptor", and can optimize the allocation of the atmospheric environmental capacity, but the method is restricted by the linear assumption and cannot handle the secondary air pollution problems with nonlinear characteristics.

[0006] The iterative simulation optimization method is based on the dynamic spatial transmission matrix, the industry contribution matrix and the precursor contribution matrix, establishes a multi-objective nonlinear optimization model, obtains multiple optimization emission reduction schemes, and through iterative simulation, obtains the pollutant emission amount corresponding to the compliance of the air quality, which is the atmospheric environmental capacity. The method can take into account the influence of natural factors such as meteorology and topography and human factors such as the spatial and industrial distribution characteristics of the pollution sources on the atmospheric environmental capacity, effectively overcomes the shortcomings of the traditional methods, and can reflect the complex atmospheric physical and chemical processes, but the method is based on the ideal assumption that the spatial and industrial distribution characteristics of the pollution sources do not change significantly, cannot optimize the allocation of the atmospheric environmental capacity, and is complex in technology and huge in calculation amount.

[0007] The mode algorithm based on the analysis of physical and chemical processes: considering that the atmospheric environmental capacity refers to the maximum allowable emission amount meeting the fine particulate matter standard, the atmospheric environmental capacity of fine particulate matter and precursors based on the fine particulate matter standard is obtained by air quality mode calculation. The method divides the atmospheric environmental capacity into two parts, atmospheric dynamic capacity and static capacity, which are indispensable. The dynamic capacity considers that the actual pollutant concentration and the given pollutant concentration threshold jointly act on the processes of transport, diffusion, sedimentation and chemical transformation, and the calculation result represents the maximum dynamic allowable emission amount.

[0008] The existing environmental capacity calculation method mainly takes fine particulate matter and its precursors as the calculation object, and only takes the concentration standards of fine particulate matter, sulfur dioxide, nitrogen oxides or inhalable particulate matter and other pollutants as constraint conditions. There is no environmental capacity estimation method taking atmospheric heavy metals as the calculation object, and there is no consideration of the health effects of the population due to the concentration of atmospheric heavy metals. SUMMARY

[0009] In view of the defects in the prior art, the present application provides an estimation method for atmospheric heavy metal environmental capacity, which can effectively solve the above problems.

[0010] The technical scheme adopted by the present application is as follows:

[0011] The present application provides an estimation method for atmospheric heavy metal environmental capacity, comprising the following steps:

[0012] Step S1, obtaining the basic terrain meteorological data of the target area to be estimated;

[0013] Step S2, performing three-dimensional gridding processing on the target area, dividing it into N layers in the vertical z direction from bottom to top, and the three-dimensional grid point coordinates of any grid i are represented as: (x i ,y i ,z i ), z i =1,2,…,N,z i =1 is the layer closest to the ground;

[0014] Input the basic terrain meteorological data into the mesoscale meteorological model WRF, and the mesoscale meteorological model WRF outputs the meteorological data of each grid i of the target area at each time period t in the simulation year;

[0015] Step S3, determining the atmospheric heavy metal emission scheme, including: the arrangement number of atmospheric heavy metal emission sources ES hm , the arrangement position of each atmospheric heavy metal emission source ES hm , and the atmospheric heavy metal emission amount E hm and emission time of each atmospheric heavy metal emission source ES hm ; wherein, the arrangement number is M, the arrangement position is 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 jz j ) update the atmospheric heavy metal emission amount of step S3, and then return to step S3;

[0022] Step S10, output the atmospheric heavy metal environmental capacity Q hm (x j ,y j ,z j ) of the layout position of each atmospheric heavy metal emission source ES hm (x j ,y j ,z j ) obtained at this time, complete the atmospheric heavy metal environmental capacity estimation.

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

[0024] Preferably, the terrain of the target area is a horizontal high-resolution terrain of the target area; the underlying surface data includes 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 in the simulation year at each time period t and each grid i, including: horizontal wind east-west component u(x i ,y i ,z i ), horizontal wind north-south component v(x i ,y i ,z i ), vertical wind speed w(x i ,y i ,z i ), air 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 ,1) of the atmospheric heavy metal concentration i ,1) of the atmospheric heavy metal concentration

[0027]

[0028] wherein: represents the heavy metal concentration at the grid (x i ,y i ,1) on the kth day of the simulation year; k = 1, 2,..., K, K being the number of days the simulation year has.

[0029] Preferably, in step S6, the following way is adopted to obtain the total non-carcinogenic risk index HI(x i ,y i ) attributed to the atmospheric heavy metal concentration:

[0030] In step Al, the non-carcinogenic daily exposure dose ADD dermal-nocar (x i ,y i ) of the heavy metal into the human body from the dermal adhesion pathway and the non-carcinogenic daily exposure dose EC inh-nocar (x i ,y i ) of the heavy metal into the human body from the respiratory pathway in the target area in the simulation year are calculated statistically by using formula (2) and formula (3):

[0031]

[0032] wherein: SA is the exposed skin surface area, AF is the dermal adhesion, ABS is the skin absorption coefficient, BW is the per capita body weight, EF is the annual exposure days, ED is the exposure years, AT nocar is the non-carcinogenic average exposure days, CF is the conversion coefficient, ET is the daily exposure time, AT inh-nocar is the non-carcinogenic average exposure days through the respiratory pathway;

[0033] In step A2, the non-carcinogenic risk index HQ dermal-nocar (x i ,y i ) under the dermal adhesion exposure pathway and the non-carcinogenic risk index HQ inh-nocar (x i ,y i ) under the respiratory exposure pathway are obtained respectively by using formula (4) and formula (5):

[0034]

[0035] wherein: RfD dermal is the oral reference dose, GLABS is the gastrointestinal absorption rate, RfCinh For respiratory reference dose;

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

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

[0038] Thus, the total non-carcinogenic risk index HI(x i ,y i ) attributed to atmospheric heavy metal concentration is obtained.

[0039] Preferably, in step S6, the total carcinogenic risk index CR(x i ,y i ) attributed to atmospheric heavy metal concentration is obtained in the following way:

[0040] Step B1, using formula (7) and formula (8), the carcinogenic daily exposure dose ADD dermal-car (x i ,y i ) of heavy metal into human body from the skin adhesion pathway and the carcinogenic daily exposure dose EC inh-car (x i ,y i ) of heavy metal into human body from the respiratory pathway in the target area in the simulation year are calculated:

[0041]

[0042] wherein SA is the exposed skin surface area, AF is the skin adhesion, ABS is the skin absorption coefficient, BW is the per capita body weight, EF is the annual exposure days, ED is the exposure period, AT car is the carcinogenic average exposure days, CF is the conversion coefficient, ET is the daily exposure time, and AT inh-car is the carcinogenic average exposure days through the respiratory pathway;

[0043] Step B2, using formula (9) and formula (10), the carcinogenic risk index CR dermal-car (x i ,y i ) under the skin adhesion exposure pathway and the carcinogenic risk index CR 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] Wherein: SF0 is the carcinogenic slope factor of heavy metal, GLABS is the gastrointestinal absorption rate, IUR is the inhalation reference concentration;

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

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

[0049] Thus the total carcinogenic risk index CR(x i ,y i ) attributed to atmospheric heavy metal concentration is obtained.

[0050] Preferably, step S7 is specifically:

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

[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 x 10 -4 ) (13)

[0054] This step ends.

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

[0056]

[0057] The atmospheric heavy metal concentration reduction amount Δc hm (x i ,y i ) is taken as the basis for reducing the atmospheric heavy metal emission source ES hm (x j ,y j ,z j ), and the emission source reduction strategy is set.

[0058] Preferably, according to the atmospheric heavy metal concentration reduction amount Δc hm (x i ,y i ), the atmospheric heavy metal emission amount ΔE hm (x j ,y j ,z j ) required to be reduced by the atmospheric heavy metal emission source ES hm (x j ,y j ,z j ) is determined, formula (15) is used, and thus the reduced atmospheric heavy metal emission amount E hm-Q (x j ,y j ,z j ) is obtained:

[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 finished.

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

[0062] Compared with the existing environmental capacity estimation method, the method for estimating the atmospheric heavy metal environmental capacity provided by the present application expands the pollutant types from fine particulate matter and its precursors to atmospheric heavy metals, promotes the constraint based on the pollutant concentration to the constraint of human health, and obtains reasonable environmental capacity results by using iterative calculation. The present application fills the gap of the atmospheric heavy metal environmental capacity estimation method, upgrades the constraint conditions of the environmental capacity estimation method, improves the goal of atmospheric environmental pollution prevention and control work from improving air quality to reducing the health risk of the population, and provides technical support for the coordinated emission reduction of multiple pollutants. BRIEF DESCRIPTION OF DRAWINGS

[0063] Figure 1 The flowchart of the method for estimating the atmospheric heavy metal environmental capacity provided by the present application is shown. DETAILED DESCRIPTION

[0064] In order to make the technical problems, technical solutions and beneficial effects solved by the present application clearer, the present application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0065] The present application provides a method for estimating the atmospheric heavy metal environmental capacity, which is used to solve the foregoing problems in the prior art. The present application provides technical support for determining the upper limit of atmospheric heavy metal carrying capacity, controlling heavy metal emission, formulating heavy metal emission reduction scheme and promoting air quality improvement.

[0066] Referring to Figure 1 The present application provides a method for estimating the atmospheric heavy metal environmental capacity, which comprises the following steps:

[0067] Step S1, obtaining the basic terrain meteorological data of the target region to be estimated;

[0068] In this step, the basic terrain meteorological data includes the terrain, underlying surface data and meteorological initial boundary data of the target region. The terrain of the target region is the horizontal high-resolution terrain of the target region; the underlying surface data includes but is not limited to the land use type and building height of the target region.

[0069] Step S2, the target area is three-dimensionally gridded, divided into N layers in the vertical z direction from bottom to top, and the three-dimensional grid point coordinates of any grid i are represented as: (xi, yi, zi), zi=1, 2, …, N, zi=1 being the layer closest to the ground; as an application, the vertical z direction can be divided into not less than 20 layers from the ground upwards.

[0070] The base terrain meteorological data is input into a mesoscale meteorological model WRF, and the mesoscale meteorological model WRF outputs the meteorological data of the target area in the simulation year at each time step t and each grid i;

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

[0072] Step S3, determining an atmospheric heavy metal emission scheme, including: the number of arrangements of atmospheric heavy metal emission sources ES hm , the arrangement positions of each atmospheric heavy metal emission source ES hm , and the atmospheric heavy metal emission amount E hm and emission time of each atmospheric heavy metal emission source ES hm ; wherein the number of arrangements is M, and the arrangement positions are 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 The annual average of atmospheric heavy metal concentration of the target area The total non-carcinogenic risk index HI(x i ,y i ) and the total carcinogenic risk index CR(x i ,y i ) attributed to the atmospheric heavy metal concentration are calculated;

[0082] Specifically, the total non-carcinogenic risk index HI(x i ,y i ) attributed to the atmospheric heavy metal concentration is obtained in the following way:

[0083] Step A1, the non-carcinogenic daily exposure dose ADD dermal-nocar (x i ,y i ) of heavy metals into the human body from the skin adhesion pathway and the non-carcinogenic daily exposure dose EC inh-nocar (x i ,y i ) of heavy metals into the human body from the respiratory pathway of the target area in the simulation year are calculated statistically by using formula (2) and formula (3):

[0084]

[0085] Wherein, SA is the exposed skin surface area, AF is the skin adhesion degree, ABS is the skin absorption coefficient, BW is the average body weight, EF is the number of exposure days per year, ED is the exposure period, AT nocar is the non-carcinogenic average exposure days, CF is the conversion coefficient, ET is the daily exposure time, and AT inh-nocar is the non-carcinogenic average exposure days through the respiratory pathway;

[0086] Step A2, the non-carcinogenic risk index HQ dermal-nocar (x i ,y i ) under the skin adhesion exposure pathway and the non-carcinogenic risk index HQ inh-nocar (x i ,y i ) under the respiratory exposure pathway are obtained respectively by using formula (4) and formula (5):

[0087]

[0088] Wherein, RfD dermal is the oral reference dose, GLABS is the gastrointestinal absorption rate, and RfC inh is the respiratory reference dose;

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

[0092] The total carcinogenic risk index CR(x i ,y i ) attributed to the atmospheric heavy metal concentration is obtained in the following way;

[0093] Step B1, the carcinogenic daily exposure dose ADD dermal-car (x i ,y i ) of the heavy metal into the human body from the skin adhesion pathway and the carcinogenic daily exposure dose EC inh-car (x i ,y i ) of the heavy metal into the human body from the respiratory pathway in the target area in the simulation year are calculated statistically by using formula (7) and formula (8):

[0094]

[0095] wherein SA is the exposed skin surface area, AF is the skin adhesion degree, ABS is the skin absorption coefficient, BW is the per capita body weight, EF is the annual exposure days, ED is the exposure period, AT car is the carcinogenic average exposure days, CF is the conversion coefficient, ET is the daily exposure time, and AT inh-car is the carcinogenic average exposure days through the respiratory pathway;

[0096] Step B2, the carcinogenic risk index CR dermal-car (x i ,y i ) under the skin adhesion exposure pathway and the carcinogenic risk index CR inh-car (x i ,y i ) under the respiratory exposure pathway are obtained respectively by using formula (9) and formula (10):

[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] wherein SF0 is the carcinogenic slope factor of heavy metal, GLABS is the gastrointestinal absorption rate, and IUR is the inhalation reference concentration;

[0100] Step B3, the total carcinogenic risk index CR(x i ,y i ) attributed to the atmospheric heavy metal concentration is obtained by using formula (11);

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

[0102] Thus, the total carcinogenic risk index CR(x i ,y i ) attributed to the atmospheric heavy metal concentration is obtained.

[0103] Step S7, the total non-carcinogenic risk index HI(x i ,y i ) is compared with the non-carcinogenic risk threshold value 1 attributed to the atmospheric heavy metal concentration to obtain a non-carcinogenic risk quotient Q HI (x i ,y i ); and the total carcinogenic risk index CR(x i ,y i ) is compared with the carcinogenic risk threshold value 1×10 -4 attributed to the atmospheric heavy metal concentration to obtain a carcinogenic risk quotient Q CR (x i ,y i );

[0104] Step S7 is specifically:

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

[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 ends.

[0109] Step S8, judge whether all the atmospheric heavy metal emission sources ES hm (x j ,y j ,z j ) are marked as capacity evaluation completed; if yes, execute step S10; if no, for each atmospheric heavy metal emission source ES hm (x j ,y j ,z j ) which is not marked as capacity evaluation completed, obtain its non-carcinogenic risk quotient Q HI (x j ,y j ) and carcinogenic risk quotient Q CR (x j ,y j ) of the projection grid in z i =1 layer, if Q HI (x j ,y j ) <1 or Q CR (x j ,y j ) <1, indicating that the non-carcinogenic and carcinogenic risks due to atmospheric heavy metal concentration are less than the threshold constraint, then determine that the atmospheric heavy metal emission amount E hm (x j ,y j ,z j ) of the atmospheric heavy metal emission source ES hm (x j ,yj ,z j ), its arranged grid (x j ,y j ,z j ) of atmospheric heavy metal environmental capacity Q hm (x j ,y j ,z j ), and mark the capacity evaluation complete; if Q HI (x j ,y j ) ≥ 1 or Q CR (x j ,y j ) ≥ 1, indicating that the non-carcinogenic and carcinogenic risks due to atmospheric heavy metal concentration are greater than the threshold constraint, determine that the atmospheric heavy metal emission amount E hm (x j ,y j ,z j ) of the current atmospheric heavy metal emission source ES hm (x j ,y j ,z j ) is not the atmospheric heavy metal environmental capacity Q j (x j ,y j ,z hm ) of the grid (x j ,y j ,z j ), and an emission amount reduction scheme for the atmospheric heavy metal emission source ES hm (x j ,y j ,z j ) needs to be developed, then step S9 is executed;

[0110] Step S9, for all the current various atmospheric heavy metal emission sources ES hm (x j ,y j ,z j ) whose capacity evaluation completion is not marked, adjust its atmospheric heavy metal emission amount according to the set emission source reduction strategy, to obtain the reduced atmospheric heavy metal emission amount E hm-Q (x j ,y j ,z j ), update the atmospheric heavy metal emission amount of step S3 with the reduced atmospheric heavy metal emission amount E hm-Q (x j ,y j ,z j ), 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 ) are large, and the atmospheric heavy metal emissions E hm (x j ,y j ,z j ) of other areas contribute significantly, the reduction method can be: in each iteration calculation, the atmospheric heavy metal emissions ΔE hm (x j ,y j ,z j ) is reduced by 1% at each level.

[0118] Step S10, output the layout position of each atmospheric heavy metal emission source ES hm (x j ,y j ,z j ) obtained at this time Atmospheric heavy metal environmental capacity Q hm (x j ,y j ,z j ) is completed Atmospheric heavy metal environmental capacity estimation.

[0119] In practical application, when estimating the atmospheric heavy metal environmental capacity based on the population health risk constraint, the supercomputer cluster can be used to complete the estimation task.

[0120] The present application provides an atmospheric heavy metal environmental capacity estimation method, compared with the existing environmental capacity estimation method, the method extends the pollutant species from fine particulate matter and its precursor to atmospheric heavy metal, and promotes the constraint based on the pollutant concentration to the constraint of population health, and uses iterative calculation to obtain reasonable environmental capacity results. The present application fills the gap of atmospheric heavy metal environmental capacity estimation method, upgrades the constraint condition of environmental capacity estimation method, improves the goal of atmospheric environmental pollution prevention and control work from improving air quality to reducing population health risk, and provides technical support for collaborative emission reduction of multiple pollutants.

[0121] The present application can serve the field of national atmospheric pollution prevention and control, provide scientific basis for determining the upper limit of atmospheric environmental carrying capacity, effectively formulating prevention and control measures, and optimizing the allocation of environmental capacity in time and space, and promoting the continuous improvement of air quality and the continuous reduction of population health risk.

[0122] The above is only the preferred embodiment of the present application, it should be pointed out that, for those skilled in the technical field, without departing from the principle of the present application, a number of improvements and refinements can be made, these improvements and refinements should be regarded as the protection scope of the present application.

Claims

1. A method of estimating the environmental capacity of heavy metals in the atmosphere, characterized by, The method comprises the following steps: S1, obtaining basic terrain meteorological data of a target region to be estimated; Step S2, the target area is three-dimensional gridding processing, in the vertical z direction is divided into N layers from bottom to top direction, any grid i three-dimensional grid point coordinates are represented as: (x i ,y i ,z i ), z i =1,2,…,N,z i =1 is the layer closest to the ground; inputting the basic terrain meteorological data into a mesoscale meteorological model WRF, wherein the mesoscale meteorological model WRF outputs per-grid i per-time-period t meteorological data of the target region in a simulation year; Step S3, determining the atmospheric heavy metal emission scheme, including: the arrangement number of the atmospheric heavy metal emission sources ES hm , the arrangement position of each atmospheric heavy metal emission source ES hm , and the atmospheric heavy metal emission amount E hm and the emission time of each atmospheric heavy metal emission source ES hm ; wherein, the arrangement number is M, and the arrangement position is represented as (x j ,y j ,z j ), j = 1, 2, …, M; Step S4, inputting the atmospheric heavy metal emission scheme and the meteorological data obtained in step S2 into an air quality model; the air quality model simulates the atmospheric heavy metal propagation mode under the action of the meteorological data to obtain the heavy metal concentration c of the target region in the simulation year per day per grid i hm (x i ,y i ,z i ); Step S5, for each grid (x i ,y i ,1) with z i =1, calculate the average of the heavy metal concentration at each day of the simulation year, to obtain the annual average of the atmospheric heavy metal concentration for each grid (x i ,y i ,1) 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, comparing the total non-carcinogenic risk index HI(x i ,y i ) with the non-carcinogenic risk threshold value 1 attributed to atmospheric heavy metal concentration, obtaining the non-carcinogenic risk quotient Q HI (x i ,y i ); comparing the total carcinogenic risk index CR(x i ,y i ) with the carcinogenic risk threshold value 1 x 10 -4 attributed to atmospheric heavy metal concentration, obtaining the carcinogenic risk quotient Q CR (x i ,y i ). Step S8, judging whether all the atmospheric heavy metal emission sources ES hm (x j ,y j ,z j ) are marked as the capacity evaluation being completed; if yes, executing step S10; if no, for each atmospheric heavy metal emission source ES hm (x j ,y j ,z j ) which is not marked as the capacity evaluation being completed, obtaining its non-carcinogenic risk quotient Q i (x HI ,y j ) and carcinogenic risk quotient Q j (x CR ,y j ) of the projection grid in the z j =1 layer, if Q HI (x j ,y j ) < 1 or Q CR (x j ,y j ) < 1, judging the atmospheric heavy metal emission amount E hm (x j ,y j ,z j ) of the atmospheric heavy metal emission source ES hm (x j ,y j ,z j ), the atmospheric heavy metal environmental capacity Q j (x j ,y j ,z hm ) of the grid (x j ,y j ,z j ) where it is arranged, and marking the capacity evaluation as completed; if Q HI (x j ,y j ) ≥ 1 or Q CR (x j ,y j ) ≥ 1, executing 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 of claim 1, wherein, The basic terrain meteorological data comprises terrain, underlying surface data and meteorological initial boundary data of the target region.

3. The method of claim 2, wherein, The terrain of the target region is horizontal-direction high-resolution terrain of the target region; the underlying surface data comprises land use types and building heights of the target region.

4. The method of claim 1, wherein, The mesoscale weather model WRF outputs the weather data of the target region at each time period t of the simulation year, including: horizontal wind east-west component u(x i ,y i ,z i ), horizontal wind south-north component v(x i ,y i ,z i ), vertical wind speed w(x i ,y i ,z i ), air 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 of claim 1, wherein, In step S5, the annual average atmospheric heavy metal concentration of each grid (x i ,y i ,1) is obtained by using formula (1) wherein: represents the heavy metal concentration at grid (x i ,y i ,1) on the kth day of the simulated year; k = 1, 2,..., K, K being the number of days the simulated year has.

6. The method of claim 1, wherein, In step S6, the total non-carcinogenic risk index HI(x i ,y i ) attributed to the atmospheric heavy metal concentration is obtained in the following manner: Step A1, the non-carcinogenic daily exposure dose of heavy metals entering the human body from the dermal adhesion pathway in the target area in the simulation year is calculated statistically using formula (2) and formula (3) dermal-nocar (x i ,y i ) and the non-carcinogenic daily exposure dose of heavy metals entering the human body from the respiratory pathway inh-nocar (x i ,y i ) where: SA is the exposed skin surface area, AF is the skin adhesion factor, ABS is the skin absorption coefficient, BW is the body weight per person, EF is the number of exposure days per year, ED is the exposure duration, AT nocar is the non-carcinogenic average exposure days, CF is the conversion factor, ET is the daily exposure time, AT inh-nocar is the non-carcinogenic average exposure days via the respiratory route; Step A2, the non-carcinogenic risk index HQ under the skin adhesion exposure route is obtained by using formula (4) and formula (5), respectively dermal-nocar (x i ,y i ) and the non-carcinogenic risk index HQ inh-nocar (x i ,y i ) under the respiratory exposure route: Where: RfD dermal is the oral reference dose, GLABS is the gastrointestinal absorption rate, RfC inh is the respiratory reference dose; Step A3, the total non-carcinogenic risk index HI(x i ,y i ) attributed to the atmospheric heavy metal concentration is obtained using formula (6): HI(x i ,y i ) = HQ dermal-nocar (x i ,y i ) + HQ inh-nocar (x i ,y i ) (6) From this the total non-carcinogenic risk index HI(x i ,y i ) attributed to the atmospheric heavy metal concentration is obtained.

7. The method of claim 1, wherein, In step S6, the total carcinogenic risk index CR(x i ,y i ) attributable to the atmospheric heavy metal concentration is obtained in the following manner: Step B1, the target area's carcinogenic daily exposure dose of heavy metals from the dermal adhesion pathway into the human body in the simulation year is calculated statistically using Formula (7) and Formula (8) dermal-car (x i ,y i ) and the carcinogenic daily exposure dose of heavy metals from the respiratory pathway into the human body in the simulation year is calculated statistically using Formula (9) and Formula (10) inh-car (x i ,y i ) wherein: SA is the exposed skin surface area, AF is the skin adhesion factor, ABS is the skin absorption coefficient, BW is the body weight per person, EF is the number of exposure days per year, ED is the exposure duration, AT car is the carcinogenic average exposure days, CF is the conversion factor, ET is the exposure time per day, AT inh-car is the carcinogenic average exposure days via the respiratory route; Step B2, the carcinogenic risk indices CR(x,y) under the skin adhesion exposure route and CR(x,y) under the respiratory exposure route are obtained respectively by using formula (9) and formula (10) dermal-car (x i ,y i ) and CR inh-car (x i ,y i ) CR dermal-car (x i ,y i ) = ADD dermal-car (x i ,y i ) x (SFO / GLABS) (9) CR inh-car (x i ,y i ) = EC inh-car (x i ,y i ) x IUR (10) Wherein: SF0 is the carcinogenic slope coefficient of the heavy metal, GLABS is the gastrointestinal absorption rate, and IUR is the inhalation reference amount; Step B3, the total carcinogenic risk index CR(x i ,y i ) attributed to the atmospheric heavy metal concentration is obtained by using formula (11). CR(x i ,y i ) = CR dermal-nocar (x i ,y i ) + CR inh-nocar (x i ,y i ) (11) From this the total carcinogenic risk index CR(x i ,y i ) attributable to the atmospheric heavy metal concentration is obtained.

8. The method of claim 1, wherein, S7 is specifically: Using equation (12) and equation (13), non-carcinogenic risk quotient Q HI (x i ,y i ) and carcinogenic risk quotient Q CR (x i ,y i ) are obtained, respectively. 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 ended.

9. The method of claim 1, wherein, In step S9, when the emission source reduction strategy is set, the atmospheric heavy metal concentration reduction amount Δc is obtained using formula (14) hm (x i ,y i ): The atmospheric heavy metal concentration reduction amount Δc hm (x i ,y i ) as the atmospheric heavy metal emission source ES hm (x j ,y j ,z j ) reduction basis, set the emission source reduction strategy.

10. The method of claim 9, wherein, According to the decrease Ac of the atmospheric heavy metal concentration hm (x i ,y i ) determine the atmospheric heavy metal emission source ES hm (x j ,y j ,z j ) the atmospheric heavy metal emission amount ΔE hm (x j ,y j ,z j ) that needs to be reduced, using formula (15), thereby obtaining the reduced atmospheric heavy metal emission amount E 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 ended. This step is ended.

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