CN115203948A - Urban street valley street tree species selection method for improving air quality - Google Patents

Abstract

The invention provides an air quality improvement-oriented tree species selection method for urban street valley street trees, which comprises the following steps: acquiring daily change data of typical weather parameters of a target area, typical street space form types, common street tree form state characteristics and hourly discharge rate of air pollutants discharged by a motor vehicle; constructing various typical street valley models, carrying out numerical simulation one by one, and then carrying out statistical analysis and evaluation, wherein the relative change rate of the exposure risk scores of residents in the street valleys is used as an index during evaluation; according to the evaluation result, selecting the tree species corresponding to the tree form with the relatively low resident exposure risk score relative change rate as the optimal street tree species in the street valley, and making a street tree shaping and trimming strategy by referring to the tree form. The method quantitatively evaluates the influence of the planting schemes of the street trees in different forms on the exposure risk of street valley residents, and provides accurate basis for the selection of the types of the street trees and the shaping and trimming.

Description

A method for selecting tree species for urban street valleys for air quality improvement

technical field

The invention belongs to the technical field of urban street valley greening design, and in particular relates to a method for selecting tree species on street valleys in an urban street valley for air quality improvement.

Background technique

Urban street canyons (street valleys) are an important part of the urban underlying surface and carry the important functions of urban residents' transportation and daily life. With the surge in the number of motor vehicles, traffic emissions have become the main source of urban air pollution. Air pollutants such as PM2.5, PM10, and NOx generated by their emissions can induce cardiovascular and respiratory diseases, posing a serious threat to the health of urban residents. Especially roadside pedestrians and people who live and work near the road. With the development of high-rise and high-density buildings in metropolitan areas, the natural ventilation and air circulation in street valleys have declined significantly, and air pollution control has become increasingly urgent.

In the existing urban built environment, the spatial elements of street valleys cannot be easily changed. In addition to measures such as controlling the number of motor vehicles, reducing the emission intensity per unit of vehicle, and promoting the use of new energy vehicles, street valley greening is considered to be one of the most important aspects of the greening because it can affect the diffusion and settlement of air pollutants and has strong operability. An effective and economical way to deal with vehicle exhaust pollution. The adsorption and deposition of the leaves and branches of the street trees in the green plants in the street valley can effectively reduce the concentration of pollutants, but the canopy can also hinder the movement of airflow, reducing the air exchange between the interior of the street valley and the atmosphere above. Under most environmental conditions, the aerodynamic effects of road trees have a far stronger negative impact on the diffusion and dilution of pollutants in street valleys than the positive effects of sedimentation effects. Inappropriate tree species selection and tree planting exacerbate the accumulation and concentration of air pollutants in street valleys. risk. In the prior art, ignoring the influence of various tree morphological characteristics on the diffusion and deposition of air pollutants, the greening model of high-density planting of street trees is obviously inapplicable in the process of alleviating air pollution in street valleys, and the most suitable method is to combine trees. The regulation mechanism of morphology on air pollutants "planting the right trees in different street valleys".

Therefore, in order to better exert the ecological benefits of street tree greening in alleviating air pollution in street valleys, it is urgent to optimize the selection method of street tree species for the improvement of street valley air quality. Synergistic effects of pollutants, scientifically formulate street tree species selection and shaping and pruning strategies that are suitable for specific street valley environments. Improve street valley air quality while meeting the needs of landscaping and thermal comfort improvement.

SUMMARY OF THE INVENTION

The technical problem to be solved by the present invention is to provide a method for selecting tree species in urban street valleys for air quality improvement. The tree species are classified and typical street tree models with different morphological characteristics are constructed, and the impact of street trees with different morphological characteristics on the air pollution exposure of pedestrians in street valleys is evaluated by numerical simulation, and then street tree species that are conducive to alleviating air pollution in street valleys are selected. Develop tree shaping and pruning strategies to optimize the ecological benefits of street trees to improve air quality in street valleys.

In order to solve the above-mentioned technical problems, the technical scheme adopted in the present invention is: a method for selecting tree species on the street in urban street valleys for air quality improvement, characterized in that the method includes:

S1. Pre-analysis stage: collect the meteorological parameters of the target area, the morphological parameters of street canyons, and the individual morphological parameters of common street trees, and conduct sorting and analysis to obtain the daily variation data of typical meteorological parameters of the target area, and the spatial form of typical street canyons. Types, types of commonly used street trees and morphological characteristics of commonly used street trees, as well as the hourly emission rate of air pollutants emitted by motor vehicles in corresponding types of street canyons in the target area; the morphological parameters of the street canyons include building height, building arrangement, road width, building material and road material;

S2. Numerical simulation stage: build a variety of typical street canyon models based on the morphological parameters of the street canyons and the individual morphological parameters of common street trees, and carry out numerical simulations one by one;

S3. Analysis and evaluation stage: carry out statistical analysis on the numerical simulation results of various typical street canyon models constructed in S2 in combination with data processing methods, and evaluate the statistical results. During the evaluation, the relative change rate of the residents’ exposure risk scores in the street canyon is used. index;

S4. Plan generation stage: According to the evaluation results, select the tree species corresponding to the tree form with a relatively low relative change rate of the residents' exposure risk score as the optimal street tree species in the corresponding type of street valley, and refer to the tree shape to formulate this type of street valley street tree species Shaping and pruning strategies.

Preferably, in S2, a typical street canyon model is constructed based on the morphological parameters of the street canyon and the individual morphological parameters of common street trees, and numerical simulation is carried out, including:

Step 201: Select ENVI-met microclimate simulation software as the numerical simulation tool;

Step 202: Set the traffic pollutant discharge source in the target area in the software database, determine the discharge height, discharge method and discharge rate of the traffic pollutant discharge source, and carry out the process in combination with the set values of the individual morphological parameters of the common street tree. Determine tree morphological types by free combination, and customize the street tree model corresponding to each tree morphological type in the target area;

Step 203: According to the traffic pollutant emission source set in step 202 and the morphological parameters of the street canyon described in S1, combined with the street tree model described in step 202 and the layout pattern of street canyons, construct multiple types of street trees corresponding to various types of street trees. A typical street canyon model, in which the street tree model of each tree form type corresponds to a typical street canyon model;

Step 204: In the multiple typical street valley models constructed in step 203, the daily variation data of the typical meteorological parameters of the target area are used as boundary conditions, and the incoming wind speed, wind direction, air temperature, relative humidity and urban roughness are set. , carry out 24-hour simulation under this background environment, and obtain hourly air pollutant concentration data in street valleys under each typical street valley model.

Preferably, the street canyon aspect ratio is calculated by the ratio between the building height and the road width, and the rules for setting the street canyon aspect ratio in the microclimate simulation software are:

The street canyon shape is classified according to the aspect ratio of the street canyon. The specific classification is as follows: when the aspect ratio of the street canyon is less than or equal to 0.5, the value is set to 0.5 in the numerical simulation; when the aspect ratio of the street canyon is greater than 0.5 and less than 1.5 , the value is set to 1 during the numerical simulation; when the aspect ratio of the street canyon is greater than 1.5 and less than 2.5, the value is set to 2 during the numerical simulation; when the aspect ratio of the street canyon is greater than or equal to 2.5, the value is set during the numerical simulation The value is 3;

The rules for setting values of individual morphological parameters of common street trees in the microclimate simulation software are:

The tree morphology is classified according to the individual morphological parameters of common street trees, and the values for numerical simulation are set; the individual morphological parameters of common street trees include the area density of street leaves, tree height, height under branches, and crown width; specifically:

When the leaf area density is less than or equal to 1, the leaf area density is set to be 1 in the numerical simulation; when the leaf area density is greater than 1 and less than 2.5, the leaf area density is set to be 1.5 in the numerical simulation; When it is greater than or equal to 2.5, the leaf area density is set to be 3 during numerical simulation;

When the tree height is less than or equal to 8, the tree height is set to 6 during the numerical simulation; when the tree height is greater than 8 and less than 12, the tree height is set to 10 during the numerical simulation; when the tree height is greater than or equal to 12, During numerical simulation, the tree height is set to be 14;

When the height under the branch is less than or equal to 3, the value of the height under the branch is set to 3 during the numerical simulation; when the height under the branch is greater than 3, the value of the height under the branch is set to 5 during the numerical simulation;

When the crown width is less than or equal to 4, the crown width is set as 3 in numerical simulation; when the crown width is greater than 4 and less than 8, the crown width is set as 6 in numerical simulation; when the crown width is greater than or equal to 8, In the numerical simulation, the crown amplitude is set to be 9.

Preferably, the numerical simulation results of various typical street canyon models constructed in S2 are statistically analyzed in combination with the data processing method in S3, and the statistical results are evaluated, and the relative change rate of the residents' exposure risk scores in the street canyon is used as an indicator during the evaluation. ; specifically:

Step 301: Use software to visualize the numerical simulation results, and perform mathematical statistics on the simulation data to obtain the average value of air pollutant concentrations on the sidewalks on both sides of the street valley in a day;

Step 302: Combine the exposure time, respiration rate and sensitivity to traffic emission pollutants exposure of different types of people in the city, calculate the exposure risk scores of residents in pedestrian areas in street valleys near motor vehicle emission sources under different scenarios, and the calculation formula is as follows:

In the formula, ERF is the resident exposure risk score; Pi is the total number of people in category _{i; RT i is} the per capita respiratory rate of group i, in m ³ /s; ET _i is the per capita population in category i Exposure time, the unit is h/d, Qi is the sensitivity coefficient of the _i -th population to the traffic discharge pollutant exposure; C is the average air pollutant concentration at the height of 1.5m on the sidewalk, the unit is kg/m ³ ; E is the consideration period The total emission of pollutants, the unit is kg; the population is divided into three categories, n is 1, 2, 3, including the elderly, adults, children, the first category of people refers to the elderly, the second category of people refers to adults Humans, group 3 refers to children, whose breathing rate and exposure time are shown in the table below:

Crowd category elderly adults Child Respiratory rate (m³/d) 10-15 15-20 10-14 Exposure time (h/d) 0.8-1.5 1.5-3 1-1.5

Step 303: Calculate the relative change of the exposure risk scores of residents in the tree-planted street valley and the tree-free street valley in multiple typical street valley models. The calculation formula is as follows:

In the formula, ΔERF is the relative change rate of the residents' exposure risk score; ERF _tree is the residents' exposure risk score in the tree-planting street valley; ERF _tree-free is the residents' exposure risk score in the tree-free street valley;

If the relative change rate of the residents' exposure risk score in the typical street valley model is less than 0, the street tree species with the corresponding tree form is obtained as the tree species selected for planting;

If the relative change of the resident exposure risk score in the typical street valley model is greater than 0, the tree species corresponding to the tree form with a small relative change rate of the resident exposure risk score is selected.

Compared with the prior art, the present invention has the following advantages:

1. The present invention combines street valley morphological parameters and tree morphological parameters to classify urban street valleys and street trees, build corresponding models, and use the method of numerical simulation to screen street tree shapes and their corresponding tree species that are conducive to improving the air quality of street valleys , to plant the correct trees in the correct location in the street valley, so as to optimize the ecological benefits of street trees and improve the air quality of the street valley, which has important theoretical and practical significance for the construction and sustainable development of a healthy city.

2. The present invention combines the influence of street trees on the diffusion and adsorption of air pollutants, and comprehensively considers the synergistic effect of meteorological conditions, street valley morphology and other factors, and quantitatively evaluates the impact of street trees with different morphological characteristics on the air pollution exposure of street valley pedestrians, It provides accurate tree species selection and shaping and pruning basis for street tree planting for the improvement of air quality in street valleys. A scientific approach to optimizing the microclimate benefits of street trees and reducing their potential negative consequences for air quality.

The technical solutions of the present invention will be further described in detail below through the accompanying drawings and embodiments.

Description of drawings

FIG. 1 is an operation flow of a method for selecting tree species for urban street valleys for air quality improvement disclosed in Embodiment 1 of the present invention.

Fig. 2 is a tree morphological type model diagram constructed according to Example 1 of the present invention, Fig. 2-(1) is a street tree with high leaf density, medium tree height, low branch height, medium crown width (DMSM), and the corresponding tree species is Platanus, Figure 2-(2) A street tree with medium leaf density, low tree height, low branch height and narrow crown width (MSLN), the corresponding tree species is Ginkgo biloba.

Fig. 3 is a street valley model constructed according to Example 1 of the present invention, Fig. 3-(1) is a three-dimensional schematic diagram of a street valley model with a tree shape of DMSM, Fig. 3-(2) is a three-dimensional street valley model with a tree shape of MSLN signal.

Fig. 4 is a graph of the concentration difference of pollutants in a street valley simulated according to Example 1 of the present invention, Fig. 4-(1) is a graph of the concentration difference of pollutants between a tree-planting street valley and a tree-free street valley where the tree form is DMSM, Fig. 4-(2) is the difference in pollutant concentration between the tree-planted street valley with MSLN and the tree-free street valley.

Detailed ways

Example 1

As shown in FIG. 1, an embodiment of the present invention is a method for selecting street tree species in urban street valleys for air quality improvement, the method includes:

S1. Preliminary analysis stage: obtain the daily variation data of typical meteorological parameters in the target area, the spatial form types of typical street valleys, the types of commonly used street trees and the morphological characteristics of commonly used street trees, and the corresponding types of street valleys in the target area. Motor vehicles emit air pollutants hourly emission rate; specifically includes:

Determine the research city area, take an imaginary small-area city as an example, collect the meteorological parameters of the target area, the meteorological parameters include air temperature, relative humidity, wind speed, wind direction, and organize the daily variation data of typical meteorological parameters;

Conduct on-the-spot investigation on the street valley environmental information such as building height, building material, building arrangement, building form, road width, road material, street canyon aspect ratio, etc., and obtain the basic information of street valley according to the classification in Table 1. The method determines the spatial form type of typical street canyons; the street canyon aspect ratio is the ratio of building height to road width;

Measure the characteristic parameters of common street trees in the target area on the spot, record the tree species, leaf area index (LAI) or leaf area density (LAD), tree height, crown width, tree shape and other data information, and table 2 The proposed tree morphological classification standard is used to organize the data, and determine the tree species corresponding to each tree morphological;

Find the traffic flow data of the road corresponding to the typical street valley spatial form type in the target area, count the hourly motor vehicle traffic flow, and query the motor vehicle emission factor at the same time, calculate the hourly pollutant emission rate generated by the corresponding road vehicles, and investigate Whether there are other pollutant emission sources within 5km around the corresponding street valley, if so, measure the pollutant concentration in the non-motorized area as the background concentration.

S2. Numerical simulation stage: Based on the morphological parameters of the street canyons and the individual morphological parameters of common street trees, a variety of typical street canyon models are constructed, and numerical simulations are carried out one by one; the specific implementation is achieved through the following steps:

Step 201: Select ENVI-met microclimate simulation software as a numerical simulation tool. ENVI-met mainly includes modules such as Space, ENVI-guide, ENVI-core, Leonardo, etc., which can input basic parameters, conduct simulation, and visualize simulation results;

Step 202: Set the traffic pollutant discharge source in the target area in the software database, determine the discharge height, discharge method and discharge rate of the traffic pollutant discharge source, and carry out the process in combination with the set values of the individual morphological parameters of the common street tree. Determine the tree morphological types by free combination, and customize the street tree model corresponding to each tree morphological type in the target area; the 3D models of street trees of different morphological types are shown in Figure 2;

Step 203: According to the traffic pollutant emission source set in step 202 and the morphological parameters of the street canyon described in S1, combined with the layout pattern of the street tree model street valley street tree described in step 202, construct a plurality of street trees corresponding to various types of street trees. Typical street valley model, in which the street tree model of each tree type corresponds to a typical street valley model; the typical street valley model is shown in Figure 3;

The street canyon aspect ratio is calculated by the ratio between the building height and the road width. The rules for setting the street canyon aspect ratio in the microclimate simulation software are:

The street canyon shape is classified according to the height-width ratio of the street canyon, and the specific classification is shown in Table 1.

Table 1 Classification of typical street valleys

type Aspect ratio (H/W) range Apply value Class I H/W≤0.5 0.5 Class II 0.5＜H/W＜1.5 1 Class III 1.5＜H/W＜2.5 2 Class IV H/W≥2.5 3

The rules for setting values of the individual morphological parameters of common street trees in the microclimate simulation software are: classify the tree morphology according to the individual morphological parameters of common street trees, and set the values for numerical simulation; the individual morphological parameters of common street trees Including the leaf area density, tree height, under-branch height, and crown width on the sidewalk; the specific classification is shown in Table 2.

Table 2. Individual morphological parameters of common street trees to tree morphological classification

Step 204: Set the incoming wind speed, wind direction, air temperature, relative humidity and urban roughness according to the daily variation data of typical meteorological parameters in the multiple typical street valley models constructed in step 203. A 24-hour simulation was carried out under the background environmental conditions to obtain hourly air pollutant concentration data in each typical street valley model. Specifically, set the boundary conditions in the ENVI-guide module;

S3. Analysis and evaluation stage: carry out statistical analysis on the numerical simulation results of various typical street canyon models constructed in S2 in combination with data processing methods, and evaluate the statistical results. During the evaluation, the relative change rate of the residents’ exposure risk scores in the street canyon is used. Indicator; it is achieved through the following steps:

Step 301: Using the Leonardo module to visualize the results of the numerical simulation, the difference in pollutant concentration between the pedestrian heights of the two typical street valley models is shown in Figure 4, and further perform mathematical statistics on the simulated data to obtain the interior of the street valley in one day. The average value of air pollutant concentrations on both sides of the sidewalk;

Step 302: Combine the exposure time, respiration rate and sensitivity to traffic emission pollutants exposure of different types of people in the city, calculate the exposure risk scores of residents in pedestrian areas in street valleys near motor vehicle emission sources under different scenarios, and the calculation formula is as follows:

In the formula, ERF is the resident exposure risk score; Pi is the total number of people in category _{i; RT i is} the per capita respiratory rate of group i, in m ³ /s; ET _i is the per capita population in category i Exposure time, the unit is h/d, Qi is the sensitivity coefficient of the _i -th population to the traffic discharge pollutant exposure; C is the average air pollutant concentration at the height of 1.5m on the sidewalk, the unit is kg/m ³ ; E is the consideration period The total emission of pollutants, the unit is kg; the population is divided into three categories, n is 1, 2, 3, including the elderly, adults, children, the first category of people refers to the elderly, the second category of people refers to adults Humans, group 3 refers to children, whose breathing rate and exposure time are shown in the table below:

Crowd category elderly adults Child Respiratory rate (m³/d) 10-15 15-20 10-14 Exposure time (h/d) 0.8-1.5 1.5-3 1-1.5

Step 303: Calculate the relative change of the exposure risk scores of residents in the tree-planted street valley and the tree-free street valley in multiple typical street valley models. The calculation formula is as follows:

In the formula, ΔERF is the relative change rate of the residents' exposure risk score; ERF _tree is the residents' exposure risk score in the tree-planting street valley; ERF _tree-free is the residents' exposure risk score in the tree-free street valley;

According to the calculated relative change rates of the residents' exposure risk scores in the multiple typical street valley models, if the relative change rate of the residents' exposure risk scores in the typical street valley models is less than 0, the street tree species with the corresponding tree shape is obtained as the Alternative planting tree species; if the relative change of the resident exposure risk score in the typical street valley model is greater than 0, the tree species corresponding to the tree form with a small relative change rate of the resident exposure risk score is selected as the alternative planting tree species. Finally, according to the alternative planting tree species, combined with the actual situation of the target area, determine the planting tree species. It can be seen from the calculation that the average ΔERF on both sides of the street valley with tree morphology is DMSM is 8.00%, and the average ΔERF on both sides of street valley with tree morphology is 3.70%.

S4. Scheme generation stage: According to the evaluation results, the ginkgo tree corresponding to the tree form MSLN with a relatively low relative change rate of the residents' exposure risk score is selected as the optimal street tree species in the corresponding type of street valley, and the street tree shaping and pruning are formulated with reference to the tree shape. Strategies to shape and prune planted street trees to reduce their negative impact on the spread of air pollutants.

The above descriptions are only preferred embodiments of the present invention, and do not limit the present invention in any way. Any simple modifications, changes and equivalent changes made to the above embodiments according to the technical essence of the invention still fall within the protection scope of the technical solutions of the present invention.

Claims (4)

1. A method for selecting tree species of urban street valley street trees for improving air quality is characterized by comprising the following steps:

s1, a preliminary analysis stage: collecting meteorological parameters of a target area, morphological parameters of street canyons and individual morphological parameters of common street trees for sorting and analyzing, and acquiring daily change data of typical meteorological weather parameters, space morphological types of typical street canyons, types of common street trees and tree morphological characteristics of common street trees of the target area, and hourly discharge rates of air pollutants discharged by motor vehicles in corresponding types of street canyons of the target area; the morphological parameters of the street canyon comprise building height, building arrangement, road width, building materials and road materials;

s2, a numerical simulation stage: constructing various typical street valley models based on the morphological parameters of the street canyons and the individual morphological parameters of the common street trees, and developing numerical simulation one by one;

s3, analysis and evaluation stage: carrying out statistical analysis on the numerical simulation results of the various typical valley models constructed in the S2 by combining a data processing method, and evaluating the statistical results, wherein the relative change rate of the exposure risk scores of residents in the valley is used as an index during evaluation;

s4, a scheme generation stage: and selecting a tree species corresponding to a tree form with a relatively low resident exposure risk score relative change rate as an optimal street tree species in the street valley according to the evaluation result, and making a street tree pruning strategy by referring to the tree form.

2. The method for selecting tree species of street valley street trees for improving air quality as claimed in claim 1, wherein in S2, a typical street valley model is constructed based on morphological parameters of the street canyons and individual morphological parameters of common street trees, and numerical simulation is carried out, specifically comprising:

step 201: selecting ENVI-met microclimate simulation software as a numerical simulation tool;

step 202: setting a traffic pollutant emission source of a target area in a software database, determining the emission height, the emission mode and the emission rate of the traffic pollutant emission source, simultaneously combining the set values of the individual form parameters of the common street trees to freely combine to determine various tree form types, and customizing a street tree model corresponding to each tree form type of the target area;

step 203: according to the traffic pollutant emission source set in the step 202 and the form parameters of the street canyon in the S1, in combination with the street tree model in the step 202 and the layout mode of street valley street trees, constructing a plurality of typical street valley models corresponding to various types of street trees, wherein each street tree model of the tree form type corresponds to one typical street valley model;

step 204: <xnotran> 203 , , , , , , 24 , . </xnotran>

3. The method for selecting the tree species of the urban street valley street trees oriented to the air quality improvement, according to the claim 2, is characterized in that the street canyon aspect ratio is calculated by the ratio of the building height to the road width, and the rule of the street canyon aspect ratio set in the microclimate simulation software is as follows:

the street valley morphology is classified according to the street valley height-width ratio, and the specific classification is as follows: when the street canyon height-to-width ratio is less than or equal to 0.5, setting the value to be 0.5 during numerical simulation; when the street canyon height-to-width ratio is more than 0.5 and less than 1.5, setting the value to be 1 during numerical simulation; when the street canyon height-to-width ratio is more than 1.5 and less than 2.5, setting the value to be 2 during numerical simulation; when the street canyon height-to-width ratio is more than or equal to 2.5, setting the value to be 3 during numerical simulation;

the rule of setting the value of the individual morphological parameters of the common street trees in the microclimate simulation software is as follows:

classifying tree forms according to individual form parameters of common street trees, and setting values during numerical simulation; the individual morphological parameters of the common street trees comprise the area density of the leaves of the street trees, the height of the trees, the height under the branches and the crown width; the method specifically comprises the following steps:

when the leaf area density is less than or equal to 1, setting the leaf area density to be 1 during numerical simulation; when the leaf area density is more than 1 and less than 2.5, setting the leaf area density to be 1.5 during numerical simulation; when the leaf area density is more than or equal to 2.5, setting the leaf area density to be 3 during numerical simulation;

when the tree height is less than or equal to 8, setting the tree height value to be 6 during numerical simulation; when the tree height is larger than 8 and smaller than 12, setting the tree height to be 10 during numerical simulation; when the tree height is greater than or equal to 12, setting the tree height value to be 14 during numerical simulation;

when the under-branch height is less than or equal to 3, setting the under-branch height value to be 3 during numerical simulation; when the under-branch height is larger than 3, setting the under-branch height to be 5 during numerical simulation;

when the crown width is less than or equal to 4, setting the crown width value to be 3 during numerical simulation; when the crown width is larger than 4 and smaller than 8, setting the crown width value to be 6 during numerical simulation; and when the crown width is more than or equal to 8, setting the crown width to be 9 during numerical simulation.

4. The method for selecting the tree species of the street valley street trees for improving the air quality as claimed in claim 2, wherein the statistical analysis is performed on the numerical simulation results of the various typical street valley models constructed in the step S2 by combining a data processing method in the step S3, and the statistical results are evaluated, wherein the relative change rate of the exposure risk scores of residents in the street valleys is used as an index during the evaluation; the method specifically comprises the following steps:

step 301: visualizing the numerical simulation result by using software, carrying out mathematical statistics on the simulation data, and obtaining the average value of the concentration of air pollutants of sidewalks at two sides inside a street valley in one day;

step 302: the method comprises the following steps of calculating the resident exposure risk score of a street valley pedestrian area close to a motor vehicle emission source under different situations by combining the exposure time, the breathing rate and the sensitivity to the traffic emission pollutant exposure of different types of urban crowds, wherein the calculation formula is as follows:

wherein ERF is the resident exposure score; p is _i Total number of people who are the ith group; RT (reverse transcription) _i The average human respiratory rate of the ith population is m ³ /s；ET _i Is the per-capita exposure time of the ith population in units of h/d, Q _i A sensitivity coefficient for exposure of the ith group to traffic emission pollutants; c is the average air pollutant concentration of the pedestrian path at the height of 1.5m, and the unit is kg/m ³ (ii) a E is the total pollutant emission in kg during consideration; the population is divided into three groups, wherein n is 1,2,3 and comprises the elderly, adults and children, the 1 st group refers to the elderly, the 2 nd group refers to the adults and the 3 rd group refers to the children, and the breathing rate and the exposure time are shown in the following table:

group of people Old people Adults Children's toy Respiration rate (m) ³ /d) 10-15 15-20 10-14 Exposure time (h/d) 0.8-1.5 1.5-3 1-1.5

Step 303: calculating the relative change of the exposure risk scores of residents in the tree-planted street valley and the non-tree street valley in a plurality of typical street valley models, wherein the calculation formula is as follows:

where Δ ERF is the relative rate of change of the resident exposure score; ERF _tree Is the exposure risk score of residents in the tree planting street valley; ERF _tree-free The exposure risk score of residents in the non-tree street valley is obtained;

if the relative change rate of the resident exposure risk scores in the typical street valley model is less than 0, obtaining the street tree species with corresponding tree forms as the tree species to be selectively planted;

and if the relative change of the resident exposure risk scores in the typical street valley model is larger than 0, selecting tree species corresponding to the tree forms with small relative change rates of the resident exposure risk scores.

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