A method for configuring garden plants to purify atmospheric particulate matter in urban green spaces

Abstract

The present invention relates to the technical field of urban planning, and specifically to a method for configuring garden plants for purifying atmospheric particulate matter in urban green spaces, including: performing parameter inversion based on the dry deposition module of air pollution in the UFORE model; calculating the dust retention amount per unit greening area in one cycle under different vegetation configurations, and iteratively determining the optimal ratio of different types of vegetation under various vegetation configurations through the maximum dust retention amount and the dust retention amount by particle size, so as to optimize the plant configuration; using R-type factor analysis to determine the weights of different vegetation configuration modes, thereby calculating the optimal dust retention configuration parameters; setting up different scenarios, and calculating the dust retention amount and its particle size composition characteristics in each administrative region of the city under this greening configuration, and finally combining different functional greening requirements, proposing configuration suggestions applicable to the urban roads and landscape greening in this city, which is more accurate than the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of urban planning, and particularly to a method for configuring garden plants for purifying atmospheric particulate matter in urban green spaces. Background Art

[0002] In the practice of plant selection and configuration, most consider the aesthetic and economic values of plant landscapes to complete the configuration of garden plants. The research on dust retention ability mostly focuses on a larger scale and cannot provide detailed and reliable green space structure configuration for improving the dust retention ability of green spaces and the atmospheric quality. In existing research, the leaf area index (LAI) and dust fall rate Vd in the purification effect of green space dust retention on the atmosphere through the UFORE model mostly come from literature research or empirical formulas. The leaf area index is only distinguished by plant types (broad-leaved forests, coniferous forests, deciduous forests, etc.), ignoring the differences caused by different plant species and the canopy differences caused by their different growth environments. The dust fall rate is mostly based on wind tunnel experiments, which require destroying the canopy structure. Compared with natural conditions, the experimental results have certain errors, and plant species are not applicable to this study.

[0003] The selection of domestic greening tree species mostly follows the principle of giving priority to native tree species, adapting to local conditions, and preferably selecting plants with strong stress resistance. In terms of plant configuration, attention is paid to the method of configuring plants in an irregular form through the natural morphological characteristics of plants, such as single planting, clump planting, group planting, belt planting, etc. With the introduction of the ecological design principle, more attention is paid to economic and beautifying functions in the configuration of green space plants, and relatively less attention is paid to landscape ecological benefits. The research on the dust retention characteristics of plant individuals and community structures at home and abroad has been relatively sufficient, but the comprehensive evaluation research on the dust retention effects of different green space types is relatively lacking. The combination of plant ecology and landscape effects, multi-level and three-dimensional landscapes in plant configuration in China still need to be improved. Although scholars at home and abroad believe that plant configuration should combine economy, ecology and aesthetics, the ecological research on plant configuration is mostly academic discussions, and the experiments are relatively complex and the index system is also uncertain. There is little discussion on the landscape effect in terms of aesthetic requirements, and it is even more difficult to correlate. Therefore, there are certain limitations in the practice of plant selection and configuration. Aiming at the problem that the research on the dust retention ability in the plant ecological effect at home and abroad mostly focuses on a larger scale and cannot provide detailed and reliable green space structure configuration for improving the dust retention ability of green spaces and the atmospheric quality. Summary of the Invention

[0004] (1) Object of the Invention

[0005] To solve the technical problems in the background art, the present invention proposes a method for configuring garden plants for purifying atmospheric particulate matter in urban green spaces.

[0006] (2) Technical Solution

[0007] To solve the above problems, the present invention provides a method for configuring garden plants for purifying atmospheric particulate matter in urban green spaces, including:

[0008] Performing parameter inversion based on the dry deposition module of air pollution in the UFORE model;

[0009] Calculating the dust retention amount per cycle per unit greening area under different vegetation configurations, and iteratively determining the optimal ratio of different types of vegetation under various vegetation configurations through the maximum dust retention amount and the dust retention amount by particle size, so as to optimize the plant configuration;

[0010] Using R-type factor analysis to determine the weights of different vegetation configuration patterns, so as to calculate the optimal configuration parameters for dust retention;

[0011] Combining the existing green space area value and meteorological parameters in the city, setting up different scenarios, quantitatively calculating the hourly dust retention amount of urban green spaces, and providing suggestions for the configuration of garden plants in different functional green spaces in the city in combination with the design requirements for the configuration of garden plants in different types / functions of green spaces.

[0012] Preferably, the formula for the pollutant reduction amount per unit greening area in the UFORE model is as follows:

[0013] M = F × LAI × T;

[0014] Wherein, M is the pollutant reduction amount per unit greening area, F is the pollutant deposition flux per unit time, LAI is the leaf area index, and T is the time for vegetation to reduce pollutants.

[0015] Preferably, the different scenarios established also include establishing different vegetation category configurations and different area ratio gradients, calculating the dust retention amount per unit greening area of different vegetation configuration patterns, and screening and calculating weights to obtain the optimal configuration pattern.

[0016] Preferably, the number of the different scenarios can be divided according to the administrative regions of the city.

[0017] Preferably, the calculation method for the outer radius of the tree crown is also included in the different scenario analyses, and the calculation formula is as follows:

[0018]

[0019] Wherein, L4 is the distance measured by laser ranging from the bottom measurement point to the outer edge of the tree crown, and Hh is the height of the tree trunk obtained by laser ranging.

[0020] Preferably, the calculation method for the outer radius of the tree crown is also included in the different scenario analyses, and the calculation formula is as follows:

[0021]

[0022] Among them, L3 is the distance from the bottom measurement point to the inner edge of the tree crown that can be measured by laser ranging, and Hh is the tree height obtained by laser ranging.

[0023] Preferably, the specific formula for the parameter inversion is as follows:

[0024]

[0025] Among them, LAI is the leaf area index, ST is the total floor area of the plants, and St is the total leaf area; F is the pollutant deposition flux per unit time, M is the pollutant reduction amount per unit greening area, Vd is the dry deposition rate, and C is the pollutant concentration;

[0026] The dust retention optimization configuration parameters under this vegetation configuration are obtained through the sedimentation rate Vd and the leaf area index LAI.

[0027] Preferably, the different vegetation configurations in calculating the dust retention amount in one cycle per unit greening area include at least two of single plant, tree-shrub, tree-grass, shrub-grass, and tree-shrub-grass.

[0028] Preferably, different types / function green spaces include road green spaces and park green spaces, and the road green spaces are mainly configured with vegetation having a strong TSP dust retention ability.

[0029] Preferably, the iteration method for the maximum dust retention amount and the dust retention amount by particle size is as follows:

[0030] When the dust retention amount in one cycle per unit greening area and the dust retention amount by particle size are the largest under different vegetation configurations, R-type factor analysis is carried out, and the optimal dust retention configuration scheme is obtained through weight calculation; when the dust retention amount in one cycle per unit greening area and the dust retention amount by particle size are not the largest under different vegetation configurations, the area ratio under this vegetation configuration mode is readjusted until the dust retention amount and the dust retention amount by particle size under this mode are the largest.

[0031] The above technical solution of the present invention has the following beneficial technical effects:

[0032] Based on the UFORE model, the dry deposition parameters are inverted, the unit greening area of different plant category configuration modes is calculated, further the optimal configuration is analyzed through the scenario analysis method, and the dust retention amount and its particle size composition characteristics of the city (each administrative region) under this greening configuration are calculated. Finally, combined with different functional greening requirements, configuration suggestions applicable to the city roads and garden greening are put forward, which is more accurate than the prior art. Description of the Drawings

[0033] Figure 1 It is a calculation flow chart of the optimal dust retention garden vegetation configuration model of the present invention. Detailed Embodiments

[0034] To make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present invention.

[0035] In this embodiment, taking Shenzhen as an example, it is only for illustration and does not impose any limitation on the present invention.

[0036] As Figure 1 shown, the dust retention amount per unit leaf area obtained by the dust retention measurement using the water elution method, the leaf area index LAI calculated by Matlab image processing, the total dust retention duration T, and the pollutant concentration C during the dust retention period are used to inversely obtain the pollutant dry deposition models of 16 plants through the UFORE model. Based on the leaf area index LAI of the optimal configuration model, the average annual TSP concentration in Guangzhou, which is similar to the situation in Shenzhen, the annual dust retention duration and the pollutant concentration levels (PM10, PM2.5) of the main administrative districts in Shenzhen, and the green area of each district, the estimated annual dust retention amount of the optimal configuration of the main administrative districts in Shenzhen is calculated through this model. The optimal configuration parameters include the TSP, PM10, and PM2.5 dry deposition rates Vd3, Vd1, Vd2, and the leaf area index LAI of this configuration. Among them, the pollutant deposition flux F is an important parameter for dry deposition, which depends not only on the deposition rate Vd and meteorological factors, but also on species, leaf area index (LAI), canopy height, and other vegetation characteristic values.

[0037] An optimal dust retention configuration model was constructed by combining the Urban Forest Effects Model (UFORE) with three-dimensional dust retention results, air quality characteristics during the dust retention period, and R-type factor analysis to optimize the configuration of common landscape plants in Shenzhen. Specifically, it includes: (1) parameter inversion based on the dry deposition module of the UFORE model for air pollution; (2) calculating the dust retention amount per unit greening area in one cycle under different vegetation configurations, and iteratively determining the optimal ratio of different types of vegetation under various vegetation configurations through the maximum dust retention amount and particle size-fractionated dust retention amount, so as to optimize the plant configuration; (3) using R-type factor analysis to determine the weights of different vegetation configuration patterns, thereby calculating the optimal configuration parameters for dust retention; (4) combining the existing green area values in the city and meteorological parameters, setting different scenarios, and quantitatively calculating the hourly dust retention amount of urban green spaces, including PM10, PM2.5, and TSP (total suspended particulates), and then providing suggestions for the configuration of landscape plants in different functional urban green spaces in combination with the design requirements for landscape plant configuration in different types / functions of green spaces. Different types / functions of green spaces include road green spaces and park green spaces, and the configuration of road green spaces mainly focuses on vegetation with strong TSP dust retention ability. Different vegetation configurations in calculating the dust retention amount per unit greening area in one cycle include single plants, tree-shrub, tree-grass, shrub-grass, and tree-shrub-grass.

[0038] The specific formula for parameter inversion is as follows:

[0039]

[0040] Among them, LAI is the leaf area index, ST is the total floor area of plants, and St is the total leaf area; F is the pollutant deposition flux per unit time, M is the pollutant reduction amount per unit greening area, Vd is the dry deposition rate, and C is the pollutant concentration.

[0041] The optimal configuration parameters for dust retention under this vegetation configuration are obtained through the deposition rate Vd and the leaf area index LAI.

[0042] The formula for the pollutant reduction amount per unit greening area in the UFORE model is as follows:

[0043] M = F × LAI × T;

[0044] Among them, M is the pollutant reduction amount per unit greening area, F is the pollutant deposition flux per unit time, LAI is the leaf area index, and T is the time for vegetation to reduce pollutants.

[0045] The different scenarios established also include establishing different vegetation category configurations and different area ratio gradients scenarios, calculating the dust retention amount per unit greening area of different vegetation configuration patterns, and screening and calculating weights to obtain the optimal configuration pattern.

[0046] Among them, the different scenarios are divided into 6 scenarios according to the 6 main administrative regions of Shenzhen.

[0047] The calculation method of the outer radius of the tree crown is also included in different scenario analyses, and the calculation formula is as follows:

[0048]

[0049] Among them, L4 is the distance from the bottom measurement point to the outer edge of the tree crown that can be measured by laser ranging, and Hh is the height of the tree trunk obtained by laser ranging.

[0050] Preferably, the calculation method of the outer radius of the tree crown is also included in different scenario analyses, and the calculation formula is as follows:

[0051]

[0052] Among them, L3 is the distance from the bottom measurement point to the inner edge of the tree crown that can be measured by laser ranging, and Hh is the height of the tree trunk obtained by laser ranging.

[0053] The iteration method for the maximum dust retention amount and the dust retention amount by particle size is as follows:

[0054] When the dust retention amount per unit greening area and the dust retention amount by particle size are the largest under different vegetation configurations, R-type factor analysis is carried out, and the optimal dust retention configuration scheme is obtained through weight calculation; when the dust retention amount per unit greening area and the dust retention amount by particle size are not the largest under different vegetation configurations, the area ratio under this vegetation configuration mode is readjusted until the dust retention amount and the dust retention amount by particle size under this mode are the largest.

[0055] Through the above-mentioned optimal dust retention garden plant configuration model, calculations and scenario analyses are completed for 6 administrative regions in Shenzhen, and the following configuration suggestions are mainly obtained:

[0056] Among different plant category configuration modes, the tree-shrub-grass mode is the optimal dust retention configuration mode. The configuration with a relatively large dust retention amount per unit greening area is Ficus virens + Ficus microcarpa 'Golden Leaves' + Ophiopogon bodinieri, with an area ratio of 1:0.1:0.9. The optimal configuration for retaining TSP is Ficus virens + Loropetalum chinense var. rubrum + Ophiopogon bodinieri, with an area ratio of 1:0.1:0.9; the optimal configuration for retaining PM10 is Lagerstroemia speciosa + Cycas revoluta + Ophiopogon bodinieri, with an area ratio of 1:0.9:0.1; the optimal configuration for retaining PM2.5 is Plumeria rubra 'Acutifolia' + Ficus microcarpa 'Golden Leaves' + Ophiopogon bodinieri, with an area ratio of 1:0.9:0.1.

[0057] The relevant parameters of the optimal configuration calculated according to the scenario analysis method, optimization configuration, and R-type factor analysis are: LAI (20.57 m2·m-2), TSP sedimentation flux FTSP (21.60 mg·h-1), PM10 deposition rate Vd10 (1.12 cm·s-1), PM2.5 deposition rate Vd2.5 (0.40 cm·s-1).

[0058] Taking Shenzhen City as an example for scenario analysis, the results show that: under the light, medium, and heavy pollution scenarios, the optimal annual dust retention amounts of each administrative district are 1.31 - 31.67 (10³t), 2.87 - 73.88 (10³t), and 11.60 - 218.27 (10³t) respectively; the total optimal annual dust retention amount in Scenario 3 (heavy) is 6.89 - 10.68 times that in Scenario 1 (light). Among them, due to the largest green area in Longgang District among the six administrative districts, the optimized annual dust retention amount is the largest in the three scenarios. And the total annual dust retention amounts of different particle sizes in it are all greater than those of the other five administrative districts.

[0059] The plant configuration suggestions according to different green space types and functional design requirements are mainly divided into road green spaces and park green spaces. Due to the large amount of road dust, it is recommended to configure plants with stronger TSP dust retention ability in road green spaces compared to park green spaces, and the annual dust retention amount per unit green space area is 2.75 - 159.43 g·m⁻². The tree-shrub-grass pattern is applied more frequently, and Lagerstroemia speciosa + Cycas revoluta + Ophiopogon bodinieri with a tree-shrub-grass area ratio of 1:0.9:0.1 has a relatively large application range. The single-plant pattern is applied less frequently. In the configuration suggestions for the sidewalk green belt, the total annual dust retention amount per unit green space area and the annual TSP dust retention amount per unit green space area of Ficus virens + Ophiopogon bodinieri are relatively large, being 159.43 and 130.69 g·m⁻² respectively; the annual PM10 dust retention amount per unit green space area of Lagerstroemia speciosa + Cycas revoluta + Ophiopogon bodinieri applied in park green spaces is relatively large, being 25.51 g·m⁻²; the annual PM2.5 dust retention amount per unit green space area of Plumeria rubra + Ficus microcarpa + Ophiopogon bodinieri applied in road green spaces and park green spaces is relatively large, being 92.57 g·m⁻².

[0060] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and the descriptions in the specification are only preferred examples of the present invention and do not limit the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for configuring garden plants to purify atmospheric particulate matter in urban green spaces, characterized in that, Including: Performing parameter inversion based on the air pollution dry deposition module of the UFORE model; Calculating the dust retention amount per unit greening area in one cycle under different vegetation configurations, and iteratively determining the optimal ratio of different types of vegetation under various vegetation configurations through the maximum dust retention amount and the dust retention amount by particle size, so as to optimize the plant configuration; Using R-type factor analysis to determine the weights of different vegetation configuration modes, so as to calculate the optimal dust retention configuration parameters; Combining the existing green area value and meteorological parameters of the city, setting up different scenarios, quantitatively calculating the hourly dust retention amount of urban green spaces, and providing suggestions for the landscape plant configuration of different functional urban green spaces in combination with the design requirements of landscape plant configurations of different types / functions of green spaces; The specific formula for the parameter inversion is as follows: Among them, LAI is the leaf area index, S T is the total floor area of the plants, S t is the total leaf area; F is the pollutant deposition flux per unit time, M is the pollutant reduction amount per unit greening area, V d is the dry deposition rate, and C is the pollutant concentration; Through the sedimentation rate V d and the leaf area index LAI, the optimized dust retention configuration parameters under this vegetation configuration are obtained; The formula for the pollutant reduction amount per unit greening area in the UFORE model is as follows: M = F × LAI × T; Wherein, M is the pollutant reduction amount per unit greening area, F is the pollutant deposition flux per unit time, LAI is the leaf area index, and T is the time for vegetation to reduce pollutants.

2. The method for configuring garden plants for purifying atmospheric particulate matter in urban green spaces according to claim 1, characterized in that The established different scenarios also include establishing different vegetation category configurations and different area ratio gradient scenarios, calculating the dust retention amount per unit greening area of different vegetation configuration modes, and screening and calculating weights to obtain the optimal configuration mode.

3. A method for configuring garden plants to purify atmospheric particulate matter in urban green spaces according to claim 2, characterized in that, The number of the different scenarios can be divided according to the administrative regions of the city.

4. A method for configuring garden plants to purify atmospheric particulate matter in urban green spaces according to claim 1, characterized in that, The calculation of different scenarios also includes the calculation method of the outer radius of the tree crown, and the calculation formula is as follows: Among them, L4 is the distance from the bottom measurement point to the outer edge of the tree crown that can be measured by laser ranging, and H h is the tree trunk height obtained by laser ranging.

5. A method for configuring garden plants to purify atmospheric particulate matter in urban green spaces according to claim 1, characterized in that, The calculation of different scenarios also includes the calculation method of the inner radius of the tree crown, and the calculation formula is as follows: Among them, L3 is the distance that can be measured by laser ranging from the bottom measurement point to the inner edge of the tree crown, and H h is the tree trunk height obtained by laser ranging.

6. The method for configuring garden plants for purifying atmospheric particulate matter in urban green spaces according to claim 1, wherein The different vegetation configurations in calculating the dust retention amount per unit greening area in one cycle include at least two of single plant, tree-shrub, tree-grass, shrub-grass, and tree-shrub-grass.

7. A method for configuring garden plants to purify atmospheric particulate matter in urban green spaces according to claim 1, characterized in that, The different types / functions of green spaces include road green spaces and park green spaces, and the configuration of road green spaces is mainly based on vegetation with strong TSP dust retention ability.

8. A method for configuring garden plants to purify atmospheric particulate matter in urban green spaces according to claim 1, characterized in that The iterative method using the maximum dust retention amount and the dust retention amount by particle size is as follows: When the dust retention amount per unit greening area in one cycle and the dust retention amount by particle size under different vegetation configurations are the largest, perform R-type factor analysis, and obtain the optimal dust retention configuration plan through weight calculation; when the dust retention amount per unit greening area in one cycle and the dust retention amount by particle size under different vegetation configurations are not the largest, readjust the area ratio under this vegetation configuration mode until the dust retention amount and the dust retention amount by particle size under this mode are the largest.

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