A remote sensing physical prediction method for the hygroscopic growth of atmospheric particles

Abstract

The present invention provides a remote sensing physical prediction method for the hygroscopic growth of atmospheric particles, comprising the steps of: obtaining a hygroscopic growth factor according to the volume of water in the atmospheric particles #imgabs0# obtaining the volume fraction of water in the atmospheric particles #imgabs1# according to the complex refractive index of the atmospheric particles after hygroscopic growth #imgabs1# step 3, obtaining the hygroscopic growth factor of the atmospheric particles used for remote sensing optics #imgabs2# The present invention provides a remote sensing physical prediction method for the hygroscopic growth of atmospheric particles, which can characterize the deliquescence behavior of aerosols and the differences in hygroscopicity of atmospheric particles in the entire humidity range and can be directly applied to satellite remote sensing, and can be widely used in the field of atmospheric measurement.

Description

Technical Field

[0001] The invention relates to the field of hygroscopic growth of atmospheric particles, and in particular to a remote sensing physical prediction method for hygroscopic growth of atmospheric particles. Background Art

[0002] Atmospheric particulate matter is an important component of the Earth's atmospheric system, including dust, smoke particles, bacteria, viruses, plant spores and pollen, as well as cloud droplets, ice crystals and rain and snow particles composed of water and ice, and gas carriers in the atmosphere. The multiphase (gas-liquid-solid mixture) system is academically called aerosol. Atmospheric particulate matter can stay in the atmosphere for a long time and be transmitted over long distances. It is one of the important monitoring indicators of the national air quality standards. In the past two decades, atmospheric particulate matter has become the primary air pollutant in my country's vast cities and rural areas. In autumn and winter, it is easy to produce smog pollution that lasts for a long time, covers a large area, and affects a large population, threatening the quality of human life and physical health.

[0003] Atmospheric particles are hygroscopic; however, the hygroscopic properties of each component in atmospheric particles are different, so the hygroscopic growth of atmospheric particles is very complex. If the hygroscopic growth of atmospheric particles is described based on the change in the size of atmospheric particles or the change in the extinction of atmospheric particles, it is called the geometric hygroscopic growth factor or the optical hygroscopic growth factor.

[0004] The ground in-situ online instrument hygroscopic tandem differential mobility analyzer can measure the hygroscopic properties of particles in the laboratory and field environment. However, the instrument cost and personnel investment are high. At present, the parameterized model of hygroscopic growth factor is widely used, but most of the parameterized models of hygroscopic growth factor rely on laboratory or field observation results, and the parameterized models of hygroscopic growth factor are Among them, f(RH) represents the hygroscopic growth factor, the relative humidity (RH) of the environment is a variable, the parameter a represents the fitting intercept, and the parameter b represents the amplitude of the scattering enhancement.

[0005] In practical applications, parameterized models of hygroscopic growth factors usually require the input of environmental relative humidity data as a driver to simulate the hygroscopic growth factor. In addition, existing parameterized models rely on empirical parameters, and it is difficult to adjust model parameters according to the characteristics of different research areas, seasons, aerosol types, etc. These all limit the direct application of parameterized models of hygroscopic growth factors in satellite remote sensing.

[0006] It can be seen that in the existing technology, there is no remote sensing physical prediction method that can well and flexibly characterize the aerosol deliquescence behavior and the differences in the hygroscopicity of atmospheric particles in the entire humidity range and can be directly applied to satellite remote sensing for the hygroscopic growth of atmospheric particles. Summary of the invention

[0007] In view of this, the main purpose of the present invention is to provide a method for predicting the hygroscopic growth of atmospheric particles that can characterize the aerosol deliquescence behavior and the hygroscopic differences of atmospheric particles in the entire humidity range and can be directly applied to satellite remote sensing.

[0008] In order to achieve the above object, the technical solution proposed by the present invention is:

[0009] A remote sensing physical prediction method for atmospheric particulate matter hygroscopic growth comprises the following steps:

[0010] Step 1: According to the volume of water absorbed by atmospheric particulate matter, the hygroscopic growth factor GF is obtained as follows:

[0011]

[0012] Among them, V wet Represents the volume of atmospheric particles after absorbing water, V dry represents the volume of atmospheric particles without water absorption, f w It represents the volume fraction of water absorbed in atmospheric particulate matter.

[0013] Step 2: According to the complex refractive index of the atmospheric particles after absorbing moisture, the volume fraction of water in the atmospheric particles is obtained. w :

[0014]

[0015] Among them, m wet Represents the real part of the complex refractive index of atmospheric particles after absorbing water, m dry Represents the real part of the complex refractive index of atmospheric particles without water absorption, m water Represents the real part of the complex refractive index of water.

[0016] Step 3: Obtain atmospheric particle hygroscopic growth factor GF for remote sensing optics

[0017]

[0018] In the present invention, the real part of the complex refractive index of water m water =1.33, the real part of the complex refractive index of the atmospheric particles without water absorption m dry =1.50~1.55.

[0019] In summary, the remote sensing physical prediction method of the optical hygroscopic growth factor of atmospheric particles described in the present invention uses satellite observation data or satellite product data to drive the model, and can simply adjust the model according to the directionality of characteristics such as different research areas, seasons, and aerosol types. The remote sensing physical prediction method of the optical hygroscopic growth factor of atmospheric particles described in the present invention characterizes the changes in the properties of atmospheric particles caused by deliquescence and drying processes by introducing microphysical characteristic parameters of particles, so that the remote sensing physical method of hygroscopic growth factor can characterize the differences in hygroscopic properties of particles caused by changes in complex chemical components in atmospheric particles. It can be seen that the remote sensing physical prediction method of the optical hygroscopic growth factor of atmospheric particles described in the present invention not only takes into account the complex chemical composition of atmospheric particles, but also takes into account the response of the deliquescence process of particles to optical remote sensing under different environmental humidity, and realizes the macroscopic, large-scale, and periodic simulation of the hygroscopic growth factor of atmospheric particles on the satellite platform, and is widely used in environmental monitoring and other multi-field applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 The figure is a flow chart of the remote sensing physical prediction method of the optical hygroscopic growth factor of atmospheric particulate matter according to the present invention.

[0021] Figure 2 The hygroscopic growth factor GF and the real part of the complex refractive index m of the atmospheric particles after absorbing water in the present invention are wet , real part of the complex refractive index of atmospheric particles without water absorption m dry Schematic diagram of the changing effect. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0023] Figure 1 FIG. 1 is a flow chart of the remote sensing physical prediction method of the optical hygroscopic growth factor of atmospheric particles according to the present invention. Figure 1 As shown, the remote sensing physical prediction method for the hygroscopic growth of atmospheric particulate matter described in the present invention comprises the following steps:

[0024] Step 1: According to the volume of water in atmospheric particulate matter, the hygroscopic growth factor GF is obtained as follows:

[0025]

[0026] Among them, V wet Represents the volume of atmospheric particles after absorbing water, V dry represents the volume of atmospheric particles without water absorption, f w It represents the volume fraction of water in atmospheric particulate matter.

[0027] Step 2: According to the complex refractive index of the atmospheric particles after absorbing moisture, the volume fraction of water in the atmospheric particles is obtained. w :

[0028]

[0029] Among them, m wet Represents the real part of the complex refractive index of atmospheric particles after absorbing water, m dry Represents the real part of the complex refractive index of atmospheric particles without water absorption, m water Represents the real part of the complex refractive index of water.

[0030] Step 3: Obtain the atmospheric particle hygroscopic growth factor GF for remote sensing optics:

[0031]

[0032] In the present invention, the real part of the complex refractive index of water m water =1.33, the real part of the complex refractive index of the atmospheric particles without water absorption m dry =1.50~1.55, therefore, a lookup table of the optical hygroscopic growth factor GF of atmospheric particles changing with the real part of the complex refractive index can be simulated. Figure 2 The hygroscopic growth factor GF and the real part of the complex refractive index m of the atmospheric particles after absorbing water in the present invention are wet , real part of the complex refractive index of atmospheric particles without water absorption m dry Schematic diagram of the changing effect. Figure 2 As shown, the real part of the complex refractive index of atmospheric particles gradually decreases with the increase of water absorption.

[0033] In summary, the remote sensing physical prediction method of the optical hygroscopic growth factor of atmospheric particles described in the present invention uses satellite observation data or satellite product data to drive the model, and can adjust the model's single parameters according to the directionality of characteristics such as different research areas, seasons, and aerosol types. The remote sensing physical prediction method of the optical hygroscopic growth factor of atmospheric particles described in the present invention introduces microphysical characteristic parameters of particles to characterize the changes in the properties of atmospheric particles caused by deliquescence and drying processes, so that the remote sensing physical method of hygroscopic growth factor can characterize the differences in hygroscopic properties of particles caused by changes in complex chemical components in atmospheric particles. It can be seen that the remote sensing physical prediction method of the optical hygroscopic growth factor of atmospheric particles described in the present invention not only takes into account the complex chemical composition of atmospheric particles, but also takes into account the response of the deliquescence process of particles to optical remote sensing under different ambient humidity, and realizes macroscopic, large-scale, and periodic simulation of the hygroscopic growth factor of atmospheric particles on satellite platforms, and is widely used in environmental monitoring and other multi-field applications.

[0034] The above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A remote sensing physical prediction method for the hygroscopic growth of atmospheric particles. It is characterized in that The remote sensing physical prediction method comprises the following steps: Step 1: According to the volume of water in atmospheric particulate matter, the hygroscopic growth factor GF is obtained as follows: Among them, V wet Represents the volume of atmospheric particles after absorbing water, V dry represents the volume of atmospheric particles without water absorption, f w It represents the volume fraction of water in atmospheric particulate matter; Step 2: According to the complex refractive index of the atmospheric particles after hygroscopicity, the volume fraction of water absorbed in the atmospheric particles is obtained. w : Among them, m wet Represents the real part of the complex refractive index of atmospheric particles after absorbing water, m dry Represents the real part of the complex refractive index of atmospheric particles without water absorption, m water represents the real part of the complex refractive index of water; Step 3: Obtain the atmospheric particle hygroscopic growth factor GF for remote sensing optics:

2. A remote sensing physical prediction method for the hygroscopic growth of atmospheric particles according to claim 1, It is characterized in that The real part of the complex refractive index of water m water =1.33, the real part of the complex refractive index of the atmospheric particles without water absorption m dry =1.50~1.55.

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