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Atmospheric pollution multi-scenario control effect rapid prediction and evaluation method

A multi-scenario and fast technology, applied in forecasting, climate sustainability, instruments, etc., can solve problems such as large amount of calculation, inability to achieve real-time air pollution control effects, dynamic forecasting and evaluation, and consumption of large computer resources to calculate time, etc., to achieve performance-enhancing effects

Active Publication Date: 2020-12-15
INST OF ATMOSPHERIC PHYSICS CHINESE ACADEMY SCI
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AI Technical Summary

Problems solved by technology

Therefore, the amount of calculation is huge, and it needs to consume a lot of computer resources (500-1000 computing cores) and computing time (20-30 days), and it is impossible to realize real-time and dynamic prediction and evaluation of the effect of air pollution control

Method used

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  • Atmospheric pollution multi-scenario control effect rapid prediction and evaluation method

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Embodiment Construction

[0043] In order to make the technical problems, technical solutions and beneficial effects solved by the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0044] The present invention provides a method for rapid prediction and evaluation of air pollution multi-scenario control effects. Since the air quality model does not need to be re-run, the air quality improvement effects of multiple control schemes can be quickly obtained, thereby supporting the comparison and optimization of multiple control schemes. Compared with the traditional scenario simulation method, the method of the present invention can quickly and quantitatively evaluate the air quality improvement effects of multiple sets of pollution control measures befo...

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Abstract

The invention provides an atmospheric pollution multi-scenario control effect rapid prediction and evaluation method. The method comprises the steps: determining the space-time range of atmospheric pollution control effect evaluation; configuring mode parameters; carrying out space-time distribution on the pollutant emission source list data; running an air quality numerical mode, and obtaining afunction relationship between the quantity of the emission precursors emitted by each pollutant emission source and the hourly benchmark simulation concentration of the grid point pollutants; calculating the total emission reduction rate of the emission precursors emitted by the pollutant emission sources under a point source control measure and a surface source control measure; and calculating the atmospheric pollutant concentration after the point source control measure and the surface source control measure are used, and evaluating the effects of the point source control measure and the surface source control measure. According to the method, the air quality improvement effects of multiple pollution control measures can be rapidly and quantitatively evaluated under the condition of reasonable calculation resource expenditure, comparison and optimization of the multiple pollution control measures are achieved, and the air quality control effect is improved.

Description

technical field [0001] The invention belongs to the technical field of environmental protection, and in particular relates to a rapid prediction and evaluation method for multi-scenario control effects of air pollution. Background technique [0002] With the continuous development of my country's economy, the discharge of various pollutants is generally high, and PM 2.5 Air pollution, which is the main pollutant, has become one of the major environmental problems at present. In order to deal with this problem, major cities across the country have successively formulated relevant pollution control measures and emergency plans for heavy pollution. In order to gradually improve the effectiveness of measures and plans, quantitative evaluation and optimization of their implementation effects is a very important link. [0003] At present, commonly used evaluation methods for air pollution control measures include: air quality numerical model scenario simulation method and respon...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06G06Q50/26
CPCG06Q10/04G06Q10/0639G06Q50/26Y02A90/10
Inventor 王文丁陈焕盛晏平仲杨文夷王自发
Owner INST OF ATMOSPHERIC PHYSICS CHINESE ACADEMY SCI
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