Design method of collaborative control system for greenhouse gas emission reduction in response to climate change and air pollution

Abstract

The application provides a kind of greenhouse gas emission reduction collaborative control system design method for coping with climate change and air pollution, relates to a nonlinear system design for realizing collaborative control of climate change and air pollution through greenhouse gas emission reduction, which can represent the coupling relationship between climate environment and main factors of social ecology. First, according to the coupling relationship between human activities, atmosphere, ecology and other circles, a mathematical model of a dynamic system representing the coupling relationship between climate change and air pollution is constructed; second, system parameters are estimated by collecting existing literature, research articles and the like, and system simulation, analysis and bounded stability are proved; finally, by adjusting the control coefficient, the emission reduction control strategy under the temperature rise target of the Paris Agreement, the temperature rise trajectory and the change rate curve of the content of PM 2.5 in the atmosphere are obtained, and the results show that the control system obtains the emission reduction control strategy for the temperature rise target, and effectively realizes the collaborative control of greenhouse gas and air pollution.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of responding to climate change, and particularly relates to a greenhouse gas emission reduction and air pollution collaborative control system design method for responding to climate change and air pollution, which can be used for controlling greenhouse gas emissions to slow down the speed of global warming, achieve the global temperature rise target, and achieve the collaborative control effect of air pollution on a medium and long term time scale. BACKGROUND

[0002] In recent decades, the continuous increase of greenhouse gas and other major atmospheric pollution emissions has caused the global to face the dual pressure of air pollution prevention and control and response to climate change. Greenhouse gases and air pollutants are of the same origin, and seeking a collaborative control strategy for greenhouse gases and air pollution is an effective way to respond to the pressure of air pollution prevention and control and the challenge of climate change.

[0003] Some exploratory researches include: the University of Stuttgart in Germany (2005) began to explore the regulation of air pollutants and greenhouse gases, and mentioned the potential of evolutionary optimization algorithm to solve such complex multi-objective problems; Lawrence Berkeley National Laboratory (2020) carried out research on traffic control strategies for simultaneously mitigating climate change and air pollution; Bangabandhu Sheikh Mujibur Rahman Science and Technology University in Bangladesh (2021) constructed a mathematical model to evaluate the impact of greenhouse gas emissions on climate change and coastal ecosystems, and controlled the concentration of greenhouse gases and mitigated the impact of climate change through two optimization control strategies of coastal green belts and desulfurization technology. The above researches either focus on the collaborative effect of air pollution and greenhouse gases, or focus on the optimization control of single regional climate targets, but there is still a lack of comprehensive consideration of the coupling of human activities, atmosphere, ecology and other multi-sphere in the construction and optimization of greenhouse gas and air pollution collaborative control system. SUMMARY

[0004] In view of the current problems and challenges of climate change and air pollution faced by human beings, the present application provides a greenhouse gas emission reduction and air pollution collaborative control system design method for responding to climate change and air pollution, which controls the temperature rise at the end of this century within the target range through emission reduction control strategies, and achieves the collaborative control effect of air pollution on a medium and long term time scale.

[0005] To achieve the above purpose, the present application adopts the following technical solutions:

[0006] A greenhouse gas emission reduction and air pollution collaborative control system design method for responding to climate change and air pollution comprises the following steps:

[0007] Step 1, constructing a climate change-air pollution coupling dynamics system representing the interaction of multiple spheres:

[0008]

[0009] In the formula, the system parameters alpha1, alpha2 and alpha3 are the natural growth rates of T, H and F respectively, delta1HG represents the concentration of greenhouse gases caused by human activities, delta2FG represents the greenhouse gas mitigation rate of the forest ecosystem, delta3T represents the influence speed of atmospheric temperature on greenhouse gas production, theta1GT represents the atmospheric temperature growth caused by greenhouse gases, theta2HT represents the increment of atmospheric temperature caused by population growth, theta3FT represents the absorption amount of the forest ecosystem to T, psi1GH represents the mitigation rate of greenhouse gases to population growth, psi2TH represents the mitigation rate of atmospheric temperature rise to population growth, psi3FH represents the promotion rate of the forest ecosystem to population growth, psi4AH represents the mitigation rate of air quality decline to population growth, epsilon1HF represents the mitigation rate of human activities to vegetation coverage in the forest ecosystem, Epsilon2GH represents the increment of vegetation coverage in the forest ecosystem caused by the rise of the concentration of greenhouse gases, epsilon3TF represents the mitigation rate of global warming to vegetation coverage in the forest ecosystem, beta1GA represents the increment of PM 2.5 in the atmosphere caused by greenhouse gases, beta2HA represents the increment of PM 2.5 in the atmosphere caused by human activities, beta3FA represents the mitigation rate of the forest ecosystem to the content of PM 2.5 in the atmosphere, wherein a and b are saturation constants, 0 < a, b < 1, and k1 and k2 are the carrying capacities of H and F respectively.

[0010] Meanwhile, the boundedness and stability of the designed climate change-air pollution coupled dynamic system are proved by using integral inequality and Jacobean matrix method respectively.

[0011] Step 2, constructing a greenhouse gas collaborative control system for coping with climate change and air pollution:

[0012]

[0013] The emission speed of greenhouse gases is taken as a control variable, and state feedback uG is introduced to alleviate the emission of greenhouse gases and climate change.

[0014] Step 3, controlling the temperature rise range:

[0015] A closed-loop control system is designed, a target temperature rise is given, and the numerical value of the optimal control parameter u is obtained according to the closed-loop control cycle.

[0016] Compared with the prior art, the present application has the beneficial effects that:

[0017] (1) In this invention, a new dynamic model is established to evaluate the impact of greenhouse gas emissions on climate change, ecosystems, population and air quality and their mutual feedback effects; at the same time, a control system is designed, with greenhouse gas emissions as the control variable, and closed-loop control is used to find emission reduction control parameters to control the target temperature rise, and the effectiveness of the control is verified through analysis.

[0018] (2) This invention provides a control method to mitigate global temperature rise by reducing greenhouse gas emissions, which is part of the overall strategy to address global climate change. Attached Figure Description

[0019] Figure 1 This is a schematic diagram illustrating the impact of greenhouse gases on global warming, population, forest ecology, and air quality in this invention;

[0020] Figure 2 This invention relates to a closed-loop control design that selects the optimal control parameter u. Detailed Implementation

[0021] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0022] like Figure 1 As shown, the design method of a greenhouse gas emission reduction synergistic control system for addressing climate change and air pollution according to the present invention includes the following steps:

[0023] Step 1: Conduct numerical simulations based on the established climate change-atmospheric pollution coupled dynamics system. Figure 1 The growth rate of greenhouse gases in the atmosphere (G), atmospheric temperature change (T), population growth rate (H), vegetation cover in forest ecosystems (F), and PM2.5 in the air. 2.5 The coupling relationship between the content of A establishes a climate change-atmospheric pollution coupled dynamic system, including atmospheric temperature, population size, and the natural growth rate of ecosystems. Human activities continuously increase greenhouse gases, deteriorate air quality, thereby harming human health and inhibiting population growth. Simultaneously, human activities and land use inhibit the growth rate of forest ecosystems. Forest ecosystems absorb greenhouse gases from the atmosphere, which promote vegetation growth within them. Greenhouse gases contribute to increased atmospheric temperature, leading to global warming. Global warming causes extreme weather events, impacting forest ecosystems. Global warming also has some influence on population growth. Carbon emissions and air pollution share a high degree of common origin; therefore, greenhouse gas emissions lead to deteriorating air quality. Forest ecosystems adsorb atmospheric pollutants, and further improvements in the natural environment of forest ecosystems promote population growth. In summary, the design of the climate change-atmospheric pollution coupled dynamic system characterizing multi-sphere interactions is shown below:

[0024]

[0025] After the establishment of the climate change-atmospheric pollution coupled dynamics system, the system parameters are estimated, including α1, α2, α3, δ1, δ2, δ3, θ1, θ2, θ3, ψ1, ψ2, ψ3, ψ4; ε1, ε2, ε3, β1, β2, β3, the meanings, values and units of which are shown in Table 1.

[0026] Table 1

[0027]

[0028]

[0029] According to the observation, the initial value (G0, T0, H0, F0, A0) = (0.005, 0.45, 1.36, 8.75, 0.05) is given as the system data in 1990, and the change path of each factor of the system is observed to the end of this century;

[0030] Step 2, the closed-loop control system in Figure 2 is used, wherein the controller is uG, the controlled object is the climate change-atmospheric pollution coupled dynamics system, the greenhouse gas collaborative control system for climate change and atmospheric pollution is as follows, the given input is the target temperature rise, the output controlled quantity is the temperature rise after control, the two are compared through a comparator, the error is required to be less than 0.001, and the optimal control parameter u is output;

[0031]

[0032] Step 3, the determined optimal control parameter u is input into the collaborative control system, the carbon emission path under the temperature rise target of the Paris Agreement, the temperature rise trajectory and the content change rate curve of PM 2.5 in the air are obtained, the temperature rise amplitude at the end of this century is limited to within 1.5℃, and the collaborative control of atmospheric pollution is realized on a medium and long term time scale.

Claims

1. A method for designing a system for synergistic control of greenhouse gas emission reduction and air pollution in response to climate change, characterized in that, Comprising the steps of: Step 1, according to the atmospheric greenhouse gas growth rate G, atmospheric temperature change T, population growth rate H, forest ecosystem vegetation coverage F and the atmospheric PM 2.5 The coupling relationship between the content A is established climate change-atmospheric pollution coupling dynamics system, and the system parameters are estimated; the system parameters include , , , , , , , , , , , , ; , , , , , ; The coupled dynamics system of climate change-atmospheric pollution is: ； wherein the system parameters , , are the natural growth rates of T, H, F, respectively, denotes the concentration of greenhouse gases caused by human activity, denotes the mitigation rate of greenhouse gases by the forest ecosystem, denotes the speed of the influence of atmospheric temperature on the production of greenhouse gases, denotes the increase in atmospheric temperature caused by greenhouse gases, denotes the increase in atmospheric temperature caused by population growth, denotes the absorption of T by the forest ecosystem, denotes the mitigation rate of population growth by greenhouse gases, denotes the mitigation rate of population growth by the increase in atmospheric temperature, denotes the promotion rate of population growth by the forest ecosystem, denotes the mitigation rate of population growth by the decrease in air quality, denotes the mitigation rate of vegetation cover in the forest ecosystem by human activity, denotes the increase in vegetation cover in the forest ecosystem due to the increase in the concentration of greenhouse gases, denotes the mitigation rate of vegetation cover in the forest ecosystem by global warming, denotes the increase in PM 2.5 in the atmosphere caused by greenhouse gases, 2.5 denotes the increase in PM 2.5 in the atmosphere caused by human activity, 2.5 denotes the mitigation rate of the content of PM 2.5 in the atmosphere by the forest ecosystem, wherein is the saturation constant, and are the carrying capacities of , respectively. Step 2, Adding control variables in the coupled system model of climate change and air pollution to simulate the impact of emission reduction control, for the control parameters under the target temperature rise, G is the growth rate of greenhouse gases in the atmosphere, so as to obtain the greenhouse gas coordinated control system for coping with climate change and air pollution; Step 3. The temperature rise is limited within the temperature rise target by adjusting the value of the control coefficient according to the temperature rise target.

2. The method of claim 1, wherein the system is designed to reduce greenhouse gas emissions and control air pollution simultaneously. The step 2 is the greenhouse gas collaborative control system for coping with climate change and atmospheric pollution: 。 3. The method of claim 2, wherein the method is characterized by: The step 3 comprises: designing a closed-loop control system according to the constructed greenhouse gas collaborative control system for climate change and air pollution, and selecting optimal control parameters The temperature rise is controlled within the target range, and the collaborative control effect on air pollution is achieved on a medium and long term time scale.

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