Park carbon emission monitoring system based on big data

Abstract

The invention relates to the technical field of carbon emission monitoring, and particularly discloses a park carbon emission monitoring system based on big data, and the system comprises a tail gas emission calibration module which is used for selecting a plurality of vehicle samples, and calculating the unit carbon emission of the vehicle samples after the vehicle samples run for unit mileage; the historical data acquisition module is used for acquiring emission points in the park and collecting carbon emission materials of the emission points; setting an acquisition period, and obtaining historical emission data and historical environment data; the historical data analysis module is used for calculating a fixed emission amount in an acquisition period according to the historical environment data and the historical material data; calculating an emission difference according to the historical environment data and the fixed emission amount; calculating a discharge difference coefficient according to the discharge difference and the rainfall in each collection period; the carbon emission monitoring module is used for acquiring current traffic flow data and current material consumption data; according to the current traffic flow data, the current material consumption data and the emission difference coefficient, the emission intensity of the greenhouse gas in the air is judged.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission monitoring, and particularly relates to a park carbon emission monitoring system based on big data. Background Art

[0002] Park carbon emission monitoring is a comprehensive system aiming to monitor and manage the carbon emissions in the park in real time; by constructing a perfect carbon emission monitoring system, the park can achieve effective management and control of carbon emissions and contribute to the realization of low-carbon development and environmental protection goals.

[0003] Park carbon emission monitoring is a process of comprehensive application of multiple dimensions and multiple technologies, which includes monitoring in multiple aspects such as data collection, data processing, monitoring processing, and feedback warning.

[0004] In the prior art, the carbon emissions in the park are volatile and are affected by various factors such as seasons and changes in production activities. This volatility makes the process of frequently collecting carbon emission data rather cumbersome and complex. In order to accurately evaluate the carbon emissions in the park, it is necessary to regularly collect and analyze data, but this requires a large amount of human, material, and time costs. In addition, due to the differences in production activities and energy consumption methods among different parks, there are certain difficulties in calculating and monitoring carbon emissions. Summary of the Invention

[0005] The purpose of the present invention is to provide a park carbon emission monitoring system based on big data to solve the above technical problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A park carbon emission monitoring system based on big data includes: Exhaust emission calibration module: Select several vehicle samples, obtain the carbon emissions after each vehicle sample travels a unit mileage, and obtain the average carbon emissions after the vehicle samples travel a unit mileage, denoted as unit carbon emissions U; Historical data collection module: Obtain the emission points in the park and obtain the carbon emission materials of the emission points. The emission points include factories, and the carbon emission materials are the source materials that generate carbon emissions during the production process of the factories; Set the collection period, obtain historical emission data, where the historical emission data includes historical material consumption data, and the historical material consumption data includes the material consumption of the carbon emission materials of the emission points in each collection period; and obtain historical environmental data, where the historical environmental data includes the rainfall, the concentration of greenhouse gases in the air, and the vehicle flow data in the park in each collection period. The vehicle flow data includes all vehicles entering and leaving the park and the driving mileage of each vehicle; Historical data analysis module: Obtain the fixed emissions within the collection period according to the historical environmental data and historical material consumption data :

[0007] Where: w i is the weight coefficient of the i-th carbon emission material at the emission point, Mc i is the material consumption of the i-th carbon emission material at the emission point, n is the number of types of carbon emission materials in the production process of the emission point, e represents the e-th emission point in the park, m is the total number of emission points in the park, L k is the driving mileage of the k-th vehicle within the collection period, and s is the total number of vehicles entering and leaving within the collection period; Obtain the emission difference according to the historical environmental data and the fixed emissions :

[0008] Where: λ x is the proportion coefficient of carbon element in the x-th greenhouse gas, Ggc x is the concentration of the x-th greenhouse gas, and h is the total number of greenhouse gas parameters within the collection period; And obtain the emission difference coefficient according to the emission difference and rainfall in each collection period :

[0009] Where: ω is the preset correction coefficient, Ed r is the emission difference in the r-th collection period, R is the total number of collection periods, f r is the rainfall in the r-th collection period; Carbon emission monitoring module: Obtain the traffic flow data in the park during the current collection period, denoted as the current traffic flow data, and obtain the material consumption of the carbon emission materials at each emission point in the park during the current collection period, denoted as the current material consumption data; Judge the emission intensity of greenhouse gases in the air according to the current traffic flow data, the current material consumption data and the emission difference coefficient.

[0010] As a further solution of the present invention: The setting process of the collection period includes: Set a time interval threshold, and the setting range of the time interval threshold is [1, 7] days; Select a time node every other time interval threshold, and obtain a collection period from every two adjacent time nodes.

[0011] As a further solution of the present invention: The material consumption of the carbon emission material is the volume or mass of the carbon emission material.

[0012] As a further solution of the present invention: the greenhouse gases include carbon dioxide and methane.

[0013] As a further solution of the present invention: the process of obtaining the weight coefficient of the carbon emission material includes: Obtain the chemical reaction formula in the production process of the emission point, and obtain the weight coefficient of the carbon emission material according to the proportion of the carbon element of the carbon emission material in the chemical reaction formula.

[0014] As a further solution of the present invention: the process of obtaining the greenhouse gas emission intensity includes: According to the current traffic flow data and the current material consumption data, obtain the current fixed emission Fe´ within the current collection period; according to the emission difference coefficient E and the current fixed emission Fe´, obtain the carbon content value Cv in the air = Fe´ - E; Set a carbon content threshold Cv´. If the carbon content value Cv ≥ Cv´, the greenhouse gas emission intensity in the air is high; otherwise, the greenhouse gas emission intensity in the air is low.

[0015] Advantages of the present invention: Through the tail gas emission calibration module of the present invention, the system can accurately obtain the carbon emissions after the vehicle travels a unit mileage, thereby providing accurate basic data for subsequent carbon emission calculations to improve the accuracy of carbon emission monitoring; the system sets a collection period and can update data regularly, thereby realizing dynamic monitoring of the carbon emissions in the park. The carbon emission monitoring module combines the traffic flow data and material consumption data of the current collection period, and combines the emission difference coefficient to judge the greenhouse gas emission intensity in the air in real time, providing timely feedback for the park managers to achieve dynamic monitoring and management; by analyzing historical data and current data, the system can help park managers identify the main carbon emission sources and emission trends, and thus formulate targeted emission reduction strategies. The calculation of the emission difference coefficient takes into account environmental factors such as rainfall, making the assessment of emissions closer to the actual situation, helping to optimize resource allocation and the implementation of emission reduction measures to optimize resource allocation and emission reduction strategies; the implementation of the method of the present invention can enhance the attention to carbon emission issues inside and outside the park, enhance environmental awareness, and through public and transparent carbon emission data, it can promote the supervision and participation of the public in the environmental protection work of the park, forming a good atmosphere of the whole society's joint attention to environmental protection to enhance environmental awareness and public participation; the park carbon emission monitoring system based on big data of the present invention has significant beneficial effects in improving monitoring accuracy, realizing dynamic management, optimizing resource allocation and enhancing environmental awareness. Description of the Drawings

[0016] The present invention will be further described below with reference to the drawings.

[0017] Figure 1 It is a schematic flow diagram of a park carbon emission monitoring system based on big data according to the present invention. Specific implementation manners

[0018] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0019] Please refer to Figure 1 As shown, the present invention is a park carbon emission monitoring system based on big data, including: Tail gas emission calibration module: Select a number of vehicle samples, obtain the carbon emissions after each vehicle sample travels a unit mileage, and obtain the average carbon emissions after the vehicle samples travel a unit mileage, denoted as the unit carbon emissions U.

[0020] It can be understood that the tail gas emission calibration module measures the carbon emissions of a number of vehicle samples after they travel a unit mileage; through averaging these sample data, the average carbon emissions after the vehicle samples travel a unit mileage are obtained, denoted as the unit carbon emissions; the purpose is to establish a benchmark for subsequent calculation of the carbon emissions generated during vehicle driving; the unit carbon emissions U, as a standard value, can be used to estimate the total carbon emissions generated by vehicle driving within the entire park.

[0021] Historical data collection module: Obtain the emission points in the park and obtain the carbon emission materials of the emission points. The emission points include factories, and the carbon emission materials are the source materials for carbon emissions generated during the production process of the factories.

[0022] It can be understood that the historical data collection module is responsible for collecting data of each emission point in the park, especially the source materials that generate carbon emissions during the production process; the emission points include industrial facilities such as factories; by collecting these data, the system can understand the carbon emission situation of each emission point in the park over a past period of time; these data are crucial for analyzing the carbon emission pattern of the park, identifying the main carbon emission sources, and formulating emission reduction strategies.

[0023] Set the collection period, obtain historical emission data, the historical emission data includes historical material consumption data, and the historical material consumption data includes the material consumption of the carbon emission materials of the emission points in each collection period; and obtain historical environmental data, the historical environmental data includes the rainfall, the concentration of greenhouse gases in the air, and the traffic flow data of the park in each collection period, and the traffic flow data includes all vehicles entering and leaving the park and the driving mileage of each vehicle.

[0024] It is understandable that in order to systematically monitor and analyze the carbon emissions in the park, a fixed time interval needs to be set to collect data for the setting of the collection period; this period can be determined according to actual needs and the accuracy requirements of data analysis; by collecting data regularly, the changing trends of carbon emissions in the park and the impact of environmental factors on carbon emissions can be tracked and recorded; the historical emission data is the data collected from each emission point in the park during each collection period; these emission points include industrial facilities such as factories, which are the main sources of carbon emissions during the production process; in addition to the data of the emission points, environmental data related to carbon emissions, that is, historical environmental data, also needs to be collected; this data includes the rainfall, the concentration of greenhouse gases in the air, and the traffic flow data in the park during each collection period; environmental data is crucial for understanding the background conditions of carbon emissions; for example, rainfall affects air quality, while the concentration of greenhouse gases in the air directly reflects the carbon emission level of the park; the traffic flow data can help analyze the contribution of traffic to carbon emissions.

[0025] It should be noted that rainfall does produce a dilution effect in the air. Rainwater will mix with greenhouse gases in the air (such as carbon dioxide, methane, etc.), resulting in a decrease in the concentration of these gases; this is because rainwater increases the humidity of the air, thus diluting the greenhouse gases; and rainfall provides necessary moisture for plants, which helps the growth of plants and the progress of photosynthesis; photosynthesis is the process by which plants absorb carbon dioxide and release oxygen. Therefore, an increase in rainfall may promote the photosynthesis of plants, thereby reducing the content of carbon dioxide in the air.

[0026] In a preferred embodiment of the present invention, the setting process of the collection period includes: Set a time interval threshold, and the setting range of the time interval threshold is [1, 7] days; select a time node every other time interval threshold, and a collection period is obtained from every two adjacent time nodes.

[0027] It is understandable that, first of all, a duration interval threshold needs to be determined. This threshold is a time range used to define the interval between two adjacent time nodes; the setting range of the duration interval threshold is [1, 7] days, which means that any day between 1 day and 7 days can be selected as the duration interval threshold; every other duration interval threshold, a time node is selected; every other duration interval threshold, a time node is selected; for example, if the duration interval threshold is set to 3 days, then the first time node may be the 0th day, the second time node is the 3rd day, the third time node is the 6th day, and so on; each adjacent pair of time nodes constitutes a collection period; for example, if the first time node is the 0th day and the second time node is the 3rd day, then the collection period between these two time nodes is from the 0th day to the 3rd day.

[0028] In a preferred embodiment of the present invention, the amount of the carbon emission material used is the volume or mass of the carbon emission material.

[0029] Historical data analysis module: Obtain the fixed emissions within the collection period according to the historical environmental data and historical material usage data :

[0030] Where: w i is the weight coefficient of the i-th carbon emission material at the emission point, Mc i is the amount of the i-th carbon emission material used at the emission point, n is the number of types of carbon emission materials in the production process at the emission point, e represents the e-th emission point in the park, m is the total number of emission points in the park, L k is the driving mileage of the k-th vehicle within the collection period, and s is the total number of vehicles entering and leaving within the collection period.

[0031] Obtain the emission difference according to the historical environmental data and the fixed emissions :

[0032] Where: λ x is the proportion coefficient of carbon element in the x-th greenhouse gas, Ggc x is the concentration of the x-th greenhouse gas, and h is the total number of greenhouse gas parameters within the collection period.

[0033] And obtain the emission difference coefficient according to the emission difference and rainfall within each collection period :

[0034] Where: ω is the preset correction coefficient, Edr is the emission difference in the r-th collection period, R is the total number of collection periods, and f r is the rainfall in the r-th collection period.

[0035] It can be understood that through the above calculations, the fixed emissions, emission differences, and emission difference coefficients for each collection period can be obtained, and these data can be used to analyze the carbon emissions in the park; the emission difference represents the degree of cleaning of the fixed emissions by the weather, that is, the reduction of the greenhouse gas concentration in the air by the rainfall during the collection period.

[0036] As a preferred embodiment of the present invention, the process for obtaining the weight coefficient of the carbon emission material includes: Obtain the chemical reaction formula during the production process at the emission point, and obtain the weight coefficient of the carbon emission material according to the proportion of the carbon element of the carbon emission material in the chemical reaction formula.

[0037] It can be understood that it is necessary to obtain the chemical reaction formula during the production process at the emission point; this formula describes the chemical reactions that occur during the production process, including reactants, products, and reaction conditions, etc.; according to the chemical reaction formula, calculate the proportion of the carbon element of the carbon emission material therein; this can be determined by analyzing the molecular structure of the reactants. For example, if the reactants contain carbon atoms, then these carbon atoms will be converted into carbon dioxide or other carbon-containing compounds after the reaction; according to the calculated proportion of the carbon element above, obtain the weight coefficient of the carbon emission material; this weight coefficient reflects the proportion of the carbon emission material in the total emissions and is one of the important indicators for evaluating carbon emissions.

[0038] Carbon emission monitoring module: Obtain the traffic flow data in the park during the current collection period, denoted as the current traffic flow data, and obtain the material consumption of the carbon emission materials at each emission point in the park during the current collection period, denoted as the current material consumption data; judge the emission intensity of greenhouse gases in the air according to the current traffic flow data, current material consumption data, and emission difference coefficient.

[0039] It can be understood that according to the above calculation results, the emission intensity of greenhouse gases in the current air can be judged; if the emission difference coefficient is large, it means that the current greenhouse gas emission intensity is high; otherwise, it means that the emission intensity is low.

[0040] As a preferred embodiment of the present invention, the process for obtaining the greenhouse gas emission intensity includes: According to the current traffic flow data and current material consumption data, obtain the current fixed emissions Fe´ during the current collection period; according to the emission difference coefficient E and the current fixed emissions Fe´, obtain the carbon content value Cv = Fe´ - E in the air; Set a carbon content threshold Cv´. If the carbon content value Cv ≥ Cv´, the greenhouse gas emission intensity in the air is high; otherwise, the greenhouse gas emission intensity in the air is low.

[0041] The above has described an embodiment of the present invention in detail, but the content described is only the preferred embodiment of the present invention and cannot be considered as defining the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application should still fall within the patent coverage scope of the present invention.

Claims

1. A park carbon emission monitoring system based on big data, characterized in that: include: Exhaust emission calibration module: select several vehicle samples, obtain the carbon emissions of each vehicle sample after driving a unit mileage, and obtain the average carbon emissions of the vehicle samples after driving a unit mileage, which is recorded as unit carbon emissions U; Historical data collection module: obtain emission points in the park and obtain carbon emission materials of the emission points, the emission points include factories, and the carbon emission materials are source materials of carbon emissions generated by the factories during the production process; Set a collection cycle to obtain historical emission data, including historical material usage data, which includes the amount of carbon emission materials used at the emission point in each collection cycle; and obtain historical environmental data, which includes rainfall in each collection cycle, greenhouse gas concentration in the air, and traffic flow data in the park, which includes all vehicles entering and leaving the park and the mileage of each vehicle; Historical data analysis module: Based on the historical environmental data and historical material data, the fixed emissions within the collection period are obtained. : Where: w i is the weight coefficient of the ith carbon emission material at the emission point, Mc i is the amount of carbon emission material used at the i-th emission point, n is the number of types of carbon emission materials in the production process of the emission point, e represents the e-th emission point in the park, m is the total number of emission points in the park, L k is the mileage of the kth vehicle during the collection period, and s is the total number of vehicles entering and leaving during the collection period; Based on the historical environmental data and fixed emissions, the emission difference is obtained. : in: λ x is the carbon content of the xth greenhouse gas, Ggc x is the concentration of the xth greenhouse gas, and h is the total number of greenhouse gas parameters in the collection period; And according to the emission difference and rainfall in each collection period, the emission difference coefficient is obtained : in: ω is the preset correction factor, Ed r is the emission difference of the rth collection period, R is the total number of collection periods, and f r is the rainfall in the rth collection period; Carbon emission monitoring module: obtain the traffic flow data in the park during the current collection period, recorded as the current traffic flow data, and obtain the amount of carbon emission materials used at each emission point in the park during the current collection period, recorded as the current material usage data; judge the greenhouse gas emission intensity in the air based on the current traffic flow data, current material usage data and emission difference coefficient.

2. According to the big data-based park carbon emission monitoring system of claim 1, it is characterized in that: The process of setting the acquisition cycle includes: A time interval threshold is set, and the setting range of the time interval threshold is [1, 7] days; a time node is selected every time interval threshold, and a collection cycle is obtained from every two adjacent time nodes.

3. According to the big data-based park carbon emission monitoring system of claim 1, it is characterized in that: The amount of the carbon emission material is the volume or mass of the carbon emission material.

4. According to the big data-based park carbon emission monitoring system of claim 1, it is characterized in that: The greenhouse gases include carbon dioxide and methane.

5. The park carbon emission monitoring system based on big data according to claim 1 is characterized in that: The process of obtaining the weight coefficient of the carbon emission material includes: A chemical reaction formula of the emission point in the production process is obtained, and a weight coefficient of the carbon emission material is obtained according to the proportion of the carbon element of the carbon emission material in the chemical reaction formula.

6. The park carbon emission monitoring system based on big data according to claim 1 is characterized in that: The process of obtaining the greenhouse gas emission intensity includes: According to the current vehicle flow data and the current material data, the current fixed emission Fe' in the current collection period is obtained; according to the emission difference coefficient E and the current fixed emission Fe', the carbon content value Cv=Fe'-E in the air is obtained; A carbon content threshold Cv´ is set. If the carbon content value Cv≥Cv´, the greenhouse gas emission intensity in the air is high; otherwise, the greenhouse gas emission intensity in the air is low.

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