A park carbon emission monitoring system based on big data

Abstract

The application relates to the technical field of carbon emission monitoring, and particularly discloses a park carbon emission monitoring system based on big data, which comprises: a tail gas emission calibration module: a plurality of vehicle samples are selected, and the unit carbon emission of the vehicle samples after driving a unit mileage is calculated; a historical data acquisition module: emission points in a park are acquired, and carbon emission materials of the emission points are collected; a collection cycle is set, and historical emission data and historical environment data are acquired; a historical data analysis module: fixed emission in the collection cycle is calculated according to the historical environment data and historical material data; emission difference is calculated according to the historical environment data and the fixed emission; emission difference coefficients are calculated according to the emission difference and rainfall in each collection cycle; and a carbon emission monitoring module: current traffic data and current material data are acquired; and the greenhouse gas emission intensity in the air is judged according to the current traffic data, the current material data and the emission difference coefficients.

Description

Technical Field

[0001] This invention relates to the field of carbon emission monitoring technology, specifically to a big data-based industrial park carbon emission monitoring system. Background Technology

[0002] The park's carbon emission monitoring is a comprehensive system designed to monitor and manage carbon emissions within the park in real time. By building a comprehensive carbon emission monitoring system, the park can effectively manage and control carbon emissions, contributing to the achievement of low-carbon development and environmental protection goals.

[0003] Carbon emission monitoring in the industrial park is a multi-dimensional and multi-technology integrated process, which includes monitoring of multiple aspects such as data collection, data processing, monitoring and processing, and feedback and early warning.

[0004] In existing technologies, carbon emissions within industrial parks fluctuate, influenced by various factors such as seasonality and changes in production activities. This volatility makes the process of frequently collecting carbon emission data cumbersome and complex. Accurately assessing the carbon emissions of industrial parks requires regular data collection and analysis, but this demands significant human, material, and time resources. Furthermore, the differences in production activities and energy consumption patterns across different industrial parks also present challenges in calculating and monitoring carbon emissions. Summary of the Invention

[0005] The purpose of this invention is to provide a big data-based carbon emission monitoring system for industrial parks, thereby solving the above-mentioned technical problems.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A big data-based carbon emission monitoring system for industrial parks includes:

[0008] Exhaust emission calibration module: Select several vehicle samples, obtain the carbon emission of each vehicle sample after driving a unit mileage, and obtain the average carbon emission of the vehicle sample after driving a unit mileage, which is denoted as unit carbon emission U.

[0009] Historical data acquisition module: acquires emission points within the park and acquires the carbon emission materials of the emission points, including factories, and the carbon emission materials are the source materials of carbon emissions generated by the factories during the production process;

[0010] Set a collection period to acquire historical emission data, which includes historical material usage data, including the amount of carbon emission materials used at the emission point in each collection period; and acquire historical environmental data, including rainfall, greenhouse gas concentration in the air, and traffic flow data in the park in each collection period, including all vehicles entering and leaving the park and the mileage of each vehicle.

[0011] Historical data analysis module: Based on the historical environmental data and historical material usage data, obtain the fixed emissions within the collection period. :

[0012]

[0013] Where: w i Mc is the weighting coefficient for the i-th carbon emission material at the emission point. i Let L be the amount of carbon-emitting material used at the i-th emission point, n be the number of types of carbon-emitting materials used in the production process at the emission point, e represent the e-th emission point in the park, m be the total number of emission points in the park, and L be the total number of emission points in the park. k The distance traveled by the kth vehicle within the data collection period is s, and the total number of vehicles entering and exiting within the data collection period is s.

[0014] Based on the historical environmental data and fixed emissions, the emission difference is obtained. :

[0015]

[0016] in: l x Ggc represents the proportion of carbon in the x-th greenhouse gas. x Let be the concentration of the x-th greenhouse gas, and h be the total number of greenhouse gas parameters collected in the collection period;

[0017] The emission difference coefficient is obtained based on the emission difference and rainfall in each collection period. :

[0018]

[0019] in: oh Ed is the preset correction factor. r Let f be the emission difference in the r-th collection cycle, R be the total number of collection cycles, and f r Let be the rainfall in the r-th data collection period;

[0020] Carbon emission monitoring module: acquires traffic flow data within the park during the current collection period, and records it as current traffic flow data; acquires the amount of carbon emission materials used at each emission point within the park during the current collection period, and records it as current material usage data; and determines the intensity of greenhouse gas emissions in the air based on the current traffic flow data, current material usage data, and emission differential coefficient.

[0021] As a further aspect of the present invention: the process of setting the acquisition period includes:

[0022] Set a time interval threshold, the time interval threshold is set in the range of [1, 7] days; select a time node every time interval threshold, and obtain a collection cycle from every two adjacent time nodes.

[0023] As a further aspect of the present invention: the amount of carbon emission material used is the volume or mass of the carbon emission material.

[0024] As a further aspect of the present invention, the greenhouse gases include carbon dioxide and methane.

[0025] As a further aspect of the present invention: the process of obtaining the weighting coefficient of the carbon emission material includes:

[0026] Obtain the chemical reaction formula of the emission point in the production process, and obtain the weighting coefficient of the carbon emission material based on the proportion of carbon element in the carbon emission material in the chemical reaction formula.

[0027] As a further aspect of the present invention: the process for obtaining the greenhouse gas emission intensity includes:

[0028] Based on the current traffic flow data and current material consumption data, obtain the current fixed emission amount Fe´ within the current collection period; based on the emission difference coefficient E and the current fixed emission amount Fe´, obtain the carbon content value in the air Cv=Fe´-E;

[0029] 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.

[0030] The beneficial effects of this invention are:

[0031] This invention utilizes an exhaust emission calibration module to accurately acquire carbon emissions per unit mileage traveled by a vehicle, providing accurate baseline data for subsequent carbon emission calculations and improving the accuracy of carbon emission monitoring. The system features a pre-set data collection cycle, enabling regular data updates and dynamic monitoring of carbon emissions within the industrial park. Based on traffic flow and material usage data from the current collection cycle, combined with emission differential coefficients, the carbon emission monitoring module determines the intensity of greenhouse gas emissions in the air in real time, providing timely feedback to park managers for dynamic monitoring and management. Furthermore, by analyzing historical and current data, the system helps park managers identify major carbon emission sources and trends, allowing for targeted development of [specific strategies / measures]. The emission reduction strategy, and the calculation of the emission difference coefficient taking into account environmental factors such as rainfall, makes the emission assessment more closely reflect the actual situation, which helps to optimize resource allocation and the implementation of emission reduction measures. The implementation of the method of this invention can increase attention to carbon emission issues both inside and outside the park, enhance environmental awareness, and promote public supervision and participation in environmental protection work in the park through open and transparent carbon emission data, forming a good atmosphere in which the whole society pays attention to environmental protection, thereby improving environmental awareness and public participation. The big data-based park carbon emission monitoring system of this invention has significant beneficial effects in improving monitoring accuracy, realizing dynamic management, optimizing resource allocation, and enhancing environmental awareness. Attached Figure Description

[0032] The invention will now be further described with reference to the accompanying drawings.

[0033] Figure 1 This is a flowchart illustrating a big data-based carbon emission monitoring system for industrial parks according to the present invention. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Please see Figure 1 As shown, this invention is a big data-based carbon emission monitoring system for industrial parks, comprising:

[0036] 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 denoted as unit carbon emissions U.

[0037] It is understood that the exhaust emission calibration module selects several vehicle samples and measures their carbon emissions after driving a unit mileage; by averaging these sample data, the average carbon emissions of the vehicle samples after driving a unit mileage are obtained, which is recorded as the unit carbon emission; the purpose is to establish a benchmark for subsequent calculation of the carbon emissions generated during vehicle operation; the unit carbon emission U is used as a standard value to estimate the total carbon emissions generated by vehicles operating in the entire park.

[0038] Historical data acquisition module: Acquire emission points within the park and acquire the carbon emission materials of the emission points, including factories, and the carbon emission materials are the source materials of carbon emissions generated by the factories during the production process.

[0039] Understandably, the historical data acquisition module is responsible for collecting data from various emission points within the park, especially those source materials that generate carbon emissions during the production process; these emission points include industrial facilities such as factories; by collecting this data, the system can understand the carbon emissions of each emission point within the park over a period of time; this data is crucial for analyzing the park's carbon emission patterns, identifying major carbon emission sources, and developing emission reduction strategies.

[0040] Set a collection period to acquire historical emission data, which includes historical material usage data, including the amount of carbon emission materials used at the emission point during each collection period; and acquire historical environmental data, including rainfall, greenhouse gas concentration in the air, and traffic flow data in the park during each collection period, including all vehicles entering and leaving the park and the mileage of each vehicle.

[0041] It is understandable that the data collection cycle is set to systematically monitor and analyze the carbon emissions of the park, requiring a fixed time interval for data collection. This cycle can be determined based on actual needs and the required accuracy of data analysis. Regular data collection allows for tracking and recording of trends in carbon emissions within the park, as well as the impact of environmental factors on carbon emissions. The historical emission data refers to data collected from various emission points within the park during each collection cycle. These emission points include industrial facilities such as factories, which are the main sources of carbon emissions during production. In addition to emission point data, it is also necessary to collect environmental data related to carbon emissions, i.e., historical environmental data. This data includes rainfall, atmospheric greenhouse gas concentrations, and traffic flow data within the park during each collection cycle. Environmental data is crucial for understanding the background conditions of carbon emissions. For example, rainfall affects air quality, while atmospheric greenhouse gas concentrations directly reflect the park's carbon emission levels. Traffic flow data helps analyze the contribution of traffic to carbon emissions.

[0042] It is worth noting that rainfall does indeed have a dilution effect in the air. Rainwater mixes with greenhouse gases (such as carbon dioxide and methane) in the air, causing a decrease in the concentration of these gases. This is because rainwater increases the humidity of the air, thereby diluting the greenhouse gases. In addition, rainfall provides plants with the necessary water, which helps plant growth and photosynthesis. Photosynthesis is the process by which plants absorb carbon dioxide and release oxygen. Therefore, increased rainfall may promote plant photosynthesis, thereby reducing the carbon dioxide content in the air.

[0043] In a preferred embodiment of the present invention, the process of setting the acquisition period includes:

[0044] Set a time interval threshold, the time interval threshold is set in the range of [1, 7] days; select a time node every time interval threshold, and obtain a collection cycle from every two adjacent time nodes.

[0045] Understandably, firstly, a time interval threshold needs to be determined. This threshold is a time range used to define the interval between two adjacent time nodes. The time interval threshold is set within the range of [1, 7] days, meaning that any day between 1 and 7 days can be selected as the time interval threshold. Every other time interval threshold, a time node is selected. For example, if the time interval threshold is set to 3 days, then the first time node might be day 0, the second time node is day 3, the third time node is day 6, and so on. Each pair of adjacent time nodes constitutes a collection cycle. For example, if the first time node is day 0 and the second time node is day 3, then the collection cycle between these two time nodes is from day 0 to day 3.

[0046] In a preferred embodiment of the present invention, the amount of carbon emission material used is the volume or mass of the carbon emission material.

[0047] Historical data analysis module: Based on the historical environmental data and historical material usage data, obtain the fixed emissions within the collection period. :

[0048]

[0049] Where: w i Mc is the weighting coefficient for the i-th carbon emission material at the emission point. i Let L be the amount of carbon-emitting material used at the i-th emission point, n be the number of types of carbon-emitting materials used in the production process at the emission point, e represent the e-th emission point in the park, m be the total number of emission points in the park, and L be the total number of emission points in the park. ks represents the mileage of the kth vehicle within the data collection period, and s represents the total number of vehicles entering and exiting within the data collection period.

[0050] Based on the historical environmental data and fixed emissions, the emission difference is obtained. :

[0051]

[0052] in: l x Ggc represents the proportion of carbon in the x-th greenhouse gas. x Let be the concentration of the x-th greenhouse gas, and h be the total number of greenhouse gas parameters collected in the sampling period.

[0053] The emission difference coefficient is obtained based on the emission difference and rainfall in each collection period. :

[0054]

[0055] in: oh Ed is the preset correction factor. r Let f be the emission difference in the r-th collection cycle, R be the total number of collection cycles, and f r Let be the rainfall in the r-th collection period.

[0056] Understandably, the above calculations can yield the fixed emissions, emission differential, and emission differential coefficient for each collection cycle. These data can be used to analyze the carbon emissions of the park. The emission differential represents the degree to which the weather cleanses the fixed emissions, i.e., the reduction in the concentration of greenhouse gases in the air due to rainfall during the collection cycle.

[0057] In a preferred embodiment of the present invention, the process of obtaining the weighting coefficient of the carbon emission material includes:

[0058] Obtain the chemical reaction formula of the emission point in the production process, and obtain the weighting coefficient of the carbon emission material based on the proportion of carbon element in the carbon emission material in the chemical reaction formula.

[0059] Understandably, it is necessary to obtain the chemical reaction formula for the emission point during the production process. This formula describes the chemical reactions that occur during production, including reactants, products, and reaction conditions. Based on the chemical reaction formula, the proportion of carbon in the carbon-emitting material is calculated. This can be determined by analyzing the molecular structure of the reactants. For example, if the reactants contain carbon atoms, these carbon atoms will be converted into carbon dioxide or other carbon-containing compounds after the reaction. Based on the calculated carbon proportion, the weighting coefficient of the carbon-emitting material is obtained. This weighting coefficient reflects the proportion of the carbon-emitting material in the total emissions and is one of the important indicators for assessing carbon emissions.

[0060] Carbon emission monitoring module: acquires traffic flow data within the park during the current collection period, and records it as current traffic flow data; acquires the amount of carbon emission materials used at each emission point within the park during the current collection period, and records it as current material usage data; and determines the intensity of greenhouse gas emissions in the air based on the current traffic flow data, current material usage data, and emission differential coefficient.

[0061] Understandably, based on the above calculation results, the current greenhouse gas emission intensity in the air can be determined; if the emission difference coefficient is large, it indicates that the current greenhouse gas emission intensity is high; conversely, it indicates that the emission intensity is low.

[0062] In a preferred embodiment of the present invention, the process of obtaining the greenhouse gas emission intensity includes:

[0063] Based on the current traffic flow data and current material consumption data, obtain the current fixed emission amount Fe´ within the current collection period; based on the emission difference coefficient E and the current fixed emission amount Fe´, obtain the carbon content value in the air Cv=Fe´-E;

[0064] 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.

[0065] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A big data-based carbon emission monitoring system for industrial parks, characterized in that, include: Exhaust emission calibration module: Select several vehicle samples, obtain the carbon emission of each vehicle sample after driving a unit mileage, and obtain the average carbon emission of the vehicle sample after driving a unit mileage, which is denoted as unit carbon emission U. Historical data acquisition module: acquires emission points within the park and acquires the carbon emission materials of the emission points, including factories, and the carbon emission materials are the source materials of carbon emissions generated by the factories during the production process; Set a collection period to acquire historical emission data, which includes historical material usage data, including the amount of carbon emission materials used at the emission point in each collection period; and acquire historical environmental data, including rainfall, greenhouse gas concentration in the air, and traffic flow data in the park in each collection period, including 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 usage data, obtain the fixed emissions within the collection period. : Where: w i Mc is the weighting coefficient for the i-th carbon emission material at the emission point. i Let L be the amount of carbon-emitting material used at the i-th emission point, n be the number of types of carbon-emitting materials used in the production process at the emission point, e represent the e-th emission point in the park, m be the total number of emission points in the park, and L be the total number of emission points in the park. k The distance traveled by the kth vehicle within the data collection period is s, and the total number of vehicles entering and exiting within the data collection period is s. Based on the historical environmental data and fixed emissions, the emission difference is obtained. : in: λ x Ggc represents the proportion of carbon in the x-th greenhouse gas. x Let be the concentration of the x-th greenhouse gas, and h be the total number of greenhouse gas parameters collected in the collection period; The emission difference coefficient is obtained based on the emission difference and rainfall in each collection period. : in: ω Ed is the preset correction factor. r Let f be the emission difference in the r-th collection cycle, R be the total number of collection cycles, and f r Let be the rainfall in the r-th data collection period; Carbon emission monitoring module: acquires traffic flow data within the park during the current collection period, and records it as current traffic flow data; acquires the amount of carbon emission materials used at each emission point within the park during the current collection period, and records it as current material usage data; and determines the intensity of greenhouse gas emissions in the air based on the current traffic flow data, current material usage data, and emission differential coefficient. The process of obtaining the greenhouse gas emission intensity includes: Based on the current traffic flow data and current material consumption data, obtain the current fixed emission amount Fe´ within the current collection period; based on the emission difference coefficient E and the current fixed emission amount Fe´, obtain the carbon content value in the air Cv=Fe´-E; 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.

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

3. The big data-based industrial park carbon emission monitoring system according to claim 1, characterized in that, The amount of carbon emission material used refers to the volume or mass of the carbon emission material.

4. The big data-based carbon emission monitoring system for industrial parks according to claim 1, characterized in that, The greenhouse gases include carbon dioxide and methane.

5. A big data-based industrial park carbon emission monitoring system according to claim 1, characterized in that, The process of obtaining the weighting coefficients for the carbon emission materials includes: Obtain the chemical reaction formula of the emission point in the production process, and obtain the weighting coefficient of the carbon emission material based on the proportion of carbon element in the carbon emission material in the chemical reaction formula.

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