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The report of the 20th National Congress of the Communist Party of China proposed to "improve the carbon emission statistical accounting system and improve the carbon emission rights market trading system", which highlights the great importance the Party Central Committee attaches to the carbon emission accounting work. Statistical accounting of carbon emissions is the cornerstone of the construction and operation of the carbon trading system, and it is also the basic basis for doing a good job in peak carbon dioxide emissions carbon neutrality. As a key element supporting the statistical accounting of carbon emissions, carbon emission monitoring plays an important role in achieving the goal of peak carbon dioxide emissions carbon neutrality as scheduled.
"Electric carbon" monitoring helps carbon emission accounting
Carbon emission monitoring is an important part of the carbon emission statistical accounting system. Scientific and orderly carbon emission monitoring can directly serve carbon emission accounting and conduct collaborative verification of accounting results, thereby effectively reducing the uncertainty of carbon emission inventories. At the same time, it can also provide quantitative process monitoring and auxiliary management means for the country, industry and enterprise's carbon emission reduction process in a timely manner.
At present, carbon emission monitoring methods have problems such as high monitoring cost, low flexibility and limited coverage. Currently widely used carbon emission monitoring methods mainly include online measurement methods and satellite remote sensing monitoring methods. Among them, the online measurement method directly measures the carbon emission concentration, flow rate, flow rate and other data of emission sources through measurement facilities, so as to obtain continuous real-time carbon emissions. This method requires the installation of additional monitoring devices, and the time and economic costs of popularizing it are high. It is difficult to effectively monitor unorganized emissions, and it is difficult to widely monitor a large number of emission sources in the short term. The satellite remote sensing monitoring method is based on the greenhouse gas concentration and meteorological field data observed in the atmosphere, combined with the atmospheric chemical transmission model, and uses the concentration observation results to invert the flux to estimate regional carbon emissions. This method is limited by the accuracy and coverage of satellite remote sensing observation data, and the monitoring results at the micro-scale are highly uncertain.
electricity is an important component of energy consumption and one of the important production factors of industry. Electricity consumption and energy activities are highly coupled, which provides a new idea for carbon emission monitoring. Power big data has the characteristics of wide collection range, high accuracy, strong real-time performance, and high value density. Based on power big data, it is expected to "see the whole leopard", effectively invert and calculate energy activities and carbon emissions. Therefore, it will have important theoretical and practical significance to study how to use power big data as the core to support the efficient development of carbon emission monitoring, reduce the cost of carbon emission monitoring, improve the flexibility and coverage of carbon emission monitoring, and meet the monitoring accuracy requirements in different application scenarios.
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