The report of the 20th National Congress of the Party proposed to "improve the statistical accounting system of carbon emissions and improve the market trading system of carbon emission rights", demonstrating the great importance of the Party Central Committee to carbon emissions accounting work. Statistical accounting of carbon emissions is the cornerstone of the construction and operation of carbon trading system, and also the basis for carbon peak carbon neutrality. As a key element to support statistical accounting of carbon emissions, carbon emission monitoring plays an important role in achieving the target of peak carbon neutrality on schedule.
"Electric carbon" monitoring helps carbon emissions accounting
Carbon emission monitoring is an important part of carbon emission statistical accounting system. Scientific and orderly carbon emission monitoring can directly serve carbon emission accounting and coordinate verification of accounting results, thus 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 carbon emission reduction process of countries, industries and enterprises in a timely manner.
At present, carbon emission monitoring methods have some problems, such as high monitoring cost, low flexibility and limited coverage. At present, the carbon emission monitoring methods widely used mainly include online measurement and satellite remote sensing monitoring. Among them, the online measurement method directly measures the carbon emission concentration, flow rate, flow rate and other data of the emission source through the metering facility, so as to obtain continuous real-time carbon emission. This method requires the installation of additional monitoring devices, and the time and economic cost of popularization is high, so it is difficult to achieve effective monitoring of unorganized emissions, and it is difficult to achieve extensive monitoring of a large number of emission sources in a short time. 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, through the data assimilation method, using the concentration observation results to invert the flux, so as to estimate the regional carbon emission. This method is limited by the accuracy and coverage of satellite remote sensing observation data, and the uncertainty of micro-scale monitoring results is high.
Electricity is an important component of energy consumption and one of the important production factors of industry. Electricity consumption is highly coupled with energy activities, which provides a new idea for carbon emission monitoring. Power big data has the characteristics of wide collection range, high accuracy, strong real-time and high value density. Based on power big data, it is expected to "see a glimpse and know the whole leopard", and effectively invert and calculate energy activities and carbon emissions. Therefore, it will have important theoretical and practical significance to study how to take power big data as the core to support the efficient development of carbon emission monitoring, promote the reduction of carbon emission monitoring costs, improve the flexibility and coverage of carbon emission monitoring, and meet the monitoring accuracy requirements in different application scenarios.
