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With the launch and promotion of national carbon trading market, accurate carbon emission data of emission control enterprises is crucial for the government to formulate policies and build carbon trading mechanisms. The current official carbon emission accounting method in China, the emission factor method, is simple and easy to use, but is highly influenced by human factors and can easily lead to quality issues with carbon data. Therefore, a rapid analysis method for coal quality indicators suitable for coal-fired power plants in the carbon market is developed based on laser induced breakdown spectroscopy (LIBS) technology. Combined with partial least squares regression (PLSR), a predictive model for carbon content and heat generation of coal elements is established. The results show that, the average absolute error (AAE) of the prediction set for the established dry based high calorific value and carbon content model is 1.10 MJ/kg and 2.72%, respectively, which can achieve fast and high-frequency detection of daily coal samples in power plants. In the application research of carbon accounting, examples show that, compared with the conventional daily measurement method, the relative deviation of monthly carbon emissions accounting obtained by the LIBS rapid detection method for daily measurement is only 0.40%, which is more accurate than that obtained by the monthly reduced coal sample detection method. In the application research of carbon verification, based on the results of the element carbon content measurement method, the average relative error (ARE) of the carbon emissions calculated using the LIBS rapid detection method has a reduction of 6.73~18.99 percentage points compared with that using the complete default value method. The LIBS rapid detection method has a testing accuracy that is close to conventional laboratory results, which can be applied to carbon verification and coal quality data verification, and be developed into a fast and low-cost practical technology to assist carbon accounting.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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