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Outline
Accurate estimation of CO2 emissions at the regional scale, particularly in large urban agglomerations, is essential for effective greenhouse gas mitigation. In this study, the WRF-STILT model, combined with three prior anthropogenic CO2 emission inventories (EDGAR v6.0, an improved version of EDGAR v6.0 integrated with GCG v1.0, and the ODIAC inventory) was used to simulate atmospheric CO2 concentrations in the Yangtze River Delta during winter 2018. Observational data from a 70-meter tower in Quanjiao, Anhui province, served as the reference. A scale factor Bayesian inversion method was applied to optimize the simulation results, allowing estimation of anthropogenic CO2 emission fluxes in the region. The results indicate that the CO2 concentrations simulated by the WRF-STILT model effectively reflect the emission characteristics of the Yangtze River Delta. In winter, simulations based on the improved inventory aligned more closely with observations than those using EDGAR v6.0alone. The posterior CO2 emission fluxes estimated using the EDGAR and improved inventories were (0.199 ± 0.005) and (0.200 ± 0.007) mg/(m2·s), respectively—representing decreases of 0.02 and 0.01mg/(m2·s) compared to the prior flux estimates. The Bayesian inversion method significantly optimized the prior emissions from the EDGAR inventory. When calculating total CO2 emissions for the region using the improved inventory, power generation and industrial sectors were identified as the primary sources of uncertainty. Additionally, due to the low nocturnal boundary layer height, the model tended to overestimate the contribution of elevated emission sources near the observation site. Future simulations should ensure the WRF model accurately captures hourly boundary layer heights, and that vertical emission profiles of point sources are incorporated into emission inventories.
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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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