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To address the issue of biases in the representational capabilities of existing assessment methods for ozone pollution meteorological conditions, stemming from a lack of boundary layer indicators, this study utilized meteorological and environmental observation data collected from 2019 to 2023. By integrating ozone numerical simulations and incorporating source tracking along with process rate analysis techniques within the model framework, we developed a joint model and observation-based Tianjin Ozone Pollution Meteorological Condition Assessment Index (OWI). This index aims to accurately assess ozone pollution meteorological conditions in Tianjin. The research findings reveal a strong correlation between ozone concentrations and various meteorological factors. The OWI index was constructed based on parameters such as average temperature, maximum temperature, relative humidity, daily precipitation, daytime ultraviolet radiation, midday ultraviolet radiation, sunshine duration, average wind speed, and wind direction. It effectively characterizes the impact of these meteorological conditions on ozone levels. Notably, this index exhibits a correlation coefficient of 0.82 with O3 concentration and demonstrates an ability to identify 82% of mild or more severe ozone pollution incidents. Furthermore, by analyzing the effects of daytime and nighttime boundary layer heights on precursor diffusion processes—such as near-surface nitrogen oxide titration and vertical exchange of ozone—the study addresses potential overestimations in O3 concentrations by the OWI index under favorable vertical diffusion conditions. To optimize the OWI index further, we incorporated indicators for both daytime and nighttime boundary layer heights. Through ozone numerical simulations, the study calculated the effects of horizontal and vertical transport, convection, chemical generation, turbulent mixing, and regional transport on ozone levels. By combining simulation results with observations, the OWI index was oized under specific conditions, such as adjusting upwards when daytime vertical transport exceeds 15µg/(m3⋅h) or daytime ozone chemical generation exceeds 20µg/(m3⋅h); and considering surrounding meteorological conditions and ozone transport impacts when regional transport was too strong.
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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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