Optimization Of PM_2.5 Dry Deposition Model Parameters And Its Application In Evaluation Of Shanghai Green Belt

Urban green spaces are essential infrastructure in the urban ecosystem which could provide the ecosystem service of air purification for cities.The airborne particulate matter is removed from the atmosphere through dry deposition on the underlying surfaces,such as vegetation and soil.This process is influenced by meteorological conditions such as precipitation and wind speed,as well as the characteristics of the vegetation itself.The Shanghai Green Belt is an important component of the ecological construction of Shanghai,and the focus of the future"Green Belt Ecological Park".The evaluation of the air purification function of vegetation in this area can guide the management and construction of urban green spaces in the future.Currently,the i-Tree model is the most widely used tool for assessing the ecological benefits of urban forests,and its sub-module,i.e.,the i-Tree Eco model,can be used to assess the air purification function of urban trees.However,the model has limitations as it is semi-mechanical.The parameters in the model are mainly based on either historical observation data or experimental results in Europe and the United States,which has uncertainties when it is extended to other countries and regions.Additionally,model results are rarely validated with experimental data.Therefore,a study was conducted in the Shanghai Green Belt to test the applicability of the i-Tree model in Shanghai by comparing the measured PM_2.5 accumulated on the leaves of the forest and the model results.Then the standard model was adjusted and optimized to adapt to the study area.Eventually,the adjusted model was applied to the green belt and four typical ecological parks of Shanghai to evaluate their deposition capacity of PM_2.5 respectively.The main study results are as follows:（1）Samplings were taken twice from broadleaved and coniferous forests in the Jinhai Wetland Park in the Shanghai Green Belt,and the PM_2.5 mass accumulated on the leaves was measured by the washing and vacuum filtration experiment.Compared with the calculated results of the i-Tree model,it was found that the model underestimated the actual deposition capacity of leaves.The measured PM_2.5 mass per unit leaf area of broadleaved forest was 25-40 times higher than the model results,and the measured value of coniferous forest leaves was 2-5 times higher than its model results.（2）The dry deposition velocity,resuspension rate,and the rain washing capacity in the model were adjusted and optimized:for broadleaved species,the dry deposition velocity was expanded to 10 times its standard value,the resuspension rate was reduced to 0.1 times the standard value,and 60%of particles on the leaf surface were scoured off after the rainfall events exceed the maximum water storage of the canopy;for coniferous species,the dry deposition velocity was taken to be the same as the standard value,the resuspension rate was reduced to 0.1 times the standard value,and40%of particles on the leaf surface were scoured off after the rainfall events exceed the maximum water storage of the canopy.（3）Using the adjusted dry deposition model,combined with the leaf area index extracted from Sentinel-2 remote sensing images,the total amount of PM_2.5 deposition in the vegetation growing season（June-October）in 2021 of the whole Shanghai Green Belt was evaluated.Results showed that 15.76 t of PM_2.5 were deposited in the whole green belt,and the PM_2.5 deposition per unit forest area was 0.30-0.65 g/m² in63.17%of the forestland.The PM_2.5 deposition capacity of different vegetation types was as follows:broadleaved forest（0.40-0.50 g/m²）>mixed broadleaf-conifer forest（0.25-0.36 g/m²）>coniferous forest（0.11-0.22 g/m²）.（4）Using UAV multispectral imaging and Li DAR scanning,high-resolution vegetation structure characteristics of four typical ecological parks in the Shanghai Green Belt were obtained to assess the deposition capacity of their vegetation.The total deposition amount of four parks in descending order:Minhang Sports Park（458.80 kg）>Jinhai Wetland Park（377.35 kg）>Kangqiao Ecological Park（239.54kg）>Decui Park（134.49 kg）.The vegetation types in Jinhai Wetland Park and Minhang Sports Park were dominated by closed broadleaved forests（i.e.,broadleaved forests with a tree canopy cover of more than 70%）,which had a stronger PM_2.5removal capacity.Nevertheless,the structure of vegetation in Decui Park was simplex,with mostly grassland and a higher degree of management,and thus had a weaker deposition capacity.Among all vegetation types in the four parks,the closed broadleaf forest has the highest leaf area index（LAI of 4.12）and the strongest PM_2.5 deposition capacity of 0.83-1.13 g/m².The study concludes that preserving the natural characteristics of this kind of woodland is critical to maintain their ecosystem service function of air purification.In conclusion,this study examines the applicability of the i-Tree model in Shanghai and optimizes the key parameters locally.The optimized model is further used to evaluate the PM_2.5 deposition capacity of vegetation in the Shanghai Green Belt,providing data support for future urban green spaces management and planning.