Parameterizing surface conductance of different urban vegetation types for the urban land surface model SUEWS with evaluation in two mid-latitude cities

Abstract

As cities are taking actions to reduce and offset part of their anthropogenic carbon dioxide (CO2) emissions, urban vegetation has become vitally important in pursuing carbon neutrality and climate mitigation. Its effectiveness in carbon sequestration, however, has large uncertainties due to the complex urban environment comprising both natural and artificial elements. By considering seven interacting land surface covers (buildings, pavement, evergreen trees, deciduous trees, grass, soil and water) within each model grid, the Surface Urban Energy and Water balance Scheme (SUEWS) is an urban land surface model that can simulate energy, water and CO2 exchanges in cities. For SUEWS to simulate the CO2 fluxes in urban green spaces, it requires information of maximum photosynthesis and surface conductance of specific urban vegetation as well as the response of surface conductance to environmental conditions. To derive these parameters, it is necessary to utilize on-site measurements conducted over urban green spaces for an accurate description of the surface processes and variables.To our knowledge, only the mixed vegetation type and street trees in Helsinki have been parameterized in SUEWS so far. In order to extend the flexibility and usability of SUEWS modelling across different cities and for specific urban vegetation, this research aims to (1) derive surface conductance and photosynthesis parameters from eddy covariance and chamber measurements conducted over several urban sites corresponding to different urban vegetation types, such as non-irrigated lawn, turf grass, park trees, urban fields, green roof and urban forests (evergreen and mixed-leaf); and (2) evaluate the impact of selected surface conductance and photosynthesis parameters on SUEWS model performance in two mid-latitude cities: Swindon, UK and Minneapolis-Saint Paul, USA.The surface conductance and photosynthesis parameters for specific urban vegetation are derived by fitting measurements to an empirical canopy-level photosynthesis model where the effect of the local conditions (i.e. meteorology and ecology) is considered. Using the bootstrapping method to randomly select seven-eighths of the available measurements for 100 times, the fitted maximum photosynthesis rates range from 5.27 μmol m-2 s-1 over an non-irrigated lawn to 10.72 μmol m-2 s-1 over an evergreen forest with the dependencies on the local environmental response functions such as air temperature, incoming shortwave radiation, specific humidity deficit and soil moisture deficit. As a following step, the choice of model parameters in SUEWS simulations will be examined in the two cities along with on-site measurements. This research improves SUEWS simulations over urban areas by deriving new surface conductance and photosynthesis parameters specific to different urban vegetation types and provides a more accurate quantification of their biogenic CO2 flux in a complex urban environment. The results also provide a better understanding on the carbon sequestration potential of urban vegetation, which will be useful in planning urban green spaces to maximize natural carbon sinks and in setting climate mitigation strategies.