Periodic Reporting for period 2 - URBANCO2FLUX (Quantifying the impact of the urban biosphere on the net flux of CO2 from cities into the atmosphere.)
Période du rapport: 2017-09-07 au 2018-09-06
The urban biosphere results in the photosynthetic uptake of CO2 and green-space initiatives are often proposed as GHG reducing strategies, despite there being very little quantitative evidence for the effectiveness or efficiency of such strategies. Uncertainty in the time scales for respiration of carbon previously taken up through photosynthesis obscures the picture even further. Additionally, as the modern urban landscape is continually evolving, with green spaces and parks becoming a more integral component and with suburbs expanding outward from city centers into previously rural, agricultural, and natural areas, it is apparent that we lack the scientific understanding of how best to implement planning strategies that minimize the impact of such land-use changes on climate. With this project, I aim to equip myself with the knowledge to improve our scientific understanding of the impact of the urban biosphere on the net flux of CO2 from cities into the atmosphere.
The main obstacle in quantifying CO2 capture by vegetation is the fact that CO2 flux observations, are influenced only by the net biogenic flux and do not contain information about the separate photosynthetic and respiratory components. Atmospheric carbonyl sulfide (COS), however, can help with this distinction. COS is a potentially transformative tracer of photosynthesis because its variability in the atmosphere has been found to be influenced primarily by vegetative uptake, scaling linearly with gross primary production (GPP).
The main conclusions of the action are that the urban biosphere is indeed an important contribution to the urban carbon footprint, and that OCS is a suitable tracer for quantifing this contribution. Further work needs to be done to improve the model at the urban scale, especially with respect to the boundary layer (BL)and the air mixing effect. BL depth drives mixing ratios, so it is important to improve the BL scheme for urban atmospheric transport models. We found that mixing ratios are driven by BL depth more so than the emissions. For the case study of San Francisco Bay Area, we found more CO2 emissions in the afternoon but lower mixing ratios because BL gets deeper.
The main obstacle in quantifying CO2 capture by vegetation is the fact that CO2 flux observations, are influenced only by the net biogenic flux and do not contain information about the separate photosynthetic and respiratory components. Atmospheric carbonyl sulfide (COS), however, can help with this distinction. COS is a potentially transformative tracer of photosynthesis because its variability in the atmosphere has been found to be influenced primarily by vegetative uptake, scaling linearly with gross primary production (GPP).
The main conclusions of the action are that the urban biosphere is indeed an important contribution to the urban carbon footprint, and that OCS is a suitable tracer for quantifing this contribution. Further work needs to be done to improve the model at the urban scale, especially with respect to the boundary layer (BL)and the air mixing effect. BL depth drives mixing ratios, so it is important to improve the BL scheme for urban atmospheric transport models. We found that mixing ratios are driven by BL depth more so than the emissions. For the case study of San Francisco Bay Area, we found more CO2 emissions in the afternoon but lower mixing ratios because BL gets deeper.
Expertise acquired: I have become familiar with several atmospheric and chemical transport models (WRF, WRF-Chem, and STEM), which I have used to simulate COS fluxes over the San Francisco Bay area. I have successfully regridded emission inventories from global biosphere models and anthropogenic emission inventories using several tools such as IOAPI library utilities and ESMF developed by NOAA. I have compared model runs with observation measurements from several towers. I have learned how to use several graphic tools such as GraDs and NCL to communicate results. I have aplied these methods for the San Francisco Bay Area (first two years of fellowship) and the Metropolitan Area of Barcelona (third and final year of fellowship in home institution). in the third year of the fellowship I have also gained expertise in producing emission files from various sources, downscaling them to urban regions, to be used as input for the WRF-Chem modeling. The main scientific impact of the research developed with UrbanCO2Flux has been to share with the scientific community that hat the urban biosphere is indeed an important contribution to the urban carbon footprint, and that OCS is a suitable tracer for quantifying this contribution. In the return phase, I have shared these results through two conference contributions, two seminars (one for ICTA-UAB and one for UC Merced), a workshop on urban air quality and the use of atmospheric models at the Masters of Modeling for Climate Change, offered by the physics dept of the UAB, and have published one paper "Environmental Assessment of the Food-Energy-Water nexus of the Urban Roof Mosaic (Journal of Industrial Ecology.OI:10.1111/jiec.12829) and have supervised 2 PhD students, 5 Master's students, and 1 postdoc. There are two scientific articles in submission/revision stage: “Simulation of Carbonyl Sulfide (OCS) to better understand the urban biosphere signal.” (journal of atmospheric environment) and, Optimizing high resolved WRFBEP/BEM simulation over Barcelona urban area (submitted to Atmospheric Environment).
During the first two years of my Marie. S. Curie fellowship URBANCO2Flux at UC Merced, California, I have broadened the applicability of COS to urban areas, progressing beyond the state of the art. Using atmospheric and chemical transport models to simulate COS concentrations over the San Francisco Bay area, I have been able to partition net ecosystem exchange (NEE) into its photosynthetic and respiratory components (Villalba, 2017). Presently, we are still working on improving the code of the chemical transport model to better represent observations. During the second phase of my fellowship, I was able to fund a one-month visit of postdoc Timothy Hilton from our group at UCMerced to come to the UAB to help me to adapt the Sulfur Transport and dEposition Model (STEM) to run in the high-performance computing environment at UAB and to simulate chemical transport in domains of interest (Barcelona, Spain) for studying relationships between urban greenspaces and urban fossil fuel emissions. I adapted the STEM source code to successfully compile and run at UAB, and adapted STEM data preprocessing code to compile and run at UAB and to prepare ancillary driver data for simulations of urban transport in Barcelona . I learned how to use the STEM transport model and its data preprocessor to simulate transport for arbitrary spatial domains. I also established new collaborations with research staff at the Super Computing Center of Barcelona with the goals of most effectively using computing resources and avoiding duplicated efforts in urban air quality and chemical transport simulations.
I have established collaborations with other institutes in Barcelona and Oslo regions (Oslo being an additional case study for comparison) to obtain all the input information needed such as: Local Climate Zones (LCZ) to better describe the urban land cover; Urban morphology (building heights/width and streets width);Anthropogenic emissions to simulate air quality; Observed meteorological and air quality data in hourly-base for comparison with the modelled data.Meteorological and air quality data from monitoring stations placed in Barcelona city, regarding the year of 2016, have been analysed to study the real influence of green areas on human comfort indicators (namely temperature, relative humidity, concentrations of NO2, O3 and PM10).
I have established collaborations with other institutes in Barcelona and Oslo regions (Oslo being an additional case study for comparison) to obtain all the input information needed such as: Local Climate Zones (LCZ) to better describe the urban land cover; Urban morphology (building heights/width and streets width);Anthropogenic emissions to simulate air quality; Observed meteorological and air quality data in hourly-base for comparison with the modelled data.Meteorological and air quality data from monitoring stations placed in Barcelona city, regarding the year of 2016, have been analysed to study the real influence of green areas on human comfort indicators (namely temperature, relative humidity, concentrations of NO2, O3 and PM10).