A high-resolution monitoring approach of urban CO2 fluxes. Part 1 - bottom-up model development.

Monitoring carbon dioxide (CO2) emissions of urban areas is increasingly important to assess the progress towards the Paris Agreement goals for climate neutrality. Cities are currently voluntarily developing their local inventories, however, the approaches used across different cities are not systematically assessed, present consistency issues, neglect the biogenic fluxes and have restricted spatial and temporal resolution. In order to assess the accuracy of the urban emission inventories and provide information which is useful for planning local climate change mitigation actions, high resolution modelling approaches combined or evaluated with atmospheric observations are needed. This study presents a new high-resolution bottom-up (BU) model which provides hourly maps of all major components contributing to the local urban surface CO2 flux (i.e. building emissions, traffic emissions, human respiration, soil respiration, plant respiration, plant photosynthetic uptake) and can therefore be used for direct comparison with in-situ atmospheric observations and development of local scale atmospheric inversion methodologies. The model design aims to be simple and flexible using inputs that are available in most cities, facilitating transferability to different locations. The inputs are primarily based on open geospatial datasets, census information, road traffic monitoring and basic meteorological parameters. The model is applied on the city centre of Basel, Switzerland, for the year 2018 and the results are compared to a local inventory. It is demonstrated that the model captures the highly dynamic spatiotemporal variability of the urban CO2 fluxes according to main environmental drivers, population activity dynamics and geospatial information proxies. The annual modelled emissions from buildings and traffic are estimated 14.8 % and 9 % lower than the respective information derived by the local inventory. The differences are mainly attributed to the emissions from the industrial areas and the highways which are beyond the geographical coverage of the model.

A high-resolution monitoring approach of urban CO2 fluxes. Part 2 - surface flux optimisation using eddy covariance observations.

Achieving climate neutrality by 2050 requires ground-breaking technological and methodological advancements in climate change mitigation planning and actions from local to regional scales. Monitoring the cities' CO2 emissions with sufficient detail and accuracy is crucial for guiding sustainable urban transformation. Current methodologies for CO2 emission inventories rely on bottom-up (BU) approaches which do not usually offer information on the spatial or temporal variability of the emissions and present substantial uncertainties. This study develops a novel approach which assimilates direct CO2 flux observations from urban eddy covariance (EC) towers with very high spatiotemporal resolution information from an advanced urban BU surface flux model (Part 1 of this study, Stagakis et al., 2023) within a Bayesian inversion framework. The methodology is applied to the city centre of Basel, Switzerland (3 × 3 km domain), taking advantage of two long-term urban EC sites located 1.6 km apart. The data assimilation provides optimised gridded CO2 flux information individually for each urban surface flux component (i.e. building heating emissions, commercial/industrial emissions, traffic emissions, human respiration emissions, biogenic net exchange) at 20 m resolution and weekly time-step. The results demonstrate that urban EC observations can be consistently used to improve high-resolution BU surface CO2 flux model estimations, providing realistic seasonal variabilities of each flux component. Traffic emissions are determined with the greatest confidence among the five flux components during the inversions. The optimised annual anthropogenic emissions are 14.7 % lower than the prior estimate, the human respiration emissions have decreased by 12.1 %, while the biogenic components transformed from a weak sink to a weak source. The root-mean-square errors (RMSEs) of the weekly comparisons between EC observations and model outputs are consistently reduced. However, a slight underestimation of the total flux, especially in locations with complex CO2 source/sink mixture, is still evident in the optimised fluxes.

Multi-Year Monitoring of Deciduous Forests Ecophysiology and the Role of Temperature and Precipitation as Controlling Factors.

Two deciduous forest ecosystems, one dominated by Fagus sylvatica and a mixed one with Quercus cerris and Quercus frainetto, were monitored from an ecophysiological perspective during a five-year period, in order to assess seasonal fluctuations, establish links between phenology and ecophysiology, and reveal climatic controls. Field measurements of leaf area index (LAI), chlorophyll content, leaf specific mass (LSM), water potential (Ψ) and leaf photosynthesis (Aleaf) were performed approximately on a monthly basis. LAI, chlorophylls and LSM fluctuations followed a recurrent pattern yearly, with increasing values during spring leaf burst and expansion, relatively stable values during summer and decreasing values during autumn senescence. However, pre-senescence leaf fall and chlorophyll reductions were evident in the driest year. The dynamically responsive Aleaf and Ψ presented considerable inter-annual variation. Both oak species showed more pronounced depressions of Aleaf and Ψ compared to beech, yet the time-point of their appearance coincided and was the same for all species each year. Spring temperature had a positive role in the increasing phase of all ecophysiological processes while rising autumn temperature resulted in retarded senescence. Precipitation showed asymmetric effects on the measured ecophysiological parameters. The between-species differences in responses, climate sensitivity and climate memory are identified and discussed.

Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts.

The measures taken to contain the spread of COVID-19 in 2020 included restrictions of people's mobility and reductions in economic activities. These drastic changes in daily life, enforced through national lockdowns, led to abrupt reductions of anthropogenic CO2 emissions in urbanized areas all over the world. To examine the effect of social restrictions on local emissions of CO2, we analysed district level CO2 fluxes measured by the eddy-covariance technique from 13 stations in 11 European cities. The data span several years before the pandemic until October 2020 (six months after the pandemic began in Europe). All sites showed a reduction in CO2 emissions during the national lockdowns. The magnitude of these reductions varies in time and space, from city to city as well as between different areas of the same city. We found that, during the first lockdowns, urban CO2 emissions were cut with respect to the same period in previous years by 5% to 87% across the analysed districts, mainly as a result of limitations on mobility. However, as the restrictions were lifted in the following months, emissions quickly rebounded to their pre-COVID levels in the majority of sites.

Urban energy exchanges monitoring from space.

One important challenge facing the urbanization and global environmental change community is to understand the relation between urban form, energy use and carbon emissions. Missing from the current literature are scientific assessments that evaluate the impacts of different urban spatial units on energy fluxes; yet, this type of analysis is needed by urban planners, who recognize that local scale zoning affects energy consumption and local climate. Satellite-based estimation of urban energy fluxes at neighbourhood scale is still a challenge. Here we show the potential of the current satellite missions to retrieve urban energy budget fluxes, supported by meteorological observations and evaluated by direct flux measurements. We found an agreement within 5% between satellite and in-situ derived net all-wave radiation; and identified that wall facet fraction and urban materials type are the most important parameters for estimating heat storage of the urban canopy. The satellite approaches were found to underestimate measured turbulent heat fluxes, with sensible heat flux being most sensitive to surface temperature variation (-64.1, +69.3 W m-2 for ±2 K perturbation).  They also underestimate anthropogenic heat fluxes. However, reasonable spatial patterns are obtained for the latter allowing hot-spots to be identified, therefore supporting both urban planning and urban climate modelling.