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 CO(2 )emissions in urbanized areas all over the world. To examine the effect of social restrictions on local emissions of CO2, we analysed district level CO(2 )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.Peer reviewe

Evaluation and use of remote sensing techniques in monitoring land ecosystem dynamics

The present study explores the potentials of multispectral and hyperspectral remote sensing imageryin the study of dynamic vegetation parameters. Initially, current multispectral satellite (AVHRR, SPOTVGT, MODIS) products were evaluated and then they were used for the study of a forest ecosystem(Quercus sp.) temporal dynamics and the development of a gross primary productivity (GPP) model(ModSat). Afterwards, the multiangle hyperspectral data of the experimental satellite CHRIS/PROBAwere processed and evaluated and an annual experimental study of irrigation treatments on anorange orchard (Citrus sinensis) was implemented through aerial high resolution narrowbandmultispectral data. In order to evaluate the remote sensing data and calibrate ModSat model, a seriesof ground ecophysiological measurements were carried out in two forests (Fagus sylvatica, Quercussp.) and a shrubland (Phlomis fruticosa). Meteorological stations (temperature, PAR, precipitation)were also installed near the study sites.The vegetation indices that were extracted from the satellite multispectral products proved to beefficient in detecting the fluctuations of ground measured leaf area index (LAI). More specifically,vegetation indices RDVI and OSAVI yielded the optimum correlations with LAI, while the widely usedvegetation index NDVI showed low sensitivity in cases of high LAI fluctuations. NDWI, an index thatwas designed to detect vegetation water status, was proved to be affected in greater degree bycanopy variations than the actual plant water status.The long NDVI time-series archive of NOAA AVHRR (1981 – 2006) showed strong trends of growthstart date shifting earlier and a gradual increase of winter NDVI values over the years in the Quercussp. forest that are possibly related to climate change. Furthermore, the comparison of satellite withthe meteorological archive revealed that precipitation of August affects positively the growth of thenext period, while temperature of August and the following months affects it negatively. Precipitationof winter months (January-February) has positive effect in the length of the following growth period.The above findings are connected to the tree internal processes that occur at the end of every growthperiod and the enrichment of the aquifer every winter.ModSat model proved to be effective in capturing the fluctuations of GPP in all functional types thatwas implemented on. Contrarily, the corresponding NASA product presented serious repetitiveaccuracy deficiencies. ModSat effectiveness indicates that the implication of oversized databasesand heavy data processing routines are not crucial for the production of accurate GPP estimations inhigh spatial scale.Satellite multiangular hyperspectral and aerial high resolution narrowband multispectral data offerenhanced possibilities in detailed detection and discrimination of vegetation parameters and in theapplication of more advanced data analysis methods compared to satellite multispectral products.Specifically, hyperspectral data, apart from estimating accurately LAI fluctuations, are capable ofdetecting leaf pigment concentrations, vegetation water status and even light use efficiency (ε) by thevegetation canopy. Thus, they offer the perspective of a direct GPP estimation by satellite data.However, soil reflectance affects greatly the effectiveness of vegetation indices, therefore highobservation angles of the sensor appear to be more suitable, eliminating canopy gap effects.Contrarily, internal canopy shadowing does not seriously affect the effectiveness of most vegetationindices.Στην μελέτη αυτή διερευνήθηκαν οι δυνατότητες που προσφέρουν τα πολυφασματικά και ταυπερφασματικά δεδομένα τηλεπισκόπησης στην μελέτη δυναμικών παραμέτρων της βλάστησης.Αρχικά, αξιολογήθηκαν τρέχοντα προϊόντα δορυφορικών πολυφασματικών αισθητήρων (AVHRR,SPOT VGT, MODIS). Μέσω αυτών μελετήθηκε η δυναμική ενός δασικού οικοσυστήματος (Quercussp.) στο χρόνο και αναπτύχθηκε ένα μοντέλο εκτίμησης ολικής πρωτογενούς παραγωγικότητας(ModSat). Στη συνέχεια, αξιολογήθηκαν τα πολυγωνιακά δεδομένα του πειραματικούυπερφασματικού δορυφόρου CHRIS/PROBA και διεξήχθη μια ετήσια πειραματική μελέτη χειρισμώνάρδευσης ενός πορτοκαλεώνα (Citrus sinensis) μέσω εναέριων πολυφασματικών δεδομένων στενώνκαναλιών πολύ υψηλής χωρικής διακριτικότητας. Για την αξιολόγηση των τηλεπισκοπικώνδεδομένων καθώς και την βαθμονόμηση του μοντέλου ModSat εκτελέσθηκαν επίγειεςοικοφυσιολογικές μετρήσεις σε δυο δασικά (Fagus sylvatica, Quercus sp.) και ένα θαμνώδεςοικοσύστημα (Phlomis fruticosa) επί σειρά ετών. Επίσης, εγκαταστάθηκαν μετεωρολογικοί σταθμοί(θερμοκρασία, PAR, βροχόπτωση) πλησίον των περιοχών μελέτης.Οι δείκτες βλάστησης που υπολογίσθηκαν από τα δορυφορικά πολυφασματικά προϊόντααποδείχθηκαν ικανοί για την αποτύπωση των διακυμάνσεων του μετρημένου επίγεια δείκτη φυλλικήςεπιφάνειας (LAI). Συγκεκριμένα, οι δείκτες βλάστησης RDVI και OSAVI απέδωσαν τις βέλτιστεςσυσχετίσεις με τον LAI, ενώ ο πιο διαδεδομένος δείκτης βλάστησης NDVI φάνηκε να χάνει τηνευαισθησία του σε περιπτώσεις που ο LAI κυμαίνεται σε υψηλές τιμές. Ο δείκτης NDWI, πουπροορίζεται για την αποτύπωση της υδατικής κατάστασης της βλάστησης, αποδείχθηκε ότιεπηρεάζεται σε πολύ μεγαλύτερο βαθμό από τις αναπτυξιακές διακυμάνσεις του θόλου παρά απότην υδατική κατάσταση των φυτών.Στο μεγάλο αρχείο NDVI των δορυφόρων NOAA AVHRR (1981 – 2006) παρατηρήθηκε μια ισχυρήτάση μετατόπισης της ημερομηνίας έναρξης της αναπτυξιακής περιόδου του δάσους Quercus sp.νωρίτερα με την πάροδο των ετών καθώς και σταδιακή αύξηση των χειμερινών τιμών NDVI,φαινόμενα τα οποία πιθανότατα σχετίζονται με τις κλιματικές αλλαγές. Επίσης, η σύγκριση τουδορυφορικού με το μετεωρολογικό αρχείο έδειξε ότι η βροχόπτωση του Αυγούστου επιδρά θετικάστην ανάπτυξη της επόμενης περιόδου, ενώ η θερμοκρασία του Αυγούστου και των ακόλουθωνμηνών επιδρά αρνητικά σε αυτή. Η βροχόπτωση και η χιονόπτωση των χειμερινών μηνών(Ιανουάριος-Φεβρουάριος) επιδρούν θετικά στην επιμήκυνση της ακόλουθης αναπτυξιακήςπεριόδου. Τα παραπάνω συνδέονται με τις εσωτερικές διεργασίες των δέντρων που λαμβάνουνχώρα στα τέλη κάθε αναπτυξιακής περιόδου και τον εμπλουτισμό του υδροφόρου ορίζοντα κάθεχειμώνα.Το μοντέλο ModSat αποδείχθηκε ικανό για ακριβή περιγραφή των διακυμάνσεων της ολικήςπρωτογενούς παραγωγικότητας (GPP) σε όλους τους λειτουργικούς τύπους βλάστησης πουεφαρμόστηκε. Αντιθέτως, το αντίστοιχο έτοιμο προϊόν της NASA εμφάνισε σοβαρές καιεπαναλαμβανόμενες ελλείψεις στην ακρίβεια των εκτιμήσεων GPP. Η επιτυχία του μοντέλου ModSatυποδεικνύει ότι δεν είναι απαραίτητη η ενσωμάτωση περίπλοκων αλγορίθμων, μεγάλων βάσεωνδεδομένων και βαριών υπολογιστικών επεξεργασιών για την παραγωγή προϊόντων GPP υψηλήςακρίβειας και μεγάλης χωρικής κλίμακας.Τα δορυφορικά υπερφασματικά – πολυγωνιακά δεδομένα και τα εναέρια πολυφασματικά δεδομέναστενών καναλιών υψηλής χωρικής διακριτικότητας αποδείχθηκε ότι προσφέρουν περισσότερεςδυνατότητες σε σχέση με τα δορυφορικά πολυφασματικά προϊόντα τόσο στην αναλυτική εκτίμησηπαραμέτρων της βλάστησης, όσο και στην εφαρμογή πιο προηγμένων μεθόδων ανάλυσης τηςπληροφορίας. Συγκεκριμένα, εκτός από την ακριβή αποτύπωση των διακυμάνσεων του μετρημένουεπίγεια LAI, τα υπερφασματικά δεδομένα είναι ικανά να ανιχνεύσουν τις συγκεντρώσεις τωνφωτοσυνθετικών χρωστικών φύλλου, την υδατική κατάσταση της βλάστησης, ακόμα και τηναποδοτικότητα χρήσης φωτός (ε) από τον θόλο της βλάστησης, παρέχοντας έτσι προοπτικήαπευθείας εκτίμησης της GPP από δορυφορικά δεδομένα. Ωστόσο, φάνηκε ότι η ανακλαστικότητατου εδάφους επηρεάζει σε μεγάλο βαθμό την απόδοση των δεικτών βλάστησης και επομένως οιυψηλές γωνίες παρατήρησης του αισθητήρα κρίνονται αποδοτικότερες διότι ελαχιστοποιούν ταπαρατηρούμενα κενά στον θόλο. Απεναντίας, οι σκιάσεις εσωτερικά του θόλου δεν επηρεάζουν σεμεγάλο βαθμό την αποτελεσματικότητα των περισσοτέρων δεικτών βλάστησης

Inter-annual variability of Eddy Covariance CO₂ flux measurements in the city center of Heraklion, Greece

Understanding the interactions between urban CO₂ emissions with urban form and function and establishing city-scale emission inventories to account cities' contribution to climate change, are current challenges for the global scientific community. The Eddy Covariance (EC) method can provide in-situ measurements of energy and CO₂ fluxes (Fc) between a surface source area (local scale) and the atmosphere, proving to be an auspicious approach for quantifying CO₂ budget of urban areas. The center of Heraklion is an interesting study area in the global network of urban EC stations due to the complex urban morphology, the Mediterranean climate and the mixture between residential neighborhoods and busy commercial zone. A tower-based EC system is active for a three-year period over the city center of Heraklion. Fc was calculated for this period at 30-min time step and the time-series were quality-controlled and gap-filled using a moving look-up table (mLUT) technique. Gap-filled time-series were then temporally aggregated to monthly and yearly emission totals. Furthermore, the annual flux source area was estimated using the Flux Footprint Prediction (FFP) model, parameterized using urban morphological parameters extracted from a Digital Surface Model. To examine the directionality of the observed fluxes, the annual Fc has been additionally estimated by dividing the source into four wind direction sectors. The diurnal patterns per sector showed significant differences, especially the ones coming from the source area that characterize the commercial zone of the city center. The latter present considerably higher Fc than the sectors related to the residential zones. The inter-annual Fc variability per sector reflects the changes in the traffic patterns in the commercial area and the residential heating contribution during winter in the residential area which is related to winter temperature. Finally, the CO₂ fluxes during the government measures for COVID-19, in March and April of 2020 are presenting an important reduction in Heraklion case study that reflects the total lockdown of the commercial and traffic activities in the city center

MODIS PRI performance to track Light Use Efficiency of a Mediterranean coniferous forest: Determinants, restrictions and the role of LUE range

The relationship between the Photochemical Reflectance Index (PRI) and Light Use Efficiency (LUE) is well established at leaf and small canopy scales, but upscaling to ecosystem level is still a challenge. Only few studies have applied satellite-derived PRI to estimate LUE, mostly using MODIS, and although the results are promising, many external factors have been identified affecting PRI performance. The present study investigates determinants and restrictions of MODIS-derived PRI potential to follow the LUE variability of a Mediterranean coniferous forest.Daily and half-hour LUE values were calculated from eddy covariance measurements, dividing GPP by either Photosynthetically Active Radiation (PAR) or the absorbed fraction of PAR (APAR). Also, various PRI datasets were created based on different sensor (Terra, Aqua, Both), reference band (1, 12, 13) and observation/illumination angles. Overall, PRI correlated better with LUE calculated using PAR instead of APAR and Aqua PRI yielded better results than Terra. Restricting acquisitions according to observation/illumination angles improves the PRI:LUE relationship (maximum R-2 = 0.512), with backscatter observations yielding the best correlations. Our findings suggest that MODIS-derived PRI is more sensitive to relatively large seasonal LUE changes, but is unable to closely follow severe drought events. Among the tested reference bands, the best results were derived using band 12 (546 - 556 nm), although the optimum reference band seems to depend on viewing conditions. The PRI:LUE relationship was further improved when half-hour LUE of the satellite overpass was used instead of daily LUE. However, it was found that the PRI:LUE relationships for the different datasets were strongly affected by the range of LUE values corresponding to each PRI group, with lower LUE variability resulting to weaker PRI:LUE correlations. LUE range effect should be accounted for in future studies, when different PRI datasets are compared and might explain the contradicting findings in the existing literature

Urban carbon dioxide flux monitoring using Eddy Covariance and Earth Observation: An introduction to diFUME project

Monitoring CO 2 emissions originating from urban areas has become a necessity to support sustainable urban planning strategies and climate change mitigation efforts. Integrative decision support, where net effects of various emission/sink components are considered and compared, is now an increasingly relevant part of urban planning processes. The current emission inventories rely on indirect approaches that use fuel and electricity consumption statistics for determining CO 2 emissions. The consistency of such approaches is questionable and they usually neglect the contribution of the biogenic components of the urban carbon cycle (i.e. vegetation, soil). Moreover, their spatial and temporal scales are restricted because consumption statistics are often available in coarse spatial scales (national, provincial/state, municipal) and usually scaled down using proxy data (e.g. population density) to city-scale annual estimates. The diFUME project (https://mcr.unibas.ch/difume/) is developing a methodology for mapping and monitoring the actual urban CO 2 flux at optimum spatial and temporal scales, meaningful for urban design decisions. The goal is to develop, apply and evaluate independent models, capable to estimate all the different components of the urban carbon cycle (i.e. building emissions, traffic emissions, human metabolism, photosynthetic uptake, plant respiration, soil respiration), combining mainly Eddy Covariance (EC) with Earth Observation (EO) data. EC provides continuous in-situ measurements of CO 2 flux at the local scale. Processing, analysis and interpretation of urban EC measurements is challenging due to the inherent spatial complexity of CO 2 source and sink configurations of the urban structure. The diFUME methodology is using multiple EO datasets to achieve multi-scale monitoring of urban cover, morphology and vegetation phenology in order to characterize the urban source/sink configurations and parameterize turbulent flux source area models. Such combination of EC and EO provides enhanced interpretation of the measured CO 2 flux, analysis of its controlling factors and therefore the potential of fine scale mapping and monitoring. The diFUME methodology is being developed and applied in the city of Basel, exploiting the available long-term database (> 15 years) of urban EC measurements. The first results highlight the potential of EO-derived geospatial data to interpret the complexity of urban EC measurements. Seasonal and land cover related trends in the EC-measured CO 2 flux are recognized, while the use of environmental, census and mobility datasets are increasing the interpretation capabilities and the modelling potential of the urban CO 2 flux patterns

Carbon dioxide emissions variability monitoring, based on four years of Eddy Covariance measurements in a typical Mediterranean city

Urban areas around the globe are growing rapidly and as a consequence the anthropogenic effects on the environment are ever-increasing. Understanding the dynamics, procedures and mechanics behind urban greenhouse gas emissions is a challenge for the scientific community. This study investigates the variability of urban CO2 emissions in the city centre of Heraklion, a typical Mediterranean city in Greece, during a four-year period with gradual changes in the traffic regulations and changes in traffic patterns due to the recent restriction measures imposed to limit the spread of the COVID-19 pandemic. The CO2 flux (Fc) was measured using the Eddy Covariance (EC) method with a single tower-based system, permanently installed in the centre of the city. Fc was calculated at a 30-min time step and the time-series were quality-controlled and gap-filled using a moving look-up table (mLUT) technique. Fc time series were then aggregated to monthly and yearly emissions totals. Annual flux source area was estimated with the Flux Footprint Prediction (FFP) model, parameterized using measured atmospheric parameters and urban morphological parameters extracted from a Digital Surface Model. The source area was characterized by complex urban morphology and land use types. Specifically, at North of the tower a commercial zone is located, where significantly higher Fc patterns were detected, compared to South, where a residential area dominates. A gradual reduction to CO2 emissions has been observed since 2016, due to urban planning interventions related to pedestalization of extended areas in the city centre and traffic regulation. During the COVID-19 lockdown period in the Spring of 2020, the diurnal Fc patterns and the monthly aggregated Fc showed significant reductions in the order of 70 % compared to the previous years. Fc values returned to the previous years' levels with the end of the lock-down in the summer 2020, as it was expected. Finally, during the second lock-down, started in Greece in November 2020, the CO2 emissions were higher compared to the first lock-down, reflecting a higher level of mobility in Heraklion centre

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, how-ever, 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 emis-sion inventories and provide information which is useful for planning local climate change mitigation actions, high res-olution 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 respi-ration, plant photosynthetic uptake) and can therefore be used for direct comparison with in-situ atmospheric obser-vations 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 pa-rameters. 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 respec-tive information derived by the local inventory. The differences are mainly attributed to the emissions from the indus-trial areas and the highways which are beyond the geographical coverage of the model

Using urban Eddy Covariance observations to inform a dynamic high-resolution urban CO2 flux model

High-resolution monitoring systems of urban CO 2 emissions integrating atmospheric observations are needed to assess the accuracy of the self-reported urban emission inventories and provide information useful for planning local climate change mitigation actions. This study presents a new approach for using direct urban CO 2 flux observations derived by Eddy Covariance towers for optimising the estimates of a bottom-up high-resolution flux model in a dynamic data assimilation framework. The methodology is developed and applied in the city centre of Basel, Switzerland, defining a study area of 3 x 3 km which includes two long-term Eddy Covariance towers located 1.6 km apart. The results show that the applied method is most efficient when the areas covered by the Eddy Covariance flux footprints present less complexity in urban structure and CO 2 source/sink mixture, such as street level sources originating from wide open areas. When strong building emissions are mixed with traffic originating by narrow urban canyon structures, then the accurate decomposition of the flux observations becomes more challenging. Additionally, the biogenic fluxes in the city green areas are a confounding factor in our results due to their extremely variable nature across the managed urban landscape. Overall, it is demonstrated that Eddy Covariance is a highly valuable tool for understanding and monitoring local scale source and sink processes within the urban environment and can be efficiently used for evaluating and optimising high-resolution models. Restrictions of the applied methodology, its scalability and complementarity to larger-scale and lower-resolution applications (e.g. atmospheric inversions) are discussed

Spatiotemporal dynamics of CO2 flux in Basel city centre

Independent, timely and accurate monitoring of urban CO 2 emissions is important to assess the progress towards the Paris Agreement goals, evaluate the mitigation potential of the implemented actions and support urban planning, policy- and decision-making processes. However, there are several challenges towards achieving comprehensive urban emission monitoring at the required scales, which are mainly related to the complexities in the urban form, the urban function and their interactions with the atmosphere. Cities are highly heterogeneous mosaics of CO 2 sources and sinks. Typically, the main emission sources in an urban neighbourhood are vehicles and buildings, while the contribution of human, plant and soil respiration can be also significant depending on population density and green area fraction. At the same time, urban vegetation acts as carbon sink, mitigating urban emissions locally. This study attempts to unravel the complex urban CO 2 flux dynamics by modelling each component separately (i.e. building emissions, traffic emissions, human metabolism, photosynthetic uptake, plant respiration, soil respiration) based on high resolution geospatial, meteorological and population activity datasets. The case study is the city centre of Basel, Switzerland. The models are calibrated and evaluated using Eddy Covariance measurements of CO 2 flux from two permanent tower sites in the city centre, covering a significant part of the study area. Moreover, an extended field campaign for the measurement of the biogenic components (i.e. photosynthetic uptake, plant respiration, soil respiration) has been active since the summer of 2020, involving regular chamber flux measurements and soil stations across the study area. The study reveals the spatial and temporal complexity of the urban CO 2 flux dynamics both diurnally and seasonally. The relative contribution of each flux component to the seasonal cycle is presented, while the mitigation potential of urban vegetation is evaluated. Cross-comparison between model outputs and Eddy Covariance measurements are discussed in respect to source area variability, airflow complexity in the urban canopy layer and irregular unrecognized emission sources