scispace - formally typeset
Open accessJournal ArticleDOI: 10.5194/ACP-21-3091-2021

Decoupling of urban CO 2 and air pollutant emission reductions during the European SARS-CoV-2 lockdown

02 Mar 2021-Atmospheric Chemistry and Physics (Copernicus GmbH)-Vol. 21, Iss: 4, pp 3091-3102
Abstract: . Lockdown and the associated massive reduction in people's mobility imposed by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) mitigation measures across the globe provide a unique sensitivity experiment to investigate impacts on carbon and air pollution emissions. We present an integrated observational analysis based on long-term in situ multispecies eddy flux measurements, allowing for quantifying near-real-time changes of urban surface emissions for key air quality and climate tracers. During the first European SARS-CoV-2 wave we find that the emission reduction of classic air pollutants decoupled from CO2 and was significantly larger. These differences can only be rationalized by the different nature of urban combustion sources and point towards a systematic bias of extrapolated urban NOx emissions in state-of-the-art emission models. The analysis suggests that European policies, shifting residential, public, and commercial energy demand towards cleaner combustion, have helped to improve air quality more than expected and that the urban NOx flux remains to be dominated (e.g., >90 % ) by traffic.

... read more

Topics: Air quality index (57.99%), Air pollution (52%)

6 results found

Open access
16 Dec 2015-
Abstract: Abstract. Flux footprint models are often used for interpretation of flux tower measurements, to estimate position and size of surface source areas, and the relative contribution of passive scalar sources to measured fluxes. Accurate knowledge of footprints is of crucial importance for any upscaling exercises from single site flux measurements to local or regional scale. Hence, footprint models are ultimately also of considerable importance for improved greenhouse gas budgeting. With increasing numbers of flux towers within large monitoring networks such as FluxNet, ICOS (Integrated Carbon Observation System), NEON (National Ecological Observatory Network), or AmeriFlux, and with increasing temporal range of observations from such towers (of the order of decades) and availability of airborne flux measurements, there has been an increasing demand for reliable footprint estimation. Even though several sophisticated footprint models have been developed in recent years, most are still not suitable for application to long time series, due to their high computational demands. Existing fast footprint models, on the other hand, are based on surface layer theory and hence are of restricted validity for real-case applications. To remedy such shortcomings, we present the two-dimensional parameterisation for Flux Footprint Prediction (FFP), based on a novel scaling approach for the crosswind distribution of the flux footprint and on an improved version of the footprint parameterisation of Kljun et al. (2004b). Compared to the latter, FFP now provides not only the extent but also the width and shape of footprint estimates, and explicit consideration of the effects of the surface roughness length. The footprint parameterisation has been developed and evaluated using simulations of the backward Lagrangian stochastic particle dispersion model LPDM-B (Kljun et al., 2002). Like LPDM-B, the parameterisation is valid for a broad range of boundary layer conditions and measurement heights over the entire planetary boundary layer. Thus, it can provide footprint estimates for a wide range of real-case applications. The new footprint parameterisation requires input that can be easily determined from, for example, flux tower measurements or airborne flux data. FFP can be applied to data of long-term monitoring programmes as well as be used for quick footprint estimates in the field, or for designing new sites.

... read more

Topics: Flux footprint (64%)

32 Citations

Open accessJournal ArticleDOI: 10.1016/J.ENVPOL.2021.117153
Marlon Brancher1Institutions (1)
Abstract: BACKGROUND: Lockdowns amid the COVID-19 pandemic have offered a real-world opportunity to better understand air quality responses to previously unseen anthropogenic emission reductions. METHODS AND MAIN OBJECTIVE: This work examines the impact of Vienna's first lockdown on ground-level concentrations of nitrogen dioxide (NO2), ozone (O3) and total oxidant (Ox). The analysis runs over January to September 2020 and considers business as usual scenarios created with machine learning models to provide a baseline for robustly diagnosing lockdown-related air quality changes. Models were also developed to normalise the air pollutant time series, enabling facilitated intervention assessment. CORE FINDINGS: NO2 concentrations were on average -20.1% [13.7-30.4%] lower during the lockdown. However, this benefit was offset by amplified O3 pollution of +8.5% [3.7-11.0%] in the same period. The consistency in the direction of change indicates that the NO2 reductions and O3 increases were ubiquitous over Vienna. Ox concentrations increased slightly by +4.3% [1.8-6.4%], suggesting that a significant part of the drops in NO2 was compensated by gains in O3. Accordingly, 82% of lockdown days with lowered NO2 were accompanied by 81% of days with amplified O3. The recovery shapes of the pollutant concentrations were depicted and discussed. The business as usual-related outcomes were broadly consistent with the patterns outlined by the normalised time series. These findings allowed to argue further that the detected changes in air quality were of anthropogenic and not of meteorological reason. Pollutant changes on the machine learning baseline revealed that the impact of the lockdown on urban air quality were lower than the raw measurements show. Besides, measured traffic drops in major Austrian roads were more significant for light-duty than for heavy-duty vehicles. It was also noted that the use of mobility reports based on cell phone movement as activity data can overestimate the reduction of emissions for the road transport sector, particularly for heavy-duty vehicles. As heavy-duty vehicles can make up a large fraction of the fleet emissions of nitrogen oxides, the change in the volume of these vehicles on the roads may be the main driver to explain the change in NO2 concentrations. INTERPRETATION AND IMPLICATIONS: A probable future with emissions of volatile organic compounds (VOCs) dropping slower than emissions of nitrogen oxides could risk worsened urban O3 pollution under a VOC-limited photochemical regime. More holistic policies will be needed to achieve improved air quality levels across different regions and criteria pollutants.

... read more

Topics: Air quality index (57.99%), Air pollution (51%), Criteria air contaminants (51%) ... show more

3 Citations

Open accessPosted ContentDOI: 10.1073/PNAS.2109481118
Abstract: The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.

... read more

Topics: Greenhouse gas (54%), Climate change (51%), Atmospheric chemistry (51%)

3 Citations

Open accessJournal ArticleDOI: 10.5194/ACP-21-14309-2021
Peter Huszar1, Jan Karlický1, Jan Karlický2, Jana Markova1  +4 moreInstitutions (3)
Abstract: . Urban areas are hot spots of intense emissions, and they influence air quality not only locally but on a regional or even global scale. The impact of urban emissions over different scales depends on the dilution and chemical transformation of the urban plumes which are governed by the local- and regional-scale meteorological conditions. These are influenced by the presence of urbanized land surface via the so-called urban canopy meteorological forcing (UCMF). In this study, we investigate for selected central European cities (Berlin, Budapest, Munich, Prague, Vienna and Warsaw) how the urban emission impact (UEI) is modulated by the UCMF for present-day climate conditions (2015–2016) using two regional climate models, the regional climate models RegCM and Weather Research and Forecasting model coupled with Chemistry (WRF-Chem; its meteorological part), and two chemistry transport models, Comprehensive Air Quality Model with Extensions (CAMx) coupled to either RegCM and WRF and the “chemical” component of WRF-Chem. The UCMF was calculated by replacing the urbanized surface by a rural one, while the UEI was estimated by removing all anthropogenic emissions from the selected cities. We analyzed the urban-emission-induced changes in near-surface concentrations of NO2 , O3 and PM 2.5 . We found increases in NO2 and PM 2.5 concentrations over cities by 4–6 ppbv and 4–6 µg m−3 , respectively, meaning that about 40 %–60 % and 20 %–40 % of urban concentrations of NO2 and PM 2.5 are caused by local emissions, and the rest is the result of emissions from the surrounding rural areas. We showed that if UCMF is included, the UEI of these pollutants is about 40 %–60 % smaller, or in other words, the urban emission impact is overestimated if urban canopy effects are not taken into account. In case of ozone, models due to UEI usually predict decreases of around −2 to −4 ppbv (about 10 %–20 %), which is again smaller if UCMF is considered (by about 60 %). We further showed that the impact on extreme (95th percentile) air pollution is much stronger, and the modulation of UEI is also larger for such situations. Finally, we evaluated the contribution of the urbanization-induced modifications of vertical eddy diffusion to the modulation of UEI and found that it alone is able to explain the modeled decrease in the urban emission impact if the effects of UCMF are considered. In summary, our results showed that the meteorological changes resulting from urbanization have to be included in regional model studies if they intend to quantify the regional footprint of urban emissions. Ignoring these meteorological changes can lead to the strong overestimation of UEI.

... read more

Topics: Urbanization (52%), Air quality index (52%)

1 Citations

Open accessJournal ArticleDOI: 10.3390/ATMOS12101366
19 Oct 2021-Atmosphere
Abstract: The combined use of Lecce-University AERONET-photometer measurements and PM2.5, PM10, NO2, CO, and SO2 concentrations from different sites of Apulia-Region Air-Quality Agency represents the peculiarity of this study, which evaluates the impact of COVID-19 lockdown (LD) measures on aerosol and gaseous pollutants. Monthly-averaged columnar and surface parameters of the 2020-year were compared with corresponding monthly parameters of the ref-year obtained by averaging 2017, 2018, and 2019 measurements in order to evaluate LD measure impacts by Average Percent Departure (APD%). Photometer measurements showed that LD measures were likely responsible for the decrease in Aerosol Optical Depth (AOD). The APD% estimated between the 2020- and ref-year AOD (at 440 nm) was characterized by negative values from June to August, reaching the smallest mean value (−46%) in June. Moreover, the columnar aerosol load appeared less affected by continental urban/industrial particles than previous years in the summer of 2020. The PM-concentration-APD% calculated at ten sites was characterized by monthly trends similar to those of AOD-APD%. PM-APD% values varied from site to site and smaller values (up to −57% in June) were on average detected at urban/suburban sites than at background sites (up to −37%). The impact of LD measures on gaseous pollutants was observed from the onset of LD.

... read more


54 results found

Open accessJournal ArticleDOI: 10.1111/J.1365-2656.2008.01390.X
Abstract: Summary 1 Ecologists use statistical models for both explanation and prediction, and need techniques that are flexible enough to express typical features of their data, such as nonlinearities and interactions 2 This study provides a working guide to boosted regression trees (BRT), an ensemble method for fitting statistical models that differs fundamentally from conventional techniques that aim to fit a single parsimonious model Boosted regression trees combine the strengths of two algorithms: regression trees (models that relate a response to their predictors by recursive binary splits) and boosting (an adaptive method for combining many simple models to give improved predictive performance) The final BRT model can be understood as an additive regression model in which individual terms are simple trees, fitted in a forward, stagewise fashion 3 Boosted regression trees incorporate important advantages of tree-based methods, handling different types of predictor variables and accommodating missing data They have no need for prior data transformation or elimination of outliers, can fit complex nonlinear relationships, and automatically handle interaction effects between predictors Fitting multiple trees in BRT overcomes the biggest drawback of single tree models: their relatively poor predictive performance Although BRT models are complex, they can be summarized in ways that give powerful ecological insight, and their predictive performance is superior to most traditional modelling methods 4 The unique features of BRT raise a number of practical issues in model fitting We demonstrate the practicalities and advantages of using BRT through a distributional analysis of the short-finned eel ( Anguilla australis Richardson), a native freshwater fish of New Zealand We use a data set of over 13 000 sites to illustrate effects of several settings, and then fit and interpret a model using a subset of the data We provide code and a tutorial to enable the wider use of BRT by ecologists

... read more

Topics: Statistical model (52%), Random forest (52%), Regression analysis (52%) ... show more

3,816 Citations

Journal ArticleDOI: 10.1016/0168-1923(95)02248-1
Abstract: The Navier-Stokes equations, after application of the Reynolds' averaging procedures, are the basis of direct surface-based measurements of turbulent fluxes via the eddy correlation method. Under restrictive conditions in the atmospheric surface layer, these equations are valid in a simplified form. These conditions are the stationarity of the data, the homogeneity of the underlying surface, a fully developed turbulence, and negligible density fluctuations. For most experiments these conditions are not fully satisfied, especially for continuous measurements over a greater period of time. Possible test algorithms are described to reflect the fulfilment of the criteria given above. As a consequence, we present a scheme for the characterization of the quality of direct turbulence measurements.

... read more

Topics: Turbulence (52%)

1,338 Citations

Journal ArticleDOI: 10.2307/1941631
01 Oct 1988-Ecology
Abstract: Ecologists are expected to play an important role in future studies of the biosphere/atmosphere exchange of materials associated with the major biogeochemical cycles and climate. Most studies of material exchange reported in the ecological literature have relied on chamber techniques. Micrometeorological techniques provide an alternative means of measuring these exchange rates and are expected to be used more often in future ecological studies, since they have many advantages over the chamber techniques. In this article we will provide an overview of micrometeorological theory and the different micrometeorological techniques available to make flux measurements.

... read more

1,193 Citations

Open accessJournal ArticleDOI: 10.1038/S41558-020-0797-X
Abstract: Government policies during the COVID-19 pandemic have drastically altered patterns of energy demand around the world. Many international borders were closed and populations were confined to their homes, which reduced transport and changed consumption patterns. Here we compile government policies and activity data to estimate the decrease in CO2 emissions during forced confinements. Daily global CO2 emissions decreased by –17% (–11 to –25% for ±1σ) by early April 2020 compared with the mean 2019 levels, just under half from changes in surface transport. At their peak, emissions in individual countries decreased by –26% on average. The impact on 2020 annual emissions depends on the duration of the confinement, with a low estimate of –4% (–2 to –7%) if prepandemic conditions return by mid-June, and a high estimate of –7% (–3 to –13%) if some restrictions remain worldwide until the end of 2020. Government actions and economic incentives postcrisis will likely influence the global CO2 emissions path for decades.

... read more

836 Citations

Open accessBook
Marc Aubinet1, Timo Vesala2, Dario PapaleInstitutions (2)
01 Jan 2012-
Abstract: Preface Chapter 1 : The eddy covariance method 1.1 History 1.2 Preliminaries 1.3. One point conservation equations 1.4 Integrated relations 1.5 Spectral analysis Chapter 2 : Measurement set-up 2.1 Introduction 2.2 Tower considerations 2.3 Sonic Anemometer 2.4 Eddy CO2 / H2O analyzer 2.5 Profile measurement Chapter 3 : Data Acquisition and Flux Calculations 3.1 Data Transfer and Acquisition 3.2 Flux calculation from raw data 3.3 Flux Determination Chapter 4 : Corrections and data quality control 4.1. Flux data correction 4.2. Effect of the unclosed energy balance 4.3 Data quality analysis 4.4. Accuracy of turbulent fluxes after correction and quality control 4.5 Overview of available correction software Chapter 5 : Night time Flux correction 5.1 Introduction 5.2 Is this problem really important? 5.3. How to implement the filtering procedure ? 5.4 Correction procedures Chapter 6: Data gap filling 6.1 Introduction 6.2 Gap-filling: why and when is it needed? 6.3 Gap-filling methods 6.4 Uncertainty and quality flags 6.5 Final remarks Chapter 7: Uncertainty quantification 7.1 Introduction 7.2 Random errors in flux measurements 7.3 Systematic errors in flux measurements 7.4 Closing ecosystem carbon budgets Conclusion Chapter 8 : Footprint analysis 8.1 Concept of footprint 8.2 Footprint models for atmospheric boundary layer 8.3 Footprint models for high vegetation 8.4 Complicated landscapes and inhomogeneous canopies 8.5 Quality assessment using footprint models 8.6 Validation of footprint models Chapter 9: Partitioning of net fluxes 9.1 Motivation 9.2 Definitions 9.3 Standard methods 9.4 Additional considerations and new approaches 9.5 Recommendations Chapter 10 : Disjunct eddy covariance method 10.1 Introduction 10.2 Theory 10.3 Practical applications of DEC 10.4 DEC in spectral space 10.5 Uncertainty due to DEC 10.6 On the history of the DEC approach Chapter 11: Eddy covariance measurements over forests 11.1 Introduction 11.2 Flux computation, selection and dependence 11.3 Additional measurements 11.4 Impact of ecosystem management and manipulation Chapter 12: Eddy covariance measurements over crops 12.1 Introduction 12.2 Measurement system 12.3 Flux calculation 12.4 Flux corrections 12.5. Data gap filling and footprint evaluation 12.6. Cumulated carbon exchange 12.7. Additional measurements 12.8. Future experimentations Chapter 13: Eddy covariance measurements over grasslands 13.1 Historic overview of grassland EC flux measurements 13.2 Peculiarities of eddy covariance flux measurements over grasslands 13.3 Estimating grassland carbon sequestration from flux measurements 13. 4 Additional measurements 13.5 Other green house gases Chapter 14: Eddy covariance measurements over wetlands 14.1 Introduction 14.2 Historic overview 14.3 Ecosystem-specific considerations 14.4 Complementary measurements 14.5 EC measurements in the wintertime 14.6 Carbon balances and climate effects 14.7 Concluding remarks Chapter 15: Eddy covariance measurements over lakes 15.1. Introduction 15.2. Existing studies 15.3. Surface-specific siting problems Chapter 16: Eddy covariance measurements over urban areas 16.1 Introduction 16.2 Conceptual framework for urban EC measurements 16.3 Challenges in the siting of urban EC stations 16.4 Implications of the peculiarities of the urban boundary layer on EC measurements 16.5 Summary and conclusions Chapter 17: Database maintenance, data sharing policy, collaboration 17.1 Data Management 17.2 Data Practices 17.3 Data User Services 17.4 Data Sharing and Policy of Uses Symbol Index Subject Index

... read more

Topics: Eddy covariance (56.99%)

720 Citations

No. of citations received by the Paper in previous years