Air quality improvements caused by COVID-19 lockdown measures in Central Europe – contributions of emission sectors and the meteorological situation

2021 ◽  
Author(s):  
Ronny Badeke ◽  
Volker Matthias ◽  
Markus Quante ◽  
Ronny Petrik ◽  
Jan Arndt ◽  
...  
Keyword(s):  
Air Quality ◽  
Central Europe ◽  
Emission Reduction ◽  
Meteorological Data ◽  
Measurement Data ◽  
Weather Conditions ◽  
Air Pollutant ◽  
Emission Data ◽  
Emission Reductions ◽  
Ship Traffic

<p>Corona lockdown measures caused unprecedented emission reductions in many parts of world. However, this does not linearly translate into improved air quality, since weather phenomena like precipitation, wind and solar radiation also show a significant impact on pollutant concentration patterns. The aim of this study is to disentangle effects of emission reduction and meteorology on the air quality in Central Europe during the first major lockdown from March to June 2020. For this purpose, the Community Multiscale Air Quality Modeling System (CMAQ) was used with updated emission data for the year 2020, including time profiles for sectors and countries that approximate the lockdown emission reductions. The contributions of street traffic, air traffic, ship traffic, residential heating and industry to NO<sub>2</sub>, O<sub>3</sub> and PM<sub>2.5</sub> concentrations were investigated. Meteorological data was derived from the regional COSMO model in CLimate Mode (COSMO-CLM). Additional city scale measurements were used to account for exceptional weather conditions as well as emission reduction effects at hotspots like traffic stations. Therefore, selected air pollutant and meteorological measurement data in the cities of Hamburg, Liége and Marseille are compared against the statistical trend of 2015 to 2019.</p>

scholarly journals The role of emission reductions and the meteorological situation for air quality improvements during the COVID-19 lockdown period in central Europe

2021 ◽  
Vol 21 (18) ◽  
pp. 13931-13971
Author(s):  
Volker Matthias ◽  
Markus Quante ◽  
Jan A. Arndt ◽  
Ronny Badeke ◽  
Lea Fink ◽  
...  
Keyword(s):  
Air Quality ◽  
Central Europe ◽  
Urban Areas ◽  
Road Traffic ◽  
Quality Improvements ◽  
Emission Data ◽  
Emission Reductions ◽  
Meteorological Situation ◽  
Weather Situation

Abstract. The lockdown measures taken to prevent a rapid spreading of the coronavirus in Europe in spring 2020 led to large emission reductions, particularly in road traffic and aviation. Atmospheric concentrations of NO2 and PM2.5 were mostly reduced when compared to observations taken for the same time period in previous years; however, concentration reductions may not only be caused by emission reductions but also by specific weather situations. In order to identify the role of emission reductions and the meteorological situation for air quality improvements in central Europe, the meteorology chemistry transport model system COSMO-CLM/CMAQ was applied to Europe for the period 1 January to 30 June 2020. Emission data for 2020 were extrapolated from most recent reported emission data, and lockdown adjustment factors were computed from reported activity data changes, e.g. Google mobility reports. Meteorological factors were investigated through additional simulations with meteorological data from previous years. The results showed that lockdown effects varied significantly among countries and were most prominent for NO2 concentrations in urban areas with 2-week-average reductions up to 55 % in the second half of March. Ozone concentrations were less strongly influenced (up to ±15 %) and showed both increasing and decreasing concentrations due to lockdown measures. This depended strongly on the meteorological situation and on the NOx / VOC emission ratio. PM2.5 revealed 2 %–12 % reductions of 2-week-average concentrations in March and April, which is much less than a different weather situation could cause. Unusually low PM2.5 concentrations as observed in northern central Europe were only marginally caused by lockdown effects. The lockdown can be seen as a big experiment about air quality improvements that can be achieved through drastic traffic emission reductions. From this investigation, it can be concluded that NO2 concentrations can be largely reduced, but effects on annual average values are small when the measures last only a few weeks. Secondary pollutants like ozone and PM2.5 depend more strongly on weather conditions and show a limited response to emission changes in single sectors.

scholarly journals The role of emission reductions and the meteorological situation for air quality improvements during the COVID-19 lockdown period in Central Europe

2021 ◽  
Author(s):  
Volker Matthias ◽  
Markus Quante ◽  
Jan A. Arndt ◽  
Ronny Badeke ◽  
Lea Fink ◽  
...  
Keyword(s):  
Air Quality ◽  
Central Europe ◽  
Urban Areas ◽  
Road Traffic ◽  
Quality Improvements ◽  
Emission Data ◽  
Emission Reductions ◽  
Meteorological Situation ◽  
Weather Situation

Abstract. The lockdown measures taken to prevent a rapid spreading of the Corona virus in Europe in spring 2020 led to large emission reductions, particularly in road traffic and aviation. Atmospheric concentrations of NO2 and PM2.5 were mostly reduced when compared to observations taken for the same time period in previous years, however, concentration reductions may not only be caused by emission reductions but also by specific weather situations. In order to identify the role of emission reductions and the meteorological situation for air quality improvements in Central Europe, the meteorology chemistry transport model system COSMO-CLM/CMAQ was applied to Europe for the period 1 January to 30 June 2020. Emission data for 2020 was extrapolated from most recent reported emission data and lockdown adjustment factors were computed from reported activity data changes, e.g. google mobility reports. Meteorological factors were investigated through additional simulations with meteorological data from previous years. The results showed that lockdown effects varied significantly among countries and were most prominent for NO2 concentrations in urban areas with two-weeks-average reductions up to 55 % in the second half of March. Ozone concentrations were less strongly influenced (up to +/−15 %) and showed both, increasing and decreasing concentrations due to lockdown measures. This depended strongly on the meteorological situation and on the NOx/VOC emission ratio. PM2.5 revealed 2–12 % reductions of two-weeks-average concentrations in March and April, which is much less than a different weather situation could cause. Unusually low PM2.5 concentrations as observed in Northern Central Europe were only marginally caused by lockdown effects. The lockdown can be seen as a big experiment about air quality improvements that can be achieved through drastic traffic emission reductions. From this investigation, it can be concluded that NO2 concentrations can be largely reduced, but effects on annual average values are small when the measures last only a few weeks. Secondary pollutants like ozone and PM2.5 depend more strongly on weather conditions and show a limited response to emission changes in single sectors.

scholarly journals Evaluation of the effect of regional joint-control measures on changing photochemical transformation: a comprehensive study of the optimization scenario analysis

2019 ◽  
Vol 19 (14) ◽  
pp. 9037-9060 ◽  
Author(s):  
Li Li ◽  
Shuhui Zhu ◽  
Jingyu An ◽  
Min Zhou ◽  
Hongli Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Emission Reduction ◽  
Meteorological Conditions ◽  
Air Pollutant ◽  
Control Measures ◽  
Joint Control ◽  
Emission Reductions ◽  
The Yrd ◽  
Comprehensive Study

Abstract. Heavy haze usually occurs in winter in eastern China. To control the severe air pollution during the season, comprehensive regional joint-control strategies were implemented throughout a campaign. To evaluate the effectiveness of these strategies and to provide some insights into strengthening the regional joint-control mechanism, the influence of control measures on levels of air pollution was estimated with an integrated measurement-emission-modeling method. To determine the influence of meteorological conditions, and the control measures on the air quality, in a comprehensive study, the 2nd World Internet Conference was held during 16–18 December 2015 in Jiaxing City, Zhejiang province, in the Yangtze River Delta (YRD) region. We first analyzed the air quality changes during four meteorological regimes and then compared the air pollutant concentrations before, during, and after the regulation under static meteorological conditions. Next, we conducted modeling scenarios to quantify the effects caused due to the air pollution control measures. We found that total emissions of SO2, NOx, PM2.5, and volatile organic compounds (VOCs) in Jiaxing were reduced by 56 %, 58 %, 64 %, and 80 %, respectively, while total emission reductions of SO2, NOx, PM2.5, and VOCs over the YRD region are estimated to be 10 %, 9 %, 10 %, and 11 %, respectively. Modeling results suggest that during the campaign from 8 to 18 December, PM2.5 daily average concentrations decreased by 10 µg m−3 with an average decrease of 14.6 %. Our implemented optimization analysis compared with previous studies also reveals that local emission reductions play a key role in air quality improvement, although it shall be supplemented by regional linkage. In terms of regional joint control, implementing pollution channel control 48 h before the event is of most benefit in getting similar results. Therefore, it is recommended that a synergistic emission reduction plan between adjacent areas with local pollution emission reductions as the core part should be established and strengthened, and emission reduction plans for different types of pollution through a stronger regional linkage should be reserved.

scholarly journals Evaluation on the effect of regional joint control measures in changing photochemical transformation: A comprehensive study of the optimization scenario analysis

2019 ◽  
Author(s):  
Li Li ◽  
Shuhui Zhu ◽  
Jingyu An ◽  
Min Zhou ◽  
Hongli Wang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Emission Reduction ◽  
Meteorological Conditions ◽  
Air Pollutant ◽  
Control Measures ◽  
Joint Control ◽  
Emission Reductions ◽  
The Yrd ◽  
Comprehensive Study

Abstract. Heavy haze usually occurs in winter in eastern China. To control the severe air pollution during the season, comprehensive regional joint-control strategies were implemented throughout a campaign. To evaluate the effectiveness of these strategies and to provide some insight into strengthening the joint-control mechanism, the influence of control measures on levels of air pollution were estimated. To determine the influence of meteorological conditions, and the control measures on the air quality, in a comprehensive study, the 2nd World Internet Conference was held during December 16~18, 2015 in Jiaxing City, Zhejiang Province in the Yangtze River Delta (YRD) region. We first analyzed the air quality changes during four meteorological regimes; and then compared the air pollutant concentrations during days with stable meteorological conditions. Next, we did modeling scenarios to quantify the effects caused due to the air pollution control measures. We found that total emissions of SO2, NOx, PM2.5 and VOCs in Jiaxing were reduced by 56 %, 58 %, 64 % and 80 %, respectively; while total emission reductions of SO2, NOx, PM2.5 and VOCs over the YRD region are estimated to be 10 %, 9 %, 10 % and 11 %, respectively. Modelling results suggest that the regional controls (including Jiaxing and surrounding area) reduced PM2.5 levels in Jiaxing between 5.5 %–16.5 % (9.9 % on average), while local control measures contributed 4.5 %–14.4 %, with an average of 8.8 %. Our implemented optimization analysis compared with previous studies also reveal that local emission reductions play a key role in air quality improvement, although it shall be supplemented by regional linkage. In terms of regional joint control, to implement pollution channel control 48 hours before the event is of most benefit in getting similar results. Therefore, it is recommended that a synergistic emission reduction plan between adjacent areas with local pollution emission reductions as the core part should be established and strengthened, and emission reduction plans for different types of pollution through a stronger regional linkage should be reserved.

scholarly journals Application of combined model of stepwise regression analysis and artificial neural network in data calibration of miniature air quality detector

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bing Liu ◽  
Qingbo Zhao ◽  
Yueqiang Jin ◽  
Jiayu Shen ◽  
Chaoyang Li
Keyword(s):  
Neural Network ◽  
Air Quality ◽  
Regression Model ◽  
Multilayer Perceptron ◽  
Stepwise Regression ◽  
Control Point ◽  
Measurement Data ◽  
Environmental Indicators ◽  
Air Pollutant ◽  
Mlp Model

AbstractIn this paper, six types of air pollutant concentrations are taken as the research object, and the data monitored by the micro air quality detector are calibrated by the national control point measurement data. We use correlation analysis to find out the main factors affecting air quality, and then build a stepwise regression model for six types of pollutants based on 8 months of data. Taking the stepwise regression fitting value and the data monitored by the miniature air quality detector as input variables, combined with the multilayer perceptron neural network, the SRA-MLP model was obtained to correct the pollutant data. We compared the stepwise regression model, the standard multilayer perceptron neural network and the SRA-MLP model by three indicators. Whether it is root mean square error, average absolute error or average relative error, SRA-MLP model is the best model. Using the SRA-MLP model to correct the data can increase the accuracy of the self-built point data by 42.5% to 86.5%. The SRA-MLP model has excellent prediction effects on both the training set and the test set, indicating that it has good generalization ability. This model plays a positive role in scientific arrangement and promotion of miniature air quality detectors. It can be applied not only to air quality monitoring, but also to the monitoring of other environmental indicators.

Comparison of Modeled-to-Monitored PM2.5 Exposure Concentrations Resulting from Transportation Emissions in a Near-Road Community

2020 ◽  
Vol 2674 (12) ◽  
pp. 130-143
Author(s):  
Mayra Chavez ◽  
Wen-Whai Li
Keyword(s):  
Air Quality ◽  
Meteorological Data ◽  
Temporal Variations ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Spatial And Temporal Variations ◽  
Quality Data ◽  
Background Concentrations ◽  
Regional Background ◽  
Transportation Emissions

Residents living in near-road communities are exposed to traffic-related air pollutants, which can adversely affect their health. Near-road communities are expected to observe significant spatial and temporal variations in pollutant concentrations. Determining these variations in the surrounding areas can help raise awareness among government agencies of these underserved communities living near highways. This study conducted traffic and air quality measurements along with emission and dispersion modeling of the exposure to transportation emissions of a near-road urban community adjacent to the US 54 highway (US 54), with annual average daily traffic (AADT) of 107,237. The objectives of this study were (i) to develop spatial and temporal patterns of pollutant concentration variation and (ii) to apportion the differences in exposure concentrations to background concentrations and those that are contributed from major highways. It was observed that: (a) particulate matter (PM2.5) in near-road communities is dominated by the regional background concentrations which account for more than 85% of the pollution; and (b) only near-road receptors are affected by the traffic-related air pollutant emissions from major highways while spatial and temporal variations of PM2.5 concentrations in near-road communities are less influenced by local traffic, subsiding rapidly to negligible concentrations at 300 m from the road. Modeled PM2.5 concentrations were compared with monitored data. For better air quality impact assessments, higher quality data such as time-specific traffic volume and fleet information as well as site-specific meteorological data could help yield more accurate concentration predictions. Modeled-to-monitored comparison shows that air quality in near-road communities is dominated by regional background concentrations.

scholarly journals Twenty-five years of continuous sulphur dioxide emission reduction in Europe

2007 ◽  
Vol 7 (13) ◽  
pp. 3663-3681 ◽  
Author(s):  
V. Vestreng ◽  
G. Myhre ◽  
H. Fagerli ◽  
S. Reis ◽  
L. Tarrasón
Keyword(s):  
Long Range ◽  
Emission Reduction ◽  
Western Europe ◽  
European Countries ◽  
Emission Data ◽  
Individual Country ◽  
Emission Reductions ◽  
Sulphur Emissions ◽  
Sulphur Emission ◽  
Gothenburg Protocol

Abstract. During the last twenty-five years European emission data have been compiled and reported under the Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP) as part of the work under the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP). This paper presents emission trends of SO2 reported to EMEP and validated within the programme for the period 1980–2004. These European anthropogenic sulphur emissions have been steadily decreasing over the last twenty-five years, amounting from about 55 Tg SO2 in 1980 to 15 Tg SO2 in 2004. The uncertainty in sulphur emission estimates for individual countries and years are documented to range between 3% and 25%. The relative contribution of European emissions to global anthropogenic sulphur emissions has been halved during this period. Based on annual emission reports from European countries, three emission reduction regimes have been identified. The period 1980–1989 is characterized by low annual emission reductions (below 5% reduction per year and 20% for the whole period) and is dominated by emission reductions in Western Europe. The period 1990–1999 is characterised by high annual emission reductions (up to 11% reduction per year and 54% for the whole period), most pronounced in Central and Eastern Europe. The annual emission reductions in the period 2000–2004 are medium to low (below 6% reduction per year and 17% for the whole period) and reflect the unified Europe, with equally large reductions in both East and West. The sulphur emission reduction has been largest in the sector Combustion in energy and transformation industries, but substantial decreases are also seen in the Non-industrial combustion plants together with the sectors Industrial combustion and Industrial production processes. The majority of European countries have reduced their emissions by more than 60% between 1990 and 2004, and one quarter have already achieved sulphur emission reductions higher than 80%. At European level, the total sulphur target for 2010 set in the Gothenburg Protocol (16 Tg) has apparently already been met by 2004. However, still half of the Parties to the Gothenburg Protocol have to reduce further their sulphur emissions in order to attain their individual country total emission targets for 2010. It is also noteworthy that, contrasting the Gothenburg Protocol requirements, a growing number of countries have recently been reporting increasing sulphur emissions, while others report only minor further decreases. The emission trends presented here are supported by different studies of air concentrations and depositions carried out within and outside the framework of the LRTAP Convention.

scholarly journals Non-linear response of PM2.5 to changes in NO<sub>x</sub> and NH<sub>3</sub> emissions in the Po basin (Italy): consequences for air quality plans

2021 ◽  
Author(s):  
Philippe Thunis ◽  
Alain Clappier ◽  
Matthias Beekmann ◽  
Jean Philippe Putaud ◽  
Cornelis Cuvelier ◽  
...  
Keyword(s):  
Air Quality ◽  
Emission Reduction ◽  
Oxidative Capacity ◽  
Nox Emission ◽  
Aerosol Formation ◽  
Linear Processes ◽  
Emission Reductions ◽  
Nh3 Emission ◽  
Non Linear ◽  
Pm2.5 Concentration

Abstract. Air pollution is one of the main causes of damages to human health in Europe with an estimate of about 380 000 premature deaths per year in the EU28, as the result of exposure to fine particulate matter (PM2.5) only. In this work, we focus on one specific region in Europe, the Po basin, a region where chemical regimes are the most complex, showing important non-linear processes, especially those related to interactions between NOx and NH3. We analyse the sensitivities of PM2.5 to NOx and NH3 emissions by means of a set of EMEP simulations performed with different levels of emission reductions, from 25 % up to a total switch-off of those emissions. Both single and combined precursor reduction scenarios are applied to determine the most efficient emission reduction strategies and quantify the interactions between NOx and NH3 emission reductions. The results confirmed the peculiarity of secondary PM2.5 formation in the Po basin, characterised by contrasting chemical regimes within distances of few (hundreds of) kilometres, as well as strong non-linear responses to emission reductions during wintertime. One of the striking results is the increase of the PM2.5 concentration levels when NOx emission reductions are applied in NOx-rich areas, such as the surroundings of Bergamo. The increased oxidative capacity of the atmosphere is the cause of the increase of PM2.5 induced by a reduction in NOx emission. This process can have contributed to the absence of significant PM2.5 concentration decrease during the COVID-19 lockdowns in many European cities. It is important to account for this process when designing air quality plans, since it could well lead to transitionary increases in PM2.5 at some locations in winter as NOx emission reduction measures are gradually implemented. While PM2.5 responses to NOx and NH3 emission reduction show large variations seasonally and spatially, these responses remain close to linear, i.e. proportional to the emission reduction levels, at least up to −50 % because secondary aerosol formation chemical regimes are not modified by those relatively moderate ranges.

scholarly journals DESIGN AND RESULTS OF AN AI-BASED FORECASTING OF AIR POLLUTANTS FOR SMART CITIES

2021 ◽  
Vol VIII-4/W1-2021 ◽  
pp. 89-96
Author(s):  
L. Petry ◽  
T. Meiers ◽  
D. Reuschenberg ◽  
S. Mirzavand Borujeni ◽  
J. Arndt ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Smart Cities ◽  
Meteorological Data ◽  
Weather Forecast ◽  
Ground Level ◽  
Urban Environments ◽  
Air Pollutant ◽  
Novel Approach

Abstract. This paper presents the design and the results of a novel approach to predict air pollutants in urban environments. The objective is to create an artificial intelligence (AI)-based system to support planning actors in taking effective and adequate short-term measures against unfavourable air quality situations. In general, air quality in European cities has improved over the past decades. Nevertheless, reductions of the air pollutants particulate matter (PM), nitrogen dioxide (NO2) and ground-level ozone (O3), in particular, are essential to ensure the quality of life and a healthy life in cities. To forecast these air pollutants for the next 48 hours, a sequence-to-sequence encoder-decoder model with a recurrent neural network (RNN) was implemented. The model was trained with historic in situ air pollutant measurements, traffic and meteorological data. An evaluation of the prediction results against historical data shows high accordance with in situ measurements and implicate the system’s applicability and its great potential for high quality forecasts of air pollutants in urban environments by including real time weather forecast data.

Downscaling EDGAR emissions to local emission sectors for Switzerland

2021 ◽  
Author(s):  
Jacinta Edebeli ◽  
Curdin Spirig ◽  
Julien Anet
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Measurement Data ◽  
Pilot Project ◽  
Air Quality Model ◽  
Quality Model ◽  
Emission Data ◽  
Traffic Pattern ◽  
Pollutant Concentrations ◽  
The Impact

&lt;p&gt;The fifth version of the Emission Database for Global Atmospheric Research (EDGAR 5.0) provides an impressive inventory of various pollutants. Pollutants from different emission sectors are available with daily, monthly and yearly temporal profiles at a high global resolution of 0.1&amp;#176;&amp;#215;0.1&amp;#176;. Although this resolution has been sufficient for regional air quality studies, the emissions appeared to be too coarse for local air quality studies in areas with complex topography. With Switzerland as a case study, we present our approach for downscaling EDGAR emission data to a much finer resolution of 0.02&amp;#176;&amp;#215;0.02&amp;#176; with the aim of modelling local air quality.&lt;/p&gt;&lt;p&gt;We downscaled the EDGAR emissions using a combination of GIS tools including QGIS, ArcGIS, and a series of python scripts. We obtained the surface coverage of different land use features within the defined EDGAR emission sectors from Open Street Map (OSM) using the &lt;em&gt;QuickOSM&lt;/em&gt; tool in QGIS. With the calculated local surface area coverage of the emissions sectors, we downscaled the EDGAR inventory data within ArcGIS using a set of developed Arcpy script tools.&lt;/p&gt;&lt;p&gt;The outcome was a much finer resolved emission dataset which we fed into the WRF-CHEM air quality model within a pilot project. A comparison of the modelled pollutant concentrations using the two datasets (original EDGAR data and the downscaled data) shows an improved agreement between the downscaled dataset and the measurement data.&lt;/p&gt;&lt;p&gt;Studies investigating the impact of urbanization, land use change or traffic pattern on air quality may benefit from our downscaling solution, which, thanks to the global coverage of OSM, can be globally applied.&lt;/p&gt;

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