scholarly journals Isolating the impact of COVID-19 lockdown measures on urban air quality in Canada

Author(s):  
Rabab Mashayekhi ◽  
Radenko Pavlovic ◽  
Jacinthe Racine ◽  
Michael D. Moran ◽  
Patrick M. Manseau ◽  
...  

AbstractWe have investigated the impact of reduced emissions due to COVID-19 lockdown measures in spring 2020 on air quality in Canada’s four largest cities: Toronto, Montreal, Vancouver, and Calgary. Observed daily concentrations of NO2, PM2.5, and O3 during a “pre-lockdown” period (15 February–14 March 2020) and a “lockdown” period (22 March–2 May 2020), when lockdown measures were in full force everywhere in Canada, were compared to the same periods in the previous decade (2010–2019). Higher-than-usual seasonal declines in mean daily NO2 were observed for the pre-lockdown to lockdown periods in 2020. For PM2.5, Montreal was the only city with a higher-than-usual seasonal decline, whereas for O3 all four cities remained within the previous decadal range. In order to isolate the impact of lockdown-related emission changes from other factors such as seasonal changes in meteorology and emissions and meteorological variability, two emission scenarios were performed with the GEM-MACH air quality model. The first was a Business-As-Usual (BAU) scenario with baseline emissions and the second was a more realistic simulation with estimated COVID-19 lockdown emissions. NO2 surface concentrations for the COVID-19 emission scenario decreased by 31 to 34% on average relative to the BAU scenario in the four metropolitan areas. Lower decreases ranging from 6 to 17% were predicted for PM2.5. O3 surface concentrations, on the other hand, showed increases up to a maximum of 21% close to city centers versus slight decreases over the suburbs, but Ox (odd oxygen), like NO2 and PM2.5, decreased as expected over these cities.

Időjárás ◽  
2021 ◽  
Vol 125 (4) ◽  
pp. 625-646
Author(s):  
Zita Ferenczi ◽  
Emese Homolya ◽  
Krisztina Lázár ◽  
Anita Tóth

An operational air quality forecasting model system has been developed and provides daily forecasts of ozone, nitrogen oxides, and particulate matter for the area of Hungary and three big cites of the country (Budapest, Miskolc, and Pécs). The core of the model system is the CHIMERE off-line chemical transport model. The AROME numerical weather prediction model provides the gridded meteorological inputs for the chemical model calculations. The horizontal resolution of the AROME meteorological fields is consistent with the CHIMERE horizontal resolution. The individual forecasted concentrations for the following 2 days are displayed on a public website of the Hungarian Meteorological Service. It is essential to have a quantitative understanding of the uncertainty in model output arising from uncertainties in the input meteorological fields. The main aim of this research is to probe the response of an air quality model to its uncertain meteorological inputs. Ensembles are one method to explore how uncertainty in meteorology affects air pollution concentrations. During the past decades, meteorological ensemble modeling has received extensive research and operational interest because of its ability to better characterize forecast uncertainty. One such ensemble forecast system is the one of the AROME model, which has an 11-member ensemble where each member is perturbed by initial and lateral boundary conditions. In this work we focus on wintertime particulate matter concentrations, since this pollutant is extremely sensitive to near-surface mixing processes. Selecting a number of extreme air pollution situations we will show what the impact of the meteorological uncertainty is on the simulated concentration fields using AROME ensemble members.


2008 ◽  
Vol 47 (7) ◽  
pp. 1853-1867 ◽  
Author(s):  
Tanya L. Otte

Abstract It is common practice to use Newtonian relaxation, or nudging, throughout meteorological model simulations to create “dynamic analyses” that provide the characterization of the meteorological conditions for retrospective air quality model simulations. Given the impact that meteorological conditions have on air quality simulations, it has been assumed that the resultant air quality simulations would be more skillful by using dynamic analyses rather than meteorological forecasts to characterize the meteorological conditions, and that the statistical trends in the meteorological model fields are also reflected in the air quality model. This article, which is the first of two parts, demonstrates the impact of nudging in the meteorological model on retrospective air quality model simulations. Here, meteorological simulations are generated by the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) using both the traditional dynamic analysis approach and using forecasts for a summertime period. The resultant fields are then used to characterize the meteorological conditions for emissions processing and air quality simulations using the Community Multiscale Air Quality (CMAQ) Modeling System. As expected, on average, the near-surface meteorological fields show a significant degradation over time in the forecasts (when nudging is not used), while the dynamic analyses maintain nearly constant statistical scores in time. The use of nudged MM5 fields in CMAQ generally results in better skill scores for daily maximum 1-h ozone mixing ratio simulations. On average, the skill of the daily maximum 1-h ozone simulation deteriorates significantly over time when nonnudged MM5 fields are used in CMAQ. The daily maximum 1-h ozone mixing ratio also degrades over time in the CMAQ simulation that uses MM5 dynamic analyses, although to a much lesser degree, despite no aggregate loss of skill over time in the dynamic analyses themselves. These results affirm the advantage of using nudging in MM5 to create the meteorological characterization for CMAQ for retrospective simulations, and it is shown that MM5-based dynamic analyses are robust at the surface throughout 5.5-day simulations.


2020 ◽  
Author(s):  
Rokjin Park ◽  
Hyeong-Ahn Kwon ◽  
Yujin Oak

<p>The Geostationary Environment Monitoring Spectrometer (GEMS) will be launched in February 2020 and will provide hourly observations of atmospheric compositions in the daytime. Prior to the GEMS launch, we explore an application of GEMS data as constraints for estimating anthropogenic volatile organic compound (AVOC) emissions in South Korea using formaldehyde (HCHO) vertical column densities observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) onboard the B200 aircraft during the KORUS-AQ campaign. Our top-down estimates of total AVOC emissions are higher by a factor of four over the petrochemical industries compared to the bottom-up emissions. However, the national AVOC emissions from the top-down estimates are by 37% lower than those of the bottom-up emission inventory in South Korea. We also show that hourly column observations of HCHO can improve not only the total magnitude of AVOC emissions but also their diurnal variation, which is poorly constrained and used in air quality models. Our hourly estimates of AVOC emissions may, thus, improve air quality model simulations in which the simulated ozone sensitivity to AVOC emission changes are also investigated.</p>


2021 ◽  
Author(s):  
Jacinta Edebeli ◽  
Curdin Spirig ◽  
Julien Anet

<p>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°×0.1°. 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°×0.02° with the aim of modelling local air quality.</p><p>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 <em>QuickOSM</em> 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.</p><p>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.</p><p>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.</p>


2018 ◽  
Vol 18 (13) ◽  
pp. 9741-9765 ◽  
Author(s):  
Emmanouil Oikonomakis ◽  
Sebnem Aksoyoglu ◽  
Martin Wild ◽  
Giancarlo Ciarelli ◽  
Urs Baltensperger ◽  
...  

Abstract. Surface solar radiation (SSR) observations have indicated an increasing trend in Europe since the mid-1980s, referred to as solar “brightening”. In this study, we used the regional air quality model, CAMx (Comprehensive Air Quality Model with Extensions) to simulate and quantify, with various sensitivity runs (where the year 2010 served as the base case), the effects of increased radiation between 1990 and 2010 on photolysis rates (with the PHOT1, PHOT2 and PHOT3 scenarios, which represented the radiation in 1990) and biogenic volatile organic compound (BVOC) emissions (with the BIO scenario, which represented the biogenic emissions in 1990), and their consequent impacts on summer surface ozone concentrations over Europe between 1990 and 2010. The PHOT1 and PHOT2 scenarios examined the effect of doubling and tripling the anthropogenic PM2.5 concentrations, respectively, while the PHOT3 investigated the impact of an increase in just the sulfate concentrations by a factor of 3.4 (as in 1990), applied only to the calculation of photolysis rates. In the BIO scenario, we reduced the 2010 SSR by 3 % (keeping plant cover and temperature the same), recalculated the biogenic emissions and repeated the base case simulations with the new biogenic emissions. The impact on photolysis rates for all three scenarios was an increase (in 2010 compared to 1990) of 3–6 % which resulted in daytime (10:00–18:00 Local Mean Time – LMT) mean surface ozone differences of 0.2–0.7 ppb (0.5–1.5 %), with the largest hourly difference rising as high as 4–8 ppb (10–16 %). The effect of changes in BVOC emissions on daytime mean surface ozone was much smaller (up to 0.08 ppb, ∼ 0.2 %), as isoprene and terpene (monoterpene and sesquiterpene) emissions increased only by 2.5–3 and 0.7 %, respectively. Overall, the impact of the SSR changes on surface ozone was greater via the effects on photolysis rates compared to the effects on BVOC emissions, and the sensitivity test of their combined impact (the combination of PHOT3 and BIO is denoted as the COMBO scenario) showed nearly additive effects. In addition, all the sensitivity runs were repeated on a second base case with increased NOx emissions to account for any potential underestimation of modeled ozone production; the results did not change significantly in magnitude, but the spatial coverage of the effects was profoundly extended. Finally, the role of the aerosol–radiation interaction (ARI) changes in the European summer surface ozone trends was suggested to be more important when comparing to the order of magnitude of the ozone trends instead of the total ozone concentrations, indicating a potential partial damping of the effects of ozone precursor emissions' reduction.


2018 ◽  
Vol 18 (3) ◽  
pp. 2175-2198 ◽  
Author(s):  
Emmanouil Oikonomakis ◽  
Sebnem Aksoyoglu ◽  
Giancarlo Ciarelli ◽  
Urs Baltensperger ◽  
André Stephan Henry Prévôt

Abstract. High surface ozone concentrations, which usually occur when photochemical ozone production takes place, pose a great risk to human health and vegetation. Air quality models are often used by policy makers as tools for the development of ozone mitigation strategies. However, the modeled ozone production is often not or not enough evaluated in many ozone modeling studies. The focus of this work is to evaluate the modeled ozone production in Europe indirectly, with the use of the ozone–temperature correlation for the summer of 2010 and to analyze its sensitivity to precursor emissions and meteorology by using the regional air quality model, the Comprehensive Air Quality Model with Extensions (CAMx). The results show that the model significantly underestimates the observed high afternoon surface ozone mixing ratios (≥ 60 ppb) by 10–20 ppb and overestimates the lower ones (< 40 ppb) by 5–15 ppb, resulting in a misleading good agreement with the observations for average ozone. The model also underestimates the ozone–temperature regression slope by about a factor of 2 for most of the measurement stations. To investigate the impact of emissions, four scenarios were tested: (i) increased volatile organic compound (VOC) emissions by a factor of 1.5 and 2 for the anthropogenic and biogenic VOC emissions, respectively, (ii) increased nitrogen oxide (NOx) emissions by a factor of 2, (iii) a combination of the first two scenarios and (iv) increased traffic-only NOx emissions by a factor of 4. For southern, eastern, and central (except the Benelux area) Europe, doubling NOx emissions seems to be the most efficient scenario to reduce the underestimation of the observed high ozone mixing ratios without significant degradation of the model performance for the lower ozone mixing ratios. The model performance for ozone–temperature correlation is also better when NOx emissions are doubled. In the Benelux area, however, the third scenario (where both NOx and VOC emissions are increased) leads to a better model performance. Although increasing only the traffic NOx emissions by a factor of 4 gave very similar results to the doubling of all NOx emissions, the first scenario is more consistent with the uncertainties reported by other studies than the latter, suggesting that high uncertainties in NOx emissions might originate mainly from the road-transport sector rather than from other sectors. The impact of meteorology was examined with three sensitivity tests: (i) increased surface temperature by 4 ∘C, (ii) reduced wind speed by 50 % and (iii) doubled wind speed. The first two scenarios led to a consistent increase in all surface ozone mixing ratios, thus improving the model performance for the high ozone values but significantly degrading it for the low ozone values, while the third scenario had exactly the opposite effects. Overall, the modeled ozone is predicted to be more sensitive to its precursor emissions (especially traffic NOx) and therefore their uncertainties, which seem to be responsible for the model underestimation of the observed high ozone mixing ratios and ozone production.


Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 722
Author(s):  
Dongsheng Chen ◽  
Dingyue Liang ◽  
Lei Li ◽  
Xiurui Guo ◽  
Jianlei Lang ◽  
...  

Ship-exhausted air pollutants could cause negative impacts on air quality, climate change, and human health. Increasing attention has been paid to investigate the impact of ship emissions on air quality. However, the conclusions are often based on a specific year, the extent to which the inter-annual variation in meteorological conditions affects the contribution is not yet fully addressed. Therefore, in this study, the Weather Research and Forecast model and the Community Multiscale Air Quality model(WRF/CMAQ) were employed to investigate the inter-annual variations in ship-contributed PM2.5 from 2010 to 2019. The Yangtze River Delta (YRD) region in China was selected as the target study area. To highlight the impact of inter-annual meteorological variations, the emission inventory and model configurations were kept the same for the 10-year simulation. We found that: (1) inter-annual meteorological variation had an evident impact on the ship-contributed PM2.5 in most coastal cities around YRD. Taking Shanghai as an example, the contribution varied between 3.05 and 5.74 µg/m3, with the fluctuation rate of ~65%; (2) the inter-annual changes in ship’s contribution showed a trend of almost simultaneous increase and decrease for most cities, which indicates that the impact of inter-annual meteorological variation was more regional than local; (3) the inter-annual changes in the northern part of YRD were significantly higher than those in the south; (4) the most significant inter-annual changes were found in summer, followed by spring, fall and winter.


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