scholarly journals Impact of Physics Parameterizations on High-Resolution Air Quality Simulations over the Paris Region

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 618 ◽  
Author(s):  
Lei Jiang ◽  
Bertrand Bessagnet ◽  
Frederik Meleux ◽  
Frederic Tognet ◽  
Florian Couvidat
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Urban Canopy ◽  
Urban Region ◽  
Pollution Episode ◽  
Sensitivity Tests ◽  
Physics Parameterizations ◽  
Paris Region ◽  
The Impact ◽  
Canopy Model

The accurate simulation of meteorological conditions, especially within the planetary boundary layer (PBL), is of major importance for air quality modeling. In the present work, we have used the Weather Research and Forecast (WRF) model coupled with the chemistry transport model (CTM) CHIMERE to understand the impact of physics parameterizations on air quality simulation during a short-term pollution episode on the Paris region. A lower first model layer with a 4 m surface layer could better reproduce the transport and diffusion of pollutants in a real urban environment. Three canopy models could better reproduce a 2 m temperature (T2) in the daytime but present a positive bias from 1 to 5 °C during the nighttime; the multi-urban canopy scheme “building effect parameterization” (BEP) underestimates the 10 m windspeed (W10) around 1.2 m s−1 for the whole episode, indicating the city cluster plays an important role in the diffusion rate in urban areas. For the simulation of pollutant concentrations, large differences were found between three canopy schemes, but with an overall overestimation during the pollution episode, especially for NO2 simulation, the average mean biases of NO2 prediction during the pollution episode were 40.9, 62.2, and 29.7 µg m−3 for the Bulk, urban canopy model (UCM), and BEP schemes, respectively. Meanwhile, the vertical profile of the diffusion coefficients and pollutants indicated an important impact of the canopy model on the vertical diffusion. The PBL scheme sensitivity tests displayed an underestimation of the height of the PBL when compared with observations issued from the Lidar. The YonSei University scheme YSU and Boulac PBL schemes improved the PBL prediction compared with the Mellor–Yamada–Janjic (MYJ) scheme. All the sensitivity tests, except the Boulac–BEP, could not fairly reproduce the PBL height during the pollution episode. The Boulac–BEP scheme had significantly better performances than the other schemes for the simulation of both the PBL height and pollutants, especially for the NO2 and PM2.5 (particulate matter 2.5 micrometers or less in diameter) simulations. The mean bias of the NO2, PM2.5, and PM10 (particulate matter 10 micrometers or less in diameter) prediction were −5.1, 1.2, and −8.6 µg m−3, respectively, indicating that both the canopy schemes and PBL schemes have a critical effect on air quality prediction in the urban region.

scholarly journals The impact of measures to reduce ambient air PM<sub>10</sub> concentrations originating from road dust, evaluated for a street canyon in Helsinki

2019 ◽  
Vol 19 (17) ◽  
pp. 11199-11212 ◽  
Author(s):  
Ana Stojiljkovic ◽  
Mari Kauhaniemi ◽  
Jaakko Kukkonen ◽  
Kaarle Kupiainen ◽  
Ari Karppinen ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Street Canyon ◽  
Dust Emission ◽  
Road Dust ◽  
Ambient Air ◽  
Air Quality Measurements ◽  
Emission Models ◽  
The Impact ◽  
Quality Measurements

Abstract. We have numerically evaluated how effective selected potential measures would be for reducing the impact of road dust on ambient air particulate matter (PM10). The selected measures included a reduction of the use of studded tyres on light-duty vehicles and a reduction of the use of salt or sand for traction control. We have evaluated these measures for a street canyon located in central Helsinki for four years (2007–2009 and 2014). Air quality measurements were conducted in the street canyon for two years, 2009 and 2014. Two road dust emission models, NORTRIP (NOn-exhaust Road TRaffic Induced Particle emissions) and FORE (Forecasting Of Road dust Emissions), were applied in combination with the Operational Street Pollution Model (OSPM), a street canyon dispersion model, to compute the street increments of PM10 (i.e. the fraction of PM10 concentration originating from traffic emissions at the street level) within the street canyon. The predicted concentrations were compared with the air quality measurements. Both road dust emission models reproduced the seasonal variability of the PM10 concentrations fairly well but under-predicted the annual mean values. It was found that the largest reductions of concentrations could potentially be achieved by reducing the fraction of vehicles that use studded tyres. For instance, a 30 % decrease in the number of vehicles using studded tyres would result in an average decrease in the non-exhaust street increment of PM10 from 10 % to 22 %, depending on the model used and the year considered. Modelled contributions of traction sand and salt to the annual mean non-exhaust street increment of PM10 ranged from 4 % to 20 % for the traction sand and from 0.1 % to 4 % for the traction salt. The results presented here can be used to support the development of optimal strategies for reducing high springtime particulate matter concentrations originating from road dust.

scholarly journals Effect of the uncertainty in meteorology on air quality model predictions

Időjárás ◽  
2021 ◽  
Vol 125 (4) ◽  
pp. 625-646
Author(s):  
Zita Ferenczi ◽  
Emese Homolya ◽  
Krisztina Lázár ◽  
Anita Tóth
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Weather Prediction ◽  
Horizontal Resolution ◽  
Model System ◽  
Air Quality Model ◽  
Quality Model ◽  
Near Surface ◽  
The Impact

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.

First year of real-time VOC measurements at the SIRTA facility (Paris region, France): diurnal and seasonal variabilities, impact of lockdowns on air quality

2021 ◽  
Author(s):  
Leïla Simon ◽  
Valérie Gros ◽  
Jean-Eudes Petit ◽  
François Truong ◽  
Roland Sarda-Esteve ◽  
...  
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Seasonal Variability ◽  
Anthropogenic Sources ◽  
First Year ◽  
Good Representation ◽  
Atmospheric Measurements ◽  
Paris Region ◽  
The Impact

&lt;p&gt;Volatile Organic Compounds (VOCs) have direct influences on air quality and climate. They also play a key role in atmospheric chemistry, as they are precursors of secondary pollutants, such as ozone (O&lt;sub&gt;3&lt;/sub&gt;) and secondary organic aerosols (SOA).&lt;/p&gt;&lt;p&gt;Long-term datasets of in-situ atmospheric measurements are crucial to characterize the variability of atmospheric chemical composition. Online and continuous measurements of O&lt;sub&gt;3&lt;/sub&gt;, NO&lt;sub&gt;x&lt;/sub&gt; and aerosols have been achieved at the SIRTA-ACTRIS facility (Paris region, France), since 2012. Regarding VOCs, they have been measured there for several years thanks to bi-weekly samplings followed by offline Gas Chromatography analysis. However, this method doesn&amp;#8217;t provide a good representation of the temporal variability of VOC concentrations. To tackle this issue, online VOC measurements using a Proton-Transfer-Reaction Quadrupole Mass-Spectrometer (PTR-Q-MS) have been started in January 2020.&lt;/p&gt;&lt;p&gt;The dataset acquired during the first year of online VOC measurements is analyzed, which gives insights on VOC seasonal variability. The additional long-term datasets obtained from co-located measurements (O&lt;sub&gt;3&lt;/sub&gt;, NO&lt;sub&gt;x&lt;/sub&gt;, aerosol physical and chemical properties, meteorological parameters) are also used for the sake of this study.&lt;/p&gt;&lt;p&gt;Due to Covid-19 pandemic, the year 2020 notably comprised a total lockdown in France in Spring, and a lighter one in Autumn. Therefore, a focus can be made on the impact of these lockdowns on the VOC variability and sources. To this end, the diurnal cycles of VOCs considered markers for anthropogenic sources are carefully investigated. Results notably indicate that markers for traffic and wood burning sources behave quite differently during the Spring lockdown in comparison to the other periods. A source apportionment analysis using positive matrix factorization allows to further document the seasonal variability of VOC sources and the impacts on air quality associated with the lockdown measures.&lt;/p&gt;

scholarly journals The Impact of “Coal to Gas” Policy on Air Quality: Evidence from Beijing, China

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3876 ◽  
Author(s):  
Zhe Liu ◽  
Xueli Chen ◽  
Jinyang Cai ◽  
Tomas Baležentis ◽  
Yue Li
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Energy Use ◽  
Northern China ◽  
Heating System ◽  
Use Efficiency ◽  
The Government ◽  
The Impact ◽  
Beijing China

Air pollution has become an increasingly serious environmental problem in China. Especially in winter, the air pollution in northern China becomes even worse due to winter heating. The “coal to gas” policy, which uses natural gas to replace coal in the heating system in winter, was implemented in Beijing in the year 2013. However, the effects of this policy reform have not been examined. Using a panel dataset of 16 districts in Beijing, this paper employs a first difference model to examine the impact of the “coal to gas” policy on air quality. Strong evidence shows that the “coal to gas” policy has significantly improved the air quality in Beijing. On average, the “coal to gas” policy reduced sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter smaller than 10 µm (PM10), particulate matter smaller than 2.5 µm (PM2.5) and carbon monoxide (CO) by 12.08%, 4.89%, 13.07%, 11.94% and 11.10% per year, respectively. We find that the “coal to gas” policy is more effective in areas with less energy use efficiency. The finding of this paper suggests that the government should continue to implement the “coal to gas” policy, so as to alleviate the air pollution in Beijing, China.

scholarly journals Evidence on the Impact of Winter Heating Policy on Air Pollution and Its Dynamic Changes in North China

2019 ◽  
Vol 11 (10) ◽  
pp. 2728 ◽  
Author(s):  
Shulin Wang ◽  
Yongtao Li ◽  
Mahfuzul Haque
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Central Government ◽  
Northern China ◽  
Policy Changes ◽  
Dynamic Changes ◽  
The Public ◽  
Local Residents ◽  
The Impact

Environmental pollution, especially air pollution, is an alarming issue for the public, which is extensively debated among academic scholars. During the winter heating season, “smog” has become somewhat a normal phenomenon to local residents’ livelihood in northern China. Based on the daily air pollution data of regional cities in China from 2014 to 2016, and using a regression discontinuity design (RDD), the study finds that winter heating makes the air quality worse in the northern part of China. With the start of the winter heating, it increases the Air Quality Index (AQI) by 10.4%, particulate matter smaller than 10 μm (PM10) by 9.77%, particulate matter smaller than 2.5 μm (PM2.5) by 17.25%, CO by 9.84%, NO2 by 5.23%, and SO2 by 17.1%. Furthermore, dynamic changes demonstrate that air quality has gradually improved due to a series of heating policy changes implemented by the central government in recent years. Specifically, from 2014 to 2016, major indicators measuring the air pollution decrease dramatically, such as AQI by 92.36%, PM10 by 91.24%, PM2.5 by 84.06%, CO by 70.97%, NO2 by 52.76%, and SO2 by 17.15%.

scholarly journals Regional contributions to particulate matter concentration in the Seoul metropolitan area, South Korea: seasonal variation and sensitivity to meteorology and emissions inventory

2017 ◽  
Vol 17 (17) ◽  
pp. 10315-10332 ◽  
Author(s):  
Hyun Cheol Kim ◽  
Eunhye Kim ◽  
Changhan Bae ◽  
Jeong Hoon Cho ◽  
Byeong-Uk Kim ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Seasonal Variation ◽  
Air Quality ◽  
South Korea ◽  
Metropolitan Area ◽  
Policy Support ◽  
Seoul Metropolitan Area ◽  
Regional Air Quality ◽  
Emissions Inventories ◽  
The Impact

Abstract. The impact of regional emissions (e.g., domestic and international) on surface particulate matter (PM) concentrations in the Seoul metropolitan area (SMA), South Korea, and its sensitivities to meteorology and emissions inventories are quantitatively estimated for 2014 using regional air quality modeling systems. Located on the downwind side of strong sources of anthropogenic emissions, South Korea bears the full impact of the regional transport of pollutants and their precursors. However, the impact of foreign emissions sources has not yet been fully documented. We utilized two regional air quality simulation systems: (1) a Weather Research and Forecasting and Community Multi-Scale Air Quality (CMAQ) system and (2) a United Kingdom Met Office Unified Model and CMAQ system. The following combinations of emissions inventories are used: the Intercontinental Chemical Transport Experiment-Phase B, the Inter-comparison Study for Asia 2010, and the National Institute of Environment Research Clean Air Policy Support System. Partial contributions of domestic and foreign emissions are estimated using a brute force approach, adjusting South Korean emissions to 50 %. Results show that foreign emissions contributed  ∼  60 % of SMA surface PM concentration in 2014. Estimated contributions display clear seasonal variation, with foreign emissions having a higher impact during the cold season (fall to spring), reaching  ∼  70 % in March, and making lower contributions in the summer,  ∼  45 % in September. We also found that simulated surface PM concentration is sensitive to meteorology, but estimated contributions are mostly consistent. Regional contributions are also found to be sensitive to the choice of emissions inventories.

scholarly journals Modified RAMS-Urban Canopy Model for Heat Island Simulation in Chongqing, China

2008 ◽  
Vol 47 (2) ◽  
pp. 509-524 ◽  
Author(s):  
Hongbin Zhang ◽  
Naoki Sato ◽  
Takeki Izumi ◽  
Keisuke Hanaki ◽  
Toshiya Aramaki
Keyword(s):  
Urban Canopy ◽  
Heat Emission ◽  
Atmospheric Modeling ◽  
Anthropogenic Heat ◽  
Urban Region ◽  
Infinite Length ◽  
Heat Island ◽  
Urban Canopy Model ◽  
Canopy Model ◽  
Anthropogenic Heat Emission

Abstract A single-layer urban canopy model was integrated into a nonhydrostatic meteorological model, the Regional Atmospheric Modeling System (RAMS). In the new model, called RAMS-Urban Canopy (RAMS-UC), anthropogenic heat emission was also considered. The model can be used to calculate radiation, heat, and water fluxes in an urban area, considering the geometric structure and thermodynamic characteristics of the urban canopy. The urban canopy was represented by normalized street canyons of infinite length, which were bordered by buildings on both sides. The urban region was covered by three types of surfaces: roof, wall, and road. Anthropogenic heat was emitted from these surfaces. Sensitivity tests between the original RAMS and the modified one were carried out by simulating the urban heat island (UHI) of Chongqing, located in an inland mountainous region in China. The results of the model were also compared with the observational data. It was found that the original model could not accurately simulate the UHI, in particular at night, whereas the accuracy was significantly improved in the RAMS-UC. The improvement is substantial even when anthropogenic heat emission is set to zero.

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