scholarly journals Air quality over Europe: modeling gaseous and particulate pollutants and the effect of precursor emissions

2013 ◽  
Vol 13 (3) ◽  
pp. 6681-6705
Author(s):  
E. Tagaris ◽  
R. E. P. Sotiropoulou ◽  
N. Gounaris ◽  
S. Andronopoulos ◽  
D. Vlachogiannis

Abstract. Air quality over Europe using Models-3 (i.e. CMAQ, MM5, SMOKE) modeling system is performed for winter (i.e. January, 2006) and summer (i.e. July, 2006) months with the 2006 TNO gridded anthropogenic emissions database. Higher ozone concentrations are illustrated in southern Europe while higher NO2 concentrations are simulated over western Europe. Elevated SO2 concentrations are simulated over eastern Europe while elevated PM2.5 levels are simulated over eastern and western Europe. Results suggest that NO2 and PM2.5 are underpredicted, SO2 is overpredicted while Max8hrO3 is overpredicted for low concentrations and is underpredicted for the higher ones. Speciated PM2.5 components suggest that NO3 is dominant during winter in western Europe and in a few eastern countries due to the high NO2 concentrations. During summer NO3 is dominant only in regions with elevated NH3 emissions. For the rest of the domain SO4 is dominant. Low OC concentrations are simulated mainly due to the uncertain representation of SOA formation. The difference between observed and predicted concentrations for each country is assessed for the gaseous and particulate pollutants. The simultaneous precursor emissions change applying scaling factors on NOx, SO2 and PM2.5 emissions based on the observed/predicted ratio for each country seems to statistically enhance model performance (in gaseous pollutants the improvement in root mean square is up to 5.6 ppbV, in the index of agreement is up to 0.3 and in the mean absolute error is up to 4.2 ppbV while the related values in PM2.5 are 4.5 μg m−3, 0.2 and 3.5 μg m−3, respectively).

2013 ◽  
Vol 13 (18) ◽  
pp. 9661-9673 ◽  
Author(s):  
E. Tagaris ◽  
R. E. P. Sotiropoulou ◽  
N. Gounaris ◽  
S. Andronopoulos ◽  
D. Vlachogiannis

Abstract. Air quality over Europe using Models-3 (i.e., CMAQ, MM5, SMOKE) modelling system is performed for winter (i.e., January 2006) and summer (i.e., July 2006) months with the 2006 TNO gridded anthropogenic emissions database. Higher ozone mixing ratios are predicted in southern Europe while higher NO2 levels are simulated over western Europe. Elevated SO2 values are simulated over eastern Europe and higher PM2.5 concentrations over eastern and western Europe. Regional average results suggest that NO2 and PM2.5 are underpredicted, SO2 is overpredicted, while Max8hrO3 is overpredicted for low mixing ratios and is underpredicted for the higher mixing ratios. However, in a number of countries observed and predicted values are in good agreement for the pollutants examined here. Speciated PM2.5 components suggest that NO3 is dominant during winter over western Europe and in a few eastern countries due to the high NO2 mixing ratios. During summer NO3 is dominant only in regions with elevated NH3 emissions. For the rest of the domain SO4 is dominant. Low OC concentrations are simulated mainly due to the uncertain representation of SOA formation.


2020 ◽  
Vol 4 (5) ◽  
pp. 951-956
Author(s):  
Miftahul Walid ◽  
Hozairi ◽  
Madukil Makruf

In this research, an analysis was carried out to develop a measuring instrument for seawater density in salt production using a microcontroller (Arduino Uno) and YL-69 sensor, this sensor was commonly used to measure soil moisture. The experimental method was used in this research to produce initial data in the form of resistance and seawater density values, then calculations are carried out using statistical methods to find equations and produce a constant variable that connects the resistance and seawater density values. The equation was used to compile the algorithm into Arduino Uno. As for the results of this research,  From six experiments conducted, two experiments produced the same sea water density value between the actual and the predicted, namely the 2nd and 5th experiments, while for other experiments there was a difference between the actual and predicted values, however, it was not too significant, the difference occurs between the value range 0 ~ 1, to determine the level of error, use the Mean Square Error (MSE) with an error level of = 0.5 and Mean Absolute Error (MAE) with an error level of = 0.6. The contribution of this research is an algorithm that can predict the density value (baume) based on the resistance value obtained from the YL 69 sensor.


2013 ◽  
Vol 13 (14) ◽  
pp. 6845-6875 ◽  
Author(s):  
Y. Zhang ◽  
K. Sartelet ◽  
S. Zhu ◽  
W. Wang ◽  
S.-Y. Wu ◽  
...  

Abstract. An offline-coupled model (WRF/Polyphemus) and an online-coupled model (WRF/Chem-MADRID) are applied to simulate air quality in July 2001 at horizontal grid resolutions of 0.5° and 0.125° over Western Europe. The model performance is evaluated against available surface and satellite observations. The two models simulate different concentrations in terms of domainwide performance statistics, spatial distribution, temporal variations, and column abundance. WRF/Chem-MADRID at 0.5° gives higher values than WRF/Polyphemus for the domainwide mean and over polluted regions in Central and southern Europe for all surface concentrations and column variables except for the tropospheric ozone residual (TOR). Compared with observations, WRF/Polyphemus gives better statistical performance for daily HNO3, SO2, and NO2 at the European Monitoring and Evaluation Programme (EMEP) sites, maximum 1 h O3 at the AirBase sites, PM2.5 at the AirBase sites, maximum 8 h O3 and PM10 composition at all sites, column abundance of CO, NO2, TOR, and aerosol optical depth (AOD), whereas WRF/Chem-MADRID gives better statistical performance for NH3, hourly SO2, NO2, and O3 at the AirBase and BDQA (Base de données de la qualité de l'air) sites, maximum 1 h O3 at the BDQA and EMEP sites, and PM10 at all sites. WRF/Chem-MADRID generally reproduces well the observed high hourly concentrations of SO2 and NO2 at most sites except for extremely high episodes at a few sites, and WRF/Polyphemus performs well for hourly SO2 concentrations at most rural or background sites where pollutant levels are relatively low, but it underpredicts the observed hourly NO2 concentrations at most sites. Both models generally capture well the daytime maximum 8 h O3 concentrations and diurnal variations of O3 with more accurate peak daytime and minimal nighttime values by WRF/Chem-MADRID, but neither model reproduces extremely low nighttime O3 concentrations at several urban and suburban sites due to underpredictions of NOx and thus insufficient titration of O3 at night. WRF/Polyphemus gives more accurate concentrations of PM2.5, and WRF/Chem-MADRID reproduces better the observations of PM10 concentrations at all sites. The differences between model predictions and observations are mostly caused by inaccurate representations of emissions of gaseous precursors and primary PM species, as well as biases in the meteorological predictions. The differences in model predictions are caused by differences in the heights of the first model layers and thickness of each layer that affect vertical distributions of emissions, model treatments such as dry/wet deposition, heterogeneous chemistry, and aerosol and cloud, as well as model inputs such as emissions of soil dust and sea salt and chemical boundary conditions of CO and O3 used in both models. WRF/Chem-MADRID shows a higher sensitivity to grid resolution than WRF/Polyphemus at all sites. For both models, the use of a finer grid resolution generally leads to an overall better statistical performance for most variables, with greater spatial details and an overall better agreement in temporal variations and magnitudes at most sites. The use of online biogenic volatile organic compound (BVOC) emissions gives better statistical performance for hourly and maximum 8 h O3 and PM2.5 and generally better agreement with their observed temporal variations at most sites. Because it is an online model, WRF/Chem-MADRID offers the advantage of accounting for various feedbacks between meteorology and chemical species. However, this model comparison suggests that atmospheric pollutant concentrations are most sensitive in state-of-the-science air quality models to vertical structure, inputs, and parameterizations for dry/wet removal of gases and particles in the model.


Slavic Review ◽  
2017 ◽  
Vol 76 (2) ◽  
pp. 297-306 ◽  
Author(s):  
Dace Dzenovska

This essay argues that what is at stake in debates about the difference between eastern and western Europe in the context of migration and asylum politics is the definition of a politically- and ethically-acceptable threshold of “too many,” which takes on concrete contours in relation to historically-formed understandings of coherent selves and viable polities. The argument derives from placing analysis of the alleged political and ethical failures of eastern Europe alongside those limits of refugee/migrant intake that are considered politically legitimate and ethically justifiable from the mainstream liberal democratic perspective. The essay proposes that in order to understand the European political landscape in relation to migration, it is necessary to undertake relational analysis of the different configurations of the Europe-wide tension between inclusion and exclusion, as well as analysis of the modes of power that differentiate between these configurations of inclusion and exclusion on moral grounds.


2017 ◽  
Vol 124 (3) ◽  
pp. 662-673 ◽  
Author(s):  
Kenta Kusanagi ◽  
Daisuke Sato ◽  
Yasuhiro Hashimoto ◽  
Norimasa Yamada

This study determined whether expert swimmers, compared with nonexperts, have superior movement perception and physical sensations of propulsion in water. Expert (national level competitors, n = 10) and nonexpert (able to swim 50 m in > 3 styles, n = 10) swimmers estimated distance traveled in water with their eyes closed. Both groups indicated their subjective physical sensations in the water. For each of two trials, two-dimensional coordinates were obtained from video recordings using the two-dimensional direct linear transformation method for calculating changes in speed. The mean absolute error of the difference between the actual and estimated distance traveled in the water was significantly lower for expert swimmers (0.90 ± 0.71 meters) compared with nonexpert swimmers (3.85 ± 0.84 m). Expert swimmers described the sensation of propulsion in water in cutaneous terms as the “sense of flow” and sensation of “skin resistance.” Therefore, expert swimmers appear to have a superior sense of distance during their movement in the water compared with that of nonexpert swimmers. In addition, expert swimmers may have a better perception of movement in water. We propose that expert swimmers integrate sensations and proprioceptive senses, enabling them to better perceive and estimate distance moved through water.


2020 ◽  
Vol 38 (3) ◽  
pp. 725-748
Author(s):  
Gizaw Mengistu Tsidu ◽  
Mulugeta Melaku Zegeye

Abstract. Earth's ionosphere is an important medium of radio wave propagation in modern times. However, the effective use of the ionosphere depends on the understanding of its spatiotemporal variability. Towards this end, a number of ground- and space-based monitoring facilities have been set up over the years. The information from these stations has also been complemented by model-based studies. However, assessment of the performance of ionospheric models in capturing observations needs to be conducted. In this work, the performance of the IRI-2016 model in simulating the total electron content (TEC) observed by a network of Global Positioning System (GPS) receivers is evaluated based on the RMSE, the bias, the mean absolute error (MAE) and skill score, the normalized mean bias factor (NMBF), the normalized mean absolute error factor (NMAEF), the correlation, and categorical metrics such as the quantile probability of detection (QPOD), the quantile categorical miss (QCM), and the quantile critical success index (QCSI). The IRI-2016 model simulations are evaluated against gridded International Global Navigation Satellite System (GNSS) Service (IGS) GPS-TEC and TEC observations at a network of GPS receiver stations during the solar minima in 2008 and solar maxima in 2013. The phases of modeled and simulated TEC time series agree strongly over most of the globe, as indicated by a high correlations during all solar activities with the exception of the polar regions. In addition, lower RMSE, MAE, and bias values are observed between the modeled and measured TEC values during the solar minima than during the solar maxima from both sets of observations. The model performance is also found to vary with season, longitude, solar zenith angle, and magnetic local time. These variations in the model skill arise from differences between seasons with respect to solar irradiance, the direction of neutral meridional winds, neutral composition, and the longitudinal dependence of tidally induced wave number four structures. Moreover, the variation in model performance as a function of solar zenith angle and magnetic local time might be linked to the accuracy of the ionospheric parameters used to characterize both the bottom- and topside ionospheres. However, when the NMBF and NMAEF are applied to the data sets from the two distinct solar activity periods, the difference in the skill of the model during the two periods decreases, suggesting that the traditional model evaluation metrics exaggerate the difference in model skill. Moreover, the performance of the model in capturing the highest ends of extreme values over the geomagnetic equator, midlatitudes, and high latitudes is poor, as noted from the decrease in the QPOD and QCSI as well as an increase in the QCM over most of the globe with an increase in the threshold percentile TEC values from 10 % to 90 % during both the solar minimum and the solar maximum periods. The performance of IRI-2016 in simulating observed low (as low as the 10th percentile) and high (higher than the 90th percentile) TEC correctly over equatorial ionization anomaly (EIA) crest regions is reasonably good given that IRI-2016 is a climatological model. However, it is worth noting that the performance of the IRI-2016 model is relatively poor in 2013 compared with 2008 at the highest ends of the TEC distribution. Therefore, this study reveals the strengths and weaknesses of the IRI-2016 model in simulating the observed TEC distribution correctly during all seasons and solar activities for the first time.


2021 ◽  
Author(s):  
Ana Isabel Lopez-Noreña ◽  
Lucas Berná ◽  
María Florencia Tames ◽  
Emmanuel Millán ◽  
Enrique Puliafito ◽  
...  

<p>The online-coupled Weather Research and Forecasting model with Chemistry (WRF-Chem v4.0), was applied to evaluate the impact of using different anthropogenic emissions inventories on regional air quality in Argentina. For this purpose, we couple the Argentinian high-resolution emissions inventory (GEAA-AHRI) and the Emissions Database for Global Atmospheric Research – Hemispheric Transport of Air Pollution (EDGAR-HTAP) and introduce them into the model, with a local optimized configuration considering 3 nested domains with a horizontal grid size of 20 x 20 km, 4 x 4 km, and 1.3 x 1.3 km and the MOZART chemical scheme. The model output for NO2, PM10, PM2.5, and O3 concentrations over the innermost domain was compared against the existing surface and satellite-derived observations for the Buenos Aires Metropolitan Area (AMBA) during austral fall 2018. We found an overall good model performance for all simulations, and large discrepancies between the emission inventories, obtaining an improved urban-scale spatio-temporal representation when the high resolution GEAA-AHRI dataset is considered. Our results show that the daytime concentrations of air pollutants are strongly influenced by the shape and shift of the hourly emissions profile before sunrise and after sunset, especially for NO2 where the inclusion of the temporal profile decreased the mean bias by ~80%. Performance criteria for modeled PM10 and PM2.5 were in general satisfied, despite having an average underestimation of observations. When compared to NO2 tropospheric columns derived from TROPOMI, The general magnitude and spatial pattern of the NO2 tropospheric column is in agreement with the mean TROPOMI columns during the modeled period, obtaining correlation coefficients higher than 0.6 for all simulations. Our results highlight the benefits of using a time-dependent and high-resolution local inventory for addressing the background air quality in AMBA. The implementation and validation of local emissions and static fields with high spatial and temporal resolution carried out in this work, establishes a benchmark for forthcoming studies in other regions of South America where different modeling tools for air quality analysis are currently being used to complement the usually sparse and discontinuous air quality networks.</p>


Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1743 ◽  
Author(s):  
Mustapha Adamu ◽  
Xinfa Qiu ◽  
Guoping Shi ◽  
Isaac Kwesi Nooni ◽  
Dandan Wang ◽  
...  

In this paper, we propose a remote sensing model based on a 1 × 1 km spatial resolution to estimate the spatio-temporal distribution of sunshine percentage (SSP) and sunshine duration (SD), taking into account terrain features and atmospheric factors. To account for the influence of topography and atmospheric conditions in the model, a digital elevation model (DEM) and cloud products from the moderate-resolution imaging spectroradiometer (MODIS) for 2010 were incorporated into the model and subsequently validated against in situ observation data. The annual and monthly average daily total SSP and SD have been estimated based on the proposed model. The error analysis results indicate that the proposed modelled SD is in good agreement with ground-based observations. The model performance is evaluated against two classical interpolation techniques (kriging and inverse distance weighting (IDW)) based on the mean absolute error (MAE), the mean relative error (MRE) and the root-mean-square error (RMSE). The results reveal that the SD obtained from the proposed model performs better than those obtained from the two classical interpolators. This results indicate that the proposed model can reliably reflect the contribution of terrain and cloud cover in SD estimation in Ghana, and the model performance is expected to perform well in similar environmental conditions.


Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 511
Author(s):  
Syuichi Itahashi ◽  
Kazuyo Yamaji ◽  
Satoru Chatani ◽  
Kyo Kitayama ◽  
Yu Morino ◽  
...  

In this study, the results for nitrate (NO3−) aerosol during winter from the first-phase model inter-comparison study of Japan’s Study for Reference Air Quality Modeling (J-STREAM) were analyzed. To investigate the models’ external and internal settings, the results were limited to Community Multiscale Air Quality (CMAQ) models. All submitted models generally underestimated NO3− over the urban areas in Japan (e.g., Osaka, Nagoya, and Tokyo); however, some model settings showed distinct behavior. The differences due to the model external settings were larger than the model internal settings. Emissions were an important factor, and emissions configured with lower NOx emissions and higher NH3 emissions led to a higher NO3− concentration as the NH3 was consumed under NH3-rich conditions. The model internal settings of the chemical mechanisms caused differences over China, and this could affect western Japan; however, the difference over Tokyo was lower. To obtain a higher NO3− concentration over the urban areas in Japan, the selection of the HONO option for the heterogenous reaction and the inline calculation of photolysis was desired. For future studies, the external settings of the boundary condition and the meteorological field require further investigation.


2018 ◽  
Vol 27 (10) ◽  
pp. 684 ◽  
Author(s):  
Joseph L. Wilkins ◽  
George Pouliot ◽  
Kristen Foley ◽  
Wyat Appel ◽  
Thomas Pierce

Wildland fire emissions are routinely estimated in the US Environmental Protection Agency’s National Emissions Inventory, specifically for fine particulate matter (PM2.5) and precursors to ozone (O3); however, there is a large amount of uncertainty in this sector. We employ a brute-force zero-out sensitivity method to estimate the impact of wildland fire emissions on air quality across the contiguous US using the Community Multiscale Air Quality (CMAQ) modelling system. These simulations are designed to assess the importance of wildland fire emissions on CMAQ model performance and are not intended for regulatory assessments. CMAQ ver. 5.0.1 estimated that fires contributed 11% to the mean PM2.5 and less than 1% to the mean O3 concentrations during 2008–2012. Adding fires to CMAQ increases the number of ‘grid-cell days’ with PM2.5 above 35 µg m−3 by a factor of 4 and the number of grid-cell days with maximum daily 8-h average O3 above 70 ppb by 14%. Although CMAQ simulations of specific fires have improved with the latest model version (e.g. for the 2008 California wildfire episode, the correlation r = 0.82 with CMAQ ver. 5.0.1 v. r = 0.68 for CMAQ ver. 4.7.1), the model still exhibits a low bias at higher observed concentrations and a high bias at lower observed concentrations. Given the large impact of wildland fire emissions on simulated concentrations of elevated PM2.5 and O3, improvements are recommended on how these emissions are characterised and distributed vertically in the model.


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