scholarly journals Comparison of PM2.5 Chemical Components over East Asia Simulated by the WRF-Chem and WRF/CMAQ Models: On the Models’ Prediction Inconsistency

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 618 ◽  
Author(s):  
Choi ◽  
Lee ◽  
Woo ◽  
Kim ◽  
Lee
Keyword(s):  
Air Quality ◽  
East Asia ◽  
East Asian ◽  
Temporal Distribution ◽  
Policy Support ◽  
Weather Research And Forecasting ◽  
Chemical Components ◽  
Atmospheric Concentration ◽  
Quality Models ◽  
Weather Research

High levels of atmospheric concentration of PM2.5 (particulate matters less than 2.5 μm in size) are one of the most urgent societal issues over the East Asian countries. Air quality models have been used as an essential tool to predict spatial and temporal distribution of the PM2.5 and to support relevant policy making. This study aims to investigate the performance of high-fidelity air quality models in simulating surface PM2.5 chemical composition over the East Asia region in terms of a prediction consistency, which is a prerequisite for accurate air quality forecasts and reliable policy decision. The WRF-Chem (Weather Research and Forecasting-Chemistry) and WRF/CMAQ (Weather Research and Forecasting/Community Multiscale Air Quality modeling system) models were selected and uniquely configured for a one-month simulation by controlling surface emissions and meteorological processes (model options) to investigate the prediction consistency focusing the analyses on the effects of meteorological and chemical processes. The results showed that the surface PM2.5 chemical components simulated by both the models had significant inconsistencies over East Asia ranging fractional differences of 53% ± 30% despite the differences in emissions and meteorological fields were minimal. The models’ large inconsistencies in the surface PM2.5 concentration were attributed to the significant differences in each model’s chemical responses to the meteorological variables, which were identified from the multiple linear regression analyses. Our findings suggest that the significant models’ prediction inconsistencies should be considered with a great caution in the PM2.5 forecasts and policy support over the East Asian region.

scholarly journals Why do models perform differently on particulate matter over East Asia? A multi-model intercomparison study for MICS-Asia III

2020 ◽  
Vol 20 (12) ◽  
pp. 7393-7410 ◽  
Author(s):  
Jiani Tan ◽  
Joshua S. Fu ◽  
Gregory R. Carmichael ◽  
Syuichi Itahashi ◽  
Zhining Tao ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
East Asia ◽  
Dust Emission ◽  
Sulfur Oxidation ◽  
Atmospheric Modeling ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Air Quality Prediction ◽  
Weather Research

Abstract. This study compares the performance of 12 regional chemical transport models (CTMs) from the third phase of the Model Inter-Comparison Study for Asia (MICS-Asia III) on simulating the particulate matter (PM) over East Asia (EA) in 2010. The participating models include the Weather Research and Forecasting model coupled with Community Multiscale Air Quality (WRF-CMAQ; v4.7.1 and v5.0.2), the Regional Atmospheric Modeling System coupled with CMAQ (RAMS-CMAQ; v4.7.1 and v5.0.2), the Weather Research and Forecasting model coupled with chemistry (WRF-Chem; v3.6.1 and v3.7.1), Goddard Earth Observing System coupled with chemistry (GEOS-Chem), a non-hydrostatic model coupled with chemistry (NHM-Chem), the Nested Air Quality Prediction Modeling System (NAQPMS) and the NASA-Unified WRF (NU-WRF). This study investigates three model processes as the possible reasons for different model performances on PM. (1) Models perform very differently in the gas–particle conversion of sulfur (S) and oxidized nitrogen (N). The model differences in sulfur oxidation ratio (50 %) are of the same magnitude as that in SO42- concentrations. The gas–particle conversion is one of the main reasons for different model performances on fine mode PM. (2) Models without dust emission modules can perform well on PM10 at non-dust-affected sites but largely underestimate (up to 50 %) the PM10 concentrations at dust sites. The implementation of dust emission modules in the models has largely improved the model accuracies at dust sites (reduce model bias to −20 %). However, both the magnitude and distribution of dust pollution are not fully captured. (3) The amounts of modeled depositions vary among models by 75 %, 39 %, 21 % and 38 % for S wet, S dry, N wet and N dry depositions, respectively. Large inter-model differences are found in the washout ratios of wet deposition (at most 170 % in India) and dry deposition velocities (generally 0.3–2 cm s−1 differences over inland regions).

scholarly journals Study of the contribution of anthropogenic and natural emissions to atmospheric pollution levels

2015 ◽  
Author(s):  
Ναταλία Λιώρα
Keyword(s):  
Air Quality ◽  
Atmospheric Pollution ◽  
Temporal Distribution ◽  
Weather Research And Forecasting ◽  
Spatial And Temporal Distribution ◽  
Air Quality Model ◽  
Quality Model ◽  
Pollution Levels ◽  
Natural Emissions ◽  
Weather Research

Σκοπός της παρούσας διδακτορικής διατριβής είναι η μελέτη της συνεισφοράς των φυσικών και ανθρωπογενών πηγών εκπομπής στα επιπεδα σωματιδιακής ρύπανσης στην Ευρώπη. Οι φυσικές εκπομπές διαδραματίζουν ένα σημαντικό ρόλο στις διεργασίες της ατμόσφαιρας επιδρώντας στο κλίμα, την ποιότητα της ατμόσφαιρας και την ανθρώπινη υγεία. Γι’ αυτό το λόγο, οι φυσικές εκπομπές θα πρέπει να συμπεριλαμβάνονται στα χημικά μοντέλα ετσι ώστε να συμβάλλουν στη βελτίωση των προσομοιώσεων της ποιότητας της ατμόσφαιρας. Οι φυσικές εκπομπές υπολογίζονται με τη χρήση του μοντέλου Natural Emissions Model (ΝΕΜΟ). Το ΝΕΜΟ χρησιμοποιείται για την ποσοτικοποίηση των σωματιδιακών εκπομπών που προέρχονται από τη σκόνη από το έδαφος, το αλάτι της θάλασσας και τα βιολογικά αιωρούμενα σωματίδια (PBAPs) καθώς και των βιογενών εκπομπών από τη βλάστηση. Για την εφαρμογή του ΝΕΜΟ χρησιμοποιούνται μετεωρολογικά δεδομένα από το μοντέλο Weather Research and Forecasting (WRF). Τα δύο μοντέλα εφαρμόστηκαν σε δύο πλέγματα διαφορετικής χωρικής ανάλυσης που καλύπτουν την Ευρώπη και τα Βαλκάνια, αντίστοιχα. Τα αποτελέσματα των φυσικών εκπομπών αναλύονται χρονικά και χωρικά σε συνδυασμό με την εξάρτηση αυτών από τη μετεωρολογία. Οι φυσικές εκπομπές χαρακτηρίζονται γενικά από μεγάλες γεωγραφικές και εποχιακές μεταβολές. Οι εκπομπές από τη σκόνη του εδάφους είναι μέγιστες τους θερινούς μήνες στη Νότια Ευρώπη ενώ οι εκπομπές από το αλάτι της θάλασσες εμφανίζουν μέγιστο στον Ατλαντικό Ωκεανό κατά τη διάρκεια της ψυχρής περιόδου. Στη Μεσόγειο θάλασσα, οι μέγιστες εκπομπές από το θαλάσσιο αλάτι παρουσιάζονται κυρίως στο Αιγαίο Πέλαγος κατά τη θερινή περίοδο. Τα βιολογικά αιωρούμενα σωματίδια παρουσιάζουν μέγιστο το καλοκαίρι ενώ σε χωρικό επίπεδο, οι ελάχιστες εκπομπές παρατηρούνται στη Σκανδιναβία ενώ στην υπόλοιπη Ευρώπη δεν παρουσιάζεται ιδιαίτερη χωρική διακύμανση. Οι ανθρωπογενείς σωματιδιακές εκπομπές βασίζονται σε μία Ευρωπαϊκή βάση δεδομένων και υπολογίζονται με τη χρήση του μοντέλου ανθρωπογενών εκπομπών Model for the Spatial and Temporal Distribution of Emissions (MOSESS). Στη διατριβή παρουσιάζεται η συνεισφορά των φυσικών και ανθρωπογενών εκπομπών στις συνολικές σωματιδιακές εκπομπές στην Ευρώπη. Τα αποτελέσματα των φυσικών (σκόνη, αλάτι, βλάστηση (βιογενείς εκπομπές)) και ανθρωπογενών εκπομπών ενσωματώνονται σε σύστημα μοντέλων που απαρτίζεται από το μετεωρολογικό μοντέλο WRF και το φωτοχημικό μοντέλο Air Quality Model with Extensions (CAMx) για να μελετηθεί η συνεισφορά των φυσικών εκπομπών στην ποιότητα της ατμόσφαιρας. Το σύστημα μοντέλων εφαρμόζεται για διαφορετικά σενάρια εκπομπών έτσι ώστε να μελετηθεί ξεχωριστά η συνεισφορά της εκάστοτε φυσικής πηγής εκπομπών αλλά και η συνολική συνεισφορά από όλες τις φυσικές πηγές. Τα αποτελέσματα του μοντέλου δείχνουν ότι η σκόνη από το έδαφος αυξάνει τα μέσα μηνιαία επίπεδα συγκεντρώσεων των ΡΜ10 κατά 7μg/m3 στην περιοχή της Ανατολικής Μεσογείου το καλοκαίρι ενώ το αλάτι της θάλασσας έχει μια πολύ σημαντική επίδραση στα επίπεδα σωματιδιακής ρύπανσης αυξάνοντας τις συγκεντρώσεις των ΡΜ10 κατά περίπου 10μg/m3 στο Αιγαίο Πέλαγος το καλοκαίρι και στον Ατλαντικό Ωκεανό το φθινόπωρο. Οι βιογενείς εκπομπές συμβάλλουν στην αύξηση των δευτερογενών οργανικών σωματιδίων με αποτέλεσμα την αύξηση των επιπέδων σωματιδιακής ρύπανσης κυρίως το καλοκαίρι σε περιοχές με μεγάλη συνεισφορά των βιογενών εκπομπών (π.χ. Βόρεια Ευρώπη) ενώ συμβάλλουν στη μείωση των θειϊκών και νιτρικών σωματιδίων σε περιοχές της Κεντρικής Ευρώπης ή της Ανατολικής Μεσογείου λόγω της συμβολής τους στη μείωση των επιπέδων υδροξυλίου στην ατμόσφαιρα.Για την αξιολόγηση του συστήματος μοντέλων χρησιμοποιούνται μετρήσεις αιωρούμενων σωματιδίων που συλλέχθηκαν από διάφορους σταθμούς μέτρησης της Ευρώπης. Τα αποτελέσματα υποδεικνύουν ικανοποιητική επίδοση του μοντέλου και καλή προσομοίωση των φυσικών εκπομπών.

scholarly journals Approximating Input Data to a Snowmelt Model Using Weather Research and Forecasting Model Outputs in Lieu of Meteorological Measurements

2019 ◽  
Vol 20 (5) ◽  
pp. 847-862 ◽  
Author(s):  
Scott Havens ◽  
Danny Marks ◽  
Katelyn FitzGerald ◽  
Matt Masarik ◽  
Alejandro N. Flores ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Wrf Model ◽  
Temporal Distribution ◽  
Meteorological Variables ◽  
Weather Research And Forecasting ◽  
Atmospheric Flow ◽  
Temperature And Precipitation ◽  
Runoff Forecasting ◽  
Input Variables ◽  
Weather Research

Abstract Forecasting the timing and magnitude of snowmelt and runoff is critical to managing mountain water resources. Warming temperatures are increasing the rain–snow transition elevation and are limiting the forecasting skill of statistical models relating historical snow water equivalent to streamflow. While physically based methods are available, they require accurate estimations of the spatial and temporal distribution of meteorological variables in complex terrain. Across many mountainous areas, measurements of precipitation and other meteorological variables are limited to a few reference stations and are not adequate to resolve the complex interactions between topography and atmospheric flow. In this paper, we evaluate the ability of the Weather Research and Forecasting (WRF) Model to approximate the inputs required for a physics-based snow model, iSnobal, instead of using meteorological measurements, for the Boise River Basin (BRB) in Idaho, United States. An iSnobal simulation using station data from 40 locations in and around the BRB resulted in an average root-mean-square error (RMSE) of 4.5 mm compared with 12 SNOTEL measurements. Applying WRF forcings alone was associated with an RMSE of 10.5 mm, while including a simple bias correction to the WRF outputs of temperature and precipitation reduced the RMSE to 6.5 mm. The results highlight the utility of using WRF outputs as input to snowmelt models, as all required input variables are spatiotemporally complete. This will have important benefits in areas with sparse measurement networks and will aid snowmelt and runoff forecasting in mountainous basins.

scholarly journals Avaliação da Qualidade do Ar (NO2, CO, O3) na Cidade de Maceió/AL Utilizando o Modelo Atmosférico WRF/CHEM (Evaluation of the air quality (NO2, CO, O3) of Maceió/AL using the atmospheric model WRF/CHEM)

2019 ◽  
Vol 12 (3) ◽  
pp. 801
Author(s):  
Marcones De Oliveira Silva ◽  
Rosiberto Salustiano da Silva Júnior
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Atmospheric Model ◽  
Sao Paulo ◽  
Weather Research And Forecasting ◽  
São Paulo ◽  
Land Use Patterns ◽  
Emissions Inventory ◽  
The One ◽  
Weather Research

Este trabalho tem como objetivo avaliar a qualidade do ar na cidade de Maceió-AL utilizando o modelo numérico de mesoescala WRF/CHEM (Weather Research and forecasting/Chemistry) durante o período de 23 a 25 de abril de 2011. O WRF/CHEM foi configurado para realizar quatro tipos de simulações: Default - simulação com a topografia e uso do solo padrões do modelo; Topo - simulação com a topografia atualizada e uso do solo padrão; IGBP - simulação com a topografia padrão e uso do solo atualizado e Topo_IGBP - simulação com a atualização da topografia e uso do solo. O inventário de emissões veiculares necessário para servir como dado de entrada no modelo foi construído de acordo com a metodologia proposta pela Companhia Ambiental do Estado de São Paulo (CETESB) onde se calculou as emissões totais em toneladas anuais de monóxido de carbono (CO), óxidos de nitrogênio (NOx), hidrocarbonetos não metano (NMHC) e material particulado (MP). O modelo WRF/CHEM foi executado com duas grades aninhadas com espaçamento de grade de 5 e 1 km. Os resultados obtidos mostraram que a resolução de 1 km obteve resultados melhores, em relação às observações, para as simulações de temperatura, umidade relativa e concentrações de dióxido de nitrogênio (NO2) do que os resultados obtidos pelas simulações utilizando a grade de 5 km, porém a variabilidade horária foi melhor representada pela resolução de 5 km. A simulação Topo foi a que apresentou melhor acurácia das simulações nas duas resoluções adotadas mostrando que a atualização da topografia é mais eficiente do que a atualização do uso do solo.Palavras-Chave: WRF/CHEM; inventário; topografia; uso do solo; resolução.   A B S T R A C TThis work aims to evaluate the air quality in the city of Maceió-AL using the numerical model of the WRF/CHEM (Weather Research and forecasting / Chemistry) during the period from April 23 to 25, 2011. The WRF/CHEM was configured to perform four types of simulations: Default - simulation with topography and land use patterns of the model; Topo - simulation with updated topography and standard soil use; IGBP - simulation with the standard topography and updated soil use and Topo_IGBP - simulation with updating topography and land use. The vehicle emissions inventory required to serve as input data in the model was constructed according to the methodology proposed by the Environmental Company of the State of São Paulo (CETESB) where the total emissions in annual tons of carbon monoxide (CO), nitrogen oxides (NOx), non-methane hydrocarbons (NMHC) and particulate matter (MP). The WR /CHEM model was run with two nested grids with grid spacing of 5 and 1 km. The results obtained showed that the resolution of 1 km obtained better results, relative to the observations, for the simulations of temperature, relative humidity and nitrogen dioxide (NO2) concentrations than the results obtained by the simulations using the 5 km grid, the hourly variability was best represented by the resolution of 5 km. The Topo simulation was the one that presented better accuracy of the simulations in the two adopted resolutions showing that the updating of the topography is more efficient than the update of the land use.Keywords: WRF/CHEM; inventory; topography; land use; resolution.

scholarly journals Multi-model simulations of springtime dust storms in East Asia: Implications of an evaluation of four commonly used air quality models (CMAQv5.2.1, CAMxv6.50, CHIMEREv2017r4, and WRF-Chem v3.9.1)

2019 ◽  
Author(s):  
Siqi Ma ◽  
Xuelei Zhang ◽  
Chao Gao ◽  
Daniel Q. Tong ◽  
Aijun Xiu ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Parameter Tuning ◽  
Dust Storms ◽  
Dust Particles ◽  
Dust Event ◽  
Local Data ◽  
Dust Source ◽  
Quality Models ◽  
Dust Flux

Abstract. Mineral dust particles play an important role in the Earth system, imposing a variety of effects on air quality, climate, human health, and economy. Accurate forecasts of dust events are highly desirable to provide early-warning and inform decision-making. East Asia is one of the largest dust sources in the world. This study applies and evaluates four widely used regional air quality models to simulate dust storms in East Asia. Three dust schemes in the Weather Research and Forecast with Chemistry (WRF-Chem) (version 3.9.1), two schemes in CHIMERE (version 2017r4) and CMAQ (version 5.2), and one scheme in CAMx (version 6.50), were applied to a dust event during May 4th~6th, 2015 in Northeastern China. Most of these models were able to capture this dust event, except CAMx which has no dust source map covering the study area, hence is excluded from subsequent analysis. Although these models reproduced the spatial pattern of the dust plume, there were large discrepancies between predicted and observed PM10 concentrations in each model. In general, CHIMERE had relatively better performance among all simulations with default configurations. After parameter tuning, WRF-Chem with the AFWA scheme using seasonal dust source map from Ginoux et al. (2012) showed the best performance, followed by WRF-Chem with UOC_Shao2011 scheme, CHIMERE, and CMAQ. This study suggested that the dust source maps should be carefully selected or replaced with a new one constructed with local data. Moreover, further study and measurement on sandblasting efficiency of different soil types and locations should be conducted to improve the accuracy of estimated vertical dust flux in air quality models.

scholarly journals Assessment of the Weather Research and Forecasting model implementation in Cuba addressed to diagnostic air quality modeling

2013 ◽  
Vol 4 (1) ◽  
pp. 64-74 ◽  
Author(s):  
Leonor Turtos Carbonell ◽  
Gil Capote Mastrapa ◽  
Yasser Fonseca Rodriguez ◽  
Lourdes Alvarez Escudero ◽  
Madeleine Sanchez Gacita ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Quality Modeling ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Quality Modeling ◽  
Weather Research

scholarly journals AIR QUALITY AND WELL-BEING AMONG MIDDLE-AGED AND OLDER ADULTS IN EAST ASIA

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S266-S267
Author(s):  
Takashi Yamashita ◽  
Giyeon Kim ◽  
Darren Liu ◽  
Anthony R Bardo
Keyword(s):  
Mental Health ◽  
Older Adults ◽  
Air Quality ◽  
Physical Health ◽  
East Asia ◽  
East Asian ◽  
Well Being ◽  
Living Environment ◽  
Linear Regression Models ◽  
Self Rated Health

Abstract There is a well-established link between air quality, an important component of one’s local living environment, and well-being. However, the link between well-being and air quality is largely based on findings from western nations, and evidence from East Asia (where air pollution is a major challenge) is scant. Thus, the present study sheds much needed light on the association between well-being and air quality in four East Asian countries (i.e., China, Japan, South Korea, and Taiwan). Data for this study were drawn from the internationally representative 2010 East Asian Social Survey Health Module. The sample was limited to middle-age and older adults (i.e., 50 years and older) to account for differential exposure across the life course (N = 4,052). Linear regression models with robust standard error estimation and full information maximum likelihood were used to examine associations between four well-being indicators (self-rated health, SF-12 physical health and mental health, and happiness) and self-reported air quality. Results showed that air quality was negatively associated with well-being across East Asian nations --- with self-rated health in Japan (b = -0.09, p < 0.05) and Taiwan (b = -0.14, p < 0.05); physical health in Japan (b = -0.96, p < 0.05); mental health in China (b = -1.05, p < 0.05) and Japan (b = -1.49 , p < 0.05); and happiness in China (b = -0.07, p < 0.05). Possible explanations underlying these distinct national patterns and strategies to enhance well-being through environmental and behavioral interventions are discussed.

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