Sensitivity of WRF/Chem simulated PM2.5 to initial/boundary conditions and planetary boundary layer parameterization schemes over the Indo-Gangetic Plain.
Environ Monit Assess
; 195(5): 560, 2023 Apr 13.
Article
de En
| MEDLINE
| ID: mdl-37052717
ABSTRACT
The ability of a chemical transport model to simulate accurate meteorological and chemical processes depends upon the physical parametrizations and quality of meteorological input data such as initial/boundary conditions. In this study, weather research and forecasting model coupled with chemistry (WRF-Chem) is used to test the sensitivity of PM2.5 predictions to planetary boundary layer (PBL) parameterization schemes (YSU, MYJ, MYNN, ACM2, and Boulac) and meteorological initial/boundary conditions (FNL, ERA-Interim, GDAS, and NCMRWF) over Indo-Gangetic Plain (Delhi, Punjab, Haryana, Uttar Pradesh, and Rajasthan) during the winter period (December 2017 to January 2018). The aim is to select the model configuration for simulating PM2.5 which shows the lowest errors and best agreement with the observed data. The best results were achieved with initial/boundary conditions from ERA and GDAS datasets and local PBL parameterization (MYJ and MYNN). It was also found that PM2.5 concentrations are relatively less sensitive to changes in initial/boundary conditions but in contrast show a stronger sensitivity to changes in the PBL scheme. Moreover, the sensitivity of the simulated PM2.5 to the choice of PBL scheme is more during the polluted hours of the day (evening to early morning), while that to the choice of the meteorological input data is more uniform and subdued over the day. This work indicates the optimal model setup in terms of choice of initial/boundary conditions datasets and PBL parameterization schemes for future air quality simulations. It also highlights the importance of the choice of PBL scheme over the choice of meteorological data set to the simulated PM2.5 by a chemical transport model.
Mots clés
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Polluants atmosphériques
/
Pollution de l'air
Type d'étude:
Diagnostic_studies
/
Prognostic_studies
Pays/Région comme sujet:
Asia
Langue:
En
Journal:
Environ Monit Assess
Sujet du journal:
SAUDE AMBIENTAL
Année:
2023
Type de document:
Article
Pays d'affiliation:
Inde