Uncertainties Caused by Major Meteorological Analysis Data Sets in Simulating Air Quality Over India

Abstract

Many places in India suffer from severe air pollution. Regional air quality simulations are essential to develop effective strategies for improving air quality, considering the nonlinear relationships between ambient pollutants and their precursor emissions. Meteorological fields used in simulations are derived from regional meteorological models with analysis data sets as inputs. This study reveals that two major analysis data sets provided by the National Centers for Environmental Prediction and the European Centre for Medium‐Range Weather Forecasts (ECMWF) cause significant differences in simulated meteorological fields over India. Especially, relative humidity values simulated using the ECMWF data set are much higher and closer to the observed values than those simulated using the National Centers for Environmental Prediction data set. Results simulated using the ECMWF data set show better model performance for most meteorological parameters over India. Differences in relative humidity originate in the data contained in the analysis data sets through grid nudging. It is not possible to avoid this underestimation by simply turning off grid nudging. The meteorological fields simulated with two major analysis data sets also lead to differences in pollutant concentrations simulated by regional chemical transport models through various physical and chemical processes. Differences originating in the two analysis data sets could be comparable with the uncertainties originating in various emission inventories in some regions and seasons in India. However, discrepancies between observed and simulated pollutant concentrations cannot be explained only by differences of the meteorological fields. Other aspects need to be explored for better performance required to develop effective strategies for India, based on accurate regional air quality simulations.

Supplementary material to "Mitigation of PM<sub>2.5</sub> and Ozone Pollution in Delhi: A Sensitivity Study during the Pre-monsoon period"

“…The model results driven by NCEP under-predict RH by 20-40%, despite an underestimation in high RH regime (RH>50%) can also be observed in the results driven by ECMWF. These findings are consistent with a recent study (Chatani and Sharma, 2018), which shows the WRF-Chem driven by ECMWF can reproduce much better meteorological conditions compared with observations over India than the driven by NCEP. They also reported that this is a general situation over the whole year (2010) of India and North Pakistan simulation, but the pre-monsoon (April-May) possibly experiences the largest underestimation of RH by S4 more than 20% over Delhi in the results driven by NCEP.…”

Mitigation of PM<sub>2.5</sub> and Ozone Pollution in Delhi: A Sensitivity Study during the Pre-monsoon period

“…The initial and boundary conditions for chemical species are provided from MOZART-4 global results (https://www.acom.ucar.edu/wrf-chem/mozart.shtml). Our baseline simulation is driven by European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological data, as we find that 135 this reproduces regional meteorology better than that from the National Centers for Environmental Prediction (NCEP) over India, consistent with a recent study (Chatani and Sharma, 2018) (Sahu et al, 2011), and is therefore closely related to traffic emissions, and we combine 155 this into the traffic sector for our study.…”

Mitigation of PM<sub>2.5</sub> and ozone pollution in Delhi: a sensitivity study during the pre-monsoon period

“…This has recently been reported in a number of Asian megacities, e.g. Shanghai (Silver et al, 2018), Beijing (Wu et al, 2015;Liu et al, 2017;Chen et al, 2018) and Guangzhou (Liu et al, 2013). Delhi and coastal cities in India, which are known to be VOC-limited (Sharma et al, 2017), may face increased O 3 as a side effect of emission controls focused on PM 2.5 .…”

“…Delhi and coastal cities in India, which are known to be VOC-limited (Sharma et al, 2017), may face increased O 3 as a side effect of emission controls focused on PM 2.5 . Therefore, studies of mitigation strategies that target both PM 2.5 and O 3 are urgently needed (Chen et al, 2018), particularly as urban air pollution in India has been much less well studied than in many other countries.…”