Exploring the potential of machine learning for simulations of urban ozone variability
Open Access
- 18 November 2021
- journal article
- research article
- Published by Springer Science and Business Media LLC in Scientific Reports
- Vol. 11 (1), 1-7
- https://doi.org/10.1038/s41598-021-01824-z
Abstract
Machine learning (ML) has emerged as a powerful technique in the Earth system science, nevertheless, its potential to model complex atmospheric chemistry remains largely unexplored. Here, we applied ML to simulate the variability in urban ozone (O3) over Doon valley of the Himalaya. The ML model, trained with past variations in O3 and meteorological conditions, successfully reproduced the independent O3 data (r2 ~ 0.7). Model performance is found to be similar when the variation in major precursors (CO and NOx) were included in the model, instead of the meteorology. Further the inclusion of both precursors and meteorology improved the performance significantly (r2 = 0.86) and the model could also capture the outliers, which are crucial for air quality assessments. We suggest that in absence of high-resolution measurements, ML modeling has profound implications for unraveling the feedback between pollution and meteorology in the fragile Himalayan ecosystem.Keywords
This publication has 56 references indexed in Scilit:
- The Himalayas must be protectedNature, 2013
- On rising temperature trends at Dehradun in Doon valley of Uttarakhand, IndiaJournal of Earth System Science, 2013
- Variabilities in ozone at a semi‐urban site in the Indo‐Gangetic Plain region: Association with the meteorology and regional processesJournal of Geophysical Research: Atmospheres, 2012
- Simulations over South Asia using the Weather Research and Forecasting model with Chemistry (WRF-Chem): chemistry evaluation and initial resultsGeoscientific Model Development, 2012
- Influences of the springtime northern Indian biomass burning over the central HimalayasJournal of Geophysical Research, 2011
- The ERA‐Interim reanalysis: configuration and performance of the data assimilation systemQuarterly Journal of the Royal Meteorological Society, 2011
- Variations in surface ozone at Nainital: A high‐altitude site in the central HimalayasJournal of Geophysical Research: Atmospheres, 2010
- Direct assessment of international consistency of standards for ground-level ozone: strategy and implementation toward metrological traceability network in AsiaJournal of Environmental Monitoring, 2007
- Atmospheric brown clouds: Impacts on South Asian climate and hydrological cycleProceedings of the National Academy of Sciences of the United States of America, 2005
- Global distribution of tropospheric ozone from satellite measurements using the empirically corrected tropospheric ozone residual technique: Identification of the regional aspects of air pollutionAtmospheric Chemistry and Physics, 2003