Modeling the Regional Effects of Climate Change on Future Urban Ozone Air Quality in Tehran, Iran
Ehsan Mosadegh, Khosro Ashrafi, Majid Shafiepour Motlagh and, Iman Babaeian

TL;DR
This study uses an artificial neural network and climate projections to estimate future ozone levels in Tehran, revealing increased exceedance days and unhealthy air quality due to climate change effects.
Contribution
It introduces a novel modeling approach combining ANN and climate projections to assess future urban ozone air quality in Tehran.
Findings
Projected increase in 8-hr O3 exceedance days by 4-14 days
Future summers will have more days exceeding air quality standards
Unhealthy days in AQI are expected to rise significantly
Abstract
Quantifying the impact of climate change on future air quality is a challenging subject in air quality studies. An ANN model is employed to simulate hourly O3 concentrations. The model is developed based on hourly monitored values of temperature, solar radiation, nitrogen monoxide, and nitrogen dioxide which are monitored during summers (June, July, and August) of 2009-2012 at urban air quality stations in Tehran, Iran. Climate projections by HadCM3 GCM over the study area, driven by IPCC SRES A1B, A2, and B1 emission scenarios, are downscaled by LARS-WG5 model over the periods of 2015-2039 and 2040-2064. The projections are calculated by assuming that current emissions conditions of O3 precursors remain constant in the future. The employed O3 metrics include the number of days exceeding one-hour (1-hr) (120 ppb) and eight-hour (8-hr) (75 ppb) O3 standards and the number of days…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAtmospheric chemistry and aerosols · Oil, Gas, and Environmental Issues · COVID-19 impact on air quality
