PM۲.۵ Under Future Climate Conditions: Projections Based on the Sixth IPCC Assessment Report

As the effects of climate change intensify, forecasting air quality becomes essential for crafting public health and environmental policies. This research investigates changes in PM۲.۵ levels using the Shared Socioeconomic Pathways (SSPs) from the Climate Model Intercomparison Project Phase ۶ (CMIP۶). Historical climate data from ۱۹۹۸-۲۰۱۴ were used to establish a baseline, while variables like maximum and minimum temperatures, precipitation, and radiation were gathered from the Iran Meteorological Organization for ۲۰۱۳-۲۰۲۲. PM۲.۵ data for this period were also incorporated. The LARS-WG ۶.۰ tool was used for statistical downscaling, and IPSL-CM۶A-ATM-ICO-LR models projected future climate scenarios based on three SSPs from the IPCC AR۶ report: SSP۱-۲.۶ (optimistic), SSP۲-۴.۵ (intermediate), and SSP۳-۷.۰ (pessimistic). The ANN-NARX model predicted PM۲.۵ concentrations for ۲۰۲۳-۲۰۵۳, with climatic factors as inputs. All scenarios forecasted rising PM۲.۵ levels, particularly under SSP۳-۷.۰, most notably in the summer. The ANN-NARX model performed well, with RMSE values of ۱۴.۱۴, ۱۶.۸۶, and ۱۵.۴۸, and correlation coefficients of ۰.۹۱, ۰.۹۲, and ۰.۹۱ for SSP۱-۲.۶, SSP۲-۴.۵, and SSP۳-۷.۰, respectively. This emphasizes the need for proactive air quality and climate adaptation measures.

کلیدواژه ها:

Particulate Matter ، Shared Socioeconomic Pathway ، Nonlinear Autoregressive with Exogenous Input ، Long Ashton Research Station Weather Generator ، Climate Change