Predicting traffic sound levels in Cairo before, during, and after the COVID-19 lockdown using Predictor-LimA software

Abstract

This study develops a replicable urban toolkit for decision-makers to improve the quality of life in Cairo for residents and visitors affected by traffic noise. Our case study in Cairo was selected using the Aviation Design Environmental Tool (AEDT) used worldwide for airports. To simulate the COVID-19 era and days after, the noise contour mapping was performed using the Predictor-LimA software at eight receiver locations at six building heights with three assumptions of 100 %, 70 %, and 50 % traffic flow. The case study ends with lessons that can be used in regional planning, urban planning, and design to raise public awareness of noise effects in public spaces. Our analysis confirmed a deep relationship between traffic flow and noise, so controlling urban activities by reducing unnecessary uses is beneficial. We recommend that urban planners and designers incorporate noise prediction into outdoor environments’ planning and design processes.

Keywords

• COVID-19 lockdown
• Noise
• Traffic flow
• Environmental psychology
• Transportation
• Urban Design