Optimal Location Selection for a New Air Quality Monitoring Station in South Manchester for Urban Nitrogen Dioxide Measurement

In this project, I conducted research on the "Optimal Location Selection for a New Air Quality Monitoring Station in South Manchester for Urban Nitrogen Dioxide Measurement." This study employed GIS-based appropriateness analysis to identify the most suitable locations for monitoring stations that would accurately reflect the local environment. The selection process utilized four key criteria: population density, proximity to main roads, industrial zones, and areas with heavy traffic, with a specific focus on nitrogen dioxide emissions.

I used the multi-ring buffer tool for all factors in my analysis, converting the data into raster format and then reclassifying it. In the ranking system, areas with the highest population density received the lowest priority (rank ten), while regions with no inhabitants were given the highest priority (rank one). This consistent method helped evaluate the best locations for the monitoring stations effectively.