A novel method to construct an air quality index based on air pollution profiles

Area of Science:

• Environmental Health
• Air Pollution Monitoring
• Public Health

Background:

• Traditional air quality indices (AQIs) often overlook the combined impact of multiple pollutants.
• Existing AQIs are primarily sensitive to the highest pollutant sub-index, potentially masking broader pollution effects.

Purpose of the Study:

• To develop a novel, concise air quality index (AQI) that incorporates the additive effects of multiple pollutants.
• To evaluate the proposed AQI's effectiveness in predicting cardiovascular and respiratory disease hospital admissions.

Main Methods:

• Collected data on particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) concentrations in Hong Kong (2001-2012).
• Derived pollutant sub-indices normalized to WHO Air Quality Guidelines (AQG).
• Aggregated sub-indices using a root-mean-power function to create the overall AQI, with optimal power determined by minimizing estimation errors.
• Assessed associations with hospital admissions using a time-stratified case-crossover design, comparing with China AQI, UK DAQI, and US EPA AQI.

Main Results:

• Mean PM10 and SO2 concentrations exceeded WHO AQG by 37% and 50%, respectively.
• The developed AQI demonstrated significant associations with cardiovascular and respiratory admissions across all age groups.
• A clear dose-response relationship was observed between increasing pollution bands of the proposed AQI and excess hospital admissions, consistent across international AQI benchmarks.

Conclusions:

• A simple and effective air quality index (AQI) method has been developed, accounting for multiple pollutants and quantifying air quality in Hong Kong.
• The proposed AQI shows promise in predicting health outcomes, with significant associations found for cardiovascular and respiratory admissions.
• Further research is recommended to adapt and validate this method for other geographical settings.