AHP-based Spatial Air Quality Impact Assessment Model of vehicular traffic change due to highway broadening in Sikkim Himalaya

Highway traffic-induced air pollution is a major concern for health and ecosystem. The SAQIAM was developed to facilitate visualization and interpretation of geographic distribution of air pollution impacts due to highway broadening in East Sikkim. An analytic hierarchy process-based Spatial Air Quality Index (SAQI) was constructed for this purpose. The individual air pollutant maps of CO, NO₂, SO₂ and suspended particulate matter were prepared using IITLS dispersal model. Model validation and spatial crossvalidation criteria suggested that SAQIAM is a reliable spatial model. Statistical analysis of SAQI showed that it is a reliable index. SAQI maps under various time horizons showed that the pre-project and project-implementation scenarios will have mostly good air quality while post-project implementation scenario will have poor air quality close to the highway. Spatially explicit sensitivity analysis indicates that SAQIAM is robust. SAQIAM has the potential to serve as decision support tool for geovisualization of transport-related project impacts on air quality. Moreover, it can facilitate environmental managers to prioritize mitigation measures by capturing the perception of stakeholders using SAQI.

Abbreviations: SAQIAM: Spatial Air Quality Impact Assessment Model; SAQI: Spatial Air Quality Index; EBK: Empirical Bayesian Kriging; IND-AQI: Indian Air Quality Index; AHP: Analytic Hierarchy Process; SESA: Spatially Explicit Sensitivity Analysis; OAT: One-At-a-Time; MACR: Mean Absolute Change Rate; ICCR: Impact Category Change Rate