Ambient PM10-linked clustering of indian cities by club convergence algorithm

Abstract In a first instance for India, annual mean ambient PM10 concentrations in 209 Indian cities, estimated from National Air Quality Monitoring Program (NAMP) database of India (2012−2021), were deployed in a structured DataFrame to simulate PM10 clubs of cities by Philips and Sul’s Club Convergence algorithm. Four PM10 clubs (Club 1: 26, Club 2: 63; Club 3: 103 and Club 4: 17 cities) were identified. Club 1 with highest ambient PM10 (decadal mean and range: 182 and 75.0−329.0 µg m− 3, respectively) had 92.3% non-attainment cities while 83.4% are inside Indo-Gangetic Plain (IGP), the most polluted region in India. Further, 71.4% cities in second-most polluted Club 2 (decadal mean and range: 114.52 and 34.0−267.7 µg m− 3, respectively), are non-attainment cities in which 28.6% cities are located inside IGP. Non-attainment cities together have a share of 48.5% in Club 3 (decadal mean and range: 75.91 and 25−329 µg m− 3, respectively) and only 4.9% are inside IGP. The cities in Club 4 with lowest ambient PM10 levels (decadal mean and range: 41.62 and 8.5−109 µg m− 3, respectively) are either located on or near coastal areas that come under the influence of land and sea breeze or in North-Eastern hilly region, characterized by low population density and limited anthropogenic and industrial activities. PM10 clubs underscore the influence of geographical location and extent of regional development on ambient PM10 pollution and the potential need for formulation of club-specific air quality management practices in India.