Abstract
Transboundary pollutant transport is considered as one of the primary factors causing the seasonal air quality deterioration in Delhi, India's capital. The highest standard deviations exceeding days in winter for NO(2) (7.14-9.63%) and SO(2) (4.04-7.42%) in 2019-2022 underscore the role of meteorological conditions in Delhi's pollution. In contrast, the post-monsoon season shows the highest pollutant exceedance days (4.52-8.00%) for CO due to stubble burning (SB) in Punjab (68,902 fires/year). Despite the government's assertions of decreasing SB events (14.68%), the city's CO exceedance days persistently rose by 6.36%. CAMS data is used for assessing contribution hotspots through back-trajectory analysis at multiple heights. An overlap hotspot of 111 sq. km area is identified in the Southeast parts of Punjab that have a higher contribution to the CO levels in Delhi during the post-monsoon season of 2019. Similarly, hotspots are also observed for SO(2) over industrial areas of Punjab during the post-monsoon and pre-monsoon seasons. The same seasons show similar contributing patterns for NO(2) highlighting the influence of consistent emission patterns and meteorological conditions. The clear delineation of hotspots using the receptor model at multiple heights coupled with source apportionment studies will assist decision-makers in addressing the pollution sources outside Delhi.