{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T11:42:12Z","timestamp":1792237332963,"version":"4.4.0"},"reference-count":51,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100007611","name":"Shiv Nadar University","doi-asserted-by":"publisher","award":["FGIR\/2023\/Proposal\/19"],"award-info":[{"award-number":["FGIR\/2023\/Proposal\/19"]}],"id":[{"id":"10.13039\/501100007611","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Science Progress"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:p>\n                    The COVID-19 pandemic and the associated nationwide lockdown provided an unprecedented natural experiment to investigate how abrupt reductions in anthropogenic activities influence urban air quality. Although several studies have quantified changes in pollutant concentrations during the lockdown, the nonlinear temporal transitions and persistence of these changes after reopening remain poorly understood. This study investigates the evolution of air quality across Delhi-NCR, India, one of the world\u2019s most polluted metropolitan regions, by examining three distinct phases associated with the COVID-19 pandemic: the pre-COVID period, the COVID period, and the post-COVID period. Daily concentrations of PM\n                    <jats:sub>2.5<\/jats:sub>\n                    , PM\n                    <jats:sub>10<\/jats:sub>\n                    , NO\n                    <jats:sub>\n                      <jats:italic toggle=\"yes\">x<\/jats:italic>\n                    <\/jats:sub>\n                    , SO\n                    <jats:sub>2<\/jats:sub>\n                    , CO, and O\n                    <jats:sub>3<\/jats:sub>\n                    , together with meteorological observations from ten CAAQMS stations, were analyzed. The analytical framework combined seasonal statistical analysis, ARIMA forecasting, Pearson correlation, principal component analysis, change-point detection, and recurrence quantification analysis to characterize statistical and nonlinear dynamical transitions in air quality. The results reveal significant reductions in pollutant concentrations and pronounced shifts in their temporal dynamics during the lockdown, characterized by multiple change points and altered recurrence structures. Source-related analysis indicates that meteorological factors and secondary pollutant formation played a greater role during the lockdown, whereas combustion and non-combustion emission sources dominated before and after the restrictions. Furthermore, cross-recurrence analysis demonstrates that post-COVID pollutant dynamics remained more synchronized with lockdown conditions than with the pre-COVID period, suggesting partial persistence of environmental improvements. By integrating conventional statistical analyses with nonlinear dynamical systems techniques, this study provides a comprehensive framework for characterizing air-quality transitions and offers policy-relevant insights for sustainable urban air-quality management in rapidly growing megacities.\n                  <\/jats:p>","DOI":"10.1177\/00368504261498073","type":"journal-article","created":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T21:11:15Z","timestamp":1792012275000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Time series evidence on air quality transitions under urban shock during COVID-19 shutdown in Delhi-NCR, India"],"prefix":"10.1177","volume":"109","author":[{"given":"Saswati","family":"Biswas","sequence":"first","affiliation":[{"name":"Shiv Nadar Institution of Eminence, Dadri"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7357-7949","authenticated-orcid":false,"given":"Samit","family":"Bhattacharyya","sequence":"additional","affiliation":[{"name":"Shiv Nadar Institution of Eminence, Dadri"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mudit","family":"Yadav","sequence":"additional","affiliation":[{"name":"Shiv Nadar Institution of Eminence"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sailesh N.","family":"Behera","sequence":"additional","affiliation":[{"name":"Shiv Nadar Institution of Eminence"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yamini Sistla","family":"Sudha","sequence":"additional","affiliation":[{"name":"Shiv Nadar Institution of Eminence"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,10,14]]},"reference":[{"key":"e_1_3_5_2_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.aba9757"},{"key":"e_1_3_5_3_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa2001017"},{"key":"e_1_3_5_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2020.139281"},{"key":"e_1_3_5_5_2","doi-asserted-by":"publisher","DOI":"10.1177\/18761364251396640"},{"key":"e_1_3_5_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2020.123622"},{"key":"e_1_3_5_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2020.139052"},{"key":"e_1_3_5_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2020.139282"},{"key":"e_1_3_5_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11869-020-00866-y"},{"key":"e_1_3_5_10_2","article-title":"Satellite images show less pollution over the us as coronavirus shuts down public places","author":"Holcombe M","year":"2020","unstructured":"Holcombe M, O\u2019Key S. 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