{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:35:01Z","timestamp":1781109301597,"version":"3.54.1"},"reference-count":76,"publisher":"National Academy of Sciences","issue":"18","license":[{"start":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T00:00:00Z","timestamp":1713830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2024,4,30]]},"abstract":"<jats:p>\n                    This paper studies the effect of air pollution on voting outcomes. We use data from 60 federal and state elections in Germany from 2000 to 2018 and exploit plausibly exogenous fluctuations in ambient air pollution within counties across election dates. Higher air pollution on election day shifts votes away from incumbent parties and toward opposition parties. An increase in the concentration of particulate matter (PM10) by 10\n                    <jats:inline-formula>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" overflow=\"scroll\">\n                        <mml:mi mathvariant=\"normal\">\u03bc<\/mml:mi>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    g\/m\n                    <jats:inline-formula>\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"inline\" overflow=\"scroll\">\n                        <mml:msup>\n                          <mml:mrow\/>\n                          <mml:mn>3<\/mml:mn>\n                        <\/mml:msup>\n                      <\/mml:math>\n                    <\/jats:inline-formula>\n                    \u2014around two within-county SDs\u2014reduces the vote share of incumbent parties by two percentage points, which is equivalent to 4% of the mean vote share. We generalize these findings by documenting similar effects with data from a weekly opinion poll and a large-scale panel survey. We provide further evidence that poor air quality leads to more negative emotions such as anger, worry, and unhappiness, which, in turn, may reduce the support for the political status quo. Overall, these results suggest that poor air quality affects decision-making in the population at large, including consequential political decisions.\n                  <\/jats:p>","DOI":"10.1073\/pnas.2314428121","type":"journal-article","created":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T13:42:38Z","timestamp":1713879758000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":10,"title":["The political fallout of air pollution"],"prefix":"10.1073","volume":"121","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4640-2967","authenticated-orcid":false,"given":"Luna","family":"Bellani","sequence":"first","affiliation":[{"name":"Department of Economics, Ulm University, Ulm 89081, Germany"},{"name":"Institute of Labor Economics, Bonn 53113, Germany"},{"name":"AXA Research Lab on Gender Equality at Centre for Research on Social Dynamics and Public Policy (DONDENA), Milan 20136, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-6555-2890","authenticated-orcid":false,"given":"Stefano","family":"Ceolotto","sequence":"additional","affiliation":[{"name":"Risk Assessment and Adaptation Strategies (RAAS), Euro-Mediterranean Center on Climate Change and Ca\u2019 Foscari University of Venice, Edificio Porta dell\u2019Innovazione - Piano 2, Venezia Marghera 30175, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6343-9393","authenticated-orcid":false,"given":"Benjamin","family":"Elsner","sequence":"additional","affiliation":[{"name":"Institute of Labor Economics, Bonn 53113, Germany"},{"name":"School of Economics, University College Dublin, Belfield D04 V1W8, Ireland"},{"name":"Centre for Research and Analysis of Migration, University College London, London WC1H 0AX, United Kingdom"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0062-9514","authenticated-orcid":false,"given":"Nico","family":"Pestel","sequence":"additional","affiliation":[{"name":"Institute of Labor Economics, Bonn 53113, Germany"},{"name":"Maastricht University, Research Centre for Education and the Labour Market, Maastricht 6211 LM, The Netherlands"},{"name":"CESifo Research Network, Munich 81679, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"341","published-online":{"date-parts":[[2024,4,23]]},"reference":[{"key":"e_1_3_4_1_2","doi-asserted-by":"publisher","DOI":"10.1257\/jel.51.3.689"},{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.copsyc.2019.06.024"},{"key":"e_1_3_4_3_2","doi-asserted-by":"crossref","unstructured":"S. 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