{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:04:11Z","timestamp":1790294651786,"version":"4.1.0"},"reference-count":45,"publisher":"American Chemical Society (ACS)","issue":"5","license":[{"start":{"date-parts":[[2017,12,29]],"date-time":"2017-12-29T00:00:00Z","timestamp":1514505600000},"content-version":"vor","delay-in-days":2916,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>One challenge in assessing the health effects of human exposure to air pollution in epidemiologic studies is the lack of widespread historical air pollutant monitoring data with which to characterize past exposure levels.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Given the availability of long-term economic data, we relate economic activity levels to patterns in vehicle-related particulate matter (PM) over a 30-year period in New Jersey, USA, to provide insight into potential historical surrogate markers of air pollution.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We used statewide unemployment and county-level trucking industry characteristics to estimate historical coefficient of haze (COH), a marker of vehicle-related PM predominantly from diesel exhaust. A total of 5,920 observations were included across 25 different locations in New Jersey between 1971 and 2003.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A mixed-modeling approach was employed to estimate the impact of economic indicators on measured COH. The model explained approximately 50% of the variability in COH as estimated by the overall R2 value. Peaks and lows in unemployment tracked negatively with similar extremes in COH, whereas employment in the trucking industry was positively associated with COH. Federal air quality regulations also played a large and significant role in reducing COH levels over the study period.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This new approach outlines an alternative method to reconstruct historical exposures that may greatly aid epidemiologic research on specific causes of health effects from urban air pollution. Economic activity data provide a potential surrogate marker of changes in exposure levels over time in the absence of direct monitoring data for chronic disease studies, but more research in this area is needed.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1289\/ehp.0901145","type":"journal-article","created":{"date-parts":[[2010,1,4]],"date-time":"2010-01-04T13:56:06Z","timestamp":1262613366000},"page":"614-619","source":"Crossref","is-referenced-by-count":31,"title":["Economic Activity and Trends in Ambient Air Pollution"],"prefix":"10.1021","volume":"118","author":[{"given":"Mary E.","family":"Davis","sequence":"first","affiliation":[{"name":"Department of Urban and Environmental Policy and Planning, Tufts University, Medford, Massachusetts, USA"},{"name":"Exposure, Epidemiology and Risk Program, Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francine","family":"Laden","sequence":"additional","affiliation":[{"name":"Exposure, Epidemiology and Risk Program, Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA"},{"name":"Channing Laboratory, Brigham and Women\u2019s Hospital and Harvard Medical School, Boston, Massachusetts, USA"},{"name":"Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaime E.","family":"Hart","sequence":"additional","affiliation":[{"name":"Exposure, Epidemiology and Risk Program, Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA"},{"name":"Channing Laboratory, Brigham and Women\u2019s Hospital and Harvard Medical School, Boston, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric","family":"Garshick","sequence":"additional","affiliation":[{"name":"Channing Laboratory, Brigham and Women\u2019s Hospital and Harvard Medical School, Boston, Massachusetts, USA"},{"name":"Pulmonary and Critical Care Medicine Section, Medical Service, VA Boston Healthcare System, West Roxbury, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas J.","family":"Smith","sequence":"additional","affiliation":[{"name":"Exposure, Epidemiology and Risk Program, Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2010,1,4]]},"reference":[{"issue":"5","key":"2026080504084718300_micit1","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1016\/S1352-2310(98)00142-3","article-title":"Field validation of a semi-continuous method for 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