Academic Journal
Using spatiotemporal prediction models to quantify PM 2.5 exposure due to daily movement
| العنوان: | Using spatiotemporal prediction models to quantify PM 2.5 exposure due to daily movement |
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| المؤلفون: | Jain, Sakshi, Presto, Albert A., Zimmerman, Naomi |
| المساهمون: | Heinz Endowments, U.S. Environmental Protection Agency, Canada Research Chairs, Natural Sciences and Engineering Research Council of Canada |
| المصدر: | Environmental Science: Atmospheres ; volume 3, issue 11, page 1665-1677 ; ISSN 2634-3606 |
| بيانات النشر: | Royal Society of Chemistry (RSC) |
| سنة النشر: | 2023 |
| الوصف: | This study estimates exposure differences when considering spatiotemporal variations in PM 2.5 concentration that a population may experience, using daily average land use regression estimates for 2017 in Pittsburgh, PA. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| DOI: | 10.1039/d3ea00051f |
| الاتاحة: | http://dx.doi.org/10.1039/d3ea00051f http://pubs.rsc.org/en/content/articlepdf/2023/EA/D3EA00051F |
| Rights: | http://creativecommons.org/licenses/by-nc/3.0/ |
| رقم الانضمام: | edsbas.E24E49A8 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1039/d3ea00051f |
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