Academic Journal

Comparing methods to impute missing daily ground-level PM10 concentrations between 2010-2017 in South Africa

التفاصيل البيبلوغرافية
العنوان: Comparing methods to impute missing daily ground-level PM10 concentrations between 2010-2017 in South Africa
المؤلفون: Arowosegbe, O. O., Röösli, M., Künzli, N., Saucy, A., Adebayo-Ojo, T. C., Jeebhay, M. F., Dalvie, M. A., de Hoogh, K.
سنة النشر: 2021
المجموعة: University of Basel: edoc
الوصف: Good quality and completeness of ambient air quality monitoring data is central in supporting actions towards mitigating the impact of ambient air pollution. In South Africa, however, availability of continuous ground-level air pollution monitoring data is scarce and incomplete. To address this issue, we developed and compared different modeling approaches to impute missing daily average particulate matter (PM10) data between 2010 and 2017 using spatiotemporal predictor variables. The random forest (RF) machine learning method was used to explore the relationship between average daily PM10 concentrations and spatiotemporal predictors like meteorological, land use and source-related variables. National (8 models), provincial (32) and site-specific (44) RF models were developed to impute missing daily PM10 data. The annual national, provincial and site-specific RF cross-validation (CV) models explained on average 78%, 70% and 55% of ground-level PM10 concentrations, respectively. The spatial components of the national and provincial CV RF models explained on average 22% and 48%, while the temporal components of the national, provincial and site-specific CV RF models explained on average 78%, 68% and 57% of ground-level PM10 concentrations, respectively. This study demonstrates a feasible approach based on RF to impute missing measurement data in areas where data collection is sparse and incomplete.
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: English
تدمد: 1660-4601
Relation: https://edoc.unibas.ch/88904/1/20220718155358_62d565f68cd04.pdf; Arowosegbe, O. O. and Röösli, M. and Künzli, N. and Saucy, A. and Adebayo-Ojo, T. C. and Jeebhay, M. F. and Dalvie, M. A. and de Hoogh, K. (2021) Comparing methods to impute missing daily ground-level PM10 concentrations between 2010-2017 in South Africa. Int J Environ Res Public Health, 18 (7). p. 3374.; info:pmid/33805155; urn:ISSN:1660-4601 (Electronic)1660-4601 (Linking)
DOI: 10.3390/ijerph18073374
الاتاحة: https://edoc.unibas.ch/88904/
https://edoc.unibas.ch/88904/1/20220718155358_62d565f68cd04.pdf
https://doi.org/10.3390/ijerph18073374
Rights: cc_by ; info:eu-repo/semantics/openAccess
رقم الانضمام: edsbas.E9296992
قاعدة البيانات: BASE
الوصف
تدمد:16604601
DOI:10.3390/ijerph18073374