Spatio-temporal characteristics and influencing factors of air quality in Hunan Province: investigation based on functional data model

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AbstractWith rapid economic growth and restriction by the adverse geographical and meteorological conditions, air quality control and improvement in Hunan Province are difficult. Based on the daily air quality data of Hunan Province from 2015 to 2019, in this paper, functional data analysis techniques (including principal component analysis, regression model, time series prediction model) were used to study the spatial-temporal characteristics, influencing factors, and future development trends of Air Pollution Index (AQI). The results showed that (1) in terms of time, the proportion of AQI days increased from 79.2% in 2015 to 89.9% in 2019, (2) from the spatial dimension, the air quality of Hunan Province is worse in the eastern, central, and northern regions, (3) among the meteorological factors, temperature and rainfall contributed to the improvement of air quality, but wind speed did not contribute to air quality improvement, (4) regarding socio-economic factors, industrial structure and urbanization by country were the main reasons for the deterioration of air quality in Hunan Province. Compared with the traditional time series model, the forecast precision of the functional time series model was higher.
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Spatio-temporal characteristics and influencing factors of air quality in Hunan Province: investigation based on functional data model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Spatio-temporal characteristics and influencing factors of air quality in Hunan Province: investigation based on functional data model Ke Li, Ya Liu, Zhenju Meng, Jiao Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2615729/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract With rapid economic growth and restriction by the adverse geographical and meteorological conditions, air quality control and improvement in Hunan Province are difficult. Based on the daily air quality data of Hunan Province from 2015 to 2019, in this paper, functional data analysis techniques (including principal component analysis, regression model, time series prediction model) were used to study the spatial-temporal characteristics, influencing factors, and future development trends of Air Pollution Index (AQI). The results showed that (1) in terms of time, the proportion of AQI days increased from 79.2% in 2015 to 89.9% in 2019, (2) from the spatial dimension, the air quality of Hunan Province is worse in the eastern, central, and northern regions, (3) among the meteorological factors, temperature and rainfall contributed to the improvement of air quality, but wind speed did not contribute to air quality improvement, (4) regarding socio-economic factors, industrial structure and urbanization by country were the main reasons for the deterioration of air quality in Hunan Province. Compared with the traditional time series model, the forecast precision of the functional time series model was higher. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental social sciences air quality functional data spatial-temporal characteristics influencing factors prediction Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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