Spatiotemporal Variation in Ground Level Ozone and Its Driving Factors: A Comparative Study of Coastal and Inland Cities in Eastern China

Mengge Zhou, Yonghua Li () and Fengying Zhang ()
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Mengge Zhou: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Yonghua Li: Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Fengying Zhang: China National Environmental Monitoring Centre, Beijing 100012, China

IJERPH, 2022, vol. 19, issue 15, 1-19

Abstract: Variations in marine and terrestrial geographical environments can cause considerable differences in meteorological conditions, economic features, and population density (PD) levels between coastal and inland cities, which in turn can affect the urban air quality. In this study, a five-year (2016–2020) dataset encompassing air monitoring (from the China National Environmental Monitoring Centre), socioeconomic statistical (from the Shandong Province Bureau of Statistics) and meteorological data (from the U.S. National Centers for Environmental Information, National Oceanic and Atmospheric Administration) was employed to investigate the spatiotemporal distribution characteristics and underlying drivers of urban ozone (O 3 ) in Shandong Province, a region with both land and sea environments in eastern China. The main research methods included the multiscale geographically weighted regression (MGWR) model and wavelet analysis. From 2016 to 2019, the O 3 concentration increased year by year in most cities, but in 2020, the O 3 concentration in all cities decreased. O 3 concentration exhibited obvious regional differences, with higher levels in inland areas and lower levels in eastern coastal areas. The MGWR analysis results indicated the relationship between PD, urbanization rate (UR), and O 3 was greater in coastal cities than that in the inland cities. Furthermore, the wavelet coherence (WTC) analysis results indicated that the daily maximum temperature was the most important factor influencing the O 3 concentration. Compared with NO, NO 2 , and NO x (NO x ≡ NO + NO 2 ), the ratio of NO 2 /NO was more coherent with O 3 . In addition, the temperature, the wind speed, nitrogen oxides, and fine particulate matter (PM 2.5 ) exerted a greater impact on O 3 in coastal cities than that in inland cities. In summary, the effects of the various abovementioned factors on O 3 differed between coastal cities and inland cities. The present study could provide a scientific basis for targeted O 3 pollution control in coastal and inland cities.

Keywords: ozone; coastal and inland cities; spatiotemporal distribution; wavelet analysis; multiscale geographically weighted regression (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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