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

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 (O3) 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 O3 concentration increased year by year in most cities, but in 2020, the O3 concentration in all cities decreased. O3 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 O3 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 O3 concentration. Compared with NO, NO2, and NOx (NOx≡ NO + NO2), the ratio of NO2/NO was more coherent with O3. In addition, the temperature, the wind speed, nitrogen oxides, and fine particulate matter (PM2.5) exerted a greater impact on O3 in coastal cities than that in inland cities. In summary, the effects of the various abovementioned factors on O3 differed between coastal cities and inland cities. The present study could provide a scientific basis for targeted O3 pollution control in coastal and inland cities.

Impact of the COVID-19 lockdown on typical ambient air pollutants: Cyclical response to anthropogenic emission reduction

“…Still, there is no clear explanation for the formation of ozone periodicity. Some studies suggest that shorter cycles, such as daily and weekly cycles, can be attributed to anthropogenic emissions, meteorological conditions, boundary layer stability [ 49 , 50 ], etc., and longer cycles can be linked to solar activity cycles [ 51 ]. Considering that ozone formation is less directly linked to anthropogenic emissions and is more stable in the atmosphere, it may be necessary to observe the impact of the epidemic lockdown over a longer period of time.…”

Political Uncertainty and Corporate Social Responsibility in a Transition Economy

“…Following Duan et al (2018) and Zhou et al (2019), we divide the sample into the coastal cities subsample and the inland cities subsample. In Panel D of Table 10, The Impact of Political Uncertainty on CSR columns 1 and 3 show that the coefficients of PUM it and PUH it are both positive and significant at the 5% level.…”

Analyzing Spatial-Temporal Change of Vegetation Ecological Quality and Its Influencing Factors in Anhui Province, Eastern China Using Multiscale Geographically Weighted Regression

“…Multiscale Geographically Weighted Regression (MGWR) can quantitatively assess the spatial variability of the effects of drivers at different scales. Based on this characteristic, MGWR has been applied in several areas, such as exploring the spatial heterogeneity of PM2.5 forcing factors [23,24], modeling urban ozone drivers [25], and integrating nighttime lighting with multi-source urban data [26]. However, it has not yet been applied to explore the driving factors of vegetation ecological quality.…”