Ground-Level Ozone Concentration and
Landscape Patterns in China’s Urban Areas
Abstract
We monitored the spatio-temporal distribution of urban
population-weighted ozone for 2014–2017 to investigate
ground-level pollution in China. During the study period,
the national average was 88.68±10.4 μg/m
3
for O3-8h, and
5.27% of the days that exceed the 160 μg/m
3
standard.
Pollution hotspots in the Tibetan Plateau are mainly at-
tributed to natural factors, while those in the North China
Plain (
NCP
), Yangtze River Delta (
YRD
), and Pearl River Delta
(
PRD
) are more closely related to anthropogenic activities.
The results indicate that the ozone pollution and its cor-
relations with the landscape are influenced by the ozone
regime and climatic factors. In the Yangtze Plain and to
its south, pollution in the ozone episodes is related to both
population size and heterogeneity. For the Yangtze Plain
and its southern urban areas in transitional ozone regimes,
sprawl, contiguity, compactness, and the size of the ur-
ban area also facilitate the accumulation of pollution.
Introduction
During the last few decades in China, the rapid industrializa-
tion and urbanization have been accompanied by elevated
air pollution at a national scale. Recently, much attention has
been paid to ground-level ozone, which is an important risk
factor for both human health and vegetation (Feng
et al.
, 2015;
Lefohn
et al.
, 2017; Lelieveld
et al.
, 2015; Liu
et al.
, 2018). It
has been reported that, in summer, most of the developed and
populated city clusters in China, such as the Yangtze River
Delta (
YRD
) (Shao
et al.
, 2016; Shu
et al.
, 2016), the Pearl River
Delta (
PRD
) (
GPEMC
, 2017), and the Beijing-Tianjin-Hebei (
BTH
)
region (Wang
et al.
, 2017), are facing serious photochemical
pollution. As a ground-level secondary pollutant, in addition
to the downward transport of stratospheric air and horizon-
tal wind transport, ground-level ozone is generated through
photochemical reactions, which is a process that requires the
presence of sunlight and the participation of emitted precur-
sors. With an abundant diversity of precursors in the differ-
ent ozone formation regimes and the complicated synoptic
meteorological conditions in China, it is a challenging task
to analyze the influence of anthropogenic activities on urban
ozone pollution.
Since the mid-2000s, several studies have been made of
surface photochemical pollution in populated areas in China,
including model simulations (Ou
et al.
, 2016), satellite data
analyses (Huang
et al.
, 2013; Jin
et al.
, 2017; Jin and Hol-
loway, 2015), and field experiments (Jia
et al.
, 2016; Shu
et
al.
, 2016). Due to the coarse spatial resolution of the data, the
observation of ozone in the first two approaches has mainly
focused on global- or regional-scale studies (Li
et al.
, 2017;
Liu
et al.
, 2018). Meanwhile, the most recent satellite remote
sensing data can provide us with the precursor distribution at
a finer spatial resolution (Jin
et al.
, 2017), which can be used
to estimate the formation mode of ground-level ozone. On
the other hand, some studies have focused on the dynamic
differences between urban and rural sites, based on large
cities (Jia
et al.
, 2016) or agglomerations (
GPEMC
, 2017), using
field observations from several ground stations. However, the
conclusions from these studies may not be comprehensive or
may even be contradictory, partly because of the limitations
of the regional climate conditions, the geographical locations,
and the development levels. For instance, Huang
et al.
(2013)
argued that tropospheric ozone was insensitive to urbaniza-
tion in three urban agglomerations in east China, while Li
et
al.
(2017) suggested that the intensified urban heat island phe-
nomenon during urbanization aggravated the ozone pollution
and the emission of its precursors in the
YRD
urban cluster. It
is also notable that relatively small cities in China account for
a substantial proportion of the population, and the ground-
level ozone situation in these areas should thus be monitored.
Since 2013, a national-scale network, which tracks and regu-
lates the Environmental Protection Agency (
EPA
)’s
six criteria
pollutants (including ground-level ozone), has been gradually
constructed by the Chinese Ministry of Ecology and Envi-
ronment (
MEE
), to facilitate the monitoring of near real-time
in-situ, ground-level ozone. This context provides us with an
opportunity to investigate the spatio-temporal characteristics
of urban ground-level ozone and its relationships with urban-
ization in multiple cities.
Urban landscape indicators are metrics that can be used
to reveal linkages between urbanization and environmental
consequences (Bai
et al.
, 2011; Fang
et al.
, 2016; Pontius and
Gilmore, 2017). The built environment in urban landscapes,
relating to the surrounding site environment, exhibits unique
radiative, thermal, moisture, and aerodynamic properties
(Frank and Engelke, 2005; Oke, 1982). The demographic
distribution in urban landscapes, influencing the metabolism
of the surrounding districts, also portrays the magnitude and
extent of human activity (Zhu
et al.
, 2015). In this context, a
number of studies have reported that urban landscapes have
a significant impact on local air pollution, such as nitrogen
oxides (NO
x
) (Bechle
et al.
, 2011; Larkin
et al.
, 2016), sulfur
dioxide (SO
2
) (Zou
et al.
, 2007), and fine particles with a
diameter of 2.5 μm or less (PM
2.5
) (Larkin
et al.
, 2016; Li
et
al.
, 2016). In recent years, the effects of urban planning and
spatial optimization methods on ground-level ozone concen-
tration have also been investigated. For instance, taking US
urban areas as the study region, population centrality has
Jiayi Li is with the School of Remote Sensing and Information
Engineering, Wuhan University, P.R. China, 129 Luoyu Road,
Wuhan, Hubei, 430079 P.R. China,
Xin Huang is with the School of Remote Sensing and
Information Engineering, Wuhan University, Wuhan 430079,
PR China; and the State Key Laboratory of Information
Engineering in Surveying, Mapping and Remote Sensing,
Wuhan University, Wuhan 430079, PR China, 129 Luoyu Road,
Wuhan, Hubei, 430079 P.R. China, (
).
Photogrammetric Engineering & Remote Sensing
Vol. 85, No. 2, February 2019, pp. 145–152.
0099-1112/18/145–152
© 2019 American Society for Photogrammetry
and Remote Sensing
doi: 10.14358/PERS.85.2.145
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
February 2019
145
