Temporal and Spatial Analysis of PM2.5 and O3 Pollution Characteristics and Transmission in Central Liaoning Urban Agglomeration from 2015 to 2020

Abstract

The central Liaoning urban agglomeration is an important heavy industry development base in China, and also an important part of the economy in northeast China. The atmospheric environmental problems caused by the development of heavy industry are particularly prominent. Trajectory clustering, potential source contribution (PSCF), and concentration weighted trajectory (CWT) analysis are used to discuss the temporal and spatial pollution characteristics of PM2.5 and ozone concentrations and reveal the regional atmospheric transmission pattern in central Liaoning urban agglomeration from 2015 to 2020. The results show that: (1) PM2.5 in the central Liaoning urban agglomeration showed a decreasing trend from 2015 to 2020. The concentration of PM2.5 is the lowest in 2018. Except for Benxi (34.7 µg/m3), the concentrations of PM2.5 in other cities do not meet the standard in 2020. The ozone concentration in Anshan, Liaoyang, and Shenyang reached the peaks in 2017, which are 68.76 µg/m3, 66.27 µg/m3, and 63.46 µg/m3 respectively. PM2.5 pollution is the highest in winter and the lowest in summer. The daily variation distribution of PM2.5 concentration showed a bimodal pattern. Ozone pollution is the most serious in summer, with the concentration of ozone reaching 131.14 µg/m3 in Shenyang. Fushun is affected by Shenyang intercity pollution, and the ozone concentration is high. (2) In terms of spatial distribution, the high values of PM2.5 are concentrated in monitoring stations in urban areas. On the contrary, the concentration of ozone in suburban stations is higher. The high concentration of ozone in the northeast of Anshan, Liaoyang, Shenyang to Tieling, and Fushun extended in a band distribution. (3) Through cluster analysis, it is found that PM2.5 and ozone in Shenyang are mainly affected by short-distance transport airflow. In winter, the weighted PSCF high-value area of PM2.5 presents as a potential contribution source zone of the northeast trend with wide coverage, in which the contribution value of the weighted CWT in the middle of Heilongjiang is the highest. The main potential source areas of ozone mass concentration in spring and summer are coastal cities and the Bohai Sea and the Yellow Sea. We conclude that the regional transmission of pollutants is an important factor of pollution, so we should pay attention to the supply of industrial sources and marine sources of marine pollution in the surrounding areas of cities, and strengthen the joint prevention and control of air pollution among regions. The research results of this article provide a useful reference for the central Liaoning urban agglomeration to improve air quality.

Analysis of air pollution characteristics, transport pathways and potential source areas identification in Beijing before, during and after the COVID-19 outbreak

“…WCWT values in southeastern Shandong and northeastern Henan province, the potential source areas during the COB period, increased from 80 to 100 μg/m 3 to 120-160 μg/m 3 . It is worth mentioning that WCWT values were notably higher in the Bohai Bay region, which may be caused by the pollutants transported from their adjacent sea areas through the sea-land winds (Wang et al, 2022). Additionally, the PSCF and CWT model adopt the same treatment for air masses at various locations (e.g., urban, suburban, rural, forest, and ocean areas), that is the contributions of unit emission from each grid cell along a trajectory are equally weighted in calculating the mole fraction at the receptor sites (Fang et al, 2018), which may cause the overestimation in the contributions from remote areas such as ocean and Mongolia.…”

“…Regarding the height of the starting point, some researchers use 500 m above ground level (AGL) to start well within the boundary layer . Others use a height of 100 m AGL to represent the near-ground situation (Gao et al, 2021;Wang et al, 2022). Therefore, backward trajectory simulations were performed at both 100 and 500 m AGL to investigate the effect of release height on clustering analysis and potential source area identification.…”

“…As a consequence, PM 2.5 (particulate matter with an aerodynamic diameter of less than 2.5 μm) and O 3 have become the major air pollutants, which can negatively affect climate and ecosystems by reducing atmospheric visibility (Yao et al, 2021) and enhancing oxidation (Wang Y. et al, 2021), induce cardiovascular and respiratory disease (Lei et al, 2019;Yang et al, 2022), and increase the risk of premature death . PM 2.5 and O 3 have a complex relationship in that they share common precursors, namely volatile organic compounds (VOCs) and nitrogen oxides (NO x ) (Wang Y. et al, 2020), and interact with each other in the atmosphere. Aerosol particles affect photolysis efficiency by interfering with ground-level radiation, as well as NOx and HO 2 uptake, thereby inhibiting O 3 formation (Li et al, 2019).…”

Spatial Expansion and Correlation of Urban Agglomeration in the Yellow River Basin Based on Multi-Source Nighttime Light Data

“…As the largest developing country, urbanization in China showed amazing speed compared to the evolution path of urban agglomerations in Western countries [9,10]. In recent years, research on urban agglomerations in China has focused on carbon emissions [11], ecological service value [12], pollution control [13], economic development [14], and urban expansion [15]. The studied areas have mostly been urban agglomerations in eastern China.…”