Temporal and Spatial Distribution Analysis of Atmospheric Pollutants in Chengdu–Chongqing Twin-City Economic Circle

Abstract

In order to study the temporal and spatial distribution characteristics of atmospheric pollutants in cities (districts and counties) in the Chengdu–Chongqing Twin-city Economic Circle (CCEC) and to provide a theoretical basis for atmospheric pollution prevention and control, this paper combined Ambient Air Quality Standards (AAQS) and WHO Global Air Quality Guidelines (GAQG) to evaluate atmospheric pollution and used spatial correlation to determine key pollution areas. The results showed that the distribution of atmospheric pollutants in CCEC presents a certain law, which was consistent with the air pollution transmission channels. Except for particulate matter with an aerodynamic diameter equal to or less than 2.5 μm (PM2.5) and ozone (O3), other pollutants reached Grade II of AAQS in 2020, among which particulate matter with an aerodynamic diameter equal to or less than 10 μm (PM10), PM2.5, sulfur dioxide (SO2), nitrogen dioxide (NO2) and carbon monoxide (CO) have improved. Compared with the air quality guidelines given in the GAQG, PM10, PM2.5, NO2 and O3 have certain effects on human health. The spatial aggregation of PM10 and PM2.5 decreased year by year, while the spatial aggregation of O3 increased with the change in time, and the distribution of NO2 pollution had no obvious aggregation. Comprehensive analysis showed that the pollution problems of particulate matter, NO2 and O3 in CCEC need to be further controlled.

Variation characteristics and coordinated emission reduction of air pollutants in megacity of Chengdu-Chongqing economic circle under dual carbon goal

“…However, the ratio in different seasons did not exceed the range (0.5-0.8) of urban areas in developed countries. The change of PM 2.5 /PM 10 ratio was due to the different dominant sources and their contribution rates in different seasons [121,129]. Furthermore, this ratio fluctuates relatively steadily from March to September every year, and it is about 0.58 between 2014 and 2020 (Fig.…”

“…Therefore, NO x emission control pattern should be carefully mapped to assess changes in O 3 . In 2020, the coal-fired boilers in Chengdu have been cleared, and the proportion of clean energy rise from 56.5% in 2015 to 62.6% in 2020 [121]. O 3 is the third largest greenhouse gas after CO 2 and CH 4 [122,123].…”

“…S10), indicating that PM pollution is still serious [80,131]. Qi et al [121] pointed out that the greater the ratio, the higher the risk to public health [121]. PM mainly comes from the construction, cement industry and automobile exhaust.…”

Verification of the Perception of the Local Community concerning Air Quality Using ADMS-Roads Modeling

“…Currently, pollution maps [ 17 ], which present the average level of pollution in a given time interval, are the main diagnostic tool used to analyze air quality in a city [ 18 ]. Next to pollution maps, the forecasting uses new methods, based, for example, on neural networks [ 19 , 20 ] or the land-use regression (LUR) technique for air pollution modeling, in order to obtain the spatial distribution of air pollutants for epidemiological studies [ 21 ].…”

Functional Data Analysis for the Detection of Outliers and Study of the Effects of the COVID-19 Pandemic on Air Quality: A Case Study in Gijón, Spain

“…Air pollution is nowadays one of the most important environmental concerns for the population of urban areas [1][2][3][4][5][6][7][8][9][10]. The reason for this lies in the threat that air pollution poses for the residents of those places, where a broad range of different sources emit great quantities of different pollutants with distinct health effects [11][12][13].…”