Particle composition, sources and evolution during the COVID-19 lockdown period in Chengdu, southwest China: Insights from single particle aerosol mass spectrometer data

Evolution of black carbon and brown carbon during summertime in Southwestern China: An assessment of control measures during the 2023 Chengdu Summer World University Games

The 31st FISU Summer World University Games (SWUG) was held in Chengdu, southwestern China, from July 22 to August 8, 2023. A series of control measures were carried out to ensure good air quality during the SWUG, providing an opportunity to investigate the atmospheric behaviors of light-absorbing aerosols under such a substantial disturbance caused by the control measures. To assess the impacts of emission controls on primary pollutants, a field campaign was conducted at a rural site in Chengdu to investigate the characterization of equivalent black carbon (eBC). The changes of eBC concentrations before, during, and after the SWUG were characterized. The sources of eBC were resolved, and the impacts of atmospheric processes on the absorption capacity were also investigated. During the SWUG, the eBC concentration decreased by 12.1 % and 25.3 % compared with those before and after the SWUG. A fossil fuel combustion (eBCff) and a biomass burning (eBCbb) originated eBC were resolved using the aethalometer model. Both eBCff and eBCbb decreased during the SWUG, indicating the effectiveness of control measures. After the SWUG, the influence of biomass burning emissions became more and more significant, and the contribution of brown carbon (BrC) to light absorption at 370-660 nm increased by 52, 19, 7, 6, and 17 % compared to those during the SWUG. As the biomass burning emitted aerosols aged, the absorption Ångström exponent and babs(BrC370nm) decreased gradually, which was mainly due to the photobleaching of the chromophores during the daytime. eBCff was mainly affected by strong wind, while high eBCbb concentration was mainly attributed to the gradual accumulation of biomass-burning emissions near the observation site. The results show the significant reduction of eBC with the implementation of the air pollution mitigation campaign, and provide insights on the impacts of atmospheric processes on BC optical properties during summertime.

Microscopic Characterization of Individual Aerosol Particles in a Typical Industrial City and Its Surrounding Rural Areas in China

Transmission electron microscopy was used to analyze individual aerosol particles collected in Lanzhou (urban site) and its surrounding areas (rural site) in early 2023. The results revealed that from the pre-Spring Festival period to the Spring Festival period, the main pollutants at the urban site decreased significantly, while the PM2.5 and SO2 concentrations increased at the rural site. During the entire sampling period, the main particles at the urban site were organic matter (OM), secondary inorganic aerosols (SIA), and OM-SIA particles, while those at the rural site were OM, SIA, and soot particles. The degree of external mixing of single particles in both sites increased from the pre-Spring Festival period to the Spring Festival period. The proportion of the OM particles increased by 11% at the urban site, and the proportion of SIA particles increased by 24% at the rural site. During the Spring Festival, the aging of the soot particles was enhanced at the urban site and weakened at the rural site. At the urban site, the SIA particle size was more strongly correlated with the thickness of the OM coating during the pre-Spring Festival period, while the correlation was stronger at the rural site during the Spring Festival.

Characterization of summertime single aerosol particles in Chengdu (China): Interannual evolution and impact of COVID-19 lockdown

To investigate the interannual evolution of air pollution in summer and the impact of the COVID-19 lockdown on local pollution in Chengdu, China, single aerosol particles were continuously measured in three summer periods: the regular period in 2020 (RP2020); the regular period in 2022 (RP2022); and the lockdown period in 2022 (LP2022). It was found that, from RP2020 to RP2022, the mass concentrations of PM2.5, PM10, SO2 and NO2 decreased by 25.6 %, 24.7 %, 28.8 % and 38.5 %, respectively, while the concentration of O3 increased by 11.0 %. Affected by regional transport, there was no significant decrease in the concentrations of various pollutants during LP2022. All single aerosol particles could be classified into seven categories: vehicle emissions (VE), dust, biomass burning (BB), coal combustion (CC), K mixed with sulfate (KSO4), K mixed with nitrate (KNO3) and K mixed with sulfate and nitrate (KSN) particles. From RP2020 to RP2022, the contributions of BB and CC particles decreased by 12.1 % and 0.9 %, respectively, while VE and dust particles increased by 3.6 % and 2.5 %, respectively; and compared to RP2022, the contributions of VE, dust and CC particles in LP2022 decreased by 22.2 %, 11.0 % and 12.7 %, respectively. The high PM2.5 pollution events in RP2020 and RP2022 were mainly caused by combustion sources (BB and CC, 51.6 %) and VE (38.3 %) particles, respectively, while the pollution event in LP2022 was contributed by BB (27.0 %) and secondary inorganic (KSO4, KNO3 and KSN, 60.2 %) particles. The formation mechanisms of different pollution events were further validated by WRF-Chem results. Although the potential source areas of particles showed a shrinking trend from RP2020 to RP2022, regional transport still caused high PM2.5 pollution events during LP2022. Photochemical processes dominated the formation of KSO4 particles, while the KNO3 and KSN particles were mainly generated by liquid-phase reactions, and this effect increased year by year.

Characterization of carbonaceous particles by single particle aerosol mass spectrometer in the urban area of Chengdu, China

Carbonaceous particles are an important chemical component of atmospheric fine particles. In this study, a single particle aerosol mass spectrometer was used to continuously measure the carbonaceous particles in Chengdu, one of the megacities most affected by haze in China, from January 22 to March 3, 2021. During the observation period, the average mass concentration of PM2.5 was 62.3 ± 37.2 μg m-3, and the emissions from mobile sources were more prominent. Carbonaceous particles accounted for 68.6% of the total particles and could be classified into 10 categories, with elemental carbon (EC) mixed with sulfate (EC-S) particles making the highest contribution (33.1%). EC particles rich in secondary components and organic carbon (OC) particles rich in secondary component exhibited different diurnal variations, suggesting different sources and mixing mechanisms. From "excellent" to "polluted" days, the contributions of EC-S, EC mixed with sulfate and nitrate (EC-SN) and OC mixed with EC (OC-EC) particles increased by 9.8%, 4.5% and 6.6%, respectively, and thus these particles are key targets for future pollution control. The potential source contribution of the southwest area was stronger than that of other areas, and the potential contribution of regional transport to EC-related particles was stronger than to OC-related particles. Most particles were highly mixed with sulfate or nitrate, and the level of secondary mixing further enhanced as pollution worsened.

Long-term spatiotemporal evolution and coordinated control of air pollutants in a typical mega-mountain city of Cheng-Yu region under the "dual carbon" goal

Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for megacities to formulate relevant air pollution prevention and control measures and achieve carbon neutrality goals. Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain-city in China, environmental problems are complex and sensitive. This research aims to investigate the exceeding standard levels and spatio-temporal evolution of criteria pollutants between 2014 and 2020. The results indicated that PM10, PM2.5, CO and SO2 were decreased significantly by 45.91%, 52.86%, 38.89% and 66.67%, respectively. Conversely, the concentration of pollutant O3 present a fluctuating growth and found a "seesaw" phenomenon between it and PM. Furthermore, PM and O3 are highest in winter and summer, respectively. SO2, NO2, CO, and PM showed a "U-shaped", and O3 showed an inverted "U-shaped" seasonal variation. PM and O3 concentrations are still far behind the WHO, 2021AQGs standards. Significant spatial heterogeneity was observed in air pollution distribution. These results are of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, and formulate a regional carbon peaking roadmap under climate coordination. Besides, it can provide an important platform for exploring air pollution in typical terrain around the world and provide references for related epidemiological research.Implications: Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain city, environmental problems are complex and sensitive. Under the background of the "14th Five-Year Plan", the construction of the "Cheng-Yu Dual-City Economic Circle" and the "Dual-Carbon" goal, this article comprehensively discussed the annual and seasonal excess levels and spatiotemporal evolution of pollutants under the multiple policy and the newest international standards (WHO,2021AQG) backgrounds from 2014 to 2020 in Chongqing. Furthermore, suggestions and measures related to the collaborative management of pollutants were discussed. Finally, limitations and recommendations were also put forward.Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for cities to formulate relevant air pollution control measures and achieve carbon neutrality goals. This study is of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, study and formulate a regional carbon peaking roadmap under climate coordination and an action plan for sustained improvement of air quality.In addition, this research can advanced our understanding of air pollution in complex terrain. Furthermore, it also promote the construction of the China national strategic Cheng-Yu economic circle and build a beautiful west. Moreover, it provides scientific insights for local policymakers to guide smart urban planning, industrial layout, energy structure, and transportation planning to improve air quality throughout the Cheng-Yu region. Finally, this is also conducive to future scientific research in other regions of China, and even megacities with complex terrain in the world.

Impact of COVID-19 lockdown on air quality analyzed through machine learning techniques

After February 2020, the majority of the world's governments decided to implement a lockdown in order to limit the spread of the deadly COVID-19 virus. This restriction improved air quality by reducing emissions of particular atmospheric pollutants from industrial and vehicular traffic. In this study, we look at how the COVID-19 shutdown influenced the air quality in Lahore, Pakistan. HAC Agri Limited, Dawn Food Head Office, Phase 8-DHA, and Zeenat Block in Lahore were chosen to give historical data on the concentrations of many pollutants, including PM2.5, PM10 (particulate matter), NO2 (nitrogen dioxide), and O3 (ozone). We use a variety of models, including decision tree, SVR, random forest, ARIMA, CNN, N-BEATS, and LSTM, to compare and forecast air quality. Using machine learning methods, we looked at how each pollutant's levels changed during the lockdown. It has been shown that LSTM estimates the amounts of each pollutant during the lockout more precisely than other models. The results show that during the lockdown, the concentration of atmospheric pollutants decreased, and the air quality index improved by around 20%. The results also show a 42% drop in PM2.5 concentration, a 72% drop in PM10 concentration, a 29% drop in NO2 concentration, and an increase of 20% in O3 concentration. The machine learning models are assessed using the RMSE, MAE, and R-SQUARE values. The LSTM measures NO2 at 4.35%, O3 at 8.2%, PM2.5 at 4.46%, and PM10 at 8.58% in terms of MAE. It is observed that the LSTM model outperformed with the fewest errors when the projected values are compared with the actual values.

Characterization and source apportionment for light absorption amplification of black carbon at an urban site in eastern China

The mass absorption efficiency (MAE) of black carbon (BC) could be amplified by both internal mixing and the lensing effect from non-absorbing coating, which could intensify the global warming effect of BC. In this study, a two-year-long continuous campaign with measurements of aerosol optical properties and chemical composition were conducted in Nanjing, a typical polluted city in the Yangtze River Delta (YRD) region. Relatively large MAE values were observed in 2016, and the high BC internal mixing level could be the main cause. The strong positive correlation between the ratio of non-absorbing particulate matter (NAPM) over elemental carbon (EC) and the MAE value indicated that the coating thickness of BC largely promotes its light absorption ability. The impacts of chemical component coating on MAE amplification in autumn and winter were greater than in other seasons. Multiple linear regression was performed to estimate the MAE amplification effect by internal mixing and the coating of different chemical components. Nitrate coating had the strongest impact on MAE amplification, followed by organic matter. The effects of organic matter and nitrate coatings on MAE amplification increased with the internal mixing index (IMI). Based on the positive matrix factorization (PMF) model, it was found that large decrease in the contribution of industrial emissions and coal combustion to PM_2.5 from 2016 to 2017 was the main cause for MAE reduction. The novel statistical model developed in this study could be a useful tool to separate the impacts of internal mixing and non-absorbing coating.