Particle size distribution, water soluble ions, and black carbon (BC) concentration in a long-term haze-fog episode were measured using a wide-range particle spectrometer (WPS), a monitor for aerosols and gases (MARGA), and an aethalometer (AE33) in Nanjing from 16 to 27 November, 2018. The observation included five processes of clean, mist, mix, haze, and fog. Combined with meteorological elements, the HYSPLIT model, and the IMPROVE model, we analyzed the particle size distribution, chemical composition, and optical properties of aerosols in different processes. The particle number size distribution (PNSD) in five processes differed: It was bimodal in mist and fog and unimodal in clean, mix, and haze. The particle surface area size distribution (PSSD) in different processes showed a bimodal distribution, and the second peak of the mix and fog processes shifted to a larger particle size at 480 nm. The dominant air masses in five processes differed and primarily originated in the northeast direction in the clean process and the southeast direction in the haze process. In the mist, mix, and fog processes local air masses dominated. NO₃⁻ was the primary component of water soluble ions, with the lowest proportion of 45.6% in the clean process and the highest proportion of 53.0% in the mix process. The ratio of NH₄⁺ in the different processes was stable at approximately 23%. The ratio of SO₄²⁻ in the clean process was 26.2%, and the ratio of other processes was approximately 20%. The average concentration of BC in the fog processes was 10,119 ng·m⁻³, which was 3.55, 1.80, 1.60, and 1.46 times that in the processes of clean, mist, mix, and haze, respectively. In the different processes, BC was primarily based on liquid fuel combustion. NO₃⁻, SO₄²⁻, and BC were the main contributors to the atmospheric extinction coefficient and contributed more than 90% in different processes. NO₃⁻ contributed 398.43 Mm⁻¹ in the mix process, and SO₄²⁻ and BC contributed 167.90 Mm⁻¹ and 101.19 Mm⁻¹, respectively, during the fog process.

To study the optical properties of background atmospheric aerosols in East China, we carried out observations of the physical, chemical and optical properties of atmospheric aerosols at the summit of Mount Tai (Mt. Tai, 1533.7 m above sea level) from 13 May to 25 June 2017. The results show that the average scattering coefficient ( ${\mathsf{\sigma }}_{\mathrm{sca},550}$ ) at 550 nm of the aerosols at the summit of Mt. Tai is 40.3 Mm⁻¹, and the average absorption coefficient ( ${\mathsf{\sigma }}_{\mathrm{abs},550}$ ) at 550 nm is 16.0 Mm⁻¹. The complex refractive index of aerosols is a key parameter for aerosol retrieval and modeling. There are few studies on the equivalent complex refractive index of aerosol in the Taishan area. We calculated the aerosol equivalent complex refractive index using the observed aerosol scattering coefficients, absorption coefficients and particle size distribution data, providing more data support for future modeling in this region. The real part (n) of the complex refractive index at 550 nm of aerosol ranges from 1.31 to 1.98 (mostly under 1.50), with an average value of 1.38, while the imaginary part (k) ranges from 0.014 to 0.251 (less than 0.10 for over 95% samples), with an average value of 0.040. The analysis of the n and k of the aerosol average complex refractive index shows that the scattering properties of the aerosols at the summit of Mt. Tai are relatively weak and the absorption properties are relatively strong when compared with those of other kinds of aerosols. The k of the aerosol complex refractive index at the summit of Mt. Tai has strong correlations with the wind speed, temperature, as revealed by the correlation analysis.

Despite the yearly decline in PM_2.5 in China, surface ozone has been rapidly increasing recently, which makes it imperative to coordinate and control both PM_2.5 and ozone in the atmosphere. This study utilized the data of pollutant concentrations and meteorological elements during 2015 to 2018 in Nanjing, China to analyze the daily correlation between black carbon and ozone (CBO), and the distribution of the pollutant concentrations under different levels of CBO. Besides, the diurnal variations of pollutant concentrations and meteorological elements under high positive and negative CBO were discussed and compared. The results show that the percentage of positive CBO had been increasing at the average rate of 7.1%/year, and it was 38.7% in summer on average, nearly twice of that in other seasons (19.2%). The average black carbon (BC), PM_2.5 and NO₂ under positive CBO was lower than those under negative CBO. It is noticeable that the surface ozone began to ascend when CBO was up to 0.2, with PM_2.5 and NO₂ decreasing and BC remaining steady. Under negative CBO, pollutant concentrations and meteorological elements showed obvious diurnal variations: BC showed a double-peak pattern and surface ozone, PM_2.5, SO₂ and CO showed single-peak patterns and NO₂ showed a trough from 10:00 to 19:00. Wind speed and visibility showed a single-peak pattern with little seasonal difference. Relative humidity rose first, then it lowered and then it rose. Under positive CBO, the patterns of diurnal variations became less obvious, and some of them even showed no patterns, but just fluctuated at a certain level.

Using an AE-33 Aethalometer, surface air pollution monitoring data, radiosonde data, and conventional meteorological observation data, the characteristics and influencing factors of black carbon (BC) pollution under PM_2.5 and O₃ pollution in Nanjing were comprehensively analyzed. The results show that the air quality saw an apparent trend of improvement from 2015 to 2020, and the number of days with excellent air quality increased by 38.2% from 2015 to 2020. The number of days when the dominant pollutant was PM_2.5 decreased each year to only 18 days in 2020, with an annual rate of decline of 16.0% from 2015 to 2020. The number of days when the dominant pollutant was O₃ increased, reaching a maximum for the 6-year period of 78 days in 2019, with an annual rate of increase of 11.1% in 2015–2019. The average mass concentration of BC when the dominant pollutant was PM_2.5 in slight, moderate, and heavy pollution decreased in 2015–2016 and then showed an increasing yearly trend in 2016–2018, with annual rates of increase of 73.8%, 105.5%, and 156.3%, respectively, reaching a maximum in 2018 and then starting to decrease thereafter. With PM_2.5, the slight pollution and moderate pollution BC mass concentrations were mainly influenced by the height of the inversion layer. The average BC mass concentrations in the case of slight and moderate pollution with O₃ as the dominant pollutant decreased significantly from 2015 to 2016, and then increased yearly from 2016 to 2019, with annual rates of increase of 112.2% and 138.6%, respectively, reaching a maximum in 2019 and then decreasing from 2020. The BC mass concentration was significantly negatively correlated with wind speed in both light and moderate O₃ pollution, with correlation coefficients of −0.79 and −0.68, respectively. The seasonal variation and dominant influencing factors of BC differed when PM_2.5 and O₃ were the dominant pollutants. When PM_2.5 was the dominant pollutant, the seasonal variation in the BC for slight pollution was winter > autumn > summer > spring, and for moderate pollution and heavy pollution was autumn > winter > spring, which were mainly affected by the inversion stratification difference and wind speed. When O₃ was the dominant pollutant, the seasonal variation in BC under slight pollution was autumn > summer > spring, and for moderate pollution, it was spring > summer > autumn, which were mainly affected by the wind speed. Studying the evolution of BC in air pollution under different dominant pollutants is important to further improve the capability and level of global climate change research and predictions and can provide a scientific basis for assessing their impact on the environment, health, and climate.