Persistent heavy haze episodes have repeatedly shrouded North China in recent years. Besides anthropogenic emissions, natural dust also contributes to the aerosols in this region. Through continuous observation by a dual-wavelength Raman lidar, the primary aerosol types and their contributions to air pollution in North China were determined. The following three aerosol types can be classified: natural dust, anthropogenic aerosols, and the mixture of anthropogenic aerosols and dust (polluted dust). The classification results are basically consistent with the classification results from the cloud–aerosol lidar and infrared pathfinder satellite observations (CALIPSO) satellite measurements. The relative bias of the lidar ratio between the Raman lidar and CALIPSO is less than 25% over 90% of the cases, indicating that the CALIPSO lidar ratio selection algorithm is reasonable. The classification results show that approximately 45% of aerosols below 1.8 km are contributed by polluted dust during our one year observations. The contribution of dust increased with height, from 6% at 500 m to 28% at 1,800 m, while the contribution of anthropogenic aerosols decreased from 49% to 25%. In addition, polluted dust is the major aerosol subtype below 1.0 km in spring (over 60%) and autumn (over 70%). Anthropogenic aerosols contribute more than 75% of air pollution in summer. In winter, anthropogenic aerosols prevailed (over 80%) in the lower layer, while polluted dust (around 60%) dominated the upper layer. Our results identified the primarily aerosol types to assess the contributions of anthropogenic and natural sources to air pollution in North China, and highlight that natural dust plays a crucial role in lower-layer air pollution in spring and autumn, while controlling anthropogenic aerosols will significantly improve air quality in winter.

Persistent wintertime heavy haze incidents caused by anthropogenic aerosols have repeatedly shrouded North China in recent years, while natural dust from the west and northwest of China also frequently affects air quality in this region. Through continuous observation by a multi-wavelength Raman lidar, here we found that wintertime aerosols in North China are typically characterized by a pronounced vertical stratification, where scattering nonspherical particles (dust or mixtures of dust and anthropogenic aerosols) dominated above the planetary boundary layer (PBL), and absorbing spherical particles (anthropogenic aerosols) prevailed within the PBL. This stratification is governed by meteorological conditions that strong northwesterly winds usually prevailed in the lower free troposphere, and southerly winds dominated in the PBL, producing persistent and intense haze pollution. With the increased contribution of elevated dust to the upper aerosols, the proportion of aerosol and trace gas at the surface in the whole column increased. Model results show that, besides directly deteriorating air quality, the key role of the elevated dust is to depress the development of PBL and weaken the turbulent exchange, mostly by lower level cooling and upper level heating, and it is more obvious during the dissipation stage, thus inhibiting the dissipation of heavy surface anthropogenic aerosols. The interactions of natural dust and anthropogenic aerosols under the unique topography of North China increase the surface anthropogenic aerosols and precursor gases, which may be one of the reasons why haze pollution in North China is heavier than that in other heavily polluted areas in China.

Due to considerable reductions in nitrogen oxides (NO_x), ozone trends and variations in eastern China remain inadequately understood. Long-term observations of ozone precursors were conducted to explore the factors influencing ozone trends in this region. Combined with satellite and surface measurements, we evaluated the trends in low (2nd percentile), typical (50th percentile), and peak (98th percentile) ozone concentrations in detail. Observations indicate a significant decrease in peak ozone concentrations (−0.5 % yr⁻¹), alongside an increase in low ozone concentrations (0.3 % yr⁻¹), across eastern China during May–September from 2017 to 2022. The decline in typical ozone concentrations is notably slower than that of peak ozone concentrations, which is approximately −0.02 ppb yr⁻¹ (−0.0 % yr⁻¹) during the same period. Anthropogenic emissions primarily drive trends in low and peak ozone concentrations in eastern China, though meteorological effects also play a role. Ozone formation sensitivity shifts from volatile organic compound (VOC)-limited or transitional regimes in the morning (08:00–11:00 local time, LT), when ozone concentrations rise sharply, to NO_x-limited regimes around peak concentrations (∼ 14:00 LT). The reduction in NO_x concentrations is identified as a key factor driving the decline in peak ozone concentrations, aiming to further reduce ozone exceedance days. Thus, controlling NO_x concentrations emerges as crucial for mitigating peak ozone levels. Moreover, the increase in low ozone concentrations can also be attributed to both anthropogenic emissions and meteorological factors. Our findings underscore the beneficial impacts of NO_x reduction on managing peak ozone levels. Regular changes in ozone formation sensitivity throughout the day should be considered when formulating effective ozone control policies.

Water vapor vertical profiles are important in numerical weather prediction, moisture transport, and vertical flux calculation. This study presents the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) retrieval algorithm for water vapor vertical profiles and the retrieved results are validated with corresponding independent datasets under clear sky. The retrieved Vertical Column Densities (VCDs) and surface concentrations are validated with the Aerosol Robotic Network (AERONET) and National Climatic Data Centre (NCDC) datasets, achieving good correlation coefficients (R) of 0.922 and 0.876, respectively. The retrieved vertical profiles agree well with weekly balloon-borne radiosonde measurements. Furthermore, the retrieved water vapor concentrations at different altitudes (100–2000 m) are validated with the corresponding European Centre for Medium-range Weather Forecasts (ECMWF) ERA-interim datasets, achieving a correlation coefficient (R) varying from 0.695 to 0.857. The total error budgets for the surface concentrations and VCDs are 31% and 38%, respectively. Finally, the retrieval performance of the MAX-DOAS algorithm under different aerosol loads is evaluated. High aerosol loads obstruct the retrieval of surface concentrations and VCDs, with surface concentrations more liable to severe interference from such aerosol loads. To summarize, the feasibility of detecting water vapor profiles using MAX-DOAS under clear sky is confirmed in this work.

The polarization–Raman Lidar combined sun photometer is a powerful method for separating dust and urban haze backscatter, extinction, and mass concentrations. The observation was performed in Beijing during the 2019 National Day parade, the particle depolarization ratio at 532 nm and Lidar ratio at 355 nm are 0.13 ± 0.05 and 52 ± 9 sr, respectively. It is the typical value of a mixture of dust and urban haze. Here we quantify the contributions of cross-regional transported natural dust and urban haze mass concentrations to Beijing’s air quality. There is a significant correlation between urban haze mass concentrations and surface PM₂.₅ (R = 0.74, p < 0.01). The contributions of local emissions to air pollution during the 2019 National Day parade were insignificant, mainly affected by regional transport, including urban haze in North China plain and Guanzhong Plain (Hebei, Tianjin, Shandong, and Shanxi), and dust aerosol in Mongolia regions and Xinjiang. Moreover, the trans-regional transmission of natural dust dominated the air pollution during the 2019 National Day parade, with a relative contribution to particulate matter mass concentrations exceeding 74% below 4 km. Our results highlight that controlling anthropogenic emissions over regional scales and focusing on the effects of natural dust is crucial and effective to improve Beijing’s air quality.