Fine particulate matter with aerodynamic diameters ≤2.5 µm (PM_2.5) has adverse effects on human health and the atmospheric environment. The estimation of surface PM_2.5 concentrations has made intensive use of satellite-derived aerosol products. However, it has been a great challenge to obtain high-quality and high-resolution PM_2.5 data from both ground and satellite observations, which is essential to monitor air pollution over small-scale areas such as metropolitan regions. Here, the space–time extremely randomized trees (STET) model was enhanced by integrating updated spatiotemporal information and additional auxiliary data to improve the spatial resolution and overall accuracy of PM_2.5 estimates across China. To this end, the newly released Moderate Resolution Imaging Spectroradiometer Multi-Angle Implementation of Atmospheric Correction AOD product, along with meteorological, topographical and land-use data and pollution emissions, was input to the STET model, and daily 1 km PM_2.5 maps for 2018 covering mainland China were produced. The STET model performed well, with a high out-of-sample (out-of-station) cross-validation coefficient of determination (R²) of 0.89 (0.88), a low root-mean-square error of 10.33 (10.93) µg m⁻³, a small mean absolute error of 6.69 (7.15) µg m⁻³ and a small mean relative error of 21.28 % (23.69 %). In particular, the model captured well the PM_2.5 concentrations at both regional and individual site scales. The North China Plain, the Sichuan Basin and Xinjiang Province always featured high PM_2.5 pollution levels, especially in winter. The STET model outperformed most models presented in previous related studies, with a strong predictive power (e.g., monthly R²=0.80), which can be used to estimate historical PM_2.5 records. More importantly, this study provides a new approach for obtaining high-resolution and high-quality PM_2.5 dataset across mainland China (i.e., ChinaHighPM_2.5), important for air pollution studies focused on urban areas.

Knowledge of aerosol size and composition is important for determining radiative forcing effects of aerosols, identifying aerosol sources and improving aerosol satellite retrieval algorithms. The ability to extrapolate aerosol size and composition, or type, from intensive aerosol optical properties can help expand the current knowledge of spatiotemporal variability in aerosol type globally, particularly where chemical composition measurements do not exist concurrently with optical property measurements. This study uses medians of the scattering Ångström exponent (SAE), absorption Ångström exponent (AAE) and single scattering albedo (SSA) from 24 stations within the NOAA/ESRL Federated Aerosol Monitoring Network to infer aerosol type using previously published aerosol classification schemes.Three methods are implemented to obtain a best estimate of dominant aerosol type at each station using aerosol optical properties. The first method plots station medians into an AAE vs. SAE plot space, so that a unique combination of intensive properties corresponds with an aerosol type. The second typing method expands on the first by introducing a multivariate cluster analysis, which aims to group stations with similar optical characteristics and thus similar dominant aerosol type. The third and final classification method pairs 3-day backward air mass trajectories with median aerosol optical properties to explore the relationship between trajectory origin (proxy for likely aerosol type) and aerosol intensive parameters, while allowing for multiple dominant aerosol types at each station.The three aerosol classification methods have some common, and thus robust, results. In general, estimating dominant aerosol type using optical properties is best suited for site locations with a stable and homogenous aerosol population, particularly continental polluted (carbonaceous aerosol), marine polluted (carbonaceous aerosol mixed with sea salt) and continental dust/biomass sites (dust and carbonaceous aerosol); however, current classification schemes perform poorly when predicting dominant aerosol type at remote marine and Arctic sites and at stations with more complex locations and topography where variable aerosol populations are not well represented by median optical properties. Although the aerosol classification methods presented here provide new ways to reduce ambiguity in typing schemes, there is more work needed to find aerosol typing methods that are useful for a larger range of geographic locations and aerosol populations.

Tropospheric ozone is an important atmospheric oxidant, greenhouse gas and atmospheric pollutant at the same time. The oxidation capacity of the atmosphere, climate, human and vegetation health can be impacted by the increase of the ozone level. Therefore, long-term determination of trends of baseline ozone is highly needed information for environmental and climate change assessment. So far, studies on the long-term trends of ozone at representative sites are mainly available for European and North American sites. Similar studies are lacking for China and many other developing countries. Measurements of surface ozone were carried out at a baseline Global Atmospheric Watch (GAW) station in the north-eastern Tibetan Plateau region (Mt Waliguan, 36°17′ N, 100°54′ E, 3816 m a.s.l.) for the period of 1994 to 2013. To uncover the variation characteristics, long-term trends and influencing factors of surface ozone at this remote site in western China, a two-part study has been carried out, with this part focusing on the overall characteristics of diurnal, seasonal and long-term variations and the trends of surface ozone. To obtain reliable ozone trends, we performed the Mann–Kendall trend test and the Hilbert–Huang transform (HHT) analysis on the ozone data. Our results confirm that the mountain-valley breeze plays an important role in the diurnal cycle of surface ozone at Waliguan, resulting in higher ozone values during the night and lower ones during the day, as was previously reported. Systematic diurnal and seasonal variations were found in mountain-valley breezes at the site, which were used in defining season-dependent daytime and nighttime periods for trend calculations. Significant positive trends in surface ozone were detected for both daytime (0.24 ± 0.16 ppbv year⁻¹) and nighttime (0.28 ± 0.17 ppbv year⁻¹). The largest nighttime increasing rate occurred in autumn (0.29 ± 0.11 ppbv year⁻¹), followed by spring (0.24 ± 0.12 ppbv year⁻¹), summer (0.22 ± 0.20 ppbv year⁻¹) and winter (0.13 ± 0.10 ppbv year⁻¹), respectively. The HHT spectral analysis identified four different stages with different positive trends, with the largest increase occurring around May 2000 and October 2010. The HHT results suggest that there were 2–4a, 7a and 11a periodicities in the time series of surface ozone at Waliguan. The results of this study can be used for assessments of climate and environment change and in the validation of chemistry–climate models.

The aerosol liquid water (ALW) content (ALWC), an important component of atmospheric particles, has a significant effect on atmospheric optical properties, visibility and multiphase chemical reactions. In this study, ALWC is determined from aerosol hygroscopic growth factor (GF) and particle number size distribution (PNSD) measurements and is also simulated by ISORROPIA II, a thermodynamic equilibrium model, with measured aerosol chemical composition data taken at an urban site in Beijing from 8 November to 15 December 2017. Rich measurements made during the experiment concerning virtually all aerosol properties allow us not only to derive the ALWC but also to study the contributions by various species for which little has been done in this region. The simulated ALWC including the contribution of organics and the calculated ALWC are highly correlated (coefficient of determination R²=0.92). The ALWC contributed by organics (ALWC_Org) accounts for 30 %±22 % of the total ALWC during the sampling period. These results suggest a significant contribution of organics to ALWC, which is rather different from previous studies that showed negligible contributions by organics. Our results also show that ALWC correlates well with the mass concentrations of sulfate, nitrate, and secondary organic aerosols (SOAs) (R²=0.66, 0.56 and 0.60, respectively). We further noted that accumulation mode particles play a key role in determining ALWC, dominating among all the aerosol modes. ALWC is an exponential function of ambient relative humidity (RH), whose strong diurnal variation influence the diurnal variation of ALWC. However, there is a 3 h lag between the extremes of ALWC and RH values, due to the diurnal variations in PNSD and aerosol chemical composition. Finally, a case study reveals that ALWC_Org plays an important role in the formation of secondary aerosols through multiphase reactions at the initial stage of a heavy-haze episode.

The effects of aerosols on visibility through scattering and absorption of light and on climate through altering cloud droplet concentration are closely associated with their hygroscopic properties. Here, based on field campaigns in winter and summer in Beijing, we compare the size-resolved hygroscopic parameter (κ_gf) of ambient fine particles derived by an HTDMA (hygroscopic tandem differential mobility analyzer) to that (denoted as κ_chem) calculated by an HR-ToF-AMS (high-resolution time-of-flight aerosol mass spectrometer) measurements using a simple rule with the hypothesis of uniform internal mixing of aerosol particles. We mainly focus on contrasting the disparity of κ_gf and κ_chem between summer and winter to reveal the impact of atmospheric processes/emission sources on aerosol hygroscopicity and to evaluate the uncertainty in estimating particle hygroscopicity with the hypothesis. We show that, in summer, the κ_chem for 110, 150, and 200 nm particles was on average ∼10 %–12 % lower than κ_gf, with the greatest difference between the values observed around noontime when aerosols experience rapid photochemical aging. In winter, no apparent disparity between κ_chem and κ_gf is observed for those >100 nm particles around noontime, but the κ_chem is much higher than κ_gf in the late afternoon when ambient aerosols are greatly influenced by local traffic and cooking sources. By comparing with the observation from the other two sites (Xingtai, Hebei and Xinzhou, Shanxi) of north China, we verify that atmospheric photochemical aging of aerosols enhances their hygroscopicity and leads to 10 %–20 % underestimation in κ_chem if using the uniform internal mixing assumption. The effect is found more significant for these >100 nm particles observed in remote or clean regions. The lower κ_chem likely resulted from multiple impacts of inappropriate application of the density and hygroscopic parameter of organic aerosols in the calculation, as well as influences from chemical interaction between organic and inorganic compounds on the overall hygroscopicity of mixed particles. We also find that local/regional primary emissions, which result in a large number of externally mixed BC (black carbon) and POA (primary organic aerosol) in urban Beijing during traffic rush hour time, cause a 20 %–40 % overestimation of the hygroscopic parameter. This is largely due to an inappropriate use of density of the BC particles that is closely associated with its morphology or the degree of its aging. The results show that the calculation can be improved by applying an effective density of fresh BC (0.25–0.45 g cm⁻³) in the mixing rule assumption. Our study suggests that it is critical to measure the effective density and morphology of ambient BC, in particular in those regions with influences of rapid secondary conversion/aging processes and local sources, so as to accurately parameterize the effect of BC aging on particle hygroscopicity.

A new mechanism of new particle formation (NPF) is investigated using comprehensive measurements of aerosol physicochemical quantities and meteorological variables made in three continents, including Beijing, China; the Southern Great Plains site in the USA; and SMEAR II Station in Hyytiälä, Finland. Despite the considerably different emissions of chemical species among the sites, a common relationship was found between the characteristics of NPF and the stability intensity. The stability parameter (ζ = Z/L, where Z is the height above ground and L is the Monin–Obukhov length) is found to play an important role; it drops significantly before NPF as the atmosphere becomes more unstable, which may serve as an indicator of nucleation bursts. As the atmosphere becomes unstable, the NPF duration is closely related to the tendency for turbulence development, which influences the evolution of the condensation sink. Presumably, the unstable atmosphere may dilute pre-existing particles, effectively reducing the condensation sink, especially at coarse mode to foster nucleation. This new mechanism is confirmed by model simulations using a molecular dynamic model that mimics the impact of turbulence development on nucleation by inducing and intensifying homogeneous nucleation events.