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A new long-term emission inventory called the Inversed Emission Inventory for Chinese Air Quality (CAQIEI) was developed in this study by assimilating surface observations from the China National Environmental Monitoring Centre (CNEMC) using an ensemble Kalman filter (EnKF) and the Nested Air Quality Prediction Modeling System. This inventory contains the constrained monthly emissions of NO x , SO 2 , CO, primary PM 2.5 , primary PM 10 , and non-methane volatile organic compounds (NMVOCs) in China from 2013 to 2020, with a horizontal resolution of 15 km × 15 km. This paper documents detailed descriptions of the assimilation system and the evaluation results for the emission inventory. The results suggest that CAQIEI can effectively reduce the biases in the a priori emission inventory, with the normalized mean biases ranging from -9.1 % to 9.5 % in the a posteriori simulation, which are significantly reduced from the biases in the a priori simulations (-45.6 % to 93.8 %). The calculated root-mean-square errors (RMSEs) (0.3 mg m -3 for CO and 9.4–21.1 µgm3 for other species, on the monthly scale) and correlation coefficients (0.76–0.94) were also improved from the a priori simulations, demonstrating good performance of the data assimilation system. Based on CAQIEI, we estimated China's total emissions (including both natural and anthropogenic emissions) of the six species in 2015 to be as follows: 25.2 Tg of NO x , 17.8 Tg of SO 2 , 465.4 Tg of CO, 15.0 Tg of PM 2.5 , 40.1 Tg of PM 10 , and 46.0 Tg of NMVOCs. From 2015 to 2020, the total emissions decreased by 54.1 % for SO 2 , 44.4 % for PM 2.5 , 33.6 % for PM 10 , 35.7 % for CO, and 15.1 % for NO x but increased by 21.0 % for NMVOCs. It is also estimated that the emission reductions were larger during 2018–2020 (from -26.6 % to -4.5 %) than during 2015–2017 (from -23.8 % to 27.6 %) for most of the species. In particular, the total Chinese NO x and NMVOC emissions were shown to increase during 2015–2017, especially over the Fenwei Plain area (FW), where the emissions of particulate matter (PM) also increased. The situation changed during 2018–2020, when the upward trends were contained and reversed to downward trends for the total emissions of both NO x and NMVOCs and the PM emissions over FW. This suggests that the emission control policies may be improved in the 2018–2020 action plan. We also compared CAQIEI with other air pollutant emission inventories in China, which verified our inversion results in terms of the total emissions of NO x , SO 2 , and NMVOCs and more importantly identified the potential uncertainties in current emission inventories. Firstly, CAQIEI suggested higher CO emissions in China, with CO emissions estimated by CAQIEI (426.8 Tg) being more than twice the amounts in previous inventories (120.7–237.7 Tg). Significantly higher emissions were also suggested over western and northeastern China for the other air pollutants. Secondly, CAQIEI suggested higher NMVOC emissions than previous emission inventories by about 30.4 %–81.4 % over the North China Plain (NCP) but suggested lower NMVOC emissions by about 27.6 %–0.0 % over southeastern China (SE). Thirdly, CAQIEI suggested lower emission reduction rates during 2015–2018 than previous emission inventories for most species, except for CO. In particular, China's NMVOC emissions were shown to have increased by 26.6 % from 2015 to 2018, especially over NCP (by 38.0 %), northeastern China (by 38.3 %), and central China (60.0 %). These results provide us with new insights into the complex variations in air pollutant emissions in China during two recent clean-air actions, which has the potential to improve our understanding of air pollutant emissions in China and their impacts on air quality. All of the datasets are available at 10.57760/sciencedb.13151 (Kong et al., 2023a). [ABSTRACT FROM AUTHOR]

The formation process of in‐cloud aqueous‐phase secondary organic matter (aqSOM) and its characteristics are unclear. Herein, water‐soluble inorganic ions, oxalate, and water‐soluble organic carbon (WSOC) were determined in cloud water and aerosol (PM2.5) samples simultaneously collected at a remote mountain site in southern China during spring 2018 and winter 2020. The molecular compositions of water‐soluble organic matter (WSOM) in cloud water and aerosols were analyzed by a Fourier transform ion cyclotron resonance mass spectrometer in negative electrospray ionization (ESI‐) mode. The results showed that the mean concentration of WSOC was 6.27–8.54 mg C L−1 in cloud water and 0.60–1.37 μg C m−3 in aerosols. The strong correlation observed between WSOM and aqueous secondary matter (e.g., NO3− and oxalate), the positive matrix factorization results, and the elevated WSOM/K+ ratios observed in cloud water suggested enhanced aqSOM formation in cloud water. According to random forest analysis, the factors related to in‐cloud WSOM variation mainly included secondary ions, K+, cloud water pH, and atmospheric NOx. Additionally, 37 characteristic in‐cloud aqSOM molecules, classified as ‐Ox, ‐NOx, ‐N2Ox, and ‐N1‐2OxS, mainly consisting of dicarboxylic acids, nitrophenols, and dinitrophenols, were identified using linear discriminant analysis effect size (LefSe). The characteristic N‐ and S‐containing molecules in in‐cloud aqSOM with carbon numbers >10 had low or extremely low volatility; therefore, they might contribute to secondary organic aerosol formation after droplet evaporation. The results revealed the modifying effects of in‐cloud processes on aerosol organic composition at the molecular level and could improve our understanding of aerosol–cloud interactions. Plain Language Summary: In this study, we determined the water‐soluble ion, water‐soluble organic matter (WSOM) and organic molecular composition of cloud water and aerosol samples collected at a remote mountain site in southern China. The results indicated the formation of secondary organic matter (SOM) in cloud water, the proportion of which in total WSOM was >50%. In addition, the characteristic molecules of SOM in cloud water were identified, some of which had low or extremely low volatility and might remain in the particulate phase after droplet evaporation. This work advanced our understanding of secondary organic aerosol formation in cloud water and its implications for the climate and the environment. Key Points: The proportion of in‐cloud aqueous‐phase secondary organic matter in WSOM was >50%Some molecules, for example, diacids and dinitrophenols, were identified as characteristic molecules of in‐cloud secondary organic matterMolecules with C numbers >10 formed by in‐cloud processes had low volatility [ABSTRACT FROM AUTHOR]

Ship emission impacts ambient air quality, especially in coastal regions, by emitting air pollutants such as fine particles, nitrogen oxides (NOx), and sulfur dioxide (SO2), yet its contributions to volatile organic compounds (VOCs) and the formation of secondary organic aerosol (SOA) and ozone (O3) are much less constrained with the challenge in distinguish ship emission from land diesel emission. In this study, we conducted a 1‐year online measurement of VOCs with a 1‐hr resolution at a coastal site in south China's Pearl River Delta region, which holds three of the world's top 10 container ports. The results revealed that C10–C12 n‐alkanes, as typical diesel‐related emission tracers, were significantly enhanced and strongly related to oceanic air masses. Receptor modeling revealed two diesel‐related sources of land diesel emission and ship emission, which could be differentiated based on their source profiles, seasonal trends and air mass back trajectories. Ship emissions contributed 6.4%, 5.0%, and 13.6% of total VOC mixing ratios, ozone formation potentials (OFPs), and secondary organic aerosol formation potentials (SOAFPs), while these percentages were 3.4%, 14.7%, and 15.9% for land diesel emission, respectively. In particular, in July, ship emissions could contribute 21.7%, 14.6%, and 31.2% of VOCs, OFPs, and SOAFPs, respectively. Our results highlight the important contribution of diesel‐related emission VOCs in forming O3 and SOA in coastal regions, and ship emission is a non‐negligible source of VOCs, particularly after the strict control of land emission sources. Plain Language Summary: Ships emit pollutants like fine particles, nitrogen oxides (NOx), sulfur dioxide (SO2), and volatile organic compounds (VOCs), impacting significantly on air quality in coastal areas. Ship‐emitted VOCs are potential precursors of secondary organic aerosol (SOA) and ozone (O3), yet its contribution to ambient VOCs even in coastal areas is highly uncertain based on bottom‐up estimates. Meanwhile, observation‐based source attribution often fails to successfully differentiate between land‐based diesel emissions and ship emissions. Here we carried out a year‐long online monitoring of VOCs at a coastal site in south China, to explore the contribution of ship emissions to VOCs by receptor modeling in consideration of air mass trajectories. We used concentration‐weighted trajectory (CWT) and air mass cluster analysis for C10–C12 n‐alkanes, which are typical diesel emission tracers, to distinguish ship emission from land‐based diesel emission. Results revealed that ship emissions on average could accounted for 6.4% of total VOCs, 5.0% of ozone formation potentials, and 13.6% of secondary organic aerosol formation potential, and in particular, these percentages could reach 21.7%, 14.6%, and 31.2% in July. This study highlights the importance of reducing ship emissions to improve air quality in coastal regions. Key Points: One‐year online monitoring of VOCs at a coastal site reveals relatively higher C10‐C12 alkanes due to diesel‐related emissionsShip and land‐diesel emissions are differentiated based on air mass back trajectories and source profilesShip emissions contributed substantially to VOC mixing ratios, OFPs and SOAFPs especially in July when air masses were mostly from the ocean [ABSTRACT FROM AUTHOR]

Biomass burning organic aerosol (BBOA) impacts significantly on climate directly through scattering and absorbing solar radiation and indirectly through acting as cloud condensation nuclei. However, fundamental parameters in the simulation of BBOA radiative effects and cloud activities such as size distribution and refractive index remain poorly parameterized in models. In this study, biomass burning events with high combustion efficiency characterized by a high black carbon (BC) to BBOA ratio (0.22 on average) were frequently observed during autumn in the Pearl River Delta region, China. An improved absorption Ångström exponent (AAE) ratio method considering both variations and spectral dependence of black carbon AAE was proposed to differentiate brown carbon (BrC) absorptions from total aerosol absorptions. BBOA size distributions, mass scattering and absorption efficiency were retrieved based on the changes in aerosol number size distribution, scattering coefficients and derived BrC absorptions that occurred with BBOA spikes. Geometric mean diameter of BBOA volume size distribution Dgv depended largely on combustion conditions, ranging from 245 to 505 nm, and a linear relationship between Dgv and ΔBC/ΔBBOA ​​​​​​​ was achieved. The retrieved real part of the BBOA refractive index ranges from 1.47 to 1.64, with evidence showing that its variations might depend largely on combustion efficiency, which is rarely investigated in existing literature but which however requires further comprehensive investigations. Retrieved imaginary parts of BBOA refractive index (mi,BBOA) correlated highly with ΔBC/ΔBBOA (R>0.88) but differ a lot from previous parameterization schemes. The reason behind the inconsistency might be that single formula parameterizations of mi,BBOA over the whole BC/BBOA range were used in previous studies which might deviate substantially for specific BC/BBOA ranges. Thus, a new scheme that parameterizes wavelength-dependent mi,BBOA was presented, which filled the gap for field-based BBOA absorptivity parameterizations of ​​​​​​​BC/BBOA >0.1. These findings have significant implications for simulating BBOA climate effects and suggest that linking both BBOA refractive index and BBOA volume size distributions to BC content might be a feasible and a good choice for climate models. [ABSTRACT FROM AUTHOR]

While the formation and evolution of nitrate in airborne particles are extensively investigated, little is known about the processing of nitrate in clouds. Here we present a detailed investigation on the in-cloud formation of nitrate, based on the size-resolved mixing state of nitrate in the individual cloud residual and cloud-free particles obtained by single particle mass spectrometry, and also the mass concentrations of nitrate in the cloud water and PM 2.5 at a mountain site (1690 m a.s.l. – above sea level) in southern China. The results show a significant enhancement of nitrate mass fraction and relative intensity of nitrate in the cloud water and the cloud residual particles, respectively, reflecting a critical role of in-cloud processing in the formation of nitrate. We first exclude the gas-phase scavenging of HNO 3 and the facilitated activation of nitrate-containing particles as the major contribution for the enhanced nitrate, according to the size distribution of nitrate in individual particles. Based on regression analysis and theoretical calculations, we then highlight the role of N 2 O 5 hydrolysis in the in-cloud formation of nitrate, even during the daytime, attributed to the diminished light in clouds. Nitrate is highly related (R2= ∼ 0.6) to the variations in [NO x ][O 3 ], temperature, and droplet surface area in clouds. Accounting for droplet surface area greatly enhances the predictability of the observed nitrate, compared with using [NO x ][O 3 ] and temperature. The substantial contribution of N 2 O 5 hydrolysis to nitrate in clouds with diminished light during the daytime can be reproduced by a multiphase chemical box model. Assuming a photolysis rate at 30 % of the default setting, the overall contribution of N 2 O 5 hydrolysis pathway to nitrate formation increases by ∼ 20 % in clouds. Given that N 2 O 5 hydrolysis acts as a major sink of NO x in the atmosphere, further model updates would improve our understanding about the processes contributing to nitrate production in cloud and the cycling of odd nitrogen. [ABSTRACT FROM AUTHOR]

Organic aerosol (OA) has a significant contribution to cloud formation and hence climate change. However, high uncertainties still exist in its impact on global climate, owing to the varying physical properties affected by the complex formation and aging processes. In this study, the hygroscopicity, volatility, cloud condensation nuclei (CCN) activity, and chemical composition of particles were measured using a series of online instruments at a rural site in the Pearl River Delta (PRD) region of China in fall 2019. During the campaign, the average hygroscopicity of OA (κOA) increased from 0.058 at 30 nm to 0.09 at 200 nm , suggesting a higher oxidation state of OA at larger particle sizes, supported by a higher fraction of extremely low volatility OA (ELVOA) for larger size particles. Significantly different diurnal patterns of κOA were observed between Aitken mode particles and accumulation mode particles. For Aitken mode particles (30–100 nm), the κOA values showed daily minima (0.02–0.07) during daytime, while the accumulation mode exhibited a daytime peak (∼ 0.09). Coincidently, a daytime peak was observed for both aged biomass burning organic aerosol (aBBOA) and less oxygenated organic aerosol (LOOA) based on source apportionment, which was attributed to the aging processes and gas–particle partitioning through photochemical reactions. In addition, the fraction of semi-volatile OA (SVOA) was higher at all measured sizes during daytime than during nighttime. These results indicate that the formation of secondary OA (SOA) through gas–particle partitioning can generally occur at all diameters, while the aging processes of pre-existing particles are more dominated in the accumulation mode. Furthermore, we found that applying a fixed κOA value (0.1) could lead to an overestimation of the CCN number concentration (NCCN) up to 12 %–19 % at 0.1 %–0.7 % supersaturation (SS), which was more obvious at higher SS during daytime. Better prediction of NCCN could be achieved by using size-resolved diurnal κOA , which indicates that the size dependence and diurnal variations in κOA can strongly affect the NCCN at different SS values. Our results highlight the need for accurately evaluating the atmospheric evolution of OA at different size ranges and their impact on the physicochemical properties and hence climate effects. [ABSTRACT FROM AUTHOR]

Atmospheric brown carbon (BrC) makes a substantial contribution to aerosol light absorption and thus global radiative forcing. Although BrC may change the lifetime of the clouds and ultimately affect precipitation, little is known regarding the optical properties and formation of BrC in the clouds. In the present study, the light-absorption properties of cloud droplet residual (cloud RES) were measured by coupled a ground-based counterflow virtual impactor (GCVI) and an aethalometer (AE-33), in addition to the cloud interstitial (cloud INT) and ambient (cloud-free) particles by PM 2.5 inlet-AE-33 at Mt. Tianjing (1690 m a.s.l.), a remote mountain site in southern China, from November to December 2020. Meanwhile, the light-absorption and fluorescence properties of water-soluble organic carbon (WSOC) in the collected cloud water and PM 2.5 samples were also obtained, associated with the concentration of water-soluble ions. The mean light-absorption coefficient (Abs 370) of the cloud RES, cloud INT, and cloud-free particles were 0.25 ± 0.15, 1.16 ± 1.14, and 1.47 ± 1.23 Mm -1 , respectively. The Abs 365 of WSOC was 0.11 ± 0.08 Mm -1 in cloud water and 0.40 ± 0.31 Mm -1 in PM 2.5 , and the corresponding mass absorption efficiency (MAE 365) was 0.17 ± 0.07 and 0.31 ± 0.21 m 2 g -1 , respectively. A comparison of the light-absorption coefficient between BrC in cloud RES and cloud INT particles, and WSOC in cloud water and PM 2.5 indicates a considerable contribution (48 %–75 %) of water-insoluble BrC to total BrC light absorption. Secondary BrC estimated by minimum R squared (MRS) method dominated the total BrC in cloud RES (67 %–85 %), rather than in the cloud-free (11 %–16 %) and cloud INT (9 %–23 %) particles. It may indicate the formation of secondary BrC during cloud processing. Supporting evidence includes the enhanced WSOC and dominant contribution of the secondary formation and biomass burning factor (>80 %) to Abs 365 in cloud water provided by positive matrix factorization (PMF) analysis. In addition, we showed that the light absorption of BrC in cloud water was closely related to humic-like substances and tyrosine-like and/or protein-like substances (r>0.63 , p<0.01), whereas only humic-like substances for PM 2.5 , as identified by excitation-emission matrix fluorescence spectroscopy. [ABSTRACT FROM AUTHOR]

The mixing states of particulate amines with different chemical components are of great significance in studying the formation and evolution processes of amine-containing particles. In this work, the mixing states of single particles containing trimethylamine (TMA) and diethylamine (DEA) are investigated using a high-performance single-particle aerosol mass spectrometer located in Nanjing, China, in September 2019. TMA- and DEA-containing particles accounted for 22.8 % and 5.5 % of the total detected single particles, respectively. The particle count and abundance of the TMA-containing particles in the total particles notably increased with enhancement of ambient relative humidity (RH), while the DEA-containing particles showed no increase under a high RH. This result suggested the important role of RH in the formation of particulate TMA. Significant enrichments of secondary organic species, including 43 C 2 H 3 O + , 26 CN - , 42 CNO - , 73 C 3 H 5 O 2- , and 89 HC 2 O 4- , were found in DEA-containing particles, indicating that DEA-containing particles were closely associated with the aging of secondary organics. The differential mass spectra of the DEA-containing particles showed a much higher abundance of nitrate and organic nitrogen species during the nighttime than during the daytime, which suggested that the nighttime production of particulate DEA might be associated with reactions of gaseous DEA with HNO 3 and/or particulate nitrate. In the daytime, the decrease in DEA-containing particles was observed with the enrichment of oxalate and glyoxylate, which suggested a substantial impact of photochemistry on the aging process of DEA-containing particles. Furthermore, more than 80 % of TMA- and DEA-containing particles internally mixed with nitrate, while the abundance of sulfate was higher in the DEA-containing particles (79.3 %) than in the TMA-containing particles (55.3 %). This suggested that particulate DEA existed both as nitrate and sulfate aminium salts, while the particulate TMA primarily presented as nitrate aminium salt. The different mixing states of the TMA- and DEA-containing particles suggested their different formation processes and various influencing factors, which are difficult to investigate using bulk analysis. These results provide insights into the discriminated fates of organics during the evolution process in aerosols, which helps to illustrate the behavior of secondary organic aerosols. [ABSTRACT FROM AUTHOR]

Atmospheric brown carbon (BrC) makes a substantial contribution to aerosol light-absorbing and thus the global radiative forcing. Although BrC may change the lifetime of the cloud and ultimately affect precipitation, little is known regarding the optical properties and formation of BrC in the cloud. In the present study, the light-absorption properties of cloud droplet residual (cloud RES) were measured by coupled a ground-based counterflow virtual impactor (GCVI) and an Aethalometer (AE-33), in addition to the cloud interstitial (cloud INT) and ambient (cloud-free) particles by PM2.5 inlet-AE-33, at Mt. Tianjing (1690 m a.s.l.), a remote mountain site in southern China, from November to December 2020. Meanwhile, the light-absorption and fluorescence properties of water-soluble organic carbon (WSOC) in the collected cloud water and PM2.5 samples were also obtained, associated with the concentration of water-soluble ions. The mean light-absorption coefficient (Abs370) of the cloud RES, cloud INT, and cloud-free particles were 0.25 ± 0.15, 1.16 ± 1.14, and 1.47 ± 1.23 Mm−1, respectively. The Abs365 of WSOC was 0.11 ± 0.08 Mm−1 in cloud water and 0.40 ± 0.31 Mm−1 in PM2.5, and the corresponding mass absorption efficiency (MAE365) was 0.17 ± 0.07 and 0.31 ± 0.21 m2·g−1, respectively. A comparison of the light-absorption coefficient between BrC in the cloud RES/cloud INT and WSOC in cloud water/PM2.5 indicates a considerable contribution (48-75 %) of water-insoluble BrC to total BrC light-absorption. Secondary BrC estimated by minimum R squared (MRS) method dominated the total BrC in cloud RES (67-85 %), rather than in the cloud-free (11-16 %) and cloud INT (9-23 %) particles. It may indicate the formation of secondary BrC during cloud processing. Supporting evidence includes the enhanced WSOC and dominant contribution of secondary formation/biomass burning factor (> 80 %) to Abs365 in cloud water provided by Positive Matrix Factorization (PMF) analysis. In addition, we showed that the light-absorption of BrC in cloud water was closely related to humic-like substances and tyrosine/proteins-like substances (r > 0.63, p < 0.01), whereas only humic-like substances for PM2.5, as identified by excitation-emission matrix fluorescence spectroscopy. [ABSTRACT FROM AUTHOR]

Characterizing the molecular composition of cloud water could provide unique insights into aqueous chemistry. Field measurements were conducted at Mt. Tianjing in southern China in May, 2018. There are thousands of formulas (C5–30 H4–55 O1–15 N0–2 S0–2) identified in cloud water by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). CHON formulas (formulas containing C, H, O, and N elements; the same is true for CHO and CHOS) represent the dominant component (43.6 %–65.3 % of relative abundance), followed by CHO (13.8 %–52.1%). S-containing formulas constitute ∼ 5 %–20 % of all assigned formulas. Cloud water has a relative-abundance-weighted average O/C of 0.45–0.56, and the double bond equivalent of 5.10–5.70. Most of the formulas (>85 %) are assigned as aliphatic and olefinic species. No statistical difference in the oxidation state is observed between cloud water and interstitial PM2.5. CHON with aromatic structures are abundant in cloud water, suggesting their enhanced in-cloud formation. Other organics in cloud water are mainly from biomass burning and oxidation of biogenic volatile organic compounds. The cloud water contains more abundant CHON and CHOS at night, which are primarily contributed by -N2 O5 function and organosulfates, demonstrating the enhanced formation in dark aqueous or multi-phase reactions. While more abundant CHO is observed during the daytime, likely due to the photochemical oxidation and photolysis of N- or S-containing formulas. The results provide an improved understanding of the in-cloud aqueous-phase reactions. [ABSTRACT FROM AUTHOR]

Mixing state of black carbon (BC) with secondary species has been highlighted as a major uncertainty in assessing its radiative forcing. While recent laboratory simulation has demonstrated that BC could serve as a catalyst to enhance the formation of sulfate, its role in the formation and evolution of secondary aerosols in the real atmosphere remains poorly understood. In the present study, the mixing of BC with sulfate/nitrate in the atmosphere of Guangzhou (China) was directly investigated with a single particle aerosol mass spectrometer (SPAMS). The peak area ratios of sulfate to nitrate (SNRs) for the BC‐containing particles are constantly higher than those of the BC‐free particles (defined as particles with negligible BC signals). Furthermore, the seasonal SNR peak is observed in summer and autumn, and the diurnal peak is found in the afternoon, consistent with the trends of radiation‐related parameters (i.e., solar radiation and temperature), pointing to the BC‐induced photochemical production of sulfate. Such hypothesis is further supported by the multilinear regression and random forest analysis, showing that the variation of SNRs associated with the BC‐containing particles could be well explained (R2 = ∼0.7–0.8) by the radiation‐related parameters (>30% of the variance) and the relative BC content (∼20%) in individual particles, but with limited influence of precursors (SO2/NOx: <5%). Differently, the radiation‐related factors only explain <10% of the SNR variation for the BC‐free particles. These results provide ambient observational evidence pointing to a unique role of BC on the photochemical formation and evolution of sulfate, which merits further quantitative evaluations. Plain Language Summary: Despite ubiquitous in the atmosphere, the potential role of BC black carbon (BC) in the formation and evolution of secondary aerosols in the real atmosphere remains poorly understood. Here, we have investigated the detailed mixing state of BC with sulfate/nitrate in the atmosphere of Guangzhou in real‐time by a Single Particle Aerosol Mass Spectrometer. We show that the distinct seasonal and diurnal variation of the enhanced sulfate/nitrate ratios is most likely driven by the BC catalytic photochemistry. Our results provide first ambient observational evidence, extending the laboratory results to the ambient atmosphere that BC could act as a photoactive and absorbing substrate, leading to an enrichment of sulfate, in particular, during summer and autumn. Thus, the BC emission controls may also mitigate the formation and evolution of sulfate and it is essential to include BC involved photochemistry in the models to account for the evolution and climate impact of BC accurately. Key Points: Enhanced sulfate to nitrate ratios (SNRs) are observed for the black carbon (BC)‐containing particlesThe distinct diurnal variation of the enhanced SNRs is most likely attributed to BC catalytic photochemistrySNRs in individual BC‐containing particles could be well predicted by the radiation‐related parameters and the relative BC content [ABSTRACT FROM AUTHOR]

Water uptake abilities of organic aerosol under sub-saturated conditions play critical roles in direct aerosol radiative effects and atmospheric chemistry; however, field characterizations of the organic aerosol hygroscopicity parameter κOA under sub-saturated conditions remain limited. In this study, a field campaign was conducted to characterize κOA at a relative humidity of 80 % with hourly time resolution for the first time in the Pearl River Delta region of China. Observation results show that, during this campaign, secondary organic aerosol (SOA) dominated total organic aerosol mass (mass fraction > 70 % on average), which provides a unique opportunity to investigate influences of SOA formation on κOA. Results demonstrate that the commonly used organic aerosol oxidation level parameter O/C was weakly correlated with κOA and failed to describe the variations in κOA. However, the variations in κOA were well reproduced by mass fractions of organic aerosol factor resolved based on aerosol mass spectrometer measurements. The more oxygenated organic aerosol (MOOA) factor, exhibiting the highest average O/C (∼ 1) among all organic aerosol factors, was the most important factor driving the increase in κOA and was commonly associated with regional air masses. The less oxygenated organic aerosol (LOOA; average O/C of 0.72) factor revealed strong daytime production, exerting negative effects on κOA. Surprisingly, the aged biomass burning organic aerosol (aBBOA) factor also formed quickly during daytime and shared a similar diurnal pattern with LOOA but had much lower O/C (0.39) and had positive effects on κOA. The correlation coefficient between κOA and mass fractions of aBBOA and MOOA in total organic aerosol mass reached above 0.8. The contrasting effects of LOOA and aBBOA formation on κOA demonstrate that volatile organic compound (VOC) precursors from diverse sources and different SOA formation processes may result in SOA with different chemical composition, functional properties and microphysical structure, consequently exerting distinct influences on κOA and rendering single oxidation level parameters (such as O/C) unable to capture those differences. Aside from that, distinct effects of aBBOA on κOA were observed during different episodes, suggesting that the hygroscopicity of SOA associated with similar sources might also differ much under different emission and atmospheric conditions. Overall, these results highlight that it is imperative to conduct more research on κOA characterization under different meteorological and source conditions and examine its relationship with VOC precursor profiles and formation pathways to formulate a better characterization and develop more appropriate parameterization approaches in chemical and climate models. [ABSTRACT FROM AUTHOR]

The contribution of new particle formation (NPF) to cloud condensation nuclei (CCN) number concentration (NCCN) varies largely under different environments and depends on several key factors such as formation rate (J), growth rate (GR), distribution of preexisting particles, and properties of new particles during NPF events. This study investigates the contribution of NPF to the NCCN and its controlling factors based on measurements conducted at the Heshan supersite, in the Pearl River Delta (PRD) region of China during fall 2019. The size-resolved cloud condensation nuclei activity and size-resolved particle hygroscopicity were measured by a cloud condensation nuclei counter (CCNc) and a hygroscopic tandem differential mobility analyzer (HTDMA), respectively, along with a scanning mobility particle sizer (SMPS) and a diethylene glycol scanning mobility particle sizer (DEG-SMPS) for particle number size distribution (PNSD). A typical NPF event on 29 October was chosen to investigate the contribution of the NPF to NCCN under several supersaturation (SS) ratios. Two particle properties (hygroscopicity and surface tension) affect CCN activation with the latter being more important in terms of the CCN concentration (NCCN). A lower value of surface tension (i.e., 0.06 N m -1) than the pure-water assumption (0.073 N m -1) could increase the NCCN at SS = 1.0 % by about 20 % during the nonevent period and by about 40 % during the event. In addition, an earlier peak time corresponding to a lower critical diameter (D50) was also observed. The results show that high formation rate, growth rate, and low background particle concentration lead to high number concentrations of newly formed particles. The high growth rate was found to have the most significant impact on the NCCN , which can be attributed to the fact that a higher growth rate can grow particles to the CCN size in a shorter time before they are scavenged by preexisting particles. Two other NPF events (an event on 18 October in this campaign and an event on 12 December 2014 in Panyu) were chosen to perform sensitivity tests under different scenarios (growth rate, formation rate, and background particle concentration). The calculated NCCN at SS = 1.0 % on 12 December 2014 was significantly lower than that from the other two events. The event on 12 December was re-simulated using the growth rate taken from the event on 18 October which resulted in similar CCN concentrations between the two events (12 December and 18 October), implying that the growth rate is the major impact factor for CCN activation. Our results highlight the importance of growth rate and surface tension when evaluating the contribution of NPF to the NCCN. [ABSTRACT FROM AUTHOR]

A 6-year-long high-resolution Chinese air quality reanalysis (CAQRA) dataset is presented in this study obtained from the assimilation of surface observations from the China National Environmental Monitoring Centre (CNEMC) using the ensemble Kalman filter (EnKF) and Nested Air Quality Prediction Modeling System (NAQPMS).This dataset contains surface fields of six conventional air pollutants in China (i.e. PM 2.5 , PM 10 , SO 2 , NO 2 , CO, and O 3) for the period 2013–2018 at high spatial (15km×15km) and temporal (1 h) resolutions. This paper aims to document this dataset by providing detailed descriptions of the assimilation system and the first validation results for the above reanalysis dataset. The 5-fold cross-validation (CV) method is adopted to demonstrate the quality of the reanalysis. The CV results show that the CAQRA yields an excellent performance in reproducing the magnitude and variability of surface air pollutants in China from 2013 to 2018 (CV R2=0.52 –0.81, CV root mean square error (RMSE) =0.54 mg/m3 for CO, and CV RMSE =16.4 –39.3 µg/m3 for the other pollutants on an hourly scale). Through comparison to the Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) dataset produced by the European Centre for Medium-Range Weather Forecasts (ECWMF), we show that CAQRA attains a high accuracy in representing surface gaseous air pollutants in China due to the assimilation of surface observations. The fine horizontal resolution of CAQRA also makes it more suitable for air quality studies on a regional scale. The PM 2.5 reanalysis dataset is further validated against the independent datasets from the US Department of State Air Quality Monitoring Program over China, which exhibits a good agreement with the independent observations (R2=0.74 –0.86 and RMSE =16.8 –33.6 µg/m3 in different cities). Furthermore, through the comparison to satellite-estimated PM 2.5 concentrations, we show that the accuracy of the PM 2.5 reanalysis is higher than that of most satellite estimates. The CAQRA is the first high-resolution air quality reanalysis dataset in China that simultaneously provides the surface concentrations of six conventional air pollutants, which is of great value for many studies, such as health impact assessment of air pollution, investigation of air quality changes in China, model evaluation and satellite calibration, optimization of monitoring sites, and provision of training data for statistical or artificial intelligence (AI)-based forecasting. All datasets are freely available at 10.11922/sciencedb.00053 (Tang et al., 2020a), and a prototype product containing the monthly and annual means of the CAQRA dataset has also been released at 10.11922/sciencedb.00092 (Tang et al., 2020b) to facilitate the evaluation of the CAQRA dataset by potential users. [ABSTRACT FROM AUTHOR]

The composition, morphology, and mixing structure of individual cloud residues (RES) and interstitial particles (INT) at a mountaintop site were investigated. Eight types of particles were identified, including sulfate-rich (S-rich), S-organic matter (OM), aged soot, aged mineral dust, aged fly ash, aged metal, refractory, and aged refractory mixture. A shift of dominant particle types from S-rich (29 %) and aged soot (27 %) in the INT to aged refractory mixture (23 %) and S-OM (22 %) in the RES is observed. In particular, particles with organic shells are enriched in the RES (27 %) relative to the INT (12 %). Our results highlight that the formation of more oxidized organic matter in the cloud contributes to the existence of organic shells after cloud processing. The fractal dimension (Df), a morphologic parameter to represent the branching degree of particles, for soot particles in the RES (1.82 ± 0.12) is lower than that in the INT (2.11 ± 0.09), which indicates that in-cloud processes may result in less compact soot. This research emphasizes the role of in-cloud processes in the chemistry and microphysical properties of individual particles. Given that organic coatings may determine the particle hygroscopicity, activation ability, and heterogeneous chemical reactivity, the increase of OM-shelled particles upon in-cloud processes should have considerable implications. [ABSTRACT FROM AUTHOR]

Heterogeneous reactions on sea spray aerosols (SSA) are the main pathway to drive the circulation of chlorine, nitrogen, and sulfur in the atmosphere. The release of Cl will significantly affect the physicochemical properties of SSA. However, the impact of organic acids and mixing state on chloride depletion of SSA is still unclear. Hence, the size and chemical composition of individual SSA particles during the East Asian summer monsoon were investigated by a single particle aerosol mass spectrometer (SPAMS). According to the chemical composition, SSA particles were classified into SSA-Aged, SSA-Bio and SSA-Ca. In comparison to the aged Na-rich SSA particles (SSA-Aged), some additional organic species related to biological origin were observed in SSA-Bio, and each of two types accounts for approximately 50 % of total SSA particles. SSA-Ca may associated with organic shell of Na-rich SSA particles, which only accounts for ~ 3 %. Strongly positive correlations between Na and organic acids (including formate, acetate, propionate, pyruvate, oxalate, malonate, succinate, and glutarate) were observed for the SSA-Aged (r² = 0.52, p < 0.01) and SSA-Bio (r² = 0.61, p < 0.01), indicating the significance of organic acids in the chloride depletion during inland transport. The contribution of these organic acids to the chloride depletion is estimated to be up to 34 %. Interestingly, the degree of chloride depletion is distinctly different between SSA-Aged and SSA-Bio. It is most probably attributed to the associated organic coating in the SSA-Bio particles, which inhibit the displacement reactions between acids and chloride. As revealed from the mixing state of SSA-Bio, Cl / Na ratio increases with increasing phosphate and organic nitrogen, which is known to originate from biological activities. This finding provides some basis for the improvement of modeling simulations in chlorine circulation and a comprehensive understanding of the effects of organics on chloride depletion of SSA particles. [ABSTRACT FROM AUTHOR]

Air pollution in China has changed substantially since 2013, and the effects such changes bring to the human health and environment has been an increasingly hot topic in many scientific fields. Such studies, however, are often hindered by a lack of long-term air quality dataset in China of high accuracy and spatiotemporal resolutions. In this study, a six-year long high-resolution Chinese air quality reanalysis datasets (CAQRA) has been developed by assimilating over 1000 surface air quality monitoring sites from China National Environmental Monitoring Centre (CNEMC) using the ensemble Kalman filter (EnKF) and the Nested Air Quality Prediction Modeling System (NAQPMS). Surface fields of six conventional air pollutants in China, namely PM2.5, PM10, SO2, NO2, CO and O3 for period 2013-2018, are provided at high spatial (15 km ×15 km) and temporal (1 hour) resolutions. This paper aims to document this dataset by providing the detailed descriptions of the assimilation system and presenting the first validation results for the reanalysis dataset. A five-fold cross validation (CV) method was used to assess the quality of CAQRA. The CV results show that the CAQRA has excellent performances in reproducing the magnitude and variability of the surface air pollutants in China (CV R2 = 0.52-0.81, CV RMSE = 0.54 mg/m3 for CO and 16.4-39.3 μg/m3 for other pollutants at the hourly scale). The interannual changes of the air quality in China were also well represented by CAQRA. Through the comparisons with the Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) produced by the European Centre for Medium-Range Weather Forecasts (ECWMF) based on assimilating satellite products, we show that the CAQRA has higher accuracy in representing the surface gaseous air pollutants in China due to the assimilation of surface observations. The finer horizontal resolution of CAQRA also makes it more suitable for the air quality studies in the regional scale. We further validate the PM2.5 reanalysis dataset against the independent datasets from the U.S. Department of State Air Quality Monitoring Program over China, and the accuracy of PM2.5 reanalysis was also compared to that of the satellite estimated PM2.5 concentrations. The results indicate that the PM2.5 reanalysis shows good agreement with the independent observations (R2 = 0.74-0.86, RMSE = 16.8-33.6 μg/m3 in different cities) and its accuracy is higher than most satellite estimates. This dataset would be the first high-resolution air quality reanalysis dataset in China that can simultaneously provide the surface concentrations of six conventional air pollutants in China, which should be of great value for many studies, such as the assessment of health impacts of air pollution, investigation of the changes of air quality in China and providing training data for the statistical or AI (Artificial Intelligence) based forecast. The whole datasets are freely available at: https://doi.org/10.11922/sciencedb.00053 (Tang et al., 2020a), and a teaser product which contains the monthly and annual mean of the CAQRA has also been released at https://doi.org/10.11922/sciencedb.00092 (Tang et al., 2020b) to facilitate the potential users to download and to evaluate the improvement of CAQRA. [ABSTRACT FROM AUTHOR]