Wintertime fine aerosol particles composition and its evolution in two megacities of southern and northern China

Study on fine aerosols composition can help understand the particles formation and is crucial for improving the accuracy of model simulations. Based on field data measured by a Q-ACSM (Quadrupole-Aerosol Chemical Speciation Monitor), we have comprehensively compared the characteristics, evolution, and potential formation mechanisms of the components in NR-PM2.5 during wintertime at two megacities (Beijing and Guangzhou) of southern and northern China. We show that as PM pollution intensifies, the mass fraction of the primary aerosols (e.g., COA, HOA) in PM2.5 in Guangzhou increased, along with a slight decline in proportion of both the secondary organic (SOA) and inorganic (SIA) aerosols; In contrast, in Beijing, the proportion of the SIA ramped up from 28 % to 53 % with the pollution evolution; and the fraction of SOA in total OA also increased due to a substantial increment in the proportion of MO-OOA (from 29 % to 48 %), suggesting a significance of the secondary processes in worsening aerosols pollution in Beijing. Our further analysis demonstrates a leading role of aqueous pathway in the secondary formation of aerosols at the Beijing site, presenting an exponential rising of SIA and SOA with the relative humidity (RH) increase. Compared to Beijing, however, we find that the photochemical oxidation other than aqueous process in Guangzhou plays a more critical role in those secondary aerosols formation. Combined with the Hysplit trajectory model, we identify the high humid conditions in Guangzhou are typically affected by clean marine air masses, explaining the slower response of secondary components to the RH changes. Moreover, the particles in Guangzhou were observed less hygroscopic that is adverse to the aerosol aqueous chemistry. The results provide basis for the precise control of PM pollution in different regions across China and would be helpful in improving model simulations.

Fine aerosol sources at an urban background site in the eastern Mediterranean (Nicosia; Cyprus): Insights from offline versus online source apportionment comparison for carbonaceous aerosols

A total of 348 daily PM_2.5 samples were collected at an urban background site of Nicosia, capital of Cyprus, for one-year period (October 2018-October 2019) to assess the origin and sources of fine PM at the eastern Mediterranean, a poorly characterized area of the world. The samples were analysed for water soluble ionic species, elemental and organic carbon, carbohydrates and trace metals, the combination of which were utilized to identify pollution sources by applying Positive Matrix Factorization (PMF). Six PM_2.5 sources, namely long-range transport (LRT; 38 %), traffic (20 %), biomass burning (16 %), dust (10 %), sea salt (9 %) and heavy oil combustion (7 %), were identified. Despite sampling in an urban agglomeration, the chemical fingerprint of the aerosol is largely dictated by air mass origin rather than local sources. Springtime is characterized by the most elevated particulate levels due to the southerly air masses carrying particles from the Sahara Desert. Northerlies are observed throughout the year but are predominant during summer allowing the LRT source to peak (54 % during summer). Only during winter, due to extensive use of biomass combustion for domestic heating (36.6 % during winter), local sources dominate. A co-located online PMF source apportionment of submicron carbonaceous aerosols (Organic Aerosols, OA; Black Carbon) was performed by the means of an Aerosol Chemical Speciation Monitor (for OA) and an Aethalometer (for BC) for a four-month period. The comparison between the two methodologies allowed to better assess the robustness and limitations of the two methodologies. More specifically, LRT OA and biomass burning BC apportioned by the offline PMF showed a strong consistency with the online apportioned more oxidized oxygenated OA and BC_wb, respectively, cross validating these sources. On the other hand, our traffic factor may contain additional hydrocarbon-like OA and BC from fossil fuel sources other than just vehicular emissions. Finally, the offline biomass burning OA source is likely to contain both primary and secondary OA.

Trace elements in ambient aerosols and size-resolved fog droplets: Trends, enrichment, and risk assessment

Ambient particulate matter (PM) is composed of inorganic and organic components. The contribution of each component is impacted by various factors such as emission sources, atmospheric aging process, and size of the PM or droplets. This study mainly focuses on the effect of the PM and droplet size on trace elemental concentrations, for which various size fractions of ambient PM (PM₁, PM_2.5) were collected on quartz filters along with fog water (FW) samples during winter. Simultaneous, online measurements of the mass concentrations of PM₁ and PM_2.5 were also carried out. At the time of the collection, the mass concentration of PM_2.5 ranged from 19 to 890 μg/m³, and its mean value was 227 μg/m³. During the sampling period, 17 fog events occurred and caused a 27% reduction in the mean pre-fog PM_2.5 concentration. All the PM and FW samples were analyzed for 12 trace elements: Ca, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, Zn, V. The concentrations of the various trace elements in the PM₁, PM_2.5, and FW samples encompassed a wide range: 10 (V)-2432 (Na) ng/m³, 34 (Mn)-13810 (Na) ng/m³, and 8 (Cr)-19870 (Ca) μg/l, respectively. The concentrations of the trace elements in the FW samples indicated a droplet-size-dependent trend: the small droplets (diameter <16 μm) had several times (3-10 times) higher concentrations than the coarser droplets (diameter >22 μm). The enrichment factor (EF) analysis revealed that the EF values for almost all the trace elements were an order of magnitude higher in the FW samples than in PM₁ and PM_2.5. Risk assessment based on toxic elements suggested a very high inhalation carcinogenic risk (231 per million) for the exposed population during foggy periods. This study will facilitate decision-making by policymakers regarding air quality and health concerns.

Surfactants in the sea surface microlayer, subsurface water and fine marine aerosols in different background coastal areas

This study aims to determine the concentrations of surfactants in the surface microlayer (SML), subsurface water (SSW) and fine mode aerosol (diameter size < 1.5 μm) at different coastal stations in Peninsular Malaysia. The concentrations of anionic and cationic surfactants were determined through colorimetric methods as methylene blue active substances (MBAS) and disulphine blue active substances (DBAS), respectively. Water-soluble ions, for the determination of fine mode aerosol sources, were determined using ion chromatography (IC) for anions (SO₄^2-, NO₃^-, Cl^- and F^-) and cations (Na⁺, K⁺, Ca²⁺ and Mg²⁺). Principal component analysis (PCA), combined with multiple linear regression (MLR), was used to identify the possible sources of surfactants in fine aerosol. The results showed the concentrations of surfactants as MBAS and DBAS in the SML ranged between 0.23 ± 0.03 and 0.35 ± 0.01 μmol L^-1 and between 0.21 ± 0.02 and 0.29 ± 0.01 μmol L^-1, respectively. The enrichment factors (Efs) ratios between MBAS and DBAS in the SML and SSW ranged between 1.04 ± 0.01 and 1.32 ± 0.04, respectively. The station that is located near to tourism and industrial activities recorded the highest concentrations of surfactants in SML and SSW. The concentrations of surfactants in fine aerosol ranged between 62.29 and 106.57 pmol m^-3. The three possible sources of fine aerosol during the northeast monsoon were aged sea spray/biomass burning (which accounted for 69% of the atmospheric aerosol), nitrate/mineral dust (23%) and sulphate/fresh sea salt (8%). During the southwest monsoon, the three main sources of atmospheric aerosol were biomass burning (71%), secondary inorganic aerosol (23%) and sea spray (6%). This study suggests anthropogenic sources are main contributors to the concentrations of surfactants in SML, SSW and fine aerosols.