Abstract. Ambient particulate matter (PM) can contain a mix of different toxic species derived from a wide variety of sources. This study quantifies the diurnal variation and nocturnal abundance of 16 polycyclic aromatic hydrocarbons (PAHs), 10 oxygenated PAHs (OPAHs) and 9 nitrated PAHs (NPAHs) in ambient PM in central Beijing during winter. Target compounds were identified and quantified using gas chromatography–time-of-flight mass spectrometry (GC-Q-ToF-MS). The total concentration of PAHs varied between 18 and 297 ng m−3 over 3 h daytime filter samples and from 23 to 165 ng m−3 in 15 h night-time samples. The total concentrations of PAHs over 24 h varied between 37 and 180 ng m−3 (mean: 97±43 ng m−3). The total daytime concentrations during high particulate loading conditions for PAHs, OPAHs and NPAHs were 224, 54 and 2.3 ng m−3, respectively. The most abundant PAHs were fluoranthene (33 ng m−3), chrysene (27 ng m−3), pyrene (27 ng m−3), benzo[a]pyrene (27 ng m−3), benzo[b]fluoranthene (25 ng m−3), benzo[a]anthracene (20 ng m−3) and phenanthrene (18 ng m−3). The most abundant OPAHs were 9,10-anthraquinone (18 ng m−3), 1,8-naphthalic anhydride (14 ng m−3) and 9-fluorenone (12 ng m−3), and the three most abundant NPAHs were 9-nitroanthracene (0.84 ng m−3), 3-nitrofluoranthene (0.78 ng m−3) and 3-nitrodibenzofuran (0.45 ng m−3). ∑PAHs and ∑OPAHs showed a strong positive correlation with the gas-phase abundance of NO, CO, SO2 and HONO, indicating that PAHs and OPAHs can be associated with both local and regional emissions. Diagnostic ratios suggested emissions from traffic road and coal combustion were the predominant sources of PAHs in Beijing and also revealed the main source of NPAHs to be secondary photochemical formation rather than primary emissions. PM2.5 and NPAHs showed a strong correlation with gas-phase HONO. 9-Nitroanthracene appeared to undergo a photodegradation during the daytime and showed a strong positive correlation with ambient HONO (R=0.90, P < 0.001). The lifetime excess lung cancer risk for those species that have available toxicological data (16 PAHs, 1 OPAH and 6 NPAHs) was calculated to be in the range 10−5 to 10−3 (risk per million people ranges from 26 to 2053 cases per year).

Abstract. Epidemiological studies have consistently linked exposure to PM2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM2.5, including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM2.5 mass concentrations (µg m−3) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM2.5 and how they affect both PM2.5 OP and the concentrations of particle-bound reactive oxygen species.

Biogenic secondary organic aerosol (BSOA) makes up a significant proportion of organic aerosol, and its formation chemistry, composition, and physical properties can be influenced by anthropogenic emissions, especially in urban areas. Organosulfates (OSs) are an important class of tracers for BSOA and have been well-studied over the past decade, although detailed ambient studies of diurnal variations are still lacking. In this study, fine particulate matter samples were collected eight times a day across summer and winter campaigns at an urban site in Guangzhou, China. Guangzhou is heavily influenced by both biogenic and anthropogenic emissions, allowing for biogenic–anthropogenic interactions to be studied. Individual OSs and nitrooxy OSs (NOSs) species derived from monoterpenes and isoprene were analyzed using ultrahigh-performance liquid chromatography tandem mass spectrometry (UHPLC–MS2) and quantified using three authentic and proxy standards. The observations show strong diurnal variations of monoterpene derived OSs and NOSs, which peaked during the night, with concentrations increasing from the early evening, highlighting the role of NO3-oxidation chemistry. Isoprene derived OSs/NOSs showed strong seasonal profiles, with summer and winter average concentrations of 181.8 and 69.5 ng m–3, respectively, with exponential increases observed at temperatures above 30 °C. Low-NO formation pathways were dominant in the summer, while high-NO pathways became more important in the winter. Isoprene OS formation was strongly dependent on the availability of particulate sulfate (SO4 2–), suggesting an extensive heterogeneous chemistry of oxidized isoprene species. Overall, this study provides further insights into biogenically derived OS and NOS formation within highly anthropogenically influenced environments.

We study the anthropogenic and biogenic contributions to organic aerosol.

Abstract. Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants in air, soil and water and known to have harmful effects on human health and the environment. The diurnal and nocturnal variation of 17-PAHs in ambient particle-bound PAHs were measured in urban Beijing (China) and Delhi (India) during the summer season using GC-Q-TOF-MS. The mean concentration of particles less than 2.5 microns (PM2.5) observed in Delhi was 3.6 times higher than in Beijing during the measurement period in both the day-time and night-time. In Beijing, the mean concentration of the sum of the 17 PAHs (∑17-PAHs) was 8.2 ± 5.1 ng m−3 in daytime, with the highest contribution from Indeno[1,2,3-cd]pyrene (12 %), while at night-time the total PAHs was 7.2 ± 2.0 ng m−3, with the largest contribution from Benzo[b]fluoranthene (14 %). In Delhi, the mean ∑17-PAHs was 13.6 ± 5.9 ng m−3 in daytime, and 22.7 ± 9.4 ng m−3 at night-time, with the largest contribution from Indeno[1,2,3-cd]pyrene in both the day (17 %) and night (20 %). Elevated mean concentrations of total PAHs in Delhi observed at night were attributed to emissions from vehicles and biomass burning and to meteorological conditions leading to their accumulation from a stable and low atmospheric boundary layer. Local emission sources were typically identified as the major contributors to total measured PAHs, however, in Delhi 25 % of the emissions were attributed to long-range atmospheric transport. Major emission sources were characterized based on the contribution from each class of PAHs, with the 4, 5, and 6 ring PAHs accounting ~ 95 % of the total PM2.5-bound PAHs mass in both locations. The high contribution of 5 ring PAHs to total PAH concentration in summer Beijing and Delhi suggests a high contribution from petroleum combustion. In Delhi, a high contribution from 6 ring PAHs was observed at night, suggesting a potential emission source from the combustion of fuel and oil in power generators, widely used in Delhi. The lifetime excess lung cancer risk (LECR) was calculated for Beijing and Delhi, with the highest estimated risk attributed to Delhi (LECR = 155 per million people), 2.2 times higher than Beijing risk assessment value (LECR = 70 per million people). Finally, we have assessed the emission control policies in each city and identified those major sectors that could be subject to mitigation measures.