Characterizing Black Carbon (BC) at regional background areas is important for better understanding its impact on climate forcing and health effects. The variability and sources of Equivalent Black Carbon (EBC) in PM₁₀ (atmospheric particles with aerodynamic diameter smaller than 10 μm) have been investigated during a 5-year measurement period at the National Atmospheric Observatory Košetice (NAOK), Czech Republic. Ground based measurements were performed from September 2012 to December 2017 with a 7-wavelength aethalometer (AE31, Magee Scientific). The contributions of fossil fuel (EBCff) and biomass burning (EBCbb) were estimated using the aethalometer model. Seasonal, diurnal and weekly variations of EBC were observed that can be related to the sources fluctuations and transport characteristic of pollutants predominantly associated with regional air masses recirculating over the Czech Republic and neighboring countries. The absorption Ångström exponent (α-value) estimated in summer (1.1 ± 0.2) was consistent with reported value for traffic, while the mean highest value (1.5 ± 0.2) was observed in winter due to increased EBCbb accounting for about 50% of the total EBC. This result is in agreement with the strong correlation between EBCbb and biomass burning tracers (levoglucosan and mannosan) in winter. During this season, the concentrations of EBCbb and Delta-C (proxy for biomass burning) reached a maximum in the evening when increasing emissions of wood burning in domestic heating devices (woodstoves/heating system) is expected, especially during the weekend. The diurnal profile of EBCff displays a typical morning peak during the morning traffic rush hour and shows a decreasing concentration during weekends due to lower the traffic emission.

Cryoconite is a dark, dusty aggregate of mineral particles, organic matter, and microorganisms transported by wind and deposited on glacier surfaces. It can accelerate glacier melting and alter glacier mass balances by reducing the surface albedo of glaciers. Biomass burning in the Tibetan Plateau, especially in the glacier cryoconites, is poorly understood. Retene, levoglucosan, mannosan and galactosan can be generated by the local fires or transported from the biomass burning regions over long distances. In the present study, we analyzed these four molecular markers in cryoconites of seven glaciers from the northern to southern Tibetan Plateau. The highest levels of levoglucosan and retene were found in cryoconites of the Yulong Snow Mountain and Tienshan glaciers with 171.4 ± 159.4 ng g⁻¹ and 47.0 ± 10.5 ng g⁻¹ dry weight (d.w.), respectively. The Muztag glacier in the central Tibetan Plateau contained the lowest levels of levoglucosan and retene with mean values of 59.8 ng g⁻¹ and 0.4 ± 0.1 ng g⁻¹ d.w., respectively. In addition, the vegetation changes and the ratios of levoglucosan to mannosan and retene indicate that combustion of conifers significantly contributes to biomass burning of the cryoconites in the Yulong Snow Mountain and Tienshan glacier. Conversely, biomass burning tracers in cryoconites of Dongkemadi, Yuzhufeng, Muztag, Qiyi and Laohugou glaciers are derived from the combustion of different types of biomass including softwood, hardwood and grass.

The fate of polycyclic aromatic hydrocarbons (PAHs) determines their potential risk in soil, which may be directly affected by abiotic conditions and indirectly through the changes in decomposer communities. In comparison, the indirect effects on the fate remain largely elusive. In this study, the fate of phenanthrene and benzo[a]pyrene and the corresponding bacterial changes were investigated in three contaminated farmland soils using a ¹⁴C tracer method and Miseq sequencing. The results showed that most benzo[a]pyrene was consistently extractable with dichloromethane (DCM) after the 60-day incubation (60.4%–78.2%), while phenanthrene was mainly mineralized to CO₂ during the 30-day incubation (40.4%–58.7%). Soils from Guangzhou (GZ) showed a different distribution pattern of ¹⁴C-PAHs exemplified by low mineralization and disparate bound residue formation. The PAH fate in the Shenyang (SY) and Nanjing (NJ) soils were similar to each other than to that in the GZ soil. The fate in the GZ soil seemed to be linked to the distinct edaphic properties, such as organic matter content, however soil microbial community could have influenced the distribution pattern of PAHs. This potential role of microorganisms was reflected by the unique changes in the copy numbers of Gram positive RHDα gene, and by the distinct shifts in bacterial community composition during the incubation. A quite different shift in bacterial communities was found in the GZ microcosms which may influence PAH mineralization and non-extractable residue (NER) formation.

Thirteen secondary organic aerosol (SOA) tracers of isoprene, monoterpenes and sesquiterpenes were measured for PM₂.₅ aerosols collected at the summit of Mt. Wuyi (1139 m, a.s.l.), to investigate their seasonality and formation mechanism. Concentrations of the isoprene and monoterpene SOA tracers were much higher in summer than those in other seasons. In contrast, β-caryophyllinic acid was found to be the lowest in summer. Concentrations of those BSOA tracers showed a positive correlation with temperature (R² = 0.52–0.70), and a negative correlation with relative humidity (R² = 0.43–0.78). Moreover, thermodynamic model (i.e., ISORROPIA-II) calculation results showed that acidity conditions are favorable for BSOA formation. Robust linear correlations between the BSOA tracers and anthropogenic pollutants such as SO₂ (R² = 0.53–0.7) and NO₂ (R² = 0.37–0.54) were observed for all the samples, suggesting that SO₂ and NOx can enhance BSOA production in the remote mountain area of southeast China, which is related to an acid-catalyzed heterogeneous chemistry. Moreover, we also found a significant correlation between the concentrations of the BSOA tracers and levoglucosan especially for β-caryophyllinic acid, indicating that biomass burning plumes from the distant lowland regions could influence the production of BSOA in the mountain free troposphere. Our results clearly demonstrated that anthropogenic emissions in China could enhance BSOA formation in the distant mountain regions.

The molecular marker-based chemical mass balance (MM-CMB) method performs well in the source apportionment of organic carbon (OC) but has some difficulty with contributions from primary sources to inorganic secondary ions when apportioning PM2.5 (particles with aerodynamic diameter of 2.5 μm or less) sources. Positive matrix factorization (PMF) with the input of inorganic and organic tracers can properly estimate the contributions of primary and secondary sources to inorganic secondary ions; however, PMF is unable to apportion several PM2.5 sources with large fractions of organic carbon and few elemental compositions. In this study regarding data collected in 2011 and 2012 at three sites in Wuhan, China, the MM-CMB model was used to apportion OC in the PM2.5, and the PMF model was used to apportion the inorganic ions (sulfate, nitrate, and ammonia), dust, and EC. The source contributions of PM2.5 were estimated by reconstructing masses of bulk chemical components that had been apportioned to real-world sources using suitable source apportionment methods. Good performance of this hybrid source apportionment strategy was observed with ten resolved factors, explaining 70–80% of measured PM2.5 mass on average. The hybrid strategy takes the advantages of both models in PM2.5 source apportionment and yields unique source apportionment results for PM2.5 bulk chemical components, which could provide new information for optimizing air quality regulations for the emission abatement of target PM mass and compositions for countries around the world.

Chemical mass balance (CMB) modeling and radiocarbon measurements were combined to evaluate the sources of carbonaceous fine particulate matter (PM2.5) in Shenzhen, China during and after the 2011 summer Universiade games when air pollution control measurements were implemented to achieve air quality targets. Ambient PM2.5 filter samples were collected daily at two sampling sites (Peking University Shenzhen campus and Longgang) over 24 consecutive days, covering the controlled and uncontrolled periods. During the controlled period, the average PM2.5 concentration was less than half of what it was after the controls were lifted. Organic carbon (OC), organic molecular markers (e.g., levoglucosan, hopanes, polycyclic aromatic hydrocarbons), and secondary organic carbon (SOC) tracers were all significantly lower during the controlled period. After pollution controls ended, at Peking University, OC source contributions included gasoline and diesel engines (24%), coal combustion (6%), biomass burning (12.2%), vegetative detritus (2%), biogenic SOC (from isoprene, α-pinene, and β-caryophyllene; 7.1%), aromatic SOC (23%), and other sources not included in the model (25%). At Longgang after the controls ended, similar source contributions were observed: gasoline and diesel engines (23%), coal combustion (7%), biomass burning (17.7%), vegetative detritus (1%), biogenic SOC (from isoprene, α-pinene, and β-caryophyllene; 5.3%), aromatic SOC (13%), and other sources (33%). The contributions of the following sources were smaller during the pollution controls: biogenic SOC (by a factor of 10–16), aromatic SOC (4–12), coal combustion (1.5–6.8), and biomass burning (2.3–4.9). CMB model results and radiocarbon measurements both indicated that fossil carbon dominated over modern carbon, regardless of pollution controls. However, the CMB model needs further improvement to apportion contemporary carbon (i.e. biomass burning, biogenic SOC) in this region. This work defines the major contributors to carbonaceous PM2.5 in Shenzhen and demonstrates that control measures for primary emissions could significantly reduce secondary organic aerosol (SOA) formation.

Ambient fine particulate matter (PM2.5) and volatile organic compounds (VOCs) collected at Mt. Tai in summer 2014 were analysed and the data were used to identify the contribution of biogenic and anthropogenic hydrocarbons to secondary organic aerosols (SOA) and their sources and potential source areas in high mountain regions. Compared with those in 2006, the 2014 anthropogenic SOA tracers in PM2.5 aerosols and VOC species related to vehicular emissions exhibited higher concentrations, whereas the levels of biogenic SOA tracers were lower, possibly due to decreased biomass burning. Using the SOA tracer and parameterisation method, we estimated the contributions from biogenic and anthropogenic VOCs, respectively. The results showed that the average concentration of biogenic SOA was 1.08 ± 0.51 μg m−3, among which isoprene SOA tracers were dominant. The anthropogenic VOC-derived SOA were 7.03 ± 1.21 μg m−3 and 1.92 ± 1.34 μg m−3 under low- and high-NOx conditions, respectively, and aromatics made the greatest contribution. However, the sum of biogenic and anthropogenic SOA only contributed 18.1–49.1% of the total SOA. Source apportionment by positive matrix factorisation (PMF) revealed that secondary oxidation and biomass burning were the major sources of biogenic SOA tracers. Anthropogenic aromatics mainly came from solvent use, fuel and plastics combustion and vehicular emissions. However, for > C6 alkanes and cycloalkanes, vehicular emissions and fuel and plastics combustion were the most important contributors. The potential source contribution function (PSCF) identified the Bohai Sea Region (BSR) as the major source area for organic aerosol compounds and VOC species at Mt. Tai.

Samples of lichens, snow and particulate matter (PM10, 24 h) are used for the source identification of air pollution in the heavily industrialized region of Ostrava, Upper Silesia, Czech Republic. An integrated approach that uses different environmental samples for metal concentration and Pb isotope analyses was applied. The broad range of isotope ratios in the samples indicates a combination of different pollution sources, the strongest among them being the metallurgical industry, bituminous coal combustion and traffic. Snow samples are proven as the most relevant indicator for tracing metal(loid)s and recent local contamination in the atmosphere. Lichens can be successfully used as tracers of the long-term activity of local and remote sources of contamination. The combination of PM10 with snow can provide very useful information for evaluation of current pollution sources.

Airborne particulate matter (PM) was collected in Beijing between 24 February and 12 March 2014 to investigate chemical characteristics and potential industrial sources of aerosols along with health risk of haze events. Results showed secondary inorganic aerosol was the major contributor to PM2.5 during haze days. Utilizing specific elements, including Fe, La, Tl and As, as fingerprinting tracers, four emission sources, namely iron and steel manufacturing, petroleum refining, cement plant, and coal combustion were explicitly identified; their elevated contributions to PM during haze days were also estimated. The average cancer risk from exposure to inhalable PM toxic metals was 1.53 × 10⁻⁴ on haze days, which is one order of magnitude higher than in other developed cities. These findings suggested heavy industries emit large amounts of not only primary PM but also precursor gas pollutants, leading to secondary aerosol formation and harm to human health during haze days.

The sensitivity of a source apportionment model to mobile source profiles was examined to determine the impact of using non-local mobile source profiles in chemical mass balance (CMB) models. We examined the impact of USA and Chinese mobile source profiles on source apportionment results in St. Louis, Missouri, and Beijing. The results showed that the use of non-local mobile source profiles did not impact the model apportionment results for vegetative detritus and biomass burning, but other primary source contributions were influenced by the use of non-local source profiles. Secondary organic carbon (SOC) contributions estimated by the CMB models with local and non-local profiles were compared to estimate of SOC from the EC tracer method and were found to be consistent with little bias. The results also showed that it is feasible to use the USA mobile profiles in China while model results were biased by using Chinese mobile profiles in the USA. Monthly and annual average concentrations of molecular markers in the source apportionment model showed lower sensitivity to source profiles than daily measurements, which has implications to the design of source apportionment studies.