Organic aerosol (OA) constitutes a substantial fraction of fine particles and affects both human health and climate. It is becoming clear that OA absorbs light substantially (hence termed Brown Carbon, BrC), adding uncertainties to global aerosol radiative forcing estimations. The few current radiative-transfer and chemical-transport models that include BrC primarily consider sources from biogenic and biomass combustion. However, radiocarbon fingerprinting here clearly indicates that light-absorbing organic carbon in winter Beijing, the capital of China, is mainly due to fossil sources, which contribute the largest part to organic carbon (OC, 67 ± 3%) and its sub-constituents (water-soluble OC, WSOC: 54 ± 4%, and water-insoluble OC, WIOC: 73 ± 3%). The dual-isotope (Δ14C/δ13C) signatures, organic molecular tracers and Beijing-tailored emission inventory identify that this fossil source is primarily from coal combustion activities in winter, especially from the residential sector. Source testing on Chinese residential coal combustion provides direct evidence that intensive coal combustion could contribute to increased light-absorptivity of ambient BrC in Beijing winter. Coal combustion is an important source to BrC in regions such as northern China, especially during the winter season. Future modeling of OA radiative forcing should consider the importance of both biomass and fossil sources.
China is facing serious haze problems due to the levels of fine particulate matter (PM2.5). Therefore, source apportionment of PM2.5 is required for formulating effective air pollution control strategies. The fast increase of the vehicle population, especially in the megacities of China in recent years, makes vehicular emissions one of the most important sources of PM2.5 and has led to it receiving great attention and concern. There is an urgent need to accurately and quantitatively estimate the contribution of vehicular emissions. A growing number of studies have been conducted for source apportionment of PM2.5 in China and report the contribution from vehicular emissions using different methods. However, it is still a big challenge as to how vehicular emissions can be accurately quantified.
This study summarizes the various methods that have been used to identify and quantify the vehicular emissions contribution to PM2.5 in published literature by international and domestic scientists, lists advantages and disadvantages of each method, and proposes ways to reduce its uncertainty. In general, methods for estimating vehicular emission contributions in previous studies include emission inventory based methods, chemical transport models, receptor models, hybrid models etc. The receptor model based method is the most commonly applied method in China. Source profiles of vehicular emissions based on source testing in China, and organic and inorganic tracers used for diagnosing vehicular emissions, which are two key factors for quantifying vehicular exhaust in receptor models, are also summarized here.
Contributions of vehicular emissions to ambient PM2.5 reported in different areas in China, especially Beijing, are listed and compared. It can be seen that the contribution of vehicular emissions to PM2.5 varies significantly with the study area, year of the study, as well as the methods in use. The vehicular emissions contribution to PM2.5 in Beijing is reported to be in the range of 4%–36% based on previous studies from 1989 to 2014, primarily using the receptor model method.
This work also points out challenges in the current studies, provides suggestions in order to better quantify the contribution from vehicular emissions in China, and proposes ways to optimize the methods. For example, besides primary emissions from vehicular exhaust, quantifying secondary organic and inorganic aerosols formed from gaseous and particulate precursors from vehicular emissions, as well as traffic related sources (e. g., resuspended road dust) is also a big concern and challenge for accurately estimating vehicular emissions. In addition, there is still a pressing need to develop more detailed and comprehensive chemical profiles and an emissions inventory of vehicular emissions, with standardized sampling and analytical protocols in the future. An improved emission inventory with high time, spatial and species resolutions should be established. A hybrid model, which integrates emission inventory, chemical transport model, receptor model and observational data is a promising direction to provide an accurate estimate of vehicular emissions in the future. In addition, there is a need to develop a system to verify the results obtained from a source apportionment study.
Many studies have focused on the physicochemical properties of aerosol particles in unusually severe hazeepisodes in North China instead of the more frequent and lesssevere hazes. Consistent with this lack of attention, the morphology and mixing state of organic matter (OM) particles inthe frequent light and moderate (L & M) hazes in winter inthe North China Plain (NCP) have not been examined, eventhough OM dominates these fine particles. In the presentwork, morphology, mixing state, and size of organic aerosolsin the L & M hazes were systematically characterized using transmission electron microscopy coupled with energydispersive X-ray spectroscopy, atomic force microscopy, andnanoscale secondary ion mass spectrometer, with the comparisons among an urban site (Jinan, S1), a mountain site(Mt. Tai, S2), and a background island site (Changdao, S3)in the same hazes. Based on their morphologies, the OM particles were divided into six different types: spherical (type 1),near-spherical (type 2), irregular (type 3), domelike (type 4),dispersed-OM (type 5), and OM-coating (type 6). In the threesampling sites, types 1–3 of OM particles were most abundant in the L & M hazes and most of them were internallymixed with non-OM particles. The abundant near-sphericalOM particles with higher sphericity and lower aspect ratioindicate that these primary OM particles formed in the cooling process after polluted plumes were emitted from coalcombustion and biomass burning. Based on the Si-O-C ratio in OM particles, we estimated that 71 % of type 1–3 OMparticles were associated with coal combustion. Our resultsuggests that coal combustion in residential stoves was awidespread source from urban to rural areas in NCP. AverageOM thickness which correlates with the age of the air massesin type 6 particles only slightly increased from S1 to S2 to S3,suggesting that the L & M hazes were usually dry (relativehumidity < 60 %) with weak photochemistry and heterogeneous reactions between particles and gases. We concludethat the direct emissions from these coal stoves without anypollution controls in rural areas and in urban outskirts contribute large amounts of primary OM particles to the regionalL & M hazes in North China.
Aerosol acidity plays an important role in atmospheric chemistry. China emits large amounts of SO2, NOx, and NH3 into the atmosphere, but aerosol acidity is poorly characterized. In this study, simultaneous 1-h measurements of particulate and gaseous compositions along with the ISORROPIA-II thermodynamic equilibrium model were used to study aerosol acidity during severe haze episodes in northern China. The summed concentration of sulfate, nitrate and ammonium was 135 ± 51 μg/m3 with a maximum of 250 μg/m3, and the gas-phase NH3 mixing ratio was 22 ± 9 ppb. Fine particles were moderately acidic, with a pH range of 3.0−4.9 and an average of 4.2, which was higher than those in the United States and Europe.Excess NH3 and high aerosol water content are responsible for the relatively lower aerosol acidity. These results suggests that the new pathways for sulfate production in China proposed by recent studies should be revisited.