Particulate matter is a component of ambient air pollution that has been linked to millions of annual premature deaths globally
. Assessments of the chronic and acute effects of particulate matter on ...human health tend to be based on mass concentration, with particle size and composition also thought to play a part
. Oxidative potential has been suggested to be one of the many possible drivers of the acute health effects of particulate matter, but the link remains uncertain
. Studies investigating the particulate-matter components that manifest an oxidative activity have yielded conflicting results
. In consequence, there is still much to be learned about the sources of particulate matter that may control the oxidative potential concentration
. Here we use field observations and air-quality modelling to quantify the major primary and secondary sources of particulate matter and of oxidative potential in Europe. We find that secondary inorganic components, crustal material and secondary biogenic organic aerosols control the mass concentration of particulate matter. By contrast, oxidative potential concentration is associated mostly with anthropogenic sources, in particular with fine-mode secondary organic aerosols largely from residential biomass burning and coarse-mode metals from vehicular non-exhaust emissions. Our results suggest that mitigation strategies aimed at reducing the mass concentrations of particulate matter alone may not reduce the oxidative potential concentration. If the oxidative potential can be linked to major health impacts, it may be more effective to control specific sources of particulate matter rather than overall particulate mass.
The North China Plain (NCP) frequently experiences heavy haze pollution, particularly during wintertime. In winter 2015–2016, the NCP region suffered several extremely severe haze episodes with air ...pollution red alerts issued in many cities. We have investigated the sources and aerosol evolution processes of the severe pollution episodes in Handan, a typical industrialized city in the NCP region, using real-time measurements from an intensive field campaign during the winter of 2015–2016. The average (±1σ) concentration of submicron aerosol (PM1) during 3 December 2015–5 February 2016 was 187.6 (±137.5) µg m−3, with the hourly maximum reaching 700.8 µg m−3. Organic was the most abundant component, on average accounting for 45 % of total PM1 mass, followed by sulfate (15 %), nitrate (14 %), ammonium (12 %), chloride (9 %) and black carbon (BC, 5 %). Positive matrix factorization (PMF) with the multilinear engine (ME-2) algorithm identified four major organic aerosol (OA) sources, including traffic emissions represented by a hydrocarbon-like OA (HOA, 7 % of total OA), industrial and residential burning of coal represented by a coal combustion OA (CCOA, 29 % of total OA), open and domestic combustion of wood and crop residuals represented by a biomass burning OA (BBOA, 25 % of total OA), and formation of secondary OA (SOA) in the atmosphere represented by an oxygenated OA (OOA, 39 % of total OA). Emissions of primary OA (POA), which together accounted for 61 % of total OA and 27 % of PM1, are a major cause of air pollution during the winter. Our analysis further uncovered that primary emissions from coal combustion and biomass burning together with secondary formation of sulfate (mainly from SO2 emitted by coal combustion) are important driving factors for haze evolution. However, the bulk composition of PM1 showed comparatively small variations between less polluted periods (daily PM2. 5 ≤ 75 µg m−3) and severely polluted periods (daily PM2. 5 > 75 µg m−3), indicating relatively synchronous increases of all aerosol species during haze formation. The case study of a severe haze episode, which lasted 8 days starting with a steady buildup of aerosol pollution followed by a persistently high level of PM1 (326.7–700.8 µg m−3), revealed the significant influence of stagnant meteorological conditions which acerbate air pollution in the Handan region. The haze episode ended with a shift of wind which brought in cleaner air masses from the northwest of Handan and gradually reduced PM1 concentration to < 50 µg m−3 after 12 h. Aqueous-phase reactions under higher relative humidity (RH) were found to significantly promote the production of secondary inorganic species (especially sulfate) but showed little influence on SOA.
Rapid industrialization and urbanization in developing countries has led to an increase in air pollution, along a similar trajectory to that previously experienced by the developed nations. In China, ...particulate pollution is a serious environmental problem that is influencing air quality, regional and global climates, and human health. In response to the extremely severe and persistent haze pollution experienced by about 800 million people during the first quarter of 2013 (refs 4, 5), the Chinese State Council announced its aim to reduce concentrations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 micrometres) by up to 25 per cent relative to 2012 levels by 2017 (ref. 6). Such efforts however require elucidation of the factors governing the abundance and composition of PM2.5, which remain poorly constrained in China. Here we combine a comprehensive set of novel and state-of-the-art offline analytical approaches and statistical techniques to investigate the chemical nature and sources of particulate matter at urban locations in Beijing, Shanghai, Guangzhou and Xi'an during January 2013. We find that the severe haze pollution event was driven to a large extent by secondary aerosol formation, which contributed 30-77 per cent and 44-71 per cent (average for all four cities) of PM2.5 and of organic aerosol, respectively. On average, the contribution of secondary organic aerosol (SOA) and secondary inorganic aerosol (SIA) are found to be of similar importance (SOA/SIA ratios range from 0.6 to 1.4). Our results suggest that, in addition to mitigating primary particulate emissions, reducing the emissions of secondary aerosol precursors from, for example, fossil fuel combustion and biomass burning is likely to be important for controlling China's PM2.5 levels and for reducing the environmental, economic and health impacts resulting from particulate pollution.
Organic aerosol (OA) represents a large fraction of submicron aerosols in the
megacity of Beijing, yet long-term characterization of its sources and
variations is very limited. Here we present an ...analysis of in situ
measurements of OA in submicrometer particles with an aerosol chemical
speciation monitor (ACSM) for 2 years from July 2011 to May 2013. The sources
of OA are analyzed with a multilinear engine (ME-2) by constraining three
primary OA factors including fossil-fuel-related OA (FFOA), cooking OA (COA),
and biomass burning OA (BBOA). Two secondary OAs (SOA), representing a less
oxidized oxygenated OA (LO-OOA) and a more oxidized (MO-OOA), are identified
during all seasons. The monthly average concentration OA varied from 13.6 to
46.7 µg m−3 with a strong seasonal pattern that is usually
highest in winter and lowest in summer. FFOA and BBOA show similarly
pronounced seasonal variations with much higher concentrations and
contributions in winter due to enhanced coal combustion and biomass burning
emissions. The contribution of COA to OA, however, is relatively stable
(10–15 %) across different seasons, yet presents significantly higher
values at low relative humidity levels (RH < 30 %),
highlighting the important role of COA during clean periods. The two SOA
factors present very different seasonal variations. The pronounced
enhancement of LO-OOA concentrations in winter indicates that emissions from
combustion-related primary emissions could be a considerable source of SOA
under low-temperature (T) conditions. Comparatively, MO-OOA shows high
concentrations consistently at high RH levels across different T levels,
and the contribution of MO-OOA to OA is different seasonally with lower
values occurring more in winter (30–34 %) than other seasons
(47–64 %). Overall, SOA (= LO-OOA + MO-OOA) dominates OA
composition during all seasons by contributing 52–64 % of the total OA
mass in the heating season and 65–75 % in non-heating seasons. The
variations in OA composition as a function of OA mass loading further
illustrate the dominant role of SOA in OA across different mass loading
scenarios during all seasons. However, we also observed a large increase in
FFOA associated with a corresponding decrease in MO-OOA during periods with
high OA mass loadings in the heating season, illustrating an enhanced role of
coal combustion emissions during highly polluted episodes. Potential source
contribution function analysis further shows that the transport from the
regions located to the south and southwest of Beijing within ∼ 250 km
can contribute substantially to high FFOA and BBOA concentrations in the
heating season.
The formation and evolution of secondary organic aerosol
(SOA) were investigated at Yorkville, GA, in late summer (mid-August to mid-October 2016). The organic aerosol (OA) composition was
measured ...using two online mass spectrometry instruments, the
high-resolution time-of-flight aerosol mass spectrometer (AMS) and the
Filter Inlet for Gases and AEROsols coupled to a high-resolution
time-of-flight iodide-adduct chemical ionization mass spectrometer
(FIGAERO-CIMS). Through analysis of speciated organics data from
FIGAERO-CIMS and factorization analysis of data obtained from both
instruments, we observed notable SOA formation from isoprene and
monoterpenes during both day and night. Specifically, in addition to
isoprene epoxydiol (IEPOX) uptake, we identified isoprene SOA formation from non-IEPOX pathways
and isoprene organic nitrate formation via photooxidation in the presence of
NOx and nitrate radical oxidation. Monoterpenes were found to be the
most important SOA precursors at night. We observed significant
contributions from highly oxidized acid-like compounds to the aged OA factor
from FIGAERO-CIMS. Taken together, our results showed that FIGAERO-CIMS
measurements are highly complementary to the extensively used AMS
factorization analysis, and together they provide more comprehensive
insights into OA sources and composition.
Delhi is one of the most polluted cities worldwide and a comprehensive understanding and deeper insight into the air pollution and its sources is of high importance. We report 5 months of highly ...time-resolved measurements of non-refractory PM2.5 and black carbon (BC). Additionally, source apportionment based on positive matrix factorization (PMF) of the organic aerosol (OA) fraction is presented. The highest pollution levels are observed during winter in December/January. During that time, also uniquely high chloride concentrations are measured, which are sometimes even the most dominant NR-species in the morning hours. With increasing temperature, the total PM2.5 concentration decreases steadily, whereas the chloride concentrations decrease sharply. The concentrations measured in May are roughly 6 times lower than in December/January. PMF analysis resolves two primary factors, namely hydrocarbon-like (traffic-related) OA (HOA) and solid fuel combustion OA (SFC-OA), and one or two secondary factors depending on the season. The uncertainties of the PMF analysis are assessed by combining the random a-value approach and the bootstrap resampling technique of the PMF input. The uncertainties for the resolved factors range from ±18% to ±19% for HOA, ±7% to ±19% for SFC-OA and ±6 % to ±11% for the OOAs. The average correlation of HOA with equivalent black carbon from traffic (eBCtr) is R2 = 0.40, while SFC-OA has a correlation of R2 = 0.78 with equivalent black carbon from solid fuel combustion (eBCsf). Anthracene (m/z 178) and pyrene (m/z 202) (PAHs) are mostly explained by SFC-OA and follow its diurnal trend (R2 = 0.98 and R2 = 0.97). The secondary oxygenated aerosols are dominant during daytime. The average contribution during the afternoon hours (1 pm–5 pm) is 59% to the total OA mass, with contributions up to 96% in May. In contrast, the primary sources are more important during nighttime: the mean nightly contribution (22 pm–3 am) to the total OA mass is 48%, with contributions up to 88% during some episodes in April.
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•Over 65% of the daily PM2.5 concentrations exceed the national air quality standard.•Exceptionally high chloride contribution during early mornings in the cold period•Significant solid fuel combustion contribution throughout the full campaign•PMF uncertainty assessment
The measurement of elements in PM10 was performed with 1 h time resolution at a rural freeway site during summer 2015 in Switzerland using the Xact1 625 Ambient Metals Monitor. On average the Xact ...elements (without accounting for oxygen and other associated elements) make up about 20 % of the total PM10 mass (14.6 µg m−3). We conducted source apportionment by positive matrix factorisation (PMF) of the
elemental mass measurable by the Xact (i.e. major elements heavier than
Al), defined here as PM10el. Eight different sources were identified in PM10el (elemental PM10) mass driven by the sum of 14 elements (notable elements in brackets): Fireworks-I (K, S, Ba and Cl), Fireworks-II (K), sea salt (Cl), secondary sulfate (S), background dust (Si, Ti), road dust (Ca), non-exhaust traffic-related elements (Fe) and industrial elements (Zn and Pb). The major components were secondary sulfate and non-exhaust traffic-related elements followed by background dust and road dust factors, explaining 21 %, 20 %, 18 % and 16 % of the analysed PM10 elemental mass, respectively, with the factor mass not corrected for oxygen content. Further, there were minor contributions (on the order of a few percent) of sea salt and industrial sources. The regionally influenced secondary sulfate factor showed negligible resuspension, and concentrations were similar throughout the day. The significant loads of the non-exhaust traffic-related and road dust factors with strong diurnal variations highlight the continuing importance of vehicle-related air pollutants at this site. Enhanced control of PMF implemented via the SourceFinder software (SoFi Pro version 6.2, PSI, Switzerland) allowed for a successful apportionment of transient sources such as the two firework factors and sea salt, which remained mixed when analysed by unconstrained PMF.
Particulate matter (PM) pollution is a severe environmental problem in the Beijing–Tianjin–Hebei (BTH) region in North
China. PM studies have been conducted extensively in Beijing, but the
chemical ...composition, sources, and atmospheric processes of PM are still
relatively less known in nearby Tianjin and Hebei. In this study, fine PM
in urban Shijiazhuang (the capital of Hebei Province) was characterized using
an Aerodyne quadrupole aerosol chemical speciation monitor (Q-ACSM) from
11 January to 18 February in 2014. The average mass concentration of
non-refractory submicron PM (diameter <1 µm, NR-PM1) was
178±101 µg m−3, and it was composed of 50 % organic aerosol
(OA), 21 % sulfate, 12 % nitrate, 11 % ammonium, and 6 % chloride.
Using the multilinear engine (ME-2) receptor model, five OA sources were
identified and quantified, including hydrocarbon-like OA from vehicle
emissions (HOA, 13 %), cooking OA (COA, 16 %), biomass burning OA (BBOA,
17 %), coal combustion OA (CCOA, 27 %), and oxygenated OA (OOA, 27 %).
We found that secondary formation contributed substantially to PM in episodic
events, whereas primary emissions were dominant (most significant) on average.
The episodic events with the highest NR-PM1 mass range of
300–360 µg m−3 were comprised of 55 % of secondary species. On the
contrary, a campaign-average low OOA fraction (27 %) in OA indicated the
importance of primary emissions, and a low sulfur oxidation degree
(FSO4) of 0.18 even at RH >90 % hinted at insufficient
oxidation. These results suggested that in Shijiazhuang in wintertime fine PM
was mostly from primary emissions without sufficient atmospheric aging,
indicating opportunities for air quality improvement by mitigating direct
emissions. In addition, secondary inorganic and organic (OOA) species
dominated in pollution events with high-RH conditions, most likely due to
enhanced aqueous-phase chemistry, whereas primary organic aerosol (POA)
dominated in pollution events with low-RH and stagnant conditions. These
results also highlighted the importance of meteorological conditions for PM
pollution in this highly polluted city in North China.
Long-term monitoring of organic aerosol is important for epidemiological studies, validation of atmospheric models, and air quality management. In this study, we apply a recently developed ...filter-based offline methodology using an aerosol mass spectrometer (AMS) to investigate the regional and seasonal differences of contributing organic aerosol sources. We present offline AMS measurements for particulate matter smaller than 10 µm at nine stations in central Europe with different exposure characteristics for the entire year of 2013 (819 samples). The focus of this study is a detailed source apportionment analysis (using positive matrix factorization, PMF) including in-depth assessment of the related uncertainties. Primary organic aerosol (POA) is separated in three components: hydrocarbon-like OA related to traffic emissions (HOA), cooking OA (COA), and biomass burning OA (BBOA). We observe enhanced production of secondary organic aerosol (SOA) in summer, following the increase in biogenic emissions with temperature (summer oxygenated OA, SOOA). In addition, a SOA component was extracted that correlated with an anthropogenic secondary inorganic species that is dominant in winter (winter oxygenated OA, WOOA). A factor (sulfur-containing organic, SC-OA) explaining sulfur-containing fragments (CH3SO2+), which has an event-driven temporal behaviour, was also identified. The relative yearly average factor contributions range from 4 to 14 % for HOA, from 3 to 11 % for COA, from 11 to 59 % for BBOA, from 5 to 23 % for SC-OA, from 14 to 27 % for WOOA, and from 15 to 38 % for SOOA. The uncertainty of the relative average factor contribution lies between 2 and 12 % of OA. At the sites north of the alpine crest, the sum of HOA, COA, and BBOA (POA) contributes less to OA (POA / OA = 0.3) than at the southern alpine valley sites (0.6). BBOA is the main contributor to POA with 87 % in alpine valleys and 42 % north of the alpine crest. Furthermore, the influence of primary biological particles (PBOAs), not resolved by PMF, is estimated and could contribute significantly to OA in PM10.
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