Vehicle Exhaust Sources Research Articles

Pollution Characteristics and Source Apportionment of VOCs in Urban Areas of Shijiazhuang in Spring

Samples of ambient volatile organic compounds （VOCs） were collected using SUMMA canisters at three Country Control Sites in Shijiazhuang during the spring of 2019, 2021, and 2022, which were detected using gas chromatography/mass spectrometry （GC/MS）. To investigate the characteristics and temporal variations of VOCs mass concentration levels, the online monitoring data of ozone （O3） and PM2.5 at the same site were also collected. Subsequently, the ozone formation potential （OFP） and secondary organic aerosol formation potential （SOAFP） were utilized to assess the chemical activity of VOCs. Additionally, the potential source areas of VOCs in spring in Shijiazhuang were further identified using the potential source contribution factor （PSCF） method and concentration weight trajectory analysis （CWT）. Hence, the major VOCs sources were evaluated with the VOCs initial mixing ratio. The results demonstrated that the averaged concentration of VOCs during the polluted period and clean period of spring in Shijiazhuang were 191.17 μg·m-3 and 122.18 μg·m-3, respectively. Meanwhile, the OFP was 361.23 μg·m-3 during the polluted period and 266.96 μg·m-3 during the clean period, whereas the SOAFP was 1.98 μg·m-3 and 1.61 μg·m-3, respectively. Therefore, effective control of benzene, toluene, ethylbenzene, and xylene （BTEX） is crucial for reducing PM2.5 and O3 pollution. Based on the results obtained from weight PSCF and CWT, the potential source areas of VOCs were further identified to be primarily located in the eastern Yuhua District, the high-tech district, and the northern Luancheng District of Shijiazhuang. These areas were influenced not only by local emissions but also by transport from neighboring regions, in which consistency between the CWT and PSCF results further supported these findings. Furthermore, the results obtained from the benzene/toluene/ethylbenzene （B/T/E） and xylene/benzene （X/B） ratios indicated that the main sources of VOCs in Shijiazhuang in spring were vehicle exhaust sources and burning sources, leading to a more serious air mass aging phenomenon. Hence, controlling vehicle emissions and implementing regional cooperative measures are the effective strategies for optimizing the air quality of Shijiazhuang.

Analysis of Ozone and VOCs Pollution Characteristics, Sources, and Abatement Control Strategies in Hebi

In order to control the increasing ozone （O3） pollution in Hebi, Henan Province, clarifying the pollution characteristics of ozone and its precursors is vital. Therefore, we conducted a comprehensive analysis of O3 pollution utilizing the OFP-PMF-EKMA method combined with online hourly resolution monitoring data of conventional pollutants and volatile organic compounds （VOCs） in the summer of 2022 （June-September）. Ozone formation potential （OFP） was used to identify the key VOCs species, and the PMF model was used to identify the VOCs emission sources, whereas EKMA curves and scenario analysis were used to identify the main ozone control area in Hebi and to determine the reduction ratio of VOCs and NOx in a scientifically refined way. In 2022, Hebi had persistent O3 pollution, with the highest concentration in June. Conditions of high temperature, low humidity, and low atmospheric pressure contributed to the O3 accumulation. Aromatic and oxygenated volatile organic compounds （OVOCs） contributed significantly to the OFP and VOCs fraction, which were the dominant active substance and concentration dominant species. The results of the VOCs source analysis indicated that vehicle exhaust sources （25.3%） were the main source of atmospheric VOCs, followed by process sources （17.7%） and biomass combustion sources （17.6%）. Thus, emission sources associated with the combustion of fossil fuels and industrial production emissions were the most urgent sources of atmospheric VOCs to be controlled in Hebi. The O3 generation in Hebi occurred in the VOCs-sensitive zones, and the emission reduction results showed that a synergistic emission reduction of VOCs and nitrogen oxide （NOx） could effectively control O3 pollution with a 75% reduction in VOCs and a 10% reduction in NOx.

Particle Size, Effects of Distance and Height from Source, Carbon Components, and Source of Dust in Nanchang, Central China

Regional air quality and major sources can be reflected by dust. 87 dust samples in Nanchang (four residential areas and three roadside points) were collected, with particle size and carbon components determined to discuss the distribution characteristics and the sources. The distribution of dust particle size in different sampling areas was similar, composed mainly of particles larger than 10 μm (over 69.8%). Dust particle size showed a decreasing trend with increasing horizontal distance from the main road and vertical height from the ground. EC in road dust was higher than that in residential dust. EC outdoors was higher than EC indoors in the same area. OC in indoor dust was higher than that in atmospheric dust when there were obvious indoor OC emission sources. The main carbon fractions in residential dust were OC3 and EC1, and in road dust were EC2 and OC3. The distribution of carbon fractions showed that OC3 and EC2 were mainly affected by human activities and motor vehicle emissions, respectively. The ratio of OC/EC and SOC in dust decreased from autumn to winter. SOC in the dust of Nanchang was at a medium level compared to other cities/regions around world. Clustering analysis and principal component analysis indicated that combustion sources (coal and biomass combustion, etc.), motor vehicle exhaust sources (gasoline and diesel vehicles), and human sources (cooking fumes, cigarette smoking, etc.) were the main contributors to the carbon components in dust.

Aerosol source apportionment uncertainty linked to the choice of input chemical components

For a Positive Matrix Factorization (PMF) aerosol source apportionment (SA) studies there is no standard procedure to select the most appropriate chemical components to be included in the input dataset for a given site typology, nor specific recommendations in this direction. However, these choices are crucial for the final SA outputs not only in terms of number of sources identified but also, and consequently, in the source contributions estimates. In fact, PMF tends to reproduce most of PM mass measured independently and introduced as a total variable in the input data, regardless of the percentage of PM mass which has been chemically characterized, so that the lack of some specific source tracers (e.g. levoglucosan) can potentially affect the results of the whole source apportionment study. The present study elaborates further on the same concept, evaluating quantitatively the impact of lacking specific sources’ tracers on the whole source apportionment, both in terms of identified sources and source contributions. This work aims to provide first recommendations on the most suitable and critical components to be included in PMF analyses in order to reduce PMF output uncertainty as much as possible, and better represent the most commons PM sources observed in many sites in Western countries. To this aim, we performed three sensitivity analyses on three different datasets across EU, including extended sets of organic tracers, in order to cover different types of urban conditions (Mediterranean, Continental, and Alpine), source types, and PM fractions. Our findings reveal that the vehicle exhaust source resulted to be less sensitive to the choice of analytes, although source contributions estimates can deviate significantly up to 44 %. On the other hand, for the detection of the non-exhaust one is clearly necessary to analyze specific inorganic elements. The choice of not analysing non-polar organics likely causes the loss of separation of exhaust and non-exhaust factors, thus obtaining a unique road traffic source, which provokes a significant bias of total contribution. Levoglucosan was, in most cases, crucial to identify biomass burning contributions in Milan and in Barcelona, in spite of the presence of PAHs in Barcelona, while for the case of Grenoble, even discarding levoglucosan, the presence of PAHs allowed identifying the BB factor. Modifying the rest of analytes provoke a systematic underestimation of biomass burning source contributions. SIA factors resulted to be generally overestimated with respect to the base case analysis, also in the case that ions were not included in the PMF analysis. Trace elements were crucial to identify shipping emissions (V and Ni) and industrial sources (Pb, Ni, Br, Zn, Mn, Cd and As). When changing the rest of input variables, the uncertainty was narrow for shipping but large for industrial processes. Major and trace elements were also crucial to identify the mineral/soil factor at all cities. Biogenic SOA and Anthropogenic SOA factors were sensitive to the presence of their molecular tracers, since the availability of OC alone is unable to separate a SOA factor. Arabitol and sorbitol were crucial to detecting fungal spores while odd number of higher alkanes (C27 to C31) for plant debris.

Influence of anthropogenic activities and loess dusts on the rainwater hydrochemistry in the Chinese Loess Plateau

Rainwater hydrochemistry is an important indicator for tracing anthropogenic input on air quality. As the fastest economically developing city in the northwestern China and the Chinese Loess Plateau, rainwater chemistry, sources of dissolved solutes, and the influence of loess dust on rainwater chemistry in Xi'an city is unclear. Inorganic ions, δD and δ18O of two years' rainwater samples were measured to decipher the above issues. Rainwater samples were weakly alkaline (pH = 7.2) with the mean total dissolved solids (TDS) values of 43 mg/L. NH4+ and Ca2+ dominated in the cations and SO42− and NO3− dominated in the anions. The wet deposition of sulfur (S) and nitrogen (N) was 70.9 ± 67 mg·(m2·month)−1 and 244.8 ± 270.9 mg·(m2·month)−1, respectively. The meteoric water line in Xi'an was δD = 7.29δ18O+3.72 (R2 = 0.99). δD, δ18O, and d-excess analysis indicated the influence of evaporation on the dissolved solutes in rainwater, especially in the dry season. Rainwater acidity in the Xi'an city was mainly neutralized by Ca2+ and NH4+, and the neutralization ability in Xi'an city is higher than the southern China cities. Correlation analysis (CA), positive matrix factorization (PMF), and the backward air masses trajectory model identified high NH4+ and Ca2+ in rainwater were mainly originated from local agricultural activities and loess dust, while NO3− and SO42− were associated with local coal combustion and vehicle exhaust sources. High inputs of dusts and coal combustion in spring and winter resulted in elevated values of pH and major ions in Xi'an. Due to the air pollution control policy, air quality in Xi'an is getting better in recent years. Our study highlights the influence of anthropogenic activities and loess dusts on the rainwater hydrochemistry in Xi'an and provides important dataset for air pollution control for other cities in semi-arid and arid regions.

Volatile Organic Compounds in the North China Plain: Characteristics, Sources, and Effects on Ozone Formation

Enhanced volatile organic compounds (VOCs) observations were made on ozone-exceeding days in June 2020 in Linyi, China. A total of 69 VOCs were collected (1 alkyne, 29 alkanes, 10 alkenes, 14 aromatic hydrocarbons, and 15 oxygenated volatile organic compounds (OVOCs)). The average concentration of total VOCs (TVOCs) was 36.0 ± 0.66 ppb, and the top three VOCs components were alkanes, OVOCs, and aromatic hydrocarbons, which accounted for 40.75%, 27.02%, and 11.30%, respectively. Based on the positive matrix factorization (PMF) model, the main sources of VOCs in Linyi City were divided into vehicle exhaust sources (39.11%), biomass combustion sources (21.82%), oil and gas volatilization sources (21.46%), and solvent use sources (17.61%). The ozone formation potential (OFP) contribution rate was dominated by alkenes, OVOCs, and aromatics, with contribution rates of 26.37%, 25.30%, and 23.65%, respectively. The top six VOCs that contributed the most to the OFP were formaldehyde, acetaldehyde, 1-butene, butadiene, trans-2-butene, and propylene. The empirical kinetic modelling approach (EKMA) curve indicated that the in situ ozone (O3) production was limited by VOCs, and reducing the concentration of O3 precursors in accordance with the VOCs/NOx concentration ratio of 1.15 can control O3 pollution more effectively.

Characterization of PM2.5 in Coastal Urban Area, Northwest Morocco: Seasonal Variations, Elemental Composition and Source Apportionment

Sale, located along the Atlantic Ocean, is the third-largest city in Morocco. The Bouregreg river separates Sale from Rabat (Morocco’s capital city). This City is characterized by a high demographic density. Their main air pollution sources are traffic, ocean, potteries, fishing, domestic heating, and artisanal activities. Ambient PM2.5 particles were collected in an urban area of Sale City (Morocco) from July 2018 to July 2019. The sampling was carried out using a Dichotomous sampler and the Total X-Ray Fluorescence technique (TXRF) was used to evaluate the elemental composition of the collected filters. In this paper, chemical characterization, and source apportionment of PM2.5 were investigated. The results showed that the PM2.5 mass concentrations vary, during the sampling period, from 3.08 µg/m3 to 49.48 µg/m3 with an average of 17.30 µg/m3. The highest values were observed in winter while the lowest in summer. The influence of atmospheric transport scenarios on the levels of PM was carried out using air mass back-trajectories, using the HYSPLIT™ model. This study allowed identifying four main clusters arriving at our receptor site in Sale City: Iberian Coast (24%), Near Atlantic Ocean (33%), Local (28%), and Oceanic (15%). For seasonal variations of metal concentrations, K, Ca, V, Mn, Fe, Ni, Cu, Zn, As, Sr, Ba, and Pb exhibited their highest concentrations during winter while Ti and Cr, their highest concentrations were observed during Autumn. The Enrichment Factor (EF) analysis showed that Ti, Sr, Mn, K, Ca, and Ba are mainly originated from airborne dust with EF < 10, V, Cu, Cr have both natural and anthropogenic sources with 10 < EF < 100, while Ni, Zn, and Pb were mainly from anthropogenic source with EF > 100. Five factors were selected in Positive Matrix Factorization (PMF) model’s analysis: crustal contribution, road dust, brake wear, heavy oil combustion, and exhaust vehicle emissions. Their contributions to PM2.5 were 5%, 53.6%, 20.1%, 14.3% and 7%, respectively. Road dust and vehicle exhaust sources showed the highest contribution in winter; while soil dust, brake wear, and oil combustion sources contributed the most in summer. The present study could be considered as the first source apportionment study on PM2.5 fractions carried out in Sale City, Morocco.

Seasonal source analysis of nitrogen and carbon aerosols of PM2.5 in typical cities of Zhejiang, China

Fine particulate matter (PM2.5) significantly impacts global air quality and human health due to its smaller particle size and larger specific surface area. Nitrogen and carbon aerosols, as the main components of PM2.5, play key roles in air pollution. This study identified the sources and seasonal variation of nitrogen and carbon aerosols in PM2.5 in typical cities of Zhejiang. The annual average PM2.5 concentrations of Hangzhou (HZ), Ningbo (NB), and Huzhou (HUZ) were 39.8 ± 19.1 μg m−‍3, 40.0 ± 21.5 μg m−3, and 50.1 ± 22.6 μg m−3, respectively, which exceeded the Chinese air quality limit of 35.0 μg m−3. The results showed that the concentrations of nitrogen aerosols (NO3− and NH4+) in water-soluble inorganic ions were higher at 9.6 ± 4.6 μg m−3, 9.0 ± 4.5 μg m−3 and 11.5 ± 5.4 μg m−3 in HZ, NB and HUZ, respectively, especially in winter, accounting for over 60% of the total. The annual average δ15N values of PM2.5 were 6.2 ± 1.9‰, 6.4 ± 2.2‰ and 6.7 ± 1.9‰ in HZ, NB and HZ, respectively; the δ15N values in winter were relatively low. A Bayesian isotopic mixing model was employed to analyse the sources of nitrogen aerosols in winter; the results showed that nitrogen concentration was mainly affected by NH3 and NOX emitted by motor vehicle exhaust, coal combustion, biomass combustion, biogenic soil emissions, animal wastes and ocean evaporation (NB). In addition, the carbon component analysis of PM2.5 showed that the annual average mass concentration of TC accounted for 18.7%, 16.4% and 20.1% of PM2.5 in HZ, HUZ and NB, respectively. The same isotope model was used to analyse the sources of carbon aerosols; the results showed that carbon aerosols were mainly affected by the sources of motor vehicle exhaust, coal combustion, biomass combustion and dust. In the PM2.5 in Zhejiang, the most contributory sources of nitrogenous aerosols and carbon aerosols were motor vehicle exhaust sources.

Characteristics and Source Apportionment of Vehicular VOCs Emissions in a Tunnel Study

To explore the emission characteristics of volatile organic compounds (VOCs) from vehicular exhaust sources and evaporative sources with ethanol gasoline (E10) as the main fuel, VOCs sampling campaigns were carried out in the north third ring tunnel of Zhengzhou city for two consecutive weeks in December 2019. In addition, the characteristics of traffic flow and environmental information were also monitored in the tunnel. Firstly, 106 VOCs were quantified using gas chromatography/mass spectrometry (GC/MS), and then source apportionment of VOCs in the tunnel was carried out using a positive matrix factorization (PMF5.0)-chemical mass balance (CMB8.2) composite model. Finally, the ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) of vehicle exhaust sources and evaporative sources were analyzed using the maximum incremental reactivity (MIR) and fractional aerosol coefficient (FAC). The results showed that ρ(VOCs) in the tunnel was (2794.5±147.4) μg·m-3 during the experiment, among which halogenated hydrocarbons[(32.4±2.0)%] accounted for the highest proportion, followed by aromatic hydrocarbons[(27.5±0.6)%] and alkanes[(23.3±0.8)%]. Source apportionment of vehicular VOCs showed that exhaust emissions (62.5%)>evaporative emissions (37.5%), whereas the contribution of OFP was that exhaust emissions (71.9%)>evaporative emissions (28.1%), and the contribution of SOAFP was that exhaust emissions (75.8%)>evaporative emissions (24.2%). The dominant components of OFP in evaporative sources were m,p-diethylbenzene, isoprene, and trans-2-pentene, whereas m,p-diethylbenzene, m,p-xylene, and 1,2,3-trimethylbenzene were the dominant components of SOAFP. The major components of OFP in exhaust sources were m,p-xylene, 1,2,4-trimethylbenzene, and 1,3,5-trimethylbenzene, whereas m,p-xylene, m,p-diethylbenzene, and 1,3,5-trimethylbenzene were the dominant components of SOAFP. In regions where ethanol gasoline is used, special attention should be paid not only to the exhaust emissions control but also to strengthening the emissions reduction of VOCs from vehicle evaporative sources, especially the high active components such as aromatic hydrocarbons and alkenes.

Characteristics, Ozone Formation Potential, and Source Apportionment of VOCs During the COVID-19 Epidemic in Xiong'an

Many restrictive measures were implemented in China from January-February 2020 to control the rapid spread of COVID-19. Many studies reported that the COVID-19 lockdown impacted PM2.5, SO2, volatile organic compounds (VOCs), etc. VOCs play important roles in the production of ozone and PM2.5. Ambient VOCs in Xiong'an were measured from December 25, 2019 to January 24, 2020 (prior to epidemic prevention, P1) and from January 25, 2020 to February 24, 2020 (during epidemic prevention, P2) through a VOCs online instrument. In the study, VOCs characteristics and ozone generation potential (OFP) of ambient VOCs were analyzed, and source apportionment of VOCs were analyzed by using Positive Matrix Factorization (PMF). The results showed that φ(TVOCs) during epidemic prevention and control was 45.1×10-9, which was approximately half of that before epidemic prevention and control (90.5×10-9). The chemical composition of VOCs showed significant changes after epidemic prevention and control, the contribution rate of alkanes increased from 37.6% to 53.8%, and the contribution rate of aromatic hydrocarbons and halogenated hydrocarbons decreased from 13.3% and 12.0% to 7.5% and 7.8%, respectively. Aromatic hydrocarbons, halogenated hydrocarbons, and OVOCs decreased by more than 60%. Seven types of the top ten species were the same before and during the epidemic prevention and control, mainly low-carbon alkanes, olefins, aldehydes, and ketones. Dichloromethane, trichloromethane, and BTEXs decreased significantly. The OPP was 566 μg·m-3 and 231 μg·m-3 in P1 and P2, respectively. The OPP of VOCs decreased by more than 30%. The proportion of OFP contribution of aromatic hydrocarbons decreased significantly after the epidemic prevention and control, and the proportion of OFP contribution of alkanes and alkynes increased significantly. Positive matrix factorization (PMF) was then applied for VOCs sources apportionment. Six sources were identified, including background sources, oil-gas volatile sources, combustion sources, industrial sources, solvent use sources, and vehicle exhaust sources. The results showed that after the epidemic prevention and control, the contribution rate of solvent use sources to TVOCs decreased from 24% to 9%. The contribution rates of background sources, oil-gas volatile sources, and combustion sources increased from 13%, 34%, and 24% to 6%, 14%, and 13%, respectively. The relative contributions of vehicle exhaust sources before and after epidemic prevention and control were 21% and 18%, respectively. The observation points were affected by the emission of VOCs from paroxysmal industrial sources before the epidemic prevention and control. The emission was stopped after the epidemic prevention and control, and its contribution rate was reduced from 22% before the epidemic prevention and control to 1%. The concentrations of industrial sources, solvent sources, motor vehicle tail gas sources, and combustion sources decreased by 97%, 82%, 61%, and 15%, respectively, after the epidemic prevention and control. The concentration of background sources remained stable, and the concentration of oil and gas volatile sources increased by 7%. The control of production and traffic activities cannot reduce the emission of VOCs from oil and gas volatile sources, which is the focus of VOCs control in Xiong'an.

Simultaneous Measurements of Carbonaceous Aerosol in Three Major Cities in the Beijing-Tianjin-Hebei Region, China

Simultaneous observations of carbonaceous aerosols in multiple cities are of great significance for a comprehensive understanding of the level of carbonaceous aerosol pollution in the Beijing-Tianjin-Hebei (BTH) region. In this study, PM2.5 samples were collected simultaneously in Beijing (BJ), Tianjin (TJ), and Shijiazhuang (SJZ) during the 2017–2018 heating season, and the contents of organic carbon (OC) and elemental carbon (EC) in the samples were measured. The mean mass concentrations were 10.15‒46.23 µg m–3 for OC, and 2.13‒10.42 µg m–3 for EC in three cities. SJZ had more serious carbonaceous aerosols pollution compared with BJ and TJ. The OC and EC levels in three cities, especially in Beijing, were significantly lower than those reported in previous studies, implying the effectivity of strict air pollution control measures in 2017. Based on the OC/EC minimum ratio method, the mass concentration of secondary organic carbon (SOC) was estimated, and SOC pollution in BJ was relatively light. Analysis of eight carbonaceous components showed that the gasoline vehicle exhaust sources made high contributions to the levels of carbonaceous aerosols in all three cities. Compared with SJZ, the carbonaceous aerosols in BJ and TJ were more affected by road dust pollution. Analysis of backward trajectory indicated that the carbonaceous aerosols in the three cities were affected by pollution transport from the BTH region and surrounding areas, in addition to local sources. In contrast to the other two cities, OC and EC in SJZ were greatly affected by short-distance air mass transport from Hebei Province.

Associations between Source-Specific Fine Particulate Matter and Mortality and Hospital Admissions in Beijing, China.

The health effects of PM2.5 exposure have become a major public concern in developing countries. Identifying major PM2.5 sources and quantifying the health effects at the population level are essential for controlling PM2.5 pollution and formulating targeted emissions reduction policies. In the current study, we have obtained PM2.5 mass data and used positive matrix factorization to identify the major sources of PM2.5. We evaluated the relationship between short-term exposure to PM2.5 sources and mortality or hospital admissions in Beijing, China, using 441 742 deaths and 9 420 305 hospital admissions from 2013 to 2018. We found positive associations for coal combustion and road dust sources with mortality. Increased hospital admission risks were significantly associated with sources of vehicle exhaust, coal combustion, secondary sulfates, and secondary nitrates. Compared to the cool season, excess mortality risk estimates of coal combustion source were significantly higher in the warm season. Our findings show that reducing more toxic sources of PM2.5, especially coal emissions, and developing clean energy alternatives can have critical implications for improving air quality and protecting public health.

Chemical Composition and Source Analysis of PM2.5 in Yuncheng, Shanxi Province in Autumn and Winter

In order to reveal the chemical composition characteristics and pollution sources of fine particulate matter (PM2.5) in autumn and winter in Yuncheng, PM2.5 samples were continuously collected using a four-channel small-flow particulate sampler from October 15, 2018 to March 15, 2019. The study prediminantly analyzed the chemical components of water-soluble ions, elemental carbon, organic carbon, and metal elements. Additionally, the chemical mass reconstruction method of particulate matter and the positive matrix factorization model (PMF) were combined for an in-depth discussion. During the sample period, the PM2.5 mass concentrations range was 29.37-370.11 μg·m-3, and 101 days during the sampling period exhibited concentrations that were higher than the secondary standard in China's Ambient Air Quality Standards (GB 3095-2012), with an exceeding rate of 70.63%. These results indicate that the air pollution in Yuncheng in autumn and winter is serious. According to the air quality index (AQI), the collected samples are classified as clean, light-moderate pollution, and heavy-severe pollution. Water-soluble ions, OC, EC and metal elements account for 40%, 19%, 5%, and 7% on clean days, 46%, 18%, 4%, and 5% on days with light-moderate pollution, and 46%, 21%, 4%, and 4% on days with heavy-severe pollution, respectively. Secondary ions NO3-, SO42-, and NH4+ are the primary components of water-soluble ions, accounting for 81% (clean days), 87% (light-moderate pollution), and 87% (heavy-severe pollution) of the total ion concentration, respectively. The OC/EC ratios during the sampling period were 3.78 (clean days), 4.02 (light-moderate pollution), and 5.37 (heavy-severe pollution). With the intensification of pollution, the pollution of secondary organic aerosols in the atmosphere becomes increasingly serious. In addition, as the air pollution increased, the concentration of Fe and Cr elements gradually decreased, while the concentration of other metal elements showed an overall upward trend. The results of the chemical mass reconstruction demonstrate that among the different pollution levels of atmospheric PM2.5 in Yuncheng, the mass percentages of secondary inorganic salt, sea salt, heavy metals, mineral dust, construction dust, organic matter, and elemental carbon were 36%, 2%, 2%, 8%, 1%, 33%, and 5% (clean days), 41%, 1%, 1%, 5%, 0.01%, 31%, and 5% (light-moderate pollution), and 41%, 1%, 1%, 4%, 0.004%, 34%, and 4% (heavy-severe pollution). The proportion of secondary inorganic ions increased and mineral dust decreased with the deterioration of air quality. The PMF analysis results suggest that secondary related sources, coal combustion sources, vehicle exhaust sources, biomass burning, and secondary organic matter are the predominant sources of PM2.5 during serious air pollution in Yuncheng.

Ambient VOCs Characteristics, Ozone Formation Potential, and Source Apportionment of Air Pollution in Spring in Zhengzhou

Ambient volatile organic compounds (VOCs) were determined by GC 5000 online gas chromatography in the urban site of Zhengzhou from April 15 to May 15, 2018. Based on chemical composition analysis, in this study, the concentrations, ozone formation potential (OFP), and source apportionment were studied. The results show that the averaged volume fraction of VOCs in Zhengzhou during spring was 40.26×10-9, which was 23% higher on polluted days (44.12×10-9) than on non-polluted days (35.82×10-9). The contribution of VOC species to OFP was in the order: alkenes > aromatics > alkanes > alkyne. The five factors identified by the PMF model were liquefied petroleum gas (LPG) volatilization sources (66.05%), motor vehicle exhaust sources (47.39%), industrial solvent sources (37.51%), fuel combustion sources (37.80%), and biogenic sources (11.25%). The contributions of LPG volatilization sources and biogenic sources on polluted days were higher by 22.92% and 68.50% than on non-polluted days, respectively.

Spatial distribution of greenhouse gases (CO2 and CH4) on expressways in the megacity Shanghai, China.

Carbon dioxide (CO2) and methane (CH4) are the two major greenhouse gases (GHGs) in the atmosphere that contribute to global warming. Vehicle emissions on expressways cannot be neglected in the megacity Shanghai because oil accounts for 41% of the total primary energy consumption, and the expressway network carries 60% of the total traffic volume. The spatial distributions of CO2 and CH4 concentrations were monitored in situ on the expressways and in road tunnels using a mobile vehicle. The average CO2 and CH4 concentrations were 472.88 ± 34.48 ppm and 2033 ± 54 ppb on the expressways and 1308.92 ± 767.48 ppm and 2182 ± 112 ppb in the road tunnels in Shanghai, respectively. The highest CO2 and CH4 concentrations appeared on the Yan'an Elevated Road and the North-South Elevated Road, respectively, while their lowest values both occurred on the Huaxia Elevated Road passing through the suburban area. The hotspots of CO2 and CH4 were not consistent, suggesting that they have different sources. Tunnels had a "push-pull effect" on GHGs, and the traffic-congested Yan'an East Road Tunnel showed a dramatically increasing trend of GHG concentration from the entrance to the exit. This traffic-congested tunnel could accumulate a very high concentration of GHGs as well as other pollutants, which could introduce unhealthy conditions for both drivers and passengers. Significant correlations between CO2 and CH4 mostly appeared on the expressways and in the tunnels in Shanghai, suggesting the influences of vehicle exhaust. ΔCH4/ΔCO2 (the slope of the linear regression between CH4 and CO2) and the CH4/CO2 ratio could be used as indicators of vehicle exhaust sources because it increases from sources (e.g., road tunnels) to the observatories in the urban area.

Observation and Source Apportionment of Trace Gases, Water-Soluble Ions and Carbonaceous Aerosol During a Haze Episode in Wuhan

As the new core region of the haze pollution, the terrain effect of sub-basin and water networks over the Twin-Hu Basin (THB) in the Yangtze River Middle-Reach (YRMR) had great impacts on the variations and distributions of air pollutants. In this study, trace gases (NH3, HNO3, and HCl), water-soluble ions (WSIs), organic carbon (OC), and elemental carbon (EC) were measured in PM2.5 from 9 January to 27 January 2018, in Wuhan using monitoring for aerosols and gases (MARGA) and a semi-continuous OC/EC analyzer (Model RT-4). The characteristics of air pollutants during a haze episode were discussed, and the PM2.5 sources were quantitatively analyzed on haze and non-haze days using the principal component analysis/absolute principal component scores (PCA/APCS) model. The average PM2.5 concentration was 122.61 μg·m−3 on haze days, which was 2.20 times greater than it was on non-haze days. The concentrations of secondary water soluble ions (WSIs) including NO3−, SO42−, and NH4+ increased sharply on haze days, which accounted for 91.61% of the total WSIs and were 2.43 times larger than the values on non-haze days. The heterogeneous oxidation reactions of NO2 and SO2 during haze episodes were proven to be the major sources of sulfate and nitrate in PM2.5. On haze days, the concentrations of EC, primary organic carbon (POC), and secondary organic carbon (SOC) were 1.68, 1.69, and 1.34 times larger than those on non-haze days, the CO, HNO3, and NH3 concentrations enhanced and relatively low SO2, O3, and HNO2 levels were observed on haze days. The diurnal variations of different pollutants distinctly varied on haze days. The PM2.5 in Wuhan primarily originated from the secondary formation, combustion, dust, industry, and vehicle exhaust sources. The source contributions of the secondary formation + combustion sources to PM2.5 on haze days were 2.79 times larger than the level on non-haze days. The contribution of the vehicle exhaust + combustion source on haze days were 0.59 times the value on non-haze days. This description is supported by a summary of how pollutant concentrations and patterns vary in the THB compared to the variations in other pollution regions in China, which have been more completely described.

A health risk-based source apportionment of ambient PM10 and its implications of pollution control strategies

Atmospheric particulate matter (PM) pollution is a major public health concern in most city clusters in Asia. PM sources and their contributions should be clearly understood before effective control strategies are formulated. Traditionally, source contributions are quantified from a PM mass point of view. However, as the ultimate goal of PM control is to protect public health, they are preferentially quantified from a health risk point of view. In this study, the spatiotemporal variations of health risks from ambient PM10 from seven monitoring stations in Hong Kong between 2000 and 2011 were analyzed. Positive matrix factorization was adopted to identify major source categories of PM10 and quantify their contributions. A point-estimated risk model was then used to identify the inhalation cancer and non-cancer risks of PM10 sources. The long-term trends of the health risks from identified local and non-local sources were explored. The reason for the increase of health risks during high PM10 days was discussed. Vehicle exhaust source was the dominant inhalation cancer risk (ICR) contributor (72%), whereas trace metals and vehicle exhaust sources contributed 27% and 21% of PM10 inhalation non-cancer risk (INCR), respectively. Local sources accounted for 80% of the ICR in HK, while contributions of the non-local and local sources for INCR are comparable. On high PM days, ICR increase was mainly attributed to coal combustion/biomass burning and secondary sulfate, while INCR increase was attributed to coal combustion/biomass burning, secondary nitrate, and trace metals. From a mass point of view, PM10 in HK was largely contributed from regional sources, i.e. emissions outside HK. However, local sources contributed dominantly to health risks, especially ICR. Therefore, local control should be further strengthened. This study highlights the importance of health risk-based source apportionment in air quality management with protecting human health as the ultimate target.

Characterization and source apportionment of health risks from ambient PM10 in Hong Kong over 2000–2011

Atmospheric particulate matter (PM) pollution is a major public health concern in Hong Kong. In this study, the spatiotemporal variations of health risks from ambient PM10 from seven air quality monitoring stations between 2000 and 2011 were analyzed. Positive matrix factorization (PMF) was adopted to identify major source categories of ambient PM10 and quantify their contributions. Afterwards, a point-estimated risk model was used to identify the inhalation cancer and non-cancer risks of PM10 sources. The long-term trends of the health risks from classified local and non-local sources were explored. Furthermore, the reason for the increase of health risks during high PM10 days was discussed. Results show that vehicle exhaust source was the dominant inhalation cancer risk (ICR) contributor (72%), whereas trace metals and vehicle exhaust sources contributed approximately 27% and 21% of PM10 inhalation non-cancer risk (INCR), respectively. The identified local sources accounted for approximately 80% of the ICR in Hong Kong, while contribution percentages of the non-local and local sources for INCR are comparable. The clear increase of ICR at high PM days was mainly attributed to the increase of contributions from coal combustion/biomass burning and secondary sulfate, while the increase of INCR at high PM days was attributed to the increase of contributions from the sources coal combustion/biomass burning, secondary nitrate, and trace metals. This study highlights the importance of health risk-based source apportionment in air quality management with protecting human health as the ultimate target.

Chemical characteristics of submicron aerosol particles during a long-lasting haze episode in Xiamen, China

A long-lasting haze episode has been first observed with a mean atmospheric visibility of 8.6 km since last decades over Xiamen. An Aerodyne Aerosol Mass Spectrometer (AMS) was deployed to obtain the size-resolved chemical composition of non-refractory submicron particles (NR-PM1) at 10 min resolution. Characteristics of aerosol particles in haze days have been analyzed and compared to in clear days and rainy days. The mean concentration of PM2.5 was about 213.3 μg m−3 (±16.9 μg m−3) during haze days, which was about 4 times higher than during clear days. Organics, sulfate and ammonium were the major components in these supper fine particles, accounting for 37.2% (±0.11), 28.7% (±0.11) and 12.0% (±0.11), respectively, during haze days. The size distributions of aerosol species were characterized by a major accumulation mode peaking at a vacuum aerodynamic diameter of 390 nm during clear days, 427 nm during rainy days and 579 nm during haze days. High concentrations of SO42−, NO3− and NH4+ were observed and the average values of sulfur oxidation ratios (SOR) and nitrogen oxidation ratios(NOR) were up to 0.56 (±0.17) and 0.25 (±0.11) during haze days. Positive Matrix Factorization (PMF) was used to identity a hydrocarbon-like organic aerosol (HOA) and an oxygenated organic aerosol (OOA) component. It showed that OOA components were probably representative of SOA in Xiamen. The average value of NO3−/SO42− was 0.28 during clear days, 0.20 during rainy days and 0.59 during haze days, indicating that pollutants from local vehicle exhaust sources were accumulated in haze days. During haze days, the main air mass (accounted for 81%) transported from the northeast of China, implying that the haze pollution was partly influenced by the pollutants transported from heavy haze areas in China. Pollution accumulated by local processes, secondary aerosol formation and the stagnation meteorological atmosphere dominated the formation of the haze event.

Polycyclic aromatic hydrocarbons (PAHs) and their derivatives (alkyl-PAHs, oxygenated-PAHs, nitrated-PAHs and azaarenes) in urban road dusts from Xi’an, Central China

Urban road dusts are carriers of polycyclic aromatic compounds (PACs) and are therefore considered to be a major source of contamination of other environmental compartments and a source of exposure to PACs for urban populations. We determined the occurrence, composition pattern and sources of several PACs (29 alkyl- and parent-PAHs, 15 oxygenated-PAHs (OPAHs), 4 azaarenes (AZAs), and 11 nitrated-PAHs (NPAHs)) in twenty urban road dusts and six suburban surface soils (0–5cm) from Xi’an, central China. The average concentrations of ∑29PAHs, ∑4AZAs, ∑15OPAHs, and ∑11NPAHs were 15767, 673, 4754, and 885ngg−1 in road dusts and 2067, 784, 854, and 118ngg−1 in surface soils, respectively. The concentrations of most individual PACs were higher in street dusts than suburban soils, particularly for PACs with molecular weight>192gmol−1. The enrichment factors of individual PACs were significantly positively correlated with log KOA and log KOW, indicating an increasing deposition and co-sorption of the PACs in urban dusts with decreasing volatility and increasing hydrophobicity. Significant correlations between the concentrations of individual and sum of PACs, carbon fractions (soot and char), and source-characteristic PACs (combustion-derived PAHs and retene, etc.), indicated that PAHs, OPAHs and AZAs were mostly directly emitted from combustion activities and had similar post-emission fates, but NPAHs were possibly more intensely photolyzed after deposition as well as being emitted from vehicle exhaust sources. The incremental lifetime cancer risk (ILCR) resulting from exposure to urban dust bound-PACs was higher than 10−6, indicating a non-negligible cancer risk to residents of Xi’an.