Chemical composition and source apportionment of size fractionated particulate matter in Cleveland, Ohio, USA

A PMF-SSD based approach for the source apportionment and source-specific ecological risk assessment of Le'an river in Jiangxi Province, China

Identifying the contamination characteristics of trace metals in river and targeting their corresponding potential contamination sources and source-specific ecological risk are of very importance for putting forward effective river environment protection strategies. Here, a detailed investigation was conducted to recognize the contamination and ecological risk characteristics of trace metals in Le'an River. To attain this objective, a PMF-SSD model (Positive Matrix Factorization-Species Sensitivity Distribution) was proposed to evaluate the ecological risk of trace metals in Le'an River. The positive matrix factorization (PMF) was employed to identify the potential source of trace metals in surface water and their corresponding contributions. The ecological risks of the sources were quantitatively calculated by PMF-SSD. In addition, the spatial dissimilarity analysis of the source contribution distributions was also conducted in this study. Results showed that the water environment in Jiangxi were considerably contaminated by trace metals (Cd, Cr, Co, Al, Mn, Cu, Zn and Ni). The concentrations of these trace metals in surface water demonstrated significant spatial variations and the ecological risk lay in high level. Mining activities were identified as the main anthropogenic sources, which should to be strictly regulated.

Causes of PM2.5 pollution in an air pollution transport channel city of northern China

To develop effective mitigation policies, a comprehensive understanding of the evolution of the chemical composition, formation mechanisms, and the contribution of sources at different pollution levels is required. PM_2.5 samples were collected for 1 year from August 2016 to August 2017 at an urban site in Zibo, then chemical compositions were analyzed. Secondary inorganic aerosols (SNA), anthropogenic minerals (MIN), and organic matter (OM) were the most abundant components of PM_2.5, but only the mass fraction of SNA increased as the pollution evolved, implying that PM_2.5 pollution was caused by the formation of secondary aerosols, especially nitrate. A more intense secondary transformation was found in the heating season (from November 15, 2016, to March 14, 2017), and a faster secondary conversion of nitrate than sulfate was discovered as the pollution level increased. The formation of sulfate was dominated by heterogeneous reactions. High relative humidity (RH) in polluted periods accelerated the formation of sulfate, and high temperature in the non-heating season also promoted the formation of sulfate. Zibo city was under ammonium-rich conditions during polluted periods in both seasons; therefore, nitrate was mainly formed through homogeneous reactions. The liquid water content increased significantly as the pollution levels increased when the RH was above 80%, indicating that the hygroscopic growth of aerosol aggravated the PM_2.5 pollution. Source apportionment showed that PM_2.5 was mainly from secondary aerosol formation, road dust, coal combustion, and vehicle emissions, contributing 36.6%, 16.5%, 14.7%, and 13.1% of PM_2.5 mass, respectively. The contribution of secondary aerosol formation increased remarkably with the deterioration of air quality, especially in the heating season.

Associations of Air Pollution and Pediatric Asthma in Cleveland, Ohio

Air pollution has been associated with poor health outcomes and continues to be a risk factor for respiratory health in children. While higher particulate matter (PM) levels are associated with increased frequency of symptoms, lower lung function, and increase airway inflammation from asthma, the precise composition of the particles that are more highly associated with poor health outcomes or healthcare utilization are not fully elucidated. PM is measured quantifiably by current air pollution monitoring systems. To better determine sources of PM and speciation of such sources, a particulate matter (PM) source apportionment study, the Cleveland Multiple Air Pollutant Study (CMAPS), was conducted in Cleveland, Ohio, in 2009-2010, which allowed more refined assessment of associations with health outcomes. This article presents an evaluation of short-term (daily) and long-term associations between motor vehicle and industrial air pollution components and pediatric asthma emergency department (ED) visits by evaluating two sets of air quality data with healthcare utilization for pediatric asthma. Exposure estimates were developed using land use regression models for long-term exposures for nitrogen dioxide (NO₂) and coarse (i.e., with aerodynamic diameters between 2.5 and 10 μm) particulate matter (PM) and the US EPA Positive Matrix Factorization receptor model for short-term exposures to fine (<2.5 μm) and coarse PM components. Exposure metrics from these two approaches were used in asthma ED visit prevalence and time series analyses to investigate seasonal-averaged short- and long-term impacts of both motor vehicles and industry emissions. Increased pediatric asthma ED visits were found for LUR coarse PM and NO₂ estimates, which were primarily contributed by motor vehicles. Consistent, statistically significant associations with pediatric asthma visits were observed, with short-term exposures to components of fine and coarse iron PM associated with steel production. Our study is the first to combine spatial and time series analysis of ED visits for asthma using the same periods and shows that PM related to motor vehicle emissions and iron/steel production are associated with increased pediatric asthma visits.

A long-term chemical characteristics and source apportionment of atmospheric rainfall in a northwest megacity of Xi'an, China

A long-term measurement on rainfall was conducted in urban Xi'an, China, from 2009 to 2016. The seasonal and annual variations of major inorganic components and their chemical properties in the rainfall were studied. The annual rainfall ranged from 165.3 to 916.3 mm. The pH value of the rainfall ranged from 6.36 to 7.19, with an average value of 6.70. The electric conductivity (EC) in the rainfall was in a range of 55.91 to 227.44 μS·cm-1. Ammonium (NH4+), calcium (Ca2+), nitrate (NO3-), and sulfate (SO42-) were the four major components, accounting for 88.5% of the total quantified inorganic ion concentration. Neutralization factors were determined for Ca2+ (1.03), NH4+ (0.57), Mg2+ (0.10), Na+ (0.06), and K+ (0.04). The high abundance of NH4+ that formed from its precursor of ammonia gas (NH3) suggested the contribution of agricultural fertilization. Ca2+ in the rainfall was mainly from natural sources such as soil dust, while anions of NO3- and SO42- originated from fossil fuel combustion. Source apportionment was conducted with positive matrix factorization (PMF) which identified that secondary inorganic formation, crustal dust, coal combustion, and biomass burning are the contributors to the rainfall. In between, secondary inorganic formation was the largest contributor, which accounted for 27.8-58.1% of the total sources, followed by crustal dust of 0.4-42.6%. The results of this long-term study demonstrated the decreasing trends of contributions from coal combustion and biomass burning under a series of air pollution control measures implemented by the government. However, continuous urbanization and development of the city caused substantial increases of the construction activities, inducing more crustal dusts to the environment in urban Xi'an.

Temporal variation characteristics and source apportionment of metal elements in PM2.5 in urban Beijing during 2018-2019

To explore high-resolution temporal variation characteristics of atmospheric metal elements concentration and more accurate pollution sources apportionment, online monitoring of metal elements in PM_2.5 with 1-h time resolution was conducted in Beijing from August 22, 2018 to August 21, 2019. Concentration of 18 elements varied between detection limit (ranging from 0.1 to 100 ng/m³) and nearly 25 μg/m³. Si, Fe, Ca, K and Al represented major elements and accounted for 93.47% of total concentration during the study period. Compared with previous studies, airborne metal pollution in Beijing has improved significantly which thanks to strict comprehensive control measures under the Clean Air Action Plan since 2013. Almost all elements present higher concentrations on weekdays than weekends, while concentrations of elements associated with dust sources during holidays are higher than those in working days after the morning peak, and there is almost no concentration difference in the evening peak period. Soil and dust, vehicle non-exhaust emissions, biomass, industrial processes and fuel combustion were apportioned as main sources of atmospheric metal pollution, accounting for 63.6%, 18.4%, 16.8%, 1.0% and 0.18%, respectively. Furthermore, main occurrence season of metal pollution is judged by characteristic radar chart of varied metal elements proposed for the first time in this study, for example, fuel combustion type pollution mainly occurs in winter and spring. Results of 72-h backward trajectory analysis of air masses showed that, except for local emissions, atmospheric metal pollution in Beijing is also affected by regional transport from Inner Mongolia, Hebei, the Bohai Sea and Heilongjiang.

Interactions of particulate matter and pulmonary surfactant: Implications for human health

Particulate matter (PM), which is the primary contributor to air pollution, has become a pervasive global health threat. When PM enters into a respiratory tract, the first body tissues to be directly exposed are the cells of respiratory tissues and pulmonary surfactant. Pulmonary surfactant is a pivotal component to modulate surface tension of alveoli during respiration. Many studies have proved that PM would interact with pulmonary surfactant to affect the alveolar activity, and meanwhile, pulmonary surfactant would be adsorbed to the surface of PM to change the toxic effect of PM. This review focuses on recent studies of the interactions between micro/nanoparticles (synthesized and environmental particles) and pulmonary surfactant (natural surfactant and its models), as well as the health effects caused by PM through a few significant aspects, such as surface properties of PM, including size, surface charge, hydrophobicity, shape, chemical nature, etc. Moreover, in vitro and in vivo studies have shown that PM leads to oxidative stress, inflammatory response, fibrosis, and cancerization in living bodies. By providing a comprehensive picture of PM-surfactant interaction, this review will benefit both researchers for further studies and policy-makers for setting up more appropriate regulations to reduce the adverse effects of PM on public health.

[Contribution of Emissions from the Iron and Steel Industry to Air Quality in China]

Based on the data from a continuous emission monitoring systems network in 2015, this study analyzed the compliance rates of exhaust gas in the processes of China's iron and steel industry, and established a high-resolution steel plant emission inventory for China (HSEC, 2015), based on the bottom-up method. The contribution of emissions from the iron and steel industry to regional air quality was quantitatively simulated using a CAMx model. The results showed that in 2015, the total emissions of SO₂, NO_x, PM₁₀, PM_2.5, PCDD/Fs, VOCs, CO, BC, OC, EC, and F were 374800 t, 720500 t, 334800 t, 150300 t, 1.91 kg, 842900 t, 34788500 t, 6400 t, 8300 t, 800 t, and 7700 t, respectively. From a regional perspective, the iron and steel industry in Shanghai and Tianjin has the highest emission intensity per unit area and contributes a high proportion to regional air pollution. From a process perspective, in 2015, the exhaust concentration of flue gas in the main process gradually decreased, with a high compliance rate, and the emission factor significantly decreased to lower than that in the existing research results. From a species perspective, in 2015, NO_x emission from the steel industry contributed the most to regional air quality, and there is therefore a great emission reduction potential for NO_x.

Inorganic ion chemistry of local particulate matter in a populated city of North China at light, medium, and severe pollution levels

Twenty-six pairs of PM_2.5 and PM₁₀ samples were collected during haze episodes in Zhengzhou (113°28' E, 34°37' N), a highly populated city in North China. The samples were used to examine the inorganic ion chemistry of particulate matter (PM) of local origin at light (PM_2.5 < 60 μg m^-3 and PM₁₀ < 135 μg m^-3), medium (PM_2.5: 60-170 μg m^-3 and PM₁₀: 135-325 μg m^-3), and severe (PM_2.5 > 170 μg m^-3 and PM₁₀ > 325 μg m^-3) pollution levels. At the light and severe pollution levels, the increase of PM₁₀ was accounted for by the increase of PM_2.5, and the variation of PM_10-2.5 was small. In contrast, the increase of PM₁₀ at the medium pollution level was caused by the increase in both PM_2.5 and PM_10-2.5. Sulfate (SO₄^2-), nitrate (NO₃^-), ammonium (NH₄⁺), and chloride in the form of ammonium chloride (Cl^-_S) accounted for 47.8% and 60.3% of the PM_2.5 mass at the light and severe levels, respectively. These values indicate a large contribution of secondary inorganic species to the PM_2.5 growth. As the pollution level changed from light to medium, the contribution of SO₄^2- to the growth of PM_2.5 decreased from 49.0% to 15.1%, while those of NO₃^- and Cl^-_S increased from 25.1% and 0.6% to 32.5% and 2.8%, respectively, indicating the substantial production of nitrate and chloride. At the severe level, the contribution of SO₄^2- was 30.1%, while those of NO₃^- and Cl^-_S were 5.9% and 0.5%, respectively, suggesting a hindering effect of sulfate on the production of nitrate and chloride. These results indicate that the production of secondary species with the increase of PM_2.5 was dominated by sulfate-associated conversions at the light and severe pollution levels and was substantially influenced by nitrate- and chloride-associated conversions at the medium pollution level. The estimation of carbonate presence in the PM indicates that part of the carbonate in coarse particles (PM_10-2.5) of crustal origin enhanced sulfate production via heterogeneous surface reactions. Quantification of the contribution of primary and secondary species to PM_2.5 showed that it was dominated by both primary and secondary particles at the light pollution level, and it was mainly composed of secondary species at the severe pollution level.

Source-apportioned coarse particulate matter exacerbates allergic airway responses in mice

Exposure to coarse particulate matter (PM) is associated with lung inflammation and exacerbation of respiratory symptoms in sensitive populations, but the degree to which specific emission sources contribute to these effects is unclear. We examined whether coarse PM samples enriched with diverse sources differentially exacerbate allergic airway responses. Coarse PM was collected weekly (7/2009-6/2010) from urban (G.T. Craig [GTC]) and rural (Chippewa Lake Monitor [CLM]) sites in the Cleveland, Ohio area. Source apportionment results were used to pool GTC filter PM extracts into five samples dominated by traffic, coal, steel (two samples), or road salt sources. Five CLM samples were prepared from corresponding weeks. Control non-allergic and house dust mite (HDM)-allergic Balb/cJ mice were exposed by oropharyngeal aspiration to 100 μg coarse GTC or CLM, control filter extract, or saline only, and responses were examined 2 d after PM exposures. In allergic mice, CLM traffic, CLM road salt and all GTC samples except steel-1 significantly increased airway responsiveness to methacholine (MCh) compared with control treatments. In non-allergic mice, CLM traffic, CLM steel-2 and all GTC samples except coal significantly increased bronchoalveolar lavage fluid (BALF) neutrophils, while only CLM traffic PM increased eosinophils in allergic mice. In non-allergic mice, CLM coal PM increased BALF interleukin (IL)-13 and GTC steel-1 PM increased TNF-α levels. These results demonstrate that equal masses of GTC and CLM coarse PM enriched with a variety of sources exacerbate allergic airway disease. Greater PM concentrations at the urban GTC site signify a greater potential for human health effects.

Organic speciation of ambient quasi-ultrafine particulate matter (PM0.36) in Augsburg, Germany: Seasonal variability and source apportionment

To investigate the organic composition and their sources of very fine atmospheric particulate matter (PM), size-segregated PM was sampled using rotating drum impactor (RDI) in series with a sequential filter sampler in Augsburg, Germany, from April 2014 to February 2015. Organic speciation analysis and organic carbon/elemental carbon (OC/EC) analysis was performed for the smallest size fraction PM_0.36 (PM<360nm). Different OC fractions were determined by thermal optical EC/OC analyzer, and OC2, OC3 and OC4 refer to OC fractions that were derived at 280, 480 and 580°C, respectively. Positive matrix factorization (PMF) analysis was applied for source apportionment study. PMF resolved 5 sources including biogenic dominated secondary organic aerosol (bioSOA), isoprene dominated SOA (isoSOA), traffic, biomass burning (BB) and biomass burning originated SOA (bbSOA). On annual average, PMF results indicate the largest contribution of biogenic originated SOA (bioSOA plus isoSOA) to OC, followed by traffic and then BB related sources (BB plus bbSOA). Traffic was found to be associated with the smallest particles; whereas bioSOA and BB are associated with larger particles. Secondary organic marker compounds from biogenic precursors, OC2, OC3 and bioSOA, isoSOA source factors show summer maximum. Polycyclic aromatic hydrocarbons (PAHs), biomass burning markers, OC4 and BB, bbSOA source factors show winter maximum. Hopanes and the traffic source factor show little seasonal variation. Summer peaks of OC3 and OC2 are well modeled by PMF and are attributed mainly to biogenic SOA. OC4 was generally poorly modeled due to lack of characteristic low volatile markers. Summer maxima of biogenic SOA related compounds and source factors are positively correlated with temperature, global radiation, O₃ concentration and mixing layer height (MLH). Winter maxima of BB related compounds and source factors are negatively correlated with temperature and MLH; whereas positively correlated with NO₂ level.