Sources Of Particulate Matter Research Articles

Chemical characterization and sources of submicron aerosols in Lhasa on the Qinghai–Tibet Plateau: Insights from high-resolution mass spectrometry

In recent years, a great number of studies has been carried out in urban cities regarding urban particulate matter (PM) pollution in China, especially in eastern China. Lhasa, the capital of the Tibet Autonomous Region in western China, is the highest (3650 m a.s.l.) city in China and has notably different lifestyles and PM sources comparing with those in eastern China. However, there is currently a lack of studies on PM pollution in this city. In this study, an Aerodyne high-resolution time-of-flight aerosol mass spectrometer was deployed along with other co-located instruments to explore the chemical characterization of ambient submicron PM (PM1) in Lhasa from 31 August 2019 to 26 September 2019. The mean ambient PM1 mass loading through this study was 4.72 μg m−3. Organic aerosols (OAs) played a dominant role with an average contribution of 82.6% to PM1, followed by 5.4% nitrate, 4.7% ammonium, 3.4% sulfate, 3.1% BC, and 0.7% chloride. The relatively lower contribution from secondary inorganic aerosols (nitrate and sulfate) in this study was distinctly different from that in eastern China, indicating lower fossil fuel usage in this city. Via positive matrix factorization (PMF), organic aerosols were decomposed into four components containing a traffic-related hydrocarbon-like OA (HOA), a cooking-related OA (COA), a biomass burning-related OA (BBOA), as well as an oxygenated OA (OOA). The OOA and COA had higher contributions (34% and 35%, respectively) to total OAs, while the rest accounted for 17% for HOA and 14% for BBOA. However, an increased mass fraction of BBOA (up to 36%) was found during the Sho Dun Festival, suggesting the importance of biomass burning emissions during the religious activities in this city. Frequent new particle formation events were observed during this study and the contribution of chemical species for the particle growth was also explored.

Indoor Air Pollution of Outdoor Origin: Mitigation Using Portable Air Cleaners in Singapore Office Building

Landscape fires in Indonesia and traffic pollution have been receiving increasing attention as sources of particulate matter (PM) in Singapore. Although mitigation measures to reduce PM levels using portable air cleaners (PACs) have been used in residential buildings, its application for office buildings is unknown. Using PAC, we demonstrated their potential for indoor particles removal in an office building and presented a method to evaluate their performance and estimate number of units to be deployed. Modelled and in-situ measured PAC effectiveness using up to twelve units was evaluated in three office sizes (30, 80 and 1490 m3). Measured effectiveness using indoor concentrations and indoor/outdoor ratios was obtained in a randomised intervention experimental design involving 3 weeks per location. Indoor particle concentration reductions in the three offices were dependent on particle size and confounded by variations in indoor emissions and outdoor levels resulting in low correlation and higher RMSE between modelled and measured effectiveness. PAC effectiveness computed using I/O ratios for removing UFP, PM2.5 and PM10 ranged 24–43%, 23–53% and 7–37% respectively. PAC has a higher in-situ effectiveness in small compared to larger spaces and the effectiveness is logarithmically dependent on the number of units deployed. We validated the use of our model to determine PAC effectiveness in the offices using up to eleven PACs (RMSE between modelled and measured data ranging from 3.9 to 6.6%). Lastly, we developed a design method to size the number of PAC needed for office buildings. The results from this study can be used for standards organization, policy makers and researchers interested in particle exposure reductions in large spaces.

The utility of alternative models in particulate matter air pollution toxicology

Exposure to particulate matter (PM) air pollution increases risk of adverse human health effects. As more attention is brought to bear on the problem of PM, traditional mammalian in vivo models struggle to keep up with the risk assessment challenges posed by the countless number of unique PM samples across air sheds with limited or no toxicity information. This review examines the utility of three higher throughput, alternative, in vivo animal models in PM toxicity research: Danio rerio (zebrafish), Caenorhabditis elegans (nematode), and Drosophila melanogaster (fruit fly). These model organisms vary in basic biology, ease of handling, methods of exposure to PM, number and types of available assays, and the degree to which they mirror human biology and responsiveness, among other differences. The use of these models in PM research dates back over a decade, with assessments of the toxicity of various PM sources including traffic-related combustion emissions, wildland fire smoke, and coal fly ash. This article reviews the use of these alternative model organisms in PM toxicity studies, their biology, the various assays developed, endpoints measured, their strengths and limitations, as well as their potential role in PM toxicity assessment and mechanistic research going forward.

Chemical Composition, Source Appointment and Health Risk of PM2.5 and PM2.5-10 during Forest and Peatland Fires in Riau, Indonesia

This study investigated the contributions of particulate matter (PM) from various emission sources during the dry season, which resulted from frequent fires occurring in degraded forests and peatlands in Indonesia. Samples of fine (PM2.5) and coarse (PM2.5-10) particles collected during the dry season in Riau, Indonesia were analyzed to determine the mass concentrations of metallic trace elements, ionic compound, black carbon (BC), and organic carbon (OC). The average concentrations of PM2.5 and PM2.5-10 at Riau, Indonesia were 63.85 ± 3.22 µg m-3 and 27.72 ± 2.40 µg m-3, respectively. The positive matrix factorization (PMF) model was adopted to identify possible PM sources and their contributions to the ambient PM level. The PMF results identified six major PM2.5 sources, including biomass burning (BB) (28.7%), secondary aerosols (SA) (26.9%), vehicle exhaust (VE) (12.8%), industrial emissions (IE) (12.3%), soil dust (SD) (11.9%), and sea salt (SS) (7.5%). Moreover, there were five primary PM2.5-10 sources, including VE (28.6%) and BB (24%), followed by IE (19.9%), SD (17.2%), and SA (15.3%). A conditional probability function (CPF) analysis revealed that the southeast sector dominated among source direction-dependent contributions. The noncarcinogenic health risks for both adults and children resulting from exposure to PM2.5 were mainly contributed by Co, Ni, and Mn, and carcinogenic risks were caused by the toxic metals Cr and Co. Both noncarcinogenic and carcinogenic health risks resulting from cumulative multielement exposure for both adults and children exceeded acceptable levels. Clearly, more attention should be devoted to reducing the noncarcinogenic and carcinogenic health risks caused by particulate-bound toxic elements through inhalation exposure.

Measurement and Analysis of PM10 and PM2.5 from Chimneys of Coal-fired Power Plants Using a Light Scattering Method

Aerial pollutants emitted from the stacks of coal-fired power plants are considered a major source of fine particulate matter released into the atmosphere. To manage such fine particles in the stacks themselves, it is necessary to know the concentration of fine particles emitted in real time; the current system to do so is tedious. In this study, a system for measuring fine particles emitted from the stacks of power plants in real-time was developed, and measurements were performed on six coal-fired power plants. Through these measurements, the mass concentration distribution, according to particle sizes, could be determined. All six stacks showed bimodal distribution, and the count median diameters of each mode were 0.5 µm and 1.1 µm. Additionally, data were compared using the gravimetric measurement method; it was found that the relative accuracies for the measured PM10 amounts were within 20% and that the values obtained using the measuring instrument proposed in this study were reliable. Three power plants were continuously measured for one month, and by comparing PM10 concentration according to the amount of power generated, it was confirmed that PM10 discharged from the stack increased as an exponential function, depending on the amount of power generated.

Assessment of the Contribution of Local and Regional Biomass Burning on PM2.5 in New York/New Jersey Metropolitan Area

The sources of fine particulate matter (PM2.5, particles with diameter < 2.5 μm) in four monitoring sites in the New York/New Jersey metropolitan statistical area from 2007 to 2017 was apportioned by positive matrix factorization (PMF) of chemical speciation data. Biomass burning, secondary inorganic (i.e., ammonium sulfate and nitrate) and primary traffic exhausts were the predominant PM2.5 sources. The declining trends of PM2.5 mass in all four sites were very well correlated with decreasing secondary sulfate levels due to SO2 emission reductions by coal-fired power plants. The contributions of secondary nitrate, primary traffic exhausts and diesel particles did not change (or slightly increased) over time except for the Queens site, where statistically significant declines were computed. Biomass burning contributions increased in the Queens and Chester sites but declined in the Division Str and Elizabeth Lab sites, although significant interannual variability was observed. Wintertime biomass burning aerosols were most likely due to combustion of contemporary biomass for industrial and domestic heating, and it was linked to the intensity (average minimum temperature) and duration (number of freezing days) of cold weather. The annual summertime biomass burning contributions were correlated with the number and area burnt by lightning-ignited wildfires. These results indicate that PM2.5 sources in urban environments is changing from anthropogenic secondary sulfate and nitrate to carbonaceous aerosol from local anthropogenic and regional climate-driven biomass burning. This trend may counterbalance emissions controls on anthropogenic activities and modify the biological and toxicological responses and resultant health effects.

Characterisation of fine particulate matter level, content and sources of a kindergarden microenvironment in Belgrade city center

In the present work, we investigated polycyclic aromatic hydrocarbons (PAHs), metals and ions of indoor and outdoor PM2.5 from 80 samples collected in the microenvironment of a kindergarten located in Belgrade city center during weekdays, from March to May 2010. The daily concentrations of PM2.5 were much higher than WHO guidance daily value. Results show similar factor profiles identified by principal component analysis (PCA) and positive matrix factorization (PMF). For indoor and outdoor environment, six principal components (PCs) were identified by PCA, and six and seven factors were identified by PMF, respectively. PCs from PCA were attributed to the following sources: combustion processes, traffic emission, coal/oil combustion, mix (stationary sources/resuspension), road salt and secondary aerosol. The resulting factors from PMF were identified as representing combustion processes, traffic emission, coal/oil combustion, soil dust, secondary aerosol and break wear. For outdoor environment, PMF identified one more source, attributed to road dust.

Effects of Payloads on Non-exhaust PM Emissions from A Hybrid Electric Vehicle during A Braking Sequence

Vehicles equipped with internal combustion engines are known as important sources of particulate matter (PM) emissions. Many countries are aware of this issue. They are keen in converting internal combustion engine vehicles to electric vehicles (EV) to reduce PM problems. However, various past research works claimed that EV also emit PM like conventional vehicles due to their non-exhaust emissions from brake wear, tyre wear, road surface wear, and resuspension of road dust. In addition, strong evidence showed that there was indeed a positive correlation between the weight of vehicle and amounts of non-exhaust PM emissions. The current study is aimed to measure on-road non-exhaust PM emissions from a hybrid electric vehicle during a braking sequence at various payloads. An onboard PM measuring device is attached nearby the center cap bore of the left front wheel on the tested hybrid electric vehicle. PM1, PM2.5, and PM10 measurements are monitored during braking sequences in the electrified vehicle mode. The increase payloads that affect tendency of non-exhaust PM emissions are observed. The PM emission pattern during braking sequence is captured by the current PM measuring setup as seen in the literature. Based on this experiment, the additional payloads of 60-70 kg increase the amount of non-exhaust PM2.5 and PM10 emissions almost 25%. The effects of increasing payloads on PM2.5 and PM10 emissions can be clearly observed as a linear relationship. However, for PM1 emissions, when increasing payloads, a certain cut point is observed at the payload of 130 kg. Adding payloads more than 130 kg do not affect the amount of PM1 emissions.

Technology for Predicting Particulate Matter Emissions at Construction Sites in South Korea

In recent years, particulate matter (PM) has emerged as a major social issue in various industries, particularly in East Asia. PM not only causes various environmental, social, and economic problems but also has a large impact on public health. Thus, there is an urgent requirement for reducing PM emissions. In South Korea, the PM generated at construction sites in urban areas directly or indirectly causes various environmental problems in surrounding areas. Construction sites are considered a major source of PM that must be managed at the national level. Therefore, this study aims to develop a technology for predicting PM emissions at construction sites. First, the major sources of PM at construction sites are determined. Then, PM emission factors are calculated for each source. Furthermore, an algorithm is developed for calculating PM emissions on the basis of an emission factor database, and a system is built for predicting PM emissions at construction sites. The reliability of the proposed technology is evaluated through a case study. The technology is expected to be used for predicting potential PM emissions at construction sites before the start of construction.

Source Apportionment of Particulate Matter in Urban Snowpack Using End-Member Mixing Analysis and Positive Matrix Factorization Model

The aim of this study was to identify particulate matter (PM) sources and to evaluate their contributions to PM in the snowpack of three East Siberian cities. That was the first time when the PM accumulated in the snowpack during the winter was used as the object for source apportionment study in urban environment. The use of long-term integrated PM samples allowed to exclude the influence of short-term weather conditions and anthropogenic activities on PM chemistry. To ascertain the real number of PM sources and their contributions to air pollution the results of source apportionment using positive matrix factorization model (PMF) were for the first time compared to the results obtained using end-member mixing analysis (EMMA). It was found that Si, Fe and Ca were the tracers of aluminosilicates, non-exhaust traffic emissions and concrete deterioration respectively. Aluminum was found to be the tracer of both fossil fuel combustion and aluminum production. The results obtained using EMMA were in good agreement with those obtained using PMF. However, in some cases, the non-point sources identified using PMF were the combinations of two single non-point sources identified using EMMA, whereas the non-point sources identified using EMMA were split by PMF into two single non-point sources. The point sources were clearly identified using both techniques.

The shift from macrophytic to algal particulate organic matter favours dissimilatory nitrate reduction to ammonium over denitrification in a eutrophic lake

Abstract In eutrophic lakes, the shift from a macrophyte‐dominated state to an algae‐dominated state changes the particulate organic matter (POM) sources, which in turn alters organic matter quality that is released and that sinks to the benthos. However, the influences of this shift on denitrification and dissimilatory nitrate reduction to ammonium (DNRA) are unclear in eutrophic lakes. Here, we elucidated how various POM sources influenced these nitrate reduction pathways in a eutrophic lake. The lake sediments from August were incubated under algae, macrophyte, and soil treatments in aquarium tanks. Potential denitrification and DNRA rates and related functional gene abundances were measured periodically. Meanwhile, the n‐alkanes composition of POM and fluorescence excitation‐emission matrices of dissolved organic matter were measured before and during incubations, respectively, to aid in the analysis of the potential mechanisms by which organic matter quality affect nitrate reduction. The results indicated that algal detritus was more labile and decomposed faster than other POM, coupled with higher DNRA rates and nrfA gene abundances. Macrophyte treatments resulted in nitrate accumulation and the increase of gene abundances related to denitrification, but no increase in denitrification rates was observed. In soil treatments, nitrate reduction processes were not significantly influenced by the addition of POM. Overall, compared with other sources, algae‐derived POM can produce high‐quality organic carbon, low dissolved oxygen and nitrate concentrations, which is more conducive to DNRA than denitrification. A loss of macrophytes and increase in algal biomass will induce changes in autochthonous POM quality and potentially drive nitrogen recycling in eutrophic lakes.

Switzerland's PM10 and PM2.5 environmental increments show the importance of non-exhaust emissions

Atmospheric particulate matter (PM) is a priority pollutant for urban air pollution management because of its negative effects on human health and visibility. Emissions from road traffic have been a major focus of management over the past few decades, but non-exhaust emissions i.e. , emissions from brake, tyre, road wear, and the resuspension of dust have emerged to become a major source of unregulated PM in many locations. Here, a filter-based sampling campaign was conducted between 2018 and 2019 where a large number of PM constituents were quantified for five sites in Switzerland for both PM 10 and PM 2.5 . This had the objective of investigating urban and urban-traffic PM increments in Switzerland. The results show that PM concentrations increased as the sampling locations moved along a rural to urban-traffic gradient. However, source apportionment analysis showed that sulfate-rich, nitrate-rich, and biogenic sources were not enhanced in urban environments, but road traffic and mineral dust sources were. The total mass enhancement for PM 10 and PM 2.5 were 2.4 μg m −3 and 2.0 μg m −3 for the urban environment while the corresponding urban-traffic enhancements were 5.7 μg m −3 and 2.8 μg m −3 . Emissions from road traffic were estimated to contribute more than 75% to the urban increments and non-exhaust emissions contributed 48% (PM 10 ) and 25% (PM 2.5 ) to the total road traffic related increment at an urban background site and 62% (PM 10 ) and 49% (PM 2.5 ) at an urban-traffic site. Analysis of the composition of Switzerland's PM showed that elements associated with non-exhaust emissions, specifically the brake wear tracers of antimony, barium, copper, and iron were the metals with the greatest urban and urban-traffic enhancements. Critically, the urban increment of these elements was enhanced for both PM 10 and PM 2.5 by about the same magnitude as the urban-traffic increment (by 2–3 times), demonstrating non-exhaust emissions are encountered across urban areas, not just the urban-traffic environment. Therefore, non-exhaust emissions were an important contributor to the urban and urban-traffic PM 10 and PM 2.5 increments in Switzerland's urban areas. The relative contributions of non-exhaust emissions to the urban and urban-traffic increments could be expected to increase due to the introduction of further exhaust after-treatment technologies (such as gasoline particulate filters; GPFs) and the transition to a more electrified vehicle fleet. A management pivot will be required to control these non-exhaust emission pathways and although this work exclusively uses data from Switzerland, the conclusions are likely relevant to many other European urban areas. • Non-exhaust road traffic emissions significantly contaminate urban environments. • Non-exhaust emissions were a large contributor to Switzerland's urban increments. • Secondary and biogenic sources were not enhanced in Switzerland's urban areas. • Brake wear tracers were the most enhanced urban and urban-traffic PM components. • Characteristic elements from abrasion processes were enhanced in PM 10 and PM 2.5

Dust storms and violent crime

Dust storms are among the largest global sources of atmospheric particulate matter and have pronounced impacts on environmental conditions and can affect individual ways-of-life. In the US, dust storm activity is generally increasing in frequency due to ongoing climate change. I shed light on a previously unknown impact of these events (on violent crimes) by exploiting their periodic occurrences as a source of exogenous environmental shocks to air pollution and daily routines. Using high-frequency data and high-dimensional fixed effects, I find strong evidence that dust storm activity is associated with violent crimes. Importantly, I show that avoidance behaviors, triggered by dust storm warnings, can largely mitigate the observed violent crime impacts. Policy implications are discussed.

Occupational exposures to particulate matter and PM2.5-associated polycyclic aromatic hydrocarbons at the Agbogbloshie waste recycling site in Ghana

Electronic waste (e-waste) disposal and recycling activities such as burning and smelting can emit particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), and other pollutants that expose workers and nearby communities. At informal e-waste recycling facilities, both emission controls and protective measures for workers are absent. This study characterizes personal exposures (breathing zone) of PM and PAHs of e-waste workers at the large Agbogbloshie e-waste site in Accra, Ghana. We collected gravimetric and optical measurements of PM2.5 and PM10 using shift samples for workers and for an age- and gender-matched reference population. PM2.5 filters were analyzed for 26 PAHs using gas chromatography/mass spectroscopy. Among e-waste workers, PM2.5 and PM10 concentrations were 99 ± 56 and 218 ± 158 µg/m3 (median ± interquartile range, optical measurements), respectively; these levels were 78 and 57% higher, respectively, than levels measured at a fixed site that was centrally located at the waste site. In the reference community, breathing zone PM2.5 and PM10 levels were lower, 49 ± 20 and 131 ± 108 µg/m3, respectively, and the fraction of coarse PM was larger. We detected all 26 target PAHs, of which naphthalene and phenanthrene were the most abundant. PAH concentrations were weakly correlated to PM levels, but PAH abundances, representing the fraction of PAH mass to the total PM2.5 mass collected, were strongly and inversely correlated to PM levels, suggesting multiple and different sources of PAHs and PM that affected exposures. Both PM and PAH levels were elevated for workers performing burning and dismantling, and both exceeded standards or risk-based guidelines, e.g., lifetime excess cancer risks for several PAHs were in the 10−4 to 10−6 range, indicating the need to reduce emissions as well as provide respiratory protection. The study emphasizes the importance of using personal and shift samples to accurately characterize worker exposure.

Morphology, composition and mixing state of individual airborne particles: Effects of the 2017 Action Plan in Beijing, China

Beijing is one of the most important Chinese megacities with extremely serious air pollution problems and human health impacts. In response to the air pollution the central and municipal governments of China have implemented a series of actions; one of which is the “Action Plan for Comprehensive Prevention and Control of Autumn and Winter Air Pollution in Beijing-Tianjin-Hebei and Surrounding Areas 2017–2018” (the Action Plan) issued in 2017. The morphology, composition and mixing state of individual particles collected after the Action Plan was implemented were analyzed by high resolution-transmission electron microscopy coupled with an energy-dispersive X-ray spectrometer (TEM-EDX). The relative percentages of different individual particle types and the main sources of the particulate pollution before and after the Action Plan were compared. The results showed that sulfur was most frequently detected in the individual particles, and the particle types were mainly composed of soot aggregates, mineral particles, organic particles, metal particles, coal fly ashes, sulfate particles, and mixture particles. The mixture and sulfate particles dominated in the autumn samples, both for the haze and non-haze days. In winter the mineral and mixture particles dominated in samples for the non-haze days, while mixture particles and sulfate dominated in the samples for the haze days. The mixture particles in autumn were mainly the soot aggregates internally mixed with sulfate (S-soot type), while the mixture particles in winter were mainly the S-soot type and the mineral particles internally mixed with sulfate (S-mineral type). After the Action Plan, the relative percentages of sulfate particles, organic particles, and soot aggregates increased, while the relative percentages of mineral particles, metal particles and fly ashes decreased. The contribution from coal-fired sources was reduced significantly as evidenced by the decrease in the fly ash particles. The vehicle emissions and secondary reaction of particulate matter became the main sources of atmospheric particulate matters as evidenced by increase in sulfate particles, organic particles, and soot aggregates. The results presented in this study will assist in other plans to improve air quality and human health in megacities around the world.

AirSensor v1.0: Enhancements to the open-source R package to enable deep understanding of the long-term performance and reliability of PurpleAir sensors

As low-cost air quality sensors become more widely utilized, more tools and methods are needed to help users access/process sensor data, identify poorly performing sensors, and analyze/visualize sensor data. Free and open-source software (FOSS) packages developed for use on FOSS data science platforms are well-suited to support this need by offering replicable and shareable tools that can be adapted to meet a user or project's specific needs. This paper describes enhancements to the FOSS AirSensor R package (version 1.0) and the DataViewer web application (version 1.0.1) that have been developed to support data access, processing, analysis, and visualization for the PurpleAir PA-II sensor. This paper also demonstrates how these enhancements may be used to track and assess the health of air sensors in real-time or for large historical datasets. The dataset used for this analysis was collected during a multi-year project (with sensors deployed from October 2017 to October 2020) involving the distribution of approximately 400 PA-II sensors across 14 communities in southern, central, and northern California. Applying the tools in the AirSensor package revealed a dramatic variability in sensor performance, mainly driven by seasonal trends or particulate matter source type. These results also indicate that this sensor can provide useful data for at least three years with little evidence of substantial or consistent drift. Further, high agreement was observed between co-located sensors deployed at different times, indicating that it may be reasonable to compare data from old and new PA-II sensors. In addition to assessing the long-term performance and reliability of the PA-II sensor, this analysis serves as a model for how data from large sensor networks may be effectively processed, evaluated, interpreted, and communicated.

Particulate Matter Dispersion Modeling in Agricultural Applications: Investigation of a Transient Open Source Solver

Agriculture is a major emitter of particulate matter (PM), which causes health problems and can act as a carrier of the pathogen material that spreads diseases. The aim of this study was to investigate an open-source solver that simulates the transport and dispersion of PM for typical agricultural applications. We investigated a coupled Eulerian–Lagrangian solver within the open source software package OpenFOAM. The continuous phase was solved using transient large eddy simulations, where four different subgrid-scale turbulence models and an inflow turbulence generator were tested. The discrete phase was simulated using two different Lagrangian solvers. For the validation case of a turbulent flow of a street canyon, the flowfield could be recaptured very well, with errors of around 5% for the non-equilibrium turbulence models (WALE and dynamicKeq) in the main regions. The inflow turbulence generator could create a stable and accurate boundary layer for the mean vertical velocity and vertical profile of the turbulent Reynolds stresses R11. The validation of the Lagrangian solver showed mixed results, with partly good agreements (simulation results within the measurement uncertainty), and partly high deviations of up to 80% for the concentration of particles. The higher deviations were attributed to an insufficient turbulence regime of the used validation case, which was an experimental chamber. For the simulation case of PM dispersion from manure application on a field, the solver could capture the influence of features such as size and density on the dispersion. The investigated solver is especially useful for further investigations into time-dependent processes in the near-source area of PM sources.

Source Apportionment of Fine Organic Particulate Matter (PM2.5) in Central Addis Ababa, Ethiopia.

The development of infrastructure, a rapidly increasing population, and urbanization has resulted in increasing air pollution levels in the African city of Addis Ababa. Prior investigations into air pollution have not yet sufficiently addressed the sources of atmospheric particulate matter. This study aims to identify the major sources of fine particulate matter (PM2.5) and its seasonal contribution in Addis Ababa, Ethiopia. Twenty-four-hour average PM2.5 mass samples were collected every 6th day, from November 2015 through November 2016. Chemical species were measured in samples and source apportionment was conducted using a chemical mass balance (CMB) receptor model that uses particle-phase organic tracer concentrations to estimate source contributions to PM2.5 organic carbon (OC) and the overall PM2.5 mass. Vehicular sources (28%), biomass burning (18.3%), plus soil dust (17.4%) comprise about two-thirds of the PM2.5 mass, followed by sulfate (6.5%). The sources of air pollution vary seasonally, particularly during the main wet season (June–September) and short rain season (February–April): From motor vehicles, (31.0 ± 2.6%) vs. (24.7 ± 1.2%); biomass burning, (21.5 ± 5%) vs. (14 ± 2%); and soil dust, (11 ± 6.4%) vs. (22.7 ± 8.4%), respectively, are amongst the three principal sources of ambient PM2.5 mass in the city. We suggest policy measures focusing on transportation, cleaner fuel or energy, waste management, and increasing awareness on the impact of air pollution on the public’s health.

Composition and sources of particulate matter in the Beijing-Tianjin-Hebei region and its surrounding areas during the heating season

This paper aimed to analyze the composition and pollution sources of particulate matter (PM) in the Beijing-Tianjin-Hebei region and its surrounding areas (henceforth the BTH region) during the heating season to support the mitigation and control of regional air pollution. Manual monitoring data from the China National Environmental Monitoring Network for Atmospheric PM in the BTH region were collected and analyzed during the 2016 and 2018 heating seasons. The positive definite matrix factor analysis (PMF) model was used to analyze the PM sources in BTH cities during the heating season. The main PM components were organic matter (OM), nitrate (NO3−), sulfate (SO42−) and ammonium salt (NH4+). Direct emission sources have decreased since 2016, indicating the effectiveness of governmental controls on these sources; however, secondary pollution showed an increasing trend, suggesting control measures should be strengthened. Daily regional average concentrations of OM, SO42−, NH4+, elemental carbon (EC), chloride (Cl−) and trace elements all showed similar trends. When air quality worsened, the concentrations of the main PM components increased, but trends of change varied among components. In 2018, concentrations of OM and chloride were highest in the Taihang Mountains, and NO3 concentrations were highest in Anyang, Hebi, Jiaozuo and Xinxiang. The SO42− concentration was highest in the southern section of the Taihang Mountains. The NH4+ and EC concentrations were generally highest in the central and southern regions. The concentration of crustal substances was highest in some cities in the north and central parts of the BTH region. In the 2018 heating season, the pollution level of five transmission channels showed an increasing trend in the Northwest, Southeast, Yanshan, South and Taihang Mountain channels. These findings provide a scientific basis for the continued management of atmospheric PM pollution.

Growth and Physiological Responses of Four Plant Species to Different Sources of Particulate Matter

Background and objective Particulate matter (PM) has a serious impact on health. Recently, studies are conducted to reduce PM in an environmentally friendly way using plants. This study investigated the physiological responses of plants and their ability to remove PM by continuously spraying different PM sources (loam, fly ash, carbon black) to four native plant species, such as &lt;italic&gt;Iris sanguinea&lt;/italic&gt;, &lt;italic&gt;Pteris multifida&lt;/italic&gt;, &lt;italic&gt;Vitis coignetiae&lt;/italic&gt;, and &lt;italic&gt;Viburnum odoratissimum&lt;/italic&gt; var. &lt;italic&gt;awabuki&lt;/italic&gt;. Methods The four plant species were randomly placed in four chambers, and 0.1 g of different PM was injected into each chamber twice a week. We measured chlorophyll, carotenoid, chlorophyll fluorescence (Fv/Fm), total leaf area, amount of leaf wax, PM10 (sPM10) and PM2.5 (sPM2.5) on the leaf surface, and PM10 (wPM10) and PM2.5 (wPM2.5) on the wax layer. Results For &lt;italic&gt;I. sanguinea&lt;/italic&gt; and &lt;italic&gt;V. coignetiae&lt;/italic&gt;, the sources of PM did not affect the growth response. &lt;italic&gt;P. multifida&lt;/italic&gt; showed high chlorophyll a, b, total chlorophyll, and carotenoid content in carbon black as well as high Fv/Fm and total leaf area, thereby proving that carbon black helped plant growth. By PM sources, sPM10 showed a significant difference in three plant species, sPM2.5 in two plant species, and wPM10 in one plant species, indicating that sPM10 was most affected by PM sources. Conclusion Carbon black increased the leaf area by affecting the growth of &lt;italic&gt;P. multifida&lt;/italic&gt;. This plant can be effectively used for PM reduction by increasing the adsorption area. &lt;italic&gt;I. sanguinea&lt;/italic&gt; and &lt;italic&gt;V. coignetiae&lt;/italic&gt; can be used as economical landscaping plants since they can grow regardless of PM sources.