Sources Of Particulate Matter Research Articles

Removal of Particulate Matter by a Non-Powered Brush Filter Using Electrostatic Forces.

In urban areas, a major source of harmful particulate matter is generated by vehicles. In particular, bus stops, where people often stay for public transportation, generate high concentrations of particulate matter compared to the general atmosphere. In this study, a non-powered type brush filter that generates electrostatic force without using a separate power source was developed to manage the concentration of particulate matter exposed at bus stops, and the removal performance of particulate matter was evaluated. The dust collection performance of the non-motorized brush filter varied by material, with particle removal efficiencies of 82.1 ± 3.4, 76.1 ± 4.7, and 73.7 ± 4.5% for horse hair, nylon, and stainless steel, respectively. In conditions without the fan running to see the effect of airflow, the particle removal efficiency was relatively low at 58.2 ± 8.4, 53.6 ± 9.2, and 58.0 ± 7.3%. Then, to check the dust collection performance according to the density, the number of brushes was increased to densify the density, and the horse hair, nylon, and stainless steel brush filters showed a maximum dust collection performance of 89.6 ± 2.2, 88.3 ± 3.2, and 82.1 ± 3.8%, respectively. To determine the replacement cycle of the non-powered brush filter, the particulate removal performance was initially 88.0 ± 3.2% when five horse hair brushes were used. Over time, particulate matter tended to gradually decrease, but after a period of time, particulate matter tended to increase again. The purpose of this study is to evaluate the particulate matter removal performance using a brush filter that generates electrostatic force without a separate power source. This study's brush filter is expected to solve the maintenance problems caused by the purchase and frequent replacement of expensive HEPA filters that occur with existing abatement devices, and the ozone problems caused by abatement devices that use high voltages.

Provenance Indication of Rare Earth Elements in Lake Particulates from Environmentally Sensitive Regions

The provenance of lake particulate matter in environmentally sensitive areas is crucial to understanding regional environmental and climatic changes. This study investigated two regions in the Northeast Tibetan Plateau, China: Region I (Keluke, Tuosu, and Gahai Lakes) and Region II (Qinghai Lake and nearby rivers). The results showed that: (1) The two regions have greater differences in the enrichment of rare earth elements (REEs) and heterogeneity in spatial distribution, both of which are characterized by relative enrichment of LREE and depletion of HREE, but to different degrees; (2) the source and formation of particulate matter in two regions are consistent. Particulate matter in Region I (Keluke and Tuosu Lakes) predominantly originates from granite rocks, which undergo weathering and transportation through rivers. Region II (Qinghai Lake and nearby rivers) particulate matter is affected by chemical weathering and partial recycling of detrital material. Diagenesis had a minimal impact on the particulate REEs. (3) This study primarily provides a preliminary understanding of REEs in lake particles, assessing particle changes during the water-to-sediment process and their provenance indication. Future studies will incorporate the solid fugacity (solid speciation) of REEs in particles, contributing to a comprehensive understanding of rare earth element geochemical processes. This study provides valuable insights into REEs distribution, source, and geochemical behavior in the Tibetan Plateau, underscoring the importance of REEs in understanding provenance processes, and is indicative of provenance studies in other climate change-sensitive regions of the world.

Mobile measurements for distribution and attribution of particulate matter in urban environments

Particulate matter (PM) sources differ in urban environments and may show spatiotemporal distinct patterns for varying particle aerodynamic diameters (DP). We here assess such patterns using high-resolution PM ≤10 μm data recorded with a cargo bike along a 14 km route through urban, suburban, and rural areas in Mainz (Germany). The measurements conducted twice a day between May and August 2021 reveal decreasing particle number concentration (PNC) with increasing DP including ∼6000 times higher particle numbers at DP 0.22–0.25 μm compared to DP 4–5 μm. Total mass concentration is bi-modally distributed and dominated by particles <0.3 μm and from 3 to 5 μm representing 36 and 22% of the entire air load, respectively. PM concentrations in Mainz are significantly higher in the morning than in the afternoon, and PM1 and PM10 are 13 and 31% higher in urban compared to surrounding suburban and rural areas. The high-resolution measurements also revealed 30% higher PM concentrations at DP 3–5 μm in the urban compared to the rural sectors, which is indicative for road dust, brake and tyre abrasion as the main source. DP distribution in rural hotspots is generally shifted toward larger particles >3 μm, most likely related to natural dust from agricultural fields. These findings show that high-resolution PM profiles can skillfully be recorded using bikes as mobile platform to identify spatial pollution patterns and attribute DP spectra to particular emission sources.

Performance evaluation of MOMA (MOment MAtching) – a remote network calibration technique for PM2.5 and PM10 sensors

Abstract. We evaluate the potential of using a previously developed remote calibration framework we name MOMA (MOment MAtching) to improve the data quality in particulate matter (PM) sensors deployed in hierarchical networks. MOMA assumes that a network of reference instruments can be used as “proxies” to calibrate the sensors given that the probability distribution over time of the data at the proxy site is similar to that at a sensor site. We use the reference network to test the suitability of proxies selected based on distance versus proxies selected based on land use similarity. The performance of MOMA for PM sensors is tested with sensors co-located with reference instruments across three Southern Californian regions, representing a range of land uses, topography and meteorology, and calibrated against a distant proxy reference. We compare two calibration approaches: one where calibration parameters get calculated and applied at monthly intervals and one which uses a drift detection framework for calibration. We demonstrate that MOMA improves the accuracy of the data when compared against the co-located reference data. The improvement was more visible for PM10 and when using the drift detection approach. We also highlight that sensor drift was associated with variations in particle composition rather than instrumental factors, explaining the better performance of the drift detection approach if wind conditions and associated PM sources varied within a month.

Gas–particle partitioning of semivolatile organic compounds when wildfire smoke comes to town

Abstract. Wildfires have become an increasingly important source of organic gases and particulate matter in the western USA. A large fraction of organic particulate matter emitted in wildfires is semivolatile, and the oxidation of organic gases in smoke can form lower-volatility products that then condense on smoke particulates. In this research, we measured the gas- and particle-phase concentrations of semivolatile organic compounds (SVOCs) during the 2017 northern California wildfires in a downwind urban area, using semivolatile thermal desorption aerosol gas chromatography (SV-TAG), and measured SVOCs in a rural site affected by biomass burning using cTAG (comprehensive thermal desorption aerosol gas chromatography mass spectrometry) in Idaho in 2018. Commonly used biomass burning markers such as levoglucosan, mannosan, and nitrocatechols were found to stay predominantly in the particle phase, even when the ambient organic aerosol (OA) was relatively low. The phase partitioning of SVOCs is observed to be dependent on their saturation vapor pressure, while the equilibrium absorption model underpredicts the particle-phase fraction of most of the compounds measured. Wildfire organic aerosol enhanced the condensation of polar compounds into the particle phase but not some nonpolar compounds, such as polycyclic aromatic hydrocarbons.

Response of organic aerosol to Delhi's pollution control measures over the period 2011–2018

Some of the world's highest air pollution episodes occur in Delhi, India and studies have shown particulate matter (PM) is the leading air pollutant to cause adverse health effects on Delhi's population. It is therefore vital to chart sources of PM over long time periods to effectively identify trends, particularly as multiple air quality mitigation measures have been implemented in Delhi over the past 10 years but remain unevaluated. An automated offline aerosol mass spectrometry (AMS) method has been developed which has enabled high-throughput analysis of PM filters. This novel offline-AMS method uses an organic solvent mix of acetone and water to deliver high extraction recoveries of organic aerosol (OA) (95.4 ± 8.3%). Positive matrix factorisation (PMF) source apportionment was performed on the OA fraction extracted from PM10 filter samples collected in Delhi in 2011, 2015 and 2018 to provide snapshots of the responses of OA to changes in sources in Delhi. The nine factors of OA resolved by PMF group into four primary source categories: traffic, cooking, coal-combustion and burning-related (solid fuel or open burning). Burning-related OA made the largest contribution during the winter and post-monsoon, when total OA concentrations were at their highest. Annual mean burning-related OA concentrations declined by 47% between 2015 and 2018, likely associated with the 2015 ban on open waste burning and controls and incentives to reduce crop-residue burning. Compositional analysis of OA factors shows municipal waste burning tracers still present in 2018, indicating further scope to reduce burning-related OA. The closure of the two coal power stations, along with initiatives to decrease coal use in industry, businesses, and residential homes, resulted in a significant decrease (87%) in coal-combustion OA. This corresponds to a 17% reduction in total OA, which shows the effectiveness of these measures in reducing PM10. Increases in traffic OA appear to have been offset by the introduction of the Bharat stage emissions standards for vehicles as the increases do not reflect the rapid increase in registered vehicles. However, daytime restrictions on heavy goods vehicles (HGVs) entering the city is linked to large increases in PM10 during the winter and post-monsoon, likely because the large influx of diesel-engine HGVs during the early mornings and evenings is timed with a particularly low planetary boundary layer height that enhances surface concentrations.

Impact of agricultural activity on PM2.5 and its compositions in elementary schools near corn and rice farms

Agricultural activity is an important source of particulate matter <2.5 μm in size (PM2.5) in rural areas. In Taiwan, many elementary schools are surrounded by farms, and studies investigating the impact of agricultural activity on air quality in schools are required. We collected PM2.5 samples from the classrooms of elementary schools near corn and rice farms during the crop cultivation stages and analyzed their concentrations and compositions to investigate whether agricultural activity affects the schools' air quality. We found that the average ratio of PM2.5/PM10 (<10 μm in particle size) was <0.6 in the school near the corn farm, and that the indoor PM2.5/PM10 ratio was significantly associated (r = 0.93, p < 0.05) with the outdoor ratio. Moreover, the potassium (K) concentration in the school near the corn farm (189.2 ± 119 ng/m3) was higher than that near the rice farm (140.9 ± 116.0 ng/m3). There were higher concentrations of K and crustal elements, and a greater crustal elements/heavy metals ratio, in the school near the corn farm during the sowing and soil covering stages than during other cultivation stages. Positive matrix factorization (PMF) results indicate that agricultural activity was a predominant contributor of PM2.5 in the schools near corn and rice farms, however, PM2.5 from industrial and traffic emissions also affected schools' air quality. In summary, agricultural activity influenced the air quality of schools, especially near the corn farm. Governments should develop air quality management policies to reduce the risk of children suffering exposure to high particle concentrations in these schools and further suggest that the impact of industrial and traffic emissions on air quality also requires attention.

Occupational health risk assessment of construction workers caused by particulate matter exposure on construction sites

Construction particulate matter is one of the main environmental impact factors in the construction process. Due to the lack of sufficient awareness and understanding of the potential health effects of particulate matter by project managers and construction workers, the on-site working environment has not been effectively improved for a long time, and construction workers have been exposed to high particulate matter concentration conditions for physical labor for a long time. The construction site is a special operation scene, and the source and diffusion of particulate matter are a complex physical change process, and the degree of damage to the health of construction workers is closely related to the exposure dose. Thus, suitable quantitative and evaluation methods need to be adopted. The current on-site particulate matter concentration control system lacks technical and data support and cannot support the needs of on-site environmental management. In this paper, three construction sites in different stages of construction in Shanghai were selected to measure the mass concentration of open source particulate matter, and on this basis, the emission factors of particulate matter in different operating areas were calculated. At foundation stage, the emission factor of TSP, PM10, PM2.5 are 0.0214 g/m2·h, 0.0067 g/m2·h, 0.0054 g/m2·h; at main structure stage, the emission factor of TSP, PM10, PM2.5 are 0.0136 g/m2·h, 0.0053 g/m2·h, 0.0041 g/m2·h; at installation and decoration stage, the emission factor of TSP, PM10, PM2.5 are 0.0165 g/m2·h, 0.0059 g/m2·h, 0.0043 g/m2·h. Using simulation software to simulate the temporal and spatial distribution of particulate matter concentration at the site of the example project, it is found that workers engaged in pit bottom operation in the foundation stage, steel bar processing in the main structure stage, and plastering, masonry and putty workers in the installation and decoration stage are the people with the highest occupational health risk at the construction site. In this study, DALYs were used as a metric to monetize the health risks of particulate matter to workers in the field. Support scientific decision-making on particulate matter control at construction sites and improve the level of on-site occupational health management.

Associations between Fine Particulate Matter Composition and Sources with Adverse Health Effects: A Systematic Review and Meta-Analysis

Associations between Fine Particulate Matter Composition and Sources with Adverse Health Effects: A Systematic Review and Meta-Analysis

Source apportionment study on particulate air pollution in two high-altitude Bolivian cities: La Paz and El Alto

Abstract. La Paz and El Alto are two fast-growing, high-altitude Bolivian cities forming the second-largest metropolitan area in the country. Located between 3200 and 4050 m a.s.l. (above sea level), these cities are home to a burgeoning population of approximately 1.8 million residents. The air quality in this conurbation is heavily influenced by urbanization; however, there are no comprehensive studies evaluating the sources of air pollution and their health impacts. Despite their proximity, the substantial variation in altitude, topography, and socioeconomic activities between La Paz and El Alto result in distinct sources, dynamics, and transport of particulate matter (PM). In this investigation, PM10 samples were collected at two urban background stations located in La Paz and El Alto between April 2016 and June 2017. The samples were later analyzed for a wide range of chemical species including numerous source tracers (OC, EC, water-soluble ions, sugar anhydrides, sugar alcohols, trace metals, and molecular organic species). The United States Environmental Protection Agency (U.S. EPA) Positive Matrix Factorization (PMF v.5.0) receptor model was employed for the source apportionment of PM10. This is one of the first source apportionment studies in South America that incorporates an extensive suite of organic markers, including levoglucosan, polycyclic aromatic hydrocarbons (PAHs), hopanes, and alkanes, alongside inorganic species. The multisite PMF resolved 11 main sources of PM. The largest annual contribution to PM10 came from the following two major sources: the ensemble of the four vehicular emissions sources (exhaust and non-exhaust), accountable for 35 % and 25 % of the measured PM in La Paz and El Alto, respectively; and dust, which contributed 20 % and 32 % to the total PM mass. Secondary aerosols accounted for 22 % (24 %) in La Paz (El Alto). Agricultural smoke resulting from biomass burning in the Bolivian lowlands and neighboring countries contributed to 9 % (8 %) of the total PM10 mass annually, increasing to 17 % (13 %) between August–October. Primary biogenic emissions were responsible for 13 % (7 %) of the measured PM10 mass. Additionally, a profile associated with open waste burning occurring from May to August was identified. Although this source contributed only to 2 % (5 %) of the total PM10 mass, it constitutes the second largest source of PAHs, which are compounds potentially hazardous to human health. Our analysis additionally resolved two different traffic-related factors, a lubricant source (not frequently identified), and a non-exhaust emissions source. Overall, this study demonstrates that PM10 concentrations in La Paz and El Alto region are predominantly influenced by a limited number of local sources. In conclusion, to improve air quality in both cities, efforts should primarily focus on addressing dust, traffic emissions, open waste burning, and biomass burning.

Trace Elements Concentrations in Urban Air in Helsinki, Finland during a 44-Year Period

The atmospheric concentrations of seventeen elements were measured in air filters at the Finnish Meteorological Institute station in Helsinki, Finland, during a period of 44 years (1962–2005). The mean annual concentrations were calculated and are presented from the lowest values to the highest ones Cr &lt; Ni &lt; Ti &lt; Br &lt; V &lt; Mn &lt; Cu &lt; Zn &lt; Cl &lt; Al &lt; Fe &lt; K &lt; Ca &lt; Na &lt; Pb &lt; Si &lt; S. Most of the elements (Fe, Si, Ti, K, Ca, Zn, Br, Pb, V, Ni, S, Cr, Na, Al, and Cl) present higher values during spring and winter season, while in summer the elements (Ti, Ca, S, and Na) are found in higher concentrationsdue to the weather conditions across seasons and the sources and emissions of air pollutants. There is a strong correlation between the elements (V-Ni, Si-Pb, Fe-Ca, V-Cr, Si-K, K-Ca, Fe-Ti, K-Na, Si-Ca, and V-S), indicating their common source. The identification of the sources of trace elements was performed based on positive matrix factorization analysis, using SoFi software. Four Suspended Particulate Matter (PM) sources were identified: road dust (due to usage of leaded fuel), heavy oil combustion/secondary sulfates, traffic emissions, and natural dust (soil). For the total of 44 years studied, significant decreases in concentrations were observed for all elements, most of which were over 50%: Na (−74%), Al (−86%), Si (−88%), S (−82%), K (−82%), Ca (−89%), Ti (−80%), V (−89%), Cr (−82%), Mn (−77%), Fe (−77%), Ni (−61%), Zn (−72%), and Pb (−95%). In general, a significant decline has been observed in the majority of the elemental concentrations since the end of the 1970s, underlying the effectiveness of different environmental policies that have been applied during the last few decades.

The origin of suspended particulate matter in the Great Barrier Reef

River run-off has long been regarded as the largest source of organic-rich suspended particulate matter (SPM) in the Great Barrier Reef (GBR), contributing to high turbidity, pollutant exposure and increasing vulnerability of coral reef to climate change. However, the terrestrial versus marine origin of the SPM in the GBR is uncertain. Here we provide multiple lines of evidence (13C NMR, isotopic and genetic fingerprints) to unravel that a considerable proportion of the terrestrially-derived SPM is degraded in the riverine and estuarine mixing zones before it is transported further offshore. The fingerprints of SPM in the marine environment were completely different from those of terrestrial origin but more consistent with that formed by marine phytoplankton. This result indicates that the SPM in the GBR may not have terrestrial origin but produced locally in the marine environment, which has significant implications on developing better-targeted management practices for improving water quality in the GBR.

Machine learning reveals the effects of drivers on PM2.5 and CO2 based on ensemble source apportionment method

Air pollution and climate change are currently common global concern issues. Understanding the main pollution sources of fine particulate matter (PM2.5) and carbon dioxide (CO2), and the drivers that accelerate their concentrations can provide novel insights into the co-benefits of air-quality improvement and climate change mitigation. Hence, in this study, we conducted source apportionment of PM2.5 and CO2, and obtained impacts of common sources on PM2.5-CO2 using an ensemble source apportionment method. Then, machine learning (ML) methods were utilized to study the effects of different drivers (including main pollution sources and meteorological factors) on PM2.5 and CO2. The results demonstrate that coal combustion (40%), vehicle exhaust (37%), and industrial emissions (23%) were the main common sources of PM2.5 and CO2. Controlling the combustion of fossil fuels and long-term vehicle electrification still hold significant importance for reducing pollutions and carbon emissions. The results of data-driven ML models show that temperature had the highest effect among meteorological factors, reflecting the seasonal changes of CO2 and PM2.5. The study provides a feasible framework for exploring co-benefits of clean air policies on greenhouse gas emissions based on online observation dataset.

Evaluating the effectiveness of low-sulphur marine fuel regulations at improving urban ambient PM2.5 air quality: Source apportionment of PM2.5 at Canadian Atlantic and Pacific coast cities with implementation of the North American Emissions Control Area

Ambient fine size fraction particulate matter (PM2.5) sources were resolved by positive matrix factorization at two Canadian cities on the Atlantic and Pacific coast over the 2010–2016 period, corresponding to implementation of the North American Emissions Control Area (NA ECA) low-sulphur marine fuel regulations. Source types contributing to local PM2.5 concentrations were: ECA regulation-related (residual oil, anthropogenic sulphate), urban transportation and residential (gasoline, diesel, secondary nitrate, biomass burning, road dust/soil), industry (refinery, Pb-enriched), and largely natural (biogenic sulphate, sea salt). Anthropogenic sources accounted for approximately 80 % of PM2.5 mass over 2010–2016. Anthropogenic and biogenic sources of PM2.5-sulphate were separated and apportioned. Anthropogenic PM2.5-sulphate was approximately 2–3 times higher than biogenic PM2.5-sulphate prior to implementation of the NA ECA low-S marine fuel regulations, decreasing to 1–2 times higher after regulation implementation. Non-marine anthropogenic sources (gasoline, road dust, local industry factors) were shown to together contribute 38 % - 45 % of urban PM2.5. At both coastal cities, the residual oil and anthropogenic sulphate factors clearly reflected the effects of the low-S fuel regulations at reducing primary and secondary sulphur-related PM2.5 emissions. Comparing a pre-regulation and post-regulation period, residual oil combustion PM2.5 decreased by 0.24–0.25 μg/m3 (94%–95 % decrease) in both cities and anthropogenic sulphate PM2.5 decreased by 0.78 μg/m3 in Halifax (47 % decrease) and 0.71 μg/m3 in Burnaby (58 % decrease). Regulation-related PM2.5 across these factors decreased by approximately 1 μg/m3 after regulation implementation, providing a quantified lower estimate of the beneficial influence of the regulations on urban ambient PM2.5 concentrations. Further reductions in coastal city ambient PM2.5 may best consider air quality strategies that include multiple sources, including marine shipping and non-marine anthropogenic source types given this analysis found that marine vessel emissions remain an important source of urban ambient PM2.5.

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution-Part B-Particle Number Concentrations.

Low-cost Particulate Matter (PM) sensors offer an excellent opportunity to improve our knowledge about this type of pollution. Their size and cost, which support multi-node network deployment, along with their temporal resolution, enable them to report fine spatio-temporal resolution for a given area. These sensors have known issues across performance metrics. Generally, the literature focuses on the PM mass concentration reported by these sensors, but some models of sensors also report Particle Number Concentrations (PNCs) segregated into different PM size ranges. In this study, eight units each of Alphasense OPC-R1, Plantower PMS5003 and Sensirion SPS30 have been exposed, under controlled conditions, to short-lived peaks of PM generated using two different combustion sources of PM, exposing the sensors' to different particle size distributions to quantify and better understand the low-cost sensors performance across a range of relevant environmental ranges. The PNCs reported by the sensors were analysed to characterise sensor-reported particle size distribution, to determine whether sensor-reported PNCs can follow the transient variations of PM observed by the reference instruments and to determine the relative impact of different variables on the performances of the sensors. This study shows that the Alphasense OPC-R1 reported at least five size ranges independently from each other, that the Sensirion SPS30 reported two size ranges independently from each other and that all the size ranges reported by the Plantower PMS5003 were not independent of each other. It demonstrates that all sensors tested here could track the fine temporal variation of PNCs, that the Alphasense OPC-R1 could closely follow the variations of size distribution between the two sources of PM, and it shows that particle size distribution and composition are more impactful on sensor measurements than relative humidity.

Development of emission reduction measures of particulate matter emitted from coal fired power plants in Indonesia

Currently, Indonesia has committed to achieve Net Zero Emissions (NZE) efforts on their Nationally Determined Contribution (NDCs) and at the same time focusing on air pollution abatement. One of the dominant emissions sources of particulate matter as well as Greenhouse Gases (GHGs) is from coal fired power plants. It contributes 50% to the total energy consumption in power generation, therefore the major power plant in Indonesia. Therefore, efforts to reduce GHGs and particulate emissions are needed to achieve the NZE target as well as to improve air quality. The research objective is to determine the particulate pollution load based on the Business as Usual (BaU) scenario and also under the emission reduction scenario for the year of 2030. Particulate pollution load was calculated using the emissions inventory methodology described in the brown cloud atmosphere workbook (ABC-EIM). Particulate emission reduction scenarios were developed using the assumption of full installation of Electrostatic Precipitator (ESP) technology to control PM emission. In 2030, the emission reductions PM10, PM2.5, Black Carbon (BC), and Organic Carbon (OC) are 57,854 ton/year, 57,854 ton/year, 432 ton/year, and 1,723 ton/year.

Efficacy of green infrastructure in reducing exposure to local, traffic-related sources of airborne particulate matter (PM)

One aim of roadside green infrastructure (GI) is to mitigate exposure to local, traffic-generated pollutants. Here, we determine the efficacy of roadside GI in improving local air quality through the deposition and/or dispersion of airborne particulate matter (PM). PM was collected on both pumped air filters and on the leaves of a recently installed ‘tredge’ (trees managed as a head-high hedge) at an open road environment next to a primary school in Manchester, U.K. The magnetic properties of PM deposited on leaves and filters (size fractions PM10 and PM2.5) were deduced from hysteresis loops, first-order reversal curves (FORCs), and low-temperature remanence measurements. These were complemented with electron microscopy to identify changes in magnetic PM concentration downwind of the tredge/GI. We show that the tredge is permeable to airflow using a simple CO2 tracer experiment; hence, it allows interception and subsequent deposition of PM on its leaves. Magnetic loadings per m3 of air from filters (PM10 saturation magnetisation, Ms, at 5 K) were reduced by 40 % behind the tredge and a further 63 % in the playground; a total reduction of 78 % compared to roadside air. For the PM2.5 fraction, the reduction in magnetic loading behind the tredge was remarkable (82 %), reflecting efficient diffusional capture of sub-5 nm Fe-oxide particles by the tredge. Some direct mixing of roadside and playground air occurs at the back of the playground, caused by air flow over, and/or through gaps in, the slowly-permeable tredge. The magnetic loading on tredge leaves increased over successive days, capturing ~23 % of local, traffic-derived PM10. Using a heuristic two-dimensional turbulent mixing model, we assess the limited dispersion of PM < 22.5 μm induced by eddies in the tredge wake. This study demonstrates that PM deposition on leaves reduces exposure significantly in this school playground setting; hence, providing a cost-effective mitigation strategy.

Source Identification and Characterization of Indoor Particulate Matter in Potala Palace Museum

This study aims to determine the sources of indoor particulate matter at the Potala Palace Museum in Tibet, China, and evaluate the potential hazards of these pollutants for cultural relics. Long-term monitoring of indoor and outdoor suspended particulate matter concentrations was conducted, and sediment particle samples were collected. The chemical composition of the deposited particles was determined using X-ray fluorescence analysis (XRF). The outdoor suspended particulate concentration was much lower than that indoors; the indoor PM1-10 concentration was much higher than that outdoors and was less affected by outdoor sources. The sources of indoor deposited particles in the high-plateau museum can be classified into four categories: soil dust brought in by tourists from the outdoors, incense ash, pollution from human activities, and ores. Based on data analysis and discussion, proper ventilation can dilute indoor suspended particulate matter, and the installation of air conditioning systems can control temperature and humidity at 20 °C and about 45–60%, respectively, and reduce the fluctuation value, so as to promote particle deposition and better protect the museum’s cultural relics.

Physical and chemical characteristics of particles emitted by a passenger vehicle at the tire-road contact

Non-exhaust emissions are now recognized as a significant source of atmospheric particulate matter and the trend towards a reduction of conventionally fueled internal combustion engine vehicles on the road is increasing their contribution to air pollution due to lower exhaust emissions. These particles include brake wear particles (BWP) and tire-road contact particles (TRCP), which are composed of tire wear particles (TWP), road wear particles (RWP) and resuspended road dust (RRD). The goal of this study has therefore been to design an original experimental approach to provide insight into the chemical composition of particles emitted at the tire-road contact, focusing on the micron (PM10–1μm) and submicron (PM1–0.1μm) fractions. Through this characterization, an examination of the different TRCP generated by different materials (tire, road surface, brake system) was conducted. To achieve this, TRCP were collected at the rear of the wheel of an instrumented vehicle during road and track tests, and a SEM-EDX analysis was performed. Our experimental conditions have allowed us to demonstrate that, at the individual particle scale, TRCP are consistently associated with road dust materials and particles solely composed of tire or road materials are practically non-existent. The contribution of BWP to TRCP is marked by the emission of Fe-rich particles, including heavy metals like Ba, Mn and Cr. TWP, which result from rubber abrasion, consist of C-rich particles abundant in Si, Zn, and S. RWP, mainly composed of Al, Si, Fe, and Ca, can be either part of RRD or internally mixed with emitted TWP. The findings of this study highlight the substantial role of RRD to TRCP emissions under real driving conditions. Consequently, it underscores the importance of examining them simultaneously to achieve a more accurate estimation of on-road traffic emissions beyond the vehicle exhaust.

Foliar particulate matter retention and toxic trace element accumulation of six roadside plant species in a subtropical city

As a major source of air pollution, particulate matter (PM) and associated toxic trace elements pose potentially serious threats to human health and environmental safety. As is known that plants can reduce air PM pollution. However, the relationship between PM of different sizes and toxic trace elements in foliar PM is still unclear. This study was performed to explore the association between PM of different sizes (PM2.5, PM10, PM>10) and toxic trace elements (As, Al, Cu, Zn, Cd, Fe, Pb) as well as the correlation among toxic trace elements of six roadside plant species (Cinnamomum camphora, Osmanthus fragrans, Magnolia grandiflora, Podocarpus macrophyllus, Loropetalum chinense var. rubrum and Pittosporum tobira) in Changsha, Hunan Province, China. Results showed that P. macrophyllus had the highest ability to retain PM, and C. camphora excelled in retaining PM2.5. The combination of P. macrophyllus and C. camphora was highly recommended to be planted in the subtropical city to effectively reduce PM. The toxic trace elements accumulated in foliar PM varied with plant species and PM size. Two-way ANOVA showed that most of the toxic trace elements were significantly influenced by plant species, PM size, and their interactions (P < 0.05). Additionally, linear regression and correlation analyses further demonstrated the homology of most toxic trace elements in foliar PM, i.e., confirming plants as predictors of PM sources as well as environmental monitoring. These findings contribute to urban air pollution control and landscape configuration optimization.