Sources Of Particulate Matter Research Articles

Review of Road Dust Resuspension Modelling Approaches and Comparisons Analysis for a UK Case Study

This report provides a review of several measurement studies and campaigns focusing on road dust resuspension (RDS), which is becoming an important source of ambient particulate matter (PM) concentrations. There is a growing requirement from stakeholders, policy makers and scientists for gathering additional data around RDS, since there is a lack of well-established methodologies or those developed for measuring or modelling this source of emissions are not very recent. Moreover, conventional inventory methodologies are not available for this source of emissions, and it is not yet covered in the UK’s National Atmospheric Emissions Inventory (NAEI) neither in the inventory guidebooks at European level. Based on the available literature and models, this paper also seeks to provide some preliminary considerations whether an approach can be tailored for application in air quality models used for modelling ambient PM concentrations in the UK in a consistent manner and demonstrated using a state-of-art air quality modelling tool, namely RapidAir®. The impact of including resuspension emissions on roadside concentrations was modelled in a UK case study with the greatest increases in modelled road PM10 concentrations observed on or near the road surface. The paper concludes with recommendations for longer-term implementation of the proposed improvements such as investigation of the temporal effects of RDS on PM levels; of the influence of different type of tyre materials and mixture (e.g., composition) and designs (e.g., shape, dimensions and tread); and influence of different existing pavements or of new road surface types.

Measurements of Particulate Matter from Electronic and Conventional Cigarettes: A Comparative Analysis of Methods

Due to the growing popularity of electronic cigarettes (ECs) and heated tobacco products (HTPs) as alternatives to conventional cigarettes (CCs), there is an increasing need to monitor the emissions of these new devices. ECs generate significant concentrations of second-hand aerosol (ECSHA), which is visible in dense clouds and can be smelled. Particulate matter (PM) is an important component of CC, HTP and EC aerosols, and Optical Particle Counters (OPCs) enable its real-time measurement, which is expressed either as the number of particles or as mass. This study specifically addresses the limitations associated with EC mass measurement using OPC technology and identifies the strict necessity of the measurement of a corresponding density (k factor) not only for each specific PM source but also for the desired PM size. Therefore, a standard measurement requires the simultaneous operation of the OPC equipment and a certified reference instrument. Four different OPCs were used. Crucially, this study also proves that this setup may be inapplicable because the extreme volatility of EC-generated aerosols makes it impractical to gauge the correct EC k factor.

Chemical characteristics analysis of automobile exhaust particles and the method for evaluating its ecological effect

Automobile exhaust has become the main source of atmospheric particulate matter with the increase in the number of automobiles. Automobile exhaust particles (AEPs) discharged into the atmosphere can enter the aquatic environment through atmospheric deposition, rain runoff, leaching, drainage water and urban sewage and further affect aquatic organisms. However, there is no comprehensive theory and method to evaluate the ecological effects of AEPs on aquatic environment. The new European driving cycle (NEDC) and the world harmonized light-duty test cycle (WLTC) were used to analyze the ecotoxicity of AEPs. The SUV gasoline, SUV hybrid and sedan gasoline under WLTC were used for further analysis. The chemical characteristics of AEPs were analyzed, and the ecotoxicity of AEPs on aquatic organisms was studied with Vibrio fischeri and Danio rerio as test organisms. The ecological effect of AEPs was studied through species sensitivity distribution based on interspecies correlation estimation (ICE) models. The results showed that (ⅰ) polycyclic aromatic hydrocarbons (PAHs) were the main organic substances in AEPs. The total concentrations of PAHs in AEPs measured under the NEDC and WLTC were 237.4 and 159.8 mg kg−1, respectively, and the EC50 values for V. fischeri measured under the NEDC and WLTC were 42.02 and 47.05 mg L−1, respectively. (ⅱ) Total heavy metal concentrations in AEPs from SUV gasoline, SUV hybrid, and sedan gasoline were 197.52, 104.86, and 89.68 mg kg−1, respectively, and the LC50 values for D. rerio were 3.22, 4.46 and 5.62 mg L−1. Cu and Mn were the main toxic heavy metals in AEPs. (ⅲ) The PNEC values of AEPs from SUV gasoline, SUV hybrid and sedan gasoline were 0.57, 0.83 and 1.02 mg L−1, respectively. This exploratory study can provide technical information on water ecological safety assessment for determining the impact of AEPs on the surface water environment and for further improving automobile exhaust emission standards.

Estimation of exposure and premature mortality from near-roadway fine particulate matter concentrations emitted by heavy-duty diesel trucks in Beijing

Traffic exhaust is a main source of fine particulate matter (PM2.5) in cities. Heavy-duty diesel trucks (HDDTs), the primary mode of freight transport, contribute significantly to PM2.5, posing a great threat to public health. However, existing research based on dispersion models to simulate pollutant concentrations lacks high-spatiotemporal-resolution emission inventories of HDDTs as input data, and the public health effects of such emissions in different populations have not been thoroughly assessed. To fill this gap, we focused on Beijing as the research area and developed a high-resolution PM2.5 emission inventory for HDDTs based on Global Navigation Satellite System-equipped vehicle trajectory data. We then simulated the fine-scale spatial distribution of diesel-related PM2.5 and assessed the population exposure by integrating the dispersion model and population distributions. Further, we quantified the mortality attributable to noncommunicable diseases (NCDs) plus lower respiratory infections (LRIs) related to PM2.5 emissions from HDDTs. Results showed that 3.3% of Beijing people lived in areas with high PM2.5 HDDT emissions, which were near intercity highways. Furthermore, the estimated number of NCD + LRI annual premature deaths attributed to PM2.5 HDDT emissions in Beijing was 339 (95% CI: 276–401). The NCD + LRI mortality increased with age, and deaths were more frequent in males than females. Our results aid the identification of HDDT PM2.5 emission exposure hotspots for the formulation of effective mitigation measures and provide important insights into the adverse health impacts of HDDT emissions.

Particulate Matter Concentration in Selected Facilities as an Indicator of Exposure to Their Service Activities.

In recent years, the correlation between the concentration of pollutants in the atmosphere and inside buildings has been reported as high. The air inside living quarters and public utility buildings or the interiors of public transport vehicles, as well as the relationship between the internal and external sources of particulate matter (PM) and gaseous pollutants, have underwent sufficient research. On the other hand, non-production rooms, i.e., offices, restaurants, beauty salons, etc. remain very poorly recognized in this respect. For the above reasons, the aim of this work is to determine the difference in the total dust (TSP) and respirable PM (PM4) concentrations in selected rooms, i.e., offices and beauty centers, in relation to their outdoor concentrations. They were measured at six locations in accordance with the standard for the conditions at workplaces by means of PM aspirators. Indoor concentrations of TSP and PM4 were much higher than those in the external surroundings of the facilities. There were no significant relationships between the TSP and PM4 concentrations inside and outside tested rooms. Although the characteristic of the internal PM essentially depends on the characteristics of the external PM migrating to the interior of the premises, considering some types of non-production premises, internal emissions fundamentally changed the characteristics of PM.

Diurnal trends of indoor and outdoor fluorescent biological aerosol particles in a tropical urban area

We evaluated diurnal trends of size-resolved indoor and outdoor fluorescent biological airborne particles (FBAPs) and their contributions to particulate matter (PM) within 0.5–20 μm. After a ten-week continuous sampling via two identical wideband integrated bioaerosol sensors, we found that both indoor and outdoor diurnal trends of PM were driven by its bioaerosol component. Outdoors, the median [interquartile range] FBAP mass concentration peaked at 8.2 [5.8–9.9] μg/m3 around sunrise and showed a downtrend from 6:00 to 18:00 during the daytime and an uptrend during the night. The nighttime FBAP level was 1.8 [1.4–2.2] times higher than that during the daytime, and FBAPs accounted for 45 % and 56 % of PM during daytime and nighttime, respectively. Indoors, the rise in concentrations of FBAPs smaller than 1 μm coincided with the starting operation of the heating, ventilation, and air conditioning (HVAC) system at 6:00, and the concentration peaked at 8:00 and dropped to the daily average by noontime. This indicated that the starting operation of the HVAC system dislodged the overnight settled and accumulated fine bioaerosols into the indoor environment. For particles larger than 1 μm, the variation of mass concentration was driven by occupancy. Based on regression modeling, the contributions of indoor PM, non-FBAP, and FBAP sources to indoor mass concentrations were estimated to be 93 %, 67 %, and 97 % during the occupied period.

Spatial and temporal evolution of soil wind erosion in the Beijing-Tianjin sandstorm sources

<p indent="0mm">Dust emissions due to soil wind erosion and its transport are the most important natural sources of inhalable particulate matter in the atmospheric environment of sandstorm sources and the regions where sandstorms occur. To control the impact of dust emissions caused by soil wind erosion on the atmospheric environment in the Beijing-Tianjin resources, the Chinese government implemented a strategic significance ecological governance project in the Beijing-Tianjin sandstorm sources at the beginning of this century. However, there is still much controversy about soil wind erosion in the Beijing-Tianjin sandstorm sources and the resulting dust emissions. Based on field surveys, laboratory tests, remote sensing images and meteorological data, this paper calculated soil wind erosion in the Beijing-Tianjin sandstorm sources under three conditions, including the typical years of 2000, 2005, 2010, and 2015, land-use change conditions (land use in 2000, 2005, 2010, and 2015 but other factors with 2015), and climate change conditions (land use in 2015 but other factors with 2000, 2005, 2010, and 2015), by using the specified soil wind erosion model in the National Plan for Dynamic Monitoring of Soil and Water Loss from 2018 to 2022 and the Technical Regulations for Dynamic Monitoring of Regional Soil and Water Loss (Trial Version). In 2000, 2005, 2010, and 2015, the fluctuation in wind erosion modulus in the Beijing-Tianjin sandstorm sources decreased. Wind erosion modulus gradually decreased from northwest to southeast, and the value in desert or sandy land was higher than that in the surrounding areas. With the advancement of governance projects in the Beijing-Tianjin sandstorm sources, the distribution of wind erosion modulus changed significantly. Wind erosion modulus in the desert steppe was the largest and was approximately 2.67–2.98 times that of the Beijing-Tianjin sandstorm sources. Wind erosion modulus in the Hetao Plain and Hunshandake Sandy Land, were roughly the same as that in the Beijing-Tianjin sandstorm sources. Wind erosion modulus in other subregions was 42.69% of that in the Beijing-Tianjin sandstorm sources. Wind erosion area and variability in the above years in the Beijing-Tianjin sandstorm sources were <sc>385800–464500 km²</sc> and −9.35%–9.14%, respectively. The area of ​​mild and moderate wind erosion accounted for 91.56%. Overall, wind erosion area in the northwestern Beijing-Tianjin sandstorm sources was large, and its area proportion was high, followed by that in the middle area, and the southeast area had the smallest area. The wind erosion area in ​​desert steppe accounted for the largest proportion, with a value of 25.88%, and that in the southern part of the Greater Khingan Mountains was only 3.18%. Intense and extremely intense soil wind erosion was concentrated in the desert steppe and the western part of the Hetao Plain. Intense soil wind erosion was mainly distributed in the Kubuqi Desert and Hunshandake Sandy Land. Moderate and mild erosion involved each subregion in the Beijing-Tianjin sandstorm sources. There were obvious differences in the changes in the wind erosion area and intensity in each subregion during 2000–2005, 2005–2010, and 2010–2015. Climate change and land-use change had important impacts on soil wind erosion in the Beijing-Tianjin sandstorm sources. The variability of the wind erosion modulus and the area affected by climate change was equivalent to the corresponding variability of the year but greater than the influence of land-use change. In addition, the area of wind erosion under land-use change generally decreased, especially from 2010 to 2015, which had a decrease of 4.10%, indicating that the Beijing-Tianjin sandstorm source control project played an important role. These results provide a scientific basis for the evaluation of the benefits of the Beijing-Tianjin sandstorm source control project and the optimization of its layout.

Inter-annual variability of source contributions to PM10, PM2.5, and oxidative potential in an urban background site in the central mediterranean

Airborne particulate matter (PM) is studied because of its effects on human health and climate change. PM long-term characterisation allows identifying trends and evaluating the outcomes of environmental protection policies. This work is aimed to study the inter-annual variability of PM2.5 and PM10 concentrations and chemical composition in an urban background site (Italy). A dataset of daily PM2.5 and PM10 was collected in the period 2016–2017, including the content of OC, EC, major water-soluble ions, main metals, and compared to a similar dataset collected in the period 2013–2014. Oxidative potential using DTT assay (dithiothreitol) was evaluated and expressed in DTTV as 0.39 nmol/min·m3 in PM10 and 0.29 in PM2.5 nmol/min·m3. PM source apportionment was computed using the EPA PMF5.0 model and source contributions compared with those of a previous dataset collected between 2013 and 2014. Multi linear regression analysis identified which source contributed (p < 0.05) to the oxidative potential of each size fraction. Inter-annual trends were more evident on PM2.5 with reductions of biomass burning contribution and increases in traffic contribution in the 2016–2017 period. Crustal contributions were similar for the two periods, in both size fractions. Carbonates were comparable in PM10 with a slight increase in PM2.5. Sea spray decreased in PM10. The DTTV of PM2.5 peaked during cold periods, while, the DTTV of the PM10-2.5 fraction peaked in summer, suggesting that different sources, with different seasonality, influence OP in the PM2.5 and PM10-2.5 fractions. Analysis showed that sea spray, crustal, and carbonates sources contribute ∼13.6% to DTTV in PM2.5 and ∼62.4% to DTTV in PM10-2.5. Combustion sources (biomass burning and traffic) contribute to the majority of DTTV (50.6%) in PM2.5 and contribute for ∼26% to DTTV in PM10-2.5. Secondary nitrate contributes to DTTV in both fine and coarse fraction; secondary sulphate contribute to DTTV in PM2.5 with negligible contributions to DTTV in PM10-2.5.

Hourly population exposure index for PM2.5 in urban street canyons

Vehicle emissions are among the primary sources of fine particulate matter (PM2.5). Assessing population exposure levels to PM2.5 from traffic emissions in street canyons is imperative. Accordingly, this study developed an hourly population exposure index (HPEI) by combining PM2.5 concentration distributions determined using computational fluid dynamics–based simulations, outdoor/indoor (O/I) concentration ratios of PM2.5 determined experimentally, and population distributions determined through an investigation. The results indicated that strength of vehicle emission sources and meteorological conditions affected the PM2.5 concentration distributions in the examined street canyon. The mean PM2.5 concentration in the middle of the street was higher than the concentrations at other positions, and PM2.5 concentrations on the leeward sides of buildings were higher than those on the windward sides. Moreover, three to five peaks of PM2.5 concentrations were observed at different measurement positions on the street and were attributed to the formation of vortex flows. The O/I concentration ratios of sulfur in PM2.5 in home, office, school, bus, and car microenvironments were 0.47, 0.50, 0.51, 0.77, and 0.61, respectively. The HPEI most closely reflected the population distribution at 7:00; however, it was derived using the PM2.5 concentration distributions and population distributions observed at 10:00. These results may help researchers understand the population exposure distribution and improve urban environmental management strategies.

Indoor Air Pollution and the Health of Vulnerable Groups: A Systematic Review Focused on Particulate Matter (PM), Volatile Organic Compounds (VOCs) and Their Effects on Children and People with Pre-Existing Lung Disease

Air pollution affects health, but much of the focus to this point has been on outdoor air. Higher indoor pollution is anticipated due to increasingly energy-efficient and less leaky buildings together with more indoor activities. Studies of indoor air pollution focusing on children and people with respiratory disease from the database Web of Science (1991–2021) were systemically reviewed according to the PRISMA guidelines, with 69 studies included in the final selection. Emissions from building materials affected indoor air quality, and ventilation also had an influence. The main indoor air pollutants are Volatile Organic Compounds (VOCs) and Particulate Matter (PM). PM sources included smoking, cooking, heating, candles, and insecticides, whereas sources of coarse particles were pets, housework and human movements. VOC sources included household products, cleaning agents, glue, personal care products, building materials and vehicle emissions. Formaldehyde levels were particularly high in new houses. Personal exposure related to both indoor and outdoor pollutant levels, highlighting home characteristics and air exchange rates as important factors. Temperature, humidity, educational level, air purifiers and time near sources were also related to personal exposure. There was an association between PM and Fractional exhaled Nitric Oxide (FeNO), lung function, oxygen saturation, childhood asthma and symptoms of chronic obstructive pulmonary disease (COPD) patients. High VOCs were associated with upper airways and asthma symptoms and cancer. Effective interventional studies for PM in the future might focus on human behavior together with air purifiers and increased ventilation, whereas VOC interventions might center more on building materials and household products, alongside purification and ventilation.

Exposure to fine particulate matter (PM2.5) during landscape fire events and the risk of cardiorespiratory emergency department attendances: a time-series study in Perth, Western Australia

BackgroundLandscape fires (LFs) are the main source of elevated particulate matter (PM2.5) in Australian cities and towns. This study examined the associations between daily exposure to fine PM2.5 during LF...

Impact of biomass burning and non-exhaust vehicle emissions on PM10 levels in a mid-size non-industrial western Iberian city

PM10 aerosol was measured during one semester, simultaneously, at a roadside (RS) and an urban background (UB) location in Coimbra, Portugal. On average, the mass concentrations were 36% higher at the RS, compared to UB. Application of Positive Matrix Factorisation (PMF) and Ionic Mass Balance (IMB) methodologies permitted to source apportion the aerosol mass. During the cold season, biomass burning was a prevalent particulate matter source at both urban locations, contributing with up to 30% of PM10. At the RS, vehicle non-exhaust emissions (brake, tyre and road dust) doubled exhaust emissions by combustion engines, accounting for 18–19% of PM10. Unreacted and reacted sea salt was an important fraction of PM10, principally during the warm season, when it composed approximately 25% of the aerosol. Secondary pollution by ammonium salts and carbonaceous matter was important across the seasons, especially at the UB location, where they dominated the particulate mass.

Winter and spring variation in sources, chemical components and toxicological responses of urban air particulate matter samples in Guangzhou, China

The sources and chemical components of urban air particles exhibit seasonal variations that may affect their hazardousness to human health. Our aims were to investigate winter and spring variation in particulate matter (PM) sources, components and toxicological responses of different PM size fractions from samples collected in Guangzhou, China. Four size-segregated PM samples (PM10–2.5, PM2.5–1, PM1–0.2, and PM0.2) were collected separately during winter (December 2017 and January 2018) and spring (March 2018). All PM samples were analyzed for chemical components and characterized by source. RAW 264.7 macrophages were exposed to four doses of PM samples for 24 h. Cytotoxicity, oxidation, cell cycle, genotoxicity and inflammatory parameters were tested. PM concentrations were higher in the winter samples and caused more severe cytotoxicity and oxidative damage than to PM in the spring samples. PM in winter and spring led to increases in cell cycle and genotoxicity. The trends of size-segregated PM components were consistent in winter and spring samples. Metallic elements and PAHs were found in the largest concentrations in winter PM, but ions were found in the largest concentrations in spring PM. metallic elements, PAHs and ions in size-segregated PM samples were associated with most toxicological endpoints. Soil dust and biomass burning were the main sources of PM in winter, whereas traffic exhaust and biomass burning was the main source with of spring PM. Our results suggest that the composition of PM samples from Guangzhou differed during winter and spring, which led to strong variations in toxicological responses. The results demonstrate the importance of examining a different particle sizes, compositions and sources across different seasons, for human risk assessment.

A study on the performance of low-cost sensors for source apportionment at an urban background site

Abstract. Knowledge of air pollution sources is important in policymaking and air pollution mitigation. Until recently, source apportion analyses were limited and only possible with the use of expensive regulatory-grade instruments. In the present study we applied a two-step positive matrix factorisation (PMF) receptor analysis at a background site in Birmingham, UK using data acquired by low-cost sensors (LCSs). The application of PMF allowed for the identification of the sources that affect the local air quality, clearly separating different sources of particulate matter (PM) pollution. Furthermore, the method allowed for the contribution of different air pollution sources to the overall air quality at the site to be estimated, thereby providing pollution source apportionment. The use of data from regulatory-grade (RG) instruments further confirmed the reliability of the results, as well as further clarifying the particulate matter composition and origin. Compared with the results from a previous analysis, in which a k-means clustering algorithm was used, a good consistency between the k means and PMF results was found in pinpointing and separating the sources of pollution that affect the site. The potential and limitations of each method when used with low-cost sensor data are highlighted. The analysis presented in this study paves the way for more extensive use of LCSs for atmospheric applications, receptor modelling and source apportionment. Here, we present the infrastructure for understanding the factors that affect air quality at a significantly lower cost than previously possible. This should provide new opportunities for regulatory and indicative monitoring for both scientific and industrial applications.

Spatiotemporal variations and sources of PM2.5 in the Central Plains Urban Agglomeration, China.

The Central Plains Urban Agglomeration (CPUA) is the largest region in central China and suffers from serious air pollution. To reveal the spatiotemporal variations and the sources of fine particulate matter (PM2.5, with an aerodynamic diameter of smaller than 2.5 μm) concentrations of CPUA, multiple and transdisciplinary methods were used to analyse the collected millions of PM2.5 concentration data. The results showed that during 2017 ~ 2020, the yearly mean concentrations of PM2.5 for CPUA were 68.3, 61.5, 58.7, and 51.5 μg/m3, respectively. The empirical orthogonal function (EOF) analysis suggested that high PM2.5 pollution mainly occurred in winter (100.8 μg/m3, 4-year average). The diurnal change in PM2.5 concentrations varied slightly over the season. The centroid of the PM2.5 concentration moved towards the west over time. The spatial autocorrelation analysis indicated that PM2.5 concentrations exhibited a positive spatial autocorrelation in CPUA. The most polluted cities distributed in the northern CPUA (Handan was the centre) formed a high-high agglomeration, and the cities located in the southern CPUA (Xinyang was the centre) formed a low-low agglomeration. The backward trajectory model and potential source contribution function were employed to discuss the regional transportation of PM2.5. The results demonstrated that internal-region and cross-regional transport of anthropogenic emissions were all important to PM2.5 pollution of CPUA. Our study suggests that joint efforts across cities and regions are necessary.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11869-022-01178-z.

Subsidy or policy certainty: Which attribute is more important for broiler farmers when investing in particulate matter abatement technology?

Broiler houses are an important source of particulate matter (PM) in the Netherlands. High concentrations of PM can threaten the environment and pose health risks to humans and animals. To address these problems, the Dutch government aims to reduce PM10 emissions originating from broiler houses by 50% between 2020 and 2030. This paper explored broiler farmers' investment preferences for different PM10 abatement techniques and how they relate to socio-economic characteristics and perceived obstacles for business development. The results of our discrete choice experiment indicate that farmers were reluctant to invest in PM10 abatement techniques. When they did invest, they had a general preference for techniques with a medium to high (31–52%) rather than a very high PM10 reduction efficiency (80%). Social factors and perceived obstacles for business development explained heterogeneity in farmers’ preferences for PM10 abatement techniques and their willingness to invest. When investing in abatement techniques, farmers attached a higher relative importance to an exemption from future PM10 legislation than to a subsidy. The findings imply that more policy-related certainty as well as financial compensation can incentivize farmers to invest in PM10 abatement.

Exposure models for particulate matter elemental concentrations in Southern California.

Due to a scarcity of routine monitoring of speciated particulate matter (PM), there has been limited capability to develop exposure models that robustly estimate component-specific concentrations. This paper presents the largest such study conducted in a single urban area. Using samples that were collected at 220 locations over two seasons, quasi-ultrafine (PM0.2), accumulation mode fine (PM0.2-2.5), and coarse (PM2.5-10) particulate matter concentrations were used to develop spatiotemporal regression, machine learning models that enabled predictions of 24 elemental components in eight Southern California communities. We used supervised variable selection of over 150 variables, largely from publicly available sources, including meteorological, roadway and traffic characteristics, land use, and dispersion model estimates of traffic emissions. PM components that have high oxidative potential (and potentially large health effects) or are otherwise important markers for major PM sources were the primary focus. We present results for copper, iron, and zinc (as non-tailpipe vehicle emissions); elemental carbon (diesel emissions); vanadium (ship emissions); calcium (soil dust); and sodium (sea salt). Spatiotemporal linear regression models with 17 to 36 predictor variables including meteorology; distance to different classifications of roads; intersections and off ramps within a given buffer distance; truck and vehicle traffic volumes; and near-roadway dispersion model estimates produced superior predictions over the machine learning approaches (cross validation R-squares ranged from 0.76 to 0.92). Our models are easily interpretable and appear to have more effectively captured spatial gradients in the metallic portion of PM than other comparably large studies, particularly near roadways for the non-tailpipe emissions. Furthermore, we demonstrated the importance of including spatiotemporally resolved meteorology in our models as it helped to provide key insights into spatial patterns and allowed us to make temporal predictions.

Mass, composition, and sources of particulate matter in residential and traffic sites of an urban environment.

Present study aims to assess the mass, composition, and sources of PM10 and PM2.5 (particulate matter having aerodynamic diameter less than or equal to 10 and 2.5µm aerodynamic diameter, respectively) in Vellore city. Seasonal samples collected in traffic and residential sites were analyzed for ions, elements, organic carbon (OC), and elemental carbon (EC). Source apportionment of PM10 and PM2.5 is carried out using Chemical Mass Balance, Unmix, Positive Matrix Factorization and Principal Component Analysis receptor models. Results showed that traffic site had higher annual concentration (PM2.5 = 62 ± 32 and PM10 = 112 ± 23µgm-3) when compared to residential site (PM2.5 = 54 ± 22 and PM10 = 98 ± 20µgm-3). Al, Ca, Fe, K, and Mg known to have crustal origin dominated the element composition irrespective of PM size and sampling site. Among ions, SO42- accounted highest in both sites with an average of 70 and 60% to PM2.5 and PM10 ionic mass. Elemental carbon contribution to PM mass was found highest in traffic site (PM2.5 = 17 to 23% and PM10 = 8 to 10%) than residential site (PM2.5 = 9 to 17% and PM10 = 4 to 8%). Elements, ions, OC, and EC accounted 12, 28, 34, and 16% of PM2.5 mass and 12, 21, 20, and 8% of PM10 mass, respectively. Different sources identified by the receptor models are resuspended road dust, crustal material, secondary aerosol, traffic, non-exhaust vehicular emissions, secondary nitrate, construction, cooking, and biomass burning. Since Vellore is aspiring to be a smart city, this study can help the policymakers in effectively curbing PM.

Source identification of water-insoluble single particulate matters in rain sequences

In this study, eight independent rainfall events were sampled sequentially from September 20, 2019 to June 15, 2020, in Bartın province located on the western Black Sea coast of Turkey. Manually collected volume-based sequential samples were analyzed for pH and water-soluble ions involving F−, Cl−, NO3−, SO42−, PO43−, Na+, K+, NH4+, Mg2+, and Ca2+. Total trace and major elements (sum of soluble and insoluble fractions), and elemental and organic carbons (EC and OC) contents of the sequential samples were measured. Water-insoluble particulate matter in the sequential samples were characterized for their sizes, morphologies, and compositions by using Scanning Electron Microscopy Energy Dispersive X-Ray Spectrometry (SEM-EDS) and a particle size analyzer. Results of SEM-EDS, particle size distributions, chemical analyses, and the upper atmospheric back trajectories were used to apportion the sources of the water-insoluble single particulate matters in sequential rain samples. Using the proposed method, iron-steel facilities, and thermal power plants were identified as the significant regional sources. Urban traffic and natural emission were identified as the local sources.

PARTICULATE MATTER EMISSION SOURCES AND THEIRCONTROL TECHNOLOGIES

Particulate matter (PM) is a complex form of air pollution that includes all types of solid and liquid droplets present in the atmosphere. Primary PM Emission rates, sizes, and composition are difficult to predict since they rely not only on the industry, but also on the fuel properties, infrastructure, and other aspects of the emission process. Normal (volcanic eruptions, forest fires, and weathering of parent material and sea salt) and anthropogenic (power plants, internal combustion engines, and the thermo-degradation process) sources of airborne particulate matter exist. In order to uphold human health conditions and a clean climate; it has become important to reduce PM concentrations. Given the negative effects of particulates, their regulation is becoming increasingly necessary. In this article, we look at all of the origins of particulate matter, their negative consequences, and the monitoring systems that are used to minimize PM emissions. However, manufacturing and plant operations will get the most attention because they are the backbone of a country’s economy as well as one of the largest causes of PM pollution and traffic regulation.