A review of the main strategies used in the interpretation of similar chemical profiles yielded by receptor models in the source apportionment of particulate matter

Improvements in source apportionment of multiple time-resolved PM2.5 inorganic and organic speciation measurements using constrained Positive Matrix Factorization

The equation of Positive Matrix Factorization (PMF) has been modified to resolve multiple time resolution inputs and applied in numerous field studies. The refined modeling results provide a solution with an increased number of factors and enriched profile features. However, the incorporation of low time-resolved data may retrieve unfavorable mixed factor profiles, introducing high uncertainties into the PMF solution computations. To address this issue, a dual-stage PMF modeling procedure with predefined constraints was proposed. Multiple time-resolved PM2.5 inorganic and organic speciation measurements were collected from autumn of 2022 to summer of 2023 in Taipei, Taiwan. Without using the proposed approach, a mixed factor of vehicle/biomass burning and an unphysically meaningful factor of sodium ion- and ammonium ion-rich were identified. After implementing the proposed approach, a refined number of eight factors with separated and reasonable profiles were retrieved. Over the sampling period, the largest contributor to PM2.5 and organic carbon was vehicle (contribution = 26% and 47%, respectively), while those for secondary inorganic aerosols of SO42-, NO3-, and NH4+ were industry (27%, 25%, and 31%, respectively), highlighting the importance of regulating these two sources. The low vehicle contribution to NO3- may be due to time-lag effects from gas-to-particle conversion, which led to different temporal patterns between NO3- and primary species. Addressing this issue is crucial in future studies for better apportionment of secondary aerosols.

Particulate matter from a tropical city in southeast Brazil: Impact of biomass burning on polycyclic aromatic compounds levels, health risks, and in vitro toxicity

In the context of a rising global temperature, biomass burning represents an increasing risk to human health, due to emissions of highly toxic substances such as polycyclic aromatic hydrocarbon (PAHs). Size-segregated particulate matter (PM) was collected in a region within the sugarcane belt of São Paulo state (Brazil), where biomass burning is still frequent, despite the phasing out of manual harvesting preceded by fire. The median of the total concentration of the 15 PAHs determined was 2.3 ± 1.8 ng m-3 (n = 19), where 63% of this content was in PM1.0. Concentrations of OPAHs and NPAHs were about an order of magnitude lower. PM2.5 collected in the dry season, when most of the fires occur, presented PAHs and OPAHs total concentrations three times higher than in the wet season, showing positive correlations with fire foci number and levoglucosan (a biomass burning marker). These results, added to the fact that biomass burning explained 65% of the data variance (PCA analysis), evidenced the importance of this practice as a source of PAHs and OPAHs to the regional atmosphere. Conversely, NPAHs appeared to be mainly derived from diesel-powered vehicles. The B[a]P equivalent concentration was estimated to be 4 times higher in the dry season than in the wet season, and was greatly increased during a local fire event. Cytotoxicity and genotoxicity of PM1.0 organic extracts were assessed using in vitro tests with human liver HepG2 cells. For both types of tests, significant toxicity was only observed for samples collected during the dry season. Persistent DNA damage that may have impaired the DNA repair system was also observed. The results indicated that there was a health risk associated with the air particulate mixture, mainly related to biomass burning, demonstrating the urgent need for better remediation actions to prevent the occurrence of burning events.

The main strategies for soil pollution apportionment: A review of the numerical methods

Nowadays, a large number of compounds with different physical and chemical properties have been determined in soil. Environmental behaviors and source identification of pollutants in soil are the foundation of soil pollution control. Identification and quantitative analysis of potential pollution sources are the prerequisites for its prevention and control. Many efforts have made to develop methods for identifying the sources of soil pollutants. These efforts have involved the measurement of source and receptor parameters and the analysis of their relationships via numerical statistics methods. We have comprehensively reviewed the progress made in the development of source apportionment methodologies to date and present our synthesis. The numerical methods, such as spatial geostatistics analysis, receptor models, and machine learning methods are addressed in depth. In most cases, however, the effectiveness of any single approach for source apportionment remains limited. Combining multiple methods to address soil quality problems can reduce uncertainty about the sources of soil pollution. This review also constructively highlights the key strategies of combining mathematical models with the assessment of chemical profiles to provide more accurate source attribution. This review intends to provide a comprehensive summary of source apportionment methodologies to help promote further development.

Is biomagnetic leaf monitoring still an effective method for monitoring the heavy metal pollution of atmospheric particulate matter in clean cities?

The development of a reasonable method for predicting heavy metals (HMs) pollution in atmospheric particulate matter (PM) remains challenging. This paper presents an elution-filtration method to collect PM from the surface of Osmanthus fragrans in a very clean area (Guiyang, China). The aim is to evaluate the effectiveness of biomagnetic leaf monitoring as a simple and rapid method for assessing HMs pollution in clean cities. For this purpose, we determined the magnetic parameters and concentrations of selected HMs in PM samples to investigate their relationships. The results showed that the magnetic minerals in PM samples were mainly low coercivity ferrimagnetic minerals, with a small amount of high coercivity minerals. The types of magnetic minerals were generally single, and the magnetic domain state was pseudo-single domain (PSD). There was a significant correlation between magnetic parameters and the heavy metal (HM) concentrations in PM. Low-field magnetic susceptibility (χ) could be used as an ideal proxy for determining anthropogenic HM pollution. Traffic emissions were the main atmospheric pollution source in urban Guiyang. Due to the incomplete traffic network and large traffic flow, traffic congestion (TC) often occurred at road intersections in the northwest and southwest corners of the city, resulting in the highest concentration of magnetic minerals and the most severe PM pollution. To mitigate atmospheric PM pollution and protect public health, it is strongly recommended that municipal authorities prioritize urban planning and traffic management to address TC. Measures should be implemented urgently to alleviate stop-and-go traffic.

Air pollution, glymphatic impairment, and Alzheimer's disease

Epidemiological evidence demonstrates a link between air pollution exposure and the onset and progression of cognitive impairment and Alzheimer's disease (AD). However, current understanding of the underlying pathophysiological mechanisms is limited. This opinion article examines the hypothesis that air pollution-induced impairment of glymphatic clearance represents a crucial etiological event in the development of AD. Exposure to airborne particulate matter (PM) leads to systemic inflammation and neuroinflammation, increased metal load, respiratory and cardiovascular dysfunction, and sleep abnormalities. All these factors are known to reduce the efficiency of glymphatic clearance. Rescuing glymphatic function by restricting the impact of causative agents, and improving sleep and cardiovascular system health, may increase the efficiency of waste metabolite clearance and subsequently slow the progression of AD. In sum, we introduce air pollution-mediated glymphatic impairment as an important mechanistic factor to be considered when interpreting the etiology and progression of AD as well as its responsiveness to therapeutic interventions.

Preliminary assessment of toxicity of aerosol samples from central-west Brazil using Artemia spp. bioassays

The present study reports the development of a bioassay using Artemia spp. to analyse the preliminary ecotoxicity of atmospheric aerosols (PM), which can affect the environment and human health. Herein, PM samples were collected in the city of Goiânia (Brazil) in 2016, extracted with ultrapure water and subsequently filtered through membranes with different pore sizes (100, 0.8, and 0.22 μm), and the extracts employed in the bioassays. The mortality rates (endpoint analysed) declined to membranes with smaller pore sizes (15 ± 4%, 47 ± 10% and 43 ± 9% for pore sizes of 100 μm, 0.8 μm and 0.22 μm, respectively). In general, the toxicity of the extract depended on its concentration, except for the sample with a higher negative particle surface charge, which presents a lower affinity for the negatively charged surfaces of cellular membranes. Moreover, although the PM concentration was higher for the sample collected during the dry season (September), the mortality rate was not significantly different to that determined for a sample with similar physical and chemical characteristics collected in the rainy season (December). This result demonstrates the importance of monitoring PM toxicities and their chemical and physical characteristics, in addition to their concentrations. Therefore, the new protocol to provide a preliminary analysis of the toxicity of the extracts of aerosol emerges as a useful, accessible, and fast tool for monitoring possible environmental hazards, and can simplify fieldwork.

Source apportionment and health impact assessment of atmospheric particulate matter in the city of São Carlos, Brazil

In this study, positive matrix factorization method was used for source apportionment of PM₁₀ in the city of São Carlos from 2015 to 2018. The annual mean concentrations of PM₁₀, 15 PAHs, 4 oxy-PAHs, 6 nitro-PAHs, 21 saccharides, and 17 ions in these samples were in the ranges 18.1 ± 6.99 to 25.0 ± 11.3 μg m^-3 for PM₁₀, 9.80 × 10^-1 ± 2.06 to 2.03 ± 8.54 × 10^-1 ng m^-3 for ΣPAHs, 83.9 ± 35.7 to 683 ± 521 pg m^-3 for Σoxy-PAHs, 1.79 × 10^-2 ± 1.23 × 10^-1 to 7.12 ± 4.90 ng m^-3 for Σnitro-PAHs, 83.3 ± 44.7 to 142 ± 85.9 ng m^-3 for Σsaccharides, and 3.80 ± 1.54 to 5.66 ± 4.52 μg m^-3 for Σions. For most species, the concentrations were higher in the dry season than in the rainy. This was related not only to the low rainfall and relative humidity characteristic of the dry season but also to an increase in fire spots recorded in the region between April and September every year from 2015 to 2018. A 4-factor solution provided the best description of the dataset, with the four identified sources of PM₁₀ being soil resuspension (28%), biogenic emissions (27%), biomass burning (27%), and vehicle exhaust together with secondary PM (18%). Although the PM₁₀ concentrations were not above the limit established by local legislation, the epidemiological study showed that by reducing PM_2.5 concentrations to the level recommended by the WHO, approximately 35 premature deaths per 100,000 population could be avoided annually. The results revealed that biomass burning continues to be one of the main anthropic sources of emissions to the atmosphere in the region, so it needs to be incorporated into the existing guidelines and policies to reduce the concentration of particulate matter to within the limits recommended by the WHO, in order to avoid premature deaths.

Health risk assessment of inorganic and organic constituents of the coarse and fine PM in an industrialized region of Brazil

A health risk assessment of inorganic and organic species associated with coarse and fine particulate matter (PM) was conducted in Southeastern Brazil. TSP, PM₁₀, and PM_2.5 samples were collected, and their elemental (metals/metalloids) and organic (PAHs) composition were determined by EDXRF and GC-MS. The health risks were determined through hazard quotient (HQ) and cancer risk (CR). It was found that different elements and routes of exposure lead to different health risks, even for the PM concentration in compliance with air quality standards. The major routes of exposure for adults were inhalation and dermal contact whereas for children were ingestion and dermal contact. High non-cancer risks (HQ) caused by Cl and Fe exposure were associated with coarser fractions, PM₁₀ and TSP, respectively, whereas high HQ for Se, Sb, and V exposure were associated with PM_2.5. HQ values for children were near twice that for adults, and CR values were 65 % to 130 % higher for children than for adults. CR posed by PAHs was negligible. The results highlighted that the HQ might be over- or underestimated depending on the form in which the element Cl is determined (elemental or ion), reinforcing the need for an embracing chemical characterization of the PM. High HQ values were found related to the exposure to some elements present in the TSP, showing that this PM fraction should not be neglected.

Cancer risk assessment and source apportionment of the gas- and particulate-phase of the polycyclic aromatic hydrocarbons in a metropolitan region in Brazil

A risk assessment and a source apportionment of the particulate- and gas-phase PAHs were conducted in a high vehicular traffic and industrialized region in southeastern Brazil. Higher concentrations of PAHs were found during summer, being likely driven by the contributions of PAHs in the vapor phase caused by fire outbreaks during this period. Isomer ratio diagnostic and Principal Component Analysis (PCA) identified four potential sources in the region, in which the Positive Matrix Factorization (PMF) model confirmed and apportioned as gasoline-related (31.8%), diesel-related (25.1%), biomass burning (23.4%), and mixed sources (19.6%). The overall cancer risk had a tolerable value, with ∑CR = 4.6 × 10^-5, being ingestion the major via of exposure (64% of the ∑CR), followed by dermal contact (33% of the ∑CR) and inhalation (3%). Mixed sources contributed up to 45% of the overall cancer risk (∑CR), followed by gasoline-related (up to 35%), diesel-related (up to 15%), and biomass burning (up to 10%). The risk assessment for individual PAH species allowed identifying higher CR associated with BaP, DBA, BbF, BaA, and BkF, species associated with gasoline-related and industrial sources. Higher risks were associated with PM_2.5-bound PAHs exposure, mainly via ingestion and dermal contact, highlighting the need for measures of mitigation and control of PM_2.5 in the region.

Systematic Evaluation of Two Classical Receptor Models in Source Apportionment of Soil Heavy Metal(loid) Pollution Using Synthetic and Real-World Datasets

Due to the lack of a priori knowledge on true source makeup and contributions, whether the source apportionment results of Unmix and positive matrix factorization (PMF) are accurate cannot be easily assessed, despite the availability of built-in indicators for their goodness of fit and robustness. This study systematically evaluated, for the first time, the applicability and reliability of these models in source apportionment of soil heavy metal(loid)s with synthetic datasets generated using known source profiles and contributions and a real-world dataset as well. For eight synthetic datasets with different pollution source characteristics, feasible Unmix solutions were close to the true source component compositions (R² > 0.936; total mean squared errors (MSEs) < 0.04), while those of PMF had significant deviations (R² of 0.484-0.998; total MSEs of 0.04-0.16). Nonetheless, both models failed to accurately apportion the sources with collinearity or non-normal distribution. Unmix generally outperformed PMF, and its solutions showed much less dependence on sample size than those of PMF. While the built-in indicators provided little hint on the reliability of both models for the real-world dataset, their sample-size dependence indicated that Unmix probably yielded more accurate solutions. These insights could help avoid the potential misuse of Unmix and PMF in source apportionment of soil heavy metal(loid) pollution.

Identifying and quantifying PM2.5 pollution episodes with a fusion method of moving window technique and constrained Positive Matrix Factorization

PM_2.5 pollution episodes rapidly and significantly deteriorate the air quality and are a critical concern worldwide. This study developed a fusion method based on the moving window dataset technique and constrained Positive Matrix Factorization (PMF) to differentiate and characterize potential factors in a PM_2.5 episode case assuming having one new contributor. The hourly PM_2.5 compositions of elements, ions and carbonaceous components, were collected from September to December 2020 in Taipei, Taiwan. Constraint targets based on the bootstrap analysis result of a PMF model using a long-term input dataset were imposed on the modeling of each moving window to ensure similar features of the retrieved factors. The constituents of an additionally differentiated factor to the episode, which was identified as regional transport, were stable among each moving window that covered the occurrence of the episode as revealed by the profile matching index. The results showed that the largest contributor to the PM_2.5 mass during the episode period of 12/12/2020 was regional transport (61%), whereas that of 12/13 was the regular pollution of industry/ammonium sulfate related (43%). According to our review of the literature, this study is the first to apply both the moving window technique and constrained PMF to characterize the episode. The findings provide valuable information that can be used to explore the causes of PM_2.5 episodes and implement air pollution control strategies.

Applications of dynamic simulation for source analysis of soil pollutants based on atmospheric diffusion and deposition model

Existing receptor-model-based source apportionment methods failed to derive source contributions to accumulation of soil heavy metals (SHMs). In this research, a dynamics-simulation-based source apportionment approach (DSSA) was developed by integrating mathematical models of source release, diffusion and deposition pathway, and receptor accumulation, to quantify accumulative contributions of SHMs. The case study was carried out in a complex industrialized region in southeast China to investigate pollution situation of SHMs (Zn, Pb, Ni, As, Cd, and Cr). The results showed that SHMs distributions were affected by seasonal variation and near-surface meteorology, which could be sequenced by correlation coefficient as temperature (0.968) > humidity (0.552) > precipitation (0.389) > wind speed (0.386). The source categories and corresponding contribution rates were identified as: i) battery plant to Zn (72.32%) and Pb (71.73%), ii) traffic to Ni (64.55%), iii) traffic and agriculture to Cd (43.26%, 41.63%), iv) agriculture to As (75.30%) and Cr (60.05%), which was similar to the results of positive matrix factorization (PMF). Furthermore, DSSA could illustrate SHMs migration process from source to receptor. The uncertainty analysis further proved the distinct advantages of DSSA. The results of this research could predict pollutant enrichment and could provide new perspective for environment and public health management.

Physical, chemical, and cell toxicity properties of mature/aged particulate matter (PM) trapped in a diesel particulate filter (DPF) along with the results from freshly produced PM of a diesel engine

The lifetime and efficiency of diesel particulate filters (DPFs) strongly depend on the proper and periodic cleaning and servicing. Unfortunately, in some cases, inappropriate methods are applied to clean the DPFs, e.g., using air compressors without proper disposal procedures which can have negative impacts on human health, the environment, and DPF's efficiency. However, there is no information available about the properties of this kind of PM. This research is therefore presented to explore the physicochemical and toxicity properties of aged PM trapped in a DPF (using compressed air for PM sampling) employing STEM, SEM, EDS, Organic Carbon Analyzer, TGA/DSC, and Raman Spectrometer for investigating the physicochemical properties, and assays of cell viability, cellular reactive oxygen species (ROS), interleukin-6, and tumor necrosis factor-alpha (TNF-α) for investigating the toxicity properties. Also, analyses from fresh PM samples from the diesel vehicle at two engine speeds are presented. It is found that at a certain/fixed PM number/mass for all three samples tested, the PM from DPF compared with the fresh PM can have both positive (particularly having the lowest water-soluble total carbon ratio) and negative impacts on human health (particularly having the highest cell death rate of 13.4%, ROS, and TNF-α) and the environment.

A global perspective of the current state of heavy metal contamination in road dust

Heavy metals are persistent and bio-accumulative, and pose potential risk to human health and ecosystem. We reviewed the current state of heavy metal contamination, the ecotoxicological and human health risk of heavy metals reported in urban road dust from various cities in different continents (Asia, Europe, Africa, America, and Australia). We compared and synthesized the findings on the methods related to sample collection, extraction, analytical tools of heavy metals, their concentrations, level of contamination, ecological risk, non-carcinogenic risk, and carcinogenic risk in road dust. Concentrations of Pb, Zn, Cu, Ni, Cd, Cr, Mn, and Fe were found to be higher than their background values in soil. As expected, the contamination levels of the heavy metals varied extensively among cities, countries, continents, and periods. A high level of contamination is observed for Pb and Cd in road dust due to operating leaded gasoline and the old vehicle population. The highest Zn contamination was observed from road dust in Europe, followed by Asia, Africa, Australia, and America (North America and South America). Cu contamination and the pollution load index (PLI) is found to be the highest in Europe and lowest in Africa, with in-between values of PLI in American and African cities. The potential ecological risk on different continents was observed highest in Asia, followed by Europe, Australia, America, and Africa. A comparative assessment of non-carcinogenic risk for children indicated that Australia is the most susceptible country due to high heavy metal exposure in road dust, followed by Asia. However, there is no susceptible risk in European, African, and American cities. We did not observe any potential risk to adults due to non-carcinogenic metals. Carcinogenic risk to all age groups was within the threshold limit range for all the regions worldwide.

The Role of Fossil Fuel Combustion Metals in PM2.5 Air Pollution Health Associations

In this review, we elucidate the central role played by fossil fuel combustion in the health-related effects that have been associated with inhalation of ambient fine particulate matter (PM2.5). We especially focus on individual properties and concentrations of metals commonly found in PM air pollution, as well as their sources and their adverse health effects, based on both epidemiologic and toxicological evidence. It is known that transition metals, such as Ni, V, Fe, and Cu, are highly capable of participating in redox reactions that produce oxidative stress. Therefore, particles that are enriched, per unit mass, in these metals, such as those from fossil fuel combustion, can have greater potential to produce health effects than other ambient particulate matter. Moreover, fossil fuel combustion particles also contain varying amounts of sulfur, and the acidic nature of the resulting sulfur compounds in particulate matter (e.g., as ammonium sulfate, ammonium bisulfate, or sulfuric acid) makes transition metals in particles more bioavailable, greatly enhancing the potential of fossil fuel combustion PM2.5 to cause oxidative stress and systemic health effects in the human body. In general, there is a need to further recognize particulate matter air pollution mass as a complex source-driven mixture, in order to more effectively quantify and regulate particle air pollution exposure health risks.