Determination of source contributions to ambient PM2.5 in Kaohsiung, Taiwan, using a receptor model

PM2.5-bound trace metals in an urban area of Northern Mexico during the COVID-19 pandemic: characterization, sources, and health risk

Abstract

A field study was carried out in the Metropolitan Area of Monterrey (MAM), the second most populated city in Mexico, characterized by increasing urbanization, high traffic density, and intense industrial activity. These characteristics commonly present high concentrations of air pollutants leading to the degradation of air quality. PM2.5 was analyzed for heavy metals at two urban sites located within the MAM (Juarez and San Bernabe) in order to determine sources, health risk, morphology, and elemental content during the COVID-19 pandemic (autumn 2020 and spring 2021). Twenty-four-hour samples of PM2.5 were collected at each site during 30-day periods using high-volume equipment. Gravimetric concentrations and 11 metals were measured (Ca, Cd, Co, Cu, Fe, K, Mg, Mn, Ni, Cr, and Pb) by different analytical techniques (flame atomic absorption spectroscopy, graphite furnace atomic absorption spectroscopy, and inductively coupled plasma optical emission spectroscopy). Selected samples were analyzed by scanning electron microscopy-energy-disperse spectroscopy in order to characterize their morphology and elemental content. PM2.5 concentrations exceeded the Mexican standard and WHO guidelines in Juarez during spring 2021. Cu, Cd, and Co were highly enriched by anthropogenic sources, and Ni, K, Cr, and Pb had a moderate enrichment. Mg, Mn, and Ca were of crustal origin. Bivariate statistics and PCA confirmed that alkaline metals originated from crustal sources and that the main sources of trace metals included traffic emissions, resuspension from soil/road dust, steel industry, smelting, and non-exhaust emissions at both sites. Lifetime cancer risk coefficients did not exceed the permissible levels established by EPA and WHO, implying that local residents are not at risk of developing cancer. Non-carcinogenic risk coefficients revealed that there is a possible risk of suffering cardiovascular and respiratory diseases due to inhalation of cobalt at the study sites.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s11869-023-01372-7.

Fifty-year change in air pollution in Kaohsiung, Taiwan

The change in air quality in cities can be the product of regulation and emissions. Regulations require enforcement of emission reduction, but it is often shifting economic and societal structures that influence pollutant emissions. This study examines the long-term record of air pollutants in Kaohsiung, where post-war industrialisation increased pollution substantially, although improvements are observed in recent decades as the city moved to a more mixed economy. The study tracks both gases and particles across a period of significant change in pollution sources in the city. Concentrations of SO₂ and aerosol SO₄^2- were especially high ~1970, but these gradually declined, although SO₄^2- to a lesser extent than its precursor, SO₂. While twenty-first century emissions of SO₂ and NO_x have declined, this has been less so for NH₃, because it arises from predominantly agricultural sources. The atmosphere in Kaohsiung continues to have high concentrations of O₃, and these have risen in the city, likely a product of less titration by NO. The changes have meant that ozone has become an increasing threat to health and agriculture. Despite a potential for producing (NH₄)₂SO₄ and NH₄NO₃ aerosols, a product of a relatively constant supply of NH₃, visibility has improved in recent years. Emissions of SO₂ and NO_x should continue to be reduced, as these strongly affect the amount of fine secondary aerosol. However, the key problem may be ozone, which is difficult to control as it requires careful consideration of the balance of NO_x and hydrocarbons so important to its production.

Ambient Air Pollution and Risk for Stroke Hospitalization: Impact on Susceptible Groups

Stroke is a leading cause of death, and air pollution is associated with stroke hospitalization. However, the susceptibility factors are unclear. Retrospective studies from 2014 to 2018 in Kaohsiung, Taiwan, were analyzed. Adult patients (>17 years) admitted to a medical center with stroke diagnosis were enrolled and patient characteristics and comorbidities were recorded. Air pollutant measurements, including those of particulate matter (PM) with aerodynamic diameters < 10 μm (PM10) and < 2.5 μm (PM2.5), nitrogen dioxide (NO2), and ozone (O3), were collected from air quality monitoring stations. During the study period, interquartile range (IQR) increments in PM2.5 on lag3 and lag4 were 12.3% (95% CI, 1.1−24.7%) and 11.5% (95% CI, 0.3−23.9%) concerning the risk of stroke hospitalization, respectively. Subgroup analysis revealed that the risk of stroke hospitalization after exposure to PM2.5 was greater for those with advanced age (≥80 years, interaction p = 0.045) and hypertension (interaction p = 0.034), after adjusting for temperature and humidity. A dose-dependent effect of PM2.5 on stroke hospitalization was evident. This is one of few studies focusing on the health effects of PM2.5 for patients with risk factors of stroke. We found that patients with risk factors, such as advanced age and hypertension, are more susceptible to PM2.5 impacts on stroke hospitalization.

Air quality warning system based on a localized PM2.5 soft sensor using a novel approach of Bayesian regularized neural network via forward feature selection

It is highly significant to develop efficient soft sensors to estimate the concentration of hazardous pollutants in a region to maintain environmental safety. In this paper, an air quality warning system based on a robust PM_2.5 soft sensor and support vector machine (SVM) classifier is reported. The soft sensor for the estimation of PM_2.5 concentration is proposed using a novel approach of Bayesian regularized neural network (BRNN) via forward feature selection (FFS). Zuoying district of Taiwan is selected as the region of study for implementation of the estimation system because of the high pollution in the region. Descriptive statistics of various pollutants in Zuoying district is computed as part of the study. Moreover, seasonal variation of particulate matter (PM) concentration is analyzed to evaluate the impact of various seasons on the increased levels of PM in the region. To investigate the linear dependence of concentration of different pollutants to the concentration of PM_2.5, Pearson correlation coefficient, Kendall's tau coefficient, and Spearman coefficient are computed. To achieve high performance for the PM_2.5 estimation, selection of appropriate forward features from the input variables is carried out using FFS technique and Bayesian regularization is incorporated to the neural network system to avoid the overfitting problem. The comparative evaluation of performance of BRNN/FFS estimation system with various other methods shows that our proposed estimation system has the lowest mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE). Moreover, the coefficient of determination (R-squared) is around 0.95 for the proposed estimation method, which denotes a good fit. Evaluation of the SVM classifier showed good performance indicating that the proposed air quality warning system is efficient.

The effects of fine and coarse particulate matter on lung function among the elderly

Impaired lung function is associated with morbidity and mortality in the elderly. However, there is a paucity of data regarding the long-term effects of particulate matter (PM) on lung function among the elderly. This study evaluated the exposure-response relationship between ambient PM and different lung function indices among the elderly in Taiwan. A cross-sectional survey of individuals aged ≥65 years was conducted in Taiwan from October 2015 to September 2016. Those who attended the annual health examination for the elderly in five hospitals of varying background PM concentrations were enrolled. The long-term (2015 annual mean concentration) exposure to air pollution was estimated by the Kriging method at the residence of each subject. The association between ambient PM exposure and lung function was evaluated by linear regression modeling, with adjustments for age, sex, height, weight, educational attainment, presence of asthma or chronic obstructive pulmonary disease, smoking status, season, and co-pollutants. There were 1241 subjects (mean age, 70.5 years). The mean residential PM_2.5 and PM_2.5–10 in 2015 was 26.02 and 18.01 μg/m³, respectively. After adjustments for confounders and co-pollutants, the FVC decrease was best associated with fine particles (PM_2.5), whereas the FEV₁, FEF_25–75%, FEF_25% and FEF_50% decreases were best associated with coarse particles (PM_2.5–10). An IQR (10 μg/m³) increase in PM_2.5 decreased FVC by 106.38 ml (4.47%), while an IQR (7.29 μg/m³) increase in PM_2.5–10 decreased FEV₁ and FEF_25–75% by 91.23 ml (4.85%) and 104.44 ml/s (5.58%), respectively. Among the Taiwanese elderly, long-term PM_2.5 exposure mainly decreases the vital capacity of lung function. Moreover, PM_2.5–10 has a stronger negative effect on the function of conductive airways than PM_2.5.

Let-7a modulates particulate matter (≤ 2.5 μm)-induced oxidative stress and injury in human airway epithelial cells by targeting arginase 2

Epidemiological studies show that particulate matter (PM) with an aerodynamic diameter ≤ 2.5 μm (PM2.5) is associated with cardiorespiratory diseases via the induction of excessive oxidative stress. However, the precise mechanism underlying PM2.5-mediated oxidative stress injury has not been fully elucidated. Accumulating evidence has indicated the microRNA let-7 family might play a role in PM-mediated pathological processes. In this study, we investigated the role of let-7a in oxidative stress and cell injury in human bronchial epithelial BEAS2B (B2B) cells after PM2.5 exposure. The let-7a level was the most significantly decreased in B2B cells after PM2.5 exposure. The overexpression of let-7a suppressed intracellular reactive oxygen species levels and the percentage of apoptotic cells after PM2.5 exposure, while the let-7a level decreased arginase 2 (ARG2) mRNA and protein levels in B2B cells by directly targeting the ARG2 3'-untranslated region. ARG2 expression was upregulated in B2B cells during PM2.5 treatment, and ARG2 knockdown could remarkably reduce oxidative stress and cellular injury. Moreover, its restoration could abrogate the protective effects of let-7a against PM2.5-induced injury. In conclusion, let-7a decreases and ARG2 increases resulting from PM2.5 exposure may exacerbate oxidative stress, cell injury and apoptosis of B2B cells. The let-7a/ARG2 axis is a likely therapeutic target for PM2.5-induced airway epithelial injury. Copyright © 2016 John Wiley & Sons, Ltd.

Ecotoxicological characterisation of exhaust particulates from diesel-powered light-duty vehicles

Diesel exhaust is one of the major sources of fine and ultrafine particulate matter in urban air. Toxicity of diesel-powered engine emissions has been quite widely assessed, however, much less information is available on their ecotoxicity. In our study the kinetic version of the Vibrio fischeri bioluminescence inhibition bioassay, based on the ISO 21338:2010 standard, was used to characterise the ecotoxicity of diesel-powered cars. The method is sensitive enough to test the ecotoxic effect of the emission of individual vehicles. In general, significant positive correlation was found between ecotoxicity (expressed as Toxic Unit /TU/values) and total carbon (TC) as well as between TU and polycyclic aromatic hydrocarbon (PAH) concentrations.

Ecotoxicity and genotoxicity assessment of exhaust particulates from diesel-powered buses

Diesel exhaust is one of the major sources of fine and ultra-fine particulate matter in urban air. Toxicity of diesel-powered engine emissions has been quite widely assessed; however, much less information is available on their ecotoxicity. In our study, the kinetic version of the Vibrio fischeri bioluminescence inhibition bioassay based on the ISO 21338:2010 standard was used to characterise the ecotoxicity of diesel-powered buses. It is a direct contact test in which solid samples are tested in suspension and test organisms are in direct contact with toxic particles. The age of the selected buses fell into a wide range; the oldest one was produced in 1987. Diesel engines of different emission standards (Euro0-Euro4) were included. Measured EC50 values of Euro0-Euro1 engine emissions fell into the same range, 1.24-0.96 μg ml(-1), respectively. On the contrary, emission of Euro4 vehicle proved to be non-toxic. Genotoxic potential of the samples was also estimated, using the colorimetric SOS-chromotest™. Genotoxicity was detected also for Euro0 and Euro1 buses, showing correlation with the ecotoxic potential. The fact that the particulates from Euro4 vehicles did not show ecotoxic/genotoxic effect implies that replacing old Euro1 and Euro2 buses can be a highly effective solution for reducing environmental hazard of automotive emissions. The whole-aerosol testing method is a cheap alternative that can be used in engine developments and emission control.

Secondary organic carbon quantification and source apportionment of PM10 in Kaifeng, China

During 2005, the filter samples of ambient PM10 from five sites and the source samples of particulate matter were collected in Kaifeng, Henan Province of China. Nineteen elements, water-soluble ions, total carbon (TC) and organic carbon (OC) contained in samples were analyzed. Seven contributive source types were identified and their contributions to ambient PM10 were estimated by chemical mass balance (CMB) receptor model. Weak associations between the concentrations of organic carbon and element carbon (EC) were observed during the sampling periods, indicating that there was secondary organic aerosol pollution in the urban atmosphere. An indirect method of "OC/EC minimum ratio" was applied to estimate the concentration of secondary organic carbon (SOC). The results showed that SOC contributed 26.2%, 32.4% and 18.0% of TC in spring, summer-fall and winter, respectively, and the annual average SOC concentration was 7.07 microg/m3, accounting for 5.73% of the total mass in ambient PM10. The carbon species concentrations in ambient PM10 were recalculated by subtracting SOC concentrations from measured concentrations of TC and OC to increase the compatibility of source and receptor measurements for CMB model.

Characteristics of indoor/outdoor PM2.5 and elemental components in generic urban, roadside and industrial plant areas of Guangzhou City, China

Quantitative information on mass concentrations and other characteristics, such as spatial distribution, seasonal variation, indoor/outdoor (I/O) ratio, correlations and sources, of indoor and outdoor PM2.5 and elemental components in Guangzhou City were provided. Mass concentration of PM2.5 and elemental components were determined by standard weight method and proton-induced X-ray emission (PIXE) method. 18 elements were detected, the results showed positive results. Average indoor and outdoor PM2.5 concentrations in nine sites were in the range of 67.7-74.5 microg/m3 for summer period, and 109.9-123.7 microg/m3 for winter period, respectively. The sum of 18 elements average concentrations were 5362.6-5533.4 ng/m3 for summer period, and 8416.8-8900.6 ng/m3 for winter period, respectively. Average concentrations of PM2.5 and element components showed obvious spatial characteristic, that the concentrations in roadside area and in industrial plant area were higher than those in generic urban area. An obvious seasonal variation characteristic was found for PM2.5 and elemental components, that the concentrations in winter were higher than that in summer. The I/O ratio of PM2.5 and some elemental components presented larger than 1 sometimes. According to indoor/outdoor correlation of PM2.5 and element concentrations, it was found that there were often good relationships between indoor and outdoor concentrations. Enrichment factors were calculated to evaluate anthropogenic versus natural elements sources.

Toxicological assessment of ambient and traffic-related particulate matter: a review of recent studies

Particulate air pollution (PM) is an important environmental health risk factor for many different diseases. This is indicated by numerous epidemiological studies on associations between PM exposure and occurrence of acute respiratory infections, lung cancer and chronic respiratory and cardiovascular diseases. The biological mechanisms behind these associations are not fully understood, but the results of in vitro toxicological research have shown that PM induces several types of adverse cellular effects, including cytotoxicity, mutagenicity, DNA damage and stimulation of proinflammatory cytokine production. Because traffic is an important source of PM emission, it seems obvious that traffic intensity has an important impact on both quantitative and qualitative aspects of ambient PM, including its chemical, physical and toxicological characteristics. In this review, the results are summarized of the most recent studies investigating physical and chemical characteristics of ambient and traffic-related PM in relation to its toxicological activity. This evaluation shows that, in general, the smaller PM size fractions (<PM(10)) have the highest toxicity, contain higher concentrations of extractable organic matter (comprising a wide spectrum of chemical substances), and possess a relatively high radical-generating capacity. Also, associations between chemical characteristics and PM toxicity tend to be stronger for the smaller PM size fractions. Most importantly, traffic intensity does not always explain local differences in PM toxicity, and these differences are not necessarily related to PM mass concentrations. This implies that PM regulatory strategies should take PM-size fractions smaller than PM(10) into account. Therefore, future research should aim at establishing the relationship between toxicity of these smaller fractions in relation to their specific sources.

Levels of total suspended particulate matter and major trace elements in Kosovo: a source identification and apportionment study

Concentration levels of total suspended particles (TSP) and 27 major, minor and trace elemental components were determined at four sites in Kosovo through a 1-year survey (January-December 2002). Ambient concentrations were evaluated in comparison to limit values. The origin of elemental TSP constituents was investigated by calculating enrichment factors and diagnostic ratios. Multivariate statistics, such as hierarchical cluster analysis and factor analysis, were also employed to identify emission sources. A multivariate statistical receptor model (Absolute Principal Component Analysis, APCA) was applied to quantify source contributions. Soil dust, cement production, vehicular emissions, brake wear, and fuel combustion were identified as major sources with variable contributions at the four sampling sites.

Receptor modeling application framework for particle source apportionment

Receptor models infer contributions from particulate matter (PM) source types using multivariate measurements of particle chemical and physical properties. Receptor models complement source models that estimate concentrations from emissions inventories and transport meteorology. Enrichment factor, chemical mass balance, multiple linear regression, eigenvector. edge detection, neural network, aerosol evolution, and aerosol equilibrium models have all been used to solve particulate air quality problems, and more than 500 citations of their theory and application document these uses. While elements, ions, and carbons were often used to apportion TSP, PM10, and PM2.5 among many source types, many of these components have been reduced in source emissions such that more complex measurements of carbon fractions, specific organic compounds, single particle characteristics, and isotopic abundances now need to be measured in source and receptor samples. Compliance monitoring networks are not usually designed to obtain data for the observables, locations, and time periods that allow receptor models to be applied. Measurements from existing networks can be used to form conceptual models that allow the needed monitoring network to be optimized. The framework for using receptor models to solve air quality problems consists of: (1) formulating a conceptual model; (2) identifying potential sources; (3) characterizing source emissions; (4) obtaining and analyzing ambient PM samples for major components and source markers; (5) confirming source types with multivariate receptor models; (6) quantifying source contributions with the chemical mass balance; (7) estimating profile changes and the limiting precursor gases for secondary aerosols; and (8) reconciling receptor modeling results with source models, emissions inventories, and receptor data analyses.