Atmospheric Pollution Research最新文献

This study investigates the acidity of particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5) in Hanoi, the capital city of Vietnam, and its influencing factors by analyzing measured concentrations of water-soluble inorganic ions (WSIIs) in 107 24-h samples collected between June 2021 and February 2022. The average sulfate, nitrate, and ammonium concentrations were 5.79, 3.55, and 5.46 μg m⁻³, respectively. Among the samples, 83 exhibited alkaline aerosols characterized by elevated ammonium-to-sulfate molar concentration ratios (ASMCR) ranging from 2.3 to 9.6, while 24 showed acidic characteristics with ASMCR ranging from 0.5 to 2.5. By employing the Extended Aerosol Inorganic Model E-AIM III, with major WSIIs as the input parameters, the estimated aerosol acidity pH ranged from 8.6 to 10.9 for alkaline aerosols and below 4.5 for acidic aerosols. These variations in ASMCR and aerosol pH highlight the distinct acidic and alkaline aerosol source regions affecting Hanoi's PM_2.5 by the monsoon air masses. The Potential Source Contribution Function (PSCF) maps of NH₄⁺ and SO₄²⁻ revealed the Northeast and Southeast monsoon upwind sources of acidic aerosols over China's Guangdong coastal region and Vietnam's offshore, respectively. Alkaline aerosols were observed during the Northeast and Southwest monsoons, with upwind sources originating in South China, Thailand, and Cambodia. The emergence of the ammonium-rich source areas in South China may be attributed to China's sustained emission control measures, targeting acidic SO₂ and NO_x emissions while leaving alkaline NH₃ emissions largely unaffected. This research provided insights into the intricate relationships between regional emissions, long-range transport, and local meteorological-driven emissions, offering valuable guidance for effective air quality management in urban environments.

This pilot study aimed to examine personal exposure to ultrafine particles (UFP or particle smaller than 100 nm) in Phnom Penh, Cambodia through the assessment of different transportation modes, travel routes, and the comparison of indoor and outdoor activities. A handheld UFP counter was used to record the UFP size, concentration and as well as Lung Deposited Surface Area (LDSA). GPS data was recorded using a GPS watch and then combined with the UFP data before further analysis with geospatial software (QGIS) along with OpenStreetMap to generate spatial data of personal exposure to UFP. The study revealed significant differences in UFP exposure between motorbike and bus users, with average UFP concentrations of approximately 114,300 and 171,700 particles/cm³ for motorbike users, and 22,600 and 37,200 particles/cm³ for bus users on lines 3 and 4A, respectively. These concentrations exceed WHO guidelines, which consider UFP levels above 20,000 particles/cm³ per hour as high and potentially harmful. The results of our study also revealed varying amounts of exposure on different roadways, with Russian Federation Blvd consistently exhibited the highest concentrations of UFP, especially during periods of peak traffic. Furthermore, indoor environments generally presented lower UFP exposure. Specific activities or events were found to generate temporary increases in particle concentration. It was shown that weekdays had elevated levels of UFP compared to weekends. Regardless of the limitations of the study, especially its small sample size, it provides significant initial observations, highlighting the urgent need for mitigation strategies and further comprehensive studies in the region.

This study focused on the measurement of BTEX (benzene, toluene, ethylbenzene, and xylene) concentrations in the air of indoor and outdoor environments of automobile workshops in Damghan, Iran. Air samples from twenty-five workshops were actively collected and analyzed using Gas Chromatography-Flame Ionization Detection (GC-FID). The results showed that the concentrations of BTEX were higher in the indoor air compared to the outdoor air. The highest mean concentration of benzene (153.22 ± 34.21 μg m⁻³), toluene (94.41 ± 25.25 μg m⁻³), and xylenes (385.38 ± 34.21 μg m⁻³) was found in auto paint (AP) workshops, while the highest mean concentration of ethylbenzene (43.39 ± 12.57 μg m⁻³) was observed in auto body (AB) workshops. The significant negative correlations between benzene, ethylbenzene, xylene isomers, and relative humidity (RH) indicated that controlling humidity is an effective strategy. The mean inhalation lifetime cancer risk (LTCR) for benzene in both indoor and outdoor air of all automobile workshops exceeded the EPA (Environmental Protection Agency) recommended limits. The highest mean LTCR values for benzene and ethylbenzene were observed in the AP (3.24E10-4) and AB (2.95E10-5) workshops, respectively. The hazard quotient (HQ) of benzene and Xylene in the indoor air of the AP and AB workshops was >1, which indicates that the non-carcinogenic risks associated with exposure to these compounds are considerable. This study underscores the need for international attention to BTEX pollution in automobile workshops, highlighting the global health risks. The findings provide crucial data for developing strategies to mitigate these risks and protect workers’ health.

In the context of climate change, increasingly frequent wildfire events are exacerbating the air quality crisis in China and have become a significant source of atmospheric PM_2.5. This study selected 12 major forest wildfire events in China from 2018 to 2023. Using atmospheric pollutant and component concentration data, as well as meteorological data, the study employed MK trend analysis, forward trajectory simulation, potential source contribution function (PSCF), and health risk indices to investigate the evolution patterns of PM_2.5 concentrations before and after each wildfire event. The study explored the driving role of meteorological factors in this evolution process and quantitatively analyzed the spatial distribution characteristics of health risks in surrounding cities post-wildfire. The results indicated that: 1) PM_2.5 levels changed significantly before and after each wildfire event, although the proportion of components remained relatively stable. 2) PM_2.5 concentrations exhibited varying characteristics within different buffer zones of the wildfire areas. In the forest wildfire events in Foshan, Guangdong Province, and Jinzhong, Shanxi Province, the average PM_2.5 concentrations within the 50 km buffer zones reached approximately 90 μg/m³, about 4–5 times the multi-year average for these areas. 3) Wildfire emissions were mainly influenced by meteorological and topographical factors. Wind field dependence diagrams showed that PM_2.5 tended to accumulate in all wind directions, particularly at lower wind speeds of 0–5 m/s 4) Potential source analysis revealed that PM_2.5 emissions from wildfires posed significant risks to surrounding areas. Multiple events had high-risk areas (WPSCF ≥0.8), and among the cities in these high-risk areas, the health risk value (ΔM) for Ya'an City reached an extremely high 85.1. This study provides a theoretical basis for policymakers to develop locally tailored wildfire management policies, ensuring the protection of the public's right to breathe clean air.

The pungent odor emitted by particleboards affect people's physical and mental health. However, traditional methods using a sensory odor panel cannot determine the chemical composition and source of odorants, and cannot assess the risk of odor. In this study, the threshold odor concentration (TOC) value of terpenes in woody raw materials were determined by gas chromatography-mass spectrometry-olfactometry (GC-MS-O), and the TOC and the lowest concentration of interest (LCI) databases of particleboard odorants was established based on self-test and literature retrieval. Then, the odor activity value (OAV) and risk value (RV) of the main odor compounds were calculated and evaluated based on their TOC and LCI value. The results showed that benzene series, terpenes, acetic acid, hexaldehydes and other small molecules were the predominant substances released from particleboards. Although acetic acid (strong, pungent, vinegar-like odor), p-, m-xylene (pungent aroma), 1-butanol (spicy alcohol), o-xylene (pungent aroma), benzaldehyde (bitter almond flavor), naphthalene (strong tar flavor) had pungent odor, the main odorants (OAV>1) were aldehydes (such as hexanal, nonanal, pentanal and heptanal), terpenes (such as longifolene), and benzene series (p-, m-xylene). The reduction of aldehydes, terpenes and benzene series was the main way to reduce the pungent odor of particleboards. Although the single RV of these substances was much less than 1, the sum of all RV in HB exceeded 1. Therefore, the use of HB indoors needs careful consideration.

Atmospheric deposition plays a crucial role in the fate and transport of per and polyfluoroalkyl substances (PFAS), especially in areas far from production sites. It could be comparable to or exceed point source inputs. This study assessed the occurrence and composition of legacy and emergent PFAS in wet deposition in the Miami-Dade area, South Florida. Rainwater samples were collected from three locations in Miami-Dade County between 2021 and November 2022 (N = 42), The sample preparation methodology was validated, involving solid phase extraction (SPE) using a weak anion exchange (WAX) cartridge, followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) using isotopically labeled internal standards. The results indicate that 74 % of the major components were perfluoroalkyl carboxylic acids (PFCAs), while 12 % were perfluoroalkyl sulfonic acids (PFSAs). Specifically, perfluoro-n-butanoic acid (PFBA) was the most frequently detected compound, detected in 95 % of the samples. Perfluorooctanesulfonic acid (PFOS) and Perfluorooctanoic acid (PFOA) levels detected are above EPA-updated health advisory levels for drinking water, averaging 0.24 ng L⁻¹ and 0.32 ng L⁻¹, respectively. PFOS and PFOA fluxes in the Southeast were similar to those reported in the Northeast United States. Compounds such as perfluoro-1-hexanesulfonate (4:2 FTS), perfluoro-1-octanesulfonate (6:2 FTS), perfluorohexanoic acid (PFHxA), perfluorohexanesulfonic acid (PFHxS), PFOA, perfluorononanoic acid (PFNA), and perfluorodecanoic acid (PFDA) showed significant seasonal variation, with higher concentrations during the dry season. The perfluoroheptanoic acid (PFHpA)/PFOA and PFOA/PFNA ratios suggest a mixture of point and non-point sources in rainwater. Air mass simulation indicated that contribution from Northwestern influences the increase in the sum of PFAS.

Aerosol mass balance studies based on filter samples require a conversion factor to derive organic matter (OM) concentrations from organic carbon (OC) measurements from thermo-optical methods. This factor provides indirect insights on the molecular structure of OM needed in chemical transport models. Site- and season-specific ratios of OC to OM (f_OM:OC) were calculated using data from five rural background sites in France between 2012 and 2021 by relating the unidentified chemical fraction in PM_2.5 samples to thermo-optical OC concentrations. Further, multiple linear formulations were used to evaluate the impact of possible artefacts on the determination of f_OM:OC. The resulting f_OM:OC was then compared to other estimates derived from online aerosol mass spectrometry data, showing good agreement. The spatial and temporal variability in f_OM:OC is discussed considering factors such as seasonality, meteorological conditions and the atmospheric oxidative potential. Linear-mixed effect models were formulated to quantitatively determine the drivers which influence the f_OM:OC at the French rural background sites. Both ozone and relative humidity were variables with statistically significant effects on f_OM:OC, indicating that differences in the contributions from both photooxidation and water content, explain the variability in f_OM:OC observed at the French rural background sites. Site-specific f_OM:OC yielded more accurate PM_2.5 mass closure and are therefore recommended in mass-balance exercises. Accurate f_OM:OC are critical to maintain consistency in OM time series, especially in cases where filter-based time series may be replaced by state-of-the-art online instrumentation.

Assessing individual exposure to PM_2.5 (particulate matter of aerodynamic diameter lesser than 2.5 μm) requires precise monitoring of PM_2.5 concentrations at specific geographical and temporal scales. This demand is met globally by low-cost particulate matter sensors, although calibrating them is difficult. In this study, four low-cost PM sensors, Sharp GP2Y1010AU0F, Honeywell HPMA115S0-XXX, Plantower PMSA003-A, and Sensirion SPS30, were calibrated and tested using various aerosols. The calibration method has three steps: individual (considering each sensor independently to a single aerosol type; n = 1), combined (all sensors for a specific model together for a specific aerosol type; n = 4), and generic (all sensors for a given model together to all aerosols; n = 16). Sensor responses are processed using linear, quadratic, power-law, and artificial neural network (ANN) algorithms in each calibration stage. Performance metrics, including coefficient of determination (R²), mean absolute percentage error (MAPE), root mean square error (RMSE), and percentage coefficient of variation (% CV), were utilized for assessment. Amongst all the four tested sensors, the Sensirion SPS30 sensors gave the best performance with a minimum R² value of 0.911 when calibrated with a generic ANN calibration algorithm. Also, the MAPE was less than 10 %, and the RMSE was less than 7 % when exposed to different particles. Sensirion SPS30 showed the lowest inter-sensor variability with % CV less than 6 %. Sensors identified monodisperse polystyrene latex (PSL) particle size in the investigation. Regardless of exposure to 0.3, 0.46, 0.60, or 1.0 μm PSL, the reported number size distribution for the PMSA003 sensor remained consistent and did not align with the results from Grimm. As the PSL size rose, the SPS30 size distribution changed towards larger particle sizes, although it did not always match Grimm data. As the PSL size increased, the sensor's PM₁, PM_2.5, and PM₁₀ mass proportions altered.

Nitrate and organic matters (OM) have become dominant components in fine particles (PM_2.5) during winter haze in recent years. Based on continuous observations of gaseous pollutants, the chemical composition of PM_2.5, and other relevant data collected over a one-month period (December 1–31, 2021), we investigated the main controlling factors contributing to the formation of wintertime haze in Yibin, located in the southern Sichuan Basin. Our observations reveal that two major haze episodes occurred during the campaign. Nitrate and OM were the dominant components in PM_2.5, with an overall contribution of more than 50%. Nitrate and OM concentrations nearly quadrupled and more than tripled, respectively, from the non-pollution phase to the pollution phase. Furthermore, the mixing ratios of high-activity VOCs also noticeably increased during the pollution period, particularly OVOCs mixing ratios increased by 123.83%. PM_2.5 concentrations were positively correlated with O_x concentrations, with a stronger relationship observed when O_x concentrations exceeded 80 μg m⁻³. There were also significant positive correlations between nitrate and O_x concentrations, as well as between OVOCs and OM concentrations. Furthermore, the pollution period showed a much higher degree of photochemical aging compared to the non-pollution period. Potential Source Contribution Function (PSCF) analysis revealed that, in addition to local emissions, regional transport, particularly air pollutants from Chengdu and Chongqing, significantly contributed to winter haze in Yibin. Our findings suggest that intense atmospheric photochemical oxidation and pronounced photochemistry contributed greatly to the occurrence of severe winter haze events.

Owing to escalating concerns regarding global warming, there has been a heightened focus on greenhouse gases emitted by vehicles. To effectively monitor and certify the fuel consumption and CO₂ emissions of heavy-duty vehicles, this study proposes a calculation model named the China Heavy-Duty Vehicle Energy Consumption and Carbon Emission Calculation Model (CHECM). The CHECM is a simulation tool based on longitudinal dynamics. A classification learner was utilised to obtain shifting strategies, achieving accuracies of 92.9% and 93.5% under regulated driving cycles. A fuel-consumption model was incorporated to predict the transient performance of the engine and transmission. In addition, the Sobol method was used to assess the sensitivities of rolling resistance, air drag and rotational mass conversion coefficients to the driving force and a method was proposed to obtain the road resistance correction factor. The test results of three China-6 heavy-duty vehicles over two regulatory test cycles were obtained and used for model accuracy evaluation. The results showed that the deviations between the measured and calculated fuel consumption were 1.25–3.57%, whereas those between the measured and calculated CO₂ emissions using the Chinese World Transient Vehicle Cycle were 3.23–4.16%. The CHECM has the potential to accurately replicate various driving conditions and vehicle configurations, particularly when specific sources of uncertainty are constrained.