Traffic Emissions Research Articles

Health risks of PM2.5-bound metals at a street canyon: implication for traffic non-exhaust emissions

Traffic non-exhaust emissions are a significant source of toxic metals in fine particular matter (PM2.5), and thus pose adverse effects on human health. PM2.5-bound metals were sampled at a street canyon and urban background site during ozone and haze periods in Zhengzhou. Higher metal concentrations were observed at the street canyon than at the urban background site, which was more affected by traffic non-exhaust, oil combustion, and dust emissions. Consequently, PM2.5-bound metals may cause significant non-carcinogenic and carcinogenic hazards to residents at the street canyon. Traffic non-exhaust and oil combustion were the primary contributors to the non-carcinogenic and carcinogenic risk at the street canyon, respectively. Furthermore, the severe health risk of PM2.5-bound metals from traffic non-exhaust emissions will remain for a long time at street canyons. This work reveals the health risks from vehicles at street canyons, which is beneficial for further reduction of traffic-related emissions.

Toward a dynamic national transportation noise map: Modeling temporal variability of spectral traffic noise emission levels.

The National Transportation Noise Map predicts time-averaged road traffic noise across the continental United States (CONUS) based on annual average daily traffic counts. However, traffic noise can vary greatly with time. This paper outlines a method for predicting nationwide hourly varying source traffic sound emissions called the Vehicular Reduced-Order Observation-based Model (VROOM). The method incorporates three models that predict temporal variability of traffic volume, predict temporal variability of different traffic classes, and use Traffic Noise Model (TNM) 3.0 equations to give traffic noise emission levels based on vehicle numbers and class mix. Location-specific features are used to predict average class mix across CONUS. VROOM then incorporates dynamic traffic class mix data to obtain dynamic traffic class mix. TNM 3.0 equations then give estimated equivalent sound level emission spectra near roads with up to hourly resolution. Important temporal traffic noise characteristics are modeled, including diurnal traffic patterns, rush hours in urban locations, and weekly and yearly variation. Examples of the temporal variability are depicted and possible types of uncertainties are identified. Altogether, VROOM can be used to map national transportation noise with temporal and spectral variability.

Characterizations of air pollutants at roadside monitoring stations and traffic emission effects: A case study in Tianjin, China

To investigate the response of Roadside Monitoring Stations (RSs) to traffic-related air pollution, traffic and pollutant characteristics, influencing factors, and potential source characterization in Tianjin, China were determined based on roadside monitoring of real-world data conducted at RSs in 2022. The diurnal variation trend of pollutants at RSs was consistent with that at the National Monitoring Station (NM), with notably higher pollutant fluctuations during the morning and evening peak traffic times at RSs, where the average diurnal concentration was 41.46 % higher than that at the NM. The generalized additive model (GAM) for nitrogen oxides (NOx) and carbon monoxide (CO), responding to the multiple influencing factors, performed well at RSs, with deviance explained by 86.6 and 61.4 %, respectively. The synergistic effects of wind direction and speed contributed to most of the variations in NOx and CO, which were 14.74 and 12.87 %, respectively. Pollutant concentrations were highest under windless conditions, with pollutants originating primarily from local vehicle emissions. The model results indicated that medium-duty truck (MDT) traffic flow predominantly contributed to the variability in NOx emissions, whereas passenger car (PC) traffic flow was the primary source of CO emissions from traffic variables. MDTs should be the focus of urban NOx traffic emissions control. Potential-source analysis validated the results obtained from the GAM, and both analyses showed that RSs can better characterize traffic-related air pollutants. Furthermore, more stringent emission standards have effectively mitigated the release of pollutants from motor vehicles and contributed to the modernization of vehicle fleet composition, effectively decreasing CO concentrations.

Estimation of Traffic Emissions by Integrating COPERT and CUBE

Air pollution caused by motor vehicles is harmful to public health. Managing the cause of this type of pollution is very difficult. Effective prediction and management of pollution can be attained only by computing air pollution. It is difficult to measure emissions directly, so it is estimated using a variety of models developed worldwide. The current study made an attempt to integrate the emission model COPERT with the traffic assignment model in CUBE software for predicting the traffic-related emissions of pollutants SO2, NO2 & PM2.5 in mixed traffic conditions by considering passenger car and light duty vehicles (LDVS), two-wheeler, auto and bus. The study also aimed to include fuel variables and meteorological variable humidity along with fleet composition, average speed and average monthly temperature as inputs. This would enable us to control the rising vehicular emission, by assessing current and future air quality and thereby implementing policy decisions.

Evaluating background and local contributions and identifying traffic-related pollutant hotspots: insights from Google Air View mobile monitoring in Dublin, Ireland

Mobile monitoring provides high-resolution observation on temporal and spatial scales compared to traditional fixed-site measurement. This study demonstrates the use of high spatio-temporal resolution of air pollution data collected by Google Air View vehicles to identify hotspots and assess compliance with WHO Air Quality Guidelines (AQGs) in Dublin City. The mobile monitoring was conducted during weekdays, typically from 7:00 to 19:00, between 6 May 2021 and 6 May 2022. One-second data were aggregated to 377,113 8 s road segments, and 8 s rolling medians were aggregated to hourly and daily levels for further analysis. We assessed the temporal variability of fine particulate matter (PM2.5), nitrogen monoxide (NO), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and carbon dioxide (CO2) concentrations at hyperlocal levels. The average daytime median concentrations of NO2 (28.4 ± 15.7 µg/m3) and PM2.5 (7.6 ± 4.7 µg/m3) exceeded the WHO twenty-four hours (24 h) Air Quality Guidelines in 49.4% and 9% of the 1-year sampling time, respectively. For the diurnal variation of measured pollutants, the morning (8:00) and early evening (18:00) showed higher concentrations for NO2 and PM2.5, mostly happening in the winter season, while the afternoon is the least polluted time except for O3. The low-percentile approach along with 1-h and daytime minima method allowed for decomposing pollutant time series into the background and local contributions. Background contributions for NO2 and PM2.5 changed along with the seasonal variation. Local contributions for PM2.5 changed slightly; however, NO2 showed significant diurnal and seasonal variability related to traffic emissions. Short-lived event enhancement (1 min to 1 h) accounts for 36.0–40.6% and 20.8–42.2% of the total concentration for NO2 and PM2.5. The highly polluted days account for 56.3% of total NO2, highlighting local traffic is the dominant contributor to short-term NO2 concentrations. The longer-lived events (> 8 h) enhancement accounts for 25% of the monitored concentrations. Additionally, conducting optimal hotspot analysis enables mapping the spatial distribution of “hot” spots for PM2.5 and NO2 on highly polluted days. Overall, this investigation suggests both background and local emissions contribute to PM2.5 and NO2 pollution in urban areas and emphasize the urgent need for mitigating NO2 from traffic pollution in Dublin.

Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows

Abstract. VERT (Vehicular Emissions from Road Traffic) is an R package developed to estimate traffic emissions of a wide range of pollutants and greenhouse gases based on traffic estimates and vehicle fleet composition data, following the EMEP/EEA methodology. Compared to other tools available in the literature, VERT is characterised by its ease of use and rapid configuration, while it maintains great flexibility in user input. It is capable of estimating exhaust, non-exhaust, resuspension, and evaporative emissions and is designed to accommodate future updates of available emission factors. In this paper, case studies conducted at both urban and regional scales demonstrate VERT's ability to accurately assess transport emissions. In an urban setting, VERT is integrated with the Lagrangian dispersion model GRAMM–GRAL and provides NOx concentrations in line with observed trends at monitoring stations, especially near traffic hotspots. On a regional scale, VERT simulations provide emission estimates that are highly consistent with the reference inventories for the Emilia-Romagna region (Italy). These findings make VERT a valuable tool for air quality management and traffic emission scenario assessment.

Impact assessment of future fleet compositions in vehicle emissions in urban areas: A methodological framework and a case study

This study explores the impact of emerging vehicle technologies on direct urban traffic emissions. It investigates emission reduction potential from shifts in fleet compositions and modal choices, especially considering climate change. To achieve this, three key research areas are explored for historical, current, and future scenarios (up to 2050): mode choice, emission factors for different vehicle categories, and diverse vehicle propulsion technologies. The estimation of the modal split is pivotal, developing a methodology utilizing Stated Preference survey data, discrete choice modeling, Monte Carlo simulations, and macroscopic traffic simulations. Future scenarios derive from the reference year’s modal split, and emission factors and fleet compositions are predetermined via an extensive literature review, aiding the assessment of their respective emissions. A subsequent sensitivity analysis identifies the impact of specific parameters on emissions, guiding future research focus. Study results underscore differences in greenhouse gas emissions and primary air pollutants between base and future scenarios.

Influence of sources and atmospheric processes on metal solubility in PM2.5 in urban Guangzhou, South China

Water-soluble metals exert a significant influence on human and ecosystem health. In this study, a comprehensive investigation was undertaken to elucidate the solubilities of metals in PM2.5 and potential influencing factors during the dry season of 2019–2020 in urban Guangzhou, South China. The observed average solubility was <20 % for Al, Fe, Sn, and Ti; 20–40 % for V, Cr, Sb, Pb, and Ni; 40–60 % for Ba and Cu; and 60–80 % for Zn, As, Se, Cd, and Mn. Metals (Al, Ti, and Fe) originated from crustal sources (e.g., soil dust) have much lower solubilities than those (Mn, Zn, As, Se, Cd, and Ba) from fossil fuel combustion sources (e.g., traffic emission, coal combustion), suggesting the dominant role the metal sources played on solubility. Enhanced solubilities of Cu, As, Se, Cd, Sn, Sb, and Pb were associated with aerosol acidity, while those of V, Cr, Mn, Ni, Zn, and Ba were linked to organic acid complexation. For the three crustal metals, the solubilities of Al and Ti primarily depended on aerosol acidity, whereas the solubility of Fe depended on both aerosol acidity under pH < 2 conditions and organic acid complexation under pH > 2 conditions. These findings underscore the primary influence of inherent properties of the metals on their solubility and reveal the varying impacts of atmospheric physicochemical processes, with changes in their solubilities being <10 % for Cd, Sn, Sb, and Pb, 10–20 % for Cu, Cr, Mn, Ni, and Ba, and 20–30 % for As, Se, and Zn.

The relationship between the inhalation bioaccessibility of potentially toxic elements in road dust from a heavily polluted industrial area and the source of their pollution

One of the sources of chronic exposure to potentially toxic elements (PTE), especially in polluted environments, is the inhalation of resuspended road dust (RD). The aim of this study is to assess the inhalation bioaccessibility of PTE in RD from highly polluted environments from mining/smelting industries and traffic, and to identify any correlations between the bioaccessibility fraction of PTE and the physicochemical characteristics of the particles. RD from the studied area contains extremely high total concentrations of Cr, V, and Mn, which are likely due to pollution from the smelting industry. Additionally, elevated total concentrations of other elements associated with traffic emissions including Zn, Cu, Pb, Sb, and Sn were also measured. The bioaccessibility of PTE was assessed using two synthetic extraction solutions - Gamble's solution (GS) and Artificial Lysosomal Fluid (ALF). The majority of elements showed negligible bioaccessibility in GS. However, quite high inhalation bioaccessibility was observed for Zn, Pb, Sb, Cd, and Mn in the ALF solution, with a mean bioaccessible fraction of 49, 51.5, 41, 50, and 40% respectively. The highest bioavailable fraction was measured for Cd (97%) in a sample collected near a steel production facility and for Pb (95%) in a sample collected near the highway. These results indicate that increased mobility of the elements in inhaled particles occurs only in the case of phagocytosis. The lowest inhalation bioavailability was measured for Cr (mean is 3%). Differential individual particle analysis revealed that about 60% of phases, mostly major (Cr,Ti,V)-bearing metallic alloys, silicates, oxides and sulphides, are stable in ALF solution, while 40% of phases, mostly (Fe,Ca,Mn)-bearing oxides, silicates, sulphides, metals and metallic alloys originating from steel production, ferrochrome, ferrosilicon and vanadium production and from traffic emissions have been heavily corroded or completely dissolved. The study provides valuable information to further assess health hazards from various emission sources.

Local contribution of road traffic and residential biomass burning to black carbon aerosols – Modelling and validation

Black carbon (BC) is a harmful pollutant to human health and the environment. The aim of this paper is to evaluate the local contribution of road traffic and residential biomass burning to BC pollution levels at urban scale by implementing an integrated modelling approach with high spatial and temporal resolution. The traffic emission was extended to include BC emission factors considering road network as line emission sources. A new module to calculate emissions from residential biomass burning was developed based on the heating degree days methodology and local surveys. The modelling approach implemented in Coimbra, Portugal, was validated with observations collected during a six-month monitoring campaign at urban traffic and urban background stations using thermo-optical and optical methods. At the traffic station, modelling results showed that 86% of BC concentrations are related to traffic activity, which are mostly due to hot exhaust emissions (76%). Nevertheless, biomass burning has a significant contribution in the whole urban area during winter. The results of monthly average BC concentrations obtained from dispersion modelling revealed a contribution from local road traffic and residential biomass burning emissions of around 4 μg m−3 at both monitoring sites during the coldest period, but this contribution was two times higher for the hotspots identified within the urban area. Moreover, hourly values at hotspots obtained from the modelling may achieve 85 μg m−3, thus stressing the importance of spatial and temporal analysis with high resolution. The validation approach applied in this work highlight the need for more transparency in defining “black carbon” reported by modelling to ensure comparability with measurements obtained by different techniques.

Characterization of PM2.5 emissions from on-road vehicles in the tunnel of a major Middle Eastern city

Traffic emissions are an important source of air pollution worldwide, but in the Middle East, this problem is exacerbated by weak or no enforcement of emission regulations. Comprehensive measurements of fine PM emission factors (EFs) from road transport in the region have not yet been conducted, but such data are necessary for quantitative assessments of the health impact of transport emissions in the region. To address this need, PM2.5 samples collected inside the Salim Slam tunnel in Beirut, Lebanon were analyzed for carbonaceous matter (organic carbon (OC) and elemental carbon (EC)), water-soluble ions, elements, and selected organic compounds. The OC/EC ratio was 1.8 for the total fleet and 2.6 for light-duty vehicles (LDV), in agreement with the dominant proportion of gasoline LDV in the Lebanese fleet. A Cu/Sb ratio of 4.2 ± 0.1 was observed, offering a valuable metric for detecting brake wear emissions in subsequent studies conducted in the region. The EFs of carbonaceous matter, elements and ions generally varied by a factor 0.1 and 10 in comparison to literature values, while those for alkanes and polycyclic aromatic hydrocarbons were similar to the upper values previously reported. The average number size distribution was characterized by a single mode around 35 nm. The particles number EF (for diameters between 10 and 480 nm) was within the range of 1014-1015 particles per kg of fuel. The chemical mass balance model showed an average contribution to EF of 62% from non-exhaust sources. This study highlights the need for more enforceable stringent vehicular regulations because of the local practices (i.e., removal of catalyst) and some EF values are very high compared to other studies/countries.

Assessment of the sustainability of online food delivery from the perspective of CO2 emissions and transport intensity: A case study in Jakarta

This study examines the impact of online food delivery on CO2 emissions and transport intensity in Jakarta, Indonesia, by integrating data from both delivery drivers and customers. A total of 235 delivery instances were analyzed to discern typical distances and patterns inherent in these services. Additionally, insights into the demand side were obtained through customer surveys, yielding 203 valid responses, that included waiting times, costs, and behaviors related to alternative meal acquisition methods. CO2 emissions generated by delivery processes were estimated, utilizing travel distances recorded by drivers. The traffic impact was assessed by calculating the road occupancy of motorcycles used for deliveries. Furthermore, the assessment of CO2 emissions and transport intensity considered hypothetical emission scenarios without such delivery services based on customer indications of their alternative means of meal acquisition. This analysis revealed that frequent short journeys by delivery motorcycles significantly contribute to urban traffic congestion and CO2 emissions, highlighting the environmental and traffic pressures resulting from the rise of food delivery services. Results from the customer survey revealed a profound dependence on these services, indicating that their availability prompts a significant number of additional trips, thereby exacerbating these impacts. The findings suggest recommendations for mitigating these adverse effects, including promoting the use of electric motorcycles for deliveries and managing demand by reassessing delivery fees to reflect the actual environmental costs.

Traffic emissions and greenspace exposure and associations with respiratory outcomes among urban children and adolescents in India

Traffic emissions and greenspace exposure and associations with respiratory outcomes among urban children and adolescents in India

Changing ozone sensitivity in Fujian Province, China, during 2012–2021: Importance of controlling VOC emissions

In the troposphere, ozone (O3) formation can be limited by NOx, VOCs, or both, complicating efforts to reduce O3 by controlling its precursors. This study used formaldehyde (HCHO) data and nitrogen dioxide (NO2) data from the Ozone Monitoring Instrument (OMI) to analyze O3 formation sensitivity in Fujian from 2012 to 2021. Over the past decade, an 8.7% reduction in NO2 VCDs and a 9.91% increase in HCHO VCDs were observed. Due to differences in the primary driving factors, HCHO VCDs exhibit a characteristic seasonal pattern with higher in summer and lower in winter, whereas NO2 VCDs show the opposite trend. O3 formation chemistry was accurately diagnosed by combining satellite-based data and ground-based O3 data. A new threshold value (3.3–4.6) was derived to determine the transition from VOC-limited to NOx-limited O3 formation regimes. Results showed that O3 sensitivity exhibited pronounced seasonal variations. The VOC-limited regime predominates throughout the entire Fujian region in winter, whereas it occupies only 5% of the area in summer. A VOC-limited region was found widely across Fujian on an annual average, but it decreased by 24% over 10 years. Transitional areas experienced a 19% increase. In two natural emission reduction cases (reductions during the Chinese Lunar New Year holiday and reductions in weekend traffic emissions compared to weekdays), ground-level O3 effectively captured the impacts of sensitivity changes. The impact suggests that when Fujian is in the VOC control region, a significant reduction in NOx, without effective VOC control, might lead to an O3 increase. The importance of controlling VOC emissions is highlighted in Fujian. This study enhances the understanding of O3 formation regimes in southeastern China, which is crucial for developing O3 prevention and control strategies.

On the accuracy of idealized sources in CFD simulations of pollutant dispersion in an urban street canyon

Idealized pollutant sources are widely used by the scientific community to replicate traffic emissions in wind tunnel tests and CFD simulations. However, it is unclear to what extent such idealized sources can adequately reproduce the emission and dispersion by cars in idle (static) or moving situations in streets. This study investigates the impact of a static idealized point source (S-IPS) versus an idling or static (S-) and a moving or dynamic (D-) realistic car source (RCS) on the pollutant dispersion in a street canyon. First, 3D steady RANS and LES simulations are performed with a S-IPS and validated by means of wind-tunnel tests. Next, LES simulations are performed to analyze the impact of S-IPS versus S-RCS. Finally, three D-RCS with different car speeds are simulated and compared with S-RCS. The results show that using a S-RCS increases the plane-averaged concentration by 11%–140 % at z/H = 0.03 and by 30%–50 % at y/H = 0, with respect to S-IPS. The comparison of S-RCS and D-RCS shows that car movement can also have a large impact on pollutant dispersion along the canyon.

Exploring the characteristics and source-attributed health risks associated with polycyclic aromatic hydrocarbons and metal elements in atmospheric PM2.5 during warm and cold periods in the northern metropolitan area of Taiwan

Polycyclic aromatic hydrocarbons (PAHs) and metal elements are commonly considered hazardous air pollutants due to their toxic, mutagenic, and carcinogenic properties. However, few studies have simultaneously examined their potential sources and health effects. This study aimed to quantify the PAHs and metal elements in atmospheric PM2.5, investigating their characteristics and potential sources to assess associated health risks in the northern metropolitan area of Taiwan. The measurements indicated that the mean concentrations of total PAHs and metal elements in PM2.5 were 0.97 ± 0.52 ng m−3 and 590 ± 200 ng m−3, respectively. Utilizing the positive matrix factorization profiles, the PAH pollution was classified into two sources: industrial emissions, traffic emissions, and coal combustion (69%) were the predominant sources of PAHs, with petroleum volatilization and biomass burning (31%) making a lesser contribution. Similarly, we traced metal elements to three potential sources: natural sources (48%), a combined source of industrial emissions, coal combustion, and traffic exhaust (32%), and a blend of non-exhaust emissions from traffic and waste incineration sources (20%). Results from the potential source contribution function model suggested that the emissions of PAHs and metals could be influenced by the eastern regions of China, although local sources, including waste incinerators, traffic, shipping, and harbor activities, were identified as the primary contributors. Source-attributed excess cancer risk revealed that industry, traffic, and coal combustion had the highest cancer risk posed by PAHs in the cold period (1.0 × 10−5), while the greatest cancer risk among metal elements was linked to non-exhaust emissions from traffic and waste incineration emissions (2.0 × 10−5). This research underscores the importance of considering source contributions to health risk and emission reduction when addressing PM2.5 pollution. These findings have direct implications for policymakers, providing them with valuable insights to develop strategies that protect public health from the detrimental effects of PAH and metal element exposure.

Spatio-temporal Heterogeneity of Factors Influencing Transportation Carbon Emissions in Provinces Along the Belt and Road

The administrative units of 17 provinces （autonomous regions and municipalities directly under the Central Government） along the "Belt and Road" were selected as basic spatial units to calculate the provincial traffic carbon emissions along the "Belt and Road" from 2000 to 2021. On the basis of analyzing the spatial and temporal characteristics of traffic carbon emissions by using the spatial autocorrelation method, the spatial and temporal heterogeneity of influencing factors of traffic carbon emissions was explored by combining a fixed-effect regression model and geographic detector. The results show that： ① The provincial traffic carbon emissions along the "Belt and Road" had significant spatial positive correlation, and the overall trend was upward. Additionally, the cluster evolution of high and low values of traffic carbon emissions presented the characteristics of polarization in space. The high value cluster area was mainly distributed in the open leading area, and the low value cluster area was mainly distributed in the core area of the silk road. ② Opening-up level and vehicle ownership were the positive driving factors of carbon emissions from transportation, whereas energy intensity, transportation structure, industry development scale, and government intervention were the negative driving factors. ③ Energy intensity and transportation structure were the main driving factors for the spatial variation of transportation carbon emissions, and most of them would produce nonlinear enhancement when they were spatially superimposed with other factors, that is, there was strong synergy among driving factors. The results showed that the provincial traffic carbon emissions along the "Belt and Road" were affected by the surrounding areas, the influence degree was increasing, and there was synergy between the key driving factors of traffic carbon emissions. Therefore, it is suggested that the provinces along the "Belt and Road" should fully consider the spatial and temporal heterogeneity of traffic carbon emission influencing factors and formulate differentiated traffic carbon emission reduction policies.

Effects of route guidance strategies on traffic emissions in urban traffic networks

Urban traffic emissions have significant environmental and health implications. Diverging from traditional research that primarily aims to improve traffic flow and efficiency, this study specifically focuses on the environmental impact on traffic emissions, conducting a comprehensive analysis within the Manhattan urban network through four route guidance strategies. The performance of these strategies is examined across various vehicle densities, and their impact on four traffic pollutant emissions (Carbon-dioxide, Nitrogen Oxides, Volatile Organic Compounds and Particulate Matter) is assessed. Moreover, our innovative approach analyzes emissions from the perspectives of both travel distance and trip frequency, placing special emphasis on trip frequency to provide practical insights with high real-world applicability. The results highlight the potential and limitation of the Congestion Coefficient Strategy. Under equal travel demands, the Congestion Coefficient Strategy showed promise in reducing carbon emissions. However, at lower vehicle densities, it led to a significant increase in emissions. This revelation pointed to the need for modifications to the strategy when applied in scenarios with lower traffic density. Recognizing this limitation, we introduced a modified strategy that achieved remarkable reductions in emissions across diverse vehicle densities, effectively overcoming the challenges posed by the original Congestion Coefficient Strategy. These findings offer valuable insights for policymakers and transportation planners in selecting optimal route guidance strategies to reduce pollutant emissions. Future studies will explore the efficacy of these strategies in road networks characterized by different topological configurations.

Pinus eldarica (L.) bark as urban atmospheric trace element pollution bioindicator: pollution status, spatial variations, and quantitative source apportionment based on positive matrix factorization receptor model.

In this study, a total of 180 Pinus eldarica bark samples were collected from different regions of Hamedan megacity, Iran, in 2023, and contents of Cd, Cr, Cu, Mn, Ni, Pb, and Zn in the samples were determined using ICP-OES. The results illustrated that the average contents of all the analyzed elements were greater than those in the background contents, which presumably demonstrated anthropogenic sources of these potentially toxic elements (PTEs). The greatest concentrations of the analyzed PTEs for different functional areas were observed in specimens collected from commercial or industrial areas, indicating the impact of human entries. The I-geo values were in the range of "unpolluted to moderately polluted" to "moderately to heavily polluted", PI showed "moderate to very high pollution", and PLI reflected high to very high pollution levels for the whole study area. Additionally, the cumulative mean value of ecological risk (RI) was found to be 152, demonstrating moderate ecological risk across the study area. The results of positive matrix factorization (PMF) showed that the PTE contamination in the air of Hamedan could mainly have an anthropogenic origin (82.7%) and that the traffic emissions as the primary pollution source (33.6%) make the highest contribution to the PTE pollution and ecological risks in the study area. In residential areas, demolition and construction activities could be considered the main sources of PTEs, while in commercial and industrial areas traffic emissions and industrial emissions, could be regarded as the main sources of such pollution, respectively. In conclusion, this study provides a useful approach to identifying the sources and contributions of the toxic elements in different functional areas and can inform future endeavors that aim at managing and controlling metal element pollution.

Optical characteristics of brown carbon in the atmospheric particulate matter of Dhaka, Bangladesh: Analysis of solvent effects and chromophore identification

The prevalence of brown carbon (BrC) in the atmosphere has experienced a notable upsurge owing to human activities of anthropogenic origin. This study aims to examine the optical characteristics of BrC in both deionized (DI) water and organic solvents (OS), alongside the identification of BrC chromophores within the ambient atmosphere of Dhaka, Bangladesh. Particulate matter (PM) samples were collected on quartz filters using a low-volume sampler from December 2021 to May 2022 at Mukarram Hussain Khundker Bhaban, University of Dhaka. The concentration of BrC was measured using soot analyzer, optical properties of BrC were determined using UV–Vis spectrometer, and BrC chromophores were identified with GC-MS. Average concentration of BrC was 19.13 ± 5.71 μgm−3. The average of absorption coefficient (babs_365), mass absorption efficiency (MAE), absorption angstrom exponent (AAE), and refractive index (kabs_365) of BrC_DI have been observed to be 38.75 ± 21.90 Mm−1, 2.16 ± 1.42 m2 g-1, 1.51 ± 0.08, 0.06 ± 0.04, respectively. The absorption coefficient and MAE of BrC_OS are 1.3 and 1.36 times, respectively higher than that of BrC_DI. Thirty chromophores of BrC have been identified, predominantly consisting of oxygenated compounds. Derivatives of Bisphenol A (C27H44O2Si2) were detected in all samples of oxygenated compounds, primarily originating from the combustion of plastic and the incineration of e-waste. Additionally, compounds containing nitrogen and sulfur, such as C14H26N2O, C31H55N, and C31H49NO3S, were identified, largely attributed to biomass combustion and traffic emissions. These chromophores play a significant role in the absorption of solar radiation, thus influencing atmospheric photochemistry.