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The emissions inventory for non-road mobile machinery (NRMM) in Korea relies on laboratory engine tests, which do not accurately reflect the real-world emissions from construction machinery. Hence, standardized real-world test conditions suitable for the Korean environment were first designed based on the manufacturer's testing methods and previous research. Next, using portable emissions measurement systems (PEMS), data on exhaust emissions and load factor (LF) were collected and analyzed during real-world tests on three types of construction machinery (excavators, loaders, and forklifts) with high registration rates and emissions in Korean environment. The improved LFs, which reflect real-world tests, were significantly lower than the existing LF value (0.48), with values of 0.38-0.5 for excavators, 0.3-0.44 for loaders and 0.26 for forklifts. The emission factors (EFs) were higher than those currently used in Korea's emissions inventory, namely, the Clean Air Policy Support System (CAPSS). Based on the results, emissions were calculated and compared using an emission calculation formula. The relationship between LFs and EFs was also investigated to address the limitations of previous studies that focused solely on EF measurements. The combined improvements in EFs + LFs can lead to slightly higher emissions inventories. The improved LFs and EFs based on the results of real-world tests reported herein can enhance the accuracy of estimating emissions from construction machinery in Korea., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Chinese diesel trucks are the main contributors to NO x and particulate matter (PM) vehicle emissions. An increase in diesel trucks could aggravate air pollution and damage human health. The Chinese government has recently implemented a series of emission control technologies and measures for air quality improvement. This paper summarizes recent control technologies and measures for diesel truck emissions in China and introduces the comprehensive application of control technologies and measures in Beijing-Tianjin-Hebei and surrounding regions. Remote online monitoring technology has been adopted according to the China VI standard for heavy-duty diesel trucks, and control measures such as transportation structure adjustment and heavy pollution enterprise classification control continue to support the battle action plan for pollution control. Perspectives and suggestions are provided for promoting pollution control and supervision of diesel truck emissions: adhere to the concept of overall management and control, vigorously promote the application of systematic and technological means in emission monitoring, continuously facilitate cargo transportation structure adjustment and promote new energy freight vehicles. This paper aims to accelerate the implementation of control technologies and measures throughout China. China is endeavouring to control diesel truck exhaust pollution. China is willing to cooperate with the world to protect the global ecological environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Vehicle emissions are recognized as a primary source of particle-phase polycyclic aromatic hydrocarbons (PAHs), significant contributors to the hazardous properties of PM 2.5 . This study investigates the profiles of PAHs through measurements conducted in a tunnel and an urban roadside environment in 2020. We quantified real-world vehicle emission factors for mixed fleets in the Zhongshu tunnel in Guizhou, southwest China, and found that the total PAHs had an emission factor of 8.15 μg veh -1 km -1 , with higher factors observed for high-ring PAHs. Additionally, we analyzed concentrations of 15 PAHs at a roadside environment in Hefei, southern China, with an average concentration of 23.81 ng/m 3 . PAHs with 4, 5, and 6 rings comprised 80% of total PAHs at the roadside and 87% in the tunnel. Gasoline emissions were the predominant source in both the tunnel and roadside environments, supplemented by non-tailpipe emissions, catering, domestic cooking, and asphalt from road surfaces. Notably, while the total toxicity equivalent concentration of Benzo[a]pyrene (BaP) significantly exceeded the World Health Organization (WHO) guidelines of 1 ng/m 3 , the presence of additional compounds such as Dibenzo[a,h]anthracene (DahA) markedly increased the toxicological impact of PM 2.5 from vehicle emissions. Therefore, it is essential to implement targeted pollution control strategies in central urban areas that address not only the overall concentration of PAHs but also their specific toxic contributions Continuous monitoring and assessment of PAHs in the urban environment are indispensable for effectively reducing their health impacts., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The effects of air pollution on human and animal health, and on the functioning of terrestrial ecosystems, are wide-ranging. This potentially includes the disruption of valuable services provided by flying insects (e.g. pollination and biological control). However, quantifying the extent of this disruption requires a clearer understanding of insect community responses at field-scale. By elevating diesel exhaust and ozone (O 3 ) pollutants, individually and in combination, over two summers, we investigated the field-scale effects of air pollution on the abundance and diversity of flying insects from pan traps. We quantified which groups of insects were more at risk of air pollution-mediated decline and whether responses to air pollution were influenced by the presence of flowering plants. In addition, a common pest of Brassicaceae, the large cabbage white butterfly (Pieris brassicae L.) was used to investigate the effects on oviposition success of the two interacting air pollutants. Air pollution had the most detrimental effects on pollinators and parasitoids, compared with other insect groups, lowering their abundance by up to 48 % and 32 %, respectively. The adverse effects of O 3 and diesel exhaust on pollinators occurred only when flowers were available, indicating the relative importance of floral odors compared with visual cues. Air pollutants resulted in either increased insect herbivore abundance or had no effect, potentially increasing the threat air pollution poses to food security. However, both pollutants resulted in decreased oviposition by cabbage white butterflies, which, if demonstrated to be a more ubiquitous phenomenon, may result in reduced larval pest damage. Quantifying the relative changes in composition and abundance among feeding guilds is valuable for predicting the effects of air pollution on insect communities. Of the groups identified, pollinators are likely to be at the greatest risk of air pollution-mediated decline due to their use of floral odour cues for foraging., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Vehicle emissions are a major source of greenhouse gases globally. Dual selective catalytic reduction (SCR), an advanced version of single SCR, is crucial under stricter nitrogen oxide (NO x ) emission standards for heavy-duty diesel vehicles (HDDVs). However, the emission characteristics of nitrous oxide (N 2 O), a byproduct of SCR and a potent greenhouse gas, remain unclear. This study investigates the N 2 O emissions from HDDVs equipped with single or dual SCR systems using heavy-duty chassis dynamometers under various ambient temperatures, altitudes, and loading masses. The results showed that the brake-specific emissions (EF b ) of N 2 O from HDDVs with single and dual SCRs were 76.28-269.65 mg/kWh and 147.50-170.22 mg/kWh, respectively. Notably, the dual SCR-equipped HDDV emitted 6-22 times more N 2 O than NO x under all tested conditions. As ambient temperature increased from -10 °C to 25 °C and from 25 °C to 40 °C, the average distance-based emission factors (EF d ) of N 2 O for the single SCR-equipped HDDV increased by 87.73% and 48.26%, respectively. However, the variation was not significant for the dual SCR-equipped HDDV. Under half- and full-load conditions, the average EF d of N 2 O for the single SCR-equipped HDDV increased by 47.57% and 110.92%, respectively, compared to those without loading. Similarly, N 2 O emissions for dual SCR-equipped HDDV increased by 41.40% and 65.37% under the same loading variations. As altitude increased from 0 m to 3000 m, the average EF d of N 2 O for the single SCR-equipped HDDV decreased by 64.31%. Additionally, N 2 O emissions were significantly affected by SCR temperature, engine power, and nitric oxide (NO)/nitrogen dioxide (NO 2 ) ratio. These findings are crucial for setting future greenhouse gas limits of HDDVs and informing carbon reduction strategies., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study uses mobile monitoring to gain a better understanding of particulate matter (PM) sources in two areas of Central and Outer London, UK. We find that, unlike emissions of nitrogen oxides (NO + NO 2 = NO x ), which are elevated in Central London due to the high number of diesel vehicles and congestion, fine particulate matter (PM 2.5 ) emissions are well-controlled. This finding provides evidence for the effectiveness of vehicle particulate filters, supporting the view that their widespread adoption has mitigated PM 2.5 emissions, even in the highly dieselized area of Central London. However, mobile monitoring also reveals infrequent elevated PM 2.5 concentrations caused by malfunctioning vehicles. These events were confirmed through simultaneous measurements of PM 2.5 and sulfur dioxide (SO 2 ), the latter being a strong tracer of engine lubricant combustion. A single event from a gasoline car, representing just 0.15% of the driving distance in Outer London, was responsible for 7.4% of the ΔPM 2.5 concentration above background levels, highlighting the ongoing importance of addressing high-emission vehicles. In a novel application of mobile monitoring, we demonstrate the ability to identify and quantify non-vehicular sources of PM. Among the sources unambiguously identified are construction activities, which result in elevated concentrations of coarse particulate matter (PM coarse = PM 10 - PM 2.5 ). The mobile measurements clearly highlight the spatial extent of the influence of such sources, which would otherwise be difficult to determine. Furthermore, these sources are shown to be weather-dependent, with PM coarse concentrations reduced by 62.1% during wet conditions compared to dry ones.

Traffic-related air pollution is a major concern for perinatal health. Determining causal associations, however, is difficult because high-traffic areas tend to correspond with lower socioeconomic neighborhoods and other environmental exposures. To overcome confounding, we compared pregnant individuals living downwind and upwind of the same high-traffic road. We leveraged vital statistics data for Texas from 2007 to 2016 (n = 3 570 272 births) and computed hourly wind estimates for residential addresses within 500 m of high-traffic roads (ie, annual average daily traffic >25 000 vehicles) (10.9% of births). We matched pregnant individuals predominantly upwind with pregnant neighbors downwind of the same road segment (n = 37 631 pairs). Living downwind was associated with a decrease of 11.6 g (95% CI, -18.01 to -5.21) in term birth weight. No associations were observed with low term birth weight, preterm birth, or very preterm birth. In distance-stratified models, living downwind within 50 m was associated with a decrease of 36.3 g (95% CI, -67.74 to -4.93) in term birth weight and living 51-100 m downwind was associated with an odds ratio of 3.68 (95% CI, 1.71-7.90) for very preterm birth. These results suggest traffic air pollution is associated with adverse birth outcomes, with steep distance decay gradients around major roads. This article is part of a Special Collection on Environmental Epidemiology., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.)

Background: Evidence suggests that long-term exposure to air pollution may increase the risk of dementia and related cognitive outcomes. A major source of air pollution is automotive traffic, which is modifiable by technological and regulatory interventions., Objectives: We examined associations of four traffic-related air pollutants with rates of cognitive decline in a cohort of older adults., Methods: We analyzed data from the Chicago Health and Aging Project (CHAP), a longitudinal (1993-2012) community-based cohort study of older adults that included repeated assessments of participants' cognitive performance. Leveraging previously developed air pollution models, we predicted participant-level exposures to the tailpipe pollutants oxides of nitrogen ( NO X ) and nitrogen dioxide ( NO 2 ), plus the nontailpipe pollutants copper and zinc found in coarse particulate matter [PM with aerodynamic diameter 2.5 μ m to 10 μ m ( PM 2.5 - 10 , Cu ) and PM 2.5 - 10 , Zn , respectively], over the 3 y prior to each participant's baseline assessment. Using generalized estimating equations, we estimated covariate-adjusted associations of each pollutant with rates of cognitive decline. We probed the robustness of our results via several sensitivity analyses, including alterations to the length of the exposure assessment window and exploring the influence of pre- and post-baseline selection bias., Results: Using data from 6,061 participants, estimated associations of these pollutant exposures with cognitive decline were largely inconsistent with large adverse effects. For example, a standard deviation ( 5.8  ppb ) increment in NO X corresponded to a slightly slower rate of cognitive decline [e.g., mean difference in change in global score, 0.010 standard unit/5 y, 95% confidence interval (CI): -0 .016 , 0.036]. The results of most of our sensitivity analyses were in generally similar to those of our main analyses, but our prebaseline selection bias results suggest that our analytic results may have been influenced by differential survivorship into our study sample., Discussion: In this large prospective cohort study, we did not observe compelling evidence that long-term TRAP exposure is associated with cognitive decline. https://doi.org/10.1289/EHP14585.

There is a body of evidence that ultrafine particles (UFP, those with diameters ≤ 100 nm) might have significant impacts on health. Accordingly, identifying sources of UFP is essential to develop abatement policies. This study focuses on urban Europe, and aims at identifying sources and quantifying their contributions to particle number size distribution (PNSD) using receptor modelling (Positive Matrix Factorization, PMF), and evaluating long-term trends of these source contributions using the non-parametric Theil-Sen's method. Datasets evaluated include 14 urban background (UB), 5 traffic (TR), 4 suburban background (SUB), and 1 regional background (RB) sites, covering 18 European and 1 USA cities, over the period, when available, from 2009 to 2019. Ten factors were identified (4 road traffic factors, photonucleation, urban background, domestic heating, 2 regional factors and long-distance transport), with road traffic being the primary contributor at all UB and TR sites (56-95 %), and photonucleation being also significant in many cities. The trends analyses showed a notable decrease in traffic-related UFP ambient concentrations, with statistically significant decreasing trends for the total traffic-related factors of -5.40 and -2.15 % yr -1 for the TR and UB sites, respectively. This abatement is most probably due to the implementation of European emissions standards, particularly after the introduction of diesel particle filters (DPFs) in 2011. However, DPFs do not retain nucleated particles generated during the dilution of diesel exhaust semi-volatile organic compounds (SVOCs). Trends in photonucleation were more diverse, influenced by a reduction in the condensation sink potential facilitating new particle formation (NPF) or by a decrease in the emissions of UFP precursors. The decrease of primary PM emissions and precursors of UFP also contributed to the reduction of urban and regional background sources., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Initial success has been achieved in Hong Kong in controlling primary air pollutants, but ambient ozone levels kept increasing during the past three decades. Volatile organic compounds (VOCs) are important for mitigating ozone pollution as its major precursors. This study analyzed VOC characteristics of roadside, suburban, and rural sites in Hong Kong to investigate their compositions, concentrations, and source contributions. Here we show that the TVOC concentrations were 23.05 ± 13.24, 12.68 ± 15.36, and 5.16 ± 5.48 ppbv for roadside, suburban, and rural sites between May 2015 to June 2019, respectively. By using Positive Matrix Factorization (PMF) model, six sources were identified at the roadside site over five years: Liquefied petroleum gas (LPG) usage (33%-46%), gasoline evaporation (8%-31%), aged air mass (11%-28%), gasoline exhaust (5%-16%), diesel exhaust (2%-16%) and fuel filling (75-9%). Similarly, six sources were distinguished at the suburban site, including LPG usage (30%-33%), solvent usage (20%-26%), diesel exhaust (14%-26%), gasoline evaporation (8%-16%), aged air mass (4%-11%), and biogenic emissions (2%-5%). At the rural site, four sources were identified, including aged air mass (33%-51%), solvent usage (25%-30%), vehicular emissions (11%-28%), and biogenic emissions (6%-12%). The analysis further revealed that fuel filling and LPG usage were the primary contributors to OFP and OH reactivity at the roadside site, while solvent usage and biogenic emissions accounted for almost half of OFP and OH reactivity at the suburban and rural sites, respectively. These findings highlight the importance of identifying and characterizing VOC sources at different sites to help policymakers develop targeted measures for pollution mitigation in specific areas., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

As a significant city in the Yangtze River Delta regions, Hefei has experienced rapid changes in the sources of air pollution due to its high-speed economic development and urban expansion. However, there has been limited research in recent years on the spatial-temporal distribution and emission of its atmospheric pollutants. To address this, this study conducted mobile observations of urban roads using the Mobile-DOAS instrument from June 2021 to May 2022. The monitoring results exhibit a favourable consistent with TROPOMI satellite data and ground monitoring station data. Temporally, there were pronounced seasonal variations in air pollutants. Spatially, high concentration of HCHO and NO 2 were closely associated with traffic congestion on roadways, while heightened SO 2 levels were attributed to winter heating and industrial emissions. The study also revealed that with the implementation of road policies, the average vehicle speed increased by 95.4%, while the NO concentration decreased by 54.4%. In the estimation of urban NO x emission flux, it was observed that in temporal terms, compared with inventory data, the emissions calculated via mobile measurements exhibited more distinct seasonal patterns, with the highest emission rate of 349 g/sec in winter and the lowest of 142 g/sec in summer. In spatial terms, the significant difference in emissions between the inner and outer ring roads also suggests the presence of the city's primary NO x emission sources in the area between these two rings. This study offers data support for formulating the next phase of air pollution control measures in urban areas., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Civil aviation is one of the industries facing the greatest challenge in reaching carbon neutrality by the middle of this century, and this sector also contributes to adverse impacts on the regional air quality and human health. China exhibits the second highest air passenger turnover worldwide. Our understanding of civil aviation emissions must be urgently enhanced, and the mitigation potential should be explored. In this study, on the basis of real domestic flight information for 2019, we built a greenhouse gas and air pollution emission inventory for the civil aviation sector in China with the fuel flow method based on the cruise and other phases. We thoroughly analyzed emissions by region, aircraft and engine types, and aircraft age, based on which we designed four measures to evaluate the abatement potential. We found that the hydrocarbon (HC), CO, NO x , SO 2 , particulate matter (PM) and CO 2 emissions in 2019 reached 79.9 kt (95% CI [51.6-114.5]), 176.3 kt (95% CI [114.5-248.2]), 304.2 kt (95% CI [203.4-420.7]), 23.2 kt (95% CI [14.2-33.7]), 1.0 kt (95% CI [0.61-1.44]) and 87.0 Mt (95% CI [57.4-119.6]), respectively. The cruise phase was the major emission phase, accounting for 67%-87% of the total pollutant emissions. If four measures were jointly implemented, the HC, CO, NO x , SO 2 , PM and CO 2 emissions could be reduced by 61%, 54%, 55%, 45%, 32% and 38%, respectively. Utilizing lower-emission aircraft and switching travel modes could substantially reduce civil aviation emissions in China., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The emission of heavy-duty vehicles has raised great concerns worldwide. The complex working and loading conditions, which may differ a lot from PEMS tests, raised new challenges to the supervision and control of emissions, especially during real-world applications. On-board diagnostics (OBD) technology with data exchange enabled and strengthened the monitoring of emissions from a large number of heavy-duty diesel vehicles. This paper presents an analysis of the OBD data collected from more than 800 city and highway heavy-duty vehicles in China using remote OBD data terminals. Real-world NO x and CO 2 emissions of China-6 heavy-duty vehicles have been examined. The results showed that city heavy-duty vehicles had higher NO x emission levels, which was mostly due to longer time of low SCR temperatures below 180°C. The application of novel methods based on 3B-MAW also found that heavy-duty diesel vehicles tended to have high NO x emissions at idle. Also, little difference had been found in work-based CO 2 emissions, and this may be due to no major difference were found in occupancies of hot running., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

Brazil's significantly large fleet of ethanol-powered vehicles makes it unique with regard to mobile source emissions. An accurate estimation of emission rates is best obtained from studies reflecting real-world vehicular conditions, such as tunnel investigations. Although laboratory-based estimations are standardized, they may not reflect reality. This study evaluates two methods for estimating emission factors that arise from the circulating fleet of vehicles that travel through the Rebouças Tunnel in Rio de Janeiro. The two monitoring points were located in the L1 gallery of the tunnel. Thirteen sampling campaigns took place between 2017 and 2020. The Pierson correlation method yielded emission rates for total aldehydes of 22.1 ± 6.9 mg km -1 , while the fuel consumption testing method resulted in rates of 17.7 ± 7.8 mg km -1 . Acetaldehyde predominated in both methods, as it is a major constituent of the exhaust emissions using ethanol as fuel, which is one of the major component fuels in the Brazilian fuel matrix. Benzene emerged as the most abundant BTEX compound, with 3.7 ± 3.2 mg km -1 , when the Pierson method was used, and 2.5 ± 0.3 mg km -1 with the fuel consumption testing method. Naphthalene, which was mainly collected in the gas phase, showed rates of 1.4 ± 1.0 mg km -1 (Pierson) and 0.9 ± 0.4 mg km -1 (fuel consumption). Despite these methodological variations, our findings converge, which suggests that the choice of method should depend on available resources. The Pierson method, which requires a vehicle counting method for traffic flow, obviates the need for CO and CO 2 concentration measurements, that are essential for determining fuel consumption., Competing Interests: Declarations. Ethics approval: All authors have read, understood, and have complied as applicable with the statement on “Ethical responsibilities of Authors” as found in the Instructions for Authors. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Air pollution from transport hubs is a recognised health concern for local urban inhabitants. Within the domain of transport hubs, significant attention has been given to larger airport and port settings, however concerns have been raised about emissions from urban railway hubs, especially those with diesel trains. This paper presents an approach that adopts low-cost monitoring (LCM) for fixed site monitoring (FSM) to quantify and disaggregate PM 2.5 and NO 2 contributions from railway station and road traffic on air quality in the vicinity of railway station in Dublin, Ireland. The NO 2 sensor showed larger discrepancies than the PM 2.5 sensor when compared to the reference monitor. Machine learning models (XGBoost and Random Forest (RF) regression) were applied to calibrate the LCM devices, with the XGBoost model (NO 2, R 2  = 0.8 and RSME = 9.1 μg/m 3 & PM 2.5 , R 2  = 0.92 and RSME = 2.2 μg/m 3 ) deemed more appropriate than the RF model. Local wind conditions, pressure, PM 2.5 concentrations, and road traffic significantly impacted NO 2 model results, while raw PM 2.5 sensor readings greatly influenced the PM 2.5 model output. This highlights that the NO 2 sensor requires more input data for accurate calibration, unlike the PM 2.5 sensor. The monitoring results from the one-month monitoring campaign from May 25, 2023 to June 25, 2023 presented elevated NO 2 and PM 2.5 concentrations measured at the railway station, which translated to exceedances of the annual WHO limits (PM 2.5  = 5 μg/m 3 , NO 2  = 10 μg/m 3 ) by 1.6-1.8 and 3.2-5.2 times respectively at the study site. A subsequent data filtering technique based on wind orientation, revealed that the railway station was the main PM 2.5 source and road traffic was the main NO 2 source when winds come from the railway station. This study highlights the value of LCM devices alongside robust machine learning techniques to capture air quality in urban settings., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Shanmuga Priyan reports financial support was provided by Environmental Protection Agency. Yuxuan Guo reports financial support was provided by Environmental Protection Agency. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Assessing the emissions of heavy-duty diesel trucks (HDDTs) is crucial for managing air quality in megacities, especially concerning nitrogen oxides (NO X ) and black carbon (BC). This study employed mobile plume chasing to monitor the real-world emissions of over 7778 HDDTs in Shenzhen. The findings indicate that the real-world NO X emission factors (EF) of China IV trucks did not differ significantly from those of China III, whereas China V and VI vehicles demonstrated fleet-averaged reductions of 27% and 85%, respectively. For China V, a significant decrease in the NO X EF for HDDTs registered after 2017 was attributed to the installation of advanced aftertreatment systems, including diesel oxidation catalysts (DOC) and Diesel Particle Filters (DPF), along with selective catalytic reduction (SCR). These technologies led to an average reduction of 42% in NO X and 61% in BC emissions. Seasonal variations were pronounced, with winter (∼20 °C) NO X EF 40% higher than summer (∼35 °C) levels. Conversely, BC EF decreased by 26% in winter, indicating significant impacts of ambient temperature on emissions. Spatial analysis revealed that the average NO X EF of HDDTs on east freeways was 1.4 times higher than that on urban expressways, influenced by variations in the proportion of vehicle types segmented by usage. These findings offer a comprehensive perspective on HDDTs emissions, highlighting the importance of large-scale emission monitoring through plume chasing for precise and effective control of real-world HDDTs emissions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

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, PM 2.5 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 10 14 -10 15 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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Accurately estimating vehicle emissions is crucial for effective air quality management. As key data for emission inventory construction, emission factors (EFs) are influenced by vehicle usage characteristics and experience deterioration. Current deterioration models often employ single-factor approaches based on vehicle age or accumulated mileage, which fail to capture the effects of varying usage intensities within the same mileage or age intervals. This study addressed this limitation by developing a novel emission deterioration model that incorporates multi-dimensional usage characteristics and that utilizes a large-scale inspection and maintenance (I/M) dataset for light-duty gasoline vehicles (LDGVs). The modeling results reveal distinct deterioration patterns for different pollutants and highlight the synergistic effects of the usage duration and intensity: natural aging significantly impacts HC and NOx emissions, while CO emissions are more strongly affected by intensive use. Specifically, China V LDGVs that were driven 4 × 10 4  km/yr exhibited HC, CO, and NOx deterioration rates per mile that were approximately 4.1 % lower, 10.3 % higher, and 1.1 % higher, respectively, than those of vehicles driven 2 × 10 4  km/yr as the mileage increased from 5 × 10 4 km to 10 × 10 4 km. By leveraging timely emission data and explicitly accounting for usage intensity, this study corrected biases in local emission estimates by 5-85 % with respect to estimates from commonly used models. This framework enables the development of more effective control strategies and refinements to policy evaluations in megacities with I/M programs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

To evaluate the measurement accuracy of horizontal and vertical remote emission sensing (RES) equipment, a real-world dynamic test was carried out in Chengdu by using electric vehicles equipped with various concentrations of standard gases. In addition, a new Image-based Spectral Processing Algorithm (ISPA) for vertical remote sensing spectral data was developed to improve the measurement capability. The results showed that the ISPA provided a greater percentage of valid data and lower relative errors; thus, our new algorithm could more effectively analyze the spectral data to measure vehicle emission levels. The percentages of valid horizontal and vertical RES data were 71% and 84%, respectively. The mean relative errors of CO 2 , CO, HC and NO measured by the vertical RES were about 5%, 20%, 20% and 40%, respectively, and those of CO 2 , CO and NO measured by the horizontal RES were 3%, 13% and 15%, respectively. For the common vehicle emission concentration, the percentage of valid data for the two RES types increased with increasing gas concentration. As the vehicle speed increased, the relative errors of the horizontal RES equipment showed an increasing trend for the same concentration of gas. Furthermore, for the same speed segment, the relative errors of the horizontal RES equipment increased as the simulated emission concentration decreased. The vertical RES equipment did not exhibit a consistent trend in terms of changes. This study provides a data quality reference for further RES applications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: The current limit on NO 2 concentrations of 40 μg/m 3 , set by the European Union, has been regularly exceeded in Munich, Germany. This limit will likely be reduced towards the WHO recommended target of 10 μg/m3. Against this backdrop, the city implemented a selective diesel vehicle ban within the existing low-emission zone in February 2023, targeting Euro 4 and older diesel vehicles. Our study investigated the effect of Munich's selective diesel vehicle ban on NO 2 concentrations, focusing on the half-year period following its implementation., Methods: Our study utilized a synthetic control approach (primary analysis) and a controlled interrupted time series approach (secondary analysis). These quasi-experimental methodologies create a 'counterfactual' no-intervention scenario, enabling comparison between observed and counterfactual scenarios to estimate an intervention effect. We employed historical controls, using routine data from multiple monitoring stations located within and outside the low-emission zone for 2014 to 2022, and considered possible confounders., Results: NO 2 concentrations within Munich's low-emission zone showed overall declining trends from August 2014 to July 2023. Effects of the selective diesel vehicle ban were small and wide confidence intervals indicate large uncertainty in the magnitude and direction of the effect. At Landshuter Allee, the average intervention effect was -2.67 μg/m 3 (95 %-CI = [-12.72; 7.38]), at Stachus it was -2.74 μg/m 3 (95 %-CI = [-9.91; 4.42]), and at Lothstrasse it was -1.03 μg/m 3 (95 %-CI = [-7.75; 5.69]). The secondary analysis confirmed these findings, reinforcing uncertainty about the effect of the intervention., Conclusion: Our study suggests that Munich's selective diesel vehicle ban had a limited effect on lowering NO 2 concentrations. Possible explanations include the ban's focus on Euro 4 and older diesel vehicles, many exemptions to the selective ban, and unclear enforcement. This highlights that comprehensive approaches and ongoing, well-designed monitoring and evaluation are crucial for addressing urban air pollution and protecting public health., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: ER declares owning a Diesel Euro 4 vehicle. The other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

We assessed the oxidative potential (OP) of PM 2.5 ( n = 230) using dithiothreitol (DTT) assay to identify the major emission sources in Bhubaneswar (20.20°N, 85.80°E), one of the non-attainment cities under the National Clean Air Program, situated on the eastern coast of India. Continuous day and night PM 2.5 samples were collected during periods influenced by marine airmass (MAM; April-May 2019) as well as continental airmass (CAM; October 2019-December 2019). Volume normalized DTT (DDTv) activities were approximately two times higher during CAM compared to MAM periods. In contrast, mass normalized DTT activity (DDTm) showed insignificant variations between CAM and MAM periods. This might be due to particulate organic matter, which accounted for more than one-fifth of the PM 2.5 mass loading and remained surprisingly invariant during the study periods. Positive matrix factorization (PMF) identified secondary aerosols (MAM: 26% and CAM: 33%) as dominant contributors to PM 2.5 mass in both periods. OP, is, however, dominated by vehicular emissions (21%) as identified through multiple linear regression. Conditional Bivariate Probability Function (CBPF) analysis indicated that local sources were the primary drivers for the catalytic activity of PM 2.5 in the study region. Additionally, stagnant meteorological conditions, combined with the chemical aging of species during regional transport of pollutants, likely enhanced redox activity of PM 2.5 during the CAM period. The study highlights that increasing traffic congestion is primarily responsible for adverse health outcomes in the region. Therefore, it is important to regulate mobility and vehicular movement to mitigate the hazardous impact of PM 2.5 in Bhubaneswar.

Ultrafine particles (UFPs; PM 0.1 ) possess intensified health risk due to their smaller size and unique spatial variability. One of major emission sources for UFPs is vehicle exhaust, which varies based on the traffic composition in each type of roadside sector. The current challenge of epidemiological UFPs study is limited characterization ability due to expensive instruments. This study assessed the UFPs particle number concentrations (UFPs PNC) exposure dose for typical healthy adults and children at three different roadside sectors, including industrial roadside (IN), residential roadside (RS), and urban background (UB). Furthermore, this study also developed and utilized machine learning (ML) algorithms that could accurately characterize the UFPs exposure dose and explain the covariates effects on the model outputs, representing the intra-urban variability of UFPs between sectors. It was found that the average inhaled UFPs dose for healthy adults and children during off-peak season (warm period) were 1.71 ± 0.19 × 10 10 ; 1.28 ± 0.22 × 10 10 ; 1.09 ± 0.18 × 10 10 #/hour and 1.33 ± 0.15 × 10 10 ; 0.99 ± 0.17 × 10 10 ; 0.86 ± 0.14 × 10 10 #/hour at IN, RS, UB. Inhaled UFPs were mainly deposited in tracheobronchial (TB) respiratory fraction for adults (67.7%) and in alveoli (ALV) fraction for children (67.5%). Among three ML algorithms implemented in this study, XGBoost possessed the highest UFPs PNC exposure dose estimation performances with R 2  = 0.965; 0.959; 0.929 & RMSE = 0.79 × 10 8 ; 0.54 × 10 8 ; 0.15 × 10 5 #/hour at IN, RS, and UB which then followed by multiple linear regression (MLR), and random forest (RF). Furthermore, SHAP analysis from the XGBoost model has successfully pointed out the spatial variability of each roadside sector by quantifying the approximated contributions of covariates to the model's output. Findings in this study highlighted the potential use of ML models as an alternative for preliminary particle exposure source apportionment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Deterioration of air quality in Kuala Lumpur caused by mobile sources and traffic-related activities with interaction with climatic conditions and dispersion in the atmosphere. This study was focused on predicting the averaged 1-h concentration of particulate matter (PM 10 ) that was emitted from private cars in Kuala Lumpur by applying the air dispersion model American Meteorological Society (AMS)/United States Environmental Protection Agency (EPA) Regulatory Model (AERMOD) in 2014. The AERMOD model indicates that private cars in Kuala Lumpur recorded 1-h concentration of PM 10 below the Malaysian Ambient Air Quality Guidelines (RMAQG) in 2014. The highest concentration was 59.2 µg/m 3 in 2014 and mainly concentrated around the city center and highway networks. The highest concentrations are recorded in early morning and late at night, with the highest concentrations at 4 am and 2 am and 48.68 µg/m 3 and 38.42 µg/m 3 , respectively. Late night to early morning is identified as the dominant time interval for pollutant dispersion. The findings demonstrated that air quality had a significant impact on the 1-h concentration of PM 10 emitted from private cars in Kuala Lumpur., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Understanding the CO 2 emission characteristics and key mitigation pathways of intercity passenger transport is crucial for achieving sustainable development in the transport system. Using origin-destination data on travel between city pairs by various transportation modes, we employ the life cycle assessment (LCA) method to estimate route-level CO 2 emissions from intercity multimodal passenger transport corridors, considering infrastructure construction and vehicle operation phases. Subsequently, a sensitivity analysis is conducted to assess the impact of 39 parameters associated with the construction phase, operation phase, and transportation modes on CO 2 emissions from corridors. Trend analysis is employed to explore the future emission mitigation potential for the parameters that have the most significant impact on corridor emissions. Four intercity multimodal passenger corridors in China are selected as case studies. Results indicate that the CO 2 emissions per passenger-kilometer from these corridors exhibit an approximate negative linear relationship with corridor lengths. The proportion of construction-related CO 2 emission intensity of various intercity passenger transport modes varies significantly, ranging from 2.5 to 32.9%. In the medium term, effective emission-mitigation strategies should focus on decreasing private car gasoline consumption in three corridors under 200 km in length, as well as decreasing private car gasoline consumption and promoting clean electricity in the Xi'an-Yan'an corridor. In the long term, efforts should be placed on increasing electric private car share and promoting clean electricity. This study lays a crucial foundation for the refined management of CO 2 emissions from future intercity passenger transport., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Emerging evidence indicates an increasing prevalence of allergic rhinitis (AR), potentially linked to air quality. The aim of the present study was to assess the relationship between traffic-related air pollutants (TRAPs) and outpatient visits for AR. Daily outpatient data for AR, air pollutant concentrations, and meteorological data were collected from January 2018 to December 2020 in Dingxi, Longnan, and Tianshui. Utilizing a Quasi-Poisson distribution, a generalized additive model (GAM) was employed in conjunction with distributed lag non-linear models (DLNM) to explore the association and lag effects of TRAPs on AR outpatient visits across the three cities. Stratified analyses based on gender, age, and season were conducted. A total of 11 106 outpatient visits for AR were recorded in the three cities. For an increase of 10 μg m -3 in PM 2.5 , the effect estimates in Dingxi, Longnan, and Tianshui reached their maximum at lag04, lag06, and lag07, respectively, with relative risk (RR) values of 4.696 (95% CI: 1.890, 11.614), 2.842 (95% CI: 2.102, 4.922), and 1.102 (95% CI: 1.066, 1.140). For NO 2 , the highest associations were exhibited in Dingxi (RR = 1.262, 95% CI: 1.081, 1.473) at lag07, in Longnan (RR = 2.554, 95% CI: 2.100, 4.805) at lag06, and in Tianshui (RR = 1.158, 95% CI: 1.106, 1.213) at lag07. Meanwhile, the strongest effects observed for a 1 mg m -3 increase in CO were 2.786 (95% CI: 1.467, 5.291) for Dingxi at lag07, 1.502 (95% CI: 1.096, 2.059) for Longnan at lag05, and 1.385 (95% CI: 1.137, 1.686) for Tianshui at lag04. Adults aged 15-64 years appeared to be more susceptible to TRAPs, and the associations were stronger in the cold season. The results of the present study indicate that exposure to TRAPs was positively correlated with outpatient visits for AR.

One of the primary causes of urban atmospheric particulate matter, which is harmful to human health in addition to affecting air quality and atmospheric visibility, is road dust. This study used online monitoring equipment to examine the characteristics of road dust emissions, the effects of temperature, humidity, and wind speed on road dust, as well as the correlation between road and high-space particulate matter concentrations. A section of a real road in Jinhua City, South China, was chosen for the study. The findings demonstrate that the concentration of road dust particles has a very clear bimodal single-valley distribution throughout the day, peaking between 8:00 and 11:00 and 19:00 and 21:00 and troughing between 14:00 and 16:00. Throughout the year, there is a noticeable seasonal change in the concentration of road dust particles, with the highest concentration in the winter and the lowest in the summer. Simultaneously, it has been discovered that temperature and wind speed have the most effects on particle concentration. The concentration of road dust particles reduces with increasing temperature and wind speed. The particle concentrations of road particles and those from urban environmental monitoring stations have a strong correlation, although the trend in the former is not entirely consistent, and the changes in the former occur approximately 1 h after the changes in the latter., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Beijing, with the highest number of motor vehicles in China, significantly contributes to O 3 pollution through substantial NO x and VOC emissions in the on-road transportation sector. Understanding the unique impact of emissions from different vehicle types on O 3 levels is crucial for developing targeted strategies for O 3 pollution. This study applied the Community Multiscale Air Quality Modeling System (CMAQ) to comprehensively investigate the impacts of emissions from different vehicle types on O 3 levels in various regions of Beijing and to provide valuable insights into source contributions and formation processes. The results revealed that various vehicle types exhibited different spatial-temporal emission patterns, with medium-heavy duty trucks (HDT) and mini-light passenger vehicles (LDPV) identified as the primary contributors to NO x (36.1 %) and VOC (57.6 %) emissions. Using the Integrated Source Apportionment Method (ISAM) coupled in CMAQ, we found the total vehicle emissions contributed to over 20 % of daily maximum 8-h average O 3 (MDA8 O 3 ) concentration, ranked as the second largest contributor after regional transport. Contributions to O 3 formation from LDPV and medium-large passenger vehicles (MDPV) were 2.6-4.0 and 4.2-6.8 ppb and mainly concentrated in urban areas, while the contributions from mini-light duty trucks (LDT) and HDT were 3.5-4.8 and 3.7-6.2 ppb and mainly concentrated in suburban areas. Through scenario analysis that removed emissions from specific types of vehicles, we found removing LDPV emissions led to decreases in daytime O 3 concentration by 0.3-3.8 ppb. In contrast, removing MDPV emissions led to notable O 3 increases by 4.0-11.8 ppb at rush hours. Removing LDT and HDT emissions resulted in 0.6-8.0 ppb increases in nocturnal O 3 concentrations while 0.8-2.0 ppb decreases during the afternoon. This research highlights the necessity of tailoring control strategies for different vehicle types to effectively reduce O 3 levels in Beijing and provides useful information for decision-makers to formulate effective measures of vehicle management in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Traffic-related air pollution (TRAP) is a major contributor to urban pollution and varies sharply at the street level, posing a challenge for air quality modeling. Traditional land use regression models combined with data from fixed monitoring stations may be unable to predict and characterize fine-scale TRAP, especially in complex urban environments influenced by various features. This study aims to estimate fine-scale (50 m) concentrations of nitrogen oxides (NO and NO₂) in Hong Kong using a deep learning (DL) structured model., Methods: We collected data from mobile air quality sensors on buses and crowd-sourced Google real-time traffic status as a proxy for real-time traffic emissions. Our DL model was compared with existing machine learning models to assess performance improvements. Using an interpretable machine learning method, we hierarchically evaluated the global, local, and interaction effects for different features., Results: Our DL model outperformed existing machine learning models, achieving R 2 values of 0.72 for NO and 0.69 for NO₂. The incorporation of traffic status as a key predictor improved model performance by 9% to 17%. The interpretable machine learning method revealed the importance of traffic-related features and their pairwise interactions., Conclusion: The results indicate that traffic-related features significantly contribute to TRAP and provide insights and guidance for urban planning. By incorporating crowd-sourced Google traffic information, we assessed traffic abatement scenarios that could inform targeted strategies for improving urban air quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Polycyclic aromatic hydrocarbons (PAHs) are air pollutants generated mainly by fuel combustion, industry, and other anthropogenic sources. The level of these pollutants can be assessed by employing biomonitors, a cost-effective and less contaminating alternative than conventional methods. In the present study, we aimed to investigate whether spiders inhabiting areas around a major city like Córdoba, Argentina, adsorb and retain PAHs in their exoskeletons. Additionally, we aimed to determine if spiders' life traits influence their capacity to accumulate PAHs and explore potential relationships between PAH levels and the types of roads where they were collected. Specimens of a funnel-shaped web spider (Aglaoctenus lagotis) and an orb-weaver (Metepeira spp.) were collected from roadsides. Roads were classified into four categories based on their traffic intensity. Using high-performance liquid chromatography (HPLC), we identified 15 different PAHs. Both species exhibited varying concentrations of PAHs, although Metepeira spp. showed 15-18 times higher PAH levels compared to A. lagotis. Moreover, A. lagotis individuals living alongside highways accumulated up to six times more PAHs compared to those along other road types. These findings suggest that spiders' life traits may influence pollutant concentrations. Our study demonstrates that spiders near roads are exposed to and accumulate PAHs on their exoskeletons, likely sourced from petrogenic vehicular emissions, highlighting their value as biomonitors and emphasizing the need for mitigation measures to address air pollutants emitted from mobile sources., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Emissions from road traffic and residential heating contribute to urban air pollution. Advances in emission reduction technologies may alter the composition of emissions and affect their fate during atmospheric processing. Here, emissions of a gasoline car and a wood stove, both equipped with modern emission mitigation technology, were photochemically aged in an oxidation flow reactor to the equivalent of one to five days of photochemical aging. Fresh and aged exhausts were analyzed by ultrahigh resolution mass spectrometry. The gasoline car equipped with a three-way catalyst and a gasoline particle filter emitted minor primary fine particulate matter (PM2.5), but aging led to formation of particulate low-volatile, oxygenated and highly nitrogen-containing compounds, formed from volatile organic compounds (VOCs) and gases incl. NO x , SO 2 , and NH 3 . Reduction of the particle concentration was also observed for the application of an electrostatic precipitator with residential wood combustion but with no significant effect on the chemical composition of PM2.5. Comparing the effect of short and medium photochemical exposures on PM2.5 of both emission sources indicates a similar trend for formation of new organic compounds with increased carbon oxidation state and nitrogen content. The overall bulk compositions of the studied emission exhausts became more similar by aging, with many newly formed elemental compositions being shared. However, the presence of particulate matter in wood combustion results in differences in the molecular properties of secondary particles, as some compounds were preserved during aging.

Ammonia (NH 3 ) plays an important role in the formation of atmospheric particulate matter, but the contribution of traffic-related emissions remains unclear, particularly in megacities with a large number of vehicles. Taking the opportunity of the stringent COVID-19 lockdowns implemented in Beijing and Shanghai in 2022, this study aims to estimate the traffic-related NH 3 emissions in these two megacities based on satellite observations. Differences between urban and suburban areas during the lockdown and non-lockdown periods are compared. It was found that despite different dominating sources, the overall NH 3 concentrations in urban and suburban areas were at a similar level, and the lockdown resulted in a more prominent decrease in urban areas, where traffic activities were most heavily affected. The traffic-related contribution to the total emission was estimated to be ∼30% in megacities, and ∼40% in urban areas, which are about 2-10 times higher than that in previous studies. The findings indicate that the traffic-related NH 3 emissions have been significantly underestimated in previous studies and may play a more critical role in the formation of air pollution in megacities, especially in winter, when agricultural emissions are relatively low. This study highlights the importance of traffic-related NH 3 emissions in Chinese megacities and the need to reassess the emissions and their impacts on air quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In near-road neighborhoods, residents are more frequently exposed to traffic-related air pollution (TRAP), and they are increasingly aware of pollution levels. Given this consideration, this study adopted portable air pollutant sensors to conduct a mobile monitoring campaign in two near-road neighborhoods, one in an urban area and one in a suburban area of Shanghai, China. The campaign characterized spatiotemporal distributions of fine particulate matter (PM 2.5 ) and black carbon (BC) to help identify appropriate mitigation measures in these near-road micro-environments. The study identified higher mean TRAP concentrations (up to 4.7-fold and 1.7-fold higher for PM 2.5 and BC, respectively), lower spatial variability, and a stronger inter-pollutant correlation in winter compared to summer. The temporal variations of TRAP between peak hour and off-peak hour were also investigated. It was identified that district-level PM 2.5 increments occurred from off-peak to peak hours, with BC concentrations attributed more to traffic emissions. In addition, the spatiotemporal distribution of TRAP inside neighborhoods revealed that PM 2.5 concentrations presented great temporal variability but almost remained invariant in space, while the BC concentrations showed notable spatiotemporal variability. These findings provide valuable insights into the unique spatiotemporal distributions of TRAP in different near-road neighborhoods, highlighting the important role of hyperlocal monitoring in urban micro-environments to support tailored designing and implementing appropriate mitigation measures., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This study investigates real-world carbon dioxides (CO 2 ) and nitrogen oxides (NO x ) emissions from diesel (Bharat Stage-IV (BS-IV)) and petrol/gasoline (BS-IV and BS-VI) cars in Indian driving conditions using a portable emission measurement system (PEMS). The paired sample t-test revealed a significant difference ( p < 0.05) in NO x and CO 2 emissions among the three types of cars, except for CO 2 emissions ( p > 0.05) between BS-IV petrol and BS-VI petrol cars. The highest NO x emission rates were observed in all car types during acceleration (> 1 m/s 2 ) and deceleration (- 2 m/s 2 ). CO 2 emission rates were also high during acceleration (> 1 m/s 2 ) for all car types. At low speeds (around 20 kmph), all car types had low emissions of CO 2 and NO x , with acceleration and deceleration rates ranging from - 0.5 to 0.5 m/s 2 . BS-IV diesel cars emit significantly higher NO x emissions compared to petrol cars, especially at vehicle-specific power (VSP) bin 0 (deceleration to idling mode) and during VSP bin 7 (acceleration mode). BS-IV diesel cars emit 228% and 530% higher NO x emissions than BS-IV and BS-VI petrol cars at VSP bins 0 and 7, respectively. CO 2 emissions from BS-VI petrol cars were 10% lower than those from BS-IV petrol cars across all VSP bins, indicating moderate reductions. Furthermore, diesel cars emit 140% less CO 2 emissions than petrol cars across various VSP bins. The findings highlight the need for cleaner technologies and responsible driving practices to address vehicular emission concerns., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This study compares different powertrains of sport utility vehicles (SUVs) with respect to ambient temperature and energy mix in Slovakia using the well-to-wheel (WTW) Life Cycle Assessment (LCA) method. Battery electric vehicles (BEV), plug-in hybrid electric vehicles (PHEV), and petrol and diesel vehicles were assessed and compared. The WTW study was conducted in SimaPro software assessing electricity/petrol/diesel production, transport, and use (energy conversion in the vehicle), with impact categories being climate change, particulates, NO x emissions, ionizing radiation, and fossil resource scarcity depending on the season (summer and winter). The results indicate that for Slovak conditions, BEV generally had the lowest environmental impact in both seasons studied. The only exceptions were ionizing radiation, which is clearly caused by the high share of nuclear power in the Slovak energy mix, and NO x emissions, which are caused by the combustion of biomass for electricity generation. The other impact categories were dominated by vehicles with an internal combustion engine. The results of emissions from fuel production are also given for each impact category. The transportation of fuel did not exceed the value of 1% for any impact category or for any powertrain. The conclusions of the study support the global trend in favour of vehicle electrification as an important way to reduce the negative environmental impacts of internal combustion engine vehicles in Slovakia., (© 2024. The Author(s).)

The average-speed emission model (Speed-based model), a widely used and simple method of calculating road vehicle emissions, offers easy accessibility by expressing emissions as a function of average speed. However, there are limitations in expressing emissions generated through complex mechanisms simply as a function of speed. Real-world driving tests using a portable emission measurement system can incorporate the impact of vehicle driving load on emissions. In this study, we analyzed real-world emissions data from 94 light-duty vehicles and developed time-based emission factors depending on vehicle speed and vehicle-specific power (VSP). We also propose a speed-VSP based model to estimate regional CO 2 and NOx emissions by combining time-based emission factors and vehicle operating times. The speed-based model and Speed-VSP based model exhibit a 44% difference in NOx emissions and a 29% difference in CO 2 emission. In a comparison of the two models against RDE test results, the speed-VSP based model achieved high accuracy in predicting NOx and CO 2 emissions with a lower root mean square error (RMSE). Specifically, for NOx emissions predictions, the speed-VSP based model achieved an RMSE of 122-270 mg/km, while the speed-based model showed a much higher RMSE of 435-476 mg/km. For CO 2 emissions predictions, the speed-VSP based model achieved an RMSE of 34-56 mg/km, while the speed-based model showed a much higher RMSE of 36-72 mg/km. The results of this study present an opportunity to reassess and improve conventional method of measuring and evaluating emissions from road transport., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

As an emerging atmospheric pollutant, airborne environmentally persistent free radicals (EPFRs) are formed during many combustion processes and pose various adverse health effects. In health-oriented air pollution control, it is vital to evaluate the health effects of atmospheric fine particulate matter (PM 2.5 ) from different emission sources. In this study, various types of combustion-derived PM 2.5 were collected on filters in a partial-flow dilution tunnel sampling system from three typical emission sources: coal combustion, biomass burning, and automobile exhaust. Substantial concentrations of EPFRs were determined in PM 2.5 samples and associated with significant potential exposure risks. Results from in vitro cytotoxicity and oxidative potential assays suggest that EPFRs may cause substantial generation of reactive oxygen species (ROS) upon inhalation exposure to PM 2.5 from anthropogenic combustion sources, especially from automobile exhaust. This study provides important evidence for the source- and concentration-dependent health effects of EPFRs in PM 2.5 and motivates further assessments to advance public health-oriented PM 2.5 emission control., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The increasing number of vehicles are emitting a large amount of particles into the atmosphere, causing serious harm to the ecological environment and human health. This study conducted the Worldwide Harmonized Light Vehicles Test Cycle (WLTC) to investigate the emission characteristics of particle number (PN) of China-VI gasoline vehicles with different gasoline. The gasoline with lower aromatic hydrocarbons and olefins reduced particulate matter (PM) and PN emissions by 24% and 52% respectively. The average PN emission rate of the four vehicles during the first 300 s (the cold start period) was 7.2 times that of the 300 s-1800s. Additionally, because the particle transmission time and instrument response time, the test results of instantaneous emissions of PN were not synchronized with vehicle specific power (VSP). By calculating the Spearman correlation coefficient between pre-average vehicle specific power (PAVSP) and the test results of PN instantaneous emissions, the delay time was determined as 10s. After the PN emissions results were corrected, the PN emissions were found to be more related to VSP. By analyzing the influence of driving status on emission, this study found that vehicles in acceleration mode increased PN emissions by 76% compared to those in constant speed mode., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Motor vehicles are among the major sources of pollutants and greenhouse gases in urban areas and a transition to "zero emission vehicles" is underway worldwide. However, emissions associated with brake and tire wear will remain. We show here that previously unrecognized volatile and semi-volatile organic compounds, which have a similarity to biomass burning emissions are emitted during braking. These include greenhouse gases or, these classified as Hazardous Air Pollutants, as well as nitrogen-containing organics, nitrogen oxides and ammonia. The distribution and reactivity of these gaseous emissions are such that they can react in air to form ozone and other secondary pollutants with adverse health and climate consequences. Some of the compounds may prove to be unique markers of brake emissions. At higher temperatures, nucleation and growth of nanoparticles is also observed. Regions with high traffic, which are often disadvantaged communities, as well as commuters can be impacted by these emissions even after combustion-powered vehicles are phased out.

The transport sector is considered the largest contributor of air pollutants in urban areas, mainly on-road vehicles, affecting the environment and human health. Bahía Blanca is a medium-sized Latin American city, with high levels of traffic in the downtown area during peak hours. In this regard, it is necessary to analyze air pollution using an air quality model considering that there are no air pollutant measurements in the central area. Furthermore, this type of study has not been carried out in the region and since the city is expected to grow, it is necessary to evaluate the current situation in order to make effective future decisions. In this sense, the AERMOD model (US-EPA version) and the RLINE source type were used in this work. This study analyzes the variations of pollutant concentrations coming from mobile sources in Bahía Blanca's downtown area, particularly carbon monoxide (CO) and nitrogen oxides (NOx) during the period Jul-2020 to Jun-2022. It is interesting to note the results show the maximum concentration values detected are not directly associated with maximum levels of vehicle flow or emission rates, which highlights the importance of meteorological parameters in the modeling. In addition, alternative scenarios are proposed and analyzed from a sustainable approach. Regarding the scenario analysis, it can be concluded that diesel vehicles have a large influence on NOx emissions. Moreover, restrictions as strict as those proposed for a Low Emission Zone would be less applicable in the city than alternative temporary measures that modify traffic at peak hours., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Concentrations of particulate matter (PM 10 , PM 2.5 ), ultrafine (UFP), particle number (PNC), black carbon (BC), nitrogen dioxide (NO 2 ) and nitrogen oxides (NO X ) were measured in train carriages on diesel and bi-mode trains on inter-city and long-distance journeys in the United Kingdom (UK) using a high-quality mobile measurement system. Air quality on 15 different routes was measured using highly-time resolved data on a total of 119 journeys during three campaigns in winter 2020 and summer 2021; this included 13 different train classes. Each journey was sampled 4-10 times with approximatively 11,000 min of in-train concentrations in total. Mean-journey concentrations were 7.552 µg m -3 (PM 10 ); 3.936 µg m -3 (PM 2.5 ); 333-11,300 # cm -3 (PNC); 225-9,131 # cm -3 (UFP); 0.6-11 µg m -3 (BC); 28-201 µg m -3 (NO 2 ); and 130-3,456 µg m -3 (NO X ). The impact of different factors on in-train concentrations was evaluated. The presence of tunnels was the factor with the largest impact on the in-train particle concentrations with enhancements by a factor of 40 greater than baseline for BC, and a factor 6 to 7 for PM and PNC. The engine fuel mode was the factor with the largest impact on NO 2 with enhancements of up to 14-times larger when the train run on diesel compared to the times running on electric on hybrid trains. Train classes with an age < 10 years observed the lowest in-train PM, BC and NO X concentrations reflecting improvements in aspects of rail technology in recent years. Air quality on UK diesel trains is higher than ambient concentrations but has lower PM 2.5 and PNC than most other transport modes, including subway systems, diesel and petrol cars. This paper adds significantly to the evidence on exposure to poor air quality in transport micro-environments and provides the industry and regulatory bodies with reference-grade measurements on which to establish in-train air quality guidelines., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The authors reports financial support was the UK Rail Safety and Standard Board., (Copyright © 2024. Published by Elsevier Ltd.)

During the unprecedented COVID-19 city lockdown, a unique opportunity arose to dissect the intricate dynamics of urban air quality, focusing on ultrafine particles (UFPs) and volatile organic compounds (VOCs). This study delves into the nuanced interplay between traffic patterns and UFP emissions in a subtropical urban setting during the spring-summer transition of 2021. Leveraging meticulous roadside measurements near a traffic nexus, our investigation unravels the intricate relationship between particle number size distribution (PNSD), VOCs mixing ratios, and detailed vehicle activity metrics. The soft lockdown era, marked by a 20-27% dip in overall traffic yet a surprising surge in early morning motorcycle activity, presented a natural experiment. We observed a consequential shift in the urban aerosol regime: the decrease in primary emissions from traffic substantially amplified the role of aged particles and secondary aerosols. This shift was particularly pronounced under stagnant atmospheric conditions, where reduced dilution exacerbated the influence of alternative emission sources, notably solvent evaporation, and was further accentuated with the resumption of normal traffic flows. A distinct seasonal trend emerged as warmer months approached, with aromatic VOCs such as toluene, ethylbenzene, and xylene not only increasing but also significantly contributing to more frequent particle growth events. These findings spotlight the criticality of targeted strategies at traffic hotspots, especially during periods susceptible to weak atmospheric dilution, to curb UFP and precursor emissions effectively. As we stand at the cusp of widespread vehicle electrification, this study underscores the imperative of a holistic approach to urban air quality management, embracing the complexities of primary emission reductions and the resultant shifts in atmospheric chemistry., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Ambient air ultrafine particles (UFP, particles with a diameter <100 nm) have gained significant attention in World Health Organization (WHO) air quality guidelines and European legislation. This review explores UFP concentrations and particle number size distributions (PNC-PNSD) in various transportation hotspots, including road traffic, airports, harbors, trains, and urban commuting modes (walking, cycling, bus, tram, and subway). The results highlight the lack of information on personal exposure at harbors and railway stations, inside airplanes and trains, and during various other commuting modes. The different lower particle size limits of the reviewed measurements complicate direct comparisons between them. Emphasizing the use of instruments with detection limits ≤10 nm, this review underscores the necessity of following standardized UFP measurement protocols. Road traffic sites are shown to exhibit the highest PNC within cities, with PNC and PNSD in commuting modes driven by the proximity to road traffic and weather conditions. In closed environments, such as cars, buses, and trams, increased external air infiltration for ventilation correlates with elevated PNC and a shift in PNSD toward smaller diameters. Airports exhibit particularly elevated PNCs near runways, raising potential concerns about occupational exposure. Recommendations from this study include maintaining a substantial distance between road traffic and other commuting modes, integrating air filtration into ventilation systems, implementing low-emission zones, and advocating for a general reduction in road traffic to minimize daily UFP exposure. Our findings provide important insights for policy assessments and underscore the need for additional research to address current knowledge gaps., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Fulvio Amato reports financial support was provided by European Commission. Xavier Querol reports financial support was provided by Spain Ministry of Science and Innovation and Government of Catalonia. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Traffic emissions have become the major air pollution source in urban areas. Therefore, understanding the highly non-stational and complex impact of traffic factors on air quality is very important for building air quality prediction models. Using real-world air pollutant data from Taipei City, this study integrates diverse factors, including traffic flow, speed, rainfall patterns, and meteorological factors. We constructed a Bayesian network probability model based on rainfall events as a big data analysis framework to investigate understand traffic factor causality relationships and condition probabilities for meteorological factors and air pollutant concentrations. Generalized Additive Model (GAM) verified non-linear relationships between traffic factors and air pollutants. Consequently, we propose a long short term memory (LSTM) model to predict airborne pollutant concentrations. This study propose a new approach of air pollutants and meteorological variable analysis procedure by considering both rainfall amount and patterns. Results indicate improved air quality when controlling vehicle speed above 40 km/h and maintaining an average vehicle flow < 1200 vehicles per hour. This study also classified rainfall events into four types depending on its characteristic. Wet deposition from varied rainfall types significantly affects air quality, with TypeⅠrainfall events (long-duration heavy rain) having the most pronounced impact. An LSTM model incorporating GAM and Bayesian network outcomes yields excellent performance, achieving correlation R 2 > 0.9 and 0.8 for first and second order air pollutants, i.e., CO, NO, NO 2 , and NO x ; and O 3 , PM 10 , and PM 2.5 , respectively., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Emerging evidence demonstrated that traffic-related air pollution induced adverse effects on cardiovascular system. We designed a population-based cross-sectional study to explore the association between residential proximity to major roadways, traffic density and the prevalence of valvular heart disease (VHD). A total of 34040 subjects from a Rural Health Project between 2013 and 2018 were collected. According to the inclusion and exclusion criteria, 4158 participants were enrolled in the final analysis. And we calculated the subjects' proximity to major roadways and collected the traffic density on the major roadways. Transthoracic echocardiography (TTE) was performed to diagnose the VHD, according to the current AHA/ACC (the American Heart Association and the American College of Cardiology) guidelines. Differences between groups were examined by the one-way ANOVAs for continuous variables and the chi-square tests for categorical variables. A logistic regression models were used to assess the associations. The stratified analysis by age and sex were conducted to further analyze the association. The restricted cubic spline analysis was performed to further evaluate the association between road way distance and VHD. Bonferroni test was used to adjust the significance level. The subjects closer to the major roads had the higher risk of tricuspid regurgitation (TR) (odds risk, OR = 1.519, 95% confidence intervals, 95%CI: 1.058-2.181), especially in female. The risk of VHD was positive (high traffic density VS low traffic density, OR = 1.799, 95%CI: 1.221-2.651), especially in female. In addition, the high traffic density was associated with the risk of mitral regurgitation (MR) (OR = 1.758, 95%CI: 1.085-2.848). The restricted cubic spline analysis found a threshold distance of about 300 m, where had the lowest risk of VHD, aortic regurgitation (AR), MR, TR. Our results found a positive association between traffic-related air pollution and VHD especially in female., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Traffic-related air pollution (TRAP) is made up of complex mixtures of particulate matter, gases and volatile compounds. However, the effects of TRAP on the cardiopulmonary system in most animal studies have been tested using acute exposure to singular pollutants. The cardiopulmonary effects and molecular mechanisms in animals that are chronically exposed to unmodified air pollution as a whole have yet to be studied. Additionally, sex-dependent toxicity of TRAP exposure has rarely been evaluated., Objectives: This study sought to assess the cardiopulmonary effect of chronic exposure to unmodified, real-world TRAP in both female and male rats., Methods: Four-week-old male and female rats were exposed to TRAP or filtered air for 14 months in a novel facility drawing air from a major freeway tunnel system in Northern California. Inflammation and oxidative stress markers were examined in the lung, heart, spleen, and plasma, and TRAP deposits were quantified in the lungs of both male and female rats., Results: Elemental analysis showed higher levels of eight elements in the female lungs and one element in the male lungs. Expression of genes related to fibrosis, aging, oxidative stress, and inflammation were higher in the rat hearts exposed to TRAP, with female rats being more susceptible than males. Enhanced collagen accumulation was found only in the TRAP-exposed female hearts. Plasma cytokine secretion was higher in both female and male rats, but inflammatory macrophages were higher only in TRAP-exposed male spleens., Discussion: Our results in rats suggest pathological consequences from chronic TRAP exposure, including sex differences indicating females may be more susceptible to TRAP-induced cardiac fibrosis. https://doi.org/10.1289/EHP7045.

Polycyclic aromatic hydrocarbons (PAHs), nitro- (NPAHs) and oxy-derivatives (OPAHs) are of considerable concern due to their toxicity and carcinogenic hazards. Ships are recognized as an important emission source of these compounds. Marine diesel oil (MDO) and heavy fuel oil (HFO) are the two most commonly used fuels. The emission characteristics and toxicities of PM 2.5 -bound PAHs, NPAHs and OPAHs due to HFO and MDO combustion in atypical ocean-going vessel were investigated. The EF variability of polycyclic aromatic compounds (PACs) varied considerably with the fuel formulation (HFO and MDO) and engine loading (20%-100%). The concentration of ΣPACs was 0.63 mg/kWh for MDO and ranged from 2.14 to 9.80 mg/kWh for HFO. Compared to HFO-20%, the EFs of ΣPAHs, ΣNPAHs and ΣOPAHs from MDO-20% were reduced by 97%, 77% and 73%, respectively. As identified through the coefficient of divergence, the profile of HFO-20% was notably different from those under the other three engine loadings for HFO. In addition, the emissions of ΣPAHs and ΣOPAHs showed a significant correlation with PM 2.5 , while they were relatively weak for ΣNPAHs. However, the CO and PAC emissions were not highly correlated. Furthermore, the BaP eq -ΣPAHs values were 0.010 mg/g for MDO and ranged from 0.092 mg/g to 0.306 mg/g for HFO, and the reduction ranged from 89% to 97% by substituting MDO for HFO. These data highlight the importance of improving fuel quality in close proximity to port areas and are useful for enhancing relevant databases., Competing Interests: Declaration of competing interest We declare that we have no conflict of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

We have studied the associations between exhaust particles and birth weight. Adjustments were made for ozone and potential confounding factors at the individual level. The study included all singletons conceived between August 2003 and February 2013 with mothers living in Greater Stockholm. We obtained record-based register data from the Swedish Medical Birth Register. Data concerning the parents were provided by Statistics Sweden. Exposure levels for nearly 187,000 pregnancies were calculated using a validated air quality dispersion model with input from a detailed emission database. A higher socioeconomic status was associated with higher levels of exhaust particles at the home address. In this region, with rather low air pollution levels, the associations between levels of exhaust particles and birth weight were negative for all three of the studied exposure windows (i.e., first and second trimester and full pregnancy). For the entire pregnancy, the linear decrease in birth weight was 7.5 grams (95% CI-12.0; -2.9) for an increase in exposure, corresponding to the inter quartile range (IQR = 209 ng/m3). We also found that the risk of being born small for gestational age increased with the level of exhaust particles in all three exposure windows, but these associations were not statistically significant., Competing Interests: The authors declare no conflict of interest

Background: Asthma is a common respiratory disease, which is linked to air pollution. However, little is known about the effect of specific air pollution sources on asthma occurrence., Objectives: To assess individual asthma risk in three urban areas in Israel characterized by different primary sources of air pollution: predominantly traffic-related air pollution (Tel Aviv) or predominantly industrial air pollution (Haifa bay area and Hadera)., Methods: The medical records of 13,875, 16- 19-year-old males, who lived in the affected urban areas prior to their army recruitment and who underwent standard pre-military health examinations during 2012-2014, were examined. Nonparametric tests were applied to compare asthma prevalence, and binary logistic regressions were used to assess the asthma risk attributed to the residential locations of the subjects, controlling for confounders, such as socio-demographic status, body mass index, cognitive abilities, and education., Results: The asthma rate among young males residing in Tel Aviv was 8.76%, compared to 6.96% in the Haifa bay area and 6.09% in Hadera. However, no statistically significant differences in asthma risk among the three urban areas was found in controlled logistic regressions (P > 0.20). This finding indicates that exposure to both industrial- and traffic-related air pollution is associated with asthma prevalence., Conclusions: Both industrial- and traffic-related air pollution have a negative effect on asthma risk in young males. Studies evaluating the association between asthma risk and specific air pollutants (e.g., sulfur dioxide, particulate matter, and nitrogen dioxide) are needed to ascertain the effects of individual air pollutants on asthma occurrence.