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Vehicles are a major source of anthropogenic emissions of carbon monoxide (CO), nitrogen oxides (NO), and black carbon (BC). CO and NO are known to be harmful to human health and contribute to ozone formation, while BC absorbs solar radiation that contributes to global warming and also has negative impacts on human health and visibility. Travel restrictions implemented during the COVID-19 pandemic provide researchers the opportunity to study the impact of large, on-road traffic reductions on local air quality. Traffic counts collected along Interstate-95, a major eight-lane highway in Maryland (US), reveal a 60% decrease in passenger car totals and an 8.6% (combination-unit) and 21% (single-unit) decrease in truck traffic counts in April 2020 relative to prior Aprils. The decrease in total on-road vehicles led to the near-elimination in stop-and-go traffic and a 14% increase in the mean vehicle speed during April 2020. Ambient near-road (NR) BC, CO, NO, and carbon dioxide (CO) measurements were used to determine vehicular emission ratios (ΔBC/ΔCO, ΔBC/ΔCO, ΔNO/ΔCO, ΔNO/ΔCO, and ΔCO/ΔCO), with each ratio defined as the slope value of a linear regression performed on the concentrations of two pollutants within an hour. A decrease of up to a factor of two in ΔBC/ΔCO, ΔBC/ΔCO, ΔNO/ΔCO, and in the fraction of on-road diesel vehicles from weekdays to weekends shows diesel vehicles to be the dominant source of BC and NO emissions at this NR site. We estimate up to a 70% reduction in BC emissions in April 2020 compared to earlier years, and attribute much of this to lower diesel BC emissions resulting from improvements in traffic flow and fewer instances of acceleration and braking. Future efforts to reduce vehicular BC emissions should focus on improving traffic flow or turbocharger lag within diesel engines. Inferred BC emissions from the NR site also depend on ambient temperature, with an increase of 54% in ΔBC/ΔCO from -5 to 20 °C during the cold season, similar to previous studies that reported increasing BC emissions with rising temperature. The default setting of MOVES3, the current version of the mobile emission model used by the US EPA, does not adjust hot-running BC emissions for ambient temperature. Future work will focus on improving the accuracy of mobile emissions in air quality modeling by incorporating the effects of temperature and traffic flow in the system used to generate mobile emissions input for commonly used air quality models.
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http://dx.doi.org/10.1016/j.atmosenv.2023.119649 | DOI Listing |
Int J Phytoremediation
September 2025
Laboratory of Applied Stress Biology, Department of Botany, University of Gour Banga, Malda, West Bengal, India.
Urbanization and increasing vehicular traffic have intensified air pollution, particularly the accumulation of particulate matter (PM), trace elements (TEs), and polycyclic aromatic hydrocarbons (PAHs) in urban environments. These pollutants pose significant risks to human health, urban ecosystems, and biodiversity. This study evaluates the efficacy of mixed-species vegetation barriers, comprising , , , and , in mitigating air pollution along three road types (highway, urban, and suburban).
View Article and Find Full Text PDFRev Infirm
September 2025
Centre bipol-AIR, 9 rue Abraham-Bloch, 69007 Lyon, France.
Functional neurological disorders are characterized by a variety of neurological symptoms that are not explained by an identifiable organic pathology. Despite their significant prevalence and major impact on quality of life, their recognition and management remain inadequate. Formerly known as hysteria, modern criteria (Diagnostic and Statistical Manual of Mental Disorders, 5th edition [DSM-5]) allow a positive diagnosis, distinct from malingering.
View Article and Find Full Text PDFEnviron Res
September 2025
Department of Environmental Epidemiology, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.
While studies have examined associations between air pollution and subjective long COVID outcomes such as fatigue and symptoms, no studies have focused on objective lung health measures. This study aimed to assess the impact of air pollution, examined through different exposure methods (exposures assigned via geospatial model, versus residential and personal measurements) on pulmonary function and radiological abnormalities in long COVID patients. We recruited 95 patients who attended a hospital outpatient clinic 3-6 months post-infection, during which pulmonary function was assessed via spirometry (FEV1,FVC,FEV1/FVC ratio) and diffusion capacity for carbon monoxide (DLCO), along with a chest CT.
View Article and Find Full Text PDFPharmacol Ther
September 2025
Department of Molecular Pharmacology, University of Groningen, Groningen, the Netherlands; Groningen Research Institute for Asthma and COPD, GRIAC, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands. Electronic address:
Air pollution is a significant public health issue that impacts lung health, particularly in vulnerable populations such as children, the elderly, and individuals with pre-existing respiratory conditions. Both natural and anthropogenic sources of air pollution give rise to a variety of toxic compounds, including particulate matter (PM), ozone (O₃), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and polycyclic aromatic hydrocarbons (PAHs). Exposure to these pollutants is strongly associated with the development and exacerbation of respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), lung cancer, and idiopathic pulmonary fibrosis (IPF).
View Article and Find Full Text PDFEnviron Int
September 2025
School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China.
Sichuan Basin (SCB) is a critical region in China facing the dual pressures of air pollution and population aging. This study constructed high resolution (1 km) PM datasets for SCB using advanced machine learning approaches - Super Resolution Generative Adversarial Networks (SRGAN) and Convolutional Neural Network - Long Short-Term Memory (CNN-LSTM). Evaluation results demonstrate good performance of the machine learning model (SRGAN: R = 0.
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