Modeling Air Quality Near Freeways Using a Three Dimensional Eulerian Model

Near-road air quality studies have indicated the presence of high levels of pollutants. In this study, a three dimensional Eulerian model is developed which can be used to study the air quality near freeways. A vehicle-induced turbulence parameterization is included in the model to estimate better the turbulent diffusion of pollutants. The near-road air quality model is used to study two different cases. In the first case, the model is validated using the data from General Motor's SF6 dispersion experiment, conducted at Michigan in 1976. Sensitivity of the model to meteorology and traffic-related parameters are studied in detail. In the second case, the spatial distribution of ozone, carbon monoxide, NOx and 1,3-Butadiene near a simulated 8-lane freeway was studied. Model simulation for the first case yielded better results than US EPA's CALINE models which were previously used for regulatory purposes. Model performance when analyzed at different wind directions shows an overall good performance. The results also show that the model performs well at surface but slightly over predicts pollutant concentration at higher elevations. The simulation results for second case at different directions of wind and at different boundary conditions for model species, places emphasis on the importance of the inclusion of the chemical mechanism in the study of near-road air quality

LongPMInd: long-term (1980-2022) daily ground particulate matter datasets in India

<p>The LongPMInd dataset, including daily PM2.5 and PM10 concentration (10km) for India during 1980-2022, is publicly accessible. All data are provided with NetCDF format with a spatial resolution of 10 km.</p&gt

Methodology and guidelines for regulating traffic flows under air quality constraints in metropolitan areas

"This project developed a methodology to couple a new pollutant dispersion model with a traffic assignment process to contain air pollution while maximizing mobility.

Significant Contributions of Isoprene to Summertime Secondary Organic Aerosol in Eastern United States

A modified SAPRC-11 (S11) photochemical mechanism with more detailed treatment of isoprene oxidation chemistry and additional secondary organic aerosol (SOA) formation through surface-controlled reactive uptake of dicarbonyls, isoprene epoxydiol and methacrylic acid epoxide was incorporated in the Community Multiscale Air Quality Model (CMAQ) to quantitatively determine contributions of isoprene to summertime ambient SOA concentrations in the eastern United States. The modified model utilizes a precursor-origin resolved approach to determine secondary glyoxal and methylglyoxal produced by oxidation of isoprene and other major volatile organic compounds (VOCs). Predicted OC concentrations show good agreement with field measurements without significant bias (MFB ∼ 0.07 and MFE ∼ 0.50), and predicted SOA reproduces observed day-to-day and diurnal variation of Oxygenated Organic Aerosol (OOA) determined by an aerosol mass spectrometer (AMS) at two locations in Houston, Texas. On average, isoprene SOA accounts for 55.5% of total predicted near-surface SOA in the eastern U.S., followed by aromatic compounds (13.2%), sesquiterpenes (13.0%) and monoterpenes (10.9%). Aerosol surface uptake of isoprene-generated glyoxal, methylglyoxal and epoxydiol accounts for approximately 83% of total isoprene SOA or more than 45% of total SOA. A domain wide reduction of NO_<i>x</i> emissions by 40% leads to a slight decrease of domain average SOA by 3.6% and isoprene SOA by approximately 2.6%. Although most of the isoprene SOA component concentrations are decreased, SOA from isoprene epoxydiol is increased by ∼16%

Air Pollution and Cognitive Impairment across the Life Course in Humans : A Systematic Review with Specific Focus on Income Level of Study Area

Cognitive function is a crucial determinant of human capital. The Lancet Commission (2020) has recognized air pollution as a risk factor for dementia. However, the scientific evidence on the impact of air pollution on cognitive outcomes across the life course and across different income settings, with varying levels of air pollution, needs further exploration. A systematic review was conducted, using Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) Guidelines to assess the association between air pollution and cognitive outcomes across the life course with a plan to analyze findings as per the income status of the study population. The PubMed search included keywords related to cognition and to pollution (in their titles) to identify studies on human participants published in English until 10 July 2020. The search yielded 84 relevant studies that described associations between exposure to air pollutants and an increased risk of lower cognitive function among children and adolescents, cognitive impairment and decline among adults, and dementia among older adults with supportive evidence of neuroimaging and inflammatory biomarkers. No study from low-and middle-income countries (LMICs)was identified despite high levels of air pollutants and high rates of dementia. To conclude, air pollution may impair cognitive function across the life-course, but a paucity of studies from reLMICs is a major lacuna in research

Year-long simulation of gaseous and particulate air pollutants in India

Severe pollution events occur frequently in India but few studies have investigated the characteristics, sources, and control strategies for the whole country. A year-long simulation was carried out in India to provide detailed information of spatial and temporal distribution of gas species and particulate matter (PM). The concentrations of O_3, NO_2, SO_2, CO, as well as PM_(2.5) and its components in 2015 were predicted using Weather Research Forecasting (WRF) and the Community Multiscale Air Quality (CMAQ) models. Model performance was validated against available observations from ground based national ambient air quality monitoring stations in major cities. Model performance of O_3 does not always meet the criteria suggested by the US Environmental Protection Agency (EPA) but that of PM_(2.5) meets suggested criteria by previous studies. The performance of model was better on days with high O_3 and PM_(2.5) levels. Concentrations of PM_(2.5), NO_2, CO and SO_2 were highest in the Indo-Gangetic region, including northern and eastern India. PM_(2.5) concentrations were higher during winter and lower during monsoon season. Winter nitrate concentrations were 160–230% higher than yearly average. In contrast, the fraction of sulfate in total PM_(2.5) was maximum in monsoon and least in winter, due to decrease in temperature and solar radiation intensity in winter. Except in southern India, where sulfate was the major component of PM_(2.5), primary organic aerosol (POA) fraction in PM_(2.5) was highest in all regions of the country. Fractions of secondary components were higher on bad days than on good days in these cities, indicating the importance of control of precursors for secondary pollutants in India