Temporal and spatial statistical analysis of ambient air quality of Assam (India)

ABSTRACT

Present paper represents the spatio-temporal variation of air quality and performances of geostatistical tools for the identification of pollutants zone in various districts of Assam (India). Geographic Information System (GIS) and geostatistical analysis were utilized to estimate the spatio-temporal variations (2015–2017) of gaseous and particulate air pollutants. Data of 23 fixed monitoring stations were collected from the Central Pollution Control Board (CPCB). It was observed that SO₂ and NO_x concentrations are the major pollutants to the deterioration of air quality in Assam State. Exploratory data analysis was considered for the determination of spatial and temporal patterns of air pollutants. Air Quality index (AQI) was calculated based on the air pollutants and particulate matter. Radial Basis Function (RBF) interpolation techniques were used to analyze the spatial and temporal variation of air quality in Assam. Cross-validation is applied to evaluate the accuracy of interpolation methods in terms of Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Nash–Sutcliffe Equation (NSE) and Accuracy Factor (ACFT). In 2015, the high value of AQI portrayed in the central and northeast of the state. In 2016, the central and entire east of the study area was recorded the highest value of AQI. In 2017, it was observed that mostly the central part of the state recorded the high value of AQI. The spatio-temporal variation trend of air pollutants provides sound scientific basis for its management and control. This information of air pollution congregation would be valuable for urban planners and decision architects to efficiently administer air quality for health and environmental purposes.     

Development of a Speciated,Hourly, and Gridded Air Pollutants Emission Modeling System—A Case Study on the Precursors of Photochemical Smog in the Seoul Metropolitan Area,Korea

ABSTRACT

A speciated, hourly, and gridded air pollutants emission modeling system (SHEMS) was developed and applied in predicting hourly nitrogen dioxide (NO₂) and ozone (O₃) levels in the Seoul Metropolitan Area (SMA). The primary goal of the SHEMS was to produce a systemized emission inventory for air pollutants including ozone precursors for modeling air quality in urban areas.

The SHEMS is principally composed of three parts: (1) a pre-processor to process emission factors, activity levels, and spatial and temporal information using a geographical information system; (2) an emission model for each source type; and (3) a post-processor to produce report and input data for air quality models through database modeling. The source categories in SHEMS are point, area, mobile, natural, and other sources such as fugitive emissions. The emission database produced by SHEMS contains 22 inventoried compounds: sulfur dioxide, NO₂, carbon monoxide, and 19 speciated volatile organic compounds. To validate SHEMS, the emission data were tested with the Urban Airshed Model to predict NO₂ and O₃ concentrations in the SMA during selected episode days in 1994. The results turned out to be reliable in describing temporal variation and spatial distribution of those pollutants.     

SARS-CoV-2 phase I transmission and mutability linked to the interplay of climatic variables: a global observation on the pandemic spread

The study aims to determine the impact of global meteorological parameters on SARS-COV-2, including population density and initiation of lockdown in twelve different countries. The daily trend of these parameters and COVID-19 variables from February 15th to April 25th, 2020, were considered. Asian countries show an increasing trend between infection rate and population density. A direct relationship between the time-lapse of the first infected case and the period of suspension of movement controls the transmissivity of COVID-19 in Asian countries. The increase in temperature has led to an increase in COVID-19 spread, while the decrease in humidity is consistent with the trend in daily deaths during the peak of the pandemic in European countries. Countries with 65°F temperature and 5 mm rainfall have a negative impact on COVID-19 spread. Lower oxygen availability in the atmosphere, fine droplets of submicron size together with infectious aerosols, and low wind speed have contributed to the increase in total cases and mortality in Germany and France. The onset of the D614G mutation and subsequent changes to D614 before March, later G614 in mid-March, and S943P, A831V, D839/Y/N/E in April were observed in Asian and European countries. The results of the correlation and factor analysis show that the COVID-19 cases and the climatic factors are significantly correlated with each other. The optimum meteorological conditions for the prevalence of G614 were identified. It was observed that the complex interaction of global meteorological factors and changes in the mutational form of CoV-2 phase I influenced the daily mortality rate along with other comorbid factors. The results of this study could help the public and policymakers to create awareness of the COVID-19 pandemic.

     

Relationships between lichen community composition and concentrations of NO2 and NH3

The relationship between different features of lichen communities in Quercus robur canopies and environmental variables, including concentrations of NO₂ and NH₃ was investigated. NO₂ concentration was the most significant variable, it was positively correlated with the proportion of lichen cover comprising nitrophytes and negatively correlated with total lichen cover. None of the lichen community features were correlated with NH₃ concentrations, which were relatively low across the site. Since nitrophytes and nitrophobes are likely to react in opposite directions to nitrogenous compounds, total lichen cover is not a suitable indicator for these pollutants. It is, therefore, suggested that the proportion of lichen cover comprising nitrophytes may be a suitable simple indicator of air quality, particularly in locations where the pollution climate is dominated by oxides of nitrogen.     

Air pollution in cities

Air quality in cities is the result of a complex interaction between natural and anthropogenic environmental conditions. Air pollution in cities is a serious environmental problem – especially in the developing countries. The air pollution path of the urban atmosphere consists of emission and transmission of air pollutants resulting in the ambient air pollution. Each part of the path is influenced by different factors. Emissions from motor traffic are a very important source group throughout the world. During transmission, air pollutants are dispersed, diluted and subjected to photochemical reactions. Ambient air pollution shows temporal and spatial variability. As an example of the temporal variability of urban air pollutants caused by motor traffic, typical average annual, weekly and diurnal cycles of NO, NO₂, O₃ and O_x are presented for an official urban air-quality station in Stuttgart, southern Germany. They are supplemented by weekly and diurnal cycles of selected percentile values of NO, NO₂, and O₃. Time series of these air pollutants give information on their trends. Results are discussed with regard to air pollution conditions in other cities. Possibilities for the assessment of air pollution in cities are shown. In addition, a qualitative overview of the air quality of the world's megacities is given.     

Ground level ozone concentrations and its association with NOx and meteorological parameters in Kathmandu valley, Nepal

This paper summarizes the results of a yearlong continuous measurements of gaseous pollutants, NO, NO₂, NO_x and O₃ in the ambient air at Kathmandu valley. Measured concentration of the pollutants in study area is a function of time. NO, NO₂ and O₃ peak occurred in succession in presence of sunlight. At the time of maximum O₃ concentration most of the NO_x are utilized. The diurnal cycle of ground level ozone concentrations, revealed mid-day peak with lower nocturnal concentrations and inverse relationship exists between O₃ and NO_x, which are evidences of photochemical O₃ formation. The observed ground level ozone during monsoon is slight lower than the pre-monsoon value. Further, lack of rainfall and higher temperature, solar radiation in the pre-monsoon have given rise to the gradual build up of ozone and it is lowest during winter. Ground level ozone concentrations measured during bandha (general strike) and weekend are 19% and 13% higher than those measured during weekdays. The most effective ozone abatement strategy for Kathmandu Valley may be control of NO_x emissions.     

Ambient air quality changes after stubble burning in rice–wheat system in an agricultural state of India

Ground-based ambient air monitoring was conducted to assess the contribution of crop residue burning of wheat (Triticum aestivum) and rice (Oriza sativa) at different locations in three districts (Kaithal, Kurukshetra, and Karnal) of the agricultural state of Haryana in India for two successive years (2016 and 2017). The Air Quality Index (AQI) and concentration of primary pollutants (SO_x, NO_x, and PM_2.5) were determined in rice and wheat crop season, for burning and non-burning periods. During crop residue burning periods, concentrations of SO_x, NO_x, and PM_2.5 were exceeded the NAAQS values by 78%, 71%, and 53%, respectively. A significant increase in SO_x (4.5 times), NO_x (3.8 times), and PM_2.5 concentration (3.5 times) was observed in stubble burning periods as compared to pre-burning (p < 0.05). A positive and significant correlation among the three pollutant concentrations was observed (p < 0.01). The AQI of KA site in Karnal district fell in severely polluted category during 2016 for rice as well as wheat residue burning period, and of KK site in Kaithal during wheat residue burning in year 2017. Results of present study indicate a remarkable increase in pollutant concentration (SO_x, NO_x, and PM_2.5) during the crop residue burning periods. To the best of our knowledge, the outcomes of present study in this region have not been reported in earlier reports. Hence, there is an urgent need to curb air pollution by adopting sustainable harvesting technologies and management of residues.

     

An assessment of the impact of climate change on air quality at two UK sites

Possible effects of climate change on air quality are studied for two urban sites in the UK, London and Glasgow. Hourly meteorological data were obtained from climate simulations for two periods representing the current climate and a plausible late 21st century climate. Of the meteorological quantities relevant to air quality, significant changes were found in temperature, specific humidity, wind speed, wind direction, cloud cover, solar radiation, surface sensible heat flux and precipitation. Using these data, dispersion estimates were made for a variety of single sources and some significant changes in environmental impact were found in the future climate. In addition, estimates for future background concentrations of NO_x, NO₂, ozone and PM₁₀ upwind of London and Glasgow were made using the meteorological data in a statistical model. These showed falls in NO_x and increases in ozone for London, while a fall in NO₂ was the largest percentage change for Glasgow. Other changes were small. With these background estimates, annual-average concentrations of NO_x, NO₂, ozone and PM₁₀ were estimated within the two urban areas. For London, results averaged over a number of sites showed a fall in NO_x and a rise in ozone, but only small changes in NO₂ and PM₁₀. For Glasgow, the changes in all four chemical species were small. Large-scale background ozone values from a global chemical transport model are also presented. These show a decrease in background ozone due to climate change. To assess the net impact of both large scale and local processes will require models which treat all relevant scales.     

Nature and COVID-19: The pandemic,the environment,and the way ahead

The COVID-19 pandemic has brought profound social, political, economic, and environmental challenges to the world. The virus may have emerged from wildlife reservoirs linked to environmental disruption, was transmitted to humans via the wildlife trade, and its spread was facilitated by economic globalization. The pandemic arrived at a time when wildfires, high temperatures, floods, and storms amplified human suffering. These challenges call for a powerful response to COVID-19 that addresses social and economic development, climate change, and biodiversity together, offering an opportunity to bring transformational change to the structure and functioning of the global economy. This biodefense can include a “One Health” approach in all relevant sectors; a greener approach to agriculture that minimizes greenhouse gas emissions and leads to healthier diets; sustainable forms of energy; more effective international environmental agreements; post-COVID development that is equitable and sustainable; and nature-compatible international trade. Restoring and enhancing protected areas as part of devoting 50% of the planet’s land to environmentally sound management that conserves biodiversity would also support adaptation to climate change and limit human contact with zoonotic pathogens. The essential links between human health and well-being, biodiversity, and climate change could inspire a new generation of innovators to provide green solutions to enable humans to live in a healthy balance with nature leading to a long-term resilient future.     

Analysis of air quality in Dire Dawa,Ethiopia

Ambient air quality was monitored and analyzed to develop air quality index and its implications for livability and climate change in Dire Dawa, Ethiopia. Using survey research design, 16 georeferenced locations, representing different land uses, were randomly selected and assessed for sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon dioxide (CO₂), carbon monoxide (CO),volatile organic compounds (VOCs), and meteorological parameters (temperature and relative humidity). The study found mean concentrations across all land uses for SO₂ of 0.37 ± 0.08 ppm, NO₂ of 0.13 ± 0.17 ppm, CO₂ of 465.65 ± 28.63 ppm, CO of 3.35 ± 2.04 ppm, and VOCs of 1850.67 ± 402 ppm. An air quality index indicated that ambient air quality for SO₂ was very poor, NO₂ ranged from moderate to very poor, whereas CO rating was moderate. Significant positive correlations existed between temperature and NO₂, CO₂, and CO and between humidity and VOCs. Significant relationships were also recorded between CO₂ and NO₂ and between CO and CO₂. Poor urban planning, inadequate pollution control measure, and weak capacity to monitor air quality have implications for energy usage, air quality, and local meteorological parameters, with subsequent feedback into global climate change. Implementation of programs to monitor and control emissions in order to reduce air pollution will provide health, economic, and environmental benefits to the city.

Implications: The need to develop and implement emission control programs to reduce air pollution in Dire Dawa City is urgent. This will provide enormous economic, health, and environmental benefits. It is expected that economic effects of air quality improvement will offset the expenditures for pollution control. Also, strategies that focus on air quality and climate change present a unique opportunity to engage different stakeholders in providing inclusive and sustainable development agenda for Dire Dawa.     

Effects of Instrument Precision and Spatial Variability on the Assessment of the Temporal Variation of Ambient Air Pollution in Atlanta,Georgia

Abstract

Data from the U.S. Environmental Protection Agency Air Quality System, the Southeastern Aerosol Research and Characterization database, and the Assessment of Spatial Aerosol Composition in Atlanta database for 1999 through 2002 have been used to characterize error associated with instrument precision and spatial variability on the assessment of the temporal variation of ambient air pollution in Atlanta, GA. These data are being used in time series epidemiologic studies in which associations of acute respiratory and cardiovascular health outcomes and daily ambient air pollutant levels are assessed. Modified semivariograms are used to quantify the effects of instrument precision and spatial variability on the assessment of daily metrics of ambient gaseous pollutants (SO₂, CO, NO_x, and O₃) and fine particulate matter ([PM_2.5] PM_2.5 mass, sulfate, nitrate, ammonium, elemental carbon [EC], and organic carbon [OC]). Variation because of instrument imprecision represented 7–40% of the temporal variation in the daily pollutant measures and was largest for the PM_2.5 EC and OC. Spatial variability was greatest for primary pollutants (SO₂, CO, NO_x, and EC). Population–weighted variation in daily ambient air pollutant levels because of both instrument imprecision and spatial variability ranged from 20% of the temporal variation for O₃ to 70% of the temporal variation for SO₂ and EC. Wind rose plots, corrected for diurnal and seasonal pattern effects, are used to demonstrate the impacts of local sources on monitoring station data. The results presented are being used to quantify the impacts of instrument precision and spatial variability on the assessment of health effects of ambient air pollution in Atlanta and are relevant to the interpretation of results from time series health studies that use data from fixed monitors.     

Binational school-based monitoring of traffic-related air pollutants in El Paso, Texas (USA) and Ciudad Juárez, Chihuahua (México)

Paired indoor and outdoor concentrations of fine and coarse particulate matter (PM), PM2.5 reflectance [black carbon(BC)], and nitrogen dioxide (NO₂) were determined for sixteen weeks in 2008 at four elementary schools (two in high and two in low traffic density zones) in a U.S.-Mexico border community to aid a binational health effects study. Strong spatial heterogeneity was observed for all outdoor pollutant concentrations. Concentrations of all pollutants, except coarse PM, were higher in high traffic zones than in the respective low traffic zones. Black carbon and NO₂ appear to be better traffic indicators than fine PM. Indoor air pollution was found to be well associated with outdoor air pollution, although differences existed due to uncontrollable factors involving student activities and building/ventilation configurations. Results of this study indicate substantial spatial variability of pollutants in the region, suggesting that children’s exposures to these pollutants vary based on the location of their school.     

Challenges of higher education related to e-learning in developing countries during COVID-19 spread: a review of the perspectives of students,instructors, policymakers,and ICT experts

The COVID-19 pandemic brought about many critical issues in all aspects such as economy, environment, health, and lifestyle, but people always try to find some response to crisis in different conditions. E-learning is defined as an elaborate response aiming at continuing education during the COVID-19 pandemic. It seems that developed countries have established and adjusted their technological infrastructures for the transition from a face-to-face education to a digital one. In contrast, developing countries were not completely prepared for this transition. Improper and deficient technological and practical fundamentals have been causing problems for all students, instructors, and other involved individuals. Therefore, we reviewed the challenges that have arisen from e-learning during the COVID-19 outbreak in different parts of tertiary education focusing on underprivileged countries.

     

Impact of Covid-19 partial lockdown on PM2.5, SO2, NO2, O3, and trace elements in PM2.5 in Hanoi,Vietnam

Covid-19 lockdowns have improved the ambient air quality across the world via reduced air pollutant levels. This article aims to investigate the effect of the partial lockdown on the main ambient air pollutants and their elemental concentrations bound to PM_2.5 in Hanoi. In addition to the PM_2.5 samples collected at three urban sites in Hanoi, the daily PM_2.5, NO₂, O₃, and SO₂ levels were collected from the automatic ambient air quality monitoring station at Nguyen Van Cu street to analyze the pollution level before (March 10th–March 31st) and during the partial lockdown (April 1st–April 22nd) with “current” data obtained in 2020 and “historical” data obtained in 2014, 2016, and 2017. The results showed that NO₂, PM_2.5, O₃, and SO₂ concentrations obtained from the automatic ambient air quality monitoring station were reduced by 75.8, 55.9, 21.4, and 60.7%, respectively, compared with historical data. Besides, the concentration of PM_2.5 at sampling sites declined by 41.8% during the partial lockdown. Furthermore, there was a drastic negative relationship between the boundary layer height (BLH) and the daily mean PM_2.5 in Hanoi. The concentrations of Cd, Se, As, Sr, Ba, Cu, Mn, Pb, K, Zn, Ca, Al, and Mg during the partial lockdown were lower than those before the partial lockdown. The results of enrichment factor (EF) values and principal component analysis (PCA) concluded that trace elements in PM_2.5 before the partial lockdown were more affected by industrial activities than those during the partial lockdown.

     

Simultaneous monitoring of SARS-CoV-2, bacteria,and fungi in indoor air of hospital: a study on Hajar Hospital in Shahrekord,Iran

The novel SARS-CoV-2 outbreak was declared as pandemic by the World Health Organization (WHO) on March 11, 2020. Understanding the airborne route of SARS-CoV-2 transmission is essential for infection prevention and control. In this study, a total of 107 indoor air samples (45 SARS-CoV-2, 62 bacteria, and fungi) were collected from different wards of the Hajar Hospital in Shahrekord, Iran. Simultaneously, bacterial and fungal samples were also collected from the ambient air of hospital yard. Overall, 6 positive air samples were detected in the infectious 1 and infectious 2 wards, intensive care unit (ICU), computed tomography (CT) scan, respiratory patients’ clinic, and personal protective equipment (PPE) room. Also, airborne bacteria and fungi were simultaneously detected in the various wards of the hospital with concentrations ranging from 14 to 106 CFU m^?3 and 18 to 141 CFU m^?3, respectively. The highest mean concentrations of bacteria and fungi were observed in respiratory patients’ clinics and ICU wards, respectively. Significant correlation (p < 0.05) was found between airborne bacterial concentration and the presence of SARS-CoV-2, while no significant correlation was found between fungi concentration and the virus presence. This study provided an additional evidence about the presence of SARS-CoV-2 in the indoor air of a hospital that admitted COVID-19 patients. Moreover, it was revealed that the monitoring of microbial quality of indoor air in such hospitals is very important, especially during the COVID-19 pandemic, for controlling the nosocomial infections.

     

Artificial intelligence modeling to evaluate field performance of photocatalytic asphalt pavement for ambient air purification

In recent years, the application of titanium dioxide (TiO₂) as a photocatalyst in asphalt pavement has received considerable attention for purifying ambient air from traffic-emitted pollutants via photocatalytic processes. In order to control the increasing deterioration of ambient air quality, urgent and proper risk assessment tools are deemed necessary. However, in practice, monitoring all process parameters for various operating conditions is difficult due to the complex and non-linear nature of air pollution-based problems. Therefore, the development of models to predict air pollutant concentrations is very useful because it can provide early warnings to the population and also reduce the number of measuring sites. This study used artificial neural network (ANN) and neuro-fuzzy (NF) models to predict NO_x concentration in the air as a function of traffic count (T_r) and climatic conditions including humidity (H), temperature (T), solar radiation (S), and wind speed (W) before and after the application of TiO₂ on the pavement surface. These models are useful for modeling because of their ability to be trained using historical data and because of their capability for modeling highly non-linear relationships. To build these models, data were collected from a field study where an aqueous nano TiO₂ solution was sprayed on a 0.2-mile of asphalt pavement in Baton Rouge, LA. Results of this study showed that the NF model provided a better fitting to NO_x measurements than the ANN model in the training, validation, and test steps. Results of a parametric study indicated that traffic level, relative humidity, and solar radiation had the most influence on photocatalytic efficiency.     

Assessment of ambient air quality in the port of Naples

Two experimental monitoring campaigns were carried out in 2012 to investigate the air quality in the port of Naples, the most important in southern Italy for traffic of passengers and one of the most important for goods. Therefore, it represents an important air pollution source located close to the city of Naples. The concentrations of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and BTEX (benzene, toluene, ethylbenzene, and xylenes) in the air were measured at 15 points inside the Naples port area through the use of passive samplers. In addition, a mobile laboratory was positioned in a fixed point inside the port area to measure continuous concentration of pollutants together with particulate matter, ambient parameters, and wind direction and intensity. The pollution levels monitored were compared with those observed in the urban area of Naples and in other Mediterranean ports. Even though the observation time was limited, measured concentrations were also compared with limit values established by European legislation. All the measured pollutants were below the limits with the exception of nitrogen dioxide: its average concentration during the exposition time exceeded the yearly limit value. A spatial analysis of data, according to the measured wind direction and intensity, provided information about the effects that ship emissions have on ambient air quality in the port area. The main evidence indicates that ship emissions influence sulfur dioxide concentration more than any other pollutants analyzed.

Implications: Two monitoring campaigns were carried out to measure BTEX, SO₂, NO₂, and PM₁₀ (particulate matter with an aerodynamic diameter <10 μm) air concentrations in the port of Naples. NO₂ hourly average and PM₁₀ daily average comply with European legislative standards. Spatial variation of pollutants long the axis corresponding to the prevailing wind direction seems to indicate a certain influence of ship emissions for SO₂. For NO₂ and PM₁₀, a correlation between concentrations in the harbor and those measured by the air quality monitoring stations sited in the urban area of Naples was observed, indicating a possible contribution of the near road traffic to the air pollution in the port of Naples.     

Synergistic effects of gaseous pollutants on hospital admissions for cardiovascular disease in Liuzhou,China

Previous studies demonstrated that short-term exposure to gaseous pollutants (nitrogen dioxide (NO₂), sulfur dioxide (SO₂), and ozone (O₃)) had a greater adverse effect on cardiovascular disease. However, little evidence exists regarding the synergy between gaseous pollutants and cardiovascular disease (CVD). Therefore, we aimed to estimate the effect of individual gaseous pollutants on hospital admissions for CVD and to explore the possible synergistic effects between gaseous pollutants. Daily hospitalization counts for CVD were collected from January 1, 2014, to December 31, 2015. We also collected daily time series on gaseous pollutants from the Environment of the People’s Republic of China, including NO₂, SO₂, and O₃. We used distributed lag nonlinear models (DLNMs) to assess the association of individual gaseous pollutants on CVD hospitalization, after controlling for seasonality, day of the week, public holidays, and weather variables. Then, we explored the variability across age and sex groups. In addition, we analyzed the synergistic effects between gaseous pollutants on CVD. Extremely low NO₂ and SO₂ increase the risk of CVD in all subgroup at lag 7 days. The greatest effect of high concentration of SO₂ was observed in male and the elderly (≥ 65 years) at lag 3 days. Greater effects of high concentration of O₃ were more pronounced in the young (< 65 years) and female at lag 3 days, while the effect of low concentration of O₃ was greater in male and the young (< 65 years) at lag 0 day. We found a synergistic effect between NO₂ and SO₂ for CVD, as well as between SO₂ and O₃. The synergistic effects of NO₂ and SO₂ on CVD were stronger in the elderly (≥ 65) and female. The female was sensitive to synergistic effects of SO₂-O₃ and NO₂-O₃. Interestingly, we found that there was a risk of CVD in the susceptible population even for gaseous pollutant concentrations below the National Environmental Quality Standard. The synergy between NO₂ and SO₂ was significantly associated with cardiovascular disease hospitalization in the elderly (≥ 65). This study provides evidence for the synergistic effect of gaseous pollutants on hospital admissions for cardiovascular disease.

     

Particulate matter,nitrogen oxides,ozone, and select volatile organic compounds during a winter sampling period in Logan,Utah, USA

Particulate matter mass (PM), trace gaseous pollutants, and select volatile organic compounds (VOCs) with meteorological variables were measured in Logan, Utah (Cache Valley), for >4 weeks during winter 2017 as part of the Utah Winter Fine Particle Study (UWFPS). Higher PM levels for short time periods and lower ozone (O₃) levels were present due to meteorological and mountain valley conditions. Nitrogenous pollutants were relatively strongly correlated with PM variables. Diurnal cycles of NO_x, O₃, and fine PM(PM 2.5) (aerodynamic diameter <2.5 μm [PM_2.5]) suggested formation from NO_x. O₃ levels increased from early morning into midafternoon, and NO_x and PM_2.5 increased throughout the morning, followed by sharp decreases. Toluene/benzene and xylenes/benzene ratios and VOC correlations with nitrogenous and PM species were indicative of local traffic sources. Wind sector comparisons suggested that pollutant levels were lower when winds were from nearby mountains to the east versus winds from northerly or southerly origins.

Implications: The Cache Valley in Idaho and Utah has been designated a PM_2.5 nonattainment area that has been attributed to air pollution buildup during winter stagnation events. To inform state implementation plans for PM_2.5 in Cache Valley and other PM_2.5 nonattainment areas in Utah, a state and multiagency federal research effort known as the UWFPS was conducted in winter 2017. As part of the UWFPS, the U.S. Environmental Protection Agency (EPA) measured ground-based PM species and their precursors, VOCs, and meteorology in Logan, Utah. Results reported here from the EPA study in Logan provide additional understanding of wintertime air pollution conditions and possible sources of PM and gaseous pollutants as well as being useful for future PM control strategies in this area.