Sulfur Dioxide Concentrations Research Articles

Long-term trends in British Columbia lower mainland air quality: Criteria air pollutants and VOC

ABSTRACT The lower mainland of British Columbia is a geographic region that comprises the districts of Metro Vancouver and the Lower Fraser Valley. It is situated in a complex topographical and coastal location in southwestern British Columbia. Metro Vancouver is Canada’s third largest population center. Accessing the Canadian National Air Pollution Surveillance Program (NAPS) database we calculated air pollutant statistics using the Canadian Ambient Air Quality Standards (CAAQS) averaging times, numerical forms, and numerical levels for the years 2001to 2020. Man Kendall and Sen statistical methods were used to test for the presence of trends and the slope of those trends in fine particulate matter (PM2.5), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and volatile organic compound (VOC) ambient air concentrations. We did not determine a significant trend in 98th percentile of the daily 24-hr average PM2.5 concentrations. We did determine significant negative trends in the annual average of the daily 24-hr average PM2.5 concentrations at 6 of the 9 locations. Episodic, multi-day duration elevated PM2.5 concentrations related to forest fires were a significant influence on PM2.5 ambient concentrations. Annual 4th highest daily maximum 8-hr average O3 concentrations showed no trend at 14 of 18 locations, declined at 3 locations, and increased at one location. We determined statistically significant declines in peak and average NO2 and SO2 concentrations, and in time-integrated annual VOC concentrations.

Determining food safety in canned food using fuzzy logic based on sulphur dioxide, benzoic acid and sorbic acid concentration

Canned food market demand has arisen due to the higher need for instant and ready-to-eat food. Food preservatives are often added to canned and processed foods to prolong their shelf life and help to sustain the quality, taste, color, and food texture. However, excessive usage of such food preservatives can lead to various diseases and health issues including palpitations, allergies, and cancer. Therefore, food preservative detection in food samples is essential for safe consumption and health well-being. This paper proposed a fuzzy logic framework to determine the safety of food products based on the concentration of sulphur dioxide (SD), benzoic acid (BA), and sorbic acid (SA) in five different food categories as referred to the Food Acts 1983 and Food Regulations 1985 in Malaysia. The fuzzy logic framework comprises of Mamdani inference system design with 90 fuzzy rules, 15 and 5 membership functions for both the input and output parameters respectively. 50 random values and 10 lab analysis results based on the industrial samples were used to validate the developed algorithms in ensuring the safety of the food products. The membership functions generated for the three inputs (SD, BA, and SA) during the fuzzification steps are based on the maximum allowable limit from the food acts. The defuzzification of fuzzy logic gave an average output value of 0.1565, 0.1350, 0.1150, 0.1100, and 0.1550 for chicken curry with potatoes, satay sauce, sardine in tomato sauce, anchovies paste, and sardine spread accordingly. Results obtained from the fuzzy logic framework concluded that all the industrial samples are safe to be eaten and comply with the Sixth Schedule, Regulation 20 in both Acts.

Can Low-Carbon City Pilot Policies Reduce Environmental Pollution? Evidence From Prefecture-Level Data in China

Based on the second batch of low-carbon city pilot policies in 2013 as a quasi-natural experiment, this study adopts the panel data of 212 cities in China from 2007 to 2017, and uses the difference-in-differences model (DID) to carry out a policy evaluation of the pollution reduction and emission reduction effects of the low-carbon pilot policies and further analyzes the transmission mechanism. Based on the DID method, the actual impacts of the government's low-carbon call policy and low-carbon governance policy on the urban ecological environment are examined. It is found that compared with non-pilot cities, low-carbon governance construction in low-carbon pilot cities significantly reduces pollutant emissions in the region. Analysis of the transmission mechanism reveals that urban low-carbon governance strengthens the strength of environmental policies and reduces urban carbon and pollutant emissions through the low-carbon treatment of urban waste and the low-carbon industrial structure. The test of regional heterogeneity found that the effect of pollution reduction and emission reduction is more significant in the eastern cities, high population concentrated cities and more economically developed cities. The results are still significant after replacing the explanatory variables with sulphur dioxide content and excluding extreme outliers. Therefore, the emission reduction policy has a significant contribution to improving the urban environment and reducing pollution emissions.

Quantifying the indirect effects of different air pollutants on crop yields in North China Plain

High concentrations of air pollutants could affect crop yield directly via influencing crop physiology and indirectly via regulating climate conditions. How multiple air pollutants affect crop yields directly and indirectly remains elusive in the North China Plain (NCP), which is the hotspot of air pollution and crop production. Here, we construct data-driven models to quantify the indirect effects of four major air pollutants on the yields of winter wheat and summer maize through modulating climate variations in the NCP during 2005–2020. Our results show that wheat has a greater negative sensitivity to absorbing aerosol optical thickness (AAOD), ozone concentration (O3), sulfur dioxide concentration (SO2) and nitrogen dioxide concentration (NO2) than maize. The indirect effects of AAOD, O3 and SO2 in November and O3 in April control wheat yield variation, while the indirect effects of AAOD and O3 in June, O3 and SO2 in July, O3 and NO2 in August, and O3 in September dominate maize yield variation. Our results emphasize the indirect effects of air pollutants on crop yield via regulating climate variations, which has great implications for improving our understanding of air pollution-climate-crop interactions and guiding targeted adaptation and mitigation efforts.

Intercomparison of Air Quality Models in a Megacity: Toward an Operational Ensemble Forecasting System for São Paulo

AbstractAn intercomparison of four regional air quality models is performed in the tropical megacity of São Paulo with the perspective of developing a forecasting system based on a model ensemble. Modeled concentrations of the main regulated pollutants are compared with combined observations in the megacity center, after analyzing the spatial scale of representativeness of air monitoring stations. During three contrasting periods characterized by different types of pollution events, the hourly concentrations of carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), and particulate matter (PM2.5 and PM10) modeled by the ensemble are in moderate agreement with observations. The median of the ensemble provides the best performance (R ≈ 0.7 for CO, 0.7 for NOx, 0.5 for SO2, 0.5 for PM2.5, and 0.4 for PM10) because each model has periods and pollutants for which it has the best agreement. NOx concentration is modeled with a large inter‐model variability, highlighting potential for improvement of anthropogenic emissions. Pollutants transported by biomass burning events strongly affect the air quality in São Paulo and are associated with significant inter‐model variability. Modeled hourly concentration of ozone (O3) is overestimated during the day (≈20 ppb) and underestimated at night (≈10 ppb), while nitrogen dioxide (NO2) is overestimated at night (≈20 ppb). The observed O3 concentration is best reproduced by the median of the ensemble (R ≈ 0.8), taking advantage of the variable performance of the models. Therefore, an operational air quality forecast system based on a regional model ensemble is promising for São Paulo.

Estimated Sulfur Dioxide Pollutant Concentrations In Medan City Using Ordinary Kriging and Inverse Distance Weighting Approaches

Sulfur dioxide (SO2) pollution is a serious problem that negatively affects air quality and human health. So2 is generated by various human activities, especially the combustion of fossil fuels, as well as from natural sources such as volcanic eruptions. The emission of SO2 in urban areas, including Medan, Indonesia, has raised concerns as it is associated with respiratory diseases and the formation of acid rain. This research aimed to estimate comparative SO2 concentrations in Medan City using geostatistical methods, specifically ordinary kriging and inverse distance weighted (IDW). Air quality monitoring data from the Dinas Lingkungan Hidup Kota Medan were collected during a certain period. The collected data were analyzed and then interpolated using ordinary kriging and IDW methods. Furthermore, the Ordinary Kriging method involves testing the OK assumption, calculation of the experimental semivariogram, calculation of the theoretical semivariogram, structural analysis, and calculation of Root Mean Square Error (RMSE). Meanwhile, the Inverse Distance Weighted method involves calculating the Euclidean distance, determining the weights based on the power parameter, calculating the RMSE value, and estimating the SO2 concentration. The comparison results show that the OK method is more accurate in determining SO2 concentration compared to the IDW method in Medan City. In the estimation of sulfur dioxide (SO2) concentration, the OK method used the best theoretical semivariogram model, namely the exponential model, and in the estimation process of the IDW method, the power parameter 1 was used.

Time evolution of sulphur dioxide concentration generated by solid fuel combustion systems during the cold periods of the year

About 99% of sulphur dioxide present in the atmosphere comes from anthropogenic activities, the main source being industrial activity that processes sulphur materials, including burning fuels (coal, oil or gas), thus releasing sulphur dioxide into the air. The purpose of this paper is to monitor the concentration of sulphur dioxide during two seasons, in the ambient air of Petroșani, with the aim of highlighting the possible atmospheric pollution caused by thermal power plants that use solid fuel during the winter period. The monitoring periods were distributed over a period of 6 months (three in summer and three in winter), namely the summer months (May, June, July of 2022), the winter months of December (2022), January and February of 2023. The main objective of the measurements is to identify if there is an increase in sulphur dioxide concentration in the atmosphere, resulting from the burning of solid fuels from household activities during the winter period. Results indicate that there is a higher degree of SO2 pollution in the winter period, but the recorded values are far below the limits set by national legislation. The paper presents some measures to limit sulphur dioxide pollution in the context of climate change.

On the state of the environment and natural environment of the East Kazakhstan region

The article analyzes the state of the environment in the East Kazakhstan region. The authors, having analyzed official sources, showed that as a result of the restoration of production volumes at non-ferrous metallurgy and thermal power enterprises, there is an increase in emissions of hazardous waste by individual enterprises in this industry into the environment. In the atmospheric air of large industrial cities and towns in the region, maximum permissible concentrations of lead, sulfur dioxide, nitrogen oxides, phenol, formaldehyde and other components are observed to be exceeded. The authors emphasize that mining enterprises have a negative impact on the state of water resources and the unsatisfactory technical condition of sewer networks and treatment facilities, which leads to bacterial contamination of water sources, including sources of drinking water supply. The authors also discuss the state of forest resources and wildlife in the region. The conclusion that was done by the authors – there is a real threat of environmental pollution from waste from non-ferrous metallurgy and mining enterprises in the region and at the present moment.

Statistical analysis of seasonal variations in pollutant concentrations in urban atmosphere

In the context of global climate change and urbanization, the issue of air quality is becoming increasingly relevant. Air pollution poses a threat to human health and ecosystems, highlighting the need for monitoring the concentrations of pollutants. This study examines the seasonal variations in the concentrations of harmful substances in the urban atmosphere using statistical methods. The aim of the research is to analyze time series data on concentrations of carbon monoxide (CO), nitrogen oxide (NO), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), ammonia (NH3), and particulate matter (PM2.5 and PM10). Correlation and factor analysis are employed to assess the relationships between pollutants and identify underlying factors. The analysis of data collected over several years emphasizes seasonal changes, showing that pollutant concentrations are subject to significant fluctuations driven by both natural and anthropogenic factors. The results can be used to develop strategies for improving air quality and predicting the health impacts of pollution on the population. This research deepens the understanding of the dynamics of atmospheric pollution and its seasonal dependence, which is important for shaping environmental policy and management decisions.

PROBLEM STATEMENT AND MODELING OF AN ENERGY TECHNOLOGY SYSTEM FOR THE JOINT PRODUCTION OF SULFURIC ACID AND CONDENSED SULFUR DIOXIDE

The article develops a mathematical model for the quantitative assessment of technological parameters of energy-technological systems for the production of sulfuric acid and condensed sulfur dioxide. When modeling, the system was considered as energy-technological, taking into account the need to reduce its negative impact on the environment, due to both industrial emissions of harmful substances and emissions of unused thermal energy. In this regard, it was envisaged to process part of the sulfur dioxide according to a cyclic scheme. To increase the intensity of the technological system and the processes occurring in it, the use of oxygen and the provision of a high concentration of sulfur dioxide in the gas mixture before the stage of its catalytic oxidation in the contact apparatus was envisaged. To reduce the total volume of reactants, an increase in pressure in the system was assumed. The carried out formalization and object-oriented decomposition of the simulated system made it possible to identify 6 functional subsystems (blocks), each of which can be modeled and investigated independently. The accepted high level of formalization made it possible to include a minimum set of real system parameters in the model. The model is capable of development and can be concretized by introducing additional parameters and mathematical models of technological functions into consideration. The developed model is recommended to be used for operational modeling of combined systems for the production of sulfuric acid and condensed sulfur dioxide in the preparation and optimization of initial data for their design. After testing and setting up the model in practice, it can be used in an automated process control system, including when creating adaptive control systems.

Дистанционная оценка качества атмосферного воздуха в населенных пунктах нефтегазовой специализации Ямало-Ненецкого автономного округа

The remote assessment of methane (CH4), nitrogen dioxide (NO2), and sulfur dioxide (SO2) concentrations in the atmosphere of oil-and-gas profile settlements within the Yamalo-Nenets Autonomous Okrug for 2019–2022 was made for the first time. Data analysis from the TROPOMI spectrometer revealed that the highest levels of atmospheric pollution are observed near industrial centers and major cities (Novy Urengoy, Salekhard, Nadym). Increased impurities were identified along gas pipelines (near compressor stations). The highest average values of nitrogen dioxide content were recorded in Novy Urengoy (1,34 mol/m², with contamination peaks occurring in winter months). Excessive concentrations of sulfur dioxide were found in urban-type settlements. The highest average values were recorded in Stary Nadym (20,35 mol/m²). The maximum methane content (1866,2 ppb) was reported in Novy Urengoy. Urban air, in general, has increased methane content. However, focuses of its spread are also observed beyond cities, which may be a consequence of global warming

Selective Wine Aroma Enhancement through Enzyme Hydrolysis of Glycosidic Precursors.

Selective enhancement of wine aroma was achieved using a broad spectrum of exogenous glycosidases. Eight different enzyme preparations were added to Verdejo wine, resulting in an increase in the levels of varietal volatile compounds compared to the control wine after 15 days of treatment. The enzyme preparations studied were robust under winemaking conditions (sulfur dioxide, reducing sugars, and alcohol content), and no inhibition of β-glucosidase activity was observed. Significant differences were detected in four individual terpenes (α-terpineol, terpinen-4-ol, α-pinene, and citronellal) and benzyl alcohol in all the treated wines compared to the control wine, contributing to the final wine to varying degrees. In addition, a significant increase in the other aromatic compounds was observed, which showed different patterns depending on the enzyme preparation that was tested. The principal component analysis of the data revealed the possibility of modulating the different aromatic profiles of the final wines depending on the enzyme preparation used. Taking these results into account, enhancement of the floral, balsamic, and/or fruity notes of wines is possible by using a suitable commercial enzyme preparation.

Estimating PM2.5 utilizing multiple linear regression and ANN techniques

The accurate prediction of air pollutants, particularly Particulate Matter (PM), is critical to support effective and persuasive air quality management. Numerous variables influence the prediction of PM, and it's crucial to combine the most relevant input variables to ensure the most dependable predictions. This study aims to address this issue by utilizing correlation coefficients to select the most pertinent input and output variables for an air pollution model. In this work, PM2.5 concentration is estimated by employing concentrations of sulfur dioxide, nitrogen dioxide, and PM10 found in the air through the application of Artificial Neural Networks (ANNs). The proposed approach involves the comparison of three ANN models: one trained with the Levenberg–Marquardt algorithm (LM-ANN), another with the Bayesian Regularization algorithm (BR-ANN), and a third with the Scaled Conjugate Gradient algorithm (SCG-ANN). The findings revealed that the LM-ANN model outperforms the other two models and even surpasses the Multiple Linear Regression method. The LM-ANN model yields a higher R2 value of 0.8164 and a lower RMSE value of 9.5223.

Study on indoor pollutants emission in Akure, Ondo State, Nigeria

PurposeThis study aimed to characterize the concentrations of indoor pollutants (such as carbon dioxide (CO2), ozone (O3), nitrogen dioxide (NO2) and sulfur dioxide (SO2), as well as particulate matter (PM) (PM1, PM2.5 and PM10) in Akure, Nigeria, as well as the relationship between the parameters’ concentrations.Design/methodology/approachThe evaluation, which lasted four months, used a low-cost air sensor that was positioned two meters above the ground. All sensor procedures were correctly carried out.FindingsCO2 (430.34 ppm), NO2 (93.31 ppb), O3 (19.94 ppb), SO2 (40.87 ppb), PM1 (29.31 µg/m3), PM2.5 (43.56 µg/m3), PM10 (50.70 µg/m3), temperature (32.4°C) and relative humidity (50.53%) were the average values obtained. The Pearson correlation depicted the relationships between the pollutants and weather factors. With the exception of April, which had significant SO2 (18%) and low PM10 (49%) contributions, NO2 and PM10 were the most common pollutants in all of the months. The mean air quality index (AQI) for NO2 indicated that the AQI was “moderate” (51–100). In contrast to SO2, whose AQI ranged from “moderate” to “very unhealthy,” O3's AQI ranged from “good” (50) to “unhealthy” (151–200). Since PM1, PM2.5 and PM10 made up the majority of PC1’s contribution, both PM2.5 and PM10 were deemed “hazardous.”Practical implicationsThe practical implication of indoor air pollution is long-term health effects, including heart disease, lung cancer and respiratory diseases such as emphysema. Indoor air pollution can also cause long-term damage to people’s nerves, brain, kidneys, liver and other organs.Originality/valueLack of literature in terms of indoor air quality (IAQ) in Akure, Ondo State. With this work, the information obtained will assist all stakeholders in policy formulation and implementation. Again, the low-cost sensor used is new to this part of the world.

SO2 Mitigation via Catalytic Oxidation using Carbonaceous Materials and Metal Oxides for Environmental Sustainability

The high concentration of sulfur dioxide (SO2) in the air that contributes to increasing health and environmental issues has caught the attention of all countries. Numerous tactics to regulate and lower the SO2 levels in the environment that have been applied through regulations and promising technology, progress has been obtained to decrease the SO2 concentration. Among methods for SO2 removal, one of the promising techniques used is the catalytic oxidation of SO2 to SO3, which not only reduces the SO2 concentration in the environment but also produces sulfuric acid (H2SO4). Thus, the performance of the catalysts that can promote the catalytic oxidation of SO2 to SO3 for environmental sustainability is reviewed in this study. The types of catalysts evaluated in this study are carbon-based materials and metal oxides. Worth noting that these catalysts are feasible to catalytically converting SO2 hazardous material to resources, viz. SO3 and H2SO4 for industrial use. The findings of this study can serve as a foundation for devising an innovative method for SO2 mitigation through catalytic oxidation. Copyright © 2023 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

Vehicular Volume and Concentration of Gaseous Atmospheric Pollutants and Particulate Matter at Selected Road Junctions in Port Harcourt, Nigeria

The increase in industrial and vehicular activities has led to the proliferation of atmospheric pollutants in cities globally. The Niger Delta region is an industrial hub and serves as the nation's resource base by exploring crude oil. This work postulated that there would be high pollutants and particulate matter at road junctions due to the multiplicity of several vehicles owned by the surging human population. The number of vehicles at each junction were counted. A multi-parameter gas monitor (A multi–RAE PLUS (PGM-50) was used to collect air samples at different junctions (n = 5). The concentration of nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), particulate matter (PM2.5, PM10), temperature, relative humidity, and wind were analyzed. The result revealed that the volume of the vehicles at road traffic junctions follows the order Rumuola>Mile 3/UST Roundabout>Choba Junction>Garrison>Lagos Bus Stop. Choba Junction had the highest concentration of pollutants. The highest concentration of vehicular pollutants was observed in the morning. Carbon monoxide (CO) had the highest concentration, followed by SO2 and NO2. While for particulate matter, PM2.5 had a higher concentration than PM10. The result implies that the number of vehicular traffic does not necessarily determine the concentration of pollutants because other anthropogenic activities are causing a spike in atmospheric pollutants within the city.

Changes in industrial air pollution and the onset of childhood asthma in Quebec, Canada

Ambient air pollution has been associated with asthma onset and exacerbation in children. Whether improvement in air quality due to reduced industrial emissions has resulted in improved health outcomes such as asthma in some localities has usually been assessed indirectly with studies on between-subject comparisons of air pollution from all sources and health outcomes. In this study we directly assessed, within small areas in the province of Quebec (Canada), the influence of changes in local industrial fine particulate matter (PM2.5), nitrogen dioxide (NO2), and sulfur dioxide (SO2) concentrations, on changes in annual asthma onset rates in children (≤12 years old) with a longitudinal ecological design. We identified the yearly number of new cases of childhood asthma in 1282 small areas (census tracts or local community service centers) for the years 2002, 2004, 2005, 2006, and 2015. Annual average concentrations of industrial air pollutants for each of the geographic areas, and three sectors (i.e., pulp and paper mills, petroleum refineries, and metal smelters) were estimated by the Polair3D chemical transport model. Fixed-effects negative binomial models adjusted for household income were used to assess associations; additional adjustments for environmental tobacco smoke, background pollutant concentrations, vegetation coverage, and sociodemographic characteristics were conducted in sensitivity analyses. The incidence rate ratios (IRR) for childhood asthma onset for the interquartile increase in total industrial PM2.5, NO2, and SO2 were 1.016 (95% confidence interval, CI: 1.006–1.026), 1.063 (1.045–1.090), and 1.048 (1.031–1.080), respectively. Positive associations were also found with pollutant concentrations from most individual sectors. Results suggest that changes in industrial pollutant concentrations influence childhood asthma onset rates in small localities.

Modelling variations of emergency attendances using data on community mobility, climate and air pollution

Air pollution is associated with morbidity and mortality worldwide. We investigated the impact of improved air quality during the economic lockdown during the SARS-Cov2 pandemic on emergency room (ER) admissions in Germany. Weekly aggregated clinical data from 33 hospitals were collected in 2019 and 2020. Hourly concentrations of nitrogen and sulfur dioxide (NO2, SO2), carbon and nitrogen monoxide (CO, NO), ozone (O3) and particulate matter (PM10, PM2.5) measured by ground stations and meteorological data (ERA5) were selected from a 30 km radius around the corresponding ED. Mobility was assessed using aggregated cell phone data. A linear stepwise multiple regression model was used to predict ER admissions. The average weekly emergency numbers vary from 200 to over 1600 cases (total n = 2,216,217). The mean maximum decrease in caseload was 5 standard deviations. With the enforcement of the shutdown in March, the mobility index dropped by almost 40%. Of all air pollutants, NO2 has the strongest correlation with ER visits when averaged across all departments. Using a linear stepwise multiple regression model, 63% of the variation in ER visits is explained by the mobility index, but still 6% of the variation is explained by air quality and climate change.

The influence of air pollutants on COVID-19 severity in the administrative and industrial city of Kharkiv

Background. Despite the official statement by the World Health Organization regarding the end of coronavirus disease (COVID-19) pandemic, the risk of an epidemic rise in morbidity remains due to the active circulation of the pathogen and its mutation. Social, natural, environmental, and other factors can contribute to the spread of COVID-19. Air pollutants are extremely dangerous for humans, and a mixture of aerosols and dust particles in the air can serve as factors for the severe acute respiratory syndrome coronavirus 2 transmission. So, the purpose of the study was to reveal the impact of air pollutants on COVID-19 severity in Kharkiv. Materials and methods. The influence of environmental factors on the manifestations of COVID-19 epidemic was assessed for 425 days. 16,723 cases of hospitalizations, 1,883 deaths, and 15,146 confirmed cases of COVID-19 in various age groups were studied. There were on average 4,663 active cases every day. Statistical analysis on assessing the impact of environmental factors on COVID-19 morbidity with different degrees of severity was performed using the non-parametric Kruskal-Wallis test in the IBM SPSS Statistics software package, and the normality of the distribution was checked using the Kolmogorov-Smirnov test. Microsoft Office Excel 2016 spreadsheet tools were used for some auxiliary calculations and graphing. Results. The influence of sulfur dioxide, nitrogen dioxide, nitrous oxide, hydrogen sulfide, phenol, soot, and formaldehyde on COVID-19 morbidity in different severity of infection course with incubation periods of 3–4, 6–7, and 10–14 days was revealed. The effect of high concentrations of nitrogen dioxide, nitrogen oxide, and formaldehyde was most significant on active, confirmed, hospitalized, and fatal cases of COVID-19. At the same time, a rise in active cases of COVID-19 was observed with increasing concentrations of sulfur dioxide and hydrogen sulfide, and high concentrations of phenol and soot had an impact on severe forms. Conclusions. Air pollution can contribute to the spread of COVID-19 and lead to its severe forms, which should be considered when predicting morbidity at different levels (national, regional, local) of epidemiological surveillance. Further research is needed to reveal causal relationships between the incidence of COVID-19 and air pollutants, considering the influence of social and natural factors.

Monitoring gaseous pollutants using passive sampling in the Philadelphia region

ABSTRACT Air pollution can have deleterious impacts on human health and the environment. Historically, air pollution studies have focused more on cities. However, it is also important to consider the impact on large suburban populations living closer to the major cities. In this study, nitrogen oxides (nitrogen dioxide and nitric oxide), sulfur dioxide, ozone, and ammonia concentrations were measured from fifteen sites in the Greater Philadelphia area, Pennsylvania, USA using Ogawa passive samplers from September 2021 to May 2022. The fall season had the highest mean NOx concentrations (11.03 ± 4.51 ppb), and spring had the highest mean O3 concentration (18.65 ± 6.71 ppb) compared to other seasons. NOx concentrations were higher at suburban (30.43 ± 33.79 ppb) and urban sites (22.49 ± 12.54 ppb) compared to semi-rural sites (11.08 ± 9.20 ppb). SO2 was not detected in most of the measurements. The positive statistically significant correlation between NO and NH3 in urban (R2 = 0.33, p-value <0.05) and suburban sites (R2 = 0.37, p-value <0.05) during winter and spring, respectively, suggests a high attribution of traffic emissions to NH3 at urban and suburban sites. Influence of traffic emissions on air pollutant values for the study region is also supported by similar NOx concentrations between suburban and urban sites as well as decreasing NO2/NOx ratios with increased distance from expressways. This study shows that passive sampling can be effectively used for assessing spatial and seasonal variations in air pollutants within an area of diverse land use. Implications: This study presents the findings of temporal and seasonal patterns for nitrogen dioxide, nitric oxide, tropospheric ozone, and ammonia at urban, suburban, and semi-rural areas of the greater Philadelphia region. The main objective of the study is to monitor air pollution in suburban and semi-rural areas which are not monitored for air pollution. We monitored from a total of fifteen sites in three seasons to assess air pollution in suburban and semi-rural areas near the major city in the United States – Philadelphia. The findings are important to learn how air quality is affected in suburban and semi-rural areas near the major city. The study also shows the useful application of inexpensive passive sampling technique for measuring air pollution.