Absorption of Gaseous Air Pollutants By a Standardized Plant Canopy

Concentration profiles for hydrogen fluoride(HF), sulfur dioxide(SO₂), ozone (O₃), nitrogen dioxide(NO₂), and nitric oxide(NO) generated in a standardized alfalfa canopy are presented. Wind, light, temperature, and carbon dioxide(CO₂) profiles, canopy pollutant uptake rates, and canopy structural data are also given. Canopy pollutant concentration profile characteristics were studied to evaluate the relative potentials for major air pollutants to penetrate into canopies. The study was conducted in an environmental growth chamber equipped to control automatically environmental conditions and monitor continuously gas exchange rates. HF, SO₂, and NO₂ profiles suggested that these gases were removed efficiently by the upper portion of the canopy as well as by the immediate subsurface vegetation. The steady state HF profile showed the greatest displacement within the canopy. The NO profile was displaced the least. The uptake rate of NO by plants was apparently too slow in comparison with gas transport and mixing within the canopy to affect the internal profile substantially. O₃ appeared to be readily deposited on the surface tissues, but the deeper tissues in the canopy had less effect on the concentration profile. Data are also presented to show the relationship between NO₂ concentration within the canopy and changes in the air concentration above the vegetation. The results indicated that gas transport between the atmosphere and canopy interior was rapid. The data presented should be of current interest to agriculturists, researchers, administrators, and environmental planners concerned with effects of air pollutants on plants and on the fate of pollutants in the microenvironment.     

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.

     

The change in O3, SO2 and NO2 concentrations in Lithuania

Due to the dynamic nature of the atmosphere, substantial amounts of gaseous and particulate pollutants are transported to the areas distant from their sources. In order to determine the regional concentration levels of atmospheric pollutants in Lithuania, concentrations of gaseous O₃, SO₂, NO₂ and other pollutants have been measured at the Preila background station (55°20′ N and 21°00′ E, 5 m a.s.l.) since 1981. The long-term concentration data set enabled us to get temporal trends, both on a seasonal and longer time scale, to identify source areas of pollutants and to relate them to the emission data. Based on the data obtained, the different tendencies in the pollutant concentration changes were revealed. Positive trends for ozone (of 2.9% per year during 1983–2000) and a distinct negative trend for both sulphur dioxide (of 3.8% per year during 1981–2000) and nitrogen dioxide (of 3.8% per year during 1983–2000) were found. The air mass back-trajectory analysis was used to assess the source region of air pollutants transported to Lithuania. The pollutant concentration levels were compared with their emission changes in Europe and Lithuania. The general trends in SO₂ as well as in NO₂ concentrations observed are consistent with changes in SO₂ and NO₂ emissions in Europe and Lithuania.     

Simulating Urban-Scale Air Pollutants and Their Predicting Capabilities over the Seoul Metropolitan Area

Abstract

Urban-scale air pollutants for sulfur dioxide, nitrogen dioxide, particulate matter with aerodynamic diameter >10 μm, and ozone (O₃) were simulated over the Seoul metropolitan area, Korea, during the period of July 2-11, 2002, and their predicting capabilities were discussed. The Air Pollution Model (TAPM) and the highly disaggregated anthropogenic and the biogenic gridded emissions (1 km × 1 km) recently prepared by the Korean Ministry of Environment were applied. Wind fields with observational nudging in the prognostic meteorological model TAPM are optionally adopted to comparatively examine the meteorological impact on the prediction capabilities of urban-scale air pollutants. The result shows that the simulated concentrations of secondary air pollutant largely agree with observed levels with an index of agreement (IOA) of >0.6, whereas IOAs of ～0.4 are found for most primary pollutants in the major cities, reflecting the quality of emission data in the urban area. The observationally nudged wind fields with higher IOAs have little effect on the prediction for both primary and secondary air pollutants, implying that the detailed wind field does not consistently improve the urban air pollution model performance if emissions are not well specified. However, the robust highest concentrations are better described toward observations by imposing observational nudging, suggesting the importance of wind fields for the predictions of extreme concentrations such as robust highest concentrations, maximum levels, and >90th percentiles of concentrations for both primary and secondary urban-scale air pollutants.     

A Model for Uptake of Pollutants by Vegetation

A mass transfer approach is used in developing a practical mathematical model of gaseous pollutant uptake by leaves in which a series of resistances is summed across a concentration difference. The body of information presented in this paper is directed to plant pathologists or physiologists in the field of vegetal-pollutant effects and to people interested in the natural removal of air pollutants by vegetation. Correlations are given to calculate the aerodynamic and the stomatal resistances to uptake, while both a qualitative investigation and quantitative estimates are made of the mesophyllic resistance. The factors which control the aerodynamic resistance, r_a, are leaf size and wind speed, while the leaf physiology is the determinant of the stomatal resistance, r_s . It is noted that the chemical reaction rate and pollutant diffusivity in the mesophyll control the mesophyllic resistance, r_m, though the overall gas phase mesophyllic resistance, Hr_m, is strongly a function of pollutant solubility in water. Finally, the overall model is compared to earlier experimental work on vegetal uptake of SO₂.     

Controls on hourly variations in urban background air pollutant concentrations

Average 21st century concentrations of urban air pollutants linked to cardiorespiratory disease are not declining, and commonly exceed legal limits. Even below such limits, health effects are being observed and may be related to transient daytime peaks in pollutant concentrations. With this in mind, we analyse >52,000 hourly urban background readings of PM₁₀ and pollutant gases throughout 2007 at a European town with legal annual average concentrations of common pollutants, but with a documented air pollution-related cardiorespiratory health problem, and demonstrate the hourly variations in PM₁₀, SO₂, NO_x, CO and O₃. Back-trajectory analysis was applied to track the arrival of exotic PM₁₀ intrusions, the main controls on air pollutants were identified, and the typical hourly pattern on ambient concentrations during 2007 was profiled. Emphasis was placed on “worst case” data (>90th percentile), when health effects are likely to be greatest. The data show marked daytime variations in pollutants result from rush-hour traffic-related pollution spikes, midday industrial SO₂ maxima, and afternoon O₃ peaks. African dust intrusions enhance PM₁₀ levels at whatever hour, whereas European PM incursions produce pronounced evening peaks due to their transport direction (across an industrial traffic corridor). Transient peak profiling moves us closer to the reality of personal outdoor exposure to inhalable pollutants in a given urban area. We argue that such an approach to monitoring data potentially offers more to air pollution health effect studies than using only 24 h or annual averages.     

Broadband UV spectroscopy system used for monitoring of SO2 and NO emissions from thermal power plants

A gas monitoring system based on broadband absorption spectroscopic techniques in the ultraviolet region is described and tested. The system was employed in real-time continuous concentration measurements of sulfur dioxide (SO₂) and nitric oxide (NO) from a 220-ton h^?1 circulating fluidized bed (CFB) boiler in Shandong province, China. The emission coefficients (per kg of coal and per kWh of electricity) and the total emission of the two pollutant gases were evaluated. The measurement results showed that the emission concentrations of SO₂ and NO from the CFB boiler fluctuated in the range of 750–1300 mg m^?3 and 100–220 mg m^?3, respectively. Compared with the specified emission standards of air pollutants from thermal power plants in China, the values were generally higher for SO₂ and lower for NO. The relatively high emission concentrations of SO₂ were found to mainly depend on the sulfur content of the fuel and the poor desulfurization efficiency. This study indicates that the broadband UV spectroscopy system is suitable for industrial emission monitoring and pollution control.     

Formation of chlorinated species through reaction of SO2 with NaClO2 powder and their role in the oxidation of NO and Hg0

This study examines gaseous chlorinated species generated from the reaction of sulfur dioxide (SO₂) with sodium chlorite powder (NaClO_2(s)) to obtain insight into the propensity of this process to enhance NO and Hg⁰ oxidation. A packed bed reactor containing NaClO_2(s) was used and the reaction temperature was set to 130 °C. Initially, we determined that the presence of SO₂ enhances the oxidation of NO and Hg⁰ by reaction with NaClO_2(s). We then introduced NO₂ into the gas mixture as a radical scavenger and determined that the chlorinated species generated by the reaction of SO₂ with NaClO_2(s) are OClO, Cl, ClO, and Cl₂. Based on these results, we suggest that such gaseous chlorinated ones are responsible for the enhancement of NO and Hg⁰ oxidation.     

Solar driven nitrous acid formation on building material surfaces containing titanium dioxide: A concern for air quality in urban areas?

The photoenhanced uptake of nitrogen dioxide (NO₂) to the surface of commercially available self-cleaning window glass has been studied under controlled laboratory conditions. This material is one of an array of modern building products which incorporate titanium dioxide (TiO₂) nanoparticles and are finding increasing use in populated urban areas. Amongst the principal drivers for the use of these materials is that they are thought to facilitate the irreversible removal of pollutants such as NO₂ and organic molecules from the atmosphere and thus act to remediate air quality. While it appears that TiO₂ materials do indeed remove organic molecules from built environments, in this study we show that the photoenhanced uptake of NO₂ to one example material, self-cleaning window glass, is in fact accompanied by the substantial formation (50–70%) of gaseous nitrous acid (HONO). This finding has direct and serious implications for the use of these materials in urban areas. Not only is HONO a harmful respiratory irritant, it is also readily photolysed by solar radiation leading to the formation of hydroxyl radicals (OH) together with the re-release of NO_x as NO. The net effect of subsequent OH initiated chemistry can then be the further degradation of air quality through the formation of secondary pollutants such as ozone and VOC oxidation products. In summary, we suggest that a scientifically conceived technical strategy for air quality remediation based on this technology, while widely perceived as universally beneficial, could in fact have effects precisely opposite to those intended.     

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.     

Traffic pollution in a downtown site of Buenos Aires City

It has recently been recognized that air and noise pollution constitutes an extended problem over the densely populated city of Buenos Aires. Traffic emissions are of paramount concern, especially along narrow and main traffic arteries. In spite of these considerations, few systematic studies have been undertaken to evaluate the air quality in the metropolitan area of the city. In 1996, concentrations of carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO₂) and ozone (O₃) were simultaneously measured for the first time using a continuous monitoring station. This station was placed in a building at Belgrano Avenue, which is a heavy traffic street in the downtown area of the city (Bogo et al., Atmospheric Environment 33 (1999) 2587. In this work, we analyze the dependence of the measured primary pollutants, CO and the mixture of nitrogen oxides (NO_x), with meteorological conditions, traffic emissions and monitoring location. We compare the registered values with the results obtained from modeling the dispersion of the pollutants emitted from mobile and area sources. We also discuss the relevance of street canyon effects compared with background concentrations of these pollutants.     

Ambient air pollution and term birth weight in Texas from 1998 to 2004

Previous studies have explored the association between air pollution levels and adverse birth outcomes such as lower birth weight. Existing literature suggests an association, although results across studies are not consistent. Additional research is needed to confirm the effect, investigate the exposure window of importance, and distinguish which pollutants cause harm.

We assessed the association between ambient pollutant concentrations and term birth weight for 1,548,904 births in TX from 1998 to 2004. Assignment of prenatal exposure to air pollutants was based on maternal county of residence at the time of delivery. Pollutants examined included particulate matter with aerodynamic diameter ≤10 and ≤2.5 µm (PM₁₀ and PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃). We applied a linear model with birth weight as a continuous variable. The model was adjusted for known risk factors and region. We assessed pollutant effects by trimester to identify biological exposure window of concern, and explored interaction due to race/ethnicity.

An interquartile increase in ambient pollutant concentrations of SO₂ and O₃ was associated with a 4.99-g (95% confidence interval [CI], 1.87–8.11) and 2.72-g (95% CI, 1.11–4.33) decrease in birth weight, respectively. Lower birth weight was associated with exposure to O₃ in the first and second trimester, whereas results were not significant for other pollutants by trimester. A positive association was exhibited for PM_2.5 in the first trimester. Effects estimates for PM₁₀ and PM_2.5 were inconsistent across race/ethnic groups.

Current ambient air pollution levels may be increasing the risk of lower birth weight for some pollutants. These risks may be increased for certain racial/ethnic groups. Additional research including consideration of improved methodology is needed to investigate these findings. Future studies should examine the influence of residual confounding.

Implications: This is one of the most comprehensive studies examining criteria air pollutants and lower birth weight in Texas. Our findings confirm results found previously for adverse effects of the air pollutant SO₂ on lower birth weight. Results from our study suggest that adverse pregnancy outcomes such as lower birth weight can occur even while maintaining air pollution levels below regulatory standards. Future studies should incorporate the assessment of differential pollutant exposure as well as effect estimates by race/ethnicity with individual and community-level social factors in order to enhance our understanding of how physical, social, and host factors influence birth outcomes.

Supplemental Materials: Supplementary information relating to characteristics of excluded births, distribution of air pollutant monitors by pollutant, and correlation coefficients of the air pollutants is available in the publisher's online edition of the Journal of the Air & Waste Management Association.     

Air pollutants and health outcomes: Assessment of confounding by influenza

We assessed confounding of associations between short-term effects of air pollution and health outcomes by influenza using Hong Kong mortality and hospitalization data for 1996–2002.Three measures of influenza were defined: (i) intensity: weekly proportion of positive influenza viruses, (ii) epidemic: weekly number of positive influenza viruses ≥4% of the annual number for ≥2 consecutive weeks, and (iii) predominance: an epidemic period with co-circulation of respiratory syncytial virus <2% of the annual positive isolates for ≥2 consecutive weeks. We examined effects of influenza on associations between nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter with aerodynamic diameter ≤10 μm (PM₁₀) and ozone (O₃) and health outcomes including all natural causes mortality, cardiorespiratory mortality and hospitalization. Generalized additive Poisson regression model with natural cubic splines was fitted to control for time-varying covariates to estimate air pollution health effects. Confounding with influenza was assessed using an absolute difference of >0.1% between unadjusted and adjusted excess risks (ER%).Without adjustment, pollutants were associated with positive ER% for all health outcomes except asthma and stroke hospitalization with SO₂ and stroke hospitalization with O₃. Following adjustment, changes in ER% for all pollutants were <0.1% for all natural causes mortality, but >0.1% for mortality from stroke with NO₂ and SO₂, cardiac or heart disease with NO₂, PM₁₀ and O₃, lower respiratory infections with NO₂ and O₃ and mortality from chronic obstructive pulmonary disease with all pollutants. Changes >0.1% were seen for acute respiratory disease hospitalization with NO₂, SO₂ and O₃ and acute lower respiratory infections hospitalization with PM₁₀. Generally, influenza does not confound the observed associations of air pollutants with all natural causes mortality and cardiovascular hospitalization, but for some pollutants and subgroups of cardiorespiratory mortality and respiratory hospitalization there was evidence to suggest confounding by influenza.     

A Statistical Assessment of Saturation and Mobile Sampling Strategies to Estimate Long-Term Average Concentrations across Urban Areast

Abstract

The objectives of this study were: (1) to quantify the errors associated with saturation air quality monitoring in estimating the long-term (i.e., annual and 5 yr) mean at a given site from four 2-week measurements, once per season; and (2) to develop a sampling strategy to guide the deployment of mobile air quality facilities for characterizing intraurban gradients of air pollutants, that is, to determine how often a given location should be visited to obtain relatively accurate estimates of the mean air pollutant concentrations. Computer simulations were conducted by randomly sampling ambient monitoring data collected in six Canadian cities at a variety of settings (e.g., population-based sites, near-roadway sites). The 5-yr (1998–2002) dataset consisted of hourly measurements of nitric oxide (NO), nitrogen dioxide (NO₂), oxides of nitrogen (NO_x), sulfur dioxide (SO₂), coarse particulate matter (PM₁₀), fine particulate matter (PM_2.5)_, and CO. The strategy of randomly selecting one 2-week measurement per season to determine the annual or long-term average concentration yields estimates within 30% of the true value 95% of the time for NO₂, PM₁₀ and NO_x. Larger errors, up to 50%, are expected for NO, SO₂, PM_2.5, and CO. Combining concentrations from 85 random 1-hr visits per season provides annual and 5-yr average estimates within 30% of the true value with good confidence. Overall, the magnitude of error in the estimates was strongly correlated with the variability of the pollutant. A better estimation can be expected for pollutants known to be less temporally variable and/or over geographic areas where concentrations are less variable. By using multiple sites located in different settings, the relationships determined for estimation error versus number of measurement periods used to determine long-term average are expected to realistically portray the true distribution. Thus, the results should be a good indication of the potential errors one could expect in a variety of different cities, particularly in more northern latitudes.     

The Steubenville Comprehensive Air Monitoring Program (SCAMP): Analysis of Short-Term and Episodic Variations in PM2.5 Concentrations Using Hourly Air Monitoring Data

Abstract

One-hour average ambient concentrations of particulate matter (PM) with an aerodynamic diameter <2.5 μm (PM_2.5) were determined in Steubenville, OH, between June 2000 and May 2002 with a tapered element oscillating microbalance (TEOM). Hourly average gaseous copollutant [carbon monoxide (CO), sulfur dioxide (SO₂), nitrogen oxide (NO_x), and ozone (O₃)] concentrations and meteorological conditions also were measured. Although 75% of the 14,682 hourly PM_2.5 concentrations measured during this period were ≤17 μg/m³, concentrations >65 μg/m³ were observed 76 times. On average, PM_2.5 concentrations at Steubenville exhibited a diurnal pattern of higher early morning concentrations and lower afternoon concentrations, similar to the diurnal profiles of CO and NO_x. This pattern was highly variable; however, PM_2.5 concentrations >65 μg/m³ were never observed during the mid-afternoon between 1:00 p.m. and 5:00 p.m. EST. Twenty-two episodes centered on one or more of these elevated concentrations were identified. Five episodes occurred during the months June through August; the maximum PM_2.5 concentration during these episodes was 76.6 μg/m³. Episodes occurring during climatologically cooler months often featured higher peak concentrations (five had maximum concentrations between 95.0 and 139.6 μg/m³), and many exhibited strong covariation between PM_2.5 and CO, NO_x, or SO₂. Case studies suggested that nocturnal surface-based temperature inversions were influential in driving high nighttime concentrations of these species during several cool season episodes, which typically had dramatically lower afternoon concentrations. These findings provide insights that may be useful in the development of PM_2.5 reduction strategies for Steubenville, and suggest that studies assessing possible health effects of PM_2.5 should carefully consider exposure issues related to the intraday timing of PM_2.5 episodes, as well as the potential for toxicological interactions among PM_2.5 and primary gaseous pollutants.     

The short-term effects of air pollution on adolescent lung function in Taiwan

A mass screening of lung function associated with air pollutants for children is limited. This study assessed the association between air pollutants exposure and the lung function of junior high school students in a mass screening program in Taipei city, Taiwan. Among 10,396 students with completed asthma screening questionnaires and anthropometric measures, 2919 students aged 12-16 received the spirometry test. Forced vital capacity (FVC) and forced expiratory flow in 1 s (FEV₁) in association with daily ambient concentrations of particulate matter with diameter of 10 μm or less (PM₁₀), sulfur dioxide (SO₂), carbon monoxide (CO), nitrogen dioxide (NO₂), and ozone (O₃) were assessed by regression models controlling for the age, gender, height, weight, student living districts, rainfall and temperature. FVC, had a significant negative association with short-term exposure to O₃ and PM₁₀ measured on the day of spirometry testing. FVC values also were reversely associated with means of SO₂, O₃, NO₂, PM₁₀ and CO exposed 1 d earlier. An increase of 1-ppm CO was associated with the reduction in FVC for 69.8 mL (95% CI: −115, −24.4 mL) or in FEV₁ for 73.7 mL (95% CI: −118, −29.7 mL). An increase in SO₂ for 1 ppb was associated with the reductions in FVC and FEV₁ for 12.9 mL (95% CI: −20.7, −5.09 mL) and 11.7 mL (95% CI: −19.3, −4.16 mL), respectively. In conclusion, the short-term exposure to O₃ and PM₁₀ was associated with reducing FVC and FEV₁. CO and SO₂ exposure had a strong 1-d lag effect on FVC and FEV₁.     

Recent spatial gradients and time trends in Dhaka,Bangladesh, air pollution and their human health implications

Dhaka, the capital of Bangladesh, is among the most polluted cities in the world. This research evaluates seasonal patterns, day-of-week patterns, spatial gradients, and trends in PM_2.5 (<2.5 µm in aerodynamic diameter), PM₁₀ (<10 µm in aerodynamic diameter), and gaseous pollutants concentrations (SO₂, NO₂, CO, and O₃) monitored in Dhaka from 2013 to 2017. It expands on past work by considering multiple monitoring sites and air pollutants. Except for ozone, the average concentrations of these pollutants showed strong seasonal variation, with maximum during winter and minimum during monsoon, with the pollution concentration of PM_2.5 and PM₁₀ being roughly five- to sixfold higher during winter versus monsoon. Our comparisons of the pollutant concentrations with Bangladesh NAAQS and U.S. NAAQS limits analysis indicate particulate matter (PM_2.5 and PM₁₀) as the air pollutants of greatest concern, as they frequently exceeded the Bangladesh NAAQS and U.S. NAAQS, especially during nonmonsoon time. In contrast, gaseous pollutants reported far fewer exceedances throughout the study period. During the study period, the highest number of exceedances of NAAQS limits in Dhaka City (Darus-Salam site) were found for PM_2.5 (72% of total study days), followed by PM₁₀ (40% of total study days), O₃ (1.7% of total study days), SO₂ (0.38% of total study days), and CO (0.25% of total study days). The trend analyses results showed statistically significant positive slopes over time for SO₂ (5.6 ppb yr^?1, 95% confidence interval [CI]: 0.7, 10.5) and CO (0.32 ppm yr^?1, 95% CI: 0.01, 0.56), which suggest increase in brick kilns operation and high-sulfur diesel use. Though statistically nonsignificant annual decreasing slopes for PM_2.5 (?4.6 µg/m³ yr^?1, 95% CI: ?12.7, 3.6) and PM₁₀ (?2.7 µg/m³ yr^?1, 95% CI: ?7.9, 2.5) were observed during this study period, the PM_2.5 concentration is still too high (~ 82.0 µg/m³) and can cause severe impact on human health.

Implications: This study revealed key insights into air quality challenges across Dhaka, Bangladesh, indicating particulate matter (PM) as Dhaka’s most serious air pollutant threat to human health. The results of these analyses indicate that there is a need for immediate further investigations, and action based on those investigations, including the conduct local epidemiological PM exposure-human health effects studies for this city, in order to determine the most public health effective interventions.     

Predicting hourly air pollutant levels using artificial neural networks coupled with uncertainty analysis by Monte Carlo simulations

Recent progress in developing artificial neural network (ANN) metamodels has paved the way for reliable use of these models in the prediction of air pollutant concentrations in urban atmosphere. However, improvement of prediction performance, proper selection of input parameters and model architecture, and quantification of model uncertainties remain key challenges to their practical use. This study has three main objectives: to select an ensemble of input parameters for ANN metamodels consisting of meteorological variables that are predictable by conventional weather forecast models and variables that properly describe the complex nature of pollutant source conditions in a major city, to optimize the ANN models to achieve the most accurate hourly prediction for a case study (city of Tehran), and to examine a methodology to analyze uncertainties based on ANN and Monte Carlo simulations (MCS). In the current study, the ANNs were constructed to predict criteria pollutants of nitrogen oxides (NO_x), nitrogen dioxide (NO₂), nitrogen monoxide (NO), ozone (O₃), carbon monoxide (CO), and particulate matter with aerodynamic diameter of less than 10 μm (PM₁₀) in Tehran based on the data collected at a monitoring station in the densely populated central area of the city. The best combination of input variables was comprehensively investigated taking into account the predictability of meteorological input variables and the study of model performance, correlation coefficients, and spectral analysis. Among numerous meteorological variables, wind speed, air temperature, relative humidity and wind direction were chosen as input variables for the ANN models. The complex nature of pollutant source conditions was reflected through the use of hour of the day and month of the year as input variables and the development of different models for each day of the week. After that, ANN models were constructed and validated, and a methodology of computing prediction intervals (PI) and probability of exceeding air quality thresholds was developed by combining ANNs and MCSs based on Latin Hypercube Sampling (LHS). The results showed that proper ANN models can be used as reliable metamodels for the prediction of hourly air pollutants in urban environments. High correlations were obtained with R ² of more than 0.82 between modeled and observed hourly pollutant levels for CO, NO_x, NO₂, NO, and PM₁₀. However, predicted O₃ levels were less accurate. The combined use of ANNs and MCSs seems very promising in analyzing air pollution prediction uncertainties. Replacing deterministic predictions with probabilistic PIs can enhance the reliability of ANN models and provide a means of quantifying prediction uncertainties.     

Detection and Measurement of Air Pollutants by Absorptions of Infrared Radiation

A technique of detecting gaseous air pollutants by means of absorption of laser radiation is under development at the NASA Electronics Research Center. The iodine infrared laser and the carbon dioxide infrared laser are forced to emit spectral lines which fall on the infrared absorption bands of atmospheric pollutants. The attenuation of a laser line when passed through an air sample is the measure of the pollutant concentration. The narrow spectral width of the laser emission permits sensitive detection, minimizes interference between pollutants, and allows penetration of atmospheric water bands. The collimation and high power outputs available from lasers permit transmission of the radiation over long straight paths through the atmosphere and over long folded paths in multiple-pass absorption cells. A sample of absorbing gas placed within the laser cavity forces the emission of the selected wavelengths. With a one-half kilometer path to a retro-reflector and back, it is predicted that the following concentrations of air pollutants will be detected by means of the indicated laser lines: carbon monoxide at 2 parts per million in air (ppm), using the 4.86 micron iodine line; nitric oxide at 1 ppm, using the 5.5 micron iodine line; ethylene at 0.1 ppm, using the 10.53 micron carbon dioxide line; sulfur dioxide at 1.5 ppm, using the 9.08 micron carbon dioxide line; and ozone at 0.15 ppm, using the 9.52 micron carbon dioxide line. It seems feasible to extend the technique to other gaseous pollutants such as nitrogen dioxide, methane, butane, and peroxy acetyl nitrate. Continuing effort is being devoted to development and construction of the laser transmitting and receiving equipment. Field testing is planned for the near future.