Seasonal variation of air pollution index: Hong Kong case study

Wang, Xiekang; Lu, Wen-Hsiang

doi:10.1016/j.chemosphere.2005.10.031

Cited by 83 publications

(41 citation statements)

References 33 publications

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“…Figure 1 demonstrates substantial diurnal and seasonal variation in outdoor NO and CO, similar to those recently described for NO 2 and CO in another urban area (Wang and Lu, 2006). Had we not adjusted for indoor monoxides, the observed seasonal increases in indoor and outdoor monoxides would have biased our results to suggest much larger increases in airway inflammation (as reflected by exhaled monoxide concentrations) than actually occurred.…”

Section: Discussionsupporting

confidence: 48%

Bias and confounding in longitudinal measures of exhaled monoxides

Dorevitch

Demirtaş

Scheff

et al. 2007

J Expo Sci Environ Epidemiol

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The measurement of exhaled nitric oxide and carbon monoxide concentrations is an emerging method of monitoring airway inflammation longitudinally in community-based studies. Inhaled concentrations of these monoxides influence exhaled concentrations. Little is known about the degree to which inhaled concentrations distort temporal trends in, or estimated effects of air pollutants on, exhaled monoxides. We sought to evaluate whether estimated effects of air pollutants on exhaled monoxides are distorted by trends in indoor and outdoor monoxides, and to characterize determinants of exhaled monoxide concentrations among residents of public housing. In a panel study, 42 residents of public housing provided over 1000 exhaled breath samples. Samples from all subjects were analyzed for nitric oxide; samples from 27 of these subjects were also analyzed for carbon monoxide. The effects of indoor and outdoor monoxide concentrations on exhaled concentrations were quantified. Confounding of associations between particulate matter concentrations and exhaled nitric oxide concentrations was explored. Determinants of exhaled monoxide concentrations among public housing residents are similar to those of other populations. Exhaled monoxide concentrations are more strongly associated with indoor than with outdoor monoxide concentrations. Approximately half of the variability in exhaled monoxide concentrations over time can be explained by changes in indoor monoxide concentrations. Indoor monoxide concentrations can markedly distort both temporal trends in exhaled concentrations as well as estimated effects of particulate matter on exhaled monoxides. Prior estimated effects of particulate matter on exhaled nitric oxide concentrations may have been confounded by nitric concentrations indoors at the time of exhaled air collection. To prevent distortions of longitudinal trends in airway inflammation and estimated health effects of air pollutants, inspiratory scrubber use is necessary but not sufficient to remove the confounding effect of indoor monoxides, and analyses should adjust exhaled monoxide concentrations for concentrations indoors.

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Section: Discussionsupporting

confidence: 48%

Bias and confounding in longitudinal measures of exhaled monoxides

Dorevitch

Demirtaş

Scheff

et al. 2007

J Expo Sci Environ Epidemiol

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“…It is widely used to express air quality level in urban areas (Longhurst 2005;Murena 2004), to find the relation between air quality and meteorology (Wang and Lu 2006;Chen et al 2008;Chu et al 2008), and to predict the index for the next day (Jiang et al 2004;Lang et al 2004;Zhou et al 2004;An et al 2001). In this study, the API of each residential station was calculated for every day between October 1999 and March 2000 using the threshold values suggested by Elshout et al (2008), and calculated station APIs were summed to obtain the API of the whole city, namely, urban air pollution index (I).…”

Section: Urban Air Pollution Indexmentioning

confidence: 99%

Air pollution forecasting in Ankara, Turkey using air pollution index and its relation to assimilative capacity of the atmosphere

Genç

Yesilyurt

Tuncel

2009

Environ Monit Assess

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Spatial and temporal variations in concentrations of CO, NO, NO(2), SO(2), and PM(10), measured between 1999 and 2000, at traffic-impacted and residential stations in Ankara were investigated. Air quality in residential areas was found to be influenced by traffic activities in the city. Pollutant ratios were proven to be reliable tracers to differentiate between different sources. Air pollution index (API) of the whole city was calculated to evaluate the level of air quality in Ankara. Multiple linear regression model was developed for forecasting API in Ankara. The correlation coefficients were found to be 0.79 and 0.63 for different time periods. The assimilative capacity of Ankara atmosphere was calculated in terms of ventilation coefficient (VC). The relation between API and VC was investigated and found that the air quality in Ankara was determined by meteorology rather than emissions.

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“…8). The general API level below 50 means that all pollutant levels are in the satisfactory range over a 24-h monitoring period and from 50 to 100 indicates the pollutants are at high level (Wang and Wei-Zhen 2006). As previously discussed, API is highly correlated with PM 10 and PM 2.5 .…”

Section: Air Pollution Indexmentioning

confidence: 89%

Meteorology drives ambient air quality in a valley: a case of Sukinda chromite mine, one among the ten most polluted areas in the world

Mishra

Pradhan

Prusty

et al. 2016

Environ Monit Assess

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The ambient air quality (AAQ) assessment was undertaken in Sukinda Valley, the chromite hub of India. The possible correlations of meteorological variables with different air quality parameters (PM10, PM2.5, SO2, NO2 and CO) were examined. Being the fourth most polluted area in the globe, Sukinda Valley has always been under attention of researchers, for hexavalent chromium contamination of water. The monitoring was carried out from December 2013 through May 2014 at six strategic locations in the residential and commercial areas around the mining cluster of Sukinda Valley considering the guidelines of Central Pollution Control Board (CPCB). In addition, meteorological parameters viz., temperature, relative humidity, wind speed, wind direction and rainfall, were also monitored. The air quality data were subjected to a general linear model (GLM) coupled with one-way analysis of variance (ANOVA) test for testing the significant difference in the concentration of various parameters among seasons and stations. Further, a two-tailed Pearson's correlation test helped in understanding the influence of meteorological parameters on dispersion of pollutants in the area. All the monitored air quality parameters varied significantly among the monitoring stations suggesting (i) the distance of sampling location to the mine site and other allied activities, (ii) landscape features and topography and (iii) meteorological parameters to be the forcing functions. The area was highly polluted with particulate matters, and in most of the cases, the PM level exceeded the National Ambient Air Quality Standards (NAAQS). The meteorological parameters seemed to play a major role in the dispersion of pollutants around the mine clusters. The role of wind direction, wind speed and temperature was apparent in dispersion of the particulate matters from their source of generation to the surrounding residential and commercial areas of the mine.

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Seasonal variation of air pollution index: Hong Kong case study

Cited by 83 publications

References 33 publications

Bias and confounding in longitudinal measures of exhaled monoxides

Bias and confounding in longitudinal measures of exhaled monoxides

Air pollution forecasting in Ankara, Turkey using air pollution index and its relation to assimilative capacity of the atmosphere

Meteorology drives ambient air quality in a valley: a case of Sukinda chromite mine, one among the ten most polluted areas in the world

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