Air Quality Health Index Research Articles

An innovative approach for determination of air quality health index

Fuzzy-analytical hierarchical process (F-AHP) can be extended to determine fuzzy air quality health index (FAQHI) for deducing health risk associated with local air pollution levels, and subjective parameters. The present work aims at determining FAQHI by considering five air pollutant parameters (SO2, NO2, O3, CO, and PM10) and three subjective parameters (population sensitivity, population density and location sensitivity). Each of the individual pollutants has varying impacts. Hence the combined health effects associated with the pollutants were estimated by aggregating the pollutants with different weights. Global weights for each evaluation alternatives were determined using fuzzy-AHP method. The developed model was applied to determine FAQHI in Howrah City, India from daily-observed concentrations of air pollutants over the three-year period between 2009 and 2011. The FAQHI values obtained through this method in Howrah City range from 1 to 3. Since the permissible value of FAQHI (as calculated for NAAQS) for residential areas is 1.78, higher index values are of public health concern to the exposed individuals. During the period of study, the observed FAQHI values were found to be higher than 1.78 in most of the day in the months of January to March, and October to December. However, the index values were below the recommended limit during rest of the months. In conclusion, FAQHI in Howrah city was above permissible limit in winter months and within acceptable values in summer and rainy months. Diurnal variations of FAQHI showed a similar trend during the three-year period of assessment.

The Air Quality Health Index and Emergency Department Visits for Urticaria in Windsor, Canada

Ambient air pollution exposure has been associated with several health conditions, limited not only to respiratory and cardiovascular systems but also to cutaneous tissues. However, few epidemiological studies examined pollution exposure on skin problems. Basically, the common mechanism by which pollution may affect skin physiology is by induction of oxidative stress and inflammation. Urticaria is among the skin pathologies that have been associated with pollution. Based on the combined effects of three ambient air pollutants, ozone (O3), nitrogen dioxide (NO2), and fine particulate matter (PM) with a median aerodynamic diameter of less than 2.5 μm (PM 2.5), on mortality, the Air Quality Health Index (AQHI) in Canada was developed. The aim of this study was to examine the associations of short-term changes in AQHI with emergency department (ED) visits for urticaria in Windsor-area hospitals in Canada. Diagnosed ED visits were retrieved from the National Ambulatory Care Reporting System (NACRS). A time-stratified case-crossover design was applied to 2905 ED visits (males = 1215; females = 1690) for urticaria from April 2004 through December 2010. Odds ratios (OR) and their corresponding 95% confidence intervals (95%CI) for ED visits associated with increase by one unit of risk index were calculated employing conditional logistic regression. Positive and significant results were observed between AQHI levels and OR for ED visits for urticaria in Windsor for lags 2 and 3 days. A distributed lag nonlinear model technique was applied to daily counts of ED visits for lags 0 to 10 and significant results were obtained from lag 2 to lag 5 and for lag 9. These findings demonstrated associations between ambient air pollution and urticarial confirming that air pollution affects skin conditions.

Air quality monitoring in communities of the Canadian Arctic during the high shipping season with a focus on local and marine pollution

Abstract. The Canadian Arctic has experienced decreasing sea ice extent and increasing shipping activity in recent decades. While there are economic incentives to develop resources in the north, there are environmental concerns that increasing marine traffic will contribute to declining air quality in northern communities. In an effort to characterize the relative impact of shipping on air quality in the north, two monitoring stations have been installed in Cape Dorset and Resolute, Nunavut, and have been operational since 1 June 2013. The impact of shipping and other sources of emissions on NOx, O3, SO2, BC, and PM2.5 pollution have been characterized for the 2013 shipping season from 1 June to 1 November. In addition, a high-resolution Air Quality Health Index (AQHI) for both sites was computed. Shipping consistently increased O3 mixing ratio and PM2.5 concentration. The 90% confidence interval for mean difference in O3 mixing ratio between ship- and no ship-influenced air masses were up to 4.6–4.7 ppb and 2.5–2.7 ppb for Cape Dorset and Resolute, respectively. The same intervals for PM2.5 concentrations were up to 1.8–1.9 μg m−3 and 0.5–0.6 μg m−3. Ship-influenced air masses consistently exhibited an increase of 0.1 to 0.3 in the high-resolution AQHI compared to no ship-influenced air masses. Trajectory cluster analysis in combination with ship traffic tracking provided an estimated range for percent ship contribution to NOx, O3, SO2, and PM2.5 that were 12.9–17.5 %, 16.2–18.1 %, 16.9–18.3 %, and 19.5–31.7 % for Cape Dorset and 1.0–7.2 %, 2.9–4.8 %, 5.5–10.0 %, and 6.5–7.2 % for Resolute during the 2013 shipping season. Additional measurements in Resolute suggested that percent ship contribution to black carbon was 4.3–9.8 % and that black carbon constituted 1.3–9.7 % of total PM2.5 mass in ship plumes. Continued air quality monitoring in the above sites for future shipping seasons will improve the statistics in our analysis and characterize repeating seasonal patterns in air quality due to shipping, local pollution, and long-range transport.

Demystifying the air quality health index.

Demystifying the air quality health index.

The association between ambient air quality and cardiac rate and rhythm in ambulatory subjects

BackgroundAcute increases in ambient air pollution have been associated with increased hospitalization for cardiac diseases and stroke. Triggering of cardiac arrhythmia by changes in air quality could theoretically predispose individuals to cardiac arrest or heart failure, or stroke through precipitation of atrial fibrillation. We investigated the association between air quality and cardiac rate and rhythm characteristics measured by ambulatory cardiac monitoring. Methods and resultsDaily ambient 3-h maximum concentrations of ozone, nitrogen dioxide and fine particulate matter, and an index summarizing these pollutants called the Air Quality Health Index (AQHI) were compared to the results of 24-h ambulatory cardiac monitoring performed for clinical purposes in 8662 patients and analyzed at the University of Ottawa Heart Institute, Canada, between 2004 and 2009. An interquartile increase in the daily 3h- maximum AQHI was associated with a 0.9% (95% CI 0.3%, 1.5%) increase in the daily maximum heart rate and a 1.17% (95% CI 1.07%, 1.29%) increase in heart block frequency. An interquartile increase in NO2 was associated with an increase in the percentage of time in atrial fibrillation of 4.39% (−0.15, 9.15) among those ≤50years old, and 7.1% (0.24, 14.5) among males. ConclusionsWe found evidence that air pollution may affect cardiac rate and rhythm. This may be one mechanism partially explaining the increase in strokes and cardiac events observed on days of higher air pollution.

Emergency department visits for asthma in relation to the Air Quality Health Index: A case-crossover study in Windsor, Canada

In this study, associations of short-term changes in ambient air pollution with emergency department (ED) visits for asthma were examined in hospitals in the area of Windsor, Ontario. Ambient air pollution quality was represented by the Air Quality Health Index(AQHI), calculated using a formula that combines the concentrations and the relative health impacts of three ambient air pollutants: ozone , nitrogen dioxide and fine particulate matter. Data on ED visits were retrieved from the National Ambulatory Care Reporting System. Only patients two years of age and older were considered. A time-stratified case-crossover design was applied to 6,697 ED visits for asthma for the period of April 2004 to December 2010. Odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) for ED visits associated with increased (by one unit) levels of AQHI were calculated by applying conditional logistic regression. Positive and statistically significant results were observed between AQHI levels and ED visits for asthma. For all patients the largest value, OR=1.17 (CI: 1.09, 1.26), was obtained for exposures lagged by 9 days in the warm season (April-September). Effects among children 2 to 14 years of age were observed for same-day exposure (lag 0), with an OR=1.11(CI: 1.01, 1.21). Exposure to ambient air pollution in Windsor increases the risk of ED visits for asthma. When the adverse effects of air pollutants are increased, patient visits to the ED depend on the patient's age.

The Air Quality Health Index as a predictor of emergency department visits for ischemic stroke in Edmonton, Canada

The Air Quality Health Index (AQHI) is an aggregate measure of outdoor air quality. We investigated associations between the AQHI and emergency department (ED) visits for acute ischemic stroke to validate the AQHI as a predictor of risk of morbidity from stroke. ED visits in Edmonton, Canada between 1998 and 2002 were linked to hourly AQHI values and concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), ozone, particulate matter with aerodynamic diameter less than 2.5 and 10 μm, and sulfur dioxide. A time-stratified case-crossover analysis was employed, and measures of association were adjusted for temperature and relative humidity. The AQHI, NO2 and CO were positively associated with the number of ED visits for ischemic stroke during April-September, and associations were strongest for persons 75 years of age and older. In this age range, the odds ratios (95% confidence intervals) for an interquartile range increase of AQHI in 1-24 h, 25-48 h, and 1-72 h lag periods were 1.23 (1.08-1.40), 1.15 (1.01-1.31), and 1.30 (1.10-1.54), respectively. Significant positive associations were also observed for NO2 and CO. Our finding that ED visits for stroke were significantly associated with the AQHI suggests that the AQHI may be a valid communication tool for air pollution morbidity effects related to stroke.

Working with you on evidence-based practice and policy

We are pleased to announce the addition of Lydia Ma, a new manager on our team. In addition to her role at the NCCEH, Lydia is the Continuing Education Director at the University of British Columbia (UBC) School of Population and Public Health (SPPH). She holds a Doctorate in pathology and a Master of Science in occupational and environmental hygiene from UBC. For the past six years, Lydia has also been the project manager of an online, on-demand, accredited, and bilingual course developed by UBC SPPH that focuses on outdoor air quality and health and the Air Quality Health Index. She currently serves on the Board of Directors of the BC Environmental and Occupational Health Research Network. Lydia looks forward to connecting with environmental health professionals across the country.

Communicating air pollution-related health risks to the public: An application of the Air Quality Health Index in Shanghai, China

The Air Quality Health Index (AQHI) was originally developed in Canada. However, little is known about its validity in communicating morbidity risks. We aimed to establish the AQHI in Shanghai, China, and to compare the associations of AQHI and existing Air Pollution Index (API) with daily mortality and morbidity. We constructed the AQHI as the sum of excess total mortality associated with individual air pollutants, and then adjusted it to an arbitrary scale (0–10), according to a time-series analysis of air pollution and mortality in Shanghai from 2001 to 2008. We examined the associations of AQHI with daily mortality and morbidity, and compared these associations with API from 2005 to 2008. The coefficients of short-term associations of total mortality with particulate matter with an aerodynamic diameter less than 10μm (PM10), PM2.5 and nitrogen dioxide (NO2) were used in the establishment of AQHI. During 2005–2008, the AQHI showed linear non-threshold positive associations with daily mortality and morbidity. A unit increase of the PM10-AQHI was associated with a 0.90% [95% (confidence interval, CI), 0.43 to 1.37], 1.04% (95%CI, 0.04 to 2.04), 1.62% (95%CI, 0.39 to 2.85) and 0.51% (95%CI, 0.09 to 0.93) increase of current-day total mortality, hospital admissions, outpatient visits and emergency room visits, respectively. The PM2.5-AQHI showed quite similar effect estimates with the PM10-AQHI. In contrast, the associations for API were much weaker and generally statistically insignificant. The AQHI, compared with the existing API, provided a more effective tool to communicate the air pollution-related health risks to the public.

The air quality health index and asthma morbidity: a population-based study.

Background: Exposure to air pollution has been linked to the exacerbation of respiratory diseases. The Air Quality Health Index (AQHI), developed in Canada, is a new health risk scale for reporting air quality and advising risk reduction actions.Objective: We used the AQHI to estimate the impact of air quality on asthma morbidity, adjusting for potential confounders.Methods: Daily air pollutant measures were obtained from 14 regional monitoring stations in Ontario. Daily counts of asthma-attributed hospitalizations, emergency department (ED) visits, and outpatient visits were obtained from a provincial registry of 1.5 million patients with asthma. Poisson regression was used to estimate health services rate ratios (RRs) as a measure of association between the AQHI or individual pollutants and health services use. We adjusted for age, sex, season, year, and region of residence.Results: The AQHI values were significantly associated with increased use of asthma health services on the same day and on the 2 following days, depending on the specific outcome assessed. A 1-unit increase in the AQHI was associated with a 5.6% increase in asthma outpatient visits (RR = 1.056; 95% CI: 1.053, 1.058) and a 2.1% increase in the rate of hospitalization (RR = 1.021; 95% CI: 1.014, 1.028) on the same day and with a 1.3% increase in the rate of ED visits (RR = 1.013; 95% CI: 1.010, 1.017) after a 2-day lag.Conclusions: The AQHI values were significantly associated with the use of asthma-related health services. Timely AQHI health risk advisories with integrated risk reduction messages may reduce morbidity associated with air pollution in patients with asthma.

Developing a risk-based air quality health index

We developed a risk-based, multi-pollutant air quality health index (AQHI) reporting system in Hong Kong, based on the Canadian approach. We performed time series studies to obtain the relative risks of hospital admissions for respiratory and cardiovascular diseases associated with four air pollutants: sulphur dioxide, nitrogen dioxide, ozone, and particulate matter with an aerodynamic diameter less than 10 μm (PM10). We then calculated the sum of excess risks of the hospital admissions associated with these air pollutants. The cut-off points of the summed excess risk, for the issuance of different health warnings, were based on the concentrations of these pollutants recommended as short-term Air Quality Guidelines by the World Health Organization. The excess risks were adjusted downwards for young children and the elderly. Health risk was grouped into five categories and sub-divided into eleven bands, with equal increments in excess risk from band 1 up to band 10 (the 11th band is ‘band 10+’). We developed health warning messages for the general public, including at-risk groups: young children, the elderly, and people with pre-existing cardiac or respiratory diseases. The new system addressed two major shortcomings of the current standard-based system; namely, the time lag between a sudden rise in air pollutant concentrations and the issue of a health warning, and the reliance on one dominant pollutant to calculate the index. Hence, the AQHI represents an improvement over Hong Kong's existing air pollution index.

The establishment and application of Shanghai air quality health index

This work aimed to construct Shanghai air quality health index (SAQHI) and to grade the air quality in Shanghai. Daily average concentrations of particulate matter with aerodynamic diameter less than 10 micrometer (PM(10)), SO(2) and NO(2) from 2001 to 2008 in the central urban areas of Shanghai were collected from Shanghai Environmental Monitoring Center. Contemporaneous data of daily average temperature and relative humidity were obtained from Shanghai Meteorological Bureau. Contemporaneous daily non-accidental mortality of registered residents in central urban areas of Shanghai were obtained from Shanghai Municipal CDC, respectively. Time-series analysis was conducted to estimate the association between air pollution and daily non-accidental mortality in the central urban areas of Shanghai. SAQHI was then established and applied to grade the air quality in Shanghai. On average, there were 122 non-accidental daily deaths in the central urban areas of Shanghai from 2001 to 2008. The contemporaneous daily average concentrations of PM(10), SO(2) and NO(2) for the same period were (97.3 ± 59.5), (50.1 ± 27.8) and (64.7 ± 23.9) µg/m(3), respectively. Daily average temperature was (17.7 ± 8.8)°C, and daily average relative humidity was (71.4 ± 11.8)%. Based on results of time series analysis, formula for SAQHI was SAQHI = 10/17× (exp (0.000 153×PM(10))-1+exp (0.000 662×NO(2))-1)×100. Air quality in Shanghai was graded according to SAQHI values as low health risk (SAQHI: 0 ∼ 3), moderate health risk (SAQHI: 4-6), high health risk (SAQHI: 7-10) and very high health risk (SAQHI: > 10). SAQHI could be applied in grading air quality in Shanghai, and reflect the effects of the overall air quality on health.

A New Multipollutant, No-Threshold Air Quality Health Index Based on Short-Term Associations Observed in Daily Time-Series Analyses

Air quality indices currently in use have been criticized because they do not capture additive effects of multiple pollutants, or reflect the apparent no-threshold concentration-response relationship between air pollution and health. We propose a new air quality health index (AQHI), constructed as the sum of excess mortality risk associated with individual pollutants from a time-series analysis of air pollution and mortality in Canadian cities, adjusted to a 0–10 scale, and calculated hourly on the basis of trailing 3-hr average pollutant concentrations. Extensive sensitivity analyses were conducted using alternative combinations of pollutants from single and multi-pollutant models. All formulations considered produced frequency distributions of the daily maximum AQHI that were right-skewed, with modal values of 3 or 4, and less than 10% of values at 7 or above on the 10-point scale. In the absence of a gold standard and given the uncertainty in how to best reflect the mix of pollutants, we recommend a formulation based on associations of nitrogen dioxide, ozone, and particulate matter of median aerodynamic diameter less than 2.5 µm with mortality from single-pollutant models. Further sensitivity analyses revealed good agreement of this formulation with others based on alternative sources of coefficients drawn from published studies of mortality and morbidity. These analyses provide evidence that the AQHI represents a valid approach to formulating an index with the objective of allowing people to judge the relative probability of experiencing adverse health effects from day to day. Together with health messages and a graphic display, the AQHI scale appears promising as an air quality risk communication tool.