Air Quality Health Index Research Articles

Air Quality Legislation in Australia and Canada—A Review

Air pollution is a pervasive global issue affecting human health, ecosystems, and the environment. This paper reviews the evolution and implementation of air quality legislation in Australia and Canada, providing a comparative analysis of their approaches to managing air pollution. Both countries have established robust legal frameworks to address air quality issues, involving governmental policies, regulatory mechanisms, and collaborative efforts among stakeholders. Australia began its air quality regulation at the state level in the 1950s, evolving into a national framework with the National Environment Protection Measure for Ambient Air Quality in 1998. In contrast, Canada centralized its efforts with the Clean Air Act in 1971, complemented by the National Air Pollution Surveillance program. Key findings reveal that, while both nations have achieved significant improvements in air quality, challenges remain in addressing the broader impacts of air pollution, such as climate change and health-related economic burdens. Australia’s air quality standards are generally more stringent than Canada’s for particulate matter but more relaxed for sulfur dioxide, nitrogen dioxide, and ozone. Both countries employ advanced air quality monitoring and reporting systems, with Australia’s Air Quality Index and Canada’s Air Quality Health Index providing critical public health information. The study highlights the need for continuous improvement and a more integrated approach to air quality management. By examining the legislative and regulatory landscapes of Australia and Canada, this paper offers valuable insights for other countries striving to enhance their air quality governance and mitigate the adverse effects of air pollution on a global scale.

The construction and validity assessment of the respiratory air quality health index (AQHI) based on the analytic hierarchy process in Tianjin, China

BackgroundAir quality health index (AQHI), as a developed air quality risk communication tool, has been proved to be more accurate in predicting air quality related health risks than air quality index (AQI) by previous studies. However, the standard method to construct AQHI is summing the excess risks of single-pollutant models directly, which may ignore the joint effect of air pollutant mixtures.MethodsIn this study, a new method which could solve the aforementioned problem, Analytic hierarchy process (AHP), was introduced. Based on this method, we constructed the respiratory health related AQHI using years of life lost (YLL) as indicator of health outcome and compared its validity with AQI.ResultsThere was a correlation between daily AQI and AQHI in 2019 (R2 = 0.830, P < 0.01), and the chi-square test between the two excellent rates showed a statistically significant difference (χ2 = 4.156, P < 0.05). Both AQI and AQHI were correlated with the daily respiratory YLL (P < 0.01), however, the coefficient of AQHI was larger than those of AQI.ConclusionsThis study indicated that compared with AQI, the constructed AQHI based on AHP may predict the health risk of air pollution more effectively. AHP may become a new method to construct AQHI which needs to be proved by taking into consideration by more studies.

Heatwave events and concurrent ozone concentrations between 2006 and 2022 at two sites in southern and northern Spain.

Hotter-than-usual days are becoming more common, such that heat waves are expected to increase in intensity, frequency, duration, and spatial extent in Spain. Within this framework, this paper looks at the combined effects of extreme temperatures and air pollution in two cities in Spain, Córdoba and Valladolid, over the period 2006-2022. Synoptic patterns and air mass movement were analysed during the eleven coincident heat waves at both locations in order to study what impact orography and local meteorology have on ozone concentrations. Weak flow conditions were the most frequent synoptic pattern in the Iberian Peninsula during heat waves. Moreover, west and local circulations characterised the main air trajectories at low levels (500m agl), while southwest maritime advections and African air mass transport were more frequent at higher levels (1500 and 3000m agl) in Córdoba and Valladolid, respectively. On average, maximum ozone values were higher in Córdoba (105.1µgm-3) than in Valladolid (80µgm-3) and were strongly correlated with extreme temperatures at both locations (r up to 0.8, p-value < 0.05). Mean temperature in Córdoba was 31.9°C, with the maximum value reaching 43.7°C, while temperatures in Valladolid were lower (28.3°C and 37.3°C, respectively). Calculation and assessment of some indices helped to understand the impact of extreme events. Caution actions based on the Heat Index characterised heat wave periods. Moderate risk was the general Air Quality Health Index feature recorded and reached a very high risk of unhealthy air quality in the June 2022 event in Córdoba.

An Improved Air Health Index Based on Short-Term Cardiovascular Effects in Tianjin, China.

To construct an improved air health index (AHI) based on cardiovascular years of life lost (YLL) in Tianjin and assess its utility. We derived the exposure-response coefficients from time-series models and calculated the excess YLL (EYLL) for simultaneous exposure to air pollution and non-optimum temperature. The AHI was developed using the EYLL at the WHO 2021 Air Quality Guideline annual mean values and optimum temperature as a reference. We assessed the validity of AHI by comparing the correlations and model fit between the AHI, air quality health index (AQHI), and air quality index (AQI) with cause-specific YLLs. Each inter quartile range (IQR) increase in AHI was associated with 256.31 (95%CI: 183.05, 329.57), 150.34 (95%CI: 108.23, 192.46), 90.41 (95%CI: 64.80, 116.02) and 60.80 (95%CI:33.41, 88.18) person-year increments for non-accidental, cardiovascular, ischaemic, and cerebrovascular YLL, respectively. The AHI, in contrast to the AQHI and AQI, showed the strongest correlations with the risks of cause-specific YLLs, both in the total population and subpopulations. The AHI based on cardiovascular YLL has a greater predictive ability for health risks.

Developing and validating intracity spatiotemporal air quality health index in eastern China

BackgroundRecently pilot published city-level air quality health index (AQHI) provides a useful tool for communicating short-term health risks of ambient air pollution, but fails to account for intracity spatial heterogeneity in exposure and associated population health impacts. This study aims to develop the intracity spatiotemporal AQHI (ST-AQHI) via refined air pollution-related health risk assessments. MethodsA three-stage analysis was conducted through integrating province-wide death surveillance data and high-resolution gridded estimates of air pollution and climate factors spanning 2016–2019 in Jiangsu Province, eastern China. First, an individual-level case-crossover design was employed to quantify the short-term risk of nonaccidental mortality associated with residential exposure to individual pollutant (i.e., PM2.5, NO2, O3, and SO2). Second, we accumulated and scaled the excess risks arising from multiple pollutants to formulate daily gridded ST-AQHI estimates at 0.1° × 0.1°, dividing exposure-related risks into low (0–3), moderate (4–6), high (7–9), and extreme high (10+) levels. Finally, the effectiveness of ST-AQHI as composite risk communication was validated through checking the dose-response associations of individual ST-AQHI exposure with deaths from nonaccidental and major cardiopulmonary causes via repeating case-crossover analyses. ResultsWe analyzed a total of 1,905,209 nonaccidental death cases, comprising 785,567 from circulatory diseases and 247,336 from respiratory diseases. In the first-stage analysis, for each 10-μg/m3 rise in PM2.5, NO2, O3, and SO2 exposure at lag-01 day, population risk of nonaccidental death was increased by 0.8% (95% confidence interval: 0.7%, 0.9%), 1.9% (1.7%, 2.0%), 0.4% (0.3%, 0.5%), and 4.1% (3.7%, 4.5%), respectively. Spatiotemporal distribution of ST-AQHI exhibited a consistent declining trend throughout the study period (2016–2019), with annual average ST-AQHI decreasing from 5.2 ± 1.3 to 4.0 ± 1.0 and high-risk days dropping from 15.8% (58 days) to 1.6% (6 days). Exposure associated health risks showed great intracity- and between-city heterogeneities. In the validation analysis, ST-AQHI demonstrated approximately linear, threshold-free associations with multiple death events from nonaccidental and major cardiopulmonary causes, suggesting excellent performance in predicting exposure-related health risks. Specifically, each 1-unit rise in ST-AQHI was significantly associated with an excess risk of 2.0% (1.8%, 2.1%) for nonaccidental mortality, 2.3% (2.1%, 2.6%) for overall circulatory mortality, and 2.7% (2.3%, 3.1%) for overall respiratory mortality, as well as 1.7%–3.0% for major cardiopulmonary sub-causes. ConclusionsST-AQHI developed in this study performed well in predicting intracity spatiotemporal heterogeneity of death risks related to multiple air pollutants, and may hold significant practical importance in communicating air pollution-related health risks to the public at the community scales.

Evaluating Indoor Air Quality in Schools: Is the Indoor Environment a Haven during High Pollution Episodes?

Pollution data were collected at five schools in Hong Kong using low-cost, sensor-based monitors both indoors and outdoors during two consecutive high pollution episodes. The pollutants monitored included NO2, O3, PM2.5, and PM10, which were also used as input to a health risk communication protocol known as Air Quality Health Index (AQHI). CO2 was also measured simultaneously. The study aimed to assess the relationship between indoor pollutant concentrations and AQHI levels with those outdoors and to evaluate the efficacy of building operating practices in protecting students from pollution exposure. The results indicate that the regular air quality monitoring stations and outdoor pollutant levels at schools exhibit similar patterns. School AQHI levels indoors were generally lower than those outdoors, with PM10 levels showing a larger proportional contribution to the calculated values indoors. NO2 levels in one school were in excess of outdoor values. CO2 monitored in classrooms commonly exceeded indoor guidelines, suggesting poor ventilation. One school that employed air filtration had lower indoor PM concentrations compared to other schools; however, they were still similar to those outdoors. O3 levels indoors were consistently lower than those outdoors. This study underscores the utility of on-site, sensor-based monitoring for assessing the health impacts of indoor and community exposure to urban air pollutants. The findings suggest a need for improved ventilation and more strategic air intake placement to enhance indoor air quality.

Constructing an AQHI as a health risk communication tool for Bangkok, Thailand

In this study, we established an air quality health index (AQHI) based on the associations between multiple air pollutants and respiratory and cardiovascular outpatient department (OPD) visits to communicate the health risks from air pollution in Bangkok, Thailand. The associations between various air pollutants, namely, suspended particulate matter (PM) with an aerodynamic diameter smaller than 2.5 µm and 10 µm (PM2.5 and PM10, respectively), sulphur dioxide (SO2), and ozone (O3) and the number of OPD visits for respiratory and cardiovascular diseases in Bangkok from 2016 to 2019 were assessed using generalised additive models with a Poisson link function. Significant associations were established between most cases of cardiovascular and respiratory diseases and these pollutants with a lag time of 0–7 days. The total excess risk was calculated to construct the AQHI, which was then adjusted to an arbitrary scale and banded into four groups based on the calculated score, where 1–3, 4–6, 7–10, and 10+ represented low risk, moderate risk, high risk, and very high risk, respectively. We found that the AQHI captured both high and very high risk levels during the day for most stations. The constructed AQHI also recorded a greater number of high and very high risk days than the currently used AQI but fewer than the WHO-based AQI. Our findings suggest that the AQHI can capture the combined effects of multiple air pollutants, which makes it an effective tool for communicating air pollution-related health risks.

Identifying decadal trends in deweathered concentrations of criteria air pollutants in Canadian urban atmospheres with machine learning approaches

Abstract. This study investigates long-term trends of criteria air pollutants, including NO2, CO, SO2, O3 and PM2.5, and Ox (meaning NO2+O3) measured in 10 Canadian cities during the last 2 to 3 decades. We also investigated associated driving forces in terms of emission reductions, perturbations due to varying weather conditions and large-scale wildfires, as well as changes in O3 sources and sinks. Two machine learning methods, the random forest algorithm and boosted regression trees, were used to extract deweathered mixing ratios (or mass concentrations) of the pollutants. The Mann–Kendall trend test of the deweathered and original annual average concentrations of the pollutants showed that, on the timescale of 20 years or longer, perturbation due to varying weather conditions on the decadal trends of the pollutants are minimal (within ±2 %) in about 70 % of the studied cases, although it might be larger (but at most 16 %) in the remaining cases. NO2, CO and SO2 showed decreasing trends in the last 2 to 3 decades in all the cities except CO in Montréal. O3 showed increasing trends in all the cities except Halifax, mainly due to weakened titration reaction between O3 and NO. Ox, however, showed decreasing trends in all the cities except Victoria, because the increase in O3 is much less than the decrease in NO2. In three of the five eastern Canadian cities, emission reductions dominated the decreasing trends in PM2.5, but no significant trends in PM2.5 were observed in the other two cites. In the five western Canadian cities, increasing or no significant trends in PM2.5 were observed, likely due to unpredictable large-scale wildfires overwhelming or balancing the impacts of emission reductions on PM2.5. In addition, despite improving air quality during the last 2 decades in most cities, an air quality health index of above 10 (representing a very high risk condition) still occasionally occurred after 2010 in western Canadian cities because of the increased large-scale wildfires.

A cohort study of the multipollutant effects of PM2.5, NO2, and O3 on C-reactive protein levels during pregnancy.

PM2.5, NO2, and O3 contribute to the development of adverse pregnancy complications. While studies have investigated the independent effects of these exposures, literature on their combined effects is limited. Our objective was to study the multipollutant effects of PM2.5, NO2, and O3 on maternal systemic C-reactive protein (CRP) levels. We used data from 1170 pregnant women enrolled in the Maternal-Infant Research on Environmental Chemicals Study (MIREC) study in Canada. Air pollution exposures were assigned to each participant based on residential location. CRP was measured in third-trimester blood samples. We fit multipollutant linear regression models and evaluated the effects of air pollutant mixtures (14-day averages) using repeated-holdout Weighted Quantile Sum (WQS) regression and by calculating the Air Quality Health Index (AQHI). In multipollutant models adjusting for NO2, O3, and green space, each interquartile range (IQR) increase in 14-day average PM2.5 (IQR: 6.9 µg/m3) was associated with 27.1% (95% confidence interval [CI] = 6.2, 50.7) higher CRP. In air pollution mixture models adjusting for green space, each IQR increase in AQHI was associated with 37.7% (95% CI = 13.9, 66.5) higher CRP; and an IQR increase in the WQS index was associated with 78.6% (95% CI = 29.7, 146.0) higher CRP. PM2.5 has the strongest relationship of the individual pollutants examined with maternal blood CRP concentrations. Mixtures incorporating all three pollutants, assessed using the AQHI and WQS index, showed stronger relationships with CRP compared with individual pollutants and illustrate the importance of conducting multipollutant analyses.

Ambient Air Quality Assessment through Air Quality Index and Air Quality Health Index for Eastern Coastal Region, Gandhidham, Gujarat, India

The impact of coastal developmental projects such as ports on regional air quality has been a matter of concern, as they are known to induce rapid industrialization and urbanization as collateral development on a long-term basis. Gandhidham-Kachchh, Gujarat, India is hub for industrialization, thus various developmental activities and port activities may release toxic gases into the environment. Thus, an attempt was made to assess the present ambient air quality in and around eastern coastal region of Gandhidham, Gujarat using Air Quality Index (AQI) and Air Quality Health Index (AQHI). The primary focus was on respirable particulate matter (PM10) and fine particulate matter (PM2.5) along with other gaseous pollutants. In total 134 samples were collected from 11 stations during January to December 2018. Sampling was carried out 24 hourly on a monthly basis. Respirable particulate matter (PM10), fine particulate matter (PM2.5), sulphur dioxide and nitrogen dioxide ranged from 29-401 µg/m3, 13-184 µg/m3, 5.9-92.6 µg/m3and 3.7-33 µg/m3, respectively. The annual mean concentrations varied from 118-227 µg/m3, 47-82 µg/m3, 10-51 µg/m3, 11-41 µg/m3 for PM10, PM2.5, sulphur dioxide and nitrogen dioxide, respectively. In most of the sampling locations both the particulate matter fractions exceeded the permissible limit as prescribed in National Ambient Air Quality Standard (NAAQS). The AQI ranged from 28 to 106, which falls under Good and Satisfactory category of pollution as per the Central Pollution Control Board (CPCB) standards except at A-11 which falls under Moderate category. The AQHI was in the range of 5.9 to 15.8, which was alarming indicating Moderate to Very Higher Risk to the people. The present findings throw light on the prevailing scenario in the ambient air quality of the studied region, thereby suggesting for strict implementation and thorough control measures for reduction of particulate matters in the air.

Update of Air Quality Health Index (AQHI) and harmonization of health protection and climate mitigation

Hong Kong has used a risk-based Air Quality Health Index (AQHI) system for nearly a decade, which aggregates hospitalization risks associated with short-term exposure to pollutants. Serving as an air pollution risk communication tool, it keeps the public informed about the current air quality, anchoring around the World Health Organization's (WHO) 2005 Air Quality Guidelines (AQGs). Given the WHO's recent update to the AQGs in 2021, it is pertinent to examine how Hong Kong's air quality risk communication might be enhanced using these updated guidelines.The AQHI currently focuses only on short-term health risks, potentially leading to an underestimation of cumulative impacts. To address this, we propose enhancing the AQHI to include both long-term and short-term health risks. Short-term risks are estimated based on excess hospitalization risks from various pollutants using local data, while long-term risks are estimated using beta coefficients from the WHO due to limited local data. We further suggest using the WHO's Interim Targets (ITs) as thresholds for health risk categories, eliminating arbitrary cut-points.Promoting both public health protection and climate mitigation is important but challenging, particularly with the surge in ozone levels due to enhanced NOx controls in VOC-limited regions like Hong Kong and Guangdong. Nevertheless, despite the rise in ozone, combined health risks in these areas have decreased due to reductions in NO2 and PM concentrations. Shifting to an AQHI-like total health risk assessment emphasizes the harmonization of health protection and climate mitigation goals. This health-focused framework posits that rigorous NOx controls can effectively serve both policy objectives in tandem.

Air pollution, weather and positive airway pressure treatment adherence in adults with sleep apnea: a retrospective community-based repeated-measures longitudinal study.

We assessed the relation between air pollution, weather, and adherence to positive airway pressure (PAP) therapy in a retrospective community-based repeated-measures study of adults with obstructive sleep apnea who purchased PAP devices from a registered provider between 2013 and 2017 (Ottawa, Ontario, Canada) and had at least one day of data. Daily PAP-derived data, air pollution, and weather databases were linked using postal code. The exposures were mean nocturnal (8:00 p.m. to 8:00 a.m.) (i) residential concentrations of nitrogen dioxide (NO2 ), fine particulate matter <=2.5 μm (PM2.5 ), ozone (O3 ), and Air Quality Health Index (AQHI), and (ii) temperature, relative humidity, and barometric pressure. Covariates in the main model were demographics, season, exposure year, and PAP therapy mode. We analysed 8148 adults (median age of 54 years and 61% men) and 2,071,588 days of data. Based on daily data, the median (interquartile range) daily PAP usage was 416 (323-487) min. Using mixed-effect regression analyses to incorporate daily data and clustering by individuals, we found a statistically significant decrease in adherence for increased levels of NO2 , PM2.5 , and AQHI. The largest effect was for NO2 : a decrease in daily PAP use while comparing the highest versus lowest quartiles (Qs) was 3.4 (95% confidence interval [CI] 2.8-3.9) min. Decreased PAP adherence was also associated with increased temperature (Q4 versus Q1: 2.6 [95% CI: 1.5-3.7] min) and decreased barometric pressure (Q1 versus Q4: 2.0 [95% CI 1.5-2.5] min). We observed modest but statistically significant acute effects of air pollution and weather on daily PAP adherence.

The Relationship Between Wildfires and Respiratory Health

Wildfires have been increasing in length and frequency since the mid-1980s, which emit pollutant matter that can adversely impact human health, specifically exacerbating negative respiratory impacts (Lipner et al., 2019). Although many studies examine the respiratory impacts of worsened wildfire conditions, a limited number take place outside of the western United States, occur over prolonged periods, and look at how air quality is changing due to warming climates. The objective of this study is to investigate how air quality health index (AQHI) values have changed over a period of two decades (January 1, 2001 to December 31, 2021) in the Great Plains Air Zone (GPAZ) in southern Saskatchewan and the potential respiratory implications of AQHI changes. The study uses a mixed methods approach: time series analysis, correlation analysis, and regression analysis to analyze AQHI and a literature review to study respiratory implications of AQHI increases. We found a significant increase in AQHI over time of 19.3% (p &lt; 0.0001, n = 7308) and three main outcomes for respiratory data: (1) individuals with respiratory conditions have increased susceptibility to worsened air conditions, (2) elevated AQHI values cause increases in healthcare admittances for respiratory conditions such as asthma and COPD, and (3) women and individuals in the age ranges of 15-65 are particularly susceptible to respiratory outcomes from wildfire smoke. The study provides areas for future research, including the implementation of apps to track respiratory outcomes, the impact of other risk factors on respiratory health, and the effects of AQHI on Indigenous populations.

A Framework for the Estimation of Air Quality by Applying Meteorological Images: Colours-of-the-Wind (COLD)

This paper presents a new framework, “colours-of-the-wind” (COLD), which is designed to estimate air quality based on images from meteorological cameras, data analytics techniques, and the application of deep learning. Existing air quality estimation systems mainly rely on physical monitoring stations, which are limited by the monitoring stations’ physical constraints. Instead of collecting data from environmental monitoring stations, COLD collects air quality data from meteorological cameras. This approach can collect data from any location where a camera could capture a reliable image, which is otherwise not collectable by the physical environmental monitoring station(s). This approach can also avoid bias due to the location of data collection. The system is evaluated by building a prototype based on the Air Quality Health Index from the Hong Kong Observatory. This is one of the unique data-analytic frameworks based on such air quality measurement. The COLD’s air quality estimation is also based on AQHI, the first machine learning-based estimation framework that generates AQHI as the proposed output. Experimental results suggest that the approach adopted by the COLD prototype is feasible and has some promising outcomes. The results also suggest possible parameters for the CNN model used for the training and analyses of the images.

A New Global Air Quality Health Index Based on the WHO Air Quality Guideline Values With Application in Cape Town.

Objectives: This study developed an Air Quality Health Index (AQHI) based on global scientific evidence and applied it to data from Cape Town, South Africa. Methods: Effect estimates from two global systematic reviews and meta-analyses were used to derive the excess risk (ER) for PM2.5, PM10, NO2, SO2 and O3. Single pollutant AQHIs were developed and scaled using the ERs at the WHO 2021 long-term Air Quality Guideline (AQG) values to define the upper level of the "low risk" range. An overall daily AQHI was defined as weighted average of the single AQHIs. Results: Between 2006 and 2015, 87% of the days posed "moderate to high risk" to Cape Town's population, mainly due to PM10 and NO2 levels. The seasonal pattern of air quality shows "high risk" occurring mostly during the colder months of July-September. Conclusion: The AQHI, with its reference to the WHO 2021 long-term AQG provides a global application and can assist countries in communicating risks in relation to their daily air quality.

A Case Study of Air Quality and a Health Index over a Port, an Urban and a High-Traffic Location in Rhodes City

One of people’s greatest concerns about air quality degradation is its impact on human health. This work is a case study that aims to investigate the air quality and the related impact on people’s health in a coastal city over the eastern Mediterranean. The analysis proceeded during a low-tourist density period, covering the days from 17 to 27 November 2022. Hourly PM2.5, NO2 and O3 concentration records from three, mobile, Air Quality Monitoring Systems (AQMS), established in an urban location, port and central area of Rhodes city, are analyzed. To investigate the impact of pollution levels on human health, the Air Quality Health Index (AQHI) is calculated. The daily and diurnal variation of pollutants’ concentration and AQHI among the different areas, as well as the relation among the ambient air pollutants and AQHI, are studied. Additionally, to investigate the impact of wind regime on the variation of pollution and AQHI levels, the hourly zonal and meridional wind-speed components, as well as the temperature at 2 m, the dew point temperature at 2 m, and the height of the boundary layer from ERA5 reanalysis, are retrieved for the region of the southeastern Mediterranean. Results show that the highest pollution level occurs in the city center of Rhodes, compared to the rest of the studied locations. In general, the findings do not show exceedances of the pollutants’ concentration according to the European Directive 2008/50/EC. Moreover, findings show that in some cases, the health risk is classified from Low to Moderate in terms of AQHI. The analysis indicates that the climate conditions affect the pollutants’ concentration due to dispersion, and likely, the atmospheric transport of pollutants. Finally, this work aims to improve the knowledge regarding the air quality of southeastern Greece, promoting the framework for the green and sustainable development of the South Aegean Sea.

Air quality health index (AQHI) based on multiple air pollutants and mortality risks in Taiwan: Construction and validation

The currently used air quality index (AQI) is not able to capture the additive effects of air pollution on health risks and reflect non-threshold concentration-response relationships, which has been criticized. We proposed the air quality health index (AQHI) based on daily air pollution-mortality associations, and compared its validity in predicting daily mortality and morbidity risks with the existing AQI. We examined the excess risk (ER) of daily elderly (≥65-year-old) mortality associated with 6 air pollutants (PM2.5, PM10, SO2, CO, NO2, and O3) in 72 townships across Taiwan from 2006 to 2014 by performing a time-series analysis using a Poisson regression model. Random effect meta-analysis was used to pool the township-specified ER for each air pollutant in the overall and seasonal scenarios. The integrated ERs for mortality were calculated and used to construct the AQHI. The association of the AQHI with daily mortality and morbidity were compared by calculating the percentage change per interquartile range (IQR) increase in the indices. The magnitude of the ER on the concentration-response curve was used to evaluate the performance of the AQHI and AQI, regarding specific health outcomes. Sensitivity analysis was conducted using coefficients from the single- and two-pollutant models. The coefficients of PM2.5, NO2, SO2, and O3 associated with mortality were included to form the overall and season-specific AQHI. An IQR increase in the overall AQHI at lag 0 was associated with 1.90%, 2.96%, and 2.68% increases in mortality, asthma, and respiratory outpatient visits, respectively. The AQHI had higher ERs for mortality and morbidity on the validity examinations than the current AQI. The AQHI, which captures the combined effects of air pollution, can serve as a health risk communication tool to the public.

Disease specific air quality health index (AQHI) for spatiotemporal health risk assessment of multi-air pollutants

While significant reductions in certain air pollutant concentrations did not induce obvious mitigations of health risks, a shift from air quality management to health risk prevention and control might be necessary to protect public health. This study thus constructed an Air Quality Health Index (AQHI) for respiratory (Res-AQHI), cardiovascular (Car-AQHI), and allergic (Aller-AQHI) risk groups using mixed exposure under multi-air pollutants and portrayed their distribution and variation at multiple spatiotemporal scales using spatial analysis in GIS with the medical big data and air pollution remote sensing data by taking Hunan Province in China as a case. Results showed that the AQHIs constructed for specific health-risk groups could better express their risks than common AQHI and AQI. Moreover, based on the spatiotemporal association of health and environmental information, the allergic risk group in Hunan provided the highest health risk mainly affected by O3. The following cardiovascular and respiratory risk groups can be significantly attributed to NO2. Moreover, the spatiotemporal heterogeneity of AQHIs within regions was also evident. On the annual scale, the population in the air health risk hotspots for respiratory and cardiovascular risk decreased, while allergic risks increased. Meanwhile, on seasonal scale, the hotspots for respiratory and cardiovascular risks expanded significantly in winter while completely disappearing for allergic risk. These findings suggest that disease specific AQHIs effectively disclose the health effects of multi-air pollutants and their subsequently varied spatiotemporal distribution patterns.

Health Risks Forecast of Regional Air Pollution on Allergic Rhinitis: High-Resolution City-Scale Simulations in Changchun, China

Accurate assessments of exposure to urban air pollution with higher traffic emissions and its health risks still face several challenges, such as intensive computation of air pollution modeling and the limited availability of personal activity data. The macroscopic health effects can be transmitted to the whole population for personal prevention via air quality health index (AQHI), but the possibility risk index of the specific allergic diseases is still lacking. This interdisciplinary study aims at evaluating the forecasted results of high-resolution air quality with updated traffic emissions and accessing the potential impacts of outdoor pollution on morbidity of rhinitis for urban residents. A high-resolution modelling system (1 km × 1 km) containing the online traffic emission model (VEIN), meteorological and air quality model (WRF-CHIMERE) and the health impact module was developed. A new health index of Potential Morbidity Risk Index (PMRI) was further established using higher resolution health risk coefficients of major air pollutants on allergic rhinitis, and different methods (with/without considering population distributions) targeting different user groups (residents, hospitals and health administrations) were calculated and analyzed. Operational forecasted results of hourly PMRI can be further combined with online map services to serve as an effective tool for patients with allergic rhinitis to arrange their daily activities so as to avoid acute exacerbation. The forecasted PMRIs accessible to the public will also be beneficial for the public health administrations in planning the medical resource and improving the outpatient efficiency.

Evaluation of the health risk using multi-pollutant air quality health index: case study in Tianjin, China.

Air pollution imposes a significant burden on public health. Compared with the popular air quality index (AQI), the air quality health index (AQHI) provides a more comprehensive approach to measuring mixtures of air pollutants and is suitable for overall assessments of the short-term health effects of such mixtures. We established an AQHI and cumulative risk index (CRI)-AQHI for Tianjin using single-and multi-pollutant models, respectively, as well as environmental, meteorological, and daily mortality data of residents in Tianjin between 2018 and 2020. Compared with the AQI, the AQHI and CRI-AQHI established herein correlated more closely with the exposure-response relationships of the total mortality effects on residents. For each increase in the interquartile range of the AQHI, CRI-AQHI and AQI, the total daily mortality rates increased by 2.06, 1.69 and 0.62%, respectively. The AQHI and CRI-AQHI predicted daily mortality rate of residents more effectively than the AQI, and the correlations of AQHI and CRI-AQHI with health were similar. Our AQHI of Tianjin was used to establish specific (S)-AQHIs for different disease groups. The results showed that all measured air pollutants had the greatest impact on the health of persons with chronic respiratory diseases, followed by lung cancer, and cardiovascular and cerebrovascular diseases. The AQHI of Tianjin established in this study was accurate and dependable for assessing short-term health risks of air pollution in Tianjin, and the established S-AQHI can be used to separately assess health risks among different disease groups.