Atmospheric pollution and mortality in Portugal: Quantitative assessment of the environmental burden of disease using the AirQ+ model

Assessment of disease burden and mortality attributable to air pollutants in northwestern Iran using the AirQ+ software

It is well known that one of the main causes of mortality and reduced life expectancy is air pollution, which carries the highest burden of diseases attributed to environmental factors. The poor air quality in Iranian cities leads to a wide range of acute and chronic health effects. This study estimates the natural deaths, ALRI, COPD, lung cancer, IHD, and strokes caused by air pollutants in Bukan, a southern city in West Azerbaijan Province, from 2011 to 2019. Population data was obtained from government organizations, and pollutant data for 2011-2019 was collected from the Bukan Environmental Protection Organization. Analyses were performed using Excel, and the data was subsequently entered into the WHO's AirQ+ model to extract the results. The study found that long-term exposure to PM10, PM2.5, NO2, and O3 resulted in an estimated 316, 241, 14, and 52 deaths, respectively. By comparing the air quality over the 8-year period, it was determined that the air quality in Bukan city is not in good condition, with particulate matter levels exceeding relevant standards. Given the increasing trend of air pollution and associated health impacts, it is essential to implement effective control policies to improve the city's air quality. This information provides a crucial step for city managers, policymakers, and health officials to mitigate the health effects caused by air pollution.

Assessment of air pollution and mortality in Portugal using AirQ+ and the effects of COVID-19 on their relationship

This study uses the World Health Organization's AirQ+ model to assess the relationship between air pollution and mortality in Portugal from 2010 to 2021, focusing on the impact of the COVID-19 pandemic. By integrating AirQ+ with Linear Mixed Models, we analyzed long-term air pollution data and its health effects. Results indicate a significant decrease in [Formula: see text] and [Formula: see text] concentrations in 2020 and 2021 due to COVID-19 restrictions and reduced transportation emissions. Conversely, [Formula: see text] exposure slightly increased. The model estimates over 5000 annual deaths from [Formula: see text] and [Formula: see text] exposure and over 139 annual deaths from [Formula: see text]-related respiratory diseases for 2010-2021. Despite limitations like the need for better assessment of pollutant mixtures and climatic variables, the study shows a decrease in [Formula: see text]-related disease burden during the pandemic. These trends reflect anomalies in mortality and pollution data rather than policy improvements. The study underscores the utility of AirQ+ in guiding public health strategies and tracking progress toward the 2030 Agenda, offering insights into reducing mortality and morbidity through decreased air pollutant exposure and highlighting the need for sustained, multidimensional pollution reduction efforts.

Impact of monthly air pollution and weather conditions on cardiorespiratory mortality in Portuguese Metropolitan Areas

This study analyses cardiorespiratory mortality rates (CARDIO) and their association with air pollutants - particulate matter with aerodynamic diameters lower of equal to 10 or 2.5 (µm) (PM10, PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3) - and meteorological variables (temperature, humidity, wind speed, direction) in the Lisbon (LMA) and Porto (PMA) metropolitan areas from 2011 to 2020. Monthly analyses reveal regional patterns and seasonal variations. The results show that PMA had a higher average CARDIO rate (202.94 [Deaths per 100 000]) compared to LMA (169.70 [Deaths per 100 000]). Linear and Poisson regression, contingency tables, correspondence analysis and Pearson's chi-squared tests confirmed significant associations between low temperature and wind speeds, high pollutant concentrations, and increased mortality. Lower temperature (≤ 13 [°C]) and wind speed (≤ 2.5 [m/s]) were consistently associated with increased CARDIO in both regions. High pollutant levels, particularly PM10 (≥ 24 [µg/m³]) and NO2 (≥ 24 [µg/m³]), were also associated with higher CARDIO rates. Additionally, high PM2.5 and CO levels were linked to increased CARDIO in LMA. The seasonal Mann-Kendall test showed no significant trend in CARDIO for LMA, but a statically significant increasing trend of 2.14 [Deaths per 100 000]) per month for PMA. This study shows the importance of mid-term exposure standards and emphasises the need for multifactorial assessments of air quality and meteorological impacts on health, as regional differences in pollutant dynamics and meteorological conditions may significantly impact cardiorespiratory mortality in urban areas.

Short-term exposure to PM2.5 pollution in Iran and related burden diseases

The objective of this study was to estimate the health effects attributed to PM2.5 exposure in southwest of Iran. In order to estimate HA-CVD, HA-RD, LC-M, I-As in children, RAD, and WDL, the exposure-response function method was used. The annual mean of PM2.5 regularly exceeded 5.26-8.5 times from 2021 annual limit value established by the WHO. The dominance of PM2.5 in PM2.5/PM10 ratio decreased -34.6% from 2015 to 2020.  The results showed that the risks of HA-CVD (- 51. 9), HA-RD (- 68.7%), LC-M (- 43.6%), I-As (- 52.1%), RAD (- 56.8%), and WDL (- 58.7%) declined per 105 inhabitants between 2018 and 2020 . Reducing the particulate emissions from industries and road traffic led to lower exposure to PM2.5, which will be effective in decrease of mortality rate.

Quantifying the health impact of PM2.5 with various chemical transport models and for different years - A case study for Poland

Poland is in the group of European countries with the most severe air quality and specific emission structure (over 80 % of PM2.5 emitted in residential combustion). In this work, we quantify the health impacts of PM2.5 concentrations in Poland using two chemical transport models (CTMs), WRF-Chem and EMEP4PL. The models were run for two years (2017 and 2018), which differed in meteorological conditions. The results show that the total number of premature deaths that could be avoided if the PM2.5 concentrations do not exceed the WHO recommended value of 5 μg m-3 exceeds 22,000 deaths for all model runs and meteorological years considered, with the lowest estimate at 22,447 (WRF-Chem model run for the year 2017; 95 % confidence intervals CI (95 % CI) 17121-25045) and the highest at 29,227 (95 % CI 22343 - 32572; EMEP4PL for the year 2018). These numbers are underestimated, as both CTMs underestimate the measured PM2.5 concentrations at site locations. The underestimation is the highest during the heating seasons and can be reduced if the emission of primary PM2.5 from residential combustion increases. The total number of estimated premature deaths is sensitive to chemical transport model selection and meteorological year. The selection of the meteorological year for the analysis may change the estimated number of premature deaths by 10 %. This change is significant compared to the estimated change in health impact due to the envisaged implementation of the Clean Air Program in Poland.

Spatio-temporal variation of particulate matter with health impact assessment and long-range transport - case study: Ankara, Türkiye

A clean atmosphere should be provided as a right for human beings to live. The reality is that a significant proportion of the population is exposed to air pollution. This study presents an in-depth investigation into the spatio-temporal dynamics of PM2.5 concentrations in Ankara, Türkiye, spanning over three years. With particular emphasis on the impact of COVID-19 lockdown measures and local air quality management strategies, data from eight air pollution monitoring stations were analyzed. The findings indicate a significant reduction in PM2.5 levels during lockdown periods, with an average decrease of 18 % observed across the city. Implementing the Ankara Provincial Clean Air Action Plan further contributed to a 9.1 % decrease in PM2.5 concentrations in 2021, followed by an additional 6.6 % decrease in 2022 compared to 2020. The spatial distribution of PM2.5 concentrations reveals the influence of industrial and urban areas on pollution levels. Potential Source Contribution Function (PSCF) and Concentration-Weighted Trajectory (CWT) methods were employed to investigate the spatial and temporal variation of long-range transport source regions contributing to the PM2.5 levels in Ankara. PSCF and CWT analyses revealed a decreasing trend in anthropogenic contribution to PM2.5 from 2020 to 2022. The AirQ+ model was employed to predict the long-term mortality rates attributable to PM2.5 across different monitoring stations. Based on the estimations, all stations' average estimated attributable proportion is 9.8 % (3.3 %-27.8 %). The results depict varying trends in estimated mortality rates, emphasizing the importance of targeted interventions to mitigate the public health risks arising from exposure to polluted air. Overall, the results of this study show significant measures for the development of effective clean air quality strategies can effectively change the direction of the adverse impact of air pollution on public health.

Pollutant-meteorological factors and cardio-respiratory mortality in Portugal: Seasonal variability and associations

Seasonal variations in cardiorespiratory diseases may be influenced by air pollution and meteorological factors. This work aims to highlight the relevance of a complete seasonal characterization of the pollutant-meteorological factors and cardio-respiratory mortality in Portugal and the relationships between health outcomes and environmental risk factors. To this end, air pollution and meteorological variables along with health outcomes were analyzed at national level and on a monthly basis for the period of 2011-2020. It was found that cardiorespiratory mortality rates during winter were 44% higher than during the summer. Furthermore, particulate matter with aerodynamic diameters of 10 and 2.5 μm (μm) or smaller (PM10 and PM2.5), carbon monoxide (CO) and nitrogen dioxide (NO2) showed a seasonal variability with the highest concentrations during winter while ozone (O3) presented higher concentrations during spring and summer. PM10, PM2.5 and NO2, showed a positive correlation between seasons, indicating similar patterns of behavior. Canonical correlation analysis (CCA) applied to pollutant-meteorological and cardiorespiratory mortality data indicates a strong linear correlation between pollutant-meteorological factors and health outcomes. The first canonical correlation was 0.889, and the second was 0.545, both statistically significant (p-value < 0.001). The CCA results suggest that there is a strong association between near-surface temperature, relative humidity, PM10, PM2.5, CO and NO2 and health outcomes. The results of this study provide important information of the seasonal variability of air pollutants and meteorological factors in Portugal and their associations with cardiorespiratory mortality.

Assessing the effect of COVID-19 pandemic on air quality change and human health outcomes in a capital city, southwestern Iran

The aimsof this study were to assess the spatial variation of PM2.5, NO2, and O3 between 2019 (before) and 2020 (during COVID-19 pandemic); and calculation the health outcomes of exposure to these pollutants. The daily PM2.5, NO2, and O3 concentrations were applied to assess health effects by relative risk, and baseline incidence. The annual PM2.5 and NO2 mean concentrations exceeded the WHO guideline values, while O3 did not exceed. The restrictive measures associated to COVID-19 led to reduction at the annual means of PM2.5 and NO2 by -25.5% and -23.1%, respectively, while the annual mean of O3 increased by +7.9%. The number of M-CVD and M-RD (-25.6%, -26.1%) related to PM2.5 exposure, and HA-COPD and HA-RD >65 years old (-21% and -3.84%) related to NO2 exposure were reduced in 2020, and O3 exposure-related M-CVD (+30.1%) and HA-RD >65 years old (+23.4%) increased compared to the previous year 2019.

Community Empowerment Assessment and Community Nursing Diagnosis for Climate Change Mitigation and Adaptation in the Northern Region of the Portuguese Atlantic Coast: A Mixed-Methods Study Using MAIEC Framework

The Community Intervention and Empowerment Assessment Model (MAIEC) offers a framework for community empowerment in several fields such as Climate Change (CC), the largest health emergency crisis globally, through diagnosis and interventions in Community Health Nursing. This study aims to assess the level of community empowerment in climate change mitigation and adaptation, and to identify nursing diagnosis through the MAIEC clinical decision matrix, within a local intermunicipal association in the northern region of the Portuguese Atlantic Coast. A convergent mixed-methods design was used, applying a focus group technique to a purposive sampling of ten key stakeholders of this community. A Portuguese version of the Empowerment Assessment Rating Scale and a questionnaire were both applied to the same participants, and qualitative and quantitative data generated were analysed using a content analysis technique and an Excel database sheet created using Microsoft Office 365. The analysis of the Portuguese northern community exposed: a low level of community empowerment for mitigation and adaptation to climate change; a nursing diagnosis of community management impairments in several dimensions, such as community process, community participation and community leadership. However, the study confirmed that MAIEC contributed to future community-based solutions, responding to the challenges of climate change, and enabling the planning of interventions to address MAIEC diagnoses in the form of CC-specific training and recommendations for new cooperation approaches from all stakeholders. This study was not registered.

Air quality trends and implications pre and post Covid-19 restrictions

Air pollution causes millions of premature deaths every year. Thus, air quality assessment is essential to preserve human health and support authorities to identify proper policies. In this study, concentration levels of 6 air contaminants (benzene, carbon monoxide, nitrogen dioxide, ground level ozone, particulate matters) as monitored in 2019, 2020 and 2021 by 37 stations, located in Campania (Italy) were analysed. Particular attention has been paid to March-April 2020 period to get clues on the possible effects of the lockdown regulations, imposed in Italy from March 9th to May 4th to limit COVID-19 spread, on atmospheric pollution. Air Quality Index (AQI), an algorithm developed by the United States Environmental Protection Agency (US-EPA), allowed us to classify the air quality from moderately unhealthy to good for sensitive groups. The evaluation of air pollution impact on human health by using the AirQ+ software evidenced a significant decrement of adult mortality in 2020 respect to 2019 and 2021. Among the six pollutants considered, PM₁₀ and PM_2.5 resulted the less affected by the lockdown restrictions. Finally, a comparison between NO₂ ground level concentration and the reprocessed Level 2 NO₂ tropospheric column concentration obtained from satellite surveys highlighted as concentration measured at the ground level stations can be strongly influenced by the station position and its surroundings.

Cardiovascular, respiratory and all-cause (natural) health endpoint estimation using a spatial approach in Malaysia

In 2016, the World Health Organization (WHO) estimated that approximately 4.2 million premature deaths worldwide were attributable to exposure to particulate matter 2.5 μm (PM_2.5). This study assessed the environmental burden of disease attributable to PM_2.5 at the national level in Malaysia. We estimated the population-weighted exposure level (PWEL) of PM10 concentrations in Malaysia for 2000, 2008, and 2013 using aerosol optical density (AOD) data from publicly available remote sensing satellite data (MODIS Terra). The PWEL was then converted to PM_2.5 using Malaysia's WHO ambient air conversion factor. We used AirQ+ 2.0 software to calculate all-cause (natural), ischemic heart disease (IHD), stroke, chronic obstructive pulmonary disease (COPD), lung cancer (LC), and acute lower respiratory infection (ALRI) excess deaths from the National Burden of Disease data for 2000, 2008 and 2013. The average PWELs for annual PM_2.5 for 2000, 2008, and 2013 were 22 μg m-3, 18 μg m-3 and 24 μg m-3, respectively. Using the WHO 2005 Air Quality Guideline cut-off point of PM_2.5 of 10 μg m-3, the estimated excess deaths for 2000, 2008, and 2013 from all-cause (natural) mortality were between 5893 and 9781 (95 % CI: 3347-12,791), COPD was between 164 and 957 (95 % CI: 95-1411), lung cancer was between 109 and 307 (95 % CI: 63-437), IHD was between 3 and 163 deaths, according to age groups (95 % CI: 2-394) and stroke was between 6 and 155 deaths, according to age groups (95 % CI: 3-261). An increase in estimated health endpoints was associated with increased estimated PWEL PM_2.5 for 2013 compared to 2000 and 2008. Adhering the ambient PM_2.5 level to the Malaysian Air Quality Standard IT-2 would reduce the national health endpoints mortality.

Health risk assessment for particulate matter: application of AirQ+ model in the northern Caribbean region of Colombia

Air pollution is considered the world's most important environmental and public health risk. The annual exposure for particulate matter (PM) in the northern Caribbean region of Colombia between 2011 and 2019 was determined using PM records from 25 monitoring stations located within the area. The impact of exposure to particulate matter was assessed through the updated Global Burden of Disease health risk functions using the AirQ+ model for mortality attributable to acute lower respiratory disease (in children ≤ 4 years); mortality in adults aged > 18 years old attributable to chronic obstructive pulmonary disease, ischaemic heart disease, lung cancer, and stroke; and all-cause post-neonatal infant mortality. The proportions of the prevalence of bronchitis in children and the incidence of chronic bronchitis in adults attributable to PM exposure were also estimated for the population at risk. Weather Research and Forecasting-California PUFF (WRF-CALPUFF) modeling systems were used to estimate the spatiotemporal trends and calculate mortality relative risk due to prolonged PM2.5 exposure. Proportions of mortality attributable to long-term exposure to PM2.5 were estimated to be around 11.6% of ALRI deaths in children ≤ 4 years of age, 16.1% for COPD, and 26.6% for IHD in adults. For LC and stroke, annual proportions attributable to PM exposure were estimated to be 9.1% and 18.9%, respectively. An estimated 738 deaths per year are directly attributed to particulate matter pollution. The highest number of deaths per year is recorded in the adult population over 18 years old with a mean of 401 events. The mean risk in terms of the prevalence of bronchitis attributable to air pollution in children was determined to be 109 per 100,000 inhabitants per year. The maximum RR values for mortality (up 1.95%) from long-term PM2.5 exposure were predicted to correspond to regions downwind to the industrial zone.

Supplementary information

The online version contains supplementary material available at 10.1007/s11869-023-01304-5.

Ambient PM2.5 and O3 pollution and health impacts in Iranian megacity

The main objectives of this study were to (i) assess variation within fine particles (PM_2.5) and tropospheric ozone (O₃) time series in Khorramabad (Iran) between 2019 (before) and 2020 (during COVID-19 pandemic); (ii) assess relationship between PM_2.5 and O₃, the PM_2.5/O₃ ratio, and energy consumption; and (iii) estimate the health effects of exposure to ambient PM_2.5 and O₃. From hourly PM_2.5 and O₃ concentrations, we applied both linear-log and integrated exposure-response functions, city-specific relative risk, and baseline incidence values to estimate the health effects over time. A significant correlation was found between PM_2.5 and O₃ (r =-0.46 in 2019, r =-0.55 in 2020, p < 0.05). The number of premature deaths for all non-accidental causes (27.5 and 24.6), ischemic heart disease (7.3 and 6.3), chronic obstructive pulmonary disease (17 and 19.2), and lung cancer (9.2 and 6.25) attributed to ambient PM_2.5 exposure and for respiratory diseases (4.7 and 5.4) for exposure to O₃ above 10 µg m^-3 for people older than 30-year-old were obtained in 2019 and 2020. The number of years of life lost declined by 11.6% in 2020 and exposure to PM_2.5 reduced the life expectancy by 0.58 and 0.45 years, respectively in 2019 and 2020. Compared to 2019, the restrictive measures associated to COVID-19 pandemic led to reduction in PM_2.5 (-25.5%) and an increase of O₃ concentration (+ 8.0%) in Khorramabad.