Air quality and characterization of synoptic circulation weather patterns in a South American city from Argentina

The potential cause-effect relationship between synoptic meteorological conditions and levels of criteria air pollutants, including CO, NO2, O3, PM10, PM2.5 and SO2, in Bahia Blanca, Argentina, was assessed for the period of 2018-2019. Daily back-trajectories and global meteorological data fields were employed to characterize the primary transport paths of air masses reaching the study site, and to identify the synoptic meteorological patterns responsible for these atmospheric circulations. Time series of surface-level meteorological parameters and midday mixing layer height were collected to examine the impact of the synoptic meteorological patterns on local meteorology. Furthermore, the NAAPS global aerosol model was utilized to identify days when contributions from long-range transport processes, such as dust and/or biomass burning smoke, impacted air quality. By applying this methodology, it was determined that the air masses coming from the N, NW and W regions significantly contributed to increased mean concentrations of coarse particles in this area through long-range transport events involving dust and smoke. Indeed, the high average levels of PM10 recorded in 2018-2019 (annual mean values of 47 and 52 μg/m3, respectively) represent the main air quality concern in Bahía Blanca. Moreover, PM10, PM2.5 and NO2 emissions should be reduced in order to meet recommended air quality guidelines. On the other hand, the results from this study suggest that the sources and meteorological processes leading to the increase in the concentrations of CO and SO2 have a local-regional origin, although these air pollutants did not reach high values probably as a consequence of the strong wind speed registered in this region during any synoptic meteorological pattern.

Air pollution, cardiovascular disease, and urban greening: an ecological blueprint

A number of studies and systematic reviews indicate that exposure to greenness reduces of all-cause, non accidental mortality, particularly from cardiopulmonary and cancer causes. There is also some evidence that green space residence may be associated with improved pregnancy and birth outcomes, and with better school performances in children. Furthermore, because at least one third of the premature deaths are globally attributable to exposure to air pollution due household agents, particularly in fragile populations living in low-income countries (i.e., children, older and deprived people, pregnant women), that houseplants are an effective and economic mean for cleaning indoor air and thus reducing volatile organic compounds such as formaldehyde, benzene, toluene and others. On the whole more prospective studies are needed to further elucidate the mechanisms linking air pollution, greenness and health outcomes, although the multiple and interacting mechanisms depicted in this article are all biologically plausible.

Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models

BACKGROUND

A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO₂. Assessing whether and to what extent air quality standards for NO₂ should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO₂ and related health risks, which have not been studied to date.

OBJECTIVE

We predicted ground NO₂ concentrations with high resolution in mainland China, explored exposure characteristics to NO₂ pollution, and assessed the mortality burden attributable to NO₂ exposure.

METHODS

Daily NO₂ concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO₂, population and area percentages with NO₂ exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO₂ exposure in China.

RESULTS

The cross-validation R²and root mean squared error of the NO₂ predicting model were 0.80 and 7.78 μg/m³, respectively,at the daily level in 2019.The percentage of people (population number) with annual NO₂ exposure over 40 μg/m³ in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 μg/m³. NO₂ levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO₂ were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit.

CONCLUSION

In China, NO₂ pollution is associated with significant mortality burden. Spatial disparities exist in NO₂ pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO₂ pollution and exposure risk. Tightening the national standards for NO₂ is needed and will lead to significant health benefits.

Proposed city-specific interim targets for India based on WHO air quality guidelines 2021

The World Health Organization has proposed the ambient air quality guidelines 2021. The uniqueness of the guidelines of the World Health Organization - air quality guidelines 2021 - is the inclusion of interim targets. Higher levels of air pollutants including PM_2.5 for ambient air in India were recorded in recent times, and its association with respiratory and cardiovascular health risks was evidenced in the recent literature. To achieve the ambient air quality standards in India as per the World Health Organization - air quality guidelines, there is a need for interim targets in the future National Ambient Air Quality Standards to be proposed in India. These interim targets may be proposed for non-attainment/attainment cities based on the PM_2.5 concentration levels to achieve a realistic target of recommended levels in a graded manner and thereby minimize air pollution in the specific location.

Evaluating the spatiotemporal ozone characteristics with high-resolution predictions in mainland China, 2013-2019

Evaluating ozone levels at high resolutions and accuracy is crucial for understanding the spatiotemporal characteristics of ozone distribution and assessing ozone exposure levels in epidemiological studies. The national models with high spatiotemporal resolutions to predict ground ozone concentrations are limited in China so far. In this study, we aimed to develop a random forest model by combining ground ozone measurements from fixed stations, ozone simulations from the Community Multiscale Air Quality (CMAQ) modeling system, meteorological parameters, population density, road length, and elevation to predict ground maximum daily 8-h average (MDA8) ozone concentrations at a daily level and 1 km × 1 km spatial resolution. The model cross-validation R² and root mean squared error (RMSE) were 0.80 and 20.93 μg/m³ at daily level in 2013-2019, respectively. CMAQ ozone simulations and near-surface temperature played vital roles in predicting ozone concentrations among all predictors. The population-weighted median concentrations of predicted MDA8 ozone were 89.34 μg/m³ in mainland China in 2013, and reached 100.96 μg/m³ in 2019. However, the long-term temporal variations among regions were heterogeneous. Central and Eastern China, as well as the Southeast Coastal Area, suffered higher ozone pollution and higher increased rates of ozone concentrations from 2013 to 2019. The seasonal pattern of ozone pollution varied spatially. The peak-season ozone pollution with the highest 6-month ozone concentrations occurred in different months among regions, with more than half domain in April-September. The predictions showed that not only the annual mean concentrations but also the percentages of grid-days with MDA8 ozone concentrations higher than 100/160 μg/m³ have been increasing in the past few years in China; meanwhile, majority areas in mainland China suffered peak-season ozone concentrations higher than the air quality guidelines launched by the World Health Organization in September 2021. The proposed model and ozone predictions with high spatiotemporal resolution and full coverage could provide health studies with flexible choices to evaluate ozone exposure levels at multiple spatiotemporal scales in the future.

The role of burden of disease assessment in tracking progress towards achieving WHO global air quality guidelines

OBJECTIVES

More than 90% of the global population live in areas exceeding the PM2.5 air quality guidelines (AQGs). We provide an overview of the ambient PM2.5-related burden of disease (BoD) studies along with scenario analysis in the framework of the WHO AQG update on the estimated reduction in the BoD if AQGs were achieved globally.

METHODS

We reviewed the literature for large-scale studies for the BoD attributed to ambient PM2.5. Moreover, we used the latest WHO statistics to calculate the BoD at current levels and the scenarios of aligning with interim targets and AQG levels.

RESULTS

The most recent BoD studies (2010 onwards) share a similar methodology, but there are differences in the input data which affect the estimates for attributable deaths (2.9-8.9 million deaths annually). Moreover, we found that if AQGs were achieved, the estimated BoD would be reduced by up to 50% in total deaths worldwide.

CONCLUSIONS

Understanding the BoD across countries, especially in those that do not align with the AQGs, is essential in order to inform actions to reduce air pollution globally.

Modelling air quality levels of regulated metals: limitations and challenges

Toxic metals as arsenic (As), cadmium (Cd), nickel (Ni), and lead (Pb) exist in the atmosphere as particulate matter components. Their concentration levels in the European Union (EU) are regulated by European legislation, which sets target and limit values as annual means, and by the World Health Organization (WHO) that defines guidelines and reference values for those metal elements. Modelling tools are recommended to support air quality assessment regarding the toxic metals; however, few studies have been performed and those assessments rely on discrete measurements or field campaigns. This study aims to evaluate the capability of air quality modelling tools to verify the legislation compliance concerning the atmospheric levels of toxic elements and to identify the main challenges and limitations of using a modelling assessment approach for regulatory purposes, as a complement to monitoring. The CAMx air quality model was adapted and applied over Porto and Lisbon urban regions in Portugal at 5 × 5-km2 and 1 × 1-km2 horizontal resolution for the year 2015, and the results were analysed and compared with the few measurements available in three locations. The comparison between modelled and measured data revealed an overestimation of the model, although annual averages are much lower than the regulated standards. The comparison of the 5-km and 1-km resolutions' results indicates that a higher resolution does not necessarily imply a better performance, pointing out uncertainties in emissions and the need to better describe the magnitude and spatial allocation of toxic metal emissions. This work highlighted that an increase of the spatial and temporal coverage of monitoring sites would allow to improve the model design, contribute to a better knowledge on toxic metals atmospheric emission sources and to increase the capacity of models to simulate atmospheric particulate species of health concern.

Bayesian geostatistical modelling of high-resolution NO2 exposure in Europe combining data from monitors, satellites and chemical transport models

Bayesian geostatistical regression (GR) models estimate air pollution exposure at high spatial resolution, quantify the prediction uncertainty and provide probabilistic inference on the exceedance of air quality thresholds. However, due to high computational burden, previous GR models have provided gridded ambient nitrogen dioxide (NO₂) concentrations at smaller areas of investigation. Here, we applied these models to estimate yearly averaged NO₂ concentrations at 1 km² spatial resolution across 44 European countries, integrating information from in situ monitoring stations, satellites and chemical transport model (CTM) simulations. The tropospheric values of NO₂ derived from the ozone monitoring instrument (OMI) onboard the National Aeronautics and Space Administration's (NASA's) Aura satellite were converted to near ground NO₂ concentration proxies using simulations from the 3-D global CTM (GEOS-Chem) at 0.5° × 0.625°spatial resolution and surface-to-column NO₂ ratios. Simulations from the Ensemble of regional CTMs at spatial resolution of 0.1° × 0.1°were extracted from the Copernicus atmosphere monitoring service (CAMS). The contribution of these covariates to the predictive capability of geostatistical models was for the first time evaluated here through a rigorous model selection procedure along with additional continental high-resolution satellite-derived products, including novel data from the pan-European Copernicus land monitoring service (CLMS). The results have shown that the conversion of columnar NO₂ values to surface quasi-observations yielded models with slightly better predictive ability and lower uncertainty. Nonetheless, the use of higher resolution CAMS-Ensemble simulations as covariates in GR models granted the most accurate surface NO₂ estimates, showing that, in 2016, 16.17 (95% C.I. 6.34-29.96) million people in Europe, representing 2.97% (95% C.I. 1.16% - 5.50%) of the total population, were exposed to levels above the EU directive and WHO air quality guidelines threshold for NO₂. Our estimates are readily available to policy makers and scientists assessing the burden of disease attributable to NO₂ in 2016.

Sampling and single particle analysis for the chemical characterisation of fine atmospheric particulates: A review

To better understand the potential environmental and human health impacts of fine airborne particulate matter (APM), detailed physical and chemical characterisation is required. The only means to accurately distinguish between the multiple compositions in APM is by single particle analysis. A variety of methods and instruments are available, which range from filter-based sample collection for off-line laboratory analysis to on-line instruments that detect the airborne particles and generate size distribution and chemical data in real time. There are many reasons for sampling particulates in the ambient atmosphere and as a consequence, different measurement strategies and sampling devices are used depending on the scientific objectives and subsequent analytical techniques. This review is designed as a guide to some of the techniques available for the sampling and subsequent chemical analysis of individual inorganic particles.

Environmental Protection Procedures in Improving Air Quality in the University of Dammam Campuses

CONTEXT

Campuses of the University of Dammam (UOD) have several sources of air pollution that can adversely affect human health, welfare and the overall efficiency of the educational process.

AIMS

This study was aiming to assess the role of environmental protection procedures in UOD and evaluate their impact on improving the air quality inside its campuses.

SETTINGS AND DESIGN

In both the new and old campuses, three different sites were selected to assess air quality level.

METHODS

Five air pollutants, in addition to environmental noise, were measured at all selected sites. These pollutants included particulate matter less than 10 microns (PM10), carbon monoxide (CO), sulfur dioxide (SO2), volatile organic compounds (VOCs) and nitrogen dioxide (NO2). The data were compared to pollutant levels, in the same locations, that were measured during a previous 6-year period, starting from 2008.

STATISTICAL ANALYSIS USED

Results of this research were statistically analyzed by the Statistical Package for the Social Sciences (Version 16, SPSS Inc., Chicago, USA).

RESULTS

The highest mean ± standard deviation of PM10 (124.5 ± 25.0 μg/m3), CO (1.9 ± 0.7 ppm), VOCs (0.12 ± 0.09 ppm), NO2 (0.039 ± 0.022 ppm), SO2 (0.036 ± 0.047 ppm) and environmental noise (71.8 ± 4.1 dB) were found in the old UOD campus. Levels of all pollutants, except environmental noise, during the morning period were higher than those in the afternoon period. In addition, the level of the five air pollutants gradually reduced from 2008 to 2013, and reached to lower than their air quality guidelines.

CONCLUSIONS

The administrative policies and management procedures of UOD had a positive effect on the level of ambient air quality and reflect the presence of a healthy and safe educational environment inside its campus.

A method to derive the relationship between the annual and short-term air quality limits--analysis using the WHO Air Quality Guidelines for health protection

The World Health Organization (WHO) Air Quality Guidelines (AQG) were launched in 2006, but gaps remain in evidence on health impacts and relationships between short-term and annual AQG needed for health protection. We tested whether relationships between WHO short-term and annual AQG for particulates (PM10 and PM2.5) and nitrogen dioxide (NO2) are concordant worldwide and derived the annual limits for sulfur dioxide (SO2) and ozone (O3) based on the short-term AQG. We obtained air pollutant data over seven years (2004-2010) in seven cities from Asia-Pacific, North America and Europe. Based on probability distribution concept using maximum as the short-term limit and arithmetic mean as the annual limit, we developed a new method to derive limit value one from another in each paired limits for each pollutant with capability to account for allowable exceedances. We averaged the limit derived each year for each city, then used meta-analysis to pool the limit values in all cities. Pooled mean short-term limit for NO2 (140.5μg/m(3) [130.6-150.4]) was significantly lower than the WHO AQG of 200μg/m(3) while for PM10 (46.4μg/m(3) [95CI:42.1-50.7]) and PM2.5 (28.6μg/m(3) [24.5-32.6]) were not significantly different from the WHO AQG of 50 and 25μg/m(3) respectively. Pooled mean annual limits for SO2 and O3 were 4.6μg/m(3) [3.7-5.5] and 27.0μg/m(3) [21.7-32.2] respectively. Results were robust in various sensitivity analyses. The distribution relationships between the current WHO short-term and annual AQG are supported by empirical data from seven cities for PM10 and PM2.5, but not for NO2. The short-term AQG for NO2 should be lowered for concordance with the selected annual AQG for health protection.