Short-term, lagged association of airway inflammation, lung function, and asthma symptom score with PM2.5 exposure among schoolchildren within a high air pollution region in South Africa.

Background: Asthma affects millions of people globally, and high levels of air pollution aggravate asthma occurrence. This study aimed to determine the association between short-term lagged PM2.5 exposure and airway inflammation, lung function, and asthma symptom scores among schoolchildren in communities in the Highveld high-pollution region in South Africa. Methods: A cross-sectional study was conducted among schoolchildren aged 9-14 years in six communities in the Highveld region in South Africa, between October 2018 and February 2019. A NIOX 200 instrument was used to measure fractional exhaled nitric oxide (FeNO). Lung function indices (forced expiratory volume in one second [FEV1]; forced vital capacity [FVC] and FEV1/FVC) were collected using spirometry and the percent of predicted of these was based on the reference equations from the Global Lung Initiative, without ethnic correction. These values were further analyzed as binary outcomes following relevant thresholds (lower limits of normal for lung function and a cutoff of 35 ppb for FeNO). Asthma symptoms were used to create the asthma symptom score. Daily averages of PM2.5 data for the nearest monitoring station located in each community, were collected from the South African Air Quality Information System and created short-term 5-day lag PM2.5 concentrations. Additional reported environmental exposures were collected using standardized instruments. Results: Of the 706 participating schoolchildren, only 1.13% of the participants had doctor-diagnosed asthma, compared to a prevalence of 6.94% with an asthma symptom score suggestive of asthma. Lag 1 (odds ratio [OR]: 1.01; 95% confidence interval [CI]: 1.00, 1.02, P = 0.039) and 5-day average lagged PM2.5 (OR: 1.02; 95% CI: 0.99, 1.04, P = 0.050) showed increased odds of the FeNO > 35 ppb. Lung function parameters (FEV1 < lower limit of normal [LLN] [OR: 1.02, 95% CI: 1.00, 1.03, P = 0.018], and FEV1/FVC < LLN [OR: 1.01; 95% CI: 1.00, 1.02, P < 0.001]) and asthma symptom score ≥ 2 (OR: 1.02; 95% CI: 1.00, 1.04, P = 0.039) also showed significant associations with lag 2, lag 4 and lag 1 of PM2.5, respectively. Conclusion: Lagged PM2.5 exposure was associated with an increased odds of airway inflammation and an increased odds of lung function parameters below the LLN particularly for the later lags, but a significant dose-response relationship across the entire sample was not consistent.

Temporal variations in the short-term effects of ambient air pollution on cardiovascular and respiratory mortality: a pooled analysis of 380 urban areas over a 22-year period.

BACKGROUND: Ambient air pollution, including particulate matter (such as PM10 and PM2·5) and nitrogen dioxide (NO2), has been linked to increases in mortality. Whether populations' vulnerability to these pollutants has changed over time is unclear, and studies on this topic do not include multicountry analysis. We evaluated whether changes in exposure to air pollutants were associated with changes in mortality effect estimates over time. METHODS: We extracted cause-specific mortality and air pollution data collected between 1995 and 2016 from the Multi-Country Multi-City (MCC) Collaborative Research Network database. We applied a two-stage approach to analyse the short-term effects of NO2, PM10, and PM2·5 on cause-specific mortality using city-specific time series regression analyses and multilevel random-effects meta-analysis. We assessed changes over time using a longitudinal meta-regression with time as a linear fixed term and explored potential sources of heterogeneity and two-pollutant models. FINDINGS: Over 21·6 million cardiovascular and 7·7 million respiratory deaths in 380 cities across 24 countries over the study period were included in the analysis. All three air pollutants showed decreasing concentrations over time. The pooled results suggested no significant temporal change in the effect estimates per unit exposure of PM10, PM2·5, or NO2 and mortality. However, the risk of cardiovascular mortality increased from 0·37% (95% CI -0·05 to 0·80) in 1998 to 0·85% (0·55 to 1·16) in 2012 with a 10 µg/m3 increase in PM2·5. Two-pollutant models generally showed similar results to single-pollutant models for PM fractions and indicated temporal differences for NO2. INTERPRETATION: Although air pollution levels decreased during the study period, the effect sizes per unit increase in air pollution concentration have not changed. This observation might be due to the composition, toxicity, and sources of air pollution, as well as other factors, such as socioeconomic determinants or changes in population distribution and susceptibility. FUNDING: None.

Elemental Characterization of Ambient Particulate Matter for a Globally Distributed Monitoring Network: Methodology and Implications.

Global ground-level measurements of elements in ambient particulate matter (PM) can provide valuable information to understand the distribution of dust and trace elements, assess health impacts, and investigate emission sources. We use X-ray fluorescence spectroscopy to characterize the elemental composition of PM samples collected from 27 globally distributed sites in the Surface PARTiculate mAtter Network (SPARTAN) over 2019-2023. Consistent protocols are applied to collect all samples and analyze them at one central laboratory, which facilitates comparison across different sites. Multiple quality assurance measures are performed, including applying reference materials that resemble typical PM samples, acceptance testing, and routine quality control. Method detection limits and uncertainties are estimated. Concentrations of dust and trace element oxides (TEO) are determined from the elemental dataset. In addition to sites in arid regions, a moderately high mean dust concentration (6 µg/m3) in PM2.5 is also found in Dhaka (Bangladesh) along with a high average TEO level (6 µg/m3). High carcinogenic risk (>1 cancer case per 100000 adults) from airborne arsenic is observed in Dhaka (Bangladesh), Kanpur (India), and Hanoi (Vietnam). Industries of informal lead-acid battery and e-waste recycling as well as coal-fired brick kilns likely contribute to the elevated trace element concentrations found in Dhaka.

Ozone-related acute excess mortality projected to increase in the absence of climate and air quality controls consistent with the Paris Agreement.

Short-term exposure to ground-level ozone in cities is associated with increased mortality and is expected to worsen with climate and emission changes. However, no study has yet comprehensively assessed future ozone-related acute mortality across diverse geographic areas, various climate scenarios, and using CMIP6 multi-model ensembles, limiting our knowledge on future changes in global ozone-related acute mortality and our ability to design targeted health policies. Here, we combine CMIP6 simulations and epidemiological data from 406 cities in 20 countries or regions. We find that ozone-related deaths in 406 cities will increase by 45 to 6,200 deaths/year between 2010 and 2014 and between 2050 and 2054, with attributable fractions increasing in all climate scenarios (from 0.17% to 0.22% total deaths), except the single scenario consistent with the Paris Climate Agreement (declines from 0.17% to 0.15% total deaths). These findings stress the need for more stringent air quality regulations, as current standards in many countries are inadequate.

Ma te Whakarongo-a qualitative study exploring the impact of middle ear disease on New Zealand Maori.

AIM: The study aimed to explore the impact of middle ear disease on the lives of New Zealand Maori. Ear disease is common, yet there is a paucity of research into the effect it has on people's lives, particularly indigenous populations. METHOD: The study used Kaupapa Maori-based qualitative methodology and involved a series of seven semi-structured interviews with Maori adults living with middle ear disease. RESULTS: All participants felt there were delays in recognition and treatment of their ear condition and that there were barriers to accessing healthcare. The ear condition prevented participation in cultural and recreational activities, particularly those involving water. The associated hearing loss affected education and employment opportunities, and together with ear discharge, resulted in social isolation and disconnection from Te Ao Maori (the Maori world). Overall, the condition impacted negatively on mental and spiritual wellbeing. Participants felt that funding for hearing aids, earlier recognition and treatment of the condition and healthcare staff with a better understanding of Te Ao Maori could reduce the morbidity associated with middle ear disease. CONCLUSION: The study demonstrates that living with middle ear disease presents many challenges and disadvantages for Maori and the importance of early detection and referral to specialist care.

The South African Pollen Monitoring Network: Insights from 2 years of national aerospora sampling (2019-2021).

BACKGROUND: Pollen monitoring has been discontinuously undertaken in South Africa, a country with high biodiversity, a seasonal rainfall gradient, and nine biomes from arid to subtropical. The South African Pollen Monitoring Network was set up in 2019 to conduct the first long-term national aerospora monitoring across multiple biomes, providing weekly reports to allergy sufferers and healthcare providers. METHODS: Daily airborne pollen concentrations were measured from August 2019 to August 2021 in seven cities across South Africa. Updated pollen calendars were created for the major pollen types (>3%), the average Annual Pollen Index over 12 months was calculated, and the results were compared to available historical data. RESULTS: The main pollen types were from exotic vegetation. The most abundant taxa were Poaceae, Cupressaceae, Moraceae and Buddleja. The pollen season start, peak and end varied widely according to the biome and suite of pollen taxa. The main tree season started in the last week of August, peaked in September and ended in early December. Grass seasons followed rainfall patterns: September-January and January-April for summer and winter rainfall areas, respectively. Major urban centres, for example, Johannesburg and Pretoria in the same biome with similar rainfall, showed substantive differences in pollen taxa and abundance. Some major differences in pollen spectra were detected compared with historical data. However, we are cognisant that we are describing only 2 years of data that may be skewed by short-term weather patterns. CONCLUSIONS: Differences in pollen spectra and concentrations were noted across biomes and between geographically close urban centres. Comparison with historical data suggests pollen spectra and seasons may be changing due to anthropogenic climate change and landscaping. These data stress the importance of regional and continuous pollen monitoring for informed care of pollinosis.

Joint effect of heat and air pollution on mortality in 620 cities of 36 countries.

BACKGROUND: The epidemiological evidence on the interaction between heat and ambient air pollution on mortality is still inconsistent. OBJECTIVES: To investigate the interaction between heat and ambient air pollution on daily mortality in a large dataset of 620 cities from 36 countries. METHODS: We used daily data on all-cause mortality, air temperature, particulate matter ≤ 10 µm (PM10), PM ≤ 2.5 µm (PM2.5), nitrogen dioxide (NO2), and ozone (O3) from 620 cities in 36 countries in the period 1995-2020. We restricted the analysis to the six consecutive warmest months in each city. City-specific data were analysed with over-dispersed Poisson regression models, followed by a multilevel random-effects meta-analysis. The joint association between air temperature and air pollutants was modelled with product terms between non-linear functions for air temperature and linear functions for air pollutants. RESULTS: We analyzed 22,630,598 deaths. An increase in mean temperature from the 75th to the 99th percentile of city-specific distributions was associated with an average 8.9 % (95 % confidence interval: 7.1 %, 10.7 %) mortality increment, ranging between 5.3 % (3.8 %, 6.9 %) and 12.8 % (8.7 %, 17.0 %), when daily PM10 was equal to 10 or 90 µg/m3, respectively. Corresponding estimates when daily O3 concentrations were 40 or 160 µg/m3 were 2.9 % (1.1 %, 4.7 %) and 12.5 % (6.9 %, 18.5 %), respectively. Similarly, a 10 µg/m3 increment in PM10 was associated with a 0.54 % (0.10 %, 0.98 %) and 1.21 % (0.69 %, 1.72 %) increase in mortality when daily air temperature was set to the 1st and 99th city-specific percentiles, respectively. Corresponding mortality estimate for O3 across these temperature percentiles were 0.00 % (-0.44 %, 0.44 %) and 0.53 % (0.38 %, 0.68 %). Similar effect modification results, although slightly weaker, were found for PM2.5 and NO2. CONCLUSIONS: Suggestive evidence of effect modification between air temperature and air pollutants on mortality during the warm period was found in a global dataset of 620 cities.

Heat-related cardiorespiratory mortality: Effect modification by air pollution across 482 cities from 24 countries.

BACKGROUND: Evidence on the potential interactive effects of heat and ambient air pollution on cause-specific mortality is inconclusive and limited to selected locations. OBJECTIVES: We investigated the effects of heat on cardiovascular and respiratory mortality and its modification by air pollution during summer months (six consecutive hottest months) in 482 locations across 24 countries. METHODS: Location-specific daily death counts and exposure data (e.g., particulate matter with diameters ≤ 2.5 µm [PM2.5]) were obtained from 2000 to 2018. We used location-specific confounder-adjusted Quasi-Poisson regression with a tensor product between air temperature and the air pollutant. We extracted heat effects at low, medium, and high levels of pollutants, defined as the 5th, 50th, and 95th percentile of the location-specific pollutant concentrations. Country-specific and overall estimates were derived using a random-effects multilevel meta-analytical model. RESULTS: Heat was associated with increased cardiorespiratory mortality. Moreover, the heat effects were modified by elevated levels of all air pollutants in most locations, with stronger effects for respiratory than cardiovascular mortality. For example, the percent increase in respiratory mortality per increase in the 2-day average summer temperature from the 75th to the 99th percentile was 7.7% (95% Confidence Interval [CI] 7.6-7.7), 11.3% (95%CI 11.2-11.3), and 14.3% (95% CI 14.1-14.5) at low, medium, and high levels of PM2.5, respectively. Similarly, cardiovascular mortality increased by 1.6 (95%CI 1.5-1.6), 5.1 (95%CI 5.1-5.2), and 8.7 (95%CI 8.7-8.8) at low, medium, and high levels of O3, respectively. DISCUSSION: We observed considerable modification of the heat effects on cardiovascular and respiratory mortality by elevated levels of air pollutants. Therefore, mitigation measures following the new WHO Air Quality Guidelines are crucial to enhance better health and promote sustainable development.

The Risk of Orofacial Cleft Lip/Palate Due to Maternal Ambient Air Pollution Exposure: A Call for Further Research in South Africa.

Background: Despite being underreported, orofacial cleft lip/palate (CLP) remains in the top five of South Africa's most common congenital disorders. Maternal air pollution exposure has been associated with CLP in neonates. South Africa has high air pollution levels due to domestic burning practices, coal-fired power plants, mining, industry, and traffic pollution, among other sources. We investigated air pollutant levels in geographic locations of CLP cases. Methods: In a retrospective case series study (2006-2020) from a combined dataset by a Gauteng surgeon and South African Operation Smile, the maternal address at pregnancy was obtained for 2,515 CLP cases. Data from the South African Air Quality Information System was used to calculate annual averages of particulate matter (PM) concentrations of particles < 10 µm (PM10) and < 2.5 µm (PM2.5). Correlation analysis determined the relationship between average PM2.5/PM10 concentrations and CLP birth prevalence. Hotspot analysis was done using the Average Nearest Neighbor tool in ArcGIS. Results: Correlation analysis showed an increasing trend of CLP birth prevalence to PM10 (CC = 0.61, 95% CI = 0.38-0.77, p < 0.001) and PM2.5 (CC = 0.63, 95% CI = 0.42-0.77, p < 0.001). Hot spot analysis revealed that areas with higher concentrations of PM10 and PM2.5 had a higher proclivity for maternal residence (z-score = -68.2, p < 0.001). CLP birth prevalence hotspot clusters were identified in district municipalities in the provinces of Gauteng, Limpopo, North-West, Mpumalanga, and Free State. KwaZulu-Natal and Eastern Cape had lower PM10 and PM2.5 concentrations and were cold spot clusters. Conclusions: Maternal exposure to air pollution is known to impact the fetal environment and increase CLP risk. We discovered enough evidence of an effect to warrant further investigation. We advocate for a concerted effort by the government, physicians, researchers, non-government organizations working with CLP patients, and others to collect quality data on all maternal information and pollutant levels in all provinces of South Africa. Collaboration and data sharing for additional research will help us better understand the impact of air pollution on CLP in South Africa.

Lagged acute respiratory outcomes among children related to ambient pollutant exposure in a high exposure setting in South Africa.

Acute ambient air pollution impacts on the respiratory health of children may be lagged across time. We determined the short-term lagged effects of particulate matter (PM2.5), sulphur dioxide (SO2), and oxides of nitrogen (NOx) on the respiratory health of children living in low-income communities. Methods: A school-based study was conducted using a repeated measures design, across summer and winter, in four schools in each of four suburbs in the Vaal Triangle, South Africa. Data for PM2.5, NOx, and SO2 were obtained from monitoring stations within close proximity of the schools. Over 10 school days in each phase, grade 4 children completed a symptoms log and lung function tests. Parents completed a child respiratory questionnaire. Generalized estimation equations models adjusted for covariates of interest in relation to lung function outcomes and air pollutants including lag effects of 1-5 days. Results: Daily PM2.5, NOx, and SO2 median concentration levels were frequently higher than international standards. Among the 280 child participants (mean age 9 years), the prevalence of symptoms based on probable asthma was 9.6%. There was a consistent increased pollutant-related risk for respiratory symptoms, except for NOx and shortness of breath. Lung function, associated with pollutant fluctuations across the different lags, was most pronounced for peak expiratory flow rate (PEFR) for PM2.5 and SO2. A preceding 5-day average SO2 exposure had the largest loss (7.5 L/minute) in PEFR. Conclusions: Lagged declines in daily lung function and increased odds of having respiratory symptoms were related to increases in PM2.5 and SO2 among a school-based sample of children.

Respiratory health among adolescents living in the Highveld Air Pollution Priority Area in South Africa.

BACKGROUND: Air pollution is a global, public health emergency. The effect of living in areas with very poor air quality on adolescents' physical health is largely unknown. The aim of this study was to investigate the prevalence of adverse respiratory health outcomes among adolescents living in a known air pollution hotspot in South Africa. METHODS: Ambient air quality data from 2005 to 2019 for the two areas, Secunda and eMbalenhle, in the Highveld Air Pollution Priority Area in Mpumalanga province, South Africa were gathered and compared against national ambient air pollution standards and the World Health Organization Air Quality Guidelines. In 2019, adolescents attending schools in the areas completed a self-administered questionnaire investigating individual demographics, socio-economic status, health, medical history, and fuel type used in homes. Respiratory health illnesses assessed were doctor-diagnosed hay fever, allergies, frequent cough, wheezing, bronchitis, pneumonia and asthma. The relationship between presence (at least one) or absence (none) of self-reported respiratory illness and risk factors, e.g., fuel use at home, was explored. Logistic regression was used to estimate the odds ratio and 95% confidence interval (CI) of risk factors associated with respiratory illness adjusted for body mass index (measured by field assistants), gender, education level of both parents / guardians and socio-economic status. RESULTS: Particulate matter and ozone were the two pollutants most frequently exceeding national annual air quality standards in the study area. All 233 adolescent participants were between 13 and 17 years of age. Prevalence of self-reported respiratory symptoms among the participants ranged from 2% for 'ever' doctor-diagnosed bronchitis and pneumonia to 42% ever experiencing allergies; wheezing chest was the second most reported symptom (39%). Half (52%) of the adolescents who had respiratory illness were exposed to environmental tobacco smoke in the dwelling. There was a statistically significant difference between the presence or absence of self-reported respiratory illness based on the number of years lived in Secunda or eMbalenhle (p = 0.02). For a one-unit change in the number of years lived in an area, the odds of reporting a respiratory illness increased by a factor of 1.08 (p = 0.025, 95% CI = 1.01-1.16). This association was still statistically significant when the model was adjusted for confounders (p = 0.037). CONCLUSIONS: Adolescents living in air polluted areas experience adverse health impacts Future research should interrogate long-term exposure and health outcomes among adolescents living in the air polluted environment.

Coarse Particulate Air Pollution and Daily Mortality: A Global Study in 205 Cities.

Rationale: The associations between ambient coarse particulate matter (PM2.5-10) and daily mortality are not fully understood on a global scale. Objectives: To evaluate the short-term associations between PM2.5-10 and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide. Methods: We collected daily mortality (total, cardiovascular, and respiratory) and air pollution data from 205 cities in 20 countries/regions. Concentrations of PM2.5-10 were computed as the difference between inhalable and fine PM. A two-stage time-series analytic approach was applied, with overdispersed generalized linear models and multilevel meta-analysis. We fitted two-pollutant models to test the independent effect of PM2.5-10 from copollutants (fine PM, nitrogen dioxide, sulfur dioxide, ozone, and carbon monoxide). Exposure-response relationship curves were pooled, and regional analyses were conducted. Measurements and Main Results: A 10 µg/m3 increase in PM2.5-10 concentration on lag 0-1 day was associated with increments of 0.51% (95% confidence interval [CI], 0.18%-0.84%), 0.43% (95% CI, 0.15%-0.71%), and 0.41% (95% CI, 0.06%-0.77%) in total, cardiovascular, and respiratory mortality, respectively. The associations varied by country and region. These associations were robust to adjustment by all copollutants in two-pollutant models, especially for PM2.5. The exposure-response curves for total, cardiovascular, and respiratory mortality were positive, with steeper slopes at lower exposure ranges and without discernible thresholds. Conclusions: This study provides novel global evidence on the robust and independent associations between short-term exposure to ambient PM2.5-10 and total, cardiovascular, and respiratory mortality, suggesting the need to establish a unique guideline or regulatory limit for daily concentrations of PM2.5-10.

Climate change and health within the South African context: A thematic content analysis study of climate change and health expert interviews.

BACKGROUND:  Climate change presents an unprecedented and urgent threat to human health and survival. South Africa's health response will require a strong and effective intersectoral organisational effort. AIM:  Exploratory interview outcomes are used to advance practice and policy recommendations, as well as for broad input in the development of a draft national framework for a health risk and vulnerability assessment (RVA) for national departments. SETTING:  Nationally in South Africa. METHOD:  Twenty key expert interviews were conducted with South African experts in the field of climate change and health. Interview data was analysed by means of thematic content analysis. RESULTS:  Findings suggest that previously poor communities are most at risk to the impacts of climate change on health, as well as those with underlying medical conditions. Climate change may also serve as a catalyst for improving the healthcare system overall and should serve as the conduit to do so. A draft climate change and health RVA should take into account existing frameworks and should be implemented by local government. It is also critical that the health and health system impacts from climate change are well understood, especially in light of the plans to implement the (South African) National Health Insurance (NHI) scheme. CONCLUSION:  Practice and policy initiatives should be holistic in nature. Consideration should be given to forming a South African National Department of Climate Change, or a similar coordinating body between the various national departments in South Africa, as health intercepts with all other domains within the climate change field.

Differential Mortality Risks Associated With PM2.5 Components: A Multi-Country, Multi-City Study.

BACKGROUND: The association between fine particulate matter (PM2.5) and mortality widely differs between as well as within countries. Differences in PM2.5 composition can play a role in modifying the effect estimates, but there is little evidence about which components have higher impacts on mortality. METHODS: We applied a 2-stage analysis on data collected from 210 locations in 16 countries. In the first stage, we estimated location-specific relative risks (RR) for mortality associated with daily total PM2.5 through time series regression analysis. We then pooled these estimates in a meta-regression model that included city-specific logratio-transformed proportions of seven PM2.5 components as well as meta-predictors derived from city-specific socio-economic and environmental indicators. RESULTS: We found associations between RR and several PM2.5 components. Increasing the ammonium (NH4+) proportion from 1% to 22%, while keeping a relative average proportion of other components, increased the RR from 1.0063 (95% confidence interval [95% CI] = 1.0030, 1.0097) to 1.0102 (95% CI = 1.0070, 1.0135). Conversely, an increase in nitrate (NO3-) from 1% to 71% resulted in a reduced RR, from 1.0100 (95% CI = 1.0067, 1.0133) to 1.0037 (95% CI = 0.9998, 1.0077). Differences in composition explained a substantial part of the heterogeneity in PM2.5 risk. CONCLUSIONS: These findings contribute to the identification of more hazardous emission sources. Further work is needed to understand the health impacts of PM2.5 components and sources given the overlapping sources and correlations among many components.

A machine learning model to estimate ambient PM2.5 concentrations in industrialized highveld region of South Africa.

Exposure to fine particulate matter (PM2.5) has been linked to a substantial disease burden globally, yet little has been done to estimate the population health risks of PM2.5 in South Africa due to the lack of high-resolution PM2.5 exposure estimates. We developed a random forest model to estimate daily PM2.5 concentrations at 1 km2 resolution in and around industrialized Gauteng Province, South Africa, by combining satellite aerosol optical depth (AOD), meteorology, land use, and socioeconomic data. We then compared PM2.5 concentrations in the study domain before and after the implementation of the new national air quality standards. We aimed to test whether machine learning models are suitable for regions with sparse ground observations such as South Africa and which predictors played important roles in PM2.5 modeling. The cross-validation R2 and Root Mean Square Error of our model was 0.80 and 9.40 µg/m3, respectively. Satellite AOD, seasonal indicator, total precipitation, and population were among the most important predictors. Model-estimated PM2.5 levels successfully captured the temporal pattern recorded by ground observations. Spatially, the highest annual PM2.5 concentration appeared in central and northern Gauteng, including northern Johannesburg and the city of Tshwane. Since the 2016 changes in national PM2.5 standards, PM2.5 concentrations have decreased in most of our study region, although levels in Johannesburg and its surrounding areas have remained relatively constant. This is anadvanced PM2.5 model for South Africa with high prediction accuracy at the daily level and at a relatively high spatial resolution. Our study provided a reference for predictor selection, and our results can be used for a variety of purposes, including epidemiological research, burden of disease assessments, and policy evaluation.

A global observational analysis to understand changes in air quality during exceptionally low anthropogenic emission conditions.

This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015-2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015-2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples' mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality. As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015-2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015-2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.

Major climate change-induced risks to human health in South Africa.

There are many climatic changes facing South Africa which already have, or are projected to have, a detrimental impact on human health. Here the risks to health due to several alterations in the climate of South Africa are considered in turn. These include an increase in ambient temperature, causing, for example, a significant rise in morbidity and mortality; heavy rainfall leading to changes in the prevalence and occurrence of vector-borne diseases; drought-associated malnutrition; and exposure to dust storms and air pollution leading to the potential exacerbation of respiratory diseases. Existing initiatives and strategies to prevent or reduce these adverse health impacts are outlined, together with suggestions of what might be required in the future to safeguard the health of the nation. Potential roles for the health and non-health sectors as well as preparedness and capacity development with respect to climate change and health adaptation are considered.

Large global variations in measured airborne metal concentrations driven by anthropogenic sources.

Globally consistent measurements of airborne metal concentrations in fine particulate matter (PM2.5) are important for understanding potential health impacts, prioritizing air pollution mitigation strategies, and enabling global chemical transport model development. PM2.5 filter samples (N ~ 800 from 19 locations) collected from a globally distributed surface particulate matter sampling network (SPARTAN) between January 2013 and April 2019 were analyzed for particulate mass and trace metals content. Metal concentrations exhibited pronounced spatial variation, primarily driven by anthropogenic activities. PM2.5 levels of lead, arsenic, chromium, and zinc were significantly enriched at some locations by factors of 100-3000 compared to crustal concentrations. Levels of metals in PM2.5 and PM10 exceeded health guidelines at multiple sites. For example, Dhaka and Kanpur sites exceeded the US National Ambient Air 3-month Quality Standard for lead (150 ng m-3). Kanpur, Hanoi, Beijing and Dhaka sites had annual mean arsenic concentrations that approached or exceeded the World Health Organization's risk level for arsenic (6.6 ng m-3). The high concentrations of several potentially harmful metals in densely populated cites worldwide motivates expanded measurements and analyses.

Short term association between ozone and mortality: global two stage time series study in 406 locations in 20 countries.

OBJECTIVE: To assess short term mortality risks and excess mortality associated with exposure to ozone in several cities worldwide. DESIGN: Two stage time series analysis. SETTING: 406 cities in 20 countries, with overlapping periods between 1985 and 2015, collected from the database of Multi-City Multi-Country Collaborative Research Network. POPULATION: Deaths for all causes or for external causes only registered in each city within the study period. MAIN OUTCOME MEASURES: Daily total mortality (all or non-external causes only). RESULTS: A total of 45 165 171 deaths were analysed in the 406 cities. On average, a 10 µg/m3 increase in ozone during the current and previous day was associated with an overall relative risk of mortality of 1.0018 (95% confidence interval 1.0012 to 1.0024). Some heterogeneity was found across countries, with estimates ranging from greater than 1.0020 in the United Kingdom, South Africa, Estonia, and Canada to less than 1.0008 in Mexico and Spain. Short term excess mortality in association with exposure to ozone higher than maximum background levels (70 µg/m3) was 0.26% (95% confidence interval 0.24% to 0.28%), corresponding to 8203 annual excess deaths (95% confidence interval 3525 to 12 840) across the 406 cities studied. The excess remained at 0.20% (0.18% to 0.22%) when restricting to days above the WHO guideline (100 µg/m3), corresponding to 6262 annual excess deaths (1413 to 11 065). Above more lenient thresholds for air quality standards in Europe, America, and China, excess mortality was 0.14%, 0.09%, and 0.05%, respectively. CONCLUSIONS: Results suggest that ozone related mortality could be potentially reduced under stricter air quality standards. These findings have relevance for the implementation of efficient clean air interventions and mitigation strategies designed within national and international climate policies.