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.

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.

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.

Short-term association between ambient temperature and homicide in South Africa: a case-crossover study.

BACKGROUND: Criminology research has traditionally investigated sociodemographic predictors of crime, such as sex, race, age, and socioeconomic status. However, evidence suggests that short-term fluctuations in crime often vary more than long-term trends, which sociodemographic factors cannot explain. This has redirected researchers to explore how environmental factors, such as meteorological variables, influence criminal behavior. In this study we investigate the association between daily ambient temperature and homicide incidence in South Africa, a country with one of the highest homicide rates in the world. METHODS: Mortality data was from South Africa's civil registration system and includes all recorded deaths in the country from 1997 to 2013 (17 years). Daily temperature was from the National Oceanographic and Atmospheric Association of the United States and South Africa's Agricultural Research Council. Data were analyzed using a time-stratified case-crossover design with conditional logistic regression. We delineated cases as either "definite" (ICD-10 codes X85-Y09, n = 68,356) or "probable" homicides (ICD-10 codes W25-W26, W32-W34, W50, Y22-Y24, Y28-Y29, n = 177,873). Case periods were defined as the day on which a death occurred. Control periods were selected using a day-of-week match within the same month and district. Analyses investigated same-day and lagged effects of maximum, mean and minimum temperature. RESULTS: A one-degree Celsius increase in same-day maximum temperature - our a priori metric of choice - was associated with a 1.5% (1.3-1.8%) increase in definite homicides and a 1.2% (1.1-1.3%) increase in total (definite + probable) homicides. Significant (p < 0.05) positive associations were also observed when applying other temperature metrics (mean, minimum) and lags (1, 0-1). The shape of the association did not display any clear non-linearities. There was no evidence of confounding by public holidays or air pollution. CONCLUSIONS: This study suggests a positive association between daily ambient temperature and homicide in South Africa. This temperature-health relationship may be of particular concern in the context of climate change. The ability to include meteorological variables as a predictor of criminal activity and violent behavior could prove valuable in resource allocation for crime prevention efforts.

Ambient Particulate Air Pollution and Daily Mortality in 652 Cities.

BACKGROUND: The systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias. METHODS: We evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 µm or less (PM10) and fine PM with an aerodynamic diameter of 2.5 µm or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration-response curves from each city were pooled to allow global estimates to be derived. RESULTS: On average, an increase of 10 µg per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration-response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations. CONCLUSIONS: Our data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.).

Students' Perceived Heat-Health Symptoms Increased with Warmer Classroom Temperatures.

Temperatures in Africa are expected to increase by the end of the century. Heat-related health impacts and perceived health symptoms are potentially a problem, especially in public schools with limited resources. Students (n = 252) aged ~14-18 years from eight high schools completed an hourly heat-health symptom log over 5 days. Data loggers measured indoor classroom temperatures. A high proportion of students felt tired (97.2%), had low concentration (96.8%) and felt sleepy (94.1%) during at least one hour on any day. There were statistically significant correlations, when controlling for school cluster effect and time of day, between indoor temperatures ≥32 °C and students who felt tired and found it hard to breathe. Consistently higher indoor classroom temperatures were observed in classrooms constructed of prefabricated asbestos sheeting with corrugated iron roof and converted shipping container compared to brick classrooms. Longitudinal studies in multiple seasons and different classroom building types are needed.

Regional Projections of Extreme Apparent Temperature Days in Africa and the Related Potential Risk to Human Health.

Regional climate modelling was used to produce high resolution climate projections for Africa, under a "business as usual scenario", that were translated into potential health impacts utilizing a heat index that relates apparent temperature to health impacts. The continent is projected to see increases in the number of days when health may be adversely affected by increasing maximum apparent temperatures (AT) due to climate change. Additionally, climate projections indicate that the increases in AT results in a moving of days from the less severe to the more severe Symptom Bands. The analysis of the rate of increasing temperatures assisted in identifying areas, such as the East African highlands, where health may be at increasing risk due to both large increases in the absolute number of hot days, and due to the high rate of increase. The projections described here can be used by health stakeholders in Africa to assist in the development of appropriate public health interventions to mitigate the potential health impacts from climate change.