Age-dependent health risk from ambient air pollution: a modelling and data analysis of childhood mortality in middle-income and low-income countries.

BACKGROUND: WHO estimates that, in 2015, nearly 1 million children younger than 5 years died from lower respiratory tract infections (LRIs). Ambient air pollution has a major impact on mortality from LRIs, especially in combination with undernutrition and inadequate health care. We aimed to estimate mortality due to ambient air pollution in 2015, particularly in children younger than 5 years, to investigate to what extent exposure to this risk factor affects life expectancy in different parts of the world. METHODS: Applying results from a recent atmospheric chemistry-general circulation model and health statistics from the WHO Global Health Observatory, combined in integrated exposure-response functions, we updated our estimates of mortality from ambient (outdoor) air pollution. We estimated excess deaths attributable to air pollution by disease category and age group, particularly those due to ambient air pollution-induced LRIs (AAP-LRIs) in childhood. Estimates are presented as excess mortality attributable to ambient air pollution and years of life lost (YLLs). To study recent developments, we calculated our estimates for the years 2010 and 2015. FINDINGS: Overall, 4·55 million deaths (95% CI 3·41 million to 5·56 million) were attributable to air pollution in 2015, of which 727 000 deaths (573 000-865 000) were due to AAP-LRIs. We estimated that AAP-LRIs caused about 237 000 (192 000-277 000) excess child deaths in 2015. Although childhood AAP-LRIs contributed about 5% of air pollution-attributable deaths worldwide, they accounted for 18% of losses in life expectancy, equivalent to 21·5 million (17 million to 25 million) of the total 122 million YLLs due to ambient air pollution in 2015. The mortality rate from ambient air pollution was highest in Asia, whereas the per capita YLLs were highest in Africa. We estimated that in sub-Saharan Africa, ambient air pollution reduces the average life expectancy of children by 4-5 years. In Asia, all-age mortality increased by about 10% between 2010 and 2015, whereas childhood mortality from AAP-LRIs declined by nearly 30% in the same period. INTERPRETATION: Most child deaths due to AAP-LRIs occur in low-income countries in Africa and Asia. A three-pronged strategy is needed to reduce the health effects of ambient air pollution in children: aggressive reduction of air pollution levels, improvements in nutrition, and enhanced treatment of air pollution-related health outcomes. FUNDING: None

Spatial Distribution of PM\u3csub\u3e2.5\u3c/sub\u3e-Related Premature Mortality in China

PM2.5 is a major component of air pollution in China and has a serious threat to public health. It is very important to quantify spatial characteristics of the health effects caused by outdoor PM2.5 exposure. This study analyzed the spatial distribution of PM2.5 concentration (45.9 μg/m3 national average in 2016) and premature mortality attributed to PM2.5 in cities at the prefectural level and above in China in 2016. Using the Global Exposure Mortality Model (GEMM), the total premature mortality in China was estimated to be 1.55 million persons, and the per capita mortality was 11.2 per 10,000 persons in the year 2016, resulting in higher estimates compared to the integrated exposure-response model. We assessed the premature mortality attributed to PM2.5 through common diseases, including ischemic heart disease (IHD), cerebrovascular disease (CEV), chronic obstructive pulmonary disease (COPD), lung cancer (LC), and lower respiratory infections (LRI). The premature mortality due to IHD and CEV accounted for 68.5% of the total mortality, and the per capita mortality (per 10,000 persons) for all ages due to IHD was 3.86, the highest among diseases. For the spatial distribution of disease-specific premature mortality, the top two highest absolute numbers of premature mortality associated with IHD, CEV, LC, and LRI, respectively, were found in Chongqing and Beijing. In 338 cities of China, we have found a significant positive spatial autocorrelation of per capita premature mortality, indicating the necessity of coordinated regional governance for an efficient control of PM2.5. Plain Language Summary Fine particulate matter (PM2.5) concentrations have increased in general, in most developing countries in recent decades. In China, PM2.5 pollution has become a major component of air pollution and has serious health impacts. To obtain a comprehensive understanding of the national health impacts of PM2.5 in China, we have used the Global Exposure Mortality Model (GEMM) to estimate the premature mortality associated with PM2.5 exposure in 338 cities in China at the prefectural level and above. In addition, we analyzed the spatial distribution of premature mortality attributed to PM2.5 for five diseases, including ischemic heart disease (IHD), cerebrovascular disease (CEV), chronic obstructive pulmonary disease (COPD), lung cancer (LC), and lower respiratory infections (LRI). Our study finds that the total premature mortality associated with PM2.5 exposure in China for 2016 was 1.55 million persons. The top two highest absolute numbers of premature mortality associated with IHD, CEV, LC, and LRI, respectively were found in Chongqing and Beijing. Furthermore, cities with high per capita premature mortality tended to be spatially connected with other cities with high per capita premature mortality, indicating the coordinated regional governance should be adopted to reduce the impact of PM2.5 on human health

Spatial Distribution of PM\u3csub\u3e2.5\u3c/sub\u3e-Related Premature Mortality in China

PM2.5 is a major component of air pollution in China and has a serious threat to public health. It is very important to quantify spatial characteristics of the health effects caused by outdoor PM2.5 exposure. This study analyzed the spatial distribution of PM2.5 concentration (45.9 μg/m3 national average in 2016) and premature mortality attributed to PM2.5 in cities at the prefectural level and above in China in 2016. Using the Global Exposure Mortality Model (GEMM), the total premature mortality in China was estimated to be 1.55 million persons, and the per capita mortality was 11.2 per 10,000 persons in the year 2016, resulting in higher estimates compared to the integrated exposure-response model. We assessed the premature mortality attributed to PM2.5 through common diseases, including ischemic heart disease (IHD), cerebrovascular disease (CEV), chronic obstructive pulmonary disease (COPD), lung cancer (LC), and lower respiratory infections (LRI). The premature mortality due to IHD and CEV accounted for 68.5% of the total mortality, and the per capita mortality (per 10,000 persons) for all ages due to IHD was 3.86, the highest among diseases. For the spatial distribution of disease-specific premature mortality, the top two highest absolute numbers of premature mortality associated with IHD, CEV, LC, and LRI, respectively, were found in Chongqing and Beijing. In 338 cities of China, we have found a significant positive spatial autocorrelation of per capita premature mortality, indicating the necessity of coordinated regional governance for an efficient control of PM2.5. Plain Language Summary Fine particulate matter (PM2.5) concentrations have increased in general, in most developing countries in recent decades. In China, PM2.5 pollution has become a major component of air pollution and has serious health impacts. To obtain a comprehensive understanding of the national health impacts of PM2.5 in China, we have used the Global Exposure Mortality Model (GEMM) to estimate the premature mortality associated with PM2.5 exposure in 338 cities in China at the prefectural level and above. In addition, we analyzed the spatial distribution of premature mortality attributed to PM2.5 for five diseases, including ischemic heart disease (IHD), cerebrovascular disease (CEV), chronic obstructive pulmonary disease (COPD), lung cancer (LC), and lower respiratory infections (LRI). Our study finds that the total premature mortality associated with PM2.5 exposure in China for 2016 was 1.55 million persons. The top two highest absolute numbers of premature mortality associated with IHD, CEV, LC, and LRI, respectively were found in Chongqing and Beijing. Furthermore, cities with high per capita premature mortality tended to be spatially connected with other cities with high per capita premature mortality, indicating the coordinated regional governance should be adopted to reduce the impact of PM2.5 on human health

Loss of life expectancy from air pollution compared to other risk factors: a worldwide perspective.

AIMS: Long-term exposure of humans to air pollution enhances the risk of cardiovascular and respiratory diseases. A novel Global Exposure Mortality Model (GEMM) has been derived from many cohort studies, providing much-improved coverage of the exposure to fine particulate matter (PM2.5). We applied the GEMM to assess excess mortality attributable to ambient air pollution on a global scale and compare to other risk factors. METHODS AND RESULTS: We used a data-informed atmospheric model to calculate worldwide exposure to PM2.5 and ozone pollution, which was combined with the GEMM to estimate disease-specific excess mortality and loss of life expectancy (LLE) in 2015. Using this model, we investigated the effects of different pollution sources, distinguishing between natural (wildfires, aeolian dust) and anthropogenic emissions, including fossil fuel use. Global excess mortality from all ambient air pollution is estimated at 8.8 (7.11-10.41) million/year, with an LLE of 2.9 (2.3-3.5) years, being a factor of two higher than earlier estimates, and exceeding that of tobacco smoking. The global mean mortality rate of about 120 per 100 000 people/year is much exceeded in East Asia (196 per 100 000/year) and Europe (133 per 100 000/year). Without fossil fuel emissions, the global mean life expectancy would increase by 1.1 (0.9-1.2) years and 1.7 (1.4-2.0) years by removing all potentially controllable anthropogenic emissions. Because aeolian dust and wildfire emission control is impracticable, significant LLE is unavoidable. CONCLUSION: Ambient air pollution is one of the main global health risks, causing significant excess mortality and LLE, especially through cardiovascular diseases. It causes an LLE that rivals that of tobacco smoking. The global mean LLE from air pollution strongly exceeds that by violence (all forms together), i.e. by an order of magnitude (LLE being 2.9 and 0.3 years, respectively)

Prácticas profesionalizantes de secundaria técnica en contexto de pandemia: tensiones entre formatos y sentidos formativos del campo

El presente artículo tiene como objetivo describir y poner en discusión el desarrollo de las Prácticas Profesionalizantes (PP) para el sostenimiento de la continuidad pedagógica durante la pandemia del COVID-19, considerando las propuestas de la especialidad “Informática profesional y personal” de tres escuelas secundarias técnicas de Corrientes. Se parte desde una perspectiva conceptual que considera la construcción del campo de PP desde dos dimensiones: la política-normativa y la pedagógica-didáctica del sentido de la práctica en la formación. Así, desde una mirada multinivel se busca poner en diálogo lo normativo con las voces de los actores involucrados. Se identifican y analizan normas referidas a las PP en pandemia y los proyectos institucionales de PP de cada escuela, como así también, se realizan entrevistas a referentes jurisdiccionales, directivos y docentes de estos espacios. Este recorrido permite describir las experiencias de PP desarrolladas en un contexto de excepcionalidad, a partir de lo cual se ponen en discusión las adaptaciones realizadas, problematizando los alcances y los sentidos desde los cuales se construyen las PP en la formación de técnicos y las complejidades de la articulación escuela y medio socio productivo

Cold cloud microphysical process rates in a global chemistry–climate model

Microphysical processes in cold clouds which act as sources or sinks of hydrometeors below 0 degrees C control the ice crystal number concentrations (ICNCs) and in turn the cloud radiative effects. Estimating the relative importance of the cold cloud microphysical process rates is of fundamental importance to underpin the development of cloud parameterizations for weather, atmospheric chemistry, and climate models and to compare the output with observations at different temporal resolutions. This study quantifies and investigates the ICNC rates of cold cloud microphysical processes by means of the chemistry-climate model EMAC (ECHAM/MESSy Atmospheric Chemistry) and defines the hierarchy of sources and sinks of ice crystals. Both microphysical process rates, such as ice nucleation, aggregation, and secondary ice production, and unphysical correction terms are presented. Model ICNCs are also compared against a satellite climatology. We found that model ICNCs are in overall agreement with satellite observations in terms of spatial distribution, although the values are overestimated, especially around high mountains. The analysis of ice crystal rates is carried out both at global and at regional scales. We found that globally the freezing of cloud droplets and convective detrainment over tropical land masses are the dominant sources of ice crystals, while aggregation and accretion act as the largest sinks. In general, all processes are characterized by highly skewed distributions. Moreover, the influence of (a) different ice nucleation parameterizations and (b) a future global warming scenario on the rates has been analysed in two sensitivity studies. In the first, we found that the application of different parameterizations for ice nucleation changes the hierarchy of ice crystal sources only slightly. In the second, all microphysical processes follow an upward shift in altitude and an increase by up to 10 % in the upper troposphere towards the end of the 21st century

Distribution of hydrogen peroxide over Europe during the BLUESKY aircraft campaign

In this work we present airborne in situ trace gas observations of hydrogen peroxide (H$_2$O$_2$) and the sum of organic hydroperoxides over Europe during the Chemistry of the Atmosphere – Field Experiments in Europe (CAFE-EU, also known as BLUESKY) aircraft campaign using a wet chemical monitoring system, the HYdrogen Peroxide and Higher Organic Peroxide (HYPHOP) monitor. The campaign took place in May–June 2020 over central and southern Europe with two additional flights dedicated to the North Atlantic flight corridor. Airborne measurements were performed on the High Altitude and LOng-range (HALO) research operating out of Oberpfaffenhofen (southern Germany). We report average mixing ratios for H$_2$O$_2$ of 0.32 ± 0.25, 0.39 ± 0.23 and 0.38 ± 0.21 ppbv in the upper and middle troposphere and the boundary layer over Europe, respectively. Vertical profiles of measured H$_2$O$_2$ reveal a significant decrease, in particular above the boundary layer, contrary to previous observations, most likely due to cloud scavenging and subsequent rainout of soluble species. In general, the expected inverted C-shaped vertical trend with maximum hydrogen peroxide mixing ratios at 3–7 km was not found during BLUESKY. This deviates from observations during previous airborne studies over Europe, i.e., 1.64 ± 0.83 ppb$_v$ during the HOOVER campaign and 1.67 ± 0.97 ppbv during UTOPIHAN-ACT II/III. Simulations with the global chemistry–transport model EMAC partly reproduce the strong effect of rainout loss on the vertical profile of H$_2$O$_2$. A sensitivity study without H$_2$O$_2$ scavenging performed using EMAC confirms the strong influence of clouds and precipitation scavenging on hydrogen peroxide concentrations. Differences between model simulations and observations are most likely due to difficulties in the simulation of wet scavenging processes due to the limited model resolution

Tropospheric ozone production and chemical regime analysis during the COVID-19 lockdown over Europe

The COVID-19 (coronavirus disease 2019) European lockdowns have led to a significant reduction in the emissions of primary pollutants such as NO (nitric oxide) and NO$_2$ (nitrogen dioxide). As most photochemical processes are related to nitrogen oxide (NO$_x$≡ NO + NO$_2$) chemistry, this event has presented an exceptional opportunity to investigate its effects on air quality and secondary pollutants, such as tropospheric ozone (O$_3$). In this study, we present the effects of the COVID-19 lockdown on atmospheric trace gas concentrations, net ozone production rates (NOPRs) and the dominant chemical regime throughout the troposphere based on three different research aircraft campaigns across Europe. These are the UTOPIHAN (Upper Tropospheric Ozone: Processes Involving HO$_x$ and NO$_x$) campaigns in 2003 and 2004, the HOOVER (HO$_x$ over Europe) campaigns in 2006 and 2007, and the BLUESKY campaign in 2020, the latter performed during the COVID-19 lockdown. We present in situ observations and simulation results from the ECHAM5 (fifth-generation European Centre Hamburg general circulation model, version 5.3.02)/MESSy2 (second-generation Modular Earth Submodel System, version 2.54.0) Atmospheric Chemistry (EMAC), model which allows for scenario calculations with business-as-usual emissions during the BLUESKY campaign, referred to as the “no-lockdown scenario”. We show that the COVID-19 lockdown reduced NO and NO$_2$ mixing ratios in the upper troposphere by around 55 % compared to the no-lockdown scenario due to reduced air traffic. O$_3$ production and loss terms reflected this reduction with a deceleration in O$_3$ cycling due to reduced mixing ratios of NO$_x$, while NOPRs were largely unaffected. We also study the role of methyl peroxyradicals forming HCHO ($^α$CH$_3$O$_2$) to show that the COVID-19 lockdown shifted the chemistry in the upper-troposphere–tropopause region to a NO$_x$-limited regime during BLUESKY. In comparison, we find a volatile organic compound (VOC)-limited regime to be dominant during UTOPIHAN

Global health burden of ambient PM2.5 and the contribution of anthropogenic black carbon and organic aerosols

Chronic exposure to fine particulate matter (PM2.5) poses a major global health risk, commonly assessed by assuming equivalent toxicity for different PM2.5 constituents. We used a data-informed global atmospheric model and recent exposure-response functions to calculate the health burden of ambient PM2.5 from ten source categories. We estimate 4.23 (95% confidence interval 3.0-6.14) million excess deaths annually from the exposure to ambient PM2.5. We distinguished contributions and major sources of black carbon (BC), primary organic aerosols (POA) and anthropogenic secondary organic aerosols (aSOA). These components make up to similar to 20% of the total PM2.5 in South and East Asia and East Africa. We find that domestic energy use by the burning of solid biofuels is the largest contributor to ambient BC, POA and aSOA globally. Epidemiological and toxicological studies indicate that these compounds may be relatively more hazardous than other PM2.5 compounds such as soluble salts, related to their high potential to inflict oxidative stress. We performed sensitivity analyses by considering these species to be more harmful compared to other compounds in PM2.5, as suggested by their oxidative potential using a range of potential relative risks. These analyses show that domestic energy use emerges as the leading cause of excess mortality attributable to ambient PM2.5, notably in Asia and Africa. We acknowledge the uncertainties inherent in our assumed enhanced toxicity of the anthropogenic organic and BC aerosol components, which suggest the need to better understand the mechanisms and magnitude of the associated health risks and the consequences for regulatory policies. However our assessment of the importance of emissions from domestic energy use as a cause of premature mortality is robust to a range of assumptions about the magnitude of the excess risk.Peer reviewe

Model simulations of atmospheric methane (1997-2016) and their evaluation using NOAA and AGAGE surface and IAGOS-CARIBIC aircraft observations

Methane (CH4) is an important greenhouse gas, and its atmospheric budget is determined by interacting sources and sinks in a dynamic global environment. Methane observations indicate that after almost a decade of stagnation, from 2006, a sudden and continuing global mixing ratio increase took place. We applied a general circulation model to simulate the global atmospheric budget, variability, and trends of methane for the period 1997–2016. Using interannually constant CH4 a priori emissions from 11 biogenic and fossil source categories, the model results are compared with observations from 17 Advanced Global Atmospheric Gases Experiment (AGAGE) and National Oceanic and Atmospheric Administration (NOAA) surface stations and intercontinental Civil Aircraft for the Regular observation of the atmosphere Based on an Instrumented Container (CARIBIC) flights, with > 4800 CH4 samples, gathered on > 320 flights in the upper troposphere and lowermost stratosphere. Based on a simple optimization procedure, methane emission categories have been scaled to reduce discrepancies with the observational data for the period 1997–2006. With this approach, the all-station mean dry air mole fraction of 1780 nmol mol−1 could be improved from an a priori root mean square deviation (RMSD) of 1.31 % to just 0.61 %, associated with a coefficient of determination (R2) of 0.79. The simulated a priori interhemispheric difference of 143.12 nmol mol−1 was improved to 131.28 nmol mol−1, which matched the observations quite well (130.82 nmol mol−1). Analogously, aircraft measurements were reproduced well, with a global RMSD of 1.1 % for the measurements before 2007, with even better results on a regional level (e.g., over India, with an RMSD of 0.98 % and R2=0.65). With regard to emission optimization, this implied a 30.2 Tg CH4 yr−1 reduction in predominantly fossil-fuel-related emissions and a 28.7 Tg CH4 yr−1 increase of biogenic sources. With the same methodology, the CH4 growth that started in 2007 and continued almost linearly through 2013 was investigated, exploring the contributions by four potential causes, namely biogenic emissions from tropical wetlands, from agriculture including ruminant animals, and from rice cultivation, and anthropogenic emissions (fossil fuel sources, e.g., shale gas fracking) in North America. The optimization procedure adopted in this work showed that an increase in emissions from shale gas (7.67 Tg yr−1), rice cultivation (7.15 Tg yr−1), and tropical wetlands (0.58 Tg yr−1) for the period 2006–2013 leads to an optimal agreement (i.e., lowest RMSD) between model results and observations