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Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter

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Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Atmos. Chem. Phys. Discuss., 15, 25329–25380, 2015 www.atmos-chem-phys-discuss.net/15/25329/2015/ doi:10.5194/acpd-15-25329-2015 © Author(s) 2015. CC Attribution 3.0 License. This discussion paper is/has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP if available. Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter B. Ford1 and C. L. Heald2 1Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA 2Department of Civil and Environmental Engineering and Department of Earth, Atmospheric and Planetary Sciences, MIT, Cambridge, MA, USA Received: 8 July 2015 – Accepted: 19 August 2015 – Published: 16 September 2015 Correspondence to: B. Ford (bonne@atmos.colostate.edu) Published by Copernicus Publications on behalf of the European Geosciences Union. ACPD 15, 25329–25380, 2015 Exploring exposure uncertainty B. Ford and C. L. Heald Title Page Abstract Introduction Conclusions References Tables Figures ◭◮ ◭◮ Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion 25329 Abstract The negative impacts of fine particulate matter (PM2.5) exposure on human health are a primary motivator for air quality research. However, estimates of the air pollution health burden vary considerably and strongly depend on the datasets and methodol5 ogy. Satellite observations of aerosol optical depth (AOD) have been widely used to overcome limited coverage from surface monitoring and to assess the global population exposure to PM2.5 and the associated premature mortality. Here we quantify the uncertainty in determining the burden of disease using this approach, discuss different methods and datasets, and explain sources of discrepancies among values in the 10 literature. For this purpose we primarily use the MODIS satellite observations in concert with the GEOS-Chem chemical transport model. We contrast results in the United States and China for the years 2004–2011. We estimate that in the United States, exposure to PM2.5 accounts for approximately 4 % of total deaths compared to 22 % in China (using satellite-based exposure), which falls within the range of previous esti15 mates. The difference in estimated mortality burden based solely on a global model vs. that derived from satellite is approximately 9 % for the US and 4 % for China on a nationwide basis, although regionally the differences can be much greater. This difference is overshadowed by the uncertainty in the methodology for deriving PM2.5 burden from satellite observations, which we quantify to be on order of 20 % due to uncertainties in 20 the AOD-to-surface-PM2.5 relationship, 10 % due to the satellite observational uncertainty, and 30 % or greater uncertainty associated with the application of concentration response functions to estimated exposure. 1 Introduction By 2030, air pollution will be the leading environmentally-related cause of premature 25 mortality worldwide (OECD, 2012). The World Health Organization (WHO) estimates that exposure to outdoor air pollution resulted in 3.7 million premature deaths in 2012. 25330 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ACPD 15, 25329–25380, 2015 Exploring exposure uncertainty B. Ford and C. L. Heald Title Page Abstract Introduction Conclusions References Tables Figures ◭◮ ◭◮ Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion Many epidemiological studies have shown that chronic exposure to fine particulate matter (PM2.5) is associated with an increase in the risk of mortality from respiratory diseases, lung cancer, and cardiovascular disease, with the underlying assumption that a causal relationship exists between PM and health outcomes (Dockery et al., 1993; 5 Jerrett et al., 2005; Krewski et al., 2000; Pope III et al., 1995, 2002, 2004, 2006). This has been shown through single and multi-population time series analyses, long-term cohort studies, and meta-analyses. In order to stress the negative impacts of air pollution on human health and inform policy development (particularly with regard to developing strategies for intervention 10 and risk reduction), many studies have calculated the total number of premature deaths each year attributable to air pollution exposure or the “burden of disease”. One of the main obstacles in attributing specific health impacts of PM2.5 is determining personal exposure and linking this to health outcomes. Jerrett et al. (2005) suggest personal monitors would be the optimal method, but point out that the financial costs and time15 intensiveness limit widespread use. Many studies have instead relied on fixed-site monitors within a certain radius to estimate exposure. However, these monitoring networks are generally located in urban regions and provide no information on concentration gradients between sites. Thus, epidemiological studies typically quantify the aggregate population response determined from a subset of individuals. 20 Estimating the burden of disease associated with particulate air pollution requires robust estimates of PM2.5 exposure. Fixed-site monitoring networks can be costly to operate and maintain, and the sampling time period for many of these monitors in the United States is often only every third or sixth day. Due to the high spatial and temporal variability in aerosol concentrations, this makes it difficult to determine expo25 sure and widespread health impacts. Worldwide, monitoring networks are even scarcer, with many developing countries lacking any long-term measurements. “Satellite-based” concentrations are now used extensively for estimating mortality burdens and health impacts (e.g. Crouse et al., 2012; Hystad et al., 2012; Evans et al., 2013). Satellite observations of aerosol optical depth (AOD) offer much needed observational constraints 25331 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ACPD 15, 25329–25380, 2015 Exploring exposure uncertainty B. Ford and C. L. Heald Title Page Abstract Introduction Conclusions References Tables Figures ◭◮ ◭◮ Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion for population-level exposure estimates in regions where surface air quality monitoring is limited; however they represent the vertically-integrated extinction of radiation due to aerosols, and thus additional information on the vertical distribution and the optical properties of particulate matter is required (often provided by a model) to translate 5 these observations to surface air quality (van Donkelaar et al., 2006, 2010; Liu et al., 2004, 2005). Alternatively, studies have relied on model-based estimates of PM2.5 exposure. Table 1 shows that the resulting estimates of premature mortality vary widely. Here, we discuss both of these methods and contrast the uncertainty in these approaches for estimating exposure for both the US, where air quality has improved due 10 to regulations and control technology, and China, where air quality is a contemporary national concern. Our objective is to investigate the factors responsible for uncertainty in chronic PM2.5 burden of disease estimates, and use these uncertainties to contextualize the comparison of satellite-based and model-based estimates of premature mortality with previous work. 15 2 Methods and tools 2.1 General formulation to calculate the burden of disease To estimate the burden of premature mortality due to a specific factor like PM2.5 exposure, we rely on Eqs. (1) and (2) (Eqs. 6 and 8 in Ostro, 2004, and as previously used in van Donkelaar et al., 2011; Evans et al., 2013; Marlier et al., 2013; Zheng et al., 20 2015). The attributable fraction (AF) of mortality due to PM2.5 exposure depends on the relative risk value (RR), which here is the ratio of the probability of mortality (allcause or from a specific disease) occurring in an exposed population to the probability of mortality occurring in a non-exposed population. The total burden due to PM2.5 exposure (∆M) can be estimated by convolving the AF with the baseline mortality (equal 25 to the baseline mortality rate Mb × exposed population P ). The relative risk is assumed to change (∆RR) with concentration, so that, in general, exposure to higher concentra- 25332 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ACPD 15, 25329–25380, 2015 Exploring exposure uncertainty B. Ford and C. L. Heald Title Page Abstract Introduction Conclusions References Tables Figures ◭◮ ◭◮ Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion tions of PM2.5 should pose a greater risk for premature mortality (Sect. 2.4). AF = (RR − 1)/(RR) (or the alternate form of AF = ∆RR/(∆RR + 1) ∆M = Mb × P × AF (1) (2) Application of this approach requires information on the baseline mortality rates and 5 population, along with the RR, which is determined through a concentration response function (including a shape and initial relative risk, Sect. 2.4), and ambient surface PM2.5 concentrations. 2.2 Baseline mortality and population For population data, we use the Gridded Population of the World, Version 3 (GPWv3), 10 created by the Center for International Earth Science Information Network (CIESIN) and available from the Socioeconomic Data and Applications Center (SEDAC). This gridded dataset has a native resolution of 2.5 arc-minutes (∼ 5 km at the equator) and provides population estimates for 1990, 1995, and 2000, and projections (made in 2004) for 2005, 2010, and 2015. We linearly interpolate between available years to 15 get population estimates for years not provided. Population density for China and the United States for the year 2000 are shown in Fig. 1 along with the projected change in population density by the year 2015, illustrating continued growth of urbanized areas (at the expense of rural regions in China). We also compare mortality estimates using only urban area population (similar to Lelieveld et al., 2013 which estimates premature 20 mortality in mega-cities). For this, we rely on the populated places dataset (provided by Natural Earth) which is determined from LandScan population estimates (Bright et al., 2008). In the US, approximately 80 % of the population lives in urban areas. For China, 36 % of the population lived in urban areas in 2000, but this number rose to 53 % in 2013 (World Bank, 2015). 25 To determine baseline mortalities in the US for cardiovascular disease, lung cancer, and respiratory disease, we use death rates for each cause of death for all ages from 25333 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ACPD 15, 25329–25380, 2015 Exploring exposure uncertainty B. Ford and C. L. Heald Title Page Abstract Introduction Conclusions References Tables Figures ◭◮ ◭◮ Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion the Center for Disease Control (cdc.gov) for each year and each state which we then multiply by the gridded population to obtain the total baseline mortality. Other studies have also used country-wide (or region) (e.g. Evans et al., 2013) or county-level (e.g. Fann et al., 2013) average deaths rates. 5 Mortality values are not as readily available for China, so we rely on country-wide values for baseline mortality (WHO age-standardized mortality rates by cause). Therefore, in China spatial variations in Mb are only due to variations in population and not regional variations in actual death rates (i.e. we do not account for death-specific mortality rates varying between provinces). In order to account for some regional variability 10 in mortality rates, we use a population threshold to distinguish between urban and rural regions for lung cancer mortality rates (Chen et al., 2013). 2.3 Relative risk The relative risk (RR) is a ratio of the probability of a health endpoint (in this case premature mortality) occurring in a population exposed to a certain level of pollution 15 to the probability of that endpoint occurring in a population that is not exposed. Values greater than one suggest an increased risk, while a value of one would suggest no change in risk. These values are determined through epidemiological studies which relate individual health impacts to changes in concentrations, and literature values span a large range (Fig. 2). While these studies attempt to account for differences in popu20 lations, lifestyles, pre-existing conditions, and co-varying pollutants, relative risk ratios determined from each study still differ. This is likely due to variables not taken into consideration, errors in exposure estimates (“exposure misclassification”) (Sheppard et al., 2012), and because, although the long-term effects of exposure to atmospheric pollutants have been well-documented, the pathophysiological mechanisms linking ex25 posure to mortality risk are still unclear (Chen and Goldberg, 2009; Pope III and Dockery, 2013; Sun et al., 2010) making it difficult to determine how transferable results are from the context in which they were generated. 25334 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ACPD 15, 25329–25380, 2015 Exploring exposure uncertainty B. Ford and C. L. Heald Title Page Abstract Introduction Conclusions References Tables Figures ◭◮ ◭◮ Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion We use risk ratios for cardiovascular and lung cancer premature mortality due to chronic exposure determined by Krewski et al. (2009), which is an extended analysis of the American Cancer Society study (Pope III et al., 1995), and for respiratory disease, from Laden et al. (2006) which is an updated and extended analysis of the Harvard Six 5 Cities study (Pope III et al., 2002). We use the updated Krewski et al. (2009) risk ratios as they are widely used in similar studies due to the large study population with national coverage, 18 year time span, and extensive analysis of confounding variables (ecological covariates, gaseous pollutants, weather, medical history, age, smoking, etc.). Using these same risk ratios also makes our results more directly comparable to studies in 10 Table 1 which rely on the risk ratios from these three studies (Krewski et al., 2009; Laden et al., 2006; Pope III et al., 2002). 2.4 Concentration response function In order to determine an attributable fraction, it is necessary to understand how the response changes with concentration (i.e. does the relative risk increase, decrease, 15 or level off with higher concentrations?). The shape of this concentration response function is an area of on-going epidemiological research (e.g. Burnett et al., 2014; Pope III et al., 2015). For our initial results, we rely on Eq. (3), where the change in relative risk (RR, given as per 10 µg m−3) linearly depends on the surface PM2.5 concentration (C, in µg m−3). In 20 this equation, C0 can be considered the “policy relevant (PRB)/target”, “natural background” or “threshold”/“counterfactual”/“lowest effect level” surface PM2.5 concentration. As studies have shown that there is no concentration level below which there is no adverse health effect for PM (e.g. Pope III et al., 2002; Shi et al., 2015), in our initial analysis, we assume this value is zero. However, other studies often set C0 to the value 25 of the lowest measured level (LML) observed in the epidemiology study from which the RRs are derived (e.g. Evans et al., 2013 use 5.8 µg m−3 with the RR from Krewski et al., 2009) or use the “policy relevant” background (PRB) concentration, which is generally determined from model simulations in which domestic anthropogenic emissions 25335 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ACPD 15, 25329–25380, 2015 Exploring exposure uncertainty B. Ford and C. L. Heald Title Page Abstract Introduction Conclusions References Tables Figures ◭◮ ◭◮ Back Close Full Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | have been turned off (e.g. Fann et al., 2012). ∆RR = (RR − 1) × (C − C0)/10 (3) Linear response functions are generally a good fit to observed responses at lower concentrations (Pope III et al., 2002). However, some studies have suggested that 5 linear response functions can greatly overestimate RR at high concentrations, where responses may start to level off. This is uncertain, as most epidemiology studies of the health effects of air pollution exposure have generally been conducted under lower concentrations (i.e. in the US). In order to determine the shape of this response at higher concentrations, smoking has been used as a proxy (Pope III et al., 2011, 2009), 10 which does show a diminishing response at higher concentrations. Therefore, both log-linear (Eqs. 4 and 5, where β = 0.15515/0.23218 for heart disease/lung cancer from Pope III et al., 2002, or β = 0.18878/0.21136 for heart disease/lung cancer from Krewski et al., 2009 in Eq. (5) and β = 0.01205/0.01328 for heart disease/lung cancer from Krewski et al., 2009, in Eq. 4) and power law (Eq. 6, where I is the inhalation rate 15 of 18 m3 day−1, β = 0.2730/0.3195, α = 0.2685/0.7433 for heart disease/lung cancer from Pope III et al., 2011, and as used in Marlier et al., 2013) functions have been also been explored in this study. We note that Cohen et al. (2005) and Anenberg et al. (2010) reference Eq. equilibrium value of MeCpG steps (,+14 deg.) [31,44]. In comparison, methylation has a significantly lower stability cost when happening at major groove positions, such as 211 and 21 base pair from dyad (mutations 9 and 12), where the roll of the nucleosome bound conformation (+10 deg.) is more compatible with the equilibrium geometry of MeCpG steps. The nucleosome destabilizing effect of cytosine methylation increases with the number of methylated cytosines, following the same position dependence as the single methylations. The multiple-methylation case reveals that each major groove meth- PLOS Computational Biology | www.ploscompbiol.org 3 November 2013 | Volume 9 | Issue 11 | e1003354 DNA Methylation and Nucleosome Positioning ylation destabilizes the nucleosome by around 1 kJ/mol (close to the average estimate of 2 kJ/mol obtained for from individual methylation studies), while each minor groove methylation destabilizes it by up to 5 kJ/mol (average free energy as single mutation is around 6 kJ/mol). This energetic position-dependence is the reverse of what was observed in a recent FRET/SAXS study [30]. The differences can be attributed to the use of different ionic conditions and different sequences: a modified Widom-601 sequence of 157 bp, which already contains multiple CpG steps in mixed orientations, and which could assume different positioning due to the introduction of new CpG steps and by effect of the methylation. The analysis of our trajectories reveals a larger root mean square deviation (RMSD) and fluctuation (RMSF; see Figures S2– S3 in Text S1) for the methylated nucleosomes, but failed to detect any systematic change in DNA geometry or in intermolecular DNA-histone energy related to methylation (Fig. S1B, S1C, S4–S6 in Text S1). The hydrophobic effect should favor orientation of the methyl group out from the solvent but this effect alone is not likely to justify the positional dependent stability changes in Figure 2, as the differential solvation of the methyl groups in the bound and unbound states is only in the order of a fraction of a water molecule (Figure S5 in Text S1). We find however, a reasonable correlation between methylation-induced changes in hydrogen bond and stacking interactions of the bases and the change in nucleosome stability (see Figure S6 in Text S1). This finding suggests that methylation-induced nucleosome destabilization is related to the poorer ability of methylated DNA to fit into the required conformation for DNA in a nucleosome. Changes in the elastic deformation energy between methylated and un-methylated DNA correlate with nucleosomal differential binding free energies To further analyze the idea that methylation-induced nucleosome destabilization is connected to a worse fit of methylated DNA into the required nucleosome-bound conformation, we computed the elastic energy of the nucleosomal DNA using a harmonic deformation method [36,37,44]. This method provides a rough estimate of the energy required to deform a DNA fiber to adopt the super helical conformation in the nucleosome (full details in Suppl. Information Text S1). As shown in Figure 2, there is an evident correlation between the increase that methylation produces in the elastic deformation energy (DDE def.) and the free energy variation (DDG bind.) computed from MD/TI calculations. Clearly, methylation increases the stiffness of the CpG step [31], raising the energy cost required to wrap DNA around the histone octamers. This extra energy cost will be smaller in regions of high positive roll (naked DNA MeCpG steps have a higher roll than CpG steps [31]) than in regions of high negative roll. Thus, simple elastic considerations explain why methylation is better tolerated when the DNA faces the histones through the major groove (where positive roll is required) that when it faces histones through the minor groove (where negative roll is required). Nucleosome methylation can give rise to nucleosome repositioning We have established that methylation affects the wrapping of DNA in nucleosomes, but how does this translate into chromatin structure? As noted above, accumulation of minor groove methylations strongly destabilizes the nucleosome, and could trigger nucleosome unfolding, or notable changes in positioning or phasing of DNA around the histone core. While accumulation of methylations might be well tolerated if placed in favorable positions, accumulation in unfavorable positions would destabilize the nucleosome, which might trigger changes in chromatin structure. Chromatin could in fact react in two different ways in response to significant levels of methylation in unfavorable positions: i) the DNA could either detach from the histone core, leading to nucleosome eviction or nucleosome repositioning, or ii) the DNA could rotate around the histone core, changing its phase to place MeCpG steps in favorable positions. Both effects are anticipated to alter DNA accessibility and impact gene expression regulation. The sub-microsecond time scale of our MD trajectories of methylated DNAs bound to nucleosomes is not large enough to capture these effects, but clear trends are visible in cases of multiple mutations occurring in unfavorable positions, where unmethylated and methylated DNA sequences are out of phase by around 28 degrees (Figure S7 in Text S1). Due to this repositioning, large or small, DNA could move and the nucleosome structure could assume a more compact and distorted conformation, as detected by Lee and Lee [29], or a slightly open conformation as found in Jimenez-Useche et al. [30]. Using the harmonic deformation method, we additionally predicted the change in stability induced by cytosine methylation for millions of different nucleosomal DNA sequences. Consistently with our calculations, we used two extreme scenarios to prepare our DNA sequences (see Fig. 3): i) all positions where the minor grooves contact the histone core are occupied by CpG steps, and ii) all positions where the major grooves contact the histone core are occupied by CpG steps. We then computed the elastic energy required to wrap the DNA around the histone proteins in unmethylated and methylated states, and, as expected, observed that methylation disfavors DNA wrapping (Figure 3A). We have rescaled the elastic energy differences with a factor of 0.23 to match the DDG prediction in figure 2B. In agreement with the rest of our results, our analysis confirms that the effect of methylation is position-dependent. In fact, the overall difference between the two extreme methylation scenarios (all-in-minor vs all-in-major) is larger than 60 kJ/mol, the average difference being around 15 kJ/ mol. We have also computed the elastic energy differences for a million sequences with CpG/MeCpG steps positioned at all possible intermediate locations with respect to the position (figure 3B). The large differences between the extreme cases can induce rotations of DNA around the histone core, shifting its phase to allow the placement of the methylated CpG steps facing the histones through the major groove. It is illustrative to compare the magnitude of CpG methylation penalty with sequence dependent differences. Since there are roughly 1.5e88 possible 147 base pairs long sequence combinations (i.e., (4n+4(n/2))/2, n = 147), it is unfeasible to calculate all the possible sequence effects. However, using our elastic model we can provide a range of values based on a reasonably large number of samples. If we consider all possible nucleosomal sequences in the yeast genome (around 12 Mbp), the energy difference between the best and the worst sequence that could form a nucleosome is 0.7 kj/mol per base (a minimum of 1 kJ/mol and maximum of around 1.7 kJ/mol per base, the first best and the last worst sequences are displayed in Table S3 in Text S1). We repeated the same calculation for one million random sequences and we obtained equivalent results. Placing one CpG step every helical turn gives an average energetic difference between minor groove and major groove methylation of 15 kJ/ mol, which translates into ,0.5 kJ/mol per methyl group, 2 kJ/ mol per base for the largest effects. Considering that not all nucleosome base pair steps are likely to be CpG steps, we can conclude that the balance between the destabilization due to CpG methylation and sequence repositioning will depend on the PLOS Computational Biology | www.ploscompbiol.org 4 November 2013 | Volume 9 | Issue 11 | e1003354 DNA Methylation and Nucleosome Positioning Figure 3. Methylated and non-methylated DNA elastic deformation energies. (A) Distribution of deformation energies for 147 bplong random DNA sequences with CpG steps positioned every 10 base steps (one helical turn) in minor (red and dark red) and major (light and dark blue) grooves respectively. The energy values were rescaled by the slope of a best-fit straight line of figure 2, which is 0.23, to por la lectura a través de la lectura de la prensa. La educación en los medios las fuerzas dispersas en función de los soportes mediáticos y orientarse más hacia la educación en medios que al dominio adquiere pleno derecho y entidad en la sección sexta titulada «competencias sociales y cívi- técnico de los aparatos. cas» que indica que «los alum- nos deberán ser capaces de juz- gar y tendrán espíritu crítico, lo que supone ser educados en los las programaciones oficiales, ya que, a lo largo de un medios y tener conciencia de su lugar y de su influencia estudio de los textos, los documentalistas del CLEMI en la sociedad». han podido señalar más de una centena de referencias a la educación de los medios en el seno de disciplinas 4. Un entorno positivo como el francés, la historia, la geografía, las lenguas, Si nos atenemos a las cifras, el panorama de la las artes plásticas : trabajos sobre las portadas de educación en medios es muy positivo. Una gran ope- prensa, reflexiones sobre temas mediáticos, análisis de ración de visibilidad como la «Semana de la prensa y publicidad, análisis de imágenes desde todos los ángu- de los medios en la escuela», coordinada por el CLE- los, reflexión sobre las noticias en los países europeos, MI, confirma año tras año, después de 17 convocato- información y opinión rias, el atractivo que ejerce sobre los profesores y los Esta presencia se constata desde la escuela mater- alumnos. Concebida como una gran operación de nal (2 a 6 años) donde, por ejemplo, se le pregunta a complementariedad entre la escuela y los profesiona- los niños más pequeños si saben diferenciar entre un les de los medios, alrededor del aprendizaje ciudada- periódico, un libro, un catálogo, a través de activida- no de la comunicación mediática, este evento moviliza des sensoriales, si saben para qué sirve un cartel, un durante toda una semana un porcentaje elevado de periódico, un cuaderno, un ordenador si son capa- centros escolares que representan un potencial de 4,3 ces de reconocer y distinguir imágenes de origen y de millones de alumnos (cifras de 2006). Basada en el naturaleza distintas. Podríamos continuar con más voluntariado, la semana permite desarrollar activida- ejemplos en todos los niveles de enseñanza y práctica- des más o menos ambiciosas centradas en la introduc- Páginas 43-48 ción de los medios en la vida de la escuela a través de la instalación de kioscos, organización de debates con profesionales y la confección por parte de los alumnos de documentos difundidos en los medios profesionales. Es la ocasión de dar un empujón a la educación en medios y de disfrutarlos. Los medios –un millar en 2006– se asocian de maneras diversas ofreciendo ejemplares de periódicos, acceso a noticias o a imágenes, proponiendo encuentros, permitiendo intervenir a los jóvenes en sus ondas o en sus columnas Esta operación da luz al trabajo de la educación en medios y moviliza a los diferentes participantes en el proyecto. 5. La formación de los docentes La formación es uno de los pilares principales de la educación en los medios. Su función es indispensable ya que no se trata de una disciplina, sino de una enseñanza que se hace sobre la base del voluntariado y del compromiso personal. Se trata de convencer, de mostrar, de interactuar. En primer lugar es necesario incluirla en la formación continua de los docentes, cuyo volumen se ha incrementado desde 1981 con la aparición de una verdadera política de formación continua de personal. Es difícil dar una imagen completa del volumen y del público, pero si nos atenemos a las cifras del CLEMI, hay más de 24.000 profesores que han asistido y se han involucrado durante 2004-05. 5.1. La formación continua En la mayoría de los casos, los profesores reciben su formación en contextos cercanos a su centro de trabajo, o incluso en este mismo. Después de una política centrada en la oferta que hacían los formadores, se valora más positivamente la demanda por parte del profesorado, ya que sólo así será verdaderamente fructífera. Los cursos de formación se repartieron en varias categorías: desde los formatos más tradicionales (cursos, debates, animaciones), hasta actividades de asesoramiento y de acompañamiento, y por supuesto los coloquios que permiten un trabajo en profundidad ya que van acompañados de expertos investigadores y profesionales. Citemos, por ejemplo en 2005, los coloquios del CLEMI-Toulouse sobre el cine documental o el del CLEMI-Dijon sobre «Políticos y medios: ¿connivencia?». Estos coloquios, que forman parte de un trabajo pedagógico regular, reagrupan a los diferentes participantes regionales y nacionales alrededor de grandes temas de la educación en medios y permiten generar nuevos conocimientos de aproximación y una profundización. Páginas 43-48 Hay otro tipo de formación original que se viene desarrollando desde hace menos tiempo, a través de cursos profesionales, como por ejemplo, en el Festival Internacional de Foto-periodismo «Visa para la imagen», en Perpignan. La formación se consolida en el curso, da acceso a las exposiciones, a las conferencias de profesionales y a los grandes debates, pero añade además propuestas pedagógicas y reflexiones didácticas destinadas a los docentes. Estas nuevas modalidades de formación son también consecuencia del agotamiento de la formación tradicional en las regiones. Los contenidos más frecuentes en formación continua conciernen tanto a los temas más clásicos como a los cambios que se están llevando a cabo en las prácticas mediáticas. Así encontramos distintas tendencias para 2004-05: La imagen desde el ángulo de la producción de imágenes animadas, el análisis de la imagen de la información o las imágenes del J.T. La prensa escrita y el periódico escolar. Internet y la información en línea. Medios y educación de los medios. 5.2 La formación inicial La formación inicial está aun en un grado muy ini- cial. El hecho de que la educación en medios no sea una disciplina impide su presencia en los IUFM (Institutos Universitarios de Formación de Maestros) que dan una prioridad absoluta a la didáctica de las disciplinas. En 2003, alrededor de 1.400 cursillistas sobre un total de 30.000 participaron en un momento u otro de un módulo de educación en medios. Estos módulos se ofrecen en función del interés que ese formador encuentra puntualmente y forman parte a menudo de varias disciplinas: documentación, letras, historia-geografía Estamos aún lejos de una política concertada en este dominio. La optativa «Cine-audiovisual» ha entrado desde hace muy poco tiempo en algunos IUFM destinada a obtener un certificado de enseñanza de la opción audiovisual y cine. Internet tiene cabida también en los cursos de formación inicial, recientemente con la aparición de un certificado informático y de Internet para los docentes, dirigido más a constatar competencias personales que a valorar una aptitud para enseñarlos. 6. ¿Y el futuro? El problema del futuro se plantea una vez más por la irrupción de nuevas técnicas y nuevos soportes. La difusión acelerada de lo digital replantea hoy muchas cuestiones relativas a prácticas mediáticas. Muchos Comunicar, 28, 2007 47 Comunicar, 28, 2007 Enrique Martínez-Salanova '2007 para Comunicar 48 trabajos que llevan el rótulo de la educación en medios solicitan una revisión ya que los conceptos cambian. La metodología elaborada en el marco de la educación en medios parece incluso permitir la inclinación de la sociedad de la información hacia una sociedad del conocimiento, como defiende la UNESCO. En Francia, se necesitaría unir las fuerzas dispersas en función de los soportes mediáticos y orientarse más hacia la educación en medios que al dominio técnico de los aparatos. Los avances recientes en el reconocimiento de estos contenidos y las competencias que supondrían podrían permitirlo. Referencias CLEMI/ACADEMIE DE BORDEAUX (Ed.) (2003): Parcours médias au collège: approches disciplinaires et transdisciplinaires. Aquitaine, Sceren-CRDP. GONNET, J. (2001): Education aux médias. Les controverses fécondes. Paris, Hachette Education/CNDP. SAVINO, J.; MARMIESSE, C. et BENSA, F. (2005): L’éducation aux médias de la maternelle au lycée. Direction de l’Enseignement Scolaire. Paris, Ministère de l’Education Nationale, Sceren/CNDP, Témoigner. BEVORT, E. et FREMONT, P. (2001): Médias, violence et education. Paris, CNDP, Actes et rapports pour l’éducation. – www.clemi.org: fiches pédagogiques, rapports et liens avec les pages régionales/académiques. – www.ac-nancy-metz.fr/cinemav/quai.html: Le site «Quai des images» est dédié à l’enseignement du cinéma et de l’audiovisuel. – www.france5.fr/education: la rubrique «Côté profs» a une entrée «education aux médias». – www.educaunet.org: Programme européen d’éducation aux risques liés à Internet. dResedfeleexliobnuetsacón Páginas 43-48
Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter
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Exploring the uncertainty associated with satellite-based estimates of premature mortality due to exposure to fine particulate matter

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