ORCID Profile
0000-0001-8256-2661
Current Organisations
University of Oklahoma
,
Universita' degli Studi di Milano
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Publisher: Oxford University Press (OUP)
Date: 31-03-2012
DOI: 10.1093/IJE/DYS042
Publisher: American Geophysical Union (AGU)
Date: 03-2023
DOI: 10.1029/2021MS002964
Abstract: Recent progress in satellite observations has provided unprecedented opportunities to monitor vegetation activity at global scale. However, a major challenge in fully utilizing remotely sensed data to constrain land surface models (LSMs) lies in inconsistencies between simulated and observed quantities. For ex le, gross primary productivity (GPP) and transpiration (T) that traditional LSMs simulate are not directly measurable from space, although they can be inferred from spaceborne observations using assumptions that are inconsistent with those LSMs. In comparison, canopy reflectance and fluorescence spectra that satellites can detect are not modeled by traditional LSMs. To bridge these quantities, we presented an overview of the next generation land model developed within the Climate Modeling Alliance (CliMA), and simulated global GPP, T, and hyperspectral canopy radiative transfer (RT 400–2,500 nm for reflectance, 640–850 nm for fluorescence) at hourly time step and 1° spatial resolution using CliMA Land. CliMA Land predicts vegetation indices and outgoing radiances, including solar‐induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and near infrared reflectance of vegetation (NIRv) for any given sun‐sensor geometry. The spatial patterns of modeled GPP, T, SIF, NDVI, EVI, and NIRv correlate significantly with existing data‐driven products (mean R 2 = 0.777 for 9 products). CliMA Land would be also useful in high temporal resolution simulations, for ex le, providing insights into when GPP, SIF, and NIRv erge.
Publisher: Oxford University Press (OUP)
Date: 12-2013
DOI: 10.1093/IJE/DYT176
Publisher: European Respiratory Society (ERS)
Date: 25-08-2022
DOI: 10.1183/13993003.00469-2022
Abstract: Chronic obstructive pulmonary disease has been associated with exposures in the workplace. We aimed to assess the association of respiratory symptoms and lung function with occupation in the Burden of Obstructive Lung Disease study. We analysed cross-sectional data from 28 823 adults (≥40 years) in 34 countries. We considered 11 occupations and grouped them by likelihood of exposure to organic dusts, inorganic dusts and fumes. The association of chronic cough, chronic phlegm, wheeze, dyspnoea, forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV 1 )/FVC with occupation was assessed, per study site, using multivariable regression. These estimates were then meta-analysed. Sensitivity analyses explored differences between sexes and gross national income. Overall, working in settings with potentially high exposure to dusts or fumes was associated with respiratory symptoms but not lung function differences. The most common occupation was farming. Compared to people not working in any of the 11 considered occupations, those who were farmers for ≥20 years were more likely to have chronic cough (OR 1.52, 95% CI 1.19–1.94), wheeze (OR 1.37, 95% CI 1.16–1.63) and dyspnoea (OR 1.83, 95% CI 1.53–2.20), but not lower FVC (β=0.02 L, 95% CI −0.02–0.06 L) or lower FEV 1 /FVC (β=0.04%, 95% CI −0.49–0.58%). Some findings differed by sex and gross national income. At a population level, the occupational exposures considered in this study do not appear to be major determinants of differences in lung function, although they are associated with more respiratory symptoms. Because not all work settings were included in this study, respiratory surveillance should still be encouraged among high-risk dusty and fume job workers, especially in low- and middle-income countries.
Publisher: Wiley
Date: 05-01-2022
Publisher: Elsevier BV
Date: 04-2022
Publisher: BMJ
Date: 08-07-2019
DOI: 10.1136/OEMED-2019-105826
Abstract: Asbestos is the main risk factor for peritoneal mesothelioma (PeM). However, due to its rarity, PeM has rarely been investigated in community-based studies. We examined the association between asbestos exposure and PeM risk in a general population in Lombardy, Italy. From the regional mesothelioma registry, we selected PeM cases diagnosed in 2000–2015. Population controls (matched by area, gender and age) came from two case–control studies in Lombardy on lung cancer (2002–2004) and pleural mesothelioma (2014). Assessment of exposure to asbestos was performed through a quantitative job-exposure matrix (SYN-JEM) and expert evaluation based on a standardised questionnaire. We calculated period-specific and gender-specific OR and 90% CI using conditional logistic regression adjusted for age, province of residence and education. We selected 68 cases and 2116 controls (2000–2007) and 159 cases and 205 controls (2008–2015). The ORs for ever asbestos exposure (expert-based, 2008–2015 only) were 5.78 (90% CI 3.03 to 11.0) in men and 8.00 (2.56 to 25.0) in women the ORs for definite occupational exposure were 12.3 (5.62 to 26.7) in men and 14.3 (3.16 to 65.0) in women. The ORs for ever versus never occupational asbestos exposure based on SYN-JEM (both periods) were 2.05 (90% CI 1.39 to 3.01) in men and 1.62 (0.79 to 3.27) in women. In men, clear positive associations were found for duration, cumulative exposure (OR 1.33 (1.19 to 1.48) per fibres/mL-years) and latency. Using two different methods of exposure assessment we provided evidence of a clear association between asbestos exposure and PeM risk in the general population.
Publisher: Oxford University Press (OUP)
Date: 24-12-2012
DOI: 10.1093/IJE/DYS193
Location: United States of America
No related grants have been discovered for Sara De Matteis.