Forest height is an important variable for modeling terrestrial carbon storage and global carbon cycle dynamics. Spaceborne SAR Interferometry (InSAR) has the sensitivity to measure canopy height and ...the underlying topography. In this paper, we refine and automate an interferometric ground finding approach that exploits few-look (2- to 4-look) averaged interferograms and incorporates the use of a coherent electromagnetic simulator and field inventory data. Using the coherent electromagnetic simulator, an InSAR simulation based on field data is performed to study the true ground position as a function of the statistics of few-look InSAR phase heights from a model perspective. With this statistical model, both the underlying topography and the canopy height (mean and top canopy height) can be estimated. Using German Aerospace Center's (DLR) single-baseline single-polarization TanDEM-X InSAR data, we validate the approach over a Brazilian tropical forest (Tapajós National Forest) with both field inventory and lidar data. As validated against lidar data, the underlying topography is estimated to an accuracy of 3 m. At one hectare aggregated pixel size, InSAR phase-center height is best compared with the field/lidar mean canopy height with an accuracy of 2–3 m, while InSAR-inverted total height best characterizes the lidar top canopy height with an accuracy of 4–5 m. Given the global data availability of TanDEM-X and the future TanDEM-L, this approach has the potential for wall-to-wall mapping of forest height as well as underlying topography and also serves as a complementary tool to other existing InSAR, Polarimetric InSAR (PolInSAR) and SAR tomography (TomoSAR) methods when only single polarization and/or baseline data are available.
•Novel few-look InSAR approach for measuring forest height and underlying topography.•Ground finding algorithm from statistics of simulated few-look InSAR phase heights.•Validation with single-pol/baseline TanDEM-X data against field and lidar data.•Forest mean and top height are measured to an accuracy of 2 m and 4 m at 1-ha scale.•Underlying ground topography is measured to an accuracy of 3 m.
Pseudomonas syringae produces highly efficient biological ice nuclei (IN) that were proposed to influence precipitation by freezing water in clouds. This bacterium may be capable of dispersing ...through the atmosphere, having been reported in rain, snow, and cloud water samples. This study assesses its survival and maintenance of IN activity under stressing conditions present at high altitudes, such as UV radiation within clouds. Strains of the pathovars syringae and garcae were compared to Escherichia coli. While UV-C effectively inactivated these cells, the Pseudomonas were much more tolerant to UV-B. The P. syringae strains were also more resistant to radiation from a solar simulator, composed of UV-A and UV-B, while only one of them suffered a decline in IN activity at -5 °C after long exposures. Desiccation at different relative humidity values also affected the IN, but some activity at -5 °C was always maintained. The pathovar garcae tended to be more resistant than the pathovar syringae, particularly to desiccation, though its IN were found to be generally more sensitive. Compared to E. coli, the P. syringae strains appear to be better adapted to survival under conditions present at high altitudes and in clouds.
Abstract
Precipitation in clouds can form by either warm-rain or ice crystal processes, referred to as warm and cold formation pathways, respectively. Here, we investigate the warm and cold pathway ...contributions to surface precipitation in simulated continental convective storms. We analyze three contrasting convective storms that are cold-based, slightly warm-based and very warm-based. We apply tracer-tagging techniques in our aerosol-cloud model to determine simulated microphysical pathways that lead to precipitation. We find cold components of graupel and rain mass were higher than warm components in cold- and slightly warm-based clouds. By contrast, in very warm-based clouds nearly 80% of surface precipitation was formed via warm-rain processes. Lowering of cloud base altitude to levels about 10–20 K warmer switched surface precipitation to being mostly warm, due to enhanced moisture content in the planetary boundary layer and larger cloud droplets aloft intensifying raindrop freezing. Our simulations indicate that warm and cold processes co-exist in any storm and the balance between them is determined by cloud base temperature and solute aerosol conditions.
Although patients’ clinical conditions have been shown to be associated with coronavirus disease (COVID-19) severity and outcome, their impact on hospital costs are not known. This economic ...evaluation of COVID-19 admissions aimed to assess direct and fixed hospital costs and describe their particularities in different clinical and demographic conditions and outcomes in the largest public hospital in Latin America, located in São Paulo, Brazil, where a whole institute was exclusively dedicated to COVID-19 patients in response to the pandemic.
This is a partial economic evaluation performed from the hospital´s perspective and is a prospective, observational cohort study to assess hospitalization costs of suspected and confirmed COVID-19 patients admitted between March 30 and June 30, 2020, to Hospital das Clínicas of the University of São Paulo Medical School (HCFMUSP) and followed until discharge, death, or external transfer. Micro- and macro-costing methodologies were used to describe and analyze the total cost associated with each patient's underlying medical conditions, itinerary and outcomes as well as the cost components of different hospital sectors.
The average cost of the 3254 admissions (51.7% of which involved intensive care unit stays) was US$12,637.42. The overhead cost was its main component. Sex, age and underlying hypertension (US$14,746.77), diabetes (US$15,002.12), obesity (US$18,941.55), chronic renal failure (US$15,377.84), and rheumatic (US$17,764.61), hematologic (US$15,908.25) and neurologic (US$15,257.95) diseases were associated with higher costs. Age strata >69 years, reverse transcription polymerase chain reaction (RT-PCR)-confirmed COVID-19, comorbidities, use of mechanical ventilation or dialysis, surgery and outcomes remained associated with higher costs.
Knowledge of COVID-19 hospital costs can aid in the development of a comprehensive approach for decision-making and planning for future risk management.
The elderly population spend relatively more time indoors and is more sensitive to air pollution–related health risks but there is limited information on the quality of the air they breathe inside ...their residences. The objectives of this work are to (i) characterise mass of size–segregated particulate matter (PM) in elderly residences in Metropolitan Area of Sao Paulo (MASP) in Brazil, (ii) assess the impact of the meteorological parameters on the behaviour of indoor PM concentrations, (iii) evaluate the indoor and outdoor relationship of PM mass concentration, and (iv) estimate the respiratory deposition doses (RDD). To achieve these objectives, we measured mass concentrations of size–segregated particles in 59 elderly residences in MASP. The measurements were made in the 0.25–10 μm size range in 5 size bins using a Personal Cascade Impactor Sampler. We evaluated the mass concentration of particles using a gravimetric method and compared our PM10 (sum of all size bins) and PM2.5 (sum of all size bins, except PM10–2.5) concentrations against the 24 h mean guidelines recommended by World Health Organization (WHO). Our results show the mean PM10 and PM2.5 measured in elderly residences in MASP as 35.2 and 27.4 μg m−3, respectively. PM2.5 and PM<0.25 (particles with aerodynamic diameter of less than 0.25 μm) contributed 78% and 38% of total PM10, respectively, clearly suggesting a significantly high exposure to fine particles by the elderly. About 13 and 43% of the measurements exceeded the WHO's PM10 and PM2.5 guidelines, respectively. The samples were clustered into five groups to found the behaviour of indoor PM. The cluster representing the residences with higher PM concentration in all size bins are predominantly residences near the heavy traffic areas during the non–precipitation days. About 68% of residences showed the highest fraction of PM<0.25, indicating a high concentration of ultrafine particles in these residences. We calculated indoor/outdoor (I/O) rates and found them as 1.89 and 1.06 for PM2.5 and PM10, respectively. About 77% and 40% of the residences had higher PM2.5 and PM10 indoors than those in outdoor environments. During seated position, the RDD rates for coarse and fine particles for male elderly were found to be about 20% and 25% higher compared with female elderly, respectively. Our findings suggest a control of indoor sources in the elderly residences to limit adverse health effects of particulate matter, especially fine particles, on elderly.
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•Size–segregated particles in 59 elderly residences of São Paulo were measured.•The dominance of fine particles was found with PM2.5 contributing 78% of total PM10.•Indoor sources dominated with I/O as 1.89 and 1.06 for PM2.5 and PM10, respectively.•Respiratory deposition for PM2.5 was almost 25% higher in male than female elderly.•Dominance of fine particles suggests control of indoor sources in elderly residences.
Tropical forest disturbance (such as selective logging and fire) along with deforestation have significant contributions to the carbon source due to land-use change and anthropogenic CO2 emissions, ...and thus envisioned by United Nation's REDD+ programme. In previous work, spaceborne single-pass InSAR phase-center height has been shown to have the capability of accurately monitoring the subtle height change due to forest growth and degradation (with meter or even sub-meter level RMSE about the regression curve fit to time). In this paper, a new approach using spaceborne SAR interferometry has been developed to detect and quantify selective logging events. In particular, a quantitative indicator of forest disturbance is first defined, namely disturbance index (DI; from 0 “no disturbance” to 1 “deforestation”). A numerical field data-based InSAR simulation is then performed to study the functional relationship between the field-measured DI and InSAR relative phase-center height change from a modeled perspective. A selective logging event (October 2015 through January 2016) over the Tapajos National Forest in Brazil is used for experimental validation. The InSAR-inverted DI estimates derived from DLR's TanDEM-X time-series data were compared with those measured from a field work over 32 quarter-hectare stands at Tapajos with relative RMSE of 30% for DI up to 0.3 and the disturbance epoch can be determined with an average accuracy of 13 days (constrained by the satellite repeat interval usually on the order of 2 weeks). As a comparison, the repeat-pass InSAR coherences from the concurrent JAXA's ALOS-2 data are shown to qualitatively correspond to the TanDEM-X results, confirming both the location and the epoch of the disturbance event. This new method is anticipated to contribute to the range of tools being developed for large-scale forest disturbance assessment and monitoring (for UN's REDD+ programme) through using spaceborne single-pass InSAR missions (e.g., DLR's TanDEM-X and in the future, TanDEM-L).
•A new InSAR approach for detecting and quantifying selective logging.•A numerical method for modeling InSAR responses to tropical selective logging.•Experimental results with spaceborne InSAR data from TanDEM-X and ALOS-2.•Selective logging disturbance index measured with RMSE of 30% over 0.25-ha stands.
•Lidar and GPS can be used to monitor logging performance.•Lidar maps of logging infrastructure coincide with ground-based GPS maps.•Lidar maps of logging disturbance reveal extensive unlogged ...areas.•Fourier methods map biomass differences within 5% of field measurements.•GPS maps of logging infrastructure are more affordable for near term monitoring.
Reduced-impact logging (RIL) is a promising management strategy for biodiversity conservation and carbon sequestration, but incentive mechanisms are hindered by inadequate monitoring methods. We mapped 937ha of logging infrastructure in a selectively harvested tropical forest to inform a scalable approach to measuring the impacts of discrete management practices (hauling, skidding, and felling). We used a lidar-derived disturbance model to map all skid trails and haul roads within 26months of the selective harvest of six blocks of dipterocarp forest in five industrial concessions in East Kalimantan, Indonesia. Lidar maps of logging impacts (220ha) agreed well with ground-based maps (total of 217ha, RMS error of 6ha or 3%), but skid trail positions agreed only 59% of the time. Due to rapid forest regeneration, total lidar-derived haul road area was 31% smaller than road area measured in the field; agreement was higher for lidar collections within a year of the harvest. Maps of carbon density generated from Fourier transforms of lidar height profiles estimated skidding and felling biomass losses to within 1–5% of ground-based measurements. Lidar-derived skidding and hauling impact zones covered only 69% of the permitted harvest area; the remaining areas showed no signs of logging disturbance, and available biophysical data did not explain their location. These results emphasize the need for more extensive mapping of logging infrastructure to capture spatial variability in skid trail density and hitherto undetected no-impact zones. While a ground-based GPS is recommended as the most affordable method for wide-scale infrastructure mapping, aerial lidar is an effective tool for remotely quantifying the extent of logging impacts in tropical forests.
We assessed predictive models (PMs) for diagnosing Pneumocystis jirovecii pneumonia (PCP) in AIDS patients seen in the emergency room (ER), aiming to guide empirical treatment decisions. Data from ...suspected PCP cases among AIDS patients were gathered prospectively at a reference hospital's ER, with diagnoses later confirmed through sputum PCR analysis. We compared clinical, laboratory, and radiological data between PCP and non-PCP groups, using the Boruta algorithm to confirm significant differences. We evaluated ten PMs tailored for various ERs resource levels to diagnose PCP. Four scenarios were created, two based on X-ray findings (diffuse interstitial infiltrate) and two on CT scans ("ground-glass"), incorporating mandatory variables: lactate dehydrogenase, O2
, C-reactive protein, respiratory rate (> 24 bpm), and dry cough. We also assessed HIV viral load and CD4 cell count. Among the 86 patients in the study, each model considered either 6 or 8 parameters, depending on the scenario. Many models performed well, with accuracy, precision, recall, and AUC scores > 0.8. Notably, nearest neighbor and naïve Bayes excelled (scores > 0.9) in specific scenarios. Surprisingly, HIV viral load and CD4 cell count did not improve model performance. In conclusion, ER-based PMs using readily available data can significantly aid PCP treatment decisions in AIDS patients.
Knowing the aboveground biomass (AGB) stock of tropical forests is one of the main requirements to guide programs for reducing emissions from deforestation and forest degradation (REDD+). Traditional ...3D products generated with digital aerial photogrammetry (DAP) have shown great potential in estimating AGB, tree density, diameter at breast height, height, and basal area in forest ecosystems. However, these traditional products explore only a small part of the structural information contained in the 3D data, thus not leveraging the full potential of the data for inventory purposes. In this study, we tested the performance of 3D products derived from DAP and a technique based on Fourier transforms of vertical profiles of vegetation to estimate AGB, tree density, diameter at breast height, height, and basal area in a secondary fragment of Atlantic Forest located in northeast Brazil. Field measurements were taken in 30 permanent plots (0.25 ha each) to estimate AGB. At the time of the inventory, we also performed a digital aerial mapping of the entire forest fragment with an unmanned aerial vehicle (UAV). Based on the 3D point clouds and the digital terrain model (DTM) obtained by DAP, vertical vegetation profiles were produced for each plot. Using traditional structure metrics and metrics derived from Fourier transforms of profiles, regression models were fit to estimate AGB, tree density, diameter at breast height, height, and basal area. The 3D DAP point clouds represented the forest canopy with a high level of detail, regardless of the vegetation density. The metrics based on the Fourier transform of profiles were selected as predictors in all models produced. The best model for AGB explained 93% (R2 = 0.93) of the biomass variation at the plot level, with an RMS error of 9.3 Mg ha−1 (22.5%). Similar results were obtained in the models fit for the tree density, diameter at breast height, height, and basal area, with R2 values above 0.90 and RMS errors of less than 18%. The use of Fourier transforms of profiles with 3D products obtained by DAP demonstrated a high potential for estimating AGB and other forest variables of interest in secondary tropical forests, highlighting the value of UAV as a low-cost tool to assist the implementation of REDD+ projects in developing countries like Brazil.
Digital aerial photogrammetry (DAP) data acquired by unmanned aerial vehicles (UAV) have been increasingly used for forest inventory and monitoring. In this study, we evaluated the potential of UAV ...photogrammetry data to detect individual trees, estimate their heights (ht), and monitor the initial silvicultural quality of a 1.5-year-old Eucalyptus sp. stand in northeastern Brazil. DAP estimates were compared with accurate tree locations obtained with real time kinematic (RTK) positioning and direct height measurements obtained in the field. In addition, we assessed the quality of a DAP-UAV digital terrain model (DTM) derived using an alternative ground classification approach and investigated its performance in the retrieval of individual tree attributes. The DTM built for the stand presented an RMSE of 0.099 m relative to the RTK measurements, showing no bias. The normalized 3D point cloud enabled the identification of over 95% of the stand trees and the estimation of their heights with an RMSE of 0.36 m (11%). However, ht was systematically underestimated, with a bias of 0.22 m (6.7%). A linear regression model, was fitted to estimate tree height from a maximum height metric derived from the point cloud reduced the RMSE by 20%. An assessment of uniformity indices calculated from both field and DAP heights showed no statistical difference. The results suggest that products derived from DAP-UAV may be used to generate accurate DTMs in young Eucalyptus sp. stands, detect individual trees, estimate ht, and determine stand uniformity with the same level of accuracy obtained in traditional forest inventories.
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