990 resultados para Passive Air Sampling
Resumo:
Nitrogen dioxide (NO$\sb2)$ levels in sixteen substandard houses located in Houston, Texas were examined. The classification of the houses as substandard was based on an assessment of structural integrity which would affect air exchange rates. In these homes, unvented gas space heaters were operated as the primary source of heat.^ The Ogawa passive sampling device was used to measure NO$\sb2$ concentrations over 24 to 48-hour periods during generally cold weather. A sampler was placed in the kitchen and bedroom of each house. The female head of household was asked to wear a monitor during area monitoring to assess her personal exposure. Outdoor levels of NO$\sb2$ were also measured.^ Mean (standard deviation) levels of kitchen, bedroom and personal exposures were 280 (125) ppb, 256 (155) ppb and 164 (102) ppb, respectively. Additional short-term ($<$24 hours) samples were measured in three houses. The mean level of NO$\sb2$ measured outdoors was 51 ppb over the course of the study.^ The measurements obtained with the Ogawa sampler were compared to those levels obtained using a reference method (chemiluminescence). Outdoor levels measured with the diffusion samplers were 48% higher.^ These results suggest that wintertime NO$\sb2$ levels within substandard houses using gas appliances for heating and cooking are extremely elevated. Further work is needed to investigate the prevalence of possible health effects associated with these exposures. ^
Resumo:
A nested case-control study design was used to investigate the relationship between radiation exposure and brain cancer risk in the United States Air Force (USAF). The cohort consisted of approximately 880,000 men with at least 1 year of service between 1970 and 1989. Two hundred and thirty cases were identified from hospital discharge records with a diagnosis of primary malignant brain tumor (International Classification of Diseases, 9th revision, code 191). Four controls were exactly matched with each case on year of age and race using incidence density sampling. Potential career summary extremely low frequency (ELF) and microwave-radiofrequency (MWRF) radiation exposures were based upon the duration in each occupation and an intensity score assigned by an expert panel. Ionizing radiation (IR) exposures were obtained from personal dosimetry records.^ Relative to the unexposed, the overall age-race adjusted odds ratio (OR) for ELF exposure was 1.39, 95 percent confidence interval (CI) 1.03-1.88. A dose-response was not evident. The same was true for MWRF, although the OR = 1.59, with 95 percent CI 1.18-2.16. Excess risk was not found for IR exposure (OR = 0.66, 45 percent CI 0.26-1.72).^ Increasing socioeconomic status (SES), as identified by military pay grade, was associated with elevated brain tumor risk (officer vs. enlisted personnel age-race adjusted OR = 2.11, 95 percent CI 1.98-3.01, and senior officers vs. all others age-race adjusted OR = 3.30, 95 percent CI 2.0-5.46). SES proved to be an important confounder of the brain tumor risk associated with ELF and MWRF exposure. For ELF, the age-race-SES adjusted OR = 1.28, 95 percent CI 0.94-1.74, and for MWRF, the age-race-SES adjusted OR = 1.39, 95 percent CI 1.01-1.90.^ These results indicate that employment in Air Force occupations with potential electromagnetic field exposures is weakly, though not significantly, associated with increased risk for brain tumors. SES appeared to be the most consistent brain tumor risk factor in the USAF cohort. Other investigators have suggested that an association between brain tumor risk and SES may arise from differential access to medical care. However, in the USAF cohort health care is universally available. This study suggests that some factor other than access to medical care must underlie the association between SES and brain tumor risk. ^
Resumo:
An investigation was undertaken to determine the chemical characterization of inhalable particulate matter in the Houston area, with special emphasis on source identification and apportionment of outdoor and indoor atmospheric aerosols using multivariate statistical analyses.^ Fine (<2.5 (mu)m) particle aerosol samples were collected by means of dichotomous samplers at two fixed site (Clear Lake and Sunnyside) ambient monitoring stations and one mobile monitoring van in the Houston area during June-October 1981 as part of the Houston Asthma Study. The mobile van allowed particulate sampling to take place both inside and outside of twelve homes.^ The samples collected for 12-h sampling on a 7 AM-7 PM and 7 PM-7 AM (CDT) schedule were analyzed for mass, trace elements, and two anions. Mass was determined gravimetrically. An energy-dispersive X-ray fluorescence (XRF) spectrometer was used for determination of elemental composition. Ion chromatography (IC) was used to determine sulfate and nitrate.^ Average chemical compositions of fine aerosol at each site were presented. Sulfate was found to be the largest single component in the fine fraction mass, comprising approximately 30% of the fine mass outdoors and 12% indoors, respectively.^ Principal components analysis (PCA) was applied to identify sources of aerosols and to assess the role of meteorological factors on the variation in particulate samples. The results suggested that meteorological parameters were not associated with sources of aerosol samples collected at these Houston sites.^ Source factor contributions to fine mass were calculated using a combination of PCA and stepwise multivariate regression analysis. It was found that much of the total fine mass was apparently contributed by sulfate-related aerosols. The average contributions to the fine mass coming from the sulfate-related aerosols were 56% of the Houston outdoor ambient fine particulate matter and 26% of the indoor fine particulate matter.^ Characterization of indoor aerosol in residential environments was compared with the results for outdoor aerosols. It was suggested that much of the indoor aerosol may be due to outdoor sources, but there may be important contributions from common indoor sources in the home environment such as smoking and gas cooking. ^
Resumo:
Objective: To assess the indoor environment of two different types of dental practices regarding VOCs, PM2.5, and ultrafine particulate concentrations and examine the relationship between specific dental activities and contaminant levels. Method: The indoor environments of two selected dental settings (private practice and community health center) will were assessed in regards to VOCs, PM 2.5, and ultrafine particulate concentrations, as well as other indoor air quality parameters (CO2, CO, temperature, and relative humidity). The sampling duration was four working days for each dental practice. Continuous monitoring and integrated sampling methods were used and number of occupants, frequency, type, and duration of dental procedures or activities recorded. Measurements were compared to indoor air quality standards and guidelines. Results: The private practice had higher CO2, CO, and most VOC concentrations than the community health center, but the community health center had higher PM2.5 and ultrafine PM concentrations. Concentrations of p-dichlorobenzene and PM2.5 exceeded some guidelines. Outdoor concentrations greatly influenced the indoor concentration. There were no significant differences in contaminant levels between the operatory and general area. Indoor concentrations during the working period were not always consistently higher than during the nonworking period. Peaks in particulate matter concentration occurred during root canal and composite procedures.^
Resumo:
There is a long tradition of river monitoring using macroinvertebrate communities to assess environmental quality in Europe. A promising alternative is the use of species life-history traits. Both methods, however, have relied on the time-consuming identification of taxa. River biotopes, 1-100 m**2 'habitats' with associated species assemblages, have long been seen as a useful and meaningful way of linking the ecology of macroinvertebrates and river hydro-morphology and can be used to assess hydro-morphological degradation in rivers. Taxonomic differences, however, between different rivers had prevented a general test of this concept until now. The species trait approach may overcome this obstacle across broad geographical areas, using biotopes as the hydro-morphological units which have characteristic species trait assemblages. We collected macroinvertebrate data from 512 discrete patches, comprising 13 river biotopes, from seven rivers in England and Wales. The aim was to test whether river biotopes were better predictors of macroinvertebrate trait profiles than taxonomic composition (genera, families, orders) in rivers, independently of the phylogenetic effects and catchment scale characteristics (i.e. hydrology, geography and land cover). We also tested whether species richness and diversity were better related to biotopes than to rivers. River biotopes explained 40% of the variance in macroinvertebrate trait profiles across the rivers, largely independently of catchment characteristics. There was a strong phylogenetic signature, however. River biotopes were about 50% better at predicting macroinvertebrate trait profiles than taxonomic composition across rivers, no matter which taxonomic resolution was used. River biotopes were better than river identity at explaining the variability in taxonomic richness and diversity (40% and <=10%, respectively). Detailed trait-biotope associations agreed with independent a priori predictions relating trait categories to near river bed flows. Hence, species traits provided a much needed mechanistic understanding and predictive ability across a broad geographical area. We show that integration of the multiple biological trait approach with river biotopes at the interface between ecology and hydro-morphology provides a wealth of new information and potential applications for river science and management.
Resumo:
The Arctic sea-ice environment has been undergoing dramatic changes in the past decades; to which extent this will affect the deposition, fate, and effects of chemical contaminants remains virtually unknown. Here, we report the first study on the distribution and transport of mercury (Hg) across the ocean-sea-ice-atmosphere interface in the Southern Beaufort Sea of the Arctic Ocean. Despite being sampled at different sites under various atmospheric and snow cover conditions, Hg concentrations in first-year ice cores were generally low and varied within a remarkably narrow range (0.5-4 ng/L), with the highest concentration always in the surface granular ice layer which is characterized by enriched particle and brine pocket concentration. Atmospheric Hg depletion events appeared not to be an important factor in determining Hg concentrations in sea ice except for frost flowers and in the melt season when snowpack Hg leaches into the sea ice. The multiyear ice core showed a unique cyclic feature in the Hg profile with multiple peaks potentially corresponding to each ice growing/melting season. The highest Hg concentrations (up to 70 ng/L) were found in sea-ice brine and decrease as the melt season progresses. As brine is the primary habitat for microbial communities responsible for sustaining the food web in the Arctic Ocean, the high and seasonally changing Hg concentrations in brine and its potential transformation may have a major impact on Hg uptake in Arctic marine ecosystems under a changing climate.
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The algorithms designed to estimate snow water equivalent (SWE) using passive microwave measurements falter in lake-rich high-latitude environments due to the emission properties of ice covered lakes on low frequency measurements. Microwave emission models have been used to simulate brightness temperatures (Tbs) for snowpack characteristics in terrestrial environments but cannot be applied to snow on lakes because of the differing subsurface emissivities and scattering matrices present in ice. This paper examines the performance of a modified version of the Helsinki University of Technology (HUT) snow emission model that incorporates microwave emission from lake ice and sub-ice water. Inputs to the HUT model include measurements collected over brackish and freshwater lakes north of Inuvik, Northwest Territories, Canada in April 2008, consisting of snowpack (depth, density, and snow water equivalent) and lake ice (thickness and ice type). Coincident airborne radiometer measurements at a resolution of 80x100 m were used as ground-truth to evaluate the simulations. The results indicate that subsurface media are simulated best when utilizing a modeled effective grain size and a 1 mm RMS surface roughness at the ice/water interface compared to using measured grain size and a flat Fresnel reflective surface as input. Simulations at 37 GHz (vertical polarization) produce the best results compared to airborne Tbs, with a Root Mean Square Error (RMSE) of 6.2 K and 7.9 K, as well as Mean Bias Errors (MBEs) of -8.4 K and -8.8 K for brackish and freshwater sites respectively. Freshwater simulations at 6.9 and 19 GHz H exhibited low RMSE (10.53 and 6.15 K respectively) and MBE (-5.37 and 8.36 K respectively) but did not accurately simulate Tb variability (R= -0.15 and 0.01 respectively). Over brackish water, 6.9 GHz simulations had poor agreement with airborne Tbs, while 19 GHz V exhibited a low RMSE (6.15 K), MBE (-4.52 K) and improved relative agreement to airborne measurements (R = 0.47). Salinity considerations reduced 6.9 GHz errors substantially, with a drop in RMSE from 51.48 K and 57.18 K for H and V polarizations respectively, to 26.2 K and 31.6 K, although Tb variability was not well simulated. With best results at 37 GHz, HUT simulations exhibit the potential to track Tb evolution, and therefore SWE through the winter season.
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The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set provides continuous measurements of partial pressure of carbon dioxide (pCO2), using a ProOceanus CO2-Pro instrument mounted on the flowthrough system. This automatic sensor is fitted with an equilibrator made of gas permeable silicone membrane and an internal detection loop with a non-dispersive infrared detector of PPSystems SBA-4 CO2 analyzer. A zero-CO2 baseline is provided for the subsequent measurements circulating the internal gas through a CO2 absorption chamber containing soda lime or Ascarite. The frequency of this automatic zero point calibration was set to be 24 hours. All data recorded during zeroing processes were discarded with the 15-minute data after each calibration. The output of CO2-Pro is the mole fraction of CO2 in the measured water and the pCO2 is obtained using the measured total pressure of the internal wet gas. The fugacity of CO2 (fCO2) in the surface seawater, whose difference with the atmospheric CO2 fugacity is proportional to the air-sea CO2 fluxes, is obtained by correcting the pCO2 for non-ideal CO2 gas concentration according to Weiss (1974). The fCO2 computed using CO2-Pro measurements was corrected to the sea surface condition by considering the temperature effect on fCO2 (Takahashi et al., 1993). The surface seawater observations that were initially estimated with a 15 seconds frequency were averaged every 5-min cycle. The performance of CO2-Pro was adjusted by comparing the sensor outputs against the thermodynamic carbonate calculation of pCO2 using the carbonic system constants of Millero et al. (2006) from the determinations of total inorganic carbon (CT ) and total alkalinity (AT ) in discrete samples collected at sea surface. AT was determined using an automated open cell potentiometric titration (Haraldsson et al. 1997). CT was determined with an automated coulometric titration (Johnson et al. 1985; 1987), using the MIDSOMMA system (Mintrop, 2005). fCO2 data are flagged according to the WOCE guidelines following Pierrot et al. (2009) identifying recommended values and questionable measurements giving additional information about the reasons of the questionability.
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Remote sensing instruments are key players to map land surface temperature (LST) at large temporal and spatial scales. In this paper, we present how we combine passive microwave and thermal infrared data to estimate LST during summer snow-free periods over northern high latitudes. The methodology is based on the SSM/I-SSMIS 37 GHz measurements at both vertical and horizontal polarizations on a 25 km × 25 km grid size. LST is retrieved from brightness temperatures introducing an empirical linear relationship between emissivities at both polarizations as described in Royer and Poirier (2010). This relationship is calibrated at pixel scale, using cloud-free independent LST data from MODIS instruments. The SSM/I-SSMIS and MODIS data are synchronized by fitting a diurnal cycle model built on skin temperature reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). The resulting temperature dataset is provided at 25 km scale and at an hourly time step during the ten-year analysis period (2000-2011). This new product was locally evaluated at five experimental sites of the EU-PAGE21 project against air temperature measurements and meteorological model reanalysis, and compared to the MODIS LST product at both local and circumpolar scale. The results giving a mean RMSE of the order of 2.2 K demonstrate the usefulness of the microwave product, which is unaffected by clouds as opposed to thermal infrared products and offers a better resolution compared to model reanalysis.