Found 10076 publications. Showing page 312 of 404:
<p><i>Background</i>: Human biomonitoring studies have demonstrated decreasing concentrations of many persistent organic pollutants (POPs) in years after emission peaks.</p> <p><i>Objectives</i>: To describe time trends of POPs in blood using four cross-sectional samples of 30 year olds from Tromsø, Norway across 1986–2007, and to compare the measured concentrations of polychlorinated biphenyl 153 (PCB-153) to model-estimated values. A second objective was to compare the repeated cross-sectional time trends with those observed in our previous longitudinal study using repeated individual measurements in older men from the same surveys.</p> <p><i>Methods</i>: Serum from 45 persons aged 30 years in each of the following years: 1986, 1994, 2001, and 2007 was analyzed for 14 POPs. Further, predicted concentrations of PCB-153 in each sampling year were derived using the emission-based CoZMoMAN model.</p> <p><i>Results</i>: The median decreases in summed serum POP concentrations (lipid-adjusted) in 1994, 2001, and 2007 relative to 1986 were − 71%, − 81%, and − 86% for women and − 65%, − 77%, and − 87% for men, respectively. The overall time trend in predicted PCB-153 concentrations demonstrated agreement with the observed trend although model predictions were higher than the measured concentrations at all time points. Compared to our previous longitudinal study of repeated individual measurements in older men, similar although more prominent declines were observed in the younger cross-sectional samples.</p> <p><i>Discussion</i>: Observed declines in serum concentrations from 1986 to 2007 were substantial for legacy POPs in men and women at reproductive ages in Northern Norway and are generally consistent with previous longitudinal biomonitoring efforts in the study population. The measured concentrations and observed declines likely reflect a combination of recent and historic exposures. Small differences in time trends observed between the studies could be attributed to different study designs (i.e. the chosen age group or sex and cross-sectional versus repeated individual measurement sampling).</p>
2019
2019
2019
2019
2019
2019
2019
2019
2019
A number of studies have shown that assimilation of satellite derived soil moisture using the ensemble Kalman Filter (EnKF) can improve soil moisture estimates, particularly for the surface zone. However, the EnKF is computationally expensive since an ensemble of model integrations have to be propagated forward in time. Here, assimilating satellite soil moisture data from the Soil Moisture Active Passive (SMAP) mission, we compare the EnKF with the computationally cheaper ensemble Optimal Interpolation (EnOI) method over the contiguous United States (CONUS). The background error–covariance in the EnOI is sampled in two ways: (i) by using the stochastic spread from an ensemble open-loop run, and (ii) sampling from the model spinup climatology. Our results indicate that the EnKF is only marginally superior to one version of the EnOI. Furthermore, the assimilation of SMAP data using the EnKF and EnOI is found to improve the surface zone correlation with in situ observations at a 95% significance level. The EnKF assimilation of SMAP data is also found to improve root-zone correlation with independent in situ data at the same significance level; however this improvement is dependent on which in situ network we are validating against. We evaluate how the quality of the atmospheric forcing affects the analysis results by prescribing the land surface data assimilation system with either observation corrected or model derived precipitation. Surface zone correlation skill increases for the analysis using both the corrected and model derived precipitation, but only the latter shows an improvement at the 95% significance level. The study also suggests that assimilation of satellite derived surface soil moisture using the EnOI can correct random errors in the atmospheric forcing and give an analysed surface soil moisture close to that of an open-loop run using observation derived precipitation. Importantly, this shows that estimates of soil moisture could be improved using a combination of assimilating SMAP using the computationally cheap EnOI while using model derived precipitation as forcing. Finally, we assimilate three different Level-2 satellite derived soil moisture products from the European Space Agency Climate Change Initiative (ESA CCI), SMAP and SMOS (Soil Moisture and Ocean Salinity) using the EnOI, and then compare the relative performance of the three resulting analyses against in situ soil moisture observations. In this comparison, we find that all three analyses offer improvements over an open-loop run when comparing to in situ observations. The assimilation of SMAP data is found to perform marginally better than the assimilation of SMOS data, while assimilation of the ESA CCI data shows the smallest improvement of the three analysis products.
2019
2019
2019
2019
Spredningsberegninger for ammoniakkutslipp. Leangen idrettsanlegg i Trondheim.
NILU har gjennomført spredningsberegninger for utslipp av ammoniakk (NH3) ved Leangen idrettsanlegg I Trondheim. Beregningene er utført for å undersøke hvilke konsentrasjoner av ammoniakk som kan forekomme i bakkenivå for ulike høyder av avkast for ammoniakkdamp. Beregningene viser at avkastet bør være 21 m over bakkenivå for å overholde grenseverdi for arbeidsatmosfære. Så lenge utslippet pågår vil det forekomme timemiddelkonsentrasjoner av ammoniakk over luktegrensen nedvinds for utslippet.
NILU
2019