Found 2533 publications. Showing page 70 of 254:
Modeling the Time-Variant Dietary Exposure of PCBs in China over the Period 1930 to 2100
This study aimed for the first time to reconstruct historical exposure profiles for PCBs to the Chinese population, by examining the combined effect of changing temporal emissions and dietary transition. A long-term (1930–2100) dynamic simulation of human exposure using realistic emission scenarios, including primary emissions, unintentional emissions, and emissions from e-waste, combined with dietary transition trends was conducted by a multimedia fate model (BETR-Global) linked to a bioaccumulation model (ACC-HUMAN). The model predicted an approximate 30-year delay of peak body burden for PCB-153 in a 30-year-old Chinese female, compared to their European counterpart. This was mainly attributed to a combination of change in diet and divergent emission patterns in China. A fish-based diet was predicted to result in up to 8 times higher body burden than a vegetable-based diet (2010–2100). During the production period, a worst-case scenario assuming only consumption of imported food from a region with more extensive production and usage of PCBs would result in up to 4 times higher body burden compared to consumption of only locally produced food. However, such differences gradually diminished after cessation of production. Therefore, emission reductions in China alone may not be sufficient to protect human health from PCB-like chemicals, particularly during the period of mass production. The results from this study illustrate that human exposure is also likely to be dictated by inflows of PCBs via the environment, waste, and food.
2018
2018
Influence of solar wind energy flux on the interannual variability of ENSO in the subsequent year
Science Press
2018
2018
Extreme winter events that damage vegetation are considered an important climatic cause of arctic browning—a reversal of the greening trend of the region—and possibly reduce the carbon uptake of northern ecosystems. Confirmation of a reduction in CO2 uptake due to winter damage, however, remains elusive due to a lack of flux measurements from affected ecosystems. In this study, we report eddy covariance fluxes of CO2 from a peatland in northern Norway and show that vegetation CO2 uptake was delayed and reduced in the summer of 2014 following an extreme winter event earlier that year. Strong frost in the absence of a protective snow cover—its combined intensity unprecedented in the local climate record—caused severe dieback of the dwarf shrub species Calluna vulgaris and Empetrum nigrum. Similar vegetation damage was reported at the time along ~1000 km of coastal Norway, showing the widespread impact of this event. Our results indicate that gross primary production (GPP) exhibited a delayed response to temperature following snowmelt. From snowmelt up to the peak of summer, this reduced carbon uptake by 14 (0–24) g C m−2 (~12% of GPP in that period)—similar to the effect of interannual variations in summer weather. Concurrently, remotely-sensed NDVI dropped to the lowest level in more than a decade. However, bulk photosynthesis was eventually stimulated by the warm and sunny summer, raising total GPP. Species other than the vulnerable shrubs were probably resilient to the extreme winter event. The warm summer also increased ecosystem respiration, which limited net carbon uptake. This study shows that damage from a single extreme winter event can have an ecosystem-wide impact on CO2 uptake, and highlights the importance of including winter-induced shrub damage in terrestrial ecosystem models to accurately predict trends in vegetation productivity and carbon sequestration in the Arctic and sub-Arctic.
2018
2018
Atmospheric DMS in the Arctic Ocean and Its Relation to Phytoplankton Biomass
American Geophysical Union (AGU)
2018
Understanding the bioaccumulation mechanisms of per- and polyfluoroalkyl substances (PFASs) across different chain-lengths, isomers and functional groups represents a monumental scientific challenge with implications for chemical regulation. Here, we investigate how the differential tissue distribution and bioaccumulation behavior of 25 PFASs in crucian carp from two field sites impacted by point sources can provide information about the processes governing uptake, distribution and elimination of PFASs. Median tissue/blood ratios (TBRs) were consistently <1 for all PFASs and tissues except bile which displayed a distinct distribution pattern and enrichment of several perfluoroalkyl sulfonic acids. Transformation of concentration data into relative body burdens (RBBs) demonstrated that blood, gonads, and muscle together accounted for >90% of the amount of PFASs in the organism. Principal component analyses of TBRs and RBBs showed that the functional group was a relatively more important predictor of internal distribution than chain-length for PFASs. Whole body bioaccumulation factors (BAFs) for short-chain PFASs deviated from the positive relationship with hydrophobicity observed for longer-chain homologues. Overall, our results suggest that TBR, RBB, and BAF patterns were most consistent with protein binding mechanisms although partitioning to phospholipids may contribute to the accumulation of long-chain PFASs in specific tissues.
2018
2018
Comparison of dust-layer heights from active and passive satellite sensors
Aerosol-layer height is essential for understanding the impact of aerosols on the climate system. As part of the European Space Agency Aerosol_cci project, aerosol-layer height as derived from passive thermal and solar satellite sensors measurements have been compared with aerosol-layer heights estimated from CALIOP measurements. The Aerosol_cci project targeted dust-type aerosol for this study. This ensures relatively unambiguous aerosol identification by the CALIOP processing chain. Dust-layer height was estimated from thermal IASI measurements using four different algorithms (from BIRA-IASB, DLR, LMD, LISA) and from solar GOME-2 (KNMI) and SCIAMACHY (IUP) measurements. Due to differences in overpass time of the various satellites, a trajectory model was used to move the CALIOP-derived dust heights in space and time to the IASI, GOME-2 and SCIAMACHY dust height pixels. It is not possible to construct a unique dust-layer height from the CALIOP data. Thus two CALIOP-derived layer heights were used: the cumulative extinction height defined as the height where the CALIOP extinction column is half of the total extinction column, and the geometric mean height, which is defined as the geometrical mean of the top and bottom heights of the dust layer. In statistical average over all IASI data there is a general tendency to a positive bias of 0.5–0.8 km against CALIOP extinction-weighted height for three of the four algorithms assessed, while the fourth algorithm has almost no bias. When comparing geometric mean height there is a shift of −0.5 km for all algorithms (getting close to zero for the three algorithms and turning negative for the fourth). The standard deviation of all algorithms is quite similar and ranges between 1.0 and 1.3 km. When looking at different conditions (day, night, land, ocean), there is more detail in variabilities (e.g. all algorithms overestimate more at night than during the day). For the solar sensors it is found that on average SCIAMACHY data are lower by −1.097 km (−0.961 km) compared to the CALIOP geometric mean (cumulative extinction) height, and GOME-2 data are lower by −1.393 km (−0.818 km).
2018