University of Bremen

About: University of Bremen is a education organization based out in Bremen, Germany. It is known for research contribution in the topics: Population & Context (language use). The organization has 14563 authors who have published 37279 publications receiving 970381 citations. The organization is also known as: Universität Bremen.

Long-term change in the nitrogen cycle of tropical forests.

Abstract: Deposition of reactive nitrogen (N) from human activities has large effects on temperate forests where low natural N availability limits productivity but is not known to affect tropical forests where natural N availability is often much greater. Leaf N and the ratio of N isotopes (δ15N) increased substantially in a moist forest in Panama between ~1968 and 2007, as did tree-ring δ15N in a dry forest in Thailand over the past century. A decade of fertilization of a nearby Panamanian forest with N caused similar increases in leaf N and δ15N. Therefore, our results indicate regional increases in N availability due to anthropogenic N deposition. Atmospheric nitrogen dioxide measurements and increased emissions of anthropogenic reactive N over tropical land areas suggest that these changes are widespread in tropical forests.

AEDGE: Atomic experiment for dark matter and gravity exploration in space

Abstract: We propose in this White Paper a concept for a space experiment using cold atoms to search for ultra-light dark matter, and to detect gravitational waves in the frequency range between the most sensitive ranges of LISA and the terrestrial LIGO/Virgo/KAGRA/INDIGO experiments. This interdisciplinary experiment, called Atomic Experiment for Dark Matter and Gravity Exploration (AEDGE), will also complement other planned searches for dark matter, and exploit synergies with other gravitational wave detectors. We give examples of the extended range of sensitivity to ultra-light dark matter offered by AEDGE, and how its gravitational-wave measurements could explore the assembly of super-massive black holes, first-order phase transitions in the early universe and cosmic strings. AEDGE will be based upon technologies now being developed for terrestrial experiments using cold atoms, and will benefit from the space experience obtained with, e.g., LISA and cold atom experiments in microgravity.

A method for evaluating bias in global measurements of CO 2 total columns from space

Abstract: . We describe a method of evaluating systematic errors in measurements of total column dry-air mole fractions of CO2 (XCO2) from space, and we illustrate the method by applying it to the v2.8 Atmospheric CO2 Observations from Space retrievals of the Greenhouse Gases Observing Satellite (ACOS-GOSAT) measurements over land. The approach exploits the lack of large gradients in XCO2 south of 25° S to identify large-scale offsets and other biases in the ACOS-GOSAT data with several retrieval parameters and errors in instrument calibration. We demonstrate the effectiveness of the method by comparing the ACOS-GOSAT data in the Northern Hemisphere with ground truth provided by the Total Carbon Column Observing Network (TCCON). We use the observed correlation between free-tropospheric potential temperature and XCO2 in the Northern Hemisphere to define a dynamically informed coincidence criterion between the ground-based TCCON measurements and the ACOS-GOSAT measurements. We illustrate that this approach provides larger sample sizes, hence giving a more robust comparison than one that simply uses time, latitude and longitude criteria. Our results show that the agreement with the TCCON data improves after accounting for the systematic errors, but that extrapolation to conditions found outside the region south of 25° S may be problematic (e.g., high airmasses, large surface pressure biases, M-gain, measurements made over ocean). A preliminary evaluation of the improved v2.9 ACOS-GOSAT data is also discussed.

A general best-fit method for concentration-response curves and the estimation of low-effect concentrations

Abstract: Risk assessments of toxic chemicals currently rely heavily on the use of no-observed-effect concentrations (NOECs). Due to several crucial flaws in this concept, however, discussion of replacing NOECs with statistically estimated low-effect concentrations continues. This paper describes a general best-fit method for the estimation of effects and effect concentrations by the use of a pool of 10 different sigmoidal regression functions for continuous toxicity data. Due to heterogeneous variabilities in replicated data (i.e., heteroscedasticity), the concept of generalized least squares is used for the estimation of the model parameters, whereas a nonparametric variance model based on smoothing spline functions is used to describe the heteroscedasticity. To protect the estimates against outliers, the generalized least-squares method is improved by winsorization. On the basis of statistical selection criteria, the best-fit model is chosen individually for each set of data. Furthermore, the bootstrap methodology is applied for constructing confidence intervals for the estimated effect concentrations. The best-fit method for the estimation of low-effect concentrations is validated by a simulation study, and its applicability is demonstrated with toxicity data for 64 chemicals tested in an algal and a bacterial bioassay. In comparison with common methods of concentration-response analysis, a clear improvement is achieved.

Magnification of atmospheric mercury deposition to polar regions in springtime: The link to tropospheric ozone depletion chemistry

Abstract: Mercury—in the chemical/physical forms present in the biosphere—is a persistent, toxic, bioaccumulative pollutant that is dispersed throughout the environment on a global scale, mainly via the atmosphere. It is among the “heavy metals” for which the natural biogeochemical cycle has been perturbed by a wide range of human activities, including fossil-fuel combustion and waste incineration. Results of our recent measurements of gaseous elemental mercury (GEM), as well as total particulate-phase mercury (TPM) concentrations in Arctic air, ‘total Hg’ concentrations in Arctic snow, and tropospheric BrO concentrations from an earth-orbiting-satellite platform are presented and discussed. Findings of our research, and the conclusions derived therefrom, are important for environmental protection as well as the health and well-being of aboriginal people in Arctic circumpolar nations.