Long-term eddy-covariance measurements from FINO2 platform above the Baltic Sea

The estimation of the carbon dioxide (CO2) fluxes above the open ocean plays an important role for the determination of the global carbon cycle. A frequently used method therefore is the eddy-covariance technique, which is based on the theory of the Prandl-layer with height-constant fluxes in the atmospheric boundary layer. To test the assumption of the constant flux layer, in 2008 measurements of turbulent heat and CO2 fluxes were started within the project Surface Ocean Processes in the Anthropocene (SOPRAN) at the research platform FINO2. The FINO2 platform is situated in the South-west of the Baltic Sea, in the tri-border region between Germany, Denmark, and Sweden. In the frame of the Research project SOPRAN, the platform was equipped with additional sensors in June 2008. A combination of 3-component sonic anemometers (USA-1) and open-path infrared gas analyzers for absolute humidity (H2O) and CO2 (LICOR 7500) were installed at a 9m long boom directed southward of the platform in two heights, at 6.8 and 13.8m above sea surface. Additionally slow temperature and humidity sensors were installed at each height. The gas analyzer systems were calibrated before the installation and worked permanently without any calibration during the first measurement period of one and a half years. The comparison with the measurements of the slow sensors showed for both instruments no significant long-term drift in H2O and CO2. Drifts on smaller time scales (in the order of days) due to the contamination with sea salt, were cleaned naturally by rain. The drift of both quantities had no influence on the fluctuation, which, in contrast to the mean values, are important for the flux estimation. All data were filtered due to spikes, rain, and the influence of the mast. The data set includes the measurements of all sensors as average over 30 minutes each for one and a half years, June 2008 to December 2009, and 10 month from November 2011 to August 2012. Additionally derived quantities for 30 minutes intervals each, like the variances for the fast-sensor variables, as well as the momentum, sensible and latent heat, and CO2 flux are presented.

Export platform FDI and firm heterogeneity

This paper investigates theoretically and empirically firms' productivity ranking among traditional horizontal foreign direct investment (HFDI), pure platform FDI (PFDI), and complex platform FDI (CFDI). Using data on Japanese outward FDI, we define firms conducting HFDI or PFDI as those Japanese firms that maintain production affiliates only in the U.S. or Mexico, respectively. The firms for CFDI are defined as having production affiliates in both the U.S. and Mexico. The theoretical illustration shows that the CFDI firms should have the highest productivity when trade costs between the U.S. and Mexico are low. By carefully disentangling firms' self-selection effects from learning-by-investing effects, we find some evidence consistent with this hypothesis for a period of relatively low trade costs. Our results indicate the importance of trade costs in developing countries with neighboring markets in attracting foreign investment by highly productive multinational firms.

Export platform foreign direct investment : theory and evidence

This paper proposes a model that accounts for “export platform” FDI – a form of FDI that is common in the data but rarely discussed in the theoretical literature. Unlike the previous literature, this paper’s theory nests all the typical modes of supply, including exports, horizontal and vertical FDI, horizontal and vertical export platform FDI. The theory yields the testable hypothesis that a decrease in either inter-regional or intra-regional trade costs induces firms to choose export platform FDI. The empirical analysis provides descriptive statistics which point to large proportions of third country exports of US FDI, and an econometric analysis, whose results are in line with the model’s predictions. The last section suggests policy implications for nations seeking to attract FDI.

An Experimental Platform for large-scale research facing FI-IoT scenarios

Providing experimental facilities for the Internet of Things (IoT) world is of paramount importance to materialise the Future Internet (FI) vision. The level of maturity achieved at the networking level in Sensor and Actuator networks (SAN) justifies the increasing demand on the research community to shift IoT testbed facilities from the network to the service and information management areas. In this paper we present an Experimental Platform fulfilling these needs by: integrating heterogeneous SAN infrastructures in a homogeneous way; providing mechanisms to handle information, and facilitating the development of experimental services. It has already been used to deploy applications in three different field trials: smart metering, smart places and environmental monitoring and it will be one of the components over which the SmartSantander project, that targets a large-scale IoT experimental facility, will rely on