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The ROMEO campaign (ROmanian Methane Emissions from Oil and gas) focused on measurements of methane (CH4) emission rates from oil and natural gas (O&G) production in Romania. The campaign took place in October 2019 and covered the southern part of Romania around the cities Bucharest, Ploiesti, Pitesti, and Craiova. This study presents emission rates calculated from mobile in situ measurement of CH4 and wind measurements using the Other Test Method 33a from U.S. Environmental Protection Agency and the Gaussian Plume Method. These methods were used to determine emission rates from 112 O&G well sites and other production-related facilities. Estimated mean CH4 emission rate with a 95% confidence interval equals 0.49 [0.35, 0.71] kg CH4 h−1 per site; 10% of all quantified sites account for 56% of the estimated emission rates. In addition, more than 1,000 O&G sites were visited for a qualitative “screening” (CH4 detection without quantification). Analysis of the screening data shows that 65% of the sites emitted methane at detectable rates. The CH4 emission rates obtained during the ROMEO campaign are comparable to the methane emission rates in study carried out in other Romanian regions.

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We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

For automotive reception of Satellite Digital Audio Radio Services (SDARS) and satellite-based Global Positioning Systems (GPS) a new satellite antenna combination is presented which shows a high efficiency for both services. The whole structure of this antenna combination requires only a small mounting volume and shows radiation patterns which are tailored to the reception of SDARS signals transmitted via Highly-Elliptical-Orbit (HEO) satellites, Geostationary Earth Orbit (GEO) satellites and terrestrial repeaters and GPS signals transmitted via Medium Earth Orbit (MEO) satellites. Simulation results and measurement results of a hardware demonstrator show the high performance of the new satellite antenna combination.