Search

Intensive coal mining activities are in the Upper Silesian Coal Basin (USCB) in southern Poland, resulting in large amounts of methane (CH4) emissions. Annual CH4 emission reached to 448 kt according to the European Pollutant Release and Transfer Register (E-PRTR, 2017). As a CH4 emission hot spot in Europe, it is of importance to investigate its emission sources and accurate emission estimates. In this study, we use satellite-based column-averaged dry-air molar fraction observations of CH4 (XCH4) from the TROPOspheric Monitoring Instrument (TROPOMI) and tropospheric XCH4 (TXCH4) from the Infrared Atmospheric Sounding Interferometer (IASI), together with the high-resolution model forecast XCH4 and TXCH4 from the Copernicus Atmosphere Monitoring Service (CAMS) to estimate the CH4 emission rate averaged over three years in the USCB region (49.3°–50.8° N and 18°–20° E). Using the CAMS inventory as the a priori knowledge of the sources, together with ERA5 wind at 330 m, the wind-assigned XCH4 anomalies for two opposite wind directions are calculated, which yields an estimated CH4 emission of 9.6E26 ± 1.4E25 molec./s for CAMS XCH4 and 9.1E26 ± 1.2E25 molec./s for CAMS TXCH4. These values are very close to the total emission of the CAMS inventory (9.7E26 molec./s). Very good agreements between CAMS and the wind-assigned model results (R2 = 0.89 for XCH4 and TXCH4) indicate that our wind-assigned method is quite robust. The similar estimates of XCH4 and TXCH4 also imply that for a strong source, the dynamically induced variations of the CH4 mixing ratio in the upper troposphere and lower stratosphere region is of secondary importance. This wind-assigned method is further applied to the TROPOMI XCH4 and TROPOMI+IASI TXCH4 with using the Carbon dioxide and Methane (CoMet) inventory performed in 2018. The calculated averaged total CH4 emission over the USCB region is about 5.7E26 ± 4.9E24 molec./s for TROPOMI XCH4 and 5.2E26 ± 2.2E25 molec./s for TROPOMI+IASI TXCH4. These results are very close and thus in agreement to the emissions given in the E-PRTR inventory (5.33E26 molec./s) and the CoMet inventory (6.6E26 molec./s). Since the wind speed is increasing with altitude, sensitivity tests show that higher CH4 emission strengths are yielded with increasing altitude and vice versa. About 23 % lower and 13 % higher estimates are obtained when using lower wind information at 10 m and higher wind information at 500 m instead of 330 m, respectively. When using different wind coverage and different wind segmentation, an uncertainty of 4.2 % and −2.1% is obtained, respectively. These results suggest that our wind-assigned method is quite robust and might also serve as a simple method to estimate CH4 or CO2 emissions for other regions.

Intensive coal mining activities in the Upper Silesian Coal Basin (USCB) in southern Poland are resulting in large amounts of methane (CH4) emissions. Annual CH4 emissions reached 448 kt according to the European Pollutant Release and Transfer Register (E-PRTR, 2017). As a CH4 emission hotspot in Europe, it is of importance to investigate its emission sources and make accurate emission estimates. In this study, we use satellite-based total column-averaged dry-air mole fraction of CH4 (XCH4) from the TROPOspheric Monitoring Instrument (TROPOMI) and tropospheric XCH4 (TXCH4) from the Infrared Atmospheric Sounding Interferometer (IASI). In addition, the high-resolution model forecasts, XCH4 and TXCH4, from the Copernicus Atmosphere Monitoring Service (CAMS) are used to estimate the CH4 emission rate averaged over 3 years (November 2017–December 2020) in the USCB region (49.3–50.8∘ N and 18–20∘ E). The wind-assigned anomaly method is first validated using the CAMS forecast data (XCH4 and TXCH4), showing a good agreement with the CAMS GLOBal ANThropogenic emission (CAMS-GLOB-ANT) inventory. It indicates that the wind-assigned method works well. This wind-assigned method is further applied to the TROPOMI XCH4 and TROPOMI + IASI TXCH4 by using the Carbon dioxide and Methane (CoMet) inventory derived for the year 2018. The calculated averaged total CH4 emissions over the USCB region is about 496 kt yr−1 (5.9×1026 molec. s−1) for TROPOMI XCH4 and 437 kt yr−1 (5.2×1026 molec. s−1) for TROPOMI + IASI TXCH4. These values are very close to the ones given in the E-PRTR inventory (448 kt yr−1) and the ones in the CoMet inventory (555 kt yr−1), and are thus in agreement with these inventories. The similar estimates of XCH4 and TXCH4 also imply that for a strong source, the dynamically induced variations of the CH4 mixing ratio in the upper troposphere and lower stratosphere region are of secondary importance. Uncertainties from different error sources (background removal and noise in the data, vertical wind shear, wind field segmentation, and angle of the emission cone) are approximately 14.8 % for TROPOMI XCH4 and 11.4 % for TROPOMI + IASI TXCH4. These results suggest that our wind-assigned method is quite robust and might also serve as a simple method to estimate CH4 or CO2 emissions for other regions.

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from three-year (April 2018 – March 2021) TROPOMI observations by combining a wind-assigned anomaly approach and a Machine Learning (ML) method, the so-called Gradient Descent. This combined approach is firstly applied to the Saudi Arabian capital city Riyadh, as a test site, and yields a total emission rate of 1.04×1026 molec./s. The ML-trained anomalies fit very well with the wind-assigned anomalies with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites where the cement plant and power plants are located and over areas along the highways. Using the same approach, an emission rate of 1.80×1025 molec./s is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable to the CAMS inventory. We also acknowledge the project of Joint R&D and Talents Program funded by the Qingdao Sino-German Institute of Intelligent Technologies (kh0100020213319) and the project of Transnational Interoperability Rules and Solution Patterns in Collaborative Production Networks based on IDS and GAIA-X funded by Ministry of Science and Technology, PRC (SQ2021YFE010470).

Taking advantage of research results about cooperative control of flow field and temperature field, the cooperative of velocity field and pressure field were further investigated by setting up indispensable parameters of heat transfer medium in refrigerated road transport carriage, according with start points of energy conservation synergistic equation and turbulent kinetic energy equation. Considering temperature distribution homogeneity as evaluation objective, the simulation distribution condition of three fields in longitudinal cross sections was qualitatively analyzed and experimentally verified. The heat transfer and pressure drop performance were fulfilled using numerical simulation analysis and comparison method for inlet orifice with three different shapes as circle holes, elliptic or regular hexagon. The test data of inside temperature in refrigerated transport carriage in fully loaded process showed that the highest temperature in cross sections with width direction dropped from 2.53? to 1.27?, and the standard deviation amplitude of temperature values dropped from 0.642? to 0.332?, respectively. The results also demonstrated that the flow resistance of elliptic air inlet orifice was smaller than other two shapes, and the consumption power of refrigeration motor-pump was fewer. The temperature distribution was more stable and homogeneity, and velocity field, temperature gradient field and pressure gradient field had favorable harmonious degree.

In today's dynamic market numerous dynamic influencing factors have seriously aggravates the difficulties of inventory planning of the complex distribution networks. This paper proposes a simulation-based hybrid approach for the optimization of the inventory policies in complex distribution networks. The initial multi-echelon inventory policies are handed over to a simulation model, which is capable of modelling complexity and uncertainties of the distribution network and simulating them under respective scenarios. Through comprehensively analysing the KPls (logistic service level and logistic costs) of this set of multi-echelon inventory policies, their levels of robustness can be clearly ascertained. Based on the simulation results, a metaheuristic-based optimizer regenerates improved multi-echelon inventory policies, which are once again comprehensively and precisely evluated through simulation. This closed feedback loop forms a simulation optimization pocess that enables autonomous evolution of multiBLechelon inventory policies of complex distribution networks. Since the simulation results can truly reflect the performance of certain inventory policies in real market environment, the new Simulation-Based Hybrid Approach is quite useful for decision making process.

Evaluating indicator for temperature distributions homogeneity was developed through optimization using orthogonal experiment. The influences of rotation speed of air refrigerating machine fan, porosity of flow equalization board and vertical space between frames on temperature distribution were analyzed. The simulation results show that the higher the fan rotation speed is, the better the temperature distribution homogeneity is, although the highest temperature in carriage is basically unchanged; the smaller the porosity is, the better temperature distribution homogeneity is; and the highest temperature in carriage is lowest when the porosity is 0.1; the smaller the frame vertical spacing is, the lower the highest temperature in carriage is and the better temperature distributions homogeneity is. For the "peak area" in temperature distribution, the carriage structure was new designed based on field-coordination principle and the temperature distributions homogeneity can be controlled by adjusting the gas curtain fan's direction in right air-returning outlet.

In this thesis an approach for the configuration of global networks is developed, to face new challenges posed by Industrie 4.0 and an increasing globalization. Industrie 4.0 leads to higher autonomy and self-organization of single supply chain processes. Globalization causes an increasing fragmentation und worldwide scattering of supply chain units. Until now, decisions for configuration are often enforced by strategic directions on a network level. However, the arrangement of the network structure takes place on a more and more detailed planning level with individual goals. Global network goals and consequences on other supply chain units are neglected. To face these challenges, a new approach is developed to enable a configuration on a more detailed planning level considering global goals on a network level. Structural decisions are made on a detailed level with regard to their impacts and contribution to global network goals. This requires consistent structural decisions between nework-, site- and process-level, which are ensured by an integrative top-down-bottom-up approach. Furthermore, the cause-and-effects-relationships between global network goals and single location factors as well as influencing factors are defined to achieve an objective and comprehensible identification of the relevant factors and their contribution to global goals. Based on that, a goal-oriented adjustment of these factors can be made by selecting effective structural measures. Altogether, the subjectiveness of structural decisions can be reduced. To consider interdependencies between supply chain units and network effects, the structural decisions in this approach are made on a holistic level considering the impacts on the complete network. Therefore, all network partners and corresponding processes along the order flow, from supplier to end customer, are considered in structural decisions. The approach is based on a continuous decision making process, so that relevant changes are detected in advance and structural adjustments can be made proactively. The development of the single steps of the approach is oriented towards an implementation in a logistics assistance system, which supports the user during the complete decision process.