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The transition from coal to more sustainable energy sources represents a critical shift for economies reliant on coal production. To investigate the intricate processes involved in such a transition, the use of powerful analytical tools is essential. This study assesses the impact of the delignification process on GDP growth over a 20-year horizon (2015–2035) in the Region of Western Macedonia, Greece, using the Vensim PLE Plus 9.0.1 software, a robust tool for system dynamics modeling. By developing a dynamic model that captures the key variables and feedback loops associated with coal transition, this research examines economic, social, and investment variables, emphasizing their causal relationships. The study integrates societal, economic, and educational impacts on production transition, addressing issues such as unemployment, financial support, and investments in human resources and R&D. Additionally, it considers the influence of climate change on GDP. The model highlights population dynamics, economic development, and education as critical factors. Scenarios explore the impact of increased funding on education, research, and financial aid efficiency, providing insights into enhancing GDP in decarbonizing regions. The study reveals that increased investment in education and human capital leads to slight improvements in local GDP, though the effects are not immediate. Enhanced efficiency in government and European spending significantly boosts local GDP by creating strong value chains and local economies of scale. It is found that the increase in financial support to the regions in transition is of the utmost importance and has a multiplicative nature, something that should encourage the European Union to increase its financial support tools. The model's simulations align closely with historical GDP data, validating its accuracy. The contributions of the present work offer valuable insights to policymakers and stakeholders engaged in the transition processes. [ABSTRACT FROM AUTHOR]

Every year, large quantities of dust are transported from North Africa to the Americas, Europe, and West Asia. The purpose of this study is to analyze four intense and pervasive dust storms that entered the Middle East from Northern Africa. Satellite products, ground-based remote sensing measurements, reanalysis data, and the outputs of the Aire Limitée Adaptation dynamique Développement InterNational-Dust (ALADIN-Dust) and the ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON-ART) forecasting models were synergized. The dust storms originated from different source regions located in the north, northeastern, and central parts of the Sahara Desert. The transport height of the main dust plumes was about 3–5 km, triggered by the westerly zonal winds. The presence of a closed low over the Eastern Mediterranean and the penetration of a deep trough into North Africa at 500 hPa were the main synoptic circulation patterns favoring long-range dust transport during the four dust events. A comparison of aerosol optical depth (AOD) outputs from the two models with satellite data revealed that although both models forecasted dust transport from Africa to the Middle East, they considerably underestimated the AOD values, especially near the dust sources. The ICON-ART model performed slightly better than ALADIN in forecasting these dust storms, and for longer forecasting leading time, although the performance of both models decreased, the superiority of the ICON-ART model became more apparent. [ABSTRACT FROM AUTHOR]

Dust storms are one of the major environmental hazards affecting the Middle East countries, and largely originate in vast deserts and narrow dried lake beds. This study analyzes the inter-annual variation in dust weather conditions from 2000 to 2020 using data obtained from ten meteorological stations located around dried (completely or partly) lakes in Northwest (Urmia Lake) and South (Bakhtegan Lake) Iran. Since the wind regime is one of the most important factors controlling dust emissions in the dust source areas, wind speed simulations from the Weather Research and Forecasting (WRF) Model for 134,113 grid points covering the Middle East area, with a resolution of 5 km, were analyzed and compared with wind measurements at the stations around Urmia and Bakhtegan Lakes from 2005 to 2015. The analysis shows that the annual number of dust days was highly variable, presenting a significant increase at the stations around Urmia Lake during 2008–2011 and at the stations around Bakhtegan Lake in 2007–2012. Eleven years of WRF simulations of the mean diurnal wind patterns revealed that the highest 10 m wind speed occurred mostly around the local noon (12 to 15 UTC), generally coinciding with the majority of the reported dust codes within this time frame, as a result of the association between wind speed and dust emissions (dust weather conditions) around these lake basins. Consequently, accurate wind simulation has high importance for unbiased numerical prediction and forecasting of dust conditions. The comparison between the measured mean monthly 10 m wind speed and WRF-simulated 10 m wind speed revealed that the model overestimated wind data in all the stations around the Bakhtegan Lake but performed better at reconstructing the wind speeds at stations around Urmia Lake. Furthermore, notable differences were observed between measured and simulated wind directions, thus leading to uncertainties in the simulations of the dust-plume transport. [ABSTRACT FROM AUTHOR]

WRF is used to simulate eight extreme precipitation events that occurred over the regions of Schleswig–Holstein and Baden–Wurttemberg in Germany. The events were chosen from the German Weather Service (DWD) catalog and exceeded the DWD's warning level 3 (i.e., rainfall > 40 mm/h). A two-way nesting approach is used with 9 and 3 km spatial resolutions. Initial and boundary conditions are obtained from the ERA5 dataset at 0.25° × 0.25°. To model each event, thirty different parameterization configurations were used, accounting for all possible combinations of five microphysics (MP), three cumulus (CU), and two planetary boundary layer (PBL) parameterization methods, yielding a total of 240 simulations. TOPSIS multicriteria analysis technique is employed to determine the performance skill of each setup and rank them, using six categorical and five statistical metrics. Resolution increase from 9 to 3 km did not improve forecasting accuracy temporally or in intensity. According to TOPSIS ranking, when treating each event individually, the ideal parameterizations combination is spatiotemporally dependent, with certain members ranking higher. When all events are considered, the Morrison double-moment MP–Grell–Freitas CU–YSU PBL combination works best with a frequency of occurrence in the top five performing scenarios of 30%, 47.5%, and 57.5% respectively. [ABSTRACT FROM AUTHOR]

The contribution of different anthropogenic source-sectors on ozone mixing ratios and PM2.5 concentrations over Europe is assessed for a summer month (July 2006) using the US Environmental Protection Agency's (EPA's) Models-3 framework and the Netherlands Organization for Applied Scientific Research (TNO) anthropogenic emissions for 2006. Anthropogenic emission sources have been classified into 10 different Standard Nomenclature for Air Pollution (SNAP) categories. The road transport category, which is mainly responsible for NOX emissions, is estimated to have the major impact on Max8hrO3 mixing ratio suggesting an increase of 6.8% on average over Europe, while locally it is more than 20%. Power generation category is estimated to have the major impact on PM2.5 concentrations since it is the major source of SO2 emissions, suggesting an increase of 22.9% on average over Europe, while locally it is more than 60%. Agriculture category is also contributing significantly on PM2.5 concentrations, since agricultural activities are the major source of NH3 emissions, suggesting an increased by 16.1% on average over Europe, while in regions with elevated NH3 emissions the increase is up to 40%. [ABSTRACT FROM AUTHOR]

SF6 and PFC are being used as state-of-the-art tracers in tracer-technology programmes aimed at efficient oil recovery in the North Sea. This study aimed at specifying sources of leakage and quantifying emission levels of such gases and at evaluating their effect on global warming. To satisfy these goals, quantification of SF6 and PFC combustion by-products under different realistic flame/temperature conditions (turbine, refinery, power plant, households and car engine) has been performed. The PFC compounds studied were PMCP (CF3C5F9), PMCH (CF3C6F11) and 1, 2-PDMCH ((CF3)2C6F10). Three-dimensional transport atmospheric modelling has been carried out using UAM-AERO for four different tracers' emissions scenarios (Base scenario, one including maximum emissions of tracers and two scenarios including overestimated emissions during loading processes and distribution over the land of Norway). The results showed a significant increase in the background concentrations of SF6 and PFC in the last two mentioned scenarios up to 6 km height approximately. These concentration profiles have been used as input to radiative models. In addition to SF6 spectral data obtained from HITRAN2K complemented with new band measurements, newly obtained data with quantitative spectral analysis for the specific PFC have been used in the line-by-line (GENLN2) and broadband models. [ABSTRACT FROM AUTHOR]

Non-road equipment has been an important source of pollutants that negatively affect air quality in China. An accurate emission inventory for non-road equipment is therefore required to improve air quality. The objective of this paper was to characterize emissions from typical diesel-fueled material handling equipment (loaders and cranes) using a portable emission measurement system. Instantaneous, modal, and composite emissions were quantified in this study. Three duty modes (idling, moving, and working) were used. Composite emission factors were estimated using modal emissions and time-fractions for typical duty cycles. Results showed that emissions from loaders and cranes were higher and more variable for the moving and working modes than the idling mode. The estimated fuel-based CO, HC, NO, and PM2.5 composite emission factors were 21.7, 2.7, 38.2, and 3.6 g/(kg-fuel), respectively, for loaders, and 8.7, 2.4, 28.3, and 0.3 g/(kg-fuel), respectively, for cranes. NO emissions were highest and should be the main focus for emission controls. CO, HC, NO, and PM2.5 emissions measured were different from emission factors in the US Environmental Protection Agency NONROAD model and the Chinese National Guideline for Emission Inventory Development for Non-Road Equipment. This indicates that improving emission inventory accuracy for non-road equipment requires more real-world emission measurements. [ABSTRACT FROM AUTHOR]

Secondary inorganic aerosol (SIA) is the key driving factor of fine-particle explosive growth (FPEG) events, which are frequently observed in North China Plain. However, the SIA simulations remain highly uncertain over East Asia. To further investigate this issue, SIA modeling over North China Plain with the 15 km resolution Nested Air Quality Prediction Model System (NAQPMS) was performed from October 2017 to March 2018. Surface observations of SIA at 28 sites were obtained to evaluate the model, which confirmed the biases in the SIA modeling. To identify the source of these biases and reduce them, uncertainty analysis was performed by evaluating the heterogeneous chemical reactions in the model and conducting sensitivity tests on the different reactions. The results suggest that the omission of the SO2 heterogeneous chemical reaction involving anthropogenic aerosols in the model is probably the key reason for the systematic underestimation of sulfate during the winter season. The uptake coefficient of the "renoxification" reaction is a key source of uncertainty in nitrate simulations, and it is likely to be overestimated by the NAQPMS. Consideration of the SO2 heterogeneous reaction involving anthropogenic aerosols and optimization of the uptake coefficient of the "renoxification" reaction in the model suitably reproduced the temporal and spatial variations in sulfate, nitrate and ammonium over North China Plain. The biases in the simulations of sulfate, nitrate, ammonium, and particulate matter smaller than 2.5 μm (PM2.5) were reduced by 84.2%, 54.8%, 81.8%, and 80.9%, respectively. The results of this study provide a reference for the reduction in the model bias of SIA and PM2.5 and improvement of the simulation of heterogeneous chemical processes. [ABSTRACT FROM AUTHOR]