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Development of Biorefineries in the Bioeconomy: A Fuzzy-Set Qualitative Comparative Analysis among European Countries

2021, Ding, Zhengqiu, Grundmann, Philipp

This study aims to identify the configurational conditions that characterize the establish-ment of biorefineries in 20 European countries. After determining the conditions which support a bioeconomy transition, secondary data from national sources are used to represent their existing conditions within respective countries. Then, a fuzzy-set qualitative comparative analysis is em-ployed to compare and contrast the effect of varying combinations of the selected conditions on the development of biorefineries. The conditions chosen include coherent bioeconomy strategies, network intensity of regional bioclusters, intellectual capital, and natural resource availability. Our results reveal that the configuration of a coherent bioeconomy strategy, sizable public spending on R&D, abundant biomass supply, and a high level of network intensity is sufficient to explain the pro-nounced biorefineries development among some European countries. We recommend that countries with fragmented approaches review and redesign the policy and regulatory framework to create a holistic and consistent bioeconomy strategy, taking into account the configurations of conditions as an important prerequisite. In particular, factors such as the lack of best practice examples, the low level of public spending on research and development, the economic capacities for a skilled workforce in addition to the sustainable supply of raw materials should be addressed as focal points.

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Machine Learning for Determining Interactions between Air Pollutants and Environmental Parameters in Three Cities of Iran

2022, Rad, Abdullah Kaviani, Shamshiri, Redmond R., Naghipour, Armin, Razmi, Seraj-Odeen, Shariati, Mohsen, Golkar, Foroogh, Balasundram, Siva K.

Air pollution, as one of the most significant environmental challenges, has adversely affected the global economy, human health, and ecosystems. Consequently, comprehensive research is being conducted to provide solutions to air quality management. Recently, it has been demonstrated that environmental parameters, including temperature, relative humidity, wind speed, air pressure, and vegetation, interact with air pollutants, such as particulate matter (PM), NO2, SO2, O3, and CO, contributing to frameworks for forecasting air quality. The objective of the present study is to explore these interactions in three Iranian metropolises of Tehran, Tabriz, and Shiraz from 2015 to 2019 and develop a machine learning-based model to predict daily air pollution. Three distinct assessment criteria were used to assess the proposed XGBoost model, including R squared (R2), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE). Preliminary results showed that although air pollutants were significantly associated with meteorological factors and vegetation, the formulated model had low accuracy in predicting (R2PM2.5 = 0.36, R2PM10 = 0.27, R2NO2 = 0.46, R2SO2 = 0.41, R2O3 = 0.52, and R2CO = 0.38). Accordingly, future studies should consider more variables, including emission data from manufactories and traffic, as well as sunlight and wind direction. It is also suggested that strategies be applied to minimize the lack of observational data by considering second-and third-order interactions between parameters, increasing the number of simultaneous air pollution and meteorological monitoring stations, as well as hybrid machine learning models based on proximal and satellite data.

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Evaluating Evaporative Cooling Assisted Solid Desiccant Dehumidification System for Agricultural Storage Application

2022, Hussain, Ghulam, Aleem, Muhammad, Sultan, Muhammad, Sajjad, Uzair, Ibrahim, Sobhy M., Shamshiri, Redmond R., Farooq, Muhammad, Usman Khan, Muhammad, Bilal, Muhammad

The study aims to investigate Maisotsenko cycle evaporative cooling assisted solid desiccant air‐conditioning (M‐DAC) system for agricultural storage application. Conventional air‐conditioning (AC) systems used for this application are refrigeration‐based which are expensive as they consume excessive amount of primary‐energy. In this regard, the study developed a lab‐scale solid silica gel‐based desiccant AC (DAC) system. Thermodynamic performance of the developed system was investigated using various adsorption/dehumidification and desorption/regeneration cycles. The system possesses maximum adsorption potential i.e., 4.88 g/kg‐DA at higher regeneration temperature of 72.6 °C and long cycle time i.e., 60 min: 60 min. Moreover, the system’s energy consumption performance was investigated from viewpoints of maximum latent, sensible, and total heat as well as latent heat ratio (LHR), which were found to be 0.64 kW, 1.16 kW, and 1.80 kW, respectively with maximum LHR of 0.49. Additionally, the study compared standalone DAC (S‐ DAC), and M‐DAC system thermodynamically to investigate the feasibility of these systems from the viewpoints of temperature and relative humidity ranges, cooling potential (Qp), and coefficient of performance (COP). The S‐DAC system showed temperature and relative humidity ranging from 39 °C to 48 °C, and 35% to 66%, respectively, with Qp and COP of 17.55 kJ/kg, and 0.37, respectively. Conversely, the M‐DAC system showed temperature and relative humidity ranging from 17 °C to 25 °C, and 76% to 98%, respectively, with Qp and COP of 41.80 kJ/kg, and 0.87, respectively. Additionally, the study investigated respiratory heat generation rate (Qres), and heat transfer rate (Qrate) by agricultural products at different temperature gradient (∆T) and air velocity. The Qres and Qrate by the products were increased with ∆T and air velocity, respectively, thereby generating heat loads in the storage house. Therefore, the study suggests that the M‐DAC system could be a potential AC option for agricultural storage application.

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Supportive Business Environments to Develop Grass Bioeconomy in Europe

2021, Orozco, Richard, Mosquera-Losada, María Rosa, Rodriguez, Javier, Adamseged, Muluken Elias, Grundmann, Philipp

Grasslands cover almost half of the total European agricultural area and are the source of a wide range of public goods and services. Yet, their potential to produce innovative bio-based products, such as paper and plastic, remains widely untapped. We employ a multiple case study approach and implement the Business Environment Framework by Adamseged and Grundmann (2020) on eighteen alternative grass-based businesses to investigate the interdependencies between these successful business models and their business environments. The subsequent analysis reveals that the deployment of funds and policies to support alternative grass-based products remains low in most regions of Europe. Our findings highlight that aligned funding mechanisms that incorporate and promote the specific benefits generated by grass-producing and grass-processing businesses are key to overcoming the barriers related to the competition of bio-based products with the established fossil-fuels-based economic system. To make alternative grass-based markets more dynamic, increasing consumer awareness through adequate marketing is perceived as an important aspect. Capacity building and alignment efforts need to be strengthened and coordinated at local and higher levels to enable the replication and scale-up of novel grass-based businesses in Europe and beyond.