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Biomethane is a flexible energy vector that can be used as a renewable fuel for both the heat and transport sectors. Recent EU legislation encourages the production and use of advanced, third generation biofuels with improved sustainability for future energy systems. The integration of technologies such as anaerobic digestion, gasification, and power to gas, along with advanced feedstocks such as algae will be at the forefront in meeting future sustainability criteria and achieving a green gas supply for the gas grid. This paper explores the relevant pathways in which an integrated biomethane industry could potentially materialise and identifies and discusses the latest biotechnological advances in the production of renewable gas. Three scenarios of cascading biomethane systems are developed.

AbstractMany developing countries are facing the difficulty of choosing between economic growth and energy conservation and emission reduction (ECER). China has strengthened the implementation of ECER by setting environmental accountability as the development goal of local governments, hoping to have better governance effects. To evaluate the actual intervention effect of this approach, this paper constructs panel data covering 46 countries from 1995 to 2014 and uses the difference-in-differences (DID) method and the composite control method to quantitatively analyse the policy effect. The results show that China can effectively curb energy consumption and carbon emission intensity per unit of GDP by adding ECER targets to the government’s five-year plan, which has significant effects on ECER. Furthermore, we use an intermediary mechanism to test and identify low-carbon alternatives and an ECER promotion mechanism for technological advancement. The conclusion shows that economic development is compatible with low carbon and energy consumption. Combined with China’s long-term goals for ECER, it can be considered that on the road to achieving carbon peaking and carbon neutrality in the future, the economy and tertiary industry should be rationally developed, the degree of urbanization should receive more attention, and the proportion of thermal power generation should be reduced.

The aim of this paper was to investigate the role of public institutions in the pursuit of sustainable development in a case study of international relevance: Taranto’s ILVA steel plant, which is one of the biggest steel and iron centres in Europe. The case study was analysed through investigating the different aspects of sustainable development in the four phases of development of the steel plant, from public direct management to private management. The analysis, based on a series of unstructured data, was carried out by applying a triple bottom line approach and the total interpretative structuring model (TISM). Evidence shows how—in the absence of stable, coherent, strong and present public institutions, capable of reading the forces of the local and international context and of intervening with regulatory actions inspired by a planned and interiorized economic strategy—the market, left in the hands of the private entrepreneur only, is destined to fail, and the paths of multidimensional sustainable development stray away from the ambitions of modern states.

Abstract As published earlier on the performance of a chimney-dependent solar crop dryer (CDSCD) designed by the authors, the solar chimney can be combined with an appropriately inclined roof of drying chamber for ventilation improvement in the dryer. Mathematical models and a computer code are now developed to simulate the ventilation in relation to the design of the CDSCD. This is done for situations without any crop (no-load) in the dryer, to relate the ventilation to the external dimensions. The pressure-loss and bulk-fluid-temperature coefficients are deduced empirically from trials on the physical model. The simulation code predicts the ventilation to within 5% and the temperatures to within 1.5% of observed data, confirming the validity of the code as an effective design tool for the CDSCD. Results of parametric studies performed with the code indicate that, maximum airflow can be achieved when the inlet-exit area ratio is around 4:1, above which the system then approaches saturation without any real variation. The drying-chamber roof inclination and the chimney height are critical for the design in the geographical regions far from the equator, whereas the decisive parameters in the regions close to the equator are the drying chamber height and the area ratio of the dryer floor to chimney cross section. A high drying chamber with a short solar chimney is generally favoured at locations close to the equator, whereas a short drying chamber with a high solar chimney is suitable for regions far away from the equator.

Abstract The objective of this study was to investigate the effects of particle size reduction and solubilization on biogas production from food waste (FW). To clarify the effects of volatile fatty acids (VFAs) in the digestion process, the relationship between particle size and VFA accumulation was investigated in detail. For this purpose, substrates of various particle sizes were prepared by bead milling to support hydrolysis. Batch anaerobic digestion experiments were carried out using these pretreated substrates at mesophilic temperature for a period of 16 days. The results of pretreatment showed that the mean particle size (MPS) of substrates ground with a bead mill decreased from 0.843 to 0.391 mm, and solubilization accounted for approximately 40% of the total chemical oxygen demand (total COD) for grinding pretreatment by bead milling. Anaerobic digestion batch experiments revealed that MPS reduced by bead milling at 1000 rpm improved methane yield by 28% compared with disposer treatment. Moreover, this may have increased microbial degradation during the VFA production process with increasing total number of revolutions (operation time × revolutions per minute). However, excessive reduction of the particle size of the substrate resulted in VFA accumulation, decreased methane production, and decreased solubilization in the anaerobic digestion process. These results suggest that optimized reduction of the particle size of the substrate in conjunction with optimized microbial growth could improve the methane yield in anaerobic digestion processes.

According to Bureau of Transportation Statistics, the U.S. transportation system handled 14,329 million ton-miles of freight per day in 2020. Understanding the generation of these freight shipments is crucial for transportation researchers, planners, and policymakers to design and plan for a more efficient and connected freight transportation system. Traditionally, the freight generation modeling has been based on Ordinary Least Square (OLS) regression, although more advanced Machine Learning (ML) algorithms have been evaluated and proven to have excellent performance in various transportation applications in recent years. Furthermore, one modeling approach applied for one industry might not always be applicable for another as their freight generation logics can be quite different. The objective of this study is to apply and evaluate alternative ML algorithms in the estimation of freight generation for each of 45 industry types. Seven alternative ML algorithms, along with the base OLS regression, were evaluated and compared. In addition, the study considered different combinations of variables in both the original and logarithmic form as well as hyperparameters of those ML algorithms in the model selection for each industry type. The results showed statistically significant improvements in the root mean square error reduction by the alternative ML algorithms over the OLS for over 80% of cases. The study suggests utilizing the alternative ML algorithms can reduce the root mean square error by about 30%, depending on industry types.

The worldwide historical carbon (C) losses due to Land Use and Land-Use Change between 1870 and 2014 are estimated at 148 Pg C (1 Pg=1billionton). South America is chosen for this study because its soils contain 10.3% (160 Pg C to 1-m depth) of the soil organic carbon stock of the world soils, it is home to 5.7% (0.419 billion people) of the world population, and accounts for 8.6% of the world food (491milliontons) and 21.0% of meat production (355milliontons of cattle and buffalo). The annual C emissions from fossil fuel combustion and cement production in South America represent only 2.5% (0.25 Pg C) of the total global emissions (9.8 Pg C). However, South America contributes 31.3% (0.34 Pg C) of global annual greenhouse gas emissions (1.1 Pg C) through Land Use and Land Use Change. The potential of South America as a terrestrial C sink for mitigating climate change with adoption of Low-Carbon Agriculture (LCA) strategies based on scenario analysis method is 8.24 Pg C between 2016 and 2050. The annual C offset for 2016 to 2020, 2021 to 2035, and 2036 to 2050 is estimated at 0.08, 0.25, and 0.28 Pg C, respectively, equivalent to offsetting 7.5, 22.2 and 25.2% of the global annual greenhouse gas emissions by Land Use and Land Use Change for each period. Emission offset for LCA activities is estimated at 31.0% by restoration of degraded pasturelands, 25.6% by integrated crop-livestock-forestry-systems, 24.3% by no-till cropping systems, 12.8% by planted commercial forest and forestation, 4.2% by biological N fixation and 2.0% by recycling the industrial organic wastes. The ecosystem carbon payback time for historical C losses from South America through LCA strategies may be 56 to 188years, and the adoption of LCA can also increase food and meat production by 615Mton or 17.6Mtonyear-1 and 56Mton or 1.6Mtonyear-1, respectively, between 2016 and 2050.