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This paper shows how to exploit the degree of freedom represented by the common-mode voltage, which is inherent in three-phase Cascaded H-Bridge (CHB) converters, to minimize the total Root Mean Square (RMS) current value of the distributed dc sources. An optimal common-mode voltage injection law is derived, constituting a Maximum Power Per Ampere (MPPA) modulation strategy with respect to the currents of the dc sources. The potential benefits introduced by the proposed algorithm are analyzed in the context of battery-fed CHB converters and validated experimentally with a three-time-constant Randles model of a battery cell. The MPPA strategy is compared with traditional common-mode voltage injection methods, and battery loss reduction is demonstrated. The obtained battery energy saving is dependent on the converter modulation index and power factor. Experimental tests on a 36-cell full-bridge CHB converter validates the simulation and numerical derivation. To demonstrate the efficacy of the proposed method in practical applications, a 3 MW Energy Storage System (ESS) and a 110 kW Battery Electric Vehicle (BEV) undergoing standard drive cycles are presented as case studies. Compared to traditional modulation strategies, the MPPA strategy reduces the battery losses by up to 10.9% in the ESS and 27.5% in the BEV application.

There are substantial differences in carbon footprints across households. This study applied an environmentally extended multiregional input–output approach to estimate household carbon footprints for 12 different income groups of China’s 30 regions. Subsequently, carbon footprint Gini coefficients were calculated to measure carbon inequality for households across provinces. We found that the top 5% of income earners were responsible for 17% of the national household carbon footprint in 2012, while the bottom half of income earners caused only 25%. Carbon inequality declined with economic growth in China across space and time in two ways: first, carbon footprints showed greater convergence in the wealthier coastal regions than in the poorer inland regions; second, China’s national carbon footprint Gini coefficients declined from 0.44 in 2007 to 0.37 in 2012. We argue that economic growth not only increases income levels but also contributes to an overall reduction in carbon inequality in China.

Due to the decreasing availability of virgin materials coupled with an increased awareness of environmental sustainability issues, many researchers have focused their efforts on investigating innovative technological solutions in the civil engineering domain. This paper aims to evaluate the suitability of construction and demolition waste (C and DW) and reclaimed asphalt pavement (RAP) reused within asphalt mixtures (AMs) prepared for the binder layer of road pavements. Both hot and cold mixing methodologies were investigated. The technical assessment was based on the volumetric and mechanical suitability, according to saturated surface dry voids (SSDV) and indirect tensile strength (ITS) tests carried out at 10 °C, respectively. Laboratory findings showed that all the hot AMs matched the desired target SSDV at the design gyrations number at different optimum bitumen content levels, alternatively showing a non-significant variation or a significant increase in ITS compared to conventional hot mix asphalt. Conversely, the cold AMs with cement and emulsion bitumen showed a greater volume of voids and moisture sensitivity, and lower temperature susceptibility compared to hot AMs, reaching, on average, 11% lower ITS when using coarse C and DW aggregates and 43% lower ITS when using filler from C and DW. These volumetric and mechanical properties were modeled by means of support vector machines and categorical boosting (CatBoost) machine learning algorithms. The results proved to be satisfactory, with CatBoost determination coefficients R2 referring to SSDV and ITS equal to 0.8678 and 0.9916, respectively. This allowed for the mechanical performance of these sustainable mixtures to be predicted with high accuracy and implemented within conventional mix design procedures.

The Ganges-Brahmaputra-Meghna (GBM) delta is one of the world's largest deltas. It is currently experiencing high rates of relative sea-level rise of about 5 mm/year, reflecting anthropogenic climate change and land subsidence. This is expected to accelerate further through the 21st Century, so there are concerns that the GBM delta will be progressively submerged. In this context, a core question is: can sedimentation on the delta surface maintain its elevation relative to sea level? This research seeks to answer this question by applying a two-dimensional flow and morphological model which is capable of handling dynamic interactions between the river and floodplain systems and simulating floodplain sedimentation under different flow-sediment regimes and anthropogenic interventions. We find that across a range of flood frequencies and adaptation scenarios (including the natural polder-free state), the retained volume of sediment varies between 22% and 50% of the corresponding sediment input. This translates to average rates of sedimentation on the delta surface of 5.5 mm/yr to 7.5 mm/yr. Hence, under present conditions, sedimentation associated with quasi-natural conditions can exceed current rates of relative sea-level rise and potentially create new land mass. These findings highlight that encouraging quasi-natural conditions through the widespread application of active sediment management measures has the potential to promote more sustainable outcomes for the GBM delta. Practical measures to promote include tidal river management, and appropriate combinations of cross-dams, bandal-like structures, and dredging.

Liberalisation of the British household electricity market, in which previously monopolised regional markets were exposed to large-scale entry, is used as a natural experiment on oligopolistic nonlinear pricing. Each oligopolist offered a single two-part electricity tariff, but inconsistent with current theory, the two-part tariffs were heterogeneous in ways that cannot be attributed to explanations such as asymmetric costs or variations in brand loyalty. Instead, the evidence suggests that firms deliberately differentiated their tariff structures, resulting in market segmentation according to consumers’ usage.

Rainfall and overland flow are fundamental processes for Earth's ecosystems but can also be land disturbing forces, particularly when triggered by extreme hydro-meteorological events. Examples of these extremes are rainstorms and related phenomena due to rainfall aggressiveness. They produce high-impact land processes such as soil erosion and nutrient losses. Economic and social consequences of these processes can be quite severe. However, hydrological extremes and their environmental implications are still poorly understood, particularly if analyzed in the context of climate change. Here, we analyze a 300 year long times series of historical rainfall patterns across the Mediterranean in the last three centuries and we investigate changes in the erosive forcing as related to climate changes. Our results show that the erosive forcing increased towards the end of the Little Ice Age (similar to 1850) over western and central Mediterranean and that has been increasing in the recent warming period at low Mediterranean latitudes, due to a higher frequency of intensive storms. Such increased concentrated precipitation may lead to an intensification of land degradation processes triggered by soil erosion and transport across a range of scales from hillslopes to small catchments.

In the last years, the concept of “smart city” has been the subject of increasing attention in urban planning and governance due to the sustainability challenges and great technological advancements. Although the relevant literature highlights those smart cities can create a fertile environment to drive innovation from a technological, managerial and organizational, and policy point of view how smart cities function, in terms of their value chain and in light of sustainability and circularity is still an open question. Based on these considerations, this work aims to investigate how smart cities deliver value by combining environmental, societal, and financial priorities to re-imagine their core business models and shift the boundaries of urban competition in light of circular economy principles. To reach this goal, the tool Sustainable Business Model Innovation Canvas has been applied in the urban context with the aim to create and leverage an environmental and societal surplus in light of circularity in the smart city framework. Preliminary results shed light on new vistas on the future and new challenges of smart cities particularly relevant for facing the current complexity of the economy, social, and environmental changes.