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Abstract Recharging infrastructure (RI) deployment plays a vital role in improving the public recharging availability for transport electrification. Decarbonizing transportation using low-emission electricity requires massive RI network. Even though the consumers are reluctant to purchase electric vehicles (EVs) until RIs are sufficiently placed, the investors are not willing to invest in RIs due to recharging demand uncertainties. Therefore, a scientific planning framework is needed to ensure the sustainable deployment of EV-RIs in complex networks. In this study, a lifecycle thinking-based multi-period infrastructure-planning framework is proposed to develop sustainable public EV-RIs in an urban context. This framework consists of a temporal model to find the dynamic EV-RI demands, a stochastic model to obtain travel distances, and a multi-objective optimization model to select the best desirable capacities and locations for potential EV-RIs. A case study of a typical medium-scale municipality in Canada was assessed using the proposed framework and validated using conventional infrastructure planning scenarios. The geo-processing data, regional travel behaviors, and recharging characteristics were used as model inputs. The results of the case study showed that the proposed framework can be used to estimate multi-period public recharging demands, minimize lifecycle costs, maximize service coverage and infrastructure utilization, and ensure reasonable paybacks compared to conventional planning approaches. Moreover, this framework can be used to compare different investment assistances, which are required in the early stages of the RI deployment process to encourage investors. Furthermore, government and private institutions can use this framework to identify recharging demands, permitting, and developing RIs in the long-run.

Abstract The residential sector accounts for most of energy-consumption in developing countries in the form of traditional energy. The use of commercial energy is nominal and confined mostly to urban areas where fuelwood is already monetized. A model, based on an end-use/process analysis approach, is developed on a spreadsheet, which is capable of simulating scenarios to address issues of increasing traditional energy-demand caused by population growth, sustainable supply capacity of the existing energy resources, potential for development of new and renewable energy resources, technology. This paper is divided into two parts: general energy issues and the modelling approach, and the application of this approach to Nepal in the context of fuelwood-supply sustainability.

Abstract Communication between vehicles and road infrastructure can enable more efficient use of the road network and hence reduce congestion in urban areas. This improvement can be enhanced by distributed control due to its lighter computational load and higher reliability. Despite favourable impacts on traffic, little is known about the effects of such systems on near-road air quality. In this study, an End-To-End (E2E) dynamic distributed routing algorithm in Connected and Automated Vehicles (CAVs) was applied in downtown Toronto, to identify whether benefits to network throughput were associated with lower near-road NO2 concentrations. We observe significant reductions in the emissions of Greenhouse Gases (GHGs) with increased penetration of CAVs. Nonetheless, at times, the emissions of nitrogen oxides (NOx) increased with higher CAVs. Besides, a higher frequency and severity of NO2 hot-spots were observed under a 100% CAV scenario. Impacts of the proposed system on electric energy consumption in a full electric vehicle network were also investigated, indicating that the addition of CAVs that are electric did not contribute to high energy savings. We propose that such new transformative technologies in transportation should be designed with air pollution and public health goals.

Abstract Conversion of carbon contained in the solid residues (tars + biochar) derived from urban biomass gasification named herein TC would allow enhancing the yield of carbon species (CO/CO2) in synthetic gas. For this purpose, three low cost materials have been tested as possible catalysts: iron species (reduced Fe), bone meal (BM), and ashes (ash) recovered from biochar complete oxidation. The parametric study used the following as variables: air GHSV, onset of reaction temperature, reaction time to optimize CO/CO2 molar ratio and tar content in the produced gas. Results showed an autocatalytic effect of biochar leading to the catalytic conversion of approximately 78% of tars by the native metals contained in TC. The catalytic effect was further enhanced by adding Fe, BM, and extra ash. Addition of Fe catalyst resulted in significant heat generation (temperature increase of ca. 500 °C) and a twofold decrease in reaction time to consume all the carbon. Use of ash and BM as catalysts exhibit heat generation comparable to Fe, along with an improved reaction time, complete tars conversion and a CO/CO2 molar ratio to above 1.3 in the produced gas.

An ecosystem in a cold climate river basin is vulnerable to the effects of climate change affecting permafrost thaw and glacier retreat. We currently lack sufficient data and information if and how hydrological processes such as glacier retreat, snowmelt and freezing-thawing affect sediment and nutrient runoff and transport, as well as N2O emissions in cold climate river basins. As such, we have implemented well-established, semi-empirical equations of nitrification and denitrification within the Soil and Water Assessment Tool (SWAT), which correlate the emissions with water, sediment and nutrients. We have tested this implementation to simulate emission dynamics at three sites on the Canadian prairies. We then regionalized the optimized parameters to a SWAT model of the Athabasca River Basin (ARB), Canada, calibrated and validated for streamflow, sediment and water quality. In the base period (1990-2005), agricultural areas (2662 gN/ha/yr) constituted emission hot-spots. The spring season in agricultural areas and summer season in forest areas, constituted emission hot-moments. We found that warmer conditions (+13% to +106%) would have a greater influence on emissions than wetter conditions (-19% to +13%), and that the combined effect of wetter and warmer conditions would be more offsetting than synergetic. Our results imply that the spatiotemporal variability of N2O emissions will depend strongly on soil water changes caused by permafrost thaw. Early snow freshet leads to spatial variability of soil erosion and nutrient runoff, as well as increases of emissions in winter and decreases in spring. Our simulations suggest crop residue management may reduce emissions by 34%, but with the mixed results reported in the literature and the soil and hydrology problems associated with stover removal more research is necessary. This modelling tool can be used to refine bottom-up emission estimations at river basin scale, test plausible management scenarios, and assess climate change impacts including climate feedback.

AbstractAutotrophs play an essential role in the cycling of carbon and nutrients, yet disease‐ecosystem relationships are often overlooked in these dynamics. Importantly, the availability of elemental nutrients like nitrogen and phosphorus impacts infectious disease in autotrophs, and disease can induce reciprocal effects on ecosystem nutrient dynamics. Relationships linking infectious disease with ecosystem nutrient dynamics are bidirectional, though the interdependence of these processes has received little attention. We introduce disease‐mediated nutrient dynamics (DND) as a framework to describe the multiple, concurrent pathways linking elemental cycles with infectious disease. We illustrate the impact of disease–ecosystem feedback loops on both disease and ecosystem nutrient dynamics using a simple mathematical model, combining approaches from classical ecological (logistic and Droop growth) and epidemiological (susceptible and infected compartments) theory. Our model incorporates the effects of nutrient availability on the growth rates of susceptible and infected autotroph hosts and tracks the return of nutrients to the environment following host death. While focused on autotroph hosts here, the DND framework is generalizable to higher trophic levels. Our results illustrate the surprisingly complex dynamics of host populations, infection patterns, and ecosystem nutrient cycling that can arise from even a relatively simple feedback between disease and nutrients. Feedback loops in disease‐mediated nutrient dynamics arise via effects of infection and nutrient supply on host stoichiometry and population size. Our model illustrates how host growth rate, defense, and tissue chemistry can impact the dynamics of disease–ecosystem relationships. We use the model to motivate a review of empirical examples from autotroph–pathogen systems in aquatic and terrestrial environments, demonstrating the key role of nutrient–disease and disease–nutrient relationships in real systems. By assessing existing evidence and uncovering data gaps and apparent mismatches between model predictions and the dynamics of empirical systems, we highlight priorities for future research intended to narrow the persistent disciplinary gap between disease and ecosystem ecology. Future empirical and theoretical work explicitly examining the dynamic linkages between disease and ecosystem ecology will inform fundamental understanding for each discipline and will better position the field of ecology to predict the dynamics of disease and elemental cycles in the context of global change.

Abstract The increased environmental awareness coupled with the recent changes in the oil prices triggered the necessity of focusing on effective management of energy systems. Global climate change has caused many people to consider ways of reducing greenhouse gases Renewable energy has become an essential feature in curtailing emission of Green House Gases, while meeting the demand for energy. This paper presents an innovation system framework for development and diffusion of renewable energy technologies. The framework is used to identify opportunities for small and medium enterprises in the renewable energy sector. A case study on a successful development, installation and implementation of solar thermal systems households in Calgary, Alberta, by an entrepreneurial firm, is also presented.

Detailed analysis of ground rods and their influence on horizontal ground conductors, such as those forming grounding grids, is performed assuming a two layer soil stratification. The study starts with a discussion about the adequacy of uniform and two-layer soils as equivalent models for actual soil structures. Following this, a typical ground rod is analysed, while it is progressively associated with other ground rods, and ultimately, with horizontal conductors. The same procedure is also applied to an horizontal conductor. The results, shown using numerous charts which can be used conveniently for practical design purposes, lead to several interesting conclusions, many of which are new or still unpublished.