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Additional file 1. Histotical and projected C stocks and fluxes.

This repository contains the raw data of the inputs and results presented in the paper "Electrification of light-duty vehicle fleet alone will not meet mitigation targets" published in Nature Climate Change (2020) by Alexandre Milovanoff, I. Daniel Posen, and Heather L. MacLean (Department of Civil & Mineral Engineering, University of Toronto).

Environmental factors may operate differently when relations are measured across different geographical locations, a phenomenon known as spatial non-stationarity. This study investigates the spatial non-stationarity effect of unhealthy food environments and green spaces on the T2DM prevalence rate at the neighborhood level in Toronto. This study also compares how the results vary between age groups, classified as all adults (20 and above), young adults (from 20 to 44), middle adulthood (from 45 to 64), and seniors (65 and above). The geographically weighted regression model is utilized to explore the impacts of spatial non-stationarity effects on the research results, which may lead to biased conclusions, which have often been ignored in past studies. The results from this study reveal that environmental variables dissimilarly affect T2DM prevalence rates among different age groups and neighborhoods in Toronto after controlling for socioeconomic factors. For example, the green space density yields positive associations with diabetes prevalence rates for elder generations but negative relationships for younger age groups in twenty-two and four neighborhoods, respectively, around Toronto East. The observed associations will provide beneficial suggestions to support government and public health authorities in designing education, prevention, and intervention programs targeting different neighborhoods to control the burden of diabetes.

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.

We evaluate the potential of using a process-based ecosystem model (BEPS) for crop biomass mapping at 20 m resolution over the research site in Manitoba, western Canada driven by spatially explicit leaf area index (LAI) retrieved from Sentinel-2 spectral reflectance throughout the entire growing season. We find that overall, the BEPS-simulated crop gross primary production (GPP), net primary production (NPP), and LAI time-series can explain 82%, 83%, and 85%, respectively, of the variation in the above-ground biomass (AGB) for six selected annual crops, while an application of individual crop LAI explains only 50% of the variation in AGB. The linear relationships between the AGB and these three indicators (GPP, NPP and LAI time-series) are rather high for the six crops, while the slopes of the regression models vary for individual crop type, indicating the need for calibration of key photosynthetic parameters and carbon allocation coefficients. This study demonstrates that accumulated GPP and NPP derived from an ecosystem model, driven by Sentinel-2 LAI data and abiotic data, can be effectively used for crop AGB mapping; the temporal information from LAI is also effective in AGB mapping for some crop types.

Global climate change poses one of the greatest challenges facing humanity in this century. This article, which introduces the American Psychologist special issue on global climate change, follows from the report of the American Psychological Association Task Force on the Interface Between Psychology and Global Climate Change. In this article, we place psychological dimensions of climate change within the broader context of human dimensions of climate change by addressing (a) human causes of, consequences of, and responses (adaptation and mitigation) to climate change and (b) the links between these aspects of climate change and cognitive, affective, motivational, interpersonal, and organizational responses and processes. Characteristics of psychology that cross content domains and that make the field well suited for providing an understanding of climate change and addressing its challenges are highlighted. We also consider ethical imperatives for psychologists' involvement and provide suggestions for ways to increase psychologists' contribution to the science of climate change.

Abstract The building industry has been developing measures for reducing operational emissions in the fight against climate change. Some of these well-intentioned measures may result in higher embodied emissions, potentially more than offsetting reductions achieved during operation. This research evaluates the effectiveness of different levels of application of five passive energy efficiency measures to reduce life cycle greenhouse gas (GHG) emissions in high-rise residential buildings in Toronto, Canada, while considering projected future climate and GHG intensity of energy sources. Through combining and automating life cycle assessment and energy simulation on a visual programing interface, the study evaluates 16,128 envelope variants, examining 56 wall, 12 roof, 6 window assemblies and 4 window-to-wall ratios (WWRs). Decreasing the WWR is found to be the most effective measure to reduce total envelope related GHG emissions (by about 28%). Increasing wall and roof insulation with GHG intensive materials (e.g., extruded polystyrene [XPS]), and increasing spandrel wall insulation potentially augment total emissions, depending on the scenario. Higher trade-offs between embodied and operational emissions are found when highly efficient electric HVAC systems are implemented (e.g., heat pumps). Results demonstrate it is imperative to assess both embodied and operational emissions during the design process of building envelopes to effectively reduce GHG emissions.

Experiments were conducted to compare the mixing and combustion properties of natural gas jets issuing from elliptical and round nozzle holes within an optically accessible combustion bomb. High speed images of combustion events were captured and analyzed along with cylinder pressure and heat release data. Hydrocarbon measurements of the combustion products were used to calculate combustion efficiencies. The elliptical nozzle holes were found to produce a more evenly distributed heat release profile, with a smoother transition from premixed to diffusion burning. The elliptical nozzle jets also produced far more luminous flames. Ignition delay and combustion efficiency were not found to vary significantly with nozzle design. The use of elliptical nozzles as a method of mixing enhancement for gaseous engine fuels remains potentially viable, although further work is necessary to fully quantify the performance and emissions impacts.