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Accurate visualization of air temperature distribution can be useful for various thermal analyses in fields such as human health and heat transfer of local area. This paper presents a novel approach to measuring air temperature from midwave hyperspectral Fourier transform infrared (FTIR) imaging in the carbon dioxide absorption band (between 4.25–4.35 μ m). In this study, the proposed visual air temperature (VisualAT) measurement is based on the observation that the carbon dioxide band shows zero transmissivity at short distances. Based on analysis of the radiative transfer equation in this band, only the path radiance by air temperature survives. Brightness temperature of the received radiance can provide the raw air temperature and spectral average, followed by a spatial median-mean filter that can produce final air temperature images. Experiment results tested on a database obtained by a midwave extended FTIR system (Telops, Quebec City, QC, Canada) from February to July 2018 show a mean absolute error of 1.25 ∘ K for temperature range of 2.6−26.4 ∘ C. [ABSTRACT FROM AUTHOR]

Biomass burning is an important and changing component of global and hemispheric carbon cycles. Boreal forest fires in Russia and Canada are significant sources of the greenhouse gases carbon dioxide (CO2) and methane (CH4). The influence of carbon monoxide (CO) on the greenhouse effect is practically absent; its main absorption bands of 4.6 and 2.3 μm are far away from the climatically important spectral regions. Meanwhile, CO concentrations in fire plumes are closely related to CO2 and CH4 emissions from fires. On the other hand, satellite measurements of CO are much simpler than those of the aforementioned gases. The Atmospheric Infrared Sounder (AIRS) operating in the Thermal IR spectral region has provided a satellite-based CO data set since October 2002. This satellite data allow to estimate CO emissions from biomass burning north of 30° N using a simple two-box mass-balance model. These results correlate closely with independently estimated CO emissions from the GFED4c bottom-up database. In 2021, both estimate record high emissions throughout the preceding two decades, double the annual emissions compared to previous periods. There have been two years with extremely high emissions (2003 and 2021) but for the rest of the data, an upward trend with a rate of 3.6 ± 2.2 Tg CO yr−2 (4.8 ± 2.7% yr−1) was found. A similar rate of CO emissions can be seen in the GFED4c data. [ABSTRACT FROM AUTHOR]

Carbon capture, utilization, and storage (CCUS) is an attractive technology for the decarbonization of global energy systems. However, its early development stage makes impact assessment difficult. Moreover, rising popularity in carbon pricing necessitates the development of a methodology for deriving carbon abatement costs that are harmonized with the price of carbon. We develop, using a combined bottom-up analysis and top-down learning curve approach, a levelized cost of carbon abatement (LCCA) model for assessing the true cost of emissions mitigation in CCUS technology under carbon pricing mechanisms. We demonstrate our methodology by adapting three policy scenarios in Canada to explore how the implementation of CO2-to-diesel technologies could economically decarbonize Canada's transportation sector. With continued policy development, Canada can avoid 932 MtCO2eq by 2075 at an LCCA of CA$209/tCO2eq. Technological learning, low emission hydroelectricity generation, and cost-effective electricity prices make Quebec and Manitoba uniquely positioned to support CO2-to-diesel technology. The additional policy supports beyond 2030, including an escalating carbon price, CO2-derived fuel blending requirements, or investment in low-cost renewable electricity, which can accelerate market diffusion of CO2-to-diesel technology in Canada. This methodology is applicable to different jurisdictions and disruptive technologies, providing ample foci for future work to leverage this combined technology learning + LCCA approach. [ABSTRACT FROM AUTHOR]