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Cold regions are warming much faster than the global average, resulting in more frequent and intense freeze-thaw cycles (FTCs) in soils. In hydrocarbon-contaminated soils, FTCs modify the biogeochemical and physical processes controlling petroleum hydrocarbon (PHC) biodegradation and the associated generation of methane (CH 4 ) and carbon dioxide (CO 2 ). Thus, understanding the effects of FTCs on the biodegradation of PHCs is critical for environmental risk assessment and the design of remediation strategies for contaminated soils in cold regions. In this study, we developed a diffusion-reaction model that accounts for the effects of FTCs on toluene biodegradation, including methanogenic biodegradation. The model is verified against data generated in a 215 day-long batch experiment with soil collected from a PHC contaminated site in Ontario, Canada. The fully saturated soil incubations with six different treatments were exposed to successive 4-week FTCs, with temperatures oscillating between -10 °C and +15 °C, under anoxic conditions to stimulate methanogenic biodegradation. We measured the headspace concentrations and 13 C isotope compositions of CH 4 and CO 2 and analyzed the porewater for pH, acetate, dissolved organic and inorganic carbon, and toluene. The numerical model represents solute diffusion, volatilization, sorption, as well as a reaction network of 13 biogeochemical processes. The model successfully simulates the soil porewater and headspace concentration time series data by representing the temperature dependencies of microbial reaction and gas diffusion rates during FTCs. According to the model results, the observed increases in the headspace concentrations of CH 4 and CO 2 by 87% and 136%, respectively, following toluene addition are explained by toluene fermentation and subsequent methanogenesis reactions. The experiment and the numerical simulation show that methanogenic degradation is the primary toluene attenuation mechanism under the electron acceptor-limited conditions experienced by the soil samples, representing 74% of the attenuation, with sorption contributing to 11%, and evaporation contributing to 15%. Also, the model-predicted contribution of acetate-based methanogenesis to total produced CH 4 agrees with that derived from the 13 C isotope data. The freezing-induced soil matrix organic carbon release is considered as an important process causing DOC increase following each freezing period according to the calculations of carbon balance and SUVA index. The simulation results of a no FTC scenario indicate that, in the absence of FTCs, CO 2 and CH 4 generation would decrease by 29% and 26%, respectively, and that toluene would be biodegraded 23% faster than in the FTC scenario. Because our modeling approach represents the dominant processes controlling PHC biodegradation and the associated CH 4 and CO 2 fluxes, it can be used to analyze the sensitivity of these processes to FTC frequency and duration driven by temperature fluctuations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In this paper, we propose an optimization model that considers two pathways for injecting renewable content into natural gas pipeline networks. The pathways include (1) power-to-hydrogen or PtH, where off-peak electricity is converted to hydrogen via electrolysis, and (2) power-to-methane, or PtM, where carbon dioxide from different source locations is converted into renewable methane (also known as synthetic natural gas, SNG). The above pathways result in green hydrogen and methane, which can be injected into an existing natural gas pipeline network. Based on these pathways, a multi-period network optimization model that integrates the design and operation of hydrogen from PtH and renewable methane is proposed. The multi-period model is a mixed-integer non-linear programming (MINLP) model that determines (1) the optimal concentration of hydrogen and carbon dioxide in the natural gas pipelines, (2) the optimal location of PtH and carbon dioxide units, while minimizing the overall system cost. We show, using a case study in Ontario, the optimal network structure for injecting renewable hydrogen and methane within an integrated natural gas network system provides a $12M cost reduction. The optimal concentration of hydrogen ranges from 0.2 vol % to a maximum limit of 15.1 vol % across the network, while reaching a 2.5 vol % at the distribution point. This is well below the maximum limit of 5 vol % specification. Furthermore, the optimizer realized a CO2 concentration ranging from 0.2 vol % to 0.7 vol %. This is well below the target of 1% specified in the model. The study is essential to understanding the practical implication of hydrogen penetration in natural gas systems in terms of constraints on hydrogen concentration and network system costs. [ABSTRACT FROM AUTHOR]

In this paper, new polygeneration processes co‐producing electricity, methanol, dimethyl ether (DME), and Fischer–Tropsch (FT) fuels from different feedstock ratios of biomass, natural gas, and nuclear hydrogen generated through a copper‐chlorine (CuCl) cycle are analyzed for operation in Canada to produce transportation fuels. This combination of carbonless heat and a 'carbon neutral' biomass feedstock would contribute to the net reduction in greenhouse gas (GHG) emissions. In Part I of this work, the model for this biomass‐gas‐and‐nuclear‐to‐liquids (BGNTL) process was developed. This work expands on it and evaluates the economic and environmental impacts this plant would have in both Ontario and Alberta based on their local costs and resource availability. The analysis demonstrates that an increase in the ratio of biomass to natural gas in feedstock reduces the emissions of the process but increases the cost of carbon dioxide equivalents (CO2e) avoided. The results show that the BGNTL concept can be an economically attractive way of reducing net transportation sector GHG emissions in both Ontario and Alberta in meaningful quantities. [ABSTRACT FROM AUTHOR]

In deregulated electricity sector climates, such as in Ontario, the production of clean or renewable energy by small power producers through distributed generation (DG) is encouraged. This paper examines the policies that can be used to encourage DG investment and incorporates them into a mathematical model. This model is then used to create scenarios for examining the economic and environmental supply-side effects of policies to a distribution system over a ten-year period. The policies analyzed include a combination of feed-in-tariffs, CO2 tax, and cap-and-trade schemes. The results are discussed in the context of the Ontario market and its Standard Offer Program, implemented on a 32-bus radial distribution system. [ABSTRACT FROM AUTHOR]

Nature-based solutions such as green infrastructure present an opportunity to reduce air pollutant concentrations and greenhouse gas emissions. This paper presents new findings from a controlled field study in Ontario, Canada, evaluating the impact of productive applications of green infrastructure on air pollution and carbon dioxide concentrations across different agricultural morphologies compared to other non-productive applications. This study demonstrates that productive green infrastructure applications are as beneficial as non-productive applications in reducing ozone, nitrogen dioxide, and carbon dioxide concentrations. Nature-based solutions present an opportunity to build climate resilience into agricultural systems through supply-side mitigation and adaptation. The implementation of productive green infrastructure could be a viable agricultural practice to address multiple climate change impacts. [ABSTRACT FROM AUTHOR]

In this paper, we model the greenhouse gas (GHG) intensity of the electric grid in Ontario, Canada, at different temporal resolutions from 2010 through 2018. We developed a stochastic approach to estimate the lifecycle GHG emissions from each type of source of electricity, by assigning uncertainties to critical parameters (carbon dioxide (CO 2), methane and nitrous oxide emissions, and global warming potentials (GWP)), based on variations reported in the literature. The annual mean lifecycle GHG emissions from electricity generated in the province has declined from 175 to 58 g CO 2 e/kWh from 2010 to 2018, considering the GWP time horizon of 100 years. The downward trend is largely associated with the phasing out of coal plants, coupled with the gradually reduced use of natural gas plants, and the increased participation of nuclear and renewables in the mix over the years. We were also able to identify large variations in the lifecycle GHG emissions across months and hours: higher values are generally associated with demand peaks registered in the months of summer and winter, and daily from 5 to 8 p.m. The method employed for the analysis in this paper can serve as a benchmark for other studies on the lifecycle GHG emissions from electricity at various levels (national, provincial, regional, etc.). The Ontario-specific data obtained can serve as a basis for the evaluation of the lifecycle of various activities and sectors within the province. At the corporate level, companies reporting the GHG emissions of their projects and products can improve their estimates by capturing the variations of emissions from electricity generation at the various temporal resolutions. Image 1 • We used hourly generation data to model GHG intensity of electricity in Ontario. • Emissions from electricity declined from 175 to 58 g CO 2 e/kWh from 2010 to 2018. • Higher emissions are due to demand peaks: summer and winter, daily from 5 to 8 p.m. • Hourly GHG intensity varies by a factor of 4–5 within a single year. • Data obtained are useful for LCA practitioners, policy makers and companies. [ABSTRACT FROM AUTHOR]

Canada's mineral reserves can play a very important role in curbing climate change if natural alkaline minerals are used for the process of mineral carbonation. In this work, the potential of using two Canadian natural silicates for accelerated carbonation is experimentally assessed: kimberlite mine tailing (Mg0.846Al0.165Fe0.147Ca0.067SiO3.381) from the Northwest Territories, and mined wollastonite ore (Ca0.609Mg0.132Al0.091Fe0.024SiO2.914) from Ontario. The aim of this work was to evaluate the weathering reactivity and CO2 uptake capacity via carbonation of these two comminuted rocks, both of which are made up of a mixture of alkaline minerals, under process conditions that spanned from milder to intensified. Research questions addressed include: does kimberlite contain a sufficient amount of reactive minerals to act as an effective carbon sink; is dehydroxylation necessary to activate kimberlite, and to what extent does it do this; do secondary phases of wollastonite hinder its reactivity; and can either of these minerals be carbonated without pH buffering, or only weathered? Incubator, slurry, and pressurized slurry methods of accelerated weathering and carbonation were used, and the effect of the process parameters (temperature, solid-to-liquid ration, reaction time, CO2 level, pH buffer) on the CO2 uptake and crystalline carbonates formation is tested. The reacted samples were analyzed by pH test, loss-on-ignition test, calcimeter test, and X-ray diffraction analysis. Results showed that wollastonite ore (rich in fast-weathering CaSiO3) is more suitable for accelerated carbonation than kimberlite tailing (containing slow-weathering hydrated magnesium silicates and aluminosilicates) when only its capability to rapidly form solid carbonates is considered. Incubator and pressurized buffered slurry methods proved to be most effective as under these conditions the precipitation of carbonates was more favorable, while the unbuffered slurry reaction conditions were more akin to accelerated weathering rather than accelerated carbonation. [ABSTRACT FROM AUTHOR]

Background: The effect of rainfall patterns on soil surface CO2 efflux, soil moisture, soil temperature and plant growth was investigated in a grassland ecosystem of northern Ontario, Canada, where climatic change is predicted to introduce new precipitation regimes. Rain shelters were established in a fallow field consisting mainly of Trifolium hybridum L., Trifolium pratense L., and Phleum pratense L. Daytime ambient air temperatures within the shelters increased by an average of 1.9°C similar to predicted future increases in air temperatures for this region. To simulate six precipitation regimes which cover the maximum range to be expected under climate change, a portable irrigation system was designed to modify the frequency of monthly rainfall events with a constant delivery rate of water, while maintaining contemporary average precipitation volumes. Controls consisted of blocks irrigated with frequencies and total monthly precipitation consistent with the 25 year average rainfall for this location. Results: Seasonal soil moisture correlated with soil surface CO2 efflux (R = 0.756, P < 0.001) and above ground plant biomass (R = 0.447, P = 0.029). By reducing irrigation frequency, soil surface CO2 efflux decreased by 80%, P < 0.001, while soil moisture content decreased by 42%, P < 0.001. Conclusions: Manipulating the number of precipitation events and inter-rainfall intervals, while maintaining monthly rainfall averages impacted CO2 efflux and plant growth. Even with monthly rainfall averages that are similar to contemporary monthly precipitation averages, decreasing the number of monthly rainfall events reduced soil surface CO2 efflux and plant growth through soil moisture deficits. Although many have speculated that climate change will increase ecosystem productivity, our results show that a reduction in the number of monthly rainfall events while maintaining monthly averages will limit carbon dynamics. [ABSTRACT FROM AUTHOR]

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