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Abstract: Warm-mix asphalt (WMA) has been gaining popularity in the asphalt industry primarily because of its ability to lower the energy required to blend asphalt mixes, which in turn results in less fuel consumption, slower aging of the asphalt binder and reduced emission of greenhouse gases. This paper evaluates the effects of different quantities of a WMA additive known as Sasobit® on the required heat energy and the amount of CO2 produced to increase the temperature of two aggregates from three sources and one binder from 25 °C to the point of mixing. The results showed that incorporating 1% Sasobit® can potentially reduce the required heat energy and amount of CO2 produced by 2.8% and 3.0%, respectively, for all aggregate types and sources investigated. The paper also presented design charts that enable energy policy makers and engineers to select the appropriate Sasobit® content to produce the most cost effective asphalt mixture with less environmental impact. The design charts show that 1.6% Sasobit® content is the most suitable proportion to be blended into the asphalt binder without compromising pavement resistance against fatigue failure. Two similar aggregates from different sources may exhibit similar specific gravities, but their specific heat capacities can vary widely. These differences have a significant effect on the required heat energy, asphalt production cost and the amount of emissions released into the environment. [ABSTRACT FROM AUTHOR]

The embodied green-house gas (GHG) emissions from the high speed rail (HSR) stations are non-negligible given the considerable scale of modern HSR stations that serve as multifunctional complex. However, the magnitude of the GHG emissions is often underestimated owing to the limited use of reliable inventory data, as well as the simplified modelling that fails to capture the versatile structural/architectural features. To fill the knowledge gap, this paper reviewed the design documents of 117 HSR stations in China to provide more reliable quantification and reveal the factors associated with the GHG emissions. The embodied GHG emissions of the HSR stations were quantified by use of the actual inventory data. Based on the quantification results, a data-driven prediction model was constructed by an optimized general regression neural network (GRNN), which identified a link between the seven design parameters of HSR stations and the embodied GHG emissions. In addition, a cost-benefit analysis was conducted considering the balance between the embodied GHG emissions and serviceability. and discussion The results revealed a non-negligible contribution of HSR stations to the embodied GHG emissions of rail infrastructure. For regional HSR lines, the embodied GHG emissions from the stations could account for over 26% of the whole line. The results also revealed the large stations to be the major source of emissions, for which the embodied emissions per area are 2.84 times of the smaller stations. A Pareto-type distribution exists as the ten largest stations (in station area) contribute nearly 60% of the total emissions of the 117 samples. A canonical correlation analysis (CCA) revealed the station area to be the most prominent factor to the embodied GHG emissions, and the optimized GRNN with CCA-processed input vector make more reliable prediction. The regional HSR lines are subject to higher risk of unsound carbon investment, owing to the low service level of some stations. [Display omitted] • Real inventory data of 117 sample HSR stations in China are used for quantification. • Large stations are responsible for more embodied emissions per station area. • The top 10 largest stations contribute about 60% of the samples' total embodied GHG emissions. • Station area is the most prominent factor affecting the embodied GHG emissions. • Stations of regional HSR lines are more vulnerable to unsound carbon investment due to low service level. [ABSTRACT FROM AUTHOR]

Carbon emission from municipal solid waste (MSW) treatment is one of the anthropogenic sources to cause climate change, which accounts for 3–5% of global greenhouse gas emissions according to the report of the United Nations Environment Programme (UNEP). At the same time, the gases and liquid discharged from MSW treatment can also cause other environmental impacts, such as climate change, photochemical ozone synthesis, and acidification, especially in huge city with huge population as Beijing, China. This paper proposed an eco-efficiency analysis method, which aimed to yield maximum overall environmental improvement per unit investment cost during its life cycle processing. This method took the overall reduction in the environmental impact of MSW treatment using cost-effective techniques as the objective to optimize waste disposal systems. The separation ratio during MSW collection and the proportion of techniques used for treatment were the major indicators for optimization measures. For Beijing, an increase in the waste separation ratio during collection proved to be the most effective measure, with an eco-efficiency score of 0.144. Adjustment of the proportion of treatment techniques used was less eco-efficient, with an increase in the proportion of composting being the most effective approach. Based on real needs, the objective should be to reduce the proportion of landfills used and increase the amount of composting and incineration. This optimization measure had the lowest cost and an eco-efficiency score of 0.0461, which is 60% higher than that for the measure with the lowest eco-efficiency. [ABSTRACT FROM AUTHOR]

Abstract: As the dominant producers of industrial greenhouse gas (GHG) emissions, companies have a vital role to play in efforts to mitigate global warming. Focussing on scope 1 and 2 emissions alone can distort a firm’s GHG estimates as scope 3 emissions often constitute a significant part of its overall GHG footprint, up to seventy-five percent in many firms. Lack of knowledge of scope 3 emissions inhibits a firm’s ability to pursue the most cost-effective carbon mitigation strategies. This paper investigates the methods and data currently used by Australian organizations to assess their scope 3 emissions. The exploratory study found a wide discrepancy in the number of emission sources reported. In addition there was a general lack of rigour in determining which emission sources to include. This suggests that more comprehensive guidance on relevant emission sources by industry or sector would likely improve the completeness and relevance of inventories in accordance with The Greenhouse Gas Protocol. [Copyright &y& Elsevier]