Teach Me To Smile

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The Flux Ratio Method for Determining the Dust Attenuation of Starburst Galaxies

The presence of dust in starburst galaxies complicates the study of their stellar populations as the dust's effects are similar to those associated with changes in the galaxies' stellar age and metallicity. This degeneracy can be overcome for starburst galaxies if UV/optical/near-infrared observations are combined with far-infrared observations. We present the calibration of the flux ratio method for calculating the dust attenuation at a particular wavelength, Att(\lambda), based on the measurement of F(IR)/F(\lambda) flux ratio. Our calibration is based on spectral energy distributions (SEDs) from the PEGASE stellar evolutionary synthesis model and the effects of dust (absorption and scattering) as calculated from our Monte Carlo radiative transfer model. We tested the attenuations predicted from this method for the Balmer emission lines of a sample starburst galaxies against those calculated using radio observations and found good agreement. The UV attenuation curves for a handful of starburst galaxies were calculated using the flux ratio method, and they compare favorably with past work. The relationship between Att(\lambda) and F(IR)/F(\lambda) is almost completely independent of the assumed dust properties (grain type, distribution, and clumpiness). For the UV, the relationship is also independent of the assumed stellar properties (age, metallicity, etc) accept for the case of very old burst populations. However at longer wavelengths, the relationship is dependent on the assumed stellar properties.Comment: accepted by the ApJ, 18 pages, color figures, b/w version at http://mips.as.arizona.edu/~kgordon/papers/fr_method.htm

An examination of motivation factors driving investor behaviours towards socially responsible community energy initiatives

Community energy initiatives play a significant role at the grassroots level in the transition to Renewable Energy Communities and a low-carbon economy. However, these initiatives are hampered by multiple barriers at the market, institutional, organisational, and individual level. Funding cuts of state-supported feed-in tariff (FiT) policy in major markets such as Germany, Japan, China and the additional capping of the number of new installations that could be accredited under the FiT scheme in the UK. In light of these market changes and the need to accelerate the development and growth through the creation of new and/or complementary future community energy models consisting of private investors, a detailed understanding of the dynamics of community energy investor characteristics and socio-psychological motivations is increasingly important. First, a review is conducted including the theories that underpin and explain the factors that affect investor behaviour, after which a conceptual framework to examine investor behaviours towards socially responsible community energy initiatives is developed. The framework is used as the basis to construct and administer a survey involving sampling of 295 UK investors in community energy initiatives and the subsequent statistical analysis of the survey data and discussions of the findings. The results first capture the differences among investors with differingregional affect and investment behaviours. The study also provides the needed insight into better understanding the dynamics of investor characteristics and motivations of community energy initiatives. Results also indicate that investors are predominantly ethically-oriented, particularly toward environmental concerns. Additionally, community and social factors also appear to play significant roles in investor participation while financial orientation is least dominant

A data envelopment analysis based evaluation of sustainable energy generation portfolio scenarios

Generating secure, affordable, and clean energy requires careful evaluation of the costs and associated risks of different energy generation sources. Portfolio optimisation models are commonly used in this regard to help diversify risks associated with generation sources. In recent times, energy policies often require the consideration of the environmental and social effects of such activity. Consequently, sustainability has become a key factor in making energy mix planning decisions. To incorporate sustainability considerations in energy mix planning, the conventional approach has been to add indicators for environmental and social costs to the total generation cost for each available technology in a portfolio optimisation model. However, this approach to developing a sustainable generation mix may not effectively address all dimensions of sustainability. In most cases, the economic dimension is prioritised over social and environmental factors. We examine how various aggregation methods impact the preference among the sources and the optimal portfolio mix and propose aggregation methods that effectively incorporate all sustainability dimensions. We observed that technology ranking based on multiplicative, pairwise interaction, and multilinear aggregation options aligns better with our sustainability goals than additive aggregation. By adopting these methods of aggregation, we were able to include more renewable and clean energy sources in our optimal portfolios

A data envelopment analysis based evaluation of sustainable energy generation portfolio scenarios

Generating secure, affordable, and clean energy requires careful evaluation of the costs and associated risks of different energy generation sources. Portfolio optimisation models are commonly used in this regard to help diversify risks associated with generation sources. In recent times, energy policies often require the consideration of the environmental and social effects of such activity. Consequently, sustainability has become a key factor in making energy mix planning decisions. To incorporate sustainability considerations in energy mix planning, the conventional approach has been to add indicators for environmental and social costs to the total generation cost for each available technology in a portfolio optimisation model. However, this approach to developing a sustainable generation mix may not effectively address all dimensions of sustainability. In most cases, the economic dimension is prioritised over social and environmental factors. We examine how various aggregation methods impact the preference among the sources and the optimal portfolio mix and propose aggregation methods that effectively incorporate all sustainability dimensions. We observed that technology ranking based on multiplicative, pairwise interaction, and multilinear aggregation options aligns better with our sustainability goals than additive aggregation. By adopting these methods of aggregation, we were able to include more renewable and clean energy sources in our optimal portfolios

An examination of motivation factors driving investor behaviours towards socially responsible community energy initiatives

Community energy initiatives play a significant role at the grassroots level in the transition to Renewable Energy Communities and a low-carbon economy. However, these initiatives are hampered by multiple barriers at the market, institutional, organisational, and individual level. Funding cuts of state-supported feed-in tariff (FiT) policy in major markets such as Germany, Japan, China and the additional capping of the number of new installations that could be accredited under the FiT scheme in the UK. In light of these market changes and the need to accelerate the development and growth through the creation of new and/or complementary future community energy models consisting of private investors, a detailed understanding of the dynamics of community energy investor characteristics and socio-psychological motivations is increasingly important. First, a review is conducted including the theories that underpin and explain the factors that affect investor behaviour, after which a conceptual framework to examine investor behaviours towards socially responsible community energy initiatives is developed. The framework is used as the basis to construct and administer a survey involving sampling of 295 UK investors in community energy initiatives and the subsequent statistical analysis of the survey data and discussions of the findings. The results first capture the differences among investors with differingregional affect and investment behaviours. The study also provides the needed insight into better understanding the dynamics of investor characteristics and motivations of community energy initiatives. Results also indicate that investors are predominantly ethically-oriented, particularly toward environmental concerns. Additionally, community and social factors also appear to play significant roles in investor participation while financial orientation is least dominant