Energy prices and CO2 emission allowance prices : a quantile regression approach

We use a quantile regression framework to investigate the impact of changes in crude oil prices, natural gas prices, coal prices, and electricity prices on the distribution of the CO2 emission allowance prices in the United States. We find that: (i) an increase in the crude oil price generates a substantial drop in the carbon prices when the latter is very high; (ii) changes in the natural gas prices have a negative effect on the carbon prices when they are very low but have a positive effect when they are quite high; (iii) the impact of the changes in the electricity prices on the carbon prices can be positive in the right tail of the distribution; and (iv) the coal prices exert a negative effect on the carbon prices.COMPETE, QREN, FEDER, Fundação para a Ciência e a Tecnologia (FCT

What explains the short-term dynamics of the prices of CO2 emissions?

Using the vector auto-regression (VAR) and the vector error-correction Models (VECM), this paper analyzes the short-term dynamics of the prices of CO2 emissions in response to changes in the prices of oil, coal, natural gas, electricity and carbon emission allowances. The results show that: (i) a positive shock to the crude oil prices has a negative effect on the CO2 allowance prices; (ii) an unexpected increase in the natural gas prices raises the price of CO2 emissions; (iii) a positive shock to the prices of the fuel of choice, coal, has virtually no significant impact on the CO2 prices; (iv) there is a clear positive effect of the coal prices on the CO2 allowance prices when the electricity prices are excluded from the VAR system; and (v) a positive shock to the electricity prices reduces the price of the CO2 allowances. We also find that the energy price shocks have a persistent impact on the CO2 allowance prices, with the largest effect occurring six months after a shock strikes. The effect is particularly strong in the case of the natural gas price shocks. Additionally, we estimate that it takes between 7.3 and 9.6 months to halve the gap between the actual and the equilibrium prices of the CO2 allowances, i.e., to erase any price over- or undervaluations after a shock strikes. Finally, the empirical findings suggest an important degree of substitution between the three primary sources of energy (i.e., crude oil, natural gas and coal), particularly, when electricity prices are excluded from the VAR system.COMPETE, QREN, FEDER, Fundação para a Ciência e a Tecnologia (FCT

Asymmetric and nonlinear pass-through of energy prices to CO2 emission allowance prices

We use the recently developed nonlinear autoregressive distributed lags (NARDL) model to examine the pass-through of changes in crude oil prices, natural gas prices, coal prices and electricity prices to the CO2 emission allowance prices. This approach allows one to simultaneously test the short- and long-run nonlinearities through the positive and negative partial sum decompositions of the predetermined explanatory variables. It also offers the possibility to quantify the respective responses of the CO2 emission prices to positive and negative shocks to the prices of their determinants from the asymmetric dynamic multipliers. We find that: (i) the crude oil prices have a long-run negative and asymmetric effect on the CO2 allowance prices; (ii) the falls in the coal prices have a stronger impact on the carbon prices in the short-run than the increases; (iii) the natural gas prices and electricity prices have a symmetric effect on the carbon prices, but this effect is negative for the former and positive for the latter. Policy implications are provided.COMPETE, QREN, FEDER, Fundação para a Ciência e a Tecnologia (FCT

Willingness to pay for residential PV: reconciling gaps between acceptance and adoption

Photovoltaic (PV) has recorded an impressive development in the last years. The increasing economic potential and further technological improvement will continue to reduce the cost of PV. However, it is not yet well adopted by household customers. Adversely, there is lacking empirical evidence for understanding residential PV adoption behaviour, which this study addresses with empirical research. Although a variety of models can be used to explain social acceptance (SA) and willingness to pay (WTP) for renewable energy, they overlook the connection between SA and WTP in the final purchase decision of a decision-maker. Based on a survey of both SA and WTP in the same observation sample of 2039 Vietnamese residents, this study introduces well-established models with a new linking psychological and economic aspects to measure multiple outcomes involving residential PV behaviours to testing hypotheses with no precedent in the literature. The theoretical and integrative moderated mediation models help to understand residential PV behaviour and suggest solutions for development by revealing how different factors affect SA and WTP in different manners. Environmental interest reveals the predictive power within the SA and WTP behaviour models. Meanwhile, PV knowledge drives SA, but not WTP in Vietnam. Attitude and Perceived behavioural control not only impact SA and WTP directly but also mediate the effect of Environmental interest and SA and WTP. Age & Marital status & Children and Place of residence are important covariates that drive in the SA and WTP models, respectively. Lastly, Income is the covariate in the SA model, but the moderator in the WTP model. In practical implications, this study provides evidence that residential PV is a lifestyle product rather than an economical product, but it is not considered as an essential good for household customers. Thereby, suggestions are given to policymakers and stakeholders to promote market development

Evaluation of a novel antibody to define histone 3.3 G34R mutant brain tumours

Missense somatic mutations affecting histone H3.1 and H3.3 proteins are now accepted as the hallmark of paediatric diffuse intrinsic pontine gliomas (DIPG), non-brain stem paediatric high grade gliomas (pHGG) as well as a subset of adult glioblastoma multiforme (GBM). Different mutations give rise to one of three amino acid substitutions at two critical positions within the histone tails, K27M, G34R/V. Several studies have highlighted gene expression and epigenetic changes associated with histone H3 mutations; however their precise roles in tumourigenesis remain incompletely understood. Determining how such amino acid substitutions in a protein affect its properties can be challenging because of difficulties in detecting and tracking mutant proteins within cells and tissues. Here we describe a strategy for the generation of antibodies to discriminate G34R and G34V mutant histone H3 proteins from their wild-type counterparts. Antibodies were validated by western blotting and immunocytochemistry, using recombinant H3.3 proteins and paediatric GBM cell lines. The H3-G34R antibody demonstrated a high degree of selectivity towards its target sequence. Accordingly, immunostaining on a cohort of 22 formalin-fixed paraffin embedded tumours with a previously known H3.3 G34R mutation status, detected successfully the corresponding mutant protein in 11/11 G34R cases. Since there was a high concordance between genotype and immunohistochemical analysis of G34R mutant tumour samples, we analysed a series of tissue microarrays (TMAs) to assess the specificity of the antibody in a range of paediatric brain tumours, and noted immunoreactivity in 2/634 cases. Importantly, we describe the generation and validation of highly specific antibodies for G34 mutations. Overall our work adds to an extremely valuable portfolio of antibodies, not only for histopathologic detection of tumour-associated mutant histone sequences, but also facilitating the study of spatial/anatomical aspects of tumour formation and the identification of downstream targets and pathways in malignant glioma progression

Harnessing artificial intelligence (AI) to increase wellbeing for all: The case for a new technology diplomacy

The field of artificial intelligence (AI) is experiencing a period of intense progress due to the consolidation of several key technological enablers. AI is already deployed widely and has a high impact on work and daily life activities. The continuation of this process will likely contribute to deep economic and social changes. To realise the tremendous benefits of AI while mitigating undesirable effects will require enlightened responses by many stakeholders. Varying national institutional, economic, political, and cultural conditions will influence how AI will affect convenience, efficiency, personalisation, privacy protection, and surveillance of citizens. Many expect that the winners of the AI development race will dominate the coming decades economically and geopolitically, potentially exacerbating tensions between countries. Moreover, nations are under pressure to protect their citizens and their interests—and even their own political stability—in the face of possible malicious or biased uses of AI. On the one hand, these different stressors and emphases in AI development and deployment among nations risk a fragmentation between world regions that threatens technology evolution and collaboration. On the other hand, some level of differentiation will likely enrich the global AI ecosystem in ways that stimulate innovation and introduce competitive checks and balances through the decentralisation of AI development. International cooperation, typically orchestrated by intergovernmental and non-governmental organisations, private sector initiatives, and by academic researchers, has improved common welfare and avoided undesirable outcomes in other technology areas. Because AI will most likely have more fundamental effects on our lives than other recent technologies, stronger forms of cooperation that address broader policy and governance challenges in addition to regulatory and technological issues may be needed. At a time of great challenges among nations, international policy coordination remains a necessary instrument to tackle the ethical, cultural, economic, and political repercussions of AI. We propose to advance the emerging concept of technology diplomacy to facilitate the global alignment of AI policy and governance and create a vibrant AI innovation system. We argue that the prevention of malicious uses of AI and the enhancement of human welfare create strong common interests across jurisdictions that require sustained efforts to develop better, mutually beneficial approaches. We hope that new technology diplomacy will facilitate the dialogues necessary to help all interested parties develop a shared understanding and coordinate efforts to utilise AI for the benefit of humanity, a task whose difficulty should not be underestimated

Optical studies of gap, hopping energies and the Anderson-Hubbard parameter in the zigzag-chain compound SrCuO2

We have investigated the electronic structure of the zigzag ladder (chain) compound SrCuO2 combining polarized optical absorption, reflection, photoreflectance and pseudo-dielectric function measurements with the model calculations. These measurements yield an energy gap of 1.42 eV (1.77 eV) at 300 K along (perpendicular) to the Cu-O chains. We have found that the lowest energy gap, the correlation gap, is temperature independent. The electronic structure of this oxide is calculated using both the local-spin-density-approximation with gradient correction method, and the tight-binding theory for the correlated electrons. The calculated density of electronic states for non-correlated and correlated electrons shows quasi-one-dimensional character. The correlation gap values of 1.42 eV (indirect transition) and 1.88 eV (direct transition) have been calculated with the electron hopping parameters t = 0.30 eV (along a chain), t_yz = 0.12 eV (between chains) and the Anderson-Hubbard repulsion on copper sites U= 2.0 eV. We concluded that SrCuO_2 belongs to the correlated-gap insulators.Comment: 24 pages, 8 figures, to be published in Phys.Rev.