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Many governments have begun to adopt aggressive targets for electric vehicles. However, studies of the drivers of electric vehicle (EV) adoption are scarce. Social media interactions can provide a new data-driven vantage point to explore such drivers. This study uses data from 36,000 public posts on Facebook to investigate intersectionality in EV-communication as per the Political, Economic, Social, Technological, Legal and Environmental (PESTLE) categories. A computational social science methodology was adopted using a mixed-method application of social network analysis and machine learning-based topic modelling through Latent Dirichlet Allocation algorithm on a 600,000-text corpus extracted from the Facebook posts. Results showed that political, economic, and legal posts had dense clusters around the technology policy of EV, the institutional discourse of electrification of the federal vehicle fleet, and tax and credit framework politics. The environmental and social dimensions had a higher discourse for social justice, clean air, and better health and well-being. A market shift towards EV as a service industry was observed in the technology and economics-related posts. These findings can help policymakers, and planners design contextualised energy policy for influencing EV adoption in the U.S. and other countries. ; This study is in parts supported by Bill & Melinda Gates Foundation under the grant number [OPP1144] through the Gates Cambridge Scholarship; Energy Transition Small Grant 2020 by the Isaac Newton Trust; and the Winter Fellowship – 2020 by the Michigan Conservative Energy Forum (MiCEF), awarded to RD at the University of Cambridge.

© 2020 Elsevier Ltd Rapid socio-economic development and urbanization have resulted in serious deterioration in air-quality in many world cities, including Beijing, China. This study attempts to examine the effectiveness of air pollution control regulations implemented in Beijing during 2008–2019 through a data-driven regulatory intervention analysis. Our proposed Bayesian deep learning model utilizes proxy data including Aerosol Optical Depth (AOD) and meteorology as well as socio-economic data, while accounting for confounding effects via propensity score estimation. Our results show that air pollution control regulatory measures implemented in China and Beijing during 2008–2019 reduced PM2.5 pollution in Beijing by 11 % on average. After the introduction of Action Plan for Clean Air in China and Beijing in late 2013, as compared to the hypothetical PM2.5 concentration (without any regulatory interventions), the estimated PM2.5 reduction increased dramatically from 15 % in 2015 to 44 % in 2018. Our results suggest that Beijing's air quality has improved gradually over the past decade, though the annual PM2.5 pollution still exceeds the WHO threshold. In this regard, the air pollution control regulations introduced in Beijing and China tend to become more effective after 2015, suggesting a 2-year time lag before the stringent air pollution control regulations starting from 2013 takes any strong positive effects. Moreover, as compared to the air pollution control regulations introduced before 2013, newly introduced policy-making governance, which couples the policy-makings of the local jurisdictions with that of the central government, and the new policy measures that tackle the vested interests of the local stakeholders in Beijing and its nearby cities, alongside with the stringent local and national air pollution control regulations and plans, should help reduce air pollution and promote healthy living in Beijing over the longer term. ; This research is supported in part by the General Research Fund of the Research Grants Council of Hong Kong, under Grant No. 17620920.

We explore the relationship between political ideology and public attitudes towards a range of energy technologies (namely: biomass, coal, shale (or coal seam) gas, natural gas, carbon capture and storage, hydroelectricity, nuclear, solar thermal and photovoltaic, wave and wind energy). Our empirical analysis draws on the results of two similar nationally representative public surveys that were conducted in Australia and the UK in 2017. Our findings suggest that political ideology is significantly associated with public attitudes towards energy technologies. Specifically, supporters of left-leaning political parties tend to be more supportive of renewables and opposed to biomass, shale (coal seam) gas, nuclear and fossil fuel energies compared to right-leaning individuals. We also create an alternative ideological proxy to capture the relative emphasis that parties place on the environment and economy and find that supporters of environmentally focused parties generally express similar energy preferences to left-leaning individuals and economy-focused respondents align with right-leaning attitudes. Our findings are robust to different choices of proxy.

Greenhouse gas removal (GGR) raises many cultural, ethical, legal, social, and political issues, yet in the growing area of GGR research, humanities and social sciences (HASS) research is often marginalized, constrained and depoliticised. This global dynamic is illustrated by an analysis of the UK GGR research programme. This dynamic matters for the knowledge produced and for its users. Without HASS contributions, too narrow a range of perspectives, futures and issues will be considered, undermining or overpromising the prospects for the responsible development of GGR (and threatening worse side-effects), and limiting our understanding of why and how policy demands GGR solutions in the first place. In response, we present policy principles for bringing HASS fully into GGR research, organized around three themes: (1) HASS-led GGR research, (2) Opening up GGR futures, and (3) The politics of GGR futures. ; We acknowledge funding from the UK GGR programme, under several specific grants: NE/P019838/1, NE/P019900/1, NE/P019951/1, NE/P019668/1, and NE/P01982X/1.

Greenhouse gas removal (GGR) raises many cultural, ethical, legal, social, and political issues, yet in the growing area of GGR research, humanities and social sciences (HASS) research is often marginalized, constrained and depoliticised. This global dynamic is illustrated by an analysis of the UK GGR research programme. This dynamic matters for the knowledge produced and for its users. Without HASS contributions, too narrow a range of perspectives, futures and issues will be considered, undermining or overpromising the prospects for the responsible development of GGR (and threatening worse side-effects), and limiting our understanding of why and how policy demands GGR solutions in the first place. In response, we present policy principles for bringing HASS fully into GGR research, organized around three themes: (1) HASS-led GGR research, (2) Opening up GGR futures, and (3) The politics of GGR futures.

Greenhouse gas removal (GGR) raises many cultural, ethical, legal, social, and political issues, yet in the growing area of GGR research, humanities and social sciences (HASS) research is often marginalized, constrained and depoliticised. This global dynamic is illustrated by an analysis of the UK GGR research programme. This dynamic matters for the knowledge produced and for its users. Without HASS contributions, too narrow a range of perspectives, futures and issues will be considered, undermining or overpromising the prospects for the responsible development of GGR (and threatening worse side-effects), and limiting our understanding of why and how policy demands GGR solutions in the first place. In response, we present policy principles for bringing HASS fully into GGR research, organized around three themes: (1) HASS-led GGR research, (2) Opening up GGR futures, and (3) The politics of GGR futures.

Climate change mitigation scenarios that meet the Paris Agreement's objective of limiting global warming usually assume an important role for carbon dioxide removal and negative emissions technologies. Direct air capture (DAC) is a carbon dioxide removal technology which separates CO2 directly from the air using an engineered system. DAC can therefore be used alongside other negative emissions technologies, in principle, to mitigate CO2 emissions from a wide variety of sources, including those that are mobile and dispersed. The ultimate fate of the CO2, whether it is stored, reused, or utilised, along with choices related to the energy and materials inputs for a DAC process, dictates whether or not the overall process results in negative emissions. In recent years, DAC has undergone significant technical development, with commercial entities now operating in the market and prospects for significant upscale. Here we review the state-of-the-art to provide clear research challenges across the process technology, techno-economic and socio-political domains. ; European Union funding: 754382

Carbon dioxide removal options have been identified as key to achieving the climate change target laid out in the 2015 Paris Agreement. Bioenergy with carbon capture and storage (BECCS) is particularly attractive because it is capable of providing negative emissions and a reliable energy source. We here explore the complexity of the infrastructures involved in realizing a large-scale system and the sequestration potential of bioenergy in Europe. Starting from a minimum cost scenario, we develop cost-optimal solutions that minimize the environmental impact of the overall BECCS supply chain according to the life cycle impact assessment methodology. Our analysis is based on cooperation among the 28 countries of the European Union (as of 2018) to achieve a global carbon removal target. Given regional biomass and marginal land availability inputs and a carbon removal target of 0.61 GtCO2/year, the minimum-cost scenario provides negative emissions, with an overall cost of 140 Eur/MWh of bioelectricity generated or 117 Eur/tCO2 removed, without considering revenues from selling the electricity produced. On the other hand, minimizing environmental impacts increased costs by 45% relative to the first scenario, but further improved the environmental performance by 23%.