• Energy Research
• 13. Climate action close
• 11. Sustainability close
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A stochastic mixed integer linear optimization scheduling model minimizing system operation costs and treating load and wind power production as stochastic inputs is presented. The schedules are updated in a rolling manner as more up-to-date information becomes available. This is a fundamental change relative to day-ahead unit commitment approaches. The need for reserves dependent on forecast horizon and share of wind power has been estimated with a statistical model combining load and wind power forecast errors with scenarios of forced outages. The model is used to study operational impacts of future high wind penetrations for the island of Ireland. Results show that at least 6000 MW of wind (34% of energy demand) can be integrated into the island of Ireland without significant curtailment and reliability problems.

While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.

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Many integrated assessment models (IAMs) rely on the availability and extensive use of biomass energy with carbon capture and storage (BECCS) to deliver emissions scenarios consistent with limiting climate change to below 2 °C average temperature rise. BECCS has the potential to remove carbon dioxide (CO _2 ) from the atmosphere, delivering ‘negative emissions’. The deployment of BECCS at the scale assumed in IAM scenarios is highly uncertain: biomass energy is commonly used but not at such a scale, and CCS technologies have been demonstrated but not commercially established. Here we present the results of an expert elicitation process that explores the explicit and implicit assumptions underpinning the feasibility of BECCS in IAM scenarios. Our results show that the assumptions are considered realistic regarding technical aspects of CCS but unrealistic regarding the extent of bioenergy deployment, and development of adequate societal support and governance structures for BECCS. The results highlight concerns about the assumed magnitude of carbon dioxide removal achieved across a full BECCS supply chain, with the greatest uncertainty in bioenergy production. Unrealistically optimistic assumptions regarding the future availability of BECCS in IAM scenarios could lead to the overshoot of critical warming limits and have significant impacts on near-term mitigation options.

Abstract Cities are the major contributors to energy consumption and CO2 emissions, as well as being leading innovators and implementers of policy measures in climate change mitigation. Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is an agglomeration of cities put forward by China to strengthen international cooperation among “Belt and Road” countries and promote low-carbon, inclusive, coordinated and sustainable development. Few studies have discussed the emission characteristics of GBA cities. This study, for the first time, compiles emission inventories of 11 GBA cities and their surroundings based on IPCC territorial emission accounting approach, which are consistent and comparable with the national and provincial inventories. Results show that (a) total emissions increased from 426 Mt in 2000 to 610 Mt in 2016, while emissions of GBA cities increased rapidly by 6.9% over 2000–2011 and peaked in 2014 (334 Mt); (b) raw coal and diesel oil are the top two emitters by energy type, while energy production sector and tertiary industry are the top two largest sectors; (c) GBA cities take the lead in low-carbon development, emitted 4% of total national emissions and contributed 13% of national GDP with less than a third of national emission intensities and less than three-quarters of national per capita emissions; (d) Macao, Shenzhen and Hong Kong have the top three lowest emission intensity in the country; (e) most of GBA cities are experiencing the shift from an industrial economy to a service economy, while Hong Kong, Shenzhen, Foshan and Huizhou reached their peak emissions and Guangzhou, Dongguan and Jiangmen remained decreasing emission tendencies; (g) for those coal-dominate or energy-production cities (i.e. Zhuhai, Zhongshan, Zhaoqing, Maoming, Yangjiang, Shanwei, Shaoguan and Zhanjiang) in mid-term industrialization, total emissions experienced soaring increases. The emission inventories provide robust, self-consistent, transparent and comparable data support for identifying spatial–temporal emission characteristics, developing low-carbon policies, monitoring mitigation progress in GBA cities as well as further emissions-related studies at a city-level. The low-carbon roadmaps designed for GBA cities and their surroundings also provide a benchmark for other developing countries/cities to adapting changing climate and achieve sustainable development.

AbstractEnvironment respect makes both the Legislator ever more careful to define urgent emissions limits than each one responsible to find the best technological and behavioral solutions. The works includes the results of combustion simulations in a MGT burner. The purpose is to verify combustion performances of some between classic and renewable fuels, with a view to design choices. The approaches: a “Laminar Flamelet” model and, especially to verify simply kinetic influences, a partially premixed model.

Significance Although the response of the Plant Kingdom to climate change is acknowledged as one of the fundamental feedback mechanisms of environmental changes on the Earth, until now, the response of plant species to in situ climate warming has been described at the level of a few fixed plant functional types (i.e. grasses, forbs, shrubs etc.). This approach is very coarse and inflexible. Here, we show that plant functional traits (i.e., plant features) can be used as predictors of vegetation response to climate warming. This finding enlarges possibilities for forecasting ecosystem responses to climate change.