Professor Myles Allen CBE FRS

Abstract:

The uncertainties over the effects of aviation non-CO2 emissions on climate and air quality are assessed in the context of potential mitigation measures for liquid hydrocarbon fuels. Aviation non-CO2 emissions that affect climate include nitrogen oxides (NOx), aerosol particles (soot and sulphur-based), and water vapour. Water vapour and aerosols have small direct radiative effects but are also involved in the formation of contrails and contrail cirrus, currently, the largest non-CO2 effect on climate. These non-CO2 effects on climate are quantified with low confidence, compared to that of CO2, which is quantified with high confidence. The sign of the NOx radiative effects may change from positive to negative. The effects of soot and sulphur emissions on cloudiness are very poorly understood and studies indicate forcings that range from large negative through to small positive. NOx and soot emissions can be reduced through changes in combustion technology but have tradeoffs with each other and CO2. Soot can also be reduced through reduced aromatic content of fuels. In all cases, there are complex choices to be made because of tradeoffs between species, and CO2. Contrail cirrus and soot aerosol–cloud interactions potentially have opposing signs but are both related to soot emissions (at present) and need to be considered together in mitigation strategies. Because of the uncertainties and tradeoffs involved, it is problematic to recommend definitive courses of action on aviation non-CO2 emissions since they may be of limited effect or have unintended consequences. Aviation's non-CO2 effects on climate are short-term, as opposed to those of CO2, which last millennia. If aviation is to contribute towards restricting anthropogenic surface warming to 1.5 or 2 °C then reduction of emissions of CO2 from fossil fuels remains the top priority. In terms of air quality, the situation is more straightforward with emissions standards being set by the International Civil Aviation Organization for NOx and non-volatile particulate matter (and other minor species), which need to be complied with

Abstract:

This study aims to improve our understanding of the response of precipitation to forcings by proposing a physically-based equation that resolves simulated precipitation based on the atmospheric energy budget. The equation considers the balance between latent heat release by precipitation and the sum of the slow response by tropospheric temperature changes and the fast response by abrupt radiative forcing (RF) changes. The equation is tuned with three parameters for each climate model and then adequately reproduces time-varying precipitation. By decomposing the equation, we highlight the slow response as the largest contributor to forcing-driven responses and uncertainty sizes in simulations. The second largest one to uncertainty is the fast-RF response from aerosols or greenhouse gases (GHG), depending on the low or highest Coupled Model Intercomparison Projection 6 future scenarios. The likely range of precipitation change at specific warming levels under GHG removal (GGR) and solar radiation management (SRM) mitigation plans is evaluated by a simple model optimizing the relationship between temperature and decomposed contributions from multi-simulations under three scenarios. The results indicate that GGR has more severe effects from aerosols than GHG for a 1.5 K warming, resulting in 0.91%–1.62% increases in precipitation. In contrast, SRM pathways project much drier conditions than GGR results due to the tropospheric cooling and remaining anthropogenic radiative heating. Overall, the proposed physically-based equation, the decomposition analysis, and our simple model provide valuable insights into the uncertainties under different forcings and mitigation pathways, highlighting the importance of slow and fast responses to human-induced forcings in shaping future precipitation changes.

Abstract:

The vast majority of agri-food climate-based sustainability analyses use global warming potential (GWP₁₀₀) as an impact assessment, usually in isolation; however, in recent years, discussions have criticised the 'across-the-board' application of GWP₁₀₀ in Life Cycle Assessments (LCAs), particularly of food systems which generate large amounts of methane (CH₄) and considered whether reporting additional and/or alternative metrics may be more applicable to certain circumstances or research questions (e.g. Global Temperature Change Potential (GTP)). This paper reports a largescale sensitivity analysis using a pasture-based beef production system (a high producer of CH₄ emissions) as an exemplar to compare various climatatic impact assessments: CO₂-equivalents using GWP₁₀₀ and GTP₁₀₀, and 'CO₂-warming-equivalents' using 'GWP Star', or GWP*. The inventory for this system was compiled using data from the UK Research and Innovation National Capability, the North Wyke Farm Platform, in Devon, SW England. LCAs can have an important bearing on: (i) policymakers' decisions; (ii) farmer management decisions; (iii) consumers' purchasing habits; and (iv) wider perceptions of whether certain activities can be considered 'sustainable' or not; it is, therefore, the responsibility of LCA practitioners and scientists to ensure that subjective decisions are tested as robustly as possible through appropriate sensitivity and uncertainty analyses. We demonstrate herein that the choice of climate impact assessment has dramatic effects on interpretation, with GWP₁₀₀ and GTP₁₀₀ producing substantially different results due to their different treatments of CH₄ in the context of carbon dioxide (CO₂) equivalents. Given its dynamic nature and previously proven strong correspondence with climate models, out of the three assessments covered, GWP* provides the most complete coverage of the temporal evolution of temperature change for different greenhouse gas emissions. We extend previous discussions on the limitations of static emission metrics and encourage LCA practitioners to consider due care and attention where additional information or dynamic approaches may prove superior, scientifically speaking, particularly in cases of decision support.

Abstract:

<jats:p>Abstract. Intergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC), including the first global stocktake under the Paris Agreement that will conclude at COP28 in December 2023. Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, surface temperature changes, the Earth's energy imbalance, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open data, open science approach, is to make annually updated reliable global climate indicators available in the public domain (https://doi.org/10.5281/zenodo.8000192, Smith et al., 2023a). As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that human-induced warming reached 1.14 [0.9 to 1.4] ∘C averaged over the 2013–2022 decade and 1.26 [1.0 to 1.6] ∘C in 2022. Over the 2013–2022 period, human-induced warming has been increasing at an unprecedented rate of over 0.2 ∘C per decade. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 54 ± 5.3 GtCO2e over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that increases in greenhouse gas emissions have slowed, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for human influence on climate. </jats:p>