B y the time the World Health Organization declared COVID-19 (scientifically referred to as the severe acute respiratory syndrome-coronavirus 2 or SARS-CoV-2) a pandemic on 11 March 2020, the virus had already spread from China to other Asian countries, Europe and the United States. As of 5 July 2020, cases have been identified in 188 countries or regions 1. This has led to unprecedented enforced and voluntary restrictions on travel and work. This in turn has led to reductions of both GHG emissions and air pollutants 2-4. Analysis of mobility data from Google 5 and Apple 6 shows that mobility declined by 10% or more during April 2020 in all but one of the 125 nations tracked. Mobility declined by 80% in five or more nations (Supplementary Fig. 1). Associated declines in air pollution have been observed from satellite data and from local ground-based observations 7,8. The large pollution declines are expected to be temporary as pollution levels are already returning to near-normal in parts of Asia 9,10. Here we build an estimate of emission changes in GHGs and air pollution due to the COVID-19 global restrictions during the period February-June 2020 and project these into the future. These emission changes are then used to make a prediction of the resultant global temperature response. We examine the temperature response of a direct recovery to pre-COVID-19 national policies and emission levels, and also explore responses where the economic recovery to COVID-19 is driven by either a green stimulus package or an increase in fossil fuel use. Emission trends Bottom-up emission-trend analyses have traditionally relied on laborious collection of various energy-industry-related indicators and statistics from multiple sources 11. The unprecedented recent access to global mobility data from Google and Apple gives a unique opportunity to compare trends across many countries with a consistent approach. We use these data to develop a new method of emission-trend analysis. The advantage over previous approaches is the possibility of near-real-time analysis, national granularity and a systematic consistent approach across nations and over time. The disadvantages are the loss of a direct connection between energy and emissions and the need to make assumptions about these relationships. There are also disadvantages over the short time history of the mobility data and opacity from the data providers around their detailed methodologies and uncertainties. Here we make a simple set of assumptions to deduce estimates of emissions change from the mobility data and test the estimates extensively against the approach of Le Quéré et al. 3. Google and Apple mobility changes and the Le Quéré et al. 3 data all indicate that >50% of the world's population reduced travel by >50% during April 2020 (Fig. 1a). Google mobility trends indicate that >80% of the population in the 114 countries in the dataset (4 billion people) reduced their travel by >50%. Google mobility data and emission reduction estimates based on confinement level analysis in L...

Abstract. Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations for these SSP scenarios – using the reduced-complexity climate–carbon-cycle model MAGICC7.0. We extend historical, observationally based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios, respectively. We also provide the concentration extensions beyond 2100 based on assumptions regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO2 emissions. By 2150, CO2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel-driven scenario projects CO2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66 % for the present day to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (RCPs), the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are more evenly spaced and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the March–April–May (MAM) season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (∼5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies' projections over the next 100 to 500 years unequivocally depict a “hockey-stick” upwards shape. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5 ∘C warming on the other.

Abstract. We present a suite of nine scenarios of future emissions trajectories of anthropogenic sources, a key deliverable of the ScenarioMIP experiment within CMIP6. Integrated assessment model results for 14 different emissions species and 13 emissions sectors are provided for each scenario with consistent transitions from the historical data used in CMIP6 to future trajectories using automated harmonization before being downscaled to provide higher emissions source spatial detail. We find that the scenarios span a wide range of end-of-century radiative forcing values, thus making this set of scenarios ideal for exploring a variety of warming pathways. The set of scenarios is bounded on the low end by a 1.9 W m−2 scenario, ideal for analyzing a world with end-of-century temperatures well below 2 ∘C, and on the high end by a 8.5 W m−2 scenario, resulting in an increase in warming of nearly 5 ∘C over pre-industrial levels. Between these two extremes, scenarios are provided such that differences between forcing outcomes provide statistically significant regional temperature outcomes to maximize their usefulness for downstream experiments within CMIP6. A wide range of scenario data products are provided for the CMIP6 scientific community including global, regional, and gridded emissions datasets.

Low-carbon investments are necessary for driving the energy system transformation called for by both the Paris Agreement and Sustainable Development Goals. Improving understanding of the scale and nature of these investments under diverging technology and policy futures is therefore of great importance to decision makers. Here, using six global modelling frameworks, we show that the pronounced reallocation of the investment portfolio required to transform the energy system will not be initiated by the current suite of countries' Nationally Determined Contributions. Charting a course toward 'well below 2 °C' instead sees low-carbon investments overtaking fossil investments globally by around 2025 or before and growing significantly thereafter. Pursuing the 1.5 °C target demands a marked up-scaling in low-carbon capital beyond that of a 2 °C-consistent future. Actions consistent with an energy transformation would increase the costs of achieving energy access and food security goals but reduce those for achieving air quality goals.

We present an overview of results from 11 integrated assessment models (IAMs) that participated in the 33 rd study of the Stanford Energy Modeling Forum (EMF-33) on the viability of large-scale deployment of bioenergy for achieving long-run climate goals. The study explores future bioenergy use across models under harmonized scenarios for future

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Abstract. We present a suite of nine scenarios of future emissions trajectories of anthropogenic sources, a key deliverable of the ScenarioMIP experiment within CMIP6. Integrated Assessment Model results for 14 different emissions species and 13 emissions sectors are provided for each scenario with consistent transitions from the historical data used in CMIP6 to future trajectories using automated harmonization before being downscaled to provide higher emission source spatial detail. We find that the scenarios span a wide range of end-of-century radiative forcing values, thus making this set of scenarios ideal for exploring a variety of warming pathways. The set of scenarios are bounded on the low end by a 1.9 W m-2 scenario, ideal for analyzing a world with end-of-century temperatures well below 2 °C, and on the high-end by a 8.5 W m-2 scenario, resulting in an increase in warming of nearly 5 °C over pre-industrial levels. Between these two extremes, scenarios are provided such that differences between forcing outcomes provide statistically significant regional temperature outcomes to maximize their usefulness for downstream experiments within CMIP6. A wide range of scenario data products are provided for the CMIP6 scientific community including global, regional, and gridded emissions datasets.

Many countries have implemented national climate policies to accomplish pledged Nationally Determined Contributions and to contribute to the temperature objectives of the Paris Agreement on climate change. In 2023, the global stocktake will assess the combined effort of countries. Here, based on a public policy database and a multi-model scenario analysis, we show that implementation of current policies leaves a median emission gap of 22.4 to 28.2 GtCO 2 eq by 2030 with the optimal pathways to implement the well below 2°C and 1.5°C Paris goals. If Nationally Determined Contributions would be fully implemented, this gap would be reduced by a third. Interestingly, the countries evaluated were found to not achieve their pledged contributions with implemented policies (implementation gap), or to have an ambition gap with optimal pathways towards well below 2°C. This shows that all countries would need to accelerate the implementation of policies for renewable technologies, while efficiency improvements are especially important in emerging countries and fossilfuel-dependent countries.