• Energy Research

AbstractThe Yedoma layer, a permafrost layer containing a massive amount of underground ice in the Arctic regions, is reported to be rapidly thawing. In this study, we develop the Permafrost Degradation and Greenhouse gasses Emission Model (PDGEM), which describes the thawing of the Arctic permafrost including the Yedoma layer due to climate change and the greenhouse gas (GHG) emissions. The PDGEM includes the processes by which high-concentration GHGs (CO2and CH4) contained in the pores of the Yedoma layer are released directly by dynamic degradation, as well as the processes by which GHGs are released by the decomposition of organic matter in the Yedoma layer and other permafrost. Our model simulations show that the total GHG emissions from permafrost degradation in the RCP8.5 scenario was estimated to be 31-63 PgC for CO2and 1261-2821 TgCH4for CH4(68thpercentile of the perturbed model simulations, corresponding to a global average surface air temperature change of 0.05–0.11 °C), and 14-28 PgC for CO2and 618-1341 TgCH4for CH4(0.03–0.07 °C) in the RCP2.6 scenario. GHG emissions resulting from the dynamic degradation of the Yedoma layer were estimated to be less than 1% of the total emissions from the permafrost in both scenarios, possibly because of the small area ratio of the Yedoma layer. An advantage of PDGEM is that geographical distributions of GHG emissions can be estimated by combining a state-of-the-art land surface model featuring detailed physical processes with a GHG release model using a simple scheme, enabling us to consider a broad range of uncertainty regarding model parameters. In regions with large GHG emissions due to permafrost thawing, it may be possible to help reduce GHG emissions by taking measures such as restraining land development.

Now that many countries have set goals for reaching net zero emissions by the middle of the century, it is important to clarify the role of each country in achieving the 1.5 °C target of the Paris Agreement. Here, we evaluated China’s role by calculating the global temperature impacts caused by China’s emission pathways available in global emissions scenarios toward the 1.5 °C target. Our results show that China’s contribution to global warming in 2050 (since 2005) is 0.17 °C on average, with a range of 0.1 °C to 0.22 °C. The peak contributions of China vary from 0.1 °C to 0.23 °C, with the years reached distributing between 2036 and 2065. The large difference in peak temperatures arises from the differences in emission pathways of carbon dioxide (CO2), methane (CH4), and sulfur dioxide (SO2). We further analyzed the effect of the different mix of CO2 and CH4 mitigation trajectories in China’s pathways on the global mean temperature. We found that China’s near-term CH4 mitigation reduces the peak temperature in the middle of the century, whereas it plays a less important role in determining the end-of-the-century temperature. Early CH4 mitigation action in China is an effective way to shave the peak temperature, further contributing to reducing the temperature overshoot along the way toward the 1.5 °C target. This underscores the necessity for early CO2 mitigation to ultimately achieve the long-term temperature goal.

International audience

Abstract Clarifying characteristics of hazards and risks of climate change at 2 °C and 1.5 °C global warming is important for understanding the implications of the Paris Agreement. We perform and analyze large ensembles of 2 °C and 1.5 °C warming simulations. In the 2 °C runs, we find substantial increases in extreme hot days, heavy rainfalls, high streamflow and labor capacity reduction related to heat stress. For example, about half of the world’s population is projected to experience a present day 1-in-10 year hot day event every other year at 2 °C warming. The regions with relatively large increases of these four hazard indicators coincide with countries characterized by small CO2 emissions, low-income and high vulnerability. Limiting global warming to 1.5 °C, compared to 2 °C, is projected to lower increases in the four hazard indicators especially in those regions.

The impact of climate change on power demand in Japan is a matter of concern for the Japanese authorities and power companies as it may have consequences on the power grid. We trained random forest models against daily power data in ten Japanese regions and for different types of power generation to project changes in future power production and its carbon intensity. To do so, we used twelve predictors: six climate variables, five variables accounting for human exposure to climate, and one variable for the level of human activities. We then used the models trained from the present-day period to estimate the future power demand, carbon intensity, and pertaining CO2 emissions over the period 2020-2100 under three SSPs scenarios (Shared Socioeconomic Pathways: SSP126, SSP370, and SSP585). The impact of climate change on CO2 emissions via power generation shows seasonal and regional disparities. In cold regions, a decrease in power demand during winter under future warming leads to an overall decrease in power demand over the year. In contrast, the decrease in winter power demand in hot regions can be overcompensated by an increase in summer power demand because of more frequent hot days, leading to an overall annual increase. From our regional models, the power demand should increase the most in most Japanese regions in May, June, September, and October and not in the middle of summer, as has been found in older studies. Such an increase could result in regular power outages during those months if not considered, as the power grid could be particularly tense. Overall, we observed that power demand in regions with extreme climates is more sensitive to global warming than in temperate regions. The impact of climate change on power demand induces a net annual decrease in CO emissions in all regions except for Okinawa, in which power demand strongly increases during the summer, resulting in a net annual increase in CO emissions. However, climate change’s impact on carbon intensity may reverse the trend in some regions (Shikoku, Tohoku). We also assessed the relative impacts of socioeconomic factors such as population, GDP, and environmental policies on CO emissions. When combined with these factors, we found that the climate change effect is more important than when considered individually and significantly impacts total CO emissions under SSP585.

Carbon Monitor est un ensemble de données en temps quasi réel pour les émissions quotidiennes de CO2 avec une couverture mondiale de 6 secteurs principaux (énergie, industrie, transport terrestre, aviation, transport résidentiel et international).Ici, nous fournissons les données annuelles de 2019 et 2020.Visitez notre site Web pour plus d'informations : https://carbonmonitor.org Carbon Monitor es un conjunto de datos casi en tiempo real para las emisiones diarias de CO2 con cobertura global de 6 sectores principales (energía, industria, transporte terrestre, aviación, transporte residencial e internacional).Aquí, proporcionamos los datos de todo el año de 2019 y 2020.Visite nuestro sitio web para obtener más información: https://carbonmonitor.org Carbon Monitor is a near real-time dataset for daily CO2 emissions with global coverage from 6 main sectors (power, industry, ground transportation, aviation, residential and international shipping).Here, we provide the whole year data of 2019 and 2020.Visit our website for more information: https://carbonmonitor.org كربون مونيتور هي مجموعة بيانات شبه آنية لانبعاثات ثاني أكسيد الكربون اليومية مع تغطية عالمية من 6 قطاعات رئيسية (الطاقة والصناعة والنقل البري والطيران والشحن السكني والدولي). نقدم هنا بيانات العام بأكمله لعامي 2019 و 2020.قم بزيارة موقعنا الإلكتروني لمزيد من المعلومات: https://carbonmonitor.org