Accurate estimation of regional-scale terrestrial carbon budgets is of great importance but remains challenging. With particular advantages, the Long Short-Term Memory (LSTM) networks method show potential in improving regional carbon budget upscaling estimations. Here, based on LSTM, we upscale regional net ecosystem carbon exchange (NEE) with available flux tower measurements and satellite land surface observations in North America. With well-established ecosystem-specific LSTMs, we produced monthly NEE at a spatial resolution of 0.1°×0.1° over 2001–2021 (labeled as CROSS2023). Our estimate pointed the largest carbon sink to the Midwest Corn-Belt area during peak growing seasons and to the Southeast on an annual basis, agreeing with empirical knowledges. Moreover, the estimated seasonal variations of NEE by CROSS2023 coincided well with those by atmospheric inversions, i.e., the ensemble mean of Orbiting Carbon Observatory-2 Model Intercomparison Project (OCO-2 v10 MIP; r = 0.95, p < 0.001) and CarbonTracker2022 (CT2022) (r = 0.97, p < 0.001). The mean annual NEE was estimated at -1.27 ± 0.12 Pg C yr-1, aligning more closely with the inversions (-0.70 to -0.63 Pg C yr-1) than with existing upscaling estimates (-3.30 to -1.81 Pg C yr-1). In addition, our estimate plausibly captured the NEE spatial anomalies caused by all the recent extreme drought and flood events. We further confirmed that considering memory effects was critical for better indicating interannual variability and spatial anomalies of NEE induced by climate extremes. This study provides an improved bottom-up estimation of North American NEE, largely narrowing the gap with top-down inversions.

Now that many countries have set goals for reaching net zero emissions in mid-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 different national emission pathways toward the net zero target. Our results showed that China’s contribution to global warming since 2005 is 0.17°C on average in 2050, with a range of 0.1°C to 0.22°C. The peak contributions of these pathways 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 from China’s pathways on the global mean temperature. We found that China’s near-term CH4 mitigation reduces the peak temperature in the mid-century by 0.02°C 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 further underscores the necessity for early CO2 mitigation to achieve the long-term temperature goal ultimately.

The hotter the climate is, the higher the demand for cooling is, leading to more electricity consumption and CO2 emissions. To understand the effect of future regional warming on the electricity demand and CO2 emissions in the Arabian Peninsula region, we selected a representative country, Qatar, and developed a model that relates daily electricity demand with temperature. By combining this model with temperature projections from of 1 23 the CMIP6 database (bias adjusted and statistically downscaled), as well as GDP and population projections from four SSP scenarios, we calculated Qatar’s demand for electricity until the end of the century. We found an average sensitivity of 1.7 GWh/°C for the electricity demand, equivalent to 0.4 MtCO2/°C for CO2 emissions. The electricity demand is projected to increase by 5 to 35% due to warming alone at the end of this century. Under SSP1, the warming-induced CO2 emissions could be offset by improvements of carbon intensity. Under SSP5, assuming no improvement of carbon intensity, future warming could add 20 to 35% of CO2 emissions per year by the end of the century, with half of the electricity demand related to extremely hot days becoming more frequent in the future. Our findings suggest that it is important to consider additional CO2 emissions arising from future warming in future temperature projections.

As the COVID-19 virus spread over the world, governments restricted mobility to slow transmission. Public health measures had different intensities across European countries but all had significant impact on people’s daily lives and economic activities, causing a drop of CO2 emissions of about 10% for the whole year 2020. Here, we analyze changes in natural gas use in the industry and built environment sectors during the first half of year 2020 with daily gas flows data from pipeline and storage facilities in Europe. We find that reductions of industrial gas use reflect decreases in industrial production across most countries. Surprisingly, natural gas use in buildings also decreased despite most people being confined at home and cold spells in March 2020. Those reductions that we attribute to the impacts of COVID-19 remain of comparable magnitude to previous variations induced by cold or warm climate anomalies in the cold season. We conclude that climate variations played a larger role than COVID-19 induced stay-home orders in natural gas consumption across Europe.