Calcination of carbonate rocks during the manufacture of cement produced 5% of global CO2 emissions from all industrial process and fossil-fuel combustion in 20131, 2. Considerable attention has been paid to quantifying these industrial process emissions from cement production2, 3, but the natural reversal of the process—carbonation—has received little attention in carbon cycle studies. Here, we use new and existing data on cement materials during cement service life, demolition, and secondary use of concrete waste to estimate regional and global CO2 uptake between 1930 and 2013 using an analytical model describing carbonation chemistry. We find that carbonation of cement materials over their life cycle represents a large and growing net sink of CO2, increasing from 0.10 GtC yr−1 in 1998 to 0.25 GtC yr−1 in 2013. In total, we estimate that a cumulative amount of 4.5 GtC has been sequestered in carbonating cement materials from 1930 to 2013, offsetting 43% of the CO2 emissions from production of cement over the same period, not including emissions associated with fossil use during cement production. We conclude that carbonation of cement products represents a substantial carbon sink that is not currently considered in emissions inventories1, 3, 4

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Retaining soluble polysulfides in the sulfur cathodes and allowing for deep redox are essential to develop high-performance lithium-sulfur batteries. The versatile textures and physicochemical characteristics of abundant biomass offer a great opportunity to prepare biochar materials that can enhance the performance of Li-S batteries in sustainable mode. Here, we exploit micro-/mesoporous coconut shell carbon (CSC) with high specific surface areas as a sulfur host for Li-S batteries. The sulfur-infiltrated CSC materials show superior discharge-charge capacity, cycling stability, and high rate capability. High discharge capacities of 1599 and 1500 mA h g were achieved at current rates of 0.5 and 2.0 C, respectively. A high reversible capacity of 517 mA h g was retained at 2.0 C even after 400 cycles. The results demonstrate a high retention and a deep lithiation of the CSC-confined sulfur. The success of this strategy provides insights into seeking high-performance biochar materials for Li-S batteries from abundant bioresources.

Abstract. Surface air temperature (Ta), as an important climate variable, has been used in a wide range of fields such as ecology, hydrology, climatology, epidemiology, and environmental science. However, ground measurements are limited by poor spatial representation and inconsistency, and reanalysis and meteorological forcing datasets suffer from coarse spatial resolution and inaccuracy. Previous studies using satellite data have mainly estimated Ta under clear-sky conditions or with limited temporal and spatial coverage. In this study, an all-sky daily mean land Ta product at a 1 km spatial resolution over mainland China for 2003–2019 has been generated mainly from the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Global Land Data Assimilation System (GLDAS) dataset. Three Ta estimation models based on random forest were trained using ground measurements from 2384 stations for three different clear-sky and cloudy-sky conditions. The random sample validation results showed that the R2 and root-mean-square error (RMSE) values of the three models ranged from 0.984 to 0.986 and from 1.342 to 1.440 K, respectively. We examined the spatiotemporal patterns and land cover type dependences of model accuracy. Two cross-validation (CV) strategies of leave-time-out (LTO) CV and leave-location-out (LLO) CV were also used to evaluate the models. Finally, we developed the all-sky Ta dataset from 2003 to 2009 and compared it with the China Land Data Assimilation System (CLDAS) dataset at a 0.0625∘ spatial resolution, the China Meteorological Forcing Data (CMFD) dataset at a 0.1∘ spatial resolution, and the GLDAS dataset at a 0.25∘ spatial resolution. Validation accuracy of our product in 2010 was significantly better than other datasets, with R2 and RMSE values of 0.992 and 1.010 K, respectively. In summary, the developed all-sky daily mean land Ta dataset has achieved satisfactory accuracy and high spatial resolution simultaneously, which fills the current dataset gap in this field and plays an important role in the studies of climate change and the hydrological cycle. This dataset is currently freely available at https://doi.org/10.5281/zenodo.4399453 (Chen et al., 2021b) and the University of Maryland (http://glass.umd.edu/Ta_China/, last access: 24 August 2021). A sub-dataset that covers Beijing generated from this dataset is also publicly available at https://doi.org/10.5281/zenodo.4405123 (Chen et al., 2021a).