• Energy Research
• 2021-2025close

AbstractEast Asia (China, Japan, Koreas, and Mongolia) has been the world's economic engine over at least the past two decades, exhibiting a rapid increase in fossil fuel emissions of greenhouse gases (GHGs) and has expressed the recent ambition to achieve climate neutrality by mid‐century. However, the GHG balance of its terrestrial ecosystems remains poorly constrained. Here, we present a synthesis of the three most important long‐lived greenhouse gases (CO2, CH4, and N2O) budgets over East Asia during the decades of 2000s and 2010s, following a dual constraint approach. We estimate that terrestrial ecosystems in East Asia is close to neutrality of GHGs, with a magnitude of between −46.3 ± 505.9 Tg CO2eq yr−1(the top‐down approach) and −36.1 ± 207.1 Tg CO2eq yr−1(the bottom‐up approach) during 2000–2019. This net GHG sink includes a large land CO2sink (−1229.3 ± 430.9 Tg CO2 yr−1based on the top‐down approach and −1353.8 ± 158.5 Tg CO2 yr−1based on the bottom‐up approach) being offset by biogenic CH4and N2O emissions, predominantly coming from the agricultural sectors. Emerging data sources and modeling capacities have helped achieve agreement between the top‐down and bottom‐up approaches, but sizable uncertainties remain in several flux terms. For example, the reported CO2flux from land use and land cover change varies from a net source of more than 300 Tg CO2 yr−1to a net sink of ∼−700 Tg CO2 yr−1. Although terrestrial ecosystems over East Asia is close to GHG neutral currently, curbing agricultural GHG emissions and additional afforestation and forest managements have the potential to transform the terrestrial ecosystems into a net GHG sink, which would help in realizing East Asian countries' ambitions to achieve climate neutrality.

Abstract Over the past three decades, China has experienced the largest volumes of urban growth worldwide accompanied by a continued increase in rural built-up areas mainly due to the Hukou system (mainland China’s household registration system, separating urban and rural residents) [1][2], with an average annual increase of 3.23% in urban and 2.73% in rural built-up areas. Since China is much rich in biodiversity and has numerous species under threat, both urban and rural built-up land expansion may exacerbate the threats. Risks to biodiversity caused by urban-rural expansion, are crucial for human development and environmental sustainability, but less well explored. Here we investigate what extent urban and rural built-up land expansion contributed to habitat losses of endangered species. We estimate that from 1990 to 2020, urban and rural built-up land expansion induced 2% and 5% of habitat losses on average for each endangered species, and threatened 70% and 82% of endangered species, respectively. Rural built-up land expansion induced more losses of habitats with higher endangered species richness compared with urban expansion. The high-threat habitat areas caused by rural built-up land expansion were 2.5 times as large as those of urban expansion, and about 82% of endangered species were mainly threatened by rural built-up land expansion. Most of them were concentrated in central and south China, one of 25 biodiversity hot spots worldwide. Abolishment of the Hukou system accompanied by more policy arrangements for sustainable development can mitigate urban-rural inequalities. In this scenario, an average of about 647 km2/year would be released from fulfilling the need of built-up area, thus remaining as habitat for biodiversity. Our findings help to provide important insights for biodiversity preservation in the countries with urbanization or rural built-up land expansion, and inform local policy makers in their assessment of prioritization of future ecological sustainability.

China is set to actively reduce its methane emissions in the coming decade. A comprehensive evaluation of the current situation can provide a reference point for tracking the country’s future progress. Here, using satellite and surface observations, we quantify China’s methane emissions during 2010–2017. Including newly available data from a surface network across China greatly improves our ability to constrain emissions at subnational and sectoral levels. Our results show that recent changes in China’s methane emissions are linked to energy, agricultural, and environmental policies. We find contrasting methane emission trends in different regions attributed to coal mining, reflecting region-dependent responses to China’s energy policy of closing small coal mines (decreases in Southwest) and consolidating large coal mines (increases in North). Coordinated production of coalbed methane and coal in southern Shanxi effectively decreases methane emissions, despite increased coal production there. We also detect unexpected increases from rice cultivation over East and Central China, which is contributed by enhanced rates of crop-residue application, a factor not accounted for in current inventories. Our work identifies policy drivers of recent changes in China’s methane emissions, providing input to formulating methane policy toward its climate goal.

Abstract. Precipitation is a crucial component of the global water cycle. Rainfall features (e.g., strength or frequency) strongly affect societal activities and are closely associated with the functioning of terrestrial ecosystems. Hence, predicting global and gridded precipitation under different emission scenarios is an essential output of climate change research, enabling a better understanding of future interactions between land biomes and climate change. Some current lower-complexity models (LCMs) are designed to emulate precipitation in a computationally effective way. However, for precipitation in particular, they are known to have large errors due to their simpler linear scaling of precipitation changes against global warming (e.g., IMOGEN; Zelazowski et al., 2018). Here, to reduce the errors in emulating precipitation, we provide a data-calibrated precipitation emulator (PREMU), offering a convenient and computationally effective way to estimate and represent precipitation well, as simulated by different Earth system models (ESMs) and under different user-prescribed emission scenarios. We construct the relationship between global and local precipitation and modes of global gridded temperature and find that the emulator shows good performance in predicting historically observed precipitation from Global Soil Wetness Project Phase 3 (GSWP3). The ESM-specific emulator also estimates well the simulated precipitation of nine ESMs and under four dissimilar future scenarios of atmospheric greenhouse gases (GHGs). Our ESM-specific emulator also reproduced well interannual fluctuations (R=0.82–0.93, p<0.001) of global land average precipitation (GLAP) simulated by the nine ESMs, as well as their trends and spatial patterns. The default configuration of our emulator only requires gridded temperature, also available from lower-complexity models such as IMOGEN (Zelazowski et al., 2018) and MESMER (Beusch et al., 2022; Nath et al., 2022), which themselves are calibrated against ESMs. Therefore, our precipitation emulator can be directly coupled within other LCMs, improving on, for instance, the current emulations of precipitation implicit in IMOGEN. The PREMU model has the opportunity to provide the driving conditions to model well the hydrological cycle, ecological processes and their interactions with climate change. Critically, the efficiency of LCMs allows them to make projections for many more potential future trajectories in atmospheric GHG concentrations than is possible with full ESMs due to the high computational requirement of the latter. By coupling with PREMU, LCMs will have the ability to emulate gridded precipitation; thus, they can be widely coupled with hydrological models or land surface models.

AbstractMicrobial communities in soils are generally considered to be limited by carbon (C), which could be a crucial control for basic soil functions and responses of microbial heterotrophic metabolism to climate change. However, global soil microbial C limitation (MCL) has rarely been estimated and is poorly understood. Here, we predicted MCL, defined as limited availability of substrate C relative to nitrogen and/or phosphorus to meet microbial metabolic requirements, based on the thresholds of extracellular enzyme activity across 847 sites (2476 observations) representing global natural ecosystems. Results showed that only about 22% of global sites in terrestrial surface soils show relative C limitation in microbial community. This finding challenges the conventional hypothesis of ubiquitous C limitation for soil microbial metabolism. The limited geographic extent of C limitation in our study was mainly attributed to plant litter, rather than soil organic matter that has been processed by microbes, serving as the dominant C source for microbial acquisition. We also identified a significant latitudinal pattern of predicted MCL with larger C limitation at mid‐ to high latitudes, whereas this limitation was generally absent in the tropics. Moreover, MCL significantly constrained the rates of soil heterotrophic respiration, suggesting a potentially larger relative increase in respiration at mid‐ to high latitudes than low latitudes, if climate change increases primary productivity that alleviates MCL at higher latitudes. Our study provides the first global estimates of MCL, advancing our understanding of terrestrial C cycling and microbial metabolic feedback under global climate change.

AbstractThe livestock sector is the largest source of anthropogenic methane emissions and is projected to increase in the future with the increased demand for livestock products. Here, we compare livestock methane emissions and emission intensities, defined by the amount of methane emitted per unit of animal proteins, estimated by different methodologies, and identify mitigation potentials in different regions of the world based on possible future projections. We show that emission intensity decreased for most livestock categories globally during 2000–2018, due to an increasing protein‐production efficiency, and the IPCC Tier 2 method should be used for capturing the temporal changes in the emission intensities. We further show that efforts on the demand‐side to promote balanced, healthy, and environmentally sustainable diets in most countries will not be sufficient to mitigate livestock methane emissions without parallel efforts to improve production efficiency. The latter efforts have much greater mitigating effects than demand‐side efforts, and hence should be prioritized in a few developing countries that contribute most of the mitigation potential.

AbstractDynamics of global wetlands are closely linked to biodiversity conservation, hydrology, and greenhouse gas emissions. However, long-term time series of global wetland products are still lacking. Using a diagnostic model based on the TOPography-based hydrological MODEL (TOPMODEL), this study produced an ensemble of 28 gridded maps of monthly global/regional wetland extents (with more reliable estimates at mid-low latitudes) for 1980–2020 at 0.25° × 0.25° spatial resolution, calibrated with a combination of four observation-based wetland data and seven gridded soil moisture reanalysis datasets. The gridded dynamic maps of wetlands capture the spatial distributions, seasonal cycles, and interannual variabilities of observed wetland extent well, and also show a good agreement with independent satellite-based terrestrial water storage estimates over wetland areas. The long temporal coverage extending beyond the era of satellite datasets, the global coverage, and the opportunity to provide real-time updates from ongoing soil moisture data make these products helpful for various applications such as analyzing the wetland-related methane emission.