Earths Future最新文献

International initiatives, such as the Bonn Challenge, Trillion Tree Campaign, New York Declaration on Forests, and United Nations Decade on Ecosystem Restoration, have set ambitious targets for forest restoration. However, the effectiveness and cost-efficiency of large-scale forest restoration projects (FRP) in different climatic zones, and the trade-off between carbon sequestration and water consumption caused by FRP are poorly understood. Here, we conducted a comprehensive examination of 2,778 counties in China, where the world's most ambitious FRP was executed during the past two decades. Results showed that, on average, each square kilometer of FRP yielded an additional 0.6 square kilometers of forests and contributed an extra 1354.9 tC to forest carbon storage, with the aridity index emerging as a key influencer. The actual expenditure incurred per ton of increased forest carbon storage amounted to approximately 118.9 USD in average, with the lowest in Southwest at 50.9 USD. The expansion of forest cover and enhanced biomass storage led to a notable increase in water consumption, and the trade-off was particularly pronounced in arid regions. Our study provides empirical evidence that FRP is an effective and cost-efficient climate change mitigation strategy for humid climate zones under current carbon prices. However, FRP is not cost-efficient in semi-arid and arid regions. These findings have significant implications for global forest restoration endeavors and formulating sound climate change mitigation policies.

This study assesses the vulnerability of Arctic coastal settlements and infrastructure to coastal erosion, Sea-Level Rise (SLR) and permafrost warming. For the first time, we characterize coastline retreat consistently along permafrost coastal settlements at the regional scale for the Northern Hemisphere. We provide a new method to automatically derive long-term coastline change rates for permafrost coasts. In addition, we identify the total number of coastal settlements and associated infrastructure that could be threatened by marine and terrestrial changes using remote sensing techniques. We extended the Arctic Coastal Infrastructure data set (SACHI) to include road types, airstrips, and artificial water reservoirs. The analysis of coastline, Ground Temperature (GT) and Active Layer Thickness (ALT) changes from 2000 to 2020, in addition with SLR projection, allowed to identify exposed settlements and infrastructure for 2030, 2050, and 2100. We validated the SACHI-v2, GT and ALT data sets through comparisons with in-situ data. 60% of the detected infrastructure is built on low-lying coast (10 m a.s.l). The results show that in 2100, 45% of all coastal settlements will be affected by SLR and 21% by coastal erosion. On average, coastal permafrost GT is increasing by 0.8°C per decade, and ALT is increasing by 6 cm per decade. In 2100, GT will become positive at 77% of the built infrastructure area. Our results highlight the circumpolar and international amplitude of the problem and emphasize the need for immediate adaptation measures to current and future environmental changes to counteract a deterioration of living conditions and ensure infrastructure sustainability.

Compound flood-heatwave extremes (CFHWs) have threatened the sustainable development of human society and ecosystems. However, the disproportionate risks in regions with different economic development under a warming climate have not been quantified. This study carries out a global investigation on the future CFHWs under three scenarios based on 11 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Results reveal a 7.5-fold increase in global annual CFHW days by 2100 under the intermediate greenhouse-gas-emission scenario SSP2-4.5 compared to that in 1980. Under SSP2-4.5, population exposure in low-income countries in the late future (2071–2090) will be about 9-fold higher than in high-income countries compared to baseline period (1995–2014). Moreover, exposure of the poor groups living on less than $6.85/day will increase by nearly 28.1-fold. Eastern Africa and South Asia are identified as particularly high-risk regions, where large populations living in poverty face rapidly increasing CFHWs. These findings indicate that climate inequality will become more pronounced if climate warming continues without immediate effective measures. Our study also underscores the urgent need for mitigation and adaptation strategies against the future increasing CFHWs, especially for the vast low-income and high-risk regions.

An essential step toward meeting agreed climate targets and policies is the ability to understand and predict near-term changes in global carbon cycle, and importantly, ocean carbon uptake. Initialized climate model simulations have proven skillful for near-term predictability of the key physical climate variables, for example, temperature, precipitation, etc. By comparison, predictions of biogeochemical fields like ocean carbon flux, are still emerging. Initial studies indicate skillful predictions are possible for lead-times up to 6 years at global scale for some CMIP6 models. However, unlike core physical variables, biogeochemical variables are not directly initialized in existing decadal prediction systems, and extensive empirical parametrization of ocean-biogeochemistry in Earth System Models introduces a significant source of uncertainty. Here we propose a new approach for improving the skill of decadal ocean carbon flux predictions using observationally-constrained statistical models, as alternatives to the ocean-biogeochemistry models. We use observations to train multi-linear and neural-network models to predict the ocean carbon flux. To account for observational uncertainties, we train using six different observational estimates of the flux. We then apply these trained statistical models using input predictors from the Canadian Earth System Model (CanESM5) decadal prediction system to produce new decadal predictions. Our hybrid GCM-statistical approach significantly improves prediction skill, relative to the raw CanESM5 hindcast predictions over 1990–2019. Our hybrid-model skill is also larger than that obtained by any available CMIP6 model. Using bias-corrected CanESM5 predictors, we make forecasts for ocean carbon flux over 2020–2029. Both statistical models predict increases in the ocean carbon flux larger than the changes predicted from CanESM5 forecasts. Our work highlights the ability to improve decadal ocean carbon flux predictions by using observationally-trained statistical models together with robust input predictors from GCM-based decadal predictions.

China has over 2,500 national and provincial industrial parks, stimulating the economics growth, meanwhile being the primary sources of carbon dioxide emissions and other pollutants. Assessing the mechanisms and impacts of the policies of pilot programs of green industrial parks on urban carbon emissions offers critical insights into the efficacy and application of green and low-carbon development. This study utilizes a staggered difference-in-differences model to examine the impact of green industrial park pilot policies. The results demonstrate that green industrial parks have effectively reduced carbon emissions of the studied counties in terms of total and intensity. The economic scales and the administrative levels of any given city significantly influence the implementation effect of green industrial park policy. In applying the green industrial park policy, reducing the carbon emissions is more pronounced in cities with larger economic scales and higher administrative levels. Environmental regulation policies and green industrial park pilot policies exhibit a certain degree of substitution effect. The green industrial parks drive urban carbon emission reduction through three main channels: enhancing green technologies, optimizing industrial structures, and elevating economic agglomeration levels. Overall, this study provides a new perspective, a methodological reference, and empirical evidence for promoting green and low-carbon development for industrial parks in the different regions and developing countries.

A probabilistic projection of sea-level rise uses a probability distribution to represent scientific uncertainty. However, alternative probabilistic projections of sea-level rise differ markedly, revealing ambiguity, which poses a challenge to scientific assessment and decision-making. To address the challenge of ambiguity, we propose a new approach to quantify a best estimate of the scientific uncertainty associated with sea-level rise. Our proposed fusion combines the complementary strengths of the ice sheet models and expert elicitations that were used in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change (IPCC). Under a low-emissions scenario, the fusion's very likely range (5th–95th percentiles) of global mean sea-level rise is 0.3–1.0 m by 2100. Under a high-emissions scenario, the very likely range is 0.5–1.9 m. The 95th percentile projection of 1.9 m can inform a high-end storyline, supporting decision-making for activities with low uncertainty tolerance. By quantifying a best estimate of scientific uncertainty, the fusion caters to diverse users.

The Eastern Nile Basin (ENB) countries of Egypt, Sudan, South Sudan, and Ethiopia are subject to pronounced water, energy, and food (WEF) insecurity. There is a need to manage the WEF nexus to meet rapidly increasing demands, but this is extremely challenging due to resource scarcity and climate change. If countries that rely on shared transboundary water resources have contradictory WEF plans, that could diminish the expected outcomes, both nationally and regionally. Egypt as the most downstream Nile country is concerned about ongoing and future developments upstream, which could exacerbate Egypt's water scarcity and affect its ability to meet its WEF objectives. In this context, we introduce a multi-model WEF framework that simulates the ENB water resources, food production, and hydropower generation systems. The models were calibrated and validated for the period 1983–2016, then utilized to project a wide range of future development plans, up to 2050, using four performance measures to evaluate the WEF nexus. A thematic pathway for regional development that shows high potential for mutual benefits is identified. However, the WEF planning outcomes for the region are sensitive to climate change, but, if social drivers could be managed (e.g., by lowering population growth rates) despite the difficulties involved, climate change impacts on WEF security could be less severe.

We generate earthquake iso-nuisance and iso-damage maps for Alberta. These maps show the spatial distribution of earthquake magnitude required to reach a specific level of nuisance and damage, considering human exposure and surficial geological conditions. We rely on population distribution for the human exposure factor while utilizing Vs30 derived from surficial geological modeling to approximate site amplification effects. By including the trailing seismicity factor, the iso-nuisance and iso-damage maps provide the base for the Magnitude Threshold for Acceptable Seismicity maps, which can set a guideline for the upper magnitude boundary, or largest magnitude event permissible, related to industrial activities causing seismicity. The trailing seismicity factor refers to the subsequent seismicity after a substantial change or end of the seismogenic operations; for instance, the cessation of seismogenic hydraulic fracturing activities under a traffic light protocol after a magnitude threshold event (red-light event). Considering variations in the trailing seismicity factor, we derive different Magnitude Threshold for Acceptable Seismicity maps for various injection-induced activities, including hydraulic fracturing and fluid disposal activities. Extended versions of the Magnitude Threshold for Acceptable Seismicity maps could allow for safety factors pertinent to critical infrastructure in a particular area, incorporating other factors beyond the population distribution and warranting a different tolerance level. These maps help to define the magnitude threshold from induced seismicity, maintaining the same tolerance levels throughout a region. Thus, they can be highly beneficial in managing current and future cases of induced seismicity related to the energy sector.

Extreme precipitation can lead to major flooding, impacting human health and safety. Thus, reliable projections of population and GDP exposure to future extreme precipitation are imperative. Here, we quantify future precipitation characteristics from robust emergent constraint relationships between historical and future monthly precipitation extremes (99th percentile) across 19 CMIP6 models (r² > 0.7 in 74–84% of 0.5° global land grids), and narrow uncertainty by 37.0–39.5% (absolute reduction being 0.753–0.774 mm/day). The constrained grid-averaged future 99th percentile extreme is 6.96 ± 0.0059, 7.03 ± 0.0061, 7.11 ± 0.0063, and 7.29 ± 0.0067 mm/day, under SSP126, SSP245, SSP370, and SSP585, respectively, which exceeds historical extremes substantially in terms of intensity (12.9–19.7%) and frequency (1.6–2.3 times more). Future population and GDP exposed to 99th percentile extreme precipitation grow quickly, and are projected to exceed 1 million people in 27–40 countries and 10 billion USD (2005 Purchasing-Power Parity) in 48–77 countries. Growth of future population exposure is dominated by an increase in extreme precipitation frequency rather than a rise in population, especially in developed countries. GDP exposure is controlled by the coupled effects of rapid socio-economic development and significant shifts in precipitation frequency. Using indices of socio-economic vulnerability, government effectiveness and economic freedom, we identify the unequal situation that high-risk countries with high exposure are commonly characterized by low GDP per capita and high sociopolitical instability.