Earths Future最新文献

The 2024 Global Economic Prospects report by the International Monetary Fund highlighted the crucial role of emerging economies in driving global economic growth. Due to their active participation in global supply chains, these emerging economies generate large amounts of methane emissions to supply the required products to the global economy. While existing research has investigated the displacement of methane emissions between nations via interregional trade, the geospatial details of global methane footprint in emerging economies, which are crucial for pinpointing location-specific mitigation strategies, remain unknown. This study addressed this gap by connecting high-resolution methane emission maps from Emissions Database for Global Atmospheric Research with the Exiobase muti-regional input-output trade database, and generated spatially explicit hotspot maps of global methane footprint in emerging economies from 1995 to 2021. Results revealed that the methane footprint of global consumption in emerging economies is primarily concentrated in resource-rich, agriculture-intensive, and well-connected areas, with major regions contributing to 70% of total methane emissions in emerging economies. The displacement of methane emissions from economically-developed regions to emerging economies has consistently increased from 1995 to 2021, with the European Union, the United States, and the Rest of the World Europe collectively accounting for 70% of global methane emissions in 2021. Evolution trends and policy implications were presented for main sectoral agents including Fuel exploitation, Enteric fermentation, and Agricultural soil. The outcomes of this study can contribute to identifying emission hotspots in emerging economies and informing international cooperation efforts aimed at reducing methane emissions.

Urban green spaces (UGSs) are recognized beneficial for thermal comfort, yet its potential effects on air quality due to biogenic volatile organic compounds (BVOCs) emissions have received concerns. UGSs affect air quality through multiple pathways, some of which were generally missing in existing literature. Here we assess the impacts of UGSs on regional climate and air quality in the Pearl River Delta (PRD) with a more comprehensive framework. We consider the impacts of BVOCs emissions, dry deposition, radiative effects of produced aerosols, and transpiration effects. UGSs tend to elevate fine particulate matter (PM_2.5) concentrations by 5.11 μg/m³, dominated by evapotranspiration (4.62 μg/m³) that lowers mixing height and offset by additional dry deposition surfaces (−1.24 μg/m³). Although emitted BVOCs enhance ozone, evapotranspiration and dry deposition counterbalance the adverse effect by ∼87%. When considering the aerosol radiative effect, our findings indicate that both BVOC emissions and evapotranspiration contribute to mitigating the urban heat island effect between 14:00 and 16:00. Our results suggest that the air quality degradation will not be serious for cities with low aerosol concentrations if vegetations with less VOCs are planned. Additionally, UGSs can further help to alleviate urban warming.

Expansion of impervious surface area (ISA) in urbanizing regions often leads to vegetation area losses, a direct impact of urbanization. Many activities driven by economic growth, population increases, targeted urban greening investments, environmental policies, and major sports events change vegetation composition, structure, and function, leading to substantial indirect (positive or negative) impacts on vegetation in urban area. In this study, we analyzed the spatial-temporal dynamics of ISA, enhanced vegetation index (EVI), and gross primary production (GPP) in the Yangtze River Delta (YRD), China, over 2000–2020. Positive indirect impacts of urbanization on EVI and GPP surged after 2011, coinciding with China's Ecological Civilization Strategy. The concurrent increases of ISA, EVI, and GPP in the YRD provide an example for our society to work and advance the UN's Sustainable Development Goal #11, “Make cities inclusive, safe, resilient, and sustainable.”

Flash droughts have become a growing concern, as they can emerge rapidly and increase the risk of crop failure. Although past studies have investigated the meteorological drivers and future changes of flash drought, why flash drought is more frequent over humid and vegetated regions remains underexplored. This study delves further into the mechanism by which vegetation regulates flash drought and its future change using observations from multiple data sets and large ensemble simulations from three Earth system models. On an interannual timescale, both observations and simulations show robust increases in flash drought frequency and a higher flash-to-sub-seasonal drought ratio during spring or antecedent conditions with dense vegetation, supporting the important role of vegetation in flash drought occurrence, especially in the northern mid-to-high latitudes. In the latter regions, the large ensemble simulations show robust increases in flash drought (e.g., 67% and 46% increases in Eastern U.S. and North Asia in 2050–2100 relative to 1950–2000 under the high emission scenario), where the growing season is lengthening. Although greening might suggest reduced drought stress, it drives precipitation-soil moisture-evapotranspiration decoupling by increasing evapotranspiration partitioning to transpiration. As transpiration can access deep soil water through the plant root system, its increased portion can weaken the constraints of concurrent precipitation on evapotranspiration, thus accelerating soil moisture depletion under high evaporative demand, driving a slow-to-rapid drought transition. How vegetation regulates flash drought by regulating surface moisture budget is supported by observations and simulations. Although warming supports early planting, agriculture may increasingly be threatened by surging flash drought risk.

Freshwater biodiversity and ecosystem services are under stress as climate change alters streamflow intermittence. We present the first continental-scale quantification of future climate change impacts on streamflow intermittence, achieved for Europe at a high spatial resolution that captures headwater streams. A hybrid modeling approach combines physics-based and data-based modeling, with a random forest model, trained on historical streamflow observations, using predictors representing the impact of climate change on high-resolution (500 m) streamflow. These predictors were derived from a low-resolution (50 km) global hydrological model, WaterGAP, which was driven by the outputs of five global climate models. The generated monthly time series of intermittence status for over 1.5 million reaches were used to calculate five ecologically relevant indicators of streamflow intermittence change. In Europe, the number of non-perennial reach-months is projected to increase in the future, for both low (SSP1-RCP2.6) and high (SSP5-RCP8.5) greenhouse gas emissions scenarios, in almost all climate zones, particularly in August and September. Under SSP1-RCP2.6, 3.8% of all reach-months may experience no-flow conditions in 2071–2100, only a small increase from 3.5% in 1985–2014. Under SSP5-8.5, however, a larger increase to 4.8% of all reach-months is expected; 2.8% of European reaches are projected to shift from being perennial to non-perennial, even where annual precipitation increases, while 0.7% are projected to shift from non-perennial to perennial. These shifts represent a fundamental change in ecological habitat and connectivity i.e. bound to erode aquatic species diversity and alter ecosystem functions across more than 87.000 km of river segments.

Bivalve mollusks are vital to coastal economies and food security, yet the impact of ocean warming and acidification on aquaculture remains unclear due to a lack of ground truth data on future production. Most experimental studies rely on short-term, single-factor experiments in stable and food-unlimited environments, making it difficult to provide practical guidance to growers and decision-makers. To address this knowledge gap, we developed a land-based automated system to expose bivalves to future climate scenarios under field-realistic conditions using unfiltered, ambient seawater, assessing survival, growth, reproduction, and next-generation development. Here we present the first results of exposing Pacific oysters and Mediterranean mussels, the two most cultivated species in the Mediterranean area, to present conditions and projected scenarios for the years 2050, 2075, and 2100. For the first time, our results reveal that future warming and acidification conditions have a dramatic impact on the production yield of oysters and mussels. Oysters exposed to conditions projected for 2100 exhibited a 7% reduction in survival and a 40% reduction in growth rate, along with lower reproductive maturity, which in turn negatively affected the early development of their offspring. Mussels are already experiencing summer temperatures above their upper thermal limits, with around 40% mortality observed under current conditions and near-total mortality under those projected for 2050. These patterns reflect sporadic mass-mortality events reported elsewhere in the Mediterranean and indicate that mussel farming in the region could be severely compromised by mid-century. Our results urgently call for the development of adaptation strategies in the Mediterranean.

The desert climate of the Arabian Peninsula (AP), marked by sparse rainfall, extreme temperatures, and frequent dust events, significantly impacts its 80-million population, environment, and economy. Rising temperatures and dust incursions exacerbate these harsh conditions, yet the AP's climate is underrepresented in global climate research. Understanding its variability is crucial for improving predictions on subseasonal-to-seasonal timescales and for developing reliable climate change projections. Existing climate models fail to capture the region's unique environment, topography, and land-use changes, leading to poor representation of key processes like local convection, aridity, and moisture transport. To address these gaps, Saudi Arabia established the Climate Change Center (CCC) in 2022, part of the Saudi Vision 2030 initiative. The CCC aims to study climate variability and project future changes using advanced Earth system models developed in collaboration with international partners. This study presents the CCC's roadmap, focusing on its relevance for global climate research and policymaking, including the Saudi and Middle East Green Initiatives. We also discuss regional uncertainties in the IPCC's climate projections for the AP and highlight the development of high-resolution regional models that account for local atmospheric, land, and oceanic processes. The CCC is developing subseasonal-to-seasonal forecasting systems and drought monitoring tools, alongside user-friendly dashboards to offer stakeholders customized climate data. These tools, set for launch in 2025, will aid informed decision-making in addressing extreme weather events and climate-related challenges in Saudi Arabia.

The summer of 2023 was the most significant wildfire and smoke season on record in Canada. Data from five different satellite instruments going back to 2001 show that Canada and most provinces and territories experienced peak visible-wavelength aerosol optical depth and ultraviolet aerosol index values in 2023. Longer-term, 2023 had the highest number of “smoke” or “haze” reports in weather records by a factor of two compared with the previous record in 1981, and by a factor of seven compared with the 1953–2022 average. These reports show an east-to-west shift in Canada's summer air pollution patterns. Smoke and haze in eastern Canada have decreased since the 1980s because of pollution control measures domestically and in the US. On the other hand, wildfire smoke has increased in the Northwest Territories, British Columbia, Alberta, and Saskatchewan since the 2010s, and is now the main air quality concern in western Canada. Interpreting the analysis here for Canada alongside previous work over the US, there was a shift over North America in summer air quality concerns from the east to the west. Climate model projections suggest more wildfire-driven smoke in the future throughout North America, particularly in the west. In contrast to air pollution from smokestacks and tailpipes that can be addressed at the source through government regulation, a future with more wildfire smoke will require downwind mitigation and will be the responsibility of public health officials.

Earth's snow cover strongly influences the climate system and represents an important resource for agricultural, industrial, and domestic water use. The last decade of snow-focused research has improved our understanding of snow across scales. These efforts have culminated in new snow measurement instruments and methods, operational models for tracking snowpack evolution and forecasting snowmelt, multi-year and international snow and remote sensing field campaigns, and satellite mission proposals to measure snowpack water resources from space, with two submitted to NASA's Earth Explorer AO and the Environment and Climate Change Canada Terrestrial Snow Mass Mission moving closer to a launch opportunity. Yet, shortcomings in each snowpack observation system still exist, including uncertainty in product performance, mission proposal advancement, and synergies across methods. The snow community aims to navigate next actionable steps toward improved and global-scale snow monitoring for climate and human purposes. Building from recent advances in snow research and operations and carrying momentum from the conclusion of the NASA SnowEx field campaigns, NASA's Terrestrial Hydrology Program (THP) sponsored a Community Snow Meeting in August 2024 in Boulder, Colorado, USA, with 200 total in-person and virtual attendees. Meeting objectives were to outline existing and ongoing snowpack monitoring techniques and identify knowledge gaps and recommended next steps for the snow community. We broadly summarize the state of numerous snow science sub-disciplines and share the insights and takeaways from the Community Snow Meeting, focused largely but not exclusively on NASA opportunities, and intended to support ongoing and future pathways toward the next decade of snow research and development.

Irrigation plays a crucial role in the earth system, yet our understanding of irrigation water withdrawal (IWW) remains limited due to the scarcity of spatially explicit data. While process-based models and remote sensing can bridge this data gap, their estimates often fail to capture real IWW and are associated with large uncertainties. Here, we present a knowledge-informed, explainable machine learning framework that combines random forest (RF) with Shapley additive explanations to generate spatially explicit IWW estimates across China. Our framework incorporates irrigation domain knowledge, state-of-the-art irrigated cropland maps, and various socioeconomic, hydroclimatic, and auxiliary factors. RF shows reasonable performance in spatial and temporal cross-validation, achieving a coefficient of determination exceeding 0.85 and a root mean square error below 0.45 km³/year when evaluated against held-out prefecture-level data. The predictions of IWW depth are primarily driven by geographic and knowledge-based predictors, most of which exhibit nonlinear and non-monotonic impacts on model outputs. By integrating the RF model with a temporal downscaling approach, we develop a new gridded IWW product for China (named CIWW1km), which provides monthly IWW depth and volume at 1 km resolution from 2000 to 2020. CIWW1km aligns closely with prefecture-level IWW reports and explains over 85% of the variance in independent IWW observations (i.e., data excluded from training) across over 150 basins and counties. It highlights a rapid increase in IWW in China's arid zone, driven by irrigated area expansions. CIWW1km outperforms existing products and is well-suited for hydrological and climate studies, and water-food nexus analyses.