Seasonal freeze-thaw modulates methane cycling in urban waters revealed by multiple isotopic constraints.

Microbial-derived carbon dominates shrub encroachment carbon loss in Inner Mongolia grasslands.

Dissolved organic matter in surface sediments along a river-to-ocean continuum: Molecular characteristics and sediment-water exchange dynamics.

The remaining global carbon budget is so small that carbon dioxide removal (CDR) measures are very likely to be required to avoid dangerous climate change. Multiple scenarios consistent with a high probability of limiting global warming to well below 2 °C include removing hundreds of gigatons of carbon dioxide. At the same time, deep decarbonization pathways show that rapid and drastic emissions reductions can substantially reduce or even avoid the need for CDR. This article discusses one major problem raised by pathways relying on large-scale CDR: By potentially discouraging or at least delaying the implementation of deep decarbonization measures, such pathways might cause a substantial overshoot of the global carbon budget that would lead to severe injustices. More specifically, it highlights the problem of substitution between large-scale CDR and deep emissions reductions by explaining the structure of this problem, stressing the ethical issues it raises, and investigating three conditions under which it is likely to occur.

Abstract Ireland’s climate legislation mandates greenhouse gas (GHG) reductions consistent with the Paris Agreement, implemented through legally binding carbon budgets (CBs) targeting a 51% reduction by 2030, relative to 2018, and climate neutrality by 2050. As an EU Member State, Ireland must also meet obligations under European climate and energy legislation, including the Emissions Trading Scheme (ETS), the Energy Efficiency Directive (EED), and the Effort Sharing Regulation (ESR). The extent to which national policy frameworks, such as Ireland’s domestic CBs, align with EU obligations is underexplored.
This study assesses the alignment of Ireland’s energy system decarbonisation pathways – developed using the TIMES-Ireland Model (TIM) and aligned with approved and adopted national CBs - with EU climate and energy targets for 2030 and 2040. The analysis focuses on a composite “TIM-CBaligned” pathway, representing the weighted average of scenarios underpinning Ireland’s third and fourth CB proposals, alongside current and planned policy scenarios. 
Results show that TIM-CBaligned outperforms the 2030 EU ETS target in power and industry sectors by 24% and exceeds the indicative EU-2040 benchmark for energy emissions by 68%. ESR compliance is achievable only with significant agricultural mitigation; otherwise, non-compliance persists even with use of flexibilities. Final energy consumption in 2030 falls 6% short of the EED target, although low energy demand scenarios help to close the gap.
These findings confirm that ambitious, CB-aligned energy pathways can deliver strong coherence between national and EU climate goals, in line with literature on multilevel climate governance. However, they also highlight the persistent risk that underperformance in non-energy sectors undermines overall compliance, which is particularly pertinent for countries with a high share of emissions from agriculture. Policy coherence requires sustained investment, accelerated demand reduction, and integrated planning across all sectors. This study contributes a novel, quantitative example of national–EU target alignment, addressing a recognised gap in the literature and providing evidence to inform both domestic and EU policy debates.

Abstract Large earthquakes in mountainous regions trigger extensive landslides, which mobilize organic carbon via soil erosion and vegetation loss, disrupting carbon reservoirs and influencing CO 2 levels. Quantifying earthquake impacts on carbon stock and cycling remains challenging. Here, we use field organic carbon data from 91 quadrats and over 20 years of remote sensing imagery to assess the impact of landslides from the 2008 M w 7.9 Wenchuan earthquake on the carbon budget. We show that these landslides removed 2.72 ± 0.52 Tg of organic carbon in the upper Min Jiang. While its oxidation releases CO 2 , rapid revegetation offsets this, making the earthquake a net carbon sink. Time-series data indicate that vegetation carbon stocks will recover to 50% of pre-earthquake levels in 74 ± 5 years, whereas soil organic carbon recovery to 50% may take 500–850 years. This study highlights the decadal to centennial-scale impact of extreme events on carbon cycling.

Extreme precipitation intensifies under global warming, yet its impact on sea-air CO2 flux (FCO2) remains underexplored. Here we show that the maximum 1-day precipitation (Rx1day) exerts a notable influence on FCO2 in the South Pacific Ocean and South Atlantic Ocean during 1990-2023. An increase in Rx1day from 0 to 30 mm causes the South Pacific Ocean and South Atlantic Ocean to shift from carbon sources to carbon sinks, with FCO2 decreasing from 96 to -27 mmolm-2month-1 and from 70 to -70 mmolm-2month-1, respectively. This reduction is likely attributed to precipitation-induced dilution effects on salinity and alkalinity. When precipitation increases by up to 20%, FCO2 exhibits maximum reductions of 27% (5.6 mmolm-2month-1) in the South Pacific Ocean and 10% (6.4 mmolm-2month-1) in the South Atlantic Ocean. Neglecting precipitation may result in a non-negligible overestimation of FCO2, underscoring the necessity of incorporating it into ocean carbon budget models.

Agricultural ponds are globally widespread and multifunctional, yet they emit substantial quantities of greenhouse gases (GHGs), notably methane (CH4) and carbon dioxide (CO2), posing a significant but poorly quantified climate disservice. This study quantified dissolved concentrations and total fluxes of CH4 and CO2 from 18 agricultural ponds in Scotland between May and September. All ponds were net GHG sources, with mean fluxes of 0.39 ± 0.41 g CH4 m-2 day-1 and 3.22 ± 1.91 g CO2 m-2 day-1. While CO2 flux dominated in absolute terms (11.4 ± 5.9 t/ha/year) CH4 had a far greater climate impact when expressed as sustained global warming potential (36.5 ± 35.5 t CO2-eq/ha/year). CH4 fluxes peaked in warmer months, while CO2 patterns were more variable. Dissolved CH4 decreased with depth, pH, oxygen, and nitrogen, while dissolved CO2 decreased with depth and pH but increased with air pressure, carbon, and sediment depth. As human-made ponds are classed as anthropogenic systems, their emissions should be included in national GHG inventories and land-based mitigation strategies. These findings highlight the importance of integrating agricultural pond emissions into climate policy and carbon budgeting.

Chemical recycling is gaining attention to advance the circular economy. This study presents the first life cycle assessment (LCA) of real-world waste polyamide 6 (PA6) remonomerization to caprolactam, evaluating four depolymerization routes: acidic, hydrothermal, alcoholysis, and alkaline. We established an automated Python-Aspen Plus-LCA workflow, systematically mapping variations in PA6 waste composition and key process parameters onto probability distributions of environmental impacts. Results show that the hydrothermal process has the highest impacts in six of nine categories, while the solvent-free, alkaline NaOH route consistently shows the lowest. Despite lower energy demands, the acidic H3PO4 process is not environmentally superior to the alcoholysis route. For the hydrothermal route, results are strongly driven by the water-to-feed ratio. However, its global warming potential (GWP) remains above that of fossil-based caprolactam. In contrast, the alcoholysis and acidic processes lower GWP by ∼35%, whereas the NaOH route achieves an ∼80% reduction to 1.46 kg CO2-eq/kg caprolactam. Although chemical recycling can mitigate impacts, no process consistently meets the net-zero emission carbon budget needed to limit global warming to 1.5 °C. As the NaOH process comes closest to this target and demonstrates the strongest environmental and economic performance, future research should focus on scaling-up solvent-free chemical recycling.

ABSTRACT The spruce budworm is one of the principal defoliators affecting forest health in Canada. Studying the impact of spruce budworm on forests including understanding the extent and severity of tree defoliation and mortality caused by the outbreaks is important for forest management. In this study, we utilized LandTrendr algorithm to get synthetic Landsat time-series data and used it to characterize spruce budworm outbreaks. Here, we built 14 configurations of predictors from different seasonal mosaics (summer mosaic, winter mosaic, and a combination of summer and winter mosaic) and various data sources including remote sensing data, aerial survey data, and a combination of both. We then employed a random forest model, incorporating data from 892 field plots to estimate defoliation and mortality caused by the spruce budworm in eastern Québec in the years 2008, 2013, 2018 and 2022. Using only remote sensing data, an R 2 value of 78% for defoliation and 55% for mortality was obtained as the best results. Incorporating aerial survey data resulted in an increase of 1% for defoliation and 7% for mortality. We also found that the combination of summer and winter mosaic data resulted in the highest R 2 values, with improvements of 1–8% for defoliation and 2–14% for mortality compared to models using data from single season. Through the variable importance ranked by the best model configurations for defoliation and mortality, we concluded that normalize burn ratio from winter mosaic served as the most important variable for the defoliation and cumulative defoliation rating from aerial survey ranked the first in mortality. The proposed approach can be used to obtain yearly continuous defoliation and mortality maps and thus assist in monitoring forests and their dynamics during spruce budworm outbreaks for carbon budget modelling.

The remaining carbon budget (RCB) of countries provides a benchmark for evaluating national mitigation efforts and was central to a recent European Court of Human Rights’ ruling. However, estimates of national RCBs are inconsistent with CO2 accounting in national greenhouse gas inventories (NGHGIs). Here, we align RCBs with NGHGI accounting standards. For 2024, NGHGI alignment reduces the 1.5 °C (50%) global RCB by ~100 GtCO2 ( ≈ 50%) and the 2 °C (66%) RCB by ~200 GtCO2 ( ≈ 20%). Thus, we estimate the 1.5 °C (50%) NGHGI-consistent global RCB to be depleted by 2027. We provide NGHGI-consistent national RCBs for common allocation methods and most countries. Following Paris Agreement equity principles, we find that by 2025, 64–85 countries could have exceeded their fair-share RCB for 1.5 °C (50%). While national RCBs depend on normative choices and are unlikely to directly drive negotiations, our framework enables more methodologically robust RCB calculations to track country-level mitigation progress.

Cyanobacterial blooms are increasing in frequency, intensity, and duration in both freshwater and marine environments, potentially enhancing carbon sequestration by producing recalcitrant dissolved organic carbon (RDOC). We conducted monthly analyses of dissolved organic matter (DOM) composition and bacterial community dynamics in Lake Taihu (Meiliang Bay), China, integrating fluorescence DOM and ¹H NMR to quantify carboxyl-rich alicyclic molecules (CRAM) as a molecular proxy for RDOC. Estimated CRAM increased from 51.86 ± 11.22 μM C in the non-bloom period to 60.80 ± 8.21 μM C during blooms (~17% higher). The annual average RDOC was 62.93 ± 10.66 μM C, accounting for ~16% of the total DOC. Bacterial community analysis revealed that labile DOC was actively metabolized and transformed into more recalcitrant compounds through microbial carbon pump mechanisms. Specifically, the CL500-29 marine group and Sphaerotilus contributed to the degradation of protein-like DOM, while the CL500-29 and hgc1 clades played key roles in CRAM formation. The pronounced RDOC enrichment in eutrophic lakes compared to non-eutrophic lakes, rivers, and marine systems underscores the potential of eutrophic lakes to function as significant carbon sinks, highlighting the necessity of integrating bloom-driven RDOC accumulation into carbon budget frameworks to reassess the long-term carbon sequestration potential of these systems.

Abstract The large annual carbon source over northern tropical Africa (NTA), inferred from satellite CO 2 , remains highly debated. Using observing system simulation experiments with Orbiting Carbon Observatory‐2 (OCO‐2) sampling, we show that seasonally dependent sampling can lead to overestimated annual fluxes. These biases arise when prior flux seasonal cycle differs from the assumed truth. Since OCO‐2 provides more observations during the non‐growing season, posterior fluxes are more constrained in that period. When prior fluxes underestimate the seasonal amplitude, the posterior carbon sink during the growing season is underestimated, leading to a net positive bias. This effect is supported by real OCO‐2 data, where we hypothesize that underestimating fire emissions during non‐growing season and weaker seasonality of prior fluxes may contribute to overestimated annual fluxes. Our results highlight the need to improve prior flux estimates and expand observational coverage during the growing season to reduce biases in regional carbon budget assessments over NTA.

Efficient energy use and carbon management are central to promoting sustainable agricultural practices. A two-year field experiment was conducted to compare direct and residual effect of soil applied Zn, B, S, and foliar applied Zn and B on system productivity, profitability, energy budgeting, and carbon efficiency in a cluster bean–mustard cropping system. Thirteen treatments, comprising soil and foliar applications of Zn, B, and S at varying levels, were evaluated in a randomized block design with three replications. Direct and residual effect of soil application of 4.0 kg Zn ha−1, 1.5 kg B ha−1, and 60 kg S ha−1 significantly improved system productivity, carbon budgeting, and energy indices of the two-year cluster bean–mustard system. The combined foliar application of Zn and B also significantly improved net energy output, energy profitability, and human energy profitability, while reducing specific energy. Maximum carbon output during I and II year (9031.42 kg ha−1, 8617.64 kg ha−1) and carbon sustainability index were achieved with soil-applied 1.5 kg B ha−1 and 0.25% foliar Zn application. Economic analysis revealed that the 4.0 kg Zn ha−1 treatment consistently achieved the highest gross returns, net returns, and benefit–cost ratio across both years. Overall, the strategic application of Zn, B, and S improved energy and carbon efficiencies, yield attributes, and profitability in cluster bean-mustard cropping, offering a sustainable and climate-resilient model for nutrient-depleted soils in India.

Nitrogen pollution alters bacterial carbonate mineralization potential in karst river.

Exploring the spatio-temporal pattern， dynamic evolution， and carbon compensation zoning of the county land use carbon budget has great practical significance for territorial spatial pattern optimization and building a fair and effective regional carbon compensation mechanism in the Beijing-Tianjin-Hebei Region. Based on land use cover， nighttime light， and energy consumption data， a land use carbon budget estimation model was constructed in the Beijing-Tianjin-Hebei Region area. Based on the exploratory spatial data analysis method and kernel density estimation， the spatio-temporal pattern and dynamic evolution trend of carbon emissions were analyzed. The economic value of carbon offsetting was calculated based on the carbon offsetting value model. Finally， carbon compensation zoning was carried out based on K-means clustering combined with ecological function zoning. The results indicated that： ① The fitting R2 of the indirect carbon emission estimation model for construction land was 0.776 8， with good simulation accuracy and the estimation effect meeting the expected standards. ② The carbon sink in the Beijing-Tianjin-Hebei Region showed a continuous growth trend； the carbon source showed a decreasing trend after peaking； and the overall increase in net carbon emissions was consistent with the carbon source and exhibited significant positive spatial correlation， with four types of aggregation patterns. ③ The absolute difference in net carbon emissions between districts and counties in the Beijing-Tianjin-Hebei Region as a whole， Tianjin， and Hebei Province showed a trend of expansion， while the absolute difference in net carbon emissions between districts in Beijing shifted from expansion to a trend of narrowing. The tailing effect in the Beijing-Tianjin-Hebei region as a whole and the three provinces was quite significant. ④ In 2022， Xicheng and Dongcheng districts in Beijing and Heping district in Tianjin were key areas for payment. Chongli district in Zhangjiakou， Daxing district in Beijing， and Fengning Manchu Autonomous County in Chengde were key areas for compensation. The compensation areas-restricted development zones included 76 districts and counties， which was the type with the highest proportion， mainly concentrated in most districts and counties of the Yanshan-Taihang Mountain ecological conservation area and the Bashang Plateau ecological protection area in Hebei Province.

Polycyclic aromatic hydrocarbons (PAHs) constitute a significant fraction of the Universe's carbon budget, playing a key role in the cosmic carbon cycle and dominating the mid-infrared spectra of astrophysical environments in which they reside. Although PAHs are known to form in the circumstellar envelopes of post-asymptotic giant branch stars, their formation and evolution are still not well understood. We aim to understand how pristine complex hydrocarbons and PAHs in circumstellar environments transition to the PAHs observed in the interstellar medium. The mid-infrared PAH spectra (5-18 of the planetary nebula, NGC 7027, were investigated using spectral cubes from JWST MIRI-MRS. We report the first detection of spatially resolved variations of the PAH spectral profiles across class ļassA, ļassAB, and ļassB in all major PAH bands (6.2, 7.7, 8.6, and 11.2 within a single source, NGC 7027. These variations are linked to morphological structures within NGC 7027. Clear correlations are revealed between the 6.2, 7.7, and 8.6 features, where the red components (6.26, 7.8, and 8.65 exhibit a strong correlation and the same is found for the blue components of the 6.2 and 7.7 features (6.205 and 7.6 The blue component of the 8.6 feature (8.56 appears to be independent of the other components. We link this behavior to differences in the molecular structure of their PAH subpopulations. Decomposition of the 11.2 band confirms two previously identified components, with the broader 11.25 component attributed to emission from very small grains or PAH clusters rather than PAH emission. We show that PAH profile classes generally vary with proximity to the central star's UV radiation field, suggesting class ļassB PAHs represent more processed species while class ļassA PAHs remain relatively pristine, challenging current notions on the spectral evolution of PAHs.

Abstract. The boreal forest has experienced the fastest warming of any forested biome in recent decades. While vegetation–climate models predict a northward migration of boreal tree cover, the long-term studies required to test the hypothesis have been confined to regional analyses, general indices of vegetation productivity, and data calibrated to other ecoregions. Here we report a comprehensive test of the magnitude, direction, and significance of changes in the distribution of the boreal forest based on the longest and highest-resolution time-series of calibrated satellite maps of tree cover to date. From 1985 to 2020, boreal tree cover expanded by 0.844 million km2, a 12 % relative increase since 1985, and shifted northward by 0.29° mean and 0.43° median latitude. Gains were concentrated between 64–68° N and exceeded losses at southern margins, despite stable disturbance rates across most latitudes. Forest age distributions reveal that young stands (up to 36 years) now comprise 15.4 % of forest area and hold 1.1–5.9 Pg of aboveground biomass carbon, with the potential to sequester an additional 2.3–3.8 Pg C if allowed to mature. These findings confirm the northward advance of the boreal forest and implicate the future importance of the region's greening to the global carbon budget.

Abstract. Long-term land-use changes have a profound impact on terrestrial ecosystems and the associated carbon balance. Current estimates of China's historical carbon emissions induced by land-use change vary widely. Here, current mainland China was taken as the study area, and the 32 provincial units (excluding Macao and Hong Kong) were merged into 25 regions. We utilized a bookkeeping method to quantify China's annual carbon budget resulting from land-use change between 1000 and 2019, driven by a millennial dataset of land-use change in China at provincial level, assisted by comprehensive soil and vegetation carbon density datasets. This approach, which was supported by high-confidence land-use change data, a comprehensive carbon density database compiled from over 10 000 existing field samples, and the latest published disturbance-response curves, enhanced the accuracy of carbon budget estimates. The results revealed that cumulative carbon emissions from land-use change in China reached 19.61 Pg C over the past millennium. Moreover, critical turning points occurred in the early 18th century and early 1980s, with emissions accelerating in the 18th century and transitioning from carbon source to carbon sink in the early 1980s. Our findings revealed that the values were 68 %–328 % higher than the previous 300-year estimates, suggesting that historical carbon emissions from land-use change in China may have been significantly underestimated. This study provides a robust historical baseline for assessing both present and future terrestrial ecosystem carbon budgets at national and provincial scales. The dataset is available at https://doi.org/10.5281/zenodo.14557386 (Yang et al., 2025).

Abstract. The partial pressure of carbon dioxide (pCO2) on the surface of the ocean is crucial for quantifying and evaluating the ocean carbon budget. Insufficient consideration of the effects at the sea area scale makes it difficult to comprehensively evaluate the spatiotemporal distribution characteristics and variation patterns of pCO2. This study constructed a pCO2 evaluation dataset based on LDEO measurement data and multi-source data. After conducting correlation testing on a global, far sea, and near sea scale, an ocean surface pCO2 evaluation model was constructed using multiple linear regression, convolutional neural network, gated recurrent unit, long short-term memory network, generalized additive model, extreme gradient boosting, least squares boosting, and random forest. Performance evaluation indicates that the random-forest model consistently achieves the best accuracy across all spatial scales, yielding a global RMSE of 6.123 µatm and an R2 of 0.986. In the open ocean, RMSE decreases to 4.699 µatm and R2 rises to 0.988, whereas in coastal waters RMSE increases to 8.044 µatm and R2 declines to 0.972. Based on this, the annual sea surface pCO2 distribution of 0.25° × 0.25° from 2000 to 2019 was reconstructed. The reconstructed field shows a typical equatorial high/polar low pattern, as well as an overall upward trend consistent with independent observations, with acceleration particularly evident in specific regions of subtropical coastal oceans.