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The substantial climate change mitigation potential of restoring peatlands through rewetting and intensifying agriculture to reduce greenhouse gas (GHG) emissions is largely recognized. The green deal in Denmark aims at restoring 100 000 ha of peatlands by 2030. This area corresponds to more than half of the Danish peatland, with an expected reduction in GHG emissions of almost half of the entire land use, land use change and forestry (LULUFC) emissions. Recent advances established the functional relationship between hydrological regimes, i.e., water table depth (WTD), and CO2 and CH4 emissions. This builds the basis for science-based tools to evaluate and prioritize peatland restoration projects. With this article, we lay the foundation of such a development by developing a high-resolution WTD map for Danish peatlands. Further, we define WTD response functions (CO2 and CH4) fitted to Danish flux data to derive a national GHG emission estimate for peat soils. We estimate the annual GHG emissions to be 2.6 MtCO2-eq , which is around 15 % lower than previous estimates. Lastly, we investigate alternative restoration scenarios and identify substantial differences in the GHG reduction potential depending on the prioritization of fields in the rewetting strategy. If wet fields are prioritized, which is not unlikely in a context of a voluntary bottom-up approach, the GHG reduction potential is just 30 % for the first 10 000 ha with respect to a scenario that prioritizes drained fields. This underpins the importance of the proposed framework linking WTD and GHG emissions to guide a spatially differentiated peatland restoration. The choice of model type used to fit the CO2 WTD response function, the applied global warming potentials and uncertainties related to the WTD map are investigated by means of a scenario analysis, which suggests that the estimated GHG emissions and the reduction potential are associated with coefficients of variation of 13 % and 22 %, respectively. [ABSTRACT FROM AUTHOR]

Atmospheric carbon dioxide (CO2) is the most significant greenhouse gas, and its concentration is continuously increasing, mainly as a consequence of anthropogenic activities. Accurate quantification of CO2 is critical for addressing the global challenge of climate change and for designing mitigation strategies aimed at stabilizing CO2 emissions. Satellites provide the most effective way to monitor the concentration of CO2 in the atmosphere. In this study, we utilized the concentration of the column-averaged dry-air mole fraction of CO2 , i.e., XCO2 retrieved from a CO2 monitoring satellite, the Orbiting Carbon Observatory-2 (OCO-2), and the net primary productivity (NPP) provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the anthropogenic CO2 emissions using the Generalized Regression Neural Network (GRNN) over East and West Asia. OCO-2 XCO2 , MODIS NPP, and the Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) CO2 emission datasets for a period of 5 years (2015–2019) were used in this study. The annual XCO2 anomalies were calculated from the OCO-2 retrievals for each year to remove the larger background CO2 concentrations and seasonal variability. The XCO2 anomaly, NPP, and ODIAC emission datasets from 2015 to 2018 were then used to train the GRNN model, and, finally, the anthropogenic CO2 emissions were estimated for 2019 based on the NPP and XCO2 anomalies derived for the same year. The estimated and the ODIAC CO2 emissions were compared, and the results showed good agreement in terms of spatial distribution. The CO2 emissions were estimated separately over East and West Asia. In addition, correlations between the ODIAC emissions and XCO2 anomalies were also determined separately for East and West Asia, and East Asia exhibited relatively better results. The results showed that satellite-based XCO2 retrievals can be used to estimate the regional-scale anthropogenic CO2 emissions, and the accuracy of the results can be enhanced by further improvement of the GRNN model with the addition of more CO2 emission and concentration datasets. [ABSTRACT FROM AUTHOR]

Scenarios avoiding global warming greater than 1.5 or 2 ∘ C, as stipulated in the Paris Agreement, may require the combined mitigation of anthropogenic greenhouse gas emissions alongside enhancing negative emissions through approaches such as afforestation–reforestation (AR) and biomass energy with carbon capture and storage (BECCS). We use the JULES land surface model coupled to an inverted form of the IMOGEN climate emulator to investigate mitigation scenarios that achieve the 1.5 or 2 ∘ C warming targets of the Paris Agreement. Specifically, within this IMOGEN-JULES framework, we focus on and characterise the global and regional effectiveness of land-based (BECCS and/or AR) and anthropogenic methane (CH4) emission mitigation, separately and in combination, on the anthropogenic fossil fuel carbon dioxide (CO2) emission budgets (AFFEBs) to 2100. We use consistent data and socio-economic assumptions from the IMAGE integrated assessment model for the second Shared Socioeconomic Pathway (SSP2). The analysis includes the effects of the methane and carbon–climate feedbacks from wetlands and permafrost thaw, which we have shown previously to be significant constraints on the AFFEBs. Globally, mitigation of anthropogenic CH4 emissions has large impacts on the anthropogenic fossil fuel emission budgets, potentially offsetting (i.e. allowing extra) carbon dioxide emissions of 188–212 Gt C. This is because of (a) the reduction in the direct and indirect radiative forcing of methane in response to the lower emissions and hence atmospheric concentration of methane and (b) carbon-cycle changes leading to increased uptake by the land and ocean by CO2 -based fertilisation. Methane mitigation is beneficial everywhere, particularly for the major CH4 -emitting regions of India, the USA, and China. Land-based mitigation has the potential to offset 51–100 Gt C globally, the large range reflecting assumptions and uncertainties associated with BECCS. The ranges for CH4 reduction and BECCS implementation are valid for both the 1.5 and 2 ∘ C warming targets. That is the mitigation potential of the CH4 and of the land-based scenarios is similar for regardless of which of the final stabilised warming levels society aims for. Further, both the effectiveness and the preferred land management strategy (i.e. AR or BECCS) have strong regional dependencies. Additional analysis shows extensive BECCS could adversely affect water security for several regions. Although the primary requirement remains mitigation of fossil fuel emissions, our results highlight the potential for the mitigation of CH4 emissions to make the Paris climate targets more achievable. [ABSTRACT FROM AUTHOR]

Recent studies have highlighted the importance of brown carbon (BrC) in various fields, particularly relating to climate change. The incomplete combustion of biomass in open and contained burning conditions is believed to be a significant contributor to primary BrC emissions. So far, few studies have reported the emission factors of BrC from biomass burning, and few studies have specifically addressed which form of light-absorbing carbon, such as black carbon (BC) or BrC, plays a leading role in the total solar light absorption by biomass burning. In this study, the optical integrating sphere (IS) approach was used, with carbon black and humic acid sodium salt as reference materials for BC and BrC, respectively, to distinguish BrC from BC on filter samples. A total of 11 widely used biomass types in China were burned in a typical stove to simulate the real household combustion process. (i) Large differences existed in the emission factors of BrC (EF BrC) among the tested biomass fuels, with a geometric mean EF BrC of 0.71 g kg -1 (0.24–2.09). Both the plant type (herbaceous or ligneous) and burning style (raw or briquetted biomass) might influence the value of EF BrC. The observed reduction in the emissions of light-absorbing carbon (LAC) confirmed an additional benefit of biomass briquetting in climate change mitigation. (ii) The calculated annual BrC emissions from China's household biomass burning amounted to 712 Gg, higher than the contribution from China's household coal combustion (592 Gg). (iii) The average absorption Ångström exponent (AAE) was (2.46±0.53), much higher than that of coal-chunk combustion smoke (AAE=1.30±0.32). (iv) For biomass smoke, the contribution of absorption by BrC to the total absorption by BC+BrC across the strongest solar spectral range of 350–850 nm (FBrC) was 50.8 %. This is nearly twice that for BrC in smoke from household coal combustion (26.5 %). (v) Based on this study, a novel algorithm was developed for estimating the FBrC for perhaps any combustion source (FBrC=0.5519ln⁡AAE+0.0067 , R2=0.999); the FBrC value for all global biomass burning (open+contained) (FBrC-entire) was 64.5 % (58.5 %–69.9 %). This corroborates the dominant role of BrC in total biomass burning absorption. Therefore, the inclusion of BrC is not optional but indispensable when considering the climate energy budget, particularly for biomass burning emissions (contained and open). [ABSTRACT FROM AUTHOR]