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Nitrous oxide (N2O) is an important greenhouse gas (GHG) that also contributes to depletion of ozone in the stratosphere. Agricultural soils account for about 60% of anthropogenic N2O emissions. Most national GHG reporting to the United Nations Framework Convention on Climate Change assumes nitrogen (N) additions drive emissions during the growing season, but soil freezing and thawing during spring is also an important driver in cold climates. We show that both atmospheric inversions and newly implemented bottom-up modeling approaches exhibit large N2O pulses in the northcentral region of the United States during early spring and this increases annual N2O emissions from croplands and grasslands reported in the national GHG inventory by 6 to 16%. Considering this, emission accounting in cold climate regions is very likely underestimated in most national reporting frameworks. Current commitments related to the Paris Agreement and COP26 emphasize reductions of carbon compounds. Assuming these targets are met, the importance of accurately accounting and mitigating N2O increases once CO2 and CH4 are phased out. Hence, the N2O emission underestimate introduces additional risks into meeting long-term climate goals.
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Most national GHG inventories estimating direct N2 O emissions from managed soils rely on a default Tier 1 emission factor (EF1 ) amounting to 1% of nitrogen inputs. Recent research has, however, demonstrated the potential for refining the EF1 considering variables that are readily available at national scales. Building on existing reviews, we produced a large dataset (n = 848) enriched in dry and low latitude tropical climate observations as compared to former global efforts and disaggregated the EF1 according to most meaningful controlling factors. Using spatially explicit N fertilizer and manure inputs, we also investigated the implications of using the EF1 developed as part of this research and adopted by the 2019 IPCC refinement report. Our results demonstrated that climate is a major driver of emission, with an EF1 three times higher in wet climates (0.014, 95% CI 0.011-0.017) than in dry climates (0.005, 95% CI 0.000-0.011). Likewise, the form of the fertilizer markedly modulated the EF1 in wet climates, where the EF1 for synthetic and mixed forms (0.016, 95% CI 0.013-0.019) was also almost three times larger than the EF1 for organic forms (0.006; 95% CI 0.001-0.011). Other factors such as land cover and soil texture, C content, and pH were also important regulators of the EF1 . The uncertainty associated with the disaggregated EF1 was considerably reduced as compared to the range in the 2006 IPCC guidelines. Compared to estimates from the 2006 IPCC EF1 , emissions based on the 2019 IPCC EF1 range from 15% to 46% lower in countries dominated by dry climates to 7%-37% higher in countries with wet climates and high synthetic N fertilizer consumption. The adoption of the 2019 IPCC EF1 will allow parties to improve the accuracy of emissions' inventories and to better target areas for implementing mitigation strategies.
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Gases de Efeito Estufa , Agricultura , Fertilizantes/análise , Gases de Efeito Estufa/análise , Nitrogênio/análise , Óxido Nitroso/análise , Solo , Clima Tropical , IncertezaRESUMO
Understanding the potential for greenhouse gas (GHG) mitigation in agricultural lands is a critical challenge for climate change policy. This study uses the DAYCENT ecosystem model to predict GHG mitigation potentials associated with soil management in Chinese cropland systems. Application of ecosystem models, such as DAYCENT, requires the evaluation of model performance with data sets from experiments relevant to the climate and management of the study region. DAYCENT was evaluated with data from 350 cropland experiments in China, including measurements of nitrous oxide emissions (N2 O), methane emissions (CH4 ), and soil organic carbon (SOC) stock changes. In general, the model was reasonably accurate with R(2) values for model predictions vs. measurements ranging from 0.71 to 0.85. Modeling efficiency varied from 0.65 for SOC stock changes to 0.83 for crop yields. Mitigation potentials were estimated on a yield basis (Mg CO2 -equivalent Mg(-1) Yield). The results demonstrate that the largest decrease in GHG emissions in rainfed systems are associated with combined effect of reducing mineral N fertilization, organic matter amendments and reduced-till coupled with straw return, estimated at 0.31 to 0.83 Mg CO2 -equivalent Mg(-1) Yield. A mitigation potential of 0.08 to 0.36 Mg CO2 -equivalent Mg(-1) Yield is possible by reducing N chemical fertilizer rates, along with intermittent flooding in paddy rice cropping systems.
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Agricultura/métodos , Poluentes Atmosféricos/análise , Poluição do Ar/prevenção & controle , Efeito Estufa/prevenção & controle , Metano/análise , Modelos Teóricos , Óxido Nitroso/análise , Carbono/análise , China , Simulação por Computador , Produtos Agrícolas , Ecossistema , Solo/químicaRESUMO
Agriculture in developing countries has attracted increasing attention in international negotiations within the United Nations Framework Convention on Climate Change for both adaptation to climate change and greenhouse gas mitigation. However, there is limited understanding about potential complementarity between management practices that promote adaptation and mitigation, and limited basis to account for greenhouse gas emission reductions in this sector. The good news is that the global research community could provide the support needed to address these issues through further research linking adaptation and mitigation. In addition, a small shift in strategy by the Intergovernmental Panel on Climate Change (IPCC) and ongoing assistance from agricultural organizations could produce a framework to move the research and development from concept to reality. In turn, significant progress is possible in the near term providing the basis for UNFCCC negotiations to move beyond discussion to action for the agricultural sector in developing countries.
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Agricultura/métodos , Poluição do Ar/prevenção & controle , Mudança Climática , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Países em DesenvolvimentoRESUMO
Natural climate solutions provide opportunities to reduce greenhouse gas emissions and the United States is among a growing number of countries promoting storage of carbon in agricultural soils as part of the climate solution. Historical patterns of soil organic carbon (SOC) stock changes provide context about mitigation potential. Therefore, our objective was to quantify the influence of climate-smart soil practices on SOC stock changes in the top 30 cm of mineral soils for croplands in the United States using the DayCent Ecosystem Model. We estimated that SOC stocks increased annually in US croplands from 1995 to 2015, with the largest increase in 1996 of 16.6 Mt C (95% confidence interval ranging from 6.1 to 28.2 Mt CO2 eq.) and the lowest increase in 2015 of 10.6 Mt C (95% confidence interval ranging from - 1.8 to 22.2 Mt C). Most climate-smart soil practices contributed to increases in SOC stocks except for winter cover crops, which had a negligible impact due to a relatively small area with cover crop adoption. Our study suggests that there is potential for enhancing C sinks in cropland soils of the United States although some of the potential has been realized due to past adoption of climate-smart soil practices.
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Agriculture soils are responsible for a large proportion of global nitrous oxide (N2O) emissions-a potent greenhouse gas and ozone depleting substance. Enhanced-efficiency nitrogen (N) fertilizers (EENFs) can reduce N2O emission from N-fertilized soils, but their effect varies considerably due to a combination of factors, including climatic conditions, edaphic characteristics and management practices. In this study, we further developed the DayCent ecosystem model to simulate two EENFs: controlled-release N fertilizers (CRNFs) and nitrification inhibitors (NIs) and evaluated their N2O mitigation potentials. We implemented a Bayesian calibration method using the sampling importance resampling (SIR) algorithm to derive a joint posterior distribution of model parameters that was informed by N2O flux measurements from corn production systems a network of experimental sites within the GRACEnet program. The joint posterior distribution can be applied to estimate predictions of N2O reduction factors when EENFs are adopted in place of conventional urea-based N fertilizer. The resulting median reduction factors were - 11.9% for CRNFs (ranging from -51.7% and 0.58%) and - 26.7% for NIs (ranging from -61.8% to 3.1%), which is comparable to the measured reduction factors in the dataset. By incorporating EENFs, the DayCent ecosystem model is able to simulate a broader suite of options to identify best management practices for reducing N2O emissions.
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Fertilizantes , Óxido Nitroso , Agricultura , Teorema de Bayes , Ecossistema , Fertilizantes/análise , Nitrogênio , Óxido Nitroso/análise , SoloRESUMO
Adoption of no-till management on croplands has become a controversial approach for storing carbon in soil due to conflicting findings. Yet, no-till is still promoted as a management practice to stabilize the global climate system from additional change due to anthropogenic greenhouse gas emissions, including the 4 per mille initiative promoted through the UN Framework Convention on Climate Change. We evaluated the body of literature surrounding this practice, and found that SOC storage can be higher under no-till management in some soil types and climatic conditions even with redistribution of SOC, and contribute to reducing net greenhouse gas emissions. However, uncertainties tend to be large, which may make this approach less attractive as a contributor to stabilize the climate system compared to other options. Consequently, no-till may be better viewed as a method for reducing soil erosion, adapting to climate change, and ensuring food security, while any increase in SOC storage is a co-benefit for society in terms of reducing greenhouse gas emissions.
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Land use and management activities have a substantial impact on carbon stocks and associated greenhouse gas emissions and removals. However, it is challenging to discriminate between anthropogenic and non-anthropogenic sources and sinks from land. To address this problem, the Intergovernmental Panel on Climate Change developed a managed land proxy to determine which lands are contributing anthropogenic greenhouse gas emissions and removals. Governments report all emissions and removals from managed land to the United Nations Framework Convention on Climate Change based on this proxy, and policy interventions to reduce emissions from land use are expected to focus on managed lands. Our objective was to review the use of the managed land proxy, and summarize the criteria that governments have applied to classify land as managed and unmanaged. We found that the large majority of governments are not reporting on their application of the managed land proxy. Among the governments that do provide information, most have assigned all area in specific land uses as managed, while designating all remaining lands as unmanaged. This designation as managed land is intuitive for croplands and settlements, which would not exist without management interventions, but a portion of forest land, grassland, and wetlands may not be managed in a country. Consequently, Brazil, Canada and the United States have taken the concept further and delineated managed and unmanaged forest land, grassland and wetlands, using additional criteria such as functional use of the land and accessibility of the land to anthropogenic activity. The managed land proxy is imperfect because reported emissions from any area can include non-anthropogenic sources, such as natural disturbances. However, the managed land proxy does make reporting of GHG emissions and removals from land use more tractable and comparable by excluding fluxes from areas that are not directly influenced by anthropogenic activity. Moreover, application of the managed land proxy can be improved by incorporating additional criteria that allow for further discrimination between managed and unmanaged land.
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[This corrects the article DOI: 10.1371/journal.pone.0172861.].
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We evaluated the accuracy and precision of the CENTURY soil organic matter model for predicting soil organic carbon (SOC) sequestration under rainfed corn-based cropping systems in the US. This was achieved by inversely modeling long-term SOC data obtained from 10 experimental sites where corn, soybean, or wheat were grown with a range of tillage, fertilization, and organic matter additions. Inverse modeling was accomplished using a surrogate model for CENTURY's SOC dynamics sub-model wherein mass balance and decomposition kinetics equations from CENTURY are coded and solved by using a nonlinear regression routine of a standard statistical software package. With this approach we generated statistics of CENTURY parameters that are associated with the effects of N fertilization and organic amendment on SOC decay, which are not as well quantified as those of tillage, and initial status of SOC. The results showed that the fit between simulated and observed SOC prior to inverse modeling (R2 = 0.41) can be improved to R2 = 0.84 mainly by increasing the rate of SOC decay up to 1.5 fold for the year in which N fertilizer application rates are over 200 kg N ha-1. We also observed positive relationships between C inputs and the rate of SOC decay, indicating that the structure of CENTURY, and therefore model accuracy, could be improved by representing SOC decay as Michaelis-Menten kinetics rather than first-order kinetics. Finally, calibration of initial status of SOC against observed levels allowed us to account for site history, confirming that values should be adjusted to account for soil condition during model initialization. Future research should apply this inverse modeling approach to explore how C input rates and N abundance interact to alter SOC decay rates using C inputs made in various forms over a wider range of rates.
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Sequestro de Carbono , Carbono/química , Solo/química , Agricultura/métodos , Algoritmos , Produtos Agrícolas , Fertilizantes , Cinética , Modelos Estatísticos , Método de Monte Carlo , Nitrogênio/química , Dinâmica não Linear , Chuva , Análise de Regressão , Sensibilidade e Especificidade , Software , Glycine max , Triticum , Estados Unidos , Zea maysRESUMO
Soil organic matter models are widely used to study soil organic carbon (SOC) dynamics. Here, we used the CENTURY model to simulate SOC in wheat-corn cropping systems at three long-term fertilization trials. Our study indicates that CENTURY can simulate fertilization effects on SOC dynamics under different climate and soil conditions. The normalized root mean square error is less than 15% for all the treatments. Soil carbon presents various changes under different fertilization management. Treatment with straw return would enhance SOC to a relatively stable level whereas chemical fertilization affects SOC differently across the three sites. After running CENTURY over the period of 1990-2050, the SOC levels are predicted to increase from 31.8 to 52.1 Mg ha-1 across the three sites. We estimate that the carbon sequestration potential between 1990 and 2050 would be 9.4-35.7 Mg ha-1 under the current high manure application at the three sites. Analysis of SOC in each carbon pool indicates that long-term fertilization enhances the slow pool proportion but decreases the passive pool proportion. Model results suggest that change in the slow carbon pool is the major driver of the overall trends in SOC stocks under long-term fertilization.
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Agricultura/métodos , Produtos Agrícolas/crescimento & desenvolvimento , Fertilizantes , Modelos Teóricos , Triticum/crescimento & desenvolvimento , Zea mays/crescimento & desenvolvimento , Carbono/análise , Ciclo do Carbono , China , Simulação por Computador , Esterco , Chuva , Solo/química , Estatística como Assunto , Temperatura , Fatores de TempoRESUMO
Grassland management affects soil organic carbon (SOC) storage and can be used to mitigate greenhouse gas emissions. However, for a country to assess emission reductions due to grassland management, there must be an inventory method for estimating the change in SOC storage. The Intergovernmental Panel on Climate Change (IPCC) has developed a simple carbon accounting approach for this purpose, and here we derive new grassland management factors that represent the effect of changing management on carbon storage for this method. Our literature search identified 49 studies dealing with effects of management practices that either degraded or improved conditions relative to nominally managed grasslands. On average, degradation reduced SOC storage to 95% +/- 0.06 and 97% +/- 0.05 of carbon stored under nominal conditions in temperate and tropical regions, respectively. In contrast, improving grasslands with a single management activity enhanced SOC storage by 14% +/- 0.06 and 17% +/- 0.05 in temperate and tropical regions, respectively, and with an additional improvement(s), storage increased by another 11% +/- 0.04. We applied the newly derived factor coefficients to analyze C sequestration potential for managed grasslands in the U.S., and found that over a 20-year period changing management could sequester from 5 to 142 Tg C yr(-1) or 0.1 to 0.9 Mg C ha(-1) yr(-1), depending on the level of change. This analysis provides revised factor coefficients for the IPCC method that can be used to estimate impacts of management; it also provides a methodological framework for countries to derive factor coefficients specific to conditions in their region.