Modelling soil carbon sequestration with biochar using RothC

The aim of this work was to assess and predict how biochar influences the soil C dynamics, by modifying the RothC model to simulate the findings of a long-term field experiment on biochar application to a short coppice rotation in Italy. We first modified the model to include two stocks of C input into the soil: the labile and the recalcitrant biochar pools. We also included a parametrized function to account for the priming effect on SOC dynamics in the soil. Secondly, we calibrated the model parameters with the data obtained from the field experiment. Finally, we validated the model results by estimating the remaining biochar amount in the site after 10 years from application, using an isotopic mass balance. The results confirm that biochar degradation can be faster in field conditions in comparison to laboratory experiments; nevertheless, it can contribute to substantially increase the C stock in the long-term. Moreover, the modified RothC model allowed to assess the SCS potential of biochar application in soils, at least in the specific conditions examined, and could represent a flexible tool to assess the effect biochar as a SCS strategy in the long-term. We are exploring the possibility to use data from other long-term field experiment to move in that direction. The results of this study could be added to the Italian biochar database, providing new knowledge about a topic that needs to be explored

Bridging Modeling and Certification to Evaluate Low-ILUC-Risk Practices for Biobased Materials with a User-Friendly Tool

Biobased materials may help to achieve a renewable, circular economy, but their impact could be similar to those of non-renewable materials. In the case of biofuels, the indirect land use change (ILUC) effects determine whether they can provide sustainability benefits compared to fossil fuels. ILUC modeling estimates have large uncertainties, making them difficult to include in a policy aiming at reducing environmental impacts. The Renewable Energy Directive (RED) II reduced ILUC estimate uncertainties by shifting the focus from ILUC environmental impacts to ILUC risk. Nevertheless, this does not take into account either certifiable additionality practices to reduce the ILUC risk for the production of biobased materials, or biobased materials other than biofuels. Here we propose a simple, user-friendly tool to bridge the gap between ILUC modeling and policy, by estimating the ILUC risk of biobased material production and to assess by how much different additionality practices can reduce that risk at different levels of the value chain. This was done by explicitly including the additionality practices in an ILUC model, simplifying the model to a spreadsheet tool that relates automatically the input provided by the user, which may be a producer or a policy maker, with a certain ILUC risk. We demonstrate the functioning of the tool on two examples: maize production in Iowa and in Romania. In Iowa, maize production is already very intensive, so the additionality practices proposed have little effect on its ILUC risk category, and the low-ILUC-risk-produced maize would amount to 0.03 t ha−1 year−1. In Romania there is ample margin for implementation of additionality practices, and thus a large potential to reduce the ILUC risk category of maize production, with low-ILUC-risk-produced maize amounting to 0.19 t ha−1 year −1

Inclusion of biochar in a C dynamics model based on observations from an 8-year field experiment

Biochar production and application as soil amendment is a promising carbon (C)-negative technology to increase soil C sequestration and mitigate climate change. However, there is a lack of knowledge about biochar degradation rate in soil and its effects on native soil organic carbon (SOC), mainly due to the absence of long-term experiments performed in field conditions. The aim of this work was to investigate the long-term degradation rate of biochar in an 8-year field experiment in a poplar short-rotation coppice plantation in Piedmont (Italy), and to modify the RothC model to assess and predict how biochar influences soil C dynamics. The RothC model was modified by including two biochar pools, labile (4% of the total biochar mass) and recalcitrant (96%), and the priming effect of biochar on SOC. The model was calibrated and validated using data from the field experiment. The results confirm that biochar degradation can be faster in field conditions in comparison to laboratory experiments; nevertheless, it can contribute to a substantial increase in the soil C stock in the long term. Moreover, this study shows that the modified RothC model was able to simulate the dynamics of biochar and SOC degradation in soils in field conditions in the long term, at least in the specific conditions examined.Biochar production and application as soil amendment is a promising carbon (C) negative technology to increase soil C sequestration and mitigate climate change. However, there is a lack of knowledge about biochar degradation rate in soil and its effects on native soil organic carbon (SOC), mainly due to the absence of long term experiments performed in field conditions. The aim of this work was to investigate the long term degradation rate of biochar in a field experiment of 8 years in a poplar short rotation coppice plantation in Piedmont (Italy), and to modify the RothC model to assess and predict how biochar influences soil C dynamics. The RothC model was modified by including two biochar pools, labile (4 % of the total biochar mass) and recalcitrant (96 %), and the priming effect of biochar on SOC. The model was calibrated and validated using data from the field experiment. The results confirm that biochar degradation can be faster in field conditions in comparison to laboratory experiments; nevertheless, it can contribute to substantially increase the soil C stock in the long-term. Moreover, this study shows that the modified RothC model was able to simulate the dynamics of biochar and SOC degradation in soils in field conditions in the long term, at least in the specific conditions examined

A Modified Version of RothC to Model the Direct and Indirect Effects of Rice Straw Mulching on Soil Carbon Dynamics, Calibrated in Two Valencian Citrus Orchards

The mulching of agricultural soils has been identified as a viable solution to sequester carbon into the soil, increase soil health, and fight desertification. This is why it is a promising solution for carbon farming in Mediterranean areas. Models are used to project the effects of agricultural practices on soil organic carbon in the future for various soil and climatic conditions, and to help policy makers and farmers assess the best way to implement carbon farming strategies. Here, we modified the widely used RothC model to include mulching practices and their direct and indirect effects on soil organic matter input, soil temperature changes, and soil hydraulic balance. We then calibrated and tested our modified RothC (RothC_MM) using the dataset collected in two field mulching experiments, and we used the tested RothC_MM to estimate the expected soil carbon sequestration due to mulching by the year 2050 for the Valencian Community (Spain). Our results show that RothC_MM improved the fit with the experimental data with respect to basic RothC; RothC_MM was able to model the effects of mulch on soil temperature and soil water content and to predict soil organic carbon (SOC) and CO2 observations taken in the field

RothC-Biochar v. 0.1

File con struttura, equazioni e algoritmi usati nella modifica del modello RothC per includere il Biochar, versione prototipo calibrata e validata su dati di campo, usata per ottenere i risultati di Pulcher et al. 2022 (DOI 10.5194/soil-8-199-2022)

EGU General Assembly Conference Abstracts 2020 May (p. 20951).

Indirect Land Use Change (ILUC) is a land use process driven by increase in land demand and mediated by the global market: for example, the increase in demand for a certain crop in a specific country due to its use for the production of bio-materials drives up the global crop price, eventually resulting in land use change in some other country. Since land demand is already high for food/feed production, ILUC often defines if the production of a bio-material is sustainable or not. ILUC is very difficult to observe and therefore it is usually estimated through models rather measured; different models depends on which part of the complex problem is taken into account: economic equilibrium models (partial, general), causal-descriptive models, normative models. Most of these models are static, i.e. time is not directly factored in the model. A study of the JRC showed that ILUC models have high levels of uncertainty, both within and among models, due to uncertainty in input data, different assumptions and modelling frameworks. The (i) lack of model transparency, (ii) lack of dynamic effects and (iii) high model uncertainties make it difficult to include ILUC in sustainable policies.Here, we present a dynamic causal-descriptive model to estimate changes in land demand as a proxy of the ILUC risk, and test it when increasing the production of bioplastic materials on a global scale. We used a system dynamic framework to (i) maintain the model easy to understand and (ii) account for dynamic effects like delays and feedback loops. We also addressed the (iii) uncertainty problem by: (a) considering ILUC on a global scale only, (b) use yearly time step to avoid short-term economic effects, (c) identifying control variables to use for model validation, (d) modelling only the projected change in land demand and translate it into global risk classes in line with the approach pursued in Europe by the Renewable Energy Directive. The model includes the relevant processes that literature identify as influential for ILUC: use of co-products, competition with the feed sector, price effect on agricultural production (intensive margin), expansion on less suitable land (extensive margin), use of agricultural residues, soil erosion, and increase in agricultural yields. The model was, then, calibrated and validated using the extensive FAOSTAT dataset and then studied using different sensitivity analysis techniques.The validation shows that the model 10 years projections are reliable (~8% error). Both local and global sensitivity analysis show that that the most relevant factor influencing ILUC risk is the trend of agricultural yields which, at the global level and contrary to what is usually assumed in other models, is insensitive to crop prices. Other relevant factors, interesting for policy makers, are the yields of bioplastics and the use of co-products. The analysis shows there are levels of production that have negligible risk in the next 30 years for specific biomasses and at specific growth and processing conditions. However, a full shift of use from fossil-based plastics to bio-based plastics would result in a 200-300 Mha land conversion globally

Funzionalit\ue0 e applicabilit\ue0 del modello LANCA a scala regionale: un caso studio in Emilia-Romagna

Il modello di caratterizzazione LANCA \ue8 stato selezionato dalla Commissione Europea per la valutazione dell\u2019impatto sulla categoria Land Use per il calcolo della Product Environmental Footiprint. Il modello LANCA fornisce valori a scala nazionale. Questo lavoro analizza funzionalit\ue0 e applicabilit\ue0 del modello a scala regionale. In particolare, il caso studio \ue8 localizzato in Emilia Romagna scegliendo seminativi avvicendati come situazione di riferimento e coltivi di mais come nuova destinazione d\u2019uso. Gli algoritmi del modello LANCA sono riprodotti su un foglio di calcolo Excel per calcolare i fattori di caratterizzazione. I risultati mostrano una notevole differenza fra i fattori di caratterizzazione calcolati su base regionale e i loro analoghi nazionali. Sono individuati i dati di input pi\uf9 influenti sui risultati tramite un\u2019analisi di sensitivit\ue0. Infine, i risultati ottenuti con il modello LANCA sono confrontati con la letteratura

A risk evaluation approach for indirect land use change associated to biobased products

Biobased products include a vast range of traditional and innovative materials and substances for purposes other than food and energy such as wood and composite materials, bio-plastics, adhesives, lubricants, paints and many other material categories feeding large economic activities. There is international recognition that developing a climate-smart bio-based economy is essential to the continuation of economic development, reduction of greenhouse gas emissions, and adaptation to climatic change. However, as biobased products are ultimately obtained from land or sea, a specific attention has to be payed when considering additional exploitation. Changes of land/sea uses can rebound and cancel out environmental performances and the original purpose of sustainability. Indirect land use change (ILUC) has been defined as an unintentional, negative, displacement effect of commodities in the primary sector such as agriculture causing additional land use changes. Provided that ILUC depends on specific legacy effects stemming from land condition prior and after land use changes, overall indirect effects are connected to the 1.1 billion tons of greenhouse gases per year generated because of land use changes. However the application of ILUC provisions as for biofuels has been and stays controversial. The Project STAR-ProBio is a multi-actor collaborative research and innovation action and supports the European Commission in the full implementation of European policy initiatives, including the Lead Market Initiative in bio-based products, the industrial policy and the European Bio-economy Strategy. One of the specific goals calls for identifying and mitigating the risks of negative ILUC effects associated to production routes for bio-based products. In this contribution the authors present the conceptual model and the results of the identification of risk factors obtained from the analysis of economic models and a sensitivity analysis performed over one selected case stud