Carbon Solutions (United States)

Public perception towards pipeline development and eminent domain concerns around pipeline routing represent a major obstacle in the implementation of carbon capture and sequestration (CCS) infrastructure. Previously, pipeline routing software and literature has focused on finding the least-cost path for routing pipelines. However, these methods often rely on incomplete information and cannot account for social issues such as negotiations with landowners or the complex cost-benefit analysis when considering alternative routing pathways. To address this, we develop and apply the k-shortest paths with limited overlap (kSPwLO) algorithm ESX to pipeline routing scenarios to provide many alternative paths and assess how these paths can inform practical pipeline development concerns. First, we apply the algorithm to a simple case of routing between one emissions source and one sequestration sink while adjusting the input parameter of the ESX algorithm. Next, we apply the algorithm to a complex network of sources and sinks to determine how alternate pipeline routes might impact the overall network structure, and we compare the costs of the alternate structure to the optimal solution provided by the SimCCSPRO CCS infrastructure design software. We find that the ESX algorithm efficiently and effectively finds alternate routing paths at a marginal increase in transportation cost (4.5–6.2%) when compared against the optimal route. We also find that many pipeline segments deploy intermittently across different routing simulations, indicating that, at the given cost uncertainty, many different solutions exist and network structure is often robust to changes in pipeline routing. We demonstrate that the ESX algorithm can be used to develop a cost-benefit analysis for choosing between multiple pipeline routes.

Soil structure can mitigate both mechanical impedance and water stress, thereby modulating root elongation and access to deep soil water. Although process-based root growth models represent soil–root interactions, they rarely account explicitly for structural conditions and their consequences for the combined effects of water and mechanical stresses on root growth. We quantify how soil structure under no-tillage influences soybean root elongation, effective rooting depth, and water-deficit mitigation, and we parameterize these effects in a biophysical root-growth model. A long-term field experiment established in 2016 compared three cropping systems preceding soybean (Glycine max): ruzigrass (Urochloa ruziziensis), maize (Zea mays), and fallow. Soybean root length density and soil physical attributes were measured in nine layers down to 210 cm. Effective rooting depth was defined as the depth containing 95% of total root length. Plant-available water was computed from soil water retention between −60 and −15,000 hPa, and readily available water was assumed as 50% of plant-available water within the rooted zone. Grain yield was determined at harvest. In addition, soybean root elongation rate was measured in the laboratory using core from field and repacked samples across gradients of degree of saturation and soil penetration resistance. The structural effect was incorporated as a parameter in a biophysical model that combines water and mechanical limitations to root elongation. Increasing soil penetration resistance from 1.0 to 3.5 MPa reduced relative root elongation by 46% in preserved structure, whereas reductions reached 76% in repacked soil. At 0.5 MPa and 60% degree of saturation, elongation in repacked soil was 29% higher than in preserved structure, but both structural conditions converged as soil penetration resistance increased to 1.0 MPa. Under 90% degree of saturation, elongation in preserved structure was nearly threefold that in repacked soil. In the field, effective soybean rooting depth (in a trench of 210 cm depth) differed among previous cropping systems, with ruzigrass promoting substantially deeper roots (154.7 cm at 95% cumulative distribution) compared with maize (127.9 cm) and fallow (121.0 cm). Root length density in the 0 to 10 cm layer was highest after ruzigrass (4.72 cm cm-3), followed by maize (3.33 cm cm-3) and fallow (2.48 cm cm-3). Cumulative root length in the soil profile from 0 to 210 cm reached 202.2 cm cm-2 after ruzigrass, compared with 128.4 cm cm-2 after maize and 94.3 cm cm-2 after fallow. Soybean yield was 2.9 (after ruzigrass), 2.6 (after maize), and 2.1 Mg ha-1 (after fallow). Plant-available water in the soybean root zone was 175 mm after ruzigrass, compared with 145 mm after maize and 140 mm after fallow, indicating a 25% increase relative to fallow. Assuming evapotranspiration of 7 mm d-1, this represents approximately 15 days of water supply after ruzigrass versus 12 days after fallow. Preserved soil structure improved soybean root performance under strong physical constraints and increased deep water access. Explicitly representing soil structural conditions in simulation models can improve predictions of rooting depth and drought mitigation under no-tillage.Acknowledgements: AGRISUS Foundation [PA 3534/23], CNPq [409621/2023-4] and FAPESP [23/10427-3 and 23/11945-8].

ABSTRACT The southeastern Amazon region represents one of the critical hotspots of land‐use change (LUC) in Brazil. Conversion of natural ecosystems to agricultural fields triggers mineralization of soil organic matter and decomposition of residual forest biomass, releasing large amounts of nitrogen (N) that, together with subsequent high N‐fertiliser applications, disrupt N biogeochemical cycles. Therefore, we hypothesize that deforestation disrupts surface soil N‐pools, causing their gradual percolation into deeper layers of these highly weathered tropical soils. To test this, we measured total‐N and key fractions—particulate organic matter N (POM‐N), mineral‐associated organic matter N (MAOM‐N), water‐extractable N (WEN), ammonium (NH 4 + ‐N) and nitrate (NO 3 − ‐N)—to 800 cm depth in forest, recently deforested, single‐crop soybean and double‐crop soybean–corn systems in Mato Grosso, Brazil. Compared to the forest, the deforested site showed a 40% reduction in soil total‐N stocks at 10 cm; however, it was 62% higher at depths of 100–300 cm. In the croplands, the soil total‐N stocks remained similar to those in the forest. The POM‐N was nearly absent in the deforested site, whereas the MAOM‐N was consistently lower in both croplands and deforested soils than in the forest. The deforested site had the highest WEN and inorganic‐N (NH 4 + ‐N and NO 3 − ‐N) stocks to 800 cm, with most concentrated in the top 0–200 cm. Croplands had the greatest NO 3 − ‐N stocks at 300–600 cm. Principal component analysis (PCA) showed that WEN and inorganic‐N in the top 100 cm clustered with the deforested site, whereas POM‐N, MAOM‐N and total‐N at the surface clustered with the forest. Below 100 cm, the soil total‐N stock was clustered with the deforested site. These results provide critical insight into the initial mechanism of deep nitrate formation: the breakdown of the N biogeochemical cycle after deforestation, fueled by decomposition and N mineralization from soil organic matter and remaining forest biomass following slash‐and‐burn events on the Amazon–Cerrado agricultural frontier. However, further studies are needed to confirm the spatial and temporal persistence of these patterns across the region.

Carbon farming (CF), also known as low-carbon agriculture or climate-smart agricultural system, has gained significant attention in recent years as a potential nature-based solution for mitigating climate change and food shortage. However, there is a common misconception that CF opposes food security, thus hindering its widespread adoption. There is also a knowledge gap on the roles of the Brazilian government in supporting food security in Africa through its training and support for agricultural practices associated with CF system. In this paper, we accentuated that CF and food security have no opposing objectives but can be achieved simultaneously through integrated agricultural systems (IAS). We further investigated CF, its practices, and agricultural outputs (here referred to as 'products') including food crops, animal products, and by-products resulting from CF systems by sampling the farmers' perceptions in Africa. We also highlighted the agricultural evolutionary reforms in Brazil, the agroecological similarities between Brazil and Africa, and how these contributed to the success of Brazil's agricultural and food security vis-a-vis support to Africa. Additionally, our work identified major Brazil's food security projects in Africa by mapping their distribution across the continent. Finally, we examined the implications of Brazil's CF for food security in Africa by identifying the driving policies, challenges and prospects of the support in improving food security for the rapidly growing African population. This study underscores Brazil's relevance as a model for carbon farming implementation in tropical regions due to its shared agroecological conditions with Africa and its demonstrated success in transforming food systems through integrated, low-carbon agricultural policies. The study will also awaken and reinvigorate the zeal in stakeholders in Africa to follow the footsteps of Brazil in developing their agricultural reforms to be self-reliance in providing enough food for the Africans. • Carbon farming and food security are not opposing but complementary goals. • Agroecological similarities between the regions promoted the success of the programs. • The newly lunched ABC Plan+ of Brazil will generate more projects and food in Africa. • For sustainable success, African heads should address key drivers of food insecurity.

Summary The assessment of soil organic carbon (SOC) stocks relies on several key factors, including the total SOC content of the soil, the bulk density (BD) of the soil, and the depth of the sampled layers. However, traditional methods, particularly those using volumetric cylinders for undisturbed soil sampling, present significant logistical challenges for large-scale projects due to their costly and time-consuming nature, often requiring the excavation of trenches. In response, automated probes, which are commonly used in geological studies, offer a promising alternative, but their application in the context of BD soil studies remains under discussion. The objective of this study was to evaluate the efficacy of a tractor-mounted probe in comparison to the conventional core method for the collection of undisturbed soil samples across a range of soil textures and depths. The results indicated that the coefficient of variation (CV) for the probe’s bulk density (BD) measurements ranged from 3 to 15% in sandy soils but remained consistently below 5% in clay-sandy-loam and clay textures. Despite small differences in BD values between the methods used, SOC stock assessments showed only minor variations across all layers, regardless of soil texture. Therefore, this study demonstrated that the tractor-mounted probe represents a viable and scalable solution for conducting large-scale SOC stock assessments, despite its susceptibility to minor variations in sandy soil conditions. This research contributed to the field of automated soil sampling tool validation and offered alternatives for field operationalization in large-scale carbon projects. It also raised new questions for further investigation into other field conditions