Land conflicts from overlapping claims in Brazil's rural environmental registry.

Satellite-based land use monitoring and farm-level traceability offer opportunities for targeted zero-deforestation interventions on private lands. Brazil's Rural Environmental Registry (Cadastro Ambiental Rural, or "CAR"), a land cadaster based on self-declaration of property boundaries, was created to monitor compliance with national forest laws. It has become an important enabling measure for sustainable supply chain initiatives like the Amazon Soy Moratorium. However, CAR enrollment is increasingly used to bolster illegal land claims, putting it at the heart of land grabbing dynamics. Self-declaration of properties in the CAR offers a unique situation to study land conflicts and their impact on land use decisions on a large scale. We quantified competing land claims among 846,420 registrations in the Brazilian Legal Amazon and applied a series of generalized linear mixed-effects models. We determined that CAR overlaps are more prevalent on larger registrations, in more densely settled areas, and in areas with less secure land tenure. We tested how landholders respond to land conflicts, finding significantly more deforestation and declared legal forest reserve on lands with multiple claims. CAR overlap results in an overestimation of forest reserves by up to 9.7 million hectares when considering double-counted and deforested areas of reserves, highlighting an overlooked form of Forest Code noncompliance. While the CAR continues to be used as evidence of land tenure, we conclude that the formalization of land claims through self-declarations is inadequate to decrease conflicts. CAR overlap information provides objective evidence of land conflict that authorities can leverage with field inspection to ensure peaceful occupation before issuing land titles.

Methane Emissions from Natural Gas Gathering Pipelines in the Permian Basin.

The rapid reduction of methane emissions, especially from oil and gas (O&G) operations, is a critical part of slowing global warming. However, few studies have attempted to specifically characterize emissions from natural gas gathering pipelines, which tend to be more difficult to monitor on the ground than other forms of O&G infrastructure. In this study, we use methane emission measurements collected from four recent aerial campaigns in the Permian Basin, the most prolific O&G basin in the United States, to estimate a methane emission factor for gathering lines. From each campaign, we calculate an emission factor between 2.7 (+1.9/-1.8, 95% confidence interval) and 10.0 (+6.4/-6.2) Mg of CH4 year-1 km-1, 14-52 times higher than the U.S. Environmental Protection Agency's national estimate for gathering lines and 4-13 times higher than the highest estimate derived from a published ground-based survey of gathering lines. Using Monte Carlo techniques, we demonstrate that aerial data collection allows for a greater sample size than ground-based data collection and therefore more comprehensive identification of emission sources that comprise the heavy tail of methane emissions distributions. Our results suggest that pipeline emissions are underestimated in current inventories and highlight the importance of a large sample size when calculating basinwide pipeline emission factors.