Earth

Many rural communities are struggling to understand the changing climate and how to mitigate and adapt to its negative effects. “Climate literacy” (i.e., an understanding of the climate system, how human actions influence it, and how it affects society and the Earth) may be a necessary precursor to climate action (i.e., steps that help to mitigate or adapt to climate change). For rural communities in the Brazilian Amazon, where access to formal education is limited, grasping abstract concepts like greenhouse gas emissions can be particularly challenging. We asked: Is climate literacy a necessary precursor to climate action? We conducted 22 semi-structured interviews with forest extractivists living within the Chico Mendes Extractive Reserve in the state of Acre, Brazil. We found that forest extractivists are experiencing the impacts of climate change but lack an understanding of its causes and forms of mitigation and are unaware of ways to adapt to it. Improved educational opportunities could support both climate literacy and, in turn, climate action.

Lake Batur, located within a volcanic caldera in Bali, Indonesia, is subjected to anthropogenic pressures related to agriculture, aquaculture, tourism, and religious activities, which may affect its water quality and ecology condition. This study investigates the physicochemical properties of lake water and diatom assemblages preserved in lake sediments to provide insight into environmental conditions in this volcanic alkaline ecosystem. Water quality parameters, including pH, temperature, electrical conductivity (EC), and total dissolved solids (TDS), were measured. Vertical profiles of temperature and conductivity revealed stable stratification, with minimal variation below 20 m water depth. Elevated nitrogen concentrations, including nitrate (NO₃⁻), nitrite (NO₂⁻), and ammonium (NH₄⁺), were observed, particularly in the southern basin, suggesting localized nutrient enrichment. Scanning electron microscopy (SEM) analysis of lake sediment samples identified ten diatom genera, including Ulnaria, Denticula, and Discostella, which are commonly associated with nutrient-enriched freshwater environments. Overall, the results indicate that Lake Batur exhibits conditions consistent with early-stage eutrophication in localized areas, highlighting the importance of continuous monitoring and targeted management strategies to protect the ecological integrity of this volcanic lake system.

This study addresses the global challenge of superficial soil contamination by heavy metals, focusing on differentiating natural geogenic sources from anthropogenic contributions in complex industrial–urban environments. We develop an integrated geostatistical and multivariate framework combining soil metal concentration analysis with AERMOD atmospheric dispersion modeling using a comparative multi-model machine learning approach (including Extreme Gradient Boosting, Random Forest, and Ridge Regression). Applied to the industrialized area of Taranto, Southern Italy, this approach incorporates spatial autocorrelation and multiple environmental predictors to identify contamination patterns and sources. The results reveal variable predictive accuracy across metals, with RF generally outperforming the other algorithms. The model achieved its highest performance for copper (R² = 0.58, RMSE = 25.82), Tin (R² = 0.53, RMSE = 5.95), and chromium, while showing instability for others. These disparities highlight the differential influence of remote sensing data on contamination mapping. The framework advances the quantitative assessment of soil pollution by linking atmospheric deposition and spatial processes with causal interpretability.