Material flow analysis and regional greenhouse gas emissions associated to permanent magnets and batteries used in electric vehicles.

Clean technologies are rapidly increasing in the last decade. In the transport sector, market share of global electric car sales has changed from 0.0 % in 2010 to 3.2 % (2.1million) in 2020, and predictions show that sales could reach near 30 % in 2030. This drastic change is mainly encouraged by environmental goals set to reduce greenhouse gas emissions (GHG) expressed in CO2-eq, not emitted by electric vehicles (EVs) during the use phase. However, clean technologies might cause other impacts during manufacture and, while clearly reduce the dependency on oil, can increase the dependency on other materials. In this context, the objectives of our work are quantifying the critical raw materials needed by permanents magnets and batteries of EVs (neodymium, lithium, and cobalt); their supply risk, performing a material flow analysis; and studying their environmental impacts using the methodology "Environmentally-Extended Multi-Regional Input-Output Analysis". This methodology is used to quantify the produced impacts and the country where the impacts are being produced, in contrast to conventional methodologies that only calculate global impacts. Therefore, environmental impacts are estimated considering different scenarios, based on environmental objectives of the European Union and China. In most scenarios China shows a key role in mining and processing of metals, being the country where major impacts are produced. Obtained results are useful to assess which environmental proposals are more effective to reduce the environmental impact of EVs and set the ground to understand the geostrategic importance of key metals used for EVs manufacture.

Probabilistic multi-pathway human health risk assessment due to heavy metal(loid)s in a traditional gold mining area in Ecuador.

Mining operations are important causes of environmental pollution in developing countries where mining waste management is not adequate. Consequently, heavy metal(loid)s are easily released into the environment, being a potential risk to human health. This study carries out a Bayesian probabilistic human health risk assessment, related to multi-pathway exposure to heavy metal(loid)s in a gold mining area in Southern Ecuador. Concentrations of As, Cd, Cr, Cu, Ni, Pb, and Zn in tap water, surface water, and soil samples, were analyzed to assess the potential adverse human health effects based on the Hazard Index (HI) and Total cancer risk (TCR). Adults and children residents were surveyed to adjust their exposure parameters to the site-specific conditions. Exposure to heavy metal(loid)s resulted in unacceptable risk levels for human health in the two age groups, both carcinogenic (TCR > 1 × 10-5) and non-carcinogenic (HI > 1) through ingestion of tap water and incidental ingestion of surface water. Sensitivity analysis showed that As concentration in waters and exposure frequency were the main contributors to risk outcome. Exposure to soil via accidental ingestion and dermal contact was below the safety limit, not posing a risk to human health. These findings can provide a baseline for the environmental management of the mining area and indicate the need for further research on As pollution in water and its implications on the health of the inhabitants of mining communities.

Ecological and probabilistic human health risk assessment of heavy metal(loid)s in river sediments affected by mining activities in Ecuador.

Gold mining is a significant source of metal(loid)s released into the environment. It is an issue of concern due to the potential adverse health effects associated with exposure to toxic elements. This study aimed to assess the ecological and human health risk caused by heavy metal(loid)s exposure in river sediments in Ponce Enríquez, one of the most important mining sites in Ecuador. Concentrations of As, Cd, Cu, Pb, and Zn were evaluated in 172 sediment samples to determine the Potential ecological risk (RI) and the carcinogenic (CR) and non-carcinogenic risk (HQ). The human exposure to polluted sediments during recreational activities was computed using Bayesian probabilistic models. Residents were randomly surveyed to adjust the risk models to the specific population data. More than 68% of the sampling stations pose a severe As and Cd ecological risk index ([Formula: see text] > 320). Likewise, residents exposed to river sediments showed a non-acceptable carcinogenic risk by incidental ingestion, being As the primary contributor to overall cancer in both children and adults receptors. Moreover, non-carcinogenic risk through the incidental ingestion of sediments was above the safe limit for children. This is the first study conducted in a mining region in Ecuador that reveals the severe levels of ecological and human health risk to which the population is exposed. These results can be applied as a baseline to develop public health strategies to monitor and reduce the health hazards of the residents of mining communities.

Optimized Production of Fatty Acid Ethyl Esters (FAEE) from Waste Frying Oil by Response Surface Methodology.

ABSTRACT: In Europe, recent regulations on advanced biofuels have prompted a search for new fuel sources and the development of synthesis methods meeting the demanding specifications of the sector. However, in developing countries such as Algeria, where a significant stock of frying oil is unused, the use of diesel engines powered with waste-oil-derived biofuels must be explored. In this work, the variables related to the transesterification reaction from this frying oil with ethanol are analyzed using response surface methodology. From this analysis, only the reaction time and temperature have been determined as relevant parameters. In addition, FT-IR analysis has proven a useful tool to analyse the conversion in the transesterification reaction of waste frying oil with ethanol and is cheaper and quicker than GC-FID. This sustainable biofuel (FAEE), mixed with a diesel and pure fuel, has been physically characterized. The mixture of FAEE at 30% by volume with diesel meets the requirements demanded in standard EN 590 and can be classified as winter diesel class D. As a pure biofuel, only its high cold flow temperatures could constitute a drawback for exporting to temperate climates but not for internal consumption.

Multi-pathway human exposure risk assessment using Bayesian modeling at the historically largest mercury mining district.

The largest mercury (Hg) mining district in the world is located in Almadén (Spain), with well-known environmental impacts in the surrounding ecosystem. However, the impact of mercury on the health of the inhabitants of this area has not been documented accordingly. This study aims to carry out a probabilistic human health risk assessment using Bayesian modeling to estimate the non-carcinogenic risk related to Hg through multiple exposure pathways. Samples of vegetables, wild mushrooms, fish, soil, water, and air were analyzed, and adult residents were randomly surveyed to adjust the risk models to the specific population data. On the one hand, the results for the non-carcinogenic risk based on Hazard Quotient (HQ) showed unacceptable risk levels through ingestion of Hg-contaminated vegetables and fish, with HQ values 20 and 3 times higher, respectively, than the safe exposure threshold of 1 for the 97.5th percentile. On the other hand, ingestion of mushrooms, dermal contact with soil, ingestion of water, dermal contact with water and inhalation of air, were below the safety limit for the 97.5th percentile, and did not represent a risk to the health of residents. In addition, the probabilistic approach was compared with the conservative deterministic approach, and similar results were obtained. This is the first study conducted in Almadén, which clearly reveals the high levels of human health risk to which the population is exposed due to the legacy of two millennia of Hg mining.