Phasing out coal-fired power plants is one of the most urgent steps needed to achieve the 1.5- or 2-degree target in the Paris Agreement. Many developed and developing countries have announced their plans to phase out coal from their electricity sectors. Managing the social and economic impacts of this energy transition is key to achieving political and social acceptability and pursuing environmental and social development hand in hand. As one of the leading countries committed to decarbonization in Latin America, Chile has launched a plan to phase out coal by 2050. To analyze the impacts of phasing out coal in Chile on jobs and value added, we combined an Input-Output analysis with ad-hoc labor surveys. We analyzed four contrasting electricity production scenarios that the Chilean government used to frame the policy debate: the current Long-Term Energy Plan (a baseline), and three scenarios that phase out coal-based generation by 2030 or 2050. Our findings show that coal phase-out will contribute to net job creation on the national level, adding 23–26 thousand jobs by 2030. In addition, value-added in the power generation sector will also grow by 1.7 billion dollars above today's levels as a result of the coal phase-out. These overall positive numbers mask a gross job destruction of 4.4 thousand jobs in coal power plants, concentrated in a few communities. In the most affected community, 7.1% of the population works in a coal power plant. Negative impacts in coal-reliant communities require special attention to ensure a just transition towards a clean power generation system. The results of this study highlight the need for strategic policy development that supports a smooth transition to a low-carbon economy, taking into account the associated national and local impacts. Our study also contributes to the literature about the evaluation framework of coal phase-out projects around the world, improving the understanding of their associated impacts beyond the case study country.

Although certain emission standards have been implemented to reduce the air pollution from the steel industry, heavy metal pollution associated with steel production in China has not been well addressed yet. Arsenic is a metalloid element, commonly present in various compounds in many minerals. When it presents in steelworks, it not only affects the quality of steel products, but also causes environmental consequences such as soil degradation, water contamination, air pollution and associated biodiversity loss and public health risks. At present, most of the studies on arsenic were limited to its removal in a certain process, while there has not been a thorough analysis of the flow path of arsenic in steelworks that can facilitate a more efficient removal from its lifecycle. To achieve this, we established a model to depict arsenic flows in steelworks for the first time using adapted substance flow analysis, and further analyzed arsenic flows in the steelworks using a case study in China. Finally, input-output analysis was applied to study the arsenic flow network and explore the reduction potential of arsenic-containing wastes in steelworks. The results show that: 1) the arsenic in the steelworks comes from inputs of iron ore concentrate (55.31 %), coal (12.71 %) and steel scrap (18.67 %), while the outputs were hot rolled coil (65.93 %) and slag (33.03 %). 2) The input, circulation, and final product content of arsenic are 96.120, 32.510, and 66.946 g/t-CS, respectively, and the recycling rate of arsenic was 48.28 %, in the steelworks. 3) The total arsenic discharge from the steelworks is 34.826 g/t-CS. 97.33 % of arsenic is discharged in the form of solid waste. 4) The reduction potential of arsenic in wastes is 14.31 % in the steelworks by adopting low-arsenic raw materials and removing arsenic from processes.

Crude oil pipelines are critical infrastructures for the energy system, but accidents can cause oil spills that pose significant public health and environmental threats to nearby communities. To better guide local environmental agencies in developing varied levels of oil spill emergency plans and to aid health departments in targeted health monitoring, we develop a novel indicator named Annual per capita oil spill exposure (APCOE). This indicator quantifies individualized exposure to oil spills resulting from pipeline accidents over a period of 55 years, at the state level in the United States. The APCOE integrates spill volumes, geographic areas, and populations to assess human exposure to oil spills. Results reveal that the Gulf Coast region has faced disproportionately high crude oil spill exposures compared to the East Coast. Within states, Wyoming, Oklahoma, and Texas maintained the highest APCOE levels from 1968 to 2022. Increased per capita income is associated with reduced APCOE. We also identify high-spill accidents, constituting the top 10% of total accidents, which are responsible for nearly 80% of the spill volumes. Monte Carlo sampling simulations suggest a 50% reduction in these high-spill accidents could decrease nationwide oil spills by 1.6 million barrels, resulting in a nearly 37% reduction in APCOE. Our research has strong policy implications for enhancing pipeline safety regulations and directing preparedness resources to states facing elevated spill exposure risks.