Ecotoxicological assessment, oxidative response, and enzyme activity disorder of the rotifer Brachionus asplanchnoidis exposed to a toxic cocktail of spent lithium-ion battery leachate.

Spent lithium-ion batteries (LIBs) have emerged as a major source of waste due to their low recovery rate. The physical disposal of spent LIBs can lead to the leaching of their contents into the surrounding environment. While it is widely agreed that hazardous substances such as nickel and cobalt in the leachate can pose a threat to the environment and human health, the overall composition and toxicity of LIB leachate remain unclear. In this study, a chemical analysis of leachate from spent LIBs was conducted to identify its primary constituents. The ecotoxicological parameters of the model organism, rotifer Brachionus asplanchnoidis, were assessed to elucidate the toxicity of the LIB leachate. Subsequent experiments elucidated the impacts of the LIB leachate and its representative components on the malondialdehyde (MDA) level, antioxidant capacity, and enzyme activity of B. asplanchnoidis. The results indicate that both the LIB leachate and its components are harmful to individual rotifers due to the adverse effects of stress-induced disturbances in biochemical indicators, posing a threat to population development. The intensified poisoning phenomenon under combined stress suggests the presence of complex synergistic effects among the components of LIB leachate. Due to the likely environmental and biological hazards, LIBs should be strictly managed after disposal. Additionally, more economical and eco-friendly recycling and treatment technologies need to be developed and commercialized.

One-third of cropland within protected areas could be retired in China for inferior sustainability and effects.

Cropland encroachment on protected areas causes natural habitat loss, which may damage ecosystem functions and biodiversity conservation, leading to trade-offs between crop production and habitat conservation. Here we investigate the sustainable utilization and effects of cropland within protected areas, on which we make trade-offs with an established framework. Analyses show that 3.08 million hectares of cropland are identified within protected areas, about two-thirds less sustainable or less beneficial. 41 % and 26 % are expected to be retired for inferior sustainability and effects under the strictest and laxest habitat protection scenario, respectively. Although these retirements would cause a loss of crop benefits of 0.3-0.7 billion US dollars, they could bring ecological benefits of 2.9-3.6 billion US dollars annually. Approximately 11 % of cropland within protected areas is identified in poor agricultural conditions, and 19 % occupies areas of high protection importance, both of which are recommended for priority retirement. This study reveals the characteristics and impacts of cropland in protected areas and provides a quantified trade-off approach for conflicts between cropland and natural habitats, with important implications for production, conservation, and their trade-offs.

Global 30 meters spatiotemporal 3D urban expansion dataset from 1990 to 2010.

Understanding the spatiotemporal dynamics of global 3D urban expansion over time is becoming increasingly crucial for achieving long-term development goals. In this study, we generated a global dataset of annual urban 3D expansion (1990-2010) using World Settlement Footprint 2015 data, GAIA data, and ALOS AW3D30 data with a three-step technical framework: (1) extracting the global constructed land to generate the research area, (2) neighborhood analysis to calculate the original normalized DSM and slope height of each pixel in the study area, and (3) slope correction for areas with a slope greater than 10° to improve the accuracy of estimated building heights. The cross-validation results indicate that our dataset is reliable in the United States(R2 = 0.821), Europe(R2 = 0.863), China(R2 = 0.796), and across the world(R2 = 0.811). As we know, this is the first 30-meter 3D urban expansion dataset across the globe, which can give unique information to understand and address the implications of urbanization on food security, biodiversity, climate change, and public well-being and health.

Space-variant Shack-Hartmann wavefront sensing based on affine transformation estimation.

The space-variant wavefront reconstruction problem inherently exists in deep tissue imaging. In this paper, we propose a framework of Shack-Hartmann wavefront space-variant sensing with extended source illumination. The space-variant wavefront is modeled as a four-dimensional function where two dimensions are in the spatial domain and two are in the Fourier domain with priors that both gently vary. Here, the affine transformation is used to characterize the wavefront space-variant function. Correspondingly, the zonal and modal methods are both escalated to adapt to four-dimensional representation and reconstruction. Experiments and simulations show double to quadruple improvements in space-variant wavefront reconstruction accuracy compared to the conventional space-invariant correlation method.