The circular valorization of industrial residues as functional materials offers a promising strategy to reduce the environmental footprint of water treatment technologies. In this study, raw coal fly ash (FA), applied without pretreatment or structural modification, was evaluated as a waste-derived photocatalyst for the degradation of metamizole, a widely detected contaminant of emerging concern. A systematic assessment under five irradiation sources (visible light, UV-A, UV-B, UV-C, and V-UV) demonstrated that genuine photocatalytic activation occurred exclusively under UV-B irradiation, achieving 96.2% removal after 150 min and outperforming direct UV-B photolysis by 14.9 percentage points. In contrast, UV-C and V-UV induced near-complete photolysis independently of catalyst presence, while visible and UV-A irradiation produced negligible degradation, consistent with the measured band gap of FA (3.1 eV). Kinetic and scavenger experiments indicated a mechanism mainly governed by valence-band holes (h+) and hydroxyl radicals (●OH), with minor contribution from superoxide species (O2●-). The photocatalytic performance remained stable in the presence of common inorganic salts, confirming robustness under realistic water matrix conditions. HPLC-MS/MS analysis enabled the detection of fourteen potential transformation products and the proposal of a degradation pathway distinguishing photocatalytic activity from direct photolysis. Under optimized UV-B/FA conditions, COD and TOC removals reached 67.11% and 56.73%, respectively, while metal leaching remained minimal. Overall, unmodified coal fly ash behaves as an intrinsic semiconductor photocatalyst under UV-B irradiation and represents a promising low-cost material for sustainable and circular water treatment applications.
Heap leaching is widely used for the recovery of copper from low-grade oxide ores. Continuous monitoring of copper concentration in the pregnant leach solution (PLS) is essential for tracking leaching kinetics, determining optimal irrigation termination, and balancing metallurgical inventories at the individual-heap level; however, measurement at heap drainage channels remains operationally challenging owing to limited accessibility and reliance on manual sampling with delayed laboratory analysis. This study characterizes the photographic and modeling parameters of a laboratory prototype that estimates copper concentration in copper sulfate solutions using empirical, image-based colorimetric regression with low-cost consumer imaging hardware rather than a laboratory spectrometer, as a basis for future in-line sensing. Synthetic PLS solutions (0 to 40 g Cu/L in sulfuric acid) were imaged under controlled illumination (fixed-color, fixed-intensity LED light, diffused inside a dark chamber and not collimated) using a Nikon D3100 digital single-lens reflex (DSLR) camera across four channels (red, green, blue, and a white composite) at three intensity levels. For each channel, an absorbance-like feature was derived from the channel intensity relative to a zero-copper blank. A dataset of 432 images was subdivided into 256 spatial sub-samples per image across four channels, generating 442,368 channel-level observations, which were reduced to 15,120 physically coherent observations by sequential filtering (Kendall rank correlation, then linear and quadratic absorbance-concentration bounds). A feedforward artificial neural network (ANN) predicted copper concentration from the four color features and was benchmarked against a multivariate linear model used as a Lambert-Beer baseline. On a separate simulated, controlled dataset, the ANN achieved an RMSE of approximately 0.55 g/L (residual standard deviation of 0.40–0.41 g/L), a reduction of approximately 37 % in residual standard deviation relative to the best linear baseline (from 0.64 to 0.40 g/L) on simulated data. Experimental validation yielded a prediction error of approximately 25 %. This error is structured rather than random, arising from intensity-level displacement caused by specular reflections on the cylindrical sample cell, and is comparable to the ∼ 20 % uncertainty of current manual sampling; it is therefore a hardware and data-acquisition limitation rather than a limitation of the sensing concept. Under real PLS conditions, the error would be expected to increase, so the laboratory value should be read as a best-case bound. A flat-window flow cell, collimated illumination, and inclusion of the recorded illumination intensity as a model input are identified as the priority improvements.
Information overload and misinformation create significant challenges in extracting meaningful narratives from large news collections. This paper defines the nascent field of Interactive Narrative Analytics (INA), which combines computational narrative extraction with interactive visual analytics to support sensemaking. INA approaches enable the interactive exploration of narrative structures through computational methods and visual interfaces that facilitate human interpretation. The field faces challenges in scalability, interactivity, knowledge integration, and evaluation standardization, yet offers promising opportunities across news analysis, intelligence, scientific literature exploration, and social media analysis. Through the combination of computational and human insight, INA addresses complex challenges in narrative sensemaking.
Aims. The chemical abundance of the interstellar medium sets the initial conditions for star formation and provides a probe of chemical galaxy evolution models. However, unresolved inhomogeneities in the electron temperature can lead to a systematic underestimation of the abundances. We aim to directly test this effect. Methods. We used the SDSS-V Local Volume Mapper to spatially map the physical conditions of the Trifid Nebula (M 20), a Galactic H II region ionized by a single mid-type O-star, at a 0.24 pc resolution. We exploited various emission lines (e.g., Hydrogen recombination lines and collisionally excited lines, including also faint auroral lines) and computed the spatially resolved maps of [O II] and [S II] electron densities, the [N II], [O II], [S II], and [S III] electron temperatures, and the ionic oxygen abundances. Results. We found internal variations of electron density that result from the ionization front, along with a negative radial gradient. However, we did not find any strong gradients or structures in the electron temperature and the total oxygen abundance, making the Trifid Nebula a relatively homogeneous H II region at the observed spatial scale. We compared these spatially resolved properties with equivalent integrated measurements of the Trifid Nebula and found no significant variations between integrated and spatially resolved conditions. Conclusions. This isolated H II region, ionized by a single O-star, represents a test case of an ideal Strömgren sphere. The physical conditions in the Trifid Nebula behave as expected, with no significant differences between integrated and resolved measurements.
This commentary broadens the terms of the debate on left-behind places. It revisits the theoretical roots of discussions about uneven development to incorporate Global South experiences and proposes a typology to understand the processes underlying abandoned, depressed, and sacrificed places.
