Journal of Environmental Engineering Technology•2026•DOI: 10.13205/j.hjgc.202604025
To meet the minute-level early-warning requirements for odor and multi-pollutant emissions at waste treatment facilities, this study proposed a multivariate short-term time-series prediction framework applicable to multi-tier scenarios covering source and boundary points (i.e., workshops and plant boundaries). Based on continuous online monitoring data with a 5-second resolution, a long short-term memory (LSTM) model using a sliding-window and recursive multi-step prediction strategy was constructed to jointly model odor concentration (OU) and pollutants including VOCs, NH3, H2S, and CH3SH (mg/m³). An evaluation protocol aligned with environmental supervision practice was established, incorporating mean absolute error (MAE), root mean square error (RMSE), goodness-of-fit (R²), skill scores (SS) relative to a persistence baseline, and threshold-based error stratification to characterize uncertainty during peak emission periods. The results showed that at workshop monitoring sites with relatively stable operating conditions, VOCs, NH3, H2S, and CH3SH exhibited a high goodness of fit and low prediction errors. In contrast, at boundary sites affected by plume arrival delays and diffusion-dilution non-stationarity, OU and VOCs displayed significantly amplified errors during peak episodes, and the skill score advantage over the baseline became unstable at certain sites. Stratified analysis consistently revealed that non-peak periods outperformed peak periods, indicating that event-driven fluctuations were the main sources of error. Accordingly, this study suggested incorporating exogenous variables such as wind speed and direction, ventilation and gate access control, and operational rhythms, along with peak-sensitive loss functions, into the model to enhance its capacity to characterize and provide early warnings for transient emission pulses. Overall, this study established a reusable methodological baseline and evaluation paradigm for minute-scale multi-pollutant prediction, providing quantitative support for the operational management and source-to-boundary coordinated control of waste treatment facilities.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3882-y
Organic semiconductor crystals with well-defined morphologies are highly desirable for high-performance optoelectronic devices, yet precise control over their growth remains a challenge. Here, a novel donor-acceptor (D-A) molecule, TQDPT, has been successfully developed, featuring a rigid π-conjugated acceptor core composed of thiazoloquinoxaline and naphthalene, coupled with phenylphenothiazine donors. This study presents a temperature-mediated crystallization strategy for precisely controlling the morphology and carrier transport properties of TQDPT single crystals. By systematically investigating the growth kinetics across a controlled temperature range (15–35°C), we reveal a distinct transition from needle-like structures to plate-like crystals, with tunable average widths spanning from around 2.8 to 30.1 μm. This morphological evolution is driven by temperature-dependent molecular diffusion and nucleation kinetics. Significantly, the plate-like crystals grown at 25°C exhibit an order-of-magnitude enhancement in mobility compared to needle-like counterparts, while higher temperatures of 35°C yield broader crystals with improved carrier mobility and device stability. This work highlights the critical role of temperature as a pivotal parameter in the dimensional and electronic optimization of organic crystals, offering an attractive approach to optimize functional materials for advanced optoelectronics.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2025092801
Urban river water quality is critically influenced by outfall discharges, yet the seasonal dynamics of dissolved organic matter (DOM) and its linkage to water quality remain poorly constrained. This study collected outfall water samples seasonally during 2023–2024 along the Nanfei River and Banqiao River in Hefei, Anhui Province. Parallel factor analysis of excitation-emission matrices identified three fluorescent components: fulvic acid-like C1, tryptophan-like (protein-like) C2, and terrestrial humic-like C3. Seasonal variations were pronounced: protein-like C2 dominated in winter and spring, whereas summer and autumn showed lower C2 proportions due to rainwater dilution and urban nonpoint source runoff inputs. Water quality indices decreased in summer and autumn, primarily attributed to dilution by rainfall runoff. Fluorescence index (FI > 1.9) and biological index (BIX > 1.0) indicated predominantly autochthonous DOM sources. During summer and autumn, humification index (HIX) and specific UV absorbance (SUVA) increased, while spectral slope ratio (SR) decreased, suggesting enhanced terrestrial and urban runoff influence. Significant positive correlations were observed between protein-like C2 and terrestrial humic-like C3 with water quality parameters, indicating their utility as precise indicators of pollution sources and seasonal water quality variations. These findings provide a scientific basis for integrated management of urban outfalls.