Poly-NIPAM/Fe3O4/multiwalled carbon nanotube nanocomposites for kerosene removal from water

Too ill to cure? - An uncertainty-based probabilistic model assessment on one of China's most eutrophic lakes

Eutrophication is a global challenge, which is exemplified by the tremendous efforts but little results in restoring the sixth largest and also one of the most eutrophic freshwater lakes in China, Lake Dianchi. Considering large parametric uncertainties in water quality modeling, the traditionally used deterministic water quality model is expanded to a probabilistic model to explore the Lake Dianchi's potential responses to different levels of pollutant load reductions. The results show that, given the long pollution history and severe pollution state in Lake Dianchi, a minimum pollution load reduction by half (base year 2003) is required to maintain the water quality state as it is now in 40 years. At least a 60% nutrient load reduction is required to generate any likelihood of water quality improvement, however, the system stabilizes quickly after about 10 years, which may explain why tremendous investments have generated little results. 80% of nutrient load reduction for 40 years has 95% probability of meeting the TN target but only a below 50% (45%) probability in meeting the TP target, and even less to meet water quality target for Chla. The feasibility of ever reaching the Chinese drinking water standards for total phosphorous and total nitrogen is questionable.

Valorization of date palm leaves for adsorptive remediation of 2,4-dichlorophenoxyacetic acid herbicide polluted agricultural runoff

Alarming rates of water contamination by toxic herbicides have prompted the need and attention for easy, efficient, and affordable treatment options with a touch of circular economy aspects. This study valorized date palm leaf (DPL) wastes into a valuable adsorbent for remediating agricultural wastewater polluted with 2,4-Dichlorophenoxyacetic acid (2,4-DPA) herbicide. The DPL precursor was modified with H₂SO₄ treatment and both biomass samples were characterized by various analytical techniques. Acid treatment modified the morphology, thermal, and textural properties of the final product (TDPL) while maintaining the structure and surface chemistry intact. Simulated wastewaters containing 2,4-DPA were subsequently treated using TDPL as an adsorbent. Optimum adsorption conditions of pH 2, dosage 0.95 g/L, shaking speed 200 rpm, time 120 min, and temperature 30 °C showed a good herbicide removal efficiency in the range of 55.1-72.6% for different initial feed concentrations (50-250 mg/L). Experimental kinetic data were better represented by the pseudo-second-order model, while the Freundlich isotherm was reliable in describing the equilibrium behavior of the adsorption system. Further, the thermodynamic analysis revealed that the adsorption occurred spontaneously, favorably, and exothermically. Plausible sorption mechanism involved electrostatic interactions, weak van der Waals forces, hydrogen bonds, and π-π interactions between the participating phases. Conspicuously, TDPL application to real-world situations of treating actual herbicide-polluted agricultural runoff resulted in a 69.4% remediation efficiency. Thus, the study demonstrated the valorization of date palm leaves into a valuable and industry-ready adsorbent that can sequester toxic 2,4-DPA herbicide contaminant from aqueous streams.

Impact of climate change on coastal water quality and its interaction with pollution prevention efforts

The impact of climate change on nearshore coastal water quality and its interaction with pollution prevention efforts (e.g., the development of green and gray water infrastructure) still lack systematic investigation. This study performed a holistic analysis of the impact of climate change on the salinity and concentrations of total nitrogen (TN), total phosphorus (TP) and chlorophyll a (Chl.a) in Shenzhen Bay between Shenzhen and Hong Kong, the two most developed megacities in South China, based on three-dimensional hydrodynamic and water quality modeling. The major study findings were as follows. First, Chl.a was the most sensitive parameter, and its bay-wide average concentration in 2100 was predicted to be approximately 13% and 46% higher than those in 2015 under mild and rapid climate change scenarios, respectively. Second, sea level rise was found to be a major driver of all four water quality parameters, while temperature and radiation mainly influenced Chl.a and precipitation mainly influenced nutrients. Third, water quality responses to climate change were highly heterogeneous over the bay. Even under a mild climate change scenario, the highest location-specific changes (2100 vs. 2015) in salinity and TN, TP and Chl.a concentrations were projected to be approximately 21%, 19%, 25%, and 65%, respectively. Fourth, changes in seasonal variation due to climate change may lead to an enhanced ecological risk of algal blooms. Finally, the effect of reducing TN and TP concentrations by proposed water infrastructure development was found to be significantly weakened (nearly 40% and 20% for TN and TP, respectively, under a mild climate change scenario), while the negative effect (i.e., increase in the Chl.a concentration) was notably accelerated. Regional cooperation is critical for protecting the water quality of the bay, particularly under climate change. The insights obtained in this study are applicable to other coastal water zones around the world with similar socioeconomic backgrounds and climatic conditions.