滇池外海北岸封闭水域控养水葫芦对水质的影响

在滇池外海北岸污染严重的0.25 km2封闭性蓝藻治理试验示范区内控养水葫芦,以削减富营养化水体内源氮(N)、磷(P)等污染物,探讨有效改善湖泊水质的生物治理措施.6月底按9.30 kg m-2投放水葫芦种苗,控养面积2.51hm2,示范区水面覆盖度为10%.结果显示:水葫芦放养后生长迅速,特别是在7-9月份,最大生长速率达37 2.7 g m-2 d-1;整个植株干物质平均N、P含量分别为23.22 g kg-1和5.03 g kg-1,每t鲜重水葫芦吸收1.63 kg N、0.35 kg P,通过水葫芦种养示范工程,直接由示范工程水域吸收带走N 1.15 t、P 0.25 t;水葫芦生长期间(7-12月),种养区较对照区水体DO、SD和p H均有下降;水葫芦根系具有较好的吸附拦截浮游藻类效果,致使种养区水体TN、TP和CODMn浓度显著高于对照区(P<0.05),并与水体Chl-a浓度显著正相关(P<0.05);水葫芦采收后并未引起二次污染,水质无恶化趋势.综上认为,规模化控养水葫芦可显著削减水体N、P等内源污染负荷,同时对浮游藻类吸附拦截效果明显,可将其滞留于特定水域,又能吸收利用藻类衰亡释放到水体的污染物,减轻外部空白水域水质恶化的压力.     

湖泊富营养化模型的研究进展

湖泊的富营养化是全球普遍关注的环境问题之一.湖泊的富营养化模型是防治、修复和治理湖泊富营养化的重要决策工具.按研究的侧重点不同,将湖泊富营养化模型分为简单回归模型、水质模型、生态模型和生态-水动力水质模型,并分别回顾了四类模型的研究进展.最后指出湖泊富营养化模型的发展趋势,强调不确定理论、3S技术、耦合模型是今后湖泊富营养化模型研究的重点,应在此基础上建立通用的模拟、预测、评价和优化模型,为湖泊富营养化管理提供科学依据.     

Long-term estimation of plastic material resources from end-of-life vehicles in China: a scenario analysis considering multiple industry standards

Journal of Material Cycles and Waste Management - The recycling and treatment of plastic waste become an increasingly serious environmental degradation challenge. To promote the recycling of...     

Fabrication and characterization of lightweight aggregate prepared from steel mill sludge in one step

Journal of Material Cycles and Waste Management - The qualified green lightweight aggregate (LWA) was successfully prepared from steel mill sludge (SMS) and fly ash (FAS) in one step using the...     

The interception effect of heavy metals in different types of Chinese fir plantations

Environmental Geochemistry and Health - The aim of this research is to investigate the interception effect of heavy metals, such as zinc (Zn), copper (Cu), lead (Pb), arsenic (As), and cadmium (Cd)...     

Improving protected area effectiveness through consideration of different human-pressure baselines

Previous assessments of the effectiveness of protected areas (PAs) focused primarily on changes in human pressure over time and did not consider the different human-pressure baselines of PAs, thereby potentially over- or underestimating PA effectiveness. We developed a framework that considers both human-pressure baseline and change in human pressure over time and assessed the effectiveness of 338 PAs in China from 2010 to 2020. The initial state of human pressure on PAs was taken as the baseline, and changes in human pressure index (HPI) were further analyzed under different baselines. We used the random forest models to identify the management measures that most improved effectiveness in resisting human pressure for the PAs with different baselines. Finally, the relationships between the changes in the HPI and the changes in natural ecosystems in PAs were analyzed with different baselines. Of PAs with low HPI baselines, medium HPI baselines, and high HPI baselines, 76.92% (n=150), 11.11% (n=12), and 22.86% (n=8) , respectively, showed positive effects in resisting human pressure. Overall, ignoring human-pressure baselines somewhat underestimated the positive effects of PAs, especially for those with low initial human pressure. For PAs with different initial human pressures, different management measures should be taken to improve effectiveness and reduce threats to natural ecosystems. We believe our framework is useful for assessing the effectiveness of PAs globally, and we recommend it be included in the Convention on Biological Diversity Post-2020 Strategy.     

Effects of bedform migration on nutrient fluxes at the sediment–water interface: a theoretical analysis

Environmental Fluid Mechanics - Nutrient fluxes at the sediment–water interface are essential for water quality and aquatic ecosystems. In this study, a unified expression for the sediment...     

A fast antibiotic detection method for simplified pretreatment through spectra-based machine learning

• A spectral machine learning approach is proposed for predicting mixed antibiotic. • Pretreatment is far simpler than traditional detection methods. • Performance of the model is compared in different influencing factors. • Spectral machine learning is promising in the detection of complex substances. Antibiotics are widely used in medicine and animal husbandry. However, due to the resistance of antibiotics to degradation, large amounts of antibiotics enter the environment, posing a potential risk to the ecosystem and public health. Therefore, the detection of antibiotics in the environment is necessary. Nevertheless, conventional detection methods usually involve complex pretreatment techniques and expensive instrumentation, which impose considerable time and economic costs. In this paper, we proposed a method for the fast detection of mixed antibiotics based on simplified pretreatment using spectral machine learning. With the help of a modified spectrometer, a large number of characteristic images were generated to map antibiotic information. The relationship between characteristic images and antibiotic concentrations was established by machine learning model. The coefficient of determination and root mean squared error were used to evaluate the prediction performance of the machine learning model. The results show that a well-trained machine learning model can accurately predict multiple antibiotic concentrations simultaneously with almost no pretreatment. The results from this study have some referential value for promoting the development of environmental detection technologies and digital environmental management strategies.     

Functional flax fiber with UV-induced switchable wettability for multipurpose oil-water separation

● A PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed. ● The property of flax fiber could be switched from hydrophobicity to hydrophilicity. ● The mechanism of the acquired UV-induced switchable wettability was discussed. ● The developed flax fiber was successfully used for multipurpose oil-water separation. The large number of oily wastewater discharges and oil spills are bringing about severe threats to environment and human health. Corresponding to this challenge, a functional PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed for efficient oil-water separation in this study. The developed flax fiber was obtained through PAA grafted polymerization and then ZnO-HDTMS nanocomposite immobilization. The as-prepared PAA-ZnO-HDTMS flax fiber was hydrophobic initially and could be switched to hydrophilic through UV irradiation. Its hydrophobicity could be easily recovered through being stored in dark environment for several days. To optimize the performance of the PAA-ZnO-HDTMS flax fiber, the effects of ZnO and HDTMS concentrations on its switchable wettability were investigated. The optimized PAA-ZnO-HDTMS flax fiber had a large water contact angle (~130°) in air and an extremely small oil contact angle (~0°) underwater initially. After UV treatment, the water contact angle was decreased to 30°, while the underwater oil contact angle was increased to more than 150°. Based on this UV-induced switchable wettability, the developed PAA-ZnO-HDTMS flax fiber was applied to remove oil from immiscible oil-water mixtures and oil-in-water emulsion with great reusability for multiple cycles. Thus, the developed flax fiber could be further fabricated into oil barrier or oil sorbent for oil-water separation, which could be an environmentally-friendly alternative in oil spill response and oily wastewater treatment.     

Techno-economic characteristics of wastewater treatment plants retrofitted from the conventional activated sludge process to the membrane bioreactor process

• Retrofitting from CAS to MBR increased effluent quality and environmental benefits. • Retrofitting from CAS to MBR increased energy consumption but not operating cost. • Retrofitting from CAS to MBR increased the net profit and cost efficiency. • The advantage of MBR is related to the adopted effluent standard. • The techno-economy of MBR improves with stricter effluent standards. While a growing number of wastewater treatment plants (WWTPs) are being retrofitted from the conventional activated sludge (CAS) process to the membrane bioreactor (MBR) process, the debate on the techno-economy of MBR vs. CAS has continued and calls for a thorough assessment based on techno-economic valuation. In this study, we analyzed the operating data of 20 large-scale WWTPs (capacity≥10000 m³/d) and compared their techno-economy before and after the retrofitting from CAS to MBR. Through cost-benefit analysis, we evaluated the net profit by subtracting the operating cost from the environmental benefit (estimated by the shadow price of pollutant removal and water reclamation). After the retrofitting, the removal rate of pollutants increased (e.g., from 89.0% to 93.3% on average for NH₃-N), the average energy consumption increased from 0.40 to 0.57 kWh/m³, but the operating cost did not increase significantly. The average marginal environmental benefit increased remarkably (from 0.47 to 0.66 CNY/g for NH₃-N removal), leading to an increase in the average net profit from 19.4 to 24.4 CNY/m³. We further scored the technical efficiencies via data envelopment analysis based on non-radial directional distance functions. After the retrofitting, the relative cost efficiency increased from 0.70 to 0.73 (the theoretical maximum is 1), while the relative energy efficiency did not change significantly. The techno-economy is closely related to the effluent standard adopted, particularly when truncating the extra benefit of pollutant removal beyond the standard in economic modeling. The modeling results suggested that MBR is more profitable than CAS given stricter effluent standards.