Micropollutant rejection by nanofiltration membranes: a mini review dedicated to the critical factors and modelling prediction

Nanofiltration (NF) membranes, extensively used in advanced wastewater treatment, have broad application prospects for the removal of emerging trace organic micropollutants (MPs). The treatment performance is affected by several factors, such as the properties of NF membranes, characteristics of target MPs, and operating conditions of the NF system concerning MP rejection. However, quantitative studies on different contributors in this context are limited. To fill the knowledge gap, this study aims to assess critical impact factors controlling MP rejection and develop a feasible model for MP removal prediction. The mini-review firstly summarized membrane pore size, membrane zeta potential, and the normalized molecular size (λ = rs/rp), showeing better individual relationships with MP rejection by NF membranes. The Lindeman-Merenda-Gold model was used to quantitatively assess the relative importance of all summarized impact factors. The results showed that membrane pore size and operating pressure were the high impact factors with the highest relative contribution rates to MP rejection of 32.11% and 25.57%, respectively. Moderate impact factors included membrane zeta potential, solution pH, and molecular radius with relative contribution rates of 10.15%, 8.17%, and 7.83%, respectively. The remaining low impact factors, including MP charge, molecular weight, logKow, pKa and crossflow rate, comprised all the remaining contribution rates of 16.19% through the model calculation. Furthermore, based on the results and data availabilities from references, the machine learning-based random forest regression model was trained with a relatively low root mean squared error and mean absolute error of 12.22% and 6.92%, respectively. The developed model was then successfully applied to predict MPs’ rejections by NF membranes. These findings provide valuable insights that can be applied in the future to optimize NF membrane designs, operation, and prediction in terms of removing micropollutants

Changes in net anthropogenic nitrogen and phosphorus inputs in the Yangtze River Economic Belt, China (1999–2018)

Since the industrial revolution, excess inputs of nitrogen (N) and phosphorus (P) from human activities have been the main threat of deterioration to water environmental quality. In this study, to understand the variation characteristics, evolutionary pattern, composition structure, and main influencing factors on net anthropogenic nitrogen inputs (NANI) and net anthropogenic phosphorus inputs (NAPI) in the Yangtze River Economic Belt, 20 years of data from 1999 to 2018 at the general, provincial and city scales were analyzed. The results showed that NANI and NAPI in the Yangtze River Economic Belt increased and then decreased from 1999 to 2007 and from 2008 to 2018, with average values of 7189.26 kg N km−2 yr−1 and 2169.31 kg P·km−2 yr−1. Fertilizer application constituted the largest source of contributions to NANI and NAPI, with average contribution rates of 66.31 % and 68.20 %. The spatial pattern of NANI and NAPI exhibited a decreasing trend from east to west and from north to south. Western Jiangsu, eastern Anhui, central Hubei, and western Sichuan were high-risk areas. The contribution rates of human activity factors were ranked as economic factors > land-use factors > social factors, and changes in economic factors contributed the most to changes in NANI and NAPI, with averages of 70.50 % and 70.10 %. The Yangtze River Economic Belt has crossed the Environmental Kuznets Curve (EKC) inflection point for the N/P input load and has entered the coordinated development stage of economic growth and environmental improvement. The city scale can effectively identify and optimize the control area compared with the provincial scale, and the proportions of the administrative areas for NANI and NAPI at different targets decreased by 4.11 % (5.20 %), 7.52 % (11.95 %), and 9.79 % (17.29 %), respectively

The Water-Saving Management Contract in China: Current Status, Existing Problems, and Countermeasure Suggestions

This study analyzed the policies and summarized the current status of the national water-saving management contract (WSMC) development as well as its implementation between 2016 and 2020. Several main problems affecting and restricting the implementation of WSMC projects were identified including the lack of awareness of the importance of water conservation among water users, the limited number and scale of water conservation service enterprises, and the inadequacy of relevant policies and systems. Subsequently, 11 countermeasure suggestions were proposed, including stimulating the endogenous power of the WSMC, strengthening policy support for the WSMC, improving the supporting systems and the service systems, increasing investment and innovation of water conservation technologies, improving technical standards, exploring innovative WSMC models, promoting pilot demonstrations, deepening water price system reforms, increasing the publicity and training of the WSMC, strengthening coordination, and linkage between multiple departments. These suggestions can provide a reference for the relevant departments to develop and promote WSMC policies

The Spatio-Temporal Variations of GPP and Its Climatic Driving Factors in the Yangtze River Basin during 2000–2018

Terrestrial gross primary productivity (GPP) is the major carbon input to the terrestrial ecosystem. The Yangtze River Basin (YRB) holds a key role in shaping China’s economic and social progress, as well as in ecological and environmental protection. However, how the GPP in the YRB responds to the climate factors remain unclear. In this research, we applied the Vegetation Photosynthesis Model (VPM) GPP data to explore the spatial and temporal variations of GPP in the YRB during 2000–2018. Based on the China Meteorological Forcing Dataset (CMFD), the partial least squares regression (PLSR) method was employed to identify the GPP responses to changes in precipitation, temperature, and shortwave radiation between 2000 and 2018. The findings showed that the long-term average of GPP in the YRB was 1153.5 ± 472.4 g C m−2 yr−1 between 2000 and 2018. The GPP of the Han River Basin, the Yibin-Yichang section of the Yangtze River mainstream, and the Poyang Lake Basin were relatively high, while the GPP of the Jinsha River Basin above Shigu and the Taihu Lake Basin were relatively low. A significant upward trend in GPP was observed over the 19-year period, with an annual increase rate of 8.86 g C m−2 yr−1 per year. The GPP of the Poyang Lake Basin and Jialing River Basin grew much faster than other water resource regions. Savannas and forests also had relatively higher GPP rate of increase compared to other vegetation types. The relative contributions of precipitation, temperature, and shortwave radiation to GPP variations in the YRB were 13.85 ± 13.86%, 58.87 ± 9.79%, and 27.07 ± 15.92%, respectively. Our results indicated that temperature was the main climatic driver on the changes of GPP in the YRB. This study contributes to an in-depth understanding of the variations and climate-impacting factors of vegetation productivity in the YRB

Study of sensitivity evaluation on ridgetail white prawn (Exopalaemon carinicauda) quality examination methods

In this paper, ridgetail white prawn (Exopalaemon carinicauda) quality evaluation was performed by electronic nose (e-nose). Physical/chemical, such as human sensory evaluation (HSE), weight loss, colour, total viable counts (TVC), GC-MS, K value, microbial, and e-nose were persistently tested. Principal component analysis (PCA) and stochastic resonance (SR) were used for measurement data processing. Results suggested that prawn quality persistently decreased due to microbial propagation. GC-MS results demonstrated that the volatile gases emitted by the samples increased during measurement. PCA could not discriminate all prawn samples, and SR eigen values discriminated all samples. Sensitivity evaluation on colour, TVC, weight loss, HSE, GC/MS, K value, and e-nose was made, and results indicated that e-nose presents some advantages including low cost, rapid examination, and good repeatability. E-nose Prawn quality evaluation model was also built for e-nose

Diffusion of Cement Kiln Co-Processing of Contaminated Soil in Selected Provinces of China: Engineering Practices, Modeling, and Driving Factors

Promoting the diffusion of remediation technologies is an attractive solution to environmental protection and urban sustainability challenges. To better understand technology diffusion, we reviewed the engineering practices of cement kiln co-processing (CKC) of contaminated soil and obtained diffusion parameters using the Bass model in three provinces of China. Our results show that CKC has been adopted for the disposal of multiple contaminants and that the optimal feed rate of contaminated soil is 4–5%. The obtained diffusion parameters can be used to analyze and predict CKC diffusion. Driving factors analysis suggest that CKC diffusion is regulation-driven and obeys the S-curve pattern. Policies at the national level shape the basic pattern of the diffusion curve, while local policies, market scales, and contaminant types produce variations in diffusion rates across provinces. Results also reveal that the co-processing quota management on contaminated soil has little impact on CKC adoption. This study provides insights into contaminated soil remediation technology diffusion and the effectiveness of environmental policy implementation at home and abroad