Salinity-mediated water self-purification via bond network distorting of H2O molecules on DRC-surface.

High salinity has plagued wastewater treatment for a long time by hindering pollutant removal, thereby becoming a global challenge for water pollution control that is difficult to overcome even with massive energy consumption. Herein, we propose a novel process for rapid salinity-mediated water self-purification in a dual-reaction-centers (DRC) system with cation-π structures. In this process, local hydrogen bond networks of H2O molecules can be distorted through the mediation of salinity, thereby opening the channels for the preferential contact of pollutants on the DRC interface. As the result, the elimination rate of pollutants increased approximately 32-fold at high salinity (100 mM) without any external energy consumption. Our findings provide a novel technology for high-efficiency and low-consumption water self-purification, which is of great significance in environmental remediation and even fine chemical industry.

Unveiling the Vertical Migration of Microplastics with Suspended Particulate Matter in the Estuarine Environment: Roles of Salinity, Particle Properties, and Hydrodynamics.

The estuary is an energetic area connecting the inland, river, and ocean. The migration of microplastics (MPs) in this highly complex area is tied to the entire ecosystem. In this study, the effects of cohesive SPM (clay) and noncohesive SPM (sand) on the vertical migration of positively buoyant MPs, polyethylene (PE), and negatively buoyant MPs, polytetrafluoroethylene (PTFE), in the estuarine environment under hydrodynamic disturbances were investigated. The settling of positively buoyant MPs was more reliant on the cohesive SPM compared to the settling of negatively buoyant MPs. Moreover, MPs interacting with the SPM mixture at a clay-to-sand ratio of 1:9 settled more efficiently than those interacting with clay alone. A significant positive correlation was observed between MP settling percentage and the salinity level. MP settling percentage was significantly negatively correlated with fluid shear stress for both types of MPs, meanwhile, negatively buoyant MPs were able to resist greater hydraulic disturbances. In the low-energy mixing state, for both types of MPs, the settling percentage reached about 50% in only 10 min. The resuspension process of MPs under hydrodynamic disturbances was also uncovered. Additionally, the migration and potential sites of MPs were described in the context of prevalent environmental phenomena in estuaries.

Analyzing variation of water inflow to inland lakes under climate change: Integrating deep learning and time series data mining.

The alarming depletion of global inland lakes in recent decades makes it essential to predict water inflow from rivers to lakes (WIRL) trend and unveil the dominant influencing driver, particularly in the context of climate change. The raw time series data contains multiple components (i.e., long-term trend, seasonal periodicity, and random noise), which makes it challenging for traditional machine/deep learning techniques to effectively capture long-term trend information. In this study, a novel FactorConvSTLnet (FCS) method is developed through integrating STL decomposition, convolutional neural networks (CNN), and factorial analysis into a general framework. FCS is more robust in long-term WIRL trend prediction through separating trend information as a modeling predictor, as well as unveiling predominant drivers. FCS is applied to typical inland lakes (the Aral Sea and the Lake Balkhash) in Central Asia, and results indicate that FCS (Nash-Sutcliffe efficiency = 0.88, root mean squared error = 67m³/s, mean relative error = 10%) outperforms the traditional CNN. Some main findings are: (i) during 1960-1990, reservoir water storage (WSR) was the dominant driver for the two lakes, respectively contributing to 71% and 49%; during 1991-2014 and 2015-2099, evaporation (EVAP) would be the dominant driver, with the contribution of 30% and 47%; (ii) climate change would shift the dominant driver from human activities to natural factors, where EVAP and surface snow amount (SNW) have an increasing influence on WIRL; (iii) compared to SSP1-2.6, the SNW contribution would decrease by 26% under SSP5-8.5, while the EVAP contribution would increase by 9%. The findings reveal the main drivers of shrinkage of the inland lakes and provide the scientific basis for promoting regional ecological sustainability.

Water rights trading planning and its application in water resources management: A water-ecology-food nexus perspective.

Nexus approach provides an effective perspective for implementing synergetic management of water resources. In this study, an interval two-stage chance-constrained water rights trading planning model under water-ecology-food nexus perspective (ITCWR-WEF) is proposed to analyze the interaction between water trading and water-ecology-food (WEF) nexus, which fills in the water resources management gaps from a novel nexus perspective. ITCWR-WEF incorporates hydrological simulation with soil and water assessment tool (SWAT), water rights configuration with interval two-stage chance-constrained programming (ITCP), and multi-criterion analysis with Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The developed ITCWR-WEF is applied to a real case of Daguhe watershed, which has characteristics of water scarcity, food producing areas and fragile ecosystem. Initial water rights allocation is addressed before the trading. Mechanisms analysis is designed to reveal mutual effect of water rights trading and WEF nexus. Optimal water management scenario is identified through multi-criterion analysis. Results reveal that the mechanism of water rights trading with WEF nexus under low constraint-violation risk level of water availability and environment capacity is recommended to promote the rational water resources allocation to balance the economic goals, water environment and water supply security, as well as ecological and food water demand guarantees.

Regional bioethanol supply chain optimization with the integration of GIS-MCDM method and quantile-based scenario analysis.

This study presents a novel decision-support framework for the bioethanol supply chain network planning and management under uncertainties. Under the holistic framework, the most suitable sites for biorefineries are first screened out by adopting a GIS-based multi-criteria decision-making approach. Then, a mixed-integer linear programming model combined with quantile-based scenario analysis is developed to determine the strategic planning (i.e. locations and size of biorefineries) and tactical management (i.e. biomass purchasing, feedstock transportation, bioethanol production, and product delivery) under uncertainties. The model can effectively search for reliable solutions under uncertainties and achieve tradeoff solutions with the consideration of decision makers' risk tolerance. The proposed framework is demonstrated through a case study in China. It is suggested to build seven biorefineries with a capacity of 100 million liters in Zhumadian city. Utilizing 41% of local agricultural residues could satisfy the bioethanol requirement in the transportation sector under the E20 policy. However, the estimated production cost of bioethanol in Zhumadian is very high, about 1.11 $/L, which makes it lose cost advantage in the fuel market. Thus, currently, effective subsidies, mandatory energy substitution policies, along other environmental regulatory measures are desired to promote the bioethanol industry development.

Water Self-Purification with Zero External Consumption by Livestock Manure Resource Utilization.

Improper disposal of waste biomass and an increasing number of emerging contaminants (ECs) in water environment are universal threats to the global environment. Here, we creatively propose a sustainable strategy for the direct resource transformation of livestock manure (LM) into an innovative catalyst (Fe-CCM) for water self-purification with zero external consumption. ECs can be rapidly degraded in this self-purification system at ambient temperature and atmospheric pressure, without any external oxidants or energy input, accompanied by H2O and dissolved oxygen (DO) activation. The performance of the self-purification system is not affected by various types of salinity in the wastewater, and the corresponding second-order kinetic constant is improved 7 times. The enhanced water self-purification mechanism reveales that intermolecular forces between anions and pollutants reinforce electron exchange between pollutants and metal sites on the catalyst, further inducing the utilization of the intrinsic energy of contaminants, H2O, and DO through the interfacial reaction. This work provides new insights into the rapid removal of ECs in complicated water systems with zero external consumption and is expected to advance the resource utilization of livestock waste.

Photocatalytic disinfection for point-of-use water treatment using Ti3+ self-doping TiO2 nanoparticle decorated ceramic disk filter.

The challenge from pathogenic infections still threatens the health and life of people in developing areas. An efficient, low-cost, and abundant-resource disinfection method is desired for supplying safe drinking water. This study aims to develop a novel Ti3+ doping TiO2 nanoparticle decorated ceramic disk filter (Ti3+/TiO2@CDF) for point-of-use (POU) disinfection of drinking water. The production of Ti3+/TiO2@CDF was optimized to maximize disinfection efficiency and flow rate. Under optimal conditions, the log reduction value (LRV) could reach up to 7.18 and the flaw rate was 108 mL/h. The influences of environmental factors were also investigated. Natural or slightly alkaline conditions, low turbidity, and low concentration of humic acid were favorable for the disinfection of Ti3+/TiO2@CDF, while co-existing HCO3- ions and diatomic cations (Ca2+ and Mg2+) exhibited the opposite effect. Furthermore, the practicability and stability of Ti3+/TiO2@CDF was demonstrated. Ti3+/TiO2@CDF showed high disinfection efficiency for E. coli and S. aureus under a range of concentrations. Long-term experiment indicated that Ti3+/TiO2@CDF was stable. The underlying disinfection mechanisms were investigated and concluded as the combination of retention, adsorption, and photocatalytic disinfection. The developed Ti3+/TiO2@CDF can provide an effective and reliable disinfection tool for POU water treatment in remote area.

Sustainable conjunctive water management model for alleviating water shortage.

Water shortage poses a great challenge to the health of population and environment and impedes socio-economic development. Therefore, a comprehensive model is necessary to promote the adaptation of the whole socio-economic system to limited water resources. To achieve it, a sustainable conjunctive water management model (SCWM) was developed. In SCWM, direct (physical) and indirect (virtual or embodied) water consumptions of multiple water resources in future scenarios are projected, and the sustainable performances of various water-saving scenarios are quantified from the perspectives of water resources, economy, and ecosystem under water capping policy. A case study of Shaanxi, a typical water shortage province in central-eastern China, is conducted aimed at conquering the irrational use of surface- and ground-water subjected to the constraint of future total water use quota. Key findings contain optimal possibility of adapting water shortage via saving water through increasing industrial water efficiency to 11.12 m3/10,000 CNY and reducing 40% of agricultural final demand (Summation of direct and indirect water savings of the two scenarios are 41.57 × 108 m3 and 20.27 × 108 m3, respectively.) and nonsynergistic effects of simultaneous decreasing final demand of multiple sectors on water consumption intensity (WCI) of total (all kinds of water) water, surface- and ground-water. To devise effective policies for conjunctive management of surface- and ground-water, positive utility, economic structure and water productivity should be heeded, and proposals emphasize trade-offs between surface water saving and groundwater conservation, water metabolic and socio-economic systems sustainability and negative interaction of multiple sectors on economy and WCI should be framed. The innovation of this study is the development of SCWM, which can provide sustainable solution for future multiple-source water saving management measures thoroughly concerning direct and indirect water and sectorial interactions. The model not only brings insights to Shaanxi's water management but also can be used for other similar arid area.

Towards low-carbon domestic circulation: Insights from the spatiotemporal variations and socioeconomic determinants of emissions embedded within cross-province trade in China.

For a country like China with unbalanced development pattern among provinces, domestic circulation (i.e., cross-province trade) is important for the long-term stability and prosperous development of economic market. However, with the rapid advance of integration of domestic regional economy, while expanding the internal market scale and deepening the provincial division of labor network for promoting the economic growth, the carbon emissions embedded within the cross-province traded products and services cannot be underestimated. Under the background of climate-trade dilemma, it is necessary to exploring the spatiotemporal variations and socioeconomic determinants of provincial "invisible" carbon emissions for a better understanding of trade-induced eco-environmental effects. To that end, this study developed an environmental-economic system model through integrating the environmentally extended multiregional input-output method and weighted average structural decomposition analysis technique to explore the trade-related emissions at the provincial level and generate the mitigation-management strategies for decisionmakers. Overall, more than half the emissions were embedded within cross-province goods and services trade over the whole study period. Furthermore, the distribution of traded emissions showed obvious spatial heterogeneity and great unbalance was existed between provincial imports and exports. Among all provinces, carbon surplus provinces were always more than deficit ones and the trading patterns of approximately 65% regions remained unchanged during 2007-2017. Remarkably, the emissions trading pattern undergone transition from carbon deficit to carbon surplus in provinces like Henan, Hubei, Guizhou, and so on. Conversely, provinces like Jilin, Shanghai, and Xinjiang showed opposite change. With the prevalence of online payment and electronic commerce in the future, the central and sub-national government could consider launching a pilot project for the design and creation of personal carbon consumption account in the carbon surplus provinces such as Guangdong, Henan, and Jiangsu. Meanwhile, for the provinces with larger carbon exports, it is necessary to establish the horizontal high technical transfer channels and vertical compensation mechanisms such as financial subsidies for improving the low-carbon production level. Our findings provided a holistic depict of national traded emissions at the provincial level, highlighting the importance of cross-province emission effect in exploring ways to promote the low-carbon transition of domestic circulation and fulfill the high-quality development of 'dual circulation' new pattern and successful achievement of 'double carbon' solemn commitment.

An improved fuzzy sorting algorithm coupling bi-level programming for synergetic optimization of agricultural water resources: A case study of Fujian Province, China.

The uneven allocation of water resources and the shortage of regional water resources pose great challenges to the economic development and regional development balance of the Fujian province. Optimizing the water allocation structure in different regions can effectively alleviate water pressure. In this study, a type-2 fuzzy bi-level programming (T2FBL) method is proposed to plan the agricultural water resource system in the Fujian province. This method uses an improved fuzzy sorting algorithm to deal with uncertain parameters in the system and combines the bi-level programming method to balance the trade-off between two levels of decision-makers, the uncertain information contained in the secondary membership function omitted in the interval type-2 fuzzy theory is considered in the new ranking algorithm. Multiple scenarios related to different food security needs and different risk indices are examined. The major findings are as follows: (i) With an average tolerance of 75%, the average gross agricultural output value under various scenarios increased (0.4% âˆ¼ 7%) (average 3.89%) after optimization. (ii) The regional water allocation scheme under different food demands and different water availability scenarios is calculated, and the results show that prioritizing adjustments to the industrial water distribution structure of Fuzhou and Zhangzhou will greatly relieve the water pressure in the Fujian province. (iii) The relationship between the availability of system water resources and economic benefits is given through the calculation results of the T2FBL model. These findings can provide an in-depth understanding of the interaction between agricultural, industrial and tertiary industry water allocation and provide technical support for agricultural water resource planning issues.

Optimal design of two-dimensional water trading based on risk aversion for sustainable development of Daguhe watershed, China.

Water related problems, including water scarcity and pollution, have become increasingly urgent challenges especially in arid and semiarid regions. Two-dimensional water trading (2DWT) mechanism has been designed to unify the quantity and quality of water for relieving the water crisis. This study aims to develop a risk aversion optimization-two dimensional water trading model (RAO-2DWTM) for planning the regional-scale water resources management system (RWMS). This is the first attempt on planning RWMS through risk aversion optimization within the two-dimensional water trading framework. RAO-2DWTM cannot only support in-depth analysis regarding the effect of decision maker's preferences on system risk in different trading scenarios, but also reflect the interaction between water right trading and effluent trading, as well as disclose the optimal scheme of water resource management under uncertainties. Twenty four scenarios associated with different trading scenarios and robust levels are analyzed. The optimization scheme under the optimal risk control level is determined based on TOPSIS. Results revealed that 2DWT would bring high benefit with reduced risk cost, water deficit and emissions, implying the effectiveness of 2DWT mechanism. The results also disclosed that risk aversion behavior can mitigate water scarcity and pollution, as well as reduce risk cost, but may lead to some losses of system benefit. Consequently, decision makers should make trade-offs between system benefit and risk in identifying desired trading schemes.

Unveiling Carbon Emission Attributions along Sale Chains.

Substantial anthropogenic emissions have resulted in serious environmental problems in China. Direct emissions and demand-pulled emissions along the supply chains have been extensively investigated. However, understanding the mechanism of how the sectoral emission is transferred through production activities along the sale chains at different production layers remains a challenge. In this paper, a top-down multilayer emission attribution model is developed to unveil the metabolism of multilayer input-driven emissions. For the first time, a diagramming approach enables the exhaustive depiction of the connections between primary input attributions and final production attributions, which allows accurate reallocation of the emission responsibilities to sectors at different production layers. Individual sale chain paths and supply chain paths have been extracted and ranked according to the contributions of emissions. A four-perspective comparison of sectoral emissions (i.e., direct emissions along sale chains, enabled emissions, direct emissions along the supply chains, and embodied emissions) is assessed. We find that at multiple production layers, sectoral direct emissions along the sale chains differ greatly from direct emissions along the supply chains. By comprehensively considering providers, consumers, and producers within a metabolic system, policy-makers should encourage upstream sectors to improve their cleaner production technologies and downstream sectors to adjust their industrial structures.

Stepwise clustering future meteorological drought projection and multi-level factorial analysis under climate change: A case study of the Pearl River Basin, China.

Climate change has significant impacts on the Pearl River Basin, and the regional ecological environment and human production may face severe challenges in the future due to changes in temperature and precipitation, as well as their derivative disasters (e.g., drought). Therefore, a full understanding of the possible impacts of climate change on Pearl River Basin is desired. In this study, the potential changes in temperature, precipitation, and drought conditions were projected through a stepwise clustering projection (SCP) model driven by multiple GCMs under two different RCPs. The developed model could facilitate specifying the inherently complex relationship between predictors and predictands, and its performance was proven to be great by comparing the observations and model simulations. A multi-level factorial analysis was employed to explore the major contributing factors to the variations in projecting drought conditions. The results suggested that the Pearl River Basin would suffer significant increasing trends in Tmean (i.e., 0.25-0.34 °C per decade under RCP4.5 and 0.42-0.60 °C per decade under RCP8.5), and the annual mean precipitation would increase under both RCPs. The drought events lasting for 1-2 months would be decreased by 7.7%, lasting for 3-4 months would be increased by 4.3%, and lasting for more than five months would be increased by 3.4% under RCP4.5, respectively. While they changed to 6.1%, 1.4%, and 4.7% under RCP8.5, respectively. More medium and long-term drought events with higher drought severity would occur. GCM has dominant influences on four different responses of drought duration, accounting for 50.20%, 52.61%, 56.71%, and 56.24% of total variabilities, respectively. Meanwhile, the effects explained by GCM*RCP interactions cannot be neglected, with an average contribution rate of 44.37%, 37.86%, 37.66%, and 35.83%, respectively.

A multi-sectoral decomposition and decoupling analysis of carbon emissions in Guangdong province, China.

Quantifying the decoupling states of carbon emissions from a multi-sectoral and dual-perspective can guide more detailed emission reduction strategies. Based on the single-regional input-output (SRIO), Tapio decoupling analysis (TDA), and structural decomposition analysis (SDA), this study investigated the dynamic variation feature and decoupling state of multi-sectoral carbon emissions, and revealed their driving factors of consumption-based emissions in Guangdong province from 2002 to 2017. The main discovery can be summarized as follows from results analysis. Firstly, electricity production sector and construction sector were the largest direct and embodied carbon emission sources, and capital formation was the most important factor with the contribution of approximately 100 % that led to embodied carbon emissions of construction. For most of the manufacturing and service sectors, the embodied carbon emissions caused by international export exceed 50 %. Secondly, the consumption structure, consumption per capita, and population effect promoted the embodied emissions during 2002-2012, while the emission intensity effect was the greatest offsetting factor for all sectors. Consumption structure effect was becoming a major driver to the increase of embodied carbon emissions for construction. Thirdly, agriculture, mining, energy transformation, and service sector showed the unsatisfactory decoupling relationship between direct carbon emissions and economic output. According to the decoupling states, the decoupling relationships in some secondary industries were overestimated under the situation of only considering direct carbon emissions. The obtained results and policy implications are expected to provide holistic reference for policymakers to promote the short-term carbon peak and long-term carbon neutrality of Guangdong province from the sectoral perspective.

How to balance ecosystem services and economic benefits? - A case study in the Pearl River Delta, China.

There is a significant challenge in resource management: the perceived trade-off between economic growth and ecosystem conservation. In this study, we integrate a variety of quantitative research methods and models, such as the ecosystem service value (ESV), interval parameter planning (IPP), Dyna-CLUE, and Monte Carlo methods, in an attempt to balance the ESV and economic benefits. The highest system benefits can be obtained, and uncertainty in the ecosystem assessment is considered. Taking the Pearl River Delta as the study area, the results show that when the GDP growth rate is less than 6%, the ESV in 2025 will be higher than the ESV in 2017. An interval approach (upper and lower bounds) is used. For a scenario with a 5% GDP growth rate, the ESV is RMB¥ [1.85, 20.79] × 109, which is more than the ESV of the scenario with a 9% GDP growth rate. When the GDP growth rates are 5% and 9%, the proportions of forestland are [61.5%, 61.7%] and [58%, 58.2%], respectively. Furthermore, spatialization was performed using the Dyna-CLUE model. In 2025, the simulated area of farmland is larger in some small regions with 9% GDP growth rate than it is in regions with 5% GDP growth rate, thus achieving a balance between occupation and compensation of regional farmland. By comparing ecosystem planning under different GDP growth rates, an optimized land-use allocation method can help decision makers balance system benefits and ecological risks, which can provide multiple options and specific locations for decision.

Planning electric power system under carbon-price mechanism considering multiple uncertainties - A case study of Tianjin.

The carbon-price mechanism has been proved to be an effective measure for promoting energy revolution and mitigating climate change. It is of vital importance to develop optimal energy development strategy for electric power-dependent regions by considering the complex interaction among carbon price, carbon emission control, and carbon-responsibility transfer. In order to fill the research gap on the optimal choice of carbon-price mechanism at the urban level, this study is the first attempt to express uncertainties embodied in the carbon price mechanism as interval values, probability distribution and downside risks. The developed risk-aversion-based interval two-stage stochastic programming (RITSP) model is effective in analyzing the effect of internal and electric-transmission related carbon-tax on power system structure. It is discovered that carbon compensation policy for imported electricity is more suitable for Tianjin's power system development. Tianjin would primarily purchase electricity from Inner-Mongolia. With the increase of carbon emission tax, Tianjin would import increasing proportion of electricity from Gansu. Due to the limited endowment of renewable energy in Tianjin, the impact of carbon emission limitations on the renewable energy power generation structure of is trivial, and it has a greater impact on stimulating the development of CCS technology. What's more, Tianjin's future power system planning is more inclined to develop CCS rather than renewable energy.

Enhanced nitrogen removal in the treatment of rural domestic sewage using vertical-flow multi-soil-layering systems: Experimental and modeling insights.

Domestic sewage in rural areas is often poorly treated and discharged into waters, resulting in negative impacts on regional environment, natural resources and human health. A cost-efficient decentralized sewage treatment technology is sustainably necessary for rural areas. In this study, a modified multi-soil-layering (MSL) system was developed to specifically treat low C/N ratio domestic sewage in rural areas. The results proved the good performance of MSLs in sewage treatment under complex conditions. The highest degradation rates of COD, TP, NH4+-N, NO3--N, TN among all the devices could reach 98.29%, 100%, 76.60%, 96.15% and 69.86%, respectively. During the operation, MSL5 and MSL6 showed the best overall performance of contaminant removal. The effects of single factors and their interactions on the performance of MSL systems were further revealed through factorial analyses. In order to simulate and predict nitrogen removal of MSL system, a statistical relationship between TN removal rate and operation parameters was also successfully developed based on stepwise cluster analysis. Such modeling of nitrogen removal model can help develop an optimal strategy for the operation of MSL in treating low C/N ratio sewage from rural areas.

Insights into the Toxicity of Triclosan to Green Microalga Chlorococcum sp. Using Synchrotron-Based Fourier Transform Infrared Spectromicroscopy: Biophysiological Analyses and Roles of Environmental Factors.

This study investigated the toxicity of triclosan to the green microalga Chlorococcum sp. under multiple environmental stressors. The interactions between triclosan and environmental stressors were explored through full two-way factorial, synchrotron-based Fourier transform infrared spectromicroscopy and principal component analyses. Phosphorus concentration, pH * phosphorus concentration, and temperature * pH * NaCl concentration were the most statistically significant factors under triclosan exposure. The variation of those factors would have a huge impact on biophysiological performances. It is interesting to find Chlorococcum sp. may become more resistant against triclosan in phosphorus-enriched environment. Besides, particular significant factors from multiple environmental stressors showed the impacts of triclosan on the corresponding response of Chlorococcum sp. owing to the specific structure and performance of biomolecular components. Moreover, two high-order interactions of temperature * pH * NaCl concentration and temperature * pH * NaCl concentration * phosphorus concentration had more contributions than others at the subcellular level, which could be attributed to the interactive complexity of biomolecular components. Due to cellular self-regulation mechanism and short exposure time, the biophysiological changes of Chlorococcum sp. were undramatic. These findings can help reveal the interactive complexity among triclosan and multiple environmental stressors. It is suggested that multiple environmental stressors should be considered during ecological risk assessment and management of emerging pollutants.

Biophysiological and factorial analyses in the treatment of rural domestic wastewater using multi-soil-layering systems.

Multi-soil-layering (MSL) system was developed as an attractive alternative to traditional land-based treatment techniques. Within MSL system, the environmental cleanup capability of soil is maximized, while the soil microbial communities may also change during operation. This study aimed to reveal the nature of biophysiological changes in MSL systems during operation. The species diversity in soil mixture blocks was analyzed using Illumina HiSeq sequencing of the 16S rRNA gene. The interactive effects of operating factors on species richness, community diversity and bacteria abundance correlated with COD, N and P removal were revealed through factorial analysis. The results indicated the main factors, aeration, bottom submersion and microbial amendment, had different significant effects on microbial responses. The surface area and porosity of zeolites in permeable layers decreased due to the absorption of extracellular polymeric substances. The findings were applied for the design and building of a full-size MSL system in field and satisfied removal efficiency was achieved. The results of this study can help better understand the mechanisms of pollutant reduction within MSL systems from microbial insights. It will have important implications for developing appropriate strategies for operating MSL systems with high efficiency and less risks.