Mass Balance Principles Research Articles

Dynamics of soluble salts in cooling systems of circulating water supply

A model of the dynamics of soluble salts in the water of cooling systems of circulating water supply was developed based on mass balance principles. The proposed model is expressed in a general form under the assumption of a constant volume of circulating water and non-stationary input and output flows. The model accounts for scenarios where the concentration of soluble salts exceeds their concentration in the circulating water, thereby considering the technological necessity to change the system's power source in the event of an emergency at the feedwater treatment facilities. The developed model enables accurate prediction of the water-chemical regime in both existing and new recirculating cooling systems, sufficient for engineering calculations. It also facilitates the selection of optimal management strategies for such systems, including stabilization methods for recirculating water, feedwater preparation, blowdown volumes, etc. The model was validated under laboratory conditions for cases of concentration and dilution of highly soluble NaCl salt, with an observed error margin not exceeding 2%, attributed to experimental and instrumental factors. The variation in the concentration factor was analyzed for different blowdown rates, assuming initial equality of soluble salt concentrations in feedwater and circulation water. It was shown that establishing dynamic equilibrium between the circulation and feed waters can require dozens or even hundreds of circulation cycles for blowdown rates of 1–4%, and this system inertia must be considered during operation and when forecasting the performance of cooling systems with circulating water supply.

Modeling and Regulation of Dynamic Temperature for Layer Houses Under Combined Positive- and Negative-Pressure Ventilation.

The environmental control of layer houses with multi-tiered cage systems is influenced by factors such as the structure of the henhouses and the heat dissipation of the flock, leading to low precision and large fluctuations in temperature control. Based on a new combined positive- and negative-pressure ventilation (CPNPV) mode, a dynamic temperature model is constructed. Additionally, a temperature control method for a layer house is designed using a variable universe fuzzy PID control algorithm (VFPID). First, based on the principles of energy and mass balance, and by decoupling the relationship between positive- and negative-pressure ventilation volumes, a dynamic temperature model for layer houses under CPNPV was established. Then, the PID parameters and the proportional relationship between positive- and negative-pressure ventilation were optimized through fuzzy rules, and a proportional exponential function was introduced to adjust the scaling of the universe, enabling fine-tuned control. Finally, a temperature control model for the layer house was built using Simulink. The results show that the coefficients of determination (R2) of the constructed dynamic temperature models are between 0.79 and 0.88, respectively, indicating high accuracy. The designed VFPID method outperformed traditional on-off control and improved control precision by 20-23.53% and 10.34-22.22% compared with PID control and fuzzy PID(FPID) control methods, respectively. This study provides new insights for the development of environmental control equipment and precise environmental regulation of layer houses.

Estimating Air Change Rate in Mechanically Ventilated Classrooms Using a Single CO2 Sensor and Automated Data Segmentation.

With a growing emphasis on indoor air quality (IAQ) in educational environments, CO2 monitoring in classrooms has become commonplace. CO2 data can be used to estimate outdoor air change rate (ACH) based on the mass balance principle, which can be further linked to human health, performance, and building energy consumption. This study used a novel machine learning method to automatically segment CO2 concentration time series data into build-up, equilibrium, and decay periods, and then estimated classroom ACH using the corresponding CO2 mass balance equations. This method, applied to 40 classrooms in two mechanically ventilated K-6 schools, generated up to ten ACH estimates per day per classroom. A comparison with ACH calculated using the mechanical ventilation rates with 100% outdoor air reported by the building automation system during the study period reveals a slight underestimation by the decay and build-up methods, while the equilibrium method produced closer estimates. These differences may be attributed to uncertainties in occupancy, activity, CO2 emission rates, and air mixing. This research underscores the potential of leveraging CO2 data for more comprehensive IAQ assessments and highlights the challenges associated with accurately estimating ACH in real-world settings.

Seawater sulfate dynamics and a new tipping point in the Earth system

Seawater sulfate (SO42−) concentrations have changed by orders of magnitude in response to atmospheric and ocean redox dynamics throughout Earth’s history. A fundamental model that constrains seawater SO42− dynamics based on the principles of mass balance, however, is still lacking. Here, we used a dynamical systems approach to determine the effects of global source and sink strengths on seawater SO42− concentrations. Our stochastic analysis of the SO42− mass balance revealed two most probable seawater SO42− concentration ranges: one under widespread oceanic anoxic conditions with SO42− concentrations <1000 µM, and the other with SO42− concentrations around or above 10,000 µM under widely oxygenated ocean conditions. Swings between these two seawater SO42− concentration ranges are notably evident during the Phanerozoic Eon and developed in response to reoccurring oceanic anoxic events. We also identified a threshold for the extent of oceanic anoxia above which seawater SO42− concentrations collapse to <1000 µM, with corresponding impacts on global biogeochemical cycles, biology, and climate.

Study on the effect of volatile organic compounds on the treatment of high-salt wastewater by low-temperature evaporation

ABSTRACT High-salinity wastewater, owing to its intricate composition and challenging treatment requirements, poses a significant hurdle in water environmental governance. In this study, low-temperature evaporation technology is used to tackle wastewater containing the volatile organic compound such as N,N-dimethylacetamide (DMAC). Utilisation of comprehensive approaches involving experimental testing, mathematical modelling, and Aspen Plus software simulations, The influence of DMAC on evaporation efficiency is researched through the following factors which encompassing its effects on boiling point elevation, partial molar activation energy, and the formation of by-products. Additionally, the comparation of the impact of temperature, ionic strength, intermolecular interactions on the evaporation rate and the concentration of the volatile component DMAC in the condensate is also conducted in this study. After conducting a multiple linear regression analysis of evaporation efficiency using the Statistical Product and Service Solutions (SPSS) tool, it was discovered that temperature serves as the primary determinant influencing the evaporation rate. Additionally, ionic strength impacts solution viscosity, intermolecular interactions, and saturated vapour pressure by altering the intermolecular forces, thereby indirectly influencing both the evaporation rate and the quality of condensate water. The comparative analysis of single-effect and double-effect evaporation indicates that the optimal operating condition for double-effect evaporation yields an evaporation rate of 70%, with a remarkable 88% reduction in steam consumption compared to single one. Based on heat and mass balance principles, the mathematical model for double-effect evaporation is established to offer crucial data support for practical industrial applications.

Inorganic carbon migration and transformation in groundwater evaporation discharge area

During groundwater evaporation discharge, a series of carbon-related water-rock interactions potentially impact the terrestrial carbon cycle significantly. However, the migration and transformation of carbon in groundwater evaporation discharge area remain inadequately understood. Using the Tumochuan Plain in Inner Mongolia as a case study, this paper constructs a carbon balance equation for groundwater evaporation discharge area by employing mass balance principles and hydrogeochemical simulation methods, thereby analyzing the mechanisms of carbon diversion during groundwater evaporation. The result showed that evaporation discharge area of Tumochuan Plain was a ‘carbon sink’. Carbon emission rate to atmosphere in study area was 7.35 g/(m2·a), while carbon fixation rate by calcite precipitation and dissolved inorganic carbon (DIC) into groundwater was 37.15 g/(m2·a). The precipitation of calcite and the dissolution of dolomite were the main water-rock interactions controlling the migration and transformation of DIC. The carbon absorbed by dolomite dissolution reached 21,698.02 t/a (30.56 g/(m2·a)), offsetting a significant portion of the CO2 emitted during calcite precipitation. In addition, the calcium released by the dissolution of dolomite and anorthite effectively promoted the precipitation of calcite, which was the primary factor for groundwater to become a carbon sink in this area.

Design and simulation of 30 000 tons per year of cumene plant from natural gas field

Abstract The research considers the design and simulation of 30 000 tons per year of cumene plant using Aspen HYSYS as the simulation tool. The feed (material content) used is the characterized natural gas from Utorogu Gas Field with composition of 0.9019 methane, 0.0694 ethane, 0.0209 propane, 0.00361 n-butane, 0.00414 i-butane, 0.00005 n-pentane and 0.00007 i-pentane. The cumene plant consist of the cryogenic distillation column, de-hydrogenator (Continuous Stirred Tank Reactor), Alkylator (Plug Flow Reactor), storage tanks, separators, pumps, heat exchanger and mixers. The size/design models of basic plant units such as de-hydrogenator, alkylator, separators, storage tanks and distillation column were developed using the principles of mass and energy balance. The result of design or size specifications in terms of equipment diameter of basic plant units obtained from HYSYS simulation are 0.8 m and 0.319 m for the cryogenic and cumene columns; 1.931 m, 2.244 m and 1.366 m for the propane, propene and cumene storage tanks; 1.868 m and 2.076 m for the de-hydrogenator and alkylator; 1.931 m and 2.146 m for propene and cumene separators respectively. The power or capacity of propane and propene pumps configured in the plant are 0.02 kW and 0.005 kW respectively. The result of the reactor and distillation column thickness specification to withstand corrosion, pressure or stress during plant operation in terms of cylindrical shell and ellipsoidal doomed head are 17.36 mm and 4.31 mm respectively. The economic evaluation (overall cost) including the cost of utilities, catalyst, operating, and maintenance for entire plant is $ 3.004 M.

Distribution and Management of Residual Antibiotics in the Litopenaeus vannamei Shrimp Farming Environment: Recommendations for Effective Control

This study specifically focused on Litopenaeus vannamei and examined the distribution of residual antibiotics in various components of shrimp ponds throughout an aquaculture cycle. The findings revealed that aquaculture feed served as the primary source of antibiotics, continuously introducing them into the ponds throughout the entire production cycle. A multimedia distribution model for antibiotics in the ponds was established based on the principle of mass balance. The distribution characteristics of six antibiotics with higher levels in the feed, namely, sulfamethoxazole (SMX), norfloxacin (NOF), levofloxacin (LEOF), tetracycline (TC), oxytetracycline (OTC), and chlortetracycline (CTC), were investigated in the pond water, sediment, and shrimp. At the end of the cultivation period, the total antibiotic residues accounted for 65~80% in various media, with the sediment containing 50~60% of the distribution proportion (p < 0.01), which was identified as the primary reservoir for most antibiotics, with LEOF and NOF accounting for the highest proportions (45.78% and 50.29%, respectively). Based on the model’s findings and the allowable daily dosage of antibiotics, recommendations were made for the effective control of antibiotic residues in shrimp farming management. To address the significant net loss of sulfonamides (SAs) and tetracyclines (TCs) in aquaculture production, it is crucial to carefully regulate their dosages and administration methods. Implementing eco-friendly additives and regularly cleaning surface sediments can aid in reducing antibiotic residue levels in various environmental media, thereby mitigating the environmental impact on aquaculture production activities.

StRaWHAT: A stochastic rainwater harvesting assessment tool for direct quantification of rainwater harvesting system performance

Rainwater harvesting (RWH) contributes to reduced flooding and relief of demand on water supply systems and is instrumental in sustainable development. The conventional analytical probabilistic approach for RWH has a limitation of requiring an assumption of the initial storage condition which may cause overestimation or underestimation of the system's performance. By deriving the average storage volume of the RWH tank to get rid of such an assumption, a stochastic rainwater harvesting assessment tool (StRaWHAT) which is comprised of a set of closed-form analytical equations was developed and proposed for use in directly quantifying the hydrological performance statistics of RWH systems. The accuracy of StRaWHAT was verified by comparing its results with those obtained from continuous simulations based on mass balance principles for a large number of design scenarios with different climate conditions (6 cities in China and the US), storage capacities (1–20 m3) and water use rates (0.5, 1, 1.5 or 2 m3/day). Close agreements (NSE = 0.984, RMSE = 0.022, and CORR = 0.995) between StRaWHAT and continuous simulation results illustrated that StRaWHAT can provide accurate results for all types of system configurations. Extensive example case studies were carried out for RWH systems located in six cities in China and the U.S. Different types of applications were also illustrated. Overall, the proposed StRaWHAT was proved to be a computationally efficient and ease-to-use tool for directly assessing the hydrological performance of RWH systems.

Determination of Reaction Kinetics by Time‐Resolved Small‐Angle X‐ray Scattering during Polymerization‐Induced Self‐Assembly: Direct Evidence for Monomer‐Swollen Nanoparticles

AbstractThe kinetics of heterogeneous polymerization is determined directly using small‐angle X‐ray scattering (SAXS). This important advancement is exemplified for the synthesis of sterically‐stabilized diblock copolymer nanoparticles by reversible addition‐fragmentation chain transfer (RAFT) dispersion polymerization of benzyl methacrylate (BzMA) in mineral oil at 90 °C. The principle of mass balance is invoked to derive a series of equations for the analysis of the resulting time‐resolved SAXS patterns. Importantly, there is a continuous change in the X‐ray scattering length density for the various components within the reaction mixture. This enables the volume fraction of unreacted BzMA monomer to be calculated at any given time point, which enables the polymerization kinetics to be monitored in situ directly without relying on supplementary characterization techniques. Moreover, SAXS enables the local concentration of both monomer and solvent within the growing swollen nanoparticles to be determined during the polymerization. Data analysis reveals that the instantaneous rate of BzMA polymerization is proportional to the local monomer concentration within the nanoparticles. In principle, this powerful new time‐resolved SAXS approach can be applicable to other heterogeneous polymerization formulations.

Determination of Reaction Kinetics by Time-Resolved Small-Angle X-ray Scattering during Polymerization-Induced Self-Assembly: Direct Evidence for Monomer-Swollen Nanoparticles.

The kinetics of heterogeneous polymerization is determined directly using small-angle X-ray scattering (SAXS). This important advancement is exemplified for the synthesis of sterically-stabilized diblock copolymer nanoparticles by reversible addition-fragmentation chain transfer (RAFT) dispersion polymerization of benzyl methacrylate (BzMA) in mineral oil at 90 °C. The principle of mass balance is invoked to derive a series of equations for the analysis of the resulting time-resolved SAXS patterns. Importantly, there is a continuous change in the X-ray scattering length density for the various components within the reaction mixture. This enables the volume fraction of unreacted BzMA monomer to be calculated at any given time point, which enables the polymerization kinetics to be monitored in situ directly without relying on supplementary characterization techniques. Moreover, SAXS enables the local concentration of both monomer and solvent within the growing swollen nanoparticles to be determined during the polymerization. Data analysis reveals that the instantaneous rate of BzMA polymerization is proportional to the local monomer concentration within the nanoparticles. In principle, this powerful new time-resolved SAXS approach can be applicable to other heterogeneous polymerization formulations.

Predicting real-time within-vehicle air pollution exposure with mass-balance and machine learning approaches using on-road and air quality data

Modelling the air pollutant concentrations within-vehicles is an essential step to estimate our daily exposure to air pollution. This is a challenging issue however, since the processes that affect the exposures within-vehicles change with different driving patterns and ventilation settings. This study introduces an innovative approach that combines mass-balance principles and machine learning techniques, leveraging ambient air quality, on-road and within-vehicle measurements of particulate matter (PM10, PM2.5, PM1), nitrogen dioxide (NO2), nitrogen oxides (NOx), aerosol lung surface deposited area (LSDA) and ultrafine particles (UFP) under different ventilation settings to estimate air pollution exposure levels within vehicles. The first model (MB) includes basic physical and chemical processes and follows a mass-balance approach to estimate the within-vehicle concentrations. The second model (ML) applies data driven machine learning algorithms to a training set of observations to predict unseen within-vehicle concentrations. By using a number generator, the whole observational dataset was divided to 80:20 and 80% was used to build and train the ML model, while 20% was used for validation. Both models demonstrated good predictions of observations apart from an underestimation in UFP and LSDA. The ML model showed better predictive power than the MB model and had skill in predicting the unseen within-vehicle exposures. The ML model predictions were as good as the MB model for most of the species and improved for NO2. The ML model demonstrated good index of agreement (IOA >0.69) and Pearson correlation coefficient (r > 0.80) for all the species. The inclusion of air quality data from nearby monitoring stations instead of on-road (sampled while driving), in the ML model showed promising and new capabilities to within-vehicle exposure predictions. In an era where air pollution is a growing concern, understanding and predicting within-vehicle air pollution exposure is of great importance for public health and environmental research. This research not only advances the field of exposure assessment but (at no extra cost) also demonstrates practical implications for real-time exposure mapping and health impact assessment of vehicle occupants with existing infrastructure.

A novel method for quantifying hydrocarbon micromigration in heterogeneous shale and the controlling mechanism

Almost 70 years after shale oil was first studied, “self-souring” was widely regarded as an essential feature of shale oil. Recently, micromigration, which is a bridge connecting hydrocarbon generation, expulsion and enrichment in shale, has been discovered and confirmed as shale oil exploration deepens. However, due to strong heterogeneity, quantitative evaluation of hydrocarbon micromigration in shale remains unclear, making scientific understanding of shale oil enrichment mechanisms highly challenging. Based on the mass balance principle, we provide a quick and novel method to quantify hydrocarbon micromigration with the most commonly available geochemical data from Rock-Eval/total organic carbon (TOC) analysis by subtracting the real hydrocarbon generation potential (HGPR) from the original hydrocarbon generation potential (HGPO). The HGPR is calculated from pyrolysis parameters after light hydrocarbon calibration. Based on a kerogen kinetic theory, the HGPO is restored by utilizing a data-driven model with IBM-SPSS statistics. The results show that the Fengcheng Formation (P1f) shale features medium TOC contents, mixed kerogen types, mature to overmature levels, and high oil contents. Sixty-five percent of the P1f shale samples exhibit hydrocarbon intramicromigration, while the rest exhibit hydrocarbon extramicromigration. Shale oil contents and composition are closely related to hydrocarbon micromigration. The greater the hydrocarbon intramicromigration is, the higher the shale oil content. Micromigration occurs due to differences in hydrocarbon expulsion, pore space, and capillary pressure among shales. This method has a worldwide application for shale oil evaluation, and the findings will help to uncover shale oil differential enrichment mechanisms.

A mass balance principle for finding loose ends in cancer genomes.

A mass balance principle for finding loose ends in cancer genomes.

An energy-efficient and cleaner production of hydrogen by steam reforming of glycerol using Aspen Plus

Hydrogen (H2) is produced in an efficient and sustainable manner using steam reforming of glycerol in this work. Two models are used to provide anticipation about how efficiently H2 can be produced: Model 1, a stoichiometric model, and Model 2, a thermodynamic model. Model 1 helps determine the water/glycerol molar input ratio and reaction pathway. The thermodynamic feasibility of Model 1 is examined using Model 2, which then determines the optimum conditions for maximal H2 generation. Model 2 produced 1275 kmol/h of H2 with an H2 mole fraction of 0.49 at 658 °C and 1 atm of pressure. The reactor's net heat load is greatly reduced through heat integration in this study. The energy required is reduced by 29.5% as compared to when no heat integration is used. The process of separating and eliminating CO2 is accomplished by employing the principles of mass and energy balance in the Aspen Plus.

Optimization of Heat Transfer Area and Steam Requirement in Multiple Effects Evaporator for Concentration of Juice in Sugar Factory

<strong>ABSTRACT.</strong> In maintaining the existence of sugar factories that exist and are still actively operating in Indonesia, efforts should be made to carry out intensification and extensification. In terms of the intensification of the process, it is necessary to periodically evaluate the performance of process tools, especially those that require utilities so that the process is effective and efficient. The process of making sugar passes through six stages, namely: milling, purification, evaporation (evaporation), cooking, screening, and packaging processes or the final stage. The evaporation process is a crucial process that determines the success of the entire process because the juice is concentrated from 11% to 64%. The evaporator is designed to use a multiple effect evaporator to increase the value of steam economy. The research objective is to optimize the number of effects that require a minimum total cost. To achieve this goal, it is necessary to survey the sugar factory to obtain the necessary valid data. Furthermore, a mathematical model is compiled based on the principle of mass and heat balance and then a software program is made so that the optimization solution can be done accurately. The conclusions that can be drawn are as follows: for a mass flow rate of 125,000 kg/hour with a concentration of 11% juice and a feed temperature of 100<sup>o</sup>C, the optimum conditions are obtained with a minimum annual production cost of IDR. 22,090,361,779.00 which is owned by the evaporator with 4 effects, total evaporator area = 2,443.81 m<sup>2</sup>, steam economy = 3.98 and steam demand = 26,028.2 kg/hour. The number of evaporator effects of 4 is common in Indonesia.

Mathematical Modeling and Analyses of Integrated Process with Blast Furnace Iron Making and Co-gasification of Coal-COG-BF Top Gas

For the blast furnace iron-making process which depends on the coke seriously and is the largest CO2 emission source in iron and steel industry, a novel technology integrated the blast furnace process and co-gasification of coal-COG-BF top gas is investigated and examined its potential of energy conservation and CO2 emission reduction. The mathematical model of the whole integrated process is established based on mass and heat balance principles. And typical operation analyses for the integrated process are demonstrated by this model. The results indicate that it takes about 4 times for the unsteady process caused by the recycling of BF top gas to reach steady. Compared with conventional blast furnace process, the coke ratios in two integrated process cases selected decrease by 33.5kg/tHM and 81.3kg/tHM obviously, and the fuel ratios decrease 1.1% and 8.2% due to the increase of coal ratios by 27.9kg/tHM and 39.1kg/tHM. The energy consumption decreases by 8.3% and 10.8%. And the CO2 emission decreases by 37.0% and 42.9%.

A comprehensive approach to SBR modelling for monitoring and control system design

The aim of this research is to provide a comprehensive description of the Sequencing Batch Reactor (SBR) modelling for monitoring, control, and plant operational optimisation validation. The paper provides a detailed modelling of the SBR, its components and constituent processes. For this purpose, the mass balance principle and continuity equations were provided with a reactive term implemented using Activated Sludge Model (ASM). The spatially discretised models (along the vertical axis) are then used in numerical experiments. Simulations performed enable comparison of the impact of different models of activated sludge settling velocity, as well as two different approaches to modelling reactions in the SBR. The latter was achieved by using the ASM2d and ASM3-BioP extended with an enzyme group modelling the lag phase observed in microorganisms during a rapid change in environmental conditions. The presented results have been obtained using the model of the SBR at Swarzewo in the North of Poland.

Evaluating Species-Specific Replenishment Solution Effects on Plant Growth and Root Zone Nutrients with Hydroponic Arugula (Eruca sativa L.) and Basil (Ocimum basilicum L.)

Managing nutrients in recirculating solutions can be challenging in hydroponic production, and poor management practices can rapidly result in root zone nutrient imbalances in reduced yield. Using mass balance principles to formulate hydroponic replenishment solutions is a proposed strategy to reduce nutrient imbalances and the need to periodically replace the hydroponic solution. Objectives were to (1) formulate species-specific nutrient replenishment solutions for arugula (Eruca sativa L.) and basil (Ocimum basilicum L.) using mass balance principles and (2) evaluate the effects of using these replenishment solutions on plant growth and root zone nutrients over time. In the first experiment, arugula and basil tissues were analyzed over 42 d for macronutrient concentrations which were used to custom formulate species-specific replenishment solutions for both species. In the second experiment, nutrients were resupplied for hydroponic arugula and basil over time using either the species-specific or a standard commercial hydroponic replenishment solution. Species-specific replenishment solutions resulted in decreased solution EC and concentrations of most macronutrients over time for both species. In contrast, replenishment with the standard hydroponic solution resulted in increased solution EC and concentrations of calcium, magnesium, and sulfate and decreased nitrogen, phosphorus, and potassium. Replenishment treatment had no effect on yield for arugula and basil; however, results suggested root zone imbalances may have still occurred eventually for both treatments and species. Species-specific replenishment solutions would be most effective in scenarios where solutions could be formulated for a specific crop, mixed using high-quality irrigation water, and where environmental conditions are controlled and stable, such as indoor farming systems. This study highlighted several practical challenges and considerations regarding the formulation of hydroponic solutions using mass balance.

Assessing pathways of heavy metal accumulation in aquaculture shrimp and their introductions into the pond environment based on a dynamic model and mass balance principle

The impact of heavy metals (HMs) on the quality of aquaculture products has attracted worldwide attention. Since Litopenaeus vannamei is a popular aquaculture product among consumers worldwide, it is of great importance to guarantee its dietary safety. An in-situ monitoring program lasting for three months in a typical Litopenaeus vannamei farm found that Pb (100 %) and Cr (86 %) in the adult shrimp were higher than the safety guidelines. In the meantime, Cu (100 %), Cd (100 %) in the water and Cr (40 %) in the feed exceeded the corresponding thresholds. Therefore, quantification of different exposure pathways of shrimp and contamination origins in pond is valuable to improve the dietary safety of the shrimp. Based on Optimal Modeling for Ecotoxicological Applications (OMEGA), Cu was primarily from the ingestion of feed, accounting for 67 % of bioaccumulation, while Cd, Pb and Cr primarily entered shrimp through the adsorption from overlying water (53 % for Cd and 78 % for Pb) and porewater (66 % for Cr), respectively. The HMs in the pond water were further tracked based on a mass balance analysis. The main source of Cu in the aquaculture environment was feed, being responsible for 37 % of the total input. Pb, Cd and Cr were primarily from the inlet water with contributions of 84 %, 54 % and 52 %, respectively. In summary, the proportions of different exposure pathways and origins of HMs in pond-cultured shrimp and its living environment varied widely. To keep end-consumers eating healthily, species specific treatment is required. Feed should be regulated more for Cu. Aimed pretreatments for Pb and Cd in influent water are needed and an additional immobilization for Cr in sediment porewater should be investigated. After implementation of these treatments, the food quality improvement could be further quantified based on our prediction model.