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Simulation of the fate and seasonal variations of α-hexachlorocyclohexane in Lake Chaohu using a dynamic fugacity model.

Kong XZ, He W, Qin N, He QS, Yang B, Ouyang H, Wang Q, Yang C, Jiang Y, Xu F - ScientificWorldJournal (2012)

Bottom Line: Seasonal patterns in various media were successfully modeled and factors leading to this seasonality were discussed.Sensitivity analysis found that parameters of source and degradation were more important than the other parameters.Uncertainty analysis showed that the model uncertainty was relatively low but significantly increased in the second half of the simulation period due to the increase in the gas-water diffusion flux variability.

View Article: PubMed Central - PubMed

Affiliation: MOE Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.

ABSTRACT
Fate and seasonal variations of α-hexachlorocyclohexane (α-HCH) were simulated using a dynamic fugacity model in Lake Chaohu, China. Sensitivity analyses were performed to identify influential parameters and Monte Carlo simulation was conducted to assess model uncertainty. The calculated and measured values of the model were in good agreement except for suspended solids, which might be due to disregarding the plankton in water. The major source of α-HCH was an input from atmospheric advection, while the major environmental outputs were atmospheric advection and sediment degradation. The net annual input and output of α-HCH were approximately 0.294 t and 0.412 t, respectively. Sediment was an important sink for α-HCH. Seasonal patterns in various media were successfully modeled and factors leading to this seasonality were discussed. Sensitivity analysis found that parameters of source and degradation were more important than the other parameters. The sediment was influenced more by various parameters than air and water were. Temperature variation had a greater impact on the dynamics of the model output than other dynamic parameters. Uncertainty analysis showed that the model uncertainty was relatively low but significantly increased in the second half of the simulation period due to the increase in the gas-water diffusion flux variability.

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Related in: MedlinePlus

Dynamic coefficients of sensitivity of the calculated concentrations of the environmental compartments to the input dynamic parameters.
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Related In: Results  -  Collection


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fig7: Dynamic coefficients of sensitivity of the calculated concentrations of the environmental compartments to the input dynamic parameters.

Mentions: The dynamic sensitivity coefficients (SCV) are shown in Figure 7. The model output was much more sensitive to temperature (T) than to the other parameters because temperature had very strong effects on Ps and H, the two important parameters in the model. Consequently, temperature played a decisive role in the distribution of α-HCH between the gaseous and particulate phases as well as between the air and water [24]. In addition, h2, Q01t, Q10t, C01t, X13, K12, K21, and Kw also had strong influences on the dynamic changes of the model output. h2 strongly affected the variation of α-HCH concentrations in the water and suspended solids; Q01t, Q10t, and C01t were associated with the atmospheric advection, which was the main source of the α-HCH in Lake Chaohu. Thus, the seasonal variations in these three parameters also had significant impacts. Cao et al. [2] found that the parameters related to source and degradation in the fugacity model were relatively more important, which was consistent with the relatively high sensitivities of Q01t, Q10t, C01t, km4, and km2. X13 had a relatively strong influence on the seasonal changes in the concentration in the atmosphere and the water bodies as well as the particulate and suspended matter content, which is in agreement with the conclusion of the Pearl River Delta study [22]; K12, K21, and Kw were the main parameters influencing the air-water interface flux due to their direct impacts and significant seasonal variations, and these three parameters are also important parameters generally. In addition, due to the insignificant effect of water inflows on the model, parameters such as Q02t, Q20t, and Q23h had little effect on the variability of the model output. Without considering the biological phase, the importance of X23 was also reduced. The low sensitivity coefficient of K42r was due to the corresponding low resuspension flux.


Simulation of the fate and seasonal variations of α-hexachlorocyclohexane in Lake Chaohu using a dynamic fugacity model.

Kong XZ, He W, Qin N, He QS, Yang B, Ouyang H, Wang Q, Yang C, Jiang Y, Xu F - ScientificWorldJournal (2012)

Dynamic coefficients of sensitivity of the calculated concentrations of the environmental compartments to the input dynamic parameters.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3539339&req=5

fig7: Dynamic coefficients of sensitivity of the calculated concentrations of the environmental compartments to the input dynamic parameters.
Mentions: The dynamic sensitivity coefficients (SCV) are shown in Figure 7. The model output was much more sensitive to temperature (T) than to the other parameters because temperature had very strong effects on Ps and H, the two important parameters in the model. Consequently, temperature played a decisive role in the distribution of α-HCH between the gaseous and particulate phases as well as between the air and water [24]. In addition, h2, Q01t, Q10t, C01t, X13, K12, K21, and Kw also had strong influences on the dynamic changes of the model output. h2 strongly affected the variation of α-HCH concentrations in the water and suspended solids; Q01t, Q10t, and C01t were associated with the atmospheric advection, which was the main source of the α-HCH in Lake Chaohu. Thus, the seasonal variations in these three parameters also had significant impacts. Cao et al. [2] found that the parameters related to source and degradation in the fugacity model were relatively more important, which was consistent with the relatively high sensitivities of Q01t, Q10t, C01t, km4, and km2. X13 had a relatively strong influence on the seasonal changes in the concentration in the atmosphere and the water bodies as well as the particulate and suspended matter content, which is in agreement with the conclusion of the Pearl River Delta study [22]; K12, K21, and Kw were the main parameters influencing the air-water interface flux due to their direct impacts and significant seasonal variations, and these three parameters are also important parameters generally. In addition, due to the insignificant effect of water inflows on the model, parameters such as Q02t, Q20t, and Q23h had little effect on the variability of the model output. Without considering the biological phase, the importance of X23 was also reduced. The low sensitivity coefficient of K42r was due to the corresponding low resuspension flux.

Bottom Line: Seasonal patterns in various media were successfully modeled and factors leading to this seasonality were discussed.Sensitivity analysis found that parameters of source and degradation were more important than the other parameters.Uncertainty analysis showed that the model uncertainty was relatively low but significantly increased in the second half of the simulation period due to the increase in the gas-water diffusion flux variability.

View Article: PubMed Central - PubMed

Affiliation: MOE Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China.

ABSTRACT
Fate and seasonal variations of α-hexachlorocyclohexane (α-HCH) were simulated using a dynamic fugacity model in Lake Chaohu, China. Sensitivity analyses were performed to identify influential parameters and Monte Carlo simulation was conducted to assess model uncertainty. The calculated and measured values of the model were in good agreement except for suspended solids, which might be due to disregarding the plankton in water. The major source of α-HCH was an input from atmospheric advection, while the major environmental outputs were atmospheric advection and sediment degradation. The net annual input and output of α-HCH were approximately 0.294 t and 0.412 t, respectively. Sediment was an important sink for α-HCH. Seasonal patterns in various media were successfully modeled and factors leading to this seasonality were discussed. Sensitivity analysis found that parameters of source and degradation were more important than the other parameters. The sediment was influenced more by various parameters than air and water were. Temperature variation had a greater impact on the dynamics of the model output than other dynamic parameters. Uncertainty analysis showed that the model uncertainty was relatively low but significantly increased in the second half of the simulation period due to the increase in the gas-water diffusion flux variability.

Show MeSH
Related in: MedlinePlus