title: Environmental Impacts of Effluent Containing EDTA from Dairy Processing Plants

authors: Xie, Congmin Zoe

subjects: EDTA

abstract: Ethylenediaminetetraacetic acid (EDTA) is a well-known chelating agent, and has numerous applications in industries, for example in dairy industry to improve the cleaning efficiency of plant and equipment.

As EDTA is water-soluble and not volatile, it is eventually released into the environment with wastewater effluent. In general, EDTA has a low toxic impact for both humans and natural environments. There are some concerns, however, about its poor biodegradation in conventional wastewater treatment plants and natural environments, and its effect in mobilizing heavy metals from solid phases to pose a risk to groundwater.

In the late 1980's the environmental impact of EDTA was scrutinized in Europe. Since then, treatment and discharge of wastewater containing EDTA is increasingly required as environmental regulations become more stringent. This is the first investigation into the effects of EDTA in New Zealand.

In the New Zealand dairy industry, EDTA has been used as an additive alongside caustic agents to improve cleaning efficiency within dairy processing plants and to minimize dairy wastewater discharge into the environment. There are two main disposal methods of dairy wastes; direct discharge into the local stream after treatment, and spray irrigation onto pasture land. The primary aim of this research is to identify whether EDTA is detectable in the environment after the release of dairy wastes containing EDTA into that environment.

For the first time in New Zealand, an analytical method using reversed-phase ion-pair liquid chromatography, was established to determine EDTA present in dairy wastewater, and then applied to surface water, soils and groundwater with appropriate modifications. Method detection limits were 5  g/L for dairy wastewater, 1  g/L for surface water, 0.15 mg/kg (dry weight) for soils, and 2  g/L for groundwater.

Significant concentrations of EDTA, as high as 83 mg/L, were observed in wastewater from dairy processing plants, when EDTA had been used alongside alkaline cleaning agents. The analyses have shown that approximate 93 % of EDTA was removed in the existing biological treatment process, which is an extended aeration activated sludge process, operated under alkaline pH 8.0-8.2 with a 3-week sludge retention time.

For surface water receiving the dairy effluent, 1 - 2.7  g/L of EDTA were found, and no particular concerns were suggested about the associated heavy metals. 

A quasi one-dimension vertical mixing model and a two-dimension (depth-averaged) 3DD hydrodynamic model were applied to simulate EDTA dispersion in the river. The modelling results for 'a worst case scenario' of high EDTA release combined with a low river flow, suggest that the dairy effluent discharge at the Fonterra Waitoa dairy site will not lead to a significant effect on the Waitoa River in terms of EDTA concentration. 

Investigation of EDTA and heavy metal concentrations in pastoral topsoil and groundwater following the land application of dairy biomass concludes that there are no specific concerns. In contrast, the analyses suggest that heavy metals may be built up over long periods of irrigation with dairy effluent in soils, and then transported to the groundwater in the presence of EDTA. However, more research would be required to clarify this matter.

text: Environmental Impacts of Effluent Containing EDTA from Dairy Processing Plants Ethylenediaminetetraacetic acid (EDTA) is a well-known chelating agent, and has numerous applications in industries, for example in dairy industry to improve the cleaning efficiency of plant and equipment.

As EDTA is water-soluble and not volatile, it is eventually released into the environment with wastewater effluent. In general, EDTA has a low toxic impact for both humans and natural environments. There are some concerns, however, about its poor biodegradation in conventional wastewater treatment plants and natural environments, and its effect in mobilizing heavy metals from solid phases to pose a risk to groundwater.

In the late 1980's the environmental impact of EDTA was scrutinized in Europe. Since then, treatment and discharge of wastewater containing EDTA is increasingly required as environmental regulations become more stringent. This is the first investigation into the effects of EDTA in New Zealand.

In the New Zealand dairy industry, EDTA has been used as an additive alongside caustic agents to improve cleaning efficiency within dairy processing plants and to minimize dairy wastewater discharge into the environment. There are two main disposal methods of dairy wastes; direct discharge into the local stream after treatment, and spray irrigation onto pasture land. The primary aim of this research is to identify whether EDTA is detectable in the environment after the release of dairy wastes containing EDTA into that environment.

For the first time in New Zealand, an analytical method using reversed-phase ion-pair liquid chromatography, was established to determine EDTA present in dairy wastewater, and then applied to surface water, soils and groundwater with appropriate modifications. Method detection limits were 5  g/L for dairy wastewater, 1  g/L for surface water, 0.15 mg/kg (dry weight) for soils, and 2  g/L for groundwater.

Significant concentrations of EDTA, as high as 83 mg/L, were observed in wastewater from dairy processing plants, when EDTA had been used alongside alkaline cleaning agents. The analyses have shown that approximate 93 % of EDTA was removed in the existing biological treatment process, which is an extended aeration activated sludge process, operated under alkaline pH 8.0-8.2 with a 3-week sludge retention time.

For surface water receiving the dairy effluent, 1 - 2.7  g/L of EDTA were found, and no particular concerns were suggested about the associated heavy metals. 

A quasi one-dimension vertical mixing model and a two-dimension (depth-averaged) 3DD hydrodynamic model were applied to simulate EDTA dispersion in the river. The modelling results for 'a worst case scenario' of high EDTA release combined with a low river flow, suggest that the dairy effluent discharge at the Fonterra Waitoa dairy site will not lead to a significant effect on the Waitoa River in terms of EDTA concentration. 

Investigation of EDTA and heavy metal concentrations in pastoral topsoil and groundwater following the land application of dairy biomass concludes that there are no specific concerns. In contrast, the analyses suggest that heavy metals may be built up over long periods of irrigation with dairy effluent in soils, and then transported to the groundwater in the presence of EDTA. However, more research would be required to clarify this matter.

year: 2009

title: Accumulation of soil organic C and change in C:N ratio after establishment of pastures on reverted scrubland in New Zealand

authors: Schipper, Louis A.

subjects: soil organic C

abstract: Rates of organic carbon accumulation and changes in C:N ratio are reported for 10 New Zealand soils converted to pastures from scrub. The data were derived from archive papers originally published in 1964, but which did not report on changes in the C contents of the soils. The soils had been sampled to 0–7.5, 7.5–15, and 15–30 cm depths and chronosequences of up to 66 years obtained by selecting sites with differing times since pasture establishment. We calculated changes in the mass of C and N in the 0–7.5 cm depth and compared that to the mass in the 0–30 cm depth of soil. The shortest time over which organic matter change was assessed was 18 years and the longest was 66 years. Nine of the ten soils showed increases in the C contents of the 0–7.5 cm depth soil, and a natural logarithmic curve generally gave a better fit to the time course data than a linear fit. However, when the full 0–30 cm depth was considered, only two soils showed a significant increase in total C, changes in the C contents of other soils were non-significant, and two soils showed a decline in total C. The rates of change in the C contents were averaged over 0–5 years, 5–25 years and 25–50 years. Across all 10 soils, the mean rates of accumulation of C in the 0–7.5 cm depth were 1.07 (between 0 and 5 years), 0.27 (between 5 and 25 years) and 0.09 Mg C ha−1 year−1 (between 25 and 50 years) and significantly (P < 0.05) greater than zero. Very similar rates were obtained for the 0–30 cm depth of soil with mean rates across all soils 1.01 (0–5 years), 0.25 (5–25 years) and 0.09 Mg C ha−1 year −1 (25–50 years), respectively. In the 0–7.5 cm depth of soil, total Kjeldahl N (TKN) increased significantly in seven of the 10 soils. When expressed for the 0–30 cm depth of soil, only five soils still showed significant increases in TKN contents over time. Using the data for the 0–7.5 cm depth, the predicted time (mean and standard error) for the soils to reach a C:N ratio of <10 was 46 ± 17 years. The soils were originally sampled over 44 years ago, suggesting that currently (2009), very few of them could be expected to have capacity for further N storage in organic matter in the surface soil unless there was an increase in soil C. Changes in soil C and N in the shallow upper soil layers are easily masked by the relatively small changes in C and N contents and much greater masses of soil at lower depths.

text: Accumulation of soil organic C and change in C:N ratio after establishment of pastures on reverted scrubland in New Zealand Rates of organic carbon accumulation and changes in C:N ratio are reported for 10 New Zealand soils converted to pastures from scrub. The data were derived from archive papers originally published in 1964, but which did not report on changes in the C contents of the soils. The soils had been sampled to 0–7.5, 7.5–15, and 15–30 cm depths and chronosequences of up to 66 years obtained by selecting sites with differing times since pasture establishment. We calculated changes in the mass of C and N in the 0–7.5 cm depth and compared that to the mass in the 0–30 cm depth of soil. The shortest time over which organic matter change was assessed was 18 years and the longest was 66 years. Nine of the ten soils showed increases in the C contents of the 0–7.5 cm depth soil, and a natural logarithmic curve generally gave a better fit to the time course data than a linear fit. However, when the full 0–30 cm depth was considered, only two soils showed a significant increase in total C, changes in the C contents of other soils were non-significant, and two soils showed a decline in total C. The rates of change in the C contents were averaged over 0–5 years, 5–25 years and 25–50 years. Across all 10 soils, the mean rates of accumulation of C in the 0–7.5 cm depth were 1.07 (between 0 and 5 years), 0.27 (between 5 and 25 years) and 0.09 Mg C ha−1 year−1 (between 25 and 50 years) and significantly (P < 0.05) greater than zero. Very similar rates were obtained for the 0–30 cm depth of soil with mean rates across all soils 1.01 (0–5 years), 0.25 (5–25 years) and 0.09 Mg C ha−1 year −1 (25–50 years), respectively. In the 0–7.5 cm depth of soil, total Kjeldahl N (TKN) increased significantly in seven of the 10 soils. When expressed for the 0–30 cm depth of soil, only five soils still showed significant increases in TKN contents over time. Using the data for the 0–7.5 cm depth, the predicted time (mean and standard error) for the soils to reach a C:N ratio of <10 was 46 ± 17 years. The soils were originally sampled over 44 years ago, suggesting that currently (2009), very few of them could be expected to have capacity for further N storage in organic matter in the surface soil unless there was an increase in soil C. Changes in soil C and N in the shallow upper soil layers are easily masked by the relatively small changes in C and N contents and much greater masses of soil at lower depths.

year: 2010

title: Does artificial intelligence modelling have anything to offer traditional management of freshwater food resources?

authors: Death, Russell G.

abstract: Management of freshwater systems and the ecosystem services they provide has become a multi-stakeholder activity. This requires information on resources and how to manage them to be disseminated to a wide range of users. While artificial intelligence modelling can provide a powerful tool in managing and understanding resources and their drivers, they can be confusing to many users. In this study, we explored the potential use of two alternative modelling approaches (Boosted Regression Trees (BRT) and Bayesian Belief Networks (BBN)) for managing three species of freshwater mahinga kai species-kākahi or kaeo (freshwater mussel), koura (freshwater crayfish) and tuna (freshwater eel). While the BBN model I sbetter for stakeholder communication, the BRT produced more accurate models for all species. However, variables identified as being important for predicting abundance and biomass of these species were often environmental parameters that cannot be managed to improve yield. The artificial intelligence modelling does provide some accurate linkages between the target species and their environmental drivers. Nevertheless, translating these relationships into management plans remains challenging. The models are clearly not a panacea for better resource management, but provide one more tool that might assist multi-stakeholder understanding of how best to manage freshwater resources.

text: Does artificial intelligence modelling have anything to offer traditional management of freshwater food resources? Management of freshwater systems and the ecosystem services they provide has become a multi-stakeholder activity. This requires information on resources and how to manage them to be disseminated to a wide range of users. While artificial intelligence modelling can provide a powerful tool in managing and understanding resources and their drivers, they can be confusing to many users. In this study, we explored the potential use of two alternative modelling approaches (Boosted Regression Trees (BRT) and Bayesian Belief Networks (BBN)) for managing three species of freshwater mahinga kai species-kākahi or kaeo (freshwater mussel), koura (freshwater crayfish) and tuna (freshwater eel). While the BBN model I sbetter for stakeholder communication, the BRT produced more accurate models for all species. However, variables identified as being important for predicting abundance and biomass of these species were often environmental parameters that cannot be managed to improve yield. The artificial intelligence modelling does provide some accurate linkages between the target species and their environmental drivers. Nevertheless, translating these relationships into management plans remains challenging. The models are clearly not a panacea for better resource management, but provide one more tool that might assist multi-stakeholder understanding of how best to manage freshwater resources.

year: 2017