title: Nutrient removal by algal polyculture in dairy farm effluent

authors: Ishan, Ilisa

abstract: Nutrient pollution from dairy farm effluent, particularly nitrogen (N) and phosphorus (P), significantly contributes to environmental degradation and eutrophication, necessitating effective bioremediation strategies. This study explores the efficacy of algae polyculture E3 in remediating dairy farm wastewater, focusing on nutrient removal and algal growth. Conducted over a 28-day period, the research compares the bioremediation capabilities of algae polyculture in autoclaved and non-autoclaved effluent samples. Findings reveal that algae polyculture demonstrates superior bioremediation performance in non-autoclaved conditions, with growth rates ranging from 8.07 to 10.13 mg L-1 d-1. The algal polyculture achieved significant nutrient removal, eliminating 90.9% of ammonium (NH₄⁺) and 99.1% of phosphate (PO₄³⁻), highlighting its potential in mitigating nutrient pollution. The study underscores the importance of operational conditions, as non-autoclaved environments fostered more robust algal growth and nutrient uptake. Further, the research involved the optimisation of the model data, leading to improved accuracy in simulating the biological removal processes. The optimised model better reflects real-world bioremediation dynamics, facilitating more reliable predictions of algal performance and nutrient cycling. Additionally, the study identifies a 10-day hydraulic retention time (HRT) as optimal for balancing algal biomass growth with nutrient removal, addressing common challenges such as algal washout and inefficiency in nutrient uptake. In conclusion, the findings advocate for the application of algae polyculture E3 in the bioremediation of dairy farm effluent, proposing a sustainable approach to addressing the critical issue of nutrient pollution. By optimizing conditions for algal growth and nutrient removal, this research contributes to the development of more effective environmental management practices.

text: Nutrient removal by algal polyculture in dairy farm effluent Nutrient pollution from dairy farm effluent, particularly nitrogen (N) and phosphorus (P), significantly contributes to environmental degradation and eutrophication, necessitating effective bioremediation strategies. This study explores the efficacy of algae polyculture E3 in remediating dairy farm wastewater, focusing on nutrient removal and algal growth. Conducted over a 28-day period, the research compares the bioremediation capabilities of algae polyculture in autoclaved and non-autoclaved effluent samples. Findings reveal that algae polyculture demonstrates superior bioremediation performance in non-autoclaved conditions, with growth rates ranging from 8.07 to 10.13 mg L-1 d-1. The algal polyculture achieved significant nutrient removal, eliminating 90.9% of ammonium (NH₄⁺) and 99.1% of phosphate (PO₄³⁻), highlighting its potential in mitigating nutrient pollution. The study underscores the importance of operational conditions, as non-autoclaved environments fostered more robust algal growth and nutrient uptake. Further, the research involved the optimisation of the model data, leading to improved accuracy in simulating the biological removal processes. The optimised model better reflects real-world bioremediation dynamics, facilitating more reliable predictions of algal performance and nutrient cycling. Additionally, the study identifies a 10-day hydraulic retention time (HRT) as optimal for balancing algal biomass growth with nutrient removal, addressing common challenges such as algal washout and inefficiency in nutrient uptake. In conclusion, the findings advocate for the application of algae polyculture E3 in the bioremediation of dairy farm effluent, proposing a sustainable approach to addressing the critical issue of nutrient pollution. By optimizing conditions for algal growth and nutrient removal, this research contributes to the development of more effective environmental management practices.

year: 2024

title: High Frequency Monitoring and Three-Dimensional Modelling of Temporal Variations in Water Quality of Lake Rotorua, New Zealand

authors: Zhang, Chenguang

subjects: Lake Rotorua

abstract: Over the last few decades, anthropogenic eutrophication has become a significant problem in New Zealand and other parts of the world. Lake Rotorua is located in the central North Island, New Zealand. It is a lake with significant historical, cultural and recreational values that has undergone anthropogenic eutrophication.

Lake Rotorua has been exposed to anthropogenic impacts through conversion of forested land to agricultural use within its catchment, and the discharge of domestic sewage into the lake. Cyanobacterial blooms have become a common occurrence in the lake each summer. These blooms not only reduce aesthetic appeal but also have potential to affect human health. Lake stratification and physical mixing events are the most important factors influencing nutrient availability and phytoplankton growth in Lake Rotorua.

The main objective of this study was to use high frequency monitoring data to investigate the significance of lake stratification events and how these events interact with the development of the cyanobacteria population and changes in nutrient concentrations in Lake Rotorua. The second objective was to use an ecological model to understand the relationship between physical, chemical and biological variables, and phytoplankton dynamics.

Data from a high frequency real-time water quality monitoring buoy was used as the basis for 12 sampling trips to Lake Rotorua timed around stratification and mixing events. Water samples were collected from five different sites for nutrient analysis, chlorophyll a analysis, and phytoplankton and zooplankton identification at depth intervals of 6 meters. Profiles were taken for temperature, dissolved oxygen and fluorescence. Total suspended solids and volatile suspended solids were also analysed. The data provided by the buoy, combined with additional sampling and measurements around stratification events, were used to calibrate a three-dimensional ecosystem model, ELCOM-CAEDYM.

Periods consisting of a few days of high solar radiation and low winds caused Lake Rotorua to become stratified between 26 January 2009 and 20 February 2009. During this stratification period the bottom waters became deoxygenated and there were large increases in of phosphorus and nitrogen concentrations in bottom waters, which were subsequently dispersed through the water column when the lake mixed again. Ammonium and phosphate were the dominant species of inorganic nitrogen and phosphorus in bottom waters during the periods of stratification. Upon mixing there was rapid growth of cyanobacteria (Microcystis sp. and Anabaena sp.). For the zooplankton community, copepod and rotifer densities increased significantly after the stratification event and replaced the previously dominant cladocerans.

In the study high frequency modelling with ELCOM-CADYM simulated the general trends of water temperature, dissolved oxygen and nutrient concentrations in Lake Rotorua. The model captured the water temperature fluctuation before, during, and after lake stratification as well as subsequent dissolved oxygen changes over time and space. Simulated nutrient concentrations were close to the field measurements, in particular NH4, TN and TP. Some issues occurred with high frequency simulations such as being unable to capture the strong fluctuations of lake surface temperature, and the magnitude of the decreases in dissolved oxygen under strong stratification.

text: High Frequency Monitoring and Three-Dimensional Modelling of Temporal Variations in Water Quality of Lake Rotorua, New Zealand Over the last few decades, anthropogenic eutrophication has become a significant problem in New Zealand and other parts of the world. Lake Rotorua is located in the central North Island, New Zealand. It is a lake with significant historical, cultural and recreational values that has undergone anthropogenic eutrophication.

Lake Rotorua has been exposed to anthropogenic impacts through conversion of forested land to agricultural use within its catchment, and the discharge of domestic sewage into the lake. Cyanobacterial blooms have become a common occurrence in the lake each summer. These blooms not only reduce aesthetic appeal but also have potential to affect human health. Lake stratification and physical mixing events are the most important factors influencing nutrient availability and phytoplankton growth in Lake Rotorua.

The main objective of this study was to use high frequency monitoring data to investigate the significance of lake stratification events and how these events interact with the development of the cyanobacteria population and changes in nutrient concentrations in Lake Rotorua. The second objective was to use an ecological model to understand the relationship between physical, chemical and biological variables, and phytoplankton dynamics.

Data from a high frequency real-time water quality monitoring buoy was used as the basis for 12 sampling trips to Lake Rotorua timed around stratification and mixing events. Water samples were collected from five different sites for nutrient analysis, chlorophyll a analysis, and phytoplankton and zooplankton identification at depth intervals of 6 meters. Profiles were taken for temperature, dissolved oxygen and fluorescence. Total suspended solids and volatile suspended solids were also analysed. The data provided by the buoy, combined with additional sampling and measurements around stratification events, were used to calibrate a three-dimensional ecosystem model, ELCOM-CAEDYM.

Periods consisting of a few days of high solar radiation and low winds caused Lake Rotorua to become stratified between 26 January 2009 and 20 February 2009. During this stratification period the bottom waters became deoxygenated and there were large increases in of phosphorus and nitrogen concentrations in bottom waters, which were subsequently dispersed through the water column when the lake mixed again. Ammonium and phosphate were the dominant species of inorganic nitrogen and phosphorus in bottom waters during the periods of stratification. Upon mixing there was rapid growth of cyanobacteria (Microcystis sp. and Anabaena sp.). For the zooplankton community, copepod and rotifer densities increased significantly after the stratification event and replaced the previously dominant cladocerans.

In the study high frequency modelling with ELCOM-CADYM simulated the general trends of water temperature, dissolved oxygen and nutrient concentrations in Lake Rotorua. The model captured the water temperature fluctuation before, during, and after lake stratification as well as subsequent dissolved oxygen changes over time and space. Simulated nutrient concentrations were close to the field measurements, in particular NH4, TN and TP. Some issues occurred with high frequency simulations such as being unable to capture the strong fluctuations of lake surface temperature, and the magnitude of the decreases in dissolved oxygen under strong stratification.

year: 2010

title: Wearable technology for hazardous remote environments: Smart shirt and Rugged IoT network for forestry worker health

authors: Hinze, Annika

subjects: software engineering

abstract: This paper introduces the architecture and details of our wearable IoT solution for workplace health and safety in rugged outdoor environments. We focus on the specific requirements defined by the New Zealand forestry environment as it is the industry with the most fatalities and highest accident rate in New Zealand. Neither consumer-level products nor professional wearables have been found to be suitable for forestry conditions. Furthermore, forestry workplaces cannot rely on existing networking infrastructure, and due to their remote and rugged nature, no permanent setup is possible.

We describe the Hakituri project in which we integrate wearable devices, networking, data analytics, and a buddy system into a novel monitoring solution for worker health and safety. Our wearable IoT solution includes a dynamic network set-up, wearables suitable for forestry conditions, contextual rule-based data analytics, and real-time alerts. A wearable smart shirt carries sensors for collecting personal data from forestry workers, while further environmental sensors capture contextual data. The IoT network is set up for communication in unreliable and rugged outdoor environments. We explore a variety of setups to achieve the best quality outcomes for health and safety in the forestry domain.

text: Wearable technology for hazardous remote environments: Smart shirt and Rugged IoT network for forestry worker health This paper introduces the architecture and details of our wearable IoT solution for workplace health and safety in rugged outdoor environments. We focus on the specific requirements defined by the New Zealand forestry environment as it is the industry with the most fatalities and highest accident rate in New Zealand. Neither consumer-level products nor professional wearables have been found to be suitable for forestry conditions. Furthermore, forestry workplaces cannot rely on existing networking infrastructure, and due to their remote and rugged nature, no permanent setup is possible.

We describe the Hakituri project in which we integrate wearable devices, networking, data analytics, and a buddy system into a novel monitoring solution for worker health and safety. Our wearable IoT solution includes a dynamic network set-up, wearables suitable for forestry conditions, contextual rule-based data analytics, and real-time alerts. A wearable smart shirt carries sensors for collecting personal data from forestry workers, while further environmental sensors capture contextual data. The IoT network is set up for communication in unreliable and rugged outdoor environments. We explore a variety of setups to achieve the best quality outcomes for health and safety in the forestry domain.

year: 2022