Seasonality of nitrous oxide emissions at six full-scale wastewater treatment plants.

Nitrous oxide (N2O) is an ozone-depleting greenhouse gas that contributes significantly to the carbon footprint of a wastewater treatment plant (WWTP). Plant-specific measurement campaigns are required to reliably quantify the emission level that has been found to significantly vary between WWTPs. In this study, the N2O emissions were quantified from five full-scale WWTPs during 4-19-day measurement campaigns conducted under both cold period conditions (water temperature below 12 °C) and warm period conditions (water temperature from 12 to 20 °C). The measurement data were studied alongside long-term monitoring data from a sixth WWTP. The calculated emission factors (EFs) varied from near 0 to 1.8% relative to the influent total nitrogen load. The results confirmed a significant seasonality of N2O emissions as well as a notable variation between WWTPs in the emission level, which a single fixed EF cannot represent. Wastewater temperature was one explanatory factor for the emission seasonality. Both low and high emissions were measured from denitrifying-nitrifying activated sludge (AS) processes, while the emissions from only nitrifying AS processes were consistently high. Nitrite (NO2-) at the end of the aerobic zones of the AS process was linked to the variability in N2O emissions during the cold period.

Effects of COVID-19 on mobility GHG emissions: Case of the city of Lahti, Finland.

The coronavirus disease COVID-19 has spread worldwide since early 2020, and it has impacted mobility emissions due to mobility restrictions and e.g. increased remote work. This creates a good opportunity to assess how mobility emissions have reduced due to COVID-19. This research is based on data related to mobility distances and modes that have been automatically collected by using a mobile phone application in the city of Lahti, Finland. The results show that mobility decreased in total by approximately 40% during the first wave of COVID-19 in spring 2020. The global warming potential decreased at the same time by approximately 36%. In addition, a considerable shift in modal shares could be seen. The relative modal share of passenger cars increased by 6 percentage points while the share of public transport decreased by 18 percentage points. Despite the considerable reduction, further reductions in emissions from mobility are needed to meet the 1.5 degree climate targets in the urban mobility sector. However, further reductions can be reached also by increasingly using renewable mobility energy sources.

Comparison of methods for nitrous oxide emission estimation in full-scale activated sludge.

Nitrous oxide (N2O) gas transfer was studied in a full-scale process to correlate liquid phase N2O concentrations with gas phase N2O emissions and compare methods of determining the volumetric mass transfer coefficient, KLa. Off-gas and liquid phase monitoring were conducted at the Viikinmäki wastewater treatment plant (WWTP) over a two-week period using a novel method for simultaneous measurement of dissolved and off-gas N2O and O2 from the same location. KLa was calculated with three methods: empirically, based on aeration superficial velocity, from experimentally determined O2 KLa, and using a static value of best fit. The findings of this study indicated trends in local emitted N2O consistently matched trends in local dissolved N2O, but the magnitude of N2O emissions could not be accurately estimated without correction. After applying a static correction factor, the O2 method, using experimentally determined O2 KLa, provided the best N2O emission estimation over the data collection period. N2O emissions estimated using the O2 method had a root mean square error (RMSE) of 70.5 compared against measured concentrations ranging from 3 to 1,913 ppm and a maximum 28% error. The KLa value, and therefore the method of KLa determination, had a significant impact on estimated emissions.

Development of an Extended ASM3 Model for Predicting the Nitrous Oxide Emissions in a Full-Scale Wastewater Treatment Plant.

An Activated Sludge Model #3 (ASM3) based, pseudomechanistic model describing nitrous oxide (N2O) production was created in this study to provide more insight into the dynamics of N2O production, consumption, and emissions at a full-scale wastewater treatment plant (WWTP). N2O emissions at the studied WWTP are monitored throughout the plant with a Fourier transform infrared analyzer, while the developed model encountered N2O production in the biological reactors via both ammonia oxidizing bacteria (AOB) nitrification and heterotrophic denitrifiers. Additionally, the stripping of N2O was included by applying a KL a-based approach that has not been widely used before. The objective was to extend the existing ASM3-based model of the plant and assess how well the full-scale emissions could be predicted with the selected model. The validity and applicability of the model were tested by comparing the simulation results with the comprehensive online data. The results show that the ASM3-based model can be successfully extended and applied to modeling N2O production and emissions at a full-scale WWTP. These results demonstrate that the biological reactor can explain most of the N2O emissions at the plant, but a significant proportion of the liquid-phase N2O is further transferred during the process.

Monitoring a municipal wastewater treatment process using a trend analysis.

New monitoring methods are required to enhance the operation of a wastewater treatment process and to meet the constantly tightening regulations for the effluent discharges. An on-line optical monitoring device, that analyses the morphological parameters of the flocs, has been shown to be a potential tool for assessing the wastewater quality and the state of the activated sludge process. In this paper, the earlier presented trend analysis method is applied to the operating conditions, the treatment results and the optical monitoring variables of a full-scale biological wastewater treatment process. The trend episodes and the deviation indices resulted from the trend analysis provide warning of the changes in the monitored variables and the received information can be used as assistance in the treatment process operation and avoiding harmful environmental risks.

Modelling effluent quality based on a real-time optical monitoring of the wastewater treatment process.

A novel optical monitoring device was used for imaging an activated sludge process in situ during a period of over one year. In this study, the dependencies between the results of image analysis and the process measurements were studied, and the optical monitoring results were utilized to predict the important quality parameters for the wastewater treatment process efficiency: suspended solids, biological oxygen demand, chemical oxygen demand, total nitrogen and total phosphorous in biologically treated wastewater. The optimal subsets of variables for each model were searched using five variable selection methods. It was shown that online optical analysis results have clear dependencies on some process variables and the purification result. The model based on optical monitoring and process variables from the early stage of the treatment process can be used to predict the levels of important quality parameters, and to show the quality of the biologically treated wastewater hours in advance. This study confirms that the optical monitoring method is a valuable tool for monitoring a wastewater treatment process and receiving new information in real time. Combined with predictive modelling, it has the potential to be used in process control, keeping the process in a stable operating condition and avoiding environmental risks.

Real-time optical monitoring of the wastewater treatment process.

One activated sludge process line was optically monitored in situ by a novel image analysis equipment. The results of the image analysis were studied to find out dependencies to the process variables of the wastewater treatment plant (WWTP) and to the quality of the treated wastewater. The quality parameter of the treated wastewater, suspended solids, was modelled using the image analysis results. The model can be used for evaluating the performance of the WWTP and for the better control for stable effluent quality. It was shown that the results of the online optical monitoring reveal useful information from the process and can be used in forecasting the quality of biologically treated wastewater. The optical monitoring method together with process measurements has an important role in keeping the process in stable operating conditions and avoiding environmental risks.