A decade of nitrous oxide (N2O) monitoring in full-scale wastewater treatment processes: A critical review

Autor: V. Vasilaki, Evina Katsou, Theoni Maria Massara, Peyo Stanchev, Francesco Fatone
Rok vydání: 2019
Předmět:
Multivariate statistics
Environmental Engineering
Process (engineering)
Emission factors
Multivariate data mining methods
0208 environmental biotechnology
ComputerApplications_COMPUTERSINOTHERSYSTEMS
02 engineering and technology
010501 environmental sciences
01 natural sciences
12. Responsible consumption
Mitigation measures
Process control
Duration (project management)
Triggering operational conditions
Process engineering
Waste Management and Disposal
0105 earth and related environmental sciences
Water Science and Technology
Civil and Structural Engineering
Nitrous oxide
Mechanistic models
business.industry
Ecological Modeling
Energy consumption
Pollution
6. Clean water
Full-scale monitoring campaigns
020801 environmental engineering
Production pathways
Wastewater
13. Climate action
Carbon footprint
Environmental science
Sewage treatment
ComputingMethodologies_GENERAL
business
Zdroj: Water Research
ISSN: 0043-1354
DOI: 10.1016/j.watres.2019.04.022
Popis: Direct nitrous oxide (N2O) emissions during the biological nitrogen removal (BNR) processes can significantly increase the carbon footprint of wastewater treatment plant (WWTP) operations. Recent onsite measurement of N2O emissions at WWTPs have been used as an alternative to the controversial theoretical methods for the N2O calculation. The full-scale N2O monitoring campaigns help to expand our knowledge on the N2O production pathways and the triggering operational conditions of processes. The accurate N2O monitoring could help to find better process control solutions to mitigate N2O emissions of wastewater treatment systems. However, quantifying the emissions and understanding the long-term behaviour of N2O fluxes in WWTPs remains challenging and costly. A review of the recent full-scale N2O monitoring campaigns is conducted. The analysis covers the quantification and mitigation of emissions for different process groups, focusing on techniques that have been applied for the identification of dominant N2O pathways and triggering operational conditions, techniques using operational data and N2O data to identify mitigation measures and mechanistic modelling. The analysis of various studies showed that there are still difficulties in the comparison of N2O emissions and the development of emission factor (EF) databases; the N2O fluxes reported in literature vary significantly even among groups of similar processes. The results indicated that the duration of the monitoring campaigns can impact the EF range. Most N2O monitoring campaigns lasting less than one month, have reported N2O EFs less than 0.3% of the N-load, whereas studies lasting over a year have a median EF equal to 1.7% of the N-load. The findings of the current study indicate that complex feature extraction and multivariate data mining methods can efficiently convert wastewater operational and N2O data into information, determine complex relationships within the available datasets and boost the long-term understanding of the N2O fluxes behaviour. The acquisition of reliable full-scale N2O monitoring data is significant for the calibration and validation of the mechanistic models -describing the N2O emission generation in WWTPs. They can be combined with the multivariate tools to further enhance the interpretation of the complicated full-scale N2O emission patterns. Finally, a gap between the identification of effective N2O mitigation strategies and their actual implementation within the monitoring and control of WWTPs has been identified. This study concludes that there is a further need for i) long-term N2O monitoring studies, ii) development of data-driven methodological approaches for the analysis of WWTP operational and N2O data, and iii) better understanding of the trade-offs among N2O emissions, energy consumption and system performance to support the optimization of the WWTPs operation.
Databáze: OpenAIRE
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