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      Estimation of countrywide N 2O emissions from wastewater treatment in Switzerland using long-term monitoring data

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          Highlights

          • Yearlong, continuous N 2O emission monitoring data from 14 WWTPs.

          • High correlation of yearly emission factor with effluent nitrite concentration.

          • WWTPs binned in 3 categories according to the nutrient removal goals.

          • Method proposed for refined countrywide emission estimation.

          • Carbon removal WWTP can emit substantially more N 2O than expected.

          Abstract

          Nitrous oxides (N 2O) emissions contribute to climate change and stratospheric ozone depletion. Wastewater treatment is an important, yet likely underestimated, source of N 2O emissions, as recent, long-term monitoring campaigns have demonstrated. However, the available data are insufficient to representatively estimate countrywide emission due to the brevity of most monitoring campaigns. This study showed that the emission estimates can be significantly improved using an advanced approach based on multiple continuous, long-term monitoring campaigns. In monitoring studies on 14 full-scale wastewater treatment plants (WWTPs), we found a strong variability in the yearly emission factors (EFs) (0.1 to 8% of the incoming nitrogen load) which exhibited a good correlation with effluent nitrite. But countrywide data on nitrite effluent concentrations is very limited and unavailable for emission estimation in many countries. Hence, we propose a countrywide emission factor calculated from the weighted EFs of three WWTP categories (carbon removal, EF: 0.1–8%, nitrification only: 1.8%, and full nitrogen removal: 0.9%). However, EF of carbon removal WWTPs are still highly uncertain given the expected variability in performance.

          The newly developed approach allows representative, country-specific estimations of the N 2O emissions from WWTP. Applied to Switzerland, the estimations result in an average EF of 0.9 to 3.6% and total emissions of 410 to 1690 tN 2O-N/year, which corresponds to 0.3–1.4% of the total greenhouse gas emissions in Switzerland. Our results demonstrate that better data availability and an improved understanding of long-term monitoring campaigns is crucial to improve current emission estimations. Finally, our results confirm several measures to mitigate N 2O emissions from wastewater treatment; year-round denitrification, limiting nitrite accumulation, and stringent control of sludge age in carbon removal plants.

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          SciPy 1.0: fundamental algorithms for scientific computing in Python

          SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
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            Array programming with NumPy

            Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves 1 and in the first imaging of a black hole 2 . Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.
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              Nitrous oxide (N2O): the dominant ozone-depleting substance emitted in the 21st century.

              By comparing the ozone depletion potential-weighted anthropogenic emissions of N2O with those of other ozone-depleting substances, we show that N2O emission currently is the single most important ozone-depleting emission and is expected to remain the largest throughout the 21st century. N2O is unregulated by the Montreal Protocol. Limiting future N2O emissions would enhance the recovery of the ozone layer from its depleted state and would also reduce the anthropogenic forcing of the climate system, representing a win-win for both ozone and climate.
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                Author and article information

                Journal
                Water Res X
                Water Res X
                Water Research X
                Elsevier
                2589-9147
                30 September 2021
                01 December 2021
                30 September 2021
                : 13
                : 100122
                Affiliations
                [a ]Eawag, Swiss Federal Institute for Aquatic Science and Technology, 8600 Duebendorf, Switzerland
                [b ]Institute of Environmental Engineering, ETH Zürich, 8093 Zürich, Switzerland
                Author notes
                [* ]Corresponding author.
                Article
                S2589-9147(21)00035-9 100122
                10.1016/j.wroa.2021.100122
                8503907
                34661091
                727fa4ec-8d96-4760-aeaa-77c74c63d5cd
                © 2021 The Authors. Published by Elsevier Ltd.

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 9 April 2021
                : 24 September 2021
                : 24 September 2021
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