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Nitrous Oxide

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An adaptive Kalman filtering algorithm based on back-propagation (BP) neural network applied for simultaneously detection of exhaled CO and NO.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
A compact high-resolution spectroscopic sensor using a thermoelectrically (TE) cooled continuous-wave (CW) room temperature (RT) quantum cascade laser (QCL) was demonstrated for simultaneous measurements of exhaled carbon monoxide (CO) and nitrous ox...

Integrated Model for Understanding NO Emissions from Wastewater Treatment Plants: A Deep Learning Approach.

Environmental science & technology
This study aims to demonstrate the application of deep learning to quantitatively describe long-term full-scale data observed from wastewater treatment plants (WWTPs) from the perspectives of process modeling, process analysis, and forecasting modeli...

An Integrated First Principal and Deep Learning Approach for Modeling Nitrous Oxide Emissions from Wastewater Treatment Plants.

Environmental science & technology
Mathematical modeling plays a critical role toward the mitigation of nitrous oxide (NO) emissions from wastewater treatment plants (WWTPs). In this work, we proposed a novel hybrid modeling approach by integrating the first principal model with deep ...

Prediction of nitrous oxide emission of a municipal wastewater treatment plant using LSTM-based deep learning models.

Environmental science and pollution research international
Accurate assessment of greenhouse gas emissions from wastewater treatment plants is crucial for mitigating climate change. NO is a potent greenhouse gas that is emitted from wastewater treatment plants during the biological denitrification process. I...

Tree-structured parzen estimator optimized-automated machine learning assisted by meta-analysis for predicting biochar-driven NO mitigation effect in constructed wetlands.

Journal of environmental management
Biochar is a carbon-neutral tool for combating climate change. Artificial intelligence applications to estimate the biochar mitigation effect on greenhouse gases (GHGs) can assist scientists in making more informed solutions. However, there is also e...

Reevaluating the Drivers of Fertilizer-Induced NO Emission: Insights from Interpretable Machine Learning.

Environmental science & technology
Direct nitrous oxide (NO) emissions from fertilizer application are the largest anthropogenic source of global NO, but the factors influencing these emissions remain debated. Here, we compile 1134 observations of fertilizer-induced NO emission factor...

Forecasting nitrous oxide emissions from a full-scale wastewater treatment plant using LSTM-based deep learning models.

Water research
Nitrous oxide (NO) emissions from wastewater treatment plants (WWTPs) exhibit significant seasonal variability, making accurate predictions with conventional biokinetic models difficult due to complex and poorly understood biochemical processes. This...

Machine learning reveals dynamic controls of soil nitrous oxide emissions from diverse long-term cropping systems.

Journal of environmental quality
Soil nitrous oxide (NO) emissions exhibit high variability in intensively managed cropping systems, which challenges our ability to understand their complex interactions with controlling factors. We leveraged 17 years (2003-2019) of measurements at t...

Deciphering and Mitigating of Dynamic Greenhouse Gas Emission in Urban Drainage Systems with Knowledge-Infused Graph Neural Network.

Environmental science & technology
Deciphering and mitigating dynamic greenhouse gas (GHG) emissions under environmental fluctuation in urban drainage systems (UDGSs) is challenging due to the absence of a high-prediction model that accurately quantifies the contributions of biologica...