This article is part of the Tribute to James J. Morgan special issue. Zero perceived human benefit leads to a human expectation of zero risk/cost. 50% of a really big problem is still a really big problem. “The animals are on fire. Everything is going to burn. Our land, our animals and our house. What else do we have anyway?”(36) The work of J.F.P. on this manuscript was funded in part by the Pensmore

Use of low-cost sensors for air quality measurements has attracted a lot of research attention in the last five years.(1) One of the central research themes has been the validation of low-cost sensor measurements against measurements from high-end instruments and development of suitable calibration algorithms. At the time of writing, a search on Google Scholar for “low-cost air quality sensor” and

Free Nitrous Acid (FNA) pre-treatment is a promising technology demonstrated effective in improving waste activated sludge degradability and anaerobic digestion (AD) performance. Pre-treatment conditions including FNA concentration and treatment duration determine operational and capital cost of full-scale implementation, which have not been studied in long-term experiments. The knowledge of FNA pre-treatment

Interest in anaerobic co-digestion (AcoD) has increased significantly in recent decades owing to enhanced biogas productivity due to the utilization of different organic wastes, such as food waste and sewage sludge. In this study, a robust AcoD model for biogas prediction is developed using deep learning (DL). We propose a hybrid DL architecture, i.e., DA–LSTM–VSN, wherein a dual-stage-attention (DA)-based

Wet deposition, including both in- and below-cloud scavenging, is critical for the atmospheric transport modeling of 137Cs following the Fukushima Daiichi Nuclear power plant (FDNPP) accident. Although intensively investigated, wet deposition simulation is still subject to uncertainties of meteorological inputs and wet scavenging modeling, leading to biased 137Cs transport prediction. To reduce the

The containment and closure policies adopted in attempts to contain the spread of the 2019 coronavirus disease (COVID-19) have impacted nearly every aspect of our lives including the environment we live in. These influences may be observed when evaluating changes in pollutants such as nitrogen dioxide (NO2), which is an important indicator for economic, industrial, and other anthropogenic activities