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The authors looked at phytoremediation, the process by which plants are used to remove pollutants from our environment, and the ability of Lemna minor to perform phytoremediation in various simulated polluted environments. The authors found that L. minor could remove pollutants from the environment and that the addition of bacteria increased this removal.

A key barrier to adoption of solar energy technology is the low efficiency of solar cells converting solar energy into electricity. Sims and Sims tackle this problem by coding a Raspberry Pi as a multimeter to determine which wavelength of light generates the most voltage and current from a solar panel.

This study hypothesized that a machine learning model could accurately predict the severity of California wildfires and determine the most influential meteorological factors. It utilized a custom dataset with information from the World Weather Online API and a Kaggle dataset of wildfires in California from 2013-2020. The developed algorithms classified fires into seven categories with promising accuracy (around 55 percent). They found that higher temperatures, lower humidity, lower dew point, higher wind gusts, and higher wind speeds are the most significant contributors to the spread of a wildfire. This tool could vastly improve the efficiency and preparedness of firefighters as they deal with wildfires.

While some believe that ride-hailing services offer reduced CO₂ emissions compared to individual driving, studies have found that driving without passengers on ride-hailing trips or "deadheading" prevents this. Here, with a mathematical model, the authors investigated if the use of electric vehicles as ride-hailing vehicles could offer reduced CO₂ emissions. They found that the improved vehicle efficiency and cleaner generation could in fact lower emissions compared to the use of personal gas vehicles.

Here, the authors investigated the ability to use fruit peels to help soil retain moisture, a property that is essential to agriculture. Across a 96-hour observation period, orange, banana, and kiwi peel water emulsions were evaluated for their effects on soil moisture. They found that orange peels retained the most moisture, but banana and kiwi peels also offered improvements over their control sample.

The authors test whether soaking maize seeds in a solution of melatonin improves seed germination and drought tolerance.

The authors looked at the emissions from a small, carbureted engine that was being powered by a mix of ethanol and methanol compared to E10 gasoline. The found that across all four pollutants measured, the ethanol-methanol mixture resulted in less emissions compared to the E10 fuel.

Algal blooms pose a threat to ecosystems, but the methods used to combat these blooms might harm more than just the algae. Halepete, Graham, and Lowe-Schmahl demonstrate negative effects of anti-algae treatments on a cyanobacterium (Spirulina major), and the water fleas (Daphnia magna) that live alongside these cyanobacteria.

This study collected samples from water bodies near hog farms and an aquatic environment not near a hog farm. It was hypothesized that water bodies near the hog farms would have lower water quality with higher turbidity, total dissolved solids (TDS), and pH than the water body not in proximity to a hog farm because of water contamination with hog waste. Results showed that the turbidity was 4–6 times higher, TDS was 1.5–2 times higher, and pH was 3 units higher in the 2 experimental locations compared to the control location. This study and its findings are important for understanding the impact of hog farming on the proximal water bodies.

Based on the success of deep learning, recent works have attempted to develop a waste classification model using deep neural networks. This work presents federated learning (FL) for a solution, as it allows participants to aid in training the model using their own data. Results showed that with less clients, having a higher participation ratio resulted in less accuracy degradation by the data heterogeneity.