Proper management of agricultural waste is challenging due to diverse sources, high production volumes, seasonal fluctuations, limited technical knowledge, and insufficient funding. These challenges often lead to soil degradation, environmental pollution, and adverse effects on ecosystems and human health. This study aims to investigate biogas production from poultry droppings using Continuous Stirred Tank Reactor (CSTR) Anaerobic Digestion (AD) technology to promote green energy use and as a sustainable solution for agricultural waste management.
Dried poultry manure samples were collected from two poultry farms in Lafia city and from their manure disposal sources. The samples were thoroughly stirred to ensure homogeneity and digested at a mesophilic temperature of 28.0 °C. With an initial solid concentration of 20.0%, the manure was diluted with water at 1:2 ratio to produce an input slurry containing 12.0% total volatile solids by weight. The experiment was conducted from July 20 to September 10, 2025. Parameters including pH, alkalinity, temperature, and biogas flow rate were monitored daily. Chemical and physical analyses of total solids, total volatile solids, and chemical oxygen demand were conducted during startup using three biological replicates (n = 3), with results expressed using statistical tool of mean ± standard error. Volatile fatty acids and alkalinity were measured using the distillation method.
“This study provides a crucial step in improving projections of water resource responses to climate change and underscores the value of integrating water transit time dynamics into future hydrologic assessments,” said Zachariah Butler. [ https://www.labroots.com/trending/earth-and-the-environment/…now-rain-2](https://www.labroots.com/trending/earth-and-the-environment/…now-rain-2)
How can climate change impact how fast snow turns into water? This is what a recent study published in Scientific Reports hopes to address as a team of scientists investigated snow drought conditions and how this could lead to poor water quality. This study has the potential to help scientists, legislators, and the public better understand the negative impacts of climate change on water management systems and how to mitigate them.
For the study, the researchers analyzed a combination of data from historical (2006−2013) and future (2086−2093) estimates from five regions in the U.S. Pacific Northwest for rain-snow transition times. The motivation behind the study comes from a knowledge gap regarding how climate change impacts the speed of water as it transitions from snow to rain, as opposed to simply the amount of water.
In the end, the researchers found that water transit times were estimated to be an average of 18 percent higher in the late 21st century if present climate change continues. These findings indicate that higher water transit times when snow becomes rainwater could result in greater levels of water contaminants due to shallower water getting into local water supplies.
On a bright morning, graduate student Jeremy Klotz and professor Shree Nayar walked through upper Manhattan with a tall tripod and a camera that takes 360-degree images. Their route took them to bike docking stations, which use solar energy to power their kiosks, docking mechanisms, wireless communication, and even E-bike recharging in recent installations. At each docking station, the researchers raised the camera above the panel, snapped a spherical picture, and sent it to Klotz’s laptop.
Seconds later, the team’s computer vision program told them something remarkable: how much energy that panel would generate in a year—and how much it could generate if it were pointed at the optimal angle.
As it turns out, the solar panels powering the bike docking stations—and likely many solar panels across New York City and other urban destinations—may be leaving significant energy untapped simply because they are not at their best orientation.
Cambridge researchers have engineered a solar-powered “artificial leaf” that mimics photosynthesis to make valuable chemicals sustainably. Their biohybrid device combines organic semiconductors and enzymes to convert CO₂ and sunlight into formate with high efficiency. It’s durable, non-toxic, and runs without fossil fuels—paving the way for a greener chemical industry.
With the rapid expansion of the global solar energy industry, the number of solar panels has surged in recent years. However, pollutants accumulating on panel surfaces can significantly reduce energy conversion efficiency while traditional cleaning methods are highly water-intensive.
In response to this challenge, an international research team led by the Department of Mechanical Engineering at City University of Hong Kong (CityUHK) has successfully developed a breakthrough technology, called “liquid droplet mops,” that uses only a minimal amount of water to effectively remove dust and pollutants from solar panel surfaces, significantly enhancing cleaning efficiency while conserving water.
The study was led by Professor Steven Wang, Associate Vice President (Resources Planning) and Associate Professor in the Department of Mechanical Engineering and the School of Energy and Environment. The project was conducted in collaboration with Professor Omar Matar from the Department of Chemical Engineering at the Imperial College London. The findings are published in Nature Sustainability.
The rapid increase in electric vehicle adoption in recent years has highlighted a crucial issue: the energy conversion efficiency of electric motors. In electric motors, iron loss or magnetic hysteresis loss is a primary source of energy dissipation, arising from the repeated reversal of magnetic fields within the motor core, made of soft magnetic materials. Moreover, electric motors typically operate in high-temperature environments, where thermal effects can lead to partial demagnetization, further complicating energy-loss mechanisms.
The structure of magnetic domains (tiny magnetic regions) of soft magnetic materials strongly influences their magnetic properties, including response to high temperatures and hysteresis loss.
Magnetic domains exhibit a variety of fine structures. In some soft magnetic materials, they form intricate zig-zag patterns known as maze domains. These maze domains show complex and abrupt temperature-dependent behavior that can significantly affect energy loss.
Using a renewable energy source has multiple benefits, including reducing harmful emissions and dependence on fossil fuels while increasing efficiency. But many renewable energy sources have a higher cost than fossil fuels due to the materials needed to make them usable, such as platinum group metals (PGMs), and the high cost of storage.
A team of researchers led by Gang Wu, a professor of energy, environmental and chemical engineering at the McKelvey School of Engineering at Washington University in St. Louis is working to change that. The team is creating a heterostructure catalyst for an anion-exchange membrane water electrolyzer (AEMWE) that splits water into hydrogen and oxygen using electricity from renewable sources. They created the catalyst with two phosphides that gave them an efficient method to extract hydrogen, a valuable yet low-cost source of zero-emissions fuel. The study is published in the Journal of the American Chemical Society.
Wu’s team has been looking for alternatives to catalysts that use expensive platinum group metals. In this research, their idea began with using sunlight, wind or water to create electricity that they could then use to separate hydrogen from water.
Advances in artificial intelligence promise to help chemical engineers discover complex new materials. These materials could be used for reactions such as turning carbon dioxide into fuel, but technical barriers have limited catalysis adoption so far. Researchers at the University of Rochester are now harnessing the benefits of large language models (LLMs) similar to ChatGPT, Claude, or Gemini to empower more researchers to use AI to discover new materials and accelerate experiment workflows.
In a study published in ACS Central Science, a team led by Marc Porosoff, an associate professor in the Department of Chemical and Sustainability Engineering, and Andrew White, visiting associate professor and the cofounder and chief technology officer of Edison Scientific, describes an AI based–method they developed that allows users to input natural language prompts about the materials they want to create and suggest optimal procedures for experiments to produce them. As the users run the experiments, they input the results back into the AI model and continue iterating until they reach their goal.
“We’re able to leverage the pre-trained knowledge of large language models and well-established statistical methods for materials discovery to help us as researchers navigate large experimental design spaces more efficiently,” says Porosoff.
A common mineral hiding in plain sight could hold the key to making copper production cleaner, faster and more efficient, just as global demand for the metal surges to power the energy transition. In an article published in Nature Geoscience, researchers from Monash University’s School of Earth, Atmosphere and Environment describe why chalcopyrite, the source of around 70% of the world’s copper, has remained so difficult to process, and how its hidden chemistry could be harnessed to unlock more sustainable extraction.
Despite being known for more than 300 years, chalcopyrite continues to frustrate scientists and industry alike, resisting low-temperature leaching and slowing efforts to extract copper from lower-grade ores. This inefficiency is a major bottleneck at a time when copper is critical for renewable energy systems, electric vehicles and modern infrastructure.
“Chalcopyrite is the world’s primary copper mineral, but it behaves in surprisingly complex ways that have limited how efficiently we can extract copper from it,” said study lead Professor Joël Brugger from the School of Earth, Atmosphere and Environment.