The Hidden Impact of Anoxic Pockets on Sandy Shores

Human activities have dramatically increased nitrogen inputs into coastal seas, leading to a significant amount of this human-derived nitrogen being removed by microorganisms in coastal sands through denitrification. However, research has shown that this process can also occur in oxygenated sands, and scientists from the Max Planck Institute for Marine Microbiology in Bremen, Germany, have now revealed how this happens.

The scientists used a method called microfluidic imaging to visualize the diverse and uneven distribution of microbes and the oxygen dynamics on extremely small scales. “Tens of thousands of microorganisms live on a single grain of sand,” explains Farooq Moin Jalaluddin from the Max Planck Institute for Marine Microbiology. The researchers could show that some microbes consume more oxygen than is resupplied by the surrounding pore water, creating anoxic pockets on the surface of the sand grains.

These anoxic microenvironments have so far been invisible to conventional techniques but have a dramatic effect: “Our estimates based on model simulations show that anaerobic denitrification in these anoxic pockets can account for up to one-third of the total denitrification in oxygenated sands,” says Jalaluddin.

The researchers calculated how relevant this newly researched form of nitrogen removal is on a global scale and found that it could account for up to one-third of total nitrogen loss in silicate shelf sands. Consequently, this denitrification is a substantial sink for anthropogenic nitrogen entering the oceans.

In conclusion, the hidden impact of anoxic pockets on sandy shores has been revealed by scientists, highlighting the importance of these microenvironments in removing nitrogen from coastal seas and emphasizing the need to consider them when assessing the overall nitrogen budget of our planet.

The article highlights a critical aspect of environmental degradation: the rising soil nitrous acid (HONO) emissions driven by climate change and fertilization, which accelerate global ozone pollution. A team of researchers from The Hong Kong Polytechnic University has examined global soil HONO emissions data from 1980 to 2016 and incorporated them into a chemistry-climate model. Their findings reveal that soil HONO emissions contribute significantly to the increase in the ozone mixing ratio in air, which has negative impacts on vegetation.

The researchers found that soil HONO emissions have increased from 9.4 Tg N in 1980 to 11.5 Tg N in 2016, with a 2.5% average annual rise in the global surface ozone mixing ratio. This increase may lead to overexposure of vegetation to ozone, affecting ecosystem balance and food crop production. Moreover, ozone damage reduces vegetation’s capacity to absorb carbon dioxide, further aggravating greenhouse gas emissions.

The study emphasizes that soil HONO emissions are influenced by nitrogen fertiliser usage and climate factors like soil temperature and water content. Emissions hotspots cluster in agricultural areas worldwide, with Asia being the largest emitter (37.2% of total).

Interestingly, regions with lower pollution levels are more affected by ozone formation due to higher volatile organic compound concentrations and lower nitrogen oxide levels. This implies that as global anthropogenic emissions decrease, the impact of soil HONO emissions on ozone levels may increase.

To mitigate this issue, Prof. Tao Wang recommends considering soil HONO emissions in strategies for reducing global air pollution. The research team developed a robust parameterisation scheme by integrating advanced modelling techniques and diverse datasets, which can facilitate more accurate assessments of ozone production caused by soil HONO emissions and their impact on vegetation.

Future studies should explore mitigation strategies to optimise fertiliser use while maintaining agricultural productivity, such as deep fertiliser placement and the use of nitrification inhibitors.

The article “Hurricane Ida’s Hidden Dangers: A Model Reveals the Worst-Case Scenario for NYC” delves into the story of Hurricane Ida, which devastated the Northeast region in 2021. While the storm caused significant damage and loss of life, researchers have simulated its trajectory using advanced models to reveal an even more catastrophic scenario had the storm track shifted just 30 miles eastward.

Philip Orton, a professor at Stevens Institute of Technology, led a team of researchers who improved upon existing modeling systems like COAWST (Coupled Ocean-Atmosphere-Waves-Sediment Transport). They incorporated pluvial flooding effects, which occurs when heavy rain falls directly onto land, and simulated the potential impact on Jamaica Bay in Queens, New York.

The study revealed that shifting the storm track eastward would have resulted in higher rainfall intensities within the flood model’s area. The researchers found that if Ida had maintained its original trajectory, it would have soaked urban centers in New Jersey but produced far more severe effects in NYC.

In the worst-case scenario, approximately 5907 buildings and 24 square miles of the Jamaica Bay watershed would have experienced deep flooding greater than one foot deep. This devastating outcome underscores the importance of capturing compound flooding events like hurricanes with extreme rainfall and storm surges.
The researchers also simulated various alternative tidal conditions, which showed that a high tide could have slightly increased flooding for certain areas, such as the east and west shores of Jamaica Bay and Hamilton Beach.

These findings highlight the model’s utility in representing compound flooding events, particularly as sea levels continue to rise. The study emphasizes the need to capture compounding effects when forecasting extreme weather events like hurricanes.

The article concludes by underscoring the significance of using advanced modeling systems like COAWST and highlighting the importance of integrating pluvial flooding effects into these models. By doing so, researchers can better predict the severity of compound flooding events and help emergency management officials prepare for worst-case scenarios.
In an effort to improve forecasting and emergency planning, this study demonstrates the potential of advanced modeling systems in representing complex weather phenomena like hurricanes.