From protecting biodiversity to ensuring the safety of drinking water, the biochemical makeup of rivers and streams around the United States is critical for human and environmental welfare. Studies have found that human activity and urbanization are driving the salinization (increased salt content) of freshwater sources across the country. In excess, salinity can make water undrinkable, increase the cost of treating water, and harm freshwater fish and wildlife. 

Along with the rise in salinity has also been an increase in alkalinity over time, and past research suggests that salinization may enhance alkalinization. But unlike excess salinity, alkalinization can have a positive impact on the environment due to its ability to neutralize water acidity and absorb carbon dioxide in the Earth’s atmosphere – a key component to combating climate change. Therefore, understanding the processes at play which are affecting salinity and alkalinity has important environmental and health implications. 

A team of researchers from Syracuse University and Texas A&M University has applied a machine learning model to explore where and to what extent human activities are contributing to the hydrogeochemical changes, such as increases in salinity and alkalinity in U.S. rivers.

The group used data from 226 river monitoring sites across the U.S. and built two machine-learning models to predict monthly salinity and alkalinity levels at each site. These sites were selected because long-term continuous water quality measurements have been recorded for at least 30 years. From urban to rural settings, the model explored a diverse range of watersheds, which are areas where all flowing surface water converges to a single point, such as a river or lake. It evaluated 32 watershed factors ranging from hydrology, climate, geology, soil chemistry, land use, and land cover to pinpoint the factors contributing to rising salinity and alkalinity. The team’s models determined human activities as major contributors to the salinity of U.S. rivers while rising alkalinity was mainly attributed more to natural processes than human activities.

The team, which included Syracuse University researchers Tao Wen, assistant professor in the College of Arts and Sciences’ Department of Earth and Environmental Sciences (EES), Beibei E, a graduate student in EES, Charles T. Driscoll, University Professor of Environmental Systems and Distinguished Professor in the College of Engineering and Computer Science, and Texas A&M assistant professor Shuang Zhang, recently had their findings published in the journal Science of the Total Environment.

What’s Driving Salinization and Alkalinization?

The results from the group’s sodium prediction model, which detected human activities such as the application of road salt as major contributions to the salinity of U.S. rivers, were consistent with previous studies. This model specifically revealed population density and impervious surface percentage (artificial surfaces such as roads) as the two most important contributors to the higher salt content in U.S. rivers.

According to Wen, the accuracy of the salinity model provided an important proof of concept for the research team.

“Regarding causes of salinity in rivers, the results from our machine learning model matched those of previous studies which focused on field observation, lab work, and statistical analysis,” says Wen. “This proved that our approach was working.”

With the salinity results confirming the accuracy of the team’s model, they then turned their attention to alkalinity. Their model identified natural processes as predominantly contributing to variation in river alkalinity, a contrast to previous research that identified human activities as the main contributor to alkalinization. They found that local climatic and hydrogeological conditions including runoff, sediment, soil pH, and moisture, were features most affecting river alkalinity.

Critical to the Carbon Cycle

Their findings have important environmental and climate implications as alkalinity in rivers forms a vital link in the carbon cycle. Consider the movement of carbon during a rainstorm. When it rains, carbon dioxide from the atmosphere combines with water to form carbonic acid. When the carbonic acid reaches the ground and comes into contact with certain rocks, it triggers a chemical reaction that extracts gaseous carbon dioxide from the atmosphere and transports it to the ocean via land water systems like lakes and rivers. Known as rock weathering, this natural process continuously erodes rocks and sequesters atmospheric CO2 over millions of years. It is also a key regulator of greenhouse gases that contribute to global warming.

“Rock weathering is the primary source of alkalinity in natural waters and is one of the main ways to bring down carbon dioxide in the air,” says Wen. Think of it as a feedback loop: when there is too much carbon dioxide in the atmosphere, temperatures increase leading to enhanced rock weathering. With more rock being dissolved into watersheds due to enhanced rock weathering, alkalinity rises and in turn, brings down carbon dioxide.

“Alkalinity is a critical component of the carbon cycle,” says Wen. “While we found that natural processes are the primary drivers of alkalinization, these natural factors can still be changed by humans. We can alter the alkalinity level in rivers by changing the natural parameters, so we need to invest more to restore the natural conditions of watersheds and tackle global warming and climate changes to deal with alkalinization in U.S. rivers.”

The results from the team’s study can help inform future research about enhanced rock weathering efforts – where rocks are ground up and spread across fields. Distributing rock dust across large areas increases the amount of contact between rain and rock, which enhances carbon removal from the atmosphere. Wen says the team’s model can help answer questions about the evolution of natural conditions in different regions – an important step needed to implement enhanced rock weathering more effectively.

The work was funded through a $460,000 National Science Foundation grant awarded to Wen.

Alpha samples of the chiplet-based transmitter platform for 400G, 800G, and 1.6T data center solutions are ready for shipment

POET Technologies has announced alpha sample readiness of POET Infinity, a chiplet-based transmitter platform for 400G, 800G, and 1.6T pluggable transceivers and co-packaged optics solutions. Two lead customers have agreed to partner with POET to test the alpha version of the Infinity chiplet.

The POETInfinity chiplet complements the POET 800G 2xFR4 Receiver optical engine that the Company announced in February 2023 and completes the 800G chipset for 2xFR4 QSFP-DD or OSFP applications with two Infinity chiplets and one Receiver optical engine. Both customers intend to develop 800G 2xFR4 QSFP-DD and OSFP transceiver solutions using the POET Optical Engine chipsets.

The Infinity chiplet is the industry’s first implementation of directly modulated lasers (DMLs) for 100G/lane applications. DMLs are power efficient, and cost-effective and become a highly scalable solution when paired with the POET Optical Interposer platform. The chiplet incorporates 100G PAM4 DMLs, DML Drivers, and an integrated optical multiplexer for a complete 400GBASE-FR4 transmitter solution on a chip. The small size of the chiplet and a daisy-chain architecture enables side-by-side placement of multiple instances to achieve 800G and 1.6T speeds.

The POET Infinity product line carries forward the POET differentiation of all passive alignments and monolithically integrated waveguides, multiplexers and demultiplexers, which translates to lower cost, lower power consumption, and ease-of-assembly benefits for customers.

“The availability of a transmitter solution for 400G, 800G, and 1.6T speeds that is power efficient, cost-effective, and highly scalable for the data center market is a major achievement,” said Dr. Suresh Venkatesan, Chairman & CEO of POET. “Our customers are excited to receive the samples and test them because it simplifies their transceiver design significantly and shortens the design cycle with POET optical engines that incorporate all of the required optical elements as well as the key electronic components, including laser drivers and trans-impedance amplifiers.”

The development of a production version of the POET Infinity chiplet is on track and POET expects to deliver beta samples by Q4 of 2023 and start production by the first half of 2024. The ethernet transceiver market for 400G and above data rates is projected to exceed $6 billion by 2028.

Densely-packed housing makes urban areas vulnerable to overheating, pollution, and dangerous wind gusts. The effects of climate change can aggravate these problems, but we can also work to prevent them. This can be done by simulating microclimates.

Cities and urban areas are characterized by high population densities and widespread man-made environments. In city centers, this means surfaces covered with concrete and asphalt, less vegetation, more air pollution, and large, densely-packed buildings that reduce both air circulation and access to daylight. 

At the same time, and especially in coastal areas, extremely high wind velocities can develop between tall buildings due to airflow channeling effects. This can make pedestrian walkways and cycle paths dangerous and unsafe, especially for vulnerable groups.

Climate change can make cities unbearable to live in

The impact of climate change may be reinforcing the negative effects of densely-packed housing, and many places in the world are at risk of becoming uninhabitable. Europe is probably not the most severely affected, but even here the effects of climate change, such as heat waves, droughts, and flooding, represent a threat to both infrastructure and human life. The European heatwave of 2003 claimed more than 70,000 lives. The summer of 2022 was the hottest ever experienced in Europe, with more than 20,000 people dying as a direct result of the heat. 

For this reason, it is increasingly important to reduce the impact of extreme heat in urban areas, especially in southern Europe, but also in Norway. In Oslo, in particular, and in the southern parts of Østlandet County, we can expect to experience heat waves in the future. This is why we must do what we can to create habitable conditions in our cities, and in urban buildings, when temperatures increase to levels that we are not used to. We must begin during the planning phase of the construction process.

Advanced simulations deliver more accurate airflow calculations

So, how can urban planners take a warmer climate into account? Advanced simulation tools such as Computational Fluid Dynamics (CFD) can calculate air movements in a variety of environments. This can be done as early as during the planning phase of larger building projects and as part of the overall urban planning process.

In brief, CFD offers a method of calculating the movement of fluids, including liquids and gases such as air. In recent decades, there has been a boom in the use of such methods, in step with the increase in the power of modern computers. In the last 15 to 20 years, the method has also been applied in studies of microclimates. Microclimates represent climatic conditions that develop at scales of less than two kilometers, and for which in the past we based our investigations on measurements and observations.

Trondheim study demonstrates the effect of different measures

Studies of the microclimate at Gløshaugen in Trondheim have demonstrated the effectiveness of the use of various building materials, as well as the impact that the volume of vegetation and natural environments had on local climatic conditions, and how these factors impact the energy consumption of buildings and the thermal comfort of people outdoors.

The simulations also showed that the cumulative evaporation from lawns and trees can reduce the air temperature by several degrees (up to 2.4 °C at Gløshaugen), and thus reduce the need for cooling the buildings in summer. 

These results can be used to look into different scenarios for urban design or to calculate future urban climates. Having said this, it is difficult to give general recommendations because the systems are highly location-specific, and measures must take into account all the relevant factors that influence the microclimate in a given situation.

Multiple applications

CFD can also be used to make high-resolution calculations of wind conditions, such as turbulence and wind speed. In this way, it will be possible to identify sites where urban wind turbines for local renewable energy generation can be profitably located. Moreover, the dispersion of harmful emissions and pollution can be simulated in areas such as heavily trafficked roads, and industrial plants, and also in the aftermath of accidents and fires. 

In other words, CFD can deliver useful information to inform construction projects, urban planning, and architecture, which in the past has been inaccessible in terms of the level of resolution, precision, and speed that we are seeing today.

Responsible AI for Safe and Equitable Health will address ethical and safety issues in AI innovation, define standards for the field, and convene experts on the topic.

Responding to rapid advances in artificial intelligence and the urgent need to define its responsible use in health and medicine, Stanford Medicine and the Stanford Institute for Human-Centered Artificial Intelligence (HAI) today announced the launch of RAISE-Health (Responsible AI for Safe and Equitable Health). This pioneering initiative seeks to address critical ethical and safety issues surrounding AI innovation and help others navigate this complex and evolving field. 

Co-led by Stanford School of Medicine dean Lloyd Minor, MD, and Stanford HAI co-director and computer science professor Fei-Fei Li, Ph.D., the new initiative will establish a go-to platform for responsible AI in health and medicine; define a structured framework for ethical standards and safeguards; and regularly convene a diverse group of multidisciplinary innovators, experts and decision-makers on the topic.

Both awareness of AI and skepticism about its use in health care have skyrocketed in the last 12 months. According to a recent Pew survey, a majority of Americans said they would be uncomfortable with their provider using AI in their own health care, underscoring the crossroads at which society finds itself.

“AI has the potential to impact every aspect of health and medicine,” Minor said. “We have to act with urgency to ensure that this technology advances in line with the interests of everyone, from the research bench to the patient bedside and beyond.”

The goals of the RAISE-Health initiative include enhancing clinical care outcomes through responsible integration of AI; accelerating research to solve the biggest challenges in health and medicine; and educating patients, care providers and researchers to navigate AI advances.

“AI is evolving at an incredible pace; so, too, must our capacity to manage, navigate and direct its path,” said Li, whose research includes a focus on ambient intelligence — using AI to monitor and respond to human activity in homes, hospitals, and other environments. “Through this initiative, we are seeking to engage our students, our faculty, and the broader community to help shape the future of AI, ensuring it reflects the interests of all stakeholders — patients, families, and society at large.”

Building on the goals of Stanford HAI, groundbreaking Stanford faculty research, and ongoing collaborations with policymakers and Silicon Valley innovators, RAISE-Health will be a trusted repository for the AI work being done at Stanford University, Stanford Medicine, and well beyond — hosting standards, tools, models, data, research, and best practices.

While AI offers the potential for transforming health globally, decision-makers must first address AI’s safety and ethical use to responsibly harness its full potential and build public trust in these systems.