Central Maine Community College

The coastal oceans, particularly in developing countries, remain largely unexplored, as most global efforts focus on open seas, resulting in significant data gaps in shelf and coastal waters. Citizen Science (CS) approaches, coupled with increasingly affordable technologies, offer a promising way to monitor the coasts by collecting extensive spatial and temporal data over shorter periods. This study reviewed 1127 marine citizen science initiatives (MCSIs) worldwide, emphasising their contributions to environmental monitoring and coastal observing. Results revealed that only 9% of the reviewed initiatives addressed environmental monitoring (physics, biogeochemistry, cross-disciplinary), with a noticeable global decline in newly formed MCSIs since 2020 across all topics. Environmental monitoring MCSIs were predominantly based in the United States and in global-scale initiatives, whereas resource-limited regions had minimal representation. Temperature, Depth, Salinity, and dissolved oxygen were the most monitored oceanographic variables, and showed strong co-occurrences with other variables. The study highlighted key technologies applied in environmental monitoring, with photography, low-cost sensors, and other oceanographic technologies emerging as the primary tools applied in MCS environmental monitoring. Mobile apps and websites were identified as key tools in facilitating stakeholder engagement, enabling data upload and access. However, data quality control methods were often poorly documented by most MCSIs, affecting the trust in CS-generated data. The study recommends supporting under-resourced regions in adopting CS approaches for coastal observing to bridge the data sparse gap, as well as improving data quality documentation and adopting best practices. MCS has demonstrated a significant potential to complement existing coastal observing systems, as evidenced by examples from New Zealand, Tanzania, and the North-east Atlantic.

Campagna, Vivian DNP, RN, CMGT-BC, CCM, ICE-CCP; Edwards, Katherine MEd, CCM, CDMS; Morgan, Patricia Kelley MS, RN, CCM, MSCC Author Information

Abstract Performance of Corrosion Resistance reinforcing steel bars including continuous galvanized (ASTM A1094) and Low-Carbon Chromium Steel bars (ASTM A1035 CS) have been evaluated for their high corrosion resistance and their mechanism to extend the service life of concrete structures. ASTM A1094 is galvanized rebar with a zinc alloy coating that provides the well-known corrosion protection of zinc and the added benefit of exceptional formability. ASTM A1094 can be bent and fabricated after galvanizing without fear of peeling or flaking unlike Batch hot dip galvanizing and epoxy coated rebars. ASTM A1035 CS rebar’s combination of high strength rebar, corrosion resistance and ductility are proven to provide superior blast protection for concrete structures. The high strength can withstand stronger forces, while the ductility dissipates the force across the structural member. In addition, the high strength rebar can be used to efficiently design structures up to 100 Ksi (690 MPa) reducing construction costs and time. Corrosion research findings discussed in this paper illustrate the efficiency in using these bars to extend the service life of concrete structures depending on the required service life of the DOD structures. In addition to the service life capabilities, supply chain availability should be considered.

Results from the article "A research and development investment strategy to achieve the Paris climate agreement".

Campagna, Vivian DNP, RN-BC, CCM, ICE-CCP; Greene, Kendra MSN, MBA/HCM, RN, CCM Author Information

This second white paper provides an overview of trending and emerging technologies related to climate and weather applications, focusing on novel extreme-scale systems, programming models for heterogeneous computing and machine learning (ML). It updates the findings highlighted in the first white paper by providing a summary of relevant efforts available in literature, as well as some early results from these fields. <br> Tracking of state-of-the-art solutions and technologies has been carried out during the ESiWACE2 project to identify recent and relevant work focusing on trends in High Performance Computing (HPC), use of hardware accelerators and machine learning for weather and climate modelling. The document summarises the main results from this tracking activity providing pointers and references to interesting articles. <br> In order to track some of the earliest work in the field, a second workshop on Emerging Technologies for Weather and Climate Modelling was held on the 7th of October as a virtual event. The workshop organised in the frame of the ESiWACE2 project aimed to bring together HPC experts from academia and industry and climate/weather scientists from the EU and USA to discuss about some of the latest developments, research opportunities and efforts. The workshop agenda was organised around three topical sessions, for a total of 14 talks, about: European Exascale hardware (Session 1), Programming models and hardware interplay (Session<br> 2) and Machine Learning (Session 3). More than 130 people from 22 countries world-wide registered to the workshop with Germany, UK, Italy, France and USA being the most represented countries.