Large-scale evaluation of microorganism inactivation by bipolar ionization and photocatalytic devices.

The COVID-19 pandemic has raised awareness in the spread of disease via airborne transmission. As a result, there has been increasing interest in technologies that claim to reduce concentrations of airborne pathogens in indoor environments. The efficacy of many of these emerging technologies is not fully understood, and the testing that has been done is often conducted at a small scale and not representative of applied settings. There is currently no standard test method for evaluating air treatment technologies, making it difficult to compare results across studies or technology types. Here, a consistent testing approach in an operational-scale test chamber with a mock recirculating heating, ventilation, and air conditioning (HVAC) system was used to evaluate the efficacy of bipolar ionization and photocatalytic devices against the non-enveloped bacteriophage MS2 in the air and on surfaces. Statistically significant differences between replicate sets of technology tests and control tests (without technologies active) are apparent after 1 h, ranging to a maximum of 0.88 log10 reduction for the bipolar ionization tests and 1.8 log10 reduction for the photocatalytic device tests. It should be noted that ozone concentrations were elevated above background concentrations in the test chamber during the photocatalytic device testing. No significant differences were observed between control and technology tests in terms of the amount of MS2 deposited or inactivated on surfaces during testing. A standardized, large-scale testing approach, with replicate testing and time-matched control conditions, is necessary for contextualizing laboratory efficacy results, translating them to real-world conditions, and for facilitating technology comparisons.

Impact of test methodology on the efficacy of triethylene glycol (Grignard Pure) against bacteriophage MS2.

The COVID-19 pandemic has raised interest in using chemical air treatments as part of a strategy to reduce the risk of disease transmission, but more information is needed to characterize their efficacy at scales translatable to applied settings and to develop standardized test methods for characterizing the performance of these products. Grignard Pure, a triethylene glycol (TEG) active ingredient air treatment, was evaluated using two different test protocols in a large bioaerosol test chamber and observed to inactivate bacteriophage MS2 in air (up to 99.9% at 90 min) and on surfaces (up to 99% at 90 min) at a concentration of approximately 1.2 - 1.5 mg/m3. Introducing bioaerosol into a TEG-charged chamber led to overall greater reductions compared to when TEG was introduced into a bioaerosol-charged chamber, although the differences in efficacy against airborne MS2 were only significant in the first 15 min. Time-matched control conditions (no TEG present) and replicate tests for each condition were essential for characterizing treatment efficacy. These findings suggest that chemical air treatments could be effective in reducing the air and surface concentrations of infectious pathogens in occupied spaces, although standard methods are needed for evaluating their efficacy and comparing results across studies. The potential health impacts of chronic exposure to chemicals should also be considered, but those were not evaluated here.

Blind testing of shoreline evolution models.

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999-2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014-2017), both approaches showed a decrease in models' capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.

Spatial response of coastal marshes to increased atmospheric CO2.

The elevation and extent of coastal marshes are dictated by the interplay between the rate of relative sea-level rise (RRSLR), surface accretion by inorganic sediment deposition, and organic soil production by plants. These accretion processes respond to changes in local and global forcings, such as sediment delivery to the coast, nutrient concentrations, and atmospheric CO2, but their relative importance for marsh resilience to increasing RRSLR remains unclear. In particular, marshes up-take atmospheric CO2 at high rates, thereby playing a major role in the global carbon cycle, but the morphologic expression of increasing atmospheric CO2 concentration, an imminent aspect of climate change, has not yet been isolated and quantified. Using the available observational literature and a spatially explicit ecomorphodynamic model, we explore marsh responses to increased atmospheric CO2, relative to changes in inorganic sediment availability and elevated nitrogen levels. We find that marsh vegetation response to foreseen elevated atmospheric CO2 is similar in magnitude to the response induced by a varying inorganic sediment concentration, and that it increases the threshold RRSLR initiating marsh submergence by up to 60% in the range of forcings explored. Furthermore, we find that marsh responses are inherently spatially dependent, and cannot be adequately captured through 0-dimensional representations of marsh dynamics. Our results imply that coastal marshes, and the major carbon sink they represent, are significantly more resilient to foreseen climatic changes than previously thought.