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Los Angeles coastal waters are an ecologically important marine habitat and a famed recreational area for tourists. Constant surveillance is essential to ensure compliance with established health standards and to address the persistent water quality challenges in the region. Remotely sensed datasets are increasingly being applied toward improved detection of water quality by augmenting monitoring programs with spatially intensive and accessible data. This study evaluates the potential of satellite remote sensing to augment traditional monitoring by analyzing the relationship between in situ and satellite-derived turbidity data. Field measurements were performed from July 2021 to March 2024 to build synchronous matchup datasets consisting of satellite and field data. Correlation analysis indicated a positive relationship between satellite-derived and field-measured turbidity (R2 = 0.451). Machine learning models were assessed for predictive accuracy, with the random forest model achieving the highest performance (R2 = 0.632), indicating its robustness in modeling complex turbidity patterns. Seasonal trends revealed higher turbidity during wet months, likely due to stormwater runoff from the Ballona Creek watershed. Despite limitations from cloud cover and spatial resolution, the findings suggest that integrating satellite data with machine learning can enhance large-scale, efficient turbidity monitoring in coastal waters.

Abstract Wildfires increase runoff and sediment yields that impact downstream ecosystems. While the effects of wildfire on stream water quality are well documented, oceanic responses to wildfire remain poorly understood. Therefore, this study investigated oceanic responses to the 2018 Woolsey Fire using satellite remote sensing and in situ data analyses. We examined 2016–2020 turbidity plume (n = 192) and 2008–2020 fecal indicator bacteria (FIB, n = 15,015) measurements at variable proximity to the Woolsey Fire. Shifts in coastal water quality were more pronounced in the “inside” region, which drained the burn area. The inside region experienced 2018–2019 plume surface area monthly means that were 10 and 9 times greater than 2016–2017 and 2017–2018 monthly means, respectively. Further, linear regressions showed that 2018–2019 three-day precipitation totals produced plumes of greater surface area. We also noted statistically significant increases in the inside region in 2018–2019 total coliform and Enterococcus monthly means that were 9 and 53 times greater than 2008–2018 monthly means, respectively. These results indicate that sediment and microbial inputs to coastal ecosystems can increase substantially post-wildfire at levels relevant to public and environmental health, and underscore the benefit of considering remote sensing and in situ measurements for water quality monitoring.

BackgroundLiterature suggests limiting consumption of animal products is key to reducing emissions and adverse planetary impacts. However, influencing dietary behavior to achieve planetary health targets remains a formidable problem.ObjectiveWe investigated the effect of changing the default meal option at catered events–from meat to plant-based–on participants' meal choices using three parallel-group, balanced, randomized controlled trials (RCT), and use these experimental results to project differences in plant-based default vs. meat default events on greenhouse gas emissions (GHGEs) (kg CO2 − eq), land use (m2), nitrogen (g N), and phosphorus (g P) footprint.MethodsData collection was performed at three catered events (n = 280) across two college campuses. The selected experimental sites used convenience sampling. Events consisted of a graduate orientation, sorority dinner, and academic conference. Eligibility of individual participants included being 18 years or older and an invitation to RSVP for an enrolled event. Participants were randomly assigned to one of two groups: the control group received a RSVP form that presented a meat meal as the default catering option; whereas the intervention group received a form that presented a plant-based meal as the default. The primary outcome of interest in each group was the proportion of participants who selected plant-based meals. To explore environmental impacts, we modeled the footprints of four hypothetical meals. Using these meals and RCT results, the impact (GHGE, land use, nitrogen, phosphorus) of two hypothetical 100-person events was calculated and compared.ResultsIn all, participants assigned to the plant-based default were 3.52 (95% CI: [2.44, 5.09]) times more likely to select plant-based meals than those assigned to the meat default. Using these results, a comparison of hypothetical events serving modeled meat-based and plant-based meals showed a reduction of up to 42.3% in GHGEs as well as similar reductions in land use (41.8%), nitrogen (38.9%), and phosphorus (42.7%).ConclusionResults demonstrated plant-based default menu options are effective, providing a low-effort, high-impact way to decrease consumption of animal products in catered events. These interventions can reduce planetary impact while maintaining participant choice.

Land use and land cover (LULC) change can have detrimental effects on water quality. In Belize, agricultural expansion creates the risk of increased sediment load and excess nutrients in runoff water, while deforestation removes potential infiltration sites for this outflow. Climate change and evolving precipitation rates can intensify the quantity of runoff, further enabling the flow of sediments and excess nutrients out to the lagoon surrounding the Belize Barrier Reef Reserve System (BBRRS). This study sought to estimate potential impacts on future water quality in Belize by first modeling LULC change through 2090 across Belize’s major watersheds based on observed trends from 2008 to 2018. Those LULC projections were subsequently combined with soil type data, elevation, and precipitation rates into a hydrologic model to produce runoff flow estimates as a proxy for water quality. The two Coupled Model Intercomparison Project phase 6 (CMIP-6) scenarios employed in the study represented bookend climate change scenarios, and both indicated generally lower precipitation rates in Belize over the next century due to climate change. The most extreme scenario predicted a 46% decrease in precipitation. When holding LULC change constant, these climate scenarios projected a decrease in runoff, suggesting a positive relationship between precipitation and runoff. In contrast with the northern watersheds, the southern watersheds are projected to experience greater decreases in annual rainfall and runoff by 2090. When holding climate constant, runoff increased by approximately 2.8% in the Conservation-focused LULC scenario by 2090, which was 28% lower than the Business as Usual scenario, and 42% lower than the Development scenario. The study’s integration of CMIP6 climate scenarios into LULC and hydrologic modeling provides a more holistic view of the future of Belize’s water quality and supports the long-term planning efforts of local decision-making agencies.