Search Results (131)

Objective: To explore the relationship between type of grocery store used (chain vs. independent), transportation access, food insecurity, and fruit and vegetable intake in Detroit, Michigan, USA, during the COVID-19 pandemic. Design: A cross-sectional online survey was conducted from December 2021 to May 2022. Setting: Detroit, Michigan. Participants: 656 Detroit residents aged 18 and older. Results: Bivariate analyses showed that chain grocery store shoppers reported significantly greater fruit and vegetable intake (2.42 vs. 2.14 times/day for independent grocery store shoppers, p < 0.001) and lower rates of food insecurity compared to independent store shoppers (45.9% vs. 65.3% for independent grocery store shoppers, p < 0.001). Fewer independent store shoppers used their own vehicle (52.9% vs. 76.2% for chain store shoppers, p < 0.001). After adjusting for socioeconomic and demographic variables transportation access was strongly associated with increased odds of shopping at chain stores (OR = 1.89, 95% CI [1.21,2.95], p = 0.005) but food insecurity was no longer associated with grocery store type. Shopping at chain grocery stores was associated with higher fruit and vegetable intake after adjusting for covariates (1.18 times more per day, p = 0.042). Qualitative responses highlighted systemic barriers, including poor food quality, high costs, and limited transportation options, exacerbating food access inequities. Conclusions: These disparities underscore the need for targeted interventions to improve transportation options and support food security in vulnerable populations, particularly in urban areas like Detroit. Addressing these structural challenges is essential for reducing food insecurity and promoting equitable access to nutritious foods. Full article

Background: COVID-19, influenza, and respiratory syncytial virus (RSV) are major respiratory infections with overlapping clinical presentations. Comparative data on the severity of these infections in hospitalized adults are limited, particularly across phases of the COVID-19 pandemic. Objectives: The objectives of this study are to compare the risk of severe outcomes among hospitalized patients with COVID-19, influenza, or RSV and to evaluate the role of vaccination and demographic subgroups using recent, real-world data. Design: This is a retrospective cohort study. Setting: Eight hospitals within the Corewell Health system in Michigan, USA, were studied. Participants: The participants included adults aged ≥ 18 years hospitalized between 1 January 2021 and 20 July 2024 with a principal diagnosis of COVID-19, influenza, or RSV. Main Outcomes and Measures: The primary outcome was a composite of ICU admission, mechanical ventilation, or in-hospital death. Multivariable Cox proportional hazard models were used to estimate adjusted hazard ratios (aHRs), with subgroup analyses in terms of vaccination status, age group, and time period. Results: Among 27,885 hospitalized patients (90.5% COVID-19, 7.2% influenza, 2.3% RSV), COVID-19 was associated with a higher risk of severe outcomes compared to influenza (aHR 1.30, 95% CI: 1.11–1.54). RSV showed no significant difference from influenza. Across all infection groups, older age (≥65 years), high comorbidity burden, and immunocompromised status were associated with an increased risk of severe outcomes. Recent COVID-19 vaccination was protective, particularly among older adults. Differences in severity were more pronounced in the pre-March 2022 period. Conclusions: Using one of the most recent large-scale datasets, this study is among the first to directly compare the severity of COVID-19, influenza, and RSV in hospitalized adults. COVID-19 continues to pose a higher risk of severe illness compared to the other viral infections. The findings underscore the importance of up-to-date vaccination and focused clinical strategies for older and high-risk individuals. This study offers timely evidence to guide future respiratory virus response strategies across hospital settings. Full article

Tailings generated by mining account for the largest world-wide waste from industrial activities. As an element, copper is relatively uncommon, with low concentrations in sediments and waters, yet is very elevated around mining operations. On the Keweenaw Peninsula of Michigan, USA, jutting out into Lake Superior, 140 mines extracted native copper from the Portage Lake Volcanic Series, part of an intercontinental rift system. Between 1901 and 1932, two mills at Gay (Mohawk, Wolverine) sluiced 22.7 million metric tonnes (MMT) of copper-rich tailings (stamp sands) into Grand (Big) Traverse Bay. About 10 MMT formed a beach that has migrated 7 km from the original Gay pile to the Traverse River Seawall. Another 11 MMT are moving underwater along the coastal shelf, threatening Buffalo Reef, an important lake trout and whitefish breeding ground. Here we use remote sensing techniques to document geospatial environmental impacts and initial phases of remediation. Aerial photos, multiple ALS (crewed aeroplane) LiDAR/MSS surveys, and recent UAS (uncrewed aircraft system) overflights aid comprehensive mapping efforts. Because natural beach quartz and basalt stamp sands are silicates of similar size and density, percentage stamp sand determinations utilise microscopic procedures. Studies show that stamp sand beaches contrast greatly with natural sand beaches in physical, chemical, and biological characteristics. Dispersed stamp sand particles retain copper, and release toxic levels of dissolved concentrations. Moreover, copper leaching is elevated by exposure to high DOC and low pH waters, characteristic of riparian environments. Lab and field toxicity experiments, plus benthic sampling, all confirm serious impacts of tailings on aquatic organisms, supporting stamp sand removal. Not only should mining companies end coastal discharges, we advocate that they should adopt the UNEP “Global Tailings Management Standard for the Mining Industry”. Full article

Soil organic carbon (SOC) plays a critical role in regulating the global carbon (C) cycle, with forest soils serving as significant C sinks. Soil aggregate stability and the distribution of SOC in different aggregate fractions would be affected by different forest types. In this study, we investigate the distribution and dynamics of SOC within different soil aggregate fractions across three main forest types in the Huron Mountains, Michigan, USA: white birch–eastern hemlock mixed forest, eastern-hemlock-dominated forest, and sugar maple forest. We hypothesize that variations in species composition and soil depth influence SOC storage and aggregate stability through mechanisms such as root interactions, microbial activity, and soil structure development. Soil samples were collected from three depth intervals (0–20 cm, 20–40 cm, and 40–60 cm) and analyzed for aggregate size distribution and SOC content. The results showed that aggregate size distribution and SOC stocks differ significantly across forest types, with the white birch–eastern hemlock mixed forest exhibiting the highest proportion of large aggregates (>1.0 mm), which contribute to more stable soil structures. This forest type also had the highest total aggregate mass and mean weight diameter, indicating enhanced soil stability. In contrast, sugar maple forest displayed a greater proportion of smaller aggregates and a lower macroaggregate-to-microaggregate ratio, suggesting fewer stable soils. SOC stocks were closely linked to aggregate size, with macroaggregates containing the highest proportion of SOC. These differences in SOC distribution and soil aggregate stability can be attributed to several underlying mechanisms, including variations in plant root interactions, microbial activity, and the physical properties of the soil. Forests with diverse species compositions, such as the white birch–eastern hemlock mixed forest, tend to support more complex root systems and microbial communities, leading to improved soil aggregation and greater SOC storage. Additionally, forest management practices such as selective thinning and mixed-species planting contribute to these processes by enhancing soil structure, increasing root biomass, and promoting soil microbial health. These interactions play a crucial role in enhancing C sequestration and improving soil health. Our findings emphasized the importance of forest composition in influencing SOC dynamics and soil stability, offering insights into the role of forest management in C sequestration and soil health. This study provided a reference to a deeper understanding of SOC storage potential in forest ecosystems and supports the development of sustainable forest management strategies to mitigate climate change. Full article

Soil fungal communities are critical for forest ecosystem functions in the Central Hardwood Region (CHR) of the USA. This evaluation, which took place in 2022–2023, investigates the influence of Juglans nigra (BW, black walnut) and Quercus rubra (NRO, Northern red oak) on soil properties and fungal community structures across three CHR sites. The objectives of this study are to investigate how the fungal communities identified beneath J. nigra and Q. rubra serve to influence biodiversity and soil health within hardwood plantations. Soils from two locations in Indiana and one in Michigan were examined and assessed for variations in fungal composition and diversity. Soil fungal communities were characterized using Illumina high-throughput sequencing while multivariate analysis was applied to analyze patterns in these fungal communities. These data provided insights into how environment, location, and tree species affect fungal community structure. Results indicate that J. nigra soils exhibited higher carbon (0.36%, 1.02%, 0.72%), nitrogen (25%, 29%, 56%), and pH (0.46, 1.08, 1.54) levels than Q. rubra soils across all three sites and foster greater fungal diversity. Specifically, J. nigra was associated with increased Ascomycota diversity, whereas Q. rubra supported a higher prevalence of Basidiomycota. Basidiomycota were negatively correlated with carbon and pH, while Ascomycota showed positive correlations with these variables. These findings highlight how crucial it is to understand how different tree species influence fungal communities and, consequently, how they influence forest soil health. Our findings serve to improve forest management practices by emphasizing the importance of fungal communities in maintaining the function and resilience of an ecosystem. Our study underscores that grasping these specific interactions is essential for effective forest management, especially when considering how to use fungal communities to boost plant growth. This work focuses on hardwood plantations rather than either agricultural ecosystems, monocultures, or native forests, thus filling a gap in the current literature where many studies are limited to specific fungal groups such as mycorrhizae. In future research, it is important to examine a wider range of tree species. This will deepen our understanding of fungal community dynamics and their impact on maintaining healthy forest ecosystems. Our hardwood plantation focus also notes the potential for adaptive forest management as environmental conditions change. Full article

Advancements in smart sensing and control technologies enable urban drainage engineers to retrofit stormwater storage facilities with real-time control devices for mitigating stormwater in-site overflow, downstream flooding, and overloaded total suspended solids (TSS) in drainage pipes. While the smart technology can improve the performance of the static drainage systems, coordinatively controlling multiple valve and gate operations poses a significant challenge, especially at a large-scale watershed. Using a benchmark stormwater model located at Ann Arbor, Michigan, USA, we assessed the impact of different real-time control strategies (local individual downstream control and system-level multiple control) on balancing flooding mitigation at downstream outlets and TSS reduction at upstream storage units, such as detention ponds. We examined changes in peak water depth, outflow, and TSS as indicators to assess changes in water quantity and quality. The results indicate that system-level control can reduce peak water depth by up to 7.3%, reduce flood duration by up to 34%, and remove up to 67% of total suspended solids compared with a baseline uncontrolled system, with the outflow from upstream detention ponds being the most important hydraulic indicator for control strategy rule set-up. We find that system-level control does not always outperform the individual downstream controls, particularly in alleviating flooding duration at some downstream outlets. With urban growth and a changing climate, this research provides a foundation for quantifying the benefits of real-time control methods as an adaptive stormwater management solution that addresses both water quantity and quality challenges. Full article

Land use regulations have played a critical role in the siting and operation of renewable energy technologies. While there is a growing literature on the siting of wind and solar technologies, less is known about the relationship between local codes and planning decisions and the development of wood-based bioenergy technologies, particularly in rural places. This research examines the relationship between local land use policies and the siting and operation of different types of wood-based bioenergy technologies in northern Michigan, USA. Land use codes including zoning laws and ordinances related to wood-burning devices from 506 cities, townships, and villages within 36 counties in northern Michigan were combined with US Census data in a GIS database. ArcGIS was used to examine geographical differences between communities and socioeconomic factors related to different regulatory approaches. We found that areas with greater population densities and higher income and education levels tended to have more nuanced land use codes related to all scales of wood-burning, including residential wood heating, commercial-scale heating, and power generation. This paper emphasizes the importance of local decision-making and land use policies in shaping the development of wood-based energy technologies, and suggests the need for greater attention to rural community dynamics in planning the shift to a lower-carbon economy. Full article

In recent years, the utilization of machine learning algorithms and advancements in unmanned aerial vehicle (UAV) technology have caused significant shifts in remote sensing practices. In particular, the integration of machine learning with physical models and their application in UAV–satellite data fusion have emerged as two prominent approaches for the estimation of vegetation biochemistry. This study evaluates the performance of five machine learning regression algorithms (MLRAs) for the mapping of crop canopy chlorophyll at the Kellogg Biological Station (KBS) in Michigan, USA, across three scenarios: (1) application to Landsat 7, RapidEye, and PlanetScope satellite images; (2) application to UAV–satellite data fusion; and (3) integration with the PROSAIL radiative transfer model (hybrid methods PROSAIL + MLRAs). The results indicate that the majority of the five MLRAs utilized in UAV–satellite data fusion perform better than the five PROSAIL + MLRAs. The general trend suggests that the integration of satellite data with UAV-derived information, including the normalized difference red-edge index (NDRE), canopy height model, and leaf area index (LAI), significantly enhances the performance of MLRAs. The UAV–RapidEye dataset exhibits the highest coefficient of determination (R²) and the lowest root mean square errors (RMSE) when employing kernel ridge regression (KRR) and Gaussian process regression (GPR) (R² = 0.89 and 0.89 and RMSE = 8.99 µg/cm² and 9.65 µg/cm², respectively). Similar performance is observed for the UAV–Landsat and UAV–PlanetScope datasets (R² = 0.86 and 0.87 for KRR, respectively). For the hybrid models, the maximum performance is attained with the Landsat data using KRR and GPR (R² = 0.77 and 0.51 and RMSE = 33.10 µg/cm² and 42.91 µg/cm², respectively), followed by R² = 0.75 and RMSE = 39.78 µg/cm² for the PlanetScope data upon integrating partial least squares regression (PLSR) into the hybrid model. Across all hybrid models, the RapidEye data yield the most stable performance, with the R² ranging from 0.45 to 0.71 and RMSE ranging from 19.16 µg/cm² to 33.07 µg/cm². The study highlights the importance of synergizing UAV and satellite data, which enables the effective monitoring of canopy chlorophyll in small agricultural lands. Full article

Lung cancer is the leading cancer-related killer in the United States. The incidence varies geographically and may be affected by environmental pollutants. Our goal was to determine associations within time series for specific air pollutants and lung cancer cases over a 33-year period in Wayne County, Michigan, controlling for population change. Lung cancer data for Wayne County were queried from the Michigan Cancer Registry from 1985 to 2018. Air pollutant data were obtained from the United States Environmental Protection Agency from 1980 to 2018. Autoregressive distributed lag (ARDL) models were estimated to investigate time lags in years between specific air pollution levels and lung cancer development. A total of 58,866 cases of lung cancer were identified. The mean age was 67.8 years. Females accounted for 53 percent of all cases in 2018 compared to 44 percent in 1985. Three major clusters of lung cancer incidence were detected with the most intense clusters in downtown Detroit and the heavily industrialized downriver area. Sulfur dioxide (SO₂) had the strongest statistically significant relationship with lung cancer, showing both short- and long-term effects (lag range, 1–15 years). Particulate matter (PM_2.5) (lag range, 1–3 years) and nitrogen dioxide (NO₂) (lag range, 2–4 years) had more immediate effects on lung cancer development compared to carbon monoxide (CO) (lag range, 5–6 years), hazardous air pollutants (HAPs) (lag range, 9 years) and lead (Pb) (lag range, 10–12 years), which had more long-term effects on lung cancer development. Areas with poor air quality may benefit from targeted interventions for lung cancer screening and reductions in environmental pollution. Full article

Ferry electrification has gained attention in the last decade as a potential path to reduce greenhouse gas emissions. This study, conducted by APS LABS at Michigan Technological University for the Mackinac Economic Alliance (MEA) and funded by the Michigan Economic Development Corporation (MEDC), looked at the feasibility and potential benefits of electrification of a particular vessel that is part of a ferry service from Mackinaw City, Michigan, USA, to Mackinac Island, Michigan, USA. The study included a comprehensive analysis of the feasibility of retrofitting the current configuration of the ferry into an all-electric ferry based on the availability of components in today’s market. A life-cycle assessment was conducted to compare the emissions between the baseline ferry rebuilt with new internal combustion engines and an all-electric ferry to understand the potential environmental benefits of ferry electrification and find the most sustainable solution for propulsion. The final prong of the three-pronged approach to this project consisted of estimating the difference in expenditures and profits for a rebuilt internal combustion (IC) engine versus electric configurations for a company operating the ferry. The analysis indicated that in the current scenario, electrification of the Mackinac Island ferry is not beneficial, and replacing the ferry’s current diesel engines with modern diesel engines is the preferred solution. Full article

Mercury (Hg) is a pollutant that bioaccumulates in the food web, leading to health issues in humans and other fauna. Although anthropogenic Hg deposition has decreased over the past 20 years, our watersheds continue to be sources of Hg to downstream communities. Wetlands, especially peatlands in the Boreal Region of the globe, play a vital role in the formation of bioaccumulative methylmercury (MeHg). Few studies have assessed how increases in temperatures such as those that have already occurred and those predicted will influence the hydrologic transport of Hg to downstream communities or the net fluxes of gaseous Hg. The results indicate that peatland pore water concentrations of MeHg are increasing with ecosystem warming, and to some degree with elevated carbon dioxide (eCO₂) in the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment at the Marcell Experimental Forest (MEF) in northern Minnesota, USA. Similar to SPRUCE, in the Biological Response to A Changing Environment (BRACE) experiment in Canada, mesocosm pore water MeHg concentrations increased with soil warming. However, long-term peatland watershed streamflow fluxes of MeHg at the MEF indicate that the competing effects of climate warming and decreased atmospheric deposition have led to overall decreases in watershed MeHg transport. Mesocosm studies in the PEATCOSM experiment in Upper Michigan, USA, indicate that simulated fluctuating water tables led to higher concentrations of MeHg in peatland pore water that is available for downstream transport when water tables rise and the next runoff event occurs. Results from a winter peatland soil freeze/thaw simulation from large mesocosm cores from Jennie’s Bog at the MEF indicate higher total Hg (THg) upon soil thawing but lower MeHg, likely a result of cold temperatures limiting methylation during thawing. Although there are lower MeHg concentrations after thawing, more THg is available for methylation once soils warm. Results from PEATCOSM and the literature also suggest that plant community changes that result in higher densities of sedges also lead to elevated MeHg in pore water. From a climate warming perspective, it appears that two complementary mechanisms, both related to decomposition, are at play that lead to increased pore water MeHg concentrations with warming. First, warming increases decomposition rates, leading to a higher availability of many ions, including Hg (and sulfur) species. Higher decomposition rates also lead to increases in soluble carbon which complexes with Hg species and assists in downstream hydrologic transport. However, if streamflow is decreasing with climate change as a result of landscape-level changes in evapotranspiration as suggested at MEF, the combination of less direct watershed Hg deposition and lower streamflow results in decreases in the watershed transport of MeHg. Given changes already occurring in extreme events and the rewetting and restoration of hydrology during peatland restoration, it is likely that methylation and pore water MeHg concentrations will increase. However, the landscape-level hydrologic cycle will be key to understanding the connection to downstream aquatic communities. Finally, gaseous Hg fluxes increase with warming and lead to decreases in peatland pools of Hg that may influence future availability for downstream transport. Full article

Forested wetlands are common ecosystems within the Great Lakes region (Michigan, Minnesota, and Wisconsin), USA. Projected increases in extreme flooding events and shifting disturbance regimes create challenges for tree regeneration. Forest managers are considering the use of enrichment planting to increase tree species diversity, but limited information is available that quantifies the interactions between the flooding and shade tolerances of candidate tree species. We used a microcosm experiment to manipulate shade and flooding conditions to determine the effects on early survival, growth, and leaf gas exchange of 23 different tree species that vary in shade and flood tolerance. Seedlings were planted in pots and placed in 227 L tanks that were randomly assigned to light reduction (full sun, 40% and 70% reduced sunlight) and flood treatments (water levels of 0, 14, or 27 cm below the soil surface). In general, flooding treatments had a greater influence on seedling growth and leaf gas exchange rates than light reduction treatments. Of the species studied, bald cypress (Taxodium distichum (L.) Rich.) was the most flood-tolerant, but American sycamore (Platanus occidentalis L.) and river birch (Betula nigra L.) were also highly tolerant of flooding conditions throughout the entire growing season. The flood tolerances of the remaining species varied, but none were tolerant of water table depths within 14 cm of the soil surface for the entire growing season. Most species did not respond to the shade treatments in terms of early growth, survival, and leaf gas exchange. When considering species for planting in forested wetlands, matching the flood tolerance of candidate species to local site hydrology is an important step. Full article

Adverse environmental impacts in the watershed are driven by urbanization, which is reflected by land use and land cover (LULC) transitions, such as increased impervious surfaces, industrial land expansion, and green space reduction. Some adverse impacts on the water environment include urban flooding and water quality degradation. Our study area, the Rouge River Watershed, has been susceptible to accelerated urbanization and degradation of ecosystems. Employing the Land Change Modeler (LCM), we designed four alternative urban development scenarios for 2023. Subsequently, leveraging the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), we utilized two models—Nutrient Delivery Ratio (NDR) and Flood Risk Mitigation (UFRM)—to evaluate and compare the performance of these scenarios, as well as the situation in 2019, in terms of nutrient export and urban flooding. After simulating these scenarios, we determined that prioritizing the medium- and high-intensity development scenario to protect open space outperforms other scenarios in nutrient export. However, the four scenarios could not exhibit significant differences in urban flooding mitigation. Thus, we propose balanced and integrative strategies, such as planning green infrastructure and compact development, to foster ecological and economic growth, and enhance the Rouge River Watershed’s resilience against natural disasters for a sustainable future. Full article

Rewilding attempts to increase biodiversity and restore natural ecosystem processes by reducing human influence. Today, there is growing interest in rewilding urban areas. Rewilding of the Detroit, Michigan, USA and Windsor, Ontario, Canada metropolitan area, and its shared natural resource called the Detroit River, has been delineated through the reintroduction of peregrine falcons and osprey, and a return of other sentinel species like bald eagles, lake sturgeon, lake whitefish, walleye, beaver, and river otter. Rewilding has helped showcase the value and benefits of environmental protection and restoration, ecosystem services, habitat rehabilitation and enhancement, and conservation, including social and economic benefits. Improved ecosystem health and rewilding have become a catalyst for re-establishing a reconnection between urban denizens and natural resources through greenways and water trails. The provision of compelling outdoor experiences in nature, in turn, can help foster a personal attachment to the particular place people call home that can help inspire a stewardship ethic. Full article

Biomaterials, used here to signify 100% biobased and biodegradable materials, can offer a promising solution for transitioning away from fossil-based resources, addressing the climate crisis, and combating plastic pollution. To ensure their environmental benefits, biomaterials must derive from regenerative, non-polluting feedstocks that do not compete with food or feed production. From this perspective, agricultural residues and by-products present a favorable feedstock option for biomaterials production. Although this is an improvement over sourcing them from primary crops, the sustainability of underlying agricultural systems must be considered. Furthermore, the nutrient value of biomaterials for specific soil ecosystems is often overlooked despite their compostability. In this research, we investigate the linkages between biomaterials development and regenerative agriculture, a set of farming practices that can effectively sustain the growing human population while enhancing, rather than degrading, ecosystem health. We explore interdependencies between biomaterials’ production and regenerative agriculture for biomass sourcing and nutrient return and suggest a methodological framework to identify mutual benefits. The extent to which regenerative farms can provide biomaterial feedstocks without compromising crop cultivation and ecosystem health is analyzed together with the potential of biomaterials to deliver beneficial nutrients and services to regenerative systems. Applying this framework to the Great Lakes Region, Michigan, USA, an agricultural hub facing environmental degradation and plastic pollution, reveals synergistic linkages that unlock novel circular economy opportunities, including local production of renewable biomaterials for various applications, enhancing food security and bolstering socio-ecological systems. Full article