Considering the ubiquitous occurrences and ecotoxicity of phthalates (PAEs), it is essential to understand their sources, distribution, and associated ecological risks of PAEs in sediments to assess the environmental health of estuaries and support effective management practices. This study provides the first comprehensive dataset on the occurrence, spatial variation, inventory, and potential ecological risk assessment of PAEs in surface sediments of commercially and ecologically significant estuaries in the southeastern United States, Mobile Bay and adjoining eastern Mississippi Sound. Fifteen PAEs were widely detected in the sediments of the study region, with total concentrations varying between 0.02 and 3.37 μg/g. The dominance of low-molecular-weight (LMW) PAEs (DEP, DBP and DiBP) relative to high-molecular-weight (HMW) PAEs (DEHP, DOP, DNP) indicates that residential activities have stronger impacts than industrial activities on PAE distributions. The total PAE concentrations displayed an overall decreasing trend with increasing bottom water salinity, with the maximum concentrations occurring near river mouths. These observations suggest that river inputs were an important pathway by which PAEs were transported to the estuary. Linear regression models identified sediment adsorption (measured by total organic carbon and median grain size) and riverine inputs (measured by bottom water salinity) as significant predictors for the concentrations of LMW and HMW PAEs. Estimated 5-year total inventories of sedimentary PAEs in Mobile Bay and the eastern Mississippi Sound were 13.82 tons and 1.16 tons, respectively. Risk assessment calculations suggest that LMW PAEs posed a medium-to-high risk to sensitive aquatic organisms, and DEHP posed a low or negligible risk to the aquatic organisms. The results of this study provide important information needed for establishing and implementing effective practices for monitoring and regulating plasticizer pollutants in estuaries.

Depression among Korean American (KA) immigrants in rural Alabama is understudied. This study aims to utilize the social determinants of health (SDOH) framework to explore factors associated with depressive symptoms among KA immigrants living in rural communities of Alabama.
Data were collected from two sites in rural Alabama from September 2019 to February 2020. Convenience sampling was conducted to recruit study participants from the KA community. A total number of 261 KA immigrants aged 23-75 were included in the study. All measures originally in English were translated into Korean using back-translation to assure comparability and equivalence in the meaning of measures. Multiple linear regression modeling was used to explore the predictors of depression.
Perceived race discrimination was significantly associated with greater depressive symptoms (β = .180, SE = .534, p < .01). Three SDOH were identified to have significant relationship with depressive symptoms. Participants who could not see a doctor because of cost (β = .247, SE = 1.118, p < .001), had lower level of health literacy (β = -.121, SE = .280, p < .05), and had higher social isolation scores (β = .157, SE = .226, p < .05) tended to have higher scores of depressive symptoms.
Rural-living KA immigrants\' depression can be significantly affected by race discrimination and SDOH factors, emphasizing the need for culturally competent interventions and services. Policymakers, federal and local governments, non-governmental organizations, and social workers can make joint efforts to address racial discrimination and improve the mental health services among immigrant populations, especially those living in rural areas.

The Blue Lentic Belt is a spatial belt of dense lentic habitats formed in the Mobile River Basin since the 1990s, and it is imposing considerable environmental stress on local and downstream aquatic habitats. Depicting the spatiotemporal evolution of the Blue Lentic Belt is essential to understanding its formation and consequential impacts on local environments. However, relevant discussion on it is absent since the Blue Lentic Belt is a new discovery. In this study, we developed a retrospective delineation method to visualize the spatiotemporal evolution of the lentic habitats in the Mobile River Basin and a tesseral model to numerically analyze the spatiotemporal expansion of the Blue Lentic Belt. In the developed method, the baseline inventory of lentic habitats is first delineated from 2019 Sentinel-2 satellite imagery at a spatial resolution of 10 m. The baseline inventory is then used to retrospectively delineate the past lentic habitats in the Mobile River Basin using the National Land Cover Database (NLCD). Kernel density surfaces of lentic habitat image objects are estimated to detect the regions of dense lentic habitats, which sequentially form spatiotemporal objects of dense lentic habitats. The spatiotemporal objects of dense lentic habitats are projected onto planar space and are then structuralized as groups of spatial tesserae, namely α-peaks, β-slopes, and γ-edges. Attributes of these tesserae are numerically derived to quantify the spatiotemporal expansion of the Blue Lentic Belt. The results indicate that the Blue Lentic Belt has 4 α-peaks, 3 β-slopes, and a single γ-edge. It is formed from 4 stable hotspots (α-peaks) of the densest lentic habitats. The expansion of the Blue Lentic Belt ranges about 15.42 km. The expansion distance is about 0.57 of the average range of the β-slopes in the Blue Lentic Belt, indicating a significant change of landscape in the Mobile River Basin. The development of the farm-raised catfish industry is considered the main driving force in the formation of the Blue Lentic Belt. The outcomes of this study have emphasized the rapid expansion of the Blue Lentic Belt and its negative impacts on local and downstream aquatic habitats, which calls for attention to systemic investigations by multiple disciplines.

Skin cancer is the most common, yet oftentimes preventable, cancer type in the United States. Exposure to ultraviolet radiation from sunlight is the most prominent environmental risk factor for skin cancer. Besides environmental exposure, demographic characteristics such as race, age, and socioeconomic status may make some groups more vulnerable. An exploratory spatial clustering method is described for identifying clusters of vulnerability to skin cancer incidence and mortality based on composite indices, which combine data from environmental and demographic risk factors.
Based on county-level ultraviolet data and demographic risk factors, two vulnerability indices for skin cancer were generated using an additive percentile rank approach. With these indices, univariate local Moran\'s I spatial autocorrelation identified significant clusters, or hotspots, of neighboring counties with high overall vulnerability indices. Clusters were identified separately for skin cancer incidence and mortality.
Counties with high vulnerabilities were spatially distributed across the United States in a pattern that generally increased to the South and West. Clusters of counties with high skin cancer incidence vulnerability were mostly observed in Utah and Colorado, even with highly conservative levels of significance. Meanwhile, clusters for skin cancer mortality vulnerability were observed in southern Alabama and west Florida as well as across north Alabama, north Georgia and up through the Tennessee-North Carolina area.
Future skin cancer research and screening initiatives may use these innovative composite vulnerability indices and identified clusters to better target resources based on anticipated risk from underlying demographic and environmental factors.

To promote the environmental sustainability of rural sanitation, a soil moisture controlled wastewater subsurface drip irrigation (SDI) dispersal system was field tested in the Black Belt Prairie of Alabama, USA. The soil moisture control strategy was designed to regulate wastewater disposal timing according to drain field conditions to prevent hydraulic overloading and corresponding environmental hazard. CW2D/HYDRUS simulation modeling was utilized to explore difficult-to-measure aspects of system performance. While the control system successfully adapted hydraulic loading rate to changing drain field conditions, saturated field conditions during the dormant season presented practical application challenges. The paired field experiment and simulation model demonstrate that soil biofilm growth was stimulated in the vicinity of drip emitters. Although biofilm growth is critical in maintaining adequate COD and NH4+-N removal efficiencies, the efficient removal of biodegradable COD itself by soil biofilm limits denitrification of formed NO3--N . Furthermore, stimulated soil biofilm growth can create soil clogging around drip emitters, which was discerned in the field experiment along with salt accumulation, both of which were verified by simulation. Comparable modeling of system performance in sand and clay media demonstrate that the placement of soil moisture sensors within the drain field can have pronounced impacts on system hydraulic performance, depending on the soil permeability. Overall, the soil moisture control strategy tested is shown as a viable supplemental technology to promote the environmental sustainability of rural sanitation systems.

Climate change has often caused failure in water treatment operations. In this study, we report a real case study at a major surface water treatment plant in Alabama, USA. Following a severe winter storm, the effluent water turbidity surged to >15.00 Nephelometric Turbidity Units (NTU), far exceeding the 0.30 NTU standard. As a result, the plant operation had to be shut down for three days, causing millions of dollars of losses and affecting tens of thousands of people. Systematic jar tests were carried out with sediment samples from 22 upstream locations. The coagulation and settleability of sediment particles were tested under simulated storm weather conditions, i.e., low temperature (7 °C) and in the presence of various types and concentrations of natural organic matter (NOM) that was extracted from the local sediments. Experimental results proved that elevated NOM (6.14 mg·L-1 as Total Organic Carbon, TOC) in raw water was the root cause for the failure of the plant while the low temperature played a minor but significant role. Pre-oxidation with permanganate and/or elevated coagulant dosage were found effective to remove TOC in raw water and to prevent similar treatment failure. Moreover, we recommend that chemical dosages should be adjusted based on the TOC level in raw water, and a reference dosage of 0.29 kg-NaMnO4/kg-TOC and 19 kg- polyaluminum chloride (PACl) /kg-TOC would be appropriate to cope with future storm water impacts. To facilitate timely adjustment of the chemical dosages, the real time key water quality parameters should be monitored, such as turbidity, TOC, Ultraviolet (UV) absorbance, pH, and color. The findings can guide other treatment operators to deal with shock changes in the raw water quality resulting from severe weather or other operating conditions.

Chlamydia gallinacea, a new chlamydial agent, has been reported in four European countries as well as Argentina and China. Experimentally infected chickens with C. gallinacea in previous study showed no clinical signs but had significantly reduced gains in body weight (6·5-11·4%). Slaughterhouse workers exposed to infected chickens have developed atypical pneumonia, indicating C. gallinacea is likely a zoonotic agent. In this study, FRET-PCR confirmed that C. gallinacea was present in 12·4% (66/531) of oral-pharyngeal samples from Alabama backyard poultry. Phylogenetic comparisons based on ompA variable domain showed that 16 sequenced samples represented 14 biotypes. We report for the first time the presence of C. gallinacea in North America, and this warrants further research on the organism\'s pathogenicity, hosts, transmission, and zoonotic potential.

The genetic diversity of Toxoplasma gondii circulating in wildlife is of interest to understand the transmission of this parasite in the environment. In the present study, we genetically characterized five T. gondii isolates from different wild animals including two isolates from a bobcat (Lynx rufus), one from a red-shouldered hawk (Buteo lineatus), one from a white-tailed deer (Odocoileus virginianus), and one from a bald eagle (Haliaeetus leucocephalus). Genotyping of these samples using 11 PCR-restriction fragment length polymorphism markers (SAG1, 5\'- and 3\'-SAG2, alt.SAG2, SAG3, BTUB, GRA6, c22-8, c29-2, L358, PK1, and Apico) revealed two types, including type I (ToxoDB#10) and type 12 (ToxoDB#5). This is the first report of genetic characterization of T. gondii strains in wildlife from Alabama and from a red-shouldered hawk.