Negative correlation between soil salinity and soil organic carbon variability.

Soil organic carbon (SOC) is vital for terrestrial ecosystems, affecting biogeochemical processes, and soil health. It is known that soil salinity impacts SOC content, yet the specific direction and magnitude of SOC variability in relation to soil salinity remain poorly understood. Analyzing 43,459 mineral soil samples (SOC < 150 g kg-1) collected across different land covers since 1992, we approximate a soil salinity increase from 1 to 5 dS m-1 in croplands would be associated with a decline in mineral soils SOC from 0.14 g kg-1 above the mean predicted SOC ([Formula: see text] = 18.47 g kg-1) to 0.46 g kg-1 below [Formula: see text] (~-430%), while for noncroplands, such decline is sharper, from 0.96 above [Formula: see text] = 35.96 g kg-1 to 4.99 below [Formula: see text] (~-620%). Although salinity's significance in explaining SOC variability is minor (<6%), we estimate a one SD increase in salinity of topsoil samples (0 to 7 cm) correlates with respective [Formula: see text] declines of ~4.4% and ~9.26%, relative to [Formula: see text] and [Formula: see text]. The [Formula: see text] decline in croplands is greatest in vegetation/cropland mosaics while lands covered with evergreen needle-leaved trees are estimated with the highest [Formula: see text] decline in noncroplands. We identify soil nitrogen, land cover, and precipitation Seasonality Index as the most significant parameters in explaining the SOC's variability. The findings provide insights into SOC dynamics under increased soil salinity, improving understanding of SOC stock responses to land degradation and climate warming.

Reassessing the role of urban green space in air pollution control.

The assumption that vegetation improves air quality is prevalent in scientific, popular, and political discourse. However, experimental and modeling studies show the effect of green space on air pollutant concentrations in urban settings is highly variable and context specific. We revisited the link between vegetation and air quality using satellite-derived changes of urban green space and air pollutant concentrations from 2,615 established monitoring stations over Europe and the United States. Between 2010 and 2019, stations recorded declines in ambient NO2, (particulate matter) PM10, and PM2.5 (average of -3.14% y-1), but not O3 (+0.5% y-1), pointing to the general success of recent policy interventions to restrict anthropogenic emissions. The effect size of total green space on air pollution was weak and highly variable, particularly at the street scale (15 to 60 m radius) where vegetation can restrict ventilation. However, when isolating changes in tree cover, we found a negative association with air pollution at borough to city scales (120 to 16,000 m) particularly for O3 and PM. The effect of green space was smaller than the pollutant deposition and dispersion effects of meteorological drivers including precipitation, humidity, and wind speed. When averaged across spatial scales, a one SD increase in green space resulted in a 0.8% (95% CI: -3.5 to 2%) decline in air pollution. Our findings suggest that while urban greening may improve air quality at the borough-to-city scale, the impact is moderate and may have detrimental street-level effects depending on aerodynamic factors like vegetation type and urban form.

Low-Cost Particulate Matter Sensors for Monitoring Residential Wood Burning.

Conventional monitoring systems for air quality, such as reference stations, provide reliable pollution data in urban settings but only at relatively low spatial density. This study explores the potential of low-cost sensor systems (LCSs) deployed at homes of residents to enhance the monitoring of urban air pollution caused by residential wood burning. We established a network of 28 Airly (Airly-GSM-1, SP. Z o.o., Poland) LCSs in Kristiansand, Norway, over two winters (2021-2022). To assess performance, a gravimetric Kleinfiltergerät measured the fine particle mass concentration (PM2.5) in the garden of one participant's house for 4 weeks. Results showed a sensor-to-reference correlation equal to 0.86 for raw PM2.5 measurements at daily resolution (bias/RMSE: 9.45/11.65 µg m-3). High-resolution air quality maps at a 100 m resolution were produced by combining the output of an air quality model (uEMEP) using data assimilation techniques with the network data that were corrected and calibrated by using a proposed five-step network data processing scheme. Leave-one-out cross-validation demonstrated that data assimilation reduced the model's RMSE, MAE, and bias by 44-56, 38-48, and 41-52%, respectively.

Atypical Scheuermann's disease with severe kyphosis and negative sagittal balance in the thoracolumbar region: A case report and literature review.

INTRODUCTION AND IMPORTANCE: Scheuermann's kyphosis is a structural deformity of the thoracolumbar spine that is classified in typical (thoracic) and atypical (lumbar and thoracolumbar) Scheuermann's disease. Surgical intervention is reserved for those with progressive kyphosis, intractable pain and neurological impairment. Although, previous literature focuses on the correction of the thoracic kyphosis (TK), recent lines of evidence recommend considering all the sagittal balance parameters when performing a surgery. We herein, report a posterior-only approach in a patient with Scheuermann's kyphosis, considering all the sagittal balance parameters. CASE PRESENTATION: The patient was a 17-year-old boy with a kyphotic deformity in the lumbar region, with urinary retention and upper back intractable pain. The preoperative physical examination was normal except for a kyphotic gait. The patient was first treated with thoracic lumbosacral orthoses (TLSO) brace that was not effective; consequently, the patient underwent posterior only approach (pedicular screw fixation along with Smith-Peterson osteotomy) with correction of the sagittal balance and kyphosis. The patient's sign and symptoms improved significantly. The surgery was uneventful and no complication was recorded. The 1-year follow-up revealed normal neurological examination and normal sagittal balance parameters. CLINICAL DISCUSSION: Atypical Scheuermann's kyphosis with neurological impairment and progressive kyphosis should be treated with surgical intervention. CONCLUSION: Considering the sagittal parameters of the spine, the surgical intervention should be designed to correct the kyphosis and the other indices of the sagittal balance. Posterior-only approach is safe and effective method for correction of the TK and improving the signs and symptoms of the patients.

Serum zinc associated with immunity and inflammatory markers in Covid-19.

This study aimed to assess the association between serum zinc level with some inflammatory and immunity factors and the duration of hospitalization and mortality rate in patients diagnosed with Covid-19. In this cross-sectional study, blood samples were taken from polymerase chain reaction (PCR) positive patients. New patients diagnosed with Covid-19, admitted to different public hospital wards, were considered eligible for entering the study. The study was done on 179 hospitalized patients diagnosed with Covid-19. Fourteen patients died during the hospitalization and the in-hospital mortality rate was 7.8%, with 9.1% (13 patients) of patients with serum zinc level less than 70 mcg/dL and 3.4% (1 patient) of patients with zinc levels more than 70 mcg/dL. Higher levels of zinc were significantly associated with a higher and lower level of interferon-gamma (IFN-γ) (p-value = 0.035) and interleukin (IL)-6 (p-value = 0.004), respectively. The level of serum zinc did not have a significant association with mortality even after adjusting for confounding factors. The relationship between zinc level and the duration of hospitalization was also not significant. In conclusion, serum zinc level had an association with IL-6 and IFN-γ level, but it did not have any significant association with hospital duration or mortality.

Global predictions of primary soil salinization under changing climate in the 21st century.

Soil salinization has become one of the major environmental and socioeconomic issues globally and this is expected to be exacerbated further with projected climatic change. Determining how climate change influences the dynamics of naturally-occurring soil salinization has scarcely been addressed due to highly complex processes influencing salinization. This paper sets out to address this long-standing challenge by developing data-driven models capable of predicting primary (naturally-occurring) soil salinity and its variations in the world's drylands up to the year 2100 under changing climate. Analysis of the future predictions made here identifies the dryland areas of South America, southern and western Australia, Mexico, southwest United States, and South Africa as the salinization hotspots. Conversely, we project a decrease in the soil salinity of the drylands in the northwest United States, the Horn of Africa, Eastern Europe, Turkmenistan, and west Kazakhstan in response to climate change over the same period.

Predicting long-term dynamics of soil salinity and sodicity on a global scale.

Knowledge of spatiotemporal distribution and likelihood of (re)occurrence of salt-affected soils is crucial to our understanding of land degradation and for planning effective remediation strategies in face of future climatic uncertainties. However, conventional methods used for tracking the variability of soil salinity/sodicity are extensively localized, making predictions on a global scale difficult. Here, we employ machine-learning techniques and a comprehensive set of climatic, topographic, soil, and remote sensing data to develop models capable of making predictions of soil salinity (expressed as electrical conductivity of saturated soil extract) and sodicity (measured as soil exchangeable sodium percentage) at different longitudes, latitudes, soil depths, and time periods. Using these predictive models, we provide a global-scale quantitative and gridded dataset characterizing different spatiotemporal facets of soil salinity and sodicity variability over the past four decades at a ∼1-km resolution. Analysis of this dataset reveals that a soil area of 11.73 Mkm2 located in nonfrigid zones has been salt-affected with a frequency of reoccurrence in at least three-fourths of the years between 1980 and 2018, with 0.16 Mkm2 of this area being croplands. Although the net changes in soil salinity/sodicity and the total area of salt-affected soils have been geographically highly variable, the continents with the highest salt-affected areas are Asia (particularly China, Kazakhstan, and Iran), Africa, and Australia. The proposed method can also be applied for quantifying the spatiotemporal variability of other dynamic soil properties, such as soil nutrients, organic carbon content, and pH.

Desiccation crisis of saline lakes: A new decision-support framework for building resilience to climate change.

River flow reductions as a result of agricultural withdrawals and climate change are rapidly desiccating endorheic lakes, increasing their salinity and affecting the bio-diversity and human wellbeing in the surrounding areas. Here we present a new framework to guide eco-hydrological restoration of saline lakes and build their resilience to climate change by optimizing agricultural land use and related water withdrawals. The framework involves four steps: 1. selection of global circulation models for the basin under study; 2. establishment of a hydrological balance over the lake's area to estimate the amount of water required for its restoration; 3. water allocation modeling to determine the water available for restoration and allocation of the remaining water across different users in the lake's basin; and 4. basin-scale optimization of land use and cropping patterns subject to water availability. We illustrated the general applicability of the framework through the case of the second largest (by volume) hyper-saline lake globally, Lake Urmia, which lost 96% of its volume in only 20 years, primarily as a result of upstream water withdrawals. Through the application of the framework, we estimated the amount of water needed to restore the lake, either fully or partially, and proposed a sustainable land-use strategy, while protect farmers' income in the basin. Considering future climate change projections under two representative concentration pathways (RCP) 4.5 and 8.5, we found that an average annual surface inflow of 3,648 Mm3 (∼70% increase in RCP 4.5) and 3,692 Mm3 (∼73% increase in RCP 8.5) would be required to restore the lake by 2050, respectively. This would require the respective conversion of 95,600 ha and 133,687 ha of irrigated land to rain-fed cropland or grassland across the basin by 2050. The proposed framework can be used for building resilience to climate change and mitigating human-induced threats to other declining saline lakes.