Explore the vast range of titles available.

In the summer of 2003, ambient air concentrations of volatile organic compounds (VOCs) were measured at 12 sites within a 3-km radius in Deer Park, Texas near Houston. The purpose of the study was to assess local spatial influence of traffic and other urban sources and was part of a larger investigation of VOC spatial and temporal heterogeneity influences in selected areas of Houston. Seventy 2-h samples were collected using passive organic vapor monitors. Most measurements of 13 VOC species were greater than the method detection limits. Samplers were located at 10 residential sites, a regulatory air monitoring station, and a site located at the centroid of the census tract in which the regulatory station was located. For residential sites, sampler placement locations (e. g., covered porch vs. house eaves) had no effect on concentration with the exception of methyl tertiary-butyl ether (MTBE). Relatively high correlations (Pearson r > 0.8) were found between toluene, ethylbenzene, and o,m,p-xylenes suggesting petroleum-related influence. Chloroform was not correlated with these species or benzene (Pearson r < 0.35) suggesting a different source influence, possibly from process-related activities. As shown in other spatial studies, wind direction relative to source location had an effect on VOC concentrations.

This study proposes a multiple mediation model to evaluate the association among diminished physical performance, malnutrition, inflammation, and delirium in seniors with community-acquired pneumonia. This retrospective cohort study included elderly patients hospitalized for community-acquired pneumonia at the Geriatrics Department of the Second People's Hospital of Lianyungang from January 1, 2020, to January 1, 2024. Logistic regression analysis was conducted to examine the associations among physical performance, nutritional status, C-reactive protein (CRP) levels, and delirium. Mediation models assessed the effects of nutritional status and CRP on the relationship between physical performance and delirium, with subgroup analyses based on diabetes status. A total of 379 patients were included, with a mean age of 80.0±7.4 years, and 51.7% were male. The incidence of delirium during hospitalization was 28.5% (n=108). Subgroup analyses revealed significant correlations between physical performance, nutritional status, and CRP (P<0.001), regardless of diabetes status. After adjusting for confounding variables, CRP was positively associated with delirium, while MNA-SF and SPPB scores showed negative correlations with delirium risk (OR=0.852, 95% CI: 0.730-0.995; OR=0.580, 95% CI: 0.464-0.727, P<0.05). Mediation analyses indicated that MNA-SF scores and CRP significantly mediated the association between SPPB and delirium. Specifically, pathways \"SPPB→ MNA-SF→ delirium\", \"SPPB→ CRP→ delirium\", and \"SPPB→ MNA-SF→ CRP→ delirium\" demonstrated significant mediating effects in patients without diabetes, while only the pathway \"SPPB→ MNA-SF→ CRP→ delirium\" was significant in those with diabetes. Older patients with community-acquired pneumonia and poor physical performance are more susceptible to delirium, with nutritional status and inflammation as key mediators.

Riverine dissolved organic carbon (DOC) plays a vital role in regional and global carbon cycles. However, the processes of DOC conversion from soil organic carbon (SOC) and leaching into rivers are insufficiently understood, inconsistently represented, and poorly parameterized, particularly in land surface and Earth system models. As a first attempt to fill this gap, we propose a generic formula that directly connects SOC concentration with DOC concentration in headwater streams, where a single parameter, the transformation rate from SOC in the soil to DOC leaching flux (Pr), accounts for the overall processes governing SOC conversion to DOC and leaching from soils (along with runoff) into headwater streams. We then derive high-resolution Pr maps over the contiguous US (CONUS) using SOC data from two different sources: the Harmonized World Soil Database v1.2 (HWSD) and SoilGrids 2.0. Both maps are developed following the same five major steps: (1) selecting independent catchments where observed riverine DOC data are available with reasonable quality; (2) estimating catchment-average SOC for the independent catchments; (3) estimating the Pr values for these catchments based on the generic formula and catchment-average SOC; (4) developing a predictive model of Pr with machine learning (ML) techniques and catchment-scale climate, hydrology, geology, and other attributes; and (5) deriving a national map of Pr based on the ML model. For evaluation, we compare the DOC concentration derived using the Pr map and the observed DOC concentration values at evaluation catchments. The resulting mean absolute scaled error and coefficient of determination are 0.73 and 0.47 for the HWSD-based model and 0.58 and 0.72 for the SoilGrids-based model, respectively, suggesting the effectiveness of the overall methodology. Efforts to constrain uncertainty and evaluate sensitivity of Pr to different factors are discussed. To illustrate the use of such maps, we derive a riverine DOC concentration reanalysis dataset over CONUS. The two Pr maps, robustly derived and empirically validated, lay a critical cornerstone for better simulating the terrestrial carbon cycle in land surface and Earth system models. Our findings not only set a foundation for improving our predictive understanding of the terrestrial carbon cycle at the regional and global scales, but also hold promises for informing policy decisions related to decarbonization and climate change mitigation. The data presented in this study are publicly available at https://doi.org/10.5281/zenodo.14563816 (Li et al., 2024).