An Environmental and Energy Information System

The Environmental Information System Office (EISO) at Oak Ridge National Laboratory (ORNL) provides information support for researchers and administrators involved with energy and environmental policy and progress. Multiple EISO activities for various governmental agencies have resulted in establishment of compatible data bases concerned with energy and environmental information, methods for effectively developing these, development and computer display of numerical data summaries, and reports evaluating published information. Direction is provided by continuing dialogue between users and information system staff

Anthropogenic Control over Wintertime Oxidation of Atmospheric Pollutants

Anthropogenic air pollutants such as nitrogen oxides (NO(x) = NO + NO(2)), sulfur dioxide (SO(2)), and volatile organic compounds (VOC), among others, are emitted to the atmosphere throughout the year from energy production and use, transportation, and agriculture. These primary pollutants lead to the formation of secondary pollutants such as fine particulate matter (PM(2.5)) and ozone (O(3)) and perturbations to the abundance and lifetimes of short-lived greenhouse gases. Free radical oxidation reactions driven by solar radiation govern the atmospheric lifetimes and transformations of most primary pollutants and thus their spatial distributions. During winter in the mid and high latitudes, where a large fraction of atmospheric pollutants are emitted globally, such photochemical oxidation is significantly slower. Using observations from a highly instrumented aircraft, we show that multi-phase reactions between gas-phase NO(x) reservoirs and aerosol particles, as well as VOC emissions from anthropogenic activities, lead to a suite of atypical radical precursors dominating the oxidizing capacity in polluted winter air, and thus, the distribution and fate of primary pollutants on a regional to global scale

The ACOS CO_2 retrieval algorithm – Part 1: Description and validation against synthetic observations

This work describes the NASA Atmospheric CO_2 Observations from Space (ACOS) X_(CO_2) retrieval algorithm, and its performance on highly realistic, simulated observations. These tests, restricted to observations over land, are used to evaluate retrieval errors in the face of realistic clouds and aerosols, polarized non-Lambertian surfaces, imperfect meteorology, and uncorrelated instrument noise. We find that post-retrieval filters are essential to eliminate the poorest retrievals, which arise primarily due to imperfect cloud screening. The remaining retrievals have RMS errors of approximately 1 ppm. Modeled instrument noise, based on the Greenhouse Gases Observing SATellite (GOSAT) in-flight performance, accounts for less than half the total error in these retrievals. A small fraction of unfiltered clouds, particularly thin cirrus, lead to a small positive bias of ~0.3 ppm. Overall, systematic errors due to imperfect characterization of clouds and aerosols dominate the error budget, while errors due to other simplifying assumptions, in particular those related to the prior meteorological fields, appear small

Improved retrievals of carbon dioxide from Orbiting Carbon Observatory-2 with the version 8 ACOS algorithm

Since September 2014, NASA's Orbiting Carbon Observatory-2 (OCO-2) satellite has been taking measurements of reflected solar spectra and using them to infer atmospheric carbon dioxide levels. This work provides details of the OCO-2 retrieval algorithm, versions 7 and 8, used to derive the column-averaged dry air mole fraction of atmospheric CO2 (XCO2) for the roughly 100&thinsp;000 cloud-free measurements recorded by OCO-2 each day. The algorithm is based on the Atmospheric Carbon Observations from Space (ACOS) algorithm which has been applied to observations from the Greenhouse Gases Observing SATellite (GOSAT) since 2009, with modifications necessary for OCO-2. Because high accuracy, better than 0.25&thinsp;%, is required in order to accurately infer carbon sources and sinks from XCO2, significant errors and regional-scale biases in the measurements must be minimized. We discuss efforts to filter out poor-quality measurements, and correct the remaining good-quality measurements to minimize regional-scale biases. Updates to the radiance calibration and retrieval forward model in version 8 have improved many aspects of the retrieved data products. The version 8 data appear to have reduced regional-scale biases overall, and demonstrate a clear improvement over the version 7 data. In particular, error variance with respect to TCCON was reduced by 20&thinsp;% over land and 40&thinsp;% over ocean between versions 7 and 8, and nadir and glint observations over land are now more consistent. While this paper documents the significant improvements in the ACOS algorithm, it will continue to evolve and improve as the CO2 data record continues to expand.</p

Limitations in representation of physical processes prevent successful simulation of PM2.5 during KORUS-AQ

High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea–United States Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by −64 % but overestimates nitrate by +36 %. The largest underestimate in sulfate occurs during the pollution event, for which models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100 % against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of 5 increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape, resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model's inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model, which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation, implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66 % to 54 %. Locally produced sulfate increased from 1 % to 25 % of locally produced PM2.5, implying that local emissions controls could have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction, which affects the aerosol liquid water abundance and chemistry driving sulfate–nitrate–ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30 % less sulfate due to 40 % less nitrate and aerosol water, and this results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate + nitrate + ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements

Alterations of renal phenotype and gene expression profiles due to protein overload in NOD-related mouse strains

BACKGROUND: Despite multiple causes, Chronic Kidney Disease is commonly associated with proteinuria. A previous study on Non Obese Diabetic mice (NOD), which spontaneously develop type 1 diabetes, described histological and gene expression changes incurred by diabetes in the kidney. Because proteinuria is coincident to diabetes, the effects of proteinuria are difficult to distinguish from those of other factors such as hyperglycemia. Proteinuria can nevertheless be induced in mice by peritoneal injection of Bovine Serum Albumin (BSA). To gain more information on the specific effects of proteinuria, this study addresses renal changes in diabetes resistant NOD-related mouse strains (NON and NOD.B10) that were made to develop proteinuria by BSA overload. METHODS: Proteinuria was induced by protein overload on NON and NOD.B10 mouse strains and histology and microarray technology were used to follow the kidney response. The effects of proteinuria were assessed and subsequently compared to changes that were observed in a prior study on NOD diabetic nephropathy. RESULTS: Overload treatment significantly modified the renal phenotype and out of 5760 clones screened, 21 and 7 kidney transcripts were respectively altered in the NON and NOD.B10. Upregulated transcripts encoded signal transduction genes, as well as markers for inflammation (Calmodulin kinase beta). Down-regulated transcripts included FKBP52 which was also down-regulated in diabetic NOD kidney. Comparison of transcripts altered by proteinuria to those altered by diabetes identified mannosidase 2 alpha 1 as being more specifically induced by proteinuria. CONCLUSION: By simulating a component of diabetes, and looking at the global response on mice resistant to the disease, by virtue of a small genetic difference, we were able to identify key factors in disease progression. This suggests the power of this approach in unraveling multifactorial disease processes

Group B Streptococcus vaccine development: present status and future considerations, with emphasis on perspectives for low and middle income countries.

Globally, group B Streptococcus (GBS) remains the leading cause of sepsis and meningitis in young infants, with its greatest burden in the first 90 days of life. Intrapartum antibiotic prophylaxis (IAP) for women at risk of transmitting GBS to their newborns has been effective in reducing, but not eliminating, the young infant GBS disease burden in many high income countries. However, identification of women at risk and administration of IAP is very difficult in many low and middle income country (LMIC) settings, and is not possible for home deliveries. Immunization of pregnant women with a GBS vaccine represents an alternate pathway to protecting newborns from GBS disease, through the transplacental antibody transfer to the fetus in utero. This approach to prevent GBS disease in young infants is currently under development, and is approaching late stage clinical evaluation. This manuscript includes a review of the natural history of the disease, global disease burden estimates, diagnosis and existing control options in different settings, the biological rationale for a vaccine including previous supportive studies, analysis of current candidates in development, possible correlates of protection and current status of immunogenicity assays. Future potential vaccine development pathways to licensure and use in LMICs, trial design and implementation options are discussed, with the objective to provide a basis for reflection, rather than recommendations

Contributions of phonological and verbal working memory to language development in adolescents with fragile X syndrome

Fragile X syndrome (FXS) is the most common inherited cause of intellectual disability. Although language delays are frequently observed in FXS, neither the longitudinal course of language development nor its cognitive predictors are well understood. The present study investigated whether phonological and working memory skills are predictive of growth in vocabulary and syntax in individuals with FXS during adolescence. Forty-four individuals with FXS (mean age = 12.61 years) completed assessments of phonological memory (nonword repetition and forward digit recall), verbal working memory (backward digit recall), vocabulary, syntax, and nonverbal cognition. Vocabulary and syntax skills were reassessed at a 2-year follow-up. In a series of analyses that controlled for nonverbal cognitive ability and severity of autism symptoms, the relative contributions of phonological and working memory to language change over time were investigated. These relationships were examined separately for boys and girls. In boys with FXS, phonological memory significantly predicted gains in vocabulary and syntax skills. Further, verbal working memory was uniquely associated with vocabulary gains among boys. In girls with FXS, phonological and working memory skills showed no relationship with language change across the 2-year time period. Our findings indicate that, for adolescent boys with FXS, acquisition of vocabulary and syntax may be constrained by the ability to maintain and manipulate phonological representations online. Implications for the identification and treatment of language disorders in this population are discussed. The present study is the first to identify specific cognitive mechanisms contributing to language growth over time in individuals with FXS