17 research outputs found
Export of Asian pollution during two cold front episodes of the TRACE-P experiment
Two cold front episodes were sampled during the two flights out of Yokota, Japan, during the Transport and Chemical Evolution Over the Pacific (TRACE-P) experiment during March 2001. The data from these two flights are examined using a mesoscale three-dimensional model. We show how these cyclonic systems have impacted the export of pollution out of the Asian continent. We contrast the relative role of convection and ascent in the warm conveyor belts associated with the cyclone during these two episodes. Although the necessary meteorological conditions for an efficient export of pollution are met during flight 13 (i.e., the occurrences of the warm conveyor belt near the source regions), no significant pollution is simulated in the mid-Pacific in the lower and middle troposphere. The efficient ventilation of the WCB by convection near the coast, the advection by the anticyclonical flow above 700 hPa, and the downward motion associated with the Pacific high in the remote ocean significantly prevent any long-range transport of undiluted pollution in the WCB. During flight 15 the conveyor belts have already moved to the remote ocean. The polluted plume is split by the rising air in the warm conveyor belt which transports CO-poor air northward and by the oceanic convection which transports clean air masses upward. These mechanisms lead to the dilution of Asian pollution in WCB en route to North America and add to the episodic nature of the Asian outflow by fragmenting the pollution plume
Aptamer-based multiplexed proteomic technology for biomarker discovery
Interrogation of the human proteome in a highly multiplexed and efficient manner remains a coveted and challenging goal in biology. We present a new aptamer-based proteomic technology for biomarker discovery capable of simultaneously measuring thousands of proteins from small sample volumes (15 [mu]L of serum or plasma). Our current assay allows us to measure ~800 proteins with very low limits of detection (1 pM average), 7 logs of overall dynamic range, and 5% average coefficient of variation. This technology is enabled by a new generation of aptamers that contain chemically modified nucleotides, which greatly expand the physicochemical diversity of the large randomized nucleic acid libraries from which the aptamers are selected. Proteins in complex matrices such as plasma are measured with a process that transforms a signature of protein concentrations into a corresponding DNA aptamer concentration signature, which is then quantified with a DNA microarray. In essence, our assay takes advantage of the dual nature of aptamers as both folded binding entities with defined shapes and unique sequences recognizable by specific hybridization probes. To demonstrate the utility of our proteomics biomarker discovery technology, we applied it to a clinical study of chronic kidney disease (CKD). We identified two well known CKD biomarkers as well as an additional 58 potential CKD biomarkers. These results demonstrate the potential utility of our technology to discover unique protein signatures characteristic of various disease states. More generally, we describe a versatile and powerful tool that allows large-scale comparison of proteome profiles among discrete populations. This unbiased and highly multiplexed search engine will enable the discovery of novel biomarkers in a manner that is unencumbered by our incomplete knowledge of biology, thereby helping to advance the next generation of evidence-based medicine
New Directions: GEIA's 2020 vision for better air emissions information
We are witnessing a crucial change in how we quantify and understand
emissions of greenhouse gases and air pollutants, with an
increasing demand for science-based transparent emissions information
produced by robust community efforts. Today’s scientific
capabilities, with near-real-time in-situ and remote sensing observations
combined with forward and inverse models and a better
understanding of the controlling processes, are contributing to
this transformation and providing newapproaches to derive, verify,
and forecast emissions (Tong et al., 2011; Frost et al., 2012) and to
quantify their impacts on the environment (e.g., Bond et al.,
2013). At the same time, the needs for emissions information and
the demands for their accuracy and consistency have grown.
Changing economies, demographics, agricultural practices, and energy
sources, along with mandates to evaluate emissions mitigation
efforts, demonstrate compliance with legislation, and verify
treaties, are leading to new challenges in emissions understanding.
To quote NOAA Senior Technical Scientist David Fahey, “We are in
the Century of Accountability. Emissions information is critical
not only for environmental science and decision-making, but also
as an instrument of foreign policy and international diplomacy.”
Emissions quantification represents a key step in explaining
observed variability and trends in atmospheric composition and
in attributing these observed changes to their causes. Accurate
emissions data are necessary to identify feasible controls that
reduce adverse impacts associated with air quality and climate
and to track the success of implemented policies. To progress
further, the international community must improve the understanding
of drivers and contributing factors to emissions, and it
must strengthen connections among and within different scientific
disciplines that characterize our environment and entities that protect
the environment and influence further emissions.
The Global Emissions InitiAtive, GEIA (http://www.geiacenter.
org/), is a center for emissions information exchange and competence
building created in 1990 in response to the need for high
quality global emissions data (Graedel et al., 1993). While the past
two decades have seen considerable progress in developing,
improving and assessing emission estimates, emissions continue
to be a major contributor to overall uncertainty in atmospheric
model simulations. Moving forward, GEIA aims to help build emissions
knowledge in a rapidly evolving society by: 1) enhancing understanding,
quantification, and analysis of emissions processes; 2)
improving access to emissions information; and 3) strengthening
the community of emissions groups involved in research, assessment,
operations, regulation and policy