Spatial and temporal variations of aerosols around Beijing in summer 2006: Model evaluation and source apportionment

Regional aerosol model calculations were made using the Weather Research and Forecasting (WRF)-Community Multiscale Air Quality (CMAQ) and WRF-chem models to study spatial and temporal variations of aerosols around Beijing, China, in the summer of 2006, when the Campaigns of Air Quality Research in Beijing and Surrounding Region 2006 (CAREBeijing) intensive campaign was conducted. Model calculations captured temporal variations of primary (such as elemental carbon. (EC)) and secondary (such as sulfate) aerosols observed in and around Beijing. The spatial distributions of aerosol optical depth observed by the MODTS satellite sensors were also reproduced over northeast China. Model calculations showed distinct differences in spatial distributions between primary and secondary aerosols in association with synoptic-scale meteorology. Secondary aerosols increased in air around Beijing on a scale of about 1000 × 1000 km2 under an anticyclonic pressure system. This air mass was transported northward from the high anthropogenic emission area extending south of Beijing with continuous photochemical production. Subsequent cold front passage brought clean air from the north, and polluted air around Beijing was swept to the south of Beijing. This cycle was repeated about once a week and was found to be responsible for observed enhancements/reductions of aerosols at the intensive measurement sites. In contrast to secondary aerosols, the spatial distributions of primary aerosols (EC) reflected those of emissions, resulting in only slight variability despite the changes in synopticscale meteorology. In accordance with these results, source apportionment simulations revealed that primary aerosols around Beijing were controlled by emissions within 100 km around Beijing within the preceding 24 h, while emissions as far as 500 km and within the preceding 3 days were found to affect secondary aerosols. Copyright 2009 by the American Geophysical Union

Quarkonium and hydrogen spectra with spin dependent relativistic wave equation

A non-linear non-perturbative relativistic atomic theory introduces spin in the dynamics of particle motion. The resulting energy levels of Hydrogen atom are exactly same as the Dirac theory. The theory accounts for the energy due to spin-orbit interaction and for the additional potential energy due to spin and spin-orbit coupling. Spin angular momentum operator is integrated into the equation of motion. This requires modification to classical Laplacian operator. Consequently the Dirac matrices and the k operator of Dirac's theory are dispensed with. The theory points out that the curvature of the orbit draws on certain amount of kinetic and potential energies affecting the momentum of electron and the spin-orbit interaction energy constitutes a part of this energy. The theory is developed for spin 1/2 bound state single electron in Coulomb potential and then further extended to quarkonium physics by introducing the linear confining potential. The unique feature of this quarkonium model is that the radial distance can be exactly determined and does not have a statistical interpretation. The established radial distance is then used to determine the wave function. The observed energy levels are used as the input parameters and the radial distance and the string tension are predicted. This ensures 100% conformance to all observed energy levels for the heavy quarkonium.Comment: 14 pages, v7: Journal reference adde

Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning

Mounting evidence from field and laboratory observations coupled with atmospheric model analyses shows that primary combustion emissions of organic compounds dynamically partition between the vapor and particulate phases, especially as near-source emissions dilute and cool to ambient conditions. The most recent version of the Community Multiscale Air Quality model version 5.2 (CMAQv5.2) accounts for the semivolatile partitioning and gas-phase aging of these primary organic aerosol (POA) compounds consistent with experimentally derived parameterizations. We also include a new surrogate species, potential secondary organic aerosol from combustion emissions (pcSOA), which provides a representation of the secondary organic aerosol (SOA) from anthropogenic combustion sources that could be missing from current chemical transport model predictions. The reasons for this missing mass likely include the following: (1) unspeciated semivolatile and intermediate volatility organic compound (SVOC and IVOC, respectively) emissions missing from current inventories, (2) multigenerational aging of organic vapor products from known SOA precursors (e.g., toluene, alkanes), (3) underestimation of SOA yields due to vapor wall losses in smog chamber experiments, and (4) reversible organic compounds–water interactions and/or aqueous-phase processing of known organic vapor emissions. CMAQ predicts the spatially averaged contribution of pcSOA to OA surface concentrations in the continental United States to be 38.6 and 23.6 % in the 2011 winter and summer, respectively. Whereas many past modeling studies focused on a particular measurement campaign, season, location, or model configuration, we endeavor to evaluate the model and important uncertain parameters with a comprehensive set of United States-based model runs using multiple horizontal scales (4 and 12 km), gas-phase chemical mechanisms, and seasons and years. The model with representation of semivolatile POA improves predictions of hourly OA observations over the traditional nonvolatile model at sites during field campaigns in southern California (CalNex, May–June 2010), northern California (CARES, June 2010), the southeast US (SOAS, June 2013; SEARCH, January and July, 2011). Model improvements manifest better correlations (e.g., the correlation coefficient at Pasadena at night increases from 0.38 to 0.62) and reductions in underprediction during the photochemically active afternoon period (e.g., bias at Pasadena from −5.62 to −2.42 µg m−3). Daily averaged predictions of observations at routine-monitoring networks from simulations over the continental US (CONUS) in 2011 show modest improvement during winter, with mean biases reducing from 1.14 to 0.73 µg m−3, but less change in the summer when the decreases from POA evaporation were similar to the magnitude of added SOA mass. Because the model-performance improvement realized by including the relatively simple pcSOA approach is similar to that of more-complicated parameterizations of OA formation and aging, we recommend caution when applying these more-complicated approaches as they currently rely on numerous uncertain parameters. The pcSOA parameters optimized for performance at the southern and northern California sites lead to higher OA formation than is observed in the CONUS evaluation. This may be due to any of the following: variations in real pcSOA in different regions or time periods, too-high concentrations of other OA sources in the model that are important over the larger domain, or other model issues such as loss processes. This discrepancy is likely regionally and temporally dependent and driven by interferences from factors like varying emissions and chemical regimes

Structural determinants of opioid and NOP receptor activity in derivatives of buprenorphine

The unique pharmacological profile of buprenorphine has led to its considerable success as an analgesic and as a treatment agent for drug abuse. Activation of nociceptin/orphanin FQ peptide (NOP) receptors has been postulated to account for certain aspects of buprenorphine’s behavioural profile. In order to investigate the role of NOP activation further, a series of buprenorphine analogues has been synthesised with the aim of increasing affinity for the NOP receptor. Binding and functional assay data on these new compounds indicate that the area around C20 in the orvinols is key to NOP receptor activity, with several compounds displaying higher affinity than buprenorphine. One compound, 1b, was found to be a mu opioid receptor partial agonist of comparable efficacy to buprenorphine, but with higher efficacy at NOP receptors

Unified theoretical framework for mixing state of black carbon

Black carbon (BC) plays an important role in the climate system due to its strongwarming effect, yet the magnitude of this effect is highly uncertain due to the complex mixingstate of aerosols. Here we build a unified theoretical framework to describe BC’s mixing states,linking dynamic processes to BC coating thickness distribution, and show its self-similarity for sites in diverse environments. The size distribution of BC-containing particles is found to followan exponential pattern and is independent of BC core size. A mixing state module is establishedbased on this finding and successfully applied in global and regional models, which increases theaccuracy of aerosol climate effect estimations. Our theoretical framework can bridge the gap be-tween observation and model simulation in both mixing state description and light absorption quantification<br

RGS4 negatively modulates Nociceptin/Orphanin FQ opioid receptor signaling: implication for L-Dopa induced dyskinesia

Background and purpose Regulator of G-protein signal 4 (RGS4) is a signal transduction protein that accelerates intrinsic GTPase activity of Gαi/o and Gαq subunits, suppressing GPCR signaling. Here we investigate whether RGS4 modulates nociceptin/orphanin FQ (N/OFQ) opioid (NOP) receptor signaling and this modulation has relevance for L-Dopa-induced dyskinesia. Experimental approach HEK293T cells transfected with NOP, NOP/RGS4 or NOP/RGS19 were challenged with N/OFQ and the small molecule NOP agonist AT-403, using D1-stimulated cAMP levels as a readout. Primary rat striatal neurons and adult mouse striatal slices were challenged with N/OFQ or AT-403 in the presence of the experimental RGS4 chemical probe, CCG-203920, and D1-stimulated cAMP or phosphorylated extracellular signal regulated kinase 1/2 (pERK) responses were monitored. In vivo, CCG-203920 was co-administered with AT-403 and L-Dopa to 6-hydroxydopamine hemilesioned rats, and dyskinetic movements, striatal biochemical correlates of dyskinesia (pERK and pGluR1 levels) and striatal RGS4 levels were measured. Key results RGS4 expression reduced NOFQ and AT-403 potency and efficacy in HEK293T cells. CCG-203920 increased N/OFQ potency in primary rat striatal neurons, and potentiated AT-403 response in mouse striatal slices. CCG-203920 enhanced AT-403 mediated inhibition of dyskinesia and its biochemical correlates, without compromising its motor-improving effects. Unilateral dopamine depletion caused bilateral reduction of RGS4 levels, which was reversed by L-Dopa. L-Dopa acutely upregulated RGS4 in the lesioned striatum. Conclusions and Implications RGS4 physiologically inhibits NOP receptor signaling. CCG-203920 enhanced NOP responses and improved the antidyskinetic potential of NOP receptor agonists, mitigating the effects of striatal RGS4 upregulation occurring during dyskinesia expression

The AeroCom evaluation and intercomparison of organic aerosol in global models

This paper evaluates the current status of global modeling of the organic aerosol (OA) in the troposphere and analyzes the differences between models as well as between models and observations. Thirty-one global chemistry transport models (CTMs) and general circulation models (GCMs) have participated in this intercomparison, in the framework of AeroCom phase II. The simulation of OA varies greatly between models in terms of the magnitude of primary emissions, secondary OA (SOA) formation, the number of OA species used (2 to 62), the complexity of OA parameterizations (gas-particle partitioning, chemical aging, multiphase chemistry, aerosol microphysics), and the OA physical, chemical and optical properties. The diversity of the global OA simulation results has increased since earlier AeroCom experiments, mainly due to the increasing complexity of the SOA parameterization in models, and the implementation of new, highly uncertain, OA sources. Diversity of over one order of magnitude exists in the modeled vertical distribution of OA concentrations that deserves a dedicated future study. Furthermore, although the OA / OC ratio depends on OA sources and atmospheric processing, and is important for model evaluation against OA and OC observations, it is resolved only by a few global models. The median global primary OA (POA) source strength is 56 Tg a−1 (range 34–144 Tg a−1) and the median SOA source strength (natural and anthropogenic) is 19 Tg a−1 (range 13–121 Tg a−1). Among the models that take into account the semi-volatile SOA nature, the median source is calculated to be 51 Tg a−1 (range 16–121 Tg a−1), much larger than the median value of the models that calculate SOA in a more simplistic way (19 Tg a−1; range 13–20 Tg a−1, with one model at 37 Tg a−1). The median atmospheric burden of OA is 1.4 Tg (24 models in the range of 0.6–2.0 Tg and 4 between 2.0 and 3.8 Tg), with a median OA lifetime of 5.4 days (range 3.8–9.6 days). In models that reported both OA and sulfate burdens, the median value of the OA/sulfate burden ratio is calculated to be 0.77; 13 models calculate a ratio lower than 1, and 9 models higher than 1. For 26 models that reported OA deposition fluxes, the median wet removal is 70 Tg a−1 (range 28–209 Tg a−1), which is on average 85% of the total OA deposition. Fine aerosol organic carbon (OC) and OA observations from continuous monitoring networks and individual field campaigns have been used for model evaluation. At urban locations, the model–observation comparison indicates missing knowledge on anthropogenic OA sources, both strength and seasonality. The combined model–measurements analysis suggests the existence of increased OA levels during summer due to biogenic SOA formation over large areas of the USA that can be of the same order of magnitude as the POA, even at urban locations, and contribute to the measured urban seasonal pattern. Global models are able to simulate the high secondary character of OA observed in the atmosphere as a result of SOA formation and POA aging, although the amount of OA present in the atmosphere remains largely underestimated, with a mean normalized bias (MNB) equal to −0.62 (−0.51) based on the comparison against OC (OA) urban data of all models at the surface, −0.15 (+0.51) when compared with remote measurements, and −0.30 for marine locations with OC data. The mean temporal correlations across all stations are low when compared with OC (OA) measurements: 0.47 (0.52) for urban stations, 0.39 (0.37) for remote stations, and 0.25 for marine stations with OC data. The combination of high (negative) MNB and higher correlation at urban stations when compared with the low MNB and lower correlation at remote sites suggests that knowledge about the processes that govern aerosol processing, transport and removal, on top of their sources, is important at the remote stations. There is no clear change in model skill with increasing model complexity with regard to OC or OA mass concentration. However, the complexity is needed in models in order to distinguish between anthropogenic and natural OA as needed for climate mitigation, and to calculate the impact of OA on climate accurately

Evolutionary Sequence Modeling for Discovery of Peptide Hormones

There are currently a large number of “orphan” G-protein-coupled receptors (GPCRs) whose endogenous ligands (peptide hormones) are unknown. Identification of these peptide hormones is a difficult and important problem. We describe a computational framework that models spatial structure along the genomic sequence simultaneously with the temporal evolutionary path structure across species and show how such models can be used to discover new functional molecules, in particular peptide hormones, via cross-genomic sequence comparisons. The computational framework incorporates a priori high-level knowledge of structural and evolutionary constraints into a hierarchical grammar of evolutionary probabilistic models. This computational method was used for identifying novel prohormones and the processed peptide sites by producing sequence alignments across many species at the functional-element level. Experimental results with an initial implementation of the algorithm were used to identify potential prohormones by comparing the human and non-human proteins in the Swiss-Prot database of known annotated proteins. In this proof of concept, we identified 45 out of 54 prohormones with only 44 false positives. The comparison of known and hypothetical human and mouse proteins resulted in the identification of a novel putative prohormone with at least four potential neuropeptides. Finally, in order to validate the computational methodology, we present the basic molecular biological characterization of the novel putative peptide hormone, including its identification and regional localization in the brain. This species comparison, HMM-based computational approach succeeded in identifying a previously undiscovered neuropeptide from whole genome protein sequences. This novel putative peptide hormone is found in discreet brain regions as well as other organs. The success of this approach will have a great impact on our understanding of GPCRs and associated pathways and help to identify new targets for drug development