LEADER 01756nam0 2200349 i 450 001 BVEE039078 005 20170908093220.0 012 $ae-i- 9.8. 6.e- riIV (3) 1698 (R)$2fei 100 $a20151029d1698 ||||0itac50 ba 101 | $alat 102 $agb 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $aAnnales Velleiani, Quintilianaei, Statiani. Seu Vitae P. Velleii Paterculi, M. Fabii Quintiliani, P. Papinii Statii, (obiterque Juvenalis,) pro temporum ordine, dispositae. Ab Henrico Dodwello A.M. Dubliniensi 210 $aOxonii$ce Theatro Sheldoniano$d1698 215 $a\12!, 306, \42! p.$d8º 300 $aSegue, a c. 2Q2r.: Appendix dissertationum duarum miscellanearum, . 300 $aSegn.: a²b⁴A-2U⁴2X² 300 $aVignetta calcogr. sul front. 316 $a1 v. (Timbro RB sul front.)$5IT-NA0079, V.F. 147 E 16 620 $aGB$dOxford$3MUSL002585 700 1$aDodwell$b, Henry$f <1641-1711>$3SBLV316699$4070$0744120 712 02$aTheatrum Sheldonianum$3UBOV122132$4650 791 02$aTheatro Sheldoniano$3BVEV070974$zTheatrum Sheldonianum 791 02$aSheldonian Theatre$c $3MILV315870$zTheatrum Sheldonianum 801 3$aIT$bIT-NA0079$c20151029 850 $aIT-NA0079 912 $aBVEE039078 950 0$aBiblioteca Nazionale Vittorio Emanuele III$c1 v.$d BNV.F. 147 E 16$e BNVA10015573985 G 1 v. (Timbro RB sul front.)$fC $h20151029$i20151029 977 $a BN 996 $aAnnales Velleiani, Quintilianaei, Statiani. Seu Vitae P. Velleii Paterculi, M. Fabii Quintiliani, P. Papinii Statii, (obiterque Juvenalis,) pro temporum ordine, dispositae. Ab Henrico Dodwello A.M. Dubliniensi$91481365 997 $aUNISANNIO LEADER 04181aam 2200505I 450 001 9910711167503321 005 20241213181716.0 024 8 $aGOVPUB-C13-0353deb555be1a558f57d6b82368ba75 035 $a(CKB)5470000002480334 035 $a(OCoLC)958885804 035 $a(EXLCZ)995470000002480334 100 $a20160921d2015 ua 0 101 0 $aeng 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aGreenhouse gas emissions and dispersion $e3. reducing uncertainty in estimating source strangth and location through plume inversion models /$fKuldeep Prasad; Adam Pintar; Heming Hu; Israel Lopez-Coto; Dennis Ngo; James R. Whetstone 210 1$aGaithersburg, MD :$cU.S. Dept. of Commerce, National Institute of Standards and Technology,$d2015. 215 $a1 online resource (28 pages) $cillustrations (color) 225 1 $aNIST special publication ;$v1175 300 $aContributed record: Metadata reviewed, not verified. Some fields updated by batch processes. 300 $aSeptember 2015. 300 $aTitle from PDF title page (viewed September 30, 2015). 320 $aIncludes bibliographical references. 330 3 $aRecent development of accurate instruments for measuring greenhouse gas concentrations and the ability to mount them in ground-based vehicles has provided an opportunity to make temporally and spatially resolved measurements in the vicinity of suspected source locations, and for subsequently estimating the source location and strength.^The basic approach of using downwind atmospheric measurements in an inversion methodology to predict the source strength and location is an ill-posed problem and results in large uncertainty.^In this report, we present a new measurement methodology for reducing the uncertainty in predicting source strength from downwind measurements associated with inverse modeling.^In order to demonstrate the approach, an inversion methodology built around a plume dispersion model is developed.^Synthetic data derived from an assumed source distribution is used to compare and contrast the predicted source strength and location.^The effect of introducing various levels of noise in the synthetic data or uncertainty in meteorological variables on the inversion methodology is studied.^Results indicate that the use of noisy measurement data had a small effect on the total predicted source strength, but gave rise to several spurious sources (in many cases 8-10 sources were detected, while the assumed source distribution only consisted of 2 sources).^Use of noisy measurement data for inversion also introduced large uncertainty in the location of the predicted sources.^A mathematical model for estimating an upper bound on the uncertainty, and a bootstrap statistical approach for determining the variability in the predicted source distribution is demonstrated.^The new measurement methodology, which involves using measurement data from two or more wind directions, combined together as part of a single inversion process is presented.^Results of the bootstrap process indicated that the uncertainty in locating sources reduced significantly when measurements are made using the new proposed measurement approach.^The proposed measurement system can be significant in determining emission inventories in urban domains at a high level of reliability, and for studying the role of remediation measures. 517 $aGreenhouse gas emissions and dispersion 606 $aGreenhouse gas emissions 606 $aQuality control 615 0$aGreenhouse gas emissions. 615 0$aQuality control. 700 $aPrasad$b Kuldeep R.$f1964-$01415551 701 $aHu$b Heming$01397615 701 $aLopez-Coto$b Israel$01397616 701 $aNgo$b Dennis$01397617 701 $aPintar$b Adam L$01394651 701 $aWhetstone$b James R$01390336 712 02$aNational Institute of Standards and Technology (U.S.).$bEngineering Laboratory. 801 0$bNBS 801 1$bNBS 801 2$bGPO 801 2$bNBS 906 $aBOOK 912 $a9910711167503321 996 $aGreenhouse gas emissions and dispersion$94302046 997 $aUNINA