scholarly journals The implementation of NEMS GFS Aerosol Component (NGAC) Version 2.0 for global multispecies forecasting at NOAA/NCEP – Part 1: Model descriptions

2018 ◽  
Vol 11 (6) ◽  
pp. 2315-2332 ◽  
Author(s):  
Jun Wang ◽  
Partha S. Bhattacharjee ◽  
Vijay Tallapragada ◽  
Cheng-Hsuan Lu ◽  
Shobha Kondragunta ◽  
...  
Keyword(s):  
New York ◽  
Biomass Burning ◽  
State University ◽  
Air Quality Model ◽  
Quality Model ◽  
Emission Data ◽  
Aerosol Component ◽  
Nasa Goddard Space ◽  
Satellite Applications ◽  
Version 2.0

Abstract. The NEMS GFS Aerosol Component Version 2.0 (NGACv2) for global multispecies aerosol forecast has been developed at the National Centers of Environment Prediction (NCEP) in collaboration with the NESDIS Center for Satellite Applications and Research (STAR), the NASA Goddard Space Flight Center (GSFC), and the University at Albany, State University of New York (SUNYA). This paper describes the continuous development of the NGAC system at NCEP after the initial global dust-only forecast implementation (NGAC version 1.0, NGACv1). With NGACv2, additional sea salt, sulfate, organic carbon, and black carbon aerosol species were included. The smoke emissions are from the NESDIS STAR's Global Biomass Burning Product (GBBEPx), blended from the global biomass burning emission product from a constellation of geostationary satellites (GBBEP-Geo) and GSFC's Quick Fire Emission Data Version 2 from a polar-orbiting sensor (QFED2). This implementation advanced the global aerosol forecast capability and made a step forward toward developing a global aerosol data assimilation system. The aerosol products from this system have been used by many applications such as for regional air quality model lateral boundary conditions, satellite sea surface temperature (SST) physical retrievals, and the global solar insolation estimation. Positive impacts have been seen in these applications.

scholarly journals The implementation of NEMS GFS Aerosol Component (NGAC) Version 2.0 for global multispecies forecasting at NOAA/NCEP: Part I Model Descriptions

2017 ◽  
Author(s):  
Jun Wang ◽  
Partha S. Bhattacharjee ◽  
Vijay Tallapragada ◽  
Cheng-Hsuan Lu ◽  
Shobha Kondragunta ◽  
...  
Keyword(s):  
New York ◽  
Biomass Burning ◽  
Air Quality Model ◽  
Quality Model ◽  
Emission Data ◽  
Aerosol Component ◽  
Nasa Goddard Space ◽  
Satellite Sst ◽  
Satellite Applications ◽  
Version 2.0

Abstract. The NEMS GFS Aerosol component (NGAC) version 2.0 for global multi-species aerosol forecast has been developed at the National Centers of Environment Prediction (NCEP) in collaboration with the NESDIS Center for Satellite Applications and Research (STAR), NASA Goddard Space Flight Center (GSFC), and University at Albany, State University of New York (SUNYA). This paper describes the continuous development of the NGAC system at NCEP after the initial global dust-only forecast implementation (NGAC version 1.0). With version 2, additional sea salt, sulfate, organic carbon and black carbon aerosol species were included. The smoke emissions are from the NESDIS STAR's Global Biomass Burning Product (GBBEPx), blended from the global biomass burning emission product from a constellation of geostationary satellites (GBBEP-Geo) and GSFC's Quick Fire Emission Data Version 2 from a polar orbiting sensor (QFED2). This implementation advanced the global aerosol forecast capability and made a step forward toward developing a global aerosol data assimilation system. The aerosol products from this system have been used by many applications such as for regional air quality model lateral boundary conditions, satellite SST physical retrievals and the global solar insolation estimation. Positive impacts have been seen in these applications.

scholarly journals Comparison of the RADM2 and RACM chemical mechanisms in O3 simulations: effect of the photolysis rate constant

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chien-Hung Chen ◽  
Tu-Fu Chen ◽  
Shang-Ping Huang ◽  
Ken-Hui Chang
Keyword(s):  
East Asia ◽  
Rate Constants ◽  
Daily Maximum ◽  
Bias Error ◽  
Air Quality Model ◽  
Quality Model ◽  
Yield Data ◽  
Emission Data ◽  
Photolysis Rate ◽  
Photolysis Rates

AbstractSince the photolysis rate plays an important role in any photoreaction leading to compound sink and radical formation/destruction and eventually O3 formation, its impact on the simulated O3 concentration was evaluated in the present study. Both RADM2 and RACM were adopted with and without updated photolysis rate constants. The newly developed photolysis rates were determined based on two major absorption cross-section and quantum yield data sources. CMAQ in conjunction with meteorological MM5 and emission data retrieved from Taiwan and East Asia were employed to provide spatial and temporal O3 predictions over a one-week period in a three-level nested domain [from 81 km × 81 km in Domain 1 (East Asia) to 9 km × 9 km in Domain 3 (Taiwan)]. Four cases were analyzed, namely, RADM2, with the original photolysis rates applied in Case 1 as a reference case, RADM2, with the updated photolysis rates applied in Case 2, and RACM, with and without the updated photolysis rates applied in Cases 3 and 4, respectively. A comparison of the simulation and observed results indicates that both the application of updated photolysis rate constants and RACM instead of RADM2 enhanced all three error analysis indicators (unpaired peak prediction accuracy, mean normalized bias error and mean absolute normalized gross error). Specifically, RADM2 with the updated photolysis rates resulted in an increase of 12 ppb (10%) in the daily maximum O3 concentration in southwestern Taiwan, while RACM without the updated photolysis rates resulted in an increase of 20 ppb (17%) in the daily maximum O3 concentration in the same area. When RACM with the updated photolysis rate constants was applied in the air quality model, the difference in the daily maximum O3 concentration reached up to 30 ppb (25%). The implication of Case 4 (RACM with the updated photolysis rates) for the formation and degradation of α-pinene and d-limonene was examined.

The Impacts of Vehicle-to-Grid Technology on Mitigating High-Energy Demand Day Emissions in New York City

2009 ◽  
Author(s):  
Charles Ferdon ◽  
Earl Foster ◽  
Jonathan Acquaviva ◽  
Shashank Rawat ◽  
K. Max Zhang
Keyword(s):  
New York ◽  
Air Quality ◽  
Energy Demand ◽  
High Energy ◽  
Air Quality Model ◽  
Quality Model ◽  
Vehicle To Grid ◽  
Electricity Rates ◽  
York Metropolitan Area ◽  
Revenue Models

In this report, a theoretical implementation of vehicle-to-grid power in the New York Metropolitan Area was evaluated with the goal of reducing peaking unit NOx emissions to comply with upcoming emissions limits on high energy demand days. In addition, the net cost of implementing this program was estimated using cost and revenue models based on available electricity rates and approximate battery cost. Finally, the improvement of air quality in some of the most populated areas of the NYMA was evaluated using the AERMOD air quality model from the EPA. By selectively offsetting the peaking units with the highest emissions rates, the average daily reduction was .25 tons at 1% penetration, 1.2 tons at 5% penetration, and 2.13 tons at 10% penetration. The implementation cost ranged from $315,000 to $9.5 million with different electricity rate structures and different penetration scenarios. Reduction of ambient particulate matter concentration was highly variable: the average reduction of all five population centers was negligible at 1% penetration, .83% at 5% penetration, and 1.42% at 10% penetration.

scholarly journals Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50

2021 ◽  
Vol 14 (3) ◽  
pp. 1681-1697
Author(s):  
Jianhui Jiang ◽  
Imad El Haddad ◽  
Sebnem Aksoyoglu ◽  
Giulia Stefenelli ◽  
Amelie Bertrand ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Experimental Studies ◽  
Organic Aerosol ◽  
Basis Set ◽  
Reference Scenario ◽  
Air Quality Model ◽  
Quality Model ◽  
The Balkans ◽  
Wall Loss

Abstract. Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models that use parameters obtained from chamber experiments. In this study, a box model with a volatility basis set (VBS) scheme was developed, and the secondary organic aerosol (SOA) yields with vapor wall loss correction were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9–4.9 and leads to better agreement with measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The model results from the VBS schemes with standard (VBS_BASE) and vapor-wall-loss-corrected parameters (VBS_WLS), as well as the traditional two-product approach, were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM) or aerosol mass spectrometer (AMS) stations in the winter of 2011. An additional reference scenario, VBS_noWLS, was also developed using the same parameterization as VBS_WLS except for the SOA yields, which were optimized by assuming there is no vapor wall loss. The VBS_WLS generally shows the best performance for predicting OA among all OA schemes and reduces the mean fractional bias from −72.9 % (VBS_BASE) to −1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µg m−3), which is 106.6 % and 26.2 % higher than VBS_BASE and VBS_noWLS, respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ∼80 % (in the Balkans). VBS_WLS also leads to better agreement between the modeled SOA fraction in OA (fSOA) and the estimated values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in parameterizations based on laboratory studies for a wider range of chamber conditions and field observations with higher spatial and temporal coverage.

Downscaling EDGAR emissions to local emission sectors for Switzerland

2021 ◽  
Author(s):  
Jacinta Edebeli ◽  
Curdin Spirig ◽  
Julien Anet
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Measurement Data ◽  
Pilot Project ◽  
Air Quality Model ◽  
Quality Model ◽  
Emission Data ◽  
Traffic Pattern ◽  
Pollutant Concentrations ◽  
The Impact

<p>The fifth version of the Emission Database for Global Atmospheric Research (EDGAR 5.0) provides an impressive inventory of various pollutants. Pollutants from different emission sectors are available with daily, monthly and yearly temporal profiles at a high global resolution of 0.1°×0.1°. Although this resolution has been sufficient for regional air quality studies, the emissions appeared to be too coarse for local air quality studies in areas with complex topography. With Switzerland as a case study, we present our approach for downscaling EDGAR emission data to a much finer resolution of 0.02°×0.02° with the aim of modelling local air quality.</p><p>We downscaled the EDGAR emissions using a combination of GIS tools including QGIS, ArcGIS, and a series of python scripts. We obtained the surface coverage of different land use features within the defined EDGAR emission sectors from Open Street Map (OSM) using the <em>QuickOSM</em> tool in QGIS. With the calculated local surface area coverage of the emissions sectors, we downscaled the EDGAR inventory data within ArcGIS using a set of developed Arcpy script tools.</p><p>The outcome was a much finer resolved emission dataset which we fed into the WRF-CHEM air quality model within a pilot project. A comparison of the modelled pollutant concentrations using the two datasets (original EDGAR data and the downscaled data) shows an improved agreement between the downscaled dataset and the measurement data.</p><p>Studies investigating the impact of urbanization, land use change or traffic pattern on air quality may benefit from our downscaling solution, which, thanks to the global coverage of OSM, can be globally applied.</p>

scholarly journals Influence of biomass burning vapor wall loss correction on modeling organic aerosols in Europe by CAMx v6.50

2020 ◽  
Author(s):  
Jianhui Jiang ◽  
Imad El-Haddad ◽  
Sebnem Aksoyoglu ◽  
Giulia Stefenelli ◽  
Amelie Bertrand ◽  
...  
Keyword(s):  
Air Quality ◽  
Biomass Burning ◽  
Experimental Studies ◽  
Organic Aerosol ◽  
Basis Set ◽  
Reference Scenario ◽  
Air Quality Model ◽  
Quality Model ◽  
Wall Loss ◽  
Product Approach

Abstract. Increasing evidence from experimental studies suggests that the losses of semi-volatile vapors to the chamber walls could be responsible for the underestimation of organic aerosol (OA) in air quality models which use parameters obtained from the chamber experiments. In this study, a box model with volatility basis set (VBS) scheme was developed and the secondary organic aerosol (SOA) yields with vapor wall loss corrected were optimized by a genetic algorithm based on advanced chamber experimental data for biomass burning. The vapor wall loss correction increases the SOA yields by a factor of 1.9–4.9, and leads to a better agreement with the measured OA for 14 chamber experiments under different temperatures and emission loads. To investigate the influence of vapor wall loss correction on regional OA simulations, the optimized parameterizations (SOA yields, emissions of intermediate-volatility organic compounds from biomass burning, and enthalpy of vaporization) were implemented in the regional air quality model CAMx (Comprehensive Air Quality Model with extensions). The modeled results from the standard and vapor wall loss corrected VBS schemes, as well as the traditional two-product approach were compared and evaluated by OA measurements from five Aerodyne aerosol chemical speciation monitor (ACSM)/aerosol mass spectrometer (AMS) stations in the winter of 2011. The vapor wall loss corrected VBS (VBS_WLS) generally shows the best performance for predicting OA among all OA schemes, and reduces the mean fractional bias from −72.9 % (with the standard VBS (VBS_BASE)) to −1.6 % for the winter OA. In Europe, the VBS_WLS produces the highest domain average OA in winter (2.3 µg m−3), which is 106.6 % and 26.2 % higher than the standard VBS and the reference scenario (VBS_noWLS, same parameterization as VBS_WLS, except with the default yields without vapor wall loss correction), respectively. Compared to VBS_noWLS, VBS_WLS leads to an increase in SOA by up to ~ 80 % in Romania. VBS_WLS also leads to a better agreement between the modeled SOA fraction in OA (fSOA) and the estimated measured values in the literature. The substantial influence of vapor wall loss correction on modeled OA in Europe highlights the importance of further improvements in the parameterizations based on laboratory studies with a wider range of chamber conditions and field observations with higher spatial and temporal coverage.

scholarly journals Changes in PM<sub>2.5</sub> concentrations and their sources in the US from 1990 to 2010

2021 ◽  
Vol 21 (22) ◽  
pp. 17115-17132
Author(s):  
Ksakousti Skyllakou ◽  
Pablo Garcia Rivera ◽  
Brian Dinkelacker ◽  
Eleni Karnezi ◽  
Ioannis Kioutsioukis ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Biomass Burning ◽  
Transport Model ◽  
Organic Aerosol ◽  
Road Transport ◽  
Air Quality Model ◽  
Chemical Transport Model ◽  
Quality Model ◽  
So2 Emissions ◽  
The Us

Abstract. Significant reductions in emissions of SO2, NOx, volatile organic compounds (VOCs), and primary particulate matter (PM) took place in the US from 1990 to 2010. We evaluate here our understanding of the links between these emissions changes and corresponding changes in concentrations and health outcomes using a chemical transport model, the Particulate Matter Comprehensive Air Quality Model with Extensions (PMCAMx), for 1990, 2001, and 2010. The use of the Particle Source Apportionment Algorithm (PSAT) allows us to link the concentration reductions to the sources of the corresponding primary and secondary PM. The reductions in SO2 emissions (64 %, mainly from electric-generating units) during these 20 years have dominated the reductions in PM2.5, leading to a 45 % reduction in sulfate levels. The predicted sulfate reductions are in excellent agreement with the available measurements. Also, the reductions in elemental carbon (EC) emissions (mainly from transportation) have led to a 30 % reduction in EC concentrations. The most important source of organic aerosol (OA) through the years according to PMCAMx is biomass burning, followed by biogenic secondary organic aerosol (SOA). OA from on-road transport has been reduced by more than a factor of 3. On the other hand, changes in biomass burning OA and biogenic SOA have been modest. In 1990, about half of the US population was exposed to annual average PM2.5 concentrations above 20 µg m−3, but by 2010 this fraction had dropped to practically zero. The predicted changes in concentrations are evaluated against the observed changes for 1990, 2001, and 2010 in order to understand whether the model represents reasonably well the corresponding processes caused by the changes in emissions.

scholarly journals Modelling winter organic aerosol at the European scale with CAMx: evaluation and source apportionment with a VBS parameterization based on novel wood burning smog chamber experiments og

2016 ◽  
Author(s):  
Giancarlo Ciarelli ◽  
Sebnem Aksoyoglu ◽  
Imad El Haddad ◽  
Emily A. Bruns ◽  
Monica Crippa ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Organic Aerosol ◽  
Basis Set ◽  
Formation Mechanisms ◽  
Smog Chamber ◽  
Air Quality Model ◽  
Quality Model ◽  
Residential Combustion ◽  
Wood Burning

Abstract. We evaluated a modified VBS (Volatility Basis Set) scheme to treat biomass burning-like organic aerosol (BBOA) implemented in CAMx (Comprehensive Air Quality Model with extensions). The updated scheme was parameterized with novel wood combustion smog chamber experiments using a hybrid VBS framework that accounts for a mixture of wood burning organic aerosol precursors and their further functionalization and fragmentation in the atmosphere. The new scheme was evaluated for one of the winter EMEP intensive campaigns (February-March 2009) against aerosol mass spectrometer (AMS) measurements performed at 11 sites in Europe. We found a considerable improvement for the modelled organic aerosol (OA) mass compared to our previous model application with the mean fractional bias (MFB) reduced from −61 % to −29 %. We performed model-based source apportionment studies and compared results against positive matrix factorization (PMF) analysis performed on OA AMS data. Both model and observations suggest that OA was mainly of secondary origin at almost all sites. Modelled secondary organic aerosol (SOA) contributions to total OA varied from 32 to 88 % (with an average contribution of 62 %) and absolute concentrations were generally under-predicted. Modelled primary hydrocarbon-like organic aerosol (HOA) and primary biomass burning-like aerosol (BBOA) fractions contributed to a lesser extent (HOA from 3 to 30 %, and BBOA from 1 to 39 %) with average contributions of 13 and 25 %, respectively. Modelled BBOA fractions was found to represent 12 to 64 % of the total residential heating related OA, with increasing contributions at stations located in the northern part of the domain. Source apportionment studies were performed to assess the contribution of residential and non-residential combustion precursors to the total SOA. Non-residential combustion and transportation precursors contributed about 30–40 % to SOA formation (with increasing contributions at urban and near industrialized sites) whereas residential combustion (mainly related to wood burning) contributed to a larger extent, around 60–70 %. Contributions to OA from residential combustion precursors in different volatility ranges were also assessed: our results indicate that residential combustion gas-phase precursors in the semi-volatile range contributed from 6 to 30 %, with higher contributions predicted at stations located in the southern part of the domain. On the other hand, higher volatility residential combustion precursors contributed from 15 to 38 % with no specific gradient among the stations. The new retrieved parameterization, although leading to a better agreement between model and observations, still under-predicts the SOA fraction suggesting remaining uncertainties in the new scheme or that other sources and/or formation mechanisms need to be elucidated.

scholarly journals Quantifying primary and secondary humic-like substances in urban aerosol based on emission source characterization and a source-oriented air quality model

2019 ◽  
Vol 19 (4) ◽  
pp. 2327-2341 ◽  
Author(s):  
Xinghua Li ◽  
Junzan Han ◽  
Philip K. Hopke ◽  
Jingnan Hu ◽  
Qi Shu ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Biomass Burning ◽  
Coal Combustion ◽  
Water Soluble ◽  
Aerosol Formation ◽  
Source Characterization ◽  
Air Quality Model ◽  
Quality Model ◽  
Coal Burning ◽  
Residential Coal

Abstract. Humic-like substances (HULIS) are a mixture of high-molecular-weight, water-soluble organic compounds that are widely distributed in atmospheric aerosol. Their sources are rarely studied quantitatively. Biomass burning is generally accepted as a major primary source of ambient humic-like substances (HULIS) with additional secondary material formed in the atmosphere. However, the present study provides direct evidence that residential coal burning is also a significant source of ambient HULIS, especially in the heating season in northern China based on source measurements, ambient sampling and analysis, and apportionment with source-oriented CMAQ modeling. Emission tests show that residential coal combustion produces 5 % to 24 % of the emitted organic carbon (OC) as HULIS carbon (HULISc). Estimation of primary emissions of HULIS in Beijing indicated that residential biofuel and coal burning contribute about 70 % and 25 % of annual primary HULIS, respectively. Vehicle exhaust, industry, and power plant contributions are negligible. The average concentration of ambient HULIS in PM2.5 was 7.5 µg m−3 in urban Beijing and HULIS exhibited obvious seasonal variations with the highest concentrations in winter. HULISc accounts for 7.2 % of PM2.5 mass, 24.5 % of OC, and 59.5 % of water-soluble organic carbon. HULIS are found to correlate well with K+, Cl−, sulfate, and secondary organic aerosol, suggesting its sources include biomass burning, coal combustion, and secondary aerosol formation. Source apportionment based on CMAQ modeling shows residential biofuel and coal burning and secondary formation are important sources of ambient HULIS, contributing 47.1 %, 15.1 %, and 38.9 %, respectively.

scholarly journals Sources of organic aerosols in Europe: A modelling study using CAMx with modified volatility basis set scheme

2019 ◽  
Author(s):  
Jianhui Jiang ◽  
Sebnem Aksoyoglu ◽  
Imad El-Haddad ◽  
Giancarlo Ciarelli ◽  
Hugo A. C. Denier van der Gon ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Basis Set ◽  
Anthropogenic Sources ◽  
Air Quality Model ◽  
Quality Model ◽  
Wood Burning ◽  
Gasoline Vehicles

Abstract. Source apportionment of organic aerosols (OA) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models act as potential tools to identify OA components and sources at high spatial and temporal resolution, however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional air quality model Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and contained more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modelled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in the previous studies which strengthens our confidence in our modelled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 μg m−3 to −0.4 μg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 %–42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %) while biogenic emissions contributed ~55 % to OA during summer in Europe on average. In both seasons, the other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (~5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modelling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.

Sign in / Sign up

Export Citation Format

Share Document