Ships, ports and particulate air pollution - an analysis of recent studies
© Mueller et al; licensee BioMed Central Ltd. 2011
Received: 24 August 2011
Accepted: 5 December 2011
Published: 5 December 2011
The duration of use is usually significantly longer for marine vessels than for roadside vehicles. Therefore, these vessels are often powered by relatively old engines which may propagate air pollution. Also, the quality of fuel used for marine vessels is usually not comparable to the quality of fuels used in the automotive sector and therefore, port areas may exhibit a high degree of air pollution. In contrast to the multitude of studies that addressed outdoor air pollution due to road traffic, only little is known about ship-related air pollution. Therefore the present article aims to summarize recent studies that address air pollution, i.e. particulate matter exposure, due to marine vessels. It can be stated that the data in this area of research is still largely limited. Especially, knowledge on the different air pollutions in different sea areas is needed.
Measurements of PM concentration in coastal regions
In a multi-year study conducted from 2003 to 2007 by Pandolfi et al., ambient PM10 and PM2.5 data were collected at four sampling locations around the Bay of Algeciras in southern Spain. To identify major PM sources - with particular attention paid to the quantification of total shipping emissions - positive matrix factorization models were used . After that, the impact of the emissions from the harbor of Algeciras and vessel traffic at the Western entrance of Mediterranean Sea were quantified. For the estimation of shipping dependent PM emissions, ambient levels of vanadium (V), nickel (Ni), lanthanum (La) and cerium (Ce) were used as markers in this study . According to the scientists, the shipping emissions were characterized by La/Ce ratios between 0.6 and 0.8 and V/Ni ratios around 3 for both PM10 and PM2.5. It was estimated that the direct contribution from shipping in the Bay of Algeciras PM10 was 1.4 to 2.6 μg/m3 (3-7%) and PM2.5 concentration was 1.2 to 2.3 μg/m3 (5-10%). The study demonstrated further, that the total contribution from shipping reached 4.7 μg/m3 (13%) for PM10 and 4.1 μg/m3 (17%) for PM2.5 .
In another study Agrawal et al. investigated the impact of primary fine particulate matter PM2.5 from ship emissions within the Southern California Air Basin. In this study also V and Ni were used as marker for the shipping emissions . V and Ni were measured in stack emissions of in-use ocean-going vessels (OGVs) and then compared with ambient measurements made at 10 monitoring stations throughout Southern California. The researcher could demonstrate that the transition metals V and Ni are robust markers for the combustion of heavy fuel oil in OGVs . In this respect, it was found that ambient measurements of fine particulate V and Ni within Southern California are shown to decrease inversely with increased distance from the ports of Los Angeles and Long Beach. To estimate the primary PM2.5 contributions from OGVs at the multiple monitoring locations the researcher used normalized emission rates. In relation to the total PM2.5 Agrawal et al. found that primary PM2.5 contributions from OGVs range from 8.8% at the monitoring location closest to the port to 1.4% monitored 80 km inland . The scientists concluded that the results of their analysis will be useful in determining the impacts of primary particulate emissions from OGVs upon worldwide communities downwind of port operations.
In the same region of Southern California, Ault et al. studied the impact of emissions during regional shipping transport events . Atmospheric aerosol measurements during time periods with regional transport showed an increase in 0.5-1 μm sized single particles with unique signatures including soot, metals (i.e., vanadium, iron, and nickel), sulfate, and nitrate in La Jolla, California . Ault et al. assumed as well that these particles can be attributed to primary emissions from residual oil sources such as ship engine exhaust. However, the authors of this study state that these particles could also be attributed to emissions of refineries and traffic in the port region as well as to secondary processing during the transport. The results of these measurements showed 2-4 times higher PM2.5 concentrations than typical average concentrations from local sources . Ault et al. therefore conclude that unless significant regulations are imposed these emission sources will become even more important to California air quality as cars and truck emissions. Elevation of PM2.5 concentration in coastal regions due to ship engine emissions was as well reported by a Canadian study carried out by Poplawski et al. They investigated the association between community level concentrations of PM2.5 with cruise ships traffic in Victoria, British Columbia . They obtained data from 2005 to 2008 at a close air quality network site (3.5 km from the study area) and took continuous measurements in the James Bay community over a three-month period during the 2009 cruise ship season. Next to PM2.5 they also investigated concentrations of some gaseous air pollutants. The measurements downwind the port showed an elevation of PM2.5 concentration on weekends when cruise ship activity reached the weekly maximum .
In Turkey, Deniz et al. investigated in 2010 within two adjacent studies the shipping emissions in coastal regions with heavy shipping traffic. The first study was carried out in the Candarli Gulf and the second study at the Ambarli Port [25, 26]. The objective of the studies was to estimate the amount of major atmospheric components emitted from heavy ship engines. Next to some gaseous air pollutants the studies focused mainly on PM with no distinction between different PM-fractions. The first study in the Candarli Gulf PM investigated the annual shipping emissions from 7520 ships during the year of 2007 and the researcher estimated 57.4 tons per year (t/y) for PM . In the second study Deniz et al. calculated the exhaust emissions from ships at the Ambarli Port by utilizing data acquired in 2005. The total emission from ships at this port was estimated with 36 t/y for PM by the scientists .
Healy et al. characterized in a 2009 study single particles from in-port ship emissions in the Port of Cork in Ireland . In this study, the size and composition of freshly emitted individual ship exhaust particles was investigated. For the measurement an aerosol time-of-flight mass spectrometer was used (ATOFMS) co-located with a suite of real-time instrumentations at a site in the Port of Cork. Clustering the collected spectra by using the K-means algorithm, they could identify a unique ship exhaust class containing internally mixed elemental and organic carbon, sodium, calcium, iron, vanadium, nickel and sulfate . During the three week measurement period in August 2008 the Healy et al. group could observe over twenty sharp emission events for this particle type. Coincident increases in mass concentrations of sulfate, elemental carbon and PM2.5 were also observed during these events in this study. Furthermore, simultaneous scanning mobility particle sizer (SMPS) measurements were used. The results of this SMPS monitoring showed that the vast majority of freshly emitted ship exhaust particles is present in the ultrafine mode (< 100 nm diameter) . A second particle class constituted of internally mixed organic carbon, elemental carbon, ammonium and sulfate. The scientists tentatively attributed this second particle class to aged or regionally transported ship exhaust. On basis of these findings, Healy et al. suggested that ATOFMS single particle mass spectra may be useful in determining the contribution of local shipping traffic to air quality in port cities, when used in conjunction with other air quality monitoring instrumentation .
Effect of ship type and fuel type on the PM concentration in ship emissions
In a recent article Johnson et al. investigated size-resolved emission factors for particle number (EF (PN)) and mass (EF (PM)) for 734 individual ship passages. This study was carried out in Sweden near the entrance to the port of Gothenburg . In their experiments an extractive sampling method of the passing ship plumes was used and next to gaseous emissions (CO2) the particle number/mass were measured with high time resolution (1 Hz). The place of measurement was situated in an emission control area (ECA) and near to populated areas. The investigation resulted in an average EF (PN) and EF (PM) of 2.55 +/- 0.11 × 1016 (kg fuel) -1 and 2050 +/- 110 mg (kg fuel)-1, respectively . For ships with multiple passages, a great reproducibility for the determined EF was shown and the EF(PN) peaked at particle sizes similar to 35 nm . Interestingly, compared to ships with diesel engines, ships equipped with gas turbine showed smaller particle sizes and less mass. On average 36 to 46% of the emitted particles by number were non-volatile .
In a 2011, a real-time study by Jayaram et al. assessed gaseous emissions and PM2.5 emissions of a ship engine powered with different fuel types . The authors measured regulated and unregulated emissions from an in-use marine propulsion engine (EPA Tier 2) on a ferry in a real-time fashion. For comparison with the certification standards and across biodiesel blends the investigated engine was operated following the loads in ISO 8178-4 E3 cycle. Furthermore, real-time measurements were made during a typical cruise in the bay. As a result Jayaram et al. were able to demonstrate that in-use PM2.5 emission factors were within the not-to-exceed standard for Tier 2 marine engines. The comparison of the fuels showed for PM2.5 a reduction of 16% on ships fuelled with Biodiesel B20 and of 25% on ships fuelled with Biodiesel B50 . Furthermore, reductions in the volume mean diameter and total number concentration in the accumulation mode with increasing biodiesel blends was observed. These findings were consistent with trends found in gravimetric PM2.5 mass emissions . In other studies similar trends of particle size and number reduction in accumulation mode with biodiesel was reported [30, 31]. Jayaram et al. were able to demonstrate the important effects of ocean/bay currents on emissions. Due to this effect, PM2.5 mass increased about 6-fold and ultrafine particles (UFP) disappeared . Based on the findings, the authors conclude that for the development of emission inventories the effect of ocean currents should be considered. In this respect, in-use measurements may provide necessary data for accurate inventories .
In regard to an approaching fuel switch within the marine sector, a study was conducted by Winnes et al. with the aim to investigate the effects of different fuel types on ship exhaust gas composition and emission factors with a focus on particles . The field emission measurements were carried out on the 4500-kW four-stroke main engine on-board a product tanker. In the study, heavy fuel oil and marine gas oil were tested on the same engine for comparable load settings . In this study PM with no distinction of different fraction was measured. The authors reported for heavy fuel oil generally higher specific PM emissions than for marine gas oil but for the smallest size-fraction containing particles 0.30- 0.40 μm in diameter, the opposite was observed . The authors' conclusion of these findings is that further regulation is needed to reduce small-sized particles and hence negative health effects of particles from ships.
Characterization of the PM composition in ship emissions
Only few published studies focused on the characterization of the PM composition in ship emissions. One project was an international study carried out by Moldanova et al. (2009) that investigated PM in emissions from a large ship diesel engine . The engine was fueled with heavy fuel oil (HFO). The investigation of the emitted PM included mass, size distribution, chemical composition and microphysical structure of the PM. The study assessed an emission factor for PM of 5.3 g (kg fuel) -1. Further, the mass size distribution showed increased particles of the accumulation mode (mean diameter of 0.5 μm) and the coarse mode (around 7 μm) . The investigation demonstrated a domination of organic carbon (OC), ash and sulfate in the PM composition whereas elemental carbon (EC) composed only a few percent. It is to point out that increase of PM in the exhaust upon cooling, was associated with increase of OC and sulfate. Interestingly, cooling of the exhaust as well showed an effect on the quantity of polycyclic aromatic hydrocarbons (PAHs) absorbed on the surface of particulates. Whereas the analysis of the adsorbed phase in the cooled exhaust presented a rich mixture of PAH species with molecular mass between 178 and 300 atomic mass units (amu) the hot exhaust showed only 4 amu of PAH . In the performed microstructure and elemental analysis of ship combustion residuals three following distinct morphological structures with different chemical composition were found: soot aggregates, significantly metal polluted; char particles, clean or containing minerals; mineral and/or ash particles . In addition, the researcher could observe organic carbon particles of unburned fuel or/and lubricating oil origin were. It should be pointed out that hazardous constituents from the combustion of heavy fuel oil (V, Ni, Ca, and Fe (iron)) were observed in the PM samples as well. These metals were also used in other studies as marker for ship emissions as described above.
In a 2009 study carried out by Murphy et al. the particulate exhaust from a modern container ship burning heavy fuel oil was characterized . The ship emissions were measured shipboard and airborne with a focus on the chemical composition and water-uptake behavior of particulate matter in the exhaust. The following results were obtained: The mass ratio of particulate organic carbon to sulfate was 0.23 +/- 0.03 at the base of the ship stack and 0.30 +/- 0.01 in the airborne exhaust plume . The additional organic mass in the airborne plume was concentrated largely in particles below 100 nm in diameter . The organic to sulfate mass ratio in the exhaust aerosol remained constant during the first hour of plume dilution into the marine boundary layer . The authors also reported that the mass spectrum of the organic fraction of the exhaust aerosol appeared to be predominantly hydrocarbon-like organic (HOA) material . The background aerosol contained a lower organic mass fraction than the fresh plume with much more oxidized organic component . With a conducted analysis of the water-uptake behavior of particulate in the exhaust the researcher showed that a volume-weighted mixing rule is able to accurately predict hygroscopic growth factors in the background aerosol. However, measured and calculated growth factors do not agree for aerosols in the ship exhaust plume. The researchers estimated the particle number emission factor at 1.3 × 1016 (kg fuel) -1, with less than 1/10 of the particles having diameters above 100 nm and 24% of particles (> 10 nm in diameter) activate into cloud droplets at 0.3% supersaturation .
A third study that aimed to characterize the PM composition in ship emissions focused on the urban area of Venice in Italy. Contini et al. estimated in this study the direct influence of ship traffic on atmospheric PM2.5 and PM10. Next to PM, the study also estimated fifteen PAHs. The sample collection was performed over the summer when ship traffic is expected to be at a maximum and on three sites in that area . From the received results the researcher concluded that the PM daily concentrations are not sufficiently detailed for the evaluation. Therefore they developed a new methodology, based on high temporal resolution measurements coupled with wind direction information and the database of ship passages of the Harbor Authority of Venice . PM10 and PM2.5 were monitored with optical detectors operating at a high temporal resolution . With this new setup, the study showed that direct contribution of ships traffic to PM2.5 and to PM10 ranges from 1% up to 8% .
We thank G. Volante for expert help. Publication of this review was partly supported by EUGT e. V.
- Elfman L, Riihimaki M, Pringle J, Walinder R: Influence of horse stable environment on human airways. J Occup Med Toxicol 2009, 4: 10. 10.1186/1745-6673-4-10PubMed CentralView ArticlePubMedGoogle Scholar
- Groneberg DA, Fischer A: Occupational medicine and toxicology. J Occup Med Toxicol 2006, 1: 1. 10.1186/1745-6673-1-1PubMed CentralView ArticleGoogle Scholar
- Groneberg DA, Nowak D, Wussow A, Fischer A: Chronic cough due to occupational factors. J Occup Med Toxicol 2006, 1: 3. 10.1186/1745-6673-1-3PubMed CentralView ArticlePubMedGoogle Scholar
- Groneberg DA, Scutaru C, Lauks M, Takemura M, Fischer TC, Kolzow S, van Mark A, Uibel S, Wagner U, Vitzthum K, et al.: Mobile Air Quality Studies (MAQS)-an international project. J Occup Med Toxicol 2010, 5: 8. 10.1186/1745-6673-5-8PubMed CentralView ArticlePubMedGoogle Scholar
- Groneberg-Kloft B, Kraus T, Mark A, Wagner U, Fischer A: Analysing the causes of chronic cough: relation to diesel exhaust, ozone, nitrogen oxides, sulphur oxides and other environmental factors. J Occup Med Toxicol 2006, 1: 6. 10.1186/1745-6673-1-6PubMed CentralView ArticlePubMedGoogle Scholar
- Sierra-Vargas MP, Guzman-Grenfell AM, Blanco-Jimenez S, Sepulveda-Sanchez JD, Bernabe-Cabanillas RM, Cardenas-Gonzalez B, Ceballos G, Hicks JJ: Airborne particulate matter PM2.5 from Mexico City affects the generation of reactive oxygen species by blood neutrophils from asthmatics: an in vitro approach. J Occup Med Toxicol 2009, 4: 17. 10.1186/1745-6673-4-17PubMed CentralView ArticlePubMedGoogle Scholar
- Six Common Air Pollutants[http://www.epa.gov/air/urbanair/]
- Europäische Union: Richtlinie 2008/50/EG des Europäischen Parlaments und des Rates - über Luftqualität und saubere Luft für Europa. Book Richtlinie 2008/50/EG des Europäischen Parlaments und des Rates - über Luftqualität und saubere Luft für Europa 2008, 9–31. (Editor ed.^eds.). pp. 9–31. CityGoogle Scholar
- Atkinson RW, Anderson HR, Sunyer J, Ayres J, Baccini M, Vonk JM, Boumghar A, Forastiere F, Forsberg B, Touloumi G, et al.: Acute effects of particulate air pollution on respiratory admissions - Results from APHEA 2 project. Am J Respir Crit Care Med 2001, 164: 1860–1866.View ArticlePubMedGoogle Scholar
- Brook RD, Rajagopalan S, Pope CA, Brook JR, Bhatnagar A, Diez-Roux AV, Holguin F, Hong YL, Luepker RV, Mittleman MA, et al.: Particulate Matter Air Pollution and Cardiovascular Disease An Update to the Scientific Statement From the American Heart Association. Circulation 2010, 121: 2331–2378. 10.1161/CIR.0b013e3181dbece1View ArticlePubMedGoogle Scholar
- Dominici F, Peng RD, Bell ML, Pham L, McDermott A, Zeger SL, Samet JM: Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. Jama-Journal of the American Medical Association 2006, 295: 1127–1134. 10.1001/jama.295.10.1127View ArticleGoogle Scholar
- Gavett SH, Koren HS: The role of particulate matter in exacerbation of atopic asthma. Int Arch Allergy Immunol 2001, 124: 109–112. 10.1159/000053685View ArticlePubMedGoogle Scholar
- Gehring U, Heinrich J, Kramer U, Grote V, Hochadel M, Sugiri D, Kraft M, Rauchfuss K, Eberwein HG, Wichmann HE: Long-term exposure to ambient air pollution and cardiopulmonary mortality in women. Epidemiology 2006, 17: 545–551. 10.1097/01.ede.0000224541.38258.87View ArticlePubMedGoogle Scholar
- Ko FWS, Hui DSC: Outdoor air pollution: impact on chronic obstructive pulmonary disease patients. Curr Opin Pulm Med 2009, 15: 150–157. 10.1097/MCP.0b013e32832185eeView ArticlePubMedGoogle Scholar
- Pope CA, Kanner RE: Acute effects of pm-10 pollution on pulmonary-function of smokers with mild-to-moderate chronic obstructive pulmonary-disease. Am Rev Respir Dis 1993, 147: 1336–1340.View ArticlePubMedGoogle Scholar
- Sint T, Donohue JF, Ghio AJ: Ambient air pollution particles and the acute exacerbation of chronic obstructive pulmonary disease. Inhal Toxicol 2008, 20: 25–29. 10.1080/08958370701758759View ArticlePubMedGoogle Scholar
- Sunyer J, Basagana X: Particles, and not gases, are associated with the risk of death in patients with chronic obstructive pulmonary disease. Int J Epidemiol 2001, 30: 1138–1140. 10.1093/ije/30.5.1138View ArticlePubMedGoogle Scholar
- Tecer LH, Alagha O, Karaca F, Tuncel G, Eldes N: Particulate matter (PM2.5, PM10–2.5, and PM10) and children's hospital admissions for asthma and respiratory diseases: A bidirectional case-crossover study. Journal of Toxicology and Environmental Health-Part a-Current Issues 2008, 71: 512–520. 10.1080/15287390801907459View ArticleGoogle Scholar
- Vidale S, Bonanomi A, Guidotti M, Arnaboldi M, Sterzi R: Air pollution positively correlates with daily stroke admission and in hospital mortality: a study in the urban area of Como, Italy. Neurol Sci 2010, 31: 179–182.View ArticlePubMedGoogle Scholar
- Yeatts K, Svendsen E, Creason J, Alexis N, Herbst M, Scott J, Kupper L, Williams R, Neas L, Cascio W, et al.: Coarse particulate matter (PM2.5–10) affects heart rate variability, blood lipids, and circulating eosinophils in adults with asthma. Environ Health Perspect 2007, 115: 709–714. 10.1289/ehp.9499PubMed CentralView ArticlePubMedGoogle Scholar
- Pandolfi M, Gonzalez-Castanedo Y, Alastuey A, de la Rosa JD, Mantilla E, de la Campa AS, Querol X, Pey J, Amato F, Moreno T: Source apportionment of PM(10) and PM(2.5) at multiple sites in the strait of Gibraltar by PMF: impact of shipping emissions. Environ Sci Pollut Res 2011, 18: 260–269. 10.1007/s11356-010-0373-4View ArticleGoogle Scholar
- Agrawal H, Eden R, Zhang X, Fine PM, Katzenstein A, Miller JW, Ospital J, Teffera S, Cocker DR III: Primary Particulate Matter from Ocean-Going Engines in the Southern California Air Basin. Environ Sci Technol 2009, 43: 5398–5402. 10.1021/es8035016View ArticlePubMedGoogle Scholar
- Ault AP, Moore MJ, Furutani H, Prather KA: Impact of Emissions from the Los Angeles Port Region on San Diego Air Quality during Regional Transport Events. Environ Sci Technol 2009, 43: 3500–3506. 10.1021/es8018918View ArticlePubMedGoogle Scholar
- Poplawski K, Setton E, McEwen B, Hrebenyk D, Graham M, Keller P: Impact of cruise ship emissions in Victoria, BC, Canada. Atmos Environ 2011, 45: 824–833. 10.1016/j.atmosenv.2010.11.029View ArticleGoogle Scholar
- Deniz C, Kilic A: Estimation and Assessment of Shipping Emissions in the Region of Ambarli Port, Turkey. Environ Prog Sustain Energy 2010, 29: 107–115.Google Scholar
- Deniz C, Kilic A, Civkaroglu G: Estimation of shipping emissions in Candarli Gulf, Turkey. Environ Monit Assess 2010, 171: 219–228. 10.1007/s10661-009-1273-2View ArticlePubMedGoogle Scholar
- Healy RM, O'Connor IP, Hellebust S, Allanic A, Sodeau JR, Wenger JC: Characterisation of single particles from in-port ship emissions. Atmos Environ 2009, 43: 6408–6414. 10.1016/j.atmosenv.2009.07.039View ArticleGoogle Scholar
- Jonsson AM, Westerlund J, Hallquist M: Size-resolved particle emission factors for individual ships. Geophys Res Lett 2011., 38:Google Scholar
- Jayaram V, Agrawal H, Welch WA, Miller JW, Cocker DR: Real-Time Gaseous, PM and Ultrafine Particle Emissions from a Modern Marine Engine Operating on Biodiesel. Environ Sci Technol 2011, 45: 2286–2292. 10.1021/es1026954View ArticlePubMedGoogle Scholar
- Heikkila J, Virtanen A, Ronkko T, Keskinen J, Aakko-Saksa P, Murtonen T: Nanoparticle Emissions from a Heavy-Duty Engine Running on Alternative Diesel Fuels. Environ Sci Technol 2009, 43: 9501–9506. 10.1021/es9013807View ArticlePubMedGoogle Scholar
- Jung H, Kittelson DB, Zachariah MR: Characteristics of SME biodiesel-fueled diesel particle emissions and the kinetics of oxidation. Environ Sci Technol 2006, 40: 4949–4955. 10.1021/es0515452View ArticlePubMedGoogle Scholar
- Winnes H, Fridell E: Particle Emissions from Ships: Dependence on Fuel Type. J Air Waste Manage Assoc 2009, 59: 1391–1398.View ArticleGoogle Scholar
- Moldanova J, Fridell E, Popovicheva O, Demirdjian B, Tishkova V, Faccinetto A, Focsa C: Characterisation of particulate matter and gaseous emissions from a large ship diesel engine. Atmos Environ 2009, 43: 2632–2641. 10.1016/j.atmosenv.2009.02.008View ArticleGoogle Scholar
- Murphy SM, Agrawal H, Sorooshian A, Padro LT, Gates H, Hersey S, Welch WA, Jung H, Miller JW, Cocker DR, et al.: Comprehensive Simultaneous Shipboard and Airborne Characterization of Exhaust from a Modern Container Ship at Sea. Environ Sci Technol 2009, 43: 4626–4640. 10.1021/es802413jView ArticlePubMedGoogle Scholar
- Contini D, Gambaro A, Belosi F, De Pieri S, Cairns WRL, Donateo A, Zanotto E, Citron M: The direct influence of ship traffic on atmospheric PM(2.5), PM(10) and PAH in Venice. Journal of Environmental Management 2011, 92: 2119–2129. 10.1016/j.jenvman.2011.01.016View ArticlePubMedGoogle Scholar
- Groneberg-Kloft B, Fischer TC, Quarcoo D, Scutaru C: New quality and quantity indices in science (NewQIS): the study protocol of an international project. J Occup Med Toxicol 2009, 4: 16. 10.1186/1745-6673-4-16PubMed CentralView ArticlePubMedGoogle Scholar
- Vitzthum K, Scutaru C, Musial-Bright L, Quarcoo D, Welte T, Spallek M, Groneberg-Kloft B: Scientometric analysis and combined density-equalizing mapping of environmental tobacco smoke (ETS) research. PLoS One 2010, 5: e11254. 10.1371/journal.pone.0011254PubMed CentralView ArticlePubMedGoogle Scholar
- Groneberg-Kloft B, Kreiter C, Welte T, Fischer A, Quarcoo D, Scutaru C: Interfield dysbalances in research input and output benchmarking: visualisation by density equalizing procedures. International journal of health geographics 2008, 7: 48. 10.1186/1476-072X-7-48PubMed CentralView ArticlePubMedGoogle Scholar
- Scutaru C, Quarcoo D, Takemura M, Welte T, Fischer TC, Groneberg-Kloft B: Density-equalizing mapping and scientometric benchmarking in Industrial Health. Ind Health 2010, 48: 197–203. 10.2486/indhealth.48.197View ArticlePubMedGoogle Scholar
- Groneberg-Kloft B, Quarcoo D, Scutaru C: Quality and quantity indices in science: use of visualization tools. EMBO Rep 2009, 10: 800–803.PubMed CentralView ArticlePubMedGoogle Scholar
- Scutaru C, Quarcoo D, Sakr M, Shami A, Al-Mutawakel K, Vitzthum K, Fischer TC, Zuberbier T, Groneberg-Kloft B: Density-equalizing mapping and scientometric benchmarking of European allergy research. J Occup Med Toxicol 2010, 5: 2. 10.1186/1745-6673-5-2PubMed CentralView ArticlePubMedGoogle Scholar
- Groneberg-Kloft B, Scutaru C, Dinh QT, Welte T, Chung KF, Fischer A, Quarcoo D: Inter-disease comparison of research quantity and quality: bronchial asthma and chronic obstructive pulmonary disease. J Asthma 2009, 46: 147–152. 10.1080/02770900802503115View ArticlePubMedGoogle Scholar
- Kusma B, Scutaru C, Quarcoo D, Welte T, Fischer TC, Groneberg-Kloft B: Tobacco control: visualisation of research activity using density-equalizing mapping and scientometric benchmarking procedures. Int J Environ Res Public Health 2009, 6: 1856–1869. 10.3390/ijerph6061856PubMed CentralView ArticlePubMedGoogle Scholar
- Groneberg-Kloft B, Scutaru C, Fischer A, Welte T, Kreiter C, Quarcoo D: Analysis of research output parameters: density equalizing mapping and citation trend analysis. BMC Health Serv Res 2009, 9: 16. 10.1186/1472-6963-9-16PubMed CentralView ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.