251 citations as recorded by crossref.

1. Model calculations of the effects of present and future emissions of air pollutants from shipping in the Baltic Sea and the North Sea J. Jonson et al. 10.5194/acp-15-783-2015
2. From Monodisciplinary via Multidisciplinary to an Interdisciplinary Approach Investigating Air-Sea Interactions – a SOLAS Initiative C. Marandino et al. 10.1080/08920753.2020.1773208
3. Ship exhaust emission estimation and analysis using Automatic Identification System data: The west area of Shenzhen port, China, as a case study L. Gan et al. 10.1016/j.ocecoaman.2022.106245
4. Statistical trajectory-distance metric for nautical route clustering analysis using cross-track distance W. Yoo & T. Kim 10.1093/jcde/qwac024
5. Analysis of the uncertainty of the AIS-based bottom-up approach for estimating ship emissions X. Chen & J. Yang 10.1016/j.marpolbul.2023.115968
6. Volatility of a Ship’s Emissions in the Baltic Sea Using Modelling and Measurements in Real-World Conditions O. Kangasniemi et al. 10.3390/atmos14071175
7. Effects of ship emissions on air quality in the Baltic Sea region simulated with three different chemistry transport models M. Karl et al. 10.5194/acp-19-7019-2019
8. Deep collaborative learning model for port-air pollutants prediction using automatic identification system S. Sim et al. 10.1016/j.trd.2022.103431
9. Shipborne nutrient dynamics and impact on the eutrophication in the Baltic Sea U. Raudsepp et al. 10.1016/j.scitotenv.2019.03.264
10. Developing a new green ship approach for flue gas emission estimation of bulk carriers L. Bilgili & U. Celebi 10.1016/j.measurement.2018.02.002
11. Projections of shipping emissions and the related impact on air pollution and human health in the Nordic region C. Geels et al. 10.5194/acp-21-12495-2021
12. The impact of nitrogen and sulfur emissions from shipping on the exceedance of critical loads in the Baltic Sea region S. Jutterström et al. 10.5194/acp-21-15827-2021
13. Establishment of the Sustainable Ecosystem for the Regional Shipping Industry Based on System Dynamics X. Geng et al. 10.3390/su9050742
14. Ship’s response strategy to emission control areas: From the perspective of sailing pattern optimization and evasion strategy selection L. Li et al. 10.1016/j.tre.2019.101835
15. Future Ship Emission Scenarios with a Focus on Ammonia Fuel D. Schwarzkopf et al. 10.3390/atmos14050879
16. Shipping emission inventories in China's Bohai Bay, Yangtze River Delta, and Pearl River Delta in 2018 Z. Wan et al. 10.1016/j.marpolbul.2019.110882
17. Ships going slow in reducing their NOx emissions: changes in 2005–2012 ship exhaust inferred from satellite measurements over Europe K. Boersma et al. 10.1088/1748-9326/10/7/074007
18. An AIS-based high-resolution ship emission inventory and its uncertainty in Pearl River Delta region, China C. Li et al. 10.1016/j.scitotenv.2016.07.219
19. High-spatiotemporal-resolution ship emission inventory of China based on AIS data in 2014 D. Chen et al. 10.1016/j.scitotenv.2017.07.051
20. COVID-19 impact on maritime traffic and corresponding pollutant emissions. The case of the Port of Barcelona A. Mujal-Colilles et al. 10.1016/j.jenvman.2022.114787
21. AIS-Based Estimation of Hydrogen Demand and Self-Sufficient Fuel Supply Systems for RoPax Ferries A. Fitz et al. 10.3390/en15103482
22. Urban population exposure to NO<sub><i>x</i></sub> emissions from local shipping in three Baltic Sea harbour cities – a generic approach M. Ramacher et al. 10.5194/acp-19-9153-2019
23. Effects of strengthening the Baltic Sea ECA regulations J. Jonson et al. 10.5194/acp-19-13469-2019
24. Estimation of exhaust emission from ocean-going vessels in Hong Kong P. Yau et al. 10.1016/j.scitotenv.2012.03.092
25. Implementation of different big-leaf canopy reduction functions in the Biogenic Emission Inventory System (BEIS) and their impact on concentrations of oxidized nitrogen species in northern Europe J. Arndt et al. 10.1016/j.atmosenv.2018.07.035
26. A spatially explicit data-driven approach to calculating commodity-specific shipping emissions per vessel W. Schim van der Loeff et al. 10.1016/j.jclepro.2018.09.053
27. Commuter Exposure to Black Carbon, Fine Particulate Matter and Particle Number Concentration in Ferry and at the Pier in Istanbul . Onat et al. 10.3390/atmos10080439
28. Advances in air quality research – current and emerging challenges R. Sokhi et al. 10.5194/acp-22-4615-2022
29. Environmental effects of Maersk Line’s global container shipping operation N. Tran & T. Tran 10.1080/16258312.2022.2159277
30. Impact analysis of ECA policies on ship trajectories and emissions J. Weng et al. 10.1016/j.marpolbul.2022.113687
31. Development of exhaust emission factors for vessels: A review and meta-analysis of available data A. Grigoriadis et al. 10.1016/j.aeaoa.2021.100142
32. Hierarchical Bayesian propulsion power models — A simplified example with cruise ships A. Solonen et al. 10.1016/j.oceaneng.2023.115226
33. Shipping and algae emissions have a major impact on ambient air mixing ratios of non-methane hydrocarbons (NMHCs) and methanethiol on Utö Island in the Baltic Sea H. Hellén et al. 10.5194/acp-24-4717-2024
34. Emission factors of SO<sub>2</sub>, NO<sub><i>x</i></sub> and particles from ships in Neva Bay from ground-based and helicopter-borne measurements and AIS-based modeling J. Beecken et al. 10.5194/acp-15-5229-2015
35. Natural hazards and extreme events in the Baltic Sea region A. Rutgersson et al. 10.5194/esd-13-251-2022
36. Ship emissions reduction using weather ship routing optimisation C. Borén et al. 10.1177/14750902221082901
37. Ship emissions and the use of current air cleaning technology: contributions to air pollution and acidification in the Baltic Sea B. Claremar et al. 10.5194/esd-8-901-2017
38. The Future Impact of Shipping Emissions on Air Quality in Europe under Climate Change M. Russo et al. 10.3390/atmos14071126
39. Big maritime data for the Baltic Sea with a focus on the winter navigation system M. Lensu & F. Goerlandt 10.1016/j.marpol.2019.02.038
40. Air pollutants from shipping: Costs of NOx emissions to the Baltic Sea I. Gren et al. 10.1016/j.jenvman.2021.113824
41. Numerical Modeling of Air Pollutants and Greenhouse Gases Emissions in Intermodal Transport Chains M. Ramalho & T. Santos 10.3390/jmse9060679
42. Parameterizing the vertical downward dispersion of ship exhaust gas in the near field R. Badeke et al. 10.5194/acp-21-5935-2021
43. Impact of Disruption on Ship Emissions in Port: Case of Pandemic in Long Beach Z. He et al. 10.3390/su15097215
44. The influence of the waterjet propulsion system on the ships' energy consumption and emissions inventories V. Durán-Grados et al. 10.1016/j.scitotenv.2018.02.291
45. Mining Channel Water Depth Information From IoT-Based Big Automated Identification System Data for Safe Waterway Navigation Z. He et al. 10.1109/ACCESS.2018.2883421
46. A Comprehensive Inventory of the Ship Traffic Exhaust Emissions in the Baltic Sea from 2006 to 2009 J. Jalkanen et al. 10.1007/s13280-013-0389-3
47. The Study of Ship Exhaust Emission Monitoring System Based on UAV 晓. 于 10.12677/DSC.2023.121001
48. The impact of ship emissions on air quality and human health in the Gothenburg area – Part 1: 2012 emissions L. Tang et al. 10.5194/acp-20-7509-2020
49. Methodologies for estimating shipping emissions and energy consumption: A comparative analysis of current methods J. Moreno-Gutiérrez et al. 10.1016/j.energy.2015.04.083
50. Significant contribution of inland ships to the total NOx emissions along the Yangtze River X. Zhang et al. 10.5194/acp-23-5587-2023
51. Characterization of OMI tropospheric NO<sub>2</sub> over the Baltic Sea region I. Ialongo et al. 10.5194/acp-14-7795-2014
52. Impact of the emissions of international sea traffic on airborne deposition to the Baltic Sea and concentrations at the coastline⁎⁎The research has received funding from the European Regional Development Fund, Central Baltic INTERREG IV A programme within the SNOOP project. M. Hongisto 10.5697/oc.56-2.349
53. Environmental accounting for Arctic shipping – A framework building on ship tracking data from satellites A. Mjelde et al. 10.1016/j.marpolbul.2014.07.013
54. The evolution of shipping emissions and the costs of regulation changes in the northern EU area L. Johansson et al. 10.5194/acp-13-11375-2013
55. Modelling of ship engine exhaust emissions in ports and extensive coastal waters based on terrestrial AIS data – An Australian case study L. Goldsworthy & B. Goldsworthy 10.1016/j.envsoft.2014.09.009
56. Reducing GHG emissions from ships in port areas H. Winnes et al. 10.1016/j.rtbm.2015.10.008
57. AIS-Based Scenario Simulation for the Control and Improvement of Ship Emissions in Ports S. Kao et al. 10.3390/jmse10020129
58. Shipping log data based container ship fuel efficiency modeling Q. Meng et al. 10.1016/j.trb.2015.11.007
59. Data analytics for fuel consumption management in maritime transportation: Status and perspectives R. Yan et al. 10.1016/j.tre.2021.102489
60. Evaluation of emission reduction strategies for berthing containerships: A case study of the Shekou Container Terminal Z. Wan et al. 10.1016/j.jclepro.2021.126820
61. AIS in maritime research M. Svanberg et al. 10.1016/j.marpol.2019.103520
62. Single-Vessel Plume Dispersion Simulation: Method and a Case Study Using CALPUFF in the Yantian Port Area, Shenzhen (China) S. Bai et al. 10.3390/ijerph17217831
63. Effect of ice class to vessel fuel consumption based on real-life MRV data M. Heikkilä et al. 10.1016/j.tranpol.2024.01.014
64. Estimation of Vessel Emissions Inventory in Qingdao Port Based on Big data Analysis X. Sun et al. 10.3390/sym10100452
65. Atmospheric Emissions in Ports Due to Maritime Traffic in Mexico G. Fuentes García et al. 10.3390/jmse9111186
66. An AIS-based approach to calculate atmospheric emissions from the UK fishing fleet J. Coello et al. 10.1016/j.atmosenv.2015.05.011
67. Health and climate impacts of ocean-going vessels in East Asia H. Liu et al. 10.1038/nclimate3083
68. Shipping emissions in the Iberian Peninsula and the impacts on air quality R. Nunes et al. 10.5194/acp-20-9473-2020
69. Estimating emissions from tourism activities M. Russo et al. 10.1016/j.atmosenv.2019.117048
70. System for Identifying Ships Using High-Sulfur-Content Fuel Oil in Port Waters X. Peng et al. 10.1061/(ASCE)EE.1943-7870.0001755
71. The impact of port congestion on shipping emissions in Chinese ports X. Li et al. 10.1016/j.trd.2024.104091
72. Phosphorus flows on ships: Case study from the Baltic Sea M. Wilewska-Bien et al. 10.1177/1475090218761761
73. The impact of the Ukraine conflict in internal and external grain transport costs G. Fernandes et al. 10.1016/j.trip.2023.100803
74. WITHDRAWN: Assessment of COVID-19 pandemic effects on ship pollutant emissions in major international seaports J. Liu et al. 10.1016/j.envres.2021.112246
75. Inland port vessel emissions inventory based on Ship Traffic Emission Assessment Model–Automatic Identification System Y. Zhang et al. 10.1177/1687814017712878
76. Potential impact of shipping on air pollution in the Mediterranean region – a multimodel evaluation: comparison of photooxidants NO2 and O3 L. Fink et al. 10.5194/acp-23-1825-2023
77. Estimating Costs and Benefits of Sulphur Content Limits in Ship Fuel J. Kalli et al. 10.1080/15568318.2013.808389
78. Significant increase of aerosol number concentrations in air masses crossing a densely trafficked sea area S. Kecorius et al. 10.1016/j.oceano.2015.08.001
79. Assessment of the impact of ship emissions on air quality based on a complete annual emission inventory using AIS data for the port of Naples D. Toscano et al. 10.1016/j.oceaneng.2021.109166
80. Assessment of atmospheric pollutant emissions with maritime energy strategies using bayesian simulations and time series forecasting J. Liu et al. 10.1016/j.envpol.2020.116068
81. Characteristics and ship traffic source identification of air pollutants in China's largest port M. Zhao et al. 10.1016/j.atmosenv.2012.10.007
82. Global assessment of shipping emissions in 2015 on a high spatial and temporal resolution L. Johansson et al. 10.1016/j.atmosenv.2017.08.042
83. A multimodel evaluation of the potential impact of shipping on particle species in the Mediterranean Sea L. Fink et al. 10.5194/acp-23-10163-2023
84. Air quality forecasting of along-route ship emissions in realistic meteo-marine scenarios A. Orlandi et al. 10.1016/j.oceaneng.2023.116464
85. A review on carbon emissions of global shipping S. Deng & Z. Mi 10.1007/s44312-023-00001-2
86. Impact of AIS Data Thinning on Ship Air Pollutant Emissions Inventories Y. Tian et al. 10.3390/atmos13071135
87. Air quality and radiative impacts of Arctic shipping emissions in the summertime in northern Norway: from the local to the regional scale L. Marelle et al. 10.5194/acp-16-2359-2016
88. Ship carbon dioxide emission estimation in coastal domestic emission control areas using high spatial-temporal resolution data: A China case H. Li et al. 10.1016/j.ocecoaman.2022.106419
89. Investigating the Effects of Environmentally Friendly Additives on the Exhaust Gas Composition and Fuel Consumption of an Internal Combustion Engine R. Krakowski & K. Witkowski 10.3390/app14072956
90. Spatial and temporal allocation of ship exhaust emissions in Australian coastal waters using AIS data: Analysis and treatment of data gaps B. Goldsworthy 10.1016/j.atmosenv.2017.05.028
91. Greenhouse gas emissions from ships in ports – Case studies in four continents L. Styhre et al. 10.1016/j.trd.2017.04.033
92. Decadal evolution of ship emissions in China from 2004 to 2013 by using an integrated AIS-based approach and projection to 2040 C. Li et al. 10.5194/acp-18-6075-2018
93. Modeling of the Concentrations of Ultrafine Particles in the Plumes of Ships in the Vicinity of Major Harbors M. Karl et al. 10.3390/ijerph17030777
94. A sampling method for calculating regional ship emission inventories X. Peng et al. 10.1016/j.trd.2020.102617
95. A comprehensive ship weather routing system using CMEMS products and A* algorithm M. Grifoll et al. 10.1016/j.oceaneng.2022.111427
96. Importance of the Panama canal in the reduction of CO2 emissions from maritime transport L. Carral et al. 10.1080/15568318.2019.1632994
97. Carbon footprints: Uncovering multilevel spatiotemporal changes of ship emissions during 2019–2021 in the U.S. N. Mou et al. 10.1016/j.scitotenv.2023.169395
98. The contribution of ship emissions to air pollution in the North Sea regions V. Matthias et al. 10.1016/j.envpol.2010.02.013
99. Emission inventory for harbour-related activities: comparison of two distinct bottom-up methodologies S. Sorte et al. 10.1007/s11869-021-00982-3
100. Ubiquity of hazardous airborne substances on passenger ferries A. Targino et al. 10.1016/j.jhazmat.2021.127133
101. A calculation algorithm for ship pollutant gas emissions and diffusions based on real-time meteorological conditions and its application S. He et al. 10.1016/j.oceaneng.2023.115825
102. A big data approach to improving the vehicle emission inventory in China F. Deng et al. 10.1038/s41467-020-16579-w
103. Ship emission inventory and its impact on the PM 2.5 air pollution in Qingdao Port, North China D. Chen et al. 10.1016/j.atmosenv.2017.07.021
104. Airborne emission measurements of SO<sub>2</sub> , NO<sub>x</sub> and particles from individual ships using a sniffer technique J. Beecken et al. 10.5194/amt-7-1957-2014
105. Estimation and spatio-temporal analysis of ship exhaust emission in a port area L. Huang et al. 10.1016/j.oceaneng.2017.06.015
106. Impact of a nitrogen emission control area (NECA) on the future air quality and nitrogen deposition to seawater in the Baltic Sea region M. Karl et al. 10.5194/acp-19-1721-2019
107. Ship fuel sulfur content prediction based on convolutional neural network and ultraviolet camera images K. Cao et al. 10.1016/j.envpol.2021.116501
108. Assessing the costs and environmental benefits of IMO regulations of ship-originated SOx and NOx emissions in the Baltic Sea S. Repka et al. 10.1007/s13280-021-01500-6
109. Spatial and Seasonal Dynamics of Ship Emissions over the Yangtze River Delta and East China Sea and Their Potential Environmental Influence Q. Fan et al. 10.1021/acs.est.5b03965
110. A ship emission modeling system with scenario capabilities D. Schwarzkopf et al. 10.1016/j.aeaoa.2021.100132
111. Underwater Noise Emissions from Ships During 2014-2020 J. Jalkanen et al. 10.2139/ssrn.3951731
112. Model for Estimation of Fuel Consumption of Cruise Ships M. Simonsen et al. 10.3390/en11051059
113. Shipping Remains a Globally Significant Source of Anthropogenic PN Emissions Even after 2020 Sulfur Regulation N. Kuittinen et al. 10.1021/acs.est.0c03627
114. An analysis of an AMSA ship survey and comparison with the Maritime Transport Emission Model (MTEM) R. Smit 10.1016/j.aeaoa.2023.100203
115. Emission performance of major ship classes: An estimation based on a new set of emission factors and realistic activity profile data A. Grigoriadis et al. 10.1088/1755-1315/899/1/012005
116. Vessel weather routing subject to sulfur emission regulation S. Lee et al. 10.1016/j.tre.2023.103235
117. Validation of the estimated ships' emissions through an experimental campaign in port L. Mocerino et al. 10.1016/j.oceaneng.2023.115957
118. Compliance and port air quality features with respect to ship fuel switching regulation: a field observation campaign, SEISO-Bohai Y. Zhang et al. 10.5194/acp-19-4899-2019
119. Calculating ships' real emissions of pollutants and greenhouse gases: Towards zero uncertainties J. Moreno-Gutiérrez & V. Durán-Grados 10.1016/j.scitotenv.2020.141471
120. Particulate exposure onboard ferryboats and relationships with environmental conditions and engine maintenance P. Krecl et al. 10.1016/j.trd.2020.102602
121. Ship emission estimation with high spatial-temporal resolution in the Yangtze River estuary using AIS data J. Weng et al. 10.1016/j.jclepro.2019.119297
122. A review of operational, regional-scale, chemical weather forecasting models in Europe J. Kukkonen et al. 10.5194/acp-12-1-2012
123. Changes in the SO2 Level and PM2.5 Components in Shanghai Driven by Implementing the Ship Emission Control Policy X. Zhang et al. 10.1021/acs.est.9b03315
124. Green shipping: using AIS data to assess global emissions T. Hensel et al. 10.1007/s00550-020-00498-x
125. Health Impact of Air Pollution from Shipping in the Baltic Sea: Effects of Different Spatial Resolutions in Sweden N. Mwase et al. 10.3390/ijerph17217963
126. Teasing out the detail: How our understanding of marine AIS data can better inform industries, developments, and planning R. Shelmerdine 10.1016/j.marpol.2014.12.010
127. Modeling chronic oil pollution from ships S. Liubartseva et al. 10.1016/j.marpolbul.2023.115450
128. Exploring the effectiveness of ECA policies in reducing pollutant emissions from merchant ships in Shanghai port waters K. Shi et al. 10.1016/j.marpolbul.2020.111164
129. Cruise ship emissions in Norwegian waters: A geographical analysis M. Simonsen et al. 10.1016/j.jtrangeo.2019.05.014
130. Port-city exhaust emission model: An application to cruise and ferry operations in Las Palmas Port M. Tichavska & B. Tovar 10.1016/j.tra.2015.05.021
131. Comparison of the Impact of Ship Emissions in Northern Europe and Eastern China D. Schwarzkopf et al. 10.3390/atmos13060894
132. Estimation of atmospheric emissions from maritime activity in the Veracruz port, Mexico G. Fuentes García et al. 10.1080/10962247.2021.1902421
133. Impact of trajectory simplification methods on modeling carbon dioxide emissions from ships T. Balcer et al. 10.1016/j.oceaneng.2024.117905
134. Modelling of ship resistance and power consumption for the global fleet: The MariTEAM model Y. Kim et al. 10.1016/j.oceaneng.2023.114758
135. Analysis of the Anthropogenic and Biogenic NOx Emissions Over 2008–2017: Assessment of the Trends in the 30 Most Populated Urban Areas in Europe A. Fortems‐Cheiney et al. 10.1029/2020GL092206
136. Ice and AIS: ship speed data and sea ice forecasts in the Baltic Sea U. Löptien & L. Axell 10.5194/tc-8-2409-2014
137. Assigning machinery power values for estimating ship exhaust emissions: Comparison of auxiliary power schemes B. Goldsworthy & L. Goldsworthy 10.1016/j.scitotenv.2018.12.014
138. Review of Top-Down Method to Determine Atmospheric Emissions in Port. Case of Study: Port of Veracruz, Mexico G. Fuentes García et al. 10.3390/jmse10010096
139. Effects of the SARS-CoV-2 Pandemic on CO2 Emissions in the Port Areas of the Strait of Messina C. Marino et al. 10.3390/su15129587
140. Air emissions from ships in port: Does regulation make a difference? M. Tichavska et al. 10.1016/j.tranpol.2017.03.003
141. Field test of available methods to measure remotely SO<sub>x</sub> and NO<sub>x</sub> emissions from ships J. Balzani Lööv et al. 10.5194/amt-7-2597-2014
142. Modelling spatial dispersion of contaminants from shipping lanes in the Baltic Sea I. Maljutenko et al. 10.1016/j.marpolbul.2021.112985
143. Estimation of ship size from satellite optical image using elliptic characteristics of ship periphery J. Park et al. 10.1080/01431161.2019.1711246
144. Dynamic calculation of ship exhaust emissions based on real-time AIS data L. Huang et al. 10.1016/j.trd.2020.102277
145. Estimating ship emissions based on AIS data for port of Tianjin, China D. Chen et al. 10.1016/j.atmosenv.2016.08.086
146. Measurement report: Characterization of uncertainties in fluxes and fuel sulfur content from ship emissions in the Baltic Sea J. Walden et al. 10.5194/acp-21-18175-2021
147. Big data–driven carbon emission traceability list and characteristics of ships in maritime transportation—a case study of Tianjin Port P. Wang et al. 10.1007/s11356-023-27104-z
148. Monitoring of compliance with fuel sulfur content regulations through unmanned aerial vehicle (UAV) measurements of ship emissions F. Zhou et al. 10.5194/amt-12-6113-2019
149. Technical note: Intermittent reduction of the stratospheric ozone over northern Europe caused by a storm in the Atlantic Ocean M. Sofiev et al. 10.5194/acp-20-1839-2020
150. Health risk assessment of engine exhaust emissions within Australian ports: a case study of Port of Brisbane S. Jahangiri et al. 10.1080/14660466.2019.1564427
151. Impact of ship-borne nitrogen deposition on the Gulf of Finland ecosystem: an evaluation**The work presented in this study was jointly funded by the European Regional Development Fund, Central Baltic INTERREG IV A Programme within the project SNOOP and the European Union’s Seventh Framework Programme FP/2007–2011 within the projects ECOSUPPORT, grant agreement No. 217246. U. Raudsepp et al. 10.5697/oc.55-4.837
152. Estimation of shipping emissions using vessel Long Range Identification and Tracking data A. Alessandrini et al. 10.1080/17445647.2017.1411842
153. Perspectives on shipping emissions and their impacts on the surface ocean and lower atmosphere: An environmental-social-economic dimension Z. Shi et al. 10.1525/elementa.2023.00052
154. Refinement of a model for evaluating the population exposure in an urban area J. Soares et al. 10.5194/gmd-7-1855-2014
155. Modelling of ships as a source of underwater noise J. Jalkanen et al. 10.5194/os-14-1373-2018
156. Effect of Seasonal Flow Field on Inland Ship Emission Assessment: A Case Study of Ferry H. Huang et al. 10.3390/su12187484
157. A data-driven study of IMO compliant fuel emissions with consideration of black carbon aerosols C. Ji & M. El-Halwagi 10.1016/j.oceaneng.2020.108241
158. A ship emission diffusion model based on translation calculation and its application on Huangpu River in Shanghai S. He et al. 10.1016/j.cie.2022.108569
159. Application of AIS data in service vessel activity description in the Gulf of Mexico M. Kaiser & S. Narra 10.1057/mel.2014.25
160. Combined machine learning and physics-based models for estimating fuel consumption of cargo ships B. Guo et al. 10.1016/j.oceaneng.2022.111435
161. Quantification of lightning-induced nitrogen oxide emissions over Europe J. Arndt et al. 10.1016/j.atmosenv.2018.12.059
162. A comprehensive review on the prediction of ship energy consumption and pollution gas emissions K. Wang et al. 10.1016/j.oceaneng.2022.112826
163. Estimating the effect of biofouling on ship shaft power based on sensor measurements H. Bakka et al. 10.1080/09377255.2022.2159108
164. Harnessing the power of Machine learning for AIS Data-Driven maritime Research: A comprehensive review Y. Yang et al. 10.1016/j.tre.2024.103426
165. CO2 emissions in a global container shipping network and policy implications N. Tran & J. Lam 10.1057/s41278-022-00242-w
166. The impact of marine shipping and its DECA control on air quality in the Pearl River Delta, China H. Liu et al. 10.1016/j.scitotenv.2018.01.033
167. Reduction of CO 2 emissions with automatic mooring systems. The case of the port of Santander A. Ortega Piris et al. 10.1016/j.apr.2017.07.002
168. Air pollution emission inventory using national high-resolution spatial parameters for the Nordic countries and analysis of PM2.5 spatial distribution for road transport and machinery and off-road sectors V. Paunu et al. 10.5194/essd-16-1453-2024
169. Air quality monitoring in communities of the Canadian Arctic during the high shipping season with a focus on local and marine pollution A. Aliabadi et al. 10.5194/acp-15-2651-2015
170. Shipping emissions and their impacts on air quality in China Y. Zhang et al. 10.1016/j.scitotenv.2016.12.098
171. Constraints on ship NO<sub>x</sub> emissions in Europe using GEOS-Chem and OMI satellite NO<sub>2</sub> observations G. Vinken et al. 10.5194/acp-14-1353-2014
172. Maritime NOx Emissions Over Chinese Seas Derived From Satellite Observations J. Ding et al. 10.1002/2017GL076788
173. Measurement and Modeling of Ship-Related Ultrafine Particles and Secondary Organic Aerosols in a Mediterranean Port City M. Karl et al. 10.3390/toxics11090771
174. Ship emissions of SO<sub>2</sub> and NO<sub>2</sub>: DOAS measurements from airborne platforms N. Berg et al. 10.5194/amt-5-1085-2012
175. Method Study on Establishing of Ship Sewage Pollutants Discharging Inventory Based on AIS R. Chen et al. 10.1088/1755-1315/237/2/022018
176. The impact of ship emissions on air quality and human health in the Gothenburg area – Part II: Scenarios for 2040 M. Ramacher et al. 10.5194/acp-20-10667-2020
177. A framework for real-time monitoring of energy efficiency of marine vessels H. Chi et al. 10.1016/j.energy.2017.12.088
178. Analysis of ship emission characteristics under real-world conditions in China C. Wang et al. 10.1016/j.oceaneng.2019.106615
179. Costs of air pollutants from shipping: a meta-regression analysis I. Gren et al. 10.1080/01441647.2020.1723733
180. Contribution of ship emissions to the concentration and deposition of air pollutants in Europe S. Aksoyoglu et al. 10.5194/acp-16-1895-2016
181. Comparison of large-scale ship exhaust emissions across multiple resolutions: From annual to hourly data B. Goldsworthy et al. 10.1016/j.atmosenv.2019.116829
182. Comparative analysis between different methods for calculating on-board ship's emissions and energy consumption based on operational data J. Moreno-Gutiérrez et al. 10.1016/j.scitotenv.2018.09.045
183. A bibliometric analysis of scientific research trends in monitoring systems for measuring ship emissions L. Egan et al. 10.1007/s11356-023-26723-w
184. Cleaner fuels for ships provide public health benefits with climate tradeoffs M. Sofiev et al. 10.1038/s41467-017-02774-9
185. Methods for identifying aged ship plumes and estimating contribution to aerosol exposure downwind of shipping lanes S. Ausmeel et al. 10.5194/amt-12-4479-2019
186. Impact of maritime transport emissions on coastal air quality in Europe M. Viana et al. 10.1016/j.atmosenv.2014.03.046
187. Methodology to Assess the Technoeconomic Impacts of the EU Fit for 55 Legislation Package in Relation to Shipping G. Mallouppas et al. 10.3390/jmse10081006
188. Sea Port SO2 Atmospheric Emissions Influence on Air Quality and Exposure at Veracruz, Mexico G. Fuentes García et al. 10.3390/atmos13121950
189. Two-phase optimal solutions for ship speed and trim optimization over a voyage using voyage report data Y. Du et al. 10.1016/j.trb.2019.02.004
190. Energy efficiency with the application of Virtual Arrival policy H. Jia et al. 10.1016/j.trd.2017.04.037
191. Port-Related Emissions, Environmental Impacts and Their Implication on Green Traffic Policy in Shanghai Y. Zhou et al. 10.3390/su12104162
192. Methodology for Predicting Maritime Traffic Ship Emissions Using Automatic Identification System Data J. Ribeiro da Silva et al. 10.3390/jmse12020320
193. Policy change driven by an AIS-assisted marine emission inventory in Hong Kong and the Pearl River Delta S. Ng et al. 10.1016/j.atmosenv.2012.07.070
194. Source apportionment of PM<sub>2.5</sub> in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements R. Healy et al. 10.5194/acp-10-9593-2010
195. How to recognize and measure the economic impacts of environmental regulation: The Sulphur Emission Control Area case A. Lähteenmäki-Uutela et al. 10.1016/j.jclepro.2017.03.224
196. Governing shipping externalities: Baltic ports in the process of SOx emission reduction D. Gritsenko & J. Yliskylä-Peuralahti 10.1186/2212-9790-12-10
197. A Big-Data-Based Experimental Platform for Green Shipping Monitoring and Its Teaching Application Y. Zhao et al. 10.3390/su15118674
198. Impacts of the COVID-19 epidemic on merchant ship activity and pollution emissions in Shanghai port waters K. Shi & J. Weng 10.1016/j.scitotenv.2021.148198
199. Estimating air emissions from ships: Meta-analysis of modelling approaches and available data sources A. Miola & B. Ciuffo 10.1016/j.atmosenv.2011.01.046
200. Trajectory Data Compression Algorithm Based on Ship Navigation State and Acceleration Variation J. Gao et al. 10.3390/jmse11010216
201. Atmospheric emissions of European SECA shipping: long-term projections J. Kalli et al. 10.1007/s13437-013-0050-9
202. Costs and benefits of low-sulphur fuel standard for Baltic Sea shipping J. Antturi et al. 10.1016/j.jenvman.2016.09.064
203. An improved method for optimizing detection bands of marine exhaust SO2 concentration in ultraviolet dual-band measurements based on signal-to-noise ratio Z. Zhang et al. 10.1016/j.apr.2022.101479
204. Dynamic NOx emission factors for main engines of bulk carriers K. Duan et al. 10.1016/j.trd.2022.103290
205. Analysis of emission characteristics associated with vessel activities states in port waters X. Gao et al. 10.1016/j.marpolbul.2024.116329
206. Microscopic Approach to Evaluate Energy Consumption and Emissions from Ships B. Ciuffo & A. Miola 10.3141/2273-06
207. Trends in Vessel Atmospheric Emissions in the Central Mediterranean over the Last 10 Years and during the COVID-19 Outbreak M. Saliba et al. 10.3390/jmse9070762
208. A multi-pollutant and multi-sectorial approach to screening the consistency of emission inventories P. Thunis et al. 10.5194/gmd-15-5271-2022
209. Observing network effect of shipping emissions from space: A natural experiment in the world’s busiest port S. Liu et al. 10.1093/pnasnexus/pgad391
210. Bayesian probabilistic forecasting for ship emissions J. Liu & O. Duru 10.1016/j.atmosenv.2020.117540
211. Extension of an assessment model of ship traffic exhaust emissions for particulate matter and carbon monoxide J. Jalkanen et al. 10.5194/acp-12-2641-2012
212. Underwater noise emissions from ships during 2014–2020 J. Jalkanen et al. 10.1016/j.envpol.2022.119766
213. A comprehensive inventory of ship traffic exhaust emissions in the European sea areas in 2011 J. Jalkanen et al. 10.5194/acp-16-71-2016
214. Environmental and Economic Evaluation of Dual-Fuel Engine Investment of a Container Ship Ç. Karatuğ et al. 10.1007/s11804-023-00381-3
215. Effects of vertical ship exhaust plume distributions on urban pollutant concentration – a sensitivity study with MITRAS v2.0 and EPISODE-CityChem v1.4 R. Badeke et al. 10.5194/gmd-15-4077-2022
216. Modeling emissions for three-dimensional atmospheric chemistry transport models V. Matthias et al. 10.1080/10962247.2018.1424057
217. Risk assessment of bilge water discharges in two Baltic shipping lanes K. Magnusson et al. 10.1016/j.marpolbul.2017.09.035
218. Establishment of Inland Ship Air Pollution Emission Inventory Based on Power Method Correction Model Z. Peng et al. 10.3390/su141811188
219. Estimated health impacts from maritime transport in the Mediterranean region and benefits from the use of cleaner fuels M. Viana et al. 10.1016/j.envint.2020.105670
220. Airborne nitrogen deposition to the Baltic Sea: Past trends, source allocation and future projections M. Gauss et al. 10.1016/j.atmosenv.2021.118377
221. Challenges of decarbonizing global maritime container shipping toward net-zero emissions B. Lu et al. 10.1038/s44183-023-00018-6
222. Human impacts and their interactions in the Baltic Sea region M. Reckermann et al. 10.5194/esd-13-1-2022
223. Emissions Assessment of Container Ships Sailing under Off-Design Conditions C. Borén et al. 10.3390/jmse11101983
224. The influence of spatiality on shipping emissions, air quality and potential human exposure in the Yangtze River Delta/Shanghai, China J. Feng et al. 10.5194/acp-19-6167-2019
225. Calculating a Drop in Carbon Emissions in the Strait of Gibraltar (Spain) from Domestic Shipping Traffic Caused by the COVID-19 Crisis V. Durán-Grados et al. 10.3390/su122410368
226. Ship emissions around China under gradually promoted control policies from 2016 to 2019 X. Wang et al. 10.5194/acp-21-13835-2021
227. Influence of Ship Emissions on Urban Air Quality: A Comprehensive Study Using Highly Time-Resolved Online Measurements and Numerical Simulation in Shanghai Z. Liu et al. 10.1021/acs.est.6b03834
228. An innovative model to design extreme emission control areas (ECAs) by considering ship's evasion strategy L. Li et al. 10.1016/j.ocecoaman.2022.106289
229. International maritime regulation decreases sulfur dioxide but increases nitrogen oxide emissions in the North and Baltic Sea W. Van Roy et al. 10.1038/s43247-023-01050-7
230. Speed Profiles for Improvement of Maritime Emission Estimation P. Yau et al. 10.1089/ees.2011.0399
231. Diffusion and Superposition of Ship Exhaust Gas in Port Area Based on Gaussian Puff Model: A Case Study on Shenzhen Port L. Gan et al. 10.3390/jmse11020330
232. The impact of shipping CO2 emissions from marine traffic in Western Singapore Straits during COVID-19 Y. Ju & C. Hargreaves 10.1016/j.scitotenv.2021.148063
233. Operational-based decarbonization of container ports: The case of Ningbo-Zhoushan Port C. Ezeh et al. 10.1080/15568318.2023.2197859
234. A numerical approach to assess air pollution by ship engines in manoeuvring mode and fuel switch conditions P. Iodice et al. 10.1177/0958305X17734050
235. An improved emission inventory method for estimating engine exhaust emissions from ships S. Jahangiri et al. 10.1016/j.serj.2018.08.005
236. Shanghai Port Carbon Emission Measurement Study L. Zhang 10.54097/fbem.v2i1.154
237. Decarbonization of Maritime Transport: Is There Light at the End of the Tunnel? H. Psaraftis & C. Kontovas 10.3390/su13010237
238. Modelling of discharges from Baltic Sea shipping J. Jalkanen et al. 10.5194/os-17-699-2021
239. Environmental cost and eco-efficiency from vessel emissions in Las Palmas Port M. Tichavska & B. Tovar 10.1016/j.tre.2015.09.002
240. Framework for the environmental impact assessment of operational shipping J. Moldanová et al. 10.1007/s13280-021-01597-9
241. A New Perspective at the Ship-Air-Sea-Interface: The Environmental Impacts of Exhaust Gas Scrubber Discharge S. Endres et al. 10.3389/fmars.2018.00139
242. Local Standards, Behavioral Adjustments, and Welfare: Evaluating California’s Ocean-Going Vessel Fuel Rule R. Klotz & J. Berazneva 10.1086/717585
243. Quantifying ship-borne emissions in Istanbul Strait with bottom-up and machine-learning approaches C. Ay et al. 10.1016/j.oceaneng.2022.111864
244. Use of AIS data for the environmental characterization of world cruise ship traffic I. Vicente-Cera et al. 10.1080/15568318.2019.1575494
245. The costs and benefits of sulphur reduction measures: Sulphur scrubbers versus marine gas oil L. Jiang et al. 10.1016/j.trd.2013.12.005
246. Atmospheric ship emissions in ports: A review. Correlation with data of ship traffic D. Toscano & F. Murena 10.1016/j.aeaoa.2019.100050
247. A genetic algorithm-based grey-box model for ship fuel consumption prediction towards sustainable shipping L. Yang et al. 10.1007/s10479-019-03183-5
248. Analyzing cruise ship itineraries patterns and vessels diversity in ports of the European maritime region: A hierarchical clustering approach I. Vicente-Cera et al. 10.1016/j.jtrangeo.2020.102731
249. Improving maritime traffic emission estimations on missing data with CRBMs A. Gutierrez-Torre et al. 10.1016/j.engappai.2020.103793
250. The significance of incorporating unidentified vessels into AIS-based ship emission inventory Y. Zhang et al. 10.1016/j.atmosenv.2018.12.055
251. Assessment of shipping emissions on four ports of Portugal R. Nunes et al. 10.1016/j.envpol.2017.08.112