Maritime transportation, widely used both in international transport of goods and touristic purposes, has been identified as a significant source of ultrafine particles (UFP). In-land passenger ferry is a source of UF...Maritime transportation, widely used both in international transport of goods and touristic purposes, has been identified as a significant source of ultrafine particles (UFP). In-land passenger ferry is a source of UFP far less addressed;however, in locations with relatively high frequency of this transportation mode, it is expected that they contribute to an increase of their concentration. Moreover, the negative effects of UFP on human health and environment are known and therefore, monitoring UFP produced by ferries is vital to assess the degree of exposure of who work or live close to ferries’ terminals or downwind to their cruising path. This work aims to study the influence of in-land ferries activities on UFP in the urban/suburban areas near ferries’ terminals and downwind across the cruising path. The UFP monitoring campaign was carried out from September to December 2018 for 19 non-consecutive periods. The sampling sites were chosen in order to maximize measurements under downwind conditions and allow the association between ferry operation and UFP concentration response. Based on data collected, correlation analysis was performed between ferry’s traffic and particle number counting (PNC) of UFP, and also with meteorological variables. Results show an increase in PNC ranging from 25 to 197% during the third minute around a ferry movement and are moderate to positive significant correlations between PNC values and the number of ferry operations (r = 0.79 to r = 0.94), showing that UFP emitted by in-land ferries contributes to PNC increase. Moreover, negative correlations (r = -0.85 to r = -0.93) between PNC and wind intensity were also found.展开更多
In this study,we identified the moisture sources for the precipitation associated with tropical cyclones(TCs)during the rapid intensification(RI)process from 1980 to 2018 by applying a Lagrangian moisture source diagnos...In this study,we identified the moisture sources for the precipitation associated with tropical cyclones(TCs)during the rapid intensification(RI)process from 1980 to 2018 by applying a Lagrangian moisture source diagnostic method.We detected sixteen regions on a global scale for RI events distributed as follows:four in the North Atlantic(NATL),two in the Central and East Pacific Ocean(NEPAC),the North Indian Ocean(NIO)and South Indian Ocean(SIO),and three in the South Pacific Ocean(SPO)and the Western North Pacific Ocean(WNP).The moisture uptake(MU)mostly was from the regions where TCs underwent RI.The Western NATL,tropical NATL,Caribbean Sea,the Gulf of Mexico and the Central America and Mexico landmass supported~85.4%of the precipitating moisture in the NATL,while the latter source and the eastern North Pacific Ocean provided the higher amount of moisture in NEPAC(~84.3%).The Arabian Sea,the Bay of Bengal and the Indian Peninsula were the major moisture sources in NIO,contributing approximately 81.3%.The eastern and western parts of the Indian Ocean supplied most of the atmospheric humidity in SIO(~83.8%).The combined contributions(~87.9%)from the western and central SPO and the Coral Sea were notably higher in SPO.Meanwhile,TCs in the WNP basin mostly received moisture from the western North Pacific Ocean,the Philippine Sea and the China Sea,accounting for 80.1%.The remaining moisture support in each basin came from the summed contributions of the remote sources.Overall,RI TCs gained more moisture up to 2500 km from the cyclone centre than those slow intensification(SI)and the total MU was approximately three times higher during RI than SI.Finally,the patterns of the MU differences respond to the typical pathways of moisture transport in each basin.展开更多
文摘Maritime transportation, widely used both in international transport of goods and touristic purposes, has been identified as a significant source of ultrafine particles (UFP). In-land passenger ferry is a source of UFP far less addressed;however, in locations with relatively high frequency of this transportation mode, it is expected that they contribute to an increase of their concentration. Moreover, the negative effects of UFP on human health and environment are known and therefore, monitoring UFP produced by ferries is vital to assess the degree of exposure of who work or live close to ferries’ terminals or downwind to their cruising path. This work aims to study the influence of in-land ferries activities on UFP in the urban/suburban areas near ferries’ terminals and downwind across the cruising path. The UFP monitoring campaign was carried out from September to December 2018 for 19 non-consecutive periods. The sampling sites were chosen in order to maximize measurements under downwind conditions and allow the association between ferry operation and UFP concentration response. Based on data collected, correlation analysis was performed between ferry’s traffic and particle number counting (PNC) of UFP, and also with meteorological variables. Results show an increase in PNC ranging from 25 to 197% during the third minute around a ferry movement and are moderate to positive significant correlations between PNC values and the number of ferry operations (r = 0.79 to r = 0.94), showing that UFP emitted by in-land ferries contributes to PNC increase. Moreover, negative correlations (r = -0.85 to r = -0.93) between PNC and wind intensity were also found.
基金support from the Xunta de Galicia(Consellería de Cultura,Educacion e Universidade)under grant No.´ED481A2020/193.R.M.T was supported by the Portuguese Science Foundation(FCT)through the project AMOTHEC(https://doi.org/10.54499/DRI/India/0098/2020)EPhysLab members are supported by the SETESTRELO project(grant no.PID2021-122314OB-I00)funded by the Ministerio de Ciencia+4 种基金Innovacion y Universidades,Spain(MICIU/AEI/´10.13039/501100011033)Xunta de Galicia under the Project ED431C2021/44(Programa de Consolidacion e Estructuraci´on´de Unidades de Investigacion Competitivas(Grupos de Ref-´erencia Competitiva)Consellería de Cultura,Educacion e´Universidade)by the European Union‘ERDF A way of making Europe’support provided by CESGA(Centro de Supercomputacion de Galicia)and RES´(Red Espanola de Supercomputaci˜on)。
文摘In this study,we identified the moisture sources for the precipitation associated with tropical cyclones(TCs)during the rapid intensification(RI)process from 1980 to 2018 by applying a Lagrangian moisture source diagnostic method.We detected sixteen regions on a global scale for RI events distributed as follows:four in the North Atlantic(NATL),two in the Central and East Pacific Ocean(NEPAC),the North Indian Ocean(NIO)and South Indian Ocean(SIO),and three in the South Pacific Ocean(SPO)and the Western North Pacific Ocean(WNP).The moisture uptake(MU)mostly was from the regions where TCs underwent RI.The Western NATL,tropical NATL,Caribbean Sea,the Gulf of Mexico and the Central America and Mexico landmass supported~85.4%of the precipitating moisture in the NATL,while the latter source and the eastern North Pacific Ocean provided the higher amount of moisture in NEPAC(~84.3%).The Arabian Sea,the Bay of Bengal and the Indian Peninsula were the major moisture sources in NIO,contributing approximately 81.3%.The eastern and western parts of the Indian Ocean supplied most of the atmospheric humidity in SIO(~83.8%).The combined contributions(~87.9%)from the western and central SPO and the Coral Sea were notably higher in SPO.Meanwhile,TCs in the WNP basin mostly received moisture from the western North Pacific Ocean,the Philippine Sea and the China Sea,accounting for 80.1%.The remaining moisture support in each basin came from the summed contributions of the remote sources.Overall,RI TCs gained more moisture up to 2500 km from the cyclone centre than those slow intensification(SI)and the total MU was approximately three times higher during RI than SI.Finally,the patterns of the MU differences respond to the typical pathways of moisture transport in each basin.
