Road salt emissions: A comparison of measurements and modelling using the NORTRIP road dust emission model

被引:19
|
作者
Denby, B. R. [1 ]
Ketzel, M. [2 ]
Ellermann, T. [2 ]
Stojiljkovic, A. [3 ]
Kupiainen, K. [3 ]
Niemi, J. V. [4 ]
Norman, M. [5 ]
Johansson, C. [5 ,6 ]
Gustafsson, M. [7 ]
Blomqvist, G. [7 ]
Janhall, S. [7 ]
Sundvor, I. [8 ]
机构
[1] Norwegian Meteorol Inst MET, POB 43, N-0313 Blindern, Norway
[2] Aarhus Univ, Dept Environm Sci, Roskilde, Denmark
[3] Nord Envicon Oy, Helsinki, Finland
[4] Helsinki Reg Environm Serv Author HSY, Helsinki, Finland
[5] Environm & Hlth Protect Adm City Stockholm, Stockholm, Sweden
[6] Stockholm Univ, Dept Appl Chem & Environm Sci ACES, Stockholm, Sweden
[7] Swedish Natl Rd & Transport Res Inst VTI, Linkoping, Sweden
[8] Norwegian Inst Air Res NILU, Kjeller, Norway
关键词
Road salt; Non-exhaust emissions; Air quality; Particulate matter; Modelling; SURFACE MOISTURE MODEL; SOURCE APPORTIONMENT; PARTICULATE MATTER; SWITZERLAND; PM10;
D O I
10.1016/j.atmosenv.2016.07.027
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
De-icing of road surfaces is necessary in many countries during winter to improve vehicle traction. Large amounts of salt, most often sodium chloride, are applied every year. Most of this salt is removed through drainage or traffic spray processes but a certain amount may be suspended, after drying of the road surface, into the air and will contribute to the concentration of particulate matter. Though some measurements of salt concentrations are available near roads, the link between road maintenance salting activities and observed concentrations of salt in ambient air is yet to be quantified. In this study the NORTRIP road dust emission model, which estimates the emissions of both dust and salt from the road surface, is applied at five sites in four Nordic countries for ten separate winter periods where daily mean ambient air measurements of salt concentrations are available. The model is capable of reproducing many of the salt emission episodes, both in time and intensity, but also fails on other occasions. The observed mean concentration of salt in PM10, over all ten datasets, is 4.2 mu g/m(3) and the modelled mean is 2.8 mu g/m(3), giving a fractional bias of -0.38. The RMSE of the mean concentrations, over all 10 datasets, is 2.9 mu g/m(3) with an average R-2 of 0.28. The mean concentration of salt is similar to the mean exhaust contribution during the winter periods of 2.6 mu g/m(3). The contribution of salt to the kerbside winter mean PM10 concentration is estimated to increase by 4.1 +/- 3.4 mu g/m(3) for every kg/m(2) of salt applied on the road surface during the winter season. Additional sensitivity studies showed that the accurate logging of salt applications is a prerequisite for predicting salt emissions, as well as good quality data on precipitation. It also highlights the need for more simultaneous measurements of salt loading together with ambient air concentrations to help improve model parameterisations of salt and moisture removal processes. (C) 2016 The Authors. Published by Elsevier Ltd.
引用
收藏
页码:508 / 522
页数:15
相关论文
共 50 条
  • [1] A coupled road dust and surface moisture model to predict non-exhaust road traffic induced particle emissions (NORTRIP). Part 1: Road dust loading and suspension modelling
    Denby, B. R.
    Sundvor, I.
    Johansson, C.
    Pirjola, L.
    Ketzel, M.
    Norman, M.
    Kupiainen, K.
    Gustafsson, M.
    Blomqvist, G.
    Omstedt, G.
    ATMOSPHERIC ENVIRONMENT, 2013, 77 : 283 - 300
  • [2] Modelling road dust emission abatement measures using the NORTRIP model: Vehicle speed and studded tyre reduction
    Norman, M.
    Sundvor, I.
    Denby, B. R.
    Johansson, C.
    Gustafsson, M.
    Blomqvist, G.
    Janhall, S.
    ATMOSPHERIC ENVIRONMENT, 2016, 134 : 96 - 108
  • [3] Calibration of the Swedish studded tyre abrasion wear prediction model with implication for the NORTRIP road dust emission model
    Lundberg, Joacim
    Janhall, Sara
    Gustafsson, Mats
    Erlingsson, Sigurdur
    INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING, 2021, 22 (04) : 432 - 446
  • [4] A coupled road dust and surface moisture model to predict non-exhaust road traffic induced particle emissions (NORTRIP). Part 2: Surface moisture and salt impact modelling
    Denby, B. R.
    Sundvor, I.
    Johansson, C.
    Pirjola, L.
    Ketzel, M.
    Norman, M.
    Kupiainen, K.
    Gustafsson, M.
    Blomqvist, G.
    Kauhaniemi, M.
    Omstedt, G.
    ATMOSPHERIC ENVIRONMENT, 2013, 81 : 485 - 503
  • [5] Comparison of the predictions of two road dust emission models with the measurements of a mobile van
    Kauhaniemi, M.
    Stojiljkovic, A.
    Pirjola, L.
    Karppinen, A.
    Harkonen, J.
    Kupiainen, K.
    Kangas, L.
    Aarnio, M. A.
    Omstedt, G.
    Denby, B. R.
    Kukkonen, J.
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2014, 14 (17) : 9155 - 9169
  • [6] An empirical model to predict road dust emissions based on pavement and traffic characteristics
    Padoan, Elio
    Ajmone-Marsan, Franco
    Querol, Xavier
    Amato, Fulvio
    ENVIRONMENTAL POLLUTION, 2018, 237 : 713 - 720
  • [7] Review of Road Dust Resuspension Modelling Approaches and Comparisons Analysis for a UK Case Study
    Galatioto, Fabio
    Masey, Nicola
    Murrells, Tim
    Hamilton, Scott
    Pommier, Matthieu
    ATMOSPHERE, 2022, 13 (09)
  • [8] Attenuation of road dust emissions caused by industrial vehicle traffic
    Gerardin, Fabien
    Midoux, Noel
    ATMOSPHERIC ENVIRONMENT, 2016, 127 : 46 - 54
  • [9] Improvement assessment of the OSPM model performance by considering the secondary road dust emissions
    Rzeszutek, Mateusz
    Bogacki, Marek
    Bzdziuch, Paulina
    Szulecka, Adriana
    TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2019, 68 : 137 - 149
  • [10] Characterization of Road Dust Emissions in Milan: Impact of Vehicle Fleet Speed
    Amato, Fulvio
    Bedogni, Marco
    Padoan, Elio
    Queroll, Xavier
    Ealo, Marina
    Rivas, Ioar
    AEROSOL AND AIR QUALITY RESEARCH, 2017, 17 (10) : 2438 - 2449