Long-term trends in PM2.5 mass and particle number concentrations in urban air : The impacts of mitigation measures and extreme events due to changing climates

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de Jesus , A L , Thompson , H , Knibbs , L D , Kowalski , M , Cyrys , J , Niemi , J V , Kousa , A , Timonen , H , Luoma , K , Petäjä , T , Beddows , D , Harrison , R M , Hopke , P & Morawska , L 2020 , ' Long-term trends in PM2.5 mass and particle number concentrations in urban air : The impacts of mitigation measures and extreme events due to changing climates ' , Environmental Pollution , vol. 263 , 114500 . https://doi.org/10.1016/j.envpol.2020.114500

Title: Long-term trends in PM2.5 mass and particle number concentrations in urban air : The impacts of mitigation measures and extreme events due to changing climates
Author: de Jesus, Alma Lorelei; Thompson, Helen; Knibbs, Luke D.; Kowalski, Michal; Cyrys, Josef; Niemi, Jarkko V.; Kousa, Anu; Timonen, Hilkka; Luoma, Krista; Petäjä, Tuukka; Beddows, David; Harrison, Roy M.; Hopke, Philip; Morawska, Lidia
Other contributor: University of Helsinki, INAR Physics
University of Helsinki, Institute for Atmospheric and Earth System Research (INAR)


Date: 2020-08
Language: eng
Number of pages: 12
Belongs to series: Environmental Pollution
ISSN: 0269-7491
DOI: https://doi.org/10.1016/j.envpol.2020.114500
URI: http://hdl.handle.net/10138/328684
Abstract: Urbanisation and industrialisation led to the increase of ambient particulate matter (PM) concentration. While subsequent regulations may have resulted in the decrease of some PM matrices, the simultaneous changes in climate affecting local meteorological conditions could also have played a role. To gain an insight into this complex matter, this study investigated the long-term trends of two important matrices, the particle mass (PM2.5) and particle number concentrations (PNC), and the factors that influenced the trends. Mann-Kendall test, Sen's slope estimator, the generalised additive model, seasonal decomposition of time series by LOESS (locally estimated scatterplot smoothing) and the Buishand range test were applied. Both PM2.5 and PNC showed significant negative monotonic trends (0.03-0.6 mg m(-3).yr(-1) and 0.40-3.8 x 10(3) particles. cm(-3). yr(-1), respectively) except Brisbane (+0.1 mg m(-3). yr(-1) and +53 particles. cm(-3). yr(-1), respectively). For the period covered in this study, temperature increased (0.03-0.07 degrees C.yr(-1)) in all cities except London; precipitation decreased (0.02-1.4 mm.yr(-1)) except in Helsinki; and wind speed was reduced in Brisbane and Rochester but increased in Helsinki, London and Augsburg. At the change-points, temperature increase in cold cities influenced PNC while shifts in precipitation and wind speed affected PM2.5. Based on the LOESS trend, extreme events such as dust storms and wildfires resulting from changing climates caused a positive step-change in concentrations, particularly for PM2.5. In contrast, among the mitigation measures, controlling sulphur in fuels caused a negative step-change, especially for PNC. Policies regarding traffic and fleet management (e.g. low emission zones) that were implemented only in certain areas or in a progressive uptake (e.g. Euro emission standards), resulted to gradual reductions in concentrations. Therefore, as this study has clearly shown that PM2.5 and PNC were influenced differently by the impacts of the changing climate and by the mitigation measures, both metrics must be considered in urban air quality management. (C) 2020 Elsevier Ltd. All rights reserved.
Subject: PM2.5
Particle number concentration
Ultrafine particles
Mitigation
Climate variabilities
FINE PARTICULATE MATTER
NORTH-ATLANTIC OSCILLATION
TIME-SERIES ANALYSIS
PACIFIC WP PATTERN
ARCTIC SEA-ICE
NEW-YORK-STATE
ULTRAFINE PARTICLES
CHEMICAL-CHARACTERIZATION
SIZE DISTRIBUTIONS
SOURCE APPORTIONMENT
116 Chemical sciences
114 Physical sciences
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