The Canadian Arctic has experienced decreasing sea ice extent and
increasing shipping activity in recent decades. While there are
economic incentives to develop resources in the north, there are
environmental concerns that increasing marine traffic will
contribute to declining air quality in northern communities. In an
effort to characterize the relative impact of shipping on air
quality in the north, two monitoring stations have been installed in
Cape Dorset and Resolute, Nunavut, and have been operational since
1 June 2013. The impact of shipping and other sources of emissions
on NO
The Arctic is a highly uncertain environment on the planet in terms of
climate change. The year-to-year and regional variability for most
environmental indicators are linked to a persistent warming trend that
began more than 30
Arctic sea ice in Canada has also retreated in recent decades with
strong negative trends in the Hudson and Baffin bays
Long-range transport, seasonal, and annual variability of surface
pollutants in the Arctic have been studied in some detail. Black
carbon (BC) is of particular interest due to significant light
absorption and reduction of surface albedo in the Arctic, particularly
during the summer
Trends in surface ozone mixing ratios in the Arctic are complicated
due to a multitude of chemical and physical processes including
long-range transport, titration, photochemistry, and halogen
chemistry. However, regarding surface levels, models suggest that
mixing ratios are expected to increase due to the influence of distance
sources by less than 8
Regarding other pollutants, measurements by
A study by
Regarding other pollutants,
While long-range transport, seasonal, and annual variations in the
Arctic air quality have been researched in considerable depth, there
is still work to be done to characterize local sources and transport
of pollutants (e.g., from ships in the Arctic) and short-term
variability in air quality caused by anthropogenic
sources. Particularly during the summer, the Arctic dome reduces
continental transfer of pollutants to the region so that the relative
contribution of local sources of emissions become higher
It has been reported that 3.3 % of global
Sulfur emissions from ships are of particular interest since, in
addition to
Various on-board control measures have also been suggested. Ship speed
and engine load are important contributors to ship emission
factors. It has been observed that speed reduction results in better
fuel economy and, hence, lower
Increasing shipping traffic in the Canadian Arctic necessitates the
understanding of its impacts on air quality, particularly relative to
other local sources. This is vital in order to properly regulate marine traffic
in the Canadian Arctic for future decades. Most recent works in this
area remain speculative in nature, solely relying on models or bulk
inventory emission analyses. While there has been some observational
success in characterizing emission factors at the “source”
(i.e., ship stacks or ship plume interception campaigns)
Site locations for air quality monitoring stations in the Canadian Arctic; monitoring station in Cape Dorset facing the Arctic Bridge near Hudson Strait; monitoring station in Resolute facing the Northwest Passage near Barrow Strait.
To measure pollution from shipping vs. other local sources in the
Canadian Arctic, two monitoring stations were set up as receptors for
Vessel traffic information was acquired from the Canadian Coast Guard,
available for Canadian government agencies and research institutions
at
As an alternative to the Canadian Coast Guard data set, the Automatic Identification System
could have been used for ship traffic tracking with greater temporal and spatial resolution but
possibly fewer ships identified. This technology has been successfully used over the European Arctic
in tracking ships
It is common to encounter location entries in the database that are
harbor or community names instead of latitude and longitude
coordinates. A lookup table has been developed and appended to
convert location names into coordinates accordingly. Vessel reporting
frequency is neither uniform in time nor homogeneous in space. Ships
communicate with a range of time resolutions from minutes to
hours. They also overreport activity in strategic locations such as
the Barrow Strait and underreport in non-critical locations
(e.g., the middle of Hudson Bay). To reconstruct high-resolution, uniform,
and homogeneous vessel coordinates, the positions were interpolated,
subject to spatial and temporal filters, a concept successfully
implemented in previous studies
A total of 27 921 ship reports were processed to create the vessel
traffic data set with a 1 min time resolution for the entire analysis
period. In total, 109 ships (with Lloyd registration numbers) were active
in the Canadian Arctic during the 2013 shipping season. These
ships were merchant, passenger, cargo, fishing, tug, cruise, coast guard icebreaker, and other types ranging
from
The monitoring stations in both locations consist of a commercially
available integrated air quality package (airpointer®,
manufactured by recordum® Messtechnik GmbH in Austria,
hardware v. 2, software v. 1.9.7). The assembly includes
There are about 45 airpointers® deployed in Canada today that
operate for the federal government (e.g., Environment Canada and Health
Canada), provincial governments, cities, universities, and
industry. The airpointer® was approved by
TÜV Rheinland
Immissionsschutz und Energiesysteme GmbH (Germany) in
January 2009 as compliant with DIN EN 14211, DIN EN 14212, DIN EN 14625,
and DIN EN 14626 Standards
Maps of Cape Dorset and Resolute with monitoring stations;
wind roses for 22.5
As per specification sheets, the lower detection limits (LDLs) for
Precision for gas pollutant measurements at lower detection limit, based on daily internal zero calibration.
Some limitations of the airpointer® are worth
mentioning. First, the airpointer® is suited for air quality
assessment near cities, towns, villages, mines, industrial processes, and monitoring moderate background level variations. However,
it is not intended to provide absolute measurements for trace level
pollutants in the parts per trillion range, so care must be
taken not to report absolute trace levels with high certainty. Our
methodology relies on clustering (grouping) of air samples and showing
statistically significant differences in their concentration
distributions. Second, the measurement of
In Resolute only, particle size and equivalent black carbon (aerosol absorption derived black carbon) measurements were also performed. These measurements were conducted inside a hut located
on Environment Canada's Upper Air Building premises, about
100
The SMPS (TSI 3034) was used to measure particle size distributions in
the 15 to 600
The CLAP
Figure
A major concern in the applicability of our results to past or future
years was whether the weather conditions at the sites for the 2013
shipping season were representative of the recent Arctic climate,
particularly for wind patterns, temperatures, and precipitation. Wind
patterns govern transport of air pollution, temperature is a key
player in atmospheric chemistry and also marine navigability, and
precipitation affects wet deposition (removal) of aerosols. We studied
the airport climatology of Cape Dorset and Resolute from NAV Canada
Emission inventories (
Monthly average temperatures for each site were obtained from Canada's
Historical Climate Data for 1995, 2000, and 2005
Monthly average precipitation for each site was also obtained for
1995, 2000, and 2005
With consideration of wind direction patterns, temperature, and precipitation trends for the 1995–2005 period, we have some confidence that our 2013 results are representative of a typical Arctic year.
Accurate source apportionment of surface pollutants in our study
required state-of-the-art air mass back trajectory analysis. This was
needed to investigate origins of different air masses that arrived at
the monitoring stations (55 and 57
To understand the relative magnitude of shipping emissions, it was
necessary to have an estimate of the entire emission inventory in the
Canadian Arctic. There is limited information on the most current
emission inventories in the Canadian Arctic. We have used the
National Pollutant Release Inventory (NPRI), available from
Environment Canada, for an initial estimate of major sources of
emissions from latitudes above 60
The only facilities reported for Cape Dorset and Resolute are the
municipal fossil fuel electric power generators. In 2012, the Cape Dorset
generator emitted 96.111 and 1.439 t of
Summaries of air-pollutant emissions for Cape Dorset and Resolute in
2011, listing only categories with emissions of
Table
Shipping traffic maps in the Canadian Arctic from
1 June 2013 to 1 November 2013; shipping activity in Mackenzie
River (Northwest Territories) not considered; shipping traffic
density plot produced with 1
The air quality index (AQI) is a numeric scale used to quantify air
pollution at a given point in time and its health significance. Most
AQIs used around the world are calculated by comparing each pollutant
in the index to its standard, and reporting the index as the number
corresponding to the pollutant that is highest relative to its
standard. On the contrary, the Air Quality Health Index used in
Canada considers the additive effects of multiple pollutants. AQHI
assumes a linear relationship between air pollution and mortality,
which is consistent with other no-threshold and dose–response
relationships proposed by the World Health Organization (WHO). AQHI
has been developed by examining all possible combinations of two to five
common pollutants and various averaging times to determine the best
and simplest index that statistically correlates with mortality
rates. The current version in use considers a trailing 3 h average of
AQHI is used as a simple tool to put our results in context. Assumptions pertaining to threshold or
no-threshold formulations, effect of long-term background pollutants, smoking habits, and other various
factors have long been debated in the formulation and output of air quality health models. If a more detailed
and accurate health impact assessment of shipping pollution in Arctic communities is desired, a more advanced
and statistical health model, such as the Air Quality Benefits Assessment Tool (AQBAT), should be used. Such a
model enables the definition of various specific scenario models from the flexibility of combining and linking
of pollutants, health endpoints, geographic areas, and scenario years
Clustering of air masses based on trajectories resulted in a few
samples identifying pollutant concentrations or AQHIs associated with
each group of trajectories. A statistical estimator was used to
construct a confidence interval for the difference in true means
between selected sample pairs. Supposing
Figure
HYSPLIT trajectory frequency plots from 1 June 2013 to 1 November 2013.
The HYSPLIT 5-day trajectory frequency plots are provided in
Fig.
Rose plots for pollution as a function of site wind direction
from 1 June 2013 to 1 November 2013; wind roses for 22.5
In a first step toward understanding air pollution, rose plots for
pollution concentrations as a function of site wind direction are
presented in Fig.
Higher
1 min resolution Air Quality Health Index (AQHI) without rounding.
The only noticeable seasonal trend in pollution measurements is the increase in
To identify the effect of shipping traffic on air pollution beyond
each site, air mass trajectories and shipping traffic in the Arctic
needed to be considered simultaneously. Clustering is the process of
grouping air mass trajectories into classes of similar objects. Many
algorithms are reported, such as TSV,
Static clustering was purely geographical and separated the
trajectories based on the place of origin into four sectors: A, B, C,
and D, specific to each site. These sectors were identified with the
aid of wind direction analysis (Fig.
Sectors used for grouping air mass trajectories: trajectories in sectors A and C weakly affected by local pollution, while trajectories in sectors B and D strongly affected by local pollution.
Dynamic clustering, on the other hand, separated the trajectories in
two groups, based on whether or not each trajectory crossed a ship at
an elevation less than 100
Before cluster statistics are discussed, four ship pollution episodes
are illustrated using 1 min resolution time series in
Fig.
Ship pollution episode analysis using time series during selected days; annotated pollution events influenced by ships (wide and low peaks) and local events (narrow and high peaks or valleys).
As a first step in static clustering of trajectories, the radius
distances of trajectories in each cluster to the monitoring stations
were computed as a function of trajectory backward time. A backward
time selection of 16
Pollution concentrations based on static clustering of air mass trajectories for Cape Dorset and Resolute; trajectories grouped
based on a 16
Static cluster sample sizes
The significant effect of local pollution can be observed comparing
Ozone variations are complicated due to a multitude of chemical
processes and interactions. The two key chemical processes involved
are titration and photochemistry
Pollution concentrations based on dynamic clustering of air mass trajectories.
Ozone mixing ratios in sector D for Cape Dorset are down to
5.0–5.1
Equivalent black carbon (EBC) based on dynamic clustering of air mass trajectories in Resolute.
There is no statistically significant difference among
AQHI based on dynamic clustering of air mass trajectories.
Estimator for differences in true means between concentrations
(ppb for gases and
Dynamic clustering of air mass trajectories was performed based on
grouping air masses into clear (A
Estimator for differences in true means between concentrations (ppb
for gases,
Particle size number fraction in Resolute.
For
Contribution of shipping and other sources to cumulative pollution; lower and upper bounds based on clear and all wind sectors.
For
The influence of shipping emissions on
Estimator for differences in true means between AQHI associated
with dynamic air mass clusters in Cape Dorset and Resolute;
In Resolute, the influence of shipping emissions on EBC concentrations is
significant only under clear wind sectors for plumes up to 24
There is a persistent increase in AQHI for ship-influenced air masses
in both sites for plumes up to 24 and 72
The fate of particles in ship plumes was studied, to a limited extent and by speculation,
using particle size number fractions in
Resolute. Figure
Figure
Parameters for the four-modal log-normal fits to the particle size number fractions as a function of ship plume age in Resolute; nucleation (Nuc), Aitken (Ait), and accumulation (Acc) modes annotated in the table.
The unpolluted number fraction (background), with long residence time
over marine boundary layer and nearby islands, exhibits two strong
modes in Aitken (28–37
Percent contribution of shipping to total pollution (
The particle size number fraction exhibits complex dynamics as the
plumes age beyond 6
Our plume aging analysis suggests that particle processing in the Arctic is very slow,
requiring up to 72
Percent contribution of shipping to total ozone titration (
To estimate the contribution of shipping to cumulative pollution,
a measure of local exposure, the surface level concentrations are
integrated over time. It can be argued that the clear wind sectors
(A
Since there are seasonal variations in
In our analysis for black carbon in Resolute, we find that EBC
constitutes 1.3–9.7 % of total
Cumulative percent ship contribution to pollution for all species is
greater in Cape Dorset, justified by a longer shipping season and
a shorter distance between ships, particularly at anchoring position,
and the monitoring station. We estimate the percent ship contribution
(
In an effort to characterize air quality in two communities of the
Canadian Arctic during the high shipping season, we have measured
surface concentrations of
For both sites, higher
The high-resolution AQHI primarily followed
seasonal
Lower and upper bounds in cumulative pollution were estimated by
grouping air masses that arrived at the sites from clear wind sectors,
dominantly influenced by ship pollution, and all wind sectors,
influenced by ship and local pollution. We estimate the percent ship
contribution to
One limitation of these estimates is the use of trajectories as opposed to plume dispersion modeling. Plume dispersion modeling for our purposes was virtually impractical since it would have required plume dispersion simulations for each ship at short time intervals for the entire shipping season, which was an immense computational calculation and beyond the scope of our analysis. Nevertheless, the order of magnitude and the comparative results between the two sites are relevant and informative to this field of research.
Continued air quality monitoring in the above sites during future shipping seasons would improve the statistics in our analysis as well as characterize repeating seasonal patterns in air quality due to shipping, local pollution, and long-range transport.
The works published in this journal are distributed under the Creative Commons Attribution 3.0 License. This license does not affect the Crown copyright work, which is re-usable under the Open Government Licence (OGL). The Creative Commons Attribution 3.0 License and the OGL are interoperable and do not conflict with, reduce or limit each other. © Crown copyright 2014
The authors are indebted to Mark Gordon for assisting in the calibration and installation of the monitoring stations, the help of Andrew Elford for setting up the data transfer protocol from the Arctic, Colin Gibson (Cape Dorset), Wayne Davidson (Resolute), and Steven Laszlo (Toronto) for the routine maintenance of the monitoring stations, the help of Daniel Veber for instrumentation of the particle measurement equipment in Resolute, the help of Jacinthe Racine for running the Canadian Meteorological Center trajectory model for comparison with HYSPLIT model, and also the assistance of David Niemi for providing land-based emission inventories in the north. We also acknowledge the expert reviews of the manuscript by Lynn Lyons and Wanmin Gong, and the useful discussions with Richard Leaitch. Authors acknowledge collaboration with John Ogren at NOAA/ESRL on the use of data collection software for the optical instruments measuring equivalent black carbon. The funding support and cooperation among various branches, directorates, and divisions within Environment Canada are acknowledged:Environmental Stewardship Branch, Energy and Transportation Directorate, Transportation Division; Science and Technology Branch, Atmospheric Science and Technology Directorate, Air Quality Research Division and Climate Research Division; and Meteorological Service of Canada, Weather and Environmental Prediction and Services Directorate, National Prediction Operations Division. Edited by: R. Ebinghaus