Local Arctic air pollution: Sources and impacts
- 1.2k Downloads
Local emissions of Arctic air pollutants and their impacts on climate, ecosystems and health are poorly understood. Future increases due to Arctic warming or economic drivers may put additional pressures on the fragile Arctic environment already affected by mid-latitude air pollution. Aircraft data were collected, for the first time, downwind of shipping and petroleum extraction facilities in the European Arctic. Data analysis reveals discrepancies compared to commonly used emission inventories, highlighting missing emissions (e.g. drilling rigs) and the intermittent nature of certain emissions (e.g. flaring, shipping). Present-day shipping/petroleum extraction emissions already appear to be impacting pollutant (ozone, aerosols) levels along the Norwegian coast and are estimated to cool and warm the Arctic climate, respectively. Future increases in shipping may lead to short-term (long-term) warming (cooling) due to reduced sulphur (CO2) emissions, and be detrimental to regional air quality (ozone). Further quantification of local Arctic emission impacts is needed.
KeywordsAir pollution Arctic Climate Human health
Air pollution in the Arctic can have adverse effects on climate, ecosystems and health. Whilst air pollutants originate primarily from mid-latitude anthropogenic emission regions in Asia, Europe and North America or from boreal or agricultural fires (Law et al. 2014), sources of local pollution are already known to be important but their emissions and impacts are poorly quantified. In addition, Arctic warming, combined with favourable economic conditions, may lead to further industrial development in the Arctic. This includes increasing possibilities for transport of goods via northern sea routes, resource extraction and associated infrastructure developments and urbanisation. Growth in such activities is likely to increase emissions of air pollutants and add to pollutant burdens in the Arctic.
Air pollutants include trace gases such as ozone [a secondary pollutant formed in the presence of nitrogen oxides (NO x ) and hydrocarbons, including volatile organic compounds (VOCs), carbon monoxide (CO) and methane], or aerosols such as black carbon (BC) or sulphate [formed from sulphur dioxide (SO2) emissions]. They are responsible for poor air quality and detrimental effects on human health even at low concentrations (European Environment Agency, EEA 2015). Air quality guidelines set thresholds for ozone and, in the case of aerosols, for particulate matter (e.g. PM2.5—sum of particle mass concentrations with an aerodynamic diameter less than 2.5 μm). Pollutants can also cause damage to ecosystems via deposition onto, for example, forests and crops, and impact climate by warming (e.g. ozone, BC) or cooling (e.g. sulphate) the atmosphere. BC can be deposited onto snow and ice surfaces decreasing surface albedo leading to additional warming. Reducing targeted emissions of the so-called short-lived climate forcers (BC, methane which is also an important ozone precursor), in addition to carbon dioxide (CO2) reductions (which is very long-lived and often co-emitted), has received much attention due to the potential co-benefits of improving air quality and slowing global/Arctic warming (e.g. Arctic Monitoring and Assessment Programme, AMAP 2015).
Whilst much attention in recent years has focused on improving the understanding about remote sources of Arctic air pollution transported from mid-latitudes and their impacts on climate, rather little attention has been paid to improving our understanding about local emissions and their impacts on climate, ecosystems and health. Earlier studies identified the existence of emissions within the Arctic such as sulphur containing pollution from metal smelting, for example in the Kola Peninsula (Russia), as a source of Arctic sulphate aerosols (e.g. Prank et al. 2010). More recently, Stohl et al. (2013), using ECLIPSE (evaluating the climate and air quality impacts of short-lived pollutants) emissions identified flaring associated with oil/gas extraction in northern Russia and seasonally varying domestic wood combustion as important sources of Arctic BC.
Previous studies also examined the effects of Arctic shipping on present-day and future atmospheric composition (Granier et al. 2006) and deposition of acidic compounds (nitrate, sulphate) in some cases leading to exceedances in critical loads (Dalsøren et al. 2007). Corbett et al. (2010) developed ship emission scenarios, taking into account future growth in shipping, emission regulations [e.g. International Maritime Organisation (IMO) sulphur reductions in ship fuel, reduced NO x emissions due to improvements in ship engines] and shipping diverted from southerly routes. Building on Corbett et al. (2010), Winther et al. (2014) developed new inventories, making use of high-resolution automatic identification system (AIS) satellite position data, and predicted modest increases in ozone (> 10%) and large increases in BC (> 80%) along Arctic diversion shipping routes in 2050.
This paper summarises the main results from the European Union ACCESS (Arctic Climate Change, Economy and Society) project (2011–2015) (see Crépin et al. 2017) aiming to improve characterisation of shipping and petroleum extraction emissions in the Arctic and their impacts on atmospheric composition, regional air quality and climate. Since characterisation of these emissions and their impacts is limited by a lack of in situ data collected in close proximity to sources under Arctic conditions (e.g. stable boundary layers, cold temperatures), new aircraft data were collected along the Norwegian coastal region, and used, together with modelling, to examine the impacts of local emissions on Arctic atmospheric composition and climate in the European Arctic. In addition, as part of ACCESS, present-day and future impacts of local pollution on climate, as well as potential impacts on regional air quality, were estimated over the Arctic using regional and global modelling. Global modelling studies were carried out in collaboration with the Norwegian project ArcAct (unlocking the Arctic Ocean: the climate impact of increased shipping and petroleum activities) (2012).
We first present the overall research objectives together with a description of the tools that were deployed, and then describe the main findings about local Arctic pollution emissions and their impacts on atmospheric composition, regional air quality and climate. Finally, we present conclusions and future perspectives.
Objectives and methodology
Derive, for the first time, independent estimates of air pollutant emissions related to Arctic shipping and oil and gas extraction activities under Arctic conditions, with a focus on the Norwegian coastal region;
Better quantify the impact of current and future Arctic shipping and oil/gas extraction activities on Arctic chemical composition, climate and regional air quality in the European Arctic and over the entire Arctic region.
ACCESS airborne campaign
A variety of models were used in ACCESS for flight planning, data analysis and to assess impacts of Arctic pollution on atmospheric composition and climate.
WRF-Chem [weather research and forecasting (WRF) mesoscale weather model, including chemistry] is a regional chemical–aerosol transport model. Model simulations, nudged using National Centres for Environmental Prediction final (FNL) meteorological analyses and including detailed chemical and aerosol schemes, were carried out at high resolution (2–3 km up to 15 km) to analyse aircraft data collected in the vicinity of local sources to validate emission inventories and examine the impacts of pollution on atmospheric composition from oil/gas extraction and shipping along the Norwegian coast (Marelle et al. 2016; Tuccella et al. 2017). Runs at lower resolution (100 km) were used to examine the relative contributions of local versus remote mid-latitude sources of emissions (Marelle 2016).
OsloCTM2 is a global chemistry transport model (CTM) for the troposphere and stratosphere run at T42 resolution (2.8 × 2.8°) with 60 vertical layers using meteorological data from the integrated forecast system (IFS) model from the European Centre for Medium-Range Weather Forecasts (Dalsøren et al. 2013). A tropospheric version of the model was used including tropospheric chemistry and sulphate, primary organic, nitrate and sea salt aerosols.
Radiative forcing (RF) model calculations were performed using a radiative transfer model (Myhre et al. 2009) developed from the DISORT code-base with four short-wave radiation bands and eight angular multiple scattering streams. Temporal and spatial resolutions were the same as OsloCTM2.
In the following sections, we describe the principal results from ACCESS related to evaluation of emission estimates and quantification of impacts of local Arctic pollution on climate and air quality at regional (European Arctic) and Arctic-wide scales.
Improved estimation of local Arctic emissions
During flights focusing on ship emissions (Fig. 2), plumes from four ships running on diesel fuel were sampled including a cargo ship, a bulk carrier and a passenger cruise ship run on heavy fuel oil emitting high NO x , SO2 and particles. A cargo ship running on marine gas oil with lower sulphur fuel content producing lower SO2 emissions was also sampled (Roiger et al. 2015; Marelle et al. 2016). Fishing ships, also running on diesel fuel, which were not included in previous inventories, such as Corbett et al. (2010), were also sampled for the first time in the Norwegian and Barents Sea showing very variable emissions but generally low SO2 and high particle number (two cases presented in Roiger et al. 2015). Marelle et al. (2016) compared plume samplings for four ships to plume dispersion simulations, performed with the Lagrangian particle dispersion model FLEXPART-WRF (Brioude et al. 2013) to derive independent estimates of NO x and SO2 emission fluxes. These estimates were used to validate emissions for sampled ships from a high-resolution inventory—ship traffic emissions assessment model, version 2 (STEAM2) based on AIS data and taking into account individual ship characteristics (e.g. speed, engine/fuel type) (Jalkanen et al. 2012). Overall, STEAM2 NO x emissions were biased high (four cases) and SO2 emissions both low and high (two cases) (see Table 4 in Marelle et al. 2016). Large biases in emission estimates by STEAM2 were attributed to incomplete technical data or implementation of emission reduction technology not yet taken into account in STEAM2.
At the same time, the regional WRF-Chem model was run with and without STEAM2 emissions for July 2012 and compared to average vertical profile data from the ACCESS airborne campaign. Whilst large biases were found in STEAM2 compared to the independent estimates for individual ships, the regional model results show better overall agreement with the observations when ship emissions are included. This suggests that STEAM2 reproduces aggregated shipping emissions along the Norwegian coast in summer. Marelle et al. (2016) also note that both STEAM2 ship emission estimates, as well as Arctic-wide emissions from Winther et al. (2014) for 2012, also based on AIS data, are significantly higher in northern Norway than older inventories (Corbett et al. 2010; Peters et al. 2011). Use of AIS data, growth in emissions, together with the inclusion of fishing ships, and more detailed emission calculations, may explain these differences. Arctic focused estimates of ship emissions, taking into account, for example, navigation in sea-ice, would also improve emission estimates (Schröder et al. 2017). Aliabadi et al. (2016) already noted that emission factors, determined from observations behind a research vessel operating in the North-West passage (Canadian Arctic), are sensitive to sea-ice presence, showing, for example, increased NO x emission factors when the ship was ice breaking.
Petroleum extraction emissions
Aircraft data collected around platforms in the southern Norwegian Sea show a very complex picture with emissions varying between different types of facility (Roiger et al. 2015). Data collected downwind of oil/gas production platforms, operating under normal conditions, showed elevated NO due to power generation, and high numbers of volatile particles but low SO2. High numbers of small nucleation mode particles suggest significant new particle production from venting/leaks of VOCs. Particles (and occasionally rBC) and NO were enhanced in plumes downwind of certain installations that were flaring but emissions were very intermittent making it difficult to draw conclusions about these emissions. In contrast, emissions from storage tankers or drilling rigs (also considered as mobile “platforms”) which are essentially stationary ships, as well as shuttle tankers, exhibited high emissions of SO2 and associated non-volatile particles (i.e. sulphate), together with high NO due to diesel combustion. Measured rBC showed enhancements downwind of mobile platforms, a potentially more important source than emissions from production platforms (Roiger et al. 2015), but, as noted earlier, instrument cut-off issues in fresh plumes meant it was not possible to characterise these emissions. Overall, measured plumes associated with oil/gas extraction were of similar magnitude compared to ship plumes in the case of NO, but tended to be smaller in the case of SO2 (see Fig. 2).
The ACCESS data were compared to WRF-Chem simulations run at high resolution (2 km) in the region of the platforms for 19/20 July 2012 using two inventories providing emissions for specific facilities: TNO-MACC emissions for 2009 and Norwegian Environment Agency (NEA) 2012 emissions (see Tuccella et al. 2017 for details). It is important to note that emissions from mobile platforms, such as certain storage tankers and drilling rigs, are not included in these inventories. In addition, NEA does not report aerosol emissions making it necessary to estimate these emissions (using ratios with NO x ) and TNO-MACC only includes emissions of NO x and VOCs. While runs using the NEA emissions agreed reasonably well with the measurements, a run with TNO-MACC, which has much lower NO x emissions compared to NEA (by factor 20–30), was unable to represent measured composition in the plumes. One difficulty associated with this analysis is the highly variable nature of emissions from oil/gas production which vary significantly depending on operating conditions, flaring, etc. These results highlight deficiencies in current inventories used in global and regional models which do not take into the account the intermittent nature of certain emissions such as flaring (since only annual average emissions are usually provided) and which do not include emissions for certain species or emissions from particular sources (e.g. mobile platforms).
Local and regional impacts on atmospheric composition and air quality
Influences of local emissions from shipping and petroleum extraction on atmospheric composition have been investigated using the WRF-Chem model for the campaign region in July 2012 and, in the case of shipping, for the entire Arctic. Whilst the campaign region and period are limited in space and time, these results provide first indications about impacts in a region where local emissions are already occurring.
Based on better agreement with ACCESS data collected around the Norwegian oil/gas platforms, the results of the high-resolution model runs (2 km) with the NEA emissions were used to assess, for the first time, potential impacts of these emissions on Arctic atmospheric composition under Arctic conditions (Tuccella et al. 2017). Modest daytime average enhancements in ozone (up to 7% above background of 25–30 ppbv) were predicted in the Arctic boundary layer with larger noontime increases of up to 4 ppbv (15%) around 600 m up to 50 km downwind of the platforms. Small enhancements in PM2.5 were also predicted (11% at the surface) with the largest increases in model BC (+ 48% at the surface). Given that emissions from mobile platforms are not included in the TNO-MACC and NEA emissions, our findings are likely to be lower estimates. However, they suggest that petroleum extraction emissions are already impacting the pristine Arctic troposphere. Fully speciated ozone precursor and aerosol emissions are required to improve predictions of these impacts as well as measurements in regions where these emissions are estimated to be larger such as in northern Russia.
Impacts of local emissions on Arctic and global climate
Climate models, including treatments of chemistry and aerosols, were used in ACCESS to quantify the impacts of local emissions on Arctic climate. The results on shipping were summarised in an ACCESS Policy Brief (see http://www.accesseu.org/en/publications/access_brief.html).
Future climate impacts of short-lived atmospheric pollutants due to global and Arctic shipping emissions were estimated by Dalsøren et al. (2013). OsloCTM2 was run with high growth (HIGH) and maximum feasible reduction (MFR) scenarios for 2030 from Corbett et al. (2010) including moderate to substantial increases in pollutants both globally and in the Arctic (especially in summer). Exceptions are found in the MFR scenario when technological advances are included reducing BC emissions by 70%. Implementation of future IMO regulations reducing fuel sulphur content leads to reductions in emissions of SO2 and therefore lower production of sulphate aerosols. In contrast to cooling from present-day shipping, predicted future changes from 2004 to 2030 result in global average net positive RF [+ 53 mW m−2 (HIGH); + 73 mW m−2 (MFR)] due to less cooling from sulphate aerosols (additional positive RFs from long-lived components N2O and CO2 were not quantified). In the Arctic, the overall RF for the HIGH scenario is a factor 1.5 larger than for the MFR scenario, opposite to the global picture, due to relatively stronger RF from ozone and BC, and smaller indirect aerosol effects, in the Arctic.
Conclusions and perspectives
Results from ACCESS have provided new insights into local Arctic pollution sources and their impacts on climate and regional atmospheric composition/air quality. Aircraft data, and subsequent analyses, have been used to validate current emission inventories for shipping and petroleum-related activities and to assess their impact on atmospheric composition during summertime conditions in the European Arctic. Independent validation of individual sources revealed variable agreement with reported emissions, due to missing sources/species, assumptions about operating conditions or emission control technologies. Current inventories (usually annual means) used by global and regional models need to be improved taking these factors, as well as the intermittent nature of certain emissions (e.g. flaring, shipping), into account. Generally, model results agree better with observations when high-resolution local emissions are included and suggest that ship and oil/gas extraction emissions off the coast of Norway are already having a significant impact on Arctic composition as well as current, and potentially, future air quality. Further characterisation of these and other local emissions (e.g. wood burning, metal smelting) are needed at other times of year, such as winter and spring (when boundary layers are more stable, snow or sea-ice may be present, etc.), to improve assessment of pollutant impacts, not only on climate and regional air quality, but also on ecosystems and human health.
Potential impacts on climate were assessed based on the available scenarios. Present-day shipping and petroleum extraction lead to cooling and warming, respectively, whereas increases in Arctic shipping, as well as shifts from southerly routes, lead to warming in the future, at least in the short term. However, results are very dependent on the employed emission scenarios and how sea-ice melt evolution, economic factors and proposed emission regulations etcetera are taken into account. Reductions in NO x emissions (e.g. via NECAs) leading to reductions in ozone, or in BC emissions, would likely benefit air quality and climate, whereas reductions in sulphur emissions from shipping are likely to improve local and regional air quality through PM2.5 reductions but warm the climate. This poses a challenge to policy makers. Reducing CO2 emissions is the key to an effective climate policy, whereas reductions in air pollutants may either lead to climate warming or cooling. As the Arctic warms, it will be necessary to monitor changes in Arctic composition and take effective mitigation measures. In parallel, further work is still needed to better assess impacts of local pollutants, including contaminants, on human health and to evaluate impacts of pollutant deposition on ecosystems (e.g. nitrate).
We acknowledge funding from the European Union under Grant Agreement no. 5265863: ACCESS Project (2012–2015) within the Ocean of Tomorrow Call of the European Commission Seventh Framework Programme. French authors acknowledge support from ANR/CNRS-LEFE Climate Impacts of Short-Lived Pollutants and Methane in the Arctic (CLIMSLIP), Chantier Arctique Pollution in the Arctic System (PARCS) Project, computer resources from IDRIS HPC Resources under GENCI and IPSL CICLAD/CLIMSERV. L. Marelle acknowledges support from TOTAL SA (ANRT Cifre PhD) for work contributing to this paper. DLR scientists acknowledge support from Deutsche Forschungsgemeinschaft under Grant SPP1294/SCHL1857/2-2 (H. Schlager), the Helmholtz Association under Grant Number VH-NG-606 (Helmholtz-Hochschul-Nachwuchsforschergruppe AerCARE) and European Research Council (ERC) Grant Agreement 640458 (A-LIFE) under EU Horizon 2020/ERC (B. Weinzierl). CICERO scientists also acknowledge support from Norwegian Research Council (Project Number 184873/S30, “Unlocking the Arctic Ocean: the climate impact of increased shipping and petroleum activities (ArcAct)”. We acknowledge ozone data from National Oceanic and Atmospheric Administration (NOAA)-Earth Systems Research Laboratory (ESRL) Global Monitoring Division (GMD) and Physical Sciences Division (PSD), Boulder (USA) at Barrow, Alaska (USA), NOAA-ESRL GMD/PSD and Rushydrometeorology at Tiksi (Russia) and NILU (Wenche Aas) at Zeppelin (Norway).
- Aliabadi, A.A., J.L. Thomas, A.B. Herber, R.M. Staebler, W.R. Leaitch, H. Schulz, K.S. Law, L. Marelle, et al. 2016. Ship emissions measurement in the Arctic by plume intercepts of the Canadian Coast Guard icebreaker Amundsen from the Polar 6 aircraft platform. Atmospheric Chemistry and Physics 16: 7899–7916. doi: 10.5194/acp-16-7899-2016.CrossRefGoogle Scholar
- AMAP. 2015. Summary for policy-makers: Arctic climate issues 2015. Oslo: Arctic Monitoring and Assessment Programme (AMAP).Google Scholar
- Dalsøren, S.B., Ø. Endresen, I.S.A. Isaksen, G. Gravir, and E. Sørgård. 2007. Environmental impacts of an expected increase in sea transportation, with particular focus on oil and gas scenarios for Norway and northwest Russia. Journal of Geophysical Research 112: D02310. doi: 10.1029/2005JD006927.CrossRefGoogle Scholar
- Eckhardt, S., O. Hermansen, H. Grythe, M. Fiebig, K. Stebel, M. Cassiani, A. Baecklund, and A. Stohl. 2013. The influence of cruise ship emissions on air pollution in Svalbard—A harbinger of a more polluted Arctic? Atmospheric Chemistry and Physics 13: 8401–8409. doi: 10.5194/acp-13-8401-2013.CrossRefGoogle Scholar
- European Environment Agency (EEA). 2015. Air quality in Europe—2015 Report. EEA Rep. No. 5/2015. doi: 10.2800/62459.
- Jonson, J.E., J.P. Jalkanen, L. Johansson, M. Gauss, and H.A.C. Denier van der Gon. 2015. Model calculations of the effects of present and future emissions of air pollutants from shipping in the Baltic Sea and the North Sea. Atmospheric Chemistry and Physics 15: 783–798. doi: 10.5194/acp-15-783-2015.CrossRefGoogle Scholar
- Marelle, L. 2016. Regional modeling of short-lived atmospheric pollutants (aerosols, ozone) in the Arctic. PhD Thesis, Atmospheric and Oceanic Physics [physics.ao-ph], Université Pierre et Marie Curie-Paris 6 (English). https://hal-insu.archives-ouvertes.fr/tel-01401552.
- Marelle, L., J.L. Thomas, J.-C. Raut, K.S. Law, J.P. Jalkanen, L. Johansson, A. Roiger, H. Schlager, et al. 2016. Air quality and radiative impacts of Arctic shipping emissions in the summertime in northern Norway: From the local to the regional scale. Atmospheric Chemistry and Physics 16: 2359–2379. doi: 10.5194/acp-16-2359-2016.CrossRefGoogle Scholar
- McClure-Begley, A., I. Petropavlovskikh, and S. Oltmans. 2014. NOAA Global Monitoring Surface Ozone Network 1973–2014. Boulder: National Oceanic and Atmospheric Administration, Earth Systems Research Laboratory Global Monitoring Division. Accessed 25 March 2016. doi: 10.7289/V57P8WBF.
- Myhre, G., T.F. Berglen, M. Johnsrud, C.R. Hoyle, T.K. Berntsen, S.A. Christopher, D.W. Fahey, I.S.A. Isaksen, et al. 2009. Modelled radiative forcing of the direct aerosol effect with multi-observation evaluation. Atmospheric Chemistry and Physics 9: 1365–1392. doi: 10.5194/acp-9-1365-2009.CrossRefGoogle Scholar
- Raut, J.-C., L. Marelle, J.D. Fast, J.L. Thomas, B. Weinzierl, K.S. Law, L.K. Berg, A. Roiger, et al. 2017. Cross-polar transport and scavenging of Siberian aerosols containing black carbon during the 2012 ACCESS summer campaign. Atmospheric Chemistry and Physics 17: 10969–10995. doi: 10.5194/acp-17-10969-2017.CrossRefGoogle Scholar
- Roiger, A., J.L. Thomas, H. Schlager, K.S. Law, J. Kim, A. Schafler, L. Marelle, J.-C. Raut, et al. 2015. Quantifying emerging local anthropogenic emissions in the Arctic region: The ACCESS aircraft campaign experiment. Bulletin of the American Meteorological Society. doi: 10.1175/BAMS-D-13-00169.1.CrossRefGoogle Scholar
- Stohl, A., Z. Klimont, S. Eckhardt, K. Kupiainen, V. Shevchenko, V.M. Kopeikin, and A.N. Novigatsky. 2013. Black carbon in the Arctic: The underestimated role of gas flaring and residential combustion emissions. Atmospheric Chemistry and Physics 13: 8833–8855. doi: 10.5194/acp-13-8833-2013.CrossRefGoogle Scholar
- Tuccella, P., J.L. Thomas, K.S. Law, J.-C. Raut, L. Marelle, A. Roiger, B. Weinzierl, and H.A.C. Denier van der Gon. 2017. Air pollution impacts due to petroleum extraction in the Norwegian Sea during the ACCESS aircraft campaign. Elementa: Science of the Anthropocene 5: 25. doi: 10.1525/elementa.124.CrossRefGoogle Scholar
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.