Parameterization of black carbon aging in the OsloCTM2 and implications for regional transport to the Arctic

Lund, Marianne T.; Berntsen, Terje

doi:10.5194/acp-12-6999-2012

Cited by 33 publications

(25 citation statements)

References 87 publications

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“…Indeed, changes in a model's aerosol scheme (i.e., treatment of microphysical properties and atmospheric removal of BC) can change simulated concentrations by more than an order of magnitude in remote regions such as the Arctic (Vignati et al, 2010). Implementing a more realistic aerosol microphysical scheme in one model increased the Arctic BC concentrations near the surface in winter, which is in better agreement with the observations, but at the same time it exacerbated the model overestimates at higher altitudes (Lund and Berntsen, 2012). Another study attributed the transition from high wintertime aerosol concentrations to low concentrations in the summer to the transition from ice-phase cloud scavenging to more efficient warm cloud scavenging, further amplified by the appearance of warm drizzling cloud in the late spring and summer boundary layer (Browse et al, 2012).…”

Section: Introductionsupporting

confidence: 78%

Black carbon in the Arctic: the underestimated role of gas flaring and residential combustion emissions

et al. 2013

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Arctic haze is a seasonal phenomenon with high concentrations of accumulation-mode aerosols occurring in the Arctic in winter and early spring. Chemistry transport models and climate chemistry models struggle to reproduce this phenomenon, and this has recently prompted changes in aerosol removal schemes to remedy the modeling problems. In this paper, we show that shortcomings in current emission data sets are at least as important. We perform a 3 yr model simulation of black carbon (BC) with the Lagrangian particle dispersion model FLEXPART. The model is driven with a new emission data set ("ECLIPSE emissions") which includes emissions from gas flaring. While gas flaring is estimated to contribute less than 3% of global BC emissions in this data set, flaring dominates the estimated BC emissions in the Arctic (north of 66° N). Putting these emissions into our model, we find that flaring contributes 42% to the annual mean BC surface concentrations in the Arctic. In March, flaring even accounts for 52% of all Arctic BC near the surface. Most of the flaring BC remains close to the surface in the Arctic, so that the flaring contribution to BC in the middle and upper troposphere is small. Another important factor determining simulated BC concentrations is the seasonal variation of BC emissions from residential combustion (often also called domestic combustion, which is used synonymously in this paper). We have calculated daily residential combustion emissions using the heating degree day (HDD) concept based on ambient air temperature and compare results from model simulations using emissions with daily, monthly and annual time resolution. In January, the Arctic-mean surface concentrations of BC due to residential combustion emissions are 150% higher when using daily emissions than when using annually constant emissions. While there are concentration reductions in summer, they are smaller than the winter increases, leading to a systematic increase of annual mean Arctic BC surface concentrations due to residential combustion by 68% when using daily emissions. A large part (93%) of this systematic increase can be captured also when using monthly emissions; the increase is compensated by a decreased BC burden at lower latitudes. In a comparison with BC measurements at six Arctic stations, we find that using daily-varying residential combustion emissions and introducing gas flaring emissions leads to large improvements of the simulated Arctic BC, both in terms of mean concentration levels and simulated seasonality. Case studies based on BC and carbon monoxide (CO) measurements from the Zeppelin observatory appear to confirm flaring as an important BC source that can produce pollution plumes in the Arctic with a high BC / CO enhancement ratio, as expected for this source type. BC measurements taken during a research ship cruise in the White, Barents and Kara seas north of the region with strong flaring emissions reveal very high concentrations of the order of 200–400 ng m⁻³. The model underestimates these concentr...

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Section: Introductionsupporting

confidence: 78%

Black carbon in the Arctic: the underestimated role of gas flaring and residential combustion emissions

et al. 2013

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“…Lack of understanding of pollutant deposition rates may be a key driver for the poor skill of many models in simulating the seasonal cycle and magnitude of aerosol pollutants when compared to Arctic measurements (AMAP, 2015;Eckhardt et al, 2015). In particular, disagreement with observations has been shown to be sensitive to the representation of wet scavenging and aerosol microphysical (e.g., black carbon aging) processes in models (e.g., Browse et al, 2012;Garrett et al, 2011;Liu et al, 2011;Lund and Berntsen, 2012). More recently, a model simulation using observed meteorology to reasonably simulate the seasonal cycle and vertical distribution of pollutants in the Arctic in the year 2008 found that aerosol wet scavenging was ∼3 times larger than dry scavenging in the Arctic (Breider et al, 2014).…”

Section: Processing Fate and Impacts Of Arctic Pollution On Climate mentioning

confidence: 99%

Arctic air pollution: Challenges and opportunities for the next decade

et al. 2016

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The Arctic is a sentinel of global change. This region is influenced by multiple physical and socio-economic drivers and feedbacks, impacting both the natural and human environment. Air pollution is one such driver that impacts Arctic climate change, ecosystems and health but significant uncertainties still surround quantification of these effects. Arctic air pollution includes harmful trace gases (e.g. tropospheric ozone) and particles (e.g. black carbon, sulphate) and toxic substances (e.g. polycyclic aromatic hydrocarbons) that can be transported to the Arctic from emission sources located far outside the region, or emitted within the Arctic from activities including shipping, power production, and other industrial activities. This paper qualitatively summarizes the complex science issues motivating the creation of a new international initiative, PACES (air Pollution in the Arctic: Climate, Environment and Societies). Approaches for coordinated, international and interdisciplinary research on this topic are described with the goal to improve predictive capability via new understanding about sources, processes, feedbacks and impacts of Arctic air pollution. Overarching research actions are outlined, in which we describe our recommendations for 1) the development of trans-disciplinary approaches combining social and economic research with investigation of the chemical and physical aspects Arctic air pollution: Challenges and opportunities for the next decade of Arctic air pollution; 2) increasing the quality and quantity of observations in the Arctic using long-term monitoring and intensive field studies, both at the surface and throughout the troposphere; and 3) developing improved predictive capability across a range of spatial and temporal scales. Domain Editor-in-Chief

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“…Koch et al (2009) evaluated Arctic atmospheric BC in AeroCom phase I models and found that increasing BC lifetime, which is accomplished by decreasing the aging rate or by reducing removal by ice clouds, has a large impact on BC surface concentrations in remote regions. Analysis of surface measurements at Barrow, Alaska, indicates that the seasonal cycle of "Arctic haze" is dominated by wet scavenging rather than efficiency of transport pathways from source regions (Garrett et al, 2010;Browse et al, 2012;Lund and Berntsen, 2012;Wang et al, 2013). Liu et al (2011) concluded that the simulation of BC in the Arctic is significantly improved by using a parameterization of BC aging rate that is proportional to the OH radical concentration, reducing dry deposition velocities over ice and snow, and decreasing ice cloud wet removal efficiency.…”

Section: Inter-model Deposition Variabilitymentioning

confidence: 99%

An AeroCom assessment of black carbon in Arctic snow and sea ice

et al. 2014

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Abstract. Though many global aerosols models prognose surface deposition, only a few models have been used to directly simulate the radiative effect from black carbon (BC) deposition to snow and sea ice. Here, we apply aerosol deposition fields from 25 models contributing to two phases of the Aerosol Comparisons between Observations and Models (AeroCom) project to simulate and evaluate within-snow BC concentrations and radiative effect in the Arctic. We accomplish this by driving the offline land and sea ice components of the Community Earth System Model with different deposition fields and meteorological conditions from 2004 to 2009, during which an extensive field campaign of BC measurements in Arctic snow occurred. We find that models generally underestimate BC concentrations in snow in northern Russia and Norway, while overestimating BC amounts elsewhere in the Arctic. Although simulated BC distributions in snow are poorly correlated with measurements, mean values are reasonable. The multi-model mean (range) bias in BC concentrations, sampled over the same grid cells, snow depths, and months of measurements, are for a more recent phase of AeroCom models (phase II), compared to the observational mean of 19.2 ng g −1 . Factors determining model BC concentrations in Arctic snow include Arctic BC emissions, transport of extra-Arctic aerosols, precipitation, deposition efficiency of aerosols within the Arctic, and meltwater removal of particles in snow. Sensitivity studies show that the model-measurement evaluation is only weakly affected by meltwater scavenging efficiency because most measurements were conducted in non-melting snow. The Arctic (60-90 • N) atmospheric residence time for BC in phase II models ranges from 3.7 to 23.2 days, implying large inter-model variation in local BC deposition efficiency. Combined with the fact that most Arctic BC deposition originates from extra-Arctic emissions, these results suggest that aerosol removal processes are a leading source of variation in model performance. The multi-model mean (full range) of Arctic radiative effect from BC in snow is 0.15 (0.07-0.25) W m −2 and 0.18 (0.06-0.28) W m −2 in phase I and phase II models, respectively. After correcting for model biases relative to observed BC concentrations in different regions of the Arctic, we obtain a multi-model mean Arctic radiative effect of 0.17 W m −2 for the combined AeroCom ensembles. Finally, there is a high correlation between modeled BC concentrations sampled over the observational sites and the Arctic as a whole, indicating that the field campaign provided a reasonable sample of the Arctic.

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Parameterization of black carbon aging in the OsloCTM2 and implications for regional transport to the Arctic

Cited by 33 publications

References 87 publications

Black carbon in the Arctic: the underestimated role of gas flaring and residential combustion emissions

Black carbon in the Arctic: the underestimated role of gas flaring and residential combustion emissions

Arctic air pollution: Challenges and opportunities for the next decade

An AeroCom assessment of black carbon in Arctic snow and sea ice

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