Person: Fisher, Jenny
Loading...
Email Address
AA Acceptance Date
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Fisher
First Name
Jenny
Name
Fisher, Jenny
6 results
Search Results
Now showing 1 - 6 of 6
Publication A mass budget for mercury and methylmercury in the Arctic Ocean(Wiley-Blackwell, 2016) Soerensen, Anne; Jacob, Daniel; Schartup, Amina; Fisher, Jenny; Lehnherr, Igor; St. Louis, Vincent L.; Heimbürger, Lars-Eric; Sonke, Jeroen E.; Krabbenhoft, David P.; Sunderland, ElynorElevated biological concentrations of methylmercury (MeHg), a bioaccumulative neurotoxin, are observed throughout the Arctic Ocean, but major sources and degradation pathways in seawater are not well understood. We develop a mass budget for mercury species in the Arctic Ocean based on available data since 2004 and discuss implications and uncertainties. Our calculations show that high total mercury (Hg) in Arctic seawater relative to other basins reflect large freshwater inputs and sea ice cover that inhibits losses through evasion. We find that most net MeHg production (20 Mg a−1) occurs in the subsurface ocean (20–200 m). There it is converted to dimethylmercury (Me2Hg: 17 Mg a−1), which diffuses to the polar mixed layer and evades to the atmosphere (14 Mg a−1). Me2Hg has a short atmospheric lifetime and rapidly degrades back to MeHg. We postulate that most evaded Me2Hg is redeposited as MeHg and that atmospheric deposition is the largest net MeHg source (8 Mg a−1) to the biologically productive surface ocean. MeHg concentrations in Arctic Ocean seawater are elevated compared to lower latitudes. Riverine MeHg inputs account for approximately 15% of inputs to the surface ocean (2.5 Mg a−1) but greater importance in the future is likely given increasing freshwater discharges and permafrost melt. This may offset potential declines driven by increasing evasion from ice-free surface waters. Geochemical model simulations illustrate that for the most biologically relevant regions of the ocean, regulatory actions that decrease Hg inputs have the capacity to rapidly affect aquatic Hg concentrations.Publication Meteorological Modes of Variability for Fine Particulate Matter (PM2.5) Air Quality in the United States: Implications for PM2.5 Sensitivity to Climate Change(European Geosciences Union, 2012) Tai, A. P. K.; Mickley, Loretta; Jacob, Daniel; Leibensperger, Eric Michael; Zhang, L.; Fisher, Jenny; Pye, H. O. T.We applied a multiple linear regression model to understand the relationships of PM2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM2.5 to climate change. We used 2004–2008 PM2.5 observations from ~1000 sites (~200 sites for PM2.5 components) and compared to results from the GEOS-Chem chemical transport model (CTM). All data were deseasonalized to focus on synoptic-scale correlations. We find strong positive correlations of PM2.5 components with temperature in most of the US, except for nitrate in the Southeast where the correlation is negative. Relative humidity (RH) is generally positively correlated with sulfate and nitrate but negatively correlated with organic carbon. GEOS-Chem results indicate that most of the correlations of PM2.5 with temperature and RH do not arise from direct dependence but from covariation with synoptic transport. We applied principal component analysis and regression to identify the dominant meteorological modes controlling PM2.5 variability, and show that 20–40% of the observed PM2.5 day-to-day variability can be explained by a single dominant meteorological mode: cold frontal passages in the eastern US and maritime inflow in the West. These and other synoptic transport modes drive most of the overall correlations of PM2.5 with temperature and RH except in the Southeast. We show that interannual variability of PM2.5 in the US Midwest is strongly correlated with cyclone frequency as diagnosed from a spectral-autoregressive analysis of the dominant meteorological mode. An ensemble of five realizations of 1996–2050 climate change with the GISS general circulation model (GCM) using the same climate forcings shows inconsistent trends in cyclone frequency over the Midwest (including in sign), with a likely decrease in cyclone frequency implying an increase in PM2.5. Our results demonstrate the need for multiple GCM realizations (because of climate chaos) when diagnosing the effect of climate change on PM2.5, and suggest that analysis of meteorological modes of variability provides a computationally more affordable approach for this purpose than coupled GCM-CTM studies.Publication Gas-Particle Partitioning of Atmospheric Hg(II) and Its Effect on Global Mercury Deposition(Copernicus GmbH, 2012) Amos, Helen; Jacob, Daniel; Holmes, C. D.; Fisher, Jenny; Wang, Qiaoqiao; Yantosca, Robert; Corbitt, Elizabeth Sturges; Galarneau, E.; Rutter, A. P.; Gustin, M. S.; Steffen, A.; Schauer, J. J.; Graydon, J. A.; Louis, V. L. St.; Talbot, R. W.; Edgerton, E. S.; Zhang, Y.; Sunderland, ElynorAtmospheric deposition of Hg(II) represents a major input of mercury to surface environments. The phase of Hg(II) (gas or particle) has important implications for deposition. We use long-term observations of reactive gaseous mercury (RGM, the gaseous component of Hg(II)), particle-bound mercury (PBM, the particulate component of Hg(II)), fine particulate matter (PM2.5), and temperature (T) at five sites in North America to derive an empirical gas-particle partitioning relationship log10(K−1) = (10±1)–(2500±300)/T where K = (PBM/PM2.5)/RGM with PBM and RGM in common mixing ratio units, PM2.5 in μg m−3, and T in K. This relationship is within the range of previous work but is based on far more extensive data from multiple sites. We implement this empirical relationship in the GEOS-Chem global 3-D Hg model to partition Hg(II) between the gas and particle phases. The resulting gas-phase fraction of Hg(II) ranges from over 90 % in warm air with little aerosol to less than 10 % in cold air with high aerosol. Hg deposition to high latitudes increases because of more efficient scavenging of particulate Hg(II) by precipitating snow. Model comparison to Hg observations at the North American surface sites suggests that subsidence from the free troposphere (warm air, low aerosol) is a major factor driving the seasonality of RGM, while elevated PBM is mostly associated with high aerosol loads. Simulation of RGM and PBM at these sites is improved by including fast in-plume reduction of Hg(II) emitted from coal combustion and by assuming that anthropogenic particulate Hg(p) behaves as semi-volatile Hg(II) rather than as a refractory particulate component. We improve the simulation of Hg wet deposition fluxes in the US relative to a previous version of GEOS-Chem; this largely reflects independent improvement of the washout algorithm. The observed wintertime minimum in wet deposition fluxes is attributed to inefficient snow scavenging of gas-phase Hg(II).Publication Riverine source of Arctic Ocean mercury inferred from atmospheric observations(Springer Nature, 2012) Fisher, Jenny; Jacob, Daniel; Soerensen, Anne; Amos, Helen; Steffen, Alexandra; Sunderland, Elsie M.Methylmercury is a potent neurotoxin that accumulates in aquatic food webs. Human activities, including industry and mining, have increased inorganic mercury inputs to terrestrial and aquatic ecosystems. Methylation of this mercury generates methylmercury, and is thus a public health concern. Marine methylmercury is a particular concern in the Arctic, where indigenous peoples rely heavily on marine-based diets. In the summer, atmospheric inorganic mercury concentrations peak in the Arctic, whereas they reach a minimum in the northern mid-latitudes. Here, we use a global three-dimensional ocean–atmosphere model to examine the cause of this Arctic summertime maximum. According to our simulations, circumpolar rivers deliver large quantities of mercury to the Arctic Ocean during summer; the subsequent evasion of this riverine mercury to the atmosphere can explain the summertime peak in atmospheric mercury levels. We infer that rivers are the dominant source of mercury to the Arctic Ocean on an annual basis. Our simulations suggest that Arctic Ocean mercury concentrations could be highly sensitive to climate-induced changes in river flow, and to increases in the mobility of mercury in soils, for example as a result of permafrost thaw and forest fires.Publication Sources of carbonaceous aerosols and deposited black carbon in the Arctic in winter-spring: implications for radiative forcing(European Geosciences Union, 2011) Wang, Qiaoqiao; Jacob, Daniel; Fisher, Jenny; Mao, Jialin; Leibensperger, Eric Michael; Carouge, C. C.; Le Sager, P; Kondo, Y.; Jimenez, J. L.; Cubison, M. J.; Doherty, S. J.We use a global chemical transport model (GEOS-Chem CTM) to interpret observations of black carbon (BC) and organic aerosol (OA) from the NASA ARCTAS aircraft campaign over the North American Arctic in April 2008, as well as longer-term records in surface air and in snow (2007–2009). BC emission inventories for North America, Europe, and Asia in the model are tested by comparison with surface air observations over these source regions. Russian open fires were the dominant source of OA in the Arctic troposphere during ARCTAS but we find that BC was of prevailingly anthropogenic (fossil fuel and biofuel) origin, particularly in surface air. This source attribution is confirmed by correlation of BC and OA with acetonitrile and sulfate in the model and in the observations. Asian emissions are the main anthropogenic source of BC in the free troposphere but European, Russian and North American sources are also important in surface air. Russian anthropogenic emissions appear to dominate the source of BC in Arctic surface air in winter. Model simulations for 2007–2009 (to account for interannual variability of fires) show much higher BC snow content in the Eurasian than the North American Arctic, consistent with the limited observations. We find that anthropogenic sources contribute 90% of BC deposited to Arctic snow in January-March and 60% in April–May 2007–2009. The mean decrease in Arctic snow albedo from BC deposition is estimated to be 0.6% in spring, resulting in a regional surface radiative forcing consistent with previous estimates.Publication Error Correlation Between CO2 and CO as Constraint for CO2 Flux Inversions Using Satellite Data(Copernicus Publications, 2009) Wang, Huiming; Jacob, Daniel; Kopacz, Monika; Jones, D.B.A.; Suntharalingam, P.; Fisher, Jenny; Nassar, R.; Pawson, S.; Nielsen, J.E.Inverse modeling of CO2 satellite observations to better quantify carbon surface fluxes requires a chemical transport model (CTM) to relate the fluxes to the observed column concentrations. CTM transport error is a major source of uncertainty. We show that its effect can be reduced by using CO satellite observations as additional constraint in a joint CO2-CO inversion. CO is measured from space with high precision, is strongly correlated with CO2, and is more sensitive than CO2 to CTM transport errors on synoptic and smaller scales. Exploiting this constraint requires statistics for the CTM transport error correlation between CO2 and CO, which is significantly different from the correlation between the concentrations themselves. We estimate the error correlation globally and for different seasons by a paired-model method (comparing GEOS-Chem CTM simulations of CO2 and CO columns using different assimilated meteorological data sets for the same meteorological year) and a paired-forecast method (comparing 48- vs. 24-h GEOS-5 CTM forecasts of CO2 and CO columns for the same forecast time). We find strong error correlations (r2>0.5) between CO2 and CO columns over much of the extra-tropical Northern Hemisphere throughout the year, and strong consistency between different methods to estimate the error correlation. Application of the averaging kernels used in the retrieval for thermal IR CO measurements weakens the correlation coefficients by 15% on average (mostly due to variability in the averaging kernels) but preserves the large-scale correlation structure. We present a simple inverse modeling application to demonstrate that CO2-CO error correlations can indeed significantly reduce uncertainty on surface carbon fluxes in a joint CO2-CO inversion vs. a CO2-only inversion.