skip to main content


Title: An improved method for atmospheric <sup>14</sup>CO measurements
Abstract. Important uncertainties remain in our understanding of the spatial andtemporal variability of atmospheric hydroxyl radical concentration ([OH]).Carbon-14-containing carbon monoxide (14CO) is a useful tracer that canhelp in the characterization of [OH] variability. Prior measurements ofatmospheric 14CO concentration ([14CO] are limited in both theirspatial and temporal extent, partly due to the very large air sample volumes that have been required for measurements (500–1000 L at standardtemperature and pressure, L STP) and the difficulty and expense associatedwith the collection, shipment, and processing of such samples. Here wepresent a new method that reduces the air sample volume requirement to≈90 L STP while allowing for [14CO] measurement uncertainties that are on par with or better than prior work (≈3 % or better, 1σ). The method also for the first time includes accurate characterization of the overall procedural [14CO] blank associated with individual samples, which is a key improvement over prior atmospheric 14CO work. The method was used to make measurements of [14CO] at the NOAA Mauna Loa Observatory, Hawaii, USA, between November 2017 and November 2018. The measurements show the expected [14CO] seasonal cycle (lowest in summer)and are in good agreement with prior [14CO] results from anotherlow-latitude site in the Northern Hemisphere. The lowest overall [14CO]uncertainties (2.1 %, 1σ) are achieved for samples that aredirectly accompanied by procedural blanks and whose mass is increased to≈50 µgC (micrograms of carbon) prior to the 14Cmeasurement via dilution with a high-CO 14C-depleted gas.  more » « less
Award ID(s):
1920602
NSF-PAR ID:
10281380
Author(s) / Creator(s):
; ; ; ; ; ; ; ;
Date Published:
Journal Name:
Atmospheric Measurement Techniques
Volume:
14
Issue:
3
ISSN:
1867-8548
Page Range / eLocation ID:
2055 to 2063
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar (Populus nigra X P. maximowiczii), switchgrass (Panicum virgatum), miscanthus (Miscanthus giganteus), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha−1 year−1) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L−1) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha−1 year−1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may leach legacy P from past cropland management. Experimental details The Biofuel Cropping System Experiment (BCSE) is located at the W.K. Kellogg Biological Station (KBS) (42.3956° N, 85.3749° W; elevation 288 m asl) in southwestern Michigan, USA. This site is a part of the Great Lakes Bioenergy Research Center (www.glbrc.org) and is a Long-term Ecological Research site (www.lter.kbs.msu.edu). Soils are mesic Typic Hapludalfs developed on glacial outwash54 with high sand content (76% in the upper 150 cm) intermixed with silt-rich loess in the upper 50 cm55. The water table lies approximately 12–14 m below the surface. The climate is humid temperate with a mean annual air temperature of 9.1 °C and annual precipitation of 1005 mm, 511 mm of which falls between May and September (1981–2010)56,57. The BCSE was established as a randomized complete block design in 2008 on preexisting farmland. Prior to BCSE establishment, the field was used for grain crop and alfalfa (Medicago sativa L.) production for several decades. Between 2003 and 2007, the field received a total of ~ 300 kg P ha−1 as manure, and the southern half, which contains one of four replicate plots, received an additional 206 kg P ha−1 as inorganic fertilizer. The experimental design consists of five randomized blocks each containing one replicate plot (28 by 40 m) of 10 cropping systems (treatments) (Supplementary Fig. S1; also see Sanford et al.58). Block 5 is not included in the present study. Details on experimental design and site history are provided in Robertson and Hamilton57 and Gelfand et al.59. Leaching of P is analyzed in six of the cropping systems: (i) continuous no-till corn, (ii) switchgrass, (iii) miscanthus, (iv) a mixture of five species of native grasses, (v) a restored native prairie containing 18 plant species (Supplementary Table S1), and (vi) hybrid poplar. Agronomic management Phenological cameras and field observations indicated that the perennial herbaceous crops emerged each year between mid-April and mid-May. Corn was planted each year in early May. Herbaceous crops were harvested at the end of each growing season with the timing depending on weather: between October and November for corn and between November and December for herbaceous perennial crops. Corn stover was harvested shortly after corn grain, leaving approximately 10 cm height of stubble above the ground. The poplar was harvested only once, as the culmination of a 6-year rotation, in the winter of 2013–2014. Leaf emergence and senescence based on daily phenological images indicated the beginning and end of the poplar growing season, respectively, in each year. Application of inorganic fertilizers to the different crops followed a management approach typical for the region (Table 1). Corn was fertilized with 13 kg P ha−1 year−1 as starter fertilizer (N-P-K of 19-17-0) at the time of planting and an additional 33 kg P ha−1 year−1 was added as superphosphate in spring 2015. Corn also received N fertilizer around the time of planting and in mid-June at typical rates for the region (Table 1). No P fertilizer was applied to the perennial grassland or poplar systems (Table 1). All perennial grasses (except restored prairie) were provided 56 kg N ha−1 year−1 of N fertilizer in early summer between 2010 and 2016; an additional 77 kg N ha−1 was applied to miscanthus in 2009. Poplar was fertilized once with 157 kg N ha−1 in 2010 after the canopy had closed. Sampling of subsurface soil water and soil for P determination Subsurface soil water samples were collected beneath the root zone (1.2 m depth) using samplers installed at approximately 20 cm into the unconsolidated sand of 2Bt2 and 2E/Bt horizons (soils at the site are described in Crum and Collins54). Soil water was collected from two kinds of samplers: Prenart samplers constructed of Teflon and silica (http://www.prenart.dk/soil-water-samplers/) in replicate blocks 1 and 2 and Eijkelkamp ceramic samplers (http://www.eijkelkamp.com) in blocks 3 and 4 (Supplementary Fig. S1). The samplers were installed in 2008 at an angle using a hydraulic corer, with the sampling tubes buried underground within the plots and the sampler located about 9 m from the plot edge. There were no consistent differences in TDP concentrations between the two sampler types. Beginning in the 2009 growing season, subsurface soil water was sampled at weekly to biweekly intervals during non-frozen periods (April–November) by applying 50 kPa of vacuum to each sampler for 24 h, during which the extracted water was collected in glass bottles. Samples were filtered using different filter types (all 0.45 µm pore size) depending on the volume of leachate collected: 33-mm dia. cellulose acetate membrane filters when volumes were less than 50 mL; and 47-mm dia. Supor 450 polyethersulfone membrane filters for larger volumes. Total dissolved phosphorus (TDP) in water samples was analyzed by persulfate digestion of filtered samples to convert all phosphorus forms to soluble reactive phosphorus, followed by colorimetric analysis by long-pathlength spectrophotometry (UV-1800 Shimadzu, Japan) using the molybdate blue method60, for which the method detection limit was ~ 0.005 mg P L−1. Between 2009 and 2016, soil samples (0–25 cm depth) were collected each autumn from all plots for determination of soil test P (STP) by the Bray-1 method61, using as an extractant a dilute hydrochloric acid and ammonium fluoride solution, as is recommended for neutral to slightly acidic soils. The measured STP concentration in mg P kg−1 was converted to kg P ha−1 based on soil sampling depth and soil bulk density (mean, 1.5 g cm−3). Sampling of water samples from lakes, streams and wells for P determination In addition to chemistry of soil and subsurface soil water in the BCSE, waters from lakes, streams, and residential water supply wells were also sampled during 2009–2016 for TDP analysis using Supor 450 membrane filters and the same analytical method as for soil water. These water bodies are within 15 km of the study site, within a landscape mosaic of row crops, grasslands, deciduous forest, and wetlands, with some residential development (Supplementary Fig. S2, Supplementary Table S2). Details of land use and cover change in the vicinity of KBS are given in Hamilton et al.48, and patterns in nutrient concentrations in local surface waters are further discussed in Hamilton62. Leaching estimates, modeled drainage, and data analysis Leaching was estimated at daily time steps and summarized as total leaching on a crop-year basis, defined from the date of planting or leaf emergence in a given year to the day prior to planting or emergence in the following year. TDP concentrations (mg L−1) of subsurface soil water were linearly interpolated between sampling dates during non-freezing periods (April–November) and over non-sampling periods (December–March) based on the preceding November and subsequent April samples. Daily rates of TDP leaching (kg ha−1) were calculated by multiplying concentration (mg L−1) by drainage rates (m3 ha−1 day−1) modeled by the Systems Approach for Land Use Sustainability (SALUS) model, a crop growth model that is well calibrated for KBS soil and environmental conditions. SALUS simulates yield and environmental outcomes in response to weather, soil, management (planting dates, plant population, irrigation, N fertilizer application, and tillage), and genetics63. The SALUS water balance sub-model simulates surface runoff, saturated and unsaturated water flow, drainage, root water uptake, and evapotranspiration during growing and non-growing seasons63. The SALUS model has been used in studies of evapotranspiration48,51,64 and nutrient leaching20,65,66,67 from KBS soils, and its predictions of growing-season evapotranspiration are consistent with independent measurements based on growing-season soil water drawdown53 and evapotranspiration measured by eddy covariance68. Phosphorus leaching was assumed insignificant on days when SALUS predicted no drainage. Volume-weighted mean TDP concentrations in leachate for each crop-year and for the entire 7-year study period were calculated as the total dissolved P leaching flux (kg ha−1) divided by the total drainage (m3 ha−1). One-way ANOVA with time (crop-year) as the fixed factor was conducted to compare total annual drainage rates, P leaching rates, volume-weighted mean TDP concentrations, and maximum aboveground biomass among the cropping systems over all seven crop-years as well as with TDP concentrations from local lakes, streams, and groundwater wells. When a significant (α = 0.05) difference was detected among the groups, we used the Tukey honest significant difference (HSD) post-hoc test to make pairwise comparisons among the groups. In the case of maximum aboveground biomass, we used the Tukey–Kramer method to make pairwise comparisons among the groups because the absence of poplar data after the 2013 harvest resulted in unequal sample sizes. We also used the Tukey–Kramer method to compare the frequency distributions of TDP concentrations in all of the soil leachate samples with concentrations in lakes, streams, and groundwater wells, since each sample category had very different numbers of measurements. Individual spreadsheets in “data table_leaching_dissolved organic carbon and nitrogen.xls” 1.    annual precip_drainage 2.    biomass_corn, perennial grasses 3.    biomass_poplar 4.    annual N leaching _vol-wtd conc 5.    Summary_N leached 6.    annual DOC leachin_vol-wtd conc 7.    growing season length 8.    correlation_nh4 VS no3 9.    correlations_don VS no3_doc VS don Each spreadsheet is described below along with an explanation of variates. Note that ‘nan’ indicate data are missing or not available. First row indicates header; second row indicates units 1. Spreadsheet: annual precip_drainage Description: Precipitation measured from nearby Kellogg Biological Station (KBS) Long Term Ecological Research (LTER) Weather station, over 2009-2016 study period. Data shown in Figure 1; original data source for precipitation (https://lter.kbs.msu.edu/datatables/7). Drainage estimated from SALUS crop model. Note that drainage is percolation out of the root zone (0-125 cm). Annual precipitation and drainage values shown here are calculated for growing and non-growing crop periods. Variate    Description year    year of the observation crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” precip_G    precipitation during growing period (milliMeter) precip_NG    precipitation during non-growing period (milliMeter) drainage_G    drainage during growing period (milliMeter) drainage_NG    drainage during non-growing period (milliMeter)      2. Spreadsheet: biomass_corn, perennial grasses Description: Maximum aboveground biomass measurements from corn, switchgrass, miscanthus, native grass and restored prairie plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2.   Variate    Description year    year of the observation date    day of the observation (mm/dd/yyyy) crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” replicate    each crop has four replicated plots, R1, R2, R3 and R4 station    stations (S1, S2 and S3) of samplings within the plot. For more details, refer to link (https://data.sustainability.glbrc.org/protocols/156) species    plant species that are rooted within the quadrat during the time of maximum biomass harvest. See protocol for more information, refer to link (http://lter.kbs.msu.edu/datatables/36) For maize biomass, grain and whole biomass reported in the paper (weed biomass or surface litter are excluded). Surface litter biomass not included in any crops; weed biomass not included in switchgrass and miscanthus, but included in grass mixture and prairie. fraction    Fraction of biomass biomass_plot    biomass per plot on dry-weight basis (Grams_Per_SquareMeter) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying column biomass per plot with 0.01 3. Spreadsheet: biomass_poplar Description: Maximum aboveground biomass measurements from poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Data shown in Figure 2. Note that poplar biomass was estimated from crop growth curves until the poplar was harvested in the winter of 2013-14. Variate    Description year    year of the observation method    methods of poplar biomass sampling date    day of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 diameter_at_ground    poplar diameter (milliMeter) at the ground diameter_at_15cm    poplar diameter (milliMeter) at 15 cm height biomass_tree    biomass per plot (Grams_Per_Tree) biomass_ha    biomass (megaGrams_Per_Hectare) by multiplying biomass per tree with 0.01 4. Spreadsheet: annual N leaching_vol-wtd conc Description: Annual leaching rate (kiloGrams_N_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_N_Per_Liter) of nitrate (no3) and dissolved organic nitrogen (don) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen leached and volume-wtd mean N concentration shown in Figure 3a and Figure 3b, respectively. Note that ammonium (nh4) concentration were much lower and often undetectable (<0.07 milliGrams_N_Per_Liter). Also note that in 2009 and 2010 crop-years, data from some replicates are missing.    Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) vol-wtd no3 conc.    Volume-weighted mean no3 concentration (milliGrams_N_Per_Liter) vol-wtd don conc.    Volume-weighted mean don concentration (milliGrams_N_Per_Liter) 5. Spreadsheet: summary_N leached Description: Summary of total amount and forms of N leached (kiloGrams_N_Per_Hectare) and the percent of applied N lost to leaching over the seven years for corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for nitrogen amount leached shown in Figure 4a and percent of applied N lost shown in Figure 4b. Note the fraction of unleached N includes in harvest, accumulation in root biomass, soil organic matter or gaseous N emissions were not measured in the study. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” no3 leached    annual leaching rates of nitrate (kiloGrams_N_Per_Hectare) don leached    annual leaching rates of don (kiloGrams_N_Per_Hectare) N unleached    N unleached (kiloGrams_N_Per_Hectare) in other sources are not studied % of N applied N lost to leaching    % of N applied N lost to leaching 6. Spreadsheet: annual DOC leachin_vol-wtd conc Description: Annual leaching rate (kiloGrams_Per_Hectare) and volume-weighted mean N concentrations (milliGrams_Per_Liter) of dissolved organic carbon (DOC) in the leachate samples collected from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2016. Data for DOC leached and volume-wtd mean DOC concentration shown in Figure 5a and Figure 5b, respectively. Note that in 2009 and 2010 crop-years, water samples were not available for DOC measurements.     Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” crop-year    year of the observation replicate    each crop has four replicated plots, R1, R2, R3 and R4 doc leached    annual leaching rates of nitrate (kiloGrams_Per_Hectare) vol-wtd doc conc.    volume-weighted mean doc concentration (milliGrams_Per_Liter) 7. Spreadsheet: growing season length Description: Growing season length (days) of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in the Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2009-2015. Date shown in Figure S2. Note that growing season is from the date of planting or emergence to the date of harvest (or leaf senescence in case of poplar).   Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation growing season length    growing season length (days) 8. Spreadsheet: correlation_nh4 VS no3 Description: Correlation of ammonium (nh4+) and nitrate (no3-) concentrations (milliGrams_N_Per_Liter) in the leachate samples from corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data shown in Figure S3. Note that nh4+ concentration in the leachates was very low compared to no3- and don concentration and often undetectable in three crop-years (2013-2015) when measurements are available. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” date    date of the observation (mm/dd/yyyy) replicate    each crop has four replicated plots, R1, R2, R3 and R4 nh4 conc    nh4 concentration (milliGrams_N_Per_Liter) no3 conc    no3 concentration (milliGrams_N_Per_Liter)   9. Spreadsheet: correlations_don VS no3_doc VS don Description: Correlations of don and nitrate concentrations (milliGrams_N_Per_Liter); and doc (milliGrams_Per_Liter) and don concentrations (milliGrams_N_Per_Liter) in the leachate samples of corn, switchgrass, miscanthus, native grass, restored prairie and poplar plots in Great Lakes Bioenergy Research Center (GLBRC) Biomass Cropping System Experiment (BCSE) during 2013-2015. Data of correlation of don and nitrate concentrations shown in Figure S4 a and doc and don concentrations shown in Figure S4 b. Variate    Description crop    “corn” “switchgrass” “miscanthus” “nativegrass” “restored prairie” “poplar” year    year of the observation don    don concentration (milliGrams_N_Per_Liter) no3     no3 concentration (milliGrams_N_Per_Liter) doc    doc concentration (milliGrams_Per_Liter) 
    more » « less
  2. Abstract. The Southern Ocean is highly under-sampled for the purpose of assessing total carbon uptake and its variability. Since this region dominates the mean global ocean sink for anthropogenic carbon, understanding temporal change is critical. Underway measurements of pCO2 collected as part of the Drake Passage Time-series (DPT) program that began in 2002 inform our understanding of seasonally changing air–sea gradients in pCO2, and by inference the carbon flux in this region. Here, we utilize available pCO2 observations to evaluate how the seasonal cycle, interannual variability, and long-term trends in surface ocean pCO2 in the Drake Passage region compare to that of the broader subpolar Southern Ocean. Our results indicate that the Drake Passage is representative of the broader region in both seasonality and long-term pCO2 trends, as evident through the agreement of timing and amplitude of seasonal cycles as well as trend magnitudes both seasonally and annually. The high temporal density of sampling by the DPT is critical to constraining estimates of the seasonal cycle of surface pCO2 in this region, as winter data remain sparse in areas outside of the Drake Passage. An increase in winter data would aid in reduction of uncertainty levels. On average over the period 2002–2016, data show that carbon uptake has strengthened with annual surface ocean pCO2 trends in the Drake Passage and the broader subpolar Southern Ocean less than the global atmospheric trend. Analysis of spatial correlation shows Drake Passage pCO2 to be representative of pCO2 and its variability up to several hundred kilometers away from the region. We also compare DPT data from 2016 and 2017 to contemporaneous pCO2 estimates from autonomous biogeochemical floats deployed as part of the Southern Ocean Carbon and Climate Observations and Modeling project (SOCCOM) so as to highlight the opportunity for evaluating data collected on autonomous observational platforms. Though SOCCOM floats sparsely sample the Drake Passage region for 2016–2017 compared to the Drake Passage Time-series, their pCO2 estimates fall within the range of underway observations given the uncertainty on the estimates. Going forward, continuation of the Drake Passage Time-series will reduce uncertainties in Southern Ocean carbon uptake seasonality, variability, and trends, and provide an invaluable independent dataset for post-deployment assessment of sensors on autonomous floats. Together, these datasets will vastly increase our ability to monitor change in the ocean carbon sink. 
    more » « less
  3. Abstract. This study considersyear-to-year and decadal variations in as well as secular trendsof the sea–air CO2 flux over the 1957–2020 period,as constrained by the pCO2 measurements from the SOCATv2021 database.In a first step,we relate interannual anomalies in ocean-internal carbon sources and sinksto local interannual anomalies insea surface temperature (SST), the temporal changes in SST (dSST/dt),and squared wind speed (u2),employing a multi-linear regression.In the tropical Pacific, we find interannual variability to be dominated by dSST/dt,as arising from variations in the upwelling of colder and more carbon-rich waters into the mixed layer.In the eastern upwelling zones as well as in circumpolar bands in the high latitudes of both hemispheres,we find sensitivity to wind speed,compatible with the entrainment of carbon-rich water during wind-driven deepening of the mixed layerand wind-driven upwelling.In the Southern Ocean,the secular increase in wind speed leads to a secular increase in the carbon source into the mixed layer,with an estimated reduction in the sink trend in the range of 17 % to 42 %.In a second step,we combined the result of the multi-linear regression andan explicitly interannual pCO2-based additive correctioninto a “hybrid” estimate of the sea–air CO2 flux over the period 1957–2020.As a pCO2 mapping method,it combines (a) the ability of a regression to bridge data gaps and extrapolate intothe early decades almost void of pCO2 databased on process-related observablesand (b) the ability of an auto-regressive interpolation to follow signalseven if not represented in the chosen set of explanatory variables.The “hybrid” estimate can be applied as an ocean flux prior foratmospheric CO2 inversions covering the whole period of atmospheric CO2 data since 1957. 
    more » « less
  4. null (Ed.)
    Abstract. Reactions of the hydroxyl (OH) and peroxy (HO2 and RO2) radicals playa central role in the chemistry of the atmosphere. In addition to controlling the lifetimes ofmany trace gases important to issues of global climate change, OH radical reactionsinitiate the oxidation of volatile organic compounds (VOCs) which can lead to the production ofozone and secondary organic aerosols in the atmosphere. Previous measurements of these radicalsin forest environments characterized by high mixing ratios of isoprene and low mixing ratios ofnitrogen oxides (NOx) (typically less than 1–2 ppb) have shown seriousdiscrepancies with modeled concentrations. These results bring into question our understanding ofthe atmospheric chemistry of isoprene and other biogenic VOCs under low NOxconditions. During the summer of 2015, OH and HO2 radical concentrations, as well as totalOH reactivity, were measured using laser-induced fluorescence–fluorescence assay by gasexpansion (LIF-FAGE) techniques as part of the Indiana Radical Reactivity and Ozone productioN InterComparison (IRRONIC). This campaign took place in a forested area near Indiana University's Bloomington campus which is characterized by high mixing ratios of isoprene (average daily maximum ofapproximately 4 ppb at 28 ∘C) and low mixing ratios of NO (diurnal averageof approximately 170 ppt). Supporting measurements of photolysis rates, VOCs,NOx, and other species were used to constrain a zero-dimensional box model basedon the Regional Atmospheric Chemistry Mechanism (RACM2) and the Master Chemical Mechanism (MCM 3.2),including versions of the Leuven isoprene mechanism (LIM1) for HOx regeneration(RACM2-LIM1 and MCM 3.3.1). Using an OH chemical scavenger technique, the study revealed thepresence of an interference with the LIF-FAGE measurements of OH that increased with bothambient concentrations of ozone and temperature with an average daytime maximum equivalentOH concentration of approximately 5×106 cm−3. Subtraction of theinterference resulted in measured OH concentrations of approximately4×106 cm−3 (average daytime maximum) that were in better agreement with modelpredictions although the models underestimated the measurements in the evening. The addition ofversions of the LIM1 mechanism increased the base RACM2 and MCM 3.2 modeled OH concentrationsby approximately 20 % and 13 %, respectively, with the RACM2-LIM1 mechanism providing thebest agreement with the measured concentrations, predicting maximum daily OH concentrationsto within 30 % of the measured concentrations. Measurements of HO2 concentrationsduring the campaign (approximately a 1×109 cm−3 average daytime maximum)included a fraction of isoprene-based peroxy radicals(HO2*=HO2+αRO2) and were found to agree with modelpredictions to within 10 %–30 %. On average, the measured reactivity was consistent with thatcalculated from measured OH sinks to within 20 %, with modeled oxidation productsaccounting for the missing reactivity, however significant missing reactivity (approximately40 % of the total measured reactivity) was observed on some days. 
    more » « less
  5. null (Ed.)
    Abstract. Reactive mercury (RM), the sum of both gaseous oxidized Hg and particulatebound Hg, is an important component of the global atmospheric mercury cycle,but measurement currently depends on uncalibrated operationally definedmethods with large uncertainty and demonstrated interferences and artifacts.Cation exchange membranes (CEMs) provide a promising alternative methodologyfor quantification of RM, but method validation and improvements are ongoing.For the CEM material to be reliable, uptake of gaseous elemental mercury(GEM) must be negligible under all conditions and RM compounds must becaptured and retained with high efficiency. In this study, the performance ofCEM material under exposure to high concentrations of GEM (1.43×106 to 1.85×106 pg m−3) and reactive gaseous mercurybromide (HgBr2 ∼5000 pg m−3) was explored using acustom-built mercury vapor permeation system. Quantification of totalpermeated Hg was measured via pyrolysis at 600 ∘C and detectionusing a Tekran® 2537A. Permeation tests wereconducted over 24 to 72 h in clean laboratory air, with absolute humiditylevels ranging from 0.1 to 10 g m−3 water vapor. GEM uptake by the CEMmaterial averaged no more than 0.004 % of total exposure for all testconditions, which equates to a non-detectable GEM artifact for typicalambient air sample concentrations. Recovery of HgBr2 on CEM filters wason average 127 % compared to calculated total permeated HgBr2 based onthe downstream Tekran® 2537A data. The lowHgBr2 breakthrough on the downstream CEMs (< 1 %) suggests thatthe elevated recoveries are more likely related to suboptimal pyrolyzerconditions or inefficient collection on the Tekran® 2537A gold traps. 
    more » « less