Persistent Heavy Winter Nitrate Pollution Driven by Increased Photochemical Oxidants in Northern China
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Poster for the Gordon Research Conference Applied and Environmental Microbiology, July 16-21 2023, South Hadley, MA.
The idea of covalency being directly correlated with selectivity in f-element separations has gained attention over the years. However, “covalency” as a concept is still under debate as it is not an experimental nor quantum mechanical observable. Regardless, covalency along with ionicity are still the main concepts used to explain the nature of the chemical bond of coordination complexes. Another concept that has gained the attention in the separations community is the hard-soft acid-base (HSAB) theory, which favors soft-donor ligands having the potential to increase selectivity for actinides (An) over the lanthanides (Ln) due to their ability to engage more effectively f-electrons in covalent interactions. However, it has been shown that while using softer donor ligands in fact increased orbital mixing and covalency with the actinides, it compromises the strength of the interaction owing to a decrease in the metal-ligand electrostatic interactions.1 Herein, we study the electronic structure of different types of chalcogenide ligands (LE, E = O, S, Se), their interaction with the uranyl ion, and their complexation free energies. Surprisingly, contrary to the expected order of covalency, i.e. An–LSe > An–LS > An–LO, our results suggest that the degree of covalency and associated complexation free energies depend on the nature of the coordinating moiety rather than solely on the directly coordinated atom. 1) Sadhu, Biswajit, and Michael Dolg. Enhancing actinide (III) over lanthanide (III) selectivity through hard-by-soft donor substitution: exploitation and implication of near-degeneracy-driven covalency. Inorganic Chemistry, 2019, 58, 9738 – 9748.
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Groundwater acidification co-occurring with nitrate pollution is a common, global environmental health hazard. Denitrifying bacteria have been leveraged for the in situ removal of nitrate in groundwater. However, co-existing stressors—such as low pH—reduce the efficacy of biological removal processes. Castellaniella sp. str. MT123 is a complete denitrifier that was isolated from acidic, nitrate-contaminated groundwater. The strain grows robustly by nitrate respiration at pH < 6.0, completely reducing nitrate to dinitrogen gas. Genomic analyses of MT123 revealed few previously characterized acid tolerance genes. Thus, we utilized a combination of proteomics, metabolomics, and competitive mutant fitness to characterize the genetic mechanisms of MT123 acclimation to growth under mildly acidic conditions. We found that glutamate accumulation is critical in the acid acclimation of MT123, possibly through consumption of intracellular protons via glutamate decarboxylation to GABA. This is despite the fact that MT123 lacks the canonical glutamate decarboxylase-glutamate/GABA antiporter system implicated in acid tolerance in other bacteria. In contrast, branched-chain amino acid (BCAA) accumulation was detrimental to cell growth at lower pHs, possibly through indirect mechanisms impacting the cellular glutamate pool. Genetic analysis previously linked MT123 to a population of Castellaniella that bloomed—concurrent to nitrate removal—during a biostimulation effort to reduce groundwater nitrate concentrations at MT123’s location of origin. Thus, our analyses provide novel insight into mechanisms of acclimation to acidic conditions in a strain with significant potential for nitrate bioremediation.
Introduction In the reprocessing of f-elements present in used nuclear fuels, a variety of diglycolamides (DGA’s) are used as extractants for actinide partitioning. In particular, the Actinide-Lanthanide Separation (ALSEP) process typically utilizes either the N,N,N’,N’-tetraoctyl diglycolamide (TODGA) or N,N,N',N'-tetra-2-ethylhexyl diglycolamide (T2EHDGA) extractant ligands following the partitioning of uranium and plutonium from used nuclear fuel. To better understand fundamental interactions in these processes, covalent bonding of several f-elements with diglycolamides, primarily TODGA, is investigated in the gas phase using nanospray ionization and a quadrupole time-of-flight mass spectrometer. Further, analysis of the identity and relative strength of the cluster is enabled by MS2 isolation and collision induced dissociation. Methods Metal ion cluster analysis was completed using a Bruker mircOTOF-Q II quadrupole time-of-flight mass spectrometer equipped with a CaptiveSpray nanospray ion source. Metal:ligand solutions were prepared as 30 µM europium nitrate, samarium nitrate, cerium nitrate, or holmium nitrate and 3 µM DGA in acetonitrile or a 50:50 mixture of acetonitrile: isopropanol. Cluster mass spectra and collision-induced dissociation experiments were conducted in positive mode. Preliminary data To examine the patterns and relative strength of lanthanide: DGA interactions, MS2 experiments were completed with each lanthanide species listed above. Preliminary analyses of samarium and europium TODGA clusters suggest several combinations of TODGA and nitrate forming. The samarium cluster experiments yielded Sm(TODGA)x clusters with a samarium:TODGA ratio of up to 1:7 able to be isolated and evidence of greater ratios present in the mass spectrum. This is surprising, as metal clusters are not expected to have a coordination space able to accommodate this many ligands as large as TODGA. MS2 experiments show that, at higher ratios and with sufficient collision energy, entire TODGA ligands are removed instead of being fragmented. These experiments show that a lower collision energy is required to remove ligands as the number of bound TODGA’s increases, suggesting that in larger clusters, ligands are more delicately complexed to the metal. In addition to Sm(TODGA)x, several clusters were observed with nitrate ions bound to the metal in addition to TODGA. With a single nitrate ion, clusters with up to six TODGA’s were able to be isolated. In a similar pattern to the samarium clusters with only TODGA, less collision energy is required to eliminate one or more TODGA’s with increasing size. MS2 experiments suggest clusters with one nitrate appear to be of an equivalent or greater stability to clusters which replace the nitrate with a TODGA, as more collision energy is required to remove a TODGA ligand. These species with one nitrate are also in a higher abundance than the equivalent TODGA only cluster. With two nitrate ions, only clusters with a single TODGA were able to be isolated. Analogous europium experiments resulted in very similar clusters. Ratios of up to 1:7 Eu:TODGA were able to be isolated, and clusters with one nitrate and up to five TODGAs were isolated. In clusters with two nitrate ions, one or two TODGA’s could also be bound to the metal. MS2 experiments suggested, similarly to samarium, that larger clusters required less collision energy to eliminate TODGA. Europium clusters with one nitrate are in greater abundance and are stronger than the equivalent cluster which replaces the nitrate with TODGA. Similar analysis with cerium and holmium is ongoing, as well as analysis with other DGA ligands to compare relative strengths of the lanthanide metals with various extractant ligands.
In July 2016, LLNL produced a report for the Kings River Watershed Coalition Authority (KRWCA) entitled “Groundwater Age and Nitrate Isotopic Composition in Alta Irrigation District Water Supply Wells” (Esser et al., 2016). That report summarized groundwater age and nitrate isotopic composition data produced by LLNL for Alta Irrigation District (AID) groundwater wells sampled by KRWCA in a pilot project to test the utility of advanced isotopic methods for constraining the timing and source of nitrate in groundwater at selected sites in the Kings River service area. One section of that report made recommendations for follow-on study. The first and strongest recommendation was to measure a wider suite of source tracers including co-contaminants such as herbicides, pesticides, pharmaceuticals, personal care products, and food constituents and additives. KRWCA followed up on this recommendation in Phase II of the pilot study by re-sampling the original set of wells and submitting the samples to a commercial laboratory for analysis of a limited range of co-contaminants (including pharmaceuticals, personal care products , and food constituents and additives, but not including herbicides or pesticides). They have asked that LLNL review and interpret these data in the context of previous LLNL analyses and to evaluate the utility of such co-contaminant analyses in providing additional constraints on the source of groundwater nitrate contamination in Alta Irrigation District water supply wells. The goal of the second phase of this pilot project is to evaluate the utility of co-contaminant occurrence for constraining nitrate source in groundwater at selected sites in the Kings River service area, with special reference to the use of such data in conjunction with advanced isotopic methods such as nitrate isotopic composition and groundwater age. Nitrate isotopic composition alone cannot distinguish nitrate derived from animal manure from nitrate derived from human septic waste. The presence or absence of agricultural chemicals (herbicides, pesticides, veterinary pharmaceuticals) or chemicals associated with people (human pharmaceuticals, artificial sweeteners) can help make this distinction. Co-contaminant analyses using multi-analyte LC-MS-MS protocols are now commercially available and reasonably priced. The feasibility and utility of the using co-contaminants for nitrate source attribution can be evaluated by 1) determining the degree to which co-contaminants occur in distinct and easily attributable groupings (e.g. agricultural chemicals vs personal care products and food additives); 2) determining the degree to which co-contaminant occurrence is consistent with nitrate isotopic composition and groundwater age (e.g. no co-contaminant occurrence in very old groundwater; co-contaminants consistent with animal manure or human septic waste occurring in groundwaters having nitrate isotopic composition also consistent with animal manure or human septic waste); and 3) determining the degree to which co-contaminants provide additional constraint on nitrate source over and beyond nitrate isotopic composition and groundwater age (e.g. distinguishing between animal manure and human septic waste).
The conversions of nitrite to nitrate, the destruction of glycolate, and the conversion of glycolate to formate and oxalate were modeled for the Nitric-Glycolic flowsheet using data from Chemical Process Cell (CPC) simulant runs conducted by Savannah River National Laboratory (SRNL) from 2011 to 2016. The goal of this work was to develop empirical correlation models to predict these values from measurable variables from the chemical process so that these quantities could be predicted a-priori from the sludge or simulant composition and measurable processing variables. The need for these predictions arises from the need to predict the REDuction/OXidation (REDOX) state of the glass from the Defense Waste Processing Facility (DWPF) melter. This report summarizes the work on these correlations based on the aforementioned data. Previous work on these correlations was documented in a technical report covering data from 2011-2015. This current report supersedes this previous report. Further refinement of the models as additional data are collected is recommended. The glass REDOX depends on the concentrations of nitrate and manganese (oxidants), and of glycolate, formate, oxalate, carbon, and antifoam (reductants) in the melter feed. The waste sludge contains nitrite, nitrate, manganese (Mn), and oxalate. Virtually all of the nitrite is converted to nitrate or NO+NO 2 +N 2 O gases in the CPC. The portion of the nitrite converted to nitrate increases the amount of nitrate in the sludge. The amount of glycolate in the final melter feed depends on the amount of the glycolic acid feed that is destroyed. Similarly, the amounts of formate and oxalate formed during the decomposition of glycolic acid are required. The material balance on carbon was found to not close in most cases. Generally, there was less carbon at the end of testing compared to the inputs. The most uncertain product variable was glycolate, so material balances were performed where the glycolate concentration was adjusted, usually upward, to close the balance. Correlation versus the original, as-measured, data was generally poor, but correlation against the material balance adjusted values was greatly improved. It was also shown that the correlation of the measured REDOX versus the predicted REDOX was much better when the material balance adjusted glycolate values were used. Three data series were primarily used during the regressions of the data; these series were 1) Sludge Batch 9 NG flowsheet simulant runs NG51-62 (SB9-NG); 2) Scaled Runs + Bounding Hydrogen Runs (SR+BH); and 3) Runs GN43-50 and 57 (43-50,57). The glycolate destruction was found to correlate with acid stoichiometry (AS), percent reducing acid (PRA), and for some data series, headspace to simulant volume ratio (HSV), mercury (Hg), and nitrate. Although glycolate destruction for pairs of data series (e.g., [SB9-NG] and [SR+BH]) were found to depend on HSV, the combination of all three data series was not found to have significant dependence on this variable. The best model for glycolate destruction depended on AS, nitrate, and Hg. This model predicted the product glycolate compositions of the data to within 92-106%. The conversion of glycolate to formate was high when noble metals and Hg were not present, with values up to 100%. When noble metals and Hg were present, this conversion ranged from zero to 7%, and was dependent on AS. Lower AS gave higher conversions to formate. The conversion to oxalate was found to depend on the AS and the initial concentration of nitrite. An alternative fit versus AS and the form of ruthenium (Ru) used is a possible alternative. This fit was somewhat less statistically significant. This second model predicts that more oxalate is formed when Ru-nitrosyl nitrate is used rather than Ru chloride. The conversion of glycolate to oxalate ranged from zero to 6%. The conversion of nitrite to nitrate depended primarily on AS and PRA, with HSV and Hg being significant when these variables were varied. For multiple series of data, nitrite was also needed to SRNL-STI-2017-00172 5HYLVLRQ viL distinguish between data series, and the effect of HSV became insignificant. The best model for nitrite to nitrate conversion depended on AS, PRA, nitrite, and Hg. The 95% confidence intervals on the predicted values of glycolate destruction, glycolate to oxalate conversion, and nitrite to nitrate conversion were used to determine the uncertainty in the predicted REDOX when starting with only the composition of the sludge, AS, and PRA. Using the 95% confidences on an individual value (that is the confidence in getting a particular value for one single test as opposed to what the mean would be for multiple tests), the uncertainty in the predicted REDOX was calculated. The uncertainty in the actual product composition glycolate, oxalate, formate, and nitrate concentrations translated to an uncertainty in the REDOX value of ±0.1,which is approximately the uncertainty claimed in the REDOX model itself.
High levels of fine particulate matter (PM2.5) pollution in East Asia often exceed local air quality standards. Observations from the Korea United States-Air Quality (KORUS-AQ) field campaign in May and June 2016 showed that development of extreme pollution (haze) occurred through a combination of long-range transport and favorable meteorological conditions that enhanced local production of PM2.5. Atmospheric models often have difficulty simulating PM2.5 chemical composition during haze, which is of concern for the development of successful control measures. We use observations from KORUS-AQ to examine the ability of the GEOS-Chem chemical transport model to simulate PM2.5 composition throughout the campaign and identify the mechanisms driving the pollution event. At the surface, the model underestimates sulfate by -64% but overestimates nitrate by +36%. The largest underestimate in sulfate occurs during the pollution event, where models typically struggle to generate elevated sulfate concentrations due to missing heterogeneous chemistry in aerosol liquid water in the polluted boundary layer. Hourly surface observations show that the model nitrate bias is driven by an overestimation of the nighttime peak. In the model, nitrate formation is limited by the supply of nitric acid, which is biased by +100% against aircraft observations. We hypothesize that this is due to a large missing sink, which we implement here as a factor of five increase in dry deposition. We show that the resulting increased deposition velocity is consistent with observations of total nitrate as a function of photochemical age. The model does not account for factors such as the urban heat island effect or the heterogeneity of the built-up urban landscape resulting in insufficient model turbulence and surface area over the study area that likely results in insufficient dry deposition. Other species such as NH3 could be similarly affected but were not measured during the campaign. Nighttime production of nitrate is driven by NO2 hydrolysis in the model, while observations show that unexpectedly elevated nighttime ozone (not present in the model) should result in N2O5 hydrolysis as the primary pathway. The model is unable to represent nighttime ozone due to an overly rapid collapse of the afternoon mixed layer and excessive titration by NO. We attribute this to missing nighttime heating driving deeper nocturnal mixing that would be expected to occur in a city like Seoul. This urban heating is not considered in air quality models run at large enough scales to treat both local chemistry and long-range transport. Key model failures in simulating nitrate, mainly overestimated daytime nitric acid, incorrect representation of nighttime chemistry, and an overly shallow and insufficiently turbulent nighttime mixed layer, exacerbate the model’s inability to simulate the buildup of PM2.5 during haze pollution. To address the underestimate in sulfate most evident during the haze event, heterogeneous aerosol uptake of SO2 is added to the model which previously only considered aqueous production of sulfate from SO2 in cloud water. Implementing a simple parameterization of this chemistry improves the model abundance of sulfate but degrades the SO2 simulation implying that emissions are underestimated. We find that improving model simulations of sulfate has direct relevance to determining local vs. transboundary contributions to PM2.5. During the haze pollution event, the inclusion of heterogeneous aerosol uptake of SO2 decreases the fraction of PM2.5 attributable to long-range transport from 66% to 54%. Locally-produced sulfate increased from 1% to 25% of locally-produced PM2.5, implying that local emissions controls would have a larger effect than previously thought. However, this additional uptake of SO2 is coupled to the model nitrate prediction which affects the aerosol liquid water abundance and chemistry driving sulfate-nitrate-ammonium partitioning. An additional simulation of the haze pollution with heterogeneous uptake of SO2 to aerosol and simple improvements to the model nitrate simulation results in 30% less sulfate due to 40% less nitrate and aerosol water, and results in an underestimate of sulfate during the haze event. Future studies need to better consider the impact of model physical processes such as dry deposition and nighttime boundary layer mixing on the simulation of nitrate and the effect of improved nitrate simulations on the overall simulation of secondary inorganic aerosol (sulfate+nitrate+ammonium) in East Asia. Foreign emissions are rapidly changing, increasing the need to understand the impact of local emissions on PM2.5 in South Korea to ensure continued air quality improvements.
Biofuel mandates can impact the environment in multiple ways that may be positive or negative, including affecting life-cycle greenhouse gas (GHG) emissions by displacing fossil fuels, affecting soil carbon stocks due to accompanying land use change, and water quality due to changes in fertilizer requirements and the mix of crops used as feedstocks. To achieve desired environmental outcomes in the presence of a biofuel mandate, additional policy instruments must be adopted to supplement the mandate. We develop an integrated and spatially explicit ecosystem-economic modeling framework to analyze the cost-effectiveness of alternative policies to achieve desired targets for GHG emissions reduction from the agricultural and fuel sectors in the USA and nitrate leaching reduction in the Gulf of Mexico below the levels that would be achieved by a corn ethanol and/or a cellulosic ethanol mandate in the USA. We find that while a corn ethanol mandate lowers GHG emissions, it increases nitrate leaching due to the expansion of corn production; a cellulosic ethanol mandate lowers both GHG emissions and nitrate leaching relative to a corn ethanol mandate, but the additional carbon and nitrate prices are needed to achieve anticipated GHG reduction and nitrate reduction targets. We also find that accompanying a biofuel mandate with a GHG reduction target alone leads to substantial nitrate reduction co-benefits, but a nitrate reduction target alone is less effective in reducing GHG emissions. Combining a GHG standard with a nitrate standard can achieve GHG and nitrate reduction targets at lower carbon and nitrate prices as compared to implementing each of these policies independently. Furthermore, our findings show that disregarding policy co-benefits can overestimate the GHG and nitrate prices needed to achieve policy targets and higher policy costs.
This report describes preliminary data to validate the Savannah River Plutonium Processing Facility’s (SRPPF) flowsheet for conversion of used Reillex HPQ anion exchange resin from the nitrate form to the sulfate form. The nitrate form is an oxidizer and therefore does not meet acceptance criteria for disposal at the Waste Isolation Pilot Plant (WIPP). The purpose of this study is to develop data to support acceptance for this disposition pathway. Due to the challenges characterizing the nitrate concentration on solid resin, the data developed to date are based upon indirect analysis of the ion exchange column effluent by ion chromatography. These challenges are discussed and two methods for quantification of nitrate directly on the resin are recommended for further development: TGA-MS and permanganate digestion followed by IC. The resin used for this work was provided in the chloride form; this is the form in which resin is supplied by the manufacturer. However, it had to be converted to the nitrate form, which is the form that will be used in SRPPF’s ion exchange process, prior to use in the sulfate conversion experiments. The chloride-form resin was characterized. A lab-scale procedure for the conversion of Reillex HPQ resin from the chloride to nitrate form was validated. The nitrate-form resin was assessed for particle size and chloride concentration to ensure it met SRPPF’s facility specifications. The baseline sulfate conversion flowsheet was tested. However, nitrate was still detectable in the effluent after approximately 10 bed volumes of 1 M sodium sulfate had been passed through the resin bed. Additional experiments were performed to assess the effect of increasing the feed volume, reducing the flowrate, the use of 2 M sulfuric acid instead of sodium sulfate, and the use of irradiated resin. The sulfuric acid test was the only one which provided a nondetectable nitrate concentration (<0.002 M) in the effluent. Detectable nitrate in the column effluent suggests that nitrate is still present on the resin itself.
High concentrations of PM 2.5 (particulate matter with an aerodynamic diameter less than 2.5 µm) in China have caused severe visibility degradation. Accurate simulations of PM 2.5 and its chemical components are essential for evaluating the effectiveness of pollution control strategies and the health and climate impacts of air pollution. In this study, we compared the GEOS-Chem model simulations with comprehensive datasets for organic aerosol (OA), sulfate, nitrate, and ammonium in China. Model results are evaluated spatially and temporally against observations. The new OA scheme with a simplified secondary organic aerosol (SOA) parameterization significantly improves the OA simulations in polluted urban areas, highlighting the important contributions of anthropogenic SOA from semivolatile and intermediate-volatility organic compounds. The model underestimates sulfate and overestimates nitrate for most of the sites throughout the year. More significant underestimation of sulfate occurs in winter, while the overestimation of nitrate is extremely large in summer. The model is unable to capture some of the main features in the diurnal pattern of the PM 2.5 chemical components, suggesting inaccuracies in the presented processes. Potential model adjustments that may lead to a better representation of the boundary layer height, the precursor emissions, hydroxyl radical concentrations, the heterogeneous formation of sulfate and nitrate, and the wet deposition of nitric acid and nitrate have been tested in the sensitivity analysis. The results show that uncertainties in chemistry perhaps dominate the model biases. The proper implementation of heterogeneous sulfate formation and the good estimates of the concentrations of sulfur dioxide, hydroxyl radical, and aerosol liquid water are essential for the improvement of the sulfate simulation. The update of the heterogeneous uptake coefficient of nitrogen dioxide significantly reduces the modeled concentrations of nitrate. However, the large overestimation of nitrate concentrations remains in summer for all tested cases. The possible bias in the chemical production and the wet deposition of nitrate cannot fully explain the model overestimation of nitrate, suggesting issues related to the atmospheric removal of nitric acid and nitrate. A better understanding of the atmospheric nitrogen budget, in particular, the role of the photolysis of particulate nitrate, is needed for future model developments. Moreover, the results suggest that the remaining underestimation of OA in the model is associated with the underrepresented production of SOA.
Abstract Organic nitrates formed from nighttime reaction between anthropogenic nitrate radicals (NO3) and biogenic volatile organic compounds (BVOCs) are potentially an important but highly uncertain source of secondary organic aerosol (SOA). Here we report on the enhanced nighttime biogenic SOA formation observed in a polluted residual layer over Sacramento, California, the morning of 15 June 2010 during the Carbonaceous Aerosols and Radiative Effects Study (CARES). Trajectory analysis showed that the residual layer air, containing trace amounts of isoprene and monoterpenes left over after nighttime oxidation, was influenced by the San Francisco Bay Area emissions the previous evening. The residual layer aerosol was also enriched in nitrate, with about 64% of it estimated to be in the form of organic nitrates. The nitrate:organic mass ratio of the SOA was about 0.47±0.044, which corresponds to the range typically found in isoprene mononitrates. Assuming the SOA was composed of organic mononitrates, its nominal molecular weight was estimated at 186±11 g mol-1, consistent with the highly functionalized isoprene hydroxynitrates that have been observed in the particle phase in the southeast United States. Overall, our findings show that the efficiency of nighttime biogenic SOA formation, expressed as the change in organic aerosol mass relative to carbon monoxide (?OA/?CO), was about 100 µg m-3 ppmv, which falls in the range 77-157 µg m-3 ppmv previously estimated for enhanced daytime SOA formation from mixed anthropogenic and biogenic emissions during CARES.
Nitrate reduction to N2O was investigated in batch cultures of Shewanella putrefaciens MR-1, MR-4, and MR-7. All three strains reduced nitrate to nitrite to N2O, and this reduction was coupled to growth, whereas ammonium accumulation was very low (0 to 1 micromol liter-1). All S. putrefaciens isolates were also capable of reducing nitrate aerobically; under anaerobic conditions, nitrite levels were three- to sixfold higher than those found under oxic conditions. Nitrate reductase activities (31 to 60 micromol of nitrite min-1 mg of protein-1) detected in intact cells of S. putrefaciens were equal to or higher than those seen in Escherichia coli LE 392. Km values for nitrate reduction ranged from 12 mM for MR-1 to 1.3 mM for MR-4 with benzyl viologen as an artifical electron donor. Nitrate and nitrite reductase activities in cell-free preparations were demonstrated in native gels by using reduced benzyl viologen. Detergent treatment of crude and membrane extracts suggested that the nitrate reductases of MR-1 and MR-4 are membrane bound. When the nitrate reductase in MR-1 was partially purified, three subunits (90, 70, and 55 kDa) were detected in denaturing gels. The nitrite reductase of MR-1 is also membrane bound and appeared as a 60-kDa band in sodium dodecyl sulfate-polyacrylamide gels after partial purification.
During the Airborne Antarctic Ozone Experiment campaign, a filter sampler was flown to measure the bulk composition of aerosol and gas phases. The background sulfate aerosol was measured in regions inside and outside of the chemically perturbed region (CPR) of the polar vortex. The mass ratio of sulfate outside to inside was 2.8. This is indicative of a cleansing mechanism effecting the CPR or of a different air mass inside versus outside. The absolute value of the sulfate mixing ratio shows that the background aerosol has not been influenced by recent volcanic eruptions. The sulfate measured on the ferry flight returning to NASA Ames shows a decrease towards the equator with increasing concentrations in the northern hemisphere. Nitrate in the aerosol phase was observed on two flights. The largest amount of nitrate measured in the aerosol was 44 percent of the total amount of nitrate observed. Other samples on the same flights show no nitrate in the aerosol phase. The presence of nitrate in the aerosol is correlated with the coldest temperatures observed on a given flight. Total nitrate (aerosol plus acidic vapor nitrate) concentrations were observed to increase at flight altitude with increasing latitude north and south of the equator. Total nitrate was lower inside the CPR than outside. Chloride and flouride were not detected in the aerosol phase. From the concentrations of acidic chloride vapor, the ratio of acidic vapor Cl to acidic vapor F and a summing of the individual chloride containing species to yield a total chloride concentration, there is a suggestion that some of the air sampled was dechlorinated. Acidic vapor phase fluoride was observed to increase at flight altitude with increasing latitude both north and south of the equator. The acidic vapor phase fluoride was the only compound measured with the filter technique that exhibited larger concentrations inside the CPR than outside.
The following variables along the Pacific equator from 145 deg E to 95 deg W were employed: surface layer phytoplankton pigment concentrations derived from Nimbus 7 coastal zone color scanner (CZCS) measurements of ocean color radiances; vertical velocities simulated at the 90-m bottom of the euphotic layer from a wind-driven ocean general circulation model; and nitrate concentrations estimated from model-simulated temperature. The upward flux of nitrate into the euphotic layer was calculated from the simulated vertical motion and nitrate concentration. The CZCS-derived phytoplankton pigment concentration was uniform from 175 deg to 95 deg W. Longitudinal profiles of upwelling, phytoplankton biomass, and 90-m nitrate flux were of different shapes. The small annual cycles of the phytoplankton pigment and nitrate flux were in phase: increased phytoplankton biomass was associated with increased upward nitrate flux, but the phase was not consistent with the annual cycles of the easterly wind or of the upwelling intensity. Variation of phytoplankton pigment concentration was greater during El Nino than during the annual cycle. The substantially reduced phytoplankton pigment concentration observed during El Nino was associated with smaller upward nitrate flux. Phytoplankton biomass during non-El Nino conditions was not related to nitrate flux into the euphotic layer.