Research ArticleENVIRONMENTAL STUDIES

Isoprene photo-oxidation products quantify the effect of pollution on hydroxyl radicals over Amazonia

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Science Advances  11 Apr 2018:
Vol. 4, no. 4, eaar2547
DOI: 10.1126/sciadv.aar2547
  • Fig. 1 Illustration of the relationship of OH and NOx.

    (A) Chemical cycles connecting OH production and loss to NOx and VOC species. (B) Dependence of OH concentration on NOx concentration. The classical dependence of the bell curve in black can be compared to the absence of a dependence (that is, the red horizontal line) below a threshold NOx concentration, as suggested by the meta-study of Rohrer et al. (4).

  • Fig. 2 Hourly variation of VOC concentrations.

    (A) Isoprene concentration CISOP and (B) sum concentration CPROD of isoprene oxidation products. The vertical dashed gray lines demarcate local sunrise, noon, and sunset (UTC less 4 hours). Data are shown in the wet and dry seasons in blue and red colors, respectively. The solid line and shaded regions, respectively, represent the median and interquartile ranges of the data sets for each hour of the day. The two black dashed lines in (A) show the simulated increase of CISOP from sunrise to midafternoon using Eq. 2 for CISOP,0 values of 0.35 and 0.6 ppb.

  • Fig. 3 Scatterplots of VOC concentrations with NOy concentration.

    (A) Isoprene concentration CISOP. (B) Sum concentration CPROD of isoprene oxidation products. (C) Concentration ratio CPROD/CISOP. Data points represent hourly averages recorded within a time window of 13:00 to 16:00 (local time) (17:00 to 20:00 UTC). Blue and red points correspond to the wet and dry seasons, respectively, for fair-weather conditions. All weather data, including periods of heavy rainfall or prolonged overcast conditions, are presented in fig. S1.

  • Fig. 4 Simulated dependence of the concentration ratio CPROD/CISOP on NOy concentration Embedded Image.

    Results are shown for two different values of COH,noon, as well as the full model compared to a model that omitted isoprene ozonolysis. At fixed COH,noon, Embedded Image affects CPROD/CISOP via the effects on Embedded Image and Embedded Image(CNOy) (Eq. 5). Solid lines show results for the full model of Eq. 5, and dashed lines show results for a model that omits isoprene ozonolysis (that is, Embedded Image = 0). For all cases, t = 8.5 hours, corresponding to 14:30 (local time).

  • Fig. 5 Dependence of inferred equivalent noontime OH concentration COH,noon on NOy concentration.

    The gray dots represent COH,noon inferred for the individual data points of Fig. 3C. The red crosses represent medians and quartiles after grouping the data points into five equally spaced bins based on logarithmic NOy concentrations. The orange line connects the medians of the binned data.

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/4/4/eaar2547/DC1

    section S1. Use of observed Formula to represent the average NOx exposure

    section S2. Determining relation Formula

    section S3. Approximation of Formula

    section S4. Derivation of Eq. 5 in the main text

    section S5. Additional note of Fig. 4 in the main text

    section S6. Sensitivity tests regarding entrainment process

    section S7. Error analysis

    section S8. Comparison of COH,noon obtained in this study with other OH studies

    fig. S1. Scatterplots of VOC concentrations with NOy concentration for all-weather condition.

    fig. S2. Simulated daily variation of photolysis frequency of ozone JO3, normalized to the noontime value JO3,noon, based on Master Chemical Mechanism.

    fig. S3. Simulated NOy dependence of effective production yields.

    fig. S4. Observation and simulation of ozone concentration Formula.

    fig. S5. Simulation using a mixed boundary layer model.

    fig. S6. Simulated relationship of equivalent noontime OH concentration COH,noon and concentration ratio CPROD/CISOP using the base-case model and a mixed boundary-layer model.

    fig. S7. Variation in model parametrizations for error analysis.

    table S1. Production yields and loss rate coefficients for isoprene oxidation products used in the model.

    table S2. Uncertainty estimates for inferred COH,noon via error propagation.

    table S3. Summary of inferred OH concentrations over tropical forests in South America.

    References (4150)

  • Supplementary Materials

    This PDF file includes:

    • section S1. Use of observed CNOy to represent the average NOx exposure
    • section S2. Determining relation y*i(CNOy)
    • section S3. Approximation of CO3
    • section S4. Derivation of Eq. 5 in the main text
    • section S5. Additional note of Fig. 4 in the main text
    • section S6. Sensitivity tests regarding entrainment process
    • section S7. Error analysis
    • section S8. Comparison of COH,noon obtained in this study with other OH studies
    • fig. S1. Scatterplots of VOC concentrations with NOy concentration for all-weather condition.
    • fig. S2. Simulated daily variation of photolysis frequency of ozone JO3 , normalized to the noontime value JO3,noon, based on Master Chemical Mechanism.
    • fig. S3. Simulated NOy dependence of effective production yields.
    • fig. S4. Observation and simulation of ozone concentration CO3.
    • fig. S5. Simulation using a mixed boundary layer model.
    • fig. S6. Simulated relationship of equivalent noontime OH concentration COH,noon and concentration ratio CPROD/CISOP using the base-case model and a mixed boundary-layer model.
    • fig. S7. Variation in model parametrizations for error analysis.
    • table S1. Production yields and loss rate coefficients for isoprene oxidation products used in the model.
    • table S2. Uncertainty estimates for inferred COH,noon via error propagation.
    • table S3. Summary of inferred OH concentrations over tropical forests in South America.
    • References (41–50)

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