Oxidation of Isoprene and Monoterpenes as a Function of Nitrogen Oxides in the Amazon Rain Forest

Zachary Moon1

Dandan Wei1,2, Jose D Fuentes1, Marcelo Chamecki3, Gabriel G Katul4, William H Brune1, John J Orlando5

1. Penn State University2. University of Michigan3. University of California, Los Angeles4. Duke University5. NCAR

Session: Session 8B Boundary Layer Processes and Biogeochemistry in AmazoniaProgram: 22nd Conference on Atmospheric Chemistry

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Goal of the work: to better simulate BVOC photochemistry in the Amazon rainforest by

- improving in-canopy gas-phase chemistry by better simulating in-canopy light and photolysis frequencies

- utilizing in-canopy wind data to improve modeled eddy diffusivity

Research objectives- Canopy export fractions of terpene BVOC- NOx sensitivity of terpene-OH interactions

Motivation• In the dense, tall canopies of the Amazon, in-canopy processes are especially important yet

poorly understood• The Amazon rainforest also experiences occasionally elevated concentrations of nitrogen

oxides due to regional biomass burning or long-range transport of urban emissions

GoAmazon field campaign April 2014 to January 20152Intro

Canopy height: 25-35 m Leaf area index: 5-7 m2 m-2

Moist -> high OH

Major BVOC source- due to high T, radiation, biomass- secondary OH production

Mostly clean- low NOx, NOx-limited regime

Turbulence data (nine levels)

O3, NOx

VOC data(isoprene, monoterpenes,methanol, acetone)

Forest-atmosphere exchange: BVOC-relevant processes

: We are mostly focusing on improving these

3Methods

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Canopy radiative transferspectrally resolved4-stream solver

ABL turbulent mixing

In-canopy turbulent mixingModeled K(z) with 1st-order closure

Emissions

Soil exchange

ABL depthFree tropospheric exchange

Background mixing

PhotochemistryBVOCs + {OH, O3, NO3} products

Deposition

+ {OH, O3, NO3}in-canopy BVOC processing

OVOC(secondary)

Gas-particle partitioning

Aerosol chemistry

A 1-D modeling system for forest-atmos photochemistry 4Methods

ABL model

Surface layer subcomponent

Canopy model

Soil subcomponent

Model top (e.g., 3–5 km)

Model level as box (0-D) model

(not to scale)

heig

ht

Emissions

Advection Advection

Vertical transport

Vertical transport

Deposition

Chemistry

Chemistry (+ SOA)• Gas-phase chemical reactions• EQ. gas-particle partitioning• Aq. aerosol-phase reactions

Canopy height (e.g., 10–40 m)

<- Including canopy radiative transfer and vertical mixing schemes

Improving photochemical reaction rates

The new model will include the option of explicit photolysis calculations

Methods

𝐽𝐽𝐴𝐴(𝑧𝑧) = �𝜆𝜆

𝐹𝐹 𝑧𝑧, 𝜆𝜆 𝜎𝜎𝐴𝐴 𝜆𝜆 𝜙𝜙𝐴𝐴 𝜆𝜆 𝑑𝑑𝜆𝜆𝐽𝐽𝐴𝐴 𝑧𝑧 =𝐸𝐸𝑃𝑃𝐴𝐴𝑃𝑃 𝑧𝑧

𝐸𝐸𝑃𝑃𝐴𝐴𝑃𝑃 𝑧𝑧 = ℎ𝑐𝑐⋅ 𝐽𝐽𝐴𝐴(𝑧𝑧 = ℎ𝑐𝑐)

PAR weighting method Spectral approach

From measurements or atmosphere model

^ Traditional approach uses a relative irradiance profile to weight a reference value

Our recent work: Moon et al (2020), in revision, AFMdemonstrates the importance of the spectral approach for in-canopy photolysis

^ Spectral approach explicitly calculates photolysis frequency using the spectral irradiance profile

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Observation-based in-canopy eddy diffusivityFreire (2017); approach outlined by Poggi et al. (2008)

Note: far-field formulation⇒ Opportunity to improve

by adding near-field corrections

6Methods

“observed” eddy diffusivity

measured variance of vertical wind

Lagrangian time scale for turbulent momentum transport~ ℎ𝑐𝑐/𝑢𝑢∗0.3 ℎ𝑐𝑐/𝑢𝑢∗ often used within canopy

Eulerian integral time scalefound by numerically integrating w’s autocorrelation function to its first zero-crossing

C2 = 2.8, C0 = 5.5 : “universal constants”

mean horizontal wind

Sensitivity to eddy diffusivity formulation

Traditional K-theory parameterization underpredicts Amazon in-canopy mixing during the day

7Preliminary results

Figures from Dandan Wei’s dissertation (2019)

Underprediction is most prominent (percentage-wise) in the lower third of canopy

Forest BVOC-NOx interactions

With sufficient NOx (= NO + NO2), peroxy radicals (HO2 and RO2) control ozone formation and modulate the atmospheric oxidative capacity,but there can be too much.

8Background

Fitzky et al. (2019)

NOx level Primary HOx loss pathway

low 10–100 pptv HO2 + HO2 → H2O2 + O2

moderate 1 ppbv OH + HO2 → H2O + O2

high 5–20 ppbv NO2 + OH +𝑀𝑀 → HNO3 (+𝑀𝑀∗)

NOx influence on HOxVOC-NOx-O3

BVOC + OH -> RO2

NOx sensitivity

Up to 1–3 ppbv,↑ NOx → ↑ OH → ↓ terpenesDue to increased ozone photolysis facilitated by NO2

Below 0.1 ppbv, less sensitive to percentage changes in NOx(log scale)

Beyond 3 ppbv NOx,↑ NOx → ↓ OH → ↑ terpenesHigh-NOx regime: OH+NO2 reaction dominates, OH loss

9Preliminary results

Average over midday (10:00-14:00) on 2nd day of simulations

from Dandan Wei’s dissertation (for Amazon)

NOx sensitivity – in-canopy terpene processing

Increasing NOx increases PF up to about 4 ppbv. • Monoterpenes react appreciably

with O3 so the subsequent decrease is less than that for isoprene

10Preliminary results

Estimated in-canopy processed fraction (PF)

* Note the different y-axis limits

NOx sensitivity – terpene-OH 11Preliminary results

Monoterpenes can be net OH sources but there is height and NOx dependenceIsoprene always a net sink

Estimated in-canopy terpene OH source/sink

source

sink

OH source/sink ratio

GoAmazon NO in ABL measured by aircraft

Summary

Improving:- modeling of in-canopy light- eddy diffusivity→ more daytime in-canopy mixing ⇒ decreased in-canopy terpene

concentrations and concentration gradients

In the Amazon, monoterpenes act as net OH sources, even under the influence of Manaus pollution.

- Strength depends on NOx

In-canopy terpene processing also depends on NOx

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Acknowledgements

ZM

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NOAA EPP / NCAS-Mthe National Oceanic and Atmospheric Administration, Educational Partnership Program, U.S. Department of Commerce, under Agreement No. NA16SEC4810006-NCAS-M