Observed and model simulated isoprene emission rates

The average surface isoprene emission rates are 6.2, 12.9 and 10.7 mg m−2 h−1 from observations in wet, dry and both seasons based on the EC technique (Fig. 1a). The observed isoprene emission rates are about 3.5, 2.4 and 3 times higher than the estimates from a satellite top-down approach based on the Ozone Monitoring Instrument (OMI) measurements in wet, dry and both seasons. Compared with the estimates from MEGAN model simulations, the observed isoprene emission rates are 10%, 43% and 35% higher in wet, dry and both seasons. We also estimated emission estimates from the aircraft observations using an independent approach, the Mixed Layer Variance technique17,18 (Supplementary Fig. 2), and the calculated isoprene emission rates are comparable with the direct EC measurements and estimates from previous studies17,19.

Figure 1: Isoprene emission estimates and maps of vegetation distributions and terrain elevation. (a) Mean values of surface isoprene emissions from MEGAN, EC and OMI for all available flights (black diamond), dry season (red triangle) and wet season (blue square), and their 25% quartile values (lower bar), 50% quartile values (middle bar) and 75% quartile values (higher bar). (b) Fractional coverage of broadleaf evergreen tropical trees from MODIS PFT land cover observation. (c) Distribution of LAI in September 2014 from MODIS observation. (d) Terrain elevation from ASTER Global Digital Elevation Map. Full size image

To accurately simulate the spatiotemporal distribution of isoprene emissions with MEGAN, it is critical to drive the model with representative land cover input data including EFs, plant functional type (PFT) and leaf area index (LAI). In this study, we use the MEGAN v2.1 model coupled with the Community Land Model (CLM) v4.5 to simulate isoprene emissions over the central Amazon forest in 2014. The MEGAN v2.1 model adopts the 16 PFT scheme used by CLM to characterize spatial variations of vegetation types, and specifies isoprene EFs based on PFT categories12. Satellite observations have been widely used to generate high-resolution land cover parameters for Earth system modelling20. By using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data, we calculated MEGAN PFT and LAI inputs for this study (Fig. 1b,c). Based on the MODIS MCD12Q1 land cover type product, the study region is dominated by only one PFT type, broadleaf evergreen tropical trees, which results in a nearly homogeneous distribution of EFs for model simulations. Although there are small percentages of other PFT (for example, grass, crop) and water (river) coverage dispersed throughout the region, their estimated contributions to the overall isoprene emission are very small (Supplementary Fig. 3). Comparing LAI data from the MODIS MCD15A2 product in each month in 2014 (Supplementary Fig. 4), the LAI in the dry season is significantly higher than in the wet season, which contributes to higher isoprene emissions in the dry season. The MEGAN model is also driven by meteorological inputs (for example, temperature, radiation) from simulations of meteorological forcing data from the Weather Research and Forecasting (WRF) Model constrained by National Center for Environmental Prediction FiNaL (NCEP FNL) operational global analysis data. Vegetation temperature and solar radiation in the dry season were higher than those in the wet season (Supplementary Figs 5 and 6), which both tend to contribute to higher isoprene emissions in the dry season. The 24-hour monthly average isoprene emission is 4.3 mg m−2 h−1 in September from MEGAN simulation, which is nearly twice the emission of 2.1 mg m−2 h−1 in March (Supplementary Fig. 7).

By comparing the emissions estimated from airborne observations with those from MEGAN simulations, we evaluated the average MEGAN emission and propose an approach for improving the model estimates. As shown in Fig. 2, there are discrepancies in the spatial distributions of isoprene emissions between MEGAN model simulations and those derived from aircraft observations. Also shown in Supplementary Fig. 8, the observed isoprene emission rates are 35% higher than average model results, while the emissions from aircraft observations are more variable indicating isoprene emission heterogeneity that is not captured by the model.

Figure 2: Surface isoprene emission flux during flight RF 20140930. (a) Spatial distributions from airborne EC method (solid circles) compared with MEGAN simulations (background colours); (b) scatter plot of the EC and MEGAN estimates, and their mean values and linear correlation coefficient are shown in the figure.. Full size image

Elevational gradient of isoprene emission

To exclude the impacts from meteorological inputs, we calculated the isoprene EFs from aircraft observations, and compared them with corresponding MEGANv2.1 EFs. While the EFs in MEGANv2.1 are dominated by one single–PFT-based MODIS land cover data, the aircraft observed EFs are significantly more variable (Supplementary Table 1), suggesting that there is greater heterogeneity in actual vegetation types and isoprene emissions. While the Amazonian forest has the richest abundance of vegetation species on Earth, there remains much unknown about the plant species distribution in the Amazon21. The emission rate variability in this diverse ecosystem must be characterized by more than one single PFT to adequately represent the entire Amazon forest. While LAI can influence isoprene emission because it represents the magnitude of the potential source, there were no clear correlations between observed EF and LAI (Supplementary Table 2). Therefore, we investigated other variations in land characteristics that could explain this variability.

Variations in ecosystem types, and their associated plant species distributions, have been observed along elevational gradients in many regions and are associated with altitude driven changes in a variety of environmental factors (for example, temperature, humidity, soil composition)22. Studies have shown floristic compositions of tree23, shrub24 and palm25 are correlated with terrain elevations in Amazonian forests. Therefore, we compared aircraft-based isoprene EF with satellite-based elevation data to investigate whether there are elevational gradients in isoprene EFs. As shown in Fig. 3, by categorizing the observed isoprene EFs using 30 m intervals in terrain elevations, there are strong positive correlations (R=0.98, P<0.018) between isoprene EFs and elevations for the dry season. This indicates that there is a notable elevational gradient of isoprene emitters in the central Amazonian forest. We hypothesize that an elevational gradient in Amazonian forest isoprene emission capacity, determined by plant species distributions, can explain a substantial degree of isoprene emission variability in Amazonian tropical forests leading to significantly improved isoprene emission estimates.

Figure 3: Correlations of terrain elevations with observed isoprene EFs and top-down isoprene emissions. The median values of isoprene EFs estimated from EC approach (red diamond), top-down biogenic isoprene emissions based on satellite data including GOME-2 (purple triangle) and OMI (blue square), and their 25% quartile values (lower bar) and 75% quartile values (higher bar) during dry (a) and wet (b) seasons compared with terrain elevations with an interval of 30 m. The black dot lines indicate the EF used in MEGAN v2.1. The colour dash lines show linear regressions for median values from each approach, and their correlation coefficients (R) are shown in the figures. Full size image

We also examined biogenic isoprene emissions from top-down estimations based on the Global Ozone Monitoring Experiment–2 (GOME-2) (2007–2012) and OMI (2005–2014) satellite formaldehyde observations (Fig. 3). Similar to the EFs from aircraft observations, there are also strong correlations (R=0.96–0.99) between top-down isoprene emissions and terrain elevation in the central Amazon. The top-down emissions are impacted by the a priori emission (MEGAN-MOHYCAN26) which has lower values at lower elevations due to the combination of river, grassland with trees in the low resolution (0.5 degree) grid. As a result, the elevational variation of vegetation composition could be impacted by the assumed land cover types. Based on aircraft observed isoprene EF and terrain elevation data, the observed relationship (EF=0.091 × Elevation+4.51) in dry season was used to modify the isoprene EFs in the central Amazon. As shown in Fig. 4, the revised EFs are consistently higher than the MEGANv2.1 EFs and there is significant horizontal heterogeneity of EFs with higher values in the northern part of the study domain. On average, the revised EFs are 71% higher than the MEGANv2.1 EFs in the study domain.

Figure 4: Distribution of isoprene EF. Comparison of isoprene EFs based on observations from airborne EC approach (a), based on MEGANv2.1 EFs and MODIS PFT land cover observations (b) and the difference between the above two data sets (c). Full size image

Model simulated regional impacts

To examine the impacts of the revised isoprene emissions, we used the Weather Research and Forecasting model coupled to Chemistry (WRF-Chem), to simulate the impact of the improved isoprene EFs on regional oxidants distributions as shown in Fig. 5. The hydroxyl radical (OH), which is the primary oxidant for most tropospheric trace gases (for example, nitrogen oxides (NO x ), formaldehyde (HCHO)), decreased by ∼19% after updating the isoprene EFs. At the same time, two important photochemical oxidation products, O 3 and peroxyacyl nitrates, decreased by ∼10% and ∼6%. This suggests that the higher isoprene emission is currently suppressing these compounds since the O 3 –NO x -VOC sensitivity is NO x -limited in the Amazonian area. This will likely not be the case if NO x emissions increase as a result of increased anthropogenic activities in the Amazon27. As the elevational gradient of the plant species distribution is also related to the height above the nearest drainage in the Amazonian forest28, we may also see future changes of biogenic isoprene emission and regional air quality if the water table depth fluctuates as a consequence of climate change or human activities.