Meteorological conditions and backward trajectories
The measurement period, December 2016 and January 2017, was during the North East Monsoon (NEM) when the prevailing wind flow is northeasterly and strong. Hourly average meteorological data consisting of temperature, relative humidity, wind (speed and direction) and irradiance were used to evaluate the weather conditions in this period. A summary of the meteorological conditions is given in Figure 4. The minima for temperature and relative humidity (RH) were 23.3 °C and 43% with average values of 27.5 °C and 82%, respectively. The maximum temperature of 32.2 °C occurred on the 13th December 2014. In January 2017, rain fell nearly continuously from the 11th to 13th January 2017 and this led to lower temperatures. The minimum temperatures recorded were during these days and were in the range 25.2 to 25.5 °C. The maximum temperature recorded in January 2017 was 29.2 °C on the 10th January.
The daily wind speed varied between 0.3 ms-1 and 8.8 ms-1 with a median value of 2.7 ms-1 during December 2016, while in January 2017 the respective values were 0.4 ms-1 and 9.3 ms-1 with a median value of 3.4 ms-1. The wind roses for these months are shown in Figure 4. The wind directions were mainly blowing from the regions around Kuantan and Pekan. The highest daily maximum value of Photo Active Radiation (PAR) was 801 mMol m-2 s-1 on the 13th December 2016 when the highest temperature was also recorded. The minimum daily PAR, 300 W, was recorded during the rain event on the 11th to 12th January 2017.
Fig. 4
The travel pathways of the 3-day (100 m) backward trajectories (BTs) at Pekan palm oil plantation were plotted (Figure 5). As an input of the trajectory model, the data set was downloaded from the National Oceanic and Atmospheric Administration (NOAA) website (link: ftp://arlftp.arlhq.noaa.gov/pub/archives/reanalysis). The date of the BTs was the 12th December 2016. This day was selected as it was the day on which the highest mixing ratios were observed for isoprene. At the measurement site, the BTs showed transport from the northeast (NE) of Peninsular Malaysia. The mixing height was about 100 m on the 12th December 2016. The results of the trajectories can be interpreted with the elevation of surface O3 as well as the change to the height of the boundary layer. During the in situ measurements at the site, the mixing ratios of surface O3 were higher at the Pekan palm oil site. The nearby city Kuantan experienced high concentrations of O3 precursors such as NOx and CO (this will be discussed in the next Section) on this day. The noted shift of air mass in this region may in part influence the anthropogenic impact on the formation of surface O3 that might move with air masses around the palm site. We can conclude that the isoprene may react with the NOx and VOCs emitted from Kuantan.
Fig. 5
Mixing ratios of isoprene, O3 and CO
The isoprene mixing ratios measured during December 2016 and January 2017 are shown in Figure 6. On some days (e.g. after 23rd December), instrumental problems resulted in no measurements being made. A strong diurnal cycle is seen with the highest values between 1200 and 1400 local time. The maximum daytime peak values observed were ~25 ppb and occurred on the 12th and 19th December 2016 and on the 7th January 2017. The lowest daytime mixing ratios (peak ~0.5 ppb) occurred on the 11th–13th January 2017. Minimum values of <5 ppb were found at night.
Fig. 6
This observation of high mixing ratios of isoprene during the day and low mixing ratios at night is consistent with many previous studies [38; 39; 40: 41]. The morning increase results principally from the strong influence of PAR and temperature on the emissions from the leaves into a stable planetary boundary layer (PBL). The rate of the afternoon decrease is additionally affected by the loss to reaction with the hydroxyl radical (timescale ~1 hour), the main chemical loss process for isoprene, and transport into the lower troposphere. The rates of all these processes vary significantly from day to day.
A similar diurnal cycle was found in the measured ozone mixing ratios, with a maximum in the day and a minimum at night (Figure 6). Typical daytime peaks are ~40–50 ppb, with the highest hourly value of 57 ppb recorded on the 12th December 2016. These values are under the Malaysian Air Quality Standard for 1 hour and 8 hours which are 180 and 100 ppb, respectively. Surface O3 values are determined by three main processes: (i) mixing in of ozone-rich tropospheric air into the PBL which is responsible for the morning increase in surface ozone; (ii) photochemical reactions involving ozone whose production will be enhanced by the presence of isoprene in NOx-rich air [9]; and (iii) deposition of ozone onto the oil palm plantation.
A strong diurnal cycle of CO2 was measured throughout December 2016 (Figure 6). Maximum mixing ratios were observed during the night and minimum values during the daytime with typical values of ~810 ppm and ~450 ppm, respectively. Plant photosynthesis and respiration are the main reasons for these variations. Plants produce CO2 all the time through respiration, but during the day (when the light intensity is high) plants use CO2 for photosynthesis, and fix CO2 into other molecules, resulting in more O2 than CO2. At night, the CO2 increases because the plants are giving off CO2 in respiration and not photosynthesising. It can take until late morning before CO2 removal by photosynthesis is observable during the day.
Physical factors effects on isoprene, surface O3 and CO2.
Effect on isoprene
It has been observed that temperature and light intensity influence the isoprene emissions from plants [42; 43; 44; 45]. The light-dependent regulation of isoprene emissions is due to the production of isoprene in the plant photosynthesis process, therefore the photosynthetic active radiation during the day leads to higher daytime isoprene [46]. In this study, the irradiance term is similar to light intensity, thus irradiance in Watt per meter square (Wm-2) will be used throughout. Figure 6 shows that increases in temperature and irradiance led to increases in isoprene mixing ratios. Strong correlations between temperature and irradiance with isoprene were observed with r2=0.91, p<0.01 and r2=0.82, p<0.01, respectively. The trends in isoprene, temperature and irradiance showed that the maximum peaks were observed during the middle of the day, from1100 to 1530. This was also observed by [41] for isoprene mixing ratios over Calabozo, Venezuela (Savanna site). They measured maximum mixing ratios of about 3.1 ppb between 1200 and 1500 local time.
The isoprene synthesis and light dependence relationship can be explained by the synthesis of isoprene in the stomata. First observation of the light dependence of isoprene emissions was by [42], indicated by the rapid appearance of the 13C label from 13C-labelled CO2 in the isoprene signal [43; 47]. An observation by [47] showed isolated chloroplasts are capable of isoprene emission which provided conclusive evidence of the functional interdependence between photosynthesis and isoprene emission.
Effect on surface O3
Previous studies have shown that surface O3 mixing ratios in ambient air are controlled by temperature [17; 18; 16]. Increases in temperature will increase the surface O3 mixing ratio in the presence of high levels of NOx. Our observed variations in the daily maximum temperature and the daily maximum O3 mixing ratios are depicted in Figure 6. Overall, the average daily maximum temperatures and surface O3 measurements for Pekan palm station show increments, especially during the hours 1100 to 1630, then gradual decreases after 1630. This profile of surface O3 was consistent throughout December 2016. The highest temperature recorded was 33 °C on the 13th December 2016 when the highest surface O3 also was observed. A similar effect of temperature on surface O3 was found over Kuala Terengganu, also on the east coast, ~200 km from Pekan was seen in the study by [48]. Other than temperature, irradiance and wind speed were also found to play a significant role in influencing O3 mixing ratios [48].
The daily maximum temperature increased steadily from 0900 due to the increase of light intensity during the peak sun hours, where the irradiance that a particular location would receive if the sun were shining at its might i.e. as strongly as it can, as in no cloud cover. The increase in irradiance causes an increase of temperature, which in turn escalates the O3 mixing ratio maximum value. Similar to the temperature effect, the daily maximum O3 mixing ratio tended to follow the intensity of irradiance, causing higher levels during daytime and lower levels at night. The correlation between daily maximum temperature and daily maximum solar radiation was r2=0.91 (p<0.01). This shows that these two parameters are strongly correlated with surface O3 production.
Effect on surface CO2
Light and temperature are two of the most influential parameters on photosynthesis activity. CO2 emissions are linked to the photosynthesis activity of plants. Plants consume more CO2 during the daytime during photosynthesis and release more during respiration at night. In this study, in contrast to the meteorological effects on isoprene and surface O3, temperature and solar radiation showed negative correlations with the CO2 mixing ratios as shown in Figure 6. The daily CO2 maxima were in the range 580 to 780 ppm during the day while the minims were in the range 440 to 468 ppm during the night. This profile of surface CO2 was consistent throughout December 2016.
These results imply that photosynthesis activity controls the mixing ratios of CO2. During the day (when light and temperature are high), CO2 is consumed to produce O2. High light intensity will lead to high temperatures usually during the daytime and results in stomata closing, which is also associated with high vapour pressure deficit (VPD). This means the effects of temperature and light intensity are reduced at low CO2 mixing ratios. According to [49], blue light (BL) has signal functions regulating many processes in chloroplast and stomatal opening in the leaf that may, in turn, affect isoprene emission. The BL also will be adsorbed by the stomata and influence CO2 diffusion in the leaf. Thus, CO2 and isoprene are believed to be influenced by the temperature and light intensity (especially the BL) over the observation site.
The relationships between isoprene-surface O3 and isoprene-CO2.
Isoprene-surface O3
As mentioned, the photochemistry of isoprene can dominate the photochemical production of O3 [50; 51; 52; 53:54]. Both the production of isoprene and surface O3 were observed during the middle of the day throughout the measurement period. It is clearly shown that isoprene production influenced the surface O3 formation during this time (1100 to 1400) (see Figure 6). Secondary products of the isoprene and OH reaction interact with NOx from anthropogenic sources to form surface O3. However, we were expecting the NOx mixing ratios over the palm oil region to be much lower compared to those over the urban area Kuantan (this will be discussed in the next Section).
The movement of vehicles (oil palm collection) is also an expected source of NOx. According to [55], O3 production resulted from the oxidation of isoprene (C5H8 + OH →→ RO2 + NO →→ O3). Higher levels of peroxyl radicals (RO2) during isoprene oxidation will enhance O3 production [55]. Therefore, if NOx levels were high over the observed area, the production of ozone due to the oxidation of isoprene is expected to be higher than in areas with low NOx emissions. [55] also suggested from their model calculation that the oxidation of isoprene also contributed to the enhancement of levels of carbonyls (such as formaldehyde and acetaldehyde). The formation of formaldehyde and acetaldehyde from isoprene oxidation will lead to the enhancement of HO2 radicals. The combination of increased carbonyls and RO2 in the atmosphere suggested the high observations of O3, especially during the middle of the day.
During the evening and night, isoprene removal is much faster (isoprene has a lifetime of ~3 hours) compared to the surface O3 removal process. These chemical removals can be explained by the lifetime of both gases, where surface O3 has longer than isoprene (a lifetime ~3 hours) in the atmosphere (depending on the NOx emissions). In this study, strong daytime correlations between isoprene and surface O3 were observed with r2=0.81 (p<0.01), while weak correlations were observed during the evening and night with r2=0.43 (p>0.01). The correlations between both gases were believed to be influenced by atmospheric lifetime and meteorological factors.
3.4.2 Isoprene-CO2
Isoprene and CO2 mixing ratios measured above the canopy are shown in Figure 6. The diurnal cycle for both measured gases shows night and daytime variability for CO2 and isoprene. The maximum CO2 levels during the night are believed to be linked to plant respiration, while during daytime CO2 is used in the photosynthesis process. Average daily mixing ratios for isoprene and CO2 were 8.9 and 527.3 ppm and 0.2 and 724.1 ppm during the daytime and night, respectively. We believe that in a peat soil ecosystem there will be higher releases of CO2, mainly from the peat, but during the daytime, CO2 is taken up by the oil palm leading to decreasing CO2 mixing ratios.
There is another unknown factor which drives the isoprene emission CO2 response. According to previous studies, high CO2 concentrations inhibit isoprene release into the atmosphere [45]. This has been hypothesized to reflect the inhibition of the activity of isoprene synthase (IspS) or another enzyme of the methylerythritol 4-phosphate (MEP) pathway [56]. This also supported by the evidence from a natural CO2 spring which showed that decreasing of isoprene emissions with increasing CO2 concentration could be linked to a reduction in IspS activity [57].
A study by [58] showed that across CO2 concentrations from 240 to 520 ppmv isoprene emissions from Eucalyptus globulus were enhanced at the lowest CO2 concentration. The study showed that the influence [58;59]. Process-based leaf-level isoprene production models were demonstrated by [59] and [58], also supporting the observation of Wilkinson et al. (2009) that enhanced CO2 levels will depress isoprene production. [60] showed that Triose Phosphate Utilization (TPU) limitation plays a key role in the suppression of isoprene emission from plants under high CO2 concentrations. Under conditions of high CO2 where TPU limits photosynthesis, both ATP and NADPH production are reduced, which under the energy hypothesis would reduce DMADP production [60]. Thus, during the night the reduction of DMADP in the Elaeis guineensis cell reduced the production of isoprene.
3.5 Background information of local influenced from nearby city.
Since we did not measure in situ NOx at the oil palm site, we used secondary 2017 data for surface O3, NO, NO2, NOx and CO from the continues air quality monitoring station (CAQMS) from the Department of Environment (DOE) sites in residential (S1) and industrial (S2) areas in Kuantan (Figure 1). These provide some information on the regional background composition. Two sites are available, one in an industrial area (N 03o57.726 and E 103o22.955), the other in a residential zone (N 03o 49.138 and E 103o17.817). No other data over the region nearby Pekan are available and so we assume that they are representative of Kuantan as a whole and indicative of the atmospheric composition at Pekan when the wind is from Kuantan (see Figure 5). Table 1 shows a summary of monthly average mixing ratios for O3, CO, NOx, NO2 and NO over the Kuantan city region during December 2017.
Table 1
Overall, the observations at the two sites are remarkably similar. The maximum average concentrations of surface O3 for the residential and industrial sites are 10 ppb and 13 ppb, respectively, while those for NOx are 10 and 15 ppb (Figure 7). The mixing ratios of O3 and its precursors show typical diurnal variation patterns as found in previous studies in locations on the east coast of Malaysia including Kuantan [16-18].
Fig. 7
Verification of WRF-CMAQ model result with observations
Isoprene
Hourly distributions of simulated and observed isoprene mixing ratios over the Pekan palm oil plantation during December 2016 are shown in Figure 8. The model captured the diurnal variations and variabilities of the isoprene mixing ratio well throughout the study period. However, the maximum level of modeled isoprene occurred around 1200 LT, two hours earlier than the observed isoprene that was measured at 1400 LT. The average modeled isoprene was 2.49 ppb, slightly lower than the average measured isoprene of 2.63 ppb. The correlation coefficient between the simulated and observed isoprene mixing ratios was found to be 0.32 with an associated mean bias of -0.14 ppb over the location during December 2016. High concentrations of isoprene were observed on the 12th, 20th and 23rd December 2016 at noon and the model is able to capture these peaks. Meteorological parameters such as temperature, RH, precipitation, PBL, wind speed and wind direction have immense control over the BVOC production, distribution and dispersion processes. Observed monthly temperatures and RHs were 27.1 °C, 26.2 °C and 68%, 81.2%, while the model found values around 26 °C, 25.8 °C and 82%, 85% in December 2016 and January 2017 respectively. This indicates a large difference in observed and simulated meteorological conditions except for wind speed (<10 %). Such differences in temperature and RH can result in large variations in the production of isoprene over the region.
Figure 8d shows the first few days of December 2016, where in the model isoprene is rigorously produced, although this turns to fall in line with the observations towards the end. For most of the days, the model could not produce isoprene concentrations (~0 ppb) but did produce precipitation over the study location. Precipitation can trigger wet scavenging and leads to decreases in isoprene concentrations. In January 2017, the model performed well on the first few days, then deviated from the observations. Simulated low temperature and high RH during the study period clearly satisfy the persistence of low isoprene mixing ratios. Like other meteorological parameters, PBL heights also have a critical role in the model to simulate BVOCs [32]. The simulated PBL height over the location is directly proportional to the simulated isoprene and inversely proportional to the observed isoprene concentrations.
On the one hand, direct involvement of PBL height can be found on the emission, dispersion and transport of isoprene in the model. The influence of meteorological parameters on surface O3 means their inclusion in the model is essential due to their effects on isoprene by formation, transport and dispersion of surface O3, especially temperature, PBLH and RH. On the other hand, direct involvement of PBL height can be found on the emission, dispersion and transport of isoprene in the model. Previous study reported that model simulated BVOCs such as isoprene, propene, acetone found low correlation coefficients with observations and large biases [61]. In general, the model was able to capture diurnal variations of the isoprene mixing ratio over the study location, but highly underestimated (30-40 %) most of the days. Such discrepancies in the model can be due to the uncertainties in the dynamics, physics, surface process and the land use/land cover.
Ozone
The correlation coefficient between the simulated and the observed surface O3 is 0.38 with rmsd of 19.1 ppb. The influence of meteorological parameters on surface O3 is essential as its effect on isoprene by formation, transport and dispersion of surface O3, especially temperature, PBL height and RH. In contrary with isoprene simulated surface O3 is overestimated most of the days (~ 35 %), which shows the model producing surface O3 irrespective of isoprene deficiency. According to [62] and [63] the enhanced surface ozone formation is mainly attributed to factors such as oxidation of BVOCs and CO and the emission of isoprene from natural source. The simulated CO and NOx are compared with simulated surface O3 and found a high correlation among each species irrespective of isoprene. This strengthens the influence of CO on surface ozone formation and has a greater effect than isoprene in the model, and led to its overestimation over the study location. The major factors that influence the formation of surface O3 in the model are model resolution, meteorological conditions, spatial distribution of O3 precursors and the non-linearity in the photo chemical O3 formation [62]. Nevertheless, [62] suggests that, the spatial resolution of the model on the formation of O3 and O3 precursors have a large impact than the effect of the resolution associated with emission inventories.
In general, the simulated isoprene and surface O3 represents well over the palm oil plantation by the model during the study period from December 2016 and January 2017. However, an underestimation (30-40%) observed on isoprene and a overestimation (<35%) observed on surface O3 by the model when compared to observation. The discrepancies in the simulation of isoprene and O3 can be improved by further experiment on different model resolutions, meteorological conditions, model physical and dynamical behaviors, emission inventories and the biogenic emission process related to the land use / land cover in the model.
Fig. 8
Model estimation of impact of land use change on the level of isoprene and ozone
The conversion of forest land to oil palm mainly occurs in the central Pekan as discussed in Figure 3. The difference of monthly-averaged isoprene profile between land use of 2016 and 2000 in December 2016 is shown in Figure 9 (a-d). The update of isoprene emission factor on oil palm region has shown clear increment over the source region. The change mainly occurred during the day from 0900 – 1900 LT while isoprene is emitted in respect of the photochemical reactions. Despite a short-lived reactive gas, emitted isoprene is able to transport to inland up to 100 km downwind. This is likely due to the prevailing northeast monsoon during the December month. With the same period of time, the change of O3 is more localized over the source region (Figure 9 (e-f)). O3 has clearly increased over the region where oil palm plantation has expanded.
Fig. 9
On the other hand, during January 2017, the isoprene does not show apparent difference compared to December 2016 and therefore O3 is not affected. The emission of isoprene greatly depends on the weather condition. The high temperature stress triggered large emission of isoprene that is potentially a self-protection mechanism. Figure 10 has shown the temperature difference between the January 2017 and December 2016. It is illustrated that the temperature in January 2017 is lower during the day as compared to December 2016. This is mainly attributed to the boreal winter cold air mass that is carried over to the SEA region along with the northeast monsoon. The model results clearly show a seasonal emission of isoprene, particularly over the east coast of west Malaysia.
Fig. 10
Implications of new oil palm plantations near cities in Malaysia
The average monthly isoprene emissions were found to be 5200 to 7000 ug m−2 h−1 over the Pekan palm oil plantation during the in situ measurements taken in December 2016 from MEGAN-based inventory as shown in Figure 11. Our emission rates were slightly higher than those of [64] over eastern Peninsular Malaysia with a range of 600 to 2500 ug m−2 h−1 during December-January-February 2005. This suggests that the impact of oil palm expansion in Malaysia is to enhance the trends of isoprene over the east coast of Peninsular Malaysia. Our measurements were similar to those of [33] and [9] over palm oil areas of Borneo Malaysia with values of ~10000 ug m−2 h−1. [24] used the MEGAN model to show the emissions of isoprene started from >6250 ug m−2 h−1 (e.g., some locations in Australia, eastern U.S., and the Amazon).
However, Silva et al. (2016) that showed their model prediction with different types of palm oil scenarios as input gave emission rates of isoprene over Borneo and Peninsula Malaysia with absolute differences in excess of 14 µmol m−2 h−1. The WRF-Chem model used by [65] showed lower emission rates of isoprene with 172.9 µg g-1 h-1 over palm oil areas in Distrito Metropolitano de Quito, Ecuador.
We concluded that the uncertainties of land use database input in different models may give different values to the emission rates. To better understand isoprene emission rates, we need more chemical transport models for comparison purposes for future emission predictions. In addition, ecosystem databases can be used to compute reasonable estimates of annual global isoprene emissions but may not produce accurate regional distributions [77].
Fig. 11