Agresividad en la adolescencia

6.2.5 CCATT-BRAMS model

The Chemistry-Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modelling System (CCATT-BRAMS) is an on-line regional chemical transport model to study local and regional atmospheric chemistry from the surface to the lower stratosphere (Longo et al., 2013). CCATT-BRAMS is based on the Regional Atmospheric Modelling System version 6 (RAMS) (Walko et al., 2000), which is a fully compressible non-hydrostatic model consistent with TRIPOLI (1982). RAMS is able to simulate meteorological processes, such as turbulence, shallow cumulus convection, deep convection, surface-air exchanges, cloud microphysics, and radiation (Hamer et al., 2013). The model BRAMS is built upon RAMS and includes further improvements for tropical regions, such as an ensemble implementation of the deep and shallow convection.

CCATT-BRAMS has already been used to study the transport and chemistry of bromoform (CHBr₃) and its product gases during a convective outflow event that occurred on sortie 3 (19 November 2011) of the SHIVA campaign (Hamer et al., 2013). A detailed description of CCATT-BRAMS can be found in Hamer et al. (2013).

The model output presented in this study is kindly provided by Paul Hamer (Centre National de Recherches M´et´eorologiques, Chimie Atmosph´erique Recherches en Mod´elisation et Assimilation, M´et´eo-France and CNRS, France, personal communication, March 2013). The emitted species provided by the CCATT-BRAMS model include HCHO, CO, NO₂, and a lumped chemical species called ’BIO’, which is mostly isoprene plus some other terpenes. The model was spun up for 2 weeks prior to the SHIVA campaign and was run for 6 weeks in total. The model ran at a horizontal resolution of 50 km x 50 km. The vertical grid consisted of 53 vertical levels with a varying resolution using a finer resolution of 50 to 500 m within the boundary layer, and a coarser resolution of 300 to 500 m between an altitude of 13 and 20 km. Further, the model was initialised, has boundary conditions from, and is forced by ECMWF wind, temperature, geopotential height, and humidity fields. Biogenic emissions were derived from the MEGAN model similar to the inventory included in TOMCAT (see Section 6.2.4). The photolysis rates were calculated on-line using the Fast-TUV radiative model of Tie et al. (2003).

6.3 Regional characteristics

Borneo is the largest island of Asia and is located at the centre of Maritime South-East Asia (http://en.wikipedia.org/wiki/Borneo). The island of Borneo is politically divided into three parts, which belong to the countries Malaysia, Indonesia, and Brunei (Figure 6.3).

Figure 6.3: Map of Borneo, adapted from Google Earth, October 2013.

During the SHIVA campaign an overflight permission over the Indonesian part of Borneo (Kali-mantan) could not be obtained, and hence, air over Kalimantan could not be probed. Brunei and the Malaysian states of Borneo (Sarawak and Sabah) are surrounded by the South China Sea in the north, the Sulu Sea in the northeast and the Celebes Sea in the east. Borneo owns one of the oldest tropical rain forests in the world. Tropical rain forests are known to emit large amounts of volatile organic compounds (VOCs) (e.g. Guenther et al., 1995, 2006). Ground-based and airborne measurements carried out during the ”Oxidant and particle photochemical processes above a South-East Asian tropical rain forest” (OP3) campaign in Borneo in 2008 (Hewitt et al., 2010) show that VOCs over the rain forest of Borneo are dominated by isoprene and its oxidation products, with a significant contribution from monoterpenes (MacKenzie et al., 2011). Isoprene is one of the most abundant biogenic VOCs naturally emitted into the atmosphere (Guenther et al., 2006). It reacts rapidly with OH and can not only enhance the formation of tropospheric ozone in polluted areas, but it can also lead to the formation of secondary organic aerosols (SOA), which can act as cloud condensation nuclei (CCN) (Kiendler-Scharr et al., 2009; Robinson et al., 2011). However, there is a strong deforestation in Borneo especially due to the development of the oil palm industry (Pyle et al., 2011). The expansion of oil palm plantations has increased rapidly in Malaysia between 1975 and 2010 (Miettinen et al., 2012a,b). Figure 6.4 shows the extent of oil palm plantations on peatland in South-East Asia for 1990 and 2010. Especially in the state of Sarawak an immense increase of palm oil plantations (≈ 40 %) is observed between 1990 and 2010 (Miettinen et al., 2012a). According to Fowler et al. (2011), VOC emissions from oil palm plantations are substantially larger than from the rain forest by roughly a factor of 3. Furthermore, a change in land-use also leads to an increase in NO_xthrough the use of fertilisers or pollution from industry and transport, thus, potentially having a major influence on the air quality (Warwick et al., 2013). Stavrakou et al. (2014) examined the isoprene emissions over Asia between 1979 and 2012, particularly regarding the impact of land-use change on climate. They claim that due to the warming trend over Asia with approximately 0.24°C per decade, the isoprene emissions in Asia may have increased by approximately 0.2 % per year since 1979. For example in Malaysia the isoprene emissions may have increased by 1.5 % from 1979 to 2005. Contrary to that but confirmed by measurements during the OP3 campaign in Borneo as well as by satellite measurements, Stavrakou et al. (2014) further state that the tropical rain forests of Indonesia and Malaysia have much lower isoprene emissions than those previously used in model calculations.

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Figure 6.4: Distribution of oil palm plantations on peatland in South-East Asia in 1990 and 2010, respectively (adapted from Miettinen et al. (2012a)). It is important to note that the map only shows oil palm plantations on peatland. The number of oil palm plantations on peatland does not necessarily correspond to the total number of oil palm plantations in this region.

Land clearing especially for oil palm plantations results in anthropogenic burning of the rain forest and the degradation of peatlands. Zender et al. (2012) applied a fire and smoke detection algorithm to investigate biomass burning plumes as detected by the MODIS (Moderate Resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectroradiometer) satellite data over Borneo between 2001 and 2009. The identified Borneo smoke plumes have a mean length of 41 km, a mean height of 708 m, and a mean width of 27 % of their length, and follow the orientation of the prevailing southeasterly winds. Zender et al. (2012) further expect that the orientation and plume width are representative for all Borneo smoke plumes. Figure 6.5 shows fire maps for the time period of the SHIVA campaign, detected by MODIS on board the TERRA and AQUA satellites. The red dots indicate the location where MODIS found at least one fire during the specified period. The fire detection algorithm is described in Giglio et al. (2003). Several fire events occurred along the coastline of Sarawak during November 2011, where several oil palm plantations are located (Figure 6.4). However, the number of fire events decreased in December 2011. During several take-offs and landings, the Falcon aircraft passed on occasion these plumes. Table 6.3 provides an overview of the fire events, which occurred in the vicinity of the different sorties of the Falcon aircraft. The fire events are simulated with the Lagrangian particle dispersion model FLEXPART (Stohl et al., 2005) (Section 6.2.1).

Figure 6.5: MODIS fire maps for a) 08.11.-17.11.2011, b) 18.-27.11.2011, c) 28.11.-07.12.2011, and d) 08.12.-17.12.2011 (http://lance-modis.eosdis.nasa.gov/imagery/firemaps/).

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Table 6.3: Overview of the contribution of CO to fire events. The data was compiled by Gis`ele Krysztofiak (CNRS, Universit´e d’Orl´eans, France, personal communication, June 2013) from FLEX-PART simulations provided by Sabine Eckhardt.

date origin emission age [days] CO from fires [ppb]

16.11.11 North Borneo 7 10-14

19.11.11a North Borneo, North Australia <10 19-25 19.11.11b North Borneo, Philippines 1-8 >2

Apart from biomass burning, other potential sources for pollution in Borneo are the emissions from oil and gas rigs and refineries. Numerous offshore oil platforms can be found along the coast of Sarawak. In addition to the emissions due to flares, process gas or oil is burned on the platforms.

Figure 6.6 shows the distribution of offshore oil rigs around Borneo. Several offshore oil rigs are located off the coast of Miri and Brunei, but also at the north-western coast close to Bintulu. The technical report of the Texas Commission on Environmental Quality Air Quality Division (TCEQ, 2007) summarises the different emissions from oil and gas production facilities. They state that the potential pollutants are mainly SO₂, NO_x, VOCs, CO, and particulate matter (PM). The largest source for SO₂, NO_x, CO, and PM is represented by the drilling rig engines and compressor engines, whereas the largest sources for VOCs can be assigned to glycol dehydrators, condensate storage tanks, or gas production wellheads.

Figure 6.6: Distribution of oil platforms around Borneo. The offshore oil platforms are marked with a yellow buoy pinned to a black square. There are many other symbols in the map representing e.g. wrecks, rocks, underwater obstructions, light towers, pile beacons, water buoys, or installation buoys, which are not relevant for this study. Extracted from the software PolarView NS Version 1.8.41 (http://www.polarnavy.com).

Further, Malaysia has an extensive coastline surrounded by mangroves or coral reefs, which are increasingly used for seaweed production (Phang, 2006). Seaweeds are macroalgae and can be classified into brown, red, and green macroalgae, based on their type of pigmentation (McHugh, 2003). They are naturally growing or farmed for food or commercial products, e.g. as a renewable source of fuel (McHugh, 2003; John et al., 2011). Particularly in the northeastern part of Sabah and the archipelagos between Sabah and the Philippines, areas with enhanced seaweed farming exist, which have grown quickly over the last two decades (Phang, 2006). Several studies in the past years have shown that macroalgae have the potential to emit halocarbons like bromoform (CHBr₃) or methyl iodide (CH₃I), as they concentrate halides from the sea water, which then act as antioxidants (e.g. Leedham et al. (2013) and references therein). Figure 6.7 shows seaweed and seaweed farms close to Semporna in the northeastern part of Borneo, recorded during sortie 4 of the SHIVA aircraft campaign. However, according to longterm halocarbon measurements (2008 -2010) at a coastal and an inland site in Sabah, Borneo, South-East Asia does not represent a hot spot for the emission of halocarbons, as has been suggested before (Robinson et al., 2014).