3. LA DELIMITACIÓN DE LA COOPERACIÓN HORIZONTAL (CONVENIOS INTERADMINISTRATIVOS)
3.1. Requisitos de la cooperación horizontal fijados por la jurisprudencia del TJUE: caso ISE- ISE-Colonia y caso Remondis
3.1.3. Requisitos teleológicos: objetivo de interés público. Actividad de mercado marginal
Surface weather analysis maps of the West-East Pacific and Alaska provided by National Climatic Data Center (NCDC; http://nomads.ncdc.noaa.gov/ncep/NCEP) indicated that the synoptic situation over the entire model domain for June 2008 had the common features of the typical summer climatology regime of storm tracks and surface winds for the Bering Sea, Aleutian Islands and Gulf of Alaska as described by Fett et al.
(1993), for instance, westerly flows occur over the Bering Sea, storms track from
southwest to northeast spread through the Aleutians into the Bering Sea and storms track occurred into the Gulf of Alaska from the region south of the Aleutians. The model captured those features very well except that it slightly overestimated wind-speed (as discussed in section 3.1).
The surface analysis maps showed a westerly flow over Siberia and across the Bering Sea that occurred during 8-15 June. This flow could potentially transport aerosols and aerosol precursors from Siberia toward Alaska. Over the Aleutian Islands, during the entire study period, the wind directions were mostly from the southwest. These flows could carry the air masses potentially polluted by Japan or ship emissions. The Gulf of Alaska regularly experienced storms moving from south of the Aleutians (days 6 to 9, 14 to 16, and 21 to 23 June). Therefore, the air over the coastal areas along the Gulf of Alaska would be strongly impacted by maritime air masses containing shipping lane emissions. WRF-Chem performed well at capturing very well the main wind direction and the storm appearances over the Pacific (Fig. 6.5).
The same meteorological initial and boundary conditions of REF were applied for IFA to exclude the impact of meteorological changes on PM2.5 distributions from our analysis, i.e. assumption made that over Alaska, synoptic conditions between June 2008 and June 2004 were approximately the same. Surface analysis synoptic maps of Alaska (Plymouth State Weather Center, 2012) indicated that June 2004 and June 2008 had similar wind patterns with calm to light winds (<5 m/s) over Interior Alaska and stronger winds (7.5-10 m/s) over the coastal areas (Fig. 6.6).
6.3.2.2 Emissions
In REF, the emission situation was characterized by high anthropogenic emissions over Japan and the North Pacific shipping lanes and high wildfire emissions over Siberia.
Anthropogenic emissions over Alaska were relatively small compared to the Japanese and ship emissions (Fig. 6.7a1, a2).
Anthropogenic PM2.5 could be from gas-to-particle conversion of precursor gases (SO2, NOx, NH3 and NMVOC) and primary PM2.5 (SO42-, NO3-, EC, OC, unspeciated-PM2.5; emission data for NH4+
were not available). The sum of hourly, regionally-averaged emissions of all PM2.5 precursor gases ( ( )) from anthropogenic sources over Japan, INTE, SAK, WAK, Interior Alaska and NAK were 12.85, 0.34, 0.27, 0.22, 0.19 and 0.18 mol km-2 hr-1, respectively. Primary PM2.5-aerosol emissions ( ( )) were 18.14, 0.66, 0.19, 0.09, 0.02 and 0.02 g km-2 hr-1 over Japan, INTE, SAK, WAK, Interior Alaska and NAK, respectively.
While anthropogenic emissions occurred only in the near-surface layer, wildfire emissions occurred throughout the vertical column from near-surface layer up to the layer corresponding to simulated smoke plume injection height. In the WRF-Chem simulations, the daily-averaged injection heights of the wildfire emissions over Siberia varied from ~750 to 8000 m above ground level depending on fire size and meteorological conditions, which were higher the observed injection heights of wildfire emissions over Siberia in 2008 reported by Jet Propulsion Laboratory (2013) (~ 719 to 1820 m above sea level). Over Siberia the column-integrated PM2.5 precursor emissions from wildfires were 6.55 mol km-2 hr-1, whereas the anthropogenic sources emitted only
0.46 mol km-2 hr-1. Also, the primary PM2.5 emissions from wildfires were 21.60 g km-2 hr-1 over Siberia. In June 2008, there was no noticeable wildfire emission in Alaska (Fig.
6.7a2) except for some relatively low wildfire emissions on 14-15 and 21-22 June (Fig.
6.8b).
Anthropogenic sources emitted higher amounts of inorganic PM2.5 precursor gases (e.g., SO2, NOx and NH3) than organic PM2.5 precursor gases (NMVOC), whereas wildfire sources emitted higher amounts of NMVOC than inorganic PM2.5 precursors.
The sum of SO2, NOx and NH3 anthropogenic emissions was approximately 4 times higher than the NMVOC anthropogenic emissions. Conversely, the NMVOC emissions from wildfires were approximately 4.5 times higher than the sum of those inorganic gases from wildfires. Therefore, the speciation of PM2.5 impacted by anthropogenic sources would be indicated by higher percentages of inorganic species (i.e., SO42-, NO3- and NH4+
) than organic species (i.e., OC); whereas, high OC percentages in PM2.5 speciation would be an indicator of wildfire emission impacts. It is well known that the low ratio EC/OC due to high OC concentrations is usually used as wildfire smoke tracer (Andreae and Merlet, 2001; Park et al., 2003; Ames et al., 2004).
IFA was assumed to have the same anthropogenic emissions as REF; however, the wildfire emission situation of IFA was very different from the wildfire emission situation in REF. In IFA, there were very high wildfire emissions in Alaska and almost no wildfire emissions in Siberia (Fig. 6.7b1, b2). In IFA, over Interior Alaska the hourly averaged, column-integrated PM2.5 precursor and primary PM2.5 emissions from wildfires were 4.57 mol km-2 hr-1 and 28.80 g km-2 hr-1, respectively. In this emission scenario,
PM2.5 precursor emissions from wildfires were 25 times higher than those of anthropogenic sources in Interior Alaska. There were no wildfire emissions in NAK, SAK and WAK during this period. Wildfire emissions over Siberia in REF and over Interior Alaska in IFA increased toward the end of the month (Fig. 6.8a).