曝光臺 注意防騙 網曝天貓店富美金盛家居專營店坑蒙拐騙欺詐消費者

Hungary Budapest 1553 1588 1602 1572 0.1 0.0 0.0 0.1 67% 63% 100% 63%
Ireland Dublin 567 622 620 520 0.2 0.1 1.5 0.1 77% 86% 76% 99%
Ireland Shannon 1146 1205 1204 1086 0.0 0.0 0.1 0.0 13% 0% 6% 0%
Italy Brindisi 778 837 865 817 0.1 0.1 0.0 0.0 99% 93% 90% 99%
Italy Milano 1786 1893 1783 1664 1.4 0.8 0.2 0.1 79% 95% 96% 100%
Italy Padova 1715 1879 1799 1673 0.3 0.6 0.4 0.2 21% 39% 78% 89%
Italy Roma 2478 2705 2699 2585 0.8 0.8 0.5 0.1 76% 93% 98% 98%
Latvia Riga 416 476 515 460 0.0 0.0 0.0 0.0 0% 0% 0% 0%
Lithuania Vilnius 356 476 583 515 0.0 0.0 0.0 0.0 0% 0% 0% 0%
Maastricht Maastricht 4207 4410 4395 4068 0.3 0.6 0.5 0.0 0% 0% 0% 0%
Malta Malta 207 223 231 233 0.0 0.0 0.0 0.0 100% 0% 0% 0%
Moldova Chisinau 75 94 110 119 0.0 0.0 0.0 0.0 0% 0% 0% 0%
Netherlands Amsterdam 1433 1490 1439 1331 0.4 0.8 1.1 0.3 80% 91% 96% 86%
Norway Bodo 508 527 530 522 0.5 0.0 0.1 0.0 8% 28% 75% 100%
Norway Oslo 830 886 929 866 0.1 0.4 0.2 0.1 48% 46% 91% 89%
Norway Stavanger 523 556 558 540 0.1 0.1 0.1 0.4 1% 11% 22% 6%
Poland Warszawa 1246 1411 1558 1438 1.5 2.3 2.2 1.8 30% 15% 4% 3%
Portugal Lisboa 1035 1096 1121 1036 0.1 0.4 0.4 0.1 82% 30% 55% 83%
Portugal Santa Maria 258 265 283 274 0.0 0.0 0.0 0.0 0% 0% 0% 0%
Romania Bucuresti 1136 1182 1212 1186 0.0 0.0 0.0 0.0 0% 0% 100% 0%
Serbia and Montenegr Beograd 1045 1218 1314 1373 0.0 0.0 0.0 0.0 4% 9% 0% 0%
Slovak Republic Bratislava 855 840 891 880 0.1 0.5 0.2 0.1 0% 0% 0% 0%
Slovenia Ljubjana 539 624 671 632 0.0 0.3 0.0 0.0 0% 3% 19% 1%
Spain Barcelona AC+AP 2115 2321 2250 2033 0.9 0.5 0.4 0.2 20% 37% 48% 33%
Spain Madrid 2688 2904 2860 2609 1.6 1.9 1.1 1.2 63% 54% 32% 36%
Spain Palma 712 749 733 678 0.3 0.6 0.9 0.6 99% 99% 99% 77%
Spain Sevilla 1025 1100 1067 956 0.4 0.3 0.1 0.2 11% 20% 7% 16%
Spain Canarias Canarias 830 844 840 730 0.5 0.4 0.5 1.7 31% 35% 35% 9%
Sweden Malmo 1323 1366 1448 1271 0.0 0.0 0.1 0.0 13% 11% 2% 15%
Sweden Stockholm 1107 1116 1128 1028 0.0 0.5 0.1 0.1 90% 97% 89% 73%
Switzerland Geneva 1704 1832 1813 1645 0.8 1.0 0.8 0.4 18% 30% 36% 46%
Switzerland Zurich 2040 2127 2156 2014 1.6 1.8 1.1 0.8 21% 33% 28% 24%
Turkey Ankara 1310 1427 1544 1600 0.1 0.2 0.5 0.2 100% 78% 55% 55%
Turkey Istanbul 1165 1470 1567 1653 0.5 0.3 0.9 1.6 96% 100% 100% 99%
Ukraine Dnipropetrovs'k 61 60 45 0.0 0.0 0.0 0% 0% 0%
Ukraine Kharkiv 276 324 308 0.0 0.0 0.0 0% 0% 0%
Ukraine Kyiv 477 547 488 0.0 0.0 0.1 100% 0% 70%
Ukraine L'viv 371 428 416 0.0 0.0 0.0 0% 0% 0%
Ukraine Odesa 183 208 202 0.0 0.0 0.0 0% 0% 0%
Ukraine Simferopol 460 481 463 0.0 0.0 0.0 0% 0% 0%
Ukraine Donets'k 37 37 0.0 0.0 0% 0%
United Kingdom London AC 5349 5508 5427 4980 0.6 0.6 0.6 0.2 1% 0% 1% 1%
United Kingdom London TC 3738 3854 3780 3480 0.8 1.0 1.1 0.6 89% 85% 93% 81%
United Kingdom Manchester 1620 1666 1569 1352 0.6 0.3 0.2 0.1 20% 37% 39% 69%
Regulations on traffic volumes EGLL60, EHFIRAM, LEBLFIN, LECMARR1 have been reclassified as airport regulations. data source : EUROCONTROL
ACCs geographical areas might change thru times, preventing year to year comparison (e.g.: SOFIA and VARNA)
Daily Traffic Delay per flight (min/flight) Airport delay share of total delay
124
ANNEX IV - TRAFFIC COMPLEXITY
The PRU, in close collaboration with ANSPs, has defined a set of complexity indicators that
could be applied in ANSP benchmarking. The complexity indicators are computed on a
systematic basis for each day of the year. This annex presents for each ANSP the complexity
score computed over the full year (365 days).
The complexity indicators are based on the concept of “interactions”. Interactions arise when
there are two aircraft in the same “place” at the same time. For the purpose of this study, an
interaction is defined as the simultaneous presence of two aircraft in a cell of 20x20 nautical miles
and 3,000 feet in height.
For each ANSP the complexity score is the product of two components:
Traffic density indicator is a measure of the potential number of interactions between aircraft.
The indicator is defined as the total duration of all interactions (in minutes) per flight-hour
controlled in a given volume of airspace.
The structural complexity originates from horizontal, vertical, and speed interactions. The
Structural index is computed as the sum of the three indicators
Horizontal interactions indicator: A measure of the
complexity of the flow structure based on the potential
interactions between aircraft on different headings. The
indicator is defined as the ratio of the duration of horizontal
interactions to the total duration of all interactions.
Vertical interactions indicator: A measure of the
complexity arising from aircraft in vertical evolution based
　
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本文鏈接地址：Performance Review Report 2009(88)