TIME AND TRAFFIC SURVEY REPORT NIMULE-ELEGU BORDER (SOUTH SUDAN/UGANDA)

FINAL REPORT Rock city parking yard TIME AND TRAFFIC SURVEY REPORT NIMULE-ELEGU BORDER (SOUTH SUDAN/UGANDA) Consultant: Lillian Muhebwa Client: Trade Mark East Africa (TMEA) June 2013

EXECUTIVE SUMMARY This is a report on the time and traffic survey undertaken at Nimule-Elegu, on the South Sudan/Uganda border in April, 2013. The assignment was aimed at obtaining baseline statistics at this border including queue time, customs processing time through country customs areas, Origin and destination of Commercial s and Buses, as well as total and daily traffic volumes. Results of the survey undertaken for a duration of seven (7) consecutive days indicate that traffic at this border is majorly commercial traffic including buses and. This traffic component accounts for 81% and 68% of the total through traffic recorded of 2159 and 2668 vehicles respectively at Elegu and Nimule respectively. Commercial traffic majorly services the towns of Kampala, Nairobi, Mombasa, Eldoret, Nakuru and Juba. A summary of the baseline statistics required as part of the terms of reference is as presented below Key traffic Parameter Elegu Outbound traffic Nimule Outbound traffic day time traffic: 1557 Vehicles 2391 Vehicles Ave daily Day time traffic 222 Vehicles 342 Vehicles Ave daily Night time traffic 86 Vehicles 40 Vehicles Estimated Night traffic 602 Vehicles 277 Vehicles Estimated traffic 2159 Vehicles 2668 Vehicles Average daily traffic 308 Vehicles 381 Average Daily Queue time 13 hours 38 Minutes 48 Minutes Average Daily Customs processing time 22 hours 12 Minutes 3 hours 28 Minutes waiting time 59 hours 50 Minutes 4 hours 16 Minutes The estimated night time traffic at Nimule is significantly lower because night counts were stopped by RSS security personnel after only three hours of the planned 12 hours for the two night surveys. Traffic Outbound at Elegu has a higher dwell time at the border because are laden and as compared to outbound traffic at Nimule that is mainly empty and thus with less procedural requirements. Overall, trailer at Elegu have the highest dwell time of 88 hours and 21 minutes with Light having the least. This dwell time is also relatively high because of the manual system used for document processing and registry. At Nimule, queue for a maximum of 5 hours 22 minutes with corresponding maximum dwell time within the customs clearing zone of 13 hours 38 minutes. The latter can mainly be explained by night time arrivals after closing time of about 19:00 EAST and have to wait until the traffic is allowed through the next morning. 1 P a g e

Table of Contents EXECUTIVE SUMMARY... 1 ACRONYMS AND KEY DEFINITIONS... 3 1 INTRODUCTION... 4 1.1 ASSIGNMENT SCOPE... 4 1.2 METHODOLOGY... 5 1.2.1 Time survey... 5 1.2.2 Traffic survey... 5 1.2.3 Data collection and preparation for survey... 7 1.2.4 Vehicle Categorisation... 8 1.2.5 Overview of truck movement procedures... 8 2 SURVEY RESULTS... 9 2.1 Traffic Volume component... 9 2.1.1 Elegu - Outbound traffic Uganda... 9 2.1.2 Nimule - Outbound traffic South Sudan... 12 2.2 Origin destination survey... 16 2.2.1 Traffic originating from Uganda... 16 2.2.2 Traffic originating from South Sudan... 16 2.3 Queue time... 18 2.3.1 Elegu-Uganda... 18 2.3.2 Nimule... 19 2.4 Processing Time... 20 2.4.1 Elegu - Uganda... 20 2.4.2 Nimule South Sudan... 21 3 CONCLUSION... 23 ANNEX I DATA COLLECTION FORMS... 24 2 P a g e

ACRONYMS AND KEY DEFINITIONS CCZ CPT DRC EAST OSBP Customs Clearing Zone Customs Processing Time Democratic Republic of Congo East Africa Standard Time One Stop Border Post TMEA TradeMark East Africa TOR URA RSS Terms of Reference Uganda Revenue Authority Republic of South Sudan 3 P a g e

1 INTRODUCTION This report presents the results of the Time and Traffic survey conducted at the Nimule-Elegu border crossing between South Sudan and Uganda. Nimule-Elegu is the main border of South Sudan to Uganda and services Juba, the capital city of the Republic of South Sudan. The survey was commissioned by TradeMark East Africa (TMEA) as part of collecting baseline data to be used in the planning, and monitoring and evaluation of its projects in particular the One-Stop Border Post (OSBP) project aimed at reducing transport and related costs along the key transport corridors in East Africa. 1.1 ASSIGNMENT SCOPE This survey involved three main components viz obtaining statistics on through traffic at the border, waiting/dwell time for commercial at the border and origin/destination survey for commercial vehicles. The study objectives were to: i) Obtain queue waiting time and customs processing time for transporting commercial cargo (both containerised and non-containerised cargo) at the Nimule-Elegu border and thus determine total waiting time at the above mentioned borders. ii) Determine baseline border crossing times against which future changes will be measured. iii) Determine baseline border traffic volumes by vehicle category and composition by types of goods (containers, petroleum products) and categories. iv) Obtain information on origin/destination of selected commercial traffic (Coaches, Coasters and all truck categories). Specifically, the survey sought to obtain statistics on: i) The average number of queuing. ii) The estimated average queue time for commercial disaggregated by category iii) The estimated average customs processing time iv) Day time traffic by category of vehicles; v) Average day time traffic by category of vehicles; vi) Estimated Night traffic by category of vehicles; vii) Average night time traffic by category of vehicles viii) Average Daily Traffic (by category) ix) Volume of traffic for the survey week x) Origin/Destinations for the selected commercial traffic (Coaches, Coasters and all truck categories). 4 P a g e

1.2 METHODOLOGY The methodology adopted for obtaining data for the different survey components is detailed below: 1.2.1 Time survey A manual queue time survey was undertaken over a period of 7 days, for 12 hours daily starting at 0600 hours East African Standard Time (EAST) and ending at 1800 hours EAST. Data collection was also undertaken for 24 hours on two days (one week day and one weekend day) to obtain representative data/information for night traffic. Eight data collection stations were commissioned as detailed below and as illustrated in the schematic in figure 1-1 below. i) Station A1 at end of the queue for arriving at the border from Uganda to obtain arrival times for traffic originating from Uganda (T 1 ) ii) Station A2 at the front exit gate on from the parking yard on the Uganda side of the border to obtain exit times for traffic originating from South Sudan(T 2 ) iii) Station A3 at the back exit gate on from the parking yard on the Uganda side of the border to obtain exit times for traffic originating from South Sudan(T 3 ) iv) Station B at the entry gate into the CCZ in front of Uganda Revenue Authority offices to obtain time of entry into the Customs area for traffic originating from the Uganda(T 4 ) v) Station C at the security stop/check point for traffic exiting South Sudan to obtain time of entry into the CCZ for traffic originating from South Sudan (T 5 ) vi) Station D1 at the T-junction before the entrance to the main vehicle parking yard at RSS customs office Nimule to obtain arrival times for traffic originating from South Sudan (T 6 ) vii) Station D2 at the junction after the rock city vehicle parking yard in Nimule long the nimule- Juba highway to obtain exit times for traffic originating from Uganda (T 7 ) Time data was also collected from the Jebel Parking yard for truck exits. Queue times are calculated as the difference between entry times at stations A and D and entry times into the CCZ at stations B and C respectively; that is [T 4 - T 1 ] and [T 6 -T 5 ]. Customs processing times are calculated as the difference between entry times into the CCZ at stations B and C and Exit times out of the CCZ in the next country at stations A and D respectively; that is [T 7 - T 4 ] and [T 6 -T 3 ] or [T 6 T 2 ] for traffic originating from Uganda and South Sudan, respectively. 1.2.2 Traffic survey This component involved traffic volume, and origin and destination survey. Manual classified traffic counts were conducted at each border crossing over a period of 7 days, for 12 hours on each day. In addition, 24 hour counts were performed for one week night and one-weekend night during the 5 P a g e

survey week to obtain indicative night traffic. Road side interviews with truck drivers were also conducted to obtain Origin/Destination information. As with the time survey component, data was collected at four stations as below: i) Stations A1 and D1 data on all vehicular traffic originating from Uganda and Rwanda respectively ii) Stations B and C - data on origin and destination for commercial traffic originating from Uganda and South Sudan respectively Figure 1-1: Schematic Layout of Survey stations 6 P a g e

1.2.3 Data collection and preparation for survey i) Data was collected by enumerators recruited from the local community as specified in the TOR. The enumerators were prepared for the survey and trained on the use of the data collection instruments. Training took place two days prior to the start of the actual data collection exercise as detailed hereafter. ii) Training details The training took a two pronged approach involving both theoretical and practical sessions. The theoretical session adopted a Class room style arrangement using simple language and participatory tools. Participants were taken through the study scope, data collection forms and key elements of the survey like Vehicle categories, survey duration and protocols as well as data quality. The practical session was done on two days and involved atransect to familiarize enumerators with proposed data collection stations, and vehicle categories. Thereafter, data collection by enumerators using the survey forms for a period of two hours each on both days of the training with each enumerator collecting data at each of the two main station categories. A debrief was held to discuss results of the exercise, clarify on any outstanding issues and agree the final team of enumerators. The second practical session was to clarify any outstanding issues and for enumerators to get more practice with the data collection forms Figure1-2 record of training session iii) Three categories of data collection forms as detailed in Annex I were used. Form category 1 to capture data on traffic volumes as well as truck arrival, Form category 2 to capture origin and destination data on buses and time (entry into CCZ) data for commercial, Form category 3 for time (exit from CCZ) data for commercial. Category 1 Forms were used at stations A1 and D1, category 2 forms at stations B and C while category 3 forms were used at stations A2, A3 and D2. 7 P a g e

1.2.4 Vehicle Categorisation For purposes of this survey, vehicles were categorized into four major categories with key subcategories as detailed in the table below: Vehicle Category Description 1.Container s: Header s All transporting removable containers (20ft and 40ft). Tankers All commercial fuel transporting vehicles 2.Non-containerised : Light truck Pickups, lorries and small carrying capacity up to 8T Medium truck Other 3.Buses: Coach Coaster Minibus 3.Passenger vehicles: Saloon/Sedan/Mini-van 4WD s Pick-ups s with equivalent carrying capacity from 8T up to 15T All other non-containerised larger than medium All commercial buses transporting 45 or more passengers All commercial buses transporting max 30 passengers All commercial buses transporting max 14 passengers Small passenger vehicles of capacity up to 7 passengers Large passenger vehicles Passenger pickups Not carrying goods 1.2.5 Overview of truck movement procedures Elegu Outbound traffic: On arrival, queue by the roadside along the Gulu-Nimule Road, the queue regularly stretching to over a kilometer. Documents are submitted to the URA official at the entry/exit gate. s are let through depending on the traffic between the exit barrier and before the bridge. Consignment details are then recorded in a manual register by URA then passed on to RSS customs officials operating in the URA office. The latter also make records in a manual register then documents are sent to Nimule for the rest of the customs process. On entry, the truck driver formalizes with Uganda immigration procedures and waits for exit advice from the customs agent before finalizing RSS immigration procedures. After crossing into the CCZ on the Nimule side of the border, s are then parked in one of the three parking yards, after registering their records in the exit register; waiting to be exited. Priority parking is in the main customs yard tankers and with relief items use the rock city parking yard and the third parking at Nimule national park entry is mainly used when the other two are full. s are exited once the customs process is complete Nimule Outbound traffic: on arrival, proceed to the security check point, the Turnman/Co-driver proceeds to clear with immigration and register truck details in the exit register. s then proceed to the Elegu side and park in the customs yard. details are recorded by URA in a manual register after completion of relevant documentation (empty manifest) and transit traffic pays the necessary road user fees at URA. s are released thereafter and exit to Uganda. 8 P a g e

2 SURVEY RESULTS 2.1 Traffic Volume component Day time traffic volumes for vehicular traffic crossing the Nimule-Elegu border were recorded daily on each of the survey days from 6:00 to 18:00 EAST. In addition, night traffic volumes were also recorded on one weekday and one weekend day at Elegu 1. Data collection on the Nimule side was only undertaken up 22:00 due to security concerns with the enumerators not being allowed at their stations by security personnel. Results of this survey component are presented in the sections that follow. 2.1.1 Elegu - Outbound traffic Uganda Results of the traffic counts are presented in table 2-1 below and also graphically illustrated in figure 2-1. Table 2-1: Through traffic statistics Day time Traffic originating from Uganda Survey Day Passenger vehicles Buses Non-containerised tankers Day 1 48 20 92 52 15 227 Day 2 21 10 95 52 19 197 Day 3 52 19 95 43 26 235 Day 4 50 19 90 52 47 258 Day 5 41 22 91 46 27 227 Day 6 85 12 69 44 19 229 Day 7 40 21 78 36 9 184 Category 337 123 610 325 162 1557 Average daily 48 18 87 46 23 222 % 22% 8% 39% 21% 10% 100% Average daily vehicular day time traffic for traffic originating from the Elegu side of the border was obtained as 222 vehicles. The total day-time through traffic for the survey week was 1557 vehicles. An analysis of the traffic composition summarized in figure 2-1indicates that commercial as defined by this survey contribute the largest proportion of through traffic at the Nimule-Elegu border, contributing 70% of the total traffic. Further analysis of this traffic category indicates that non containerized account for the largest proportion of commercial - 39% of total traffic, with the containerized ( tankers and ) contributing 31% of total traffic. 1 Night time data collection was disrupted on both days planned for 24 hour data collection 9 P a g e

Traffic volume Vehicle Traffic composition - Elegu Buses 8% Passenger vehicles 22% Commercial s 70% Noncontanerised 39% Containerised s 31% Figure 2-1: Vehicle Traffic Composition - Elegu The daily traffic variation presented in figure 2-2 below shows that the daily traffic volumes across the different survey days are within the same range, with a standard deviation of 25. The highest daily traffic volume obtained was on day 4 (258 vehicles) and the lowest on day 7 (184 vehicles), both of which are weekdays. Daily traffic volume variation - Elegu 300 250 200 150 100 50 0 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 tankers 15 19 26 47 27 19 9 52 52 43 52 46 44 36 Non-contanerised 92 95 95 90 91 69 78 Buses 20 10 19 19 22 12 21 Passenger vehicles 48 21 52 50 41 85 40 Figure 2-2: Daily Traffic Variation 10 P a g e

6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 1:00 2:00 3:00 4:00 5:00 Traffic Volume Overall there are significant traffic volumes obtained across the different vehicle categories. Commercial traffic in particular is high at this border. The average daily truck volumes are disaggregated as 87 non-containerized, 23 tankers and 46 trailer. Night time traffic volumes are also significant and the results are presented in table 2-2: Table 2-2: Through traffic statistics Night Traffic originating from Uganda Survey Day Passenger vehicles Buses Noncontanerised tankers Weekend day 10 8 32 14 12 76 Week day 12 7 38 18 21 96 Average daily Night traffic 11 8 35 16 17 86 Night time traffic is quite high at the Nimule-Elegu border. The average daily night traffic on the Elegu side for the two survey days was obtained as 86 vehicles. Most of the night time traffic is commercial traffic comprising mainly the non-containerized. Traffic on weekend days of the survey is lower, about 79% of that recorded on the week days. 160 140 120 100 80 60 40 20 0 Vehicular Traffic hourly variation Hour Comparison of day time and night time traffic volumes indicates that traffic is largely day time traffic, this comprising an estimated 72% of the total traffic. Vehicle arrival trends across the survey week as summarized in figure 2-4 aside, further reinforce the traffic flow trend. It is noted that most of the traffic is day time traffic with Figure 2-4: Hourly traffic flow variation several peaks. The highest hourly traffic volumes were recorded in the morning from 6:00am to 10:00am, at 13:00 hours and 16:00hours. From the figure, the most notable hourly traffic volume peaks are early morning between 7:00 and 9:00 EAST and afternoon at 13:00 and 16:00 EAT. This indicates that traffic builds up creating long queues as shown in the frame in figure 2-5 below. Night time traffic recorded was on average less than 20 vehicles per hour, Night traffic tails off about 23:00 hours and starts to pick up at 04:00hours. 11 P a g e

Figure 2-5: Illustration of queuing at Elegu The estimate of the total through traffic at Elegu is presented in Table 2-3 below: Table 2-3: Estimated Through traffic statistics From Uganda Parameter Passenger vehicles Buses Non-contanerised tankers day traffic 337 123 610 325 162 1557 Ave Night traffic 11 8 35 16 17 86 Estimated Night traffic 77 53 245 112 116 602 Estimated traffic 414 176 855 437 278 2159 *- Estimated night traffic is obtained using statistical average not the rounded average figure The estimated total through traffic was obtained as 2159 vehicles translating to an estimated daily average of 308 Vehicles. The corresponding volumes for the different vehicle categories are shown in table 2-3. As with both Night and Day time traffic statistics, the total traffic is largely commercial vehicles i.e. s and Buses, contributing 68% of the total traffic. 2.1.2 Nimule - Outbound traffic South Sudan Results of the traffic counts are presented in table 2-4 below and also graphically illustrated in figure 2-5. 12 P a g e

Survey Day Table 2-4: Through traffic statistics Day time Traffic originating from South Sudan Passenger vehicles Buses Non-containerised tankers Day 1 78 16 137 37 35 303 Day 2 137 22 142 38 43 382 Day 3 141 20 130 41 39 371 Day 4 147 44 131 52 31 405 Day 5 74 33 145 60 22 334 Day 6 112 21 112 14 11 270 Day 7 126 16 132 34 18 326 Category 815 172 929 276 199 2391 Average Daily 116 25 133 39 28 342 % 34% 7% 39% 12% 8% 100% Average daily vehicular day time traffic for traffic originating from the Nimule side of the border was obtained as 342 vehicles. The total day-time through traffic for the survey week was 2391 vehicles. An analysis of the traffic composition summarized in figure 2-6 indicates that commercial as defined by this survey contribute the largest proportion of through traffic from Nimule, contributing 59% of the total traffic. Further analysis of this traffic category indicates that non containerized account for the largest proportion of commercial - 39% of total traffic, with the containerized ( tankers and ) contributing 20% of total traffic. Vehicle Traffic composition - Nimule Passenger vehicles 34% Buses 7% Commercial s 59% Noncontanerised 39% Containerised s 20% Figure 2-6: Vehicle Traffic Composition - Nimule 13 P a g e

Traffic volume The daily traffic variation presented in figure 2-7 below shows that the daily traffic volumes across the different survey days are within the same range, with a standard deviation of 47. The highest daily traffic volume obtained was on day 4 (405 vehicles) and the lowest on day 6 (270 vehicles), both of which are weekdays. 450 400 350 300 250 200 150 100 50 0 Day Day Day Day Day Day Day 1 2 3 4 5 6 7 tankers 35 43 39 31 22 11 18 Figure 2-7: Daily Traffic Variation Daily traffic volume variation - Nimule 37 38 41 52 60 14 34 Non-contanerised 137 142 130 131 145 112 132 Buses 16 22 20 44 33 21 16 Passenger vehicles 78 137 141 147 74 112 126 As with Outbound traffic at Elegu, significant traffic volumes across all the different vehicle categories were recorded at the Nimule side of the border. The average daily traffic volumes obtained are 116 passenger vehicles, 25 Buses, 133 non-containerized, 28 tankers and 39 trailer. The night time traffic component could not be accurately estimated since data collection at night was not possible as a result of stoppages by RSS security personnel. Counts were recorded for an average of 3 hours; up to 22:00 on the week day and up to 21:00 on the weekend day and results obtained for records up to 21:00 are presented in table 2-6: Table 2-6: Through traffic statistics Night Traffic originating from South Sudan Survey Day Passenger vehicles Buses Non-contanerised tankers Weekend day 0 0 9 3 1 13 Week day 10 1 39 11 5 66 Average Night traffic 5 1 24 7 3 40 14 P a g e

6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 1:00 2:00 3:00 4:00 5:00 Traffic Volume The average daily night time traffic for the two survey days was obtained as 40 vehicles. 61% of the night time traffic recorded is of non-containerized truck category. Night time traffic on the weekend day of the survey is about 19% of that recorded on the week day. Comparison of day time and night time volumes shows that traffic from South Sudan is also largely day time traffic, this comprising an estimated 88% of the total traffic. Hourly traffic volume trends across the survey week as summarized in figure 2-8 below also present a similar scenario. The figure further reiterates traffic flow behavior; almost all the traffic flows before 18:00 (day time close) with hardly any traffic recorded between the hours of 18:00 and 22:00. 300 250 200 150 100 50 0 Vehicular Traffic hourly variation Hour Figure 2-8: Hourly Traffic Variation There are several notable traffic peaks within the day in the hours of 6:00, 7:00, 9:00, 13:00, 15:00 and 16:00. The hourly total day-time volumes are at least 150 vehicles. Estimated total through traffic was obtained as 2668 vehicles translating to an estimated daily average of 382 Vehicles. The corresponding volumes for the different vehicle categories are shown in table 2-7 below. More than 1000 non-containerised were recorded during the survey week and a total of 1642 commercial were recorded Table 2-7: Through traffic statistics Night Traffic originating from South Sudan Parameter Noncontainerised Passenger Buses vehicles tankers day traffic 815 172 929 276 199 2391 Ave Estimated Night traffic 5 1 24 7 3 40 Estimated Night traffic 35 4 168 49 21 277 Estimated traffic 850 176 1097 325 220 2668 15 P a g e

2.2 Origin-Destination survey The second component of this survey involved an origin and destination analysis for selected commercial traffic that included all, coasters and coaches. Results of the analysis for this component are presented hereafter. 2.2.1 Traffic originating from Uganda The majority of commercial traffic into the Nimule- Elegu border originates from six principal towns Kampala, Mombasa, Nairobi, Eldoret, Tororo and Nakuru comprising both transits and local exports. Figure 2-9 aside illustrates this and it shows that almost all the commercial traffic at this border originates from Uganda and Kenya. Less than 2% of the total commercial traffic was recorded to originate from Rwanda (Kigali) and Tanzania (Isaka and Dar). The presentation of origin in table 2-8 below provides a further analysis of origin by vehicle category. This informs the nature of traffic and therefore the business from those origins. Kampala with the highest percentage (37%) is mainly trade in general merchandise as noted from the high composition of non-containerised, Mombasa (22%) Foreign imports, Nairobi (15%) industrial goods, Eldoret (8%), Nakuru (3%) and Kisumu (2%) s, and Tororo (7%) Cement. 99% of the traffic is destined to Juba. Clearly the Elegu-Nimule border is a key transit route for commercial traffic to Juba the capital of South Sudan and hence commercial hub for the country. 2.2.2 Traffic originating from South Sudan OtherKigali TZ Eastern Ug. 4% 1% 0% Eldoret 8% Kisumu Northern Ug. 7% 2% 1% Kampala 37% Principle Origins - Elegu Nakuru 3% Nairobi 15% Mombasa 22% Figure 2-9: Commercial Traffic composition - principal origins For traffic originating from South Sudan, the scenario is the reverse of traffic into South Sudan. As depicted in figure 2-10 aside and table 2.9 below most of the commercial traffic is returning empty, mainly from Juba (82%), after delivery of goods. The other significant portion of traffic originates from Nimule (15%) and comprises commuter taxis and local delivery. As with the principal origins for outbound traffic at Elegu, this traffic is destined to Kampala (36%), Nairobi(19%), Mombasa(13%) and Eldoret(5%). A significant portion (15%) of the traffic from Nimule Principle Vehicle Origins - Nimule Nimule 15% Wau 1% Other 2% Juba 82% 16 P a g e

terminated in Elegu. This comprised of commuter taxis and delivering construction materials within Elegu. Table 2-8: Origin & Destination summary Elegu outbound traffic Origin Destination Coach Coaster Light Medium Other Tanker Adjumani Juba 3 3 Arua Juba 2 2 4 Nimule 1 1 Atiak Magwi 1 1 Busia Juba 1 1 Dar Juba 6 6 Eldoret Juba 2 3 104 109 Elegu Juba 1 1 Nimule 2 2 Entebe Juba 1 1 Goli Juba 1 1 Gulu Juba 5 2 7 Hoima Juba 1 4 5 Iganga Juba 1 1 Isaka Juba 11 1 12 Isingiro Juba 7 7 Jinja Juba 1 1 2 KabaramaiJuba 2 2 Kahama Juba 1 1 Bor 2 2 Elegu 1 1 Juba 59 3 159 133 76 90 6 526 Kampala Nimule 1 1 Wau 1 1 Panyang 1 1 Rumbek 1 1 Kayunga Juba 1 1 Kiboga Juba 2 2 Kigali Juba 2 2 Kigumba Juba 1 1 2 Kiguru Juba 1 1 Kiryadong Juba 1 1 Kisumu Juba 1 23 24 Lira Juba 1 14 2 17 Lusaka Juba 1 1 Luwero Juba 1 1 Malaba Juba 1 3 4 Masaka Juba 2 2 Masindi Juba 1 1 Mbale Juba 9 9 Mbarara Juba 8 1 9 Aweil 1 1 Mombasa Juba 9 6 47 242 16 320 Nairobi Juba 4 17 15 80 75 20 211 Panyang 1 1 Nakuru Juba 1 38 39 Paidha Juba 1 3 4 soroti Juba 22 22 Tororo Juba 1 3 49 5 58 17 P a g e

Table 2.9: Origin & Destination summary Nimule outbound traffic Origin Coach coaster Light Medium Other Grand Tanker Aweil 1 1 Bentiu 1 1 Bor 1 5 1 7 Juba 83 1 176 269 128 241 278 1176 KAPOETA 1 1 Malakia 1 1 MELEWA 1 1 Nimule 2 1 210 5 2 1 221 Panyang 1 1 Pibor 1 1 Rumbek 1 1 Torit 2 2 1 5 Wau 1 5 4 4 1 5 20 YAMBIO 1 1 YEI 1 1 2 1 5 Category 86 1 185 486 150 247 288 1443 2.3 Queue time As noted in section 1.2, queue time was taken as the difference between the time a truck arrives at the border and the time it enters the customs clearing area. 2.3.1 Elegu-Uganda For traffic originating from the Uganda side of Nimule-Elegu border, queue time was computed as [T 3 - T 1 ] with parameters defined as in section 1.2.1 above. Table 2-10 below shows the average queue times obtained for traffic recorded during the survey week. Table 2-10: Average Queue Times for Traffic originating from Uganda Average Queue time by truck category - Elegu frequency distribution by category Light Medium Other Tanker Ave. Daily Light Other Tanker Grand Survey Day Medium Day 1 7:32 13:18 16:57 13:48 10:23 12:54 29 14 34 48 12 137 Day 2 8:18 15:55 17:45 17:08 10:46 14:23 39 18 38 55 19 169 Day 3 8:09 14:40 16:18 17:03 13:46 13:57 30 18 15 42 24 129 Day 4 7:16 12:22 19:11 21:36 14:30 15:57 29 25 32 55 50 191 Day 5 6:09 4:07 11:43 10:29 6:10 8:26 31 15 33 47 30 156 Day 6 8:59 21:52 20:40 23:06 16:52 18:31 24 10 20 38 13 105 Day 7 2:03 10:59 4:58 3:36 16 3 2 21 Daily Average 7:15 13:12 16:55 17:02 12:05 13:38 198 103 172 287 148 908 18 P a g e

6:00 7:00 8:00 9:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 0:00 1:00 2:00 4:00 5:00 Queue time (Hr:Min) The average daily queue time for commercial truck traffic was obtained as 13 hours 38 minutes. The queues are contributed by the high traffic obtained at this border as indicated in section 1.2.1. The average hourly commercial traffic is about 16 vehicles with peaks at particular hours like early morning and early evening, which contributes to the high queue times. The limited manoeuver space on the road (particularly that leading to the CCZ and to the bridge), limited parking space in the RSS customs yard, and early arrivals before border operations commence also contribute to the high queue times. Queue time variation across the different truck categories is quite significant with the heavier goods vehicles queuing longer. It is noted that light have the shortest queue time of 7 hours 15 minutes as compared to the other categories. This may be because of the ability to easily maneuver on the narrow road. Figure 2-11 below shows that the earlier a truck arrives the shorter its queue time. s that arrive in the early morning hours have the shortest queue times. The queue times increase as operational hours progress peaking at 18:00 hours. Generally, lower queue times were noted for traffic arriving outside of the border operational hours. 19:12 16:48 Average Hourly Queue Time variation 14:24 12:00 9:36 7:12 4:48 2:24 0:00 Arrival hour Figure 2-11: Variation of Queue Time by Arrival Hour 2.3.2 Nimule For traffic originating from Nimule, queue time was computed as and [T 4 -T 5 ], all parameters as previously defined. Table 2-11 below shows the queue average times obtained for traffic recorded during the survey week. 19 P a g e

Queue Time [Hr:Min] Table 2-11: Average Queue Times for Traffic originating from Nimule Average Queue time by truck category - Nimule frequency distribution by category Survey Day Light Medium Other Tanker Ave. Daily Light Medium Other Tanker Grand Day 1 5:46 0:15 0:12 0:28 0:16 1:39 39 20 33 39 27 158 Day 2 3:30 0:28 0:25 0:18 0:27 1:11 31 19 20 22 32 124 Day 3 0:14 0:08 0:05 0:11 0:08 0:10 47 21 25 39 35 168 Day 4 0:56 2:07 2:00 2:21 1:48 1:45 68 17 52 55 31 223 Day 5 0:05 0:03 0:07 0:08 0:05 0:06 59 18 24 43 18 162 Day 6 0:05 0:04 0:05 0:41 0:01 0:07 71 5 13 8 7 104 Day 7 0:14 0:09 0:13 0:07 0:18 0:12 73 15 29 43 17 177 Daily Ave. 1:07 0:29 0:40 0:43 0:32 0:48 388 115 196 249 167 1116 Results from the survey indicate an average daily queue time of forty eight minutes. s from Nimule queue have a much shorter time, because most of them are returning empty so do not require elaborate procedures to scrutinize the documentation and/or a lot of time consuming preparation to clear with border agencies. Queue times could be shorter if Average Hourly Queue time variation - Nimule the border operated 24 hours 16:48 and therefore that arrive 14:24 in the late evening did not have 12:00 to queue while waiting for the 9:36 border to open in the morning. 7:12 4:48 2:24 0:00 Arrival hour Figure 2-11: Hourly Queue time variation - Nimule This is illustrated in figure 2-12 aside that shows the queue time variation with truck arrival hour. A steep rise in queue time is noted from 19:00 hours when the border 2.4 Processing Time Customs processing time was obtained as the dwell time for within the customs clearing area; this was taken as the difference in time from when a truck enters the customs clearing area in one country to the time it exits in the next country after clearing with all border formalities. 2.4.1 Elegu - Uganda For traffic originating from Uganda, was calculated as [T 2 - T 4 ] all parameters as previously defined. Results of data analysis are summarized in table 2-12 below: 20 P a g e

Table 2-12: Average Customs processing Times for Traffic originating from Uganda Average CP time by truck category - Elegu frequency distribution by category Light Other Tanker Ave. Daily Light Other Tanker Grand Survey Day Mediu Medium m Day 1 26:10 52:45 50:14 81:05 71:43 61:37 14 24 26 49 5 118 Day 2 37:08 29:33 53:52 73:54 52:24 53:27 27 6 26 29 19 107 Day 3 19:56 38:28 62:46 68:16 49:38 51:47 22 22 31 41 11 127 Day 4 20:38 49:04 34:43 62:54 48:16 41:27 24 17 18 15 25 99 Day 5 18:19 26:53 45:41 38:01 45:30 32:00 20 21 9 7 16 73 Day 6 16:22 24:18 4:47 17:03 15:46 16 5 5 2 28 Day 7 6:46 7:34 2:08 1:10 3:02 5:00 9 4 5 1 4 23 Daily Average 22:40 38:47 47:42 71:19 47:20 46:12 132 99 120 142 82 575 Average customs processing time for the survey week was obtained as 46 hours 12 minutes. The highest daily average processing time of 61 hours 37 minutes was obtained on day one and the lowest of 5 hours on day seven customs processing times gradually dropping as the survey week progressed. The higher processing times at the beginning of the survey week can be attributed to the backlog that had been created by truck drivers strike on the two days prior to the start of the survey when were not crossing from Uganda into South Sudan. The times dropped as the situation progressively normalized. Within truck categories, light generally have the lowest processing times and trailer the highest. There is no obvious trend in the customs processing times obtained pointing to the possibility that several different factors influence the clearing process. 2.4.2 Nimule South Sudan Results of the analysis for from South Sudan are summarized in table 2-13 below. Table 2-13: Average Customs processing Times for Traffic originating from South Sudan Average Customs processing time by truck category - Nimule frequency distribution by category Survey Day Light Medium Other Tanker Ave. Daily Light Medium Other Tanker Grand Day 1 1:26 1:26 4:32 6:05 1:37 3:12 29 20 24 34 27 134 Day 2 1:54 1:18 8:16 2:32 5:35 3:54 23 14 17 28 27 109 Day 3 0:34 2:05 3:00 5:52 1:10 2:46 29 20 29 41 36 155 Day 4 0:39 2:06 5:08 2:13 1:07 2:18 38 17 36 50 27 168 Day 5 1:00 1:11 5:50 3:06 1:44 2:47 40 22 38 43 23 166 Day 6 13:44 1:36 2:11 1:45 1:33 15:23 23 6 14 11 7 61 Day 7 0:34 1:17 1:50 1:53 1:00 1:18 41 19 33 33 20 146 Daily Ave. 4:45 1:34 4:22 3:31 2:01 3:28 223 118 191 240 167 939 StdDev 9:07 2:36 9:51 6:24 7:09 4:31 21 P a g e

The average customs processing time obtained across the survey week was three hours twenty eight minutes. The dwell time within the CCZ is shorter for Traffic outbound on the Nimule side because most of the commercial traffic is empty returning after delivery of goods. Average processing times across the different truck categories are within the same range with a standard deviation of four hours thirty one minutes [04:31min] on the average daily customs processing time. There is a wide variation particularly for the light category and in the other category. This is particularly noted on day 6 under the light category with an average CPT of 13 hours 44 Minutes. Data in the sections above indicates that traffic from the Uganda side of the border outbound to South Sudan, has a higher processing time and thus spends longer in the customs clearing zone. This is because traffic outbound from this side of the border is laden with goods, which implies customs clearing and verification processes to ensure the requisite taxes and procedures are adhered to. In addition, these processes are manual with very limited / almost no data sharing between the customs of both countries, making the process even longer. In comparison, traffic outbound on the Nimule side is mainly empty returning from delivering goods and is subject to fewer procedures mainly recording of truck details (like registrations and origin/destination) and payment of road user levies. 22 P a g e

3 CONCLUSION This survey sought to obtain baseline traffic and time statistics for the Nimule-Elegu border to South Sudan and Uganda. A summary of the key baseline statistics required as defined in the TOR is presented in table 3-1 below. Traffic on both sides of the border is largely day time traffic with similar figures obtained for traffic volumes. The total estimated weekly through traffic is 2159 for outbound traffic at Elegu and 2668 for outbound traffic at Nimule. This corresponds to an average daily traffic of over 300 vehicles on either side. The higher traffic from Nimule is attributable to traffic that terminates in Elegu. Statistics indicate a very high percentage of non-containerised traffic on either side of the border, however with a significant proportion of Containerised. Table 3-1: summary baseline statistics Elegu Outbound traffic Nimule Outbound traffic Traffic volume Parameter Passenger vehicles Buses Noncontanerised tankers Passenger vehicles Buses Noncontanerised tankers day time traffic 337 123 610 325 162 1557 815 172 929 276 199 2391 Ave daily Day time traffic 48 18 87 46 23 222 116 25 133 39 28 342 Ave daily Night time traffic 11 8 35 16 17 86 5 1 24 7 3 40 Estimated Night traffic 77 53 245 112 116 602 35 4 168 49 21 277 Estimated week traffic 414 176 855 437 278 2159 850 176 1097 325 220 2668 Ave. daily traffic 59 25 122 62 40 308 121 25 157 46 31 381 Dwell time Parameter Light Medium Light Medium Ave. Other Ave. Daily Other Tanker Tanker Daily Ave Daily Queue time 7:15 13:12 16:55 17:02 12:05 13:38 1:07 0:29 0:40 0:43 0:32 0:48 Ave Daily CPT 22:40 14:47 23:42 23:19 23:20 22:12 4:45 1:34 4:22 3:31 2:01 3:28 waiting time 29:56 52:00 64:37 88:21 59:25 59:50 5:52 2:04 5:02 4:14 2:34 4:16 Principal commercial vehicle origin Principal commercial vehicle Destination Kampala, Nairobi, Eldoret, Mombasa, Nakuru Juba Juba, Nimule Kampala, Nairobi, Eldoret, Mombasa The time statistics obtained indicate that queue longer at Elegu and customs processing time for outbound traffic is also higher. The average total dwell time for outbound traffic was obtained as 59 hours 50 minutes; this is a total waiting time of over four days as compared to Nimule outbound commercial traffic that on average spends 4 hours in at the border. This can be attributed to several factors related to customs clearance since truck traffic from Uganda is mainly laden as compared to truck traffic from the South Sudan side that is mainly empty requiring less procedures and checks. In addition, there was a strike for two days prior to the start of the survey which may have contributed to the high CPT particularly on days 1 and 2 due to traffic buildup. The principal origin and destination towns for commercial traffic are key commercial towns in Uganda, Kenya and South Sudan. Some traffic was also recorded as originating from Dar, Isaka and Kigali. This indicates that Nimule-Elegu border is an important transit route on the Northern and Central corridor routes for commercial vehicle traffic to Juba. 23 P a g e

ANNEX I DATA COLLECTION FORMS FORM CATEGORY 1 Border station: NIMULE/ELEGU Date: Shift: (Day, Evening, Night) Weather ( Rainy/ sunny/clear): TRUCKS FROM UGANDA Hour starting Arrival time Number plate (Reg #) truck (1x40, 2x20, or 1x20) tanker (tick) Light truck (tick) Medium truck (tick) Other - heavy goods (tick) FORM CATEGORY 2 Border station: NIMULE/ELEGU Shift (Day, Eve, Night) VEHICLES FROM UGANDA Date: Weather ( Rainy/ sunny/clear): Hour starting Entry time to Customs clearing area Number plate (Reg #) truck Other - Light Medium (1x40, 2x20, heavy tanker truck truck or 1x20) goods coach - 60 pax Coaster- 30 pax Origin Destination 24 P a g e

FORM CATEGORY 3 Border station: NIMULE/ELEGU Date: Shift: (Day, Evening, Night) Weather ( Rainy/ sunny/clear): TRUCKS FROM NIMULE Hour starting Exit time from Customs clearing area Number plate (Reg #) truck (1x40, 2x20, or 1x20) tanker (tick) Light truck (tick) Medium truck (tick) Other - heavy goods (tick) 25 P a g e