# Optimal Policies for Aggregate Recycling from Decommissioned Forest Roads

Matthew Thompson Æ John Sessions

Received: 28 November 2006 / Accepted: 20 April 2008 / Published online: 15 May 2008
 Springer Science+Business Media, LLC 2008

Abstract To mitigate the adverse environmental impact of forest roads, especially degradation of endangered salmonidhabitat, many public and private land managers in the western United States are actively decommissioning roads wherepractical and affordable. Road decommissioning is associated with reduced long-term environmental impact. When decommissioning a road, it may be possible to recover some aggregate (crushed rock) from the road surface. Aggregate is used on many low volume forest roads to reduce wheel stresses transferred to the subgrade, reduce erosion, reduce maintenance costs, and improve driver comfort. Previous studies have demonstrated the potential for aggregate to be recovered and used elsewhere on the road network, at a reduced cost compared to purchasing aggregate from a quarry. This article investigates the potential for aggregate recycling to provide an economic incentive to decommissionadditional roads by reducing transport distance and aggregate procurement costs for other actively used roads. Decommissioning additional roads may, in turn, result in improved aquatic habitat. We present real-world examples of aggregate recycling and discuss the advantages of doing so. Further, we present mixed integer formulations todetermine optimal levels of aggregate recycling under economic and environmental objectives. Tested on an exampleroad network, incorporation of aggregate recycling demonstrates substantial cost-savings relative to a baseline scenariowithout recycling, increasing the likelihood of road decommissioning and reduced habitat degradation. We find that aggregate recycling can result in up to 24% in cost savings (economic objective) and up to 890% in additional length of roads decommissioned (environmental objective).

Keywords Aggregate recycling

 Transportation planning

 Forest roads

 Aquatic habitat

 Road decommissioning

 Watershed restoration

 Mixed integer programming

 Optimization

Introduction

Public and private land managers in the western United States are increasingly removing forest roads to mitigatenegative environmental impacts associated with the presence of roads on the landscape. The USDA Forest Service’s Road Management Policy, for instance, states the agency’s intent to ‘‘reverse adverse ecological impacts associated with roads’’ by, in part, ‘‘decommissioning unnecessary and unclassified roads.’’ (USDA 2001 ) Other federal agencieshave also sought to decommission roads for ecological reasons, such as the USDI National Park Service within Redwood National Park in 1978 (Madej 2001 ). Some privateland managers are seeking to remove roads to restore ecosystems, such as the Nature Conservancy’s Ellsworth Creek project (Tom Kollasch, project manager, February 2006, personal communication). Though roads provide many benefits, such as access for timber extraction, fire prevention, recreation and research, roads can also adversely influence hydrology, geomorphology, and ecosystem processes (Switalski and others 2004 ). Road decommissioning has been identified as a pro-active mechanism for preventing future habitat degradation and increasing the likelihood of endangered salmonid survival (Harr and Nichols 1993 ).
Forest roads are associated with accelerated erosion and can be a major source of sediment delivery to streams, which M. Thompson ( & )

 J. Sessions Department of Forest Engineering, Oregon State University, 204 Peavy Hall, Corvallis, OR 97331, USA e-mail: Matthew.Thompson@oregonstate.edu



# 123 Environmental Management (2008) 42:297–309

DOI 10.1007/s00267-008-9136-0can degrade aquatic ecosystems (Jones and others 2000 ; Lugo and Gucinksi 2000 ; Forman and Alexander 1998 ). Chronic erosion contributes fine sediment and is generated by surface erosion processes along the road prism (Reid and
Dunne 1984 ). Episodic erosion occurs in the form of masswasting and fluvial erosion due to culvert failures and is often triggered by intense rain events (Reid and Dunne 1984 ).
Roads have been found to contribute as much as 40% of the total erosion associated with forest management activities (Gucinski and others 2001 ) and are responsible for themajority of episodic erosion events, such as hillslope failures, in steep forested areas subject to logging (Furniss and
others 1991 ). Elevated levels of in-stream sediment can negatively affect salmonids through mortality, reduced growth rates, disruption of egg and larvae development, and reduction in available food (Newcombe and MacDonald
1991 ; Hicks and others 1991 ). Degradation of aquatic habitat is of special concern in the western United States where endangered salmonid species spawn and rear in watersheds containing potentially erosive forest roads.Appropriate road management can mitigate the environmental impact of the road system by limiting chronic erosion and reducing the risk associated with large-scale episodic events (Weaver and Hagans 1999 ). Roads no longer required for transportation can be closed and/or decommissioned. High maintenance needs or high levels of environmental damage are also reasons to decommission a road. Closing a road frequently consists of barricading or gating the road to prevent unauthorized use, particularly during wet seasons, outsloping the surface and installing rolling dips and/orwaterbars, and may involve removing some high-risk culverts. A closed road can be re-opened for future use or later decommissioned, and generally requires only periodic inspection. Decommissioning a road may involve removingculverts under significant fills, ripping the roadbed, recontouring hillslopes, and may include planting or seeding the road surface. A decommissioned road is not passable andrequires no future maintenance. A common goal of decommissioning is to restore the natural hydrologic processes and prevent future sedimentation; a decommissioned road has lower longer-term environmental impacts than a closed road due to significantly reduced risk of chronic and episodic erosion (Switalski and others 2004 ; Kolka and Smidt 2004 ; Madej 2001 ; Trombulak and Frissell 2000 ; Weaver and Hagans 1999 ; Harr and Nichols 1993 ). Unfortunately decommissioning costs can be high and that may prevent desirable projects from being undertaken. This is especially true with federal agencies, such as theUSDA Forest Service, which has a minimal road maintenance budget due in large part to substantial reductions intheir timber sale program. Forest road networks under federal ownership are often characterized by substandard conditions. As of 2002, less than twenty percent of national forest roads were maintained to planned safety and environmental standards (USDA 2002 ). A recent report from the
Pinchot Institute for Conservation found that four of five casestudy national forests—Allegheny (PA), ChequamegonNicolet (WI), Fremont-Winema (OR), and Mt. Hood (OR)— had a backlog of road maintenance and decommission needs, stating that there were ‘‘...some or, in other cases, numerous inadequately maintained roads, many of which are no longer needed for land management.’’ (Sample and others 2007 , p 68) The report recommended that national forests completeroads analyses to determine essential transportation networks and to identify surplus roads that can be decommissioned. Efficient planning and implementation is therefore crucial to achieve restoration objectives in this
resource-constrained environment.Road decommissioning decisions are complex and influenced by a variety of factors, such as road location, sediment delivery risk, and available resources. Often, only a few ‘‘problem’’ roads produce the majority of the sediment, and it therefore may be efficient to direct efforts towards those roads first (Luce and Black 1999). Weaver and Hagans ( 1999)contend that it is rarely cost-effective to undertake a decommission project without first evaluating its relative importance to overall watershed condition. Similarly, Luce and others (2001 ) state that road removal efforts must be prioritized, and argue that management criteria should include economic and social concerns. Lugo and Gucinski (2000) agree that decommissioning decisions should not be made based upon ecological criteria alone, and caution that in some cases, the environmental disruption from decommissioning may be less desirable than leaving the road to reach some level of stability. Anderson and others (2006) point out that decommissioning decisions involve weighing the relative risks of road failure, limited access for fire suppression, and limited access for future market opportunities. Managers are thus faced with the difficult task to develop efficient road management strategies that satisfy economic, ecological and social goals, subject to legal and practical realities. In such planning environments, decision aids can and have been used to facilitate decision-making. For instance, federal land management agencies in the Pacific Northwest used the Ecosystem Management Decision Support (EMDS http://www.institute.redlands.edu/emds/) system to characterize the ecological condition and help prioritize restoration of watersheds and aquatic ecosystems on public land (Reeves and others 2006 ). To date, monitoring results indicate that watershed condition is being improved, in part, through road removal (Reeves and others 2006 ). Watersheds with the greatest assessed improvement had relatively extensive road removal programs (Gallo and
others 2005 ), and a majority of the funding to date has been allocated for road-related treatments (Heller 2002 ). Girvetz and Shilling ( 2003 ) used EMDS to analyze the Tahoe 298 Environmental Management (2008) 42:297–309



# 123National Forest road system for potential environmental impacts according to the USDA Forest Service’s ‘‘Roads Analysis’’ guidance document (USDA 1999 ). Roads with greater potential to cause environmental damage were assigned higher scores and these scores were used to negatively weight roads for a least-cost network analysis. The authors found that over 50% of the total road length, and 40% of aggregate road length, could be removed while ensuring access to critical points in the road network.
Relevant characteristics of the road network included in the analysis were the number of stream crossings, distance from the road to a stream, position of the road on a slope, slope steepness, soil erodibility, and road surface type. In other applications, researchers have based roadremoval decisions on economic or sediment-related objectives. Anderson and others ( 2006 ) used dynamicprogramming to determine optimal road class and deactivation strategies, but did not include environmental considerations in the formulation. Thompson and Tomberlin ( 2005 ) applied stochastic dynamic programming to minimize the cost of erosion control on an unused logging road in the Caspar Creek watershed in northern California (also see
Tomberlin and others 2002 ), where the decisions included whether to maintain, upgrade, or decommission the road. Allison and others ( 2004 ) applied a decision analysis framework to generate a ranking of the expected benefits of proposed deactivation strategies for forest roads in steep terrain, where benefits were expressed in terms of avoided damages from road-related slope failures. Bettinger and others (1998) used a tabu search metaheuristic procedure toschedule harvest and road activities with sediment production constraints to achieve aquatic habitat goals. Madej and others ( 2006 ) and Eschenbach and others ( 2005 ) employed dynamic programming and a genetic algorithm to maximize the sediment saved from entering stream channels as a result of applying various road removal treatments in the Lost Man
Creek Basin in Redwood National Park.

Aggregate Recovery and Reuse

Aggregate (crushed rock) is often placed on low volume forestry roads to reduce wheel load stresses to the subgrade,reduce chronic erosion from the roadbed, reduce maintenance costs, and improve driver comfort. Aggregate surfaced roads generally produce significantly less sediment thannative-surfaced (dirt) roads, and enable operations to continue during the wet season in areas with high precipitation, such as western Oregon and Washington. Over time, aggregate degrades or is lost from the roadway and no longer functions as intended, so that aggregate must be reapplied, with associated maintenance costs. Demand for aggregate also stems from road upgrading and construction. Although aggregate is typically procured from a local pit or quarry, existing forest roads can also be sources of aggregate. It is often possible to recover aggregate from the road surface during decommissioning. Depending on quality and intended use, the recovered aggregate can be used interchangeably with new rock, or screened, or mixed with fresh aggregate. Sessions and others ( 2006 ) discuss rock recycling for timber production scenarios where mixing with fresh aggregate is necessary. The rock may also be washed to remove silt, clay, or leftover vegetative matter. Unprocessed, screened recycled rock can be used for a base layer on construction projects or as a surface layer for roads reserved for timber haul. If the recovered rock is of sufficient quality it could be processed (crushed) for use as a surface layer on roads serving public traffic. Quarries are commonly the source for higher quality aggregate with smaller particle sizes for use as a surface layer, whereas local borrow pits, if available, are more generally used to obtain aggregate for the base layer. The presence of geotextiles can increase the percentage of aggregate recovery. Geotextiles are used to prevent contamination of the base layer by the subgrade material,but they can also increase recovery rates. Foreword-looking managers seeking to keep the option to recover aggregate in the future may opt to construct new roads using geotextiles. Opportunities for recovery from forest roads are site specific. On private ownerships where road construction and reconstruction is common, there is likely high potential for recovery and reuse of aggregate material, especially ifmanagers opt to use geotextiles. On public land, opportunities may be more limited. In some wet areas, vegetation can grow to cover the road template, effectively preventing recovery, and in some dry locations aggregate placed for erosion control is applied thinly and provides a minimalamount to recover (Tom Erkert, Group Leader, Transportation Planning, Operations and Maintenance, USFS PacificNorthwest Region, November 2007, personal communication). Limited use and maintenance, however, keep many suitable roads free of vegetation. For example, many forest
roads in the Pacific Northwest considered for decommissioning generally have 15–30 cm of aggregate depth available for recovery (Mark Truebe, Assistant Forest Engineer, Willamette National Forest, November 2007, personal communication). The quality of aggregate available to be recovered is another important variable. Foltz and Truebe ( 2003 ) tested a variety of aggregates available from local sources in the Pacific Northwest, including alluvial surfacing material
recovered from forest roads in the Willamette National Forest in Oregon. The recycled surfacing was consistentwith fresh aggregates in terms of runoff volume and sediment production from simulated rainfall, but produced Environmental Management (2008) 42:297–309 299



# 123above average rut depths in response to simulated passes from a logging truck. Overall, the recycled aggregate was within the range of variability of the eighteen aggregates tested. Notably, the recovered aggregate had been ‘‘in place’’ for at least 20 years, suggesting that aggregate from legacy forest roads can still provide utility if recovered. This is significant as on many national forests roads now being decommissioned were constructed many years ago. Recovered aggregate can be delivered to other roads forconcurrent maintenance or construction projects, with associated recovery and delivery costs. Alternatively, aggregate required for maintenance or construction can be obtained from either local pits or quarries with associated procurement and delivery costs. Re-use of the recovered aggregate within the forest road network may significantly reduce rock transport distance, especially when quarries are far away. Delivery costs (vehicle costs and associated road wear costs associated with delivery of aggregate) vary depending upon vehicle type, speed, and surface type (paved or aggregate roads.) As we willdemonstrate, there are opportunities for significant cost savings even for small-scale projects, and these savings can be expected to increase as fuel costs rise. The option to recycle aggregate therefore presents an opportunity to offset decommissioning costs, wherein the recovered aggregate can provide a lower cost alternativefor road construction or maintenance projects. This suggests federal land management agencies, and others, could perform more road management projects at a particular budget, in theory decommissioning additional roads and improving aquatic habitat.

Applications of Aggregate Recycling

Numerous aggregate recycling projects have been implemented on publicly and privately owned lands throughout the western United States. On the Umpqua National Forest in Oregon, for example, 2300 m 3 were recovered and stockpiled for re-use from a road decommissioned in 2003 at a cost of $5.35/m3 . Four years later 230 m 3 were recovered from a short spur road and stockpiled at a cost of $6.90/m 3 , with the cost increase largely attributable to increased fuel costs (Michael Karr, Work Supervisor, Road Maintenance and Project Team, Umpqua National Forest, November 2007, personal communication). The Umpqua National Forest is actively pursuing future opportunities to salvage rock from decommissioning projects in the future. Industrial owners, such as Plum Creek, the largest forestland owner in the United States, while not decommissioning many roads, are experimenting with aggregate recovery because of the high cost of transporting quarry rock long distances. Sessions and others ( 2006 ) described two recovery operations by the Oregon Department of Forestry. After the Vesper No. 2 Timber Sale in 1989, aggregate was recovered from spur roads that had been constructed using geotextiles. A grader made consecutive passes gradually lifting the aggregate from the fabric, and windrowed the material to be picked up by a front-end loader. The rock was then loaded into dump trucks and transported for use as a base layer on a collector road being constructednearby. In 2003, the Cow Creek mainline road was relocated from a stream to a ridge top, and aggregate recovered during the decommissioning process was used as a base layer for the new mainline. In that case, a hydraulic excavator with a ditching bucket lifted the rock from the road surface and loaded dump trucks and off-road trucks. In both cases, estimates for recovery reached as high as 90%, and minimal processing was required. We now describe in greater detail an aggregate recycling application by the Washington Department of Natural Resources (WADNR). In particular we examine the road plan for the Highway Alder Timber Sale, which occurred in the winter of 2007, using data provided by Jennie Cornell, Straits District Engineer. Our intent is to illustrate the cost-savings potential of aggregate recovery
and reuse. The WADNR road plan included reclamation of rock from four decommissioned roads to serve as base layer for maintenance and construction projects. Specifically, theproject called for ‘‘medium abandonment,’’ which consisted of: (1) reclaiming base layer and surfacing to within 3 cm of the geotextile fabric and endhauling to a stockpile; (2) constructing non-drivable water bars at a maximum spacing of 30 m; (3) removing all culverts; (4) ripping road and landing surfaces to a minimum depth of 46 cm; (5) seeding and mulching; and (6) constructing tank traps. All abandoned roads had been constructed using geotextiles, and new spurs were also constructed using geotextiles, presumably preventing contamination and improving recovery rates. Hereafter, for consistency, we refer to abandonment as decommissioning.
Table 1 presents the unit costs for procuring aggregate from the various sources (abandoned/decommissioned

Table 1 Unit costs ($/m 3 ) for aggregate from decommissioned roads, local borrow pit, and quarry; WADNR example

Operation/source Decommissioned roads Pit Quarry

Dig and load $0.00 $0.57 $0.00
Purchase $0.00 $0.00 $7.26
Haul $1.43 $7.14 $8.46 Spread $0.46 $0.46 $0.46 Compact $0.52 $0.52 $0.52
Reclamation $0.57 $0.00 $0.00
Totals $2.99 $8.69 $16.70 300 Environmental Management (2008) 42:297–309



# 123roads, pit, and quarry). Had spur roads not been slated for decommissioning or had WADNR not pursued recycling, base rock could alternatively have been procured from a borrow pit located 18 km away. Aggregate for surfacing was purchased from a commercial quarry located 41 km away. Recovered aggregate on the other hand was brought to a nearby stockpile ( \ 2 km), greatly reducing transport
cost. Table 1 demonstrates the potential substantial costsavings from reuse of aggregate recovered from decommissioned roads.
Table 2 describes the maintenance and construction projects, their respective needs for aggregate, and total aggregate-related costs. The table also presents costs for a contrasting hypothetical scenario wherein no recycling is permitted and aggregate must be procured from the local pit. In total, using recovered aggregate was $19,232 less than the hypothetical alternative of using the local borrowpit. The total amount of aggregate recovered from the decommissioned roads was 1988 m 3 , which supplied all the necessary aggregate. We exclude surfacing needs as the suitability of the recovered aggregate for processing is unknown, and because in this case surfacing was procured solely from the quarry. If fuel costs continue to rise, recycling aggregate, and possibly processing for use as surfacing where appropriate, will become increasingly attractive options. Our understanding is that most projects have been planned on a case-by-case basis. We propose that more comprehensive analyses might yield opportunities for increased efficiency, resulting in improved transportation systems with less negative environmental impacts. In the next section we present tactical planning frameworks to generate optimal policies for aggregate recovery and

reuse. Optimal Aggregate Management Policies

In practice, managers often make decisions regarding road removal treatments according to some set of decision rules. Some may, as a policy, seek to minimize total costs by treating as few roads as practicable. Other managers may seek to treat the greatest length of road for a given budget, a common policy among public managers in the western United States (Madej and others 2006 ). In this article we present two mixed integer formulations representative of general policies a transportation manager may follow: to
minimize costs and maximize environmental benefits. Here we consider two road treatments, (1) closure and(2) decommissioning, with the expectation that decommissioning entails significantly greater environmental benefits. We assume an experienced professional has identified which road segments require removal, and that
the decision variable is whether to close or decommission a particular road segment. If a road is decommissioned, the aggregate can be recovered and used for other scheduled maintenance and construction projects.Previous mathematical formulations regarding aggregate management include Kirby and Lowe ( 1975 ) and Sessions and others ( 2006 ). Kirby and Lowe ( 1975 ) presented a model to schedule the opening/closing of pits and assign roads to pits in order to minimize the discounted sum of manufacturing, transport, and fixed costs. Their model is an integer formulation with multiple pits, roads, and planning periods. Sessions and others ( 2006 ) presented a tactical planning model that maximizes net present value of timber harvest less crushed aggregate costs, where the
decision variables are when to harvest a unit and from where to procure aggregate for spur roads, which can come from either a pit or previously used spur roads. Our models

Table 2 Total aggregate costs, with and without aggregate recycling, for scheduled maintenance and construction projects in the road plan for the WADNR Highway Alder Timber Sale

Project type Road Aggregate demanded (m3 ) Total aggregate cost ($)

Decommissioned roads Local pit (hypothetical)

Maintenance PA-S-2500 23 $117 $341
PA-S-2550 31 $156 $455

Construction 1 + 17 spur 83 $426 $1239

1 + 40 spur 96 $492 $1433

1 + 44 spur 98 $500 $1455

1 + 60 spur 107 $547 $1592

1 + 70 spur 83 $574 $1672

5 + 00 spur 289 $1476 $4298

12 + 35 spur 708 $3616 $10,529

Reconstruction 7 + 36 spur 422 $2156 $6277
Totals 1969 $10,059 $29,291 Environmental Management (2008) 42:297–309 301



# 123build on previous work, broadening the context to watershed restoration with environmental objectives, and including road removal treatment as a decision variable.

Model I: Minimize Costs

The first model seeks to minimize the discounted costs of
the sum of treatment costs for roads that have been identified for removal, plus the cost of aggregate procurement and delivery costs for roads that are to be maintained or constructed on the road network (Equation 1 ).
Minimize: X

i X

j X

t p t c ijtX ijt þ X

s X

j X

t p t g sjt Y sjt

þ X

i X

k X

t p t h iktZ ikt ð 1 Þ

Subject to: X

i X ijt þ X

s Y sjt 1⁄4 D jt 8 j
; t ð 2 Þ

X

j X ijt X

k rf iktA itZ ikt 8 i
; t ð 3 Þ

X

k Z ikt 1⁄4 1 8 i
; t ð 4 Þ

Z

ikt 2 0

; 1 f g 8 i
; k

; t ð 5 Þ

where p t = present net value factor for period t, dimensionless; X ijt = aggregate recovered from road i and
delivered to road j in period t, m3 ; Y sjt = aggregate taken
from source s (pit or quarry) and delivered to road j in period t, m 3 ; Z ikt = 1 if road i is removed at treatment level
k in period t, 0 otherwise; c ijt = cost to recover aggregate from road i and deliver to road j in period t, $/ m 3 ;

g sjt = cost to procure aggregate from source s and deliver
to road j in period t, $/ m3 ; h ikt = cost to remove road i at treatment level k in period t, $; A it = aggregate available for recovery from road i in period t, m 3 ; D jt = aggregate required for road j in period t, m 3 ; and rf ikt = aggregate recovery factor for road i removed at treatment level k in period t, m3/m 3 . Implicit in our formulation is that the subscript i is indexed over only the set of roads slated for removal, rather than all road segments. Likewise, j is indexed over the set of all roads requiring aggregate for construction or maintenance, k the set of possible treatments, s the set of possible sources, and t the periods in the planning horizon. Equation 2 specifies that demand for aggregate be met from decommissioned roads and/or quarries. Equation 3 specifies the upper limit on aggregate able to be recovered in a given period, conditional on the level of treatment (if any) in that period; in our framework, the recovery factor is set to zero for closure. Equation 4 ensures that all roads scheduled for removal must be assigned to either closure or decommissioning. Equation 5 declares that the removal treatment variables are binary (0/1). Intuitively, the best answer would seem to be assigning all appropriate road segments to closure, which minimizes costs, but may not provide as large an environmental benefit. However, recycling aggregate may be the superior option, given reduced transport costs and avoidance of aggregate purchase costs. As procurement and delivery costs for quarry aggregate rise, this model will likely schedule additional roads to be decommissioned. Thus, although not specifically represented in the objective function, the economics of the situation may induce a manager to decommission more roads, thereby providing ecological benefits over the alternative of merely closing a road to remove it from the transportation network. Model I is readily extendible to situations involving road construction and the decision of whether to use geotextiles.Constructing temporary roads using geotextiles may substantially improve aggregate recovery rates, although incurring a higher upfront cost (Sessions and others 2006 ). The example applications we presented demonstrated that some landowners, in this case state agencies, have and continue to utilize geotextiles. In such scenarios, the objective function becomes Equation 6 . Additional constraints are necessary to ensure appropriate aggregate recovery rates are used conditional on whether a road was constructed with geotextiles, and to ensure the geotextile decision remains binary. If the planning horizon extends through the time period in which a constructed road is decommissioned, Equation 6 implicitly captures the economic benefits associated with use of geotextiles.
Minimize: X

i X

j X

t p t c ijtX ijt þ X

s X

j X

t p t g sjt Y sjt

þ X

i X

k X

t p t h iktZ ikt þ X

j 2 CJ X

t p t m jt W jt ð 6 Þ

where W jt = 1 if geotextiles are used in the construction of
road j in period t, 0 otherwise; m jt = cost to purchase and install geotextiles for road j ; and CJ the subset of roads requiring aggregate that are scheduled to be constructed.

Model II: Maximize Environmental Benefit

The second model seeks to maximize the hazard-weightedlength of roads decommissioned, as a proxy for environmental benefit (Equation 7 ). To account for differences between road segments, we can define a i to be the hazard rating for road segment i , perhaps identified using EMDS
or some other decision aid. This method is similar to that 302 Environmental Management (2008) 42:297–309



# 123employed by Girvetz and Shilling ( 2003 ), who assigned a score to each segment based upon its likely environmental impact and then maximized the hazard-weighted length of roads decommissioned. Another possible method is that employed by Madej and others ( 2006 ), who estimated expected erosion and delivery from sediment estimates by segment rather than by length.
Maximize: X

i X

k X

t a i li Z ikt ð 7 Þ

Subject to: X

i X

j c ijtX ijt þ X

s X

j g sjt Y sjt þ X

i X

k h iktZ ikt b t 8 t

ð 8 Þ

where li = length of road segment i ; b t = budget in period

t ; and all other variables and parameters are as defined
above. Equation 8 ensures that the total costs of road closure, decommissioning, and aggregate procurement and delivery do not exceed periodic budgets. Additional constraints are identical to Equations 2

–5 in the first model.

Example Application

We examine four scenarios in total, wherein we solve ourtwo models with and without the option to recycle aggregate. We expect that in the first (minimize cost) model, recycling aggregate will reduce overall total cost, while still decommissioning more roads than would occur under a scenario where recycling does not occur. In the second (maximize environmental benefit) model we expect that a greater length of roads will be decommissioned. In general we hypothesize that considering recovery and reuse as a decision variable in tactical transportation planning with environmental objectives will lead to more efficient and effective restoration policies. We present a two period hypothetical planning example using the transportation network of the South Zone of the McDonald-Dunn Research Forest, managed by the College of Forestry, Oregon State University. The South Zone spans 1910 hectares and encompasses 72 kilometers of unpaved forest roads. Roads within this zone are managed for a variety of uses, including access for teaching, research, demonstration, recreation, and timber transport. Although the opportunity to recover aggregate has been discussed in the past, the Forest has not yet pursued any recovery projects. Aggregate can be purchased from a quarry located 16 km north of the Forest, and there are no working pits in the forest due to low rock quality (Dave Young, Roads and Trails Specialist, OSU College Forests). Alternatively, we assume, aggregate may be recovered from decommissioned spur roads. Figure 1 displays the South Zone’s road network and identifies the project types considered. In our example, 7 road segments require removal (0.21, 0.35, 0.39, 0.59, 0.73, 0.84, and 2.42 km), 5 segments require construction (0.21, 0.28, 0.63, 0.90, and 2.34 km), and 2 require maintenance (0.75 and 3.20 km). The roads in need of maintenance are a connector (Rd. 660) and mainline (Rd. 600) that serve public traffic, meaning if recovered aggregate is to be used as a surface course it must first be processed. A portable rock crusher is used for the processing requirements. The segments to be constructed are low-standard roads reserved for timber transport, and thus require no processing of recovered aggregate beyond screening. For now we exclude the option to construct using geotextiles andtherefore do not consider the extension to Model I (Equation 6 ). While maintenance on a road can take a variety of forms, we limit our discussion here to re-surfacing, andassume that recovered aggregate can be used interchangeably with quarry aggregate. In this model we assume that all road segments slated for removal are equally detrimental, and therefore the optimal treatment from an environmental perspective is simply a function of length. In other words, we set the hazard rating ( a) to one for each road segment. This assumption is reasonable if we also assume an experiencedprofessional has identified appropriate levels of decommissioning such that the expected future impacts per unit length from each segment are nearly identical.
Tables 3

–6 provide input data used for the models.
Table 3 presents the aggregate required for maintenance and construction projects (D jt) , and Table 4 presents the aggregate available for recovery ( A it) from the roads slated for removal along with removal costs (h ikt). Note that different segments of Road 660 are slated for removal and maintenance. Aggregate quantity for maintenance purposes was estimated assuming 15 cm of re-surfacing was required along the length of the road, with connector roads and mainlines having a width of 4.3 m and 4.9 m,respectively. Aggregate quantity on spur roads was estimated assuming a surface width of 3.7 m and a road depth
of 25 cm.
Table 5 presents costs for aggregate purchase, recovery, and processing, estimated from Sessions and others ( 2006 ). Recovered aggregate used as a base layer (recovery + screening) costs $2.65/m 3 , whereas aggregate to be used as a surface layer costs $5.70/m 3 (recovery + screening + crushing), exclusive of transport costs. Delivery costs were estimated to be $0.35/m 3–km (Sessions and others 2006 ).
We used a real discount rate of 4% and values of 70% and 90% for the aggregate recovery factor ( rf ikt), where the higher value is roughly representative of situations where Environmental Management (2008) 42:297–309 303



# 123geotextiles are present. Table 6 presents estimated procurement, processing and delivery costs ($/m 3 ) for aggregate (g sjt). For simplicity, we based all costs on ‘‘in place’’ cubic meters, although in practice, transport costs are expected to be slightly higher because the volume of rock is about 30% larger prior to compaction on the road
surface. For road removal costs, we obtained values from Weaver and Hagans ( 2007 ). Closure costs may vary greatlydepending upon the intensity of management and road specific conditions. We estimated $7500/km, assuming closure is defined as filling ditches and outsloping the road surface. Likewise, decommissioning costs may vary; the estimates from (Weaver and Hagans 2007 ) range from $1200 to $32,000/km depending upon road type and complexity of decommissioning. For this example, we used a range of values from $10,000/km to $25,000/km in $5000 intervals.
Table 4 presents removal costs assuming an intermediate value of $20,000/km. We felt it was sufficient to only vary decommissioning costs for sensitivity analysis because it is largely the relative cost difference between the treatments that drives the decision to pursue one treatment over another. To arrive at appropriate annual budgets for the benefit maximization objective we calculated total expenditures excluding the option to recycle. The budgets were $95,000 and $115,000 for periods 1 and 2, respectively. Fig. 1 Road plan for the South Zone, with project types labeled 304 Environmental Management (2008) 42:297–309



# 123All models were solved to optimality using What’sBest 8.0, a spreadsheet optimization tool that is an add-in for Microsoft Excel, provided by Lindo Systems, Inc.

Results

Tables 7 and 8 present the results of the McDonald Dunn South Zone planning example. The baseline, no recycling,
cost minimization scenario resulted in a total discounted cost of $198,413, with no road segments scheduled to be decommissioned. Allowing the model to assign segments for decommissioning and to recycle the aggregate provided for cost savings and additional environmental benefit, as measured by length of roads decommissioned. In the best case scenario ($10,000/km decommissioning cost, 90%recovery rate), the model decommissions all roads requiring removal, for an overall cost reduction of over $47,000, or 24%. Clearly this is a preferable outcome over thebaseline. Including recycling as a decision variable generally yields improvements in terms of economic and ecologic objectives. Table 7 presents the results of our different cost-minimization scenarios, which vary by aggregate recovery rate and decommissioning cost; all results use a closure cost of $7500/km. At low decommissioning costs (relative to closure costs) the model schedules all or most roads to bedecommissioned in order to take advantage of the additional cost savings from using recovered versus quarrypurchased aggregate (see Table 6 ). At the same decommissioning cost, a higher recovery rate provides for costsavings and additional roads decommissioned. This finding, which was expected, could be viewed as an incentive to use geotextiles in construction.
Baseline results for the environmental benefit maximization scenario vary with decommissioning cost. At$10,000/km, the model schedules 1.79 km for decommissioning at a total cost of $202,803. Total benefits and costs are (0.56 km, $202,609), (0.35 km, $202,741), and (0.35 km, $204,473) for decommissioning costs of $15,000, $20,000, and $25,000/km, respectively. Including the option to recycle aggregate resulted in increased
environmental benefits. Unlike the cost minimization scenario, wherein some results achieved total costs no betterthan the baseline (i.e., no objective function improvements), here the model always generated improvements in
terms of additional kilometers of road slated for decommissioning. Table 3 Aggregate demanded (Djt) for maintenance and construction projects (m 3 ), by period for the South Zone example

Project type Road Length (m) Period Aggregate
demanded (m3 )

Maintenance 600 3189 1, 2 2520

660 747 1 518

Construction 650 2343 2 743

761 902 1 939

800 628 2 654

811 205 2 213

6021 280 1 292

Totals 6666 5879

Maintenance projects require higher quality surfacing rock, whereas construction projects require base layer quality

Table 4 Removal costs (h ikt) and aggregate available ( A it) from spurs slated for removal (m 3 ); South Zone example

Road Removal period Length (m) Aggregate available (m 3 ) Closure cost ($) Decommissioning cost ($)

620 1 393.61 410 $2952 $7872
630 1 213.23 222 $1599 $4265
660 1 346.27 360 $2597 $6925
681 2 835.06 869 $6263 $16,701
720 2 2417.22 2515 $18129 $48,344
762 2 732.97 763 $5497 $14,659
771 2 588.47 612 $4413 $11,769
Totals 5526.80 5751 $41,451 $110,536

Costs presented were calculated using $7500/km for closure and $20000/km for decommissioning Table 5 Unit costs ($/m 3 ) for aggregate procured from decommissioned roads and quarry; South Zone example

Operation/source Decommissioned roads Quarry

Purchase $0.00 $5.75 Recovery $1.15 $0.00 Screening $1.50 $0.00 Crushing $3.05 $0.00
Totals $2.65–5.70 $5.75

Aggregate procured from quarries entails purchase costs, whereas aggregate procured from decommissioned roads entails recovery and processing (screening and/or crushing) costs Environmental Management (2008) 42:297–309 305



# 123Table 8 presents the results of our environmental benefit maximization scenarios, which vary with recovery rate and decommissioning cost. In some instances costs are greater than the baseline scenario, which makes sense given the objective to decommission a greater length of roads. However, for the most part, decommissioning additional roads also yielded cost savings due to lower aggregatecosts. As with the above model, length of roads decommissioned decreases with increasing decommissioning cost. Higher recovery rates lead to substantial improvements both in terms of cost savings as well as total length decommissioned, again providing a possible incentive for use of geotextiles. For brevity we limit our presentation of detailed results to a single scenario, that in which the objective was to minimize total cost, decommissioning cost was $15,000/ km, and the recovery factor was 70%. In the first period, all roads slated for removal (620, 630, and 660) were Table 6 Unit Costs ($/m 3 ) for procurement, processing, and delivery (gsjt) of aggregate from sources (abandoned roads and quarry) to other road segments in need of aggregate

Aggregate sources Segments demanding aggregate

Maintenance Construction

Decommissioned roads 600 660 650 761 800 811 6021
620 $5.97 $8.00 $4.43 $7.12 $5.41 $5.17 $8.26
630 $5.85 $7.71 $4.14 $7.29 $5.49 $5.25 $7.86
660 $6.46 $5.94 $3.41 $9.15 $7.37 $7.12 $7.13
681 $8.23 $8.23 $5.18 $5.70 $9.04 $8.79 $5.61
720 $7.74 $10.48 $6.91 $5.58 $4.76 $4.52 $10.79
762 $9.45 $12.19 $8.62 $4.07 $6.54 $6.30 $9.71
771 $9.24 $9.76 $6.19 $5.31 $7.35 $7.11 $7.17 Quarry $18.10 $20.32 $20.32 $21.60 $19.84 $19.59 $24.04

Maintenance projects have higher processing costs if the source is recovered aggregate

Table 7 Cost savings and additional kilometers of road decommissioned over the baseline, cost-minimization scenario; South Zone example

Recovery rate Decommissioning cost ($/km) Cost savings ($) Length decommissioned (km) Roads decommissioned

70% $10,000 $36,430 5.53 All
$15,000 $10,828 4.21 620, 630, 660, 681, 720
$20,000 $0.00 0.00 None
$25,000 $0.00 0.00 None
90% $10,000 $47,009 5.53 All
$15,000 $21,108 4.79 620, 630, 660, 681, 720, 771
$20,000 $2866 1.79 620, 630, 660, 681
$25,000 $0.00 0.00 None

Table 8 Results for the environmental benefit maximization model; South Zone example

Recovery rate Decommissioning cost ($/km) Cost savings ($) Additional decommissioning (km) Roads decommissioned

70% $10,000 $28,548 3.74 (5.53) All $15,000 $-2967 4.97 (5.53) All $20,000 $960 1.44 (1.79) 620, 630, 660, 681 $25,000 $2282 0.26 (0.61) 620, 630 90% $10,000 $33,856 3.74 (5.53) All $15,000 $6908 4.97 (5.53) All $20,000 $993 3.86 (4.21) 620, 630, 660, 681, 720 $25,000 $-791 1.20 (1.55) 620, 630, 660, 771

Cost savings and additional decommissioning are presented relative to a scenario where no aggregate recycling is permitted. Values in parentheses in the 4 th column represent total length of roads decommissioned 306 Environmental Management (2008) 42:297–309



# 123decommissioned rather than closed. From road 620,
287 m 3 of recovered aggregate was delivered to road 761. Note this represents the entirety of the aggregate that can be recovered (70% of 410 m 3 is 287 m 3 ; see Table 4 ). Recovered aggregate from decommissioned road 630 was delivered to road 761 (116 m 3 ) and to road 6021 (39 m 3 ), and recovered aggregate from road 660 was delivered to road 6021 (252 m 3 ). Aggregate required for maintenance on road 600 came entirely from the quarry, as did the remainder of the aggregate required for roads 660 (518 m 3 ) and 761 (536 m3 ). Although decommissioning these roads resulted in a cost increase of $7148 over the option to close, cost savings still occurred due to recycling rather than purchasing quarry aggregate. Had aggregate for road761 been obtained from the quarry instead of from decommissioned roads 620 and 630, procurement and transport costs would have risen to $8705, an increase of $5816. Likewise, costs would have increased by $4892 had aggregate for road 6021 been obtained from the quarry
instead of from decommissioned roads 630 and 660. In the first period, then, decommissioning and aggregate recovery resulted in a net cost decrease of $3560. In the second period, two roads (762 and 771) were closed, and two were decommissioned (681 and 720). From road 681, 608 m3 were delivered to road 650. Recovered aggregate from road 720 was delivered to roads 600 (759 m3 ), 650 (135 m3 ), 800 (654 m 3 ), and 811 (213 m3 ). This arrangement satisfied all aggregate demand for roads 650, 800, and 811, and the remaining 1761 m3 required by road 600 was obtained from the quarry. Decommissioning roads 681 and 720 increased total removal costs by $24,392, but recycling rock versus obtaining purely from the quarry saved $31,951, for a net reduction of $7559. When discounted, this amounts to a savings of $7268; summing the savings from periods 1 and 2 results in approximate total savings of $10,828, which agrees with the value presented in Table 7

.

Discussion

Incorporating aggregate recycling into the decommission process can provide for significant cost savings, effectively subsidizing the decommissioning project. This ‘‘subsidy’’ may pay for additional decommissioning projects or may be re-invested into other road improvement projects. If implemented successfully, public land managers should see improvements in overall mitigation efforts at a givenbudget. Private owners should also be interested in recycling due to the cost-saving potential and the opportunity to demonstrate responsible stewardship. We first demonstrated this finding in our Washington Department of Natural Resources case study, where recycling resulted in over $19,000 of savings relative to a hypothetical alternative of using a local borrow pit. Where local pits are not available and more distant quarries must be used, cost savings can be expected to increase. As fuel costs continue to rise, these cost savings are expected to increase. In our McDonald Dunn Research Forest example we showed that cost savings could reach $47,000, which represents a 24% reduction over the no recycling scenario.Maximum savings are achieved in concert with the maximum possible length of roads decommissioned, 5.53 km (Table 7 ). Compared to the no recycling, cost minimization scenario in which no roads were decommissioned, thisobviously represents substantial environmental and economic benefit. Under the no recycling, environmental benefit maximization scenario there is always some length of roads slated for decommissioning, although including the opportunity to recycle can increase benefit by up to 890%, often with the co-benefit of cost savings (Table 8 ). Again, this emphasizes the point that aggregate recyclingmay subsidize environmentally beneficial road decommissioning projects. Haul distance appears to be a primary factor influencing the relative merits of aggregate recycling. In our McDonaldDunn Research Forest example, no local pits were available, which highlighted the haul distance differential between quarry-purchased and recovered aggregate. In other circumstances where local rock is available, results may be different, though we still expect that aggregate recovery and reuse could be an economical alternative. Of course, this also depends on other factors such as rock quality and intended use; where processing requirementsare higher than those presented, we would expect the relative merits of aggregate recycling to decrease. Absent from our models are the ecological costs of not taking action to decommission at-risk roads. As we cite in the introduction, unused forest roads can be a source of both chronic and episodic sediment to fish-bearing streams, with associated adverse impacts to aquatic species. For instance, unmaintained and/or under-maintained culverts maybecome blocked during high flow events, preventing effective drainage in subsequent storms. When water is redirected over the surface of the road the fill may become saturated andultimately fail, in some situations releasing massive quantities of sediment down slope (Flanagan and others 1998 ). On abandoned, unmaintained roads in the Redwood Creek watershed in northern California, stream-crossing diversions were found to be the leading cause of sediment production (Weaver and Hagans 1999 ). The potential for future ecological damage is clearly high, especially considering thatmany legacy roads are located near streams home to threatened and endangered salmonids. Pursuing valuation methods for quantifying the ecological damages however is beyond the scope of this article. Environmental Management (2008) 42:297–309 307



# 123A more immediate addition to the model, one that could be the subject of future research, is to include expected monetary damages from possible road failure. Thompson and Tomberlin (2005 ) and Tomberlin and others (2002) included probability distributions for landslide and stream crossing erosion when calculating expected erosion control costs. Allison and others (2004) also assigned a risk-weighted cost for damage control after possible road failure. Extending the planning horizon and including discounted expected costsfrom erosion control after failure may induce a cost-minimization model to schedule more road segments for decommissioning, with associated environmental benefits. Another possible extension to our work is to consider the cost effectiveness of implementing geotextiles. The tradeoffs are increased construction costs today versus increased recovery rates should aggregate recycling be pursued at some point in the future, and the associated costsavings. Our results indicate that geotextiles offer substantial economic benefit: when the recovery factor raises to 90% from 70% cost savings increased by as much as $10,000 (Table 7 ). Whether that cost savings offsets the implementation costs is not an avenue we pursued here however. It may be interesting at the road segment and network scale to relate the costs of implementation today to the benefit of implementation some years into the future.Of course, the benefits that geotextiles provide by preventing contamination of the base layer by the subgrade
material should also be considered. Recycling rock also increases the attractiveness of usingreduced tire inflation for aggregate transport. Rock transport vehicles, with heavy wheel loads and rigid suspensions, can be the most damaging to a road surface. Since moving from one road to another will usually involve short distances at low speeds, transport vehicles can run at reduced inflation pressures without needing expensive pressure controls. Reduced tire pressures reduce stresses to the subgrade, impact loadings and rut depth. If the trucks will not be run at highway speeds (i.e., maintained speeds of less than 60 km/hr), the air pressure can be manually reduced for the duration of the recycling project. The advantages of reduced tire inflation pressure are reduced road and truck maintenance needs, and if used during the wet season, reduced sedimentation from forest roads (Brown and Sessions 1999 ; Foltz and Burroughs 1991 ).

Conclusion

We presented a cost minimization model for aggregate recovery and reuse, and demonstrated that use of such amodel could result in substantial cost savings to landowners, possibly freeing up resources to implement other restoration-oriented projects. We also presented a model to maximize environmental benefit from road removal, using the total length of roads decommissioned as a proxy. Use ofthese models with appropriate computer applications constitutes a decision support aid that can be used to facilitate road removal decisions. Our models are general and easily extendable to other formulations, and should scale up to larger planning problems readily given advancements in computing capacity and commercially available solvers. While several simplifying assumptions were made for expository purposes, the management models presented here have practical applications. Aggregate recycling does occur in practice, as we demonstrated, and the formulation and data can be adjusted accordingly for specific situations.Future research could incorporate a broader road management optimization procedure, including additional removal treatments, maintenance regimes, and the decision of when to remove a road. Further work could also seek to apply an appropriate environmental hazard weighting techniques to maximize the hazard-weighted kilometers of road
decommissioned. We believe this article demonstrates the advantages ofrecycling aggregate, which are both economic and environmental. Where feasible, transportation managers should investigate opportunities to recover and reuse suitable aggregate, thereby increasing efficiency while yielding environmental benefits. Using models such as we presented here, it should be possible to identify which roads should be treated at a given level and how aggregate sources should be allocated, in order to best achieve landowner objectives.

Acknowledgments Numerous individuals contributed to this article, for which we are grateful. We would like to thank two anonymous reviewers, Randy Foltz of the USDA Forest Service, and the associate editor for their constructive and helpful comments. We would also like to thank Jennie Cornell of the Washington State Department of Natural Resources, Mark Karr from the Umpqua National Forest, and Tom Kollasch from the Nature Conservancy for providing data from real-world instances of aggregate recycling. Tom Erkert and Mark Truebe of the USDA Forest Service provided invaluable insight into the opportunities for aggregate recycling on national forests. Dave Young of the OSU Research Forest office provided helpful information regarding road management on the McDonald-Dunn Forest. The primary author completed work on this article while a graduate student at Oregon State University as a recipient of the Wes and Nancy Lematta Fellowship and the Dorothy M. Hoener Fellowship.

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