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 salmonid

habitat, many public and private land managers in the western United States are actively decommissioning roads where

practical 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 decommission

additional 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 to

determine optimal levels of aggregate recycling under economic and environmental objectives. Tested on an example

road network, incorporation of aggregate recycling demonstrates substantial cost-savings relative to a baseline scenario

without 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 mitigate

negative 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 agencies

have also sought to decommission roads for ecological reasons, such as the USDI National Park Service within

Redwood National Park in 1978 (Madej 2001). Some private

land 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/s00267-008-9136-0
can 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 the

majority 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/or

waterbars, 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 removing

culverts under significant fills, ripping the roadbed, recontouring hillslopes, and may include planting or seeding the

road surface. A decommissioned road is not passable and

requires 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 the

USDA Forest Service, which has a minimal road maintenance budget due in large part to substantial reductions in

their 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 case

study 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 complete

roads 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

123
National 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 road

removal decisions on economic or sediment-related objectives. Anderson and others (2006) used dynamic

programming 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 to

schedule 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 than

native-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 if

managers 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 minimal

amount to recover (Tom Erkert, Group Leader, Transportation Planning, Operations and Maintenance, USFS Pacific

Northwest 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 consistent

with fresh aggregates in terms of runoff volume and sediment production from simulated rainfall, but produced

Environmental Management (2008) 42:297–309 299

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above 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 for

concurrent 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 will

demonstrate, 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 alternative

for 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 m3 were recovered and stockpiled for re-use from a road decommissioned in 2003 at a cost

of $5.35/m3

. Four years later 230 m3 were recovered from a

short spur road and stockpiled at a cost of $6.90/m3

, 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 constructed

nearby. 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, the

project 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 ($/m3) 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

123
roads, 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 cost

savings 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 borrow

pit. The total amount of aggregate recovered from the decommissioned roads was 1988 m3

, 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

123
build 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

ptcijtXijt þ X

s

X

j

X

t

ptgsjtYsjt

þ X

i

X

k

X

t

pthiktZikt ð1Þ

Subject to:

X

i

Xijt þ X

s

Ysjt 1⁄4 Djt 8 j; t ð2Þ

X

j

Xijt X

k

rfiktAitZikt 8 i; t ð3Þ

X

k

Zikt 1⁄4 1 8 i; t ð4Þ

Zikt 2 f g 0; 1 8 i; k; t ð5Þ

where pt = present net value factor for period t, dimensionless; Xijt = aggregate recovered from road i and

delivered to road j in period t, m3

; Ysjt = aggregate taken

from source s (pit or quarry) and delivered to road j in

period t, m3

; Zikt = 1 if road i is removed at treatment level

k in period t, 0 otherwise; cijt = cost to recover aggregate

from road i and deliver to road j in period t, $/ m3

;

gsjt = cost to procure aggregate from source s and deliver

to road j in period t, $/ m3

; hikt = cost to remove road i at

treatment level k in period t, $; Ait = aggregate available

for recovery from road i in period t, m3

; Djt = aggregate

required for road j in period t, m3

; and rfikt = aggregate

recovery factor for road i removed at treatment level k in

period t, m3

/m3. 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

ptcijtXijt þ X

s

X

j

X

t

ptgsjtYsjt

þ X

i

X

k

X

t

pthiktZikt þ X

j2CJ

X

t

ptmjtWjt ð6Þ

where Wjt = 1 if geotextiles are used in the construction of

road j in period t, 0 otherwise; mjt = 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-weighted

length of roads decommissioned, as a proxy for environmental benefit (Equation 7). To account for differences

between road segments, we can define ai 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

123
employed 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

ailiZikt ð7Þ

Subject to:

X

i

X

j

cijtXijt þX

s

X

j

gsjtYsjt þX

i

X

k

hiktZikt bt 8 t

ð8Þ

where li = length of road segment i; bt = 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 our

two 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 and

therefore 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, and

assume 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 experienced

professional 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 (Djt), and Table 4 presents the

aggregate available for recovery (Ait) from the roads slated

for removal along with removal costs (hikt). 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/m3

, whereas aggregate to be used as

a surface layer costs $5.70/m3 (recovery + screening +

crushing), exclusive of transport costs. Delivery costs were

estimated to be $0.35/m3

–km (Sessions and others 2006).

We used a real discount rate of 4% and values of 70% and

90% for the aggregate recovery factor (rfikt), where the

higher value is roughly representative of situations where

Environmental Management (2008) 42:297–309 303

123
geotextiles are present. Table 6 presents estimated procurement, processing and delivery costs ($/m3

) for

aggregate (gsjt). 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 greatly

depending 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

123
All 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 the

baseline. 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 be

decommissioned 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 cost

savings 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 better

than 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 (m3

), 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 (hikt) and aggregate available (Ait) from spurs slated for removal (m3); South Zone example

Road Removal period Length (m) Aggregate available (m3

) 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 ($/m3) 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

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Table 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 aggregate

costs. 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 ($/m3) 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 4th column represent total length of roads decommissioned

306 Environmental Management (2008) 42:297–309

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decommissioned rather than closed. From road 620,

287 m3 of recovered aggregate was delivered to road 761.

Note this represents the entirety of the aggregate that can

be recovered (70% of 410 m3 is 287 m3

; see Table 4).

Recovered aggregate from decommissioned road 630 was

delivered to road 761 (116 m3

) and to road 6021 (39 m3),

and recovered aggregate from road 660 was delivered to

road 6021 (252 m3

). Aggregate required for maintenance

on road 600 came entirely from the quarry, as did the

remainder of the aggregate required for roads 660 (518 m3

)

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 road

761 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 m3), 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 given

budget. 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, this

obviously 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 recycling

may subsidize environmentally beneficial road decommissioning projects.

Haul distance appears to be a primary factor influencing

the relative merits of aggregate recycling. In our McDonald

Dunn 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 requirements

are 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 may

become 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 and

ultimately 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 that

many 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

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A 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 costs

from 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 cost

savings. 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 using

reduced 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 a

model 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 of

these 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 of

recycling 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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