Journal of Green Engineering

Vol: 4    Issue: 4

Published In:   July 2014

Machine Utilization Rates, Energy Requirements and Greenhouse Gas Emissions of Forest Road Construction and Maintenance in Romanian Mountain Forests

Article No: 5    Page: 325-350    doi: https://doi.org/10.13052/jge1904-4720.445

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Machine Utilization Rates, Energy Requirements and Greenhouse Gas Emissions of Forest Road Construction and Maintenance in Romanian Mountain Forests

Received 4 July 2014; Accepted 27 November 2014; Publication 19 March 2015

A. Enache and K. Stampfer

• University of Natural Resources and Life Sciences, Vienna, Austria

Abstract

The FAO and EU forest strategies advocate the use of forest resources in ways which minimize the impact on the environment and climate. However, in forests with poor accessibility, the environmental footprint of forest operations is significant due to the long timber extraction distances. Thus, improving the environmental performance of forest operations requires a well-developed forest infrastructure, specifically the density and quality of roads. The aim of this paper was to assess the environmental footprint of forest roads in terms of embodied energy and greenhouse gas emissions due to construction and maintenance. In this respect, life cycle assessment approach was used to develop an input-output model for benchmarking two case study areas, considering real machine utilization rates, fuel consumption and labor requirements. The forest road life cycle was set to 30 years. Direct energy requirements derived from the fuel consumed by the machinery were considered. Construction and maintenance required energy inputs of 490.9 MJ m−1 and 580.4 MJ m−1, respectively about 36.6 kg CO2eq m−1 and 43.1 kg CO2eq m−1 emission rates in the two case study areas, while occupying productive land with forest roads triggered a loss of 3.95 kg CO2eq m−1 y−1 and 4.40 kg CO2eq m−1 y−1 during the life cycle of the forest road. However, the CO2eq loss due to road construction and maintenance is insignificant when compared to the CO2eq stored in the growing stock of the opened forest area. Terrain characteristics showed a strong influence on the amount of fuel consumption, required energy input and GHG emissions, leading to higher environmental burden and higher road construction costs.

Keywords

• Emissions
• energy efficiency
• forest
• greenhouse gases
• LCA
• Romania

1 Introduction

The EU 20-20-20 targets on climate change and energy sustainability envisage 20% reduction of greenhouse gas (GHG) emissions from 1990 levels and improving with 20% the energy efficiency by year 2020. Forests and their sustainable management play a major role in the reduction of GHG emissions level and in carbon storage in forest biomass (Kilpeläinen et al. 2011). The FAO and EU forest policy framework promote a holistic approach to the challenges of the entire forest value chain for adapting forests to climate change and for reducing the environmental footprint of forest operations within the framework of a low carbon economy. However, in forests with poor accessibility, the environmental footprint of forest operations is significant due to the long timber extraction distances.

Romanian forests cover 6.65 million ha (29% of the total land area; Abrudan et al. 2009) and have a poorly developed and unevenly distributed infrastructure (road density 6.5 m ha−1; Olteanu 2008). Thus, skidding is the main method of timber extraction and the mean skid distance is about 1.8 km at national level (Popovici et al. 2003). Consequently, the environmental footprint of forest operations is high, while the productivity in timber harvesting and extraction is rather low (Borz et. al 2013; Enache et al. 2013). The average annual growth of Romanian forests is about 37 million m3, the annual allowable cut (AAC) is 22.3 million m3 and the average annual removal is about 17.0 million m3 (World Bank 2012). About 65% of the forests are located in mountain ranges, 55% are state-owned forests and 45% non-state forests. The underdeveloped forest infrastructure makes sustainable forest management challenging, with significant pressure and environmental footprint on the accessible forests. However, the net forest growth in the last decades was positive, ranging between 15–17 million m3 each year, triggering a consequent increase of carbon storage (World Bank 2012). This means there is significant potential for increasing the sustainable wood mobilization, which requires a well-developed forest infrastructure.

Timber harvesting and road engineering have the most visible environmental impact in the forest sector. The life cycle assessment (LCA) is a suitable tool for approaching such challenges of the wood supply chain and for producing reliable indicators on the environmental performance of systems and processes in the forest sector (Heinimann 2012). Meister (1995) emphasized that the environmental balance of forest operations is based on mass flows and energy balance of inputs and outputs of a system. In addition, Richter (1995) stressed that defining the boundaries of a LCA system is difficult, highlighting that wood supports most of the negative burdens of the forest management activities, while other ecosystem services of the forest management with direct positive effects on people and the environment do not. The environmental performance of silviculture operations, timber harvesting and transport have been extensively addressed in the literature (Berg and Lindholm 2005; Johnson et al. 2005; Klvac and Skouppy 2009; Michelsen et al. 2008; Seppala et al. 1998; Klvac et al. 2012), while only few studies have included forest roads in the analyzed system boundaries (Berg and Karjalainen 2003; Bosner et al. 2012; Whittaker et al. 2011). American researchers focused more on the effects of forest roads on soil erosion, sedimentation and water quality (Coulter 2004; Mills, 2006; Loeffler et al. 2008), whilst European researchers focused on the embodied energy and GHG emissions of forest roads (Heinimann and Maeda-Inhaba 2003; Heinimann 2012; Whittaker et al. 2011). Since the environmental impact of roads relate to their construction, maintenance and use (Treloar et al. 2004), complete LCA of forest roads is difficult and time consuming, depending on the system boundaries and on the number of inputs in the process analysis. Hence, a hybrid process based and input-output based LCA approach is recommendable for estimating project specific environmental impacts of forest roads (Treloar et. al 2004; Sharrard 2007).

In this context, considering the current concerns on the environmental performance of forest management activities (Abrudan et al. 2009; Karjalainen et al. 2003; Michelsen et al. 2008; Olofsson et al., 2011), the aim of this paper was to quantify the embodied energy, the loss of productive land and the GHG emissions from forest roads construction and maintenance through a comparative assessment of two case study areas. In this respect, a hybrid LCA approach was used, referring to the functional unit of road.

2 Material and Methods

2.1 Pre-Set Standards

This study focused on the energy requirements and GHG emissions of forest roads due to construction and maintenance during their life cycle. In this respect, the following standards were established: real utilization rates of machinery and consumption rates of materials and labor; real transport distances for machinery and materials; AAC of the forest area assigned to the forest roads; the life cycle of the forest roads was set to 30 years. The CO2eq emissions were determined for a complete cycle of the diesel combustion process based on a stoichiometric combustion model (Heinimann 2012), for a net calorific value of diesel engines of 42.76 MJ kg−1 (Stanescu 2012) and the diesel density of 0.835 kg m−3 (Berg and Karjalainen 2003). The loss of productive land due to road construction was quantified for an average annual growth of 6.0 m3ha−1. For timber transport, the truck and trailer system with loading capacity of 25 m3 was considered.

2.2 Input-Output LCA Model and System Borders

The energy efficiency and the emissions of greenhouse gases are important elements in LCA which focuses on the global warming potential (GWP) of a system. A typical LCA consists of setting goals and objectives, inventory analysis, impact assessment and interpretation of results (Heinmann 2012), while an optimal hybrid LCA model for construction should include economics, on-site activities, equipment, transportation, water, energy and social equity related aspects (Sharrard 2007). The hybrid LCA is based on deriving an input-output (I-O) LCA model and then case-specific LCA data for the analyzed system which are substituted in the I-O model (Treloar et al. 2004).

Heinimann and Maeda-Inaba (2003) showed how the concepts of commodities and activities and the oriented graph theory can be used in investigating I-O flows in forest roads construction. Figure 1 shows the LCA model of forest roads developed in this study for investigating the input-output flows of the road construction and maintenance works. This model refers only to the life cycle inventory of the roads and allows identification of material, energy, labor and emission flows within the system. The model was applied for both road construction and maintenance works, referring to activities such as: preparatory works (i.e. transport of machinery and material to the site, road bed clearance); embankments execution, drainage system and pavement finishing; and maintenance works (i.e. pavement reshaping; ditches reshaping). Direct energy requirements and greenhouse gas emissions were derived from the fuel consumed by machinery to carry out specific tasks (Whittaker et al. 2011), disregarding the energy and the emissions embodied in the machinery manufacture. The functional unit of the analyzed system set in this study was one meter of road.

Figure 1 Life cycle I-O model for forest road construction and maintenance.

Except for the timber cleared during the road construction, timber harvesting and transport were not included in analysis in this study. Accounting of the energy and emissions applied to timber harvesting and extraction with and without forest road will be approached in another study.

2.3 Building Technology Matrices

The quantification of the input and output flows for each phase of the LCA (Figure 1) were based on the technology matrices approach, using a system of linear equations which describe the flow of commodities into the system (Michelsen et al. 2008; Heinimann 2012), an example of which is presented in Table 1 for the phase of pavement works. The first row of the matrix shows the flow of labor necessary for a given process, taking into account the effective working time of a machine operator. The second row shows the fuel consumption rates of the machineries per productive system hour (PSH), which means the system includes both the machinery and the operator. The following rows were filled using the same reasoning. Thus, if a machine was not used in the system, all values in the row assigned to that machine were set to zero, except the diagonal value which was always set to value 1.

Table 1 Flow of commodities into the functional unit of road for pavement works

According to Heinimann (2012), assuming that each process can be scaled by a variable xi(i=1 ÷ n), the system of equations can be solved for the vector X (x1, x2,..., xn) if the total production of the system is known, that is vector Y, using the equations bellow.

$Equation (1) A ⋅ X=Y$

$Equation (2) X = A−1 ⋅ Y$

The economic performance of the systems was determined using a cost vector based on the machine hour costs computed with the FAO cost calculation scheme (Holzleitner, 2011), which was then multiplied with the performance vector X. Considering the direct correlation between the flow of commodities and their environmental footprint (Heinimann 2012), an environmental matrix similar to the technology matrix from the Table 1 was developed. This matrix was then multiplied with the performance vector X, and the environmental footprint vector of the analyzed system was thus determined. The technology matrix approach was used in benchmarking both forest road construction and maintenance works.

2.4 Case Study Areas (CSAs)

The research was conducted in Lignum Forest Enterprise, located in Bacau County (Romania), Eastern Carpathian Mountains (46°21′02"N, 26°20′42"E; Figure 2), in the surroundings of Accumulation Lake “Valea Uzului” which provides drinking water for 27 communities with about 370 000 inhabitants.

Figure 2 Location of the case study areas (CSA).

The forest enterprise manages about 6 500 ha of mixed broadleaves-coniferous forests, of which 85% have mainly protective functions for water quality. The rotation of forest stands is about 100–110 years for conifers and 110–120 years for broadleaves. The bedrock is of Paleocene age, mainly sandstones, marl schist and alluvial formations, while the most common soil types are brown forest soils (75% of the area) and acid brown soils (25%). The density of forest roads is about 7.6 m ha−1, with roads located mostly along the valleys. Timber extraction is done by tractors and skidders (65% of AAC), forwarders (21%), horse harnesses (8%) and cable yarders (6%). Two case study areas were selected for analysis: CSA 1 – Forest Road Plopu-Lapos and CSA 2 – Forest Road Coporaia (Table 2).

Table 2 Key facts about case study areas

 Item CSA 1 CSA 2 Length of the new forest road (m) 1 707 1 968 Forest area served by the road (ha) 841.8 704.0 Current standing volume (m3) 287 754 252 042 Estimated increment in 30 years (m3) 151 376 142 032 Estimated gross standing volume after 30 years (m3) 439 130 394 074 Estimated harvests in 30 years (m3) 120 000 113 600 Estimated net standing volume in 30 years (m3) 319 130 280 474

For each CSA, data of the following machineries used in road construction was collected from the records of the forest enterprise: chainsaw, excavator, stone crusher, grader, front loader, compactor, dump truck, trailer and timber lorry (Table 3). For road maintenance, data was gathered from the records of the maintenance works conducted in 2013 across the entire forest district for old valley forest roads, for the following machinery: backhoe loader, stone crusher, grader, compactor, dump truck and trailer.

Table 3 Key facts of the machinery used in road construction and maintenance

2.4.1 CSA 1 – Forest Road “Plopu-Lapos”

3

Table 4 Classification of forest roads by slope classes of the terrain in each CSA

Table 5 Characteristic of embankment works in each CSA

3 Results

3.1 Machine Utilization Rates

The fuel consumption rates and the machine utilization rates for each phase of the road construction in CSA 1 are depicted in Table 6. For building one meter of road in CSA 1, 0.930 man-hours, 6.19 liters of diesel and 0.772 machine-hours were required. Out of the latter ones about 28% were excavator hours, 27% were dump truck hours and 15% were front loader hours.

Table 6 Utilization rates of fuel, labor and machinery in CSA 1

The most intensive phases of road construction (in terms of labor, fuel consumption and machine utilization) were the embankments execution and the pavement works. The execution of embankments required about 26% of the labor, 39% of the fuel and 25% of the machinery utilization from the total amounts needed for building the road. For the pavement works, about 62% of the labor, 52% of the fuel and 60% of the machinery utilization were required.

The fuel consumption rates and the machine utilization rates for each phase of the road construction in CSA 2 are depicted in Table 7. For building one meter of road in CSA 2 were necessary about 8.59 liters of diesel and 1.084 machine-hours, out of which 31% were excavator hours, 23% were dump truck hours and 15% were front loader hours. Similar to CSA 1, the most intensive phases of the road construction in terms of labor requirements, fuel consumption and machinery utilization in CSA 2 were the embankments execution and the pavement works. The execution of embankments required 43% of the labor, 59% of the fuel and 43% of the machine-hours from the total amounts needed for building the road, while the execution of pavement finishing required 38% of the labor, 33% of the fuel and 38% of the machinery utilization.

Table 7 Utilization rates of fuel, labor and machinery in CSA 2

The utilization rates of the machinery used in one road maintenance operation are depicted in Table 8. About 0.5 liter of fuel and 0.072 machine-hours were required for maintaining one meter of road. Hence, during the entire life cycle of the forest road, maintenance works for one meter of road would require about 7.5 liters of fuel and 1.073 machine-hours utilization. The maintenance works of the drainage systems (i.e. reshaping the side ditches and cleaning the culverts) consumed about 60% of the total labor and fuel required for the road maintenance.

Table 8 Machinery utilization rates for one process of road maintenance

3.2 Cost Appraisal

Table 9 shows the structure of the road construction and maintenance effort by type of costs. The total road construction costs were 88.2 € m−1 in CSA 1, respectively 119.6 € m−1 in CSA 2. The costs reported for road maintenance, respectively 2.91 € m−1, are those required for performing one operation. Regarding the road construction, in both CSAs, the labor was the most intensive cost factor, representing about 55% (CSA 1) and 56% (CSA 2) of the total costs, respectively. The second most important cost factor in road construction was the utilization of machineries, with a share of 25% in CSA 1 and 32% in CSA 2 from the total costs. The most important cost factor in road maintenance was the machinery with about 51% of the total maintenance costs, while labor and fuel consumption had similar shares from the total costs, respectively 24% and 25%.

Table 9 Structure of the road construction and maintenance costs

Figure 3 Forest road costs by category of works.

Table 10 presents the utilization rates, the fuel consumption rates and the system hour costs of the machinery (including fuel and labor costs). Slight variations of the machinery system hour costs were noticed between CSA 1 and CSA 2, respectively between road construction and road maintenance. This was probably because of the effective utilization time of the machineries and due to different operators running specific machineries. It has to be noted the forest enterprise used both local labor and Austrian labor for operating the machinery, the latter case being much more expensive, but however with more experience than local operators.

Table 10 Total utilization rates, fuel consumption and costs of machinery

3.3 Embodied Energy, GHG Emissions and Loss of Productive Land

The most energy intensive phases in road construction are the embankment and the pavement works in both CSAs (Figure 4).

Figure 4 Energy requirements of road construction and maintenance.

Figure 4 reveals a significantly higher energy demand for the embankments execution in CSA 2 (181.4 MJ m−1) compared to CSA 1 (86.4 MJ m−1). This was due to the steeper terrain and more rock excavations in CSA 2 than in CSA 1 (Table 4 and Table 5), which required more machinery utilization. The total amount of energy required for road construction was 223.12 MJ m−1 in CSA 1 and 312.60 MJ m−1 in CSA 2 (Figure 4). The execution of pavement finishing was the most energy intensive phase in CSA 1, accounting for about 52% of the total energy input, while the most energy intensive phase in CSA 2 was the embankment execution, which accounted for about 58% of the total energy input.

One complete process of road maintenance required about 10.98 MJ m−1 for the construction of the drainage system and about 6.87 MJ m−1 for the pavement works. Although these figures might seem less energy intensive than the road construction, due to the repetition of this process at regular intervals during the entire life cycle of the road, the energy requirements of the maintenance works might equal or outweigh the energy input required in road construction: 164.70 MJ m−1 for drainage system and 103.05 MJ m−1 for pavement works. Therefore, the total energy embodied in forest roads due to construction and maintenance would beabout 490.87 MJ m−1 in CSA 1 and 580.35 MJ m−1 in CSA 2. Considering the allowable cut of each CSA and the life cycle of the forest roads, this means an energy input per cubic meter of timber harvested of about 7.0 MJ in CSA 1, respectively 7.3 MJ in CSA 2.

In what concerns the global warming potential of the forest road construction and maintenance, Table 11 shows the emission rates of CO2eq. per meter of road.

Table 11 Emission rates of CO2eq from road construction and maintenance

The permanent surface occupied by the road bed was 10 219 m2 in CSA 1 and 13 108 m2 in CSA 2 (Table 12). The loss of productive land due to road construction was about 5.07 m2 y−1 per cubic meter of wood in CSA 1, respectively 5.82 m2 y−1 in CSA 2. Considering the mean annual growth of forests in the study area (6 m3 ha−1 y−1) and that one cubic meter of wood binds about 1.1 tones CO2eq from the atmosphere (Hasenauer, 2014), this means about 6.74 t CO2eq in CSA 1 and 8.65 t CO2eq in CSA 2 are not bound each year due to the loss of productive forest land. Reporting these figures to the road unit, it means that occupying productive forest land with forest roads requires 3.95 kg CO2eq m−1 y−1 in CSA 1 and 4.40 kg CO2eq m−1 y−1 in CSA 2.

Table 12 Impact of road bed clearance on CO2eq emissions

 Index Item CSA 1 CSA 2 1 Cleared road bed surface (ha) 1.02 1.31 2 CO2eq emissions due to loss of productive land (t CO2eq) 202.2 259.5 3 CO2eq from timber harvest road bed (t), of which: 447.7 326.7 4 – stored in wood products (t CO2eq) 179.1 130.7 5 – emissions to atmosphere (t CO2eq) 268.6 196.0 6 CO2eq balance of the road bed clearance (t CO2eq) [(6) = (4) – (5) – (2)] −291.7 −324.8

The CO2eq emissions due to loss of productive land can be only partially compensated by the CO2eq stored in the timber harvested from the road bed clearance (Table 12). For clearing the road bed, about 407 m3 were harvested in CSA 1 and 297 m3 in CSA 2, which is equivalent to 447.7 CO2eq and 326.7 t CO2eq, respectively. Considering that approximately 40% of the harvested timber is used for wood products and 60% as energy wood by the forest enterprise, this means during the life cycle of the forest roads approximately 130.7 t CO2eq in CSA 2 and 179.1 t CO2eq in CSA 1 can be stored in wood products, the rest being released back in the atmosphere through the burning process. Table 12 reveals that occupying productive forest land with roads means a net loss of 291.7 t CO2eq in CSA 1 and 324.8 t CO2eq in CSA 2.

Notwithstanding, the net CO2eq emissions due to loss of productive land are insignificant when compared to the amount of CO2eq stored in the growing stock of the opened forest area. Table 13 shows the balance of CO2eq due to the loss of productive land occupied by the roads during their entire life cycle for the forest area opened by the road construction in both CSAs. The CO2eq balance was calculated as an algebraic sum of the CO2eq gains (i.e. current standing volume, increment during the life cycle of the road, storage in wood products) and CO2eq losses (i.e. emissions in atmosphere by combustion of energy wood). The CO2eq emissions due to machinery utilization in timber harvesting were not included in this analysis.

Table 13 Impact of lost productive land on CO2eq emissions during road life cycle

 Index Item CSA 1 CSA 2 1 Total CO2eq of current standing volume (t CO2eq) 316 530 282 750 2 Total CO2eq of timber harvested in 30 years (t CO2eq), of which: 132 000 124 960- 3 – stored in timber products (t CO2eq) 52 800 50000- 4 – emissions in atmosphere by energy wood (t CO2eq) 79 200 84960- 5 CO2eq of net standing volume in 30 years (t CO2eq) 351 040 308 520- 6 CO2eq balance of the road bed clearance (t CO2eq) –291.7 –324.8 7 CO2eq balance of road construction and maintenance (t CO2eq) –62.4 −84.8 8 CO2eq balance of the opened forest area (t CO2eq) [(8) = (7) + (6) + (5) + (3) − (4)] 324 285 273 150

4 Discussions and Conclusions

Forest road construction is an intensive process in what concerns machinery utilization, labor required, energy input and GHG emissions. The most energy intensive processes in road construction reported in this study were the embankment and the pavement works, accounting for about 90% of the total energy requirements in each CSA. The most intensive energy consumers and CO2 emissions generators were the excavator, the dump truck and the front loader, accounting for about 70% of the total necessary machine utilization hours in each case study area.

The total energy embodied in forest roads (construction and maintenance) was 490.87 MJ m−1 in CSA 1 and 580.35 MJ m−1 in CSA 2, respectively. In comparison, Heinimann (2012) estimated energy input rates for road construction and maintenance between 315 and 735 MJ m−1 road, depending on the side slope variation, while Whittaker et al. (2011) reported energy requirements of 403 MJ m−1 for road construction and 102 MJ m−1 for road maintenance, including the requirements of machine manufacture and maintenance. However, all these figures should be cautiously interpreted, looking at the characteristics of each study layout (i.e. topographical conditions, definition of the system borders).

The input-output LCA approach proved to be a useful tool for assessing the energy requirements and GHG emission levels of forest roads. Though, setting the system boundaries and the time scale, gathering and analyzing data represent challenging and time consuming tasks. A natural further step of this study would be the accounting of the energy and emissions of different harvesting systems in mountain regions with and without forest roads, in order to see the impact of forest infrastructure development on the environmental footprint of harvesting operations.

5 Acknowledgments

The authors would like to thank Hendrik Schubert and Constantin Vasilică from Lignum Forest Enterprise for their support in data collection and feedback during data analysis. We would also like to thank the two anonymous reviewers for their valuable comments and suggestions.

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Biographies

Adrian Enache is a research associate at the Institute of Forest Engineering from the University of Natural Resources and Life Sciences (BOKU) –Vienna, Austria. His work focuses on efficiency gaps analysis and multiple criteria decision making in timber harvesting and road network planning in mountain forests (ARANGE project). He holds a doctor degree in forestry (Transilvania University of Brasov – UNITBV, Romania, 2013), a master degree in mountain forestry (BOKU, 2009), a certification in project management (CODECS, 2007) and a diploma engineer degree in forestry (UNITBV, 2005). Since 2011 he is enrolled in a PhD program at BOKU.

Karl Stampfer is professor at the Institute of Forest Engineering at BOKU, Vienna. His expertize is related to the multi-dimensional aspects of the wood supply chain (i.e. timber harvesting, road network planning, logistics, cable yarding, ergonomics). He holds a doctoral degree in forestry since 1996 (BOKU) and his habilitation was in 2002 (BOKU). He received several international awards and he is member in numerous international professional societies (i.e. IUFRO, Austrian Association for Agricultural Research, Croatian Academy of Forestry Sciences). Since 2003 he is the chairman of FORMEC – International Symposium on Forestry Mechanization.