Development of a Life-Cycle Assessment Tool to Quantify the Environmental Impacts of Airport Pavement Construction

Transcription

1 Development of a Life-Cycle Assessment Tool to Quantify the Environmental Impacts of Airport Pavement Construction Rebekah Yang and Imad L. Al-Qadi The environmental impacts of airport pavement construction were evaluated in this study through a life-cycle analysis approach. Total primary energy (TPE) consumption and greenhouse gas (GHG) emissions from material production and construction of pavement were determined by using life-cycle assessment (LCA), a quantitative methodology described in the ISO series. A tool was developed to implement a probabilistic LCA through the Monte Carlo method. This tool allowed for consideration of uncertainty from life-cycle inventory data. A case study on the construction of Runway 10R-28L at Chicago O Hare International Airport focused on mainline and shoulder pavement designs. Environmental impacts from producing materials for the pavements increased from lower to upper layers, while asphalt layers had relatively higher TPE consumption than the upper portland cement concrete layer and vice versa for GHGs. Impacts from material production overshadowed those from construction, which contributed less than 2% of TPE consumption and GHGs. Further analysis showed that two production processes for asphalt binder and portland cement were the leading contributors (45.3% and 29.2%, respectively) of TPE consumption, while the latter was the leading contributor (73.4%) of GHGs. A probabilistic analysis compared the original 10R-28L runway design and a modified design that did not use recycled materials or warm-mix asphalt technology. The results from 1,000 Monte Carlo simulations showed that the environmental impacts from the two cases were statistically significant, with the original design having lower TPE consumption (482 versus 693 MJ/yd 2 for TPE) and GHGs (37.5 versus 53.9 kg of carbon dioxide equivalent per square yard). The air transportation industry is a major part of the transportation sector, with 3.3 billion passengers having traveled and 51.7 million tonnes of freight moved in 2014 (1). In the same year, commercial airlines collected $758 billion in revenue, with an expenditure of $716 billion, 25% of which was used to purchase fuel (1). While the air transportation industry has made significant improvement in aircraft fuel economy, air transportation still contributed 2% (or approximately 724 million tonnes) of global nonnatural carbon dioxide (CO 2 ) in 2014 (1). While the majority of environmental impacts from an airport must be attributed to aircraft themselves rather than to airport infrastructure, the impact on the environment Department of Civil and Environmental Engineering, University of Illinois at Urbana Champaign, 205 North Mathews Avenue, Urbana, IL Corresponding author: R. Yang, ryyang3@illinois.edu. Transportation Research Record: Journal of the Transportation Research Board, No. 2603, 2017, pp from construction, maintenance, and expansion of airport runways, taxiways, and aprons is also important. In the United States, more than 9,000 airports have paved runways (2). The total area of pavement runway surfaces in the United States was approximately 650 million square yards in 2009, with $4 billion spent annually to maintain these surfaces, which support more than 40 million takeoffs and landings per year (2). A corresponding environmental cost of maintaining these surfaces also results from activities needed to sustain and use these airport runaways, taxiways, and aprons. The air transportation industry has acknowledged that steps must be taken to ensure sustainable operation of its airports for future generations. This paper focuses on evaluating the environmental sustainability of airport pavement so that airport operators can better determine the environmental impacts associated with constructing and managing runways, taxiways, and aprons. A life-cycle analysis approach was used to quantify the greenhouse gas (GHG) emissions and energy consumption associated with the construction of airport pavement. ISO guidelines for life-cycle assessment (LCA) were followed, and a tool was developed to facilitate the application of LCA to a case study at Chicago O Hare International Airport (3). In addition, the uncertainty of life-cycle inventory (LCI) data was taken into account by using the Monte Carlo method to allow for a probabilistic analysis of the case study. Background Evaluating Airport Sustainability Approaches used to evaluate the environmental impacts of a system are often divided into two categories: qualitative and quantitative. Qualitative approaches are typically implemented by using sustainability rating systems, while quantitative approaches include accounting methods such as carbon footprinting and LCA. In the United States, sustainability management manuals have been developed by various airport operators. Most notable are the Sustainable Airport Manual from the Chicago Department of Aviation (4) and the Sustainable Airport Planning, Design and Construction Guidelines from Los Angeles World Airports (5). These manuals use a checklist system to rate aspects of planning, design, and construction similar to that implemented by the Leadership in Energy and Environmental Design program for buildings. Quantitative approaches are also used by airport operators to account for environmental metrics such as air pollutants, GHGs, and energy consumption. Various tools and reporting systems have been developed for carbon footprinting, while LCA implementations 89

2 90 Transportation Research Record 2603 are largely limited to case studies. For example, Airport Carbon Accreditation is an independent certification program initiated by the Airports Council International in 2007 to provide a common framework for GHG accounting for airports (6). In 2016, 10 North American airports (five in the United States) were accredited through the program and another 92 airports in Europe and 26 airports in Asia. To be accredited, airports must calculate their emissions by using GHG tools such as the Airport Carbon and Emissions Reporting Tool (7). This tool, first released in 2012, considers the following sources of emissions: airside vehicles, equipment, and machinery; on-site electricity and heat generation; purchased off-site electricity and heat; waste and wastewater; and aircraft activity. Another emissions estimating tool, Airport Construction Emissions Inventory Tool, was released in 2014 to model emissions from construction activities related to parking lots, terminal buildings, runways, aprons, taxiways, cargo buildings, and the like (8). Environmental Analyses of Airport Pavement The use of LCA to evaluate roadway pavements in the last two decades preceded the use of LCA to evaluate airport pavements. Airport and highway roadway pavements have a great deal in common (e.g., general materials, equipment, and life cycle), so reference to examples of roadway LCA is useful when LCA is being applied to airport pavement. In particular, various LCA tools for highway pavements have emerged in recent years [e.g., Al-Qadi et al. (9), Huang et al. (10), Mukherjee and Cass (11), and the Athena Impact Estimator for Highways (12)]. Initial LCA works that considered airport pavement were often within the context of a comparative LCA for different modes of transportation, including air. Stripple and Erlandson evaluated the life-cycle environmental impacts of airport infrastructure and aircraft operations from a Swedish airport as part of a larger study on road, rail, and air transportation (13). The study found that aircraft operations overshadowed airport infrastructure by contributing more than 90% of environmental impacts; within airport infrastructure, the greatest contributing components were airport operations, construction work, and electric power generation. Chester and Horvath argued for the need to consider relevant upstream processes and infrastructure in the environmental assessment of passenger transportation, including air, in addition to tailpipe or downstream emissions (14). For air transportation, they determined that 2% to 14% of the total life-cycle energy consumption resulted from nonoperational components, including upstream fuel production, vehicle manufacturing, and maintenance as well as infrastructure construction, operation, and maintenance. Lopes performed an LCA of an Airbus A aircraft (15). While most of that work focused on the manufacture and operation of the aircraft, Lopes also considered airport construction and maintenance by using default commercial inventory data. Infrastructure was seen to contribute more than aircraft manufacturing in relation to climate change, although it was still severely overshadowed by aircraft operation, which contributed 99.9% of the climate change impacts. Finally, Lewis also considered airport construction, operations, and maintenance in his environmental assessment of air passenger transportation (16). Lewis used an economic input output approach to determine the environmental contribution of infrastructure, which contributed between 0.4% and 2.1% for infrastructure construction and between 0.8% and 3.5% for infrastructure operations, figures that depended on aircraft type and functional unit. While these cited studies included airport infrastructure, they mainly focused on aircraft operations, with infrastructure as a supporting component. A handful of studies exist whose primary focus was airport pavement. Pittenger ranked the sustainability of various pavement treatments by using economic (life-cycle cost analysis), social (Greenroads), and environmental (raw material consumption) metrics (17). A weighted value was given to each treatment through a standard utility method that is based on expected service life per unit area. Giustozzi et al. evaluated a specific construction process to be used in airport pavement subbase layers involving the cement or lime stabilization of in situ soils (18). Only equipment-related emissions were considered and not material production, and it was determined that using in situ cement soil stabilization provided a 65% savings in GHGs compared with the use of virgin aggregates. Mosier et al. proposed the use of a carbon footprint cost index to measure the sustainability of airport pavements (19). This index is comparative in that it uses the difference in life-cycle cost between alternatives multiplied by the energy consumption of the alternative design of interest. A related study by Shen et al. performed a comparative LCA on two pavement maintenance techniques (geothermal heated pavement versus traditional snowplow blower and deicing) for snow removal on airport runways (20). Finally, an LCA study focusing specifically on airport pavements was performed in 2015 by Kulikowski (21). This study considered material production, construction, maintenance, and use of the pavement. An LCA tool was developed, and a case study was performed to compare three rehabilitation strategies for an airport pavement. Motivation Clearly, aviation industry and airport operators have taken measures to increase sustainability awareness, reporting, and practices in the last two decades. The use of qualitative and quantitative measurements of environmental sustainability is emerging in practice (i.e., in the form of sustainable rating systems and carbon accreditation) as well as in literature case studies. However, the use of a comprehensive, quantitative method such as LCA as an approach to sustainability measurement for airport pavements is still in its early stages. LCA has been used mainly for highway infrastructure or for air transportation as a whole, with a lesser emphasis on infrastructure. Thus, this paper addresses the research gap in application of LCA to airport pavements in such a way that also considers the uncertainty of the data used. As airport operators strive to set and obtain sustainability goals for their airports, the use of LCA to measure the environmental impacts of their airport pavements systematically and quantitatively will be a valuable asset. Method Goal and Scope The life-cycle analysis for this paper was performed in accordance with LCA guidelines in the ISO series (3). The intended audience for this study is airport operators, designers, and contractors who are interested in the use of LCA to evaluate the environmental sustainability of their airport pavements. This study is a stand-alone attributional LCA study that calculated the environmental burdens directly associated with the life cycle of the product system

3 Yang and Al-Qadi 91 (i.e., airport pavement). A partial life-cycle approach was used in this study, which considered the materials and construction of the product system. The functional unit used in this work was 1 yd 2. Typically, environmental impacts are normalized over the spatial and temporal dimensions of the project, but in this case, only the initial construction was considered, so the temporal dimension was in essence 1 year. The product system included the mainline, shoulders, and all pavement layers, excluding lighting, signage, drainage, landscaping, and other supporting elements. The system boundaries of the study, shown in Figure 1, include processes from the production of materials as well as construction. The use, maintenance, and end-of-life stages were considered beyond the scope of the work but should be considered in future work to extend the study from a partial to a full life-cycle analysis. In addition, any delays attributable to initial construction were removed from the scope and assumed to be negligible for the new runway construction analyzed in the case study. In this study, LCI data were obtained from secondary sources, including a commercial database that provided a comprehensive set of upstream processes. Key assumptions were made in relation to cut-off rules for upstream and downstream processes. Upstream infrastructure impacts were not included (e.g., construction and maintenance of plant facilities, manufacture and upkeep of equipment). In the construction stage, only impacts related to fuel production and combustion in different types of equipment were considered. Additional emissions, such as dust particulates from material handling and laying, were beyond the scope of this study. Any processes related to worker commuting and human labor were not considered. Finally, a cut-off allocation method was chosen for recycled materials such as recycled asphalt pavement (RAP), recycled asphalt shingles (RAS), and recycled concrete aggregate. Thus, only the environmental burdens directly associated with processing recycled materials were attributed to the recycled material; environmental burdens associated with producing the original material were not allocated to the recycled material. This LCA study considered total primary energy (TPE) consumption and GHGs. TPE consumption (or cumulative energy demand) included primary energy used as fuel, in addition to that used as material (e.g., plastics and asphalt binder, which are petroleum products that contain embodied energy). The impact assessment methodology used to calculated GHGs was the Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts developed by the U.S. Environmental Protection Agency (22). Data Collection and Assessment In this LCA study, the data used to determine environmental impacts of various processes largely come from secondary sources, such as literature, reports, software, and commercial databases. The LCI software SimaPro was used to model the processes along with the Ecoinvent 2.2 database (for the United States) (23). In general, secondary sources were used to determine major activitylevel data (i.e., amount of fuel and raw materials), which were then modeled by using corresponding unit processes in SimaPro to ensure that upstream materials and resources were taken into consideration. The quality of the inventory data was assessed by using the six parameters used by Ecoinvent: completeness, reliability, geographical correlation, temporal correlation, further technological correlation, and sample size (24). While Ecoinvent assigns these values at the emissions level, this study assigned the data quality at the unit process level. Thus, a geometric standard deviation was calculated for each unit process by means of the procedure used by Ecoinvent so that the lognormal distribution of its environmental impacts can be quantified (24). A summary of the unit processes modeled in this study, along with corresponding data sources and geometric standard deviations, appears in Table 1 (25 35). The unit processes listed in Table 2 were modeled to represent as closely as possible the case study about a 2015 runway construction in Illinois. The processes related to asphalt materials (i.e., prime and tack coats and asphalt binder) were developed on the basis of a model representing petroleum production in the U.S. Midwest (25). The processes for production of both portland cement and natural and manufactured aggregate and for ready-mix concrete plants were modeled from inventory collected by the Portland Cement Association and meant to represent the U.S. industry (27). Various default processes from the Ecoinvent database were used when insufficient secondary data were found; this information included processes related to steel production, trucking, and lime production (23). The production of admixtures were taken from a set of environmental product declarations from the European Federation of Concrete Admixture Associations (23 30). The data used to model hot-mix asphalt and warm-mix asphalt plant operations were taken from information by the National Asphalt Pavement Association in the United States (34). Finally, environmental impacts related to off-road vehicle operations were modeled from simulations generated with the U.S. Environmental Protection Agency s MOVES2014 software, for SYSTEM BOUNDARY Construction Construction Construction TRP TRP TRP Production Raw Materials Recycled Materials TRP Construction Use Maintenance Fuel Performance of Pavement Albedo Routine Maintenance Minor Repairs End-of-Life Recycling Landfill TRP Plant Operations Delays Carbonation Rehabilitation FIGURE 1 System boundaries of LCA study (TRP = transportation).

4 92 Transportation Research Record 2603 TABLE 1 Summary of Unit Processes Unit Process Unit Data Source GSD Prime coat T Tack coat T Asphalt binder T PCC T Natural aggregate T Manufactured aggregate T Steel T Lime T Fly ash T RCA from PCC runways T RAP T Assume same as RCA RAS T Assume same as RCA Lime kiln dust T Assume negligible na Water-reducing admixture oz Water-retarding and -reducing admixture oz High range admixture oz Air entraining admixture oz Ready mix concrete plant yd HMA plant T WMA plant (foaming) T Trucking T-mi Various equipment (diesel) gal 23, Various equipment (two-stroke gasoline) gal 23, Various equipment (four-stroke gasoline) gal 23, Note: GSD = geometric standard deviation; T = short ton; PCC = portland cement concrete; RCA = recycled concrete aggregate; HMA = hot-mix asphalt; WMA = warm-mix asphalt; T-mi = short ton mile. which the simulation parameters reflected conditions found in Cook County, Illinois, the location of the case study (35). Development of LCA Tool A tool to facilitate the implementation of LCA for the case study as well as for future analyses was developed in Microsoft Excel by using Visual Basic for Applications. The framework of the tool is shown in Figure 2 and is implemented through a series of graphical user interfaces. With the tool, the user begins a project that can include a variety of construction activities. These activities can be major activities occurring during initial construction as well as future maintenance and rehabilitation as needed. For each activity, the user then specifies details about the activity, such as the cost and year performed, as well as the materials, equipment, and plant operations required. For those last three components, the user selects unit processes from the LCI database (e.g., asphalt binder) and indicates the quantity of the material or fuel usage of the equipment needed as well as the hauling or mobilization distance. The results of the project are calculated in a similar top-down method. Deterministic results for TPE consumption and GHGs are calculated by using the expected (mean) value of the environmental impacts. Probabilistic results for the environmental impacts are obtained through the Monte Carlo method and the lognormal distributions of the environmental impacts for each unit process selected (Table 1). TABLE 2 Statistical Analysis of 1,000 Monte Carlo Simulations for Original and Modified Projects Environmental Impact Case Mean Standard Deviation 95% Confidence Interval TPE (MJ/yd 2 ) Original to 480 Modified to 690 GHG (kg CO 2 e/yd 2 ) Original to 37.3 Modified to 53.7 Case Study Background The case study chosen for this work covered the newly constructed 10R-28L runway at Chicago O Hare International Airport. The 10R-28L runway, which opened in October 2015, is part of a $6.6 billion series of infrastructure projects known as the O Hare Modernization Program, which began in The runway is 13,000 ft long and 150 ft wide with shoulders 35 ft wide. The original contract

5 Yang and Al-Qadi 93 Project Activity Activity Activity Cost, Year, etc. Materials Plant Operations FIGURE 2 Framework of LCA tool. also includes connecting taxiways that are 35 ft wide as well as associated lighting and signage, but the case study focuses specifically on the runway. The mainline and shoulder pavement designs are shown in Figure 3. In the mainline design, the portland cement concrete contained approximately 23% fly ash. The subsequent bituminous concrete base was made by using a WMA foaming technique and contained approximately 20% RAP and 2.5% RAS. The asphalt-treated permeable base was hot-mix asphalt with approximately 5% RAP and 2% RAS. Lime kiln dust was used to stabilize the subgrade. In the shoulder design, WMA was used for both the bituminous concrete surface and base layers, the former of which had approximately 16% RAP and 2.5% RAS. The aggregate subgrade consisted of crushed concrete from previous PCC runways at O Hare. The actual hauling distances of raw materials to the on-site plants were obtained for each of these mix designs. In addition to information on the mix designs, data were also collected about fuel usage for the contract. Fuel usage was collected on a daily basis, but the activities covered by the contract could not be assigned to individual pieces of equipment with any certainty. Thus, because of the significance of the runway work, the authors assumed that all fuel used during the days in which major construction work on the runway was scheduled (May 21, 2014, to January 21, 2015) was attributed to the 10R-28L runway. This assumption likely overestimated the amount of fuel allocated to the runway construction included in the system boundaries, as other activities such as lighting and signage installation were also taking place at that time. Deterministic Environmental Analysis The deterministic results of the LCA are discussed in relation to the functional unit: 1 yd 2. Figure 4 shows a breakdown of the environmental impacts of the analysis by material production (including transportation to site) of various structural components as well as construction. The components in Figure 4 are ordered structurally for the mainline and shoulder from bottom to top, which is also the order in which environmental impacts generally increase. This order results because the binder amounts (i.e., asphalt binder in the asphalt-treated permeable base, WMA base, and portland cement in PCC) increase in the upper layers of the pavement and the production of these binders has a high environmental impact (i.e., a large amount of energy is required to extract and refine the asphalt for the binder from crude oil). The TPE reported includes the feedstock energy, which is up to seven times the process energy needed to produce the binder (25); however, the method of reporting feedstock energy is currently debated within the pavement industry. In contrast, portland cement requires a great deal of energy to produce in a kiln, but it also emits large amounts of carbon dioxide through the calcination process. Thus, the combined hot-mix asphalt products (i.e., asphalt-treated permeable base, WMA base, and WMA surface) tend to have higher relative TPE consumption contributions, while PCC has a higher relative GHG contribution. The lime-stabilized subgrade and recycled concrete aggregate subbase have small contributions, as the materials used in these processes are byproducts (i.e., lime kiln dust) or recycled 17-in. PCC 6-in. Bituminous Concrete Base 3-in. Bituminous Concrete Surface 4-in. Bituminous Concrete Base 6-in. Asphalt-Treated Permeable Base 20-in. Aggregate Subbase 12-in. Stabilized Subgrade FIGURE 3 Runway 10R-28L pavement designs for mainline and shoulders.

6 94 Transportation Research Record 2603 FIGURE 4 Impacts from production of various structural components and from overall construction of runway on TPE consumption and GHGs (ATPB = asphalt-treated permeable base). materials (i.e., recycled concrete aggregate). Finally, the production and combustion of fuel used during the construction of the runway itself comprise less than 2% of the total TPE consumption and GHGs. Figure 5 shows a more detailed breakdown of the individual unit processes that compose the project analysis. The major processes contributing to TPE consumption and GHG emissions are the production of portland cement, asphalt binder, and aggregate as well as operation of asphalt and PCC plants. Again, the percentage contributions of portland cement and asphalt binder are not the same for TPE consumption and GHGs because of reasons already noted. TPE consumption and GHGs from plant operations differ because asphalt plants in Illinois largely use natural gas, which emits less GHGs than other fossil fuels when consumed. The Other category in Figure 5 includes the production of admixtures, tack coat, and lime kiln dust (transportation only). FIGURE 5 Contribution of various material production processes and equipment usage in runway construction to total TPE consumption and GHGs.

7 Yang and Al-Qadi 95 FIGURE 6 Monte Carlo simulation results of original project for TPE consumption and GHGs. Probabilistic Environmental Analysis While a deterministic analysis allows for a detailed evaluation of both the project and its individual components, the use of deterministic results to compare alternative designs does not allow for incorporation of the pervasive uncertainty inherent in most LCA studies. Uncertainty may arise in the LCA process from upstream and downstream inventory data as well as through incomplete information and assumptions. Thus, the use of a stochastic method to compare LCA results gives a more holistic perspective that incorporates uncertainty. In this study, 1,000 Monte Carlo simulations were run to incorporate uncertainty of LCI data in analyzing the 10R-28L runway project. Figure 6 shows the results of the simulations for TPE consumption and GHG emissions per square yard, and the results appear to be normally distributed. In addition to analyzing individual projects, probabilistic LCA also provides a more comprehensive perspective when used to compare pavement systems. In this study, a recent 2015 runway construction project was analyzed; that project included various sustainable strategies such as the use of recycled material and warmmix technology. A modified project that did not include these sustainable strategies was also analyzed. Recycled concrete aggregate was replaced with manufactured aggregates; the aggregate portions of RAS and RAP were replaced with manufactured aggregates; and the recycled asphalt binder content was replaced with virgin binder. The WMA plant operations used to model the WMA base and surface mixes used in the pavement were replaced with hot-mix asphalt plant operations. Finally, the fly ash used in the PCC slabs was replaced with virgin portland cement. Thus, one-to-one substitutions were made, as was the assumption that the modified mixes had the same functionality as the original mixes. Figure 7 shows the distribution of the 1,000 Monte Carlo simulations for the original and modified mixes. In addition, a summary of the major statistical properties of the distributions is given in Table 2. A two-sample z-test provided strong evidence that the means of the two samples were significantly different, with the original case incurring less environmental impacts for both TPE consumption and GHGs. The z-statistics were approximately 100 for both TPE and GHGs because of the large sample size; thus, the p-values were much lower than.001. In this case, the two samples examined were extremes and thus provided more straightforward comparisons: one sample incorporated sustainable strategies, while the other replaced major sustainable strategies with those that were expected to result in more environmental impacts. In addition, only initial construction was included in the scope of this work. In future work, this type of probabilistic LCA comparison can be valuable for more competitive Probability Probability TPE (MJ/yd 2 ) GHG (kg CO 2 e/yd 2 ) FIGURE 7 Probabilistic results of original and modified projects for TPE consumption and GHGs.

8 96 Transportation Research Record 2603 alternative designs and for considering the entire life cycle, including future maintenance and rehabilitation. also thank Ross Anderson and Casey Venzon for their help in relation to the 10R-28L runway at Chicago O Hare International Airport. Summary The main objective of this study was to evaluate the environmental impacts of airport pavement construction by using a life-cycle approach. A tool was developed to facilitate the implementation of LCA by means of various secondary inventory sources to model various production and construction processes. In addition, uncertainty distributions were assigned to each unit process to allow for a probabilistic aspect in the LCA. A case study evaluated the TPE consumption and GHG emissions from the construction of Runway 10R-28L at Chicago O Hare International Airport. The evaluation showed that the environmental impacts from producing materials for the pavement increased from lower to upper layers because of the increase in asphalt binder and the use of portland cement closer to the surface in the pavement structure. In general, the asphalt layers had a relatively higher TPE consumption than the PCC layer because of the feedstock energy in the asphalt binder, while the PCC layer had relatively higher GHGs than the asphalt layers because of the calcination required in the production of the portland cement. A breakdown of the individual unit processes showed that the production of asphalt binder (45.3%) and of portland cement (29.2%) was the largest contributor to TPE consumption, while the former (73.4%) was by far the leading contributor of GHGs to the project. The impacts from construction activity itself were less than 2% for both TPE consumption and GHGs. A probabilistic analysis was conducted by using the 1,000 Monte Carlo simulations to consider the uncertainty of the LCI used in the LCA. A comparison of the probabilistic analyses of the original 10R-28L design and a modified design that did not use recycled materials or WMA technology showed that the impacts from the two projects were significantly different. The mean TPE consumption for the original project was 482 MJ/yd 2 compared with 693 MJ/yd 2 for the modified project, while the GHG emissions were 37.5 kg CO 2 equivalent per square yard for the original project compared with 53.9 kg CO 2 equivalent per square yard for the modified project. This study considered the first stages of an airport pavement life cycle: material production and construction. Future work should consider maintenance, rehabilitation, use, and the end of life of the pavement and should include the pavement s expected performance. However, even with a partial life-cycle implementation, the methodology, inventory data, and tool developed in this work can be directly used by airport operators and stakeholders. The LCA tool allows for a streamlined, probabilistic analysis of the environmental impacts related to the material production, pavement construction, and future maintenance activities on an airport pavement system. Users of the tool will be able to obtain quantitative results about the environmental footprints of past, present, and future airport pavements, better informing the holistic management of their pavement systems to contribute ultimately to more sustainable airport infrastructure. Acknowledgments This work was sponsored by the Airport Cooperative Research Program through a Graduate Research Award. The authors acknowledge Eric Amel, Larry Goldstein, and Dominque Pittenger for their guidance and investment in this research. In addition, the authors References 1. Industry Statistics. Fact Sheets. 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