Verification of Performance Standards for Construction Equipment in Terms of CO₂ Emissions

Abstract

Almost every civil engineering project involves heavy construction equipment to create earthworks. This in turn is connected with carbon dioxide emissions, which are hazardous to the environment, especially in densely populated areas. Strict control and regulation of emissions from construction equipment has already been introduced in Hong Kong. This paper presents the results of several years of field research on the performance of construction equipment (excavators). The comparative analysis concerns the data obtained during a field survey in relation to the outlays proposed in the catalogues of material outlays commonly used in Poland (KNR catalogues.) The presented problem fills in the gaps in research on the performance of construction equipment. The results of the study clearly show the discrepancy between theoretical data from the KNR and the actual use of construction equipment during the construction of underground sanitary networks. Apart from the excessive consumption of diesel fuel, sequentially increased CO₂ emissions occur. The presented research results allow for the development of an innovative method for the optimal use of heavy construction equipment, thus reducing CO₂ emissions. This study is a continuation of a pilot study conducted by the staff of the Institute of Civil Engineering, Warsaw University of Life Science.

1. Introduction

Construction equipment causes significant emissions of greenhouse gases and air pollutants during construction of infrastructure such as earthworks, roadwork, and line construction work. Many of these pollutants are related to the operation of heavy equipment designed to construct earthworks. Emissions of carbon dioxide and pollutants from the combustion of diesel fuel by construction equipment are a growing global concern. A considerable number of countries have implemented standardization processes for the legal requirements that construction equipment should meet in terms of CO₂ emissions. Heavy diesel-powered construction equipment emits toxic pollutants, including NOx, HC, and particulate matter, as well as CO₂. Thus, it is important to recognize the cost-effectiveness of replacing old construction equipment with a new equipment with better “emissions” performance. At present, toxic emissions into the atmosphere can be measured, among other things, based on specific emission factors, modified by load factors, operating time, equipment wear, etc. However, the emission factors themselves may depend on the year the equipment was manufactured, engine power, and the degree of engine wear [1,2]. This type of data is somewhat theoretical, and only field measurements can bring researchers closer to defining real CO₂ emission levels [1,2].

The process of CO₂ emissions has been discussed in many sources. Fan [3] addressed carbon dioxide emissions from diesel-powered construction equipment. Barati and Shen [4] presented an operational-level model to estimate emission rates of carbon monoxide (CO), carbon dioxide (CO₂), hydrocarbons (HC), and nitrogen oxides (NOx) from road construction equipment, in which the data collection procedure included instrumentation, laboratory tests, and field measurements. Finally, the authors verified the model by comparing the estimated results with actual data collected by the PEMS and engine data logger in field experiments. Subsequently, Barati and Shen [5], in order to study the effect of construction equipment operating parameters on exhaust emissions, conducted least-squares (OLS) and multivariate linear regression (MLR) analyses. The analysis of the results shows that as the equipment’s payload and road slope increase, its exhaust emissions increase significantly, while the optimal driving speed is correspondingly lower. A model for predicting the CO₂ performance of crawler excavators and dump trucks using multiple regression and neural network methods is also presented in the Rogalska and Hejducki paper [6]. On the other hand, Runkiewicz [7] presented an original point of view on the implementation of construction equipment in accordance with the principles of sustainable development. The researcher in his work emphasized that economic development contributes to the violation of the balance prevailing in the environment. To reduce this negative impact of economic development on the environment, the concept of sustainable development was proposed, that is, development that guarantees satisfaction of the needs of the current generations without limiting the ability of future generations to meet their needs.

The new trend of looking at sustainable engineering in urban design, which includes catchment planning, green building, optimizing water reuse, reclaiming urban spaces, green street initiatives, and sustainable urban planning, was presented by Sarte in [8]. In addition, the paper by Wieczorek and Zima [9] presented the analysis of the selection of materials for road construction with consideration of carbon footprint and construction costs, as well as an integrated analysis of the cost and amount of greenhouse gas emissions over the life cycle of a building. The literature also shows research by Golanski on CO₂ emissions regarding building materials and their selection in [10] in the terms of sustainability presented by Rogalski and Hejducki [11]. Additionally, topics related to sustainability and CO₂ emissions are in sources [12,13,14,15,16]. However, there are few studies from actual construction processes in the literature, particularly from Polish sites [17]. Therefore, according to the authors, analyses and studies that are based on actual measurements during construction projects should be of key importance.

The paper aims to supplement the present research, proceeding from a literature search, and to point out that a major problem of the parties involved is a lack of data which would enable us to accurately predict the performance standards for construction work. The paper also verifies the compliance of the currently available performance standards for construction equipment with the Polish workload (KNR) and if CO₂ emissions resulting from diesel fuel consumption are consistent with actual data obtained during construction work. Consequently, the researchers present the results of several years of field research on the performance of construction equipment (excavators).

The article describes previously unpublished research results on the efficiency of construction equipment in the construction of underground sanitary networks.

It is worth noting that the problem presented herein is not local and may be dealt with differently in different countries be due to various local regulations, guidelines, or standards. In Poland, the catalogues of material outlays, such as KNR, KSNR, etc., are commonly used, although they are not obligatory, while in other countries there may be different types of classifications of works or other methods of evaluating works. According to Tomczewski et al. [18], in the United States there are classifications of works from 1948 (MasterFormat), 1993 (Uniformat), and the currently developed OmniClass. There are five classes adopted for determining the value of construction works at various stages of preparation and implementation of the project—from class five, characterized by the accuracy of the valuation (+/−20%), to classes 1 and 2, which are equivalent to our detailed cost estimate and developed with high accuracy (+/−5%). Interestingly, in some calculations, there is a distinction between union and labour rates. It should be noted that many elements of the cost estimation process in the US coincide with their Polish counterparts. They are distinguished by the consistent classification of works in the US, which allows for standardization of cost estimates and specifications and makes the design and cost estimate documentation for each project predictable and easier to manage. The existence of extensive (incomparable to Polish) price catalogues, cost estimation programs, manuals, guidelines, and specimen specifications is immensely helpful. On the other hand, Rogoda [19] presented the structure of costs and degrees of calculation of construction investments in Germany and the methods of calculation of construction works used by our neighbour. In addition, the paper discusses the standard layout of the pre-tender of works—STL-Bau as a basis for preparing cost estimates and cost estimation programs based on DBD-Daten—Dynamic Construction Data. The paper shows that the German system of cost estimation of works is based on several particularly important standards, which include:

• model cost structure according to DIN 276,
• standard for dynamically created descriptions of works—STLB-Bau—Dynamische BauDaten,
• standard technical specifications defining the transfer to the contractor of the necessary information about construction products, local conditions for the execution of works, or rules of pre-timing/timing and billing—VOB (C),
• standard formats for data exchange between participants in the construction process—GAEB.

Cost estimation of construction works in China and Mongolia is described by Sekunda in his work [20]. According to his research, the valuation of works in these countries is based on the use of a normative base of material inputs—labour, materials and equipment or integrated inputs, and price bases for specific industry works legislated. The costing process in China originates from local standardization achievements, although its roots are in the period of cooperation with the USSR. In the Far East, due to the rapidly developing economy, the processes of investment valuation at the stage of both investment preparation and settlement are constantly changing. BIM-based projects are also introduced there (albeit slowly and with great reluctance, due to the legacy of the communist economy) [21,22].

Kulejewski [23] emphasizes that the basic method of costing in the countries of the European Union is simplified, and it involves the use of unit prices for construction works. In the costing calculation prepared for the needs of the ordering party, unit prices of works are usually adopted based on relevant guides to market prices in construction. Contractors, on the other hand, calculate unit prices for works based on costing.

The valuation of construction works in Ukraine is carried out on the basis of the “Instruction for determining the cost of construction”. It is up-to-date and mandatory for use in the construction industry. The instructions define the basic rules for the application of costing and price norms in the construction industry for determining the cost of construction. The price system in construction is based not only on costing norms, but also on costing indexes and current prices of labour, technical and material resources [24].

The cost of using construction machinery and mechanisms is determined by the standard time of their use, the requirements to perform the scope of construction work specified in the design documentation, and the cost of using construction machinery and mechanisms per unit time of their use (machine–hour) in current price.

According to Kulejewski [23], cost estimating standards can be established in several ways:

• Use of normative documents that provide guidance and recommendations on the labour intensity of a construction work. For example, in Ukraine, there are the regulations of the State Construction Standards, which contain information on productivity standards for different types of work.
• Analysis of completed construction projects in which similar types of work were performed. An assessment is made of the time required to perform a certain amount of work, and performance standards are formulated on this basis.
• Use of expert evaluation. Experts can estimate the performance of different types of works based on their experience and knowledge.

2. Materials and Methods

To collect research material, the authors conducted a field study. As research material, data from an investment implemented in 2018–2023 were used. The scope of work was divided into individual tasks, where task 1 consisted of construction of a sewage pumping station with a capacity of 39 l/s, pressure sewers D 250 L 1459 m, sanitary sewers Dn 0.2 L ca 1218 m, Dn 0.4 L 98.87 m, Dn 0.3 L 35.58 m, water pipe, reconstruction of a gas pipeline Dn 40 PE steel medium pressure to Dn 63 PE 100 SDR 11 with a length of L 74 m. Task 2 included construction of sanitary sewer network DN 200 mm L ca 348 m. Task 3 included execution of sanitary sewer network DN 200 mm L ca 75 m. The investment was carried out in the city of Warsaw.

The research began on the day the equipment was moved to the site. Data from 4 June 2018 initiated the process of data archiving. The data acquisition process was staggered, as the execution stage of the work was extended for reasons beyond the contractor’s control.

For archiving, a spreadsheet (progress report of works with resource consumption) was first developed, which was designed in such a way as to record data with highest possible level of accuracy. This spreadsheet was made available to the executives implementing the construction project under the study via the Works Contractor’s server. The researchers had continuous online access to the archived field data. Due to the quality of the archived material, it was decided to enter the data daily.

In order to compare the results from the field survey against the assumptions regarding the theoretical performance of construction equipment, the researchers developed a quantity survey of works according to KNR guidelines using the software of the most popular cost estimation program on the Polish market, which is Norma Pro.

The process of developing the comparative material was established in accordance with the widely used Polish standards of bills of quantities [25], according to which the bill of quantities should include pre-measurement items corresponding to the basic works. The quantity sheet does not contain temporary works and services and includes all works that, according to KNR costing, require the use of construction equipment in the form of excavators. Thus, the following works were analysed: earthworks directly related to the implementation of the sanitary sewer network with connections to property boundaries, earthworks for the foundation of the sewage pumping station chamber, the gate valve chamber and pressure sewers and the reconstruction of the water supply network. In addition, the road scope was included in the list of quantity survey of works.

Subsequently, carbon emission simulation calculations were carried out based on the collected data. A calculation example was made based on the resulting difference in the equipment work, measured in horsepower hours, between the amount created from KNR catalogues and field data.

3. Results

Table 1. Data from the field survey (own research).

No.	Type of Equipment	Excavator Model	Number of Moto Hours [m-h]	Amount of Fuel Consumed [dm3]	Average Diesel Consumption [dm3/m-h]
1	Wheeled excavator (CAT 318F)	CAT 318F	1876.00	11,425.00	6.09
2	Wheeled excavator (Doosan 190W-5, No. 2)	Doosan 190W-5 (1)	1824.00	11,998.00	6.58
3	Tracked excavator (CASE CX210 B)	CASE CX210 B	939.00	8479.00	9.03
4	Wheeled excavator (CASE WX185)	CASE WX185	511.00	5412.00	10.59
5	Backhoe loader (CASE 695)	CASE 695	89.00	550.00	6.18
6	Wheeled excavator (Doosan 160 W-5, no 3)	Doosan 160 W-5	289.00	1815.00	6.28
7	Wheeled excavator (Doosan 190W-5, No. 1)	Doosan 190W-5 (2)	138.00	620.00	4.49
8	Wheeled excavator (Doosan DX 210W-5 Dx 210W-5)	Doosan DX 210W-5 Dx 210W-5	575.00	3679.00	6.40
9	Wheeled excavator (Komatsu PW200)	Komatsu PW200	515.00	5216.00	10.13
10	Wheeled excavator (Doosan Dx190W-5 DX-190 W-5, No. 4)	Doosan Dx190W-5 (3)	60.00	640.00	10.67
11	Tracked excavator (Doosan DX85R-3)	Doosan DX85R-3	206.00	1483.20	7.20
Total			7022.0	51,317.2	-

shows direct data from the field survey in terms of actual equipment operating hours during the implementation of the project under study and diesel fuel consumption.

Table 2. Physical outlays according to the KNR.

No.	Type of Equipment	Number of Moto Hours [m-h]	Assumption of Fuel Consumption [dm3/h]	Assumed Amount of Fuel Consumed [dm3]
1	Wheeled excavator 0.60 dm3	1683.02	6.09	10,249.61
2	Crawler dozers	559.22	10.67	5966.88
3	Mobile crane 4 t	404.82	6.58	2663.73
4	Manual winch 3–5 t	808.20	4.49	3628.94
Total		3455.29	-	22,509.15

below shows the number of man-hours quantified on the basis of the KNR. It should be noted that due to their presence during field observations (where the use of an excavator for other activities was identified), the researchers also included items such as a backhoe dozer, truck crane, and hand winch in the analysis. These assumptions are necessary for the comparative analysis because, as found during the field survey, the contractor did not mobilize construction equipment other than excavators for the work in this area. For example, the dismantling of the road system (substructure) along the route of the excavation was carried out with an excavator and not a crawler dozer as suggested by the KNR. The identical situation applies to the vertical transport of materials (in this case, pipes and sewer wells) into the excavation. For this purpose, too, an excavator was used instead of a crane or hand winch (proposed according to the KNR).

Since the KNR does not provide specifications for construction equipment (the type of excavator, horsepower, year of manufacture, etc.) or the amount of diesel fuel burned, for analysis purposes it was assumed that the average diesel fuel consumption of the various machines proposed by the KNR would be at the level derived from the field survey. Finally, it was assumed that single wheeled excavator consumed fuel at the rate of 6.09 dm³/m-h; crawler dozers 10.67 [dm³/m-h]; mobile crane 4 t = 6.58 [dm³/m-h]; and hand winches 3—5 t: 4.49 [dm³/m-h]. The authors are aware of the simplifications made in this step; however, the paramount goal within the framework of this study is to demonstrate the differences in the proposed inputs according to the KNR in terms of motor hours and the actual field measurement.

Equation (1) was used to calculate probable CO₂ emissions, and the results are shown in

Table 3. CO₂ emissions in terms of actual construction equipment operation (own research).

No.	Type of Equipment	Total Amount of Fuel Consumed [dm3]	Assumption CO2 Emission from Burning 1 dm3 Diesel Fuel	CO2 Emissions [kg] CO2
1	Wheeled excavator (CAT 318F)	11,425.00	2.67	30,619.00
2	Wheeled excavator (Doosan 190W-5, No. 2)	11,998.00	2.67	32,154.64
3	Tracked excavator (CASE CX210 B)	8479.00	2.67	22,723.72
4	Wheeled excavator (CASE WX185)	5412.00	2.67	14,504.16
5	Backhoe loader (CASE 695)	428.00	2.67	1147.04
6	Wheeled excavator (Doosan 160 W-5, no 3)	1815.00	2.67	4864.05
7	Wheeled excavator (Doosan 190W-5, No. 1)	442.00	2.67	1184.56
8	Wheeled excavator (Doosan DX 210W-5 Dx 210W-5)	3679.00	2.67	9859.72
9	Wheeled excavator (Komatsu PW200)	5216.00	2.67	13,978.88
10	Wheeled excavator (Doosan Dx190W-5 DX-190 W-5, No. 4)	743.00	2.67	1991.24
11	Tracked excavator (Doosan DX85R-3)	641.00	2.67	1717.88
			Total	134,744.89

and

Table 4. CO₂ emissions for planned construction equipment (own research).

No.	Type of Equipment	Assumption of Amount of Fuel Consumed	Assumption of CO2 Emission from Burning 1 dm3 Diesel Fuel [kg]	CO2 Emissions [kg]
1	Wheeled excavator 0.60 dm3	10,249.61	2.67	27,366.45
2	Crawler dozers	5966.88	2.67	15,931.56
3	Mobile crane 4 t	2663.73	2.67	7112.17
4	Manual winch 3–5 t	3628.94	2.67	9689.26
			Total	60,099.44

. For the purposes of the analysis, CO₂ emissions from burning 1 dm³ of diesel fuel were assumed to be 2.67 kg of CO₂ [26].

Fuel consumption × emissions from burning 1 dm³ of diesel fuel = Total emissions

(1)

Figure 1 shows fuel consumption according to field survey data (Table 2 and Table 3).

As a consequence of the calculations, a significant difference was obtained between planned and actual CO₂ emissions. Equation (2) was used for the calculations:

Actual emissions (134,744.89) − Planned emissions (60,099.44) = 74,645.45 [kg CO₂]

(2)

Result Overrun = 224%. Figure 2 shows the carbon emission of construction equipment according to the field survey data (Table 3).

4. Discussion

It is possible to predict the carbon dioxide emissions of a set of earth-moving machines using analytical methods such as neural networks, as described by Rogalska [6] and Hassanean et al. [27]. The researchers used data from the Catalogue of Labor Standards 2-01 for their calculations. The author analysed tracked backhoe, backhoe, scraper and grapple excavators. Only the amount of fuel consumed was estimated based on data from the construction company. Chlopek [28] in his research introduced the concept of emission characteristics of internal combustion engines operating under dynamic conditions. The proposed solution refers to the emission characteristics of automotive engines under dynamic conditions. Kryzia et al. [29] attempted to apply three different types of solutions to the research problem, which were fitting linear and nonlinear models, modelling with network and clustering methods using fuzzy logic algorithms, and Monte Carlo simulation. Shahnavaz and Akhavian [30] created their model based on machine learning (ML) methods to predict the level of emissions from heavy construction equipment. Subsequently, Lee et al. [31] defined the aim of their research as a comparison of emission regulations and the validity of the emission factors applied as inputs of the air pollutant inventory.

Unfortunately, most of the analyses presented in the literature are numerical studies not supported by comprehensive field surveys. Therefore, the data presented in this paper should be treated as innovative, for the purposes of planning branch works, such as sanitary underground networks. The use of predictive models requires data that are as close as possible to real data measured in the past, which the authors did during their research.

A common method for determining excavator productivity is interpolation of KNR data. However, as demonstrated in the article, this is not a valid method due to the lack of simple linear or polynomial relationship between, for example, excavator bucket capacity and productivity. In this paper, the authors show that the KNR inputs, which in most cases are used to calculate the outlays of construction equipment, do not always correspond to the quantities actually used during construction projects. Given the increasingly stringent regulations that apply to the emission of harmful gases throughout the European Union, it seems important to reliably forecast CO₂ emissions.

The authors are aware of the simplifications made in calculating CO₂ emissions (e.g., the lack of use of specialized sensors to measure emissions mounted on construction equipment), so they leave this problem for further research and analysis which will be presented in later publications. There is also the need to introduce many changes in Poland regarding not only the preparation and implementation of investments, but also the approach to cost planning and accounting of construction works.

It should be noted that the performance of construction equipment, in addition to CO₂ emissions in a significant way, has a direct impact on the budget plan of a given investment.

5. Conclusions

The authors found that during the contract under review there was a significant over-utilization of construction equipment. Thus, a greater amount of diesel fuel was used, which consequently led to significant carbon dioxide emissions.

Assuming that the baseline CO₂ emissions will be equivalent to the KNR data, then in the case of the analysed contract the increment from the baseline is within 224%. Such a large value of the exceeded CO₂ parameter clearly indicates that the topic covered in this article should be extended to other studies, since diesel-powered construction equipment is a major source of greenhouse gas and exhaust emissions at the stage of construction.

This article presents a comprehensive framework for measuring data on carbon dioxide emissions from the construction equipment. A model for estimating emissions at the operational level was developed by the direct analysis of collected field data. The results of the model show that the starting material for deconstructing CO₂ emissions should be diesel fuel consumption data, correlated with the amount of equipment operation measured in horsepower.

A critical review and analysis of the literature shows that there is no method available on the market with which to develop optimization plans for work with heavy construction equipment on interdisciplinary investments such as those involving the implementation of underground sanitary networks with associated works.

In addition, an in-depth analysis of the literature revealed a lack of previous studies on determining actual carbon dioxide emissions directly during sanitary sewer construction, particularly field (in situ) studies. Thus, the authors began a multi-year period of filling the resulting research gap, which should be considered a novel approach to the procedure of analysing emissions of harmful substances into the atmosphere during construction projects. The final stage of the research will be the development of a method for optimizing construction processes in the context of minimizing emissions of harmful substances into the atmosphere.