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Discuss about the impact of carbon dioxide emissions from transport infrastructure engineering construction work in Australia.

Research Aims

It has been observed that increase in the anthropogenic “greenhouse gases (GHGs)” is identified to be responsible for the increase in the global surface temperatures in the last 100 years. The annual emissions of the CO2 which is most significant with the more than 80% of GHG emissions in Australia. The on-site and the off-site construction activities or transport project are seen to be the major contributors for the GHG emissions. Moreover, the transportation Administration agencies of the countries have also worked towards reducing the infrastructure projects to zero by 2050. Despite of these, the present assessment for life-cycle is considered with several approach for estimating the GHG emissions which is seen to be independent and static in nature and do not account for dynamics of construction. The important consideration of the present study aims to explore the extent to which transport infrastructure had increased carbon dioxide emissions in Australia (Data.worldbank.org, 2018).

The main extent of the research has been depicted with performing exploratory research thereby formulating a deduction method which will be implemented to depict the feasibility study and design stage for the various types of identified problems of the present situation. Some of the main project life-cycle has been considered with investigations on the data available for CO2 emissions from World Bank and comparing the same with the carbon dioxide emissions from the transportation infrastructures (Chen, Wiedmann, Hadjikakou, & Rowley, 2016). Some of the important structure of the research have depicted the aim of the research, formulation of research questions, implementation of appropriate method and evaluating the findings and analysis of the research study. The main goal of carbon dioxide reduction is also considered in the recommendation and conclusion section (Bitre.gov.au, 2018).

The research aims to identify the impact of carbon dioxide emissions from transport infrastructure engineering construction work in Australia.

  • What is the carbon footprint from transport infrastructure in Australia?
  • What is the significance of transport infrastructure engineering construction work with CO2 emissions?

Some of the key terms associated to the literature review can be directly depicted with

  • CO2 emissions from transport infrastructure
  • Carbon foot and transport infrastructure
  • Construction sector
  • Transport Infrastructure Activities

The construction sector is depicted to be directly and indirectly responsible for 18% of GHG emissions as per the data available in 2010. This is considered as the largest consumer of material in 2005 with several implications on the use of energy and greenhouse gas emissions. Among the various major construction activities in Australia, the transport infrastructure construction sector offers wide range of opportunities both in terms of economic importance and at the same time GHG emissions embodied within the construction supply chain. In a review of life-cycle energy in buildings it has been discerned that the entire life-cycle energy consumption was between 10-97% of the entire life-cycle carbon emissions (V. Sejian et al., 2018). Based on the building function, may trail use, location and several types of assumptions about service life the proportion of transport infrastructure tends to increase from low energy, zero energy to a passively conventional high energy infrastructure building activities. The various sets of other studies of Ireland and Norway’s construction industry have shown that there is a considerable amount of share of renewable energy for enhancing and maintenance of machinery and equipment thereby optimising operations and reducing the amount of carbon intensive material used (Oecd.org, 2018).

Research Questions

Based on the several types of previous research, it has been found that Australia has accounted for only 0.33% of total population however it is one of the highest in terms of carbon emitting countries in the world. Since the implementation of Paris climate change agreement, the global transition to no net emissions was well before the end of the century. In addition to this, it has been seen that Australia has a significant agreement for aiming to achieve the net zero goal by 2054 remaining within the prescribed budget of Carbone of 1% (Mancini et al., 2016). At the same time, the countries seem to contribute more than 28% of the carbon emissions for targeting and saving up to AUD 20 billion. It is seen to be of great significance for tracking the carbon emissions as a result of infrastructural construction activities wherever possible, so that the economic position can be properly evaluated (Visser, Dargusch, Smith, & Grace, 2014).

Based on the ABS trend chain volume measure, the construction industry is responsible for sharing 7164% of GDP which is constituted of the second-highest behind mining. Despite of total value falling in the recent years, the Australian construction industry estimated that construction will remain at this level for a few more years due to increasing infrastructural building construction activity (Juvan & Dolnicar, 2014). There has been for the prediction of rise in the non-infrastructural facilities as well. A significant nature of the previous studies conducted by the “Australian bureau of statistics” have been able to state that the construction sector in Australia has relatively small direct emissions as a result of fuel combustion. However, there is a significantly embodied omission from other sectors. Taking into consideration the emissions, there has been a considerable amount of impact in infrastructure construction with fourth-largest in indirect emitting sector behind the various types of manufacturing activities including electricity, water and gas (Veerasamy Sejian et al., 2018).

Transportation industry is considered as one of the fastest growing industry globally which is responsible for climate change and carbon dioxide emissions. There are several exports foresees a five times increase in the carbon dioxide emissions from the transportation in Asian countries in 2000. The strategies adopted by ADB have gained assistance from various member countries in shifting the economy is to a low carbon growth parts and reduce the overall carbon footprint in the Asian countries (Biswas, 2014).

The quantification of the direct emissions is considered to be more difficult and challenging in assigning the responsibilities of greenhouse gas generation. The different types of considerations for the assessment of life-cycle on building case studies and completing the infrastructural projects has been conducted in various areas during early 1980s. These studies have used several techniques for concluding a comparison between unrealistic studies for supply chain emissions of the construction sector. Henceforth, the input and output analysis are routinely applied to evaluate the carbon footprint and energy consumption in the construction activities for infrastructural support. There are several strategies which have aimed at making more investments for reducing the carbon dioxide emissions and reduction in locally, pollution thereby imposing huge costs on public health (Pandey & Agrawal, 2014).

Literature Review

The advent of increasing transportation and urbanization in Australia seemed to be having a substantial increase in human activities such as transportation for structured development which is related to rising energy demand. Henceforth, it is imperative for the technical know-how on carbon emissions due to the roadway infrastructure and advanced accomplishment of sustainable environment. In several cases the carbon footprint calculator was used to quantify the carbon footprints across different pavement systems and high construction in Australia. This tool was considered as a part of the main study in terms of depicting the major contributors of GHG emissions (Gollnow et al., 2014). Some of the important aspects associated to the emissions have been taken into consideration with the military production aspect, pavement design aspect and transportation from source to cite with various pavement system and expected regular operation during the pavement’s design life. Some of the different empirical research have shown how different types of mathematical models have been used to estimate the overall amount of the GHG emissions with the total carbon dioxide involved during the construction process of infrastructural activities (McAusland & Najjar, 2015). The carbon footprints have been for the depicted with several types of other studies which have shown how the construction of roadways have contributed to the life-cycle assessment perspective. In general, it has been envisioned that will utilise design engineers can optimise the design methodology in the construction practices and creating a greener sustainable environment (Wolfram, Wiedmann, & Diesendorf, 2016).

Introduction to the data collection

The important consideration of the research has been based on quantitative techniques. The primary data for the CO2 Emissions from Transport (% of total fuel combustion) and Transport percentage of total major infrastructure engineering construction work done has been collected from the World Bank portal and ABS. The main interpretations of the primary techniques have used MS Excel to interpret the relation of transportation infrastructure in carbon dioxide emissions with descriptive statistics and regression analysis (Research Methodology, 2017).

Based on the formulation of the research the respective dependent variable (DV) is identified with “CO2 Emissions from Transport (% of total fuel combustion)” while the independent variable (IDV) of the study is the “Transport percentage of total major infrastructure engineering construction work done” (Kothari, Kumar, & Uusitalo, 2014).

Data Links

https://data.worldbank.org/indicator/EN.CO2.TRAN.ZS

https://www.abs.gov.au/AUSSTATS/[email protected]/DetailsPage/8755.0Mar%202018?OpenDocument

The main sample of the data is collected across 29 years ranging from 1986 to 2014. It needs to be further identified that the data collected is based stratified sampling method as the categories of the various data has been clearly identified with one being dependent and other being independent in nature.

The important consideration of method of the research has been applied with quantitative research technique. This research technique is appropriate for identifying the main significance of contribution of carbon dioxide emissions as a result of transport infrastructure. Moreover, the several types of research approach are also taken into account with applying descriptive statistic tools such as mean, standard error, median, standard deviation, sample variance, courtesies and skewness of the data (Research Methodology editors, 2018). In addition to this, the regression analysis has found the standard r square and adjusted r square to interpret the main results among the relation between the dependent variable CO2 Emissions from Transport (% of total fuel combustion) and independent variable Transport percentage of total major infrastructure engineering construction work done (Matthijsse, De Leeuw, & Hox, 2015). Based on the nature of research, the research is exploratory nature as there has not been significant studies conducted to establish the operational and improvement concepts as they do to the research design. The exploratory design is for the conducive in determining selection of subjects, data collection and overall research design (Vosloo, 2014).

GHG implications of transport infrastructure construction sector

The main data for the research is based on primary data which has been collected from reliable data source available in the World Bank website and ABS.

The use of quantitative techniques such as descriptive statistics have been conducive in determining the mean percentage of CO2 Emissions from Transport and construction work associated to infrastructure engineering. Furthermore, the regression analysis performed in this study is able to show the multiple r, r square and adjusted r square to find the significance level of the two variables selected for the study (Vosloo, 2014).

The main findings of the research have been based on collection of the necessary information on CO2 emissions from transport and transport percentage of total major infrastructure engineering construction work. The total number of data seemed to be collected across 29 years.

Year

CO2 Emissions from Transport (% of total fuel combustion)

Transport percentage of total major infrastructure engineering construction work done

1986-87

25.38

70.47

1987-88

24.66

71.95

1988-89

24.66

74.89

1989-90

24.07

80.38

1990-91

23.88

75.08

1991-92

23.20

77.55

1992-93

23.41

67.59

1993-94

23.49

66.77

1994-95

23.58

61.09

1995-96

23.67

48.35

1996-97

23.66

62.16

1997-98

23.54

65.06

1998-99

22.04

63.54

1999-00

22.12

45.65

2000-01

22.41

35.27

2001-02

21.82

43.74

2002-03

21.81

51.37

2003-04

21.65

50.78

2004-05

21.59

59.37

2005-06

21.33

58.81

2006-07

21.53

47.64

2007-08

21.57

42.88

2008-09

21.86

42.74

2009-10

21.46

40.78

2010-11

22.49

43.84

2011-12

23.29

51.37

2012-13

23.48

48.80

2013-14

24.10

42.76

2014-15

24.74

39.33

Table 1: Percentage of CO2 emission from transport and infrastructure engineering construction

 (Source: As created by the author)

As per the descriptive statistics, the mean of CO2 Emissions from Transport (% of total fuel combustion) is depicted as 22.98% and the mean of Transport percentage of total major infrastructure engineering construction work done is considered as 56.20%. The standard error for the dependent variable is seen to be 0.22 while independent variable standard error is 2.44. In addition to this, the median value of carbon dioxide emissions is 23.29% for carbon dioxide emissions from transport infrastructure and 51.37% from transport infrastructure as a result of engineering and construction work. The overall sample variances for the dataset is computed as 1.401 for the CO2 Emissions from Transport and 172.591 for total major infrastructure engineering construction work done. The Kurtosis for the data is further seen as -1.136 for the carbon dioxide emissions from transport and -1.208 from the transport percentage of total major infrastructure engineering construction work.

CO2 Emissions from Transport (% of total fuel combustion)

Transport percentage of total major infrastructure engineering construction work done

Mean

22.983

Mean

56.207

Standard Error

0.220

Standard Error

2.440

Median

23.294

Median

51.371

Standard Deviation

1.184

Standard Deviation

13.137

Sample Variance

1.401

Sample Variance

172.591

Kurtosis

-1.136

Kurtosis

-1.208

Skewness

0.188

Skewness

0.274

Range

4.057

Range

45.112

Minimum

21.327

Minimum

35.268

Maximum

25.384

Maximum

80.380

Sum

666.505

Sum

1630.015

Count

29

Count

29

Table 2: Descriptive Statistics Results of Study

 (Source: As created by the author)

The important depictions made from the regression analysis has shown that the multiple R value has a result of 0.495, R Square as 0.245, adjusted R Square as 0.2175 and standard error of 1.047. It needs to be further discern that there is a key value of 1.52E-19 for intercept and 0.006281 for X variable 1.

Regression Statistics

Multiple R

0.495

R Square

0.245

Adjusted R Square

0.21750

Standard Error

1.047

Observations

29

ANOVA

df

SS

MS

F

Significance F

Regression

1

9.628

9.63

8.78

0.0062

Residual

27

29.59

1.096

Total

28

39.22

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Lower 95.0%

Upper 95.0%

Intercept

20.47

0.868

23.5

1.52E-19

18.692

22.25

18.69

22.25

X Variable 1

0.044

0.015

2.963

0.006281

0.013732

0.075

0.013

0.075

Table 3:Regression Results of the Study

 (Source: As created by the author)

The overall analysis of the mean value of CO2 Emissions from Transport have been able to state that the CO2 emissions from the transport is on an average 22.98% in Australia from 1986 to 2014. In addition to this, total major infrastructure engineering construction work done in Australia is 56.2% during the same time period. The depictions made on the Sample variance you decide is lot more deviation of results in case of the independent variable. It can be further seen that the maximum range of CO2 emissions from transport is 25.38% while the minimum range is 21.32%. This is considered to be significantly low. However, in terms of Transport percentage of total major infrastructure engineering construction work done the percentage of minimum value is determined with 35.26% while the maximum value is considered as 80.38, which shows that there is a significant amount of major infrastructure engineering construction work being done in Australia. These findings are directly related to GHG implications of transport infrastructure construction sector.

Construction Sector in Australia

Moreover, the depictions made from the regression analysis (R square) of 0.24 clearly states that there is a very weak coefficient determination of total major infrastructure engineering construction work done and “CO2 Emissions from Transport (% of total fuel combustion)”. In addition to this, the correlation coefficient of 0.49 proves the implication on CO2 Emissions from Transport to have an insignificant effect from total major infrastructure engineering construction work done. Henceforth, despite of considerable amount of impact of carbon footprint from transport infrastructure in Australia, it cannot be stated that there is a significant impact of transport infrastructure on the engineering construction work in relation to the CO2 emissions. The significance of the results of the P value has been also determined with 0.0062 which shows a very weak relation between the dependent and independent variables from the collected samples. The findings are directly relevant to quantifying embodied GHG emissions.

Conclusion and Recommendation 

The research questions have been clearly linked with the literature review, findings and analysis of the study. Henceforth, the main finding of the first question about carbon footprint from transport infrastructure in Australia can be clearly stated with having a low significance which is inferred from a weak regression value of R square. Moreover, the significance of transport infrastructure engineering construction work with CO2 emissions is also seen to be very low in nature as per the data available from 1985 to 2014.

The significant influence of the data collected from descriptive statistics have shown that mean value of CO2 Emissions from Transport has been able to state that the CO2 emissions from the transport is on an average 22.98% in Australia from 1986 to 2014. In addition to this, total major infrastructure engineering construction work done in Australia is 56.2% during the same time period. The depictions made on the Sample variance you decide is lot more deviation of results in case of the independent variable. It can be further seen that the maximum range of CO2 emissions from transport is 25.38% while the minimum range is 21.32%. In addition to this, depictions made from the regression analysis (R square) of 0.24 clearly states that there is a very weak coefficient determination of total major infrastructure engineering construction work done and “CO2 Emissions from Transport (% of total fuel combustion)”. In addition to this, the coalition coefficient of 0.49 proves the implication on CO2 Emissions from Transport to have an insignificant effect from total major infrastructure engineering construction work done. Henceforth, despite of considerable amount of impact of carbon footprint from transport infrastructure in Australia, it cannot be stated that there is a significant impact of transport infrastructure on the engineering construction work in relation to the CO2 emissions.

The main limitation of the study has been based on performing only considering the total major infrastructure engineering construction work done in Australia, whereas there are various other sources of CO2 emissions. These are not considered under the study.

The key development activities for sustaining the present CO2 emissions should be based on exploring more opportunities for adopting low carbon initiatives by the state. In addition to this, there should be considerable amount of funding associated to land transport and carbon free infrastructural developmental activities. The investment strategies for infrastructural projects should be done in an isolated area where the impact of carbon dioxide emissions would be as low as possible.

Reference List

Biswas, W. K. (2014). Carbon footprint and embodied energy assessment of a civil works program in a residential estate of Western Australia. International Journal of Life Cycle Assessment, 19(4), 732–744. https://doi.org/10.1007/s11367-013-0681-2

Bitre.gov.au. (2018). [online] Available at: https://bitre.gov.au/publications/2016/files/BITRE_yearbook_2016_pocket_book.pdf [Accessed 1 Jun. 2018].

Chen, G., Wiedmann, T., Hadjikakou, M., & Rowley, H. (2016). City carbon footprint networks. Energies, 9(8). https://doi.org/10.3390/en9080602

Data.worldbank.org. (2018). CO2 emissions from transport (% of total fuel combustion) | Data. [online] Available at: https://data.worldbank.org/indicator/EN.CO2.TRAN.ZS?locations=AU [Accessed 1 Jun. 2018].

Gollnow, S., Lundie, S., Moore, A. D., McLaren, J., van Buuren, N., Stahle, P., … Rehl, T. (2014). Carbon footprint of milk production from dairy cows in Australia. International Dairy Journal, 37(1), 31–38. https://doi.org/10.1016/j.idairyj.2014.02.005

Juvan, E., & Dolnicar, S. (2014). Can tourists easily choose a low carbon footprint vacation? Journal of Sustainable Tourism, 22(2), 175–194. https://doi.org/10.1080/09669582.2013.826230

Kothari, C., Kumar, R., & Uusitalo, O. (2014). Research Methodology. New Age International. https://doi.org/https://196.29.172.66:8080/jspui/bitstream/123456789/2574/1/Research%20Methodology.pdf

Mancini, M. S., Galli, A., Niccolucci, V., Lin, D., Bastianoni, S., Wackernagel, M., & Marchettini, N. (2016). Ecological Footprint: Refining the carbon Footprint calculation. Ecological Indicators, 61, 390–403. https://doi.org/10.1016/j.ecolind.2015.09.040

Matthijsse, S. M., De Leeuw, E. D., & Hox, J. J. (2015). Internet panels, professional respondents, and data quality. Methodology, 11(3), 81–88. https://doi.org/10.1027/1614-2241/a000094

McAusland, C., & Najjar, N. (2015). Carbon Footprint Taxes. Environmental and Resource Economics, 61(1), 37–70. https://doi.org/10.1007/s10640-013-9749-5

Oecd.org. (2018). [online] Available at: https://www.oecd.org/derec/adb/47170274.pdf [Accessed 1 Jun. 2018].

Pandey, D., & Agrawal, M. (2014). Carbon footprint estimation of agriculture sector. In Assessment of Carbon Footprint in Different Industrial Sectors, Volume 1 (Vol. 1, pp. 25–48). https://doi.org/10.1007/978-981-4560-41-2

Research Methodology editors. (2018). Snowball sampling. Research Methodology Website . https://doi.org/https://dx.doi.org/10.4135/9781412963947.n535

Research Methodology. (2017). Cluster Sampling - Research Methodology. Research Methodology. Retrieved from https://research-methodology.net/sampling-in-primary-data-collection/cluster-sampling/

Sejian, V., Prasadh, R. S., Lees, A. M., Lees, J. C., Al-Hosni, Y. A. S., Sullivan, M. L., & Gaughan, J. B. (2018). Assessment of the carbon footprint of four commercial dairy production systems in Australia using an integrated farm system model. Carbon Management. https://doi.org/10.1080/17583004.2017.1418595

Sejian, V., Prasadh, R. S., Lees, A. M., Lees, J. C., Al-Hosni, Y. A. S., Sullivan, M. L., & Gaughan, J. B. (2018). Assessment of the carbon footprint of four commercial dairy production systems in Australia using an integrated farm system model. Carbon Management, 9(1), 57–70. https://doi.org/10.1080/17583004.2017.1418595

Visser, F., Dargusch, P., Smith, C., & Grace, P. R. (2014). A Comparative Analysis of Relevant Crop Carbon Footprint Calculators, with Reference to Cotton Production in Australia. Agroecology and Sustainable Food Systems, 38(8), 962–992. https://doi.org/10.1080/21683565.2014.923799

Vosloo, J. J. (2014). Research Design and Methodology. Methodology, 299–353.

Wolfram, P., Wiedmann, T., & Diesendorf, M. (2016). Carbon footprint scenarios for renewable electricity in Australia. Journal of Cleaner Production, 124, 236–245. https://doi.org/10.1016/j.jclepro.2016.02.080

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