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Bibliometric and text mining approaches to evaluate landfill design standards

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Abstract

In 2014, Canadians generated 961 kg of waste per capita. Landfilling is a logical choice for many Canadian communities because of land availability. This paper examines and compares five different design criteria from provincial standards and guidelines in British Columbia, Alberta, Manitoba, Nova Scotia, and the Northwest Territories. Text mining including word counts, word frequency analysis, lexical quantification, and the Gunning-Fog Index are used to identify linguistic and stylistic features in the corpora. Results show that design standards and guidelines tend to be driven by climate, demographic, and environmental considerations. Rank–frequency analysis showed that the design standards were non-Zipfian (0.409 < exponent < 0.681), but a power relationship generally fit well (0.90 < R2 < 0.99). Lexical density and the Gunning-Fog Index do not consider content in figures and tables, which are key components in engineering design standards and guidelines, so a Table and Figure Factor was developed. The factor was negatively (R2 = 0.735; Slope = − 1.1) related to lexical density, supporting the use of tables and figures in engineering design standards and guidelines. Comparing equivalent word counts in standards to landfilling rate and landfills per capita yielded better results (Spearman R = − 0.7, p = 0.08) compared to government expenditure on waste management. Lexical density and Gunning-Fog Index may be good metrics when comparing landfill efficiency metrics. The study’s outcomes may help to develop better landfill design standards in English speaking countries.

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Fig. 1

Adapted from British Columbia Ministry of Environment (2016)

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Abbreviations

AB:

Alberta

BC:

British Columbia

GFI:

Gunning-Fog Index

CV:

Coefficient of variation

MB:

Manitoba

NS:

Nova Scotia

ON:

Ontario

TaFF:

Table and figure factor

NWT:

Northwest territories

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Acknowledgements

The research reported in this paper was supported by a grant from the Natural Sciences and Engineering Research Council of Canada (RGPIN-385815), using computing equipment funded by FEROF at University of Regina. The authors are grateful for their support. The views expressed herein are those of the writers and not necessarily those of our research and funding partners.

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  1. Environmental Systems Engineering, University of Regina, Regina, SK, S4S 0A2, Canada

    Amy Richter, Kelvin Tsun Wai Ng & Bahareh Fallah

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  1. Amy Richter
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Correspondence to Kelvin Tsun Wai Ng.

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Richter, A., Ng, K.T.W. & Fallah, B. Bibliometric and text mining approaches to evaluate landfill design standards. Scientometrics 118, 1027–1049 (2019). https://doi.org/10.1007/s11192-019-03011-4

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