Designing a Sustainability Assessment Framework for Selecting Sustainable Wastewater Treatment Technologies in Corporate Asset Decisions
Abstract
:1. Introduction
- Comprehensiveness: sustainability assessment should cover a holistic scope integrating the environmental, social and economic dimension of sustainability
- Pluralism: compared to the prescriptive process of other impact assessments, each sustainability assessment process should be designed and tailored to the specific context [15]
- Intergenerational equity: wider and long-term impacts should also be assessed to ensure the decision demonstrates corporate social responsibility and value for future generations [17]
2. Materials and Methods
2.1. Understand the Decision Context
- (1)
- What is your role and daily activities in the company?
- (2)
- What are the current decision-making practices and drivers for wastewater asset investment?
- (3)
- What are the biggest challenges in making that decision?
2.2. Development of the Criteria Hierarchy
2.3. Development of Weightings
2.3.1. Weighting Allocation Using AHP
2.3.2. Group Weightings
2.4. Score Aggregation and Options Ranking
- Activated Sludge Process (solo, as a baseline) (ASP)
- Dissolved Air Flotation (DAF)
- Chemically Assisted Primary Settlement (CAPS)
- Ballasted Activated Sludge Process (B-ASP)
- Sequencing Batch Reactor (SBR)
- Granular Activated Sludge Process (G-ASP)
- Mainstream De-ammonification process (De-ammo)
2.5. Sensitivity Analysis
3. Results and Discussion
3.1. Preliminary Interviews and Thematic Analysis
- The decision-making process in wastewater asset planning is complex and faces multiple challenges. Making the right balance between different decision-making criteria is difficult in practice.
- The current investment decisions are primarily driven by the whole life cost and compliance risk whilst there is an increasing demand for an integrated system that incorporates wider dimensions of sustainability. This is similar to the results of decision mapping conducted by Ashley et al. (2008) which suggested that costs and risks are the main drivers of asset decisions in the UK water industry [21].
- Decision support tools should be understandable and communicable at a managerial level.
- They also need to be flexible to accommodate different STW programmes and adapt to new business needs and priorities.
3.2. Criteria Hierarchy
3.3. Weightings
3.4. Score Aggregation and Options Ranking
3.5. Sensitivity Analysis
3.6. Strengths and Limitations
3.6.1. Simplicity and Usability
3.6.2. Stakeholder Engagement
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Research Ethical Statement
Appendix A
Indicators | Criteria | Definitions | Type of Value Indication |
---|---|---|---|
Energy neutrality | Environmental impact | Net carbon consumption of the wastewater treatment process (Consumption minus recovery from sludge) | Negative |
Total emission | Environmental impact | Total of direct and indirect carbon emission associated with the wastewater treatment process | Negative |
Chemical consumption | Environmental impact | The total amount of chemical use in the operation of wastewater treatment (e.g., chemical dosing and polymer) | Negative |
Opex | Economic viability | Cost related to materials (consumables), staff cost (operators), power consumption, hired and contracted services (e.g., transport; service contract for specific treatment process) | Negative |
Capex | Economic viability | Capital cost related to the construction and commissioning of the treatment process or technology. | Negative |
Flexibility | Resilience | The ability of technology/process to adjust or upgrade to adapt to climate change, population growth and regulatory changes. | Positive |
Compliance | Resilience | The ability and the overall confidence of technology/process to meet the site compliance such as flow and quality consents and risks to failure. | Positive |
Odour | Social impact | The odour impact of the treatment process and sludge storage on the community | Negative |
Operability | Social impact | The ease to operate the process, which is associated with the manpower resource as well as the level of skills and training required for operators. | Positive |
ASP | DAF | CAPS | G-ASP | SBR | G-ASP | De-Ammo | |
---|---|---|---|---|---|---|---|
Energy neutrality | 3.00 | 2.67 | 2.67 | 2.67 | 2.00 | 4.00 | 3.40 |
Chemical consumption | 3.33 | 2.67 | 1.83 | 1.67 | 3.50 | 3.67 | 3.80 |
Total emission | 2.00 | 2.80 | 2.80 | 2.00 | 2.20 | 3.80 | 2.60 |
Odour | 2.67 | 3.17 | 3.33 | 2.50 | 3.17 | 3.50 | 2.40 |
Operability | 5.00 | 2.83 | 2.67 | 2.83 | 3.33 | 2.83 | 2.80 |
Capex | 4.41 | 5.00 | 3.17 | 3.58 | 4.30 | 1.00 | 3.58 |
Opex | 3.70 | 2.42 | 1.00 | 2.39 | 2.76 | 5.00 | 2.39 |
Flexibility | 1.43 | 3.00 | 2.86 | 2.57 | 2.29 | 3.71 | 2.83 |
Compliance | 4.33 | 3.00 | 2.83 | 3.17 | 2.17 | 2.67 | 3.00 |
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Dimension | Indicator | Unit | References |
---|---|---|---|
Environmental and Technical | Energy consumption | kWh/yr | [27,28,29,33,36] |
Land required | m2/p.e. | [27,28,29,33,37,38] | |
Pollutants removal potentials | % | [27,28,29,33,36,39] | |
Amount of sludge produced | kg/yr | [28,29,39] | |
Resource recovery potential | - | [28,29] | |
Greenhouse gas emission | kgCO2 eq/yr | [36,39] | |
Social | Public acceptance | Qualitative | [28,29,33,37,38] |
Odour impact | Qualitative | [27,28,29,33] | |
Noise impact | Qualitative | [28,29,33] | |
Visual impact | Qualitative | [28,29,33] | |
Reliability | Qualitative | [29,33,37,38] | |
Complexity | Qualitative | [27,28,29,33,38] | |
Economic | Capex | £k | [27,28,29,33,38] |
Opex | £k/yr | [27,28,29,33,38] |
Scale Intensity | Definition |
---|---|
1 | Equally important |
3 | Moderately more important |
5 | Strongly more important |
7 | Very strongly more important |
9 | Extremely more important |
2, 4, 6, 8 | Intermediate values between two scale points |
Reciprocals | The preference order is inversed |
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | Group Weights | Rank | |
---|---|---|---|---|---|---|---|---|---|---|---|
Energy neutrality | 0.183 | 0.053 | 0.067 | 0.096 | 0.096 | 0.058 | 0.129 | 0.029 | 0.054 | 0.085 | 6 |
Chemical consumption | 0.044 | 0.106 | 0.084 | 0.061 | 0.318 | 0.058 | 0.045 | 0.029 | 0.054 | 0.078 | 7 |
Total emission | 0.063 | 0.106 | 0.106 | 0.229 | 0.175 | 0.174 | 0.031 | 0.087 | 0.108 | 0.119 | 3 |
Odour | 0.041 | 0.058 | 0.114 | 0.028 | 0.112 | 0.022 | 0.023 | 0.096 | 0.081 | 0.061 | 9 |
Operability | 0.047 | 0.037 | 0.114 | 0.118 | 0.049 | 0.100 | 0.057 | 0.038 | 0.031 | 0.067 | 8 |
Opex | 0.084 | 0.133 | 0.129 | 0.090 | 0.052 | 0.259 | 0.093 | 0.082 | 0.182 | 0.126 | 2 |
Capex | 0.084 | 0.133 | 0.129 | 0.030 | 0.052 | 0.086 | 0.278 | 0.082 | 0.182 | 0.111 | 4 |
Flexibility | 0.113 | 0.187 | 0.043 | 0.058 | 0.049 | 0.049 | 0.069 | 0.140 | 0.077 | 0.088 | 5 |
Compliance | 0.340 | 0.187 | 0.214 | 0.290 | 0.098 | 0.195 | 0.276 | 0.419 | 0.230 | 0.266 | 1 |
ASP | DAF | CAPS | B-ASP | SBR | G-ASP | De-Ammo | Spearman’s Coefficient | |
---|---|---|---|---|---|---|---|---|
Ranking based on this assessment framework | 1 | 3 | 7 | 6 | 5 | 2 | 4 | ρ = 0.75 (p = 0.052) |
Ranking from previous decision by stakeholders | 1 | 3 | 5 | 6 | 4 | 2 | 7 |
ASP | DAF | CAPS | B-ASP | SBR | G-ASP | De-Ammo | |
---|---|---|---|---|---|---|---|
Group weightings | 1 | 3 | 7 | 6 | 5 | 2 | 4 |
Stakeholder 1 | 1 | 3 | 6 | 5 | 7 | 2 | 4 |
Stakeholder 2 | 2 | 3 | 7 | 6 | 5 | 1 | 4 |
Stakeholder 3 | 1 | 3 | 7 | 6 | 5 | 2 | 4 |
Stakeholder 4 | 1 | 4 | 6 | 5 | 7 | 2 | 3 |
Stakeholder 5 | 2 | 4 | 6 | 7 | 5 | 1 | 3 |
Stakeholder 6 | 2 | 3 | 7 | 6 | 5 | 1 | 4 |
Stakeholder 7 | 1 | 2 | 7 | 4 | 5 | 6 | 3 |
Stakeholder 8 | 1 | 3 | 6 | 5 | 7 | 2 | 4 |
Stakeholder 9 | 1 | 2 | 7 | 6 | 5 | 3 | 4 |
Group Weights | Absolute Changes | Relative Changes % | |
---|---|---|---|
Energy neutrality | 0.085 | −0.224 | 263 |
Chemical consumption | 0.078 | −0.659 | 844 |
Total emission | 0.119 | −0.124 | 105 |
Odour | 0.061 | −0.270 | 442 |
Operability | 0.067 | 0.103 | 154 |
Opex | 0.126 | −0.172 | 137 |
Capex | 0.111 | 0.066 | 59 |
Flexibility | 0.088 | −0.098 | 112 |
Compliance | 0.266 | 0.135 | 51 |
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Ling, J.; Germain, E.; Murphy, R.; Saroj, D. Designing a Sustainability Assessment Framework for Selecting Sustainable Wastewater Treatment Technologies in Corporate Asset Decisions. Sustainability 2021, 13, 3831. https://doi.org/10.3390/su13073831
Ling J, Germain E, Murphy R, Saroj D. Designing a Sustainability Assessment Framework for Selecting Sustainable Wastewater Treatment Technologies in Corporate Asset Decisions. Sustainability. 2021; 13(7):3831. https://doi.org/10.3390/su13073831
Chicago/Turabian StyleLing, Jiean, Eve Germain, Richard Murphy, and Devendra Saroj. 2021. "Designing a Sustainability Assessment Framework for Selecting Sustainable Wastewater Treatment Technologies in Corporate Asset Decisions" Sustainability 13, no. 7: 3831. https://doi.org/10.3390/su13073831
APA StyleLing, J., Germain, E., Murphy, R., & Saroj, D. (2021). Designing a Sustainability Assessment Framework for Selecting Sustainable Wastewater Treatment Technologies in Corporate Asset Decisions. Sustainability, 13(7), 3831. https://doi.org/10.3390/su13073831