Cross-Scale Water and Land Impacts of Local Climate and Energy Policy—A Local Swedish Analysis of Selected SDG Interactions
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Analytical Approach
2.2.1. Energy Model and Scenario Development
2.2.2. Mapping of CLEW Resource Interactions
2.2.3. Assessing Sensitivity and Scalability of Results
3. Results
3.1. Impact of Local Climate Targets on Energy, Water and Land Use
3.2. Geographical Distribution of Energy-Related Impacts on Water and Land Use
3.3. Sensitivity and Scalability of Local Case Results
3.3.1. Sensitivity Analysis for Cross-Resource Factors
3.3.2. Scaling to National Energy End Uses
4. Discussion
4.1. Cross-Resource and Cross-Scale Implications
4.2. SDG Relations and Interactions
4.3. Uncertainty Implications
5. Concluding Remarks
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Appendix A. Model Design and Assumptions
Appendix A.1. Final Energy (Service) Demands
Appendix A.2. Energy Efficiency, Supply Technologies, and Fuel Availability
Efficiency Measure | Efficiency Improvement by 2030 Compared to Baseline | Reference |
---|---|---|
Residential and commercial electrical appliances | 50% | [95] |
Residential cooking energy intensity | 20% | [96] |
Residential and commercial lighting | 85% | [70] |
Residential and commercial building insulation—impacting total heating demand by… | 20% | [70] |
Street light energy intensity | 50% | [97] |
Energy intensity of industry | 38% | [76] finds potential to reduce by 40% compared to present level. Since the baseline energy intensity increases, this is a more conservative assumption. |
Freight transport within the municipality | 10% reduction in vehicle-kilometres travelled by freight transports | This is a modest estimate by the authors based on unquantified ambitions to decrease the number of vehicle-kilometres travelled [51]. |
Energy System Component | Technology/Fuel Switch | Reference |
---|---|---|
Industrial process heat | Fossil oil is replaced with (>80% biomass based) district heat and electricity (district heating assumed to be feasible up to 89% (modelled in the biofuels scenario). In the electricity scenario, electricity and district heating cover 50% each of the replaced oil heating demand. | Based on the patterns suggested by [76] |
Freight transport and agricultural sector | All use of fossil diesel is replaced by biodiesel (pure FAME) | According to [98] the use of pure FAME based on RME is increasing. |
Space Heating Technology | Baseline Scenario | ‘Electricity’ Scenario | ‘Biofuels’ + ‘Mixed’ Scenarios |
---|---|---|---|
Detached houses | % shares in 2030 | % shares in 2030 | % shares in 2030 |
| 50.6 | 65 | 65 |
| 3.6 | 4 | 4 |
| 45 | 23 | 23 |
| 0.8 | 0 | 0 |
| 0 | 8 | 8 |
Apartments | |||
| 15.8 | 16 | 12 |
| 84 | 80 | 84 |
| 0.2 | 0 | 0 |
| 0 | 4 | 4 |
Commercial buildings | |||
| 58 | 76 | 58 |
| 20 | 20 | 38 |
| 22 | 0 | 0 |
| 0 | 4 | 4 |
Vehicle Fleet in Year… | 2012 | 2030 in Each Scenario: | |||
---|---|---|---|---|---|
Baseline | Electricity and Mixed | Biofuels | |||
Personal Vehicles (no. of vehicles) | Diesel | 2262 | 7130 | 233 * | 1094 * |
Gasoline | 10925 | 4942 | 310 | 310 | |
Plug in electric | 61 | 94 | 1068 | 1463 | |
Biogas | 34 | 150 | 444 | 6216 | |
Ethanol | 653 | 2340 | 537 | 1468 | |
Electric | 1 | 4 | 10986 | 3027 | |
Total | 13936 | 14660 | 13577 | 13577 | |
Public transport (no. of buses) | Diesel | 20 | 20 | 0 | 0 |
Biogas | 0 | 0 | 7 | 37 | |
Plug in electric | 0 | 0 | 35 | 5 | |
Total | 20 | 20 | 42 | 42 |
Appendix A.3. Water and Land-Use Impacts
Fuel | Geographic Origin (of Fuel) | Consumptive Water Use (m3/TJ) | Geographic Origin of Reference | Reference | Land Use (ha/TJ) | Geographic Origin of Reference | Reference |
---|---|---|---|---|---|---|---|
Crude oil—refined to heating oil, gasoline and diesel | Russia | 133 | Spain | Calculated based on data from [79,99] | 0.1266 | Canada | Calculated based on reported data from [82]. |
Electricity (incl. (nuclear) fuel extraction) | Sweden (Canada) | 2222 | Russia | Calculated from electricity generation factors per source fuel and the Swedish electricity mix.
| 0.266 | Nordic (Canada) | Calculated from electricity generation factors per source fuel [37,53,104] and the Swedish electricity mix [61]. |
Wind power | Oskarshamn | 0 | USA / Global | Assumed negligible by [79,105]. | 3.47 | Oskarshamn | [53] |
Biogas (if imported) | Oskarshamn (Sweden) | 0 (454) | Italy | Locally produced biogas is assumed to come from sewage sludge, manure and similar wet waste products (requiring no added water). Imported biogas may come from dry matter, therefore requiring water in the anaerobic process as assumed by [27] | 0 (5.6) | EU | [36] |
Biomass (from forest residues) | Oskarshamn | 612 | USA | [106] | 2.5 | Spain | [107], assuming forest residues to “occupy” 5% of the land they are harvested from |
Biomass (from Grass) | Oskarshamn | 0 | Sweden | Based on description in [108] | 8.4 | Oskarshamn | Swedish Biogas International AB (2008), assuming that the crop ”occupy” 70% of the land it is harvested from (assumption based on data patterns in [36]. |
Ethanol from sugar cane | Brazil | 24695 | “Global average” | [81] | 5.0 | Latin America | [36] |
Biodiesel from rapeseed | EU (Sweden and Germany) | 57047 | USA | [79] | 11.9 | EU | [36] |
- Solid biofuels (biomass) are included in the Oskarshamn energy model in two formats: forest based pellets or wood fuel for residential heating and district heating, and grassy biomass for biogas production (in conjunction with manure and municipal sewage) and for district heating. It is assumed that the grassy biomass is inserted in the energy system without pre-processing, thereby requiring no additional water. Further, the grass is expected to grow without irrigation. Conversion of forest biomass to pellets are considered to require some water.
- As highlighted in the main manuscript all data describing cross-resource interaction between water, land and energy are reported in large ranges. Data points selected to describe these relationships in the model are therefore to be interpreted as reasonable guesses rather than exact representations of the real interactions. See further discussion on sensitivity of results and need for further developments in data collection and modelling approaches in main manuscript.
Appendix A.3.1. References of Data Sources Reviewed for Energy Related Water Use and Land Use
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Appendix B. Supplementary Figures
- Nuclear energy land use requirements are not including estimated land use needs for final repository of used fuel. It is therefore anticipated that the total land area excluded from other uses due to nuclear energy is larger than reported here.
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Fuel Group | Primary Geographic Origin | Reference |
---|---|---|
Crude oil—refined to heating oil, gasoline and diesel | Russia | [54] |
Electricity (incl. (nuclear *) fuel extraction) | Sweden (Canada) | [37,55,56] |
Wind power | Oskarshamn | [52] |
Biogas (if imported) | Oskarshamn (Sweden) | [57,58] |
Biomass | Oskarshamn | [59] |
Ethanol from sugar cane | Brazil | [36] |
Biodiesel from rapeseed | EU (Sweden and Germany) | [36,60] |
Key Measures of Change between Year 2012 and Year 2030 | Measure Taken in… | |
---|---|---|
1 | Increased energy efficiency in residential and commercial buildings related to cooking (20%), lighting (85%) and electrical appliances (50%). | All fossil free scenarios |
2 | Improved insulation in residential and commercial buildings, decreasing final space heating demands (20%) | All fossil free scenarios |
3 | Moderate increase in the share of solar panels on residential and commercial buildings for space and water heating demands (share in 2030: detached houses 8%; apartments 4%; commercial buildings 4%). | All fossil free scenarios |
4 | Increased share of biomass based (>80% of input fuels) district heating to meet space and water heat demands in commercial buildings (from 20% in 2012 to 38% in 2030). | ‘Biofuels’ scenario |
5 | Increased share of heat pumps to meet space and water heat demands in residential and commercial buildings (from 50% to 65% in detached houses; from 58% to 76% in commercial buildings) | ‘Electricity’ scenario |
6 | Energy efficiency of street lighting is improved (75%) | All fossil free scenarios |
7 | Decoupling GDP growth with industrial energy use, decreasing overall industrial energy demands (38%) | All fossil free scenarios |
8 | A shift from fossil fuel based process heat in the industrial sector to equal shares of electricity powered heating and biomass (>80% of input fuels) based district heating. * | ‘Electricity’ scenario |
9 | A shift from fossil fuel based process heat in the industrial sector to biomass (>80% of input fuels) based district heating (89%) and electricity (11%). * | ‘Biofuels’ and ‘mixed’ scenarios |
10 | All fossil diesel is replaced with biodiesel in the agricultural sector. | All fossil free scenarios |
11 | Public transport reaches a 15% market share by 2026 (the county’s goal is to reach this in 2020 [75], but a recent decrease in number of buses in Oskarshamn is estimated by the authors to delay this goal by 6 years) | All fossil free scenarios |
12 | A small share of personal vehicle transports (4%) are removed from the system, assumed to be replaced by biking and walking. | All fossil free scenarios |
13 | Total freight transport (in vehicle-kilometres per vehicle) is reduced by 10% through improved physical planning and route optimisation in the municipality. | All fossil free scenarios |
14 | All fossil diesel is replaced with biodiesel in the municipal freight transport. | ‘Biofuels’ and ‘mixed’ scenarios |
15 | The municipal freight transport largely is electrified. Fossil diesel is replaced by biodiesel in 20% of the heavy-duty transport, where electrification is considered unfeasible. | ‘Electricity’ scenario |
16 | Fossil fuelled personal vehicles are replaced by predominantly biodiesel, ethanol and biogas (33 % of personal vehicles electrified in 2030, the remainder fuelled with biofuels) | ‘Biofuels’ scenario |
17 | Fossil fuelled personal vehicles are replaced by predominantly electric vehicles (95% of personal vehicles electrified in 2030, the remainder fuelled with liquid biofuels and biogas). | ‘Electricity’ and ‘mixed’ scenario |
18 | The assessed municipal wind power potential [53] is fully exploited, to cover 87% of municipal electricity demands. ** | Scenarios with local wind power |
Water Related SDG Targets/Indicators | Land Related SDG Targets/Indicators | |||||
---|---|---|---|---|---|---|
6.4 By 2030, substantially increase water-use efficiency across all sectors and ensure sustainable withdrawals and supply of freshwater to address water scarcity and substantially reduce the number of people suffering from water scarcity | 2.4 By 2030, ensure sustainable food production systems (…) that increase productivity and production, (…) | 15.1 (…) ensure the conservation, restoration and sustainable use of terrestrial (…) ecosystems and their services (…) | 15.3 (…) combat desertification, restore degraded land and soil (…) and strive to achieve a land degradation-neutral world | |||
6.4.1: Change in water-use efficiency over time | 6.4.2: Level of water stress… * | 2.4.1: Proportion of agricultural area under productive and sustainable agriculture | 15.1.1: Forest area as a proportion of total land area | 15.3.1: Proportion of land that is degraded over total land area | ||
Local Decarbonisation scenarios, supporting SDGs 7, 11 and 13 | ‘Electricity’ scenario | The least ** water consuming scenario, while meeting the same final energy demand. | Highest ** water withdrawal (but primarily in Sweden—projected to remain a water rich region). | Lowest ** land-use impact and little change compared to ‘Baseline’. Moderate increase in biofuel use may cause a shift from food to fuel crops. | Lowest ** land-use impact and little change compared to ‘Baseline’. Moderate increase in biofuel use may encroach on forests. | Lowest ** overall land-use impact, indicating least impact on land degradation. |
‘Biofuels’ scenario | The most ** water consuming (primarily related to imported biodiesel) scenario. | Large imports of biodiesel from moderately water stressed EU countries. | Large increase in biofuel demands, that may require shifts from food to fuel crops. | As land requirements for biofuels increase, forest area may decrease. | Increased use for heating requires more forestry residues and may compete with biodiversity needs. | |
‘Mixed’ scenario | High water consumption, primarily related to imported biodiesel. | Large imports of biodiesel from moderately water stressed EU countries | Large increase in biofuel demands, that may require shifts from food to fuel crops | As land requirements for biofuels increase, forest area may decrease. | Increased use for heating requires more forestry residues and may compete with biodiversity needs. | |
‘Mixed’ scenario with local wind power | High water consumption related to imported biodiesel. | Lowest ** total water withdrawal when thermal and hydropower decrease in favour of wind power | As above, but may also be affected by wind power’s land use. | As above, but may also be affected by wind power’s land use. | As above, and scenario with the largest overall land use. ** |
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Engström, R.E.; Destouni, G.; Howells, M.; Ramaswamy, V.; Rogner, H.; Bazilian, M. Cross-Scale Water and Land Impacts of Local Climate and Energy Policy—A Local Swedish Analysis of Selected SDG Interactions. Sustainability 2019, 11, 1847. https://doi.org/10.3390/su11071847
Engström RE, Destouni G, Howells M, Ramaswamy V, Rogner H, Bazilian M. Cross-Scale Water and Land Impacts of Local Climate and Energy Policy—A Local Swedish Analysis of Selected SDG Interactions. Sustainability. 2019; 11(7):1847. https://doi.org/10.3390/su11071847
Chicago/Turabian StyleEngström, Rebecka Ericsdotter, Georgia Destouni, Mark Howells, Vivek Ramaswamy, Holger Rogner, and Morgan Bazilian. 2019. "Cross-Scale Water and Land Impacts of Local Climate and Energy Policy—A Local Swedish Analysis of Selected SDG Interactions" Sustainability 11, no. 7: 1847. https://doi.org/10.3390/su11071847