| Literature DB >> 32489422 |
Jessica Varela Villarreal1, Cecilia Burgués1, Christine Rösch1.
Abstract
BACKGROUND: The development of alternative pathways for sustainable fuel production is a crucial task for politics, industry and research, since the current use of fossil fuels contributes to resource depletion and climate change. Microalgae are a promising option, but the technology readiness level (TRL) is low and cannot compete economically with fossil fuels. Novel genetic engineering technologies are being investigated to improve productivity and reduce the cost of harvesting products extracted from or excreted by microalgae for fuel production. However, high resource efficiency and low costs alone are no guarantee that algae fuels will find their way into the market. Technologies must be accepted by the public to become valuable for society. Despite strong efforts in algae research and development, as well as political commitments at different scales to promote algae biofuels for transport sectors, little is known about public acceptance of this alternative transport fuel. Despite the advantages of algae technology, genetically engineered (GE) microalgae can be controversial in Europe due to risk perception. Therefore, the aim of this study was to investigate, for the first time, the knowledge and views of European experts and stakeholders on the conditions and requirements for acceptability of GE microalgae for next generation biofuel production.Entities:
Keywords: Acceptance; Algae; Biofuel; Gene editing; Genetically modified organisms; Risk perception; Social perception; Survey
Year: 2020 PMID: 32489422 PMCID: PMC7245023 DOI: 10.1186/s13068-020-01730-y
Source DB: PubMed Journal: Biotechnol Biofuels ISSN: 1754-6834 Impact factor: 6.040
Fig. 1Sociodemographic data (absolute results are shown in brackets)
Fig. 2Perceptions of respondents about expected benefits of GE algae biofuel among fossil fuels, established biofuels and natural algae biofuels
Fig. 3Perceptions of respondents about general risks of future mobility fuels or power sources
Fig. 4Opinions of respondents about general social acceptance of GE algae biofuel in the EU (absolute amounts are in brackets)
Fig. 5Opinions of respondents about the improvement of acceptance of GE algae biofuel due to the use of gene-editing techniques (absolute amounts are in brackets)
Fig. 6Opinions of respondents about not regulating gene-editing as GMO (absolute amounts are in brackets)
Fig. 7Willingness to spend more money on GE algae biofuel if higher engine performances than those for established biofuels (blue) were achieved, and if environmental advantages compared to fossil fuels (green) were attained
Fig. 8Suggestions of the respondents on how to improve social acceptance of GE algae biofuel
Fig. 9Summary and overview of variables and the statistic tests performed to find statistical relationships
Correlation coefficients and p values (only p values < 0.05 are shown) after Spearman’s rank order between sociodemographic ordinal variables and opinion ordinal variables
| Sociodemographic ordinal variables | Opinion ordinal variables | Spearman’s rank order coefficient | |
|---|---|---|---|
| Age | |||
| Less environmental impact | − 0.17 | 0.025 | |
| Reduced GHG emissions and climate change | − 0.19 | 0.023 | |
| Educational level | |||
| Less environmental impact | 0.02 | 0.044 | |
| Reduced GHG emissions and climate change | − 0.03 | 0.001 | |
| New rural jobs | 0.06 | 0.040 | |
| Require less energy | − 0.03 | 0.021 | |
Chi-square test correlations (p values < 0.05) and respective Cramer’s V values between sociodemographic ordinal variables and opinion nominal variables
| Sociodemographic ordinal variables | Opinion nominal variables | Cramer’s V | |
|---|---|---|---|
| Age | |||
| Closed production systems with high security standards | 0.041 | 0.221 | |
| Use of new precise gene editing tools instead of traditional genome engineering | 0.044 | 0.220 | |
| Educational level | |||
| Opinion about being final consumer of GE algae biofuel | 0.037 | 0.251 | |
| Clear communication of risks and benefits of genome engineering technologies | 0.004 | 0.346 | |
| Experience in algae industry | |||
| Opinion about being final consumer of GE algae biofuel | 0.024 | 0.236 | |
Chi-square test correlations (p values < 0.05) and respective Cramer’s V values between sociodemographic nominal variables and opinion nominal variables
| Sociodemographic nominal variables | Opinion nominal variables | χ2-test | Cramer’s V |
|---|---|---|---|
| Gender | |||
| Hydropower | 0.034 | 0.285 | |
| Working field | |||
| No competition with food | 0.011 | 0.246 | |
| Require less energy | 0.016 | 0.242 | |
| Improve the controllability of the process | 0.050 | 0.225 | |
| Opinion about regulating gene-edited organisms as GMOs | 0.024 | 0.236 | |
| Fossil fuels | 0.022 | 0.237 | |
| Wind power | 0.002 | 0.267 | |
Sociodemographic ordinal variables
| Variable name | Answers |
|---|---|
| Age | < 20 years 20–30 years 31–60 years > 61 years |
| Educational level | Did not complete high school High school Bachelor’s degree Master’s degree Other university degree PhD |
| Experience in algae industry | Never < 3 years 3–10 years > 10 years |
Opinion ordinal variables (4 Likert scale)
| Variable name | Answers |
|---|---|
| Less environmental impact | Totally not agree Rather not agree Rather agree Totally agree Do not know |
| Reduced greenhouse gas emissions and climate change | |
| No competition with food | |
| Superior engine performance | |
| New rural jobs | |
| Reduced fuel import dependency | |
| Less environmental impact | Totally not agree Rather not agree Rather agree Totally agree Do not know |
| Reduced greenhouse gas emissions and climate change | |
| Less occupational risk | |
| New rural jobs | |
| Reduced fuel import dependency | |
| Improve productivity | Totally not agree Rather not agree Rather agree Totally agree Do not know |
| Require less energy | |
| Need less nutrients uptake | |
| Need less use of fresh water | |
| Improve the controllability of the process | |
| Improve economic feasibility | |
| GMOs should partially replace fossil fuels | Totally not agree Rather not agree Rather agree Totally agree Do not know |
| Fossil fuels | Entirely harmless Rather harmless Rather alarming Entirely alarming Prefer not to answer |
| Established biofuels | |
| Solar photovoltaic power | |
| Wind power | |
| Hydropower | |
| Opinion about general social acceptance | No acceptance Low Medium High acceptance Prefer not to answer |
| Variation of public acceptance in case of using gene-editing techniques | Lower No difference Slightly higher Noticeably higher Do not know |
| Opinion about regulating gene-edited organisms as GMOs | Totally not agree Rather not agree Rather agree Totally agree Prefer not to answer |
Sociodemographic nominal variables
| Variable name | Answers |
|---|---|
| Gender | Female Male |
| Land | Austria; Belgium; Bulgaria; Croatia; Cyprus; Czech Republic; Denmark; Estonia; Finland; France; Germany; Greece; Hungary; Ireland; Italy; Latvia; Lithuania; Luxembourg; Malta; Netherlands; Poland; Portugal; Romania; Slovakia; Slovenia; Spain; Sweden; United Kingdom |
| Working field | Education/academia Industry/consulting/management Government Non-governmental organization Journalism Other |
Opinion nominal variables
| Variable name | Answers |
|---|---|
| Opinion about being final consumer of GE algae biofuel | Yes No Do not know |
| Willingness to pay more money if higher engine performances were achieved compared to established biofuels | Yes, < 5% Yes, 5–10% more Yes, 10–20% more Yes, > 20% Yes, do not know how much more No |
| Willingness to pay more money if environmental advantages were achieved compared to fossil fuels | |
| Regulations before any genome engineered species is implemented | Yes No |
| Higher or same economic benefits than using fossil fuels | |
| Clear evidence of benefits | |
| Clear communication of risks and benefits of genome engineering technologies | |
| Rigorous risk assessments of GM algae, involving scientists with minimal conflicts of interest, independent peer review, and public participation | |
| Closed production systems with high security standards | |
| Use of genetic markers | |
| Minor survivability compared to natural strains | |
| Use of new precise gene editing tools instead of traditional genome engineering | |
p values after Spearman’s rank order correlation coefficients between sociodemographic ordinal variables (Appendix A: Table 4) and opinion ordinal variables (Appendix A: Table 5)
| Sociodemographic ordinal variables | Opinion ordinal variables | Spearman’s rank order coefficient | |
|---|---|---|---|
| Age | |||
| Less environmental impact | − | ||
| Reduced GHG emissions and climate change | − | ||
| No competition with food | − 0.02 | 0.915 | |
| Superior engine performance | − 0.09 | 0.268 | |
| New rural jobs | − 0.13 | 0.389 | |
| Reduced fuel import dependency | 0.03 | 0.637 | |
| Less environmental impact | − 0.05 | 0.345 | |
| Reduced GHG emissions and climate change | − 0.05 | 0.391 | |
| Less occupational risk | − 0.25 | 0.326 | |
| New rural jobs | − 0.06 | 0.807 | |
| Reduced fuel import dependency | − 0.02 | 0.949 | |
| Improve productivity | − 0.23 | 0.148 | |
| Require less energy | − 0.23 | 0.109 | |
| Need less nutrients uptake | − 0.18 | 0.326 | |
| Need less use of fresh water | − 0.08 | 0.902 | |
| Improve the controllability of the process | − 0.2 | 0.355 | |
| Improve economic feasibility | − 0.19 | 0.554 | |
| GMOs should partially replace fossil fuels | − 0.02 | 0.255 | |
| Opinion about general social acceptance | − 0.15 | 0.167 | |
| Variation of public acceptance in case of using gene-editing techniques | − 0.04 | 0.662 | |
| Opinion about regulating gene-edited organisms as GMOs | 0.09 | 0.665 | |
| Fossil fuels | 0.06 | 0.528 | |
| Established biofuels | 0.01 | 0.858 | |
| GE algae biofuel | 0.06 | 0.972 | |
| Solar photovoltaic power | 0.06 | 0.851 | |
| Wind power | 0.07 | 0.907 | |
| Hydropower | − 0.02 | 0.897 | |
| Educational level | |||
| Less environmental impact | |||
| Reduced GHG emissions and climate change | − | ||
| No competition with food | 0.12 | 0.058 | |
| Superior engine performance | − 0.04 | 0.314 | |
| New rural jobs | |||
| Reduced fuel import dependency | − 0.02 | 0.126 | |
| Less environmental impact | 0.04 | 0.158 | |
| Reduced GHG emissions and climate change | − 0.06 | 0.085 | |
| Less occupational risk | − 0.08 | 0.619 | |
| New rural jobs | 0.02 | 0.068 | |
| Reduced fuel import dependency | − 0.13 | 0.071 | |
| Improve productivity | 0.01 | 0.598 | |
| Require less energy | − | ||
| Need less nutrients uptake | 0.06 | 0.696 | |
| Need less use of fresh water | 0.03 | 0.860 | |
| Improve the controllability of the process | − 0.06 | 0.321 | |
| Improve economic feasibility | − 0.05 | 0.313 | |
| GMOs should partially replace fossil fuels | − 0.02 | 0.420 | |
| Opinion about general social acceptance | − 0.09 | 0.927 | |
| Variation of public acceptance in case of using gene-editing techniques | 0.04 | 0.776 | |
| Opinion about regulating gene-edited organisms as GMOs | 0.06 | 0.216 | |
| Fossil fuels | − 0.08 | 0.933 | |
| Established biofuels | 0.05 | 0.740 | |
| GE algae biofuel | − 0.07 | 0.335 | |
| Solar photovoltaic power | 0.04 | 0.637 | |
| Wind power | − 0.15 | 0.780 | |
| Hydropower | − 0.16 | 0.086 | |
| Experience in algae industry | |||
| Less environmental impact | 0 | 0.927 | |
| Reduced GHG emissions and climate change | − 0.11 | 0.659 | |
| No competition with food | 0.01 | 0.397 | |
| Superior engine performance | − 0.01 | 0.624 | |
| New rural jobs | − 0.06 | 0.828 | |
| Reduced fuel import dependency | 0.03 | 0.727 | |
| Less environmental impact | − 0.11 | 0.560 | |
| Reduced GHG emissions and climate change | − 0.11 | 0.822 | |
| Less occupational risk | 0.04 | 0.928 | |
| New rural jobs | − 0.01 | 0.989 | |
| Reduced fuel import dependency | − 0.02 | 0.977 | |
| Improve productivity | − 0.06 | 0.416 | |
| Require less energy | 0.03 | 0.488 | |
| Need less nutrients uptake | − 0.04 | 0.256 | |
| Need less use of fresh water | 0.08 | 0.107 | |
| Improve the controllability of the process | − 0.06 | 0.953 | |
| Improve economic feasibility | − 0.15 | 0.174 | |
| GMOs should partially replace fossil fuels | 0.04 | 0.366 | |
| Opinion about general social acceptance | 0 | 0.657 | |
| Variation of public acceptance in case of using gene-editing techniques | 0.02 | 0.666 | |
| Opinion about regulating gene-edited organisms as GMOs | − 0.02 | 0.410 | |
| Fossil fuels | − 0.09 | 0.450 | |
| Established biofuels | − 0.02 | 0.951 | |
| GE algae biofuel | − 0.02 | 0.784 | |
| Solar photovoltaic power | − 0.02 | 0.714 | |
| Wind power | − 0.03 | 0.808 | |
| Hydropower | − 0.06 | 0.835 | |
Chi-square test p values between sociodemographic nominal variables (Appendix A: Table 6) and opinion nominal variables (Appendix A: Table 7)
| Sociodemographic nominal variables | Opinion nominal variables | Chi2 | Fisher’s test |
|---|---|---|---|
| Gender | |||
| Opinion about being final consumer of GE algae biofuel | 0.467 | ||
| Willingness to pay more money if higher engine performances were achieved compared to established biofuels | 0.959 | ||
| Willingness to pay more money if environmental advantages were achieved compared to fossil fuels | 0.504 | ||
| Regulations before any genome engineered species is implemented | 0.091 | 0.144 | |
| Higher or same economic benefits than using fossil fuels | 0.774 | 0.824 | |
| Clear evidence of benefits use of genetic markers | 0.479 | 0.516 | |
| Clear communication of risks and benefits of genome engineering technologies | 0.983 | 1.000 | |
| Rigorous risk assessments of GM algae, involving scientists with minimal conflicts of interest, independent peer review, and public participation | 0.079 | 0.122 | |
| Closed production systems with high security standards | 0.217 | 0.268 | |
| Use of genetic markers | 0.132 | 0.193 | |
| Minor survivability compared to natural strains | 0.665 | 0.818 | |
| Use of new precise gene editing tools instead of traditional genome engineering | 0.224 | 0.256 | |
| Regulations before any genome engineered species is implemented | 0.055 | 0.069 | |
| Working field | |||
| Opinion about being final consumer of GE algae biofuel | 0.910 | ||
| Willingness to pay more money if higher engine performances were achieved compared to established biofuels | 0.757 | ||
| Willingness to pay more money if environmental advantages were achieved compared to fossil fuels | 0.637 | ||
| Regulations before any genome engineered species is implemented | 0.389 | ||
| Higher or same economic benefits than using fossil fuels | 0.375 | ||
| Clear evidence of benefits use of genetic markers | 0.184 | ||
| Clear communication of risks and benefits of genome engineering technologies | 0.931 | ||
| Rigorous risk assessments of GM algae, involving scientists with minimal conflicts of interest, independent peer review, and public participation | 0.922 | ||
| Closed production systems with high security standards | 0.753 | ||
| Use of genetic markers | 0.900 | ||
| Minor survivability compared to natural strains | 0.136 | ||
| Use of new precise gene editing tools instead of traditional genome engineering | 0.500 | ||
| Regulations before any genome engineered species is implemented | 0.304 | ||
Fisher’s test was done in cases of having two dichotomous categorical variables
Chi-square test p values between sociodemographic ordinal variables (Appendix A: Table 4) and opinion nominal variables (Appendix A: Table 7)
| Sociodemographic ordinal variables | Opinion nominal variables | Cramer’s V | |
|---|---|---|---|
| Age | |||
| Opinion about being final consumer of GE algae biofuel | 0.422 | ||
| Willingness to pay more money if higher engine performances were achieved compared to established biofuels | 0.512 | ||
| Willingness to pay more money if environmental advantages were achieved compared to fossil fuels | 0.724 | ||
| Regulations before any genome engineered species is implemented | 0.152 | ||
| Higher or same economic benefits than using fossil fuels | 0.985 | ||
| Clear evidence of benefits use of genetic markers | 0.771 | ||
| Clear communication of risks and benefits of genome engineering technologies | 0.372 | ||
| Rigorous risk assessments of GM algae, involving scientists with minimal conflicts of interest, independent peer review, and public participation | 0.485 | ||
| Closed production systems with high security standards | |||
| Use of genetic markers | 0.914 | ||
| Minor survivability compared to natural strains | 0.945 | ||
| Use of new precise gene editing tools instead of traditional genome engineering | |||
| Regulations before any genome engineered species is implemented | 0.180 | ||
| Educational level | |||
| Opinion about being final consumer of GE algae biofuel | |||
| Willingness to pay more money if higher engine performances were achieved compared to established biofuels | 0.580 | ||
| Willingness to pay more money if environmental advantages were achieved compared to fossil fuels | 0.651 | ||
| Regulations before any genome engineered species is implemented | 0.565 | ||
| Higher or same economic benefits than using fossil fuels | 0.188 | ||
| Clear evidence of benefits use of genetic markers | 0.325 | ||
| Clear communication of risks and benefits of genome engineering technologies | |||
| Rigorous risk assessments of GM algae, involving scientists with minimal conflicts of interest, independent peer review, and public participation | 0.662 | ||
| Closed production systems with high security standards | 0.467 | ||
| Use of genetic markers | 0.915 | ||
| Minor survivability compared to natural strains | 0.045 | ||
| Use of new precise gene editing tools instead of traditional genome engineering | 0.855 | ||
| Regulations before any genome engineered species is implemented | 0.184 | ||
| Experience in algae industry | |||
| Opinion about being final consumer of GE algae biofuel | |||
| Willingness to pay more money if higher engine performances were achieved compared to established biofuels | 0.078 | – | |
| Willingness to pay more money if environmental advantages were achieved compared to fossil fuels | 0.458 | – | |
| Suggestions to improve general social acceptance | |||
| Regulations before any genome engineered species is implemented | 0.912 | ||
| Higher or same economic benefits than using fossil fuels | 0.988 | ||
| Clear evidence of benefits use of genetic markers | 0.339 | ||
| Clear communication of risks and benefits of genome engineering technologies | 0.822 | ||
| Rigorous risk assessments of GM algae, involving scientists with minimal conflicts of interest, independent peer review, and public participation | 0.562 | ||
| Closed production systems with high security standards | 0.412 | ||
| Use of genetic markers | 0.672 | ||
| Minor survivability compared to natural strains | 0.734 | ||
| Use of new precise gene editing tools instead of traditional genome engineering | 0.353 | ||
| Regulations before any genome engineered species is implemented | 0.749 | ||
Cramer’s V values were calculated just in cases where p values < 0.05
Chi-square test p values between sociodemographic nominal variables (Appendix A: Table 6) and opinion ordinal values (Appendix A: Table 6)
| Sociodemographic nominal variables | Opinion ordinal variables | Cramer’s V | |
|---|---|---|---|
| Gender | |||
| Less environmental impact | 0.281 | ||
| Reduced GHG emissions and climate change | 0.492 | ||
| No competition with food | 0.773 | ||
| Superior engine performance | 0.778 | ||
| New rural jobs | 0.866 | ||
| Reduced fuel import dependency | 0.973 | ||
| Less environmental impact | 0.412 | ||
| Reduced GHG emissions and climate change | 0.800 | ||
| Less occupational risk | 0.639 | ||
| New rural jobs | 0.302 | ||
| Reduced fuel import dependency | 0.143 | ||
| Improve productivity | 0.299 | ||
| Require less energy | 0.413 | ||
| Need less nutrients uptake | 0.408 | ||
| Need less use of fresh water | 0.863 | ||
| Improve the controllability of the process | 0.920 | ||
| Improve economic feasibility | 0.686 | ||
| GMOs should partially replace fossil fuels | 0.382 | ||
| Opinion about general social acceptance | 0.129 | ||
| Variation of public acceptance in case of using gene-editing techniques | 0.177 | ||
| Opinion about regulating gene-edited organisms as GMOs | 0.256 | ||
| Fossil fuels | 0.770 | ||
| Established biofuels | 0.144 | ||
| GE algae biofuel | 0.536 | ||
| Solar photovoltaic power | 0.358 | ||
| Wind power | 0.887 | ||
| Hydropower | |||
| Working field | |||
| Less environmental impact | 0.926 | ||
| Reduced GHG emissions and climate change | 0.993 | ||
| No competition with food | |||
| Superior engine performance | 0.822 | ||
| New rural jobs | 0.132 | ||
| Reduced fuel import dependency | 0.443 | ||
| Less environmental impact | 0.750 | ||
| Reduced GHG emissions and climate change | 0.981 | ||
| Less occupational risk | 0.200 | ||
| New rural jobs | 0.802 | ||
| Reduced fuel import dependency | 0.786 | ||
| Improve productivity | 0.276 | ||
| Require less energy | |||
| Need less nutrients uptake | 0.138 | ||
| Need less use of fresh water | 0.286 | ||
| Improve the controllability of the process | |||
| Improve economic feasibility | 0.138 | ||
| GMOs should partially replace fossil fuels | 0.634 | ||
| Opinion about general social acceptance | 0.843 | ||
| Variation of public acceptance in case of using gene-editing techniques | 0.720 | ||
| Opinion about regulating gene-edited organisms as GMOs | |||
| Fossil fuels | |||
| Established biofuels | 0.238 | ||
| GE algae biofuel | 0.126 | ||
| Solar photovoltaic power | 0.056 | 0.230 | |
| Wind power | |||
| Hydropower | 0.427 | ||
Cramer’s V values were calculated only in cases where p values < 0.05