New technological trajectories to reduce fossil-fuel pollution and support sustainable socioeconomic systems

doi:10.21203/rs.3.rs-2323975/v1

Download PDF

Research Article

New technological trajectories to reduce fossil-fuel pollution and support sustainable socioeconomic systems

https://doi.org/10.21203/rs.3.rs-2323975/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

One of the fundamental problems in modern economies is high carbon emissions and diffusion of pollutants from industrial activities focused on fossil-based energy that generate detrimental effects on climate, environment and human population. The goal of this study is to analyze new trajectories of technologies that can reduce, whenever possible, environmental degradation and support a sustainable growth. A model of technological evolution is proposed to detect new technological trajectories directed to sustainability. Results reveal that technologies with a high sustainability perspective for reducing environmental pollution and climate change are: offshore wind turbines, carbon capture storage technology associated with renewable energy, cellular agriculture and blockchain technology directed positive environmental impact. Findings here can sustain decision making of policymakers towards investment in promising technological directions that reduce environmental pollution and sustain ecological transition and sustainable development in human society.

Renewable Resources

Environmental Policy

Environmental Economics

Sociology

Other Economics

fossil-based energy

environmental degradation

global warming

resources depletion

sustainable technologies

clean energy

The study concerning the human impact on the environment begins in 1860s (Marsh, 1864). The environmental change, driven by human and technological development, has increased since the first industrial revolution, such that several scholars suggest a new geological epoch called Anthropocene, which is based on a huge and predominant impact of human activities on earth and atmosphere (Crutzen and Stoermer, 2000; Zalasiewicz et al., 2011). Ruddiman (2003) defines the onset of the Anthropocene from a rise in CO₂ started 6,000 years-ago, whereas Crutzen and Stoermer (2000) and Steffen et al. (2007) argue the onset of the Anthropocene with the industrial age in the 18th century and with the acceleration of climate change from 1900s (cf., Bowman et al., 2011; Glikson, 2013; Steffen et al., 2007). Foley et al. (2013, p. 83) argue that from 1780s period begins the immense rises in human population and carbon emissions as well as atmospheric CO₂ levels, generating the so-called ‘great acceleration’. Chin et al. (2013, p. 1) maintain that the impact of human activities on environment is due to urban development, population growth, polluting industrialization, land cleaning, etc. (Coccia, 2021; Coccia and Bellitto, 2018). In particular, the industrialization of Europe, North America and emerging countries (e.g., Brazil, Turkey, India, etc.) is generating economic growth but also aspects of unsustainability that generate climate and sociodemographic change (Steingraber, 1997). Constant et al. (2014) argue that environmental pollution and economic growth have trends in the same direction. This relation is associated with a progressive urbanization and population growth that generate more consumption, resources depletion, and as a consequence, pollution and environmental change. Overall, then, population growth, technological development, mass production and consumption, and resources depletion, engender environmental pollution having critical climate and social impacts (Coccia, 2021). In this global context with a lot of environmental risks because of negative impact of human activities on natural resources that generates pollution and consequential climate change, one of the fundamental problems is the detection of sustainable technologies and eco innovations that can reduce environmental vulnerabilities for more sustainable socioeconomic systems (Sanni and Verdolini, 2022). The goal of the study here is to analyze directions of new technological trajectories that may reduce risk factors of increasing CO₂ emissions and support a sustainable development¹.

¹ For studies on sources and evolution of technologies see, Coccia, 2017, 2017a, 2017b, 2018a, 2018b, 2018c, 2020a, 2020b, 2020c, 2020b, 2022, Coccia and Bellitto, 2018; Coccia and Finardi, 2013; Coccia and Rolfo, 2000)

Ayres (1998) argues that fossil fuels and radical technological innovations are fundamental drivers of past and present human development (Sterner et al., 1998, p. 254; Coccia, 2010). Industrialization in the post-World War II is based on coal, natural gas, and petroleum-based feedstocks (cf., Campbell, 2002), which have generated economic growth and several innovations in heavy organic chemical industry, synthetic materials and petrochemicals (Ayres, 1990a, 1990b; Coccia, 2009, 2010, 2014, 2017c, 2018). However, industrialization and technological transformations are main drivers of urbanization, population growth and high environmental pollution that generate an anthropogenic and social change (cf., Belpomme et al., 2007). Meadows et al. (1972) argued that the natural resources of the Earth and the overall world ecosystem may not sustain economic and demographic growth rates well beyond the year 2100s, even with high technological development. The critical interrelated factors of this prediction are based on high population growth, deterioration of agricultural production, depletion of non-renewable resources, high industrial production and environmental pollution. However, the Club of Rome's report (Meadows et al., 1972) also suggests that the human society can create an ecosystem on Earth to indefinitely live if humanity imposes limits on the production of goods and utilization of natural resources and foster the recycle of materials directed to achieve and sustain a sustainable development for satisfying current needs without deteriorating environment for future generations.

Adam (2021) discusses the forecasting by United Nations that global population will grow to reach roughly 11 billion by 2100. In 2014, the International Institute for Applied Systems Analysis in Austria suggests that world population is likely to peak at 9.4 billion around 2070 and then will fall to 9 billion by 2090s, whereas the University of Washington in Seattle (USA) argues that global population will peak at around 9.7 billion in 2060s, and then will decline to about 8.8 billion by 2100. The different results of these demographic projections are due to the uncertainty of long-run change of fertility rates and population numbers associated with unforeseen events, such as pandemics of new vital agents (e.g., COVID-19), conflicts, natural disasters, etc. High population growth generates some critical aspects in socioeconomic systems (Global change, 2022): increase of the extraction and/or consumption of natural resources (fossil fuels, minerals, trees, water); high urbanization; high production and consumption of goods; tons of waste dumped on the planet; high environmental pollution, pathogenic microorganisms in the environment; etc. (cf., La Scalia et al., 2022). These aspects are main drivers of climate change and global warming. In fact, many countries focus on cheap fossil fuels to support their economies especially after pandemic crisis or international crises for wars, but carbon emissions for fossil fuel consumption are supporting a + 5°C of warming by 2100 also with thawing permafrost (Hausfather and Peters, 2020; Moss et al., 2010; Tollefson, 2020). Long-term effects of climate change in human society are due to (IPCC, 2007; 2013; NASA Global climate change, 2022): the growth of the length of the frost-free season (and the corresponding growing season) because of heat-trapping gas emissions, average growth of precipitation, droughts and heat waves are projected to become more intense, the growth of the intensity, frequency and duration of hurricanes, increase of global sea level by more than 5 inches and it is projected to rise another 1 to 10 feet by 2100 because of melting land ice. Current economies in 2020s are based on cheap fossil fuels and nuclear power that create environmental pollution or renewable energy that is still costly to produce and does not satisfy energy consumption of countries. Scholars are that to cope with climate change, future societies have to be more resilient and better adapted to deal with extreme environmental and social threats (Campbell, 2002). Ali et al. (2021) show a positive relation between natural resource depletion and environmental degradation in developed countries, whereas renewable consumption of energy has negative influence on environmental deterioration. Human activities have caused main environmental and atmospheric damages with an irreversible decline of atmospheric O₂ and now societies should take actions to reduce risk factors of environmental deterioration. Hence, in order to reduce environmental risks, driven by human development, nations have, more and more, to find solutions and resolutions directed to new sustainable technologies for improving environment and wellbeing of people. Next section presents the methodology to detect, whenever possible, sustainable technologies that may mitigate environmental vulnerabilities and natural resources depletion for a global sustainable future.

Sources and Sample

The study uses data of Scopus (2022), a multidisciplinary database covering journal articles, conference proceedings, and books. Scopus (2022) database also includes patent records derived from different world-wide patent offices. In particular, the window of "Search documents" in the Scopus (2022) database is used to identify scientific documents and patents having in article title, abstract or keywords the terms described in Table 1 that are main sustainable technologies according to current literature of environmental and sustainability science (Gonzalo et al., 2022; Li et al., 2022; Wang et al., 2022; Balaji and Rabiei, 2022; Elavarasan et al., 2022; Chapman et al., 2022; Gadikota, 2021; Bapat et al., 2022; Moritz et al., 2022; Esmaeilzadeh, 2022; Strepparava et al., 2022). Data are downloaded on 30th March 2022. Scientific products (articles, conference papers, conference reviews, book chapters, short surveys, letters, etc.) and patents are basic units here for scientific and technology analyses (Coccia et al., 2022) that can explain the interactions between natural and social systems, and with how those interactions affect the reduction of environmental pollution and support goals of sustainability to meet present and future generations while conserving the planet's life support systems.

Table 1

Queries and data analyzed
Queries of research on sustainable technologies	Data analyzed and type
"offshore wind turbine"	6,978 document results
	3,791 patent results
"aluminium battery"	228 document results
	1,033 patent results
"green hydrogen"	1,000 document results
	172 patent results
"blue hydrogen"	77 document results
	198 patent results
"carbon-negative technologies"	34 document results
	10 patent results
"floating photovoltaic systems"	76 document results
	43 patent results
"carbon capture and storage"	7,005 document results
	1,204 patent results
"thermal energy storage"	15,573 document results
	8,888 patent results
"blockchain technology"	10,768 document results
	7,848 patent results
"cellular agriculture"	81 document results
	21 patent results
"clean steel production"	92 document results
	28 patent results
"wave power systems"	78 document results
	341 patent results

Measures

The scientific development of sustainable technologies is investigated considering:

Number of articles and all scientific products using the search queries described in Table 1 for all technologies under study; the year 2022 is excluded because ongoing and data do not affect the evolution of trends.

This study also analyzes patents that indicate inventions and potential innovations and show the evolution of new technological trajectories that affect the challenges of sustainability:

Number of patents using the search queries described in Table 1 for all technologies under study to detect the technological trajectories; the year 2022 is also excluded here because ongoing and data do not affect the detection of trends.
Data analysis procedure and models of analysis

Descriptive statistics of data described in Table 1 is performed, using mean, standard deviation, skewness and kurtosis coefficients to check the normality of distribution and if variables are not normal, it is applied a logarithmic transformation to have normality and perform appropriate parametric analysis for robust and consistent results.

The tool "Search documents" in Scopus (2022) provides a time series of document results and patents of terms indicated in Table 1.

Firstly, trends of research field/technology i at t are visualized with the following model:

Log y _i,t = a + b time + u_i,t [1]

y _t is scientific products or patents; t = time
a is a constant; b is the coefficient of regression; u_t = error term
log has base e = 2.7182818

Secondly, the evolution of sustainable technologies to detect future projection is analyzed with a model of technological diffusion in which the number of patents (Y) is a function of the number of scientific production (X) over time, considering X and Y two basic elements of technological system (cf., Sahal, 1981). This approach provides the relative rate of growth that shows how sustainable technology evolves over the course of time. To operationalize this technology analysis, proposed model measures the effects of the accumulation of scientific knowledge (publications) on patents’ growth to detect the evolution of sustainable technologies (cf., Sahal, 1981):

\({log}Y={log}A+{B}_{}{log}X\) [1]

A = constant; B is the evolutionary coefficient of growth that measures the evolution of technology Y in relation to scientific production X.

The value of \(B\) in the model [1] measures the relative growth of Y in relation to the growth of X and it indicates different patterns of technological evolution as follows:

B<1, the whole system of sustainable technology has a slowing down evolution over the course of time.
B=1, the whole system here has a proportional evolution of its elements (growth).
B>1, this pattern denotes disproportionate advances of technology Y that has an accelerated evolution over the course of time.

This log-log model [1] has linear parameters that are estimated with the Ordinary Least-Squares Method (OLS). Statistical analyses are performed with the IBM SPSS Statistics 26 ®.

First, data are transformed in logarithmic scale to have normality in the distribution of variables for appropriate parametric analyses and a better visual representation of trends.

Model [1] is used to visualize trends of publications and patents of sustainable technologies. In particular, Fig. 1 shows the scientific development of different sustainable technologies, whereas Fig. 2 shows the evolution of sustainable technologies based on patents.

Trends of Figs. 1 and 2 are combined and analyzed with model [2] to assess the relative rate of growth of these technologies over time.

Table 2

Estimated relationships of patents on scientific production of technologies for a sustainable future
Sustainable technologies	Coefficient b₁	Constant a	F	R²
Offshore wind turbines	1.062***	−0.968**	391.65***	.949
Floating photovoltaic systems	.309	.840*	2.75	.282
Wave power systems	.840**	1.16***	7.68**	.22
Green hydrogen	.584***	.101	45.84***	.741
Blue hydrogen	.542*	.956***	6.33*	.297
Carbon negative technologies	.039	.383	.015	.004
Clean steel production	−.063	.379	.046	.005
Aluminum battery	.600***	2.295***	19.71***	.461
Carbon Capture storage	2.28***	−9.73***	165.09***	.92
Thermal energy storage	.935**	.036	319.33***	.87
Cellular agriculture	2.76*	−6.65*	374.61*	.99
Blockchain technology	1.22***	−2.100**	317.03***	.99

Note: log-log model. Dependent variable: Patents of sustainable technology i; Explanatory variable: publications of sustainable technology i; *** significant at 1‰; ** significant at 1%; * significant at 5%. F is the ratio of the variance explained by the model to the unexplained variance. R² is the coefficient of determination.

Table 2, using the coefficients of regression of model [2], reveals that sustainable technologies that have B > 1, i.e., accelerated pathway of technological evolution directed to challenges of sustainability, are:

Offshore wind turbines
Carbon Capture storage
Cellular agriculture
Blockchain technology

Instead, sustainable technologies that have B < 1, a slowdown of technological evolution are:

Wave power systems
Green hydrogen
Blue hydrogen
Aluminum battery
Thermal energy storage

Other technologies do not a significant coefficient B, and as a consequence are not considered.

In particular, the coefficient B > 1 of evolution of sustainable technologies in Table 2 suggests a disproportionate (accelerated) growth of these technologies over time: they can affect future sustainability with consequential economic and social change. In particular, these technologies directed to challenges of sustainability are described below to clarify their potential applications for a revolutionary shift in future socioeconomic systems:

Offshore wind turbines. Wind power can be onshore (land) and offshore (sea) based on the location of the wind farm. Offshore wind farms generate more power, less environmental impact, and have the possibility to be of larger in size (Gonzalo et al., 2022). This renewable and sustainable energy production system offers promising perspectives for the future sustainability. In fact, technologies for wind energy are a main renewable energy, since production and maintenance of costs decrease for learning processes, and their efficiency and reliability increase, favoring the competitiveness of this industry (Oh, 2020). Wang et al. (2022) argue that from 2005 to 2019, wind power technology has experienced significant development with over 1,100% increase in global cumulative installed wind capacity, achieving about 651 GW at the end of 2019. This development is due to a wind industry that is moving to offshore, since the wind speed in offshore locations is steadier and stronger and there is more space available at sea to install powerful wind turbines when compared to the land. Li et al. (2022) show that coastal communities can have energy savings with the support of a hybrid offshore wind and tidal stream energy generation system.
Carbon capture storage. Balaji and Rabiei (2022) argue that Carbon Capture, Storage and Utilization (CCUS) is a key activity used for reduction of carbon emissions and support a sustainable transition from traditional power sectors to low-carbon economy. In this context, carbon-dioxide pipelines are important technologies for proper and safe deployment of CCUS infrastructure. Elavarasan et al. (2022) analyze European areas and argue that in achieving climate neutrality, various decarbonization policies should be directed to district heating network with bio- and geothermal energy resource that highly favors clean heat transformation scenario. In addition, new technologies of hydrogen utilization and carbon capture storage and utilization can pivot climate neutrality in sectors that are difficult to decarbonize. Gadikota (2021) maintains that a main goal in science and society is new chemical processes that can reduce the carbon intensity of energy and resource conversion processes. Diverse interventionist technologies to capture current CO₂ emissions, reuse and store CO₂ continue to be developed, but a main aspect across different technologies is the role of inorganic solid carbonate transformations using anthropogenic CO₂ and the development of predictive controls over these pathways. Chapman et al. (2022) argue that to keep global temperature increase below 1.5 degrees because of greenhouse gas emissions, it is more and more important the achievement of carbon neutrality. This goal can be achieved with new technologies that include hydrogen materials, bio-mimetic catalysts, electrochemistry, thermal energy and absorption, carbon capture, storage and management and refrigerants. Of course, this goal needs an international policy based on multidisciplinary international collaboration.
Cellular agriculture. Agricultural energy use and practices generate 1% of CO₂ emissions and 38% of methane emissions, the latter mainly from livestock production. Carbon emissions can be reduced through more sustainable farming practices, such as regenerative agriculture that enhances soil carbon storage and protects biodiversity, agroecological systems and cellular agriculture (Cho, 2022; Pronti and Coccia, 2021). Moreover, current food production systems have to cope with the growth of world-wide population that is predicted to achieve about 10 billion by 2100 (Willett et al., 2019). In the presence of a growing demographic trend and more demand for protein food, human society needs of new model and approach of agricultural and livestock production to supply nutritious food, preserving whenever possible sustainability challenges directed to reduce deforestation, CO₂ emissions, climate change, environmental pollution, emerging diseases, etc. (Bontempi and Coccia, 2021; Bontempi et al., 2021; Coccia, 2020; Edeme et al., 2020; Pronti and Coccia, 2021). Cellular agriculture can be a main element of new food agriculture systems. Cellular agriculture, vertical urban farming, and digital agriculture associated with traditional means can support an industrial change to transform food agriculture and manufacturing systems to be resilient and to satisfy increasing demand of food worldwide and sustain planet's life support systems (Bapat et al., 2021). This systemic transformation from conventional agricultural systems to a sustainable cellular agriculture is based on new cell-cultivation technologies to produce animal products (Cavallo et al., 2015; Pronti and Coccia, 2021). The study by Moritz et al. (2022) argues that the political and policy stakeholders are aware of the changes that are needed, nevertheless a large-scale industrial change from conventional to the cellular agriculture system may not be a plausible solution in the near future.
Blockchain technology. Environmental, social and economic sustainability issues are challenging the current socioeconomic systems. Blockchain is a disruptive technology that could fundamentally generate industrial and corporate change to support innovative efforts, enabling technology transfer to create a sustainable and clean global future (Howson, 2019). Blockchain is not limited to digital currencies and is a general technology that can be used in several industrial sectors such as healthcare, supply chain management, digital rights management, energy, and public governance (Hughes et al., 2019; Coccia, 2017b; 2020a). Blockchain platforms use a decentralized network of distributed nodes to validate transactions and maintain the system’s data integrity (Centobelli et al., 2021). Thus, a chain of blocks containing operation information avoids having a central repository or middleman to complete transactions. Results show that although blockchain technology may create several benefits, its applications in specific sectors, such as healthcare, are still in their early stages (Esmaeilzadeh, 2022). For instance, in the presence of the problem of reducing greenhouse gas emissions by 2050, one of the solutions is the integration of an increasing number of distributed renewable energy sources into energy supply systems: from the conventional top-down flow of electricity (with large powerplants covering all power demand) to decentralized system in which energy is created and stored at the end-user level (Javid et al., 2021). This industrial change can support a local energy market (LEM) in a specific location such that energy customers are inter-related with producers to trade energy on a market platform. In particular, a LEM based on the usage of a blockchain technology tailored for internet of things applications provides new potential for decentralized market architectures and to deliver user-friendly tools that are required for the customers to engage in a wise energy consumption process (Strepparava et al., 2022).

Technological change supports human development based on industrial expansion and mass production in society, but it also generates resource-consuming and environmental damaging. To put it differently, human activity and development induce anthropogenic environmental effects damaging ecosystems (Coccia, 2021). Some scholars consider the relationship between human development and negative impact on environment as an inverted U-shaped curve –environmental Kuznets curve – because technological change increases the pollution in the early stages of economic development, but beyond some levels of wealth, wealthier geographical areas can lead to environmental improvement with sustainable technologies and environmental policies (Ansuategi et al., 1998; Coccia, 2018, 2021, 2019a; Stern, 2004). Current, capitalism model has positive sides but it is also the source of high rate of resource use, mismanagement of both renewable and nonrenewable resources, social inequality, and environmental pollution (Baumol et al., 2007). Meadows et al. (1972) argue that in conventional environmental analyses the issue of a shortage or depletion of natural resources is due to overpopulation (Malthusian approach). The Royal Society of London suggests the need “to develop socio-economic systems and institutions that are not dependent on continued material consumption growth” (Sulston, 2012). The solution of these problems of capitalism and continuous development is to stop high level of capital accumulation to mitigate the risk factors of degradation of the environment at a global level. The organization of economic system should be directed to sustainable technologies, eco innovations and circular economies in local, regional, and global ecosystems to reduce environmental risks and preserve a healthy biosphere for all people (Magdoff, 2013; Magdoff and Bellamy Foster, 2011; Saeli et al., 2022). The world can experience in future a period of great tension internationally for energy issues, conflicts and climate change, such that the transition to sustainable energy systems and technologies will represent an important goal to achieve as soon as possible. Countries have to support the rapid development of alternative renewable energy sources and sustainable technologies for a comprehensive green strategy to mitigate, whenever possible, next social, economic and political tensions with the transition from conventional to sustainable energy systems (Calza et al., 2020; Nti et al., 2022). As urban and national conditions can likely deteriorate still further for energy, economic and social issues, a sustainable world needs resolution approaches and to reduce unsustainable energy and industrial policies, associated with manifold risk factors, and foster new sustainable communities based on an equilibrium between environment, natural resources and human society: a model of ecosocialism for a better cooperation among people to deal with resource limits (Aidnik, 2022; Adaman and Devine, 2022). In addition, the reduction of negative impact of human activity and environmental risks on ecosystems should be also based on industrial policies to support sustainable technological innovations (cf., Khan et al., 2022; Sterner and Coria, 2012).

As far as I am concerned, technological change is a human activity that has a main role for human development and wellbeing, though it is generating anthropogenic environmental change and a huge negative impact on ecosystems. However, some negative effects can be removed in the long run with new sustainable technology, eco innovations, green strategies and new organization of socioeconomic systems directed to reduce environmental pollution. In brief, human activity should be engaged in sustainable technological innovations and economic systems wot a lung-run strategies to reduce coal and petroleum-based economies and, as a consequence, the negative impact of human interactions on ecosystems for the real well-being of future generations. According to Linstone (2010, p. 1417, original emphasis): “the global future will strongly depend on our willingness to take near-term action for a sustainable long-term future” (cf., Rosen, 2010).

This study has tried to provide, through empirical evidence, main technological trajectories for future sustainability. However, we know that other things are often not equal over time because technological development, human conflicts, continuous production and high resource depletion have an infinite set of consequences on environment and human society with a growing population, such that results provide temporary and partial truths in the presence of complex systems and interactions. Despite some limitations, the results presented here illustrate critical technological trajectories for sustainable development that may reduce risk factors of environmental pollution and health disorders. The description of these directions of sustainable technologies here provide information to extend knowledge to support numerous implications for decision making of policymakers and funding agencies regarding sponsoring specific research fields and technological trajectories that can accelerate the development of sustainable socioeconomic systems (cf., Coccia, 2018d, 2019, 2021a).

Nevertheless, these conclusions are of course tentative. Future research should consider new data when available, and when possible, apply new approaches to reinforce proposed results directed to explain the evolution of sustainable technologies. Hence, there is need for much more research in these topics because of complex confounding and situational factors that affect the interactions between natural and socioeconomic systems.

Declaration of competing interest

The author declares that he is the sole author of this manuscript, and he has no known competing financial interests or personal relationships that could influence the work reported in this paper. This study has no funders.

Adam D. (2021). How far will global population rise? Researchers can't agree. Nature, 597(7877), 462–465. https://doi.org/10.1038/d41586-021-02522-6
Adaman Fikret & Pat Devine (2022) Revisiting the Calculation Debate: A Call for a Multiscale Approach, Rethinking Marxism, 34:2, 162–192, DOI: 10.1080/08935696.2022.2051374
Aidnik Martin (2022) Envisioning a Utopian Ecosocialism in the Darkness of the Covid-19 Pandemic, Capitalism Nature Socialism, DOI: 10.1080/10455752.2021.2016878
Ali A., Audi, M., & Roussel, Y. (2021). Natural Resources Depletion, Renewable Energy Consumption and Environmental Degradation: A Comparative Analysis of Developed and Developing World. International Journal of Energy Economics and Policy, 11(3), 251–260.
Ansuategi A, Barbier E.B, Perrings C.A. 1998. The environmental Kuznets curve. In J.C.J.M van den Bergh, M.W Hofkes (Eds.), Theory and implementation of economic models for sustainable development, Kluwer, Dordrecht.
Ayres R. U. 1998. Towards a Disequilibrium Theory of Endogenous Economic Growth. Environmental and Resource Economics, vol. 11, n. 3–4, pp. 289–300.
Ayres R.U. 1990b. Technological transformations and long waves. Part II. Technol. Forecast. Soc. Chang. 37 (2), 111–137.
Ayres R.U., 1990a. Technological transformations and long waves. Part I. Technol. Forecast. Soc. Chang. 37 (1), 1–37.
Balaji K., Rabiei M. 2022. Carbon dioxide pipeline route optimization for carbon capture, utilization, and storage: A case study for North-Central USA. Sustainable Energy Technologies and Assessments 51,101900
Bapat, S., Koranne, V., Shakelly, N., (...), Rajurkar, K.P., Malshe, A.P. 2022. Cellular agriculture: An outlook on smart and resilient food agriculture manufacturing. Smart and Sustainable Manufacturing Systems 6(1), pp. 1–11.
Baumol W. J., Litan R.E., Schramm C. J. 2007. Good Capitalism, Bad Capitalism, and the Economics of Growth and Prosperity, Yale University Press (New Haven, USA)
Belpomme D., Irigaray P., Hardell L., Clapp R., Montagnier L., Epstein S., Sasco A.J.(2007) “The multitude and diversity of environmental carcinogens”, Environmental Research, vol. 105, n. 3, pp. 414–429.
Bontempi E., Coccia M., 2021. International trade as critical parameter of COVID-19 spread that outclasses demographic, economic, environmental, and pollution factors, Environmental Research, vol. 201, n. 111514, https://doi.org/10.1016/j.envres.2021.111514
Bontempi E., Coccia M., Vergalli S., Zanoletti A. 2021. Can commercial trade represent the main indicator of the COVID-19 diffusion due to human-to-human interactions? A comparative analysis between Italy, France, and Spain, Environmental Research, vol. 201, n. 111529, https://doi.org/10.1016/j.envres.2021.111529
Bowman D.M. et al. 2011. The human dimension of fire regimes on Earth. Journal of Biogeography, vol. 38, n. 12, pp. 2223–2236.
Calza F., Parmentola A., Tutore I., 2020. Big data and natural environment. How does different data support different green strategies? Sustainable Futures, Volume 2, n. 100029, https://doi.org/10.1016/j.sftr.2020.100029.
Campbell C.J. 2002. Petroleum and People. Population and Environment, vol. 24, n. 2, pp. 193–207.
Cavallo, E., Ferrari E., Coccia M. 2015. Likely technological trajectories in agricultural tractors by analysing innovative attitudes of farmers. International Journal of Technology, Policy and Management, vol. 15, n. 2, pp. 158–177, http://dx.doi.org/10.1504/IJTPM.2015.069203
Centobelli P, Cerchione R, Del Vecchio P, Oropallo E, Secundo G. Blockchain technology for bridging trust, traceability and transparency in circular supply chain. Inf Manag 2021; 103508
Chapman, A., Ertekin, E., Kubota, M., (...), Kirchheim, R., Sofronis, P. 2022. Achieving a Carbon Neutral Future through Advanced Functional Materials and Technologies, Bulletin of the Chemical Society of Japan 95(1), pp. 73–103
Chin A., Fu R., Harbor J., Taylor M. P., Vanacker V. (2013) “Anthropocene: Human interactions with earth systems”, Anthropocene, vol. 1, pp. 1–2.
Cho R. 2022. What Is Decarbonization, and How Do We Make It Happen? Columbia Climate School, https://news.climate.columbia.edu/2022/04/22/what-is-decarbonization-and-how-do-we-make-it-happen/
Coccia M. 2009. Measuring the impact of sustainable technological innovation. International Journal of Technology Intelligence and Planning, vol. 5, n. 3, pp. 276–288. https://doi.org/10.1504/IJTIP.2009.026749
Coccia M. 2010. Foresight of technological determinants and primary energy resources of future economic long waves. International Journal of Foresight and Innovation Policy, vol. 6, n. 4, pp. 225–232, https://doi.org/10.1504/IJFIP.2010.037468
Coccia M. 2014. Steel market and global trends of leading geo-economic players. International Journal of trade and global markets, vol. 7, n.1, pp. 36–52, http://dx.doi.org/10.1504/IJTGM.2014.058714
Coccia M. 2017. Sources of technological innovation: Radical and incremental innovation problem-driven to support competitive advantage of firms. Technology Analysis & Strategic Management, vol. 29, n. 9, pp. 1048–1061, https://doi.org/10.1080/09537325.2016.1268682
Coccia M. 2017a. A new classification of technologies, Working Paper CocciaLab n. 26/2, Arizona State University (USA), Available at permanent arXiv eLibrary: http://arxiv.org/abs/1712.07711
Coccia M. 2017b. The Fishbone diagram to identify, systematize and analyze the sources of general purpose technologies. J. Adm. Soc. Sci., vol. 4, n. 4, pp. 291–303, http://dx.doi.org/10.1453/jsas.v4i4.1518
Coccia M. 2017c. New directions in measurement of economic growth, development and under development, Journal of Economics and Political Economy, vol. 4, n. 4, pp. 382–395, http://dx.doi.org/10.1453/jepe.v4i4.1533
Coccia M. 2018. An introduction to the theories of national and regional economic development, Turkish Economic Review, vol. 5, n. 4, pp. 350–358, http://dx.doi.org/10.1453/ter.v5i4.1794
Coccia M. 2018a. Classification of innovation considering technological interaction, Journal of Economics Bibliography, vol. 5, n. 2, pp. 76–93, http://dx.doi.org/10.1453/jeb.v5i2.1650
Coccia M. 2018b. Competition between basic and applied research in the organizational behaviour of public research labs, Journal of Economics Library, vol. 5, n. 2, pp. 118–133, http://dx.doi.org/10.1453/jel.v5i2.1652
Coccia M. 2018c. General properties of the evolution of research fields: a scientometric study of human microbiome, evolutionary robotics and astrobiology, Scientometrics, vol. 117, n. 2, pp. 1265–1283, https://doi.org/10.1007/s11192-018-2902-8
Coccia M. 2018d. Motivation and theory of self-determination: Some management implications in organizations, Journal of Economics Bibliography, vol. 5, n. 4, pp. 223–230, http://dx.doi.org/10.1453/jeb.v5i4.1792
Coccia M. 2019. Intrinsic and extrinsic incentives to support motivation and performance of public organizations, Journal of Economics Bibliography, vol. 6, no. 1, pp. 20–29, http://dx.doi.org/10.1453/jeb.v6i1.1795
Coccia M. 2019a. Comparative World-Systems Theories. A. Farazmand (ed.), Global Encyclopedia of Public Administration, Public Policy, and Governance, Springer, https://doi.org/10.1007/978-3-319-31816-5_3705-1
Coccia M. 2020. Factors determining the diffusion of COVID-19 and suggested strategy to prevent future accelerated viral infectivity similar to COVID, Science of the Total Environment, volume, 729, n. 138474, https://doi.org/10.1016/j.scitotenv.2020.138474
Coccia M. 2020a. Fishbone diagram for technological analysis and foresight. Int. J. Foresight and Innovation Policy, Vol. 14, Nos. 2/3/4, pp. 225–247. DOI: 10.1504/IJFIP.2020.111221
Coccia M. 2020b. Destructive Technologies for Industrial and Corporate Change. In: Farazmand A. (eds), Global Encyclopedia of Public Administration, Public Policy, and Governance. Springer Cham, https://doi.org/10.1007/978-3-319-31816-5_3972-1
Coccia M. 2020c. Asymmetry of the technological cycle of disruptive innovations. Technology Analysis & Strategic Management, vol. 32, n. 12, p. 1462–1477. https://doi.org/10.1080/09537325.2020.1785415
Coccia M. 2020d. The evolution of scientific disciplines in applied sciences: dynamics and empirical properties of experimental physics, Scientometrics, n. 124, pp. 451–487. https://doi.org/10.1007/s11192-020-03464-y
Coccia M. 2021. Effects of human progress driven by technological change on physical and mental health, STUDI DI SOCIOLOGIA, 2021, N. 2, pp. 113–132, https://doi.org/10.26350/000309_000116
Coccia M. 2021a. Comparative Critical Decisions in Management. In: Farazmand A. (eds), Global Encyclopedia of Public Administration, Public Policy, and Governance. Springer, Cham. https://doi.org/10.1007/978-3-319-31816-5_3969-1
Coccia M. 2022. Technological trajectories in quantum computing to design a quantum ecosystem for industrial change, Technology Analysis & Strategic Management. https://doi.org/10.1080/09537325.2022.2110056
Coccia M., Bellitto M. 2018. A critique of human progress: a new definition and inconsistencies in society, Quaderni IRCrES-CNR, 4(3), 51–67. http://dx.doi.org/10.23760/2499-6661.2018.017
Coccia M., Benati I. 2018. Rewards in public administration: A proposed classification, Journal of Social and Administrative Sciences, vol. 5, n. 2, pp. 68–80, http://dx.doi.org/10.1453/jsas.v5i2.1648
Coccia M., Finardi U. 2013. New technological trajectories of non-thermal plasma technology in medicine. Int. J. Biomedical Engineering and Technology, vol. 11, n. 4, pp. 337–356, DOI: 10.1504/IJBET.2013.055665
Coccia M., Mosleh M., Roshani S., 2022. Evolution of quantum computing: Theoretical and innovation management implications for emerging quantum industry. IEEE Transactions on Engineering Management, DOI: 10.1109/TEM.2022.3175633
Coccia M., Rolfo S. 2000. Ricerca pubblica e trasferimento tecnologico: il caso della regione Piemonte in Rolfo S. (eds) Innovazione e piccole imprese in Piemonte, FrancoAngeli Editore, Milano (Italy), pp. 236–256. ISBN: 9788846418784
Constant K., Nourry C., Seegmuller T. (2014) “Population growth in polluting industrialization”, Resource and Energy Economics, vol. 36, n. 1, pp. 229–247.
Crutzen P.J., Stoermer E.F. 2000. “The Anthropocene”, Global IGBP Change Newsletter, n. 41, pp. 17–18.
Edeme R. K., Nelson C. Nkalu, Janefrancis C Idenyi, Winnie O. Arazu, 2020. Infrastructural Development, Sustainable Agricultural Output and Employment in ECOWAS Countries, Sustainable Futures, Volume 2, bn. 100010, https://doi.org/10.1016/j.sftr.2020.100010.
Elavarasan Madurai, R., Pugazhendhi, R., Irfan, M., (...), Khan, I.A., Campana, P.E. 2022vision. Renewable 159,112204
Elavarasan R. M., Pugazhendhi R., Muhammad Irfan, Lucian Mihet-Popa, Irfan Ahmad Khan, Pietro Elia Campana. 2022. State-of-the-art sustainable approaches for deeper decarbonization in Europe – An endowment to climate neutral vision. Renewable and Sustainable Energy Reviews, vol. 159, 112204,https://doi.org/10.1016/j.rser.2022.112204.
Esmaeilzadeh, P. 2022. Benefits and concerns associated with blockchain-based health information exchange (HIE): a qualitative study from physicians' perspectives. BMC Medical Informatics and Decision Making, 22(1),80
Foley S. F., Gronenborn D., Andreae M. O., Kadereit J. W., Esper J., Scholz D., Pöschl U., Jacob D. E., Schöne B. R., Schreg R., Vött A., Jordan D., Lelieveld J., Weller C. G., Alt K. W., Gaudzinski-Windheuser S., Bruhn K. C., Tost H., Sirocko F., Crutzen P. J. 2013. The Palaeoanthropocene – The beginnings of anthropogenic environmental change, Anthropocene, vol. 3, pp. 83–88.
Gadikota G. 2021Carbon mineralization pathways for carbon capture, storage and utilization. Communications Chemistry 4(1),23
Glikson A. 2013. Fire and human evolution: The deep-time blueprints of the Anthropocene. Anthropocene, vol. 3, pp. 89–92.
Global change 2022. Population growth. A project of the University of California Museum of Paleontology https://ugc.berkeley.edu/background-content/population-growth/ (accessed March 2022)
Gonzalo Peinado, A., Benmessaoud, T., Entezami, M., García Márquez, F.P. 2022. Optimal maintenance management of offshore wind turbines by minimizing the costs, Sustainable Energy Technologies and Assessments, 52,102230
Hausfather Z., Peters G. P. 2020. Emissions - the 'business as usual' story is misleading. Nature, 577(7792), 618–620. https://doi.org/10.1038/d41586-020-00177-3
Howson P. 2019. Tackling climate change with blockchain. Nat. Clim. Chang. 9, 644–645 (2019). https://doi.org/10.1038/s41558-019-0567-9
Hughes A., Park A., Kietzmann J., Archer-Brown C. 2019. Beyond Bitcoin: what blockchain and distributed ledger technologies mean for firms. Bus Horiz., 62, pp. 273–81.
IPCC 2007, Summary for Policymakers, in Climate Change 2007: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK, p. 17.
IPCC, 2013: Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Javid, I., Chauhan, A., Thappa, S., Verma, S.K., Anand, Y., Sawhney, A., Tyagi, V.V., Anand, S., 2021. Futuristic decentralised clean energy networks in view of inclusive-economic growth and sustainable society. J. Cleaner Prod. 127304.
Khan, M.N., Huang, J., shah, A., (...), Zhang, H., Núñez-Delgado, A. 2022. Mitigation of greenhouse gas emissions from a red acidic soil by using magnesium-modified wheat straw biochar. Environmental Research 203,111879
La Scalia G, La Fata CM, Certa A, Micale R. 2022. A multifunctional plant for a sustainable reuse of marble waste toward circular economy. Waste Management & Research. 2022;40(6):806–813. doi:10.1177/0734242X211029161
Li M., Cao S., Zhu X., Xu Y. 2022. Techno-economic analysis of the transition towards the large-scale hybrid wind-tidal supported coastal zero-energy communities. Applied Energy 316,119118
Linstone H. A. 2010. Historians and complexity: trends vs. collapses? Technological Forecasting and Social Change, vol. 77, n. 8, pp. 1415–1428.
Magdoff F. 2013. Global Resource Depletion: Is Population the Problem? Monthly Review, DOI: https://doi.org/10.14452/MR-064-08-2013-01_2
Magdoff F., Bellamy Foster J. 2011. What Every Environmentalist Needs to Know About Capitalism. Monthly Review Press, New York, pp. 124–131.
Marsh G.P. (1864) Man and Nature. Reprinted in 1965. Harvard University Press, Cambridge.
Meadows D., Meadows D. Randers J., Behrens III W.W (1972). The Limits to Growth; A Report for the Club of Rome's Project on the Predicament of Mankind. New York: Universe Books. ISBN 0876631650.
Moritz, J., Tuomisto, H.L.,Ryynänen, T. 2022. The transformative innovation potential of cellular agriculture: Political and policy stakeholders’ perceptions of cultured meat in Germany Journal of Rural Studies, 89, pp. 54–65
Moss, R., Edmonds, J., Hibbard, K. et al. 2010. The next generation of scenarios for climate change research and assessment. Nature 463, 747–756 (2010). https://doi.org/10.1038/nature08823
NASA Global climate change (2022). The Effects of Climate Change. https://climate.nasa.gov/effects/ (Accessed March 2022)
Nti K. E., Samuel Jerry Cobbina, Eunice Efua Attafuah, Evelyn Opoku, Michael Amoah Gyan, 2022. Environmental sustainability technologies in biodiversity, energy, transportation and water management using artificial intelligence: A systematic review,Sustainable Futures,Volume 4, n. 100068, https://doi.org/10.1016/j.sftr.2022.100068.
Oh H. S. 2020. Unit commitment considering the impact of deep cycling, Sustainable Futures, Volume 2, n. 100031,https://doi.org/10.1016/j.sftr.2020.100031.
Pronti, A., Coccia, M. 2021. Agroecological and conventional agricultural systems: comparative analysis of coffee farms in Brazil for sustainable development, Int. J. Sustainable Development, Vol. 23, Nos. 3/4, pp. 223–248, https://doi.org/10.1504/IJSD.2020.115223
Rosen R.A., Electris C., Raskin P.D. (2010), Global Scenarios for the Century Ahead, Tellus Institute.
Ruddiman W. F. 2003. The anthropogenic greenhouse era began thousands of years ago. Climate Change, vol. 61, pp. 261–293.
Saeli M.i, N. Capela M., Campisi T., Seabra M. P., Tobaldi D. M., La Fata C. M., 2022. Architectural technologies for life environment: Spent coffee ground reuse in lime-based mortars. A preliminary assessment for innovative green thermo-plasters, Construction and Building Materials, Volume 319,n. 126079, https://doi.org/10.1016/j.conbuildmat.2021.126079.
Sahal, D. 1981. Patterns of Technological Innovation; Addison-Wesley Publishing Company, Inc.: Reading, MA, USA.
Sanni M., Verdolini E., 2022. Eco-innovation and openness: Mapping the growth trajectories and the knowledge structure of open eco-innovation. Sustainable Futures, Volume 4, n. 100067, https://doi.org/10.1016/j.sftr.2022.100067.
Scopus 2022. Start exploring, search documents. ttps://www.scopus.com/search/form.uri?display=basic#basic (accessed “5 March 2022)
Steffen W., Crutzen P.J., McNeill J.R. 2007. The Anthropocene: are humans now overwhelming the great forces of nature? AMBIO, vol. 36, pp. 614–621.
Steingraber S. (1997) Industrial pollution, pesticides, and cancer. Living Downstream. An Ecologist Looks at Cancer and the Environment. Reading, Addison-Wesley, Massachusetts, ISBN 0-201-48303-3.
Stern D. I. 2004. The Rise and Fall of the Environmental Kuznets Curve, World Development, vol. 32, n. 8, pp. 1419–1439,https://doi.org/10.1016/j.worlddev.2004.03.004
Sterner T., Coria J. (2012) Policy instruments for environmental and natural resource management, 2nd ed. RFF Press and Routledge, New York, NY.
Sterner T., Jeroen C. J., Van Den Bergh M. (1998) “Frontiers of Environmental and Resource Economics”, Environmental and Resource Economics, vol. 11, n. 3–4, pp. 243–260.
Strepparava, D., Nespoli, L., Kapassa, E., (...), Katelaris, L., Medici, V. 2022Deployment and analysis of a blockchain-based local energy market, Energy Reports 8, pp. 99–113
Sulston J. 2012. People and the Planet, The Royal Society (Britain), http://royalsociety.org.
Tollefson J. (2020). How hot will Earth get by 2100? Nature, 580(7804), 443–445. https://doi.org/10.1038/d41586-020-01125-x
Wang, L., Kolios, A., Liu, X., Venetsanos, D., Rui, C. 2022. Reliability of offshore wind turbine support structures: A state-of-the-art review. Renewable and Sustainable Energy Reviews 161,112250
Willett, W., Rockström, J., Loken, B., Springmann, M., Lang, T., Vermeulen, S., Wood, A. J.T.L., 2019. Food in the anthropocene: the EAT. Lancet Commiss. Healthy Diets Sustain. Food Syst. 393 (10170), 447–492. https://doi.org/10.1016/S0140-6736 (18)31788-4.
Zalasiewicz, J., Williams, M., Haywood, A., Ellis, M. (2011) “The Anthropocene: a new epoch of geological time?” Philos. Trans. R. Soc. A, vol. 369, pp. 835–841. Ayres, R.U., 1990a. Technological transformations and long waves. Part I. Technol. Forecast. Soc. Chang. 37 (1), 1–37.

Download PDF

Version 1

posted

You are reading this latest preprint version

New technological trajectories to reduce fossil-fuel pollution and support sustainable socioeconomic systems

Status:

Version 1

Abstract

Figures

1. Goal Of Investigation

2. Environmental Risk Factors: A General Overview

3. Study Design

4. Technologies For Reducing Risk Factors Of Environmental Deterioration: Main Results And Discussions

5. Conclusions And Future Perspectives

Declarations

Declaration of competing interest

References

Status:

Version 1