2020
DOI: 10.3390/su12135382
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Multi-Vector Approach to Cities’ Transition to Low-Carbon Emission Developments

Abstract: Globally, cities have made efforts to shift to low-carbon emission development (LED), amidst air pollution, greenhouse gas (GHG) emissions, and high temperature anomalies. However, the emphasis on cities to help shift the global economy to LED has been on a single individual sector approach operating in silos rather than the inter and intra-specific outcomes of multiple sectors. Thus, there are uncertainties of adopting suitable pathways for cities’ transition to LED, due largely to data paucity and po… Show more

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Cited by 5 publications
(13 citation statements)
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“…Butler et al, 2014;Chelleri et al, 2016), whereas in middle to high income contexts there is more emphases on mainstreaming and reaching climate targets (e.g. Dovie et al, 2020). This resonates with Chapter 20 of AR5, which notes that development responses differ regarding socioeconomic, cultural, biophysical and institutional contexts (Denton et al, 2014).…”
Section: Conceptual Advances and Ambiguities In The Development Domainmentioning
confidence: 91%
See 3 more Smart Citations
“…Butler et al, 2014;Chelleri et al, 2016), whereas in middle to high income contexts there is more emphases on mainstreaming and reaching climate targets (e.g. Dovie et al, 2020). This resonates with Chapter 20 of AR5, which notes that development responses differ regarding socioeconomic, cultural, biophysical and institutional contexts (Denton et al, 2014).…”
Section: Conceptual Advances and Ambiguities In The Development Domainmentioning
confidence: 91%
“…for water management in Australia's Murray-Darling basin (Abel et al, 2016), for rural livelihoods in Indonesia (Butler et al, 2014), or for Small Island Developing States (Mycoo, 2018)), whereas less focus on mitigation (e.g. in cities (Dovie et al, 2020)). The fewest number of papers offer a case which combines adaptation and mitigation.…”
Section: Conceptual Advances and Ambiguities In The Domain Of Climate Action (Adaptation And Mitigation)mentioning
confidence: 99%
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“…The PSO algorithm is a swarm intelligence algorithm, which thinks that particles are in dimensional space, passes information according to a specific rule, and changes the selforganization behavior generated by their state according to the change of information [41][42][43]. The schematic diagram of information transmission between particles in the particle swarm optimization algorithm is shown in Figure 3.…”
Section: Adaptive Particle Swarm Optimization (Apso)mentioning
confidence: 99%