Reducing environmental impacts through socioeconomic transitions: critical review and prospects

Abstract

Rapid socioeconomic development has caused numerous environmental impacts. Human production and consumption activities are the underlying drivers of resource uses, environmental emissions, and associated environmental impacts (e.g., ecosystem quality and human health). Reducing environmental impacts requires an understanding of the complex interactions between socioeconomic system and environmental system. Existing studies have explored the relationships among human society, economic system, and environmental system. However, it is unclear about the research progress in the effects of socioeconomic activities on environmental impacts and the potential directions of future research. This critical review finds that existing studies have identified critical regions, sectors, and transmission pathways for resource uses, environmental emissions, and environmental impacts from supply chain perspectives. Moreover, scholars have characterized the impacts of socioeconomic transitions on resource uses and environmental emissions. However, existing studies overlook the dynamic nature of the interconnections among human society, economic system, and environmental system. In addition, the effects of socioeconomic structural transitions on environmental impacts remain unknown. This review proposes four prospects and possible solutions that will contribute to a better understanding of the complex interactions among human society, economic system, and environmental system. They can help identify more effective solutions to reduce environmental impacts through socioeconomic transitions.

Natural Environment Protection Strategy Based on Cyclic Neural Network

“…When applying the CNN model, when the input mode and output mode are different or the similarity is low, generally we will choose to build a hidden layer between the input and output layers, so as to achieve the purpose of nonlinear conversion of the signals in the input layer of the neural network; On the contrary, if the input and output modes of the neural network are very similar, a two-layer network topology can be considered [14,15]. In general, to determine the number of nodes in the hidden layer of the neural network according to empirical formulas, step by step testing and other methods, the first thing to do is to set the initial threshold in advance, then accumulate one by one on the basis of the preset initial value, and then compare the predicted performance of the network model that determines the number of nodes in the hidden layer each time.…”

Carbon-Neutrality Research in China—Trends and Emerging Themes

“…Urbanization, on the one hand, enhances efficiency, effectiveness, and productivity of a country and provides job opportunities to all city-dwellers, including migrants from rural areas and immigrants. On the other hand, urban areas consume unproportioned amounts of energy, food, water, and other resources at an ever-increasing rate due to increases in population, affluence, and technology use [4][5][6]. According to UN-Habitat's Urban Energy [7], the world's urban areas consume about 80% of global primary energy directly and indirectly, and produce over 60% of the total greenhouse gases (GHG).…”

Eco-Efficiency, Environmental and Sustainable Innovation in Recycling Energy and Their Effect on Business Performance: Evidence from European SMEs

“…The World Business Council for Sustainable Development (WBCSD) first coined the term "eco-efficiency", which goes beyond just one particular activity to reduce environmental impact. Under eco-efficiency, the measures and activities that can reduce environmental problems and the ecological footprint are widely recognized in the literature and have practical implications [7]. Small and medium-sized enterprises (SMEs) make up the bulk of business ventures-specifically within the European Union.…”