Linkage analysis of economic consumption, pollutant emissions and concentrations based on a city-level multi-regional input–output (MRIO) model and atmospheric transport

Wang, Yuan; Li, Xinming; Sun, Yun; Zhang, Lanxin; Qiao, Zhi; Zhang, Zengkai; Zheng, Heran; Meng, Jing; Lü, Yanbin; Li, Yue

doi:10.1016/j.jenvman.2020.110819

Cited by 28 publications

(6 citation statements)

References 43 publications

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“…Initially, a correlation analysis is required in DEA to reach reliable results (Kao & Liu, 2021; Wang, Li, et al, 2020) If an input is observed to be in a low correlation with all of the outputs, that input is considered to be not significant for the model and can be omitted (Yang, 2009). In correlation analysis, it is preferred that the effects of inputs on outputs are in the same direction.…”

Section: Resultsmentioning

confidence: 99%

How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis

Bulak

Küçükvar

2021

Sustainable Development

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This paper presents an integrated approach combining the optimization‐based frontier model with a global multiregional input–output (MRIO) analysis for food consumption in Europe. The weighted and conventional data envelopment analysis models are coupled with production and consumption‐based environmental and economic footprint data obtained from the environmental footprint explorer database. Eco‐efficiency assessment is carried out using multiple undesirable environmental outputs such as carbon emission, total energy consumption, land use, material use, water use, and one desirable economic output, which is the gross value‐added (GVA). This assessment indicates an efficiency level of each economic activity associated with its environmental impacts and policies are made as a result of the efficiency level to propose an equilibrium between economic development and environmental impacts. Finally, a sensitivity analysis of each parameter, variability analysis between weighted and non‐weighted models, and performance improvement projections are presented. Based on the results, four countries become efficient when moving from production‐based accounting (PBA) to consumption‐based accounting (CBA). France, United Kingdom, Italy, and Sweden are efficient countries in both findings. Denmark caused the highest carbon emission from the production point of view. Germany is the largest importer in all environmental categories such as carbon emission, energy usage, material use, land use, and water use. Additionally, the weight‐restricted model indicated a noticeable difference concerning the eco‐efficiency scores under the PBA and CBA approach, where land use and material footprint categories were found to be the most sensitive parameters for eco‐efficiency scores. The authors believe that this integrated approach will aid in decision‐making and help build a composite eco‐efficiency score when comparing the performance of food consumption with multiple environmental and economic metrics.

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Section: Resultsmentioning

confidence: 99%

How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis

Bulak

Küçükvar

2021

Sustainable Development

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“…The MRIO model, which elucidates the mutual interrelation among sectors or regions from the perspective of supply chain, is a prevalent approach for investigating energy [35,36], water [37,38], CO2 emissions [39,40], and other pollutant emissions [41][42][43] embedded within interregional trade. Consistent with Qian et al [16], this study first esti- The MRIO model, which elucidates the mutual interrelation among sectors or regions from the perspective of supply chain, is a prevalent approach for investigating energy [35,36], water [37,38], CO 2 emissions [39,40], and other pollutant emissions [41][42][43] embedded within interregional trade. Consistent with Qian et al [16], this study first estimated the SO 2 emissions attributable to production, consumption, and income using the MRIO model.…”

Section: Multi-regional Input-output (Mrio) Analysismentioning

confidence: 99%

Inequality Evolution of Economic Gains and Environmental Losses in Chinese Interprovincial Trade during 2007–2017

Qian,

Zheng,

Cao

et al. 2024

Sustainability

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A reduction in SO2 emissions is important for sustainable development. However, China uses territorial emissions to determine its SO2 emission mitigation targets, ignoring the emissions that are incorporated into interregional trade. In addition to the transfer of pollution, value added can also be exchanged with trade, resulting in environmental inequality among regions. In this study, we estimate the embodied SO2 emissions (ESE) under production-, consumption-, and income-based accounting principles and quantify the embodied value added (EVA) within the interprovincial trade during 2007–2017 using the multi-regional input–output (MRIO) model. The inequalities between the ESE and EVA are further investigated using the Gini coefficients method and the regional environmental index method. The results indicate that ~34.7–43.4% of SO2 emissions and ~24.6–30.8% of value added were triggered by interprovincial trade. Furthermore, developed provinces mainly outsourced their emissions to less developed provinces, particularly to those nearby. Concerning the value added, it was mainly outsourced from less developed provinces to developed provinces during 2007–2010, with no clear patterns observed during 2012–2017. The study’s findings indicate that the high inequality of SO2 emissions and value added also occurred between developed and less developed provinces. Particularly, the Gini coefficients of value inflow–SO2 outflow (VISO) were larger than those of value outflow–SO2 inflow (VOSI), which indicated that, besides the direct emissions, consumption-based emissions should be considered when allocating the environmental responsibility among provinces. These findings are valuable for shaping pathways towards achieving regional economic coordination and sustainable development.

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“…To evaluate inter-city economic consumption, pollutant emission, and concentration among 13 cities in the Beijing-Tianjin-Hebei (BTH) urban agglomeration, this study combines an inter-city multi-regional input-output (MRIO) model with an air quality dispersion model consisting of a weather research and forecasting (WRF) model and the CALPUFF model (WRF/CALPUFF) (Wang et al, 2020). As an example, NOx is used.…”

Section: Sustainability and Manufacturingmentioning

confidence: 99%

Multi-region Input-Output-based Carbon and Energy Footprint Analysis of U.S. Manufacturing

Abbood

Eğilmez

Mészáros

2023

Period. Polytech. Soc. Man. Sci.

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In this research, U.S. manufacturing activities' life cycle-based carbon and energy footprint impacts have been quantified, taking international trade linkages with the rest of the world into account. The U.S economy has been integrated into a multi-region input-output (MRIO) life cycle assessment framework where total of 40 major economies, including the USA, China, Russia, and others, plus the rest of the world (ROW) were modelled to assess global energy and carbon footprint impacts. Each country's economy is assumed to compromise 35 major industries based on the WIOD database classification. A total of 1435 (41 × 35 = 1435) industries has therefore been taken to represent the global structure of the world economy. The novelty of the approach is that the MRIO model has been developed in a stochastic fashion, plus global trade-linked uncertainties have also been taken into consideration. Top carbon emitting and energy consumer industries and countries have been analysed using data analytics and statistical modelling methods. The results show that the USA is the largest contributor to the total carbon footprint (CFP) and the total energy footprint (EFP) with 81.73% and 84%, respectively. Moreover, the agriculture/hunting forestry/fishing sector and the electricity/gas/water supply sectors dominate the overall U.S. carbon footprint, contributing 22% and 21.28%, respectively. The coke/refined petroleum/nuclear fuel sector has the largest share of the total energy footprint, with 47.9% of the total impacts.

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Linkage analysis of economic consumption, pollutant emissions and concentrations based on a city-level multi-regional input–output (MRIO) model and atmospheric transport

Cited by 28 publications

References 43 publications

How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis

How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis

Inequality Evolution of Economic Gains and Environmental Losses in Chinese Interprovincial Trade during 2007–2017

Multi-region Input-Output-based Carbon and Energy Footprint Analysis of U.S. Manufacturing

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