scholarly journals ENVIRON: Environmental Impacts from Advanced Communications - Evidence from an Input-Output Theory

2013 ◽  
Vol 4 (1) ◽  
pp. 15-28
Keyword(s):  
Economic System ◽  
Environmental Impacts ◽  
Mobile Communications ◽  
Input Output ◽  
Theory Analysis ◽  
Output Analysis ◽  
Positive Effects ◽  
Industry Sectors ◽  
Business Sectors ◽  
Of Greece

The ENVIRON model estimates environmental impacts (positive, negative) from the introduction and use of Advanced Communications (AC); Information Society Technologies (IST) in industrial, commercial and business sectors in Greece. The model estimates effects on output, employment, income, environment and energy requirements. It is based on the: (i) Leontief Input-Output theory-analysis, (ii) Introduction of AC/IST and in particular of the Telematics as a new sector into the economic system of a country, and (iii) Incorporation of pollution emission factors into the system. The types of AC represented are grouped into six categories: access to information systems, electronic transactions, robotics and tele-action, tele-working, mobile communications and video facilities. Industry sectors considered are transport, business and services, public and domestic. The application of ENVIRON indicates that the introduction of AC into the production process will result into a 15.8% decrease of energy consumption, a reduction of 14.32-10.14% in SO2, and it will have strong positive effects on the economic system of Greece especially on profits related to environmental protection. The model demonstrates the use of the Leontief Input-Output analysis in environmental impacts analysis matters and policy.

scholarly journals Environmental impacts of European trade: interpreting results of process-based LCA and environmentally extended input–output analysis towards hotspot identification

2019 ◽  
Vol 25 (12) ◽  
pp. 2432-2450 ◽  
Author(s):  
Antoine Beylot ◽  
Sara Corrado ◽  
Serenella Sala
Keyword(s):  
Life Cycle ◽  
Impact Assessment ◽  
Environmental Impacts ◽  
Impact Categories ◽  
Input Output ◽  
Output Analysis ◽  
Input Output Analysis ◽  
European Trade ◽  
The Impact ◽  
Modelling Approaches

Abstract Purpose Trade is increasingly considered a significant contributor to environmental impacts. The assessment of the impacts of trade is usually performed via environmentally extended input–output analysis (EEIOA). However, process-based life cycle assessment (LCA) applied to traded goods allows increasing the granularity of the analysis and may be essential to unveil specific impacts due to traded products. Methods This study assesses the environmental impacts of the European trade, considering two modelling approaches: respectively EEIOA, using EXIOBASE 3 as supporting database, and process-based LCA. The interpretation of the results is pivotal to improve the robustness of the assessment and the identification of hotspots. The hotspot identification focuses on temporal trends and on the contribution of products and substances to the overall impacts. The inventories of elementary flows associated with EU trade, for the period 2000–2010, have been characterized considering 14 impact categories according to the Environmental Footprint (EF2017) Life Cycle Impact Assessment method. Results and discussion The two modelling approaches converge in highlighting that in the period 2000–2010: (i) EU was a net importer of environmental impacts; (ii) impacts of EU trade and EU trade balance (impacts of imports minus impacts of exports) were increasing over time, regarding most impact categories under study; and (iii) similar manufactured products were the main contributors to the impacts of exports from EU, regarding most impact categories. However, some results are discrepant: (i) larger impacts are obtained from IO analysis than from process-based LCA, regarding most impact categories, (ii) a different set of most contributing products is identified by the two approaches in the case of imports, and (iii) large differences in the contributions of substances are observed regarding resource use, toxicity, and ecotoxicity indicators. Conclusions The interpretation step is crucial to unveil the main hotspots, encompassing a comparison of the differences between the two methodologies, the assumptions, the data coverage and sources, the completeness of inventory as basis for impact assessment. The main driver for the observed divergences is identified to be the differences in the impact intensities of goods, both induced by inherent properties of the IO and life cycle inventory databases and by some of this study’s modelling choices. The combination of IO analysis and process-based LCA in a hybrid framework, as performed in other studies but generally not at the macro-scale of the full trade of a country or region, appears a potential important perspective to refine such an assessment in the future.

scholarly journals Identifying Hub Wastewater Propagation Chains in China’s National Economic System: A Model Coupled Input-Output Analysis with Graphical Theory

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2351
Author(s):  
Xuefeng Li ◽  
Xiuli Liu
Keyword(s):  
Economic System ◽  
National Level ◽  
Policy Implications ◽  
Wastewater Management ◽  
Traditional Model ◽  
Wastewater Discharge ◽  
Input Output ◽  
Output Analysis ◽  
Input Output Analysis ◽  
National Economic

Wastewater propagation chains (WPCs) measure inter-sector average propagation lengths (APL) of wastewater discharge. To achieve sustainable wastewater management, one needs to understand the propagation mechanisms by identifying WPCs at a national level over time. However, the traditional model of identifying WPCs is prone to retaining APLs with lower values but larger wastewater discharge intensities, ignoring many linkages whereby intensities are less than a preset threshold. Nevertheless, these overlooked linkages are valuable in understanding wastewater propagation mechanisms. This study proposed a new model coupled input-output analysis with the graphical theory, called the average propagation lengths-hub covariance graph (APL-HCG). This model can investigate WPCs where the closeness of sector linkages exceeds the preset thresholds. Furthermore, it is capable of retaining linkages for identifying hub wastewater propagation chains (HWPCs). Based on APL-HCG, the resultant HWPCs are decomposed as separated sub-chains which are basically composed of linkages among certain significant sectors belonging to the secondary industry or the tertiary industry. Scenario analyses show that HWPCs are effective in reducing wastewater discharge in the national economic system. The total wastewater discharge would decrease by 1.36%, 2.53%, 2.46%, and 2.11% if we reduced 10% of the final demand of all sectors in HWPCs in 2002, 2007, 2012, and 2017. The APL-HCG model outperforms the traditional model on WPCs by 0.14%, 1.61%, 0.47%, and 0.10%, respectively. The APL-HCG model is 0.21%, 0.68%, 0.70%, and 0.35% better than the scenario of random sampling with the number of sectors equal to HWPCs, respectively. Certain policy implications were provided to reduce wastewater effectively at the national level.

scholarly journals Linkage Analysis of Large and Medium Manufacturing Industry Sectors In East Java Province Using Input-Output

2018 ◽  
Vol 1 (1) ◽  
pp. 29-36
Author(s):  
Betty Silvia Ayu Utami
Keyword(s):  
Manufacturing Industry ◽  
Petroleum Refinery ◽  
Economic Sector ◽  
Cross Section Data ◽  
Input Output ◽  
Economic Sectors ◽  
Output Analysis ◽  
Section Data ◽  
Forward Linkage ◽  
Industry Sectors

The purpose of this research is to know and analyze the role and backward linkage and forward linkage of big and medium manufacturing industry in East Java Province. The data used in this study is cross section data, data to measure the linkage of economic sector. While the population of this research is all economic sector in East Java Province, which is divided into 66 economic sectors in accordance with Input-Output analysis (I-O). From the analysis result, it is concluded that the backward linkage condition shows the bamboo, wood and rattan industry sub sector, the non-metallic minerals sub industry, and the cement sub-industry has the greatest value, while from the forward linkage shows that the petroleum refinery industry sub sector, sub industry of goods.

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