scholarly journals Comparison of Diesel Tractor Emissions in Korea

2021 ◽  
Author(s):  
Gyu Gang Han ◽  
Jun Hyuk Jeon ◽  
Myoung Ho Kim ◽  
Jeong Min Lee ◽  
Seong Min Kim
Keyword(s):  
Air Pollutants ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Agricultural Labor ◽  
The Hours ◽  
High Emission ◽  
Soil Preparation ◽  
Power Tiller ◽  
Agricultural Tractors ◽  
Tier 3

Due to the shortage of agricultural labor forces and rapid aging of farmers, the utilization of tractors is becoming popular and essential in Korea. Tractors can be classified into two types, a walking tractor called as a power tiller and a riding tractor. In this study, agricultural tractors including walking and riding types were categorized into 4 levels by rated output power. And diesel emission inventory of tractors was established and analyzed using 2011 and 2019 survey data in Korea. Emission inventory including CO, NOx, SOx, TSP(PM10), PM2.5, VOCs and NH3 were established using Tier 3 methodology. The total amount of emission using agricultural tractors was decreased about 13% from 2011 to 2019. The number of walking tractors were decreased by about 19% in 8 years, on the other hand that of riding tractors were increased by about 12%. However, the emission reduction is about 48% for walking tractors and the emission increment is about 5% for riding tractors. Thus, the total emission from agricultural tractors was decreased by about 16% in those periods. It is due to the decrease of 21% and 15% in the hours of use of walking and riding tractors, respectively, in 2019. Walking tractors mainly emit air pollutants from spraying and transporting. Riding tractors mainly 61% of total air pollutants emits from soil preparation and transporting operations. Geographic information system (GIS) was used to spatially assign air pollutants variables into 17 provinces and metropolitan cities in Korea. High emission generating regions and changes of emissions during 8 years were clearly seen in GIS analysis. High air pollutant emitting regions are mainly located in the western and southern regions of Korea, which have plenty of arable areas compared to other regions in Korea.

scholarly journals Analysis of Air Pollutant Emission Inventory from Farm Tractor Operations in Korea

2021 ◽  
Vol 11 (1) ◽  
pp. 17
Author(s):  
Gyu-Gang Han ◽  
Jun-Hyuk Jeon ◽  
Myoung-Ho Kim ◽  
Seong-Min Kim
Keyword(s):  
Air Pollutants ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Pollutant Emission ◽  
Agricultural Labor ◽  
National Agency ◽  
Metropolitan Cities ◽  
Agricultural Tractors ◽  
Engine Size

Due to the decline in the agricultural labor force and rapid aging of farmers, agricultural machinery is becoming larger, higher-performance, and diversified. In this study, an air pollutant emission inventory for agricultural tractors was analyzed and compared with the inventory developed by a national agency. Agricultural tractors include walking and riding tractors and, further, riding tractors were divided into three subcategories based on their engine size. In addition, tractor emissions were classified according to the usage time of each operation. Seven air pollutants, such as CO, NOx, SOx, TSP, VOCs (PM10), PM2.5, and NH3, were included in the inventory. The results showed that the total yearly emissions in 2017 were 3300 Mg, 9110 Mg, 4 Mg, 567 Mg, 522 Mg, 759 Mg, and 33 Mg for CO, NOx, SOx, TSP, VOCs, PM10, PM2.5, and NH3, respectively. The most emitted air pollutant in the transporting operation using walking tractors is NOx, and the amount of emission is 1023 Mg/y. Riding tractors mainly emit a large amount of NOx, in the order of medium, large, and small tractors. The NOx emissions from medium, large, and small riding tractors are 1103 Mg/y, 676 Mg/y, and 322 Mg/y, respectively, from harrowing operations and are 445 Mg/y, 273 Mg/y, and 130 Mg/y, respectively, from tilling operations. The results also showed that the total pollutant emissions from tractors were increased 10% compared to the emission inventory developed by a national agency due to categorizing riding tractors into three subcategories. A geographic information system (GIS) was used to spatially assign air pollutant variables to 17 provinces and metropolitan cities in Korea.

scholarly journals Emerging Concerns on Air Pollutants from Chemistry Laboratories of University: Ozone Formation Potential, Emission Characteristics, and Emission Inventory in Beijing, China

2021 ◽  
Author(s):  
Chenlong Wang ◽  
Xiaoxi Zhang ◽  
Kun Wang ◽  
Jiajia Gao ◽  
Penglai Zuo ◽  
...  
Keyword(s):  
Air Pollutants ◽  
Emission Inventory ◽  
Raw Materials ◽  
Air Pollutant ◽  
Atmospheric Pollutants ◽  
Pollutant Emissions ◽  
Ozone Formation ◽  
Formation Potential ◽  
Ozone Formation Potential ◽  
Materials Used

Abstract Chemical laboratories of Universities are an important source of air pollutant emissions in urban area, but their detailed emission factors have rarely been investigated. This study determined the concentration level and chemical composition spectrum of air pollutants from 21 typical chemical laboratories of universities in Beijing. Based on quantitative analysis using a GC-MS/FTIR/FID system, the emission intensity of each laboratory area was estimated, the ozone formation potential (OFP) was calculated, and the emission inventory of atmospheric pollutants in chemical laboratories of universities in Beijing was estimated. According to the results, the atmospheric pollutants discharged by the laboratories could be characterized by wide species distribution and low concentrations of single components. The average concentrations of atmospheric pollutants from the three outlets were 20.6 ± 8.9 µmol/mol (mean ± S.D.), 26.5 ± 4.8 µmol/mol, and 14.7 ± 5.8 µmol/mol. VOC emission was significantly affected using organic solvents. Pollutant emissions from the laboratories exhibited strong periodicity, and the raw materials used in the experiments were the main factor affecting the final pollutant concentration. The emission intensities of atmospheric pollutants from the three outlets were 35.06 ± 38.08 g/(m2·d), 22.83 ± 18.88 g/(m2·d) and 24.03 ± 28.78 g/(m2·d), and their TOFP were 27.8 ± 39.1 µmol/mol, 22.0 ± 21.2 µmol/mol, and 14.5 ± 28.9 µmol/mol. The total emission of atmospheric pollutants from university chemical laboratories in Beijing in 2019 was estimated at approximately 2630.8 ± 2710.3 t, including 675.8 ± 610.6 t of inorganic gaseous pollutants and 1932.0 ± 2081.2 t of VOCs, with Haidian District as the largest contributor.

scholarly journals High-resolution simulation of link-level vehicle emissions and concentrations for air pollutants in a traffic-populated East Asian city

2016 ◽  
Author(s):  
Shaojun Zhang ◽  
Ye Wu ◽  
Ruikun Huang ◽  
Han Yan ◽  
Yali Zheng ◽  
...  
Keyword(s):  
High Resolution ◽  
East Asia ◽  
Air Pollutants ◽  
Vehicle Emissions ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Assessment Tools ◽  
Vehicle Emission ◽  
Temporal And Spatial ◽  
Resolution Simulation

Abstract. Vehicle emissions of air pollutants created substantial environmental impacts on air quality for many traffic-populated cities in East Asia. A high-resolution emission inventory is an irreplaceable tool compared with traditional tools (e.g., registration data based approach) to accurately evaluate real-world traffic dynamics and their environmental burden. In this study, Macao, one of the most populated cities in the world, is selected to demonstrate a high-resolution simulation of vehicular emissions and their contribution to air pollutant concentrations by coupling multi-models. First, traffic volumes by vehicle category on 47 typical roads were investigated during weekdays of 2010 and further applied in a networking demand simulation with the TransCAD model to establish hourly profiles of link-level vehicle counts. Local vehicle driving speed and vehicle age distribution data were also collected in Macao. Second, based on a localized vehicle emission model (e.g., the EMBEV-Macao), this study established a link-based vehicle emission inventory in Macao with high resolution meshed in a temporal and spatial framework. Furthermore, we employed the AERMOD model to map concentrations of CO, NO2 and primary PM2.5 contributed by local vehicle emissions during the weekdays of November 2010. This study has discerned the strong impact of traffic flow dynamics on the temporal and spatial patterns of vehicle emissions, such as a geographic discrepancy of spatial allocation up to 25 % between THC and PM2.5 emissions owing to spatially heterogeneous vehicle-use intensity between motorcycles and diesel fleets. We also identified that local vehicles are a dominant source of ambient NO2 in traffic-populated areas as evidenced by good agreement between AERMOD-simulated data and observed results. Therefore, this paper provides a case study and a solid framework for developing high-resolution environment assessment tools for other vehicle-populated cities in East Asia.

scholarly journals Assessment of China's virtual air pollution transport embodied in trade by using a consumption-based emission inventory

2015 ◽  
Vol 15 (10) ◽  
pp. 5443-5456 ◽  
Author(s):  
H. Y. Zhao ◽  
Q. Zhang ◽  
D. B. Guan ◽  
S. J. Davis ◽  
Z. Liu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Pollutants ◽  
Emission Inventory ◽  
Economic Status ◽  
Air Pollutant ◽  
Pollutant Emission ◽  
Pollution Transport ◽  
Economic Activities ◽  
Model Framework ◽  
Central Regions

Abstract. Substantial anthropogenic emissions from China have resulted in serious air pollution, and this has generated considerable academic and public concern. The physical transport of air pollutants in the atmosphere has been extensively investigated; however, understanding the mechanisms how the pollutant was transferred through economic and trade activities remains a challenge. For the first time, we quantified and tracked China's air pollutant emission flows embodied in interprovincial trade, using a multiregional input–output model framework. Trade relative emissions for four key air pollutants (primary fine particle matter, sulfur dioxide, nitrogen oxides and non-methane volatile organic compounds) were assessed for 2007 in each Chinese province. We found that emissions were significantly redistributed among provinces owing to interprovincial trade. Large amounts of emissions were embodied in the imports of eastern regions from northern and central regions, and these were determined by differences in regional economic status and environmental policy. It is suggested that measures should be introduced to reduce air pollution by integrating cross-regional consumers and producers within national agreements to encourage efficiency improvement in the supply chain and optimize consumption structure internationally. The consumption-based air pollutant emission inventory developed in this work can be further used to attribute pollution to various economic activities and final demand types with the aid of air quality models.

scholarly journals Gridded Emissions of Air Pollutants for the period 1970–2012 within EDGAR v4.3.2

2018 ◽  
Author(s):  
Monica Crippa ◽  
Diego Guizzardi ◽  
Marilena Muntean ◽  
Edwin Schaaf ◽  
Frank Dentener ◽  
...  
Keyword(s):  
Time Series ◽  
Air Pollutants ◽  
Emission Inventory ◽  
Ghg Emissions ◽  
Emission Factors ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Activity Data ◽  
Time Period ◽  
Over Time

Abstract. The new version v4.3.2 of the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2) compiles gaseous and particulate air pollutant emissions, making use of the same anthropogenic sectors, time period (1970–2012) and international activity data as used for estimating GHG emissions as described in a companion paper (Janssens-Maenhout et al., 2017). All human activities, except large scale biomass burning and land use, land-use change and forestry, are included in the emissions calculation. The bottom-up compilation methodology of sector-specific emissions was applied consistently for all world countries, providing methodological transparency and comparability between countries. In addition to the activity data used to estimate GHG emissions, air pollutant emissions are determined by the process technology and end-of-pipe emission reduction abatements. Region-specific emission factors and abatement measures were selected from recent scientific available literature and reports. Compared to previous versions of EDGAR, the EDGAR v4.3.2 dataset covers all gaseous and particulate air pollutants, has extended time series (1970–2012) and has been evaluated with QC/QA procedures both for the emission time series (e.g. PM mass balance, gap-filling for missing data, split-up of countries over time, etc.) and gridmaps (full coverage of the world, complete mapping of EDGAR emissions with sector-specific proxies, etc.). This publication focuses on the gaseous air pollutants of CO, NOx, SO2, total NMVOC and NH3 and on the aerosols PM10, PM2.5, BC and OC. Considering the 1970–2012 time period, global emissions of SO2 increased from 99 to 103 Tg, CO from 441 to 562 Tg, NOx from 68 to 122 Tg, NMVOC from 119 to 170 Tg, NH3 from 25 to 59 Tg, PM10 from 37 to 65 Tg, PM2.5 from 24 to 41 Tg, BC from 2.7 to 4.5 Tg and OC from 9 to 11 Tg. We present the country-specific emission totals and analyse the larger emitting countries (including the European Union), to provide insights on major sector contributions. In addition, per capita and per GDP emissions and implied emission factors – the apparent emissions per unit of production or energy consumption are presented. We find that the implied EFs are higher for low income countries compared to high income countries, but in both cases decreasing from 1970 to 2012. The comparison with other global inventories, such as HTAP v2.2 and CEDS, reveals insights on the uncertainties as well as the impact of data revisions (e.g. activity data, emission factors, etc.). As an additional metric we analyse the emission ratios of some pollutants to CO2 (e.g. CO/CO2, NOx/CO2, NOx/CO and SO2/CO2) by sector, region and time to identify any decoupling of air pollutant emissions from energy production activities and to demonstrate the potential of such ratios to compare to satellite derived emission data. Gridded emissions are also made available for the 1970–2012 historic time series, disaggregated for 26 anthropogenic sectors using updated spatial proxies. The analysis of the evolution of hot spots over time allowed us to identify areas with growing emissions and where emissions should be constrained to improve global air quality (e.g. China, India, Middle East and some Southern American countries are often characterized by high emitting areas which are changing rapidly compared to Europe or USA where stable or decreasing emissions are evaluated). Sector-and component specific contributions to gridcell emissions may help the modelling and satellite communities to disaggregate atmospheric column amounts and concentrations into main emitting sectors. This work addresses not only the emission inventory and modelling communities, but also aims to broaden the usefulness information available in a global emission inventory such as EDGAR to also include the measurement community. Data are publicly available online through the EDGAR website http://edgar.jrc.ec.europa.eu/overview.php?v=432_AP&SECURE=123 and registered under DOI: https://data.europa.eu/doi/10.2904/JRC_DATASET_EDGAR.

scholarly journals EVOLUTION OF POLLUTANTS EMISSIONIN RELATION TOROAD TRAFFIC IN THE CITY OF LOME (TOGO) FROM 2010 TO 2019

2021 ◽  
Vol 9 (12) ◽  
pp. 51-57
Author(s):  
Kokou SABI ◽  
◽  
Hezouwe SONLA ◽  
Moursalou KORIKO ◽  
Kokou Eric GBEDJANGNI ◽  
...  
Keyword(s):  
Air Pollutants ◽  
Emission Inventory ◽  
Road Traffic ◽  
Petroleum Products ◽  
Air Pollutant ◽  
Capital City ◽  
Pollutant Emission ◽  
Volatile Organic ◽  
Pollutants Emission ◽  
The City

The automobile fleet in Togo has increased in the last decades with a patchwork of vehicles that are in majority older than ten (10) years. Until 2019, the car fleet in Togo was almost dependent upon petroleum products, and was consequentlya source of air pollutants emission. Lome is the capital city of Togo with the characteristic of having the highest road traffic volume that significantly impacts air quality. In accordance with the EMEP/EEA air pollutant emission inventory guide and the COPERT method, emissions of carbone monoxide (CO), nitrogen oxides (NOx), non-methane volatile organic compounds (NMVOCs) and particulate matter (PM) are respectively estimated to: 2621.674 tCO 82.444 tNOx 558.778 tNMVOC and 7.241 tPM. In the time series 2010-2019, emissions of CO, NMVOCs and NOx fell overall with average yearly rates by respectively 83,0234 66,4888 and 0,8073 t/year whereas the PM emission rose(0,8208 t/year).

scholarly journals Assessment of China's virtual air pollution transport embodied in trade by a consumption-based emission inventory

2014 ◽  
Vol 14 (18) ◽  
pp. 25617-25650 ◽  
Author(s):  
H. Y. Zhao ◽  
Q. Zhang ◽  
S. J. Davis ◽  
D. Guan ◽  
Z. Liu ◽  
...  
Keyword(s):  
Air Pollution ◽  
Supply Chain ◽  
Air Pollutants ◽  
Emission Inventory ◽  
Economic Status ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Pollution Transport ◽  
Economic Activities ◽  
Goods And Services

Abstract. High anthropogenic emissions from China have resulted in serious air pollution, and it has attracted considerable academic and public concern. The physical transport of air pollutants in the atmosphere has been extensively investigated, however, understanding the mechanisms how the pollutants were transferred through economic and trade activities remains challenge. In this work, we assessed China's virtual air pollutant transport embodied in trade, by using consumption-based accounting approach. We first constructed a consumption-based emission inventory for China's four key air pollutants (primary PM2.5, sulfur dioxide (SO2), nitrogen oxides (NOx) and non-methane volatile organic compounds (NMVOC)) in 2007, based on the bottom-up sectoral emission inventory concerning their production activities – a production-based inventory. We used a multiregional input-output (MRIO) model to integrate the sectoral production-based emissions and the associated economic and trade activities, and finally obtained consumption-based inventory. Unlike the production-based inventory, the consumption-based inventory tracked emissions throughout the supply chain related to the consumption of goods and services and hereby identified the emission flows followed the supply chains. From consumption-based perspective, emissions were significantly redistributed among provinces due to interprovincial trade. Large amount of emissions were embodied in the net imports of east regions from northern and central regions; these were determined by differences in the regional economic status and environmental policies. We also calculated the emissions embodied in exported and imported goods and services. It is found that 15–23% of China's pollutant emissions were related to exports for foreign consumption; that proportion was much higher for central and export-oriented coastal regions. It is suggested that measures should be introduced to reduce air pollution by integrating cross-regional consumers and producers in national agreements to encourage efficiency improvement in the supply chain and optimizing consumption structure internationally. The consumption-based air pollutants emission inventory developed in this work can be further used to attribute pollution to different economic activities and final demand types with the aid of air quality models.

scholarly journals High-resolution simulation of link-level vehicle emissions and concentrations for air pollutants in a traffic-populated eastern Asian city

2016 ◽  
Vol 16 (15) ◽  
pp. 9965-9981 ◽  
Author(s):  
Shaojun Zhang ◽  
Ye Wu ◽  
Ruikun Huang ◽  
Jiandong Wang ◽  
Han Yan ◽  
...  
Keyword(s):  
High Resolution ◽  
Air Pollutants ◽  
Vehicle Emissions ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Assessment Tools ◽  
Vehicle Emission ◽  
Eastern Asia ◽  
Temporal And Spatial ◽  
Resolution Simulation

Abstract. Vehicle emissions containing air pollutants created substantial environmental impacts on air quality for many traffic-populated cities in eastern Asia. A high-resolution emission inventory is a useful tool compared with traditional tools (e.g. registration data-based approach) to accurately evaluate real-world traffic dynamics and their environmental burden. In this study, Macau, one of the most populated cities in the world, is selected to demonstrate a high-resolution simulation of vehicular emissions and their contribution to air pollutant concentrations by coupling multimodels. First, traffic volumes by vehicle category on 47 typical roads were investigated during weekdays in 2010 and further applied in a networking demand simulation with the TransCAD model to establish hourly profiles of link-level vehicle counts. Local vehicle driving speed and vehicle age distribution data were also collected in Macau. Second, based on a localized vehicle emission model (e.g. the emission factor model for the Beijing vehicle fleet – Macau, EMBEV–Macau), this study established a link-based vehicle emission inventory in Macau with high resolution meshed in a temporal and spatial framework. Furthermore, we employed the AERMOD (AMS/EPA Regulatory Model) model to map concentrations of CO and primary PM2.5 contributed by local vehicle emissions during weekdays in November 2010. This study has discerned the strong impact of traffic flow dynamics on the temporal and spatial patterns of vehicle emissions, such as a geographic discrepancy of spatial allocation up to 26 % between THC and PM2.5 emissions owing to spatially heterogeneous vehicle-use intensity between motorcycles and diesel fleets. We also identified that the estimated CO2 emissions from gasoline vehicles agreed well with the statistical fuel consumption in Macau. Therefore, this paper provides a case study and a solid framework for developing high-resolution environment assessment tools for other vehicle-populated cities in eastern Asia.

scholarly journals Gridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2

2018 ◽  
Vol 10 (4) ◽  
pp. 1987-2013 ◽  
Author(s):  
Monica Crippa ◽  
Diego Guizzardi ◽  
Marilena Muntean ◽  
Edwin Schaaf ◽  
Frank Dentener ◽  
...  
Keyword(s):  
Time Series ◽  
Air Pollutants ◽  
Emission Inventory ◽  
Ghg Emissions ◽  
Emission Factors ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Emission Data ◽  
Activity Data ◽  
Time Period

Abstract. The new version of the Emissions Database for Global Atmospheric Research (EDGAR v4.3.2) compiles gaseous and particulate air pollutant emissions, making use of the same anthropogenic sectors, time period (1970–2012), and international activity data that is used for estimating GHG emissions, as described in a companion paper (Janssens-Maenhout et al., 2017). All human activities, except large scale biomass burning and land use, land-use change, and forestry are included in the emissions calculation. The bottom-up compilation methodology of sector-specific emissions was applied consistently for all world countries, providing methodological transparency and comparability between countries. In addition to the activity data used to estimate GHG emissions, air pollutant emissions are determined by the process technology and end-of-pipe emission reduction abatements. Region-specific emission factors and abatement measures were selected from recent available scientific literature and reports. Compared to previous versions of EDGAR, the EDGAR v4.3.2 dataset covers all gaseous and particulate air pollutants, has extended time series (1970–2012), and has been evaluated with quality control and quality assurance (QC and QA) procedures both for the emission time series (e.g. particulate matter – PM – mass balance, gap-filling for missing data, the split-up of countries over time, few updates in the emission factors, etc.) and grid maps (full coverage of the world, complete mapping of EDGAR emissions with sector-specific proxies, etc.). This publication focuses on the gaseous air pollutants of CO, NOx, SO2, total non-methane volatile organic compounds (NMVOCs), NH3, and the aerosols PM10, PM2.5, black carbon (BC), and organic carbon (OC). Considering the 1970–2012 time period, global emissions of SO2 increased from 99 to 103 Mt, CO from 441 to 562 Mt, NOx from 68 to 122 Mt, NMVOC from 119 to 170 Mt, NH3 from 25 to 59 Mt, PM10 from 37 to 65 Mt, PM2.5 from 24 to 41 Mt, BC from 2.7 to 4.5 Mt, and OC from 9 to 11 Mt. We present the country-specific emission totals and analyze the larger emitting countries (including the European Union) to provide insights on major sector contributions. In addition, per capita and per GDP emissions and implied emission factors – the apparent emissions per unit of production or energy consumption – are presented. We find that the implied emission factors (EFs) are higher for low-income countries compared to high-income countries, but in both cases decrease from 1970 to 2012. The comparison with other global inventories, such as the Hemispheric Transport of Air Pollution Inventory (HTAP v2.2) and the Community Emission Data System (CEDS), reveals insights on the uncertainties as well as the impact of data revisions (e.g. activity data, emission factors, etc.). As an additional metric, we analyze the emission ratios of some pollutants to CO2 (e.g. CO∕CO2, NOx∕CO2, NOx∕CO, and SO2∕CO2) by sector, region, and time to identify any decoupling of air pollutant emissions from energy production activities and to demonstrate the potential of such ratios to compare to satellite-derived emission data. Gridded emissions are also made available for the 1970–2012 historic time series, disaggregated for 26 anthropogenic sectors using updated spatial proxies. The analysis of the evolution of hot spots over time allowed us to identify areas with growing emissions and where emissions should be constrained to improve global air quality (e.g. China, India, the Middle East, and some South American countries are often characterized by high emitting areas that are changing rapidly compared to Europe or the USA, where stable or decreasing emissions are evaluated). Sector- and component-specific contributions to grid-cell emissions may help the modelling and satellite communities to disaggregate atmospheric column amounts and concentrations into main emitting sectors. This work addresses not only the emission inventory and modelling communities, but also aims to broaden the usefulness of information available in a global emission inventory such as EDGAR to also include the measurement community. Data are publicly available online through the EDGAR website http://edgar.jrc.ec.europa.eu/overview.php?v=432_AP and registered under https://doi.org/10.2904/JRC_DATASET_EDGAR.

Emissions Responsibility and Relative Importance of the Productive Sectors in Turkey: 2002-2011

2014 ◽  
Author(s):  
Celal Taşdoğan ◽  
Bilgen Taşdoğan
Keyword(s):  
Air Pollutants ◽  
Economic Value ◽  
Value Added ◽  
High Growth ◽  
Air Pollutant ◽  
Sustainable Growth ◽  
Environmental Damage ◽  
Relative Importance ◽  
Input Output ◽  
Key Sectors

Turkey has realized high growth rates during the period of 2002-2011, except in 2008 and 2009 years. It is thought that the rapidly growing in the country may cause a lot of environmental damage, especially air pollution problems. In other words, the productive sectors have produced two outputs which are economic value added and air pollutants. This study used input output matrixes are to find out the strategically important sectors as it is known key sectors and weak sectors caused the environmental effects in the country. For this purpose, it has been tried to investigate air pollutant quantities which caused by the production process of the sectors in the period of 2002-2011 and performed the input-output tables for Turkey constructed in the World Input Output Database (WIOD) Project. These input-output tables include the emission satellite accounts, which are CO2 emissions and other air pollutants, respectively N2O, CH4, N2O, NOx, SOx, CO, NMVOC and NH3, disaggregated for the 34 sectors. It is expected that the outcomes of the study may contribute to sustainable growth debates and environmental policy implementations in Turkey.

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