3.1 Introduction
The greenhouse effect and its potential to raise global temperatures has become an important international issue. Greenhouse gases (GHGs) consist of CO2, CH4, N2O, HFCs, PFCs and SF6
that are generated from various human activities. The most important GHG is CO2 that accounts for a half of GHG contribution from human activities (IPCC, 2006). Since 1985, Thailand has achieved a high economic growth as the economic structure has significantly changed from being agriculturally oriented to an industrially oriented economy. The gross domestic product (GDP) annual growth rate in Thailand averaged 3.69% from 1994 until 2016, reaching an all-time high of 15.30% in the fourth quarter of 2012 and a record low of -12.50% in the second quarter of 1998 (NESDB, 2016). It should be noted that this growth has been at the expense of natural resource exploitation, by increases in fossil fuel use and deforestation ultimately leading to increase in the GHGs emitted to atmosphere. In addition, other air pollutant emissions (SO2, NOx and particulate matter) are also increasing in Thailand due to the increasing demand for electricity and transportation fuels. The industrial growth, coupled with accelerated urbanization, can be held responsible for this increasing demand for electricity and transportation fuels.
Combustion of fuels that contained sulphur generated SO2 that was emitted into the atmosphere. SO2 is an important pollutant that contributes to acid deposition and leads to potential changes arising in the quality of soil and water. The endpoint impacts of acid deposition can be effects on aquatic ecosystems and damage to vegetation. Acidification can also result in damage to construction. In addition, SO2 also formulate to form the particulate aerosols in the atmosphere. SO2 emitted from fuel combustion mainly depends on the sulfur content of the fuel and, unlike CO2 and NOx emissions, that depends on the operating conditions in the combustion process. The NOx generation is dependent on the excess air in the combustion system and the flame temperature. NOx are an important family of air polluting chemical compounds, but they also react in the atmosphere to generate ozone (O3) and acid rain. Automobiles and other mobile sources generate accounting for a half of the NOx that is emitted. Boilers in the power plants are stationary sources that contribute about 40% of the NOx emissions. In addition, NOx emissions are also added from industrial boilers, incinerators, iron and steel manufacturing, cement production, glass production, petroleum refineries, and nitric acid production. The natural sources of NOx include forest fires, grass fires, and agricultural residues burning (WHO, 2006).
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Particulate matter (PM) is a pervasive air pollutant, comprising of a mixture of solid and liquid particles suspended in the air. The common indicators of PM that are relevant to health impacts refer to the mass concentration of particles with a diameter of less than 10 µm (PM10) and of particles with a diameter of less than 2.5 µm (PM2.5). Particles are classified as the primary PM and secondary particles, depending on the compounds and processes related to its formation.
Primary PM is a particle form that is produced at the emissions source, such as the smoke at the stack of power plant, etc. Secondary PM is produced from chemical and physical reactions relating to the different precursor gases, such as SO2 and NOx (WHO, 2006).
To understand the embodied impacts of each industrial sector on the GHG emissions and other air pollutants, this study developed an environmental inventory database based on an input–
output analysis (IOA) regarding Thailand’s 2005 economic IO tables (THIO). The environmental issues included the GHG emissions (CO2, CH4, and N2O), and other air pollutants (SO2, NOx, and PM).
3.2 Methodology
3.2.1 Environmental inventory database development based on IO model
This study uses the 2005 IO table of Thailand which consists of 180×180 sectors in the analyses. The calculation steps for the environmental intensity database are presented in Figure 3-1.
Figure 3-1. Calculation steps of the environmental intensity database using the THIO table.
Various statistical data
i) Collect data on the energy use in each sector by fuel types, emission factor by fuel types, non-energy related emissions, etc.
Apply to IO table
ii) Distribute the energy use and non-energy related emissions data to each sectors
iii) Calculate the energy-related air emissions from ii) and multiply by emission factor
Direct environmental intensity
From ii) and iii) divide by the domestic production of each sector (d = E / Xj)
Step 1 Calculation of direct environmental intensity (d) Step 2 Calculation of Leontief's inverse matrix (I – A)-1 Input-Output Table (2005)
i) Create the production matrix table
Prepare square matrix aij= Xij/ Xj
Calculate the inverse matrix of Leontief
Environmental Footprint Intensity (e) = d * (I – A)-1 Step 3 Calculation of environmental footprint inventory (e)
GHGs E11 E12 E13 ……… E1j
SO2 E21 E22 E23 ……… E2j
PM10 Ek1 Ek2 Ek3 ……… Ekj
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The applying IOA in this study involves some assumptions summarized in the following:
Constant technological coefficients: the amount of input necessary to produce one unit of output is assumed to be constant in the short term, regardless to price effects, changes in technology or economies of scale.
Linear production functions: the IOA assumes that if the output level of industry changes, the input requirements will change proportionally.
It is assumed that each economic sector produces and sells one and only one homogeneous good.
There are no resource constraints. Supply is assumed infinite and perfectly elastic.
Local resources are efficiently employed. There is no underemployment of resources.
IO tables describe an economy in a specific period; they do not highlight the trend of the economic interrelationship in a long time.
This study was considered effect within domestic and import from the rest of the world (RoW). Imports from the RoW implicitly assumes that the same production characteristics and technologies as comparable products made in Thailand. It is also assumed in this model that RoW have the same technology, and although there are the difference between the domestic or import commodity price. We assumed that other countries have the same technology and direct environmental coefficients as the country analyzed. In this case, the environmental impact embodied in imports can be defined as the foreign environmental impacts represent the actual impact generated by Thailand.
3.2.1.2 Calculation of direct environmental intensity
The modified IO model adds a row for environmental aspects to show the environmental issues involved in production processes, thus quantifying the environmental footprint for the final demand in different sectors. The environmental footprint matrix (d) is an extension of the direct input coefficient matrix for environmental issues. Where d is a k x j matrix, Ekj is environmental issue k (e.g., CO2, CH4, N2O, SO2, NOx, and PM10) per monetary output of sector j. The matrix d is defined as:
d = dkj = Ekj / Xj (k = 1,…, m; j = 1, … , n) (3-1)
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This study analyzes six different environmental inventories, the dimensions of the environmental matrix are d (6 × 180). Elements in the environmental matrix reflect the impacts per sectoral output, e.g., 50 kg CO2 per 1000 Thai Baht for the paddy rice sector.
3.2.1.3 Calculation of Leontief’s inverse matrix
The direct input coefficient is the ratio of the intermediate demand inputs (sales from sector i to sector j) (Xij) and the total output of sector j (Xj). The set of input coefficients of all economic sectors is expressed in the square matrix A (n x n), which is called the direct input coefficient matrix. n is the number of sectors or the dimension of the economic system. The matrix A defined as:
A = aij = Xij / Xj (i, j = 1, … , n) (3-2)
so that in matrix notation equation (3-2) becomes
x = Ax + Y (3-3)
Solving for x yields
x = (I – A)-1 Y (3-4)
where I is the identity matrix (n x n), Y is the vector of final demand and (I - A)-1 is called the Leontief inverse matrix.
This study developed the input coefficient matrix based on the 2005 economic IO table of Thailand with 180 × 180 economic sectors.
3.2.1.4 Calculation of total environmental impacts
The total environmental impact vector (f) of goods or services versus a given amount for economic demand is:
𝑓 = 𝑑x = 𝑑 (𝐼 − 𝐴)−1 Y (1-5)
where A is the direct input coefficient matrix (calculated by dividing the industry-by-industry direct requirements of sectoral inputs by the sectoral output); I is the identity matrix; d is the environmental footprint matrix; and Y is the final demand vector. (I − A)−1 is the matrix of
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input–output multipliers and shows the total effects (direct and indirect) on sectoral production caused by unitary changes in the final demand of sectors.
3.2.2 Data processing
This study developed the environmental inventory database based on the IO model using Thailand 180-sector input–output table in 2005 (NESDB, 2014). The model represents a picture of the Thai economy and environmental impact in 2005. Before applying IOA, the collected data must be harmonized with the compatible IO table form. This can be done by following tables are consistent with the classification of IO table and specification of each industrial sector. The environmental inventory established in this study included CO2, CH4, N2O, SO2, NOx, and PM10. The summary of environmental indicators used in this study is presented in Table 3-1.
Table 3-1. Summary of environmental indicators used in the study.
Measure Indicators Unit Definition Data Source Data
Year
Greenhouse gases (GHGs)
Total GHGs
emissions kg CO2 eq.
Total GHGs (CO2, CH4 and N2O) generated for the production of goods and
services.
DEDE (2005a) DEDE (2005b) DEDE (2005c) IPCC (2006) OAE (2009)
2005
Sulphur dioxide SO2 kg SO2
Total SO2 generated for the production of goods and
services.
DEDE (2005a) DEDE (2005b) DEDE (2005c) EEA (2013) OAE (2009)
2005
Nitrogen oxides NOx kg NOx
Total NOx generated for the production of goods and
services.
DEDE (2005a) DEDE (2005b) DEDE (2005c) EEA (2013) OAE (2009)
2005
Particulate
matter PM10 kg PM10
Total PM10 generated for the production of goods and
services.
DEDE (2005a) DEDE (2005b) DEDE (2005c) EEA (2013) OAE (2009)
2005
The data mapping steps of the environmental inventory data into the environmentally extended input-output model are presented in Figure 3-2.
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Figure 3-2. Data mapping steps of the environmental inventory data into the THIO table.
Greenhouses (GHGs) emissions
GHGs emissions (CO2, CH4 and N2O) from energy use in each industrial sector were estimated from the energy combustion and chemical reactions (flue gas desulfurization) in the energy transformation processes, based on the 2006 IPCC guidelines. To estimate the GHGs emissions from the industrial process such as cement, lime, pulp and paper, iron and steel, petrochemical, food and beverage industries were calculated based on the IPCC guidelines.
Emissions from methane and other gases such N2O, from the enteric fermentation, iron and steel, rice cultivation, burning of crop residues and agriculture soils was estimated based on the 2006 IPCC guidelines (IPCC, 2006).