1. business and industrial
2. agriculture and forestry
3. crops and seed

ENVIRONMENTAL IMPACTS OF RICE
PRODUCTION
USING LIFE CYCLE ASSESSMENT
Sumiani Yusoff, PhD.,
Punithawaty Panchakaran
Faculty of Engineering
University of Malaya, Malaysia
INTRODUCTION
ABOUT MALAYSIAN RICE PRODUCTION:
• Malaysia : total production 0.4 % of world output
• 1 hectare = approx. 3.7 tonnes of rice, 85% of total paddy areas are in
peninsular Malaysia
• Rice Production in 2010 = 1,588,456 MT
Rice Production in 2011 = 1,661,260 MT
• We produce less than 70% of what we need (rest imported from Vietnam,
Thailand, even US); average Malaysian citizen consumes 85-90 kg of rice/yr
• A typical rice production process:
Land Preparation
Sprout Planting
Harvesting
Rice milling
GOAL AND SCOPE
GOAL
 To study the environmental impacts of rice production in a chosen
paddy field in Kedah, focusing on the paddy growing stages
 To compare the impact contributions of different chemical inputs used
in two separate seasons of rice planting
 To make informed recommendations with regards to pesticide and
fertilizer use to reduce the environmental impacts
 The intended audience will be the paddy growers - so they may be able
to make environmentally smarter decisions to achieve sustainable rice
farming
GOAL AND SCOPE
SCOPE
 Functional Unit = 1MT of harvested rice grains
 The system boundary set for the this study is Cradle-to-Gate
• The process flow chart, shown in the next slide, details the system
boundary as well as the raw material and energy use
 Spacial scope: approx. 4 hectares (1 paddy farm)
• Location – Gunung Keriang, Alor Setar, Kedah
 Temporal scope: 2 seasons; 2010 and 2011
 The software used: JEMAI LCA Pro ver. 2.1.2
 Impact analysis is based on LIME and Eco Indicator 95
SYSTEM BOUNDARY
Raw Material:
• Paddy seeds
Chemicals used:
• Pesticides
(various)
• Fertilizer
1.Compound
Fertilizer
2.NPK Fertilizer
3.Urea
Land Preparation
(Soil ploughing, flooding)
Product:
• Unmilled Rice
Grains
Sprout Planting
Nutrient Management
Air Emissions
Pest Management
Utilities and Fuel:
• Water
• Diesel
• Petrol
Water Emissions
Harvesting
System Boundary for “Cradle-to-Gate” of Rice Production
INVENTORY ANALYSIS
Data collection:
Primary Source
• Information regarding pesticide and fertilizer type and
quantity was extracted from invoices, purchase order
forms and receipts obtained from the paddy grower
• Phone enquiries made to MADA, National Farmer’s
Association and local suppliers to obtain more details
Secondary Source
• Journals and past studies were used to predict emissions
for many of the unknown chemicals that are not included
in the JEMAI LCA Pro Database
INVENTORY ANALYSIS
Basic Information
Rice Farm Size
3.856 hectares
Distance From Farm to Mill
15.3 km
Season
Feb-June
Water Usage
38000 m3
2010
2011
Rice Output: 9440 kg
Rice Output: 9260 kg
Total Fertilizer Used: 2137 kg
Total Fertilizer Used: 1867 kg
Total Pesticide Used: 23 kg
Total Pesticide Used: 21 kg
INVENTORY ANALYSIS
PESTICIDE USAGE – RAW DATA (SAMPLE)
Brand Name
Unit Qty per Total Qty Active Ingredient
s
unit
2
1L
2000 mL paraquat dichloride
(25%w/w)
1
PARAKUAT
2
505
2
3
TAPISAN
6
250 g
4
KARATE
2
1L
5 ACTARA 25 WG
2
100 g
200 g
Thiamethoxam
(25%)(250g/kg)
6 NOMINEE 100
SC
3
250 mL
750 mL
Bispyribac-sodium
10% w/w
500 mL 1000 mL
Chlorpyrifos (50%
w/w), Cypermethrin
(5% w/w)
1500 g
Buprofezin (10%),
Cartap Hydrochloride
(50%)
2000 mL lambda-cyhalothrin
(50 g/L)(20%)
Inert Ingredients
Company Supplier
Sodium
dodecylbenzenesulfonate
(10%), amines, C13-15alkyl, ethoxylated (5%)
calcium salt of alkyl benzene
alkene benzene sulphonic
acid, polyethanoxy ether of
nonyl phenol (6%),
polyethnoxy propoxy ether
2.5%, o-xylene 30%
surfactant (10%)
Titanium dioxide,
Naphthalene (3%),
benzisothiazol3(2H)-one
Diamotaceuous earth,
Cristalline silica, Starch
Agricultural
Chemicals (M)
Sdn. Bhd.
Syngenta Crop
Protection Sdn.
Bhd.
Syngenta Crop
Protection Sdn.
Bhd.
Agricultural
Chemicals (M)
Sdn. Bhd.
INVENTORY ANALYSIS
Example from 2011 Inventory Data
Pesticide Active Ingredient Input and Output Based on Functional Unit
Input/Active Ingredient (kg)
Brand Name
Chemical Name
Parakuat
Paraquat dichloride
C12H14Cl2N2
Chlorpyrifos
C9H11Cl3NO3PS
Cypermethrin
C22H19Cl2NO3
Buprofezin
C16H23N3OS
Cartap Hydrochloride
C7H16ClN3O2S2
KARATE
lambda-cyhalothrin
C23H19ClF3NO3
ACTARA 25 WG
Thiamethoxam
C8H10ClN5O3S
505
Tapisan
Output/Emissions (kg)
Chemical Formula Total Weight
Primary Data + Secondary Data
Quantity Used Based on Original purchasing receipts
Chemical composition based on Corporate MSDS
0.067
0.075
0.006
0.016
0.080
0.057
0.05
CO2
Cl2
NO2
SO2
N
P
H2O
F2
1.38E-01
9.20E-03 1.19E-02 0.00E+00 3.63E-03 0.00E+00 2.80E-02 0.00E+00
8.55E-02
9.97E-02 4.97E-03 1.38E-02 1.51E-03 6.70E-03 2.14E-02 0.00E+00
2.09E-01
1.53E-02 2.48E-03 0.00E+00 7.56E-04 0.00E+00 3.69E-02 0.00E+00
1.07E-02 0.00E+00 1.08E-03 9.72E-04 3.24E-04 0.00E+00 3.13E-03 0.00E+00
8.97E-02
1.04E-02 2.01E-02 3.73E-02 6.12E-03 0.00E+00 4.19E-02 0.00E+00
6.46E-02
4.54E-03 2.92E-03 0.00E+00 8.92E-04 0.00E+00 2.18E-02 7.24E-03
6.48E-03
6.48E-04 2.16E-03 1.19E-03 6.48E-04 0.00E+00 1.65E-03 0.00E+00
Secondary data
Derived from: Journals
Final value based on calculation + estimation
INVENTORY ANALYSIS
Example from 2011 Inventory Data
Pesticide Inert Ingredient Input and Output Based on Functional Unit
Brand Name
Parakuat
505
Input/Inert Ingredients (kg)
Chemical
Chemical Name
Formula
Sodium
C18H29NaO3
dodecylbenzenesulfo
S
nate
amines, C13-15-alkyl,
C16H37NO
ethoxylated
calcium salt of alkyl
C36H58CaO6
benzene sulphonic
S2
acid
o-xylene
Tapisan
KARATE
ACTARA 25 WG
NOMINEE 100 SC
C8H10
Sodium
C18H29NaO3
dodecylbenzenesulfo
S
nate
Output/Emissions (kg)
Total
Weight
CO2
Cl2
NO2
SO2
N
P
H2O
Na
Ca
0.022
5.13E-02
0.00E+00
0.00E+00
4.10E-03
0.00E+00
0.00E+00
1.69E-02
1.49E-03
0.00E+00
0.005
4.18E-02
0.00E+00
1.37E-03
0.00E+00
4.16E-04
0.00E+00
1.98E-02
0.00E+00
0.00E+00
0.006
1.36E-02
0.00E+00
0.00E+00
1.08E-03
0.00E+00
0.00E+00
4.43E-03
0.00E+00
3.24E-04
0.031
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.016
3.67E-02
0.00E+00
0.00E+00
3.02E-03
0.00E+00
0.00E+00
1.21E-02
1.08E-03
0.00E+00
n-hexane
C6H14
0.028
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
benzisothiazol3(2H)-one
C7H5NOS
0.010
2.19E-02
0.00E+00
3.24E-03
4.54E-03
0.00E+00
0.00E+00
3.13E-03
0.00E+00
0.00E+00
Sodium lauryl sulfate
NaC12H25SO4
0.001
6.80E-03
0.00E+00
0.00E+00
8.64E-04
0.00E+00
0.00E+00
2.92E-03
2.98E-04
0.00E+00
Sodium lauryl sulfate
NaC12H25SO4
0.004
6.80E-03
0.00E+00
0.00E+00
8.64E-04
0.00E+00
0.00E+00
2.92E-03
2.98E-04
0.00E+00
n-hexane
C6H14
0.010
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
o-xylene
C8H10
0.021
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
0.00E+00
Primary Data + Secondary Data
Quantity Used Based on Original purchasing receipts
Chemical composition based on Corporate MSDS
Secondary data
Derived from: Journals
Final value based on calculation + estimation
INVENTORY ANALYSIS
Example from 2011 Inventory Data
Fertilizer Input and Output Based on Functional Unit
Input/Fertilizer (kg)
Output/Emissions (kg)
Brand Name
Ingredient
Total Weight (kg)
Compound
NH4NO3 (17.5%), P2O5
(15.5%), KCl (10%)
101.512
Urea
CH4N2O
43.089
NPK
NH4NO3 (17%), P2O5 (3%), KCl
(20%)
57.019
Primary Data
Obtain from: Original purchasing receipts + MADA
CO2
31.6
NH3
PO3
N2
Cl2
K
H20
17.5
6.216
4.935
7.992
1.9
3.39
5.548
4.361
24.42
Secondary data
Derived from: MADA, Journals
Final value based on calculation + estimation
INVENTORY ANALYSIS
Inventory Analysis Methodology: Input Data
Brand
Name
Parakuat
Quantity
500 mL
Primary Data
Original data
obtained from
purchase receipts
Composition
%
Density of
Chemical
(g/cm3)
Paraquat Dichloride
25
1.25
625 (FU=67)
Sodium dodecylbenzenesulfonate
10
1.06
212 (FU=22)
amines, C13-15-alkyl, ethoxylated
5
0.5
55 (FU=5)
Chemical
Constituents
Weight of
Chemical (g)
Secondary Data
Calculated
Ingredient data obtained from corporate msds
Many MSDS available online for the same product
Data was cross-checked for consistency
Input data calculated
based on primary and
secondary data to fit for
use in JEMAI
ASSUMPTIONS:
Chemical with a composition % of below 5% are not included (cut-off rule).
Inert ingredients that were not identified is assumed to be lower than 5% in composition OR they do not pose an
environmental threat.
This assumption is the subject of the sensitivity analysis because we know that heavy metals exist
.
in pesticide and toxic solvents form a larger % of composition based on EPA report Trade Secrets!
INVENTORY ANALYSIS
Caution note from EPA
INVENTORY ANALYSIS
Inventory Analysis Methodology: Output Data
Brand
Name
Chemical
Constituents
Paraquat Dichloride
Parakuat
Chemical
Formula
C12H14Cl2N2
Sodium
dodecylbenzenesulfonate
C18H29NaO3S
amines, C13-15-alkyl,
ethoxylated
C16H37NO
Fate and
Transport
Mechanism
Final
Emission
Form
Most pesticides and fertilizer
end up in soil and water
where they are degraded
efficiently by microbes
These chemicals are not
present in air for very long
CO2
CH4
NOx
SOx
etc
(See next slide)
Emission data not available, hence journal were used as reference for calculation and estimation
Value of final emission calculated via mass balance and basic chemistry
1.
2.
Molecular formula
Balanced Chemical Equation for Microbial Respiration (oxidation reaction)
INVENTORY ANALYSIS
Fate and
Transport
Mechanism
Final
Emission
Form
(Bodegom, 2001)
INVENTORY ANALYSIS
This study shows that CH4 and CO2 concentration
(moles) in soil are equal under anaerobic paddy field
condition
This is why CH4 is a serious problem
INVENTORY ANALYSIS
Energy Raw Data
Utilities
Tractor+
Rotator
Tractor+
Leveller
Dry tillage
2 time
3500
3.856 ha
Diesel
Fuel
consumption
rate
8 l/relung
Wet tillage
2 time
3300
3.856 ha
Diesel
7.5 l/relung
Tractor+
Leveller
Car
Dry tillage
2 time
3300
3.856 ha
Diesel
7 l/relung
2 trip
955
9.2 km
Petrol
13.5km/l
4 trip
1500
18.4 km
Diesel
-
-
Harvester
Seed&
Pesticides
delivery
Fertilizer
delivery
Harvesting
45
mins/relung
-
2 time
8500
3.856 ha
Diesel
12 l/relung
Lorry B
Paddy delivery
10000
30 km
Diesel
-
45
mins/relung
-
Lorry A
Process
Frequency Weight
Total
(kg)
distance/area
Fuel
Time
consumption
rate
1hr 15
mins/relung
1
hour/relung
INVENTORY ANALYSIS
Energy Input and Output Based on Functional Unit
Weight
(kg)
Distance/
Total
return
distance/a
trip(km)
rea
Fuel
Total fuel
consumption
Funtional
unit 2011
(L)
N20
(kg)
CO2
(kg)
CH4
(kg)
Utilities
Process
Frequency/
season
Tractor+
Rotator
Dry tillage
1 time
3500
-
3.856 ha
Diesel
107.11
11.57
0.00134
42
0.004
Tractor+
Leveller
Wet tillage
1 time
3300
-
3.856 ha
Diesel
193.42
10.84
0.00122
35
0.003
Car
Seed&
Pesticides
delivery
1 trip
955
4.6
4.6 km
Petrol
0.34
0.037
Lorry A
1500
Fertilizer
delivery
2 trip
1500
4.6
9.2 km
Diesel
Harvester
Harvesting
1 time
8500
-
3.856 ha
Diesel
160.67
17.35
0.0013
40
0.0077
Lorry B
(2010)
Paddy
delivery
10 000
30 km
Diesel
Lorry B
(2011)
Paddy
delivery
10 000
30 km
Diesel
Fuel efficiency data retrieved from machine operator
Output emission data for tractors and harvester calculated based on data retrieved from
journals.
Journals provide emission of pollutants per litre of fuel used.
INVENTORY ANALYSIS
Example of Inventory Analysis Result from JEMAI
IMPACT ASSESSMENT
• Impact assessment was performed using two methods mainly;
the Eco Indicator 95 and LIME (Life Cycle Impact Assessment
Method based on Endpoint Modeling)
• All impact categories were considered
• The steps taken into account (under ISO 14040):
1. Classification
2. Characterization
3. Normalization
4. Weighting
IMPACT ASSESSMENT
ECO INDICATOR 95
• Characterization Results
2010
2011
 For both years, Global Warming was the greatest impact followed by Eutrophication
 Value from 2010 to 2011 varies very slightly
IMPACT ASSESSMENT
ECO INDICATOR 95
• Normalization Results
2010
2011
 For both years, Eutrophication and Global Warming still remain the top two impact
 Eutrophication impact is largely due to the heavy use of fertilizers in both years
• up to 230kg (in total) per 1MT of rice produced
IMPACT ASSESSMENT
LIME
• Characterization Results
2010
2011
2.93E+01
 For both years, top three impacts were Fossil Energy Resource Consumption, Global
Warming and Eutrophication
IMPACT ASSESSMENT
LIME
• Impact Charts
2010
2011
IMPACT ASSESSMENT
LIME
2010
CO2 ~ 52.9%
CH4 ~ 46.4%
2011
CO2 ~ 54.3%
CH4 ~ 45.0%
FERTILIZERS
2010
PO4 ~ 72.4%
NH4 ~ 17.6%
2011
PO4 ~ 79.5%
NH4 ~ 20.5%
IMPACT ASSESSMENT
LIME
2010
2011
2010
2011
IMPACT ASSESSMENT
2010
2011
IMPACT ASSESSMENT
2010
2011
IMPACT ASSESSMENT
2010
2011
INTERPRETATION
SENSITIVITY ANALYSIS
Initial Assumption:
In sensitivity analysis:
1) Input data of inert
chemicals in pesticides:
- info not revealed, or;
- quantities are small
1) Increase amount of inert
substances:
- 15% of solvent &
- very small quantities of
heavy metal; As, Pb, Cd
Sensitivity Analysis is a
method to:
From previous
studies/literatures, large
percentage of solvent and
small amount of heavy
metal were found in
pesticides
- evaluate/estimate
potential significance of
data gap
- see how much potential
impacts vary when data
changes
Limitation/Data gaps:
- Information are protected
by trade secret
Sensitivity analysis
investigation is
performed using
method:
- LIME
- Eco-Indicator 95
LIME CHARACTERIZATION
Results projection from
sensitivity analysis using LIME:
• Presence of new potential
impacts (human toxicity &
ecotoxicity) – however from
the weightage perspective,
the impact contributions are
very small.
• Initial findings still stand
Increase amount of substances in LCI
• Nonetheless, results must be
treated with caution.
ECO-INDICATOR 95
Eco-Indicator 95
unable to show
potential impacts in
impacts category of
heavy metals &
carcinogen due to
very small
contributions.
CONCLUSION
 The three most significant potential environmental impacts of rice production
in a chosen paddy field in Kedah for both seasons are:
1. Fossil energy consumption
2. Global warming
3. Eutrophication
 Although different pesticides were used in each season, the quantities in
which they were used were very small and therefore, did not cause much
change between the two seasons.
 However, it is clear from our findings that the high use of fertilizers has left
the greatest impact. The microbial degradation of the fertilizers leads to
eutrophication and global warming through the release of phosphate and
ammonium ions as well as GHGs (CO2 and CH4).
• Values in 2010 are slightly more elevated as the quantity of fertilizers
were greater
 It is recommended to adopt sustainability in pest and fertilizer management
and reducing the usage of pesticides and chemical fertilizer by introducing
eco-friendly method and formulations or organic farming.
Limitations:
 Data gaps
 Poor
access to data
 Trade secrets
 Uncertain fate and transport of the
chemicals
 Time constraint
 Lack of any national data base, specific for
rice production
Recommendations:
 Sustainable
pest management, decrease or
eliminate pesticide and chemical fertilizer
usage
 Implementation of IPM(integrated pesticide
management)
 Developing rice varieties with built-in
resistance to common pests and diseases
 Adopting ecological engineering
Chinese eco-friendly rice farming
methods
Rice duck farming
Inter-cropping system
Rice fish farming
68% less chemical pesticide
use and 24% less chemical
fertilizer use
Light trap
Global warming impact:
 More CO2 in the
atmosphere coupled with rising
temperatures, is making rice agriculture a larger source of
the potent GHG
 Simple changes in rice cultivation could help reduce
methane emissions:
- mid-season drainage
- alternative fertilizer
- switching to more heat-tolerant rice cultivars
- adjusting sowing dates that yield decline due to
temperature increase can be prevented