Carbon footprint estimation and data sampling method: a case study of ecologically cultivated rice produced

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1 Carbon footprnt estmaton an ata samplng metho: a case stuy of ecologcally cultvate rce prouce n Japan Naok Yoshkawa 1, Tomohro Ikea 1, Koj Amano 1, Koj Shmaa 1 College of Scence an Engneerng, Rtsumekan Unversty, Nojhgash, Kusatsu, Shga, , Japan, College of Economcs, Rtsumekan Unversty, Nojhgash, Kusatsu, Shga, , Japan 3 ABSTRACT Carbon footprnt estmaton of foo proucts s consere to requre collectng ata on a number of agrcultural proucers to ensure statstcal representatveness of nventory ata. Ths stuy evaluate the carbon footprnt of ecologcally cultvate rce prouce n Japan an eamne the representatveness of nventory ata employng survey samplng theory. Fve lfe cycle stages were set for estmaton: raw-materal proucton, rce polshng, strbuton an retalng, rce cookng, an waste treatment. Foregroun ata on over 100 proucers were collecte n agrcultural proucton. The results show that the carbon footprnt of rce s 7.7 kg-co eq/package (4 kg of polshe rce). The contrbuton of raw-materal proucton s conserable, especally that of methane emssons from pay fels. Representatveness s eamne by the stanar-error rato of estmate nputs. The stanar error rato of greenhouse gas (GHG) emssons evaluate by poststratfe estmator was 3.8%, whch seeme to have enough representatveness. However, the results suggeste a smaller sample can mprove representatveness f mplementng an optmal sample survey. Keywors: carbon footprnt, rce, ata samplng 1. Introucton Japanese actvtes relate to the carbon footprnt of proucts (CFP) starte n 008, an have reache the stage of sale n stores. Regarng carbon footprnt estmaton of foo proucts, although there stll s no consensus on ata collecton base on statstcal theory, researchers may have to survey foregroun ata on a number of agrcultural proucers to ensure representatveness of nventory ata. Ths mght make CFP n foo an agrculture unafforable, especally for smaller supplers, or unrelable wthout reasonable guelnes for ata collecton on mass supplers. Ths stuy estmate the carbon footprnt of ecologcally cultvate rce prouce n Shga prefecture, Japan, whch s the frst prouct sol n stores to carry a carbon footprnt label. In aton, we eamne the representatveness of nventory ata an the ata collecton methos, utlzng survey-samplng theory.. Estmatng the carbon footprnt of rce.1. Summary of CFP calculaton The prouct subject to estmaton of CFP s specally cultvate polshe rce (varety: Koshhkar) prouce n the northern area of Shga Prefecture, Japan (Fgure 1). Ths prouct s treate wth less than one-half the conventonal applcaton of chemcal ntrogen fertlzer an agrochemcals n rce cultvaton. Begnnng n January 010, packages wth a CFP

2 label have been sol n retalers aroun Japan. The functonal unt n ths stuy s one package (4 kg polshe rce). GHG (CO, CH 4, an N O) emssons were estmate employng a crale-to-grave analyss... System bounares Fve lfe cycle stages of rce were set for estmaton: raw materal proucton, rce polshng, strbuton an retalng, rce cookng, an waste treatment. Fgure shows the system bounary of each stage. In rce polshng stage, both the man prouct (polshe rce) an coproucts (rce bran, utlze as fertlzer materal) are prouce.the envronmental loas of both proucts n the rce-cultvaton an rce polshng stages were allocate by economcal value. Fgure 1: Prouct subject to CFP estmaton Envronmental loa relate to urables (agrcultural equpment, facltes, cookng equpment, etc.) are not nclue because of uncertanty about ther urable peros. Wasterecyclng processes are not estmate n orer to avo ouble countng wth utlzaton of recycle materals. atons of consumers between ther homes an Raw materal proucton See rce proucton See rce Brown rce cultvaton process Nursery preparaton Co-proucts Rough rce Rce processng processng plant Dryng fertlzer proucton Agrochemcals proucton Fertlzer Agrochemcals Seeng Lan preparaton Plantng Cultvaton management Rough rce Rce processng on-farm Dryng Huskng Grang Co-proucts Brown rce Huskng Grang Packagng Weghng Brown rce Harvestng Packagng Preservaton Coprouct Packagng materals proucton Waste aton Materals proucton Packagng materals brown rce shpment Packagng materals polshe rce shpment Waste treatment aton Materals polshe rce shpment Waste Waste treatment Fgure : System bounares

3 retalers are also not taken nto account..3. Data collecton Actvty ata were collecte as foregroun ata when possble, though some ata were collecte as backgroun ata. Major nput materals n each stage are summarze n Table 1. In the raw materal proucton stage, over 400 proucers cultvate the rce for the subject prouct. Ths stuy collecte ata on 109 proucers. These ata cover over 50% of all the proucts, whch the current Japanese carbon footprnt calculaton rules (Prouct Category Rules, or PCR) for rce requre as the stanar for ata collecton. Input ata of fertlzer, agrochemcals, fuels, an electrcty, n each agrcultural proucer an rce-processng plant, were surveye. CH 4 an N O emssons from pay fels also were taken nto conseraton (GIO, 009). Actual ata of transportaton stance were collecte for the man prouct; the stance (500 km) an loang factor scenaros were use for transport of nputs. Foregroun ata were surveye n the rce polshng stage an the strbuton an retalng stage. Emssons from the rce polshng stage were calculate from energy usage n rcepolshng plants. Energy use n retalers was collecte from chan stores ealng n the subject prouct. Data on whole stores were allocate to each prouct by calculatng the emsson factor per retal prce. The average transport stance between stores an rce polshng plants was use for transport of package proucts base on past recors of elvery. In the cookng stage, we utlze the PCR scenaro, whch nclues average electrcty an water use ata n rce cookng usng an average omestc rce cooker. In the waste treatment stage, we estmate ata for ncneraton an sposal n lanflls of plastc rce packages. The rato of treatments use s the average value n Japan. Table 1: Summary of ata collecton Lfe cycle stage Inputs Data source of backgroun ata Lfe cycle stage Inputs Data source of backgroun ata Raw materal proucton Energy JEMAI, 009a Rce polshng Energy Fertlzer Dstrbuton & Energy JEMAI, 009b Agrochemcals retalng aton JEMAI, 009a Packagng materals JEMAI, 009a Energy Cookng Sees Ajnomoto Co., Inc.,007 Water supply GHG from pay fel GIO, 009 Waste treatment Waste treatment.4. Results of carbon footprnt estmaton Fgure 3 shows the results of carbon footprnt estmaton per package (4 kg polshe rce). CFP n all stages s 7.7 kg-co eq/package. About 65% of emssons were relate to the raw materal proucton stage; almost all emssons come from agrcultural proucton. CH 4 emsson from pay fels, whch s cause by anaerobc fermentaton, accounts for 50% of LC-GHGs from agrcultural proucton, although uncertanty concernng ts emsson factor s hgh. Beses CH 4 emsson, emsson of GHGs from fertlzer, energy, an transportaton of nput materals each accounte for more than 5% of LC-GHGs n agrcultural proucton. After the raw materal proucton stage, the strbuton an retalng stage an the rce cookng stage are key stages for emsson of LC-GHGs. Most emssons n the cookng stage were Fgure 3: Results of carbon-footprnt calculaton

4 from electrcty use by rce cookers. All transportaton of proucts an nputs accounte for 6.5% of LC-GHGs. 3. Evaluaton of representatveness of nventory ata 3.1. Approach When calculatng the CFP of agrcultural proucton usng actvty ata surveye by ata samplng, uncertanty relate to statstcal errors n process ata becomes an ssue, as well as uncertanty of emssons factors an system bounares. If mplementng naequate ata samplng, the cost of surveyng CFP rses to ensure relablty of actvty ata. Samplng survey theory can be applcable for evaluatng agrcultural actvtes nvolvng a large number of small proucers. Ths stuy evaluate the representatveness of CFP ata by estmatng the varablty of calculate ata an consere optmal ata samplng. Data varablty s eamne by the stanar error rato of materal nput quantty by parent populaton (all proucers), estmate from ata on sample proucers. Stanar error rato, corresponng to coeffcent of varance of estmates, s evaluate by uncertanty of nput ata an samplng rato from parent populaton. Ths ncates representatveness of nventory ata because both average nventory ata estmate from ata wth hgh uncertantes an that from few samples have poor relablty to use the ata as representatve ata. Snce cultvate area vares by proucer as seen n Table, t s assume that the nput quantty of each materal correlate wth cultvaton area. Cultvaton area can be more sute for an aulary varable than the proucton, because proucton changes every year by varous factors when cultvaton area oesn t change for years. The survey can be esgne before harvestng by usng cultvaton area as an aulary varable. On the other hans, another tren of materal nput seeme to be foun by farm-sze level (Table 3). Therefore, ths stuy uses two types of estmaton: rato estmator an poststratfe rato estmator. Table : Dstrbuton an samplng of proucers by farm sze Samplng rato Table 3: Coeffcents of varance n materal nput of surveye ata ha 5ha Over 5ha total Gasolne Desel ol Fertlzer Agrchemcals N applcaton The rato estmator s the amount of nputs by parent populaton estmate usng nputs by the sample an the rato between the aulary varables of the sample an the parent populaton. Ths case utlzes the cultvaton area of rce as an aulary varable as shown as equaton (1). τ = τ ( ) (1) ˆ y, R y Where, ˆy τ s the estmate amount of nput y,,r τ s the total cultvaton area of the parent populaton, y s the average nput of materal n surveye proucers, s the average rce cultvaton area n surveye proucers, an s the type of nput. Stanar error rato of the rato estmator s appromate as equaton ().

5 τ n 1 CV ( ˆ τ = τ (), y, R ) (1 ) ( yj Rˆ j ) ˆ y R N n ( n 1) j Wth CV ( ˆ τ y,r ) : stanar error rato of total nput quantty estmaton of materal, or coeffcent of varance of estmates ˆy τ,, R n : number of samples n materals, N : number of all proucers, y j : total nput materals by proucer j, Rˆ : stans for y, j : rce cultvaton area of proucer j, j : proucer.. The poststratfe rato estmator ves the sample nto several strata an estmates usng a rato estmator n each stratum. In ths case, stratfe survey samplng has not been mplemente, however, here assumes stratfe samplng e-post facto by utlzng estng sample ata. Ths stuy ve the sample nto three strata by cultvaton area as shown n Table. The equaton of estmaton by the poststratfe estmator s shown as equaton (3). ˆ τ y PS = y, τ, (, ) (3) Where, ˆy τ s the poststratfe estmate amount of nput y,ps, τ s the total cultvaton, area of the parent populaton n stratum, y, s the average nput of materal n surveye proucers of stratum, an s the average rce cultvaton area n the surveye proucers of stratum. Stanar error ratos n poststratfe rato moel are also calculate. In ths case, the ata representatveness of gasolne, esel ol, fertlzer, an ntrogen fertlzer applcaton (N O), an of agrochemcals, was evaluate because these ata were collecte by each proucer surveye. The percentages of the sample for whch each nput atum n the parent populaton was collecte are presente n Table 4. Actvty ata relate to fertlzer an agrochemcals were collecte n all surveye proucers because such ata on ths prouct are manage by agrcultural cooperatves to confrm cultvaton stanars. However, snce energy consumpton ata have not been collecte routnely, the response rate for ths ata was lower. The stanar error rato of the total GHG emssons from fve materal nputs was estmate by Monte Carlo smulaton usng the stanar error rato of each materal as the source of the parameters of the (normal) strbuton. In aton, optmal samplng esgn was consere n ths case. Stratfe samplng an Neyman allocaton (Optmal alocaton) were apple. The number of proucers to survey was estmate when the confence level was 95 %. Table 4: Samplng rato by nput materals Gasolne Desel ol Fertlzer Agrchemcals N applcaton Samplng rato 16% 16% 6% 6% 6% 3.. Results of representatveness evaluaton Table 5 ncates the stanar error rato of each materal an the total GHG emssons from fve materals nput. The surveye ata of gasolne s conserably varable, as shown n Table 3, an ts uncertanty uner both estmaton methos s hgher than that of other nput materals. However, the poststratfe estmator performe better than the rato estmator for other nput materals. An especally sgnfcant effect of stratfcaton was foun n fertlzer an agrochemcals. The stanar error rato of total GHG emssons s about 3.8%, corresponng to a ± 7% confence nterval at the 95% confence level. Ths survey s consere to have suffcent relablty n terms of ata representatveness. The requre number of samples when mplementng stratfe samplng s represente n Fgure 4. Tolerances are set as 1% an 5% n the 95% confence level. Ths s a strcter cr-

6 teron than the performance that resulte n Table 5. Total ncates the mnmum sample sze that mantans the performance set for all nput materals. The number of requre samples n the case of 5% tolerance s lower than n the survey actually mplemente, although the accuracy s better uner optmal samplng that covers smaller proucers. Stanar error rato Average GHG emsson CO eq/10a 4. Dscusson Table 5: Results of stanar-error rato estmatons N Gasolne Desel ol Fertlzer Agrchemcals O from N applcaton Total rato estmator 11.3% 7.6% 11.% 13.8% 9.1% 5.9% poststratfe estmator 11.3% 5.8% 5.7% 6.5%.3% 3.8% rato estmator poststratfe estmator Fgure 4: Number of samples requre at 95% confence level In CFP calculaton, CH 4 emssons mae mportant contrbutons to total GHG emssons. Although ths stuy coul not apply etale estmaton by restrcton of ata, t s necessary to conuct evaluaton n etal nclung emssons moels or measurements, an to make efforts to reuce emssons. The results on transportaton of man proucts an nputs mply the potental effect of local proucton an consumpton, an ts lmtatons. Although the results of analyss of ata representatveness are lmte to those consstng of some major nput materals, ths suggeste the mportance of mplementng sample surveys on CFP for proucts from a large number of supplers to mprove ata relablty an feasblty. Ths stuy collecte ata on varablty of materal nputs, an these ata can be applcable n sample esgn for CFP of rce prouce n stuatons smlar to ths case. Also ths metho can apply to the ata qualty evaluaton n case of ata efcency among large number of proucers. Net step wll be nclung varablty of yel n evaluaton for precse ata qualty assessment, because ths stuy evaluate only that of nput materals. Beses, further ata collecton to epan applcablty an efnton of a framework enablng smple an relable evaluaton of ata representatveness wll be neee. 5. References Ajnomoto Co. Inc. (007): Ajnomoto Group LC-CO emssons factor atabase for foorelate materals Greenhouse Gas Inventory Offce of Japan (GIO) (009): Natonal GHGs Inventory Report of Japan The Japan Envronmental Management Assocaton for Inustry (JEMAI) (009a): Common backgroun atabase of CFP The Japan Envronmental Management Assocaton for Inustry (JEMAI) (009b: Reference ata for PCR PA-AA-01(Rce)