Journal of Climate Change Research 2015, Vol. 6, No. 3, pp. 233~241 DOI: http://dx.doi.org/10.15531/ksccr.2015.6.3.233 * * * * * ** ** *, ** Post-2020 Emission Projection and Potential Reduction Analysis in Agricultural Sector Jeong, Hyun Cheol *, Lee, Jong Sik *, Choi, Eun Jung *, Kim, Gun Yeob *, Seo, Sang Uk *, Jeong, Hak Kyun ** and Kim, Chang Gil ** * Division of Climate Change & Agroecology, Department of Agricultural Environment, National Academy of Agricultural Science, Wanju 55365, Korea ** Dept. of Resource & Environment Research, Korea Rural Economic Institute, Naju 58217, Korea ABSTRACT In 2014, the United Nations Framework Convention on Climate Change (UNFCCC) agreed to submit the Intended Nationality Determined Contributions (INDCs) at the conference of parties held in Lima, Peru. Then, the South Korean government submitted the INDCs including GHGs reduction target and reduction potential on July, 2015. The goal of this study is to predict GHGs emission and to analyze reduction potential in agricultural sector of Korea. Activity data to estimate GHGs emission was forecast by Korea Agricultural Simulation Model (KASMO) of Korea Rural Economic Institute and estimate methodology was taken by the IPCC and guideline for MRV (Measurement, Reporting and Verification) of national greenhouse gases statistics of Korea. The predicted GHGs emission of agricultural sectors from 2021 to 2030 tended to decrease due to decline in crop production and its gap was less after 2025. Increasing livestock numbers such as sheep, horses, swine, and ducks did not show signigicant impact the total GHGs emission. On a analysis of the reduction potential, GHGs emission was expected to reduce 253 Gg CO 2-eq. by 2030 with increase of mid-season water drainage area up to 95% of total rice cultivation area. The GHGs reduction potential with intermittent drainage technology applied to 10% of the tatal paddy field area, mid-drainage and no organic matter would be 92 Gg CO 2-eq. by 2030. Key Words: INDCs, GHG, Agricultural Sector, Projection, Methane, Nitrous Oxide 1. 서론 2014년페루리마에서개최된제20차기후변화협약 (United Nations Framework Convention on Climate Change, UNFCCC) 당사국총회 (Conference of the Parties, COP) 에서는각국이정하는자발적기여방안 (Intended Nationality Determined Contributions, INDCs) 을 2015년까지제출하기로합의하였으며, 사무국은같은해 10월까지제출된 INDCs 의종합적효과에대한종합보고서를 11월까지준비하기로합의하였다 (KCRC, 2014). INDCs 에는온실가스감축목표와관련된기준년도, 기간, 범위, 방법론등과자국의기여에대한정보를담도록하였고, 각국이현재수준보다강화된 후퇴 (Backsliding) 없는 수준에서온실가스감축목표를제출하도록합의하였다 (KIEP, 2015; UN- FCCC, 2014). 이미우리나라는 2009년온실가스감축목표를 2020년배출전망치 (Business As Usual, BAU) 대비 30% 로결정하고국제사회에약속한바있으며, 국내적으로는저탄소녹색성장기본법에온실가스감축목표에대해명시하고있다. 우리나라는온실가스감축목표달성을위해 7개산업부문별로감축량을할당하였고, 농림어업부문도 5.2%(1,484 천톤 CO 2-eq.) 의온실가스의무감축을할당받았다 ( 환경부, 2014). 농업부문 Corresponding author : taiji152@korea.kr Received August 31, 2015 / Revised September 11, 2015 / Accepted September 21, 2015
234 정현철 이종식 최은정 김건엽 서상욱 정학균 김창길 에서는논간단관개면적확대, 화학비료사용절감, 가축분뇨처리시설확대및양질조사료보급확대, 에너지이용효율화등을통해 2020년까지온실가스감축목표를달성할계획이다 (Lee et al., 2014). 우리나라농업부문에서발생하는온실가스배출량은국가전체배출량의약 3.2% 로타산업에비해온실가스배출에미치는영향은작다 ( 환경부온실가스종합정보센터, 2014). 그러나농업은기후에직접적으로노출되어있고, 식량안보와같은국민의생존과직결되어있기때문에온실가스감축과적응에있어신중한접근이필요하다 (Myeong, 2014). 또한우리나라를포함한유럽등주요선진국들은이미농업부문에서온실가스감축을해왔기때문에감축잠재량은개도국에비해적다 (Myeong, 2014). 우리나라는지난 7월 UNFCCC 에 INDCs 를제출한바있고, 온실가스감축목표달성을위해향후감축기술선정, 감축이행계획수립등많은노력을기울여야한다. 본연구는 2021년부터 2030년까지농경지분야온실가스배출량을전망하고, 국가온실가스감축목표에기여하기위한감축잠재량을평가하였다. 감축잠재량전망을위해현재까지개발된벼논간단관개, 논물얕게대기, 무경운, 유기물관리, 토양개량제시용등의감축기술들중우리나라농업여건과수리시설현황, 농업생산성, 식량안보, 통계구축현황등을고려하여감축기술을선정하고, 기술보급에따른감축량을산정하였다 (Ju et al., 2013; Kim et al., 2013a; Shin et al., 2003; Yagi and Minami, 1990). 2. 자료및방법 2.1 활동자료전망농업부문온실가스배출량전망을위해서는작물재배면적및생산량, 화학비료생산량, 가축사육두수등의활동자료가필요하다. 이를위해 2023년까지의활동자료는한국농촌경제연구원 (Korea Rural Economic Institute, KREI) 에서개발한장기전망활동자료모형인 KASMO(Korea Agricultural Simula tion Model) 를활용하였고, 2023년부터 2030년까지는로그함수를이용하여추정하였다. 활동자료전망을위한전제조건으로는인구, GDP, 소비자물가, 생산자물가, 환율, 국제원유가등의거시경제변수를적용하였고, 농산물시장개방과관련하여한 EU FTA, 한 미 FTA, 한 호주 FTA 등의결과가반영되었다. KASMO 모형은거시경제부문, 투입제가격부문, 재배업부문, 축산부문, 농가인구부문, 농업총량부문의 6개부문으로상호연계되어있다. Fig. 1은 KASMO 모형의구조를나타낸다 (Kim et al., 2013c). KASMO 모형에의해전망된활동자료는 Table 1, 2, 3과같다. 벼, 보리, 밀재배면적은 2021 년이후 2030 년까지지속적으로감소할것으로전망되었다 (Table 1). 작물생산량의경우, 벼, 보리, 옥수수의생산량은지속적으로감소하는추세를보이는반면, 밀의생산량은증가할것으로전망되었다. 두류생산량은 2030년까지다소감소할것으로전망되었고, 양파생산량은증가할것으로전망되었다 (Table 2). 화학비료 ( 질소 ) 투입량은 2015년 291천톤에서 2030년에는 253천톤으로감소할것으로전망되었다. 가축사육두수의경우, 한 육우는 2025 년까지증가하다 2030년까지는감소할것으로전망되었고, 젖소는 2030년까지지속적으로감소할것으로전망되었다. 돼지, p Fig. 1. Structure of KASMO (Korea Agricultural Simulation Model) (Source : Kim et al., 2013c). Journal of Climate Change Research 2015, Vol. 6, No. 3
2020 년이후농업부문온실가스배출량전망과감축잠재량분석 235 Table 1. Projection of cultivation area for GHGs emission estimation in agricultural sector from 2021 to 2030 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 ha Rice 759,527 754,665 749,913 737,554 736,254 734,954 733,654 732,354 731,054 728,825 Barely + wheat 21,870 21,820 21,796 21,783 21,723 21,663 21,727 21,739 21,459 21,350 Table 2. Projection of crops production for GHGs emission estimation in agricultural sector from 2021 to 2030 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 ton Rice 3,809,948 3,785,597 3,761,791 3,699,886 3,695,345 3,675,248 3,656,132 3,637,905 3,620,489 3,603,814 Barely 36,674 36,117 35,638 35,180 34,830 34,535 33,698 32,918 32,189 31,504 Wheat 31,834 32,792 33,744 34,706 34,611 34,904 35,671 36,438 37,204 37,971 Potato 550,465 547,551 544,463 541,285 539,090 535,511 532,198 529,113 526,228 523,517 Sweet potato 351,346 355,072 359,004 362,977 366,551 367,933 369,204 370,381 371,477 372,501 Corn 68,330 66,981 65,546 63,994 61,465 60,978 60,526 60,106 59,713 59,343 Red pepper 276,013 274,588 273,055 271,502 267,946 266,410 264,949 263,556 262,224 260,949 Galic 316,547 316,075 315,659 315,293 312,608 311,835 311,099 310,395 309,721 309,075 Sesame 11,541 11,602 11,663 11,724 11,779 11,831 11,879 11,924 11,967 12,008 Onions 1,487,589 1,503,589 1,521,899 1,542,286 1,542,903 1,546,741 1,550,331 1,553,703 1,556,883 1,559,890 Soybean 121,646 119,928 117,926 115,774 113,814 112,253 110,808 109,462 108,204 107,022 닭, 말의경우는지속적으로증가하고, 산양, 사슴등은크게 감소할것으로전망되었다 (Table 3). CH 4 = Σ(EF i t A 10 6 ) EF i = EF C SF W SF O (kg CH 4 ha 1 day 1 ) (1) 2.2 온실가스배출량전망방법론온실가스배출량은 IPCC 가이드라인 (IPCC, 1996, 2000, 2003, 2006) 과 2014 국가온실가스통계산정 보고 검증지침 ( 환경부온실가스종합정보센터, 2014) 에따라벼재배에의한 CH 4 배출, 농경지토양에서의 N 2 O 배출및작물잔사를소각하는과정에서의 CH 4, N 2 O 배출로구분하여전망하였다. 벼재배에의한 CH 4 배출량은상시담수, 유기물무시용조건의기본배출계수 (EF C ) 에물관리방법별보정계수 (SF W ), 유기물시용량별보정계수 (SF O ) 를곱하고, 일배출계수 (EF i ) 를산출하며, 재배일수 (t) 138일과벼재배면적 (A) 전망자료를곱하여산정하였다. 벼재배에의한 CH 4 배출량산정방법은식 (1) 과같다. CH 4 Emission EF i : A daily emission factor(kg CH 4 ha 1 day 1 ) EF C : Baseline emission factor for continuously flooded fields without organic amendments SF W : Scaling factor to account for the differences in water regime during the cultivation period SF O : Scaling factor should vary for both types and amount of organic amendment applied A : Cultivation area(ha yr 1 ) t : Cultivation days 농경지토양에서의질소투입에따른 N 2 O 배출량전망은식 (2) 와같다. 농경지토양에서의 N 2 O 배출은질소투입원 ( 화학비료, 가축분뇨, 두과작물에의한질소고정, 잔물잔사환원 ) 에따라구분하고, 배출량은직접배출 (N 2 O DIRECT emission) 과 http://www.ekscc.re.kr
236 정현철 이종식 최은정 김건엽 서상욱 정학균 김창길 Table 3. Projection of livestock heads for GHGs emission in agricultural sector from 2021 to 2030 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 head Dairy cattle 401,901 396,798 391,521 386,055 377,002 375,192 373,539 372,019 370,612 369,302 Non-dairy cattle 2,658,528 2,687,241 2,716,277 2,745,500 2,735,500 2,725,500 2,715,500 2,705,500 2,695,500 2,685,500 Sheep 4,857 4,927 4,993 5,055 5,115 5,171 5,225 5,276 5,325 5,372 Goats 223,388 219,301 215,362 211,562 207,890 204,339 200,901 197,568 194,335 191,196 Horses 33,453 33,878 34,286 34,677 35,053 35,415 35,763 36,099 36,424 36,738 Swine 10,127,983 10,171,707 10,219,477 10,270,997 10,274,573 10,284,121 10,292,838 10,300,857 10,308,281 10,315,192 Chicken 165,140,975 165,613,349 166,188,967 166,861,923 166,970,219 167,572,397 168,148,365 168,941,969 169,700,289 170,426,331 Ducks 18,118,865 18,687,707 19,224,070 19,742,877 19,768,627 19,794,377 19,820,127 19,845,451 20,100,427 20,337,804 Deer 37,782 37,282 36,782 36,282 35,782 35,282 34,782 34,282 33,782 33,282 간접배출 (N 2 O INDIRECT emission) 로구분하여산정하였다. N 2 O Emission N 2 O DIRECT = (F SN F AW F BN F CR ) EF 1 44/28 (2) F SN : Annual amount of synthetic fertilizer nitrogen applied to soils adjusted to account for the amount that volatilises as NH 3 and NOx (kg N yr 1 ) F AW : Manure nitrogen used as fertilizer in country, corrected for NH 3 and NOx emission (kg N yr 1 ) F BN : N fixed by N-fixing crops in country (kg N yr 1 ) F CR : N in crop residues returned to soils in country (kg N yr 1 ) EF 1 : Emission factor for emission from N inputs (kg N 2 O- N kg 1 N input) 44/28 : Conversion factor to convert N 2 O-N into N 2 O N 2 O INDIRECT = N 2 O (G) N 2 O (L) N 2 O (G) = (N FERT Frac GASF + N EX Frac GASM ) EF 4 44/28 N 2 O (L) = [(N FERT + N EX ) Frac LEACH )] EF 5 44/28 N FERT : Fertilizer nitrogen use in country (kg N yr 1 ) N EX : Livestock nitrogen excretion in country (kg N yr 1 ) Frac GASF : Fraction of synthetic fertilizer nitrogen applied to soils that volatilises as NH 3 and NOx emission Frac GASM : Fraction of livestock nitrogen excretion that volatilises as NH 3 and NOx emission Frac LEACH : Fraction of nitrogen input to soils that is lost through leaching and runoff (kg N 2 O-N kg 1 N) EF 4 (N deposition) = Emission factor for atmospheric deposition (kg N 2 O-N kg 1 N) EF 5 (leaching/runoff) = Emission factor for leaching/runoff (kg N 2 O-N kg 1 N) 작물잔사소각에의한 CH 4 및 N 2 O 배출량산정은작물별생산량전망에잔사 / 곡실비율, 건물율, 소각률, 산화율, 질소및탄소함량, 가스배출률을곱하여산정하였다. 2.3 배출계수및보정계수 Table 4는배출량전망시적용한배출계수와보정계수를나타낸다. 배출계수와보정계수는국내에서개발한국가고유배출 / 보정계수와 IPCC 가이드라인의기본계수를혼용하여 Tier 1 2 수준으로하였다. 벼재배에의한 CH 4 배출량산정시기본배출계수 (EFc) 는국가고유배출계수 2.32 kg ha 1 day 1 를적용하였고 (Kim et al., 2013), 유기물보정계수 (EF O ) 는 2.5, 물관리보정계수 (EF W ) 는 0.66을적용하였다. 농경지토양에서화학비료시용량에따른 N 2 O 직접배출계수는밭의경우국가고유배출계수인 0.00596 kg N 2 O-N kg 1 N을적용하였고, 논의경우 2006 IPCC 가이드라인의기본배출계수 0.003 kg N 2 O-N kg 1 N을적용하였다. 가축분뇨시용량에따른 N 2 O 직접배출계수는 1996 IPCC 가이드라인의기본배출계수인 0.0125kg N 2 O-N kg 1 N을적용하였다. 농경지토양에서의 N 2 O 간 Journal of Climate Change Research 2015, Vol. 6, No. 3
2020 년이후농업부문온실가스배출량전망과감축잠재량분석 237 Table 4. Emission factors and scaling factors for estimation of GHGs emission Emission sources Rice cultivation (CH 4 ) Agricultural soils (N 2 O) Emission/ scaling factors Unit EF C kg 1 ha 1 day 1 2.32 SF W - 2.50 SF O - 0.66 EF 1 (Country specific) Developed kg N 2 O-N kg 1 N 0.00596 EF 1 (Default) kg N 2 O-N kg 1 N 0.0125 EF 1FR kg N 2 O-N kg 1 N 0.003 EF 4 kg N 2 O-N kg 1 N 0.01 EF 5 kg N 2 O-N kg 1 N 0.025 접배출계수는대기휘산의경우 0.01 kg N 2 O-N kg 1 N 을적 용하였고, 수계유출의경우 0.025 kg N 2 O-N kg 1 N 을적용하 였다 (Table 3). 리방법과유기물시용에따른 CH 4 배출량으로구분하여전망한결과, 작기중상시담수를하고유기물을시용한처리에서가장높았고, 중간낙수를하고유기물을시용하지않은처리에서가장낮았다. 이번배출량전망에서는물관리비율이나유기물시용비율은 2021년부터 2030년까지동일하게적용하여전체배출량변화에는영향을미치지않았다 (Fig. 2a). 벼재배에의한 CH 4 총배출량은 2021년 6,271천톤 CO 2-eq. 에서 2025년 6,122천톤 CO 2-eq., 2030년 6,051천톤 CO 2-eq. 으로감소할것으로전망되었다. 이는 2021년대비 3.5%, 2025년대비 1.2% 감소한양으로감소폭은 2030년으로갈수록다소작아질것으로전망되었다 (Fig. 2b). 이러한배출량감소의직접적인원인은벼재배면적의지속적인감소때문이며, 향후물관리방법이나유기물시용면적비율의전망이가능하다면좀더정확한전망이가능할것으로생각된다. Fig. 3은 2021년부터 2030년까지농경지토양에서의 N 2 O 배출량을직접배출과간접배출로구분하여전망한결과이다. N 2 O 직접배출량을질소투입원별로전망한결과, 가축분뇨에 2.4 감축기술적용 온실가스감축잠재량전망을위해두가지온실가스감축기술을적용하였다. 첫번째감축기술은벼재배논에서작기중중간물떼기를통한온실가스감축이다. 이방법은벼재배논에서 CH 4 배출을줄일수있는가장효과적인방법으로상시담수대비약 34% 의온실가스감축효과가있다. 중간물떼기는 2011 년우리나라전체논면적의 85.6% 를차지하고있고, 2020년까지 90% 의면적까지확대할계획이다. INDCs 온실가스목표달성을위해 2030년까지적용면적을 92.5%, 95%, 97.5% 로하여감축잠재량을분석했다. 두번째감축기술은벼재배논에서이앙후초기담수와논물얕게대기를통한온실가스감축기술이다. 이기술은상시담수대비약 55%, 간단관개대비약 40% 의온실가스를감축할수있다 (Kim, 2013b). 가장최근에개발된기술로유기물을무시용한간단관개논면적의 10% 를 2030년까지적용할경우의감축잠재량을분석했다. (a) The projection of CH 4 emission according to mid-season water management and organic matter treatment 3. 결과및고찰 3.1 농경지부문온실가스배출량전망 2021 년부터 2030 년까지벼재배에의한 CH 4 배출량전망 결과는 Fig. 2 와같다. 배출량에영향을미치는작기중물관 (b) The projection of total CH 4 emission Fig. 2. The projected CH 4 emission in paddy fields from 2021 to 2030. http://www.ekscc.re.kr
238 정현철 이종식 최은정 김건엽 서상욱 정학균 김창길 (a) The projected N 2 O direct emissions (b) The projected N 2 O indirect emissions (c) The projected N 2 O total emission Fig. 3. The N 2 O emission projection by N-input in agricultural soils from 2021 to 2030. 속적으로감소할것으로전망되었고, 감소폭은대기휘산보다수계유출에의한배출이좀더큰것으로분석됐다. 이는질소투입원의 30% 가수계로유출되기때문이며, 대기휘산의경우화학비료는투입량의 10%, 가축분뇨는투입량의 20% 가대기로휘산되기때문인것으로분석되었다 (Fig. 3b). 직접배출과간접배출을합한농경지 N 2 O 총배출량은 2021년이후 2030년까지지속적으로감소하는것으로전망되었고, 가축분뇨에의한직접배출이증가하는 2025년까지는감소폭이다소적을것으로전망되었다 (Fig. 3c). 작물을수확하고난후남은잔사를농경지에서소각할때발생하는 CH 4 및 N 2 O 배출량전망은 Fig. 4와같다. 농업부문온실가스배출량중작물잔사소각에의한온실가스배출량이차지하는비중은 1% 내외로, 전체배출량에는큰영향을미치지않는다. 2030년까지작물잔사소각에의한온실가스배출량은조금씩감소하는것으로전망되었는데, 이는농경지에서소각하는작물인옥수수, 고추, 양파, 참깨와같은작물의재배면적및생산량이감소했기때문인것으로분석됐다. 작물생산량이증가한고구마등의작물은잔사를소각하지않기때문에생산량증가가잔사소각시발생하는온실가스배출량에영향을미치지는않았다 (Fig. 4). 작물잔사의소각비율은 2030년까지 2014년조사자료를일괄적용했기때문에향후작물별잔사소각률전망이가능하다면좀더정확한배출량전망이가능할것으로생각된다. Fig. 5는 2021년부터 2030년까지경종분야온실가스총배출량전망을나타낸다. 벼재배, 농경지토양및작물잔사소각과정에서의온실가스총배출량은 2021년이후작물재배면적및생산량, 화학비료생산량, 가축사육두수감소에따라지속적으로감소할것으로전망되었다. 일부가축사육두수증가에따른가축분뇨투입량증가는 N 2 O 배출량증가에약간의영향을미쳤으나, 총배출량변화에는큰영향을미치지않을것 의한배출량이가장많았고, 질소고정작물에의한배출량이가장적었다. 가축분뇨에의한 N 2 O 배출량은 2025 년까지다소증가하다가이후로는감소할것으로전망되었는데, 이는일부가축을제외한양, 말, 돼지, 닭, 오리등의사육두수가증가했기때문인것으로분석되었다. 화학비료에의한 N 2 O 배출량은작물재배면적감소와그에따른화학비료생산량감소로배출량또한지속적으로감소할것으로전망되었다. 질소고정작물에의한 N 2 O 배출량과작물잔사환원에의한 N 2 O 배출량은총배출량에 3% 이하로전체배출량에는큰영향을미치지않을것으로전망되었다 (Fig. 3a). 대기휘산과수계유출에의한 N 2 O 간접배출량또한 2021년이후 2030년까지지 Fig. 4. The projection of CH 4 and N 2 O emissions by field burning of crop residues. Journal of Climate Change Research 2015, Vol. 6, No. 3
2020 년이후농업부문온실가스배출량전망과감축잠재량분석 239 Fig. 5. The projeion of total GHGs emission in the agricultural sector from 2021 to 2030. (a) Comparison of GHGs emission between BAU and mid-season drainage 으로분석됐다 (Fig. 5). 3.2 경종부문온실가스감축잠재량전망 이번연구에서온실가스감축잠재량을분석하기위해적용한기술은벼재배과정에서중간물떼기방법을통한온실가스감축기술이다. 작기중중간물떼기 CH 4 감축기술은가장널리적용되는방법으로 2011 년통계조사결과, 우리나라는이미 85.6% 의면적에서중간낙수를시행하고있고, 2015년부터 2020년온실가스감축목표달성을위해 90% 까지확대하기로결정한바있다. 이러한기술을 2030년까지확대적용하여확대비율을 93%, 95%, 97% 로설정하여 BAU 대비감축잠재량을분석하였다 (Fig. 6a). 감축잠재량분석결과, 중간물떼기비율을 93% 까지확대할경우 BAU 대비 3.3%(202 천톤 CO 2-eq. ), 95% 까지확대할경우 4.2%(253 천톤 CO 2-eq. ), 97% 까지확대할경우 5.0%(305 천톤 CO 2-eq. ) 까지온실가스감축이가능할것으로전망되었다 (Fig. 6b). 우리나라벼재배논에서의관개시설과농업여건을고려할때 95% 까지는확대가가능할것으로기대된다. 두번째적용한온실가스감축기술은벼재배논에서논물얕게대기방법이다. Fig. 7은논물얕게대기방법을 2021년 1% 확대를시작으로 2030년까지상시담수, 유기물무시용논면적에 10% 까지적용했을때의온실가스배출량및감축잠재량변화를나타낸다 (Fig. 7a). 논물얕게대기감축기술은상시담수와유기물시용하지않은논에서의연구결과로우리나라논면적중여기에해당하는면적은 2021 년은 309천 ha, 2030년은 298천 ha가될것으로전망됐다. 논물얕게대기감축기술을 2021 년부터적용가능면적에 1% 씩확대적용하여 2030 년에는 10% 까지적용할경우, 온실가스감축잠재량은 2030년까지약 92천톤 CO 2-eq. 의온실가스를감축할수있을것으로전망되었다 (Fig. 7b). 4. 결론 (b) The GHGs mitigation potential according to mid-drainage extension rate during rice cultivation Fig. 6. The GHGs emission projection and mitigation potential apply to mid-drainage in paddy fields from 2021 to 2030. (a) Comparison of GHGs emission projection between BAU and intermittently drainage (b) The GHGs mitigation potential by intermittently drainage Fig. 7. The GHGs emission projection apply to intermittently drainage in paddy fields from 2021 to 2030. http://www.ekscc.re.kr
240 정현철 이종식 최은정 김건엽 서상욱 정학균 김창길 감축목표달성을위한감축잠재량분석을위해 2021년부터 2030년까지우리나라농경지부문온실가스배출량을전망하고, 농업여건을고려한적용가능감축기술을선정하여감축잠재량을분석했다. 이번배출량전망과감축잠재량평가는작물재배면적및생산량, 화학비료생산량, 가축사육두수의전망자료를근거로평가하였다. 경종부문에서의온실가스배출량은 2021년부터 2030 년까지지속적으로감소할것으로전망되었고, 감소폭은다소작아질것으로전망되었다. 배출량감소의직접적인원인은주요작물의재배면적과생산량감소, 그에따른화학비료생산량감소때문인것으로분석되었다. 일부작물의재배면적과가축사육두수증가에따른농경지 N 2 O 배출량은다소증가하나, 경종부문총배출량에는큰영향을미치지않는것으로분석되었다. 벼재배논에서작기중물관리방법과논물얕게대기방법을통한온실가스감축잠재량을분석한결과, 2030년에중간낙수면적을 95% 까지확대할경우약 253천톤 CO 2-eq. 의온실가스감축이가능할것으로전망되었고, 논물얕게대기방법을상시담수유기물무시용논면적의 10% 까지보급할경우약 92천톤 CO 2-eq. 의온실가스감축이가능할것으로전망되었다. 이번배출량전망은활동자료와국가고유배출계수를일부적용한 Tier 1 2 수준의평가로향후기후변화영향등을반영해불확도를줄이고, 신뢰도높은전망을위해서는 Tier 3 수준의배출량평가가필요할것으로판단된다. 농업부문의경우, 기후변화에가장큰영향을받으면서도국민의식량안보와직결되는만큼온실가스감축기술선정과보급에있어신중한결정이필요하며, 생산성은유지하면서온실가스감축을위한전략수립이무엇보다도중요하다. 사사 본연구는농촌진흥청국립농업과학원농업과학기술연구개발사업 (PJ01003004) 의지원에의해이루어진것임. REFERENCES IPCC. 1996. Revised 1996 IPCC guidelines for national greenhouse gas inventories. IPCC. 2000. Good practice guidance and uncertainty management in national greenhouse gas inventorise. Penman J, Kruger D, Galbally I, Hiraishi T, Nyenzi B, Emmanual S, Buendia L, Hoppaus R, Martinsen T, Meijer J, Miwa K, Tanabe K. (Eds). IPCC/OECD/IEA/IGES. Hayama, Japan. IPCC. 2003. Good practice guidance for land use, land-use change and forestry. Penman J, Gytarsky M, Hiraishi T, Krug T, Kruger D, Pipatti R, Buendia L, Miwa K, Ngara T, Tanabe K, Wagner F. (Eds). IPCC/IGES, Hayama, Japan. IPCC. 2006. 2006 IPCC guidelines for national greenhouse gas inventories. Ju OJ, Won TJ, Cho KR, Choi BR, Seo JS, Park IT, Kim GY. 2013. New estimates of CH 4 emission scaling factors by amount of rice straw applied from Korea paddy fields. Kor J of Environmental Agriculture 32(3):179-184. Kim GY, Lee JS, Jeong HC, Choi EJ, Sonn YK, Kim PJ. 2013a. Effects of water management methods on CH 4 and N 2 O emission from rice paddy field. Kor J Soil Sci Fert 46(6):590-605. Kim GY, Jeong HC, Ju OJ, Kim HK, Park JH, Gwon HS, Kim PJ. 2013b. Establishment of baseline emission factor of methane in Korean rice paddy soil. Kor J of Environmental Agriculture 32(4):359-365. Kim MH, Han SH, Jo JS, Kim TW, Lee CS. 2013c. Prospection model for agricultural sector. KREI 1-77. Korea Carbon Capture & Sequestration R&D Center(KCRC). 2014. Analysis and its implications about 20 th UNFCCC COP 20 Negotiation. Korea Institute for International Economic Policy(KIEP). 2015. Analysis and its implications about LIMA UNFCCC COP. World Economy Update 15(2):1-10. Lee DB, Jung SC, So KH, Kim GY, Jeong HC. 2014. A study on carbon footprint and mitigation for low carbon apple production using life cycle assessment. Journal of Climate Change Research 5(3):189-197. Ministry of Environment. Greenhouse Gas Inventory and Research Center(GIR). 2014. 2014 national greenhouse gas inventory report of Korea. Ministry of Environment. Greenhouse Gas Inventory and Research Center(GIR). 2014, Guideline for MRV(Measurement, Reporting and Verification) of national greenhouse gases statistics. Ministry of Environment. 2014. A study for evaluation management for post-2020 and GHGs mitigation goals. Myeong SJ. 2014. Agriculture under UNFCCC and its policy implications. Journal of Climate Change Research 5(4):313- Journal of Climate Change Research 2015, Vol. 6, No. 3
2020 년이후농업부문온실가스배출량전망과감축잠재량분석 241 321. Shin YK, Kim GY, Ahn JW, Koh MH, Eom KC. 2003. Effect of rice vegetation and water management on turnover of incorporated organic materials to methane in Korean paddy. Soil Kor J Soil Sci Fert 36(1):50-56. UNFCCC (United Nations Framework Conversion on Climate Change). 2014. Lima call for climate action, Decision-/ CP.20. Advance unedited version. http://unfccc.int/focus/ indc_portal/items/8766.php Yagi K, Minami K. 1990. Effect of organic matter application on methane emission from some Japanese paddy fields. Soil Sci Plant Nutr 36:599-610. http://www.ekscc.re.kr