Comparative environmental assessment of three systems for organic pig production in Denmark

Organic pig production has emerged as an alternative to the intensive conventional pig production in Europe with the animals confined indoors and often an imbalance between livestock and land for feed production and manure utilisation. The organic systems aim at improving animal welfare by supporting the pig’s natural behaviour (Hermansen et al., 2003), and improving soil fertility by better linking crop and livestock production from an agro-ecological point of view. The differences between organic and conventional pig production is more fundamental than for example differences between dairy production systems, which may be why the share of pig herds within the organic holdings is considerably lower than the percentage of pig herds in conventional agriculture in both the UK (ADAS, 2001), Germany (Willer, et al., 2002) and Denmark (Plant Directorate, 2004b). However, the recent development has seen a dramatic increase in demand for organic pig meat in Denmark, Germany and the UK and present production cannot meet demand. Besides regulation on use of feedstuffs, the organic pig production has a main challenge in the regulation for housing. The sows need access to grazing in the summer time, and growing pigs need as a minimum requirement access to an outdoor run. In addition, the area requirements for indoor housing are higher than for conventional production. These requirements have a major impact on what systems to consider, both from economical and agro-ecological points of view. And therefore, efforts to improve organic pig production should focus on the integration of livestock production and land use, but considering environmental impacts on local and global scales. The most commonly used system in Denmark is to combine an outdoor sow production all year round with rearing growing pigs in barns with an outdoor run (Hermansen & Jakobsen, 2004). The type of stable most commonly used by full time producers in Denmark is a system with deep litter in the entire indoor area or deep litter/straw bed in half the area while the outdoor area consists of a concrete area. The use of a concrete covered area, from which the manure can be collected, is a way to comply with the environmental regulations stating that the outdoor run should be constructed in a way that prevents leaching. Research shows that very good production results can be obtained in such systems in terms of litter size, daily gain, feed consumption and health (Hermansen et al., 2003). However, two possible drawbacks exist. First, the space requirement per growing pig in housing facilities is considerable and, thus, capital demanding. For fattening pigs of 85-100 kg live weight, the indoor space required is equivalent to 1.3 m2/pig (of which at least 0.65 m2 must consists of a solid floor) and 1.0 m2 outdoors run (Council Regulation, 1999). In addition, each lying zone, i.e. straw bedding area, must be able to accommodate all pigs at a time. This put a heavy burden on costs of buildings (money and resource use) and at the same time it can be questioned if such rearing systems comply with the consumer expectations. Second, the outdoor sow production has been connected with high environmental burden in the form of N losses (Larsen et al., 2000; Eriksen et al., 2002). This made us to consider two alternatives to the organic pic system most often used presently. A system where all pigs were reared outdoors on grassland (and saving buildings) and a system where sows and growing pigs were kept in a tent system placed upon a deep litter area in order to reduce risk for N leaching. Both have been used under commercial conditions. In order to assess the possible trade-offs between environmental impacts on the one hand and the assumed advantages of these alternative systems (animal welfare, low investment) on the other hand an Environmental Impact Assessment was needed. Environmental assessment of livestock farming systems can be done on an area basis (e.g. nutrient losses per ha) or on a product basis (e.g. Green House Gas emission per kg meat or milk; Haas et al., 2001; van der Werf & Petit, 2002; De Boer, 2003; Halberg et al., 2005). The area based assessment is relevant for locally important emissions such as nitrate leaching but a product based assessment is more relevant for emissions, which have a less localised impact (acidification) or even a global character (Green House Gasses). Moreover, since the organic production is often considered a more sustainable alternative to conventional intensive pig production, from a consumer point of view it might be interesting to compare the eutrophication per kg meat produced from different organic and compared to conventional systems. The objective of this paper is to compare the environmental impact and green house gas emission of organic pig production systems with different levels of integration of livestock and land use

Life cycle modelling of environmental impacts of application of processed organic municipal solid waste on agricultural land (EASEWASTE)

A model capable of quantifying the potential environmental impacts of agricultural application of composted or anaerobically digested source-separated organic municipal solid waste (MSW) is presented. In addition to the direct impacts, the model accounts for savings by avoiding the production and use of commercial fertilizers. The model is part of a larger model, Environmental Assessment of Solid Waste Systems and Technology (EASEWASTE), developed as a decisionsupport model, focusing on assessment of alternative waste management options. The environmental impacts of the land application of processed organic waste are quantified by emission coefficients referring to the composition of the processed waste and related to specific crop rotation as well as soil type. The model contains several default parameters based on literature data, field experiments and modelling by the agro-ecosystem model, Daisy. All data can be modified by the user allowing application of the model to other situations. A case study including four scenarios was performed to illustrate the use of the model. One tonne of nitrogen in composted and anaerobically digested MSW was applied as fertilizer to loamy and sandy soil at a plant farm in western Denmark. Application of the processed organic waste mainly affected the environmental impact categories global warming (0.4–0.7 PE), acidification (–0.06 (saving)–1.6 PE), nutrient enrichment (–1.0 (saving)–3.1 PE), and toxicity. The main contributors to these categories were nitrous oxide formation (global warming), ammonia volatilization (acidification and nutrient enrichment), nitrate losses (nutrient enrichment and groundwater contamination), and heavy metal input to soil (toxicity potentials). The local agricultural conditions as well as the composition of the processed MSW showed large influence on the environmental impacts. A range of benefits, mainly related to improved soil quality from long-term application of the processed organic waste, could not be generally quantified with respect to the chosen life cycle assessment impact categories and were therefore not included in the model. These effects should be considered in conjunction with the results of the life cycle assessment

Impact of organic pig production systems on CO2 emission, C sequestration and nitrate pollution

Organic rules for grazing and access to outdoor area in pig production may be met in different ways, which express compromises between considerations for animal welfare, feed self-reliance and negative environmental impact such as greeehouse gas emissions and nitrate pollution. This article compares environmental impact of the main organic pig systems in Denmark. Normally sows are kept in huts on grassland and finishing pigs are being raised in stables with access to an outdoor run. One alternative practised is rearing also the fattening pigs on grassland all year round. The third method investigated was a one-unit pen system mainly consisting of a deep litter area under a climate tent and with restricted access to a grazing area. Using life cycle assessment (LCA) methodology, the emissions of greenhouse gasses of the all free range system was estimated to be 3.3 kg CO2-equivalents kg-1 liveweight pig, which was significantly higher than the indoor fattening system and the tent system yeilding 2.9 and 2.8 kg CO2-eq. kg-1 pig respectively. This was 7-22% higher compared with Danish conventional pig production but, due to the integration of grass-clover in the organic crop rotations these had an estimated net soil carbon sequestration. When carbon sequestration was included in the LCA then the organic systems had lower green house gas emissions compared with the conventional pig production. Eutrophication in nitrate equivalents per kg pig was 21-65% higher in the organic pig systems and acidification was 35-45% higher per kg organic pig compared with the conventional system. We conclude that even though the all free range system theoretically has agro-ecological advantages over the indoor fattening system and the tent system due to a larger grass-clover area this potential is difficult to implement in practice due to problems with leaching on sandy soil. Only if forage can contribute a larger proportion of the pigfeed-uptake may the free range system be economically and environmentally competitive. Improvement of nitrogen cycling and efficiency is the most important factor for reducing the overall environmental load from organic pig meat. Presently a system with pig fattening in stables and concrete covered outdoor runs seems to be the best solution from an environmental point of view

Life Cycle Assessment of Biofuels in Sweden

The purpose of this study is to carry out updated and developed life cycle assessments of biofuels produced and used in Sweden today. The focuses are on making the assessments as relevant and transparent as possible and to identify hot spots which have significant impacts on the environmental performance of the specific biofuel production chains. The study includes sensitivity analyses showing the impact on changed future conditions. The results should be seen as current and average environmental performance based on updated calculation methods. Thus individual systems developed by specific companies may have somewhat different performances. The biofuels analysed are ethanol from wheat, sugar beet and sugar cane (imported from Brazil), RME from rapeseed, biogas from sugar beet, ley crops, maize and organic residues, such as municipal waste, food industry waste and liquid manure. The study also includes co-production of ethanol and biogas from wheat. Final use in both light and heavy duty vehicles, and related emissions, are assessed. Environmental impact categories considered are climate change, eutrophication, acidification, photochemical oxidants, particles and energy balances. The calculations include emissions from technical systems, e.g. energy input in various operations and processes, and biogenic emissions of nitrous oxide and carbon dioxide from direct land use changes (LUC). The potential risk of indirect land use changes (ILUC) is also assessed. By-products are included by three different calculation methods, system expansion, energy allocation and economic allocation. The results are presented per MJ biofuel, but the alternative functional unit per hectare cropland is also used regarding the greenhouse gas performance of crop-based biofuels. Finally, estimations are carried out regarding the current environmental performance of the current various biofuel systems based on system expansion, recommended by the ISO-standardisation of LCA, and energy allocation, utilised in the standardisation of biofuels within the EU’s Renewable Energy Directive (RED)

Nitrogen loss assessment and environmental consequences in the loess soil of China

Attention is focused on fertilizer nitrogen loss and the environmental consequences in Shaanxi Province in loess region of China, including N losses to the atmosphere via ammonia volatilization, nitrification and denitrification, N losses to groundwater by leaching, and crop uptake by roots. Three soils were selected, Entisol, Anthrosol and Luvisol from north, central and south Shaanxi, respectively. Nitrification and NH4+ fixation were measured using a closed chamber method in the laboratory. Denitrification was tested in the laboratory with intact soil cores, C2H2 inhibition techniques. N2O emission was assessed via in situ measurement of N2O in the soil profile and at the soil surface in field experiments. Fertilizer use and crop yields obtained by the farmers were investigated on a large scale in Shaanxi Province. Transformation of fertilizer NH4+ to NO3- was within nine days in the Entisol and Anthrosols, but it took 40 days in Luvisol due to NH4+ fixation by clay minerals. In the pot experiment open to the wind and sunshine with different water content, applied N fertilizer recovery was 74.2% for the Luvisol and 61.3% for the Entisol. The results for the Luvisol showed lower nitrogen recovery as initial soil water content increased. When the fertilizer was incorporated, the recovery was 91.6% at 8% and 68.9% at 28% water content. Recovery increased with increasing soil clay content. Large amount of nitrate was accumulated at 200-400 cm depth in the soil profile and accounted for 362-543, 144-677 and 165-569 kg N ha-1 in terrace and bottom land in north Shaanxi, terrace land in Guanzhong and south Shaanxi, respectively. N2O measurements also showed that N2O spatial variation in the profile could be ranked as, 10 cm < 30 cm < 150 cm < 90 cm < 60 cm. Temporal variation was correlated with rainfall or irrigation. Closed chamber measurements or calculations from profile concentrations resulted in N2O emission of less than 1 kg N2O ha-1 y-1. An investigation showed that soil fertility in the Guanzhong area is high, but yield has not increased with increasing N fertilizer application during the last five years. Over-application of N fertilizer was very common in the Guanzhong area and ranged from 100 to 382 kg N ha-1 for wheat and from 106 to 530 kg N ha-1 for maize. The results of the experiments indicate that the N fertilizer recovery efficiency is about 30% and the consequences of N losses are seriously threatening the environment by leaching to the groundwater and by denitrification to the atmosphere

The effects of nitrogen fertilizer rates in a long-term reduced tillage cropping system on dry matter and nitrogen accumulation in an oil radish (Raphanus sativus L.) cover crop

This study was undertaken to evaluate the effects of long-term N fertilizer application rates on dry matter (DM) production and nitrogen (N) accumulation in an oil radish (Raphanus sativus L.) cover crop. The N fertilizer application was done to the main crop winter wheat (Triticum spp.) before oil radish. The experiment was carried out at the research station (Lönnstorp) at SLU, Alnarp in a long-term experiment with (conventional and reduced tillage systems) different N fertilizer application rates in a crop rotation including cover crops. The autumn cover crop DM production and N accumulation were significantly increased with the increased amount of N fertilizer applications to the main crop. According to the hypothesis, the observations of DM production and N accumulation were expected to be in a linear trend with the N levels but they were highly significant with the N levels without any linear increasing tendency. A socio-economic evaluation of cover crops was estimated by comparing the establishment costs of cover crop and the economic value of N conserved in the cover crop, assuming its value to be similar to the value of synthetic N fertilizer. The results showed that the cost of establishing oil radish as cover crop was not completely compensated by the economic value of N conserved in the system. However, several other beneficial aspects of cover crops are discussed to have positive effects in agrosystems, but their economic valuations are complex. Incorporation of cover crop in cropping system has shown to improve biodiversity, suppress of pests and weeds, reduce soil erosion, improve soil organic matter (SOM) and soil texture and structure. Finally, considering the beneficial environmental aspects of cover crops, introducing more subsidies from national and international levels will increase the interest of farmers to grow more cover crops to improve sustainability of cropping system

Investigation Of Agricultural Damages Caused By Air Pollution Over Europe By Using Wrf/cmaq Modelling System

Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, Yüksek LisansM.Sc. (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, YAŞAR BURAK ÖZTANERThe population of Europe, including non-EU countries located in continental Europe, is estimated to be around 740 million, which corresponds to 10% of the world's population (United Nations-UN, 2015). Wheat production in between 1996-2014 in Europe is 133.9 million tons (Mt). This corresponds to 21% of world's wheat production (FAO, 2015). In addition, because of Industrial Revolution in Europe an increasing trend in air pollution and pollutants that persists up to present day can be observed. This increase in air pollution is the cause of critical environmental impacts. Even though there are various studies in Europe about impacts of ozone on human health, not many studies exist to investigate ozone's impact on agriculture. Besides the negative impact on human health, exposure to high concentrations of ozone is a threat to food security and agricultural activities. Elevated O3 concentrations and changes in the concentrations affect plant life functions such as photosynthesis, transpiration, and gas exchanges. It has been found by many scientific studies that ground-level ozone exposure reduces photosynthesis of crops since it damages substomatals apoplast, cell membranes and walls. Decreased photosynthesis result in low growth rates in terms of volume or biomass. In Europe and United States of America (USA), various observational and experimental studies conducted on this subject. These studies resulted in different empirical ozone exposure equations for different parts of the world. Agricultural production losses can be calculated because of these equations. In Europe, AOT40 (cumulative summation of differences in high ozone concentrations over 40 ppb) is a widely used method which is a product of experimental studies conducted in Europe. However, in USA, W126 method (summation of weighted ozone concentrations in day light time by using sigmoidal distribution equation) is being widely used. Other than these two methods there are many other methods used around the world to calculate agricultural production loss due to ozone impacts. Some of these methods are daily summation of difference of threshold values (SUM-X method) or daily mean calculation (M-X method). There are several studies from different parts of the world that were conducted on the impacts of ozone on agricultural crops (i.e., wheat, soybean, rice, potato), their yield losses, and relative yield losses. In a study by USEPA, a 10% crop loss due to ozone was observed in agricultural production in USA. A similar study for the Europe found that the loss was around 5% in Europe. Tropospheric ozone as a regional and global threat to plants threatens our current and future food security. In literature, there are studies conducted on impacts of ozone on agricultural productions for different regions in the world. Even though these studies can show the local loss, they fail to perform well for regional impacts. For this reason, some scientific studies focused on quantifying the impact of ozone pollution on crops using regional or global atmospheric models. Low spatial resolution of global models affects the level of representation of results. Spatial resolution is better in regional studies compared to global ones, however, there are studies utilizing this higher resolution to calculate agricultural production losses. In a study, in India, conducted on impacts of ozone on wheat production loss using WRF/Chem regional chemical transportation model it was found that wheat production loss was 5 Mt for 2005. In a similar study, Eta-CMAQ regional chemical transport model was used to estimate the soybean loss in USA (2005), and found that amount of loss was in range of 1.7-14.2 %. Due to regional changes in ozone concentrations, working with a regional chemistry model yields better results for the calculation of agricultural production loss. In global models, there are many uncertainties due to low resolutions. In this study, WRF/CMAQ modeling system with three different ozone crop exposure indices (AOT40, W126, and M7) was used to estimate wheat production loss in Europe. Growing season was selected as May – July for wheat in Europe. European Environmental Agency (EEA) AirBase database ozone observations were used to calculate mean ozone values for growing season of years 2008 to 2012. The highest growing season average (45.6 ppb) was found in 2009. Averages for other years are as follows, 33.28 ppb for 2008, 29.29 ppb for 2010, 39.12 ppb for 2011, and 30.42 for 2012. This is the reason behind the selected study period growing season (May-July) of 2009. Country based total wheat production data for 2009 were obtained from Food and Agriculture Organizations (FAO). Spatial distribution of country based total wheat production data was performed by using gridded global wheat production map (for year 2000) from studies of Monfreda et al. (2008) and Ramankutty et al. (2008). For each grid cell countries contain a total value was found. These totals then divided by number of grid cells countries contain and grid cell ratios were calculated. These ratios were multiplied with total wheat production data of FAO 2009 and spatially distributed. This created map then remapped according to model area and resolution. In this study, modeling method is WRF / CMAQ modeling system with 30 km spatial resolution. As Meso-scale Atmosphere Circulation Model, WRF-ARW 3.6 (Weather Research and Forecast-Advanced Research WRF) was used with 35 horizontal levels, and with 191 cells in east-west and 159 cells in north-south direction. Also, 0.75 degree ECWMF Era-Interim Reanalysis data was used to prepare initial and boundary conditions of the model. For land-use, MODIS-30 20-class data was prepared. DUMANv2.0 emission model (developed by Istanbul Technical University, Eurasia Institute of Earth Science) was used for emission modeling. Inputs of emission model were anthropogenic, biogenic, and fire emissions. Anthropogenic emissions are created from TNO-2009 database by using DUMANv2.0 with CB05-AERO5 chemical mechanism. MEGAN v2.10 biogenic emission model was used for biogenic emissions. Fire emissions were calculated by data obtained from GFASv1.0 satellite dataset. CMAQv4.7.1 model with CB05-AERO5 chemical mechanism was used for chemical transportation modeling. WRF outputs were converted into M3MODEL structure by using MCIP (Meteorology-Chemistry Interface Processor). ICON (Initial Cond.) and BCON (Boundary Cond.) were used to create initial and boundary conditions. Inputs for these modules were obtained from ECMWF – MACC 3-hour model output with spatial resolution of 80-100 km. Open sky photolysis data were prepared with JPROC (Photolysis Rate Processor). Ozone variable was obtained from CMAQv4.7.1 model and applied to three ozone exposure indices. Gridded map of wheat production map of 2009 were multiplied with these values, thus calculated the wheat loss in each cell. Total economic loss was calculated by multiplication of calculated production loss and FAO 2009 country based wheat production price index. In order to calculate economic loss between countries, each country's 2009 GDP was normalized. The highest wheat loss was found in Russia (7.14 Mt - 11.6% and 17.3 Mt – 28%) by AOT40 and M7 methods while W126 method found the highest loss in Italy (1.54 Mt-24%). Following countries generally have higher wheat loss in every method, Turkey (6.8 Mt), France (3.47 Mt), Germany (2.45 Mt), and Egypt (5.54 Mt). According to the regional results the highest loss was found in South (8.3 Mt – 61%) and East (12.8 Mt – 37%) Europe, the lowest loss was found in Northern European countries (2.2%- 0.65Mt). Greatest losses were found in M7 method while W126 method has the lowest loss values. This provides a range (min-max) for ozone caused wheat loss in Europe. The highest economic loss was in Russia with 2.23 billion American Dollar (USD). Turkey ($2.24 bn), Italy ($1.64 bn), and Egypt ($1.59 bn) were other countries with high economic loss, right after Russia. Eastern Europe has the highest regional economic losses with ($1.6 bn) USD and Southern Europe ($2.8 bn). The lowest economic loss was in Northern Europe ($0.01 bn). Reason behind the high wheat loss values in Southern and Eastern Europe region is due to ozone precursor transport from Middle – Western European region via southerly – easterly meteorological systems. This causes higher ozone concentrations in Southern and Eastern Europe and affect wheat loss. Emission regulations should be more focused and applied in Middle – Western European countries.Avrupa nüfusu – Avrupa Birliği üyesi olmayana ama kıtasal Avrupa'da yer alan ülkelerle birlikte – 740 milyon civarındadır. Bu dünya nüfusunun %10'una denk gelmektedir (United Nations-UN, 2015). Ayrıca, Avrupa'nın 1996 – 2014 yılları arası toplam buğday üretim miktarı ortalaması 133.9 milyon metrik ton olduğu görülmektedir. Dünya buğday üretiminin %21'ne karşılık gelmektedir (FAO,2015). Buna ek olarak, Endüstri Devrimi'nin Avrupa'da gerçekleşmesinin bir sonucu olarak, bölgenin hava kirliliğinde ve kirletici emisyonlarında günümüze kadar bir artış gözlemlenmiştir. Bu artış beraberinde ciddi çevresel etkileri getirmektedir. Avrupa'da insan sağlığı üzerine yapılan çeşitli çalışmalar ile ozon etkisi tespit edilse de,tarım üzerine odaklanmış çok fazla çalışma bulunmamaktadır. Yüksek Ozon konsantrasyonuna maruziyet, insan sağlığına olan zararlı etkilerinin yanı sıra gıda güvenliğine ve tarımsal aktivitelere ciddi etkileri gözlemlenmiştir. Yüksek ozon konsantrasyonu ve ozon konsantrasyonundaki değişimler, fotosentez, terleme ve gaz alışverişi gibi bitki yaşam fonksiyonlarını ciddi şekilde etkilemektedir. Literatürde birçok çalışma, yüksek ozon konsantrasyonundan dolayı bitkilerin alt stoama çeperinin, hücre zarı ve duvarlarının zarar gördüğünü göstermiştir. Bu zarar fotosentez hızını düşürmektedir. Bu durum bitki büyümesi hacim ve kütle olarak azalmasına neden olmaktadır. Avrupa'da ve Amerika Birleşik Devletleri'nde (USA) bir çok farklı deneysel ve gözlemsel çalışmalar yapılmıştır. Bu çalışmalar sayesinde dünyanın farklı bölgelerinde daha iyi çalıştığı düşünülen ampirik ozon maruziyet denklemleri üretilmiştir. Tarımsal üretim kayıpları bu ve bunun gibi denklemler sayesinde hesaplanabilmektedir. Avrupa'da yapılan deneysel çalışmalar neticesinde AOT40 – 40 ppb'den yüksek ozon konsantrasyonlarınının farkının kümülatif toplamları – yöntemi yaygın olarak kullanılmaktadır. USA'da ise W126 yöntemi USEPA tarafından önerilmektedir. W126 yöntemi sigmoidal dağılım fonksiyonunu kullanarak ozon konsantrasyonlarına ağırlık ataması yapıp gün ışığı süresince olan toplamı almaktadır. Bu iki yöntem dışında belirli eşik değerlerinin farkının günlük toplam şeklinde hesaplanması (SUM-X yöntemi) veya günlük ortalama şeklinde hesaplanması (M-X yöntemi) gibi bir çok yöntemde ozondan kaynaklı tarımsal üretim kaybının hesaplanmasında dünya çapında kullanılmaktadır. Dünyanın çeşitli yerlerinde yapılan çalışmalar ozonun buğday, soya fasulyesi, pirinç patates gibi tarım ürünlerinin üretiminde ve veriminde kayıplar olduğu söylemiştir. USEPA tarafından 1996 yılında USA için yapılan bir çalışmada yüksek ozon konsantrasyonuna maruz kalması sebebiyle tarımsal üretimde %10 için kayıp olduğu tespit edilmiştir. Benzer bir çalışma bu kaybın Avrupa %5 civarında olduğu göstermektedir. Küresel ve bölgesel bir problem olarak ozon, bitkiler üzerindeki bu etkisi sebebiyle günümüzdeki ve gelecekteki gıda güvenliğini tehdit etmektedir. Literatürde dünyanın çeşitli bölgelerinde ozonun çeşitli tarım ürünleri üzerindeki etkisini ölçümler ile inceleyen çalışmalar mevcuttur. Bu çalışmalar lokal kaybı gösterse de bölgesel etkiyi göstermekte zayıftır. Bu yüzden bölgesel veya küresel olarak modelleme yöntemi ile üretim kaybı hesaplayan bilimsel çalışmalar literatürde bulunmaktadır. Küresel model yaklaşımı yapılan çalışmaların yersel çözünürlüklerinin düşük olması, elde edilen sonuçların temsiliyetini etkilemektedir. Bölgesel çalışmalarda ise çözünürlük iyi olmasına rağmen, tarım üretim kaybı hesabı hemen hemen hiç bir çalışma da hesaplanmamıştır. WRF/Chem bölgesel kimyasal taşınım modeli ile Hindistan için yapılan bir çalışmada 2005 yılında ozondan kaynaklı buğday üretim kaybı 5 milyon metrik ton olarak hesaplanmıştır. Yine benzer bir çalışmada Eta-CMAQ modeli ile USA'daki soya fasulyesi üretim kaybı 1.7 – 14.2 % olarak hesaplanmıştır. Ozonun bölgesel değişimi sebebiyle bölgesel kimyasal model ile çalışmak hesaplanan tarımsal üretim kaybındaki belirsizliği azalmaktadır. Küresel modellerde yüzeyin tanımlanması, yersel çözünürlüğün düşük olması gibi birden çok belirsizlik söz konusudur. Bu çalışmada WRF/CMAQ model sistemi ile Avrupa'daki Buğday üretim kaybının üç farklı ozon maruziyet denklemi (AOT40, W126 ve M7) kullanılarak belirlenmiştir. Bunu için öncelikle buğday bitkisini büyüme mevsimi (Avrupa için Mayıs – Temmuz ) literatüre göre tespit edilmiştir. Avrupa Çevre Ajansı (Europen Enviromental Agency - EEA) AirBase veri tabanı ozon gözlemleri 2008 -2012 yılları büyüme mevsimleri ortalamaları hesaplanmış ve incelenmiştir. En yüksek buğday büyüme mevsimi ortalaması (45.6 ppb) 2009 yılında bulunmuştur. Bu değer 2008 yılında 33.28 ppb, 2010 yılında 29.29 ppb, 2011 yılında 39.12 ve 2012 yılında 30.42 ppb olarak hesaplanmıştır. Bu yüzden çalışma dönemi olarak 2009 büyüme mevsimi (Mayıs - Temmuz) seçilmiştir. Çalışmada Food and Agriculture Organizations (FAO)'dan seçilen yıl 2009 için ülke bazlı toplam buğday üretim verisi temin edilmiştir. Ülke bazlı toplam buğday üretim verilerinin yersel dağılımı ise Monfreda vd. (2008) ve Ramankutty vd. (2008) çalışmalarında yayınlanan küresel ve gridlenmiş 2000 yılı için buğday üretim haritası kullanılarak yapılmıştır. Bunun için ülkelere düşen her grid hücresinin ülke bazlı toplamı alınmıştır. Hesaplanan toplamlar, grid hücrelerindeki değerlere bölünerek her bir hücrenin oranı belirlenmiştir. Bu oranlar FAO 2009'dan temin edilen toplam buğday üretim verisi ile çarpılarak 2009 yılı FAO buğday üretim verileri yersel olarak dağıtılmıştır. Hazırlanan harita, model alanı ve çözünürlüğüne göre yeniden haritalandırılmıştır. Çalışmada modelleme yöntemi olarak WRF / CMAQ model sistemi 30 km yersel çözünürlükle kurgulanmıştır. Mezo-ölçek Atmosfer Sirkülasyon Modeli olarak WRF-ARW 3.6 (Weather Research and Forecast-Advanced Research WRF) modeli, düşeyde 35 seviye, doğu-batı yönünde 191 ve kuzey-güney yönünde 159 hücre ile çalıştırılmıştır. Ayrıca 0.75 derece ECWMF Era-Interim Reanalysis verisi modelin başlangıç ve sınır koşullarının hazırlanması için kullanılmıştır. Yüzey kullanımı için MODIS-30s 20-Sınıf verisi hazırlanmıştır. Emisyon modellemesi, İTÜ Avrasya Yer Bilimleri Enstitüsü tarafından geliştirilen DUMANv2.0 modeli kullanılarak yapılmıştır. Emisyon modeline insan kaynaklı, biyojenik ve yangın emisyonları girdi olarak verilmiştir. İnsan kaynaklı emisyonlar, TNO-2009 veri tabanından elde edilmiş ve DUMANv2.0 tarafından CB05-AERO5 kimyasal mekanizmasına göre işlenmiştir. Biyojenik emisyonlar için MEGAN v2.10 kullanılmıştır. Yangın emisyonları ise literatürde yer alan ve GFASv1.0 uydu veri setinden elde edilen bilgilerle hesaplanmıştır. Kimyasal Taşınım modeli olarak CMAQv4.7.1 modeli CB05-AERO5 kimyasal mekanizmasına göre çalıştırılmıştır. İlk olarak WRF çıktıları MCIP (Meteorology-Chemistry Interface Processor) kullanılarak M3MODELs yapısına çevrilmiştir. ICON (Initial Cond.) ve BCON (Boundary Cond.) modülleri kimyasal başlangıç ve sınır koşullarını oluşturmak için çalıştırılmıştır. Bu modüllere girdi bilgisi ECMWF – MACC 3 saatlik model (yersel çözünürlüğü 80-100 km) çıktılarından sağlanmıştır. JPROC (Photolysis Rate Processor) ile açık gökyüzü şartlarındaki fotoliz bilgisi hazırlanmıştır. CMAQv4.7.1 modelinden ozon değişkeni temin edilmiş ve belirlenen üç ozon maruziyet denklemlerine uygulanmıştır. Hazırlanan 2009 yılı için gridlenmiş buğday üretim haritası ile çarpılarak her hücredeki buğday kaybı hesaplanmıştır. Bu kayıplar ile FAO'dan 2009 yılı için alınan ülke bazlı buğday üretici fiyat indeksi çarpılarak her bir ülkenin toplam ekonomik kaybı hesaplanmıştır. Ülkeler arası ekonomik kaybı hesaplayabilmek için her ülkenin 2009 yılı için GDP'si ile normalize edilerek yorumlanmıştır. Buna göre, en yüksek buğday kaybı AOT40 ve M7 yöntemleri ile Rusya'da (7.14 Mt - %11.6 ve 17.3 Mt %28), W126 yöntemi ile İtalya'da (1.54 Mt-%24) hesaplanmıştır. Genel olarak kaybın tüm yöntemlerde yüksek görüldüğü diğer ülkeler, Türkiye (6.8 Mt), Fransa (3.47 Mt), Almanya (2.45 Mt) ve Mısır (5.54 Mt)'dır. Bölgesel olarak kayıplar incelendiğinde ise tüm yöntemler içinde en yüksek Güney (8.3 Mt - %61) ve Doğu (12.8 Mt – %37 ) Avrupa'da, en düşük bölge ise kuzey Avrupa ülkeleri (%2.2- 0.65Mt) olduğu belirlenmiştir. En yüksek hesaplanan kayıplar M7 yönteminde, en düşük kayıplar ise W126 yöntemi ile yapılan hesaplamada bulunmuştur. Bu sonuç Avrupa'da ozondan kaynaklı buğday kaybı hakkında bir aralık (minimum - maksimum) sunmaktadır. En yüksek ekonomik kayıp Rusya'da 2.23 Milyar Amerikan Doları (USD) olarak hesaplanmıştır. Turkiye ($2.24 Milyar), Italya ($1.64 Milyar), Mısır ($1.59 Milyar) Rusya'yı takip etmektedir. Hesaplanan ekonomik kayıplara göre, en yüksek kayıplar Doğu ($1.6 Milyar) ve Güney ($2.8 Milyar) Avrupa ülkelerinde, en düşük ekonomik zarar yine Kuzey Avrupa ülkelerinde ($0.01 Milyar) görülmüştür. Güney ve Doğu Avrupa'da bu derece yüksek kayıpların çıkması, Merkez ve Batı Avrupa ülkelerindeki endüstriden kaynaklı ozon öncül kirleticilerin güney ve doğu yönlü meteorolojik sistemlerle taşınmasıdır. Bu sebeple Avrupa'nın güneyinde ve doğusunda ozon yüksektir ve buğday kaybı bundan dolayı daha yüksek hesaplanmıştır. Emisyon kontrolleri Batı ve Merkez Avrupa ülkelerinde daha yoğun şekilde uygulanmalıdır.M.Sc.Yüksek Lisan

Enhancing the Sustainability of Integrated Biofuel Feedstock Production Systems

As use of second-generation biofuel crops increases, so do questions about sustainability, particularly their potential to affect fossil energy consumption and greenhouse gas emissions. Nitrogen (N)-fixing legumes interseeded into switchgrass (Panicum virgatum L.) may be an alternative to inorganic fertilizer in forage-feedstock systems. Research herein is divided into four general experiments: I). N replacement and feedstock impacts from legume intercrops and biochar in switchgrass; II). N-fixation rates in intercrop systems; III). impacts of biofuel systems under enhanced climate change; and, IV). projected sustainability of regional switchgrass production. Approaches included: characterization of feedstock/forage quality traits based on legume, biochar and synthetic-N applications, and harvest timing; quantification of nitrogenease activity in legumes via two techniques (15N [isotopic] enrichment and N-difference); and, determine impacts from regional switchgrass production, N-input sensitivities, and legume-intercropping via life cycle assessment (LCA). Results suggest pigeon pea, sun hemp, red clover, and partridge pea intercrops, and in some instances, biochar may supply analogous-N to that of synthetic fertilizers to Panicum species. Specifically, selected legume fixation may exceed recommended inorganic-N levels (67 kg [kilogram] N ha-1 [hectare]) in both temperate humid and semiarid tropical pasture/feedstock systems. N-difference method may be used to measure biological fixation, as it estimated comparable fixation rates to that of benchmark 15N enrichment values. Furthermore, harvest timing can be manipulated to obtain desired feedstock traits. Specifically, overwintering harvests minimized phosphorus and potassium removal, and maximize ethanol yield, hemicellulose, and in field dry-down [10.84 vs. 24.81% (P≤0.05)]. However, yield losses were observed (22%). Forage yields were generally more responsive to legumes, and legume intercropping may increase switchgrass forage quality (P-1rate. Intercropping selected legumes in switchgrass may enhance forage/feedstock quality and yield while reducing non-renewable inputs and greenhouse gas emissions