Greenhouse gas emissions of small scale ornamental plant production in Austria - A case study

Accepted Manuscript Greenhouse gas emissions of small scale ornamental plant production in Austria - A case study Marie-Theres Wandl, Helmut Haberl PII:

S0959-6526(16)31434-2

DOI:

10.1016/j.jclepro.2016.09.093

Reference:

JCLP 8053

To appear in:

Journal of Cleaner Production

Received Date: 25 May 2016 Revised Date:

8 September 2016

Accepted Date: 13 September 2016

Please cite this article as: Wandl M-T, Haberl H, Greenhouse gas emissions of small scale ornamental plant production in Austria - A case study, Journal of Cleaner Production (2016), doi: 10.1016/ j.jclepro.2016.09.093. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Abstract The aim of this paper is to analyze the greenhouse gas (GHG) emissions from floricultural production in Austria based on a small-scale case study in which emissions were calculated using highly detailed

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accounts of a specific nursery for the years 2009 to 2013. The nursery produces a large assortment of cut flowers and pot plants. In terms of methods, the study is based on a life cycle assessment approach, presenting global warming as impact indicator. To reach a meaningful comparison of cut flowers and pot plants, the functional unit “days of flowering” is developed, referring to the function of ornamental

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plants. This new functional unit enables to a comparison of different kind of products based on their longevity. Including this factor allows a more nuanced comparison of flowers in terms of their GHG emissions. For example, if the widespread functional unit “piece of product” is applied, cyclamen appear

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functional unit “days of flowering” is used.

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to be associated with high emissions, whereas their emissions are slightly below average when the

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1. Introduction Humans have been using ornamental plants since ancient times. Throughout history, and especially within the last decades, the production of ornamental plants has developed into a highly specialized,

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intensive form of agriculture. Increasing use of technologies such as heated glasshouses, artificial fertilizers, assimilation lighting and others lead to growing environmental impact of ornamental plant production (Lazzerini et al., 2014).

The main purpose of ornamental flowers and plants is their decorative function. Thus, there is the need

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for high-quality products that meet the expectations of customers in the market place. To comply with these criteria, ornamental plant production has developed into a very specific form of agricultural

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production. In contrast to other forms of agriculture, e.g. arable farming, the production of flowers and ornamental plants is often characterized by the use of greenhouses, high inputs of human labor and technology, in addition to intensive fertilizer and pesticide use (Abeliotis et al., 2015; Russo et al., 2008; Sahle and Potting, 2013).

Production of flowers and ornamental plants in Austria mostly occurs in small nurseries. Nurseries are agricultural production sites where flowers and ornamental plants are propagated and grown. According

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to the latest relevant statistical survey in 2010, 89% of nurseries that mainly produce flowers and ornamental plants have a production area smaller than 1 hectare; only 3% exceed 3 hectares (Statistik Austria, 2015). An overwhelming fraction of the cut flowers and ornamental plants produced in Austria are intended for the national market and not for export. Despite the relatively small area per nursery,

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the range of products is high, with an emphasis on balcony and flowerbed plants. This makes Austrian floricultural production an interesting object of research, as it is challenging to estimate and allocate

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emissions correctly.

Life cycle assessment (LCA) is a wide-spread method to evaluate environmental impacts of products and processes. LCA has been used to assess various types of agricultural products, including tomatoes (Theurl et al., 2014), wheat (Meisterling et al., 2009), biofuels (Cherubini et al., 2009) or wine (Vázquez-Rowe et al., 2012). The scope of such studies comprises cradle-to-grave, cradle-to-gate approaches as well as analyses that are targeting one specific production site such as a farm or a nursery (Haas et al., 2000). Currently, relatively few studies on the environmental impact of the production of cut flowers and ornamental plants exist compared to other agricultural products. LCA studies on flowers focus on countries such as Kenya, Ethiopia, The Netherlands, Italy, Ecuador, Colombia, and Greece, where 1

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different climatic conditions and cultivation techniques are found. The flower most often analyzed is the cut rose (Franze and Ciroth, 2011; Russo et al., 2008; Russo and De Lucia Zeller, 2008; Sahle and Potting, 2013; Soode et al., 2015; Torrellas et al., 2012; Williams, 2007) which seems to be motivated by the fact that it is by far the most prominent cut flower nowadays. One common finding of these studies is that as

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soon as some kind of greenhouse heating system using fossil energy is involved, the total emissions will be dominated by greenhouse heating. In comparison, cut roses produced in the open field show much lower emissions, even if they had been imported to Europe from Africa by airfreight (Williams, 2007). Soode et al. (2015) show that cut roses grown in the open field in Germany can also have low emissions,

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similar to those grown in Kenya or Ethiopia. Abeliotis et al. (2015) investigate the environmental impact of carnations in Greece. They find that two thirds of the total CO2-eq emissions are caused by the preservation phase. Greek carnations are grown in greenhouses but without any heating requirement.

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The life cycle of pot plants has been analyzed as well. Russo and De Lucia Zeller (2008) studied sowbread, Russo et al. (2007) cyclamen and Soode et al. (2015) orchids. Lazzerini et al. (2014, 2015) analyzed various ornamental plants that require multi-annual production cycles. They show that in-pot production is connected with higher emissions than production in the open field, due to the substrate mix used, having a high peat content, and the use of plastic pots. So far none of these analyses is focusing on smallscale floricultural production without any significant vertical (production of one specific product – e.g.

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cut roses) or horizontal (focus on a particular stage of production – e.g. production of young plants) specialization.

For any LCA study, the definition of the functional unit is an important stage because this choice strongly

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influences its outcomes. Choice of functional unit is difficult for flowers as they serve a purpose that is difficult to measure and compare across types of products. As our study includes the production of cut flowers as well as of pot plants, the question of comparability is even more complex. To contribute to

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this riddle, the suitability of the new functional unit “days of flowering” is introduced to compare the emissions related to the production of different cut flowers and pot plants. The purpose of this study is: •

To quantify greenhouse gas (GHG) emissions of the production of cut flowers and pot plants in a small scale ornamental plant nursery in Austria.

•

To detect GHG emission hotspots at the producing nursery.

•

To discuss merits of different functional units for comparing different kinds of ornamental plants, especially with regard to the comparison of pot plants and cut flowers. 2

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These questions are tackled based on an analysis of greenhouse gas emissions in a case study on one nursery.

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2. Materials and Methods 2.1. Goal and scope This study is based on principles of standardized Life Cycle Assessment (International Organization for Standardization, 2006a,b). The farm, in this case the nursery, is considered to be the center of agricultural production and therefore the initial point for the identification and reduction of negative

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environmental impacts (Haas et al., 2000). The GHG emissions related to the production process in one selected nursery (details see below) serving as our case study are quantified. In LCA terminology, this approach is known as cradle-to-gate, although in this case for some products the notion gate-to-gate

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would be more appropriate because some products have already gone through stages of their life cycle before they entered the nursery. Plants that are solely traded in the nursery without undergoing any significant production process are not included in this study.

Figure 1 (a) presents the production process and its stages with respect to the different major production lines, namely pot plant production and cut flower production, with either annual or perennial

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production cycles. Figure 1 (b) illustrates the production system and its inputs as well as the associated emissions accounted for in this study, as indicated with a light grey background. The stages of the life cycle after the product is classified as ready for sale are not included, namely storage, floristry (processing), transportation, the use phase and the end of life stage. Pre-production processes in

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previous nurseries are also outside the scope of this study. 13% of all products are propagated and fully produced in the nursery, 57% are not propagated but fully produced in the nursery, 29% enter the

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nursery as young plants and the main production phase occurs in the nursery and only to 1% of products produced enter the nursery as semi-finished products, therefor half of the production (excl. propagation) occurs in the nursery.

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(a)

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(b)

Figure 1 (a) Schematic illustration of the life cycle of ornamental plant production with respect to the three main types of production that occur in the nursery – production of pot plants, production on annual cut flowers and the production of perannial cut flowers. (b) The production system and the inputs to it. A dark grey background indicates that emissions related to the input are not accounted for in this study. Boxes with a light grey background describe what type of embedded GHG emissions have been accounted for. YP = young plants, SFP = semi-finished product 4

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2.2. Functional Unit The definition of a suitable functional unit is crucial for the ability of LCA methods to allow comparison of alternative goods or services (International Organization for Standardization, 2006a, 2006b; Rebitzer et al., 2004). As one of the goals of this study is to show the relevance of the choice of the functional unit

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when analyzing floricultural production, the results will be presented using different functional units. Advantages and disadvantages of each functional unit are discussed in depth in the discussion section. The functional unit “days of flowering” was developed to address the question “What is the function of cut flowers and ornamental plants and which attribute ensures this function”? This unit is based on the assumption that the function is to beautify the environment within which humans live. The main

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attribute of ornamental flowers and plants providing this function is the bloom. Though there are foliage plants, which do not necessarily have blooms, the bloom is the main decorative element of pot plants

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and cut flowers produced in the nursery. For cut flowers, the indicator vase life is defined as a proxy for days of flowering. Vase life is referred to as the time period a cut flower or foliage lasts in a vase if treated right. This parameter is well established because producers have an interest in a long vase life and different types of flowers are bred to have a long vase life. Data on vase life taken from Maree and Van Wyk (2010) is assumed to be robust, as there is a body of research and development on this subject matter (primary on cut roses), however there is currently no standard protocol to test and assess vase

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life (Fanourakis et al., 2013). Table 1 includes the range of vase life; the averaged values were used as basis for defining the functional unit days of flowering. For pot plants, there is no equivalent indicator to vase life. To overcome that hurdle, data from expert interviews are used asking the question how long the product will flower on average assuming adequate care. In addition to the functional unit days of

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flowering the results will be presented per piece of product (i.e. one pot plant or one stem in case of cut

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flowers) as well as on the level of the entire nursery.

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Table 1 Number of days of flowering for each product category, for cut flowers number of days of flowering represents the mean value of vase life as taken from Maree and Van Wyk (2010), additionally the respective minima and maxima are included. Days of Vase life

Vase life

used in this

min (days)

max (days)

study Cut flowers 9

2

14

Chrysanthemum

12

10

14

Freesia and ranunculus

7

6

9

Spring flowers

7

5

Iris

4

2

Lilies

7

5

Roses

10

5

14

Summer cut flowers

7

5

9

35

Azalea

49

Bedding and balcony plants

98

Cyclamen

56

Hyacinths

14

Primula

6 9

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Amaryllis

Poinsettia

8

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Pot plants

Pelargonium

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Calla

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flowering

140 49

21

Viola

56

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2.3. Case study The nursery is located in Linz, a city in the north-western part of Austria. The city is located at 48° 18′ 11" north latitude and 14° 17′ 26" east longitude, on average 260 meters above sea level (Stadt Linz, 2015).

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Average rainfall is 871 mm per year, average annual air temperature 9.9 °C with January being the coldest month with an average temperature of -0.4 °C and July, the warmest month, with 19.9°C, based on values from the years 1981 to 2010 (ZAMG, 2016). Average temperature over the 5 years studied is 2% below the average of 1981-2010. Precipitation over the study period was 11% lower than the average 1981-2010. The nursery is characterized by a small production area and the production of a variegated assortment of flowers. It is operating with rather long-established production practices, a low level of mechanization, long life span of greenhouses as well as high levels of human labor, compared to modern, large-scale 6

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production practices. It is not only a production site but at the same time the point of sale for the flowers that are produced there. Flowers are also traded in the nursery but these are excluded from the study. When referring to the company level, only the production within the company is addressed. In total, the

of the production are under glass and 480 m² on the open field.

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nursery covers an area of about 2000 m² of which 1880 m² are considered as production area. 1400 m²

In total, around 160 different flowers, plants and vegetables of different expressions and varieties are produced in the nursery. These plants were aggregated into 21 product categories. Decisive for the definition of the categories was their similarity in terms of crop management to ensure that GHG

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emissions could be adequately allocated. As vegetables (3 categories) are not in the focus of the study, results for these plants are not discussed in this paper. Dahlia was excluded for lack of cropping data.

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However, CO2-eq. emissions of those categories are included in the results on a company level. In contrast to industrial production, agriculture is not solely based on human-controlled inputs, given that environmental conditions such as sunlight, ambient temperature, rain water and soil nutrients are also indispensable for the production process. To a certain extent, these environmentally determined inputs can be technologically controlled by the farmer. However, environmental conditions are significant and may determine the amount of input factors provided by the farmer: for example, the

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quality and nutrient content of the soil determines the amount of fertilizer needed, the ambient temperature influences heating requirements, and the amount of rainfall affects the need for irrigation. 2.4. Data acquisition GHG emissions were aggregated using appropriate equivalence factors for a 100 year time frame to

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convert carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) to CO2 equivalents, according to (IPCC, 2013). Global warming was chosen as impact category because of its high importance in both the

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political and the scientific sphere. Emissions factors are taken mainly from the ProBas database (Umweltbundesamt, 2015) as well as data from the academic literature, industry reports (EPAGMA, 2012) and IPCC assessment reports (IPCC, 2013), see Table 3 and Wandl (2015) for further specifications. All calculations were performed using a spreadsheet editor. The primary data were derived from the company’s accounts. In-depth expert interviews with the owner and production manager of the nursery were conducted which was especially helpful to correctly allocate the various inputs to product categories. Data gaps on greenhouse structure, substrate composition, seed demand and other minor input categories were filled based on academic literature (e.g. Kowata et al., 2008), industry reports (EPAGMA, 2012) and catalogues from suppliers (Austrosaat, 7

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2015, 2014, 2013, 2009). Full accounts data were available for the period 2009 to 2013. As stocks of many important products (e.g. fertilizers and pesticides) are relatively large compared to their annual use and stock data were not available, allocation of inputs to individual years was not feasible. Instead, average annual use rates were calculated from total purchases over the five years, assuming that stock

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changes are of minor importance compared to the sum totals of the input flows over this relatively long period.

For measuring the production of cut flowers and pot plants, different approaches were used as

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presented in Table 2.

Table 2 Data basis and sources for calculation of number of products produced; C=cutting, B=bulb, YP=young plant, SFP=semi- finished product, S=seed. The production loss represents the assumed

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mortality rate during the production process.

Production loss

Data basis Cut flowers Calla

Cropping data 2014

Chrysanthemum

Number of input YP, C

Freesia and ranunculus

Cropping data 2014

Spring flowers

Number of input B

Iris

Year

Specifications

2014

ø 09 -13

Number of cuttings produced in the nursery derived from expert interviews

2014

Data adjusted by values from literature, 2014s yield exposed to high for average year

-7,50%

ø 09 -13

Crop yield for the subcategory daffodil was assumed 2,5

Number of input B

-7,50%

ø 09 -12

No production in 2013

Lilies

Number of input B

-7,50%

ø 09 -13

Roses

Cropping data 2015

Number of input S, YP

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Summer cut flowers

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-7,50%

2015

96,25 m² production area / 165 stems per m²

ø 09 -13

Number of plants per gram of seeds was calculated using data on seed requirements per 1, 000 plants as reported by Austrosaat. The amount of plants was multiplied by specific crop yield per plant (expert interviews)

Pot plants

Amaryllis, hyacinths

Number of input B

Azalea, Poinsettia

Number of Input SFP

Bedding plants

Number of input C, YP, SFP

-7,50%

ø 09 -13

Cyclamen, primula, viola

Number of input YP

-7,50%

Ø 09 -13

Pelargonium

Number of input C, YP, SFP

-7,50%

ø 09 -13

and

balcony

-7,50%

ø 09 -13 ø 09 -13 Number of cuttings produced in the nursery derived from expert interviews

Number of cuttings produced in the nursery derived from expert interviews, SFP in 2009 and 2010 only

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As no construction plans of the greenhouses were available, the amount of material (steel, aluminum, zinc, concrete, PE foil and twin wall sheet) was calculated using insights from previous research (Kowata

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et al., 2008; Theurl, 2008; Zabeltitz, 2011). The material requirements suggested by those studies were adapted to the size and construction specifics of the greenhouses in the nursery. The amount of glass used was calculated specifically by multiplying the total surface area of the greenhouses with the specific weight of 10kg/m² for 4mm thick glass. The amount of insulation foil was calculated by multiplying the required area during heating season with a respective weight of 0.41 kg/m². A lifespan of 40 years,

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acknowledging a replacement rate of 10% and 15% for aluminum and glass within the last 10 years, has been identified through one of the expert interviews. Shorter lifespans were considered for the covering

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materials PE foil (10 years), bubble foil (15 years) and twin wall sheets (20 years), also based on the expert interviews.

Small amounts of organic fertilizers are used as well but were not taken into consideration as the amount was considered to be negligible, accounting for less than 4% of the total amount of pure nutrients supplied as fertilizers. Emissions both from fertilizer supply as well as direct and indirect N2O emissions caused by denitrification and nitrification processes were considered as follows: As there are

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no specific studies on N2O emissions caused by fertilizer applications for the production of ornamental plants, calculations were made according to IPCC (2006) using default values. 2.5 Allocation Allocation is a crucial step within any application of the LCA methodology. In this study, inputs are

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allocated to products according to a scheme based on the specific characteristics of crop management for each product category. The allocation involved complex procedures which differed between products

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that are explained in detail in the supplementary material to this article; further information can be found in Wandl (2015). 3. Results

3.1. Emissions at the company level Total GHG emissions of the nursery in per average year are shown in Table 3. At the company level (see 2.3. for specific characteristics), total emissions are dominated by the emissions from heating of greenhouses (76% of yearly total GHG emissions). With 7%, home- and ready-made substrate is the second biggest contributor of emissions. The greenhouse infrastructure is also a relevant aspect (5%). Fuel (i.e. heating oil) used for soil sterilization is the 4th biggest contributor to emissions on a company 9

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level accounting for 4%. Another 4% of the emissions stem from the use of peat. Summarizing all inputs concerning growing media (substrate and peat) and soil preparation, this group accounts for 16% of the

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total emissions. Fertilizer, pesticides and pots can be considered of minor relevance.

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Pesticides

%

Emission factors

101

0,10%

Unit

Source

12,59

kg/kg

ProBas

441

0,50%

Mineral fertilizer N

363

0,40%

7,64

kg/kg

ProBas

Mineral fertilizer P

32

<0,05%

1,27

kg/kg

ProBas

Mineral fertilizer K

47

0,10%

1,22

kg/kg

Comment

ProBas

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Fertilizer production (subtotal)

kg CO2eq

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Table 3 Yearly GHG emissions aggregated to CO2 equivalents at the company level, respective emission factors (as derived in February 2014) and their sources.

Calculations based on IPCC Guidelines Fertilizer application (N2O estimation)

295

0,30%

6.818

7,40%

3.829

4,20%

Substrate ready-made

Substrate for pot plant production Substrate for YP production

2.989

Plastic (Plant pot) Fuel (for machinery) Heating energy (greenhouse heating) Greenhouse infrastructure (subtotal)

EPAGMA 2012

183,90

kg/m³

EPAGMA 2012

159,40

kg/m³

EPAGMA 2012/ Emission calculator Umweltbundesamt (AT)

EPAGMA 2012

4,20%

175,00

kg/m³

516

0,60%

3,13

kg/kg

ProBas

4,40%

2,98

kg/l

69.762

76,10%

0,24

kg/kWh

Environmental statement energy supplier

5,40%

1,20%

2,63

kg/kg

ProBas

2.537

2,80%

20,07

kg/kg

ProBas

Zinc

10

<0,05%

5,79

kg/kg

ProBas

Glass

826

0,90%

1,15

kg/kg

ProBas

Concrete

384

0,40%

0,21

kg/kg

ProBas

PE Foil

30

<0,05%

2,53

kg/kg

ProBas

Insulation foil

37

<0,05%

2,53

kg/kg

ProBas

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Twin-wall sheet

Value calculated referring to emissions factors for single components – peat, compost, fuel (steamer)

4.037

4.995

Aluminum

Mean value of different substrate mixes reported Mean value of different substrate mixes reported

Emission calculator Umweltbundesamt (AT)

1.113

Steel

Total

kg/m³

3.826

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Peat

Electricity

3,30%

151,80

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Substrate home-made

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for National Greenhouse Gas Inventories 2006 Substrate (subtotal)

Based upon Gemis Austria

58

0,10%

8,80

kg/kg

ProBas

902

1,00%

0,15

kg/kg

Electricity mix energy supplier October 2012 to September 2013

91.692

100,00%

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When looking at the results per product category (Figure 2), emissions from heating energy are the major influence factor for 15 of 17 different product categories. It accounts for more than 90% of total emissions for calla, hyacinths, iris, poinsettia and roses, followed by 87% for amaryllis and 84% for azalea and cyclamen. The only two categories where heating energy is a minor contributor to the total

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emissions are chrysanthemums and summer flowers with a share of 7% and 4%, respectively.

100%

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90% 80% 70%

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60% 50% 40% 30% 20% 10%

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0%

Fertilizer

Substrate

Plant pots

Peat

Fuel

Electricity

Greenhouse Structure

Heating energy

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Pesticides

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Figure 2 Relative contribution of individual input factors to the total global warming potential of GHG emissions per product category Substrate is the second-most important contributor to overall emissions per product category. Substrate accounts for 47% of the emissions for spring flowers and on average 13% to emissions of pot plants that are planted in the sales pot in the nursery. Emissions resulting from the greenhouse structure account for 3-13 % of total emissions in the different product categories. Peat and heating oil show similar patterns because their use is linked with one another: peat is always applied after the soil bed in question has been sterilized, which requires heating oil for steam production. The relative share of those two factors varies from 1.5% of total emissions per product 12

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category to 48% within the five categories where they are used. For both product categories not dominated by emissions from heating energy, summer flowers and chrysanthemums, peat and heating oil are used for soil preparation which explains the high range in shares. Planting pots contribute to 5 %

values for the other pot plants lie within this range.

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of emissions for viola 5% for bedding and balcony plants but only slightly less than 1% for cyclamen. The

All other production factors never contribute to more than 5% of total emissions per category, which is similar to results obtained on a company basis.

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3.2. Total emissions per functional unit The application of the two functional units “piece of product” and “days of flowering” yields different results, as shown in Figure 3 and Figure 4. When choosing piece of product as functional unit, cyclamen

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are highest rated with 5.6kg CO2-eq/piece of product, followed by amaryllis and azalea with around 3.6 kg CO2-eq/piece of product. Spring flowers on the other hand are associated with the lowest emissions <0.1 kg CO2-eq/piece of product. When applying days of flowering as functional unit, the production of iris is associated the highest emission amongst all production categories analyzed (0.4 kg/day of flowering),

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whereas viola has the lowest emissions.

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5

3

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2

1

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kg CO2-eq/piece of product

4

0

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product category

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Figure 3 Global warming potential (kg CO2-eq) per piece of product. Pot plants are presented in light grey, cut flowers are presented in black, ( ) mean value, ( ) ½ standard deviation.

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0.5 0.45

0.35 0.3

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kg CO2-eq/day of flowering

0.4

0.25 0.2 0.15

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0.1 0.05

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0

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product category

4. Discussion

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Figure 4 Global warming potential (kg CO2-eq) per day of flowering. The number in brakets indicates the total number of days of flowering. Pot plants are presented in light grey, cut flowers are presented in black, ( ) mean value, ( ) ½ standard deviation.

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4.1. Data accuracy and uncertainties The accuracy of our results is best at the company level (i.e. for all products generated within one average year) because inputs can be accurately calculated based on the accounts data and almost no allocation of inputs to individual production processes within the company is required. All inputs except heating energy, electricity and infrastructure (see the SI) could be unambiguously assigned to the production processes based on their characteristics (e.g., supplier, type of product, or packaging size) and area of application. If the allocation of an item to a production process was ambiguous based on the information from the accounts, the assignment was done using expert interviews. At the product level, allocation of inputs to individual product categories is only based on expert judgements which may introduce ambiguities. Only a monitoring system in the nursery would have 15

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allowed a more accurate allocation of GHG emissions to individual product categories. Such a monitoring is absent in the nursery because many production processes depend on human labor rather than on machines and are thus not controlled by computers recording the inputs required for each individual production process. The absence of exact data on square meter of gross production area for each

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product category required some simplifications that introduce inaccuracies which cannot be exactly quantified.

Water, other production related infrastructure, equipment, beneficial insects and human labor were not included due to methodological constraints. Furthermore, a potential Albedo effect of greenhouses, as

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described by Muñoz et al. (2010), and the CO2 uptake of the flowers and plants were not considered. The underestimation of total GHG emissions resulting from this choice of system boundary could not be

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exactly quantified due to the study design. The further the production was advanced when plants entered the nursery, the larger those impacts will generally be (i.e. option 4 implies higher upstream emissions than option 2 and 3). Table 4 presents the applicable options for the categories. For some categories more than one option applies, however, due to reasons of data accuracy and complexity no specific results for the different options per category can be reported. It seems likely that the heating requirements during these upstream stages are decisive. Propagation and young plant cultivation

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generally requires higher temperatures than the main cultivation period which would result in higher emissions. On the other hand, young plants require much less space than more mature plants; a higher number of plants per m2 reduces emissions per plant. Russo and De Lucia Zeller (2008) reported that baby plant production was negligible for cut roses, whereas they were significant for cyclamen. Hence,

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impacts from production processes outside the system boundary of this study can be expected to differ among products. Quantifying these emissions at the same level of data accuracy was not feasible due to

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lacking data access. Very limited results from previous studies further impede judging the importance of stages of production outside this study’s system boundary.

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Option 2

Option 3

B & B Plants (9%)

Amaryllis

B & B Plants (58%)

Chrysanthemum (28%)

B & B Plants (25%)

Chrysanthemum (72%)

Pelargonium (47%)

Calla (PA)

Cyclamen

Summer cut flowers (47%)

Freesia and ranunculus

Pelargonium (47%)

Hyacinths

Primula

Iris

Summer cut flowers

Roses (PA)

B & B Plants (7%)

Poinsettia

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Lilies

Option 4

Azalea

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Option 1

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Table 4 Production options for the different categories as presented in Figure 1. If there are more than one option for a category, the % value in brackets indicated the relative share. (PA) marks cut flowers with perennial production cycles.

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Spring flowers Summer cut flowers (53%)

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4.2. Influence factors and reduction potentials at a company level

As 76% of all emissions stem from heating greenhouses this area offers the highest potentials for reducing GHG emissions. One option can be a change in the type of energy carrier used in the heating system. The switch from natural gas to district heating in 2010 reduced the emission of the nursery by

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nearly 30% for the whole examination period. Other measures could be better insulation, either achieved by a switch of covering materials from glass to plastic alternatives or through additional

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insulation measures. Additionally, changes in the production process which allow for lowering the required temperature inside the greenhouse could help reducing GHG emissions. Such reductions could also help to reduce production costs as energy costs contribute significantly to the total costs of production. However, all possible changes may influence the growing conditions of the flowers and plants and thus could lead to a decrease in yield or other unintended consequences that need to be avoided or at least minimized. The only two product categories not dominated by heating emissions are chrysanthemums and summer cut flowers. The main cultivation of chrysanthemums season is from October to April, so their production requires no or minimal heating energy. Summer flowers spend only little time in greenhouse during the 17

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very first phase of the cultivation period and are mostly cultivated in the open field after the propagation phase. Chrysanthemums are mostly harvested before the heating period reaches its maximum. Peat, substrate and methods of soil preparation contribute 16% to the total GHG emissions of the

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nursery. These factors can potentially be influenced by the choice of the producer and the mode of production and do not directly underlie influences by annual seasonal or climatic variances. Infrastructure, which contributes 7% to the total emissions is another relevant factor. The life span of greenhouses (40 years) is long compared to other studies, which report life spans from 10 to 20 years (Kowata et al., 2008). Even though the greenhouses of the nursery are meanwhile outdated, the big

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difference between previous assumed life spans and our findings suggest that the life span of greenhouses is a factor that deserves closer attention as it likely to be longer than previously assumed.

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From an economic point of view, a renewal of greenhouse infrastructure after 10 or 20 years seems hardly profitable for small ventures. This factor is of particular importance if materials associated with a great amount of emissions such as steel and aluminum are used as construction materials. Pesticides and fertilizer are of minor importance, however, they might be a bigger contributor when other impact categories related to other environmental issues (e.g., toxicity) are in focus. Ornamental plant production is determined by annual variability stemming, for example, from different

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weather conditions or from events such as diseases or pest infestations. Therefore, in contrast to industrially manufactured products, the inputs required in agricultural production fluctuate. Our results suggest that temperature is the major external determinant of emissions induced by floricultural production under the climatic conditions of the present study site. Assuming that all other input factors

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remain constant and only the heating energy demand is adapted to the yearly requirements, emissions on a company level vary between 65,500 and 75,700 kg CO2-eq per year. Figure 5 shows the correlation

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between the amounts of heating energy used per month (according to the accounts) and the heating degree days in Linz as available in national statistics. The high R² of 0.94 supports the obvious assumption that heating requirements are a strong driver of heating energy demand.

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120 R² = 0.9441

80 60

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heating degree days

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4.3. Effects of different functional units

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Figure 5 Correlation of monthly MWh of heating energy consumed in the nursery and heating degree days in Linz

Pieces of product, cropped area (m2), mass of final product (kg) and energy or protein content are prominent functional units used for agricultural products (Roy et al., 2009). LCA studies of agricultural

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products often include more than one functional unit, as each unit has advantages and disadvantages. The choice of the functional unit can strongly influence the results and usually stems from the specific analytical perspective of the researcher. With regard to meat production, Roy et al. (2008) showed that either chicken or pork can be seen as environmentally least detrimental depending on the choice of

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functional unit as either protein or food energy content. For an analysis on cut flowers and ornamental plants, neither of these two functional units seems appropriate as they are not used as food. Studies of the life cycle of cut flowers and ornamental plants have so far seldom used multiple functional units. To

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our knowledge, the only study using more than one functional unit for flowering plants was that by Lazzerini et al. (2015) who considered “area” and “piece of product” (plant) to compare the impacts of different production lines in different nursery and various plant typologies. In contrast to other agricultural products, cut flowers and pot plants are usually not traded on the basis of mass units. Flowers are valued for their ornamental quality which largely depends on color, form, length, number of florescences and other qualitative criteria whereas their mass is not relevant for their use value or market value. When comparing cut plants and pot plants, the use of mass as a functional unit raises the problem that pot plants are usually sold with roots and planted in a pot filled with 19

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substrate, while cut flowers consist basically only of a stem, leaves and blooms. Therefore, such a comparison would be disproportionate. Additionally, the problem of data accessibility arises because mass of sold flowers is not accounted for. According to our knowledge, no database presenting weights of cut flowers and ornamental plants exists, neither in fresh nor dry weight. Dry weight might be chosen

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as functional unit, when ornamental flowers and plants are compared with other agricultural products when the question in focus is targeting at a comparison of different types of agricultural production systems.

When different types of nurseries or farms are compared against each other, area can be an appropriate

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functional unit, especially when the different types of production sites are all producing the same or very similar products. One major problem is that the productivity of the production system is not reflected

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with the area unit. Different floricultural systems can have the same GHG emissions per unit area while having different yields. In this case, the higher yielding products incur lower emissions per unit of product unit, as for example Williams et al. (2006) show for tomato production. To overcome this issue, Abeliotis et al. (2015) use yield of carnation per ha, in their case 1.5 million stems, as functional unit. Area was not chosen as functional unit in this study, as it would not reflect the fact that there are several different products produced in the nursery, with differences in yields and production characteristics. Our

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data basis would not have allowed for a presentation of results per yield of category/production area. So far, most studies of floricultural production used the functional unit piece of product. Especially when one single product is analyzed or different production processes related to the same product are compared, this functional unit is most frequently applied (e.g. Franze and Ciroth, 2011; Sahle and

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Potting, 2013). However, given the different size and mass of different flowers, or the difference between cut flowers and pot plants, this unit is often not appropriate due to quite obvious differences in

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area or other input requirements resulting from the size/mass differences of the respective products. The functional unit “days of flowering” allows for better comparison between different kinds of flowers and ornamental plants irrespective of their shape. This functional unit is not only useful for the nursery owner but also provides the consumer a basis for an environmentally friendly choice of flowers with respect to durability. Another argument in favor of days of flowering is that it actually upholds to ISO 14040 and 14044 in so far as it quantifies the performance of a product system, in this case the ornamental service provided by the flower.

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One main issue of this functional unit is that the actual durability of ornamental flowers and plants is dependent of the consumer’s treatment. It was assumed that the plant is provided with fertilizer, water, location and temperature according to its specific needs, providing optimal treatment. Further the plant is not infested with serious pest of fungal infestations and is treated with plant protecting agents if minor

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infestations occur. Another disadvantage of this functional unit is the fact that it is tailor-made for the analysis of ornamental flowers and plants and does not allow comparison to other agricultural products. Furthermore, it is possible that more than one cut flower is required to reach an equal decorative function compared to e.g. one pot plant having more than one bloom. To overcome this issue, a possible

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advancement could be the functional unit “per days of flowering per bloom”. However, this addition would make it much harder to operationalize the functional unit. Yet, the fact remains that there are

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different sizes of blooms, so it is not possible to completely eliminate all dissimilarities. Additionally, pot plants are living organism and not all blooms are flowering at the same time. Ornamental flowers and plants still remain agricultural products and even if highly standardized, there always will be differences in shape and appearance. In the end it remains in the eye of the beholder how decorative one ornamental flower or plants is.

As shown in Figures 3 and 4, these two distinct functional units yield different answers to the question

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which ornamental flower or plant has the highest and the lowest emission, respectively, in relation to the service it delivers. In both cases, half of the standard deviation was defined as bounds for high and low emitting categories, respectively. When applying the functional unit days of flowering only cut flowers are high emitters according to this definition. In this case spring flowers, summer cut flowers and

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chrysanthemum are the only cut flowers at the lower side of the emission spectrum, while the ranking is led by three pot plants being the lowest emitting products. Using piece of product as functional unit, on

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the other hand, shows that calla are the only cut flowers among the high emission products. Whereas four types of pot plants can be characterized as high emitters. In contrast to that, the two lowest emitting categories are cut flowers, in total four cut flowers can be categorized as low emitters but only three pot plants.

Under the application of the functional unit days of flowering pot plants are more likely linked with lower emissions compared to cut flowers as their durability outweighs the potentially higher emissions in the production process. However, our results do not lead to a general rule as there are pot plants that are still associated with higher emissions per days of flowering than certain cut flowers.

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4.5. Comparison with other studies Due to the relatively limited number of studies analyzing GHG emissions of cut flowers and pot plants it is difficult to compare our results with the literature. Moreover, comparisons are made even more difficult by the fact that only few study report GHG emissions as total numeric values. For cut roses,

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where the biggest body of literature is available, the reported emissions fall within the range of 0.04 kg to 2.9 kg CO2-eq per stem (Sahle and Potting, 2013; Soode et al., 2015; Torrellas et al., 2012; Williams, 2007). Production on the open field is on the lower end of that span, whereas production in heated greenhouses causes much higher emissions. Abeliotis et al. (2015) report 0.01 kg CO2-eq emission per stem of carnation, excluding the preservation phase, which accounts for 65,6% of total emissions in this

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particular case. Soode et al. (2016) report 3.9 kg CO2-eq for conventionally produced orchids (incl. packaging) per plant.

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5. Conclusions

This study confirms results from previous studies in terms of emission hotspots in floricultural production: if heated greenhouses are required during a relevant time of the cultivation process, the overall emissions are dominated by GHG emissions from heating energy requirements. However, this does not guarantee that products produced without glasshouse heating would always have low

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emissions per functional unit. Other input factors such as peat can also result in high emissions. For the first time, this study analyses different production lines within one nursery. The results of this study presents a first, preliminary empirical basis for considering GHG emissions when choosing flowers or ornamental plants from a broader spectrum of products.

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So far, no fully satisfactory functional unit for comparing GHG emissions of ornamental flowers and plant is available. Our results suggest that the use of days of flowering as functional unit is a promising

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approach to compare different flowers and plants which provide primarily or exclusively decorative services. For the first time this approach takes into account the actual function of the product and provides an indicator which makes very different products that basically fulfill the same function comparable. The functional unit could be suitable for certification schemes to foster sustainable consumer choices. However, while this functional unit can address some important aspects (e.g. longevity of the flowers), some problems inherent in any attempt to compare qualitatively different products remain, e.g. the question of different sizes of flowers. The study further identifies methodological challenges when analyzing small agricultural production system with means of LCA methodology. Even with access to all data usually available in a typical 22

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company, LCA of small nursery or farms remain hard to conduct. Small nursery and farms often do not collect data for which they do not have an immediate need or legal obligation that might be a valuable asset for detailed allocation of inputs. This changes when analyzing bigger companies that are managed using computers for monitoring. One approach to get more or better data on small nurseries or farms

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can be the implementation of smartphone applications collecting data on inputs and outputs. This can help the owners and managers to better manage their companies while simultaneously providing data for research.

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Acknowledgements

We want to declare that the nursery is owned and run by the lead author’s parents, which made it

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possible to receive full access to all available company data, including data often deemed sensible by managers of similar enterprises. We thank the team of the nursery for the willingness to share their knowledge and experience during the interviews.

This work was supported by a scholarship [Förderungsstipendium, 2. Tranche 2014] of the Alpen-Adria

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Highlights Introduction of a new functional unit “days of flowering” “Days of flowering” allows for better comparison of various types of flowers & plants

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GHG emissions of various types of flowers and plants are presented