Life cycle assessment of 36 dairy farms with by-product feeding in Southwestern China

Science of the Total Environment 696 (2019) 133985

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Science of the Total Environment journal homepage: www.elsevier.com/locate/scitotenv

Life cycle assessment of 36 dairy farms with by-product feeding in Southwestern China Lin Wang a,c, Akira Setoguchi a, Kazato Oishi a, Yuta Sonoda a, Hajime Kumagai a, Chagan Irbis b, Tatsuya Inamura a, Hiroyuki Hirooka a,⁎ a b c

Graduate School of Agriculture, Kyoto University, Kitashirakawa-oiwake-cho, Sakyo, Kyoto 606-8502, Japan Faculty of Life Science and Technology, Kunming University of Science and Technology, 727 Jingming Road (South), Chenggong New District, Kunming, Yunnan 650500, China College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T

• Environmental impacts of 36 dairy farms in China were assessed on farm scale. • The dairy systems were unique in that male calves were kept for beef production. • The dairy systems used a large amount of by-product feeds. • The beef production contributed about 40% of the total environmental impacts. • Feeding patterns greatly affected the variability of environmental impacts.

a r t i c l e

i n f o

Article history: Received 17 May 2019 Received in revised form 17 August 2019 Accepted 18 August 2019 Available online 20 August 2019 Editor: Deyi Hou Keywords: Acidification Dairy cattle Eutrophication Global warming Life cycle assessment Principal component

a b s t r a c t In Southwestern China, dairy farms utilized by-product feeds in dairy production and surplus calves were kept for producing beef as a by-product. However, it is unclear how the environmental impacts are in such dairy production system. This study evaluated, for the first time, the global warming potential (GWP), acidification potential (AP), eutrophication potential (EP) and energy consumption (EC) of 36 intensive dairy farms by life cycle assessment (LCA) in China, and investigated the effects of the feeding patterns on the environmental impacts by a principal component analysis (PCA). The results of the LCA showed that the impacts of beef production by surplus calves and culled cows accounted for 43, 41, 41 and 40% of the total GWP, AP, EP and EC values, respectively, despite the fact that beef was considered as a by-product in the dairy system. Five feeding patterns were distinguished as principal components (PCs): vegetable residue-based concentrate feeding (PC1), beverage byproduct feeding (PC2), corn grain-stover feeding (PC3), corn silage-stover feeding (PC4) and rice straw-based brewers' grain feeding (PC5). The results of the PCA indicated that the farms utilizing by-product feeds purchased from companies near the study area had relatively low environmental impacts. In contrast, the farms that managed cows without precise nutritional planning showed relatively high impacts in terms of GWP, AP, EP and EC. Other impact categories, such as abiotic depletion and land use, would be considered for a complete assessment of dairy production in future studies. The consequences of this study could have a certain reference value on making policy/planning for developing dairy-beef production in China. © 2019 Elsevier B.V. All rights reserved.

⁎ Correspondence author. E-mail address: [email protected] (H. Hirooka).

https://doi.org/10.1016/j.scitotenv.2019.133985 0048-9697/© 2019 Elsevier B.V. All rights reserved.

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L. Wang et al. / Science of the Total Environment 696 (2019) 133985

1. Introduction Asia has recently shown remarkable growth in the production and consumption of milk and related dairy products as the population grows. India is the largest milk producer worldwide according to the Organization for Economic Cooperation and Development and the Food and Agriculture Organization (OECD-FAO, 2014) Agricultural Outlook 2014–2023 (2014), and local milk production has greatly increased in Thailand (Phi, 2017). In China, by 2050, the milk demand is expected to be triple the production level in 2010 (Bai et al., 2018). On the other hand, the increase in dairy production has had various side effects on the environment. Dairy farms contribute to global greenhouse gas emissions, primarily through the emissions of enteric CH4 and N2O from excreta of dairy cows (Chianese et al., 2009; Gerber et al., 2013). The emissions of gases (SO2, NOX, and NH3) from dairy production have resulted in acidification of the ecosystem (Audsley et al., 1997), which may affect plants, animals and humans. Moreover, increased discharge of manure aggravates water pollution (Strokal et al., 2016), which causes eutrophication. To address such problems, reducing the environmental impacts of dairy production is essential. Life cycle assessment (LCA) is one of the most internationally accepted methods for examining the environmental impacts associated with dairy production systems. A large number of LCA studies were conducted on dairy production systems in the EU and the US (e.g., Baldini et al., 2017; Chen and Holden, 2017; Rotz et al., 2010; Mc Geough et al., 2012; O'Brien et al., 2012; Bartl et al., 2011). Cederberg and Mattsson (2000) performed an LCA on conventional and organic milk production at the farm level with two relatively large dairy farms in Sweden. Similarly, in the Netherlands, LCA was used to compare the environmental impact of conventional and organic milk production systems, and the assessment was based on 21 commercial dairy farms (Thomassen et al., 2008). Series of strategies focusing on different aspects have been proposed by LCA studies in order to decrease the environmental burden. Bacenetti et al. (2016) reported that the increase of milking frequency improved environmental performances, especially for the acidification and eutrophication potentials. In the pasturebased dairy system, strategic grazing could decrease 20% CH4 emission intensity and 18% CH4 yield (Congio et al., 2018). In intensive dairy production, improving farm profitability also could reduce the greenhouse gas emission (Jayasundara et al., 2019). In contrast, LCA studies for dairy production have been limited in Asian countries. In Japan, Ogino et al. (2008) assessed the environmental impact of two types of dairy farming systems in Japan; one system used whole-crop rice silage, and the other system was conventional. In China, Wang et al. (2016) investigated greenhouse gas emissions and land use of dairy farming, and indicated that increasing milk productivity by replacing some parts of concentrates with alfalfa hay could decrease greenhouse gas emissions. More recently, Wang et al. (2018) assessed environmental impacts and resource use of milk production on the North China Plain, and suggested that returning manure to nearby cropland could decrease environmental impacts. China is a large country, and there are various dairy production systems. The protection of the environment is one of the basic state policies of the Chinese government (Zhang and Wen, 2008). Especially in the farms which are closer to the city, the environmental policy is stricter with dairy production according to The State Council of the People's Republic of China (2013). Therefore, further LCA studies on different dairy production systems in China are required. There are animal production systems under well-developed integration of crop and animal production in Southwestern China. In these systems, animals are fed various residues that are agricultural by-products from cropping farms and some purchased feed products. In turn, animals provide manure for the maintenance and improvement of soil fertility of the croplands and greenhouses. Utilization of by-products from some local industries as feed is an important characteristic in livestock production (Anzai et al., 2016). When feed ingredients and compositions are varied, the environmental impacts on production systems

should be evaluated by considering the environmental emissions from feed production and transport as well as animal excretion (Oishi et al., 2013). There is a knowledge gap in relationship among by-product feeding and environmental impacts in this area. Therefore, to evaluate environmental loads from dairy farms in this area, the effects of the various by-product feeding patterns on environmental impacts for the entire production system should be assessed. Moreover, surplus calves were not sent away immediately, but kept for 24 months for meat due to the economic superiority of beef production in this area. As a matter of fact in China, male dairy calves have been considered as an important source for beef production under the situation with insufficient beef sources (Cao, 2009). Government has started to encourage some leading dairy enterprises to fatten male dairy calves to develop the standardized scale production according to the Ministry of Agriculture and Rural Affairs of the People's Republic of China (MOA, 2015a). Some local government has put forward a series of concrete measures and points of policy to promote fattening the male calves (MOA, 2015b). It is however important to evaluate the environmental impacts of such dairy farms with beef production which would be adopted in intensified dairy production in China in near future. The first objective of this study was to assess environmental impacts (global warming, acidification, eutrophication and energy consumption) of 36 dairy farms with by-products feeding by an LCA methodology and a principal component analysis (PCA) based on survey data in Southwestern China where a wide diversity of by-product feeding is practiced. This information will be useful for dairy farms to optimize feeding pattern considering the environmental impacts. The second objective was to estimate the environmental impacts from beef production from culled cows and rearing surplus calves in the dairy systems, providing valuable guidance on making policy/planning for developing beef production from rearing male dairy calves in China. 2. Materials and methods 2.1. Study area The farm surveys of the present study were conducted at Xiaojie Town in Songming County, located in central Yunnan Province in Southwestern China, 43 km away from the capital city, Kunming. The total number of dairy farmers in this study area is 70, with 340 m2 arable land per capita according to information from the village office. Large areas of arable land are covered with greenhouses for growing vegetables. Each year, a large amount of local vegetables is transported to other provinces in China or other countries abroad. Dairy production is also an important agricultural activity in this area and is mainly conducted for milk consumption (milk and dairy products) in Yunnan Province. The surveys of dairy farms were conducted from November 2014 to June 2016, and among the farms, 36 dairy farms with sufficient information for an assessment of the environmental impacts by an LCA were selected. The total number of dairy cattle in the study area is 2250 heads according to the inquiry with the village office. Two large brewery companies in/near the target area provided brewers' grains and distillers' grains as by-product feeds for dairy farms. 2.2. Description of the dairy production system Based on the interviews with farmers, it was found that dairy management, except for supplied feed and milk yield, was similar among farms. Therefore, representative dairy management was assumed as follows: The first calving of a heifer occurs at 24 months of age with 500 kg of body weight, the lactation period is 305 days, and the dry cow period is 60 days. The average calving number and birth weight of calves are 6 and 40 kg, respectively. One of six calves is kept as a replacement heifer to maintain the herd size for the farms, and the remaining five calves are used for beef production. All calves are fed some rice straw from 1 month of age and are weaned at 2–3 months of age. All male and

L. Wang et al. / Science of the Total Environment 696 (2019) 133985

surplus female calves are raised within the farms until 24 months of age without any fattening treatments and sold at 24 months. Thus, the following three animal categories were defined: “cows for milk production”, “female calf for replacement” and “surplus calves and culled cows for beef production”. Information on milk yield and the amount and composition of feeds were collected from each farm through our field survey. The selected dairy farms were repeatedly visited during the survey period (from November 2014 to June 2016) in order to collect reliable information as possible. Milk production from each dairy farm was measured by electronic meter, and there was variability in this information among the farms in this study. The feed ingredients used in this system were corn gluten feed, corn grain, brewers' grains, distillers' grains, rice straw, corn stover, corn silage and vegetable residues (mainly romaine lettuce). The feeds for male calves were the same as those for cows. The ratio of ingredients was assumed to be constant for each farm, and the average amount of feed intake was estimated to meet the metabolized energy requirement derived from the Feeding Standard of Dairy Cattle (Ministry of Agriculture of the People's Republic of China, 2004). 2.3. Definition of the system boundary and the functional unit for LCA The first step of an LCA is the definition of the goal and scope of the analysis and the functional unit. The goal of the analysis was to evaluate the environmental impacts of a dairy production system based on survey data from 36 farms. The definition of the LCA boundary in the

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present study is presented in Fig. 1. It includes five processes: feed production, feed transportation, animal management, enteric fermentation, and manure management. The functional unit in this study was defined as 1 kg of fat and protein-corrected milk (FPCM). The FPCM production was calculated using the following equation (Eq. (1)) (IDF, 2010) based on a milk fat percentage of 3.65% and protein percentage of 3.1% according to information from the local milk company: FPCMðkg=yrÞ ¼ Productionðkg=yrÞ  ½0:1226  Fat% þ 0:0776  True Protein% þ 0:2534

ð1Þ

Multiple products (milk from lactating cows and beef from rearing surplus calves and culled cows) were produced in this dairy system, and therefore, an economic allocation was conducted to evaluate the whole system by LCA. The milk price was 3.3 yuan/kg, and the price of steers or heifers was assumed to be 15,000 yuan/head, while the price of culled cows was assumed to be 7000 yuan/head. 2.4. Life cycle inventory The second step of an LCA is to develop an inventory of the resources and emissions released to the environment that are relevant to all the processes in the system boundary. The inventory classified information into the categories feed production, feed transportation, animal management, enteric methane and manure treatment, which are listed in Table 1 in detail.

Fig. 1. Definition of the dairy system boundary in the study area.

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L. Wang et al. / Science of the Total Environment 696 (2019) 133985

Table 1 Inventory data for coefficients of emissions in this study. Source

Output coefficient

Reference

3889 7500 3000 7751 3707

kg/ha kg/ha kg/ha kg/ha kg/ha

Survey data Survey data Gao et al. (2012) Long and Li (2015) McKenzie et al. (2004)

200 150

kg kg

Sorghum Wheat Barley N manure application Corn P fertilizer application Corn Rice

280 180 148

kg kg kg

Liu et al. (2012) Sun et al. (2015) and Wang (2010) Gao et al. (2012) Long and Li (2015) McKenzie et al. (2004)

50

kg

Liu et al. (2012)

68 83

kg kg

Sorghum Wheat Barley P manure application Corn K fertilizer application Corn Rice

105 47 74

kg kg kg

Liu et al. (2012) Sun et al. (2015) and Wang (2010) Gao et al. (2012) Long and Li (2015) McKenzie et al. (2004)

25

kg

Liu et al. (2012)

105 188

kg kg

Wheat Barley By-product feed production See text

69 57

kg kg

Liu et al. (2012) Sun et al. (2015) and Wang (2010) Long and Li (2015) McKenzie et al. (2004)

Feed production Crop production Corn yield Rice yield Sorghum yield Wheat yield Barley yield N fertilizer application Corn Rice

Feed transportation CO2 emission from gasoline SO2 emission from gasoline NOX emission from gasoline Animal management NH3 from housing Enteric methane CH4 emission Manure treatment CH4 from manure NH3 from manure N2O from manure

Ramirez et al. (2008) and Xu (2013) 237.7

kg/t/1000 km 181.56 g/1000 km

Yang (2002)

764.1

g/1000 km

Yang (2002)

4.5

%

Koerkamp et al. (1998)

See text 13 12 0.5

Yang (2002)

Shibata (1993) and Sekine (1986) kg/head/year IPCC, 2006 Table 10.14 % Payraudeau et al. (2007) % IPCC, 2006 Table 10.21

Corn stover was harvested manually and transported to dairy farms by dairy farmers to make silage. Vegetables were harvested from the greenhouse and then transported to processing companies. Dairy farmers can obtain vegetable residues from either greenhouses or processing companies for free. The emissions from the production of corn stover and vegetable residues were not considered in this study because they were either free or inexpensive and had minimal energy costs. By-product feeds such as distillers' grains, brewers' grains, corn gluten feed and rice straw were also fed to dairy cattle; thus, economic allocation was used for the partitioning of pollutant emissions from the production of the main product. Due to the yield and price, 99% and 1% of the emissions from liquor production were allocated to the main product liquor and its by-product, distillers' grains, respectively. Similarly, 99% and 1% of the emissions from beer production were allocated to the beer and brewers' grains, respectively. The inventory data of these two by-product feeds are listed in Table 2. Approximately 13% of the emissions was allocated from corn gluten feed, while 87% was

allocated from corn starch production (Ramirez et al., 2008; Xu, 2013). Additionally, 13% was allocated from rice straw, and 87% was allocated from rice grain production. The allocation factors and emissions of feeds after allocation are shown in Tables 3 and 4, respectively. The emissions from feed transportation were determined by multiplying the unit of emissions by the product of feed weight and transportation distance. Corn gluten feed, corn grain and corn stover were purchased or obtained locally, and the distance of transport for these local feeds was assumed to be 2 km. Distillers' grains and brewers' grains were assumed to be transported from liquor and beer companies, respectively, located 33.8 km from the study area. The distance of transporting rice straw was defined as 89.4 km based on the route from Xundian County to Xiaojie Town. A large number of vegetable residues were transported from vegetable processing companies to dairy farms, and the distance was assumed to be 20 km. The transport distance for the vegetable residues from the greenhouses was assumed to be 2 km. CO2, SO2 and NOX emissions from gasoline consumption were obtained from the data reported by Yang (2002). Feed preparation and removing the manure out of dairy farms should be considered as work for animal management. Due to the fact that feed preparation and removing the manure were done by labours according to the survey, the energy consumption was assumed to be zero. NH3 emissions from animal management were assumed to be 4.5% from N excretion (Koerkamp et al., 1998). Manure was collected twice per day and placed at dairy farms temporarily and then manure was removed and transported to the place for composting so that vegetable farms used it as an organic fertilizer. The impact of composting manure was also considered in this system. CH4 emissions from manure were 13 kg/head/year (IPCC, 2006). NH3 emissions from manure composting were 12% from N excretion (Payraudeau et al., 2007). N2O emissions from manure were 0.5% from N excretion (IPCC, 2006). Enteric CH4 emissions from dairy cattle were calculated from dry matter intake (DMI) using the quadratic regression reported by Shibata (1993) as follows: CH4 production L=day ¼ −17:766 þ 42:793  ðkgDMI=dayÞ−0:849  kgDMI=dayÞ2 ð2Þ

Table 2 Inventory data of brewers' grains and distillers' grains.

Input Material Wheat Refined rice Sorghum Rice husk Corn Barley Fuel Steam Coal Electricity Output Beer Brewers' grains Distilled liquor Distillers' grains Pollutants CO2 CH4 N2O SO2 NOX NH3

Brewers' grains processing

Distillers' grains processing

Unit

146.9 49.1 0 0 0 0

1000.8 987.2 1269.2 666.67 225.6 73.6

g g g g g g

499.8 71.4 –

– 2254 0.095

g g kWh

1 0.18 – –

– – 1 0.77

kg kg kg kg

20.9 0.09 0.01 0.07 0.08 0.09

130.6 0.43 0.04 0.45 0.49 0.47

g/kg g/kg g/kg g/kg g/kg g/kg

L. Wang et al. / Science of the Total Environment 696 (2019) 133985 Table 3 Summary of allocation factors used in this study. Products

Liquor production Liquor Distillers' grains Beer production Beer Brewers' grains Starch production Corn starch Corn gluten feed Rice production Rice grain Rice straw

Allocation factor

Market value (yuan/kg)

Percentage by weight (%) 56 44

54.9 0.7

– 0.01

85 15

7.5 0.5

– 0.01

91 9

2 3

– 0.13

53 47

1.5 0.3

– 0.13

ð3Þ

Nitrogen (N) content in excreted manure per kg of 4% fat-corrected milk (FCM) for lactating cows (g/kg) was calculated by the following multiple regression (Terada et al., 1997): Excreted N ¼ −14:48  ln ðFCMÞ þ 0:806  CP þ 0:769  DMI þ 31:4

A range of different feeding patterns exist in the 36 dairy farms. To quantify the effects of the feeding patterns on the variation in the environmental impacts of the 36 dairy farms, PCA was performed to summarize the pattern of different feeds among the dairy farms. A varimax rotation was applied to the retained components to redistribute the variance among factors to obtain coefficients for PCA. Five principal components (PCs) were extracted according to the eigenvalues, which were higher than 0.95. All eight variables were represented in one of the PCs, where the dominant variables in each PC were highly correlated. The PCA was performed using the PRINCOMP procedure in SAS 9.3 (2008). Finally, the relationship between the variation in environmental impacts and feeding pattern expressed by the PC scores was analyzed using the REG procedure in SAS 9.3 (2008). 3. Results 3.1. Characteristics of the 36 dairy farms in the study area

ð4Þ

The N content in the excreted manure of calves, heifers, and dry cows (g/day) was calculated as follows (MAFF, 1999): Excreted N ¼ ðCP−RP−PPÞ=6:25

equivalent (SO2e) and the SO2e factors for SO2 = 1, NOX = 0.7 and NH3 = 1.88 were used (Heijungs et al., 1992). Moreover, the eutrophication potential refers to the potential N and P input to the aquatic ecosystem, which is caused by NOX and NH3 emission. The PO4 equivalent (PO4e) factors for NOX = 0.13 and NH3 = 0.33 were used to calculate the eutrophication potential (Heijungs et al., 1992). Energy consumption includes the use of energy from non-renewable sources. 2.6. Principal component analysis

The CH4 emissions from calves were calculated as a function of weeks of age as follows (Sekine, 1986): CH4 production L=day ¼ 3:4  ðweek of ageÞ−1:2

5

ð5Þ

where CP is the crude protein intake (g/day), RP is the retained protein (g/day) and PP is the pregnancy protein (g/day) calculated according to the China Feeding Standard of Dairy Cattle (Ministry of Agriculture of the People's Republic of China, 2004).

A summary of the means and the standard deviations of herd size, amount of each feed ingredient offered and milk yield of the 36 dairy farms are shown in Table 5. Vegetable residues made up the largest amount of the feeds. The two beverage by-product feeds, brewers' grains and distillers' grains, were used in average amounts of 6.2 and 5.4 kg/head/d, respectively, in the diet, and these amounts were numerically higher than the amounts of other feeds in the diets except that of vegetable residues. The large value of the standard deviation for each feed indicated that the amount of each feed offered greatly differed among the 36 dairy farms. The average milk yield of the 36 dairy farms was 18.3 kg/head/d.

2.5. Life cycle impact assessment The environmental impacts included four categories of impacts in the present study: global warming, acidification, eutrophication and energy consumption. The global warming potential refers to emission of the greenhouse gases CH4, mainly from enteric fermentation and manure treatment, and N2O mainly due to N fertilizer application in the soil and also from manure treatment. The emissions of CH4 and N2O are expressed in CO2 equivalent (CO2e). The global warming potential was calculated according to the CO2e factors from the International Panel on Climate Change (IPCC) (IPCC, 2006) for CO2 = 1, CH4 = 25 and N2O = 298. These factors were set based on a time horizon of 100 years (IPCC, 2007). Regarding the acidification potential, the NOX emission is mainly from N input and NH3 emission is mainly from manure treatment. The emissions of NOX and NH3 are expressed in SO2

Table 4 Inventories of feeds for quantifying environmental impacts after allocation.

After allocation Corn grain Corn gluten feed Brewers' grains Distillers' grains Rice straw

CO2

CH4

N2O

SO2

NOx

NH3

329.8 124.3 20.9 130.6 34.2

0.00 0.00 0.09 0.43 3.10

0.50 0.16 0.01 0.04 0.01

1.00 0.36 0.07 0.45 0.10

1.06 0.40 0.08 0.49 0.12

6.38 2.09 0.09 0.47 0.69

3.2. Environmental impacts on dairy production systems Fig. 2 illustrates the global warming potential (A), acidification potential (B), eutrophication potential (C) and energy consumption (D) from each process in dairy production based on 36 dairy farms. The global warming potential from “cows for milk production” (638.97 g CO2e) accounted for 57% of the total potential for the dairy

Table 5 Characteristics of the 36 dairy farms from interviews in the study area. Item Herd size Number of dairy cattle Number of lactating cow Amount of each feeda Corn gluten feed Corn grain Brewers' grains Distillers' grains Rice straw Corn stover Corn silage Vegetable residues Milk yield a

Based on fresh weight.

Mean ± SD

Unit

32 ± 15 12 ± 7

head head

3.8 ± 1.93 2.7 ± 1.20 6.2 ± 4.65 5.4 ± 3.82 3.6 ± 2.98 2.6 ± 3.22 4.7 ± 4.82 20.4 ± 14.11 18.3 ± 5.23

kg/head/d kg/head/d kg/head/d kg/head/d kg/head/d kg/head/d kg/head/d kg/head/d kg/head/d

6

L. Wang et al. / Science of the Total Environment 696 (2019) 133985

Fig. 2. Global warming potential (A), acidification potential (B), eutrophication potential (C) and energy consumption (D) per FPCM after allocation from the dairy system in the study area.

system. Although beef is not the main product in the dairy system, 43% of global warming potential was attributed to the “surplus calves and culled cows for beef production” (480.87 g CO2e). Regarding the global warming potential from different processes, enteric methane emissions accounted for the highest percentage of global warming potential at 53% of the total contribution in the dairy system, and feed transportation contributed the lowest portion (0.7%) in the dairy system. Feed production and manure treatment contributed 33% and 14%, respectively, to the total global warming potential. The emissions attributed to the acidification potential were 8.78 g SO2e from “cows for milk production” and 6.19 g SO2e from “surplus calves and culled cows for beef production”. The contribution percentages from feed production were 58% for “cows for milk production” and 58% for “surplus calves and culled cows for beef production”. The contribution of feed transportation to the acidification potential was small, which was consistent with the results of the global warming potential. Animal management (housing) and manure treatment accounted for 12% and 30%, respectively, of total acidification potential. In terms of the eutrophication potential, the emissions were 1.46 g PO4e and 1.03 g PO4e from “cows for milk production” and “surplus calves and culled cows for beef production”, respectively. Feed production was responsible for over 50% of these eutrophication emissions for the entire dairy system, while the emissions from housing and manure treatment accounted for 12% and 31%, respectively. In this dairy production, energy consumption originated from feed production and transportation. Feed production contributed over 95% of energy consumption for the total dairy system.

3.3. Variation in environmental impacts among 36 dairy farms Table 6 shows the basic statistics for the global warming potential, acidification potential, eutrophication potential and energy consumption of the 36 dairy farms. The variations in the environmental impacts were large and varied from 857.49 to 1528.65 g CO2e, from 11.46 to 20.07 g SO2e, from 1.92 to 3.34 g PO4e, and from 1.68 to 3.44 MJ. 3.4. Effects of the feeding patterns on the environmental impacts The feeding patterns determined by the PCA are shown in Table 7. Five principle components were extracted. Because PC1 had a highly negative loading for corn gluten feed and positive loadings for brewers' grains and vegetable residues, PC1 was defined as the component representing vegetable residue-based concentrate (corn gluten feed or brewers' grains) feeding. PC2 was mainly related to the concentrates and two beverage by-product feeds (brewers' grains and distillers' grains) and was defined as the component representing beverage byproduct feeding. High loadings for corn-related feeds, including corn grain, corn stover and corn silage, were reflected in either PC3 or PC4. PC5 had a highly positive relation to rice straw and a negative relation to brewers' grains. Based on the results from the analyses of the effects of the five component scores on environmental emissions, the global warming potential, acidification potential, eutrophication potential and energy consumption were modeled as the following equations: Global warming potential ðg CO2 eÞ ¼ 1127:42–68:0 PC4

ð6Þ

L. Wang et al. / Science of the Total Environment 696 (2019) 133985 Table 6 Global warming, acidification, eutrophication potentials and energy consumption of 36 dairy farms after allocation in the study area. Mean GWP, g CO2 equivalent (per kg-FPCM) Feed production Feed transportation Housing Enteric methane Manure Total AP, g SO2 equivalent (per kg-FPCM) Feed production Feed transportation Housing Enteric methane Manure Total EP, g PO4 equivalent (per kg-FPCM) Feed production Feed transportation Housing Enteric methane Manure Total EC, MJ (per kg-FPCM) Feed production Feed transportation Housing Enteric methane Manure Total

Minimum Maximum Standard deviation

367.31 7.56 / 595.35 157.20 1127.42

242.38 4.79 / 432.09 109.21 857.49

499.60 10.85 / 825.82 238.91 1528.65

60.40 1.28 / 94.16 29.95 175.07

8.78 0.0228 1.76 / 4.48 15.04

5.73 0.0145 1.30 / 3.30 11.46

12.47 0.0327 2.40 / 6.10 20.07

1.59 0.0039 0.27 / 0.69 2.29

1.41 0.0032 0.31 / 0.79 2.51

0.92 0.0020 0.23 / 0.58 1.92

2.01 0.0045 0.42 / 1.07 3.34

0.26 0.0005 0.05 / 0.12 0.38

2.43 0.11 / / / 2.54

1.55 0.07 / / / 1.68

3.32 0.16 / / / 3.44

0.41 0.02 / / / 0.42

GWP, global warming potential; AP, acidification potential; EP, eutrophication potential; EC, energy consumption; FPCM, fat and protein corrected milk.

Acidification potential ðg SO2 eÞ ¼ 15:04–1:00 PC4

ð7Þ

Eutrophication potential ðg PO4 eÞ ¼ 2:51–0:17 PC4

ð8Þ

Energy consumption ðMJÞ ¼ 2:54 þ 0:13 PC2–0:18 PC4

ð9Þ

These equations indicated that PC4 was a significant key contributor in global warming potential, acidification potential, eutrophication potential and energy consumption (P b 0.05). In addition, PC2 had a significant effect on energy consumption (P b 0.05). The PC scores derived from the five PCs (PC1 to PC5) for global warming potential, acidification potential, eutrophication potential and energy consumption for each dairy farm are listed in Appendix I.

Table 7 Results from the principal component analysis showing the feeding patterns in the study area. Variable

Corn gluten feed Corn grain Brewers' grains Distillers' grains Rice straw Corn stover Corn silage Vegetable residues

Principal components PC1

PC2

PC3

PC4

PC5

−0.77⁎ −0.02 0.57⁎

−0.30 0.27 −0.46⁎ 0.90⁎

0.11 0.85⁎ −0.22 0.08 −0.07 −0.68⁎ −0.11 0.04

0.17 −0.25 0.04 0.07 −0.04 −0.55⁎ 0.90⁎ 0.19

−0.17 −0.06 −0.48⁎ −0.04 0.92⁎

0 0.23 0.11 0.07 0.70⁎

−0.06 0.23 0.11 −0.19

−0.03 −0.05 0.14

PC1, PC2, PC3, PC4 and PC5 were extracted according to the eigenvalues, which were higher than 0.95. ⁎ p b 0.05.

7

4. Discussion 4.1. Environmental impacts of 36 dairy farms in the study area In general, large variations have been obtained from LCA results of dairy production, ranging from 0.41 to 2.46 kg CO2e per kg of milk (Pirlo, 2012; Asselin-Balençon et al., 2013) due to the difference in the applied methods, data sources and targeted dairy farming systems. In Europe, Fantin et al. (2012) reported greenhouse gas emissions ranging between 0.8 and 1.5 kg CO2e per kg of milk for a collection of LCA studies. The mean values of environmental impacts in our study area in Southwestern China were higher than the values in some dairy production systems in Europe (Cederberg and Mattsson, 2000; Iepema, 2001; Thomassen et al., 2008; Mc Geough et al., 2012) but lower than values of environmental impacts in the North China Plain (Wang et al., 2018). In the North China Plain, most of the feeds for rearing dairy cattle including maize silage, maize straw silage, alfalfa hay, leymus chinensis and commercial concentrate, were transported from other provinces in China (Wang et al., 2018). In our study area, the local dairy farmers used a large amount of free vegetable residues from the vegetable farms. Some other by-product feeds could be obtained nearby so the environmental impacts from transportation were really low in our study area, which might cause lower GWP, AP and EP values although the milk production were lower in this study. In addition, it was suggested that environmental impacts could be decreased by encouraging dairy farmers to return manure to nearby croplands in the North China Plain (Wang et al., 2018), which was consistent with the manure treatment in our study. Hence, the milk production is small but the environment impacts are also lower compared with some other LCA studies. It should be however noted that among the 36 dairy farms, the milk production and environmental impacts were negatively correlated. Emitted enteric methane in the present study accounted for the highest portions of global warming potential, even when compared with several previous studies that noted that enteric methane emissions of cattle were the key contributor to global warming potential (Johnson and Johnson, 1995; Boadi et al., 2004; Wang et al., 2016; Guest et al., 2017; Wang et al., 2018). Ogino et al. (2008) reported that the total contributions to global warming potential, acidification potential and eutrophication potential were 972 g CO2e, 7.13 g SO2e, and 1.23 g PO4e, respectively, with the functional unit as 1 kg of 4% FCM in the dairy system, which were lower than the mean values of our results. However, unlike the dairy system in our study, newborn calves were shipped out immediately after birth in the Japanese dairy farming system (Ogino et al., 2008). Feed production was the important factor in energy consumption among the 36 dairy farms in the study area. Diesel was used for crop production, including corn, sorghum, wheat and barley while electricity and coal were mainly used in manufacture processing, such as beer production and liquor production, which were closely related to the by-product feed production. It should be noted that only four impact categories (GWP, AP, EP and EC) were evaluated in the present study, but other impact categories, such as abiotic depletion, land use and human health toxicity, would be considered for a complete assessment of dairy production in future studies. There have been very few LCA studies of dairy farms focusing on the variation in environmental impacts at a farm scale, and most previous LCA studies (Cederberg and Mattsson, 2000; Thomassen et al., 2008; Ogino et al., 2008; Nguyen et al., 2010) have demonstrated comparisons between different dairy production systems (organic vs. conventional, extensive vs. intensive and dairy-based vs. suckler-based). In this study, the environmental impacts revealed large variations among the 36 dairy farms despite the fact that the data were collected from farms in the same area (Table 6). The different feeding patterns, especially in terms of the amount of each feed, may result in different milk yields and compositions of cows (Jenkins and McGuire, 2006; Prayitno et al., 2017), and the differences may lead to different environmental impacts within a dairy system. Moreover, excessive vegetable residues with high

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water content might cause greater variations in nutrient intake among the different dairy farms in our study area. In the US, an extensive nationwide survey of dairy farms was used to estimate the greenhouse gas emissions from milk production, and the variability in greenhouse gas emissions was analyzed based either on farm size or region (Thoma et al., 2013). The present study suggested that it would be of great importance to investigate the individual environmental impacts of each farm due to the large variations among them. Dairy production at the target farms in the present study was quite distinctive in that beef production is carried out on dairy farms. In general, beef is not a main product for dairy farms in China. Wang et al. (2008) reported that in China, most of the bull calves from dairy herds are slaughtered immediately after birth for the purpose of serum production for medicinal use. Therefore, Wang et al. (2016) assumed in their LCA analysis that bull calves were usually sold immediately after birth in the Guanzhong Plain of China. In contrast, according to our surveys, dairy farmers in our study area explained that their dairy systems could become more profitable when male calves are reared for beef production rather than for sale for serum production after birth. Many byproduct feeds from nearby companies or greenhouses are available for dairy farmers, and farmers can keep surplus calves for beef production owing to sufficient feed scenarios. 4.2. Effects of feeding patterns among farms based on LCA results In some environmental studies, a PCA was used to analyze relationships between environmental criteria. Gutierrez et al. (2010) explored the combined use of the two methods, LCA and PCA, to uncover and visualize the structure of large multidimensional data sets in the context of wastewater treatment plants. In our study, PCA was used to summarize the feeding patterns among 36 farms and to evaluate the effect of differences in feeding patterns on global warming potential, acidification potential, eutrophication potential and energy consumption. The feeding patterns identified by PCA indicated that corn stover and corn silage (PC4) were the key factors in decreasing environmental impacts (Eqs. 6, 7, 8 and 9). The farmers who utilized less corn stover and more corn silage for feeding dairy cattle gained higher milk yields, reflecting that higher productivity in dairy farms could reduce the environmental impacts of dairy production. Several studies have reported a variety of useful methods to improve cow productivity (i.e., genetic improvement, adequate nutritional management, extending lactation and early postpartum treatment) (Grisart et al., 2002; West, 2003; Lehmann et al., 2014; Carpenter et al., 2016). The present study revealed that improving the quality and quantity of the diet for dairy cattle should be the most useful way to mitigate environmental impacts in this study area. Brewers' grains and distillers' grains, which are by-products from beverage industries, were also used as concentrates (Tables 2 and 3). The CO2 emissions from distillers' grains and brewers' grains were 130.6 g/kg and 20.9 g/kg, respectively, after allocation (Table 2). The distillers' grains having higher CO2 emissions than the brewers' grains may be due to the different manufacturing processes with different materials and fuels (Table 2). This result indicates that utilization of by-product feeds, such as brewers' grains, especially in the study area, can be a useful way to reduce the environmental load. As mentioned above, because different feeding patterns caused large variations in environmental impacts among the dairy farms in our study, it could be crucial to conduct proper nutritional planning for dairy production in the study area. Improving farmers' educational levels and increasing experience with rearing dairy cows would help local dairy farmers become aware of the importance of nutritional planning for dairy production. 5. Conclusion The global warming potential, acidification potential, eutrophication potential and energy consumption per kg FPCM of the 36 dairy farms

with by-product feeding in the same dairy production region were estimated by LCA. Although the production processes were almost identical in this area, a large fluctuation in the environmental impacts (GWP, AP, EP and EC) was found among the 36 dairy farms due to the different feeding patterns of the 36 dairy farms. From the PCA results for the feeding patterns, it can be concluded that utilizing the by-product feeds near the study area is the most advantageous for reducing environmental impacts. However, utilization of feeds for dairy cattle without any effective nutritional planning was the main reason for the relatively high global warming potential, acidification potential and eutrophication potential of the 36 dairy farms. Therefore, improving the nutrient management of diets for dairy and beef production is a practical way to decrease negative impacts on the environment. Furthermore, future investigations would be needed to evaluate other impact categories for a complete assessment of dairy farms in the study area. Supplementary data to this article can be found online at https://doi. org/10.1016/j.scitotenv.2019.133985.

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