This chapter analyses the trends of nutrient balances in OECD countries and discusses the role of crop mix, livestock composition, improved practices, technological innovations, and policies on nutrient surpluses. An econometric estimation of the determinants of nutrient balances in OECD countries is undertaken and the policy lessons from Korean and Danish experiences fighting high levels of nutrient surpluses distilled.
Trends and Drivers of Agri‑environmental Performance in OECD Countries
3. Nutrient balances in agriculture
Copy link to 3. Nutrient balances in agricultureAbstract
The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.
Key messages
Copy link to Key messagesSince 2000, OECD countries have on average experienced declining trends in nutrient surpluses. Although almost all OECD countries recorded a decrease in phosphorus surpluses, the picture is mixed in the case of nitrogen due to increased nitrogen fertiliser application rates. For some countries, progress in reducing nutrient surpluses has deteriorated, and nutrient balances have even increased in the last decade.
Reduced phosphorus fertiliser application rates seem to be the main driver of reduced phosphorus surpluses, although livestock, crop-mix changes, and policy interventions are associated with reductions in both nitrogen and phosphorus nutrient balances. Phosphorus fertiliser application rates fell for most OECD countries, possibly as a result of improved farm practices.
In the last decade, the rates of decline in phosphorus surpluses have accelerated while they have decelerated for nitrogen, raising concerns about the ability of OECD countries to maintain nitrogen surpluses reductions in the future.
In several countries that have reduced their nitrogen surpluses, changes in livestock composition and crop mix played a role. In particular, an increase in oil crops as a share of total harvested crops and a decrease in cattle as a share of total livestock significantly reduced nutrient surpluses.
Technological innovations used in precision agriculture have the potential to reduce nutrient surpluses. Enhanced efficiency nitrogen fertilisers can improve crop uptake of nitrogen and reduce the risk of nitrogen leaching. The ultimate environmental impact of these technologies, however, is highly dependent on the type of crop and the biophysical conditions of the farm, as well on other management practices.
Distortionary support policies seem to be associated with larger surpluses, while countries that adopted policies targeting nitrogen pollution also reduced both nitrogen and phosphorus surpluses.
Korea and Denmark show how two different approaches to reducing nutrient surpluses can be effective. Korea has gradually removed distortionary agricultural support polies, while Denmark acted early and persistently to adopt a mix of policies with aligned objectives and clear targets on reducing both nitrogen and phosphorus, combined with monitoring and evaluating the impact of policies to improve their effectiveness.
3.1. The role of nutrients in agriculture and their environmental impacts
Copy link to 3.1. The role of nutrients in agriculture and their environmental impactsPhosphorus (P) and nitrogen (N) are essential nutrients for supporting plant growth. Nitrogen is necessary for protein build-up and phosphorus is required for energy use and transfer (Conley et al., 2009[1]). Nutrient inputs in agriculture are thus fundamental to maintaining and increasing crop and forage productivity (OECD, 2013[2]). Agricultural areas with sustained nutrient deficits may suffer reductions in soil fertility, while nutrient surpluses are likely to contribute to water and air pollution (OECD, 2013[2]; OECD, 2008[3]).
A complex range of physical processes drives the nutrient cycle in the environment (OECD/EUROSTAT, 2012[4]; OECD/EUROSTAT, 2012[5]). Agricultural activities contribute to nutrient build-up and have significantly affected nutrient cycles (Liu et al., 2010[6]). Fertiliser use and manure application are some of the most significant ways agriculture supplies nutrients to the environment. While some of those nutrients are taken up by crops and forage, nutrient inputs exceed nutrient outputs on most agricultural lands, thereby creating nutrient surpluses (Liu et al., 2010[6]; Bouwman, 2013[7]).
Nitrogen is an abundant element in the atmosphere, mainly present in gas form. It is a key nutrient for crop growth, and is added in inorganic fertilisers and manure. It is estimated that 40% to 60% of N fertiliser is absorbed by crops and the remainder is lost in the environment (Sebilo, 2013[8]). Some nitrogen stays in the soil and some volatilises during and shortly after fertiliser applications and manure spreading in the form of ammonia (NH3) and nitric oxide (NO) (Mosier et al., 1998[9]). Ammonia volatilisation also occurs after animal excretion and during storage of livestock manure. Nitrogen is highly mobile and can reach groundwater reservoirs by leaching; it can also reach surface water via runoff.
An excess of nitrogen in surface water leads to excessive plant and algal growth, producing eutrophication. Eutrophic water bodies can suffer biodiversity losses and fish deaths. Nitrate concentrations in groundwater pose risks to livestock and human health. Nitrogen volatilisation contributes to higher concentrations of nitrous oxide (N2O), a potent greenhouse gas, and can lead to soil and water acidification, potentially affecting crop yields and biodiversity (Goulding, 2016[10]).
In contrast to nitrogen, phosphorus sources are naturally limited as phosphorus comes from mineral sources. Phosphorus uptake rates by plants are estimated to be relatively low, between 10% to 15%; the remainder stays in the soil or ends up in water bodies (Roberts, 2015[11]). Phosphorus is relatively immobile so it can remain in the soil for years. Soil P retention depends on several soil characteristics. In many OECD countries, phosphorus application rates have been declining because soils are already P saturated (OECD, 2013[2]).
Phosphorus deficiency in the soil can lead to declining fertility in areas under crop or forage production (OECD, 2008[3]; OECD, 2013[2]). In contrast, a phosphorus surplus is associated with environmental risks as excess P can lead to surface water contamination due to runoff and soil erosion (EUROSTAT, 2017[12]; Bomans E., 2005[13]). While phosphorus concentrations in water do not pose a direct risk to human health, they are an indirect risk as they favour the growth of cyanobacteria and algal blooms in bodies of water. An excess of algae in water bodies diminishes the amount of oxygen available for other organisms and leads to biodiversity losses and fish deaths. Cyanobacteria can produce toxic substances that can affect human and animal health (Chorus, 1999[14]; Hitzfeld, 2000[15]).
3.2. Trends in nutrient balance indicators
Copy link to 3.2. Trends in nutrient balance indicatorsOverall, nutrient surpluses (see description of indicators in Annex 3.A) show a decreasing trend in OECD countries since 1992. From 1992 to 2014, the average nitrogen surplus fell from 85 kg/ha to 67kg/ha (Figure 3.1) and the phosphorus surplus from 13 kg/ha to 6 kg/ha (Figure 3.2). Although almost all countries recorded a reduction in their phosphorus surplus over the analysed period, the picture is more mixed for nitrogen balances.
While the nitrogen surplus in OECD countries overall has decreased since 1992, the pace of the reduction has slowed over the period 2002-14. Australia, Austria, Iceland, Italy, Japan, Latvia, Mexico, Norway, Portugal, Slovak Republic and Turkey even reversed the declining trends seen in the period 1992-2004 and exhibited positive growth rates in the last decade (Figure 3.1). Notably, this happened in countries that already had high levels of N surplus per hectare, such as Japan and Norway.
Since 2002, OECD countries have enhanced their efforts to reduce phosphorus surpluses. The P surplus for OECD countries fell, on average, more quickly in the period 2004-14 (4.1%) than the period 1992-2002 (3%) (Figure 3.2), signalling these increased efforts. Almost all countries exhibited a steeper downward trend in the most recent period analysed. Only a few countries, such as Austria, Iceland, Mexico and Turkey, reversed the reduction they experienced in the 1990s and increased their surpluses per hectare in the 2000s.
Figure 3.1. Nitrogen balance per hectare of agricultural land in OECD countries, 1992-2014
Copy link to Figure 3.1. Nitrogen balance per hectare of agricultural land in OECD countries, 1992-2014
Notes: n.a. Not available. Balance (surplus or deficit) expressed as kg nitrogen per hectare of total agricultural land.
Countries are ranked in descending order according to average annual percentage change 2002-04 to 2012 14.
1. For Portugal, 1992-94 is replaced by 1995-97.
2. For Switzerland, total agricultural area includes summer grazing.
3. The OECD total does not include Chile, Estonia, Hungary and Israel.
4. For the United Kingdom, 1992-94 is replaced by 1995.
5. For Germany, Ireland, Sweden and Switzerland, 2012-14 is replaced by 2011-13.
6. For Estonia, 2002-04 is replaced by 2004-06.
Source: OECD (2018[16]).
Figure 3.2. Phosphorus balance per hectare of agricultural land in OECD countries, 1992-2014
Copy link to Figure 3.2. Phosphorus balance per hectare of agricultural land in OECD countries, 1992-2014
Notes: n.a. Not available. Balance (surplus or deficit) expressed as kg phosphorus per hectare of total agricultural land.
Countries are ranked in descending order of their average annual percentage change 2002-04 to 2012 14.
1. The OECD total does not include Chile, Estonia, Hungary, Israel and Luxembourg.
2. For the United Kingdom, 1992-94 is replaced by 1995.
3. In the case of Switzerland, total agricultural area includes summer grazing.
4. For Germany, Ireland, Sweden and Switzerland, 2012-14 is replaced by 2011-13.
5. For Estonia, 2002-04 is replaced by 2004-06. The average annual percentage change refers to change in phosphorus deficit.
6. For Portugal, 1992-94 is replaced by 1995-97.
7. EU15 does not include Luxembourg.
8. For the Slovak Republic, 1992-94 is replaced by 1993-95.
Source: OECD (2018[16]).
Several countries that significantly reduced the growth rates of N surpluses from the period 1992-2002 to 2002-14 also reduced the growth of P surpluses. For countries such as Canada, France, Greece, Ireland, New Zealand, Slovenia, Spain, and the United States, progress in reducing the growth rates of N surpluses between the first and latest periods analysed has been accompanied by similar progress in P surplus trends.
On average, OECD countries reduced N inputs due to reduced manure inputs and despite increased N inputs from fertiliser. In parallel, crop uptake significantly increased, further lowering the overall N surplus. For most countries that experienced reductions in N surpluses in the period 2002-04 to 2012-14, fertiliser and net inputs of manure also declined. Some countries, such as Canada, Estonia, Hungary, Israel and the United States, increased both inputs and outputs, but the rate of change in N outputs was large enough to compensate for the increase in N inputs (Figure 3.3), leading to overall reductions in N surpluses in those countries.
Figure 3.3. Contribution of specific nitrogen inputs and outputs to total changes in nitrogen surplus, 2002-14
Copy link to Figure 3.3. Contribution of specific nitrogen inputs and outputs to total changes in nitrogen surplus, 2002-14Percentage change between 2002-04 and 2012-14
Note: For EU countries, Norway, the OECD and Switzerland, output category “nutrient removal by crop residues removed from the field” is not shown on the graph.
Source: OECD (2018[16]).
Fertiliser was the main component driving the reduction in P surpluses. Most OECD countries, with the exception of Canada, Latvia, Mexico and Turkey, saw reductions in P inputs in the period 2002-2004 to 2012-2014 (Figure 3.4). Declining fertiliser use and higher P crop uptake explain most of the reductions in P inputs and surplus. Interestingly, most countries that experienced increases in P input also experienced N input growth.
Figure 3.4. Contribution of specific phosphorus inputs and outputs to total changes in phosphorus surplus, 2002-14
Copy link to Figure 3.4. Contribution of specific phosphorus inputs and outputs to total changes in phosphorus surplus, 2002-14Percentage change between 2002-04 and 2012-14
Note: For EU countries, Norway, the OECD and Switzerland, output category “nutrient removal by crop residues removed from the field” is not shown on the graph.
Source: OECD (2018[16]).
3.3. Key drivers of nutrient balance indicators
Copy link to 3.3. Key drivers of nutrient balance indicatorsThis section relates the observed trends in nutrient balances to potential drivers. The existing literature identifies three key drivers: livestock composition, crop mix and the adoption of improved cultivars, agricultural policies, and management practices. For each driver, an attempt is made to empirically relate nutrient balance indicators to variables that reflect those drivers.
Livestock composition and crop mix
Livestock density and livestock composition are relevant to nutrient surpluses. Cattle usually have higher N and P excretion rates (kg per animal) than pigs and poultry (Sebek et al., 2014[17]; Velthof, Hou and Oenema, 2015[18]), with dairy cows having the highest rates among cattle. The crop mix in a given country is another crucial factor, which is in turn influenced by demand and trade policies (Billen, Lassaletta and Garnier, 2015[19]). The N uptake of oil crops is relatively high compared to other crops such as cereals and fruits and vegetables (Zhang et al., 2015[20]).
To better relate changes in the crop mix and livestock composition to changes in inputs and outputs observed in the period 2002-14 (Figure 3.3 and Figure 3.4), t tests of equality of annual growth rates of livestock densities and cropland types over the same period were performed, comparing countries that increased their inputs or outputs, and those that decreased them. Table 3.1 and Table 3.2 display the results for nitrogen and phosphorus respectively.
Countries that increased their N inputs also increased the area under oil crops at a higher rate (6.5% per year) than those that decreased their N inputs (2.7% per year) and the difference is statistically significant at the 5% level (Table 3.1). In the case of N outputs, there were statistically significant differences between the growth rates in the areas cultivating oil crops and fruit and vegetables, as well as livestock densities, between countries that increased versus those that decreased N outputs. Countries that increased N uptake experienced a stronger expansion in the area of oil crop cultivation, a larger decrease in the area of fruit and vegetable cultivation, and a reduction in livestock density, compared to countries that reduced N uptake.
Table 3.1. Differences in livestock density and crop mix for countries that increased versus those that decreased N inputs and outputs
Copy link to Table 3.1. Differences in livestock density and crop mix for countries that increased versus those that decreased N inputs and outputs|
Inputs |
Outputs |
|||||
|---|---|---|---|---|---|---|
|
Change in input/output |
Observations |
Mean of annual growth rates |
Difference (mean decrease-mean increase) |
Observations |
Mean of annual growth rates |
Difference (mean decrease-mean increase) |
|
|
Oil crops (ha) |
Oil crops (ha) |
||||
|
Decrease |
264 |
0.027 |
-0.04** |
168 |
0.011 |
-0.05*** |
|
Increase |
216 |
0.065 |
312 |
0.062 |
||
|
|
Fruit and vegetables (ha) |
Fruit and vegetables (ha) |
||||
|
Decrease |
264 |
-0.002 |
0.02 |
168 |
-0.001 |
0.01*** |
|
Increase |
216 |
-0.022 |
312 |
-0.017 |
||
|
|
Cereals (ha) |
Cereals (ha) |
||||
|
Decrease |
264 |
-0.006 |
-0.006 |
168 |
-0.008 |
-0.007 |
|
Increase |
216 |
0.000 |
312 |
-0.001 |
||
|
|
Livestock heads/ha |
Livestock heads/ha |
||||
|
Decrease |
264 |
0.001 |
0.005 |
168 |
0.008 |
0.01* |
|
Increase |
228 |
-0.004 |
324 |
-0.002 |
||
|
|
Cattle/ha |
Cattle/ha |
||||
|
Decrease |
264 |
0.005 |
0.007 |
168 |
0.008 |
0.006 |
|
Increase |
228 |
-0.002 |
324 |
0.002 |
||
|
|
Chickens/ha |
Chickens/ha |
||||
|
Decrease |
264 |
0.034 |
0.004 |
168 |
0.046 |
0.02 |
|
Increase |
228 |
0.030 |
324 |
0.025 |
||
|
|
Pigs/ha |
Pigs/ha |
||||
|
Decrease |
264 |
0.002 |
0.009 |
168 |
0.006 |
0.01 |
|
Increase |
228 |
-0.007 |
324 |
-0.006 |
||
Notes: Two-tailed t-tests on mean differences of annual growth rates of livestock and crop indicators between the countries that decreased and those that increased N inputs and outputs in the period 2002-14. ***, **, * implies that the difference is different from zero and statistically significant at the 1%, 5% and 10% levels.
Sources: Nitrogen input and output was obtained from OECD (2018[16]) and data on land use and livestock from FAOSTAT (2018[21]).
Similar results are found for changes in P inputs and outputs (Table 3.2). Countries that increased both P inputs and outputs expanded their oil crop cultivation and reduced fruit and vegetable cultivation. They also reduced livestock densities, although the difference is not statistically significant.
Table 3.2. Differences in livestock density and crop mix for countries that increased versus those that decreased P inputs and outputs
Copy link to Table 3.2. Differences in livestock density and crop mix for countries that increased versus those that decreased P inputs and outputs|
|
Inputs |
Outputs |
||||
|---|---|---|---|---|---|---|
|
Change in input/output |
Observations |
Mean of annual growth rates |
Difference (mean decrease-mean increase) |
Observations |
Mean of annual growth rates |
Difference (mean decrease-mean increase) |
|
|
Oil crops (ha) |
Oil crops (ha) |
||||
|
Decrease |
336 |
0.027 |
-0.057*** |
168 |
0.013 |
-0.047*** |
|
Increase |
144 |
0.084 |
312 |
0.060 |
||
|
|
Fruit and vegetables (ha) |
Fruit and vegetables (ha) |
||||
|
Decrease |
336 |
-0.006 |
0.01** |
168 |
0.002 |
0.019*** |
|
Increase |
144 |
-0.024 |
312 |
-0.018 |
||
|
|
Cereals (ha) |
Cereals (ha) |
||||
|
Decrease |
336 |
-0.006 |
-0.008 |
168 |
-0.008 |
-0.007 |
|
Increase |
144 |
0.002 |
312 |
-0.001 |
||
|
|
Livestock heads/ha |
Livestock heads/ha |
||||
|
Decrease |
348 |
0.003 |
0.005 |
168 |
0.007 |
0.008 |
|
Increase |
144 |
-0.002 |
324 |
-0.001 |
||
|
|
Cattle/ha |
Cattle/ha |
||||
|
Decrease |
348 |
0.006 |
0.006 |
168 |
0.007 |
0.004 |
|
Increase |
144 |
-0.001 |
324 |
0.002 |
||
|
|
Chickens/ha |
Chickens/ha |
||||
|
Decrease |
348 |
0.037 |
0.016 |
168 |
0.048 |
0.02 |
|
Increase |
144 |
0.021 |
324 |
0.024 |
||
|
|
Pigs/ha |
Pigs/ha |
||||
|
Decrease |
348 |
-0.004 |
-0.007 |
168 |
0.003 |
0.01 |
|
Increase |
144 |
0.003 |
324 |
-0.005 |
||
Notes: This table shows the results of two-tailed t-tests on mean differences of annual growth rates of livestock and crop indicators between countries that decreased and those that increased P inputs and outputs in the period 2002-14. ***, **, * implies that the difference is different from zero and statistically significant at the 1%, 5% and 10% levels.
Sources: Nitrogen input and output was obtained from OECD (2018[16]) and data on land use and livestock from FAOSTAT (2018[21]).
Countries that experienced increases in both N inputs and outputs reduced the area devoted to fruit and vegetables and increased that devoted to oil crops. Considering these patterns can both generate increases in nutrient inputs and outputs, the effect on the balance is unclear. Livestock changes also seem to play an important role in changing nutrient inputs and outputs. A further investigation into the situation in Canada can help to illustrate these developments. Canada is one of the few countries where nutrient surpluses declined despite increases in fertiliser inputs (Figure 3.1 and Figure 3.4).
The evolution of Canada’s livestock composition and crop mix since the 1990s illustrates the relevance and complexity of such drivers. Canada’s N surplus per hectare grew by an average 8.2% per year in the 1990s, but fell by 0.5% a year in the 2000s, while P surpluses went from an annual growth of 5.3% to an annual reduction of 13.7% over the same period. Most of this decline can be explained by a combination of changes in livestock density, livestock composition, crop mix, and improved cultivars. The number of cattle as a share of the total number of livestock fell 30% between 1992 and 2014, and harvested oil crops as a share of total harvested crops increased 210% over the same period (Figure 3.5). Farmers have also adopted cultivars with more efficient nutrient uptakes, reducing the need for fertiliser while improving yields (Han et al., 2015[22]; Iqbal et al., 2016[23]; Morrison et al., 2016[24]; De Bruin and Pedersen, 2009[25]). Most of these changes occurred over the last decade; over the 2002-14 period, livestock density decreased on average 1.6% per year, mainly due to a reduction in cattle heads (Figure 3.5).
Figure 3.5. Canada’s agricultural sector produces more oil crops and less cattle, 1992-2014
Copy link to Figure 3.5. Canada’s agricultural sector produces more oil crops and less cattle, 1992-2014
Note: Oil crops and total harvested crops are measured in cultivated hectares.
Source: OECD (2018[16]).
Policy instruments
Agricultural policies can affect environmental outcomes by influencing production patterns, farming practices, and input use (Henderson and Lankoski, 2019[26]). An OECD evaluation of agricultural support policies on the environment found that market price support and payments based on input use appear to consistently increase nitrogen runoff, while payments based on non-current area (cultivated area in previous seasons) and decoupled payments in general seem to have no impact on nutrient balances (Henderson and Lankoski, 2019[26]). As well as general forms of support to agriculture, countries have multiple policies that deal with nutrient surpluses and their impact on water quality, including limits on fertiliser application and livestock density, guidelines for manure application, taxes and subsidies, voluntary schemes, information-based policies, water quality trading, co-operative agreements, and natural-capital-based nutrient allocations (OECD, 2012[27]; OECD, 2017[28]). Countries also have a diverse policy mix in terms of the types of policies they adopt and their geographical scope. This is not surprising considering nutrient pollution sources from agriculture are difficult to identify (nonpoint); a mix of policies and regulatory approaches are often more effective than a single policy at tackling non-point source pollution (OECD, 2010[29]; OECD, 2017[28]).
While there is no “one-size fits all” policy, some attributes of policies can improve the effectiveness of the policy mix, such as monitoring and enforcing the policy, or appropriate targeting (OECD, 2010[29]; OECD, 2017[28]; OECD, 2017[30]). Targeting addresses questions about who and to what degree a regulation should apply. Poorly targeted policy instruments are likely to be ineffective at tackling nutrient balance surpluses, which are mainly generated locally.
An example of a targeted policy is the Nitrate Vulnerable Zones (NVZs) policy mandated by the European Union (EU) Nitrates Directive (OECD, 2017[28]) and, by definition, confined to EU countries. NVZs are those land areas that drain into polluted waters or water sources at risk of nitrate pollution if no action is taken. EU Member States are required to declare NVZs and revise and update them every four years. States that implement a national action program covering all its territory to tackle nitrogen pollution are not required to designate NVZs. Austria, Denmark, Finland, Germany, Ireland, Lithuania, Luxembourg, Malta, the Netherlands, and Slovenia, as well as the region of Flanders and Northern Ireland have implemented action programs. For the rest of EU Member countries, NVZs have been progressively expanded over time and by 2015 covered on average 30% of their respective territories (Figure 3.6). In some cases, however, there have been delays in the implementation of policies (OECD, 2018[31]).
Figure 3.6. Designated nitrate vulnerable zones as submitted by EU Member States
Copy link to Figure 3.6. Designated nitrate vulnerable zones as submitted by EU Member States
Note: Countries that followed a whole-territory approach to NVZs are excluded from this figure.
Source: (OECD, 2018[31]).
Farmers in NVZs must comply with measures included in the Codes of Good Agricultural Practice. Although each individual EU Member State defines these practices, they must include “measures limiting the periods when nitrogen fertilisers can be applied on land in order to target application to periods when crops require nitrogen and prevent nutrient losses to waters; measures limiting the conditions for fertiliser application (on steeply sloping ground, frozen or snow covered ground, near water courses, etc.) to prevent nitrate losses from leaching and run-off; requirement for a minimum storage capacity for livestock manure; and crop rotations, soil winter cover, and catch crops to prevent nitrate leaching and run-off during wet seasons” (European Commission, 2018[32]). The application of both fertiliser and livestock manure is limited in NVZs; in the case of fertiliser, it is based on crop needs and all N inputs into the soil, while manure is limited to 170 kg nitrogen/hectare/year including both manure spreading and direct application by grazing animals.
In order to empirically relate nutrient balances to agricultural policies (both general and targeted at addressing N pollution), as well as livestock and cropland types, an econometric analysis was carried out to correlate agriculture, economic and policy variables with N and P balances (Table 3.3). The analysis considered two types of policy variables: those specifically addressing nitrogen issues and those affecting all agriculture. Policies directly addressing nutrient pollution are represented by variables that take a value of one for the period when a given country applied a national program to tackle nitrogen pollution “NVZ (whole country)” or a program in a specific territory “NVZ (partial region)”. Agriculture support figures were obtained from Anderson and Valenzuela (2008[33]) and are divided into distortionary policies (labelled “coupled support”) and decoupled policies (labelled “decoupled payments”). The former include market price support and subsidies linked to input or production, while the latter represent support not linked to current production, inputs or area of production.1 Livestock and cropland mix variables were included to control for the composition of the sector. To assess the impact of the level of development of a given country, per capita gross domestic product (GDP) was also included as an explanatory variable.
Table 3.3. The role of livestock, crop mix and agricultural policies on nutrient balances
Copy link to Table 3.3. The role of livestock, crop mix and agricultural policies on nutrient balances|
N per ha |
P per ha |
|||
|---|---|---|---|---|
|
Controls |
Model 1 |
Model 2 |
Model 1 |
Model 2 |
|
GDP per capita |
0.144 |
0.107 |
1.176* |
0.491 |
|
(0.129) |
(0.139) |
(0.618) |
(0.610) |
|
|
Nitrate Vulnerable Zone (whole country) |
-0.280*** |
-0.224*** |
-0.443*** |
-0.300** |
|
(0.058) |
(0.048) |
(0.145) |
(0.135) |
|
|
Nitrate Vulnerable Zone (partial region) |
-0.013 |
0.036 |
-0.138 |
0.028 |
|
(0.059) |
(0.051) |
(0.135) |
(0.126) |
|
|
Coupled support |
0.112*** |
0.078*** |
0.206*** |
0.122** |
|
(0.024) |
(0.025) |
(0.056) |
(0.055) |
|
|
Decoupled payments |
-0.007 |
0.005 |
0.015 |
0.023 |
|
(0.017) |
(0.012) |
(0.048) |
(0.037) |
|
|
Oil crops (share of cultivated area) |
0.133* |
0.163 |
||
|
(0.067) |
(0.100) |
|||
|
Cereals (share of cultivated area) |
0.174 |
0.683 |
||
|
(0.193) |
(0.430) |
|||
|
Fruit and Vegetable (share of cultivated area) |
-0.124 |
0.062 |
||
|
(0.124) |
(0.240) |
|||
|
Cattle (heads per hectare) |
0.308** |
0.354 |
||
|
(0.139) |
(0.329) |
|||
|
Poultry (heads per hectare) |
0.080 |
0.653*** |
||
|
(0.074) |
(0.219) |
|||
|
Pigs (heads per hectare) |
0.161 |
0.356 |
||
|
(0.102) |
(0.260) |
|||
|
Trend |
0.004 |
-0.004 |
-0.050*** |
-0.062*** |
|
(0.007) |
(0.005) |
(0.018) |
(0.018) |
|
|
Year fixed effect |
Yes |
Yes |
Yes |
Yes |
|
Country fixed effect |
Yes |
Yes |
Yes |
Yes |
|
Observations |
566 |
545 |
524 |
504 |
|
R-squared |
0.332 |
0.410 |
0.495 |
0.554 |
|
Number of countries |
35 |
34 |
34 |
33 |
Notes: Coefficients were estimated using a fixed effects model and robust standard errors are presented in parenthesis. *, ** and *** represent statistically significant coefficients at the 10%, 5% and 1% levels, respectively. All variables were transformed to logarithms, except for NVZs, which are dummy variables that take a value of 1 when a given country declared NVZs. Due to data availability for policy variables, the sample covers 1990-2011.
Sources: N and P balances were obtained from the OECD (2018[16]). Coupled and decoupled support variables were obtained from Anderson and Valenzuela (2008[33]), livestock and cropland composition variables were downloaded from FAOSTAT (2018[21]), and GDP per capita from the World Bank Development Indicators Database (World Bank, 2018[34]). NVZs dummies were constructed from the information provided by the Nitrates Directive (European Commission, 2018[32]).
The analysis estimated two econometric models for each nutrient balance: Model 1 includes only economic and policy controls and Model 2 adds livestock and cropland composition explanatory variables. The main results suggest that:
For countries that declared NVZs, both NVZ variables (whole country and partial regions) are associated with decreased nutrient balances per hectare. However, only the whole-country NVZ approach is statistically significant in both specifications (declaring a whole-country NVZ is associated with a 22% decrease in N balance and a 30% decrease in P balance).2 Considering only EU countries have NVZ policies, the NVZ finding does not imply that other forms of policy interventions that non-EU countries may have enacted were not effective; to the extent that other countries’ N policies are omitted from the analysis, the fact that the NVZ coefficient is statistically significant reflects that NVZ policies tend to stand out compared to other countries’ policies.3 Interestingly, while NVZs mostly target N, they also seem to affect P, possibly to the fact that regulations in NVZs, are also likely to impact P surpluses
Distortionary forms of agriculture support are positively associated with increases of both surpluses in a statistically significant way (a 1% increase in this form of support is associated with a 0.07% increase in N balance and a 0.12% increase in P balance), decoupled support has no statistically significant association with balances.
Oil crops are positively associated with N balance and this association is statistically significant at the 10% level: a 1% increase in the oil-crop cultivation area is associated with a 0.13% increase in N balance; while they are also positively associated with P balance, the coefficient is not statistically significant.
Livestock density, particularly cattle density, has a strong and positive association with N balances (a 1% increase in cattle density is associated with a 0.3% increase in N balance), while poultry density is associated with P balances (a 1% increase in poultry density is associated with a 0.7% increase in P balance). Livestock density is highly associated with the intensification of livestock operations, which has been on the rise globally, contributing to an increase in animal production (Liu et al., 2010[35]). Highly intensive livestock operations rely on concentrated feed and are less dependent on open-range feeding (Bouwman, 2013[7]). While intensive operations tend to lead to more efficient nutrient uptake by individual animals, at the livestock system scale, once the cultivation of feed crops has been taken into account, the efficiency gains from those systems are not clear (Bouwman, 2013[7]). These systems face additional challenges such as the handling of large amounts of manure and, when established in areas with limited amounts of agricultural land, few possibilities for its reuse.
Improved farm management practices
The reduction in P surpluses observed in the majority of OECD countries in the last two decades can be partly associated with higher rates of soil testing in farms (Figure 3.2). Through soil testing in areas such as Western Europe, which have historically had persistently high rates of P applications, farmers have recognised that they can reduce P application rates without compromising yields (Schoumans, 2015[36]).
Soil testing is part of a group of practices branded “improved farm management practices” or “best management practices” (BMPs), which aim to decrease the environmental and health impacts from agricultural activities while maintaining farm productivity. There are a large variety of BMPs, from practices that require significant effort, like introducing conservation tillage and crop rotation, to simple actions like avoiding the application of manure when rain is forecast (Sharpley et al., 2006[37]). Consequently, the economic cost of implementing different BMPs can vary substantially, depending on their scope and complexity. Big structural changes, like implementing manure storage systems, are usually more expensive than more basic measures, such as choosing the right time for manure application (Sharpley et al., 2006[37]); establishing livestock watering systems away from stream corridors can be comparably more costly than creating grass or forest buffers (Shortle et al., 2013[38]). Moreover, the implementation of BMPs will also vary according to the type of farm and the geographic condition where the farm is located (Shortle et al., 2013[38]).
Best management practices for applying fertiliser are usually linked to the 4R Principles: right rate, right timing, right source and right placement. The International Plant Nutrition Institute (2007[39]) summarises these principles as follows:
Right rate: Assess and make decisions based on soil nutrient supply and plant needs.
Right timing: Assess and make decisions based on the dynamics of crop uptake, soil supply, nutrient loss risks and field operation logistics.
Right source: Ensure a balanced supply of essential nutrients, considering both naturally available sources and the characteristics of specific products.
Right placement: Address root-soil dynamics and nutrient movement, and manage spatial variability within the field to meet site-specific crop needs and limit potential losses from the field.
Soil testing is crucial for reducing nutrient application rates and it is directly related to the “right rate” principle. Other BMPs such as conservation tillage, conservation crop rotation and cover crops can also reduce nutrient surpluses (OECD, 2016[40]). Numerous previous studies have found positive impacts from BMPs in reducing nitrate leaching and improving water quality. For instance, pre-sidedress nitrate tests4 have significantly reduced post-harvest residual soil nitrates (NO3) in cornfields (Durieux et al., 1995[41]; Justes et al., 2012[42]). Similarly, conservation tillage practices have resulted in reduced NO3 leaching when compared with conventional tillage (Randall and Iragavarapu, 1995[43]; Weed and Kanwar, 1996[44]). Other studies have shown that the use of cover crops during the inter-growing season has led to lower residual soil NO3 and reduced leaching in corn and other field crops (McCracken et al., 1994[45]; Mary et al., 1999[46]; Justes et al., 2012[42]). New technologies emerging in the agriculture sector can facilitate BMPs and, therefore, affect nutrient balances (Box 3.1).
Other technological developments include enhanced efficiency N fertilisers (EEFs) which release N at a slower rate than conventional fertilisers or delay the N transformation processes by using inhibitors or coating materials. These can improve crop uptake of N and reduce the risk of N leaching, but their performance depends on the type of crop and the biophysical conditions of the farm, as well on management practices. EEFs can be categorised into four types (Li et al., 2018[47]): 1) urease inhibitors, which delay urea hydrolysis, thus lowering ammonia emission potential; 2) nitrification inhibitors, which reduce the activities of nitrifying bacteria, thereby reducing the risks of nitrate leaching and nitrous oxide emission; 3) double inhibitors, which are designed to lower ammonia, nitrate and nitrous oxides emission losses by combining urease and nitrification inhibitors; and 4) polymer-coated fertilisers, which use partially permeable coating material to control N release. According to a meta-analysis of studies conducted from 1970 to 2016, urease inhibitors and polymer-coated fertilisers were the most effective EEFs for reducing ammonia emissions (Pan et al., 2016[48]). Double inhibitors were most effective in increasing yields and improving nitrogen uptake when applied on grassland, while EEFs were in general less effective in wheat and maize systems (Li et al., 2018[47]). While EEFs can potentially increase yields and reduce environmental risks, their effectiveness is highly dependent on farm management practices (Li et al., 2018[47]).
Box 3.1. The potential impact of precision agriculture on nutrient pollution
Copy link to Box 3.1. The potential impact of precision agriculture on nutrient pollutionPrecision agriculture aims to monitor and improve the financial performance of farms at within-field resolution by providing detailed information on site-specific yield, nutrient recovery and income (Wong, M.; Asseng, H.; Zhang, H., 2005[49]). Recovery of nutrients can be used to evaluate and manage environmental risk such as nitrate leaching (Ortega and et al., 2003[50]). Some of the most important groups of technologies used in precision agriculture are:
Geographic Information Systems (GIS): Software to manage spatial data
Global Positioning Systems (GPS): Provides topographical information used by GISs
Remote sensors: Cameras on satellites and airplanes to identify the characteristics of a given area
In situ sensors: Electronic devices to measure soil properties, pests, crop health, etc.
Yield monitoring: Measures the crop yield during harvest, providing a yield map with information on production and variability
Variable rate technology: It applies inputs according to specific needs at a precise location (Joint Research Centre (JRC) of the EC, 2014[51]; OECD, 2016[40]; OECD, 2019[52]).
GIS and GPS technology
Field studies have shown that site-specific in-season adjustments of fertiliser inputs to account for climatic conditions and varying yield potential differences increase fertiliser nitrogen use efficiency up to 368% compared with common farming practices (Diacono, 2013[53]). When sensors are used with GPS, and GIS is used to produce prescription maps (e.g. for guiding variable fertiliser or irrigation applications), the extra cost savings can be over 10-20%, depending on the inherent variability and need for variable inputs in a given field (Diacono, 2013[53]). Research has also shown that the use of GPS (“autosteer”) in farm machinery can increase the efficiency of nutrient use by 5-10% (Craighead and Yule, 2001[54]). GPS-based guidance systems with automatic controls allow farmers to precisely apply inputs by both modulating the quantities and by reducing nutrient usage in no-application areas and can therefore generate positive environmental effects (Bongiovanni and Lowenberg-Deboer, 2004[55]).
Variable rate technologies
Thoele and Ehlert (2010[56]) analysed the potential impact of using a mechanical crop biomass sensor (“crop meter”). They found that its use improved N efficiency by 10-15%, and reduced N fertiliser applications without reducing crop yields. Other studies (Anselin, Bongiovanni and Lowenberg-DeBoer, 2004[57]; Meyer-Aurich et al., 2010[58]) concluded that site-specific management of nitrogen fertiliser leads to improvements on N efficiency by 10-15%. Applying at variable rates may not necessarily result in lower fertiliser application rates, however (Dillon and Kusunose, 2013[59]). A similar mixed picture can be found among country experiences with variable rate applications of nitrogen (Lawes, 2011[60]; Boyer et al., 2011[61]; Olesen et al., 2004[62]; Biermacher et al., 2009[63]).
Remote sensors
Mounted in satellites or aircraft, sensors have the potential to produce relevant data for improving the environmental performance of agricultural activities (OECD, 2019[52]). The most relevant applications for agriculture are monitoring crop yield, biomass, crop nutrient and water stress, and detection of pests and soil properties (Mulla, 2013[64]). These technologies have the potential to improve the effectiveness of agri-environmental policies and the quality and scope of agri-environmental indicators (OECD, 2018[16]; OECD, 2019[52]).
3.4. Policy lessons from Korea and Denmark
Copy link to 3.4. Policy lessons from Korea and DenmarkThis section delves further into the role that policies play in decreasing nutrient inputs in soils by describing the approaches of two OECD countries, Korea and Denmark, that best illustrate this.
Korea
Removing some of the most distortionary agricultural subsidies not only creates efficiency gains but can also help reduce environmental pressures. Korea experienced the largest decrease in N fertiliser inputs from 2002 to 2014 in the OECD (Figure 3.7). Decoupling farmers’ payments from input use was one of the main reasons behind this change. Nevertheless, Korea still faces significant challenges in dealing with high input levels from manure.
The Korean government has implemented a variety of measures to reduce the overuse of chemical fertilisers. In 1990, it liberalised the sale of agricultural chemicals by progressively reducing domestic subsidies.5 Although some restrictions on domestic sales of formulated products by foreign companies remained, these were removed at the end of 1999 (OECD, 1999[65]). Since the 2000s, Korea has framed its policies within specific targets. Through the Environmentally Friendly Agriculture Fostering Act, enacted in 1997, the Korean government has established policy plans every five years, starting in 2001, to promote “environmental friendly agriculture”. This is defined as a type of agriculture that does not use “chemical materials, such as synthetic agricultural chemicals, chemical fertilisers, antibiotics and antimicrobials, or that minimises the use of such materials, while maintaining and preserving the agricultural ecosystem and environment by recycling by-products of agriculture, fisheries, stock breeding or forestry” (Ministry of Agriculture, Food and Rural Affairs, 2015[66]).
In particular, the plans focus on promoting the safe and appropriate use of agricultural chemicals, setting maximum limits for chemical residues and effluent from livestock excretion, encouraging compliance with fertiliser application rates for each crop, banning the dumping of agricultural waste, and establishing requirements for converting animal excretion into solid and liquid manure. They also define a framework for certifying environmentally friendly agricultural products and establish direct payments to compensate for reduced yields that result from adopting environmentally friendly farming practices (OECD, 2008[67]). For example, a policy objective in the most recent five-year plan (2016-20) is to reduce the quantity of chemical fertilisers and pesticides by 9% relative to 2014 levels.
The Korean government began to decrease subsidies for chemical fertilisers in 1996, and these have now been completely eliminated. This policy change was the main reason for the reduction in chemical fertiliser use over the last decade (Korean Fertilizer Association, 2015[68]), and manure is now the main nutrient input into soils (Figure 3.7).
However, the rapid transformation of the Korean agriculture sector over the last five decades has been driven mainly by new patterns of food consumption: meat consumption increased from 5.2 kg per person in 1970 to 46.8 kg in 2015, and consumption of dairy products increased from 1.6 kg per person in 1970 to 75.7 kg in 2015 (OECD, 2018[69]). As a consequence, the livestock sector experienced the sharpest growth in the country’s agriculture sector from 1970 to 2013; the value of livestock products increased from 15% of total agricultural production to 46% over that period (OECD, 2018[69]). To cope with the increasing demand for meat and dairy products, livestock density has increased, leading to greater environmental pressures per unit of land.
While Korea has successfully lowered fertiliser use, mainly by eliminating fertiliser subsidies, manure management remains a challenge. Korea has the largest nitrogen surplus per hectare among OECD countries (Figure 3.2) and the second largest phosphorus surplus per hectare (Figure 3.3). Since the size of the livestock industry keeps growing while the total area of cropland keeps declining, the management of an excess supply of manure is a pressing issue. The Livestock Excretion Management and Use Act passed in 2007 promotes the recycling of manure, mainly to produce and use solid/liquefied fertiliser and energy (Gruère, Ashley and Cadilhon, 2018[70]). While the programme got off to a slow start, chemical fertiliser is increasingly being replaced by recycled manure to deal with the environmental pressures derived from livestock waste.
Figure 3.7. Evolution of nitrogen and phosphorus inputs in Korea, 1985-2015
Copy link to Figure 3.7. Evolution of nitrogen and phosphorus inputs in Korea, 1985-2015Kg/ha
Denmark
Acting early, defining clear nutrient pollution reduction targets, constant monitoring and evaluation of policies, and a coherent policy mix can yield sustained reductions in nutrient surpluses while improving the performance of agriculture. Denmark is one of the few OECD countries that has simultaneously experienced an expansion in agricultural production and a decline in nutrient balance surpluses since the 1990s. Underlying this success is a long history of adopting, monitoring and evaluating regulations, as well as combining a wide range of command-and-control, market-based, voluntary, and information regulations.
Denmark’s nitrogen and phosphorus balances per hectare have consistently fallen since the 1990s while agricultural production has exhibited steady growth (Figure 3.8). Denmark and the Netherlands are the only OECD countries that have achieved significant nutrient balance reductions and steady agricultural production growth in the last two decades. Moreover, despite having one of the most developed environmental regulation systems in the world (Grinsven et al., 2012[71]), agricultural exports account for more than double its domestic consumption (FAO, 2014[72]) and more than 60% of Denmark’s land area is used for agriculture.
Denmark acted early to monitor and combat nitrogen pollution. High nitrogen concentrations were detected in groundwater used for household consumption during the 1980s, and surveys and monitoring of oxygen concentrations in the Danish marine waters indicated an increase in the frequency of oxygen depletion events (Kronvang et al., 2008[73]). Since the early 1980s, multiple regulations have been implemented via the Action Plans for Aquatic Environment (1987, 1998, and 2004), Sustainable Agriculture (1990 and 1996) and Green Growth (2009) policies. The Danish policy mix falls into three categories (Dalgaard et al., 2014[74]): command and control measures, market-based regulations, and information and voluntary action. In particular, the policy mix often includes targets for both reductions of N and P discharges, includes fertiliser accounting systems, N quota systems which regulate the use of fertilisers, bans on manure application on bare fields, fertiliser taxes for non-agricultural uses, taxes on phosphorus content in feed, agri-environmental schemes, and advisory services (OECD, 2018[69]).
Figure 3.8. Agricultural production and nutrient balances in Denmark, 1990-2015
Copy link to Figure 3.8. Agricultural production and nutrient balances in Denmark, 1990-2015
Sources: Nitrogen and phosphorus balance were obtained from OECD (2018[16]); agricultural production index from FAOSTAT (2018[21]).
While Denmark has a multiplicity of regulatory instruments in place, they all contribute to the achievement of clear and well-established targets defined in the action plans. More importantly, even though targets are not always reached, constant monitoring and evaluation of plans and policies have been key to improving the effectiveness of policies (OECD, 2018[69]; Tan and Mudgal, 2013[75]). Since the 1990s, with the implementation of environmentally sensitive areas (ESAs), Denmark has also started to move towards geographically targeted regulations, which tend to be more cost-effective.
References
[33] Anderson, K. and E. Valenzuela (2008), Estimates of Global Distortions to Agricultural Incentives, 1955 to 2007, World Bank, http://dx.doi.org/www.worldbank.org/agdistortions.
[57] Anselin, L., R. Bongiovanni and J. Lowenberg-DeBoer (2004), “A spatial econometric approach to the economics of site-specific nitrogen management in corn production”, American Journal of Agricultural Economics, Vol. 86/3, pp. 675-687, http://dx.doi.org/10.1111/j.0002-9092.2004.00610.x.
[63] Biermacher, J. et al. (2009), “The economic potential of precision nitrogen application with wheat based on plant sensing”, Agricultural Economics, Vol. 40, pp. 397–407, http://dx.doi.org/10.1111/j.1574-0862.2009.00387.x.
[19] Billen, G., L. Lassaletta and J. Garnier (2015), “A vast range of opportunities for feeding the world in 2050: Trade-off between diet, N contamination and international trade”, Environmental Research Letters, Vol. 10/2, http://dx.doi.org/10.1088/1748-9326/10/2/025001.
[13] Bomans E., F. (2005), Addressing phosphorus related problems in farm practice, Final report to the European Commission. Soil Service of Belgium.
[55] Bongiovanni, R. and J. Lowenberg-Deboer (2004), “Precision agriculture and sustainability”, Precision Agriculture, Vol. 5/4, pp. 359-387, http://dx.doi.org/10.1023/B:PRAG.0000040806.39604.aa.
[7] Bouwman, L. (2013), “Exploring global changes in nitrogen and phosphorus cycles in agriculture induced by livestock production over the 1900-2050 period”, PNAS, Vol. 110/52, pp. 20882-20887.
[61] Boyer, C. et al. (2011), “Profitability of variable rate nitrogen application in wheat production”, Precision Agriculture, Vol. 12/4, pp. 473-487, https://doi.org/10.1007/s11119-010-9190-5.
[14] Chorus, I. (1999), Toxic cyanobacteria in water: A guide to their public health consequences, monitoring and management, E & FN Spon, London.
[1] Conley, D. et al. (2009), “Controlling Eutrophication: Nitrogen and Phosphorus”, Science, Vol. 323/5917, pp. 1014-1015, http://dx.doi.org/10.1126/science.1167755.
[54] Craighead, M. and I. Yule (2001), “Opportunities for increased profitability from precision agriculture”, Geospatial Information and Agriculture, http://www.regional.org.au/au/gia/13/439yule.htm.
[74] Dalgaard, T. et al. (2014), “Policies for agricultural nitrogen management—trends, challenges and prospects for improved efficiency in Denmark.”, Environmental Research Letters, Vol. 9/11, http://dx.doi.org/10.1088/1748-9326/9/11/115002.
[25] De Bruin, J. and P. Pedersen (2009), “Growth, Yield, and Yield Component Changes among Old and New Soybean Cultivars”, Agronomy Journal, Vol. 101/1, p. 124, http://dx.doi.org/10.2134/agronj2008.0187.
[53] Diacono, M. (2013), “Precision nitrogen management of wheat. A review”, Agronomy for Sustainable Development, Vol. 33/1, https://doi.org/10.1007/s13593-012-0111-z.
[41] Durieux, R. et al. (1995), “Implications of nitrogen management strategies for nitrate leaching potential: Roles of nitrogen source and fertilizer recommendation system”, Agronomy Journal, Vol. 87/5, pp. 884-887, http://dx.doi.org/10.2134/agronj1995.00021962008700050017x.
[32] European Commission (2018), Nitrates Directive, http://ec.europa.eu/environment/water/water-nitrates/index_en.html.
[12] EUROSTAT (2017), Agri-environmental indicator - risk of pollution by phosphorus:, http://ec.europa.eu/eurostat/statistics-explained/index.php/Agri-environmental_indicator_-_risk_of_pollution_by_phosphorus#cite_note-6.
[72] FAO (2014), The State of Food and Agriculture, FAO publications, Rome.
[21] FAOSTAT (2018), Food and agriculture data, http://www.fao.org/faostat/en/#home.
[10] Goulding, K. (2016), “Soil acidification and the importance of liming agricultural soils with particular reference to the United Kingdom”, Soil Use and Management, Vol. 32/3, pp. 390–399, https://doi.org/10.1111/sum.12270.
[71] Grinsven, V. et al. (2012), “Management, regulation and environmental impacts of nitrogen fertilization in northwestern Europe under the Nitrates Directive: a benchmark study”, Biogeosciences, 9(12), 5143-5160., Vol. 9/12, pp. 5143-5160, https://doi.org/10.5194/bg-9-5143-2012.
[70] Gruère, G., C. Ashley and J. Cadilhon (2018), “Reforming water policies in agriculture: lessons from past reforms”, OECD Food, Agriculture and Fisheries Papers 113, https://doi.org/10.1787/1826beee-en.
[22] Han, M. et al. (2015), “The Genetics of Nitrogen Use Efficiency in Crop Plants”, Annual Review of Genetics, Vol. 49/1, pp. 269-289, http://dx.doi.org/10.1146/annurev-genet-112414-055037.
[26] Henderson, B. and J. Lankoski (2019), “Evaluating the environmental impact of agricultural policies”, OECD Food, Agriculture and Fisheries Papers, No. 130, OECD Publishing, Paris, https://dx.doi.org/10.1787/add0f27c-en.
[15] Hitzfeld, B. (2000), “Cyanobacterial Toxins: Removal during Drinking Water Treatment, and Human Risk Assessment”, Environ Health Perspect, Vol. 1/1, pp. 8113–122, https://doi.org/10.2307/3454636.
[39] International Plant Nutrition Institute (2007), Right product, right rate, right time and right place… the foundation of best management practices for fertilizer, http://www.ipni.net/publication/bettercrops.nsf/0/91607AF3210A609F852579800080C01C/$FILE/Better%20Crops%202007-4%20p14.pdf.
[23] Iqbal, M. et al. (2016), “Genetic Improvement in Grain Yield and other Traits of Wheat Grown in Western Canada”, Crop Science, Vol. 56/2, p. 613, http://dx.doi.org/10.2135/cropsci2015.06.0348.
[59] J.V., S. (ed.) (2013), Dispelling misperceptions regarding variable rate application, Wageningen Academic Publishers, https://doi.org/10.3920/978-90-8686-778-3_95.
[51] Joint Research Centre (JRC) of the EC (2014), Precision Agriculture: An Opportunity for EU farmers- Potential support with the CAP 2014-2020, https://www.europarl.europa.eu/RegData/etudes/note/join/2014/529049/IPOL-AGRI_NT%282014%29529049_EN.pdf.
[42] Justes, E. et al. (2012), Réduire les fuites de Nitrate au moyen de cultures intermédiaires, https://oatao.univ-toulouse.fr/16383/11/Justes_16383.pdf.
[68] Korean Fertilizer Association (2015), Statistical Yearbook of Fertiliser.
[73] Kronvang, B. et al. (2008), “Effects of policy measures implemented in Denmark on nitrogen pollution of the aquatic environment”, Environmental Science & Policy, Vol. 11/2, pp. 144-152, https://doi.org/10.1016/j.envsci.2007.10.007.
[60] Lawes, R. (2011), “Whole farm implications on the application of variable rate technology to every cropped field”, Field Crops Research, Vol. 124/2, pp. 142-48, https://doi.org/10.1016/j.fcr.2011.01.002.
[47] Li, T. et al. (2018), “Enhanced-efficiency fertilizers are not a panacea for resolving the nitrogen problem”, Global Change Biology, http://dx.doi.org/10.1111/gcb.13918.
[6] Liu, J. et al. (2010), “A high-resolution assessment on global nitrogen flows in cropland”, PNAS, Vol. 107/17, pp. 8035-8040, https://doi.org/10.1073/pnas.0913658107.
[35] Liu, J. et al. (2010), “A high-resolution assessment on global nitrogen flows in cropland”, PNAS, Vol. 107/17, pp. 8035–8040.
[46] Mary, B. et al. (1999), “Calculation of nitrogen mineralization and leaching in fallow soil using a simple dynamic model”, European journal of soil science, Vol. 50/4, pp. 549-566, https://doi.org/10.1046/j.1365-2389.1999.00264.x.
[45] McCracken, D. et al. (1994), “Nitrate leaching as influenced by cover cropping and nitrogen source”, Soil Science Society of America Journal, Vol. 58/5, pp. 1476-1483, http://dx.doi.org/10.2136/sssaj1994.03615995005800050029x.
[58] Meyer-Aurich, A. et al. (2010), “Optimal site-specific fertilization and harvesting strategies with respect to crop yield and quality response to nitrogen”, Agricultural Systems, Vol. 103/7, pp. 478-485, http://dx.doi.org/10.1016/j.agsy.2010.05.001.
[66] Ministry of Agriculture, Food and Rural Affairs (2015), Act on the promotion of environment-friendly agriculture and fisheries and the management of and support for organic foods, http://elaw.klri.re.kr.
[24] Morrison, M. et al. (2016), “Canola yield improvement on the Canadian Prairies from 2000 to 2013”, Crop and Pasture Science, Vol. 67/4, p. 245, http://dx.doi.org/10.1071/CP15348.
[62] Mosier, A. and J. Freney (eds.) (2004), “Integrated nitrogeninput systems in Denmark”.
[9] Mosier, A. et al. (1998), “Closing the global N2O budget : nitrous oxide emissions through the agricultural nitrogen cycle inventory methodology”, Nutrient Cycling in Agroecosystems, Vol. 52/2–3, pp. 225–248, https://doi.org/10.1023/A:1009740530221.
[64] Mulla, D. (2013), “Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps”, Biosystems Engineering, http://dx.doi.org/10.1016/j.biosystemseng.2012.08.009.
[52] OECD (2019), Digital Opportunities for Better Agricultural Policies, OECD Publishing, Paris, https://dx.doi.org/10.1787/571a0812-en.
[16] OECD (2018), Agri-environmental indicators, http://dx.doi.org/www.oecd.org/agriculture/sustainable-agriculture/agri-environmentalindicators.htm.
[31] OECD (2018), Agri-environmental indicators, http://www.oecd.org/tad/sustainable-agriculture/agri-environmentalindicators.htm.
[69] OECD (2018), Innovation, Agricultural Productivity and Sustainability in Korea, OECD Food and Agricultural Reviews, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264307773-en.
[28] OECD (2017), Diffuse Pollution, Degraded Waters: Emerging Policy Solutions, OECD Studies on Water, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264269064-en.
[30] OECD (2017), Water Risk Hotspots for Agriculture, OECD Studies on Water, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264279551-en.
[40] OECD (2016), Farm Management Practices to Foster Green Growth, OECD Publishing, Paris, https://doi.org/10.1787/22229523.
[2] OECD (2013), OECD Compendium of Agri-environmental Indicators, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264186217-en.
[27] OECD (2012), Water Quality and Agriculture: Meeting the Challenge, OECD Studies on Water, OECD Publishing, http://dx.doi.org/10.1787/22245081.
[29] OECD (2010), Guidelines for Cost-effective Agri-environmental Policy Measures, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264086845-en.
[3] OECD (2008), Environmental Performance of Agriculture in OECD Countries Since 1990, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264040854-en.
[67] OECD (2008), Evaluation of Agricultural Policy Reforms in Korea, OECD, Paris, http://www.oecd.org (accessed on 26 February 2018).
[65] OECD (1999), Review of Agricultural Policies: Korea 1999: National Policies and Agricultural Trade, OECD Publishing, Paris., http://dx.doi.org/10.1787/9789264172623-en.
[4] OECD/EUROSTAT (2012), OECD/EUROSTAT Nitrogen Balance Handbook, OECD Publishing.
[5] OECD/EUROSTAT (2012), OECD/EUROSTAT Phosphorus Balance Handbook, OECD Publishing.
[50] Ortega, R. and et al. (2003), patial variability of wine grape yield and quality in Chilean vineyards: Economic and environmental impacts.
[48] Pan, B. et al. (2016), “Ammonia volatilization from synthetic fertilizers and its mitigation strategies: A global synthesis”, Agriculture, Ecosystems and Environment, http://dx.doi.org/10.1016/j.agee.2016.08.019.
[43] Randall, G. and T. Iragavarapu (1995), “Impact of long-term tillage systems for continuous corn on nitrate leaching to tile drainage.”, Journal of Environmental Quality, Vol. 24/2, pp. 360-366, http://dx.doi.org/10.2134/jeq1995.00472425002400020020x.
[11] Roberts, T. (2015), “Phosphorus use efficiency and management in agriculture”, Resources, Conservation and Recycling, Vol. 105, pp. 275–281, https://doi.org/10.1016/j.resconrec.2015.09.013.
[36] Schoumans, O. (2015), “Phosphorus management in Europe in a changing world”, Ambio, Vol. 44/2, pp. S180-92, https://doi.org/10.1007/s13280-014-0613-9.
[17] Sebek, L. et al. (2014), Nitrogen and phosphorous excretion factors of livestock, Livestock Research, Wageningen University.
[8] Sebilo, M. (2013), “Long-term fate of nitrate fertilizer in agricultural soils”, PNAS, Vol. 110/45, pp. 18185-9, https://doi.org/10.1073/pnas.1305372110.
[37] Sharpley, A. et al. (2006), Best Management Practices To Minimize Agricultural Phosphorus Impacts on Water Quality, United States Department of Agriculture, ARS-163(July).
[38] Shortle, J. et al. (2013), Building Capacity to Analyze the Economic Impacts of Nutrient Trading and Other Policy Approaches for Reducing Agriculture’s Nutrient Discharge into the Chesapeake Bay Watershed Executive Summary, USDA, https://www.usda.gov/oce/environmental_markets/files/EconomicTradingCBay.pdf (accessed on 15 May 2018).
[75] Tan, A. and S. Mudgal (2013), DYNAMIX policy mix evaluation Reducing fertiliser use in Denmark, http://dynamix-project.eu/sites/default/files/Fertilisers_Denmark.pdf.
[56] Thoele, H. and D. Ehlert (2010), “Biomass Related Nitrogen Fertilization with a Crop Sensor”, Applied Engineering in Agriculture, Vol. 26/5, http://dx.doi.org/10.13031/2013.34937.
[18] Velthof, G., Y. Hou and O. Oenema (2015), “Nitrogen excretion factors of livestock in the European Union: A review”, Journal of the Science of Food and Agriculture, https://doi.org/10.1002/jsfa.7248.
[44] Weed, D. and R. Kanwar (1996), “Nitrate and water present in and flowing from root-zone soil”, Journal of Environmental Quality, Vol. 25/4, pp. 709-719, http://dx.doi.org/10.2134/jeq1996.00472425002500040010x.
[49] Wong, M.; Asseng, H.; Zhang, H. (2005), Precision agriculture improves efficiency of nitrogen use and minimises its leaching at within-field to farm scales.”, In 5th European Conference on Precision Agriculture.
[34] World Bank (2018), World Development Indicators, http://datatopics.worldbank.org/world-development-indicators/.
[20] Zhang, X. et al. (2015), “Managing nitrogen for sustainable development”, Nature, Vol. 528/7580, pp. 51-59, http://dx.doi.org/doi:10.1038/nature15743.
Annex 3.A. Nutrient balance indicators
Copy link to Annex 3.A. Nutrient balance indicatorsNutrient balance indicators can act as a signal for the potential environmental impact of agriculture on water and air. The OECD agricultural nutrient balance indicators are gross balances. They are calculated at the national level, and measure the difference between the total quantity of nutrient inputs entering an agricultural system (mainly fertilisers and livestock manure), and the quantity of nutrient outputs leaving the system (mainly the uptake of nutrients by crops and grassland) (OECD/EUROSTAT, 2012[4]; OECD/EUROSTAT, 2012[5]). In the case of nitrogen, the gross nutrient balance includes all emissions of environmentally harmful nitrogen compounds from agriculture into the soil, water and the air, while the net balance excludes air emissions (OECD/EUROSTAT, 2012[4]). In the case of phosphorus, there are no air emissions so the gross balance is the same as the net balance (Figure 3.A.1).
Gross balances are expressed in kilogrammes of nutrient surplus per hectare of agricultural land per annum. It is important to bear in mind that these indicators are proxies for environmental pressures at the national level, and do not consider sub-national differences. There are several limitations that could limit cross-country comparisons of nutrient balance levels such as the precision and accuracy of the underlying nutrient conversion factors and the uncertainties involved in estimating nutrient uptake by pasture areas and some fodder crops (OECD, 2013[2]).
Annex Figure 3.A.1. Main components of the gross nitrogen and phosphorus balance calculation
Copy link to Annex Figure 3.A.1. Main components of the gross nitrogen and phosphorus balance calculationNotes
Copy link to Notes← 1. While the OECD Producer Support Estimate database is more accurate and can be divided in different categories of support, it was not possible to use it for this exercise as EU support is reported as an aggregate, so all the variability needed to identify the effects of other policies would have been lost.
← 2. The lack of a statistically significant coefficient on NVZ (Partial region) should not be considered as a reason to argue against the effectiveness of the partial territory approach, as it may be explained by the fact that the dependent variable is a crude whole-country measure of the nitrogen balance and it could be masking improvements in specific regions within countries that have declared regional NVZs.
← 3. To test the robustness of these findings, the specifications were estimated only for EU countries and the results did not change the main conclusions.
← 4. A soil nitrate test used to determine if additional fertiliser nitrogen is needed for corn.
← 5. In the case of pesticides, subsidies were supplied through the National Agricultural Co-operatives Federation (NACF). As for fertilisers, from 1982 to 1994, the government subsidised their prices through the Agricultural Chemicals Account (OECD, 1999[65]).