This article appeared on Teagasc Daily 4th June 2020

Background: Water Quality in Ireland and EU Directives

The European Union (EU) has introduced a number of directives aimed at improving water quality, such as the Nitrates Directive (ND) (91/676/EEC) and Water Framework Directive (WFD) (2000/60/EC). The WFD set out to achieve ‘good status’ in surface waters by2027 at the latest but also aims to ensure that there is no decrease in quality. Nitrogen and phosphorus losses from agriculture have attracted considerable attention. In Ireland, water quality had stabilised and began to improve over the last few decades.

However, the Environmental Protection Agency (EPA) water quality report 2013-2018, showed a 5.5 % net decline in quality of rivers over the period. According to the EPA a total of 53 % of river water bodies were at high or good quality with the remaining 47 % at moderate or worse. The percentage of high-quality monitoring sites was just 17%, down from 32% in the 1987–1990 period, which is a significant decline.

In response to decreasing water quality, the 4th Nitrates Action Programme (NAP) which started in 2017, sees the introduction of additional measures aimed at reducing the overall level of nutrient losses from agriculture. These measures relate to the location of drinking points on farms, spreading of fertiliser, farmyards, roads and cattle exclusion from watercourses (DAFM, 2018).

In addressing climate and environmental needs at local level, voluntary and mandatory measures can be used in a more targeted way. With increasing pressure on the Common Agricultural Policy (CAP) budget and limited resources, EPA funded this study to create a database which can ensure money is spent as efficiently as possible.

The 4th NAP of the Nitrates Directive (ND) requires farms with an allowance (derogation, so called as they derogate from the directive) to farm at a grassland stocking rate over 170 kg N/ha, to prevent cattle from accessing watercourses from January 2021. This 170 kg N/ha relates to the spreading of organic manure or slurry and that deposited by the animals themselves. Five EU member states apply for a derogation from the Nitrates Directive; Belgium (Flanders), UK (Northern Ireland), Denmark, Ireland and Italy (Piedmont and Lombardy). Derogations are reviewed every four years like the Nitrates Directive.

Impact and potential benefits of fencing off watercourses

This research uses Land Parcel Identification System (LPIS) data from the Department of Agriculture, Food and the Marine (DAFM) along with the Ordnance Survey Ireland (OSI) database PRIME2. PRIME2 is the most sophisticated dataset produced by OSI. It contains every building and feature in the country (houses, sheds, roads, field boundaries, rivers, railways).

One of the issues with the LPIS data is that it is not spatially accurate. Field boundaries zig-zag across the landscape. Matching the LPIS with the PRIME2 dataset produced a spatial database SLIDE (Spatial Land Identification Database for Éire), containing all 130,000 farms and over 2 million individual fields in Ireland. The figure shows a sub-sample of the information contained in the SLIDE database.

The objective was first to quantify the total amount of on-farm watercourses in Ireland and secondly using stocking rate, create a measure of potential damage to watercourses arising from livestock dung (and faecal matter), as other studies have found that cattle drinking in streams prefer to defecate in the stream as opposed to in the field.

Studies have estimated that cattle produce on average 23kg of faecal matter daily. If given access to a river, between 7-10% of 23kg will be deposited in-stream. Over the entire grazing season, that would be over 100kg per cow. In addition to the damage caused by the faecal matter, there is the additional damage due to sediment, damage to the riverbank and increased risk of disease.

To judge the effectiveness of a policy, the benefits and costs must be considered. The costs are measured by cost of the fencing and lost area around the riverbank. The benefits are measured by reduced faecal matter deposited in the river. The stocking rate is therefore an important determinant of cost effectiveness, as the more intensive a farm is, the more faecal matter deposited and the greater risk to water courses. The results of the cost benefit analysis show that farms with the highest stocking rates and largest paddocks with access to a watercourse should be prioritized for fencing. Although some areas might have higher amounts of on-farm watercourses, if agricultural intensity is low, the cost effectiveness of fencing is reduced.

These important local differences can only be calculated and identified using highly detailed information as it is not feasible to go through each of the 130,000 farms one by one to identify needs and suitable environmental measures. This is where the use of technology can help. The SLIDE maps can be utilised to identify the areas with the greatest level of cost effectiveness for a particular measure, thus achieving greater impact.

Place based approaches using technology can be used to implement more targeted policies. Rather than using a national approach, we can use large scale datasets to implement more locally relevant policies. One example is fencing of water courses another could be fertiliser application periods.

In 2020, the European Court of Auditors completed an audit in how new imaging technologies can be used to monitor the Common Agricultural Policy (CAP). Normally the LPIS is only updated every 3 years with a need to carry out ground inspections of ~5% of farms (6,500 farms in Ireland). Machine learning algorithms can be used to identify noncompliance reducing the need for random inspections and allow for more targeted inspections. Article

Summary

• The areas where fencing off water courses is most cost effective are located in the south of the country.
• Farm size and shape and farmer characteristics all play a role in determining the level of cost effectiveness of fencing individual farms.
• The study confirms that fencing areas according to agricultural intensity as recommended in the 4th NAP of the Nitrates Directive is a cost effective solution.
• CAP: Move away from one-size-fits-all regulation and incentives for farm management practices.
• Agri-Environmental Schemes: A local approach to regulation and AES design could be more beneficial in ensuring more targeted and efficient use of resources.

The results and findings in this article come from the published article:

Kilgarriff, P., Ryan, M., O’Donoghue, C., Green, S., Ó hUallacháin, D. 2020. Livestock Exclusion from Watercourses: Policy Effectiveness and Implications. Environmental Science and Policy. 106 58-67. https://doi.org/10.1016/j.envsci.2020.01.013

This research was funded by the Environmental Protection Agency (EPA), Ireland as part of the Research Programme 2014–2020 as part of the COSAINT project: Cattle exclusion from watercourses: Environmental and socio-economic implications. The entire report [pdf] can be viewed on the EPA website [1]

[1] DISCLAIMER: Although every effort has been made to ensure the accuracy of the material contained in this journal article, complete accuracy cannot be guaranteed. Neither the Environmental Protection Agency nor the authors accept any responsibility whatsoever for loss or damage occasioned or claimed to have been occasioned, in part or in full, as a consequence of any person acting or refraining from acting, as a result of a matter contained in this journal article.

The slides from my presentation “Change in Artificial Land Use over time across European Cities: A rescaled radial perspective” can be found here.

Workshops

The first workshop was given by Prof. Nick Holliman of Newcastle University looking at data visualisation and exploring the use of Microsoft Power Bi for visualising data. He also presented some of the data currently being collected in the Newcastle Urban Observatory using censors.

The second workshop explored the use of API’s, what they are and how to use them. This workshop was run by researchers from the Newcastle Urban Observatory. Materials from the API workshop can be found here.

The workshop on Wednesday morning was run by Dr. Robin Lovelace and Dr. Nick Bearman and explored mapping in R. Robin presented some materials from his latest book ‘Geocomputation with R’. More details of the book here. Documents and reproducible code from the GIS mapping in R workshop can be found here.

Finally the last workshop was given by Dr. Laura Hanson along with a number of other researchers and spatial analysts from both the private and public sector.

Conference

One of the main trends I picked up from this conference was the use of visual aids and GIF’s created in R. Any of the presentations which used these presented their research in a particularly powerful way. As researchers one of the biggest challenges is presenting our research in a format which is quick and easy to understand. This can be difficult and sometimes require many graphs, figures and tables to get a point across. Such animations present research in a dynamic way.

R code

From an organisational viewpoint the name badges and reusable coffee cup given out at the start of the conference were two welcome features. The name badges made the first name particularly easy to read without a need to strain your eyes while the coffee cups meant a substantial reduction in disposable coffee cup usage given the approximate 200 attendance.

Twitter

An analysis of the tweets from the conferences reveals some interesting trends. It was not surprising to see the term ‘reproducible’ so high up the list. There is a growing number of publications and producing reproducible research along with the code is fast becoming the norm. Representing the code from R or PyQGIS on GitHub alongside the results that appear in the academic article or conference presentation. It is heartening to see such sharing of knowledge in the geocomputation community and will surely only lead to better outcomes in terms of improved research and evidence for policymakers.Code for carrying this out in R can be found in my GitHub here.

Newcastle

One of the most famous features of Newcastle are the seven bridges which cross the River Tyne ranging in both size and age.

There is also the Newcastle castle and gate house. There is a good mixture in this city of both the new with the historic. Nearby Newcastle is situated Durham Cathedral. Construction started in 1093. The cathedral houses the relics of Saint Cuthbert.

The compactness of the city was evident throughput. Public transport also made it very easy to get around with intercity trains, buses and a metro. The city appears to be going from strength to strength.

The conference dinner took place at St. James’s Park home to Newcastle United FC. The pride of the north east (although I am not sure Sunderland or Middlesbrough fans will agree!!) it has been a trophy less period for the magpies over the last couple of decades despite coming close to breaking Manchester United’s dominance in the mid-nineties under Kevin Keegan. An impressive stadium it has a certain character that a lot of modern stadia lack.

The measure of a household’s income should include not only monetary components such as job salary but also non-monetary components and in-kind benefits, such as imputed rent. Imputed rent is the rent an owner can expect to receive were the house on the rental market. Being an owner-occupier does not provide a rental income however, it saves the owner from having to pay market rent. This is turn can increase a household’s potential to consume other products and services.

The measure of a household’s income should include not only monetary components such as job salary but also non-monetary components and in-kind benefits, such as imputed rent. Imputed rent is the rent an owner can expect to receive were the house on the rental market. Being an owner-occupier does not provide a rental income however, it saves the owner from having to pay market rent. This is turn can increase a household’s potential to consume other products and services.

Results show that the imputed cash flows from property ownership decreases the income share of those at the bottom of the income distribution and is inequality increasing, except in the case of those aged 65 +. Spatially the benefits of housing are greatest in urban areas where property values are highest. The small area measurements of imputed rent highlight the dis-equalising impact imputed rent and housing wealth has on inequality; the rich being able to consume more housing and thus have higher imputed rents.

Increases inequality from a Gini of 0.37159 to 0.38595.

A reverse mortgage/annuity (RMA) enables owner-occupiers to use their home as equity to buy an annuity, which provide them with regular payments, without the need to move out or sell the house therefore providing security of tenure. Without including reverse mortgage/annuity in the analysis, the household would leave behind a significant amount of equity,which is then bequeathed to descendants contributing to inequality. Using reverse mortgage/annuity however treats households as separate units as the household will consume the value of the property before death. Households can over consume to make up for periods of under consumption, i.e. when paying a mortgage. Reverse mortgage/annuity has the potential to financially protect households 65 + by acting as an additional pension, they have paid into over the term of the mortgage. The stream of consumption value provided by housing compensates the elderly who are ‘cash poor but asset rich’.

Policy Implications

After accounting for housing costs in the form of rent and mortgage payments and housing benefits in the form of imputed rent and reverse mortgage/annuity, the spatial distribution of welfare changes. On average the income share of the Greater Dublin Area (GDA)increases, however when the movers are examined, the high rents and property values and overall benefits to owner occupiers in the GDA, are masking the high costs young renters face. This highlights the importance of examining issues such as housing inequality at a detailed spatial scale as opposed to aggregate totals. However, overall the net gain to owner-occupiers does not exceed the net loss to non-owner-occupiers and inequality nationally increases. The inequality measures show that overall housing costs and benefits are having a regressive impact on the income distribution with those at the lower end of the income distribution disproportionately affected. The income share of lower groups decreases after net imputed rent.

In terms of policy implications, a tax on imputed rent should be examined which may reduce the inequality between those who own a house and those who are renting. The current LPT is attempting to address this however the tax is levied on all properties, this is despite private renters not receiving the same level of benefits from housing as owner-occupiers.The LPT should account for the variation in housing benefits across the life-cycle. Effective implementation may incentivise those in the older age categories to take out a reverse mortgage/annuity.

Increased uptake of RMA may result in the older age categories consuming the housing wealth as opposed to bequeathing.This can address issues relating to the inequality of inherited wealth. The high rental values particularly in the GDA may hinder an individual’s ability to save and eventually draw down a mortgage. Solutions are required to increase an individual’s potential to save. There are clear benefits to owner-occupation especially for the elderly. If current trends of decreasing home ownership levels continue, future elderly groups will be particularly vulnerable, as they would not have the financial safety net in the form of a housing asset.

Methodology

This study examined the impact of net imputed rent on the distribution of income in a spatial context. The spatial impact of net imputed rent, mortgage payments, private rent, public rent(social housing schemes) and reverse mortgage/annuity on the spatial distribution of disposable income was examined for the year 2011. A spatial microsimulation model, simulated model of the Irish local economy (SMILE), was used to simulated disposable income at a detailed spatial scale. Rental and property values are estimated at a spatial scale adopting the kriging methodology. The created rental and property data were merged into the SMILE simulated dataset to examine the impact of housing on the spatial distribution of disposable income at a small area level.

Funding

This research was funded under the John and Pat Hume Doctoral Awards at Maynooth University.

The SCALE-IT-UP project, funded by the Luxembourg National Research Fund (FNR) under the CORE scheme, will investigate the role of city size, measured in terms of population and artificial land use, on a set of environmental and economic attributes. Re-scaling cities to control for variation in population and land use, allows for relevant comparative analysis. The scaling with population of structural aspects of cities is examined, namely the internal organisation of built-up land, non-built land and transport, thus providing the ability to separate city size effects from urban and transport pattern effects on environmental outcomes.

The outcomes from this project can inform urban policy around how to organise the built, non-built and transport elements of a city in a more sustainable manner, irrespective of city size or given the particularities related to its size. The empirical evidence based on a large set of cities is lacking. This will be a major deliverable of this project. In the mid/longer run, this research should also support urban planning policies by suggesting generic sustainable strategies for organising cities internally and/or adapting these strategies to city size if needs be.

In addition, given that intra-urban and inter-urban are typically analysed separately, this project will bridge this gap, at least from the empirical point of view. Progressing the linkage between urban scaling laws and intra-urban approaches is a second objective of the project. The goal is not “simply” to prove or disprove that cities are “greener as they get bigger”. The goal is to understand how, the relative arrangement of land use, and their conjoint (or differentiated) dispersion from city centres, affect sustainable environmental outcomes.

This research follows on from a previous FNR funded project “ALONSOEU” by Prof.Geoffrey Caruso and Dr. Remi Lemoy.

This research analysed the GMES/Copernicus Urban Atlas 2006 land use data for 300 cities along with Geostat data at a spatially disaggregated scale. Using radial analysis two scaling laws were developed, one for land use and one for population density. A consistent pattern of radial profiles across different city sizes was discovered. In other words, cities of varying sizes have similar land use and population density profiles, this also challenges the claim that larger cities are more efficient in the use of land per capita. This work built upon previous literature which examined population and surface area by extending this to a radial distance profile, thus linking intra-urban radial analysis and systems of cities.

The key paper of this project, on top of which the SCALE-IT-UP project is derived is available at ttps://doi.org/10.1177/2399808318810532

The core project team consists of:

Geoffrey Caruso – Project PI – LISER & University of Luxembourg

Remi Lemoy – Université de Rouen

Paul Kilgarriff – Post-Doc Researcher – LISER

Yufei Wei – PhD candidate – University of Luxembourg

Kerry Schiel – University of Luxembourg

and two other PhD projects are closely connected:

Marlène Boura – University of Luxembourg

Estelle Mennicken – LISER