Modeling Vienna’s traffic: air pollution and health

By Anneke Brand, IIASA science communication intern 2016.

Accidents, lane closures, and congestion all affect the flow of road traffic and harmful emissions from vehicles. Live traffic data allow congestion to be detected more accurately and provide a more precise overview of vehicle emissions at different times and places. In his project for the Young Scientists Summer Program (YSSP), Fabian Heidegger investigates how road traffic affects air pollution in cities, using Vienna and surrounding areas as a case study.

Air pollution is a major problem in Europe and globally. Health impacts of air pollution include a range of respiratory and cardiovascular diseases. “10-20% of Europe’s urban population is exposed to excessive levels of nitrogen dioxide (NO2), along with several other air pollutants. NO2 pollution is highest along busy roads. Technical measures have so far often been circumvented, so cities are looking for other measures to reduce the pollution load. Traffic management has therefore gained interest as a way to reduce air pollution,” says Jens Borken-Kleefeld, Heidegger’s study leader at IIASA.

To calculate the amount of air pollution that cars and other vehicles release into the air, researchers use models that apply various sets of data: traffic networks, where and how far people drive, and emission factors of different vehicle categories. Input data for the model may include how many people live in a certain area, how many of them use cars, where they normally drive, and how many grams of pollutants (such as nitric oxide and NO2 gases) their type of cars emit per kilometer.

© Radub85 | Dreamstime.com

Inner city Vienna. © Radub85 | Dreamstime.com

Most of these models rely on average daily traffic data. For Heidegger’s YSSP project, which is related to his PhD work at the University of Natural Resources and Life Sciences  in Vienna, he is incorporating real-time data, measured every five minutes, into a traffic simulation model developed by Intelligent Transport Systems Vienna Region. A set of detectors in and around the city record the number and speed of vehicles. In addition, location data from the taxi fleet is incorporated into the traffic simulation. Heidegger can therefore immediately identify adverse traffic conditions like stop-and-go traffic, which has a high impact on emissions. This allows for a more accurate calculation and can help design traffic interventions for improving both traffic flow and air quality.

“In the case of a road closure, local emissions will obviously be lower at the specific road but total emissions for the area could be higher than before when drivers use alternative, longer routes or end up in stop-and-go traffic,” says Heidegger.

In order to understand how these diversions and the displacement of pollutants can affect overall emissions, Heidegger will first determine the emissions per street section, and second, what the effects are of diversions from day-to-day traffic patterns. Together with researchers from the Air Quality and Greenhouse Gases Program at IIASA, Heidegger plans to assess the impact of different intervention scenarios, for example an environmental zone in the city, where only modern cars will be allowed to enter. In a second scenario he will look at the effect of people commuting to Vienna, and a third scenario will explore the consequences of expanding pedestrian zones. The researchers hope that this study will better their understanding of the potential of traffic management to reduce air pollution.

 

More information

Air Pollution Policy Review 2011-2013

GAINS Model

AIR Program

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

 

Interview: Plants and their fungi to slow down climate change

César Terrer, participant in the IIASA 2016 Young Scientists Summer Program, and PhD student at Imperial College London, recently made a groundbreaking contribution to the way scientists think about climate change and the CO2 fertilization effect. In this interview he discusses his research, his first publication in Science, and his summer project at IIASA.

Conducted and edited by Anneke Brand, IIASA science communication intern 2016.

César Terrer ©Vilma Sandström

César Terrer ©Vilma Sandström

How did your scientific career evolve into climate change and ecosystem ecology?
I studied environmental science in Spain and then I went to Australia, where I started working on free-air CO2 enrichment, or FACE experiments. These are very fancy experiments where you fumigate a forest with CO2 to see if the trees grow faster. In 2014 I moved to London for my PhD project. There, instead of focusing on one single FACE experiment, I collected data from all of them. This allowed me to make general conclusions on a global scale rather than a single forest.

You recently published a paper in Science magazine. Could you summarize the main findings?
We found that we can predict how much CO2 plants transfer into growth through the CO2 fertilization effect, based on two variables—nitrogen availability and the type of mycorrhizal, or fungal, association that the plants have. The impact of the type of mycorrhizae has never been tested on a global scale—and we found that it is huge. I think it’s fascinating that such tiny organisms play such a big role at a global scale on something as important as the terrestrial capacity of CO2 uptake.

How did you come up with the idea? One random day in the shower?
Long story short, researchers used to think that plants will grow faster, and take up a lot of the CO2 we emit. They assumed this in most of their models as well. But plants need other elements to grow besides CO2. In particular, they need nitrogen. So scientists started to question whether the modeled predictions overestimated the CO2 fertilization effect, because the models did not consider nitrogen limitation. To find out, I analyzed all the FACE experiments and indeed I saw that in general plants were not able to grow faster under elevated CO2 and nitrogen limitation. However, in some cases plants were able to take advantage of elevated CO2 even under nitrogen limitation. I grouped together the experiments where plants could grow under nitrogen limitation and after a lot of reading I saw what they had in common: the type of fungi! It turned out that one type of mycorrhizae is really good at transferring large quantities of nitrogen to the plant and the other type is not.

How did that feel?
Awesome! When I saw the graph, I knew: this is going to be important. Of course, after this, my coauthors helped me to polish the story. Without them, the conclusions would not be as robust and clear.

So how does this process work? Where do the fungi get the nitrogen from?
Particular soils might have a lot of nitrogen, but the amount available for plants to absorb might be low. Also, plants have to compete with non-fungal microorganisms for nitrogen. So if there is not much there, the microorganisms take it all. It’s called immobilization. Instead of mineralizing nitrogen, they immobilize it so that plants cannot take it up, at least not in the short term. Some types of fungi are much more efficient in accessing nitrogen, and associated with roots they allow plants to overcome limitations.

Nitrogen mobilization abilities of different types of fungi. Growth of plants associated with fungi not beneficial for nitrogen uptake (illustrated as grass roots on the left) could be limited by low nitrogen availability in soil. Other plants have the advantage of increased nitrogen uptake due to their beneficial association with certain types of fungi (illustrated as yellow mushrooms connected to the roots of the tree on the right). ©Victor O. Leshyk.

Nitrogen mobilization abilities of different types of fungi. Growth of plants associated with fungi not beneficial for nitrogen uptake (illustrated as grass roots on the left) could be limited by low nitrogen availability in soil. Other plants have the advantage of increased nitrogen uptake due to their beneficial association with certain types of fungi (illustrated as yellow mushrooms connected to the roots of the tree on the right). ©Victor O. Leshyk.

What is the impact of your findings?
Plants currently take up 25-30% of the CO2 we emit, but the question is whether they will be able to continue to do so in the long term. Our findings bring good and bad news. On the one hand, the CO2 fertilization effect will not be limited entirely by nitrogen, because some of the plants will be able to overcome nitrogen limitation through their root fungi. But on the other hand, some plant species will not be able to overcome nitrogen limitation.

There was a big debate about this. One group of scientists believed that plants will continue to take up CO2 and the other group said that plants will be limited by nitrogen availability. These were two very contrasting hypotheses. We discovered that neither of the hypotheses was completely right, but both were partly true, depending on the type of fungi. Our results could bring closure to this debate. We can now make more accurate predictions about global warming.

What will you do at IIASA and how will you link it to your PhD?
I want to upscale and quantify how much carbon plants will take up in the future. If we are to predict the capacity of plants to absorb CO2, we need to quantify mycorrhizal distribution and nitrogen availability on a global scale. We are updating mycorrhizal distribution maps according to distribution of plant species. We know for instance that pines are associated with ectomycorrhizal fungi and always will be. To quantify nitrogen availability we use maps of different soil parameters that are available on a rough global scale.

© Adam Edwards | Dreamstime.com

© Adam Edwards | Dreamstime.com

About César Terrer
Prior to his PhD, Terrer studied at the University of Murcia in Spain and the University of Western Sydney in Australia.

Currently he is a member of the Department of Life Sciences at Imperial College London, UK. For this study he collaborated with researchers from the University of Antwerp, Northern Arizona University, Indiana University and Macquarie University.

In the IIASA Young Scientists Summer Program, Terrer works together with Oskar Franklin from the Ecosystem Services and Management Program and Christina Kaiser from the Evolution and Ecology Program.

Further reading

 

Note: This article gives the views of the interviewee, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

How coordination can boost the resilience of complex supply chains

By Célian Colon, PhD student at the Ecole Polytechnique in France & IIASA Mikhalevich award winner

How can we best tackle risks in our complex and interconnected economies? With globalization and information technologies, people and processes are increasingly interdependent. Great ideas and innovations can spread like wildfire. However, so can turbulence and crises. The propagation of risks is a key concern for policymakers and business leaders. Take the example of production disruption: with global supply chains, local disasters or man-made accidents can propagate from one place to another, and generate significant impact. How can this be prevented?

Risk propagation is like a domino effect. Credit: Martin Fisch (cc) via Flickr

Risk propagation is like a domino effect. Credit: Martin Fisch (cc) via Flickr

As part of my PhD research, I met professionals on the ground and realized that supply risk propagation is a particularly tricky issue, since most parts of the chains are out of their control. Supply chains can be very long, and change with time. It is difficult to keep track of who is working with whom, and who is exposed to which hazard. How then can individual decisions mitigate systemic risks? This question directly connects to the deep nature of systemic problems: everyone is in the same boat, shaping it and interacting with each other, but no one is individually able to steer it. Surprising phenomena can emerge from such interactions, wonderfully illustrated by bird flocking and fish schooling.

As an applied mathematician thrilled by such complexities, I was enthusiastic to work on this question. I built a model where firms produce and interact through supply chain relationships. Pen and paper analyses helped me understand how a few firms could optimally react to disruptions. But to study the behavior of truly complex chains, I needed the calculation power of computers. I programmed networks involving a large number of firms, and I analyzed how localized failures spread throughout these networks, and generate aggregate losses. Given the supply strategy adopted by each firm, how could systemic risk be mitigated?

With my collaborators at IIASA, Åke Brännström, Elena Rovenskaya, and Ulf Dieckmann, we have highlighted the key role of coordination in managing risks. Each individual firm affects how risks propagate along the chain. If they all solely focus on maximizing their own profit, significant amounts of risk remain. But if they cooperate, and take into account the impact of their decisions on the risk profile of their trade partners, risk can be effectively mitigated. Reducing systemic risks can thus be seen as a common good: costs are heterogeneously borne by firms while benefits are shared. Interestingly, even in long supply chains, most systemic risks can be mitigated if firms only cooperate with only one or two partners. By facilitating coordination along critical supply chains, policy-makers can therefore contribute to the reduction of risk propagation.

Colon's model analyzes how firms produce and interact through supply chain relationships. Credit: Jan Buchholtz (cc) via Flickr

Colon’s model analyzes how firms produce and interact through supply chain relationships. Credit: Jan Buchholtz (cc) via Flickr

Drawing robust conclusions from such models is a real challenge. On this matter, I benefited from the experience of my IIASA supervisors. Their scientific intuitions greatly helped me focusing on the most fertile ground. It was particularly exciting to borrow techniques from evolutionary ecology and apply them to an economic context. Conceptually, how economic agents co-adapt and influence each other shares many similarities with the co-evolution of individuals in an ecological environment. To address such complex issues, I strongly believe in the plurality of approaches: by illuminating a problem from different angles, we can hope to see it more clearly!

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

Climate change, bioenergy, and ozone in the EU

By Carlijn Hendriks, Netherlands Organization for Applied Scientific Research (TNO) & IIASA Peccei award winner

Last summer, I participated in IIASA’s Young Scientist Summer Program, working with the Mitigation of Air Pollution and Greenhouse Gases and Ecosystems Services and Management programs. My research focused on what impacts the EU climate and air quality policy could have on ground level ozone around the middle of this century. While clean air policies should help reduce the pollution that can lead to ozone formation, we found that that climate change and energy policies will still increase ozone concentrations and damage by mid-century, unless stricter air pollution measures are implemented.

Ozone forms through reactions of various pollutants - a process that speeds up at higher temperatures. © Damián Bakarcic via Flickr

Ozone forms through reactions of various pollutants and chemicals in the atmosphere – a process that speeds up at higher temperatures. © Damián Bakarcic via Flickr

Ozone at ground level is an air pollutant, causing health and ecosystem problems. It is also an important component of summer smog. Ozone is not emitted into the atmosphere directly, but is produced when volatile organic carbons are oxidized in the presence of  nitrogen oxides and light. Nitrogen oxides are released into the atmosphere mainly as a result of combustion processes (like car engines and industry), while non-methane volatile organic carbons (NMVOCs)  come in large part from vegetation, especially broad-leaf trees and some fast-growing crops.

Part of the EU energy policy is to stimulate the use of sustainable biomass as an energy source. This could lead to expansion of commercial bioenergy crop production in plantations and an increasing use of  forests. While this may help to reduce greenhouse gas emissions, it will also increase NMVOC emissions. At the same time, EU air quality policies aim to reduce emissions of air pollutants such as nitrogen oxides and man-made NMVOC. Because some steps in the ground level ozone formation process are driven by absorption of light and/or proceed faster with higher temperatures, climate change could lead to higher ground level ozone concentrations in the future.

The separate effects of these three trends on ground level ozone have been studied before, but the question remains: what will be the combined impact of a) an increase of bioenergy plantations, b) EU’s air quality policy and c) climate change on health and ecosystem damage from ground level ozone? And which of the trends is the most important? To answer these questions, I used three models to study two energy and air quality scenarios for Europe under current and possible future climate conditions.

Two energy scenarios calculated by the Price-Induced Market Equilibrium System (PRIMES) model form the basis of this work. We used a reference scenario and one in which Europe reaches 80% CO2 emission reduction in 2050. These energy scenarios were used as a basis to calculate air pollutant emissions with IIASA’s  Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model. Then we put the same scenarios into IIASA’s Global Biosphere Model GLOBIOM to obtain the change in land cover because of increasing bioenergy demand. I combined these datasets in chemistry transport model LOTOS-EUROS (the model of choice at my home institute, TNO) to calculate the impact on ground level ozone concentrations across Europe. To simulate ‘future climate’ we used the year 2003, in which Europe had a very warm summer, with temperatures 2-5 °C higher than normal.

Difference in average ozone concentration (in µg/m3) between the current situation and the 80% CO2 reduction scenario in 2050 under future climate change conditions for the period April-September. Negative numbers mean a decrease in ozone levels.

Difference in average ozone concentration (in µg/m3) between the current situation and the 80% CO2 reduction scenario in 2050 under future climate change conditions for the period April-September. Negative numbers mean a decrease in ozone levels.

We found that especially for the CO2-reduction scenario, the increase in bioenergy production could cause a slight increase in ozone damage. However, the impact of reduced emissions because of more stringent air quality policies far outweighs this effect, leading to a net reduction of ozone damage. The third effect, more efficient ozone formation in a warming climate, is so strong that in 2050 ozone damage to human health could be worse than today, especially for northwestern Europe. Stringent air quality policies close to a maximum feasible reduction scenario would be needed to make sure that health and ecosystem damage towards the middle of the century is smaller than it is today.

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

This summer in Moscow: Impressions from Moscow Summer Academy 2015

By M. Nazli Koseoglu, MSA 2015 Participant, School of Geosciences, Environmental Economics, Edinburgh University, Scotland

M. Nazli Koseoglu

M. Nazli Koseoglu

The Summer Academy on Economic Growth and Governance of Natural Resources took place at Lomonosov Moscow State University from 20th July to 1st August 2015.

As an environmental economist working on economic valuation and optimisation of water use, the academy was very interesting for me. Water management is a dynamic process and requires bringing perspectives and expertise from different disciplines together. Application of systems analysis enables us to combine aspects from various domains, come up with models that identify nonlinearities, project regime shifts, and tipping points in the management of water as well as other natural resources. Such projects require interdisciplinary collaboration and communicable results to inform policy. Scientists need to translate their results to a language accessible to the policymakers, in order for society to pick up on and capitalize on the research efforts. The MSA 2015 provided me with necessary training to go deeper into different modelling methodologies, and learn the concepts and principles of science for policy first-hand from IIASA scientists.

The reading list sent before the course gave me the impression that I would probably be the only environmental economist amongst a crowd of mathematical modellers. However, arriving in Moscow, I found that the MSA 2015 participants came from a broad range of backgrounds and countries at different stages of their careers in academia or policy. We all came  to learn and discuss the natural resource constraints to infinite economic growth on finite planet.

During lectures, the theoretical foundations of different mathematical approaches such as dynamical systems theory, optimal control theory and game theory were presented by leading scientists, such as Michael Ghil. Fundamentals of addressing challenges of natural resource management and comparing contemporary models of economic growth were also covered as central themes.

The course acknowledged the issues related with ecosystems services, public goods, inter-generational and international fairness, and public and common pool resource dynamics in the face of economic growth and resource constraints. The training underlined feedbacks between institutional dynamics and resource dynamics in complex social-ecological system and need for interdisciplinary and policy-relevant research, an important take-home message for next generation scientists.

Photos by M. Nazli Koseoglu

Photos by M. Nazli Koseoglu

What makes the MSA so special?
Apart from lectures, we had tutorials, a group project, poster and project presentation sessions, as well as interesting talks on IIASA activities by Margaret Goud-Collins and Elena Rovenskaya, and an inspiring session on the importance of finding the right mentor for a successful career by Prof Nøstbakken. The  MSA 2015 program had a good balance of theory and practice, which encouraged participants to be proactive and engaged.

I particularly liked the poster session. We presented our ongoing projects and received feedback from the lecturers and other participants. It was great to get comments and perspectives that I never thought of, and tips from senior researchers. In the late days of the academy we were assigned to prepare a group project on Artic systems which allowed us to put what we had learned at the lectures into practice and apply important topics outside our exact fields of study; in my case, these topics were petroleum economics and artic futures. I found the multi-disciplinary group work to be a great exercise for the development of my current study.

Attending the MSA 2015 provided useful training, both theoretical and practical, for understanding systems analysis approaches better. The host institution and organizing committee at Lomonosov Moscow State Univesrity provided impeccable hospitality, and the setting, in a landmark building in a landmark city, was a great perk. I received very constructive feedback, and made good connections around the world. I would recommend all early-career researchers in relevant fields to take this great opportunity next summer!

More information about MSA 2015

Participants in the MSA 2015. Photo Credit: M. Nazli Koseoglu

Participants in the MSA 2015. Photo Credit: M. Nazli Koseoglu

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied

Systems Analysis.