The lowest hanging fruit on the coconut tree: India's climate transition through the price system in the power sector

by Akshay Jaitly and Ajay Shah.

The world is projected to emit about 50GT of CO2 per year by 2055. Climate scientists say (net) emissions need to be ended by 2055, in order to avoid catastrophic events with reasonable probability. At present, India is emitting 2.5GT per year with a long term trend growth rate of about 5%. India is the 4th largest source of CO2 in the world, accounting for 7\% of emissions, with emissions that are roughly as large as those of the European Union. In a new paper, The lowest hanging fruit on the coconut tree: India’s climate transition through the price system in the power sector, we engage in strategic thinking about India's decarbonisation.

Decarbonising any economy is a large and complex problem. The electricity sector is a key site of the carbon transition, as it directly makes CO2 (e.g. by burning coal and gas), and because decarbonisation in other areas (e.g. cooking) involves switching away from fossil fuels to electricity. The sector is formally organised, which makes it more susceptible to policy intervention. Thus, in every country, decarbonisation calls for a large modification of the resource allocation in the electricity sector. Technical and business model decisions are required at each location in an economy about the optimal mix of renewables, storage and demand-side adjustment for the zero emissions world.

The Indian electricity sector is poorly placed to perform the required modification of this resource allocation. At present, it is a centrally planned system that is under growing financial stress. The process of private investment in electricity has lost momentum. Resource allocation is inefficient owing to multiple prices and a command-and-control system, rather than one based on producers and users that respond to prices. The command-and-control system works poorly in steady state, and particularly poorly when large changes in the resource allocation are required. By imposing enlarged costs upon the economy, a centrally planned decarbonisation runs the risk of greater political difficulties. The electricity sector is thus the critical choke point in India's climate transition.

Looking forward, the problems of the electricity sector are likely to deepen. Rising Indian emissions in coming years will sit uneasily alongside a decarbonising world. Regardless of the speed at which Indian policy makers might desire a change in course, there are forces reshaping the behaviour of Indian firms which are narrowing the options. Indian firms now operate under international asset pricing, and ESG investment has changed the incentives of Indian firms to favour buying and selling renewables. Some large economies could, in coming years, introduce trade taxes upon the carbon content of Indian exports. This would additionally induce Indian firms to desire reducing emissions in their supply chain. The cross-subsidy system within the electricity sector will come under increasing stress when buyers see renewables inducing some combination of a lower cost of capital, a lower operating cost and reduced trade barriers.

For 30 years now, political and fiscal resources have been expended in periodic incremental reforms of the electricity sector. These have not delivered the desired results. It is unlikely that similar efforts will work in coming years. In the meantime, 2021 is likely to be a turning point in the demands made upon the electricity sector owing to the carbon transition.

The climate transition is one of the most complex problems in Indian public policy and will now be subject to the new commitments made at COP26. A coherent strategy needs to be established and articulated, which can reshape the behaviour of a billion private persons across space and time.

This involves going with the grain of the price system, i.e. stepping away from the command-and-control system. All firms in the electricity sector need to be creatures of the market economy, which constantly reshape technology and business models in response to prices. Such firms have the incentive and the ability to look at the changing landscape of technology, financing and carbon taxation, and solve local maximisations that yield the correct engineering and business solutions all across the country. This distributed intelligence, this self-organising system, processes information better, values profit over conservatism and populism, engages in a process of search with risk-taking where some win and some lose, and avoids the state capacity constraints that hamper the central planning system. It will achieve the required Indian climate transition at a lower cost to the economy when compared with a centrally planned path.

Under an electricity sector that is grounded in the price system, there is a clear pathway to the climate transition: the single instrument of the carbon tax. Following a 5-10 year reform process of the electricity sector, the Indian state would announce levels of carbon taxation for the next 25 years, based on international commitments towards decarbonisation and net zero. Private persons would respond to these numerical values with business and technological strategies that are optimal at every location in the country. Every five years, policy makers would review the emissions, and modify the trajectory of taxes for the coming 20 years. Policy makers would control this one lever -- the carbon tax -- and the decarbonisation of the economy would be achieved through private decisions on the demand side, in generation and in storage.

Without a carbon tax, the union government lacks instruments for carbon policy, and intricate regulatory activities will induce enhanced costs upon the economy. Without an electricity sector that is organised around the price system, the resource allocation will be distorted thus enhancing the economic cost of decarbonisation. The optimal way forward is a combination of electricity regulation at state governments, a carbon tax led by the union government, and a private electricity sector organised around the price system.

While this appears to be an attractive vision, it is also a difficult policy project. Immense effort has been put into electricity reform in the past, by insightful policy makers. These leaders of Indian electricity reform, of the last 30 years, stayed within the strategy of a centrally planned electricity system. Why do we believe that things could work differently today?

There are six aspects in which the present situation is different, which creates a pathway to the fundamental reform that was elusive for the last 30 years: (1) There is greater understanding of the political economy landscape, and it is possible to design bargains where the losers from the reform are compensated. (2) State capacity in regulation is essential for the operation of an electricity sector organised around the price system, and there is now a greater understanding in India of how to establish the objectives and methods of regulation. (3) There is a path to electricity reform, one state at a time, which is more tractable and feasible when compared with grand schemes led by the union government which apply to the entire country. (4) The materiality of climate policy in the international discourse has shifted the political salience of domestic electricity reforms. Alongside this, the domestic policy envelope on establishing more market-led solutions has improved. (5) It is possible to fund the transition. (6) The fiscal cost of upholding the status quo in the electricity sector is likely to rise.

A frugal air quality monitor

by Ayush Patnaik.

The problem

In many parts of the world, poor air quality has shaped up as a major health hazard. While air quality is traditionally seen as the source of respiratory ailments, there is mounting evidence that low air quality has far reaching impacts upon human health. As an example, it exacerbates the deteriorative illnesses of old age.

Ordinarily, we see clean air as a pure public good. There is little that one person can do about it. However, there is much value for an individual in having a right-now-right-here measure of air quality. As an example:

• Air quality is hyperlocal; it varies quite a bit by small changes in location. A person may choose which room or which floor in a building is better based on the information.
• Physical exercise should be avoided when air quality is worse than certain thresholds.
• The decision to use a mask or not.
• The decision to buy or switch on an air purifier.
• Testing the correct working of an air purifier by examining the air quality at inlet versus exhaust.

To do these things, we need an inexpensive, convenient, portable air quality meter. While there are many dimensions to clean air, for the present purpose, we will focus on solid particulate matter with particle size below 2.5 microns ("pm2.5").

Solution 1: the Origins Laser Egg

Pros

• Shows and logs PM2.5 readings.
• Only two button, power and menu. This makes the Laser Egg easy to operate.
• Connects to wifi and uploads data on a server.

Cons

• Costs approximately USD 130. Too expensive for countries with air quality issues.
• It is 288 grams, and not small enough to be carried in a pocket.
• It has to be regulary charged.

Can we do better?

Everyone walks around carrying a mobile phone, which contains a battery, a CPU, a display, a GPS, and a connection to the Internet. This makes it possible to sharply reduce the cost and complexity of measuring air quality. All that we'd need is a sensor that reads the air quality, and gives this information to the phone. Everything else can be done on the phone.

I chose a sensor, the SDS021, which costs roughly $20. I wrote the software which runs on an Android phone and takes in data from this sensor and displays it.

Advantages Over The Laser Egg

• It costs about $20, which is significantly cheaper.
• It is much lighter and smaller. It fits in a pocket.
• Doesn't have to be charged regularly since it takes power from a phone.
• The data is processed in a phone. Other sensors in the phone such as GPS can be collaborated.

Instructions

1. Buy this sensor, e.g. from Aliexpress.
2. Buy an adapter to connect into micro USB or USB C , depending on what your phone requires.
3. Install my program Aqui from the Google play store or APK
4. Run the program, plug in the sensor.

Future development

Aqui is built as an open source system on github. A lot of interesting work can and should be done here:

1. Send data to a central database
2. Maps display of my data juxtaposed with data from other Aqui users
3. Support for diverse sensors.

 

Ayush Patnaik is student of Physics and Mathematics at Australian National University.

Describing Delhi's air quality crisis

by Dhananjay Ghei, Arjun Gupta and Renuka Sane.

One of the most important elements of public health is regulatory interventions that yield clean air.  In late 2016, we await the air quality crisis of the Delhi winter with trepidation. A few attempts at solving the problem have begun. The Government of Delhi experimented with an odd-even policy to regulate traffic between 1 January 2016 to 15 January 2016, and then between 15 April 2016 to 22 April 2016. The results of these experiments have been mixed [here and here].

What you measure is what you can manage. Only when we are able to marshal evidence in a systematic way about the extent and nature of the problem, will we be able to design and deliver a response. The measurement of air pollution in Delhi has begun on a small scale. In this post, we describe patterns seen in the available data.

Why is PM 2.5 a good measure?

There are many pollutants in the air such as carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), ozone (O3). The worst among these is small particulate matter, or PM 2.5, which are a mixture of solid and liquid droplets floating in the air whose diameters are less than 2.5 micrometers. These fine particles are produced from all types of combustion, including motor vehicles and power plants and some industrial processes.

The health impact from pollution is a complex transform of exposure to all pollutants. However, of the pollutants, PM 2.5 particles are considered the most harmful as they are able to enter deep into the respiratory tract, reaching the lungs. This can cause short-term health effects such as eye, nose, throat and lung irritation, coughing, sneezing, runny nose and shortness of breath, and in the long-term can affect lung function and worsen medical conditions such as asthma and heart disease. We, therefore, narrow our attention to the measure of PM 2.5. The unit of measurement of PM 2.5 is µg/m³ and the breakpoints of raw PM 2.5 values by the US Environmental Protection Agency are the following:

24-hr PM 2.5	AQI Categories	Health Effects Statements
0.0-12.0	Good	None
12.1-35.4	Moderate	Respiratory symptoms possible in unusually sensitive individuals, possible aggravation of heart or lung disease in people with cardiopulmonary and older adults.
35.5-55.4	Unhealthy for Sensitive Groups	Increasing likelihood of respiratory symptoms in sensitive individuals, aggravation of heart or lung disease and premature mortality in people with cardiopulmonary disease and older adults.
55.5-150.4	Unhealthy	Increased aggravation of heart or lung disease and premature mortality in people with cardiopulmonary disease and older adults; increased respiratory effects in general population.
150.5-250.4	Very Unhealthy	Significant aggravation of heart or lung disease and premature mortality in people with cardiopulmonary disease and older adults; significant increase in respiratory effects in general population
250.5-500	Hazardous	Serious aggravation of heart or lung disease and prematuremortality in people with cardiopulmonary disease and older adults; serious risk of respiratory effects in general population.

 

Data

We fetch raw PM 2.5 values from two data sources on pollution in Delhi. The first is put out by the US Embassy based in Chanakyapuri. In addition, the Central Pollution Control Board also puts out real time data for various locations across India. We select 4 locations which provided us with the most consistent dataset. This gives us a total of 5 locations for which we have data:

1. R K Puram
2. Punjabi Bagh
3. Mandir Marg
4. US Embassy (Chanakyapuri)
5. Anand Vihar

We use hourly data from the locations mentioned above for a time period from January 2013 to October 2016. It should be noted that values are missing from certain sections of the data. These missing observations are excluded from our analysis.

Drawing upon the Chinese experience, it's interesting to ask: Do the Indian government sources tally with the US Embassy data?  We can't say, as there is no measurement for a location near the US Embassy by the CPCB.

Dimensions of variation

These are three types variations seen in PM 2.5.

Figure 1: Variation by time of day

Time Effect: Figure 1 above shows the variation in hourly pollution levels during different days of a week. Darker colors represent increased PM 2.5 matter in the air. We see that the pollution levels are low during the day, but start increasing post 6 p.m. and remain elevated till 9 a.m. of the next day. The average PM 2.5 concentration from 6 p.m. to 9 a.m. is 140 µg/m³, whereas the average PM 2.5 concentration from 9 a.m. to 6p.m. is 108 µg/m³. PM 2.5 levels in the range of 101-200 can cause breathing discomfort to anyone with prolonged exposure to the air during these times. This graph suggests that a measure that restricts traffic during the day such as the odd-even policy is unlikely to be as effective as a measure that restricts emissions at night.

Figure 2: Variation by month

Month Effect : Figure 2 shows the hourly variation in pollution levels during different months of the year. Note that the scale for this figure is different from that used in Figure 1. The monsoon months have the lowest levels of PM 2.5 particulate matter. Larger particles are settled in few hours due to gravity, but smaller particles such as PM 2.5 are removed by precipitation. Winters have the highest levels of PM2.5 matter in the air, on account of low wind speed and high relative humidity. PM 2.5 concentration reaches above 200 in the winter months, which can cause respiratory illness to people on prolonged exposure and puts people with respiratory illness, and heart disease on a far greater risk.

Figure 3: Variation by location

Location Effect: Figure 3 shows the hourly variation in pollution levels at the five locations where instruments are available. Chanakyapuri seems to perform better than other areas of Delhi, in terms of PM 2.5 particulate matter. Anand Vihar has the highest pollution levels amongst the 5 different locations, and has severe levels of air pollution in the night. This can cause respiratory impact even on healthy people, and serious health impacts on people with lung/heart diseases.

Thus, we see that there is a strong location effect on pollution levels. This can be due to the varying population densities of these locations as well as the proximity to industries etc. This could lead to location-specific policy initiatives such as closing down factories or modifying vehicular traffic.

Reproducible research

Data and R code.



Dhananjay Ghei and Arjun Gupta are researchers at the National Institute of Public Finance and Policy. Renuka Sane is an academic at the Indian Statistical Institute, Delhi Centre.

Highways: from good to great

In 2006, I had written a blog post titled Why are elephants attacking people? On a related note is the problem of roads and other barriers interfering with the natural migration paths of elephants in the wild. In India, we are in a great phase of building infrastructure, but alongside this is a new level of distortion imposed upon the animals.

Mark Thoma's blog just led me to fascinating pictures from Kenya about elephant-friendly underpasses. This will reduce destructive human-animal interactions, and improve gene flow.

In Canada recently, I saw some remarkable construction work on the big highways. They have huge overpasses which are then forested over, to permit the animals to cross from one side to another. Here is the Google satellite imagery:

The scale on the left suggests that the overpass is roughly 50m wide, which is quite a bit. It is wide enough for grizzly bears and elk to cross without necessarily having unpleasant encounters with each other. The photograph also shows trees growing on the overpass. Here is what it looks like while on the road:

I had never imagined something of this scale before, but there appears to be a flourishing effort worldwide of this nature. Also see Home on the range: A corridor for wildlife by Cornelia Dean in the New York Times from 23 May 2006.

I rode by train through Rajaji National Park recently, and the train went very slow and made noise constantly, in an attempt to avoid killing elephants. The initiatives at reducing collisions between trains and elephants in that region appear to be working. In 2012, I read a story by Nidhi Sharma in the Economic Times about NHAI building 13 underpasses for animals over a 9 kilometer stretch on NH-7 through Pench Tiger Reserve. This is an important dimension to the fresh focus on road safety that needs to be a part of the large scale building of new roads that is now taking place in India.

Reintroduction of tigers into Sariska

Indian Express has an article by Neha Sinha on the relocation of tigers to Sariska and the problems of wildlife conservation in Sariska and Ranthambore. While reading this, I wondered: Sariska has an area of 866 sq.km. - is that enough to hold a Minimum Viable Population (MVP) of tigers? Do look at this cool blog by Aditya Singh.

Futures on carbon credits

Mobis Philipose has an interesting article in Mint on the emerging market of futures trading on carbon credits.

When a powerful urge to do good crowds out hard thinking

Stephen Dubner and Steve Levitt have an article in The New York Times that reminded me a lot about the pitfalls of public policy in India.

When a powerful urge to do good crowds out hard thinking, the results are often different from what might have been intended. Their article has two interesting examples:

• The `Americans With Disabilities Act' in the US involves all kinds of privileges for disabled people. E.g. it allows a patient to place the costs of a sign-language interpreter on the doctor. A paper by Acemoglu and Angrist found that when the law was enacted in 1992, employment of disabled workers went down sharply. Employers were concerned that the law would limit their ability to discipline or sack disabled people who happened to be incompetent, and chose to avoid recruiting them in the first place.
• The `Endangered Species Act' in the US allows the notification of `critical habitats' for endangered species. As a consequence, when a landowner feels that endangered species are possibly inhabiting his privately owned forest land, he often takes care to raze the trees to make sure that he is not expropriated. This leads to more habitat destruction, not less. They describe the cactus ferruginous pygmy owl, studied in a paper by List, Margolis and Osgood: landowners near Tucson, Arizona `rushed to clear their property for development rather than risk having it declared a safe haven for the owl'.

As Dubner and Levitt summarise:

So does this mean that every law designed to help endangered animals, poor people and the disabled is bound to fail? Of course not. But with a government that is regularly begged for relief these days, from mortgage woes, health-care costs and tax burdens and with every presidential hopeful making daily promises to address these woes, it might be worth encouraging the winning candidate to think twice (or even 8 or 10 times) before rushing off to do good.

Dark skies, Ladakh

I noticed a fascinating article The Dark Side by David Owen, in New Yorker magazine, which incited me to look for and find the International Dark-Sky Park program. On a related note, see this article by H. T. Goranson. It struck me that Ladakh fits the bill as being a place with an incredibly clear and dark sky. The `Bortle Dark Sky Scale', measures the darkness of the sky but googling didn't yield the value for Ladakh.

What google earth can do for illegal land development

Ubiquitous access to Google Earth has many interesting implications for the land market.

I have seen many signs where obscure little real estate brokers, by the road side, offer to show you properties through Google Earth.

Nancy Sajben sent me a pointer to a blog entry talking about how land acquisition for an SEZ was influenced by Google Earth: farmers were able to argue their position more clearly by utilising this information.

In cities like Bombay and Delhi, I sometimes think the resolution of Google Earth pictures are so high that one can even identify illegal construction where a house spills into the road. The puzzle is: who will do this?

I have long been highly conscious about illegal land development on the boundaries of national parks by developers who chip away, one acre at a time. I don't know the legal foundations surrounding Borivli National Park, but the amount of construction taking place at the edges of the park seems very, very suspicious to me. And this is Bombay - anywhere outside Bombay I'm sure the dangers of encroachment are much worse.

It would be wonderful if an environmental activist group would engage in the following steps:

1. Utilise the public records to make a .kmz file of the boundary of all the national parks in India,
2. Setup software which watches google earth, and throws up an alert when it looks like there is some habitation in what ought to be park land.

Update: I just noticed some work in South America which sounds like this.

Why are elephants attacking people?

In 1997, I was at Mudumalai National Park which was teeming with elephants. The ground rules at the place when walking in the forest were: "If you see an elephant, run away". There were endless local stories about vicious elephants going after people. This wasn't just forest rangers engaging in risk-averse overkill to save themselves the trouble of stupid tourists who get hurt. Elephants attacking humans seemed to be regularly happening. Elephants kill vastly more people than tigers in India.

It always felt strange to me. When one read older stories in the forests, like the books by Jim Corbett, it didn't feel that the elephants were dangerous. And domesticated elephants are the loveliest, friendliest and charming animals. So why were wild elephants so dangerous?

I read a great article in New York Times today about this question. Their main argument is that elephants normally have a complex nurturing childhood in a social setting where they are brought up by a mother and other elders. When elephants grow up without such an upbringing, they are unsocialised. Too often, young elephants are exposed to violence by humans. This seems to set the stage for violence against humans. The NYT article has a fascinating interplay between the problems of young elephants in Africa who grow up as orphans surrounded by violence and young humans in Africa who also suffer the same. Both sides seem to grow up poorly socialised and violent.

It reminded me of the violent young people growing up in inner city Los Angeles, where many children do not have an opportunity to grow up with a nurturing mother and family. I know, this is anthropomorphisation run amuck. But the NYT article seems to suggest that elephants are highly intelligent and highly social, so the analogies with human behaviour actually have scientific merit.

Dancing with Giants: China, India and the Global Economy

The World Bank has produced a draft volume Dancing with Giants: China, India and the global economy, edited by L. Alan Winters and Shahid Yusuf. Six areas are covered: global industrial geography, competing with giants, international financial integration, energy and emissions, regional variations in growth within the giants, and governance.

Groundwork towards this was done in the form of 21 background papers. Drafts of the book, and the 21 background papers, have been placed on the web. It is good work.