The Effect of Delhi Metro on Air Pollution in Delhi

Deepti Goel Delhi School of Economics

and Sonam Gupta

University of Florida

February 22, 2013, ISI Delhi

Research Question

Has the Delhi Metro (DM) resulted in an improvement in air quality

in the city?

MotivationAdverse health effects of air pollution

Block et al. (2012); Damage to central nervous system, cardiovascular disease, asthma

Currie & Walker (2011); Moretti and Neidell (2011);

High levels of pollution in Delhi

Several criteria pollutants exceed national standards

Net effect of public transport ambiguousTraffic Diversion EffectTraffic Creation EffectPower Plants (in case of Delhi Metro (DM))

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CO 8hr Average µg/m³- ITO on Tuesdays in 2006 (Mornings and Nights)

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O3 8hr Average µg/m³- ITO on Tuesdays in 2006 (Mornings and Nights)

Main Contributions

First study to econometrically analyze the effect of the Delhi Metro (DM) on air quality in Delhi

We identify the effect of several extensions of the DM rail network

We determine the cumulative effect of DM over a fifteen month period

Summary of Main Results

DM led to statistically significant decline in two main vehicular pollutants, nitrogen dioxide and carbon monoxide Suggestive of a traffic diversion effect

Rest of the Presentation

Identification Strategy

Graphical Presentation of Identification

Estimation Results

Robustness Checks

Conclusions

Identification StrategyOLS suffers from upward biasRegression Discontinuity Design

Outcome variable: Hourly air pollutant measure

Treatment: Operation of Delhi MetroAssignment Variable: Time

Main Identifying AssumptionIn the absence of the metro rail

extension, conditional on weather, we would observe a smooth time trend for the pollutant measure (Chen and Whalley, 2012)

Econometric Framework

Suppose is pollution in the absence of metro,

is pollution in the presence of metro.

tt

tt

t

YY

YY

tPYE

01

01

0 )(')(

tY0 tY1

This leads to the regression,

ttt DMtPY )('where

TtDM

TtDM

t

t

,0

,1

is when metro was extended

T

(Rough) Graphical Presentation of

Identification Strategy

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Monthwise Average Daily Metro Ridership, 2004-2006

-20

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Monthwise Percentage Change in Average Daily Metro Ridership, 2004-2006

NO2 at ITO, Blue Line Second Extension4

4.5

55.

5

08oct2006 29oct2006 19nov2006 10dec2006date

Fitted values lno2ito_dailyavg

CO at ITO, Blue Line Second Extension7

7.5

88.

5

08oct2006 29oct2006 19nov2006 10dec2006date

Fitted values lcoito_dailyavg

EstimationData and Regression Results

Data and Study PeriodCPCB: Hourly Pollution Data from three different Monitoring Stations in Delhi (ITO, Sirifort, DCE)Four criterion pollutants: NO2, SO2, CO and O3

IMD: Hourly weather data for Delhi Temperature, Relative humidity, Rainfall and

Wind speedDMRC: Monthly Ridership Data

Overlapping data on pollution and weather only available for 2004-2006

Pollution data also suffers from missing observations

Map of Delhi and Delhi Metro

Phase Wise Extension of the Delhi Metro

Extensions of the metro network 2004-2006

Red Line Extension 2 March 31, 2004

Yellow Line Introduction December 20, 2004

Yellow Line Extension 1 July 3, 2005 Blue Line Introduction December 31,

2005 Blue Line Extension 1 April 1, 2006 Blue Line Extension 2 November

11, 2006

Estimation Equation

tttt u+P(t)'+x'+DM+=Y tY Observed Pollutant measure in logs

tDM 1 for time periods after extension and 0 otherwise

tx Quartic in current and 1 hour lags of humidity, rainfall, temperature, and wind speed ; hour of the day; weekday; and their interactions

P(t) Third order polynomial in time

Estimate for each extension of DM:

t2t10t +D+P(t)'+x+=Y ti Mi

We also estimate an equation with contiguous extensions included to measure cumulative effect (for CO at ITO between Nov 2004 to Jan 2006)

Estimation Equation

Missing Pollution Data

Focus on only those extensions that have at least four weeks of data on each side of the extension, with no more than 20 percent of observations missing

Discontinuities Studied at ITO, 2004-2006

Permissible window length in weeksNO2 CO SO2 O3

Yellow Line Introduction

9 9

Yellow Line Extension 19 41 37

Blue Line Introduction

13 13

Blue Line Extension 2

13 13 9

Nine week window results: ITO

NO2 CO SO2 O3

Yellow Introd; Dec 2004 17.6 36.1***std. error; obs 11.7; 1579 10.5; 1555Yellow Ext; Jul 2005 -6.9 -68.6*** 90.682***std. error; obs 6.4; 1466 3.8; 1506 17.4; 1478Blue Introd; Dec 2005 -29.3*** -60.1***std. error; obs 4.9; 1639 3.5; 1608Blue Ext. 2; Nov 2006 -23.6*** -26.4*** 14.5**std. error; obs 3.7; 1605 4.7; 1605 6.0; 1566

Robust std. errors reported

Nine week window results: Siri Fort

NO2 CO SO2 O3Yellow Introd; Dec 2004 -39.9*** -89.2*** 27.5**std. dev; obs 2.7; 1555 1.6; 1571 12.1; 1572Yellow Ext; Jul 2005std. dev; obsBlue Introd; Dec 2005 std. dev; obsBlue Ext. 2; Nov 2006 -37.3*** -22.0*** -34.6***std. dev; obs 3.5; 1601 6.3; 1532 5.2; 1557

Robust std. errors reported

Cumulative Effect for the period Nov 2004 to Jan 2006: CO at ITO

CO

Yellow Introd; Dec 2004 -15.4**std. error 6.6Yellow Ext; Jul 2005 -33.3***std. error 3.3Blue Introd; Dec 2005 -31.9***std. error 6observations 9914Robust std. errors reported

RD Design Validity

Other DiscontinuitiesShorter Window

Artificial Discontinuities TestAppropriate Polynomial OrderNon parametric or Local Linear Regression

RD Design Validity: Robustness Checks

Other DiscontinuitiesConstruction activity undertaken to

build DMRegulation that might cause

discontinuous changeManipulation of choice of extension

date

Five week window results: ITO

NO2 CO SO2 O3Yellow Introd; Dec 2004 2.2 90.9***std. error; obs 15.4; 865 20.5; 861Yellow Ext; Jul 2005 -17.5** -77.6*** 89.6***std. error; obs 8.1; 757 3.8; 848 24.4; 759Blue Introd; Dec 2005 -52.8*** 31.7***std. error; obs 3.8; 848 11.1; 835Blue Ext. 2; Nov 2006 -20.3*** -24.0*** 5.7std. error; obs 3.8; 935 5.0; 935 5.1; 930

Robust std. errors reported

Five week window results: Siri Fort

Robust std. errors reported

NO2 CO SO2 O3Yellow Introd; Dec 2004 -29.4*** -76.9*** -8.5std. dev; obs 4.4; 842 3.7; 854 12.4; 853Yellow Ext; Jul 2005std. dev; obsBlue Introd; Dec 2005 std. dev; obsBlue Ext. 2; Nov 2006 -34.2*** -21.9*** -25.3***std. dev; obs 3.4; 934 6.5; 871 5.2; 901

Main ResultsNitrogen Dioxide

Decrease for both stations across all extensions

For ITO, 24 and 29 percent across extensionsFor Siri Fort, 37 and 40 percent across extensions

Carbon MonoxideDecrease for both stations across all extensions

For ITO, 26 and 69 percent across extensionsFor ITO cumulative effect of 15, then 33 and

then 32 percent for three consecutive extensions between Nov 2004 and Jan 2006

For Siri Fort, 22 percent

Main ResultsSulphur Dioxide

For ITO, increase (90 percent)For Siri Fort, decrease (35 to 89 percent

across extensions)

OzoneFor ITO, sign flips across extensions for 9

week window(increase across extensions for 5 week window)

For Siri Fort, increase for 9 week window(insignificant for 5 week window)

Work Ahead Artificial discontinuities Test

Smoothness tests for residuals after controlling for weather

Different orders of time polynomial (AIC criteria)Non parametric Estimation with optimal bandwidth

Better Understand SO2 and O3 resultsObtain additional data

Vehicular registrations to support traffic diversion effect

Power generation by coal based power plants within Delhi