Examining the Inter-Regional Pollution Spillover: Evidence from Visibility in China

Abstract

By utilizing a novel and unique dataset of daily measures of visibility, we propose regression-based new methods that are easy to implement to quantify the long-range spillover of air pollutants. In applying them to China, we find significant externalities of air pollution: an increase in the local pollution intensity by 10% can increase the pollutant intensity of a region 1,000 kilometers away by over 1%.

Keywords:

• visibility
• air pollution
• environmental externalities
• China

JEL classifications:

• H8
• R1
• Q2

Acknowledgments

We are indebted to the coeditor of this journal, Prof Ni Jinlan, and the two anonymous referees for helping us to substantially improve the article. All errors are our own.

FUNDING

The first author acknowledges the financial support of FDCT/064/2014/A from the Macau Science and Technology Foundation.

Notes

1 Stern (2005) employs a database of SO₂, which documents and imputes the Global Sulfur Emissions at the country level from 1850–2003.

2 Cohen et al. (2005) estimates that “… fine particulate air pollution (PM(2.5)), causes about 3% of mortality from cardiopulmonary disease, about 5% of mortality from cancer of the trachea, bronchus, and lung, and about 1% of mortality from acute respiratory infections in children under 5 yr, worldwide.” (doi:10.1080/15287390590936166).

3 Due to the data limitation, in the regression we cannot control for terrain and wind direction.

4 Relative humidity is associated with dew point and temperature. At a given barometric pressure, independent of temperature, the dew point indicates the mole fraction of water vapor in the air and therefore determines the humidity. A high relative humidity level indicates that the dew point is closer to the current air temperature. If the relative humidity is 100%, the dew point is equal to the current temperature.

5 Note that some stations censor visibility above 20 miles (i.e., visibility was reported as 20 miles when the actual visibility is greater). An ordinary least squares (OLS) estimation of the visibility-GDP elasticity may be biased downward due to this censoring.