Odd-even phase one implemented in January was more effective than phase two in April in curbing the Capital’s pollution, said an analysis by The Energy and Resources Institute (TERI).
In the second phase, there was a 17% decrease in car numbers and 13% increase in vehicle speed. In contrast, the first phase saw a 21% reduction in cars and 18% increase in speed, the analysis said.
The think tank on Tuesday released an impact assessment study on the two phases of the scheme that limited the number of private cars on the roads for a 15-day period.
It observed that the scheme only led to “marginal” reductions (4-7%) of PM 2.5 pollutants during both phases as private cars make a limited contribution to the fine particles.
TERI experts used a box model to delineate odd-even’s effect on PM2.5 concentrations from daily changes due to meteorological factors such as wind speeds.
“…the concentrations could have been 4% higher (during April 15-30) than those observed in the absence of odd-even scheme. This reduction, however, was 7% in phase 1 (January 1-15)…,” said Sumit Sharma, who led the monitoring team.
“This decline could be probably due to people opting for second cars with alternative number plates, installations of CNG kits or enhanced use of taxis. The results of the two phases of odd-even scheme in Delhi suggest that it is useful only when high pollution episodes are expected,” Dr Ajay Mathur, Director General, TERI, said.
TERI had collected daily data from four Delhi Pollution Control Committee monitoring stations and was also monitoring another five locations for air quality during the odd-even phases.
Even overall average of pollution data showed that phase one trumped phase two in terms of effectiveness. During phase one, there was an increase of 25%, 22%, and 27% in PM2.5, PM10, and NOx concentrations, respectively. In the second phase, however, the increase was 39%, 26%, and 25%, respectively.
“The main reasons for the increase were meteorological factors and background influences. During both the odd-even scheme periods, lower wind speeds and mixing height values led to relatively lesser dispersion of the pollutants, leading to higher concentrations,” Sharma said.
Background influences refers to emissions from neighbouring states.