Loss of crop yields in India due to surface ozone: an estimation based on a network of observations

Autor: Ujjaini Sarkar, S. Venkataramani, Harish Gadhavi, Jagdish Chandra Kuniyal, Kotalo Rama Gopal, Kandikonda Maharaj Kumari, Manish Naja, Tuhin Kumar Mandal, Pradip Kumar Bhuyan, Trupti Das, Yerramsetti Venkata Swamy, Modathi Kottungal Satheesh Kumar, Shyam Lal, Sachchida Nand Tripathi
Rok vydání: 2017
Předmět:
Zdroj: Environmental science and pollution research international. 24(26)
ISSN: 1614-7499
Popis: Surface ozone is mainly produced by photochemical reactions involving various anthropogenic pollutants, whose emissions are increasing rapidly in India due to fast-growing anthropogenic activities. This study estimates the losses of wheat and rice crop yields using surface ozone observations from a group of 17 sites, for the first time, covering different parts of India. We used the mean ozone for 7 h during the day (M7) and accumulated ozone over a threshold of 40 ppbv (AOT40) metrics for the calculation of crop losses for the northern, eastern, western and southern regions of India. Our estimates show the highest annual loss of wheat (about 9 million ton) in the northern India, one of the most polluted regions in India, and that of rice (about 2.6 million ton) in the eastern region. The total all India annual loss of 4.0–14.2 million ton (4.2–15.0%) for wheat and 0.3–6.7 million ton (0.3–6.3%) for rice are estimated. The results show lower crop loss for rice than that of wheat mainly due to lower surface ozone levels during the cropping season after the Indian summer monsoon. These estimates based on a network of observation sites show lower losses than earlier estimates based on limited observations and much lower losses compared to global model estimates. However, these losses are slightly higher compared to a regional model estimate. Further, the results show large differences in the loss rates of both the two crops using the M7 and AOT40 metrics. This study also confirms that AOT40 cannot be fit with a linear relation over the Indian region and suggests for the need of new metrics that are based on factors suitable for this region.
Databáze: OpenAIRE