Deb Roy Sompriti, Bano Shahana, Beig Gufran, Murthy Bandarusatya
Indian Institute of Tropical Meteorology (IITM), Pune-411008, Maharashtra, India.
National Institute of Advanced Studies, Indian Institute of Science Campus, Bengaluru, 560012, India.
Environ Monit Assess. 2023 Jan 27;195(2):338. doi: 10.1007/s10661-022-10889-w.
Surface ozone is a damaging pollutant for crops and ecosystems, and the ozone-induced crop losses over India remain uncertain and a topic of debate due to a lack of sufficient observations and uncertainties involved in the modeled results. In this study, we have used the observational data from MAPAN (Modelling Air Pollution And Networking) for the first time to estimate the relative yield losses, crop production losses, and economic losses for the two major crops (wheat and rice). The detailed estimation has been done focusing on three individual suburban sites over India (Patiala, Tezpur, and Delhi) and compared with other related studies over the Indian region. We have used the concentration-based metric (M7, 7-h average from 09:00 to 15:59 h) along with the cumulative ozone exposure indices (AOT40, accumulated exposure over a threshold of 40 ppb) and applied the exposure-response (E-R) functions for the calculation of the crop losses. Our study shows that the yearly crop losses can reach the level of 12.4-40.8% and 2.0-11.1% for the wheat and rice crops, respectively, at certain places like Patiala in India. The annual economic loss can be as high as $4.6 million and $0.7 million for wheat and rice crops, respectively, even at individual locations in India. Our estimated %RYL (relative yield loss) lies in the range of 0.3 + /0.6 times the recent regional model estimates which use only the AOT40 metric. Region-specific E-R functions based on factors suitable for the Indian region needs to be developed.
地表臭氧是对农作物和生态系统有害的污染物,由于缺乏足够的观测数据以及模型结果存在不确定性,印度因臭氧导致的作物损失仍不明确,是一个备受争议的话题。在本研究中,我们首次使用了MAPAN(空气污染建模与网络)的观测数据来估算两种主要作物(小麦和水稻)的相对产量损失、作物产量损失和经济损失。详细估算聚焦于印度的三个郊区站点(帕蒂亚拉、提斯普尔和德里),并与印度地区的其他相关研究进行了比较。我们使用了基于浓度的指标(M7,09:00至15:59时的7小时平均值)以及累积臭氧暴露指数(AOT40,超过40 ppb阈值的累积暴露量),并应用暴露-响应(E-R)函数来计算作物损失。我们的研究表明,在印度的某些地方,如帕蒂亚拉,小麦和水稻作物的年度作物损失分别可达12.4 - 40.8%和2.0 - 11.1%。即使在印度的个别地点,小麦和水稻作物的年度经济损失分别可能高达460万美元和70万美元。我们估算的相对产量损失(%RYL)是近期仅使用AOT40指标的区域模型估算值的0.3至0.6倍。需要基于适合印度地区的因素开发特定区域的暴露-响应函数。