Recent climate and air pollution impacts on Indian agriculture

Abstract

Recent research on the agricultural impacts of climate change has primarily focused on the roles of temperature and precipitation. These studies show that India has already been negatively affected by recent climate trends. However, anthropogenic climate changes are a result of both global emissions of long-lived greenhouse gases (LLGHGs) and other short-lived climate pollutants (SLCPs). Two potent SLCPs, tropospheric ozone and black carbon, have direct effects on crop yields beyond their indirect effects through climate; emissions of black carbon and ozone precursors have risen dramatically in India over the past three decades. Here, to our knowledge for the first time, we present results of the combined effects of climate change and the direct effects of SLCPs on wheat and rice yields in India from 1980 to 2010. Our statistical model suggests that, averaged over India, yields in 2010 were up to 36% lower for wheat than they otherwise would have been, absent climate and pollutant emissions trends, with some densely populated states experiencing 50% relative yield losses. [Our point estimates for rice (-20%) are similarly large, but not statistically significant.] Upper-bound estimates suggest that an overwhelming fraction (90%) of these losses is due to the direct effects of SLCPs. Gains from addressing regional air pollution could thus counter expected future yield losses resulting from direct climate change effects of LLGHGs.

Keywords: India; aerosols; agriculture; climate impacts; ozone.

Fig. 1.

(A) Cultivated fraction of each 5′ x 5′ cell for (Left) wheat and (Right) rice. States included in this analysis for each crop are labeled. Data are from ref. . (B) MODIS (Terra) Aerosol Optical Depth at 550 nm in 2008 for (Left) March–April–May average, coinciding with the peak of the wheat season, and (Right) August–September–October, coinciding with the peak of the kharif rice season. (C) Modern-Era Retrospective Analysis (MERRA) estimated 24-h average surface ozone mixing ratio (ppbv) in 2008 for (Left) wheat harvest season, March–April–May average, and (Right) kharif rice harvest season, August–September–October average (64).

Fig. 2.

Relationship between yearly mean ozone and precursor concentrations at European monitoring stations observing ozone, NOx, and NMVOCs. Main plot shows the existence of low- and high-NOx regimes (with opposite-signed relationships). (Inset) The relationship between ozone and the NMVOC:NOx ratio. These data were used to guide choice of functional form in our model. Data from AirBase v.6 (65).

Fig. 3.

RYC resulting from climate and SLCPs for (A) wheat and (B) rice. For both crops, RYC is calculated as [Model_{(2006–2010 avg)} − Baseline_{(2006–2010 avg)}]/Baseline_{(2006–2010 avg)} (plotted as red diamonds). The portion of the total yield change because of temperature and precipitation trends (blue bars) is estimated using the coefficients in Table S1 and the average trends in T and P (Fig. S4). The remainder is a result of SLCPs. Country totals are estimated by summing state values weighted by total area. Error bars are constructed for each state by bootstrap resampling the model 1,000 times and selecting the 95% range.

Fig. 4.

(Left) Map of India showing average December–January–February HCHO:NO₂ ratio. The 2° cells in Punjab (red) and UP/Bihar (blue) are used for comparative analysis in the right panel. (Right) Distribution of HCHO:NO₂ ratio in grid cells in two comparison regions for 2008, by month. The line (ratio = 4) represents the empirically derived transition between ozone titrating (i.e., the relationship between columnar ozone and NO₂ is negative) and NOx-sensitive (the relationship is positive) regimes. In the wheat-growing season, Punjab/Haryana is largely NOx-saturated, whereas UP/Bihar is NOx-sensitive.