The impact of tropospheric ozone pollution on trial plot winter wheat yields in Great Britain – An econometric approach

Abstract

Econometric study of British winter wheat trial plot data suggests lower economic loss than predicted from experiments. a r t i c l e i n f o a b s t r a c tNumerous experiments have demonstrated reductions in the yields of cereal crops due to tropospheric O 3 , with losses of up to 25%. However, the only British econometric study on O 3 impacts on winter wheat yields, found that a 10% increase in AOT40 would decrease yields by only 0.23%. An attempt is made here to reconcile these observations by developing AOT40 maps for Great Britain and matching levels with a large number of standardised trial plot wheat yields from many sites over a 13-year period. Panel estimates (repeated measures on the same plots with time) show a 0.54% decrease in yields and it is hypothesised that plant breeders may have inadvertently selected for O 3 tolerance in wheat. Some support for this is provided by fumigations of cultivars of differing introduction dates. A case is made for the use of econometric as well as experimental studies in prediction of air pollution induced crop loss.

Emission inventories and projections

“…Such studies have consistently demonstrated that O 3 can negatively influence a variety of forest responses from crown condition to radial growth [Braun S et al, 2010]. More recently, similar spatially relevant studies have been extended to crop loss assessments [Fishman et al, 2010;Kaliakatsou et al, 2010]. These studies have found that the influence of O 3 can be detected in regional level production statistics and field trial data although damage estimates have been found to differ from those obtained from risk assessments performed using empirically derived dose-response relationships [Kaliakatsou et al, 2010].…”

“…More recently, similar spatially relevant studies have been extended to crop loss assessments [Fishman et al, 2010;Kaliakatsou et al, 2010]. These studies have found that the influence of O 3 can be detected in regional level production statistics and field trial data although damage estimates have been found to differ from those obtained from risk assessments performed using empirically derived dose-response relationships [Kaliakatsou et al, 2010]. This may be due to these methods being most effective in those regions characterized by higher average O 3 concentrations [Fishman et al, 2010] where the O 3 signal is strong enough to overcome the influence of confounding variables affecting yield.…”

Effects of ozone on agriculture, forests and grasslands

“…Epidemiological studies detected the influence of O 3 in national level agricultural production statistics [14,15]. These studies use statistical multiple linear regression models to analyse 5–30-year time series of historical data to explore the relationship between past crop yield outcomes and trends or inter-annual variations in weather variables (e.g.…”

“…A study on soya bean growing across the mid-west USA over a 5-year period was able to detect a 10% reduction in yield [14]. By contrast, only a 0.54% decrease in yield with a 10% increase in O 3 concentrations (characterized using the AOT40 metric (see §3a)) was found at wheat trial sites across the UK over a 13-year period, lower than would be expected according to experimental data [15]. Understanding such discrepancies is important and may be due to the influence of confounding factors (e.g.…”

Measuring the impact of surface ozone on rice production in China: a normalized profit function approach

“…, 2017; Saxena et al. , 2020), wheat (Kaliakatsou et al. , 2010; Burney and Ramanathan, 2014), maize (Westenbarger and Frisvold, 1995; Peng et al.…”