Assessment of O3-induced yield and economic losses for wheat in the North China Plain from 2014 to 2017, China☆
Graphical abstract
Introduction
Tropospheric ozone (O3) is a pollutant of widespread concern around the world owing to its negative effects on human health, crop yields and climate change (The Royal Society, 2008; Screpanti and De Marco, 2009; Stella et al., 2011; Ainsworth et al., 2012; Feng et al., 2019a). As a secondary air pollutant, ground-level O3 is formed by a chemical reaction of nitrogen oxides (NOX), volatile organic compounds (VOCS) and methane (CH4) under strong solar radiation (Ramaswamy et al., 2001). The emission of O3 precursors has increased a lot since the end of 19th century due to the rapid growth of fossil fuel-based economies, leading to an increase in O3 concentration from 10 to 15 ppb to approximately 50 ppb (8-h summer seasonal average) in the Northern Hemisphere (The Royal Society, 2008). Models have predicted that the level of O3 at global scale is projected to increase further by 20–25% between 2015 and 2050 if current emission trends continue (Meehl et al., 2007). Such levels of O3 are enough to damage most crops by reducing leaf chlorophyll content and photosynthesis rates and altering carbon allocation to different pools (Anav et al., 2011; Feng et al., 2015). It can also promote leaf senescence (Feng and Kobayashi, 2009), change susceptibility to abiotic and biotic stress (Anav et al., 2016), and lead to stomatal sluggishness response to environmental conditions (Hoshika et al., 2017). Furthermore, O3 will also cause a large amount of grain reduction in the future. Indeed, an estimate of global crop losses to elevated O3 indicates an increase to 4–26% for wheat, 9.5–19% for soybean, and to 2.5–8.7% for maize in 2030 based on the AOT40 and M12 metrics, with economic losses of $12-$35 billion each year (Avnery et al., 2011a). In contrast, world crop yields must increase in order to meet the growing demand imposed by an expected world population of 9 billion in 2050 (Ray et al., 2013), in line with the United Nation Sustainable Development goals of promoting sustainable agriculture, achieving food security and ending hunger by 2030 (UNSDG2). Therefore, high ground-level O3 represents a current and future threat for food security that will hinder the fulfilment of the above goals.
Wheat, a kind of O3-sensitive crop, accounts for the largest proportion among the world’s grain output. China is the largest producer of wheat, accounting for 17.8% of the global wheat production and 40.5% of Asian wheat production (FAOSTAT, 2016). Among the different wheat types cultivated in China, winter wheat is dominant, representing about 94% of total wheat production (Zhou et al., 2014). The North China Plain (NCP) is China’s main winter wheat producing region, contributing to nearly 60% of winter wheat production in China (National Bureau of Statistics, 2014–2017). As NCP is subject to severe O3 pollution (Tang et al., 2013; Tai et al., 2014; Li et al., 2018), ozone-induced yield reductions in this region is an issue of global importance for food security.
For assessing the potential risk of surface O3 to crops, exposure- and flux-based O3 metrics have been used (Musselman et al., 2006; Paoletti et al., 2007; Lefohn et al., 2018). Among them, AOT40 (accumulated ozone exposure over an hourly threshold of 40 ppb) is an exposure index most commonly applied (Mills et al., 2007; Li et al., 2018) during the last two decades as it can be easily calculated, and some studies have shown that it is closely correlated with the relative yield of different types of crops (Liu et al., 2009; Mills et al., 2007; Wang et al., 2012; Zhu et al., 2015). Therefore many studies have used AOT40-based response functions to estimate crop yield loss caused by O3 exposure around the world (Debaje, 2014; Sicard et al., 2017; Sinha et al., 2015; Zhu et al., 2015). In comparison to other countries, research in this area started earlier in Europe, where several response functions for O3-induced relative yield losses (RYL) were at first proposed from local experiments conducted in Open Top Chambers (Mills et al., 2007; LRTAP, 2017), and then observational O3 data were used to derive yield losses. In other countries, due to the lack of local experiments, AOT40-based response functions were taken from experiments conducted in USA and/or Europe (Amin, 2014; Debaje, 2014; Lal et al., 2017; Zhu et al., 2015). This can be problematic as, because of the differences of climatic conditions and crop varieties in different regions, crop responses to O3 may be quite different (Feng et al., 2015; Pleijel et al., 2007; Zhang et al., 2017). More recently, exposure-response functions for the Yangtze River Delta and Jiangsu province in China (Wang et al., 2012; Feng et al., 2012) have been proposed, which are more suitable for estimating wheat yield losses in this country.
Due to the frequent absence of observational data on O3 concentration, estimation of crop yield losses has been usually based on model simulation results (Amin, 2014; Avnery et al., 2011b; Dingenen et al., 2009; Tang et al., 2013). However, modelling approaches may be subjected to large uncertainties. For example, different factors (e.g., emissions, transport, chemistry, mixing, deposition and boundary conditions) of the Chemical Transport Model (CTM) systems needed to simulate O3 concentrations may be affected by large uncertainties (Stevenson et al., 2006). Therefore, when available, the use of a large amount of O3 observation data in combination with local AOT40-based response functions to assess crop yield losses caused by O3 exposure reduces uncertainties and is an accurate and reliable method to provide such estimations (Feng et al., 2019b). As China’s air pollution was dominated by SO2 and PM10 in the last two decades, a lower attention was paid in the past to O3. However, in recent years, as the air pollution in China converted to complex pollution characterized by PM2.5 and O3 (Song et al., 2017; Xie et al., 2015; Zhang et al., 2015), the Chinese government has recognized the importance of O3 pollution, and research on this topic has increased. At a local scale, however, there are still many gaps in AOT40-based response functions and O3 observational data. Ozone-wheat response functions in the Yangtze River Delta and Jiangsu province have been established (Wang et al., 2012; Feng et al., 2012), but not for the NCP, despite being of top importance as wheat producer area. Therefore, in this paper the ozone-wheat response functions derived from Chinese experiments is used because it is the best available one. As for the O3 data, in January 2013, the China National Environmental Monitoring Center (CNEMC) has adopted National Ambient Air Quality Standards −2012 and released hourly air pollutant concentration monitoring data in a web platform, which provides an excellent opportunity for researchers to study spatiotemporal variations of air pollutants and its associated risk to agricultural crops. As currently there are four complete years available of both wheat yield production and O3 data, it is now possible to conduct for the first time a multi-year study on O3 effects wheat yield in the NCP. The inclusion of several years increases the representative of the results, as yearly data are affected by different climatic conditions, natural disasters and pest incidence. In addition, we have assessed the yield losses at a very detailed level, as both yield data and AOT40 were estimated per county, which increases the accuracy with regard to estimations based on larger administrative units, e.g. province. In comparison with a previous study also based on O3 observational data, which covered all China for years 2015 and 2016 (Feng et al., 2019b), the present study focusses on the NCP, includes four consecutive years (with a notably increase in O3 concentrations as shown later), a higher density of plots, and provides statistics at country level, therefore increasing the temporal representativity and accuracy of the results for this area.
The main objectives of the present paper are: 1) to estimate grain yield and economic losses for winter wheat in NCP of four consecutive years based on measured data and local AOT-40 response function, 2) to provide our estimates by using data at county level, which may better reflect RYL.
Section snippets
Data sources
The Ministry of Environmental Protection of China had set up 1,497 air quality monitoring stations which provided the concentration data of major atmospheric pollutants across the country. From 2014, real time monitoring data of hourly O3 concentration had been released by CNEMC on a web platform (http://106.37.208.233:20035/) (Zhao et al., 2018). Since the study area of this paper is focused on the North China Plain, which represents the largest wheat production area of China, the hourly O3
Results
As shown in Fig. 2, the overall values of AOT40 during the winter wheat growing season from 2014 to 2017 in 288 counties of the NCP ranged from 3.1 to 14.9 ppm h, 4.89–17.5 ppm h, 7.27–17.6 ppm h, and 10.5–18.6 ppm h, respectively, with a mean of 9.57 ppm h, 11.5 ppm h, 13.2 ppm h and 15.5 ppm h, respectively. The value of AOT40 showed an increasing trend, and in the northern part of NCP the value was much higher than that in the southern part. Along the four years considered, there was a clear
AOT40 in NCP
Ground-level O3 is considered as one of the major air pollutant, causing serious negative impact on agriculture crops. The North China Plain has the highest production of wheat and also the highest O3 concentration in China (Li et al., 2019). In this area, O3 precursors are abundant, which, together with favorable conditions such as high-pressure system, sunny weather etc., boost O3 formation (Wang et al., 2017). Our study shows for the first time the high risks of O3 for wheat on the basis of
CRediT authorship contribution statement
Tingjian Hu: Methodology, Data curation, Writing - original draft. Shuo Liu: Software, Data curation. Yansen Xu: Software, Data curation. Zhaozhong Feng: Conceptualization, Methodology, Project administration, Writing - review & editing, Supervision. Vicent Calatayud: Conceptualization, Writing - review & editing.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This study was funded by the National Key Research and Development Program of China (2017YFE0127700, 2017YFC0210106), the Startup Foundation for Introducing Talent of Nanjing University of Information Science & Technology (No. 002992). V.C. thanks project IMAGINA (PROMETEU 2019; Generalitat Valenciana).
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This paper has been recommended for acceptance by Yong Sik Ok.