<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>To determine the effects of air pollution on crop yields, weather, air pollution, and maize and winter wheat yield data from 331 cities in China from 2014 to 2016 were collected and analysed. Furthermore, support vector regression and the crop growth model were applied to extrapolate the air pollution data of Beijing and Hetian and verify the relationship between air pollution and yield. Precisely, heavy air pollution usually occurred in North China, but less than moderate air pollution levels affected crop yields statistically insignificantly. Moreover, both the winter wheat and maize yields increased in moderate air pollution periods but decreased in heavy air pollution periods in 2014, 2015 and 2016. Importantly, a threshold value was necessary for the heavy air pollution periods to trigger a yield decrease. The threshold values of maize in 2015 and 2016 were 7 days and 5 days, respectively, while that of winter wheat was 10 days in both 2015 and 2016. Once the heavy air pollution periods exceeded the threshold value, both the winter wheat and maize yields decreased linearly with the periods. PM2.5 was the main air pollutant in Beijing in 2014, while PM2.5 and PM10 were the main air pollutants in Hetian in both 2015 and 2016. Regardless of whether the main air pollutant was PM2.5 or PM10, the simulated potential winter wheat yields by the crop growth model with moderate air pollution for the whole growth period were all higher than the yields under observed and heavy air pollution conditions.</p>
</abstract>

To determine the effects of air pollution on crop yields, weather, air pollution, and maize and winter wheat yield data from 331 cities in China from 2014 to 2016 were collected and analysed. Furthermore, support vector regression and the crop growth model were applied to extrapolate the air pollution data of Beijing and Hetian and verify the relationship between air pollution and yield. Precisely, heavy air pollution usually occurred in North China, but less than moderate air pollution levels affected crop yields statistically insignificantly. Moreover, both the winter wheat and maize yields increased in moderate air pollution periods but decreased in heavy air pollution periods in 2014, 2015 and 2016. Importantly, a threshold value was necessary for the heavy air pollution periods to trigger a yield decrease. The threshold values of maize in 2015 and 2016 were 7 days and 5 days, respectively, while that of winter wheat was 10 days in both 2015 and 2016. Once the heavy air pollution periods exceeded the threshold value, both the winter wheat and maize yields decreased linearly with the periods. PM2.5 was the main air pollutant in Beijing in 2014, while PM2.5 and PM10 were the main air pollutants in Hetian in both 2015 and 2016. Regardless of whether the main air pollutant was PM2.5 or PM10, the simulated potential winter wheat yields by the crop growth model with moderate air pollution for the whole growth period were all higher than the yields under observed and heavy air pollution conditions.

Impact of Air Pollution on Maize and Wheat Production

State Key Laboratory of Water Resources and Hydropower Engineering Science

Ecological Chemistry and Engineering S

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Impact of Air Pollution on Maize and Wheat Production"}

To determine the effects of air pollution on crop yields, weather, air pollution, and maize and winter wheat yield data from 331 cities in China from 2014 to...

Impact of Air Pollution on Maize and Wheat Production

Data publikacji: 17 sie 2022

Zakres stron: 237 - 256

DOI: https://doi.org/10.2478/eces-2022-0018

Słowa kluczowe
maize, wheat, air pollution, support vector regression, environment

© 2022 Haorui Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Impact of Air Pollution on Maize and Wheat Production

Data publikacji: 17 sie 2022

Zakres stron: 237 - 256

DOI: https://doi.org/10.2478/eces-2022-0018

Słowa kluczowemaize, wheat, air pollution, support vector regression, environment

© 2022 Haorui Chen et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
maize, wheat, air pollution, support vector regression, environment