Estimating ammonia emissions from a winter wheat cropland in North China Plain with field experiments and inverse dispersion modeling

2015 ◽  
Vol 104 ◽  
pp. 1-10 ◽  
Author(s):  
Qing Huo ◽  
Xuhui Cai ◽  
Ling Kang ◽  
Hongsheng Zhang ◽  
Yu Song ◽  
...  
Keyword(s):  
Winter Wheat ◽  
North China Plain ◽  
North China ◽  
Field Experiments ◽  
Dispersion Modeling ◽  
Ammonia Emissions ◽  
Inverse Dispersion ◽  
Inverse Dispersion Modeling

Use of the open-path TDL analyzer to monitor ammonia emissions from winter wheat in the North China Plain

2014 ◽  
Vol 99 (1-3) ◽  
pp. 107-117 ◽  
Author(s):  
Wen-Liang Yang ◽  
An-Ning Zhu ◽  
Xiao-Min Chen ◽  
Jia-Bao Zhang ◽  
Xiao-Hui Xu ◽  
...  
Keyword(s):  
Winter Wheat ◽  
North China Plain ◽  
North China ◽  
Ammonia Emissions ◽  
The North ◽  
The North China Plain ◽  
Open Path

scholarly journals Crop Water Production Functions for Winter Wheat with Drip Fertigation in the North China Plain

Agronomy ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 876
Author(s):  
Xiaojun Shen ◽  
Guangshuai Wang ◽  
Ketema Tilahun Zeleke ◽  
Zhuanyun Si ◽  
Jinsai Chen ◽  
...  
Keyword(s):  
Winter Wheat ◽  
North China Plain ◽  
North China ◽  
Field Experiments ◽  
Nitrogen Levels ◽  
Growing Seasons ◽  
The North ◽  
The North China Plain ◽  
Irrigation Levels ◽  
Drip Fertigation

During four consecutive growing seasons (2014–2018), field experiments were conducted in the North China to determine winter wheat production function. The field experiments were carried out using winter wheat subjected to four N levels (N120, N180, N240, and N300) and three irrigation levels (If, I0.8f, and I0.6f). The main aims were to characterize winter wheat productivity, drought response factor Ky, and the winter wheat grain yield production functions in relation to water supply under the different N fertilizer levels. The amount of water supply (rain + irrigation) were 326–434, 333–441, 384–492, and 332–440 mm in 2014–2015, 2015–2016, 2016–2017, and 2017–2018 growing seasons, respectively. Similarly, the values of ETa (including the contribution from soil water storage) were 413–466, 384–468, 401–466, and 417–467 mm in 2014–2015, 2015–2016, 2016–2017, and 2017–2018, respectively. ETa increased as the amount of irrigation increased. The average values of If, I0.8f, and I0.6f over the four growing seasons were 459–465, 432–446, and 404–413 mm, respectively. For the same amount of irrigation, there was only small difference in ETa among different nitrogen levels; for the three irrigation levels, the values of ETa in N120, N180, N240, and N300 ranged from 384 to 466, 384 to 466, 385 to 467, and 407 to 468 mm, respectively. Water productivity values ranged from 1.69 to 2.50 kg m−3 for (rain + irrigation) and 1.45 to 2.05 kg·m−3 for ETa. The Ky linearly decreased with the increase in nitrogen amount, and the values of r were greater than 0.92. The values of Ky for winter wheat in N120, N180, N240, and N300 were 1.54, 1.41, 1.28, and 1.25, respectively. The mean value of Ky for winter wheat over the three irrigation levels and the four nitrogen levels was 1.37 (r = 0.95). In summary, to gain higher grain yield and WUE, optimal combination of N fertilizer of 180–240 kg·ha−1 and irrigation quota of 36–45 mm per irrigation should be applied for winter wheat with drip fertigation in the North China Plain.

scholarly journals The water-saving potential of using micro-sprinkling irrigation for winter wheat production on the North China Plain

2021 ◽  
Vol 20 (6) ◽  
pp. 1687-1700
Author(s):  
Li-chao ZHAI ◽  
Li-hua LÜ ◽  
Zhi-qiang DONG ◽  
Li-hua ZHANG ◽  
Jing-ting ZHANG ◽  
...  
Keyword(s):  
Winter Wheat ◽  
North China Plain ◽  
North China ◽  
Water Saving ◽  
Wheat Production ◽  
The North ◽  
The North China Plain

Inverse AERMOD and SCIPUFF Dispersion Modeling for Farm-Level PM10 Emission Rate Assessment

2021 ◽  
Vol 64 (3) ◽  
pp. 801-817
Author(s):  
Bin Cheng ◽  
Aditya Padavagod Shiv Kumar ◽  
Lingjuan Wang-Li
Keyword(s):  
Wind Speed ◽  
Egg Production ◽  
Single Point ◽  
Dispersion Modeling ◽  
Emission Rates ◽  
Farm Level ◽  
Area Source ◽  
Inverse Dispersion ◽  
Pm10 Emission ◽  
Inverse Dispersion Modeling

HighlightsAERMOD and SCIPUFF were employed to back-calculate farm-level PM10 emission rates based on inverse modeling.Both AERMOD and SCIPUFF did not capture the diurnal and seasonal variations of farm-level PM10 emission rates.AERMOD modeling results were affected by wind speed, with higher wind speed leading to higher emission rates.Higher numbers of receptors and PM10 measurements with greater time resolution may be recommended in the future.Abstract. Air pollutant emissions from animal feeding operations (AFOs) have become a serious concern for public health and ambient air quality. Particulate matter with aerodynamic equivalent diameter less than or equal to 10 µm (PM10) is one of the major air pollutants emitted from AFOs. To assess the impacts of PM10 emissions from AFOs, knowledge about farm-level PM10 emission rates is needed but is challenging to obtain through field measurements. The inverse dispersion modeling approach provides an alternative way to estimate farm-level PM10 emission rates. In this study, two dispersion models, AERMOD and SCIPUFF, were employed to back-calculate farm-level PM10 emission rates based on hourly PM10 concentration measurements at four downwind locations in the vicinity of a commercial egg production farm in the southeast U.S. Onsite meteorological data were simultaneously recorded using a 10 m weather tower to facilitate the dispersion modeling. The modeling results were compared with PM10 emission measurements from two layer houses on the farm. Single-area source, double-area source, and double-volume source were used in AERMOD, while only single-point source was used in SCIPUFF. The inverse modeling results indicated that both SCIPUFF and AERMOD did not capture the diurnal and seasonal variations of the farm-level PM10 emission rates. In addition, the AERMOD modeling results were affected by wind speed, and higher emission rates may be predicted at higher wind speeds. The single-point source for SCIPUFF, the plume rise simplification for AERMOD, and insufficient concentration measurement resolution in response to temporal changes in wind direction may have added uncertainties to the modeling results. The results of this study suggest that more receptors covering more representative downwind locations should be considered in future modeling for farm-level emissions assessment. Moreover, ambient data collection with greater time resolution (e.g., less than one hour) is recommended to capture diurnal and seasonal patterns more rigorously. Only in this way can researchers achieve a better understanding of the effectiveness of inverse dispersion modeling for estimation of pollutant emission rates. Keywords: AERMOD, Animal feeding operations, Egg production, Farm-level emission rate, Inverse dispersion modeling, PM10, SCIPUFF.

scholarly journals Does Crop Rotation Enhance Groundwater Health? A Review of the Winter Wheat Fallow Policy in the North China Plain

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2416
Author(s):  
Ming Lei ◽  
Yuqian Zhang ◽  
Yuxuan Dang ◽  
Xiangbin Kong ◽  
Jingtao Yao
Keyword(s):  
Winter Wheat ◽  
Water Consumption ◽  
North China Plain ◽  
North China ◽  
Shallow Groundwater ◽  
Agricultural Water ◽  
The North ◽  
The North China Plain ◽  
The World ◽  
Shallow Groundwater Level

Agricultural water management is a vital component of realizing the United Nation’s Sustainable Development Goals because of water shortages worldwide leading to a severe threat to ecological environments and global food security. As an agro-intensified irrigation area, the North China Plain (NCP) is the most important grain basket in China, which produces 30%–40% of the maize and 60%–80% of the wheat for China. However, this area has already been one of the largest groundwater funnels in the world due to long-term over-exploitation of groundwater. Due to the low precipitation during the growing period, winter wheat requires a large amount of groundwater to be pumped for irrigation, which consumes 70% of the groundwater irrigation. To alleviate the overexploitation of groundwater, the Chinese government implemented the Winter Wheat Fallow Policy (WWFP) in 2014. The evaluation and summarization of the WWFP will be beneficial for improving the groundwater overexploitation areas under high-intensity irrigation over all the world. So far, there have been few attempts at estimating the effectiveness of this policy. To fill this gap, we assessed the planting area of field crops and calculated the evapotranspiration of crops based on remote-sensed and meteorological data in the key area—Hengshui. We compared the agricultural water consumption before and after the implementation of this policy, and we analyzed the relationship between changes in crop planting structure and groundwater variations based on geographically weighted regression. Our results showed the overall classification accuracies for 2013 and 2015 were 85.56% and 82.22%, respectively. The planting area of winter wheat, as the most reduced crop, decreased from 35.71% (314,053 ha) in 2013 to 32.98% (289,986 ha) in 2015. The actual reduction in area of winter wheat reached 84% of the target (26 thousand ha) of the WWFP. The water consumption of major crops decreased from 2.98 billion m3 of water in 2013 to 2.83 billion m3 in 2015, a total reduction of 146 million m3, and 88.43% of reduced target of the WWFP (166 million m3). The planting changes of winter wheat did not directly affect the change of shallow groundwater level, but ET was positively related to shallow groundwater level and precipitation was negatively related to shallow groundwater levels. This study can provide a basis for the WWFP’s improvement and the development of sustainable agriculture in high-intensity irrigation areas.

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