Simulation of nitrogen deposition in the North China Plain by the FRAME model

Abstract

Abstract. Simulation of atmospheric nitrogen (N) deposition in the North China Plain (NCP) at high resolution, 5 × 5 km 2 , was conducted for the first time by the Fine Resolution Atmospheric Multi-pollutant Exchange (FRAME) model. The total N deposition budget was 1481 Gg in this region, with 77 % from reduced N and 23 % from oxidized N, and the annual deposition rate (47 kg N ha −1 ) was much higher than previously reported values for other parts of the world such as the UK (13 kg N ha −1 ), Poland (7.3 kg N ha −1 ) and EU27 (8.6 kg N ha −1 ). The exported N component (1981 Gg) was much higher than the imported N component (584 Gg), suggesting that the NCP is an important net emission source of N pollutants. Contributions of N deposition budgets from the seven provinces in this region were proportional to their area ratios. The calculated spatial distributions of N deposition displayed high rates of reduced N deposition in the south and of oxidized N deposition in the eastern part. The N deposition exceeded an upper limit of 30 kg N ha −1 for natural ecosystems over more than 90 % of the region, resulting in terrestrial ecosystem deterioration, impaired air quality and coastal eutrophication not only in the NCP itself but also in surrounding areas including the Bohai Sea and the Yellow Sea.

Characteristics of ammonia, acid gases, and PM2.5 for three typical land-use types in the North China Plain

“…However, it is important to note that annual NH 3 levels show a slight increasing trend at the five sites. This finding is consistent with the increasing trend of NH 3 emissions during recent years in the NCP due to intensified agricultural activities (Zhang et al 2010 , 2011b ). The largest annual mean NH 3 concentration was observed at QZ (16.9 ± 5.9 μg m −3 ), followed by YC (13.8 ± 1.5 μg m −3 ), CAU (13.1 ± 1.0 μg m −3 ), ZZ (11.1 ± 2.0 μg m −3 ), and SZ (10.5 ± 1.1 μg m −3 ) (Fig.…”

“…This makes the NCP one of the greatest emitters of air pollutants (e.g., NH 3 , NO x , and SO 2 ) nationally and globally (Clarisse et al 2009 ; Zhang et al 2009 ; Gu et al 2012 ; Huang et al 2012 ) and a serious PM 2.5 pollution region in China (Wang et al 2014b ). Some studies have focused on the measurements of atmospheric NO 2 and NH 3 at various sites in the NCP (Shen et al 2009 , 2011 ; Meng et al 2011 ; Pan et al 2012 ; Luo et al 2013 ) and on estimating of emissions of NO 2 and NH 3 from anthropogenic sources (Zhang et al 2010 , 2011b ). Very few studies in the NCP have considered ambient HNO 3 measurements (Shen et al 2009 ; Luo et al 2013 ).…”

Increased nitrogen deposition alleviated the competitive effects of the introduced invasive plant Robinia pseudoacacia on the native tree Quercus acutissima

“…Each cultivation type received four N treatments: 0, 3, 6 and 12 g m −2 year −1 (designated N0, N1, N2 and N3). N0 was set as the control; N1 and N2 corresponded to levels of N deposition already recorded in some areas of northern and southern China (Lü and Tian 2007;Zhang et al 2011); N3 represented a high deposition level that may be reached in the future. There were 12 treatment combinations in total and each combination contained six pots as replicates.…”

The influence of model grid resolution on estimation of national scale nitrogen deposition and exceedance of critical loads

“…It was subsequently improved to include a detailed representation of oxidised nitrogen and sulphur deposition (Fournier et al, 2004;Dore et al, 2007;Vieno et al, 2010b) to be used for assessment of the exceedance of critical loads for nitrogen deposition and acid deposition (Matejko et al, 2009). Other regional scale applications of the model include estimation of ammonia concentrations and deposition of reduced nitrogen in Poland (Kryza et al, 2011) and application to the North China Plains (Zhang et al, 2011), an area demonstrated by remote sensing to be a global hot spot for ammonia concentrations (Clarisse et al, 2009). The relative simplicity of the model corresponds to a fast simulation time (of approximately 12 h for a 1 km resolution using 24 processors on a High Performance Computational Linux cluster).…”