Article pubs.acs.org/est
Cite This: Environ. Sci. Technol. 2018, 52, 3926−3934
Identifying Ammonia Hotspots in China Using a National Observation Network Yuepeng Pan,*,† Shili Tian,† Yuanhong Zhao,‡ Lin Zhang,‡ Xiaying Zhu,§ Jian Gao,∥ Wei Huang,† Yanbo Zhou,† Yu Song,⊥ Qiang Zhang,# and Yuesi Wang† †
State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China ‡ Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China § National Climate Center, China Meteorological Administration, Beijing 100081, China ∥ State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China ⊥ Department of Environmental Science, Peking University, Beijing 100871, China # Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China S Supporting Information *
ABSTRACT: The limited availability of ammonia (NH3) measurements is currently a barrier to understanding the vital role of NH3 in secondary aerosol formation during haze pollution events and prevents a full assessment of the atmospheric deposition of reactive nitrogen. The observational gaps motivated us to design this study to investigate the spatial distributions and seasonal variations in atmospheric NH3 on a national scale in China. On the basis of a 1-year observational campaign at 53 sites with uniform protocols, we confirm that abundant concentrations of NH3 [1 to 23.9 μg m−3] were identified in typical agricultural regions, especially over the North China Plain (NCP). The spatial pattern of the NH3 surface concentration was generally similar to those of the satellite column concentrations as well as a bottom-up agriculture NH3 emission inventory. However, the observed NH3 concentrations at urban and desert sites were comparable with those from agricultural sites and 2−3 times those of mountainous/forest/grassland/waterbody sites. We also found that NH3 deposition fluxes at urban sites account for only half of the emissions in the NCP, suggesting the transport of urban NH3 emissions to downwind areas. This finding provides policy makers with insights into the potential mitigation of nonagricultural NH3 sources in developed regions.
1. INTRODUCTION The intensive human activities of past decades have significantly affected the global nitrogen cycle by fixing N2, both deliberately for fertilizer production and inadvertently during fossil fuel combustion.1 Rapid increases in reactive nitrogen emissions to the atmosphere have resulted in serious reactive nitrogen pollution in the air and excessive nitrogen deposition in natural ecosystems worldwide.2 To reduce these adverse impacts, previous efforts have been made to reduce oxidized nitrogen, such as NOx emissions, whereas a reduction in reduced nitrogen (NHx), especially in ammonia (NH3) emissions, has not been fully implemented.3,4 Between 2002 and 2013, NH3 levels over agricultural regions experienced significant increasing trends across the U.S. (2.6% year−1), the European Union (1.8% year−1), and China (2.3% year−1), as observed from satellite.5 It is demonstrated that the deposition of reactive nitrogen in the U.S. has recently shifted from nitrate-dominated to ammonium-dominated conditions,6 while NHx plays a key role in atmospheric © 2018 American Chemical Society
nitrogen deposition in China, contributing from 71% to 88% of the total depositions in hotspot regions, such as the North China Plain (NCP).7 In addition, there is increasing evidence indicating the critical role of NH3 in the formation of secondary aerosols.3,8 Extensive observations reveal that ammonium and related sulfate and nitrate contribute 10% and 35% of the particulate mass during haze events, respectively.9 The profound role of NH3 in haze pollution has also been highlighted by recent studies arguing its capability to neutralize aerosol pH, which can strongly enhance the formation of sulfate through the heterogeneous oxidation of SO2 by NO2.10 All evidence leads to increasing concerns that future progress toward reducing the nitrogen-related impacts on Received: Revised: Accepted: Published: 3926
October 11, 2017 February 24, 2018 March 2, 2018 March 2, 2018 DOI: 10.1021/acs.est.7b05235 Environ. Sci. Technol. 2018, 52, 3926−3934
Article
Environmental Science & Technology aerosol pollution and nitrogen deposition will be increasingly difficult without a well-resolved spatiotemporal picture of NH3. Compared with the increasing number of rich data sets of satellite observations of atmospheric NH3 concentration,5,11,12 surface network data sets covering large geographical areas are still lacking,13,14 especially in China.15,16 To fill the observational data gaps, in this study, a year-round campaign was launched to measure monthly NH3 by using uniform protocols with a diffusive technique and other supporting data across China. The objectives of the present study are to (1) identify the hotspots of NH3 in China, (2) explore the variability of atmospheric NH3, and (3) present the implications for mitigating NH3 on a national scale. To our knowledge, this study represents the first national observations of NH3 in China, especially in background regions, setting a baseline against which concentration changes resulting from future emission control strategies can be assessed. The data collected here are unique and will advance our understanding of atmospheric chemistry and related processes. The results will also be valuable for scientists and policy makers to estimate excess nitrogen inputs into ecosystems and validate atmospheric chemistry and transport models, including seasonal trends and regional variability.
2. MATERIALS AND METHODS 2.1. Ammonia Sampling Networks. Accurately measuring NH3 concentrations in the air is not an easy task because of the interference of particle-borne ammonium.17 However, this problem can be solved using the well-known fact that when ambient air passes through a tube, gas molecules diffuse much more quickly than particles onto the tube wall.18 The main disadvantage of this manual sampling method (hereafter referred to as the diffusive sampling technique) is its low temporal resolution when high-frequency measurements (e.g., hourly) are needed. However, such a simple and cost-effective technique can increase the spatial resolution of the measurement and aid in screening studies to evaluate monitoring site locations14 or in long-term measurements for trend analyses.13 For large-scale surveys of NH3 variability across China, starting in September 2015, we implemented a passive NH3 monitoring network based on the diffusive technique with monthly integrated measurements at 53 sites. The current Ammonia Monitoring Network in China (AMoN-China) was established mainly based on the Chinese Ecosystem Research Network (CERN, http:// www.cern.ac.cn/0index/index.asp) and the Regional Atmospheric Deposition Observation Network on the NCP (READ-NCP).7 AMoN-China includes 13 mountain and forest, 5 water body, 7 grassland, 4 desert, 11 farmland, and 13 urban/suburban/ industrial sites (Figure 1). All of the sites are selected to be far away (>1 km) from a known source of NH3 (e.g., feedlot areas) considering that the NH3 concentrations decrease significantly away from the source (several hundred meters).19 More details on the site selection and siting protocols can be found in Supporting Information (SI, text and Table S1). Sites were assigned to regions to assess whether the seasonal variations and spatial distributions of NH3 concentrations show different patterns in different broad areas of China (Figure 2). The regions are defined as follows: the NCP (11 sites), northeast China (NE, 9 sites); northwest China (NW, 5 sites), southeast China (SE, 13 sites), southwest China (SW, 9 sites), and Central China (Central, 6 sites). The regions were chosen based on the spatially different geographical, climate, and available characteristics of the sites. 2.2. Chemical Analysis and Validation of Ammonia Samplers. The year-round sampling campaign was carried out
Figure 1. Spatial distribution of ammonia concentrations observed from the surface network (site) versus satellite column data (grid) in China. The detailed surface observation site information can be found in Table 1 and SI. Satellite NH3 total column distributions were derived from the infrared atmospheric sounding interferometer (IASI) aboard MetOp-A for the year 2015. We collected the observations from morning overpass time (9:30 LTC) and filtered the columns with relative error above 100% following procedures presented in Van Damme et al.12 The filtered IASI satellite columns were then mapped to a 0.25° × 0.25° horizontal resolution by averaging available observations within each grid cell. The provincial boundary layer with a scale of 1:4,000,000 was obtained from the National Geomatics Center of China (http://ngcc. sbsm.gov.cn/). Maps were generated based upon a geospatial analysis using ESRI ArcGIS software (version 10.1, http://www.esri.com/software/arcgis/ arcgis-for-desktop).
from September 2015 to August 2016. In total, 636 samples of NH3 were collected using diffusive samplers (Analysts, CNR-Institute of Atmospheric Pollution, Roma, Italy). The passive sampler is made of polyethylene and employs a phosphorus-acid-impregnated glass microfiber filter as an adsorption layer. The sampler is a robust and reliable tool for measuring atmospheric NH3; the development, theory, laboratory validation, and field application of the sampler have been fully described elsewhere.20 During sample collection, the passive samplers were exposed at a height of 2 m with their open ends oriented downward to exclude the dry deposition of particles. In addition, the sampler was protected from rain and direct sunlight by an inverted stainless-steel shield. After exposure, the passive samplers were returned to Beijing for analysis at the State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences. In the laboratory, 5 mL of deionized water was used to extract the exposed samples, and the ammonium ion concentration in the extraction was determined via ion chromatography with a cation separator and conductivity detector (Dionex Corp., Sunnyvale, CA, USA). The ambient NH3 concentrations (cNH3, μg m−3) were calculated based on the amount of ammonium (mNH+4 , μg) 3927
DOI: 10.1021/acs.est.7b05235 Environ. Sci. Technol. 2018, 52, 3926−3934
Article
Environmental Science & Technology
Figure 2. Seasonal variations of ammonia concentrations observed from the surface network (53 sites) in China.
collected on the exposed filter and the sample collection time (t, hour), which can be expressed using the following equation: 2
c NH3 = 9.06 × 10 ×
passive sampler. This formula assumes that the average temperature (T) during sampling is 20 °C. In the case that
(
m NH+4
293
1.8
)
temperature is different, a correction coefficient of 273 + T is applied to cNH3. Such a temperature effect is negligible, with the corrected NH3 concentrations being less than 5% at each 5 °C interval. Most of the sampling sites belong to the CERN,
t
where 9.06 × 10 is the conversion factor from the manufacturer’s description, which is a function of the parameters of the 2
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DOI: 10.1021/acs.est.7b05235 Environ. Sci. Technol. 2018, 52, 3926−3934
Article
Environmental Science & Technology
Figure 3. Comparisons of passive diffusion sampler to the continuously active analyzers of MARGA and DELTA. Ammonia concentrations are aggregated to monthly data points.
where the temperature was measured at each site using an automatic meteorological observation instrument (Milos520, Vaisala, Finland). In the case that the temperature was not measured at the site, the nearest meteorological observation station available on the China Meteorological Data Sharing Services System Web site (http://cdc.cma.gov.cn/) was used in this study. Before and during the study period, comparisons with automatic reference methods were performed during two campaigns. During 2013, the Analysts passive sampler (monthly samples) were compared to the continuously active analyzers of MARGA (a model ADI 2080 online analyzer for the Monitoring of Aerosols and Gases, Applikon Analytical B.V. Corp., The Netherlands, aggregated to monthly data points), showing a linear regression slope of 1.10 ± 0.14 and R2 of 0.94 (Figure 3a). This strong linear relationship indicates that the Analyst passive sampler is reliable for such a study, assuming that the NH3 concentration values measured by the wet chemistry instruments are more accurate.17 During this study, we also compared the Analysts passive samplers to DELTA (Denuder for Long-Term Atmospheric Sampling, Centre for Ecology and Hydrology, UK) at a monthly resolution. This comparison shows a linear regression slope close to unity (1.04 ± 0.17) and an intercept of 2.06 ± 2.23 μg m−3 (Figure 3b); the bias appears to be systematic and thus does not impact the patterns of the spatial distributions or seasonal variations. 2.3. Dry Deposition Velocity Simulation. The inferential technique,7 which combines the measured NH3 concentration and a modeled dry deposition velocity (Vd) from the Goddard Earth Observing System-Chem (GEOS-Chem; http://geos-chem.org) chemical transport model, was used to estimate the dry deposition fluxes of NH3. The GEOS-Chem simulation of nitrogen dry deposition has been described by Zhao et al.21 The model is driven by the latest version of GEOS-FP assimilated meteorological fields from the NASA Global Modeling and Assimilation Office (GMAO), which has been applied to analyze particle pollution over the NCP.22 Our simulation used the native GEOC-FP resolution of 0.25° latitude ×0.3125° longitude over East Asia (70°E−140°E, 15°N−55°N) and a coarse resolution of 2° latitude ×2.5° longitude over other places of the world. Follow the standard big-leaf resistance-in-series model,23 Vd in GEOS-Chem was calculated by considering the aerodynamic resistance, the boundary layer resistance, and the surface resistance. We did not consider air−surface bidirectional exchange of NH3,24 and we treated the NH3 fluxes as uncoupled emission and deposition processes. The model was run from 2014 to 2016, and we applied the monthly Vd at a reference height of 2 m to the observed NH3 concentrations to obtain monthly NH3 dry deposition fluxes. The NH3 monthly dry deposition fluxes calculated using the monthly mean concentration and Vd are
approximately 7% higher than the hourly integrated values, reflecting some small covariance between the NH3 concentrations and Vd in the model.
3. RESULTS AND DISCUSSION 3.1. Spatial Distribution of Ammonia in China. Large spatial differences in NH3 concentrations were found at the 53 sites in the sampling network, with annual mean NH3 concentrations during the 1-year period ranging from 1 to 23.9 μg m−3, as illustrated in Table 1 and Figure 1. The upper range is higher than the concentrations observed in China around 2012 (0.3− 13.1 μg m−3)16 and Asia around 2000 (
