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Sensitivity of summer ozone to precursor emission change over Beijing during 2010–2015: A WRF-Chem modeling study
Atmospheric Environment 218 (2019) 116984
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Sensitivity of summer ozone to precursor emission change over Beijing during 2010–2015: A WRF-Chem modeling study
T
Wei Weia,b,∗, Yue Lia, Yunting Rena, Shuiyuan Chenga,b, Lihui Hana,b a b
Department of Environmental Science and Engineering, Beijing University of Technology, Beijing, 100124, China Key Laboratory of Beijing on Regional Air Pollution Control, Beijing, 100124, China
ARTICLE INFO
ABSTRACT
Keywords: Surface ozone Sensitivity Precursor emission change WRF-Chem simulation
Beijing as the capital of China releases massive air pollutants and experiences the worsening summer O3 pollution recently. This study estimates Beijing ozone precursor emission, anthropogenic VOCs (AVOCs) being 325.3 kilotons in 2010, 231.8 kilotons in 2013 and 190.7 kilotons in 2015 and NOx being 211.3 kilotons in 2010, 238.3 kilotons in 2013 and 166.2 kilotons in 2015. Then, we conduct surface O3 simulation based on WRF-Chem through using different precursor emissions, to evaluate the influence of precursor control measures on Beijing O3. From 2010 to 2013, AVOCs reduction in Beijing would lead to O3 decrease in urban and suburban areas and O3 increase in some parts of northern rural areas; while from 2013 to 2015, AVOCs and NOx reductions would produce O3 increase in urban and northern suburban areas and O3 decrease in southern suburban and northern rural areas. Overall, the synergic reduction during 2010–2015 could effectively mitigate summer O3 pollution over Beijing, with daily maximum 1-h ozone (DAM1h O3) reduction exceeding 3 ppb. Finally, based on 2015 emission condition, 30% NOx and 30% VOCs emission reduction are further simulated to study O3-NOx-VOCs sensitivity over Beijing. The simulated DAM1h O3 reduction due to NOx- or VOCs-reduction shows that O3 is predominantly sensitive to VOCs in urban and northern suburban Beijing, but seems to be control more by the mixed chemistry in southern suburban and northern rural Beijing. However, NOx-sensitive condition is never found in rural Beijing. The distribution of simulated H2O2/HNO3 for the distinguished VOCs- and NOx-sensitive grids shows that 95th percentile for VOCs-sensitive distribution and 5th percentile for the NOx-sensitive distribution are 2.48 and 1.17 in all simulated days. According to the determined transition values, most Beijing is under VOCs-sensitive regime on the condition of 2015 precursor emission.
1. Introduction Tropospheric or surface ozone (O3) is a major concern for air quality due to its adverse impact on human health (Lippmann, 1993) and ecosystem (U.S. NRC, 1991). Besides, O3 is a significant greenhouse gas with the third highest radiative forcing just after carbon dioxide (CO2) and methane (CH4) (IPCC, 2013). Surface ozone originates from stratospheric troposphere exchange and photochemical reactions between volatile organic compounds (VOCs) and nitrogen oxides (NOx). In between, photochemistry is the most important source and responsible for ~90% of surface ozone, approximately 4500 Tg per year in global troposphere, with remaining approximately 500 Tg transported from stratosphere (IPCC, 2013). Therefore, O3 has received worldwide attention from both the scientific and regulatory communities. In the past two decades, for the rapid urbanization and industrialization causing great increases in anthropogenic emissions into
∗
atmosphere, China has experienced severe air pollution problems, presented as fall and winter fine particulate matter pollution and summertime ozone pollution. Wang et al. (2017) reviewed China's ozone pollution and found that Beijing located in the Northern China Plain has the highest peak ozone concentrations. In the Northern China Plain, aircraft measurement by Tang et al. (2009) showed that summertime boundary-layer ozone increased by 2% per year during 1995–2005 and the daily maximum1-hour ozone (DAM1h O3) in urban Beijing also increased at a rate of 1.3% per year during 2001–2006; Ma et al. (2016) found an increase in daily maximum 8-h ozone (DAM8h O3) at Shangdianzi that is a background station in Beijing-Tianjin-Hebei region (BTH), at a rate of 1.1 ppb per year during 2003–2015; Sun et al. (2016) conducted a non-continuous observations at Mt. Tai and reported an ozone increase of 1.7%~2.1% per year during the summer months during 2003–2015. The air quality data published by China's national and local environmental agencies since 2013 (http://www.
Corresponding author. Key Laboratory of Beijing on Regional Air Pollution Control, Beijing, 100124, China. E-mail address: [email protected] (W. Wei).
https://doi.org/10.1016/j.atmosenv.2019.116984 Received 10 April 2019; Received in revised form 15 September 2019; Accepted 17 September 2019 Available online 19 September 2019 1352-2310/ © 2019 Elsevier Ltd. All rights reserved.
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mep.gov.cn), also reveals that surface O3 concentrations in major urban areas have continued to increase during 2013–2016. The highest 90th percentile of DAM8h O3 in 74 cities increased from 69.5 ppb in 2013 to 75.0 ppb in 2016, the percentage of nonattainment cities increased from 23% to 38%, and Beijing still has the highest 90th percentile of DAM8h O3 level (~93.3 ppb at 273 K, 101.3 kPa). All of these results point to a worsening photochemical pollution in China's major developed regions, especially in Beijing and its surrounding areas. Severe ozone pollution is consistently associated with the large emission of anthropogenic precursors. Oxidation of VOCs promotes RO2 radical production, RO2 enhances the conversion of NO to NO2, and NO2 photolysis results in the production and accumulation of O3. High concentration of NOx is the direct precursor of O3 pollution in developed region. Multi-resolution emission inventory for China (MEIC, http://meicmodel.org/) shows that in 2012, NOx emission in China and BTH reached 29.16 million tons and 3.04 million tons respectively, and annual NOx emission intensity exceeded 15 ton·km−2 in BTH. Then, with the implementation of China Air Pollution Prevention and Control Plan 2013–2017 (CAPPCP), in 2016 NOx emission in China and in BTH decreased to 22.51 million tons and to 2.29 million tons respectively, with a reduction of ~25%. On the other hand, anthropogenic VOCs (AVOCs) emission little changed during 2012–2016, remaining around ~28.0 million tons per year in China and ~2.6 million tons per year in BTH reported by MEIC. It throws a doubt whether NOx reduction brings about ozone increase of eastern China, for the complicated nonlinear chemistry involved in photochemical ozone formation. Thus, it is essential to capture the chemistry nature of photochemical ozone before developing the effective surface ozone control strategies. In China, three-dimensional air quality model has been widely applied in determination of NOx-sensitive or VOCs-sensitive in O3 photochemical production (Liu et al., 2010; Tie et al., 2013; Wang et al., 2015), apportionment of ozone contributing sources (Wang et al., 2009; Li et al., 2012) and evaluation of precursor control strategies (Xing et al., 2011; Qu et al., 2014). Liu et al. (2010) found the significant contribution of gas-phase chemistry and vertical transport to summer O3, and indicated a VOClimited O3 chemistry in winter, NOx-limited in summer, and either VOCor NOx-limited in spring and autumn over most of eastern China. Xing et al. (2011) applied CMAQ model in three megacities of eastern China (Beijing, Shanghai and Guangzhou), and concluded NOx control would likely be more effective than anthropogenic VOCs control during periods of heavy photochemical pollution. Tie et al. (2013) employed WRF-Chem model in Yangtze River Delta, showed a VOC-limited condition in Shanghai and its surrounding regional area, and suggested the VOCs control strategy to mitigate ozone pollution there. It can be seen that the nonlinear response of photochemical ozone to precursors over East China is still speculative and far from being understood. And recently with the considerable change in precursors’ emissions under CAPPCP, the chemistry nature of photochemical ozone over China may vary and will make this scientific issue more complex. This study aims to examine the sensitivity of surface ozone to precursor emission change over Beijing during 2010–2015. In Beijing, the seasonal variation of ozone has a summer maximum and winter minimum, and ozone pollution frequently occurs during July to August (Cheng et al., 2017). Thus, we focus on the vulnerable season of summer, mainly evaluate the influence of precursor reduction on Beijing summer ozone, and determine the photochemical ozone formation regime for summer Beijing, through a WRF-Chem modeling study. This study would be helpful for better understanding the roles played by precursor reduction and developing ozone control strategy in China.
year 2010, 2013 and 2015, according to following equations (1) and (2):
EVOC , s =
Aj × EFj, voc × (1
j, voc )
j
ENOx =
Aj × EFj, nox × (1
j, nox )
j
× Pj, s
(1) (2)
Where, E is the annual emission of AVOCs species s or NOx (ton); j is the emission source; Aj is the annual activity data of source j, mainly including fuel consumptions (kiloton), industrial product yields (kiloton), solvent consumptions (kiloton), vehicle kilometers travelled (VKT, kilometer), etc.; EFj is the uncontrolled VOCs or NOx emission factor for source j, expressed by g VOC/kg fuel, g VOC/kg product, g VOC/kg solvent or g VOC/km VKT; and ηj is the average removal efficiency of VOCs or NOx in Beijing source j (%); Pj,s is the mass proportion of organic species s in VOCs released from source j (%). In this study, total 150 types of sources are considered, mainly including industrial and residential fuel combustions, road and non-road transportations, petrochemical industries, industrial paint coating and ink printing, gasoline evaporation, oil storage and transportation, and so on. For these sources, previous inventory studies made literature research and summarized a set of EFs of AVOCs and NOx suitable for China (Wei et al., 2008; MEEC, 2014; CNEMC, 2016). The corresponding activity data for studied year are from the statistical year books. In detail, the consumption amounts of fossil fuels in industrial boilers and residential stoves from CNSB (2011a, 2014a and 2016a), the annual yields of various industrial products from CNSB (2011b, 2014b and 2016b), the vehicle population from CNDRC (2011, 2014 and 2016), and VKT from Lang et al. (2016) respectively. AVOCs and NOx control in industrial sources are respectively from the investigation of Li et al. (2017) and CNEMC (2016). And the species mass proportion of VOCs released from various sources are from Wei et al. (2008). 2.2. WRF-chem model configuration For ozone simulation, the option of regarding gas-phase chemical mechanism is especially important, and SAPRC-99 mechanism (Carter, 2007) is applied for its complicated VOCs grouped classes and related reactions. The aerosol module is the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) that uses 4 volatility bins with the Volatility Basis Set (VBS) for organic aerosol evolution. And in physical options, Purdue Lin is selected as microphysics option, Goddard as shortwave radiation option, RRTMG as longwave radiation, NOAH as land surface option, Monin-Obukhov as surface layer option, Yonsei University Scheme (YSU) as planetary boundary layer option, and KainFritsch as cumulus option. While considering the significant influence of aerosols on meteorology in China (Yang et al., 2016), this study turns on the aerosol feedback. In our simulation, the metrological initial and boundary conditions are predicted based on U.S. geological survey terrain and land use data (https://www2.acom.ucar.edu/wrf-chem) and U.S. national center for environmental prediction final operational global analysis data (http://rda.ucar.edu). Then the simulation is performed over three domains, as shown in Fig. 1. Domain 1 covers East Asia at a 36 km resolution, Domain 2 covers North-Eastern China at a 12 km resolution and Domain 3 mainly covers Beijing with a 4 km resolution. The simulations of Domain 1 and 2 mainly provide the boundary conditions, and the simulation of Domain 3 is used for air quality prediction analysis. Sharma et al. (2017) reviewed a large number of studies on surface ozone simulation and suggested the horizontal domain resolution of < 10 km, considering that coarse resolution always deteriorates simulation performance due to dilution of precursor emissions and premature mixing of urban and background air masses in coarser grid. Our horizontal resolution in Domain 3 (4 km × 4 km) satisfies this recommendation. For Domains 1 and 2, the anthropogenic emissions of gaseous pollutants (SO2, NOx, CH4, CO, NH3 and VOCs groups) and particulate matter (OC, EC, PM2.5
2. Methodologies 2.1. Emission estimate of precursors (AVOCs and NOx) An up-bottom approach is adopted to estimate speciated AVOCs emission and NOx emission at a high spatial resolution over Beijing for 2
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Fig. 1. WRF-Chem modeling domains (red block means the meteorological station and black dot mean the air quality station). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2. Time series of simulated and observed 1-h O3 in four stations (the red solid lines refer to the simulated O3, and the black dash lines refer to the observed O3). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
and PM10) are taken from MEIC (www.meicmodel.org); for Domain 3, VOCs and NOx emissions are from this study and other pollutants ’emissions were from Li et al. (2015) and Chen et al. (2017).
reduction scenario, to explore the formation regime of Beijing photochemical O3 during summer. 2.4. Model performance of S2015 simulation
2.3. Simulation scenarios design
Accurate modeling of ozone concentration is very complex due to its high reactivity with other pollutants and meteorological interactions. In meteorological evaluation, the Mean Bias (MB) for temperature at 2-m (T2), relative humidity at 2-m (HR2) and wind speed at 10-m (WS10) at MET station (as shown in Fig. 1) reaches 0.2K, −11.0% and 0.5 m/s, generally agreeing with the criteria promoted by Emery et al. (2001). In the evaluation of chemical simulations, four air quality stations of DS, GY, LLH and MYX (as shown in Fig. 1) are selected, which respectively represents the eastern urban area, western urban area, southern suburb area and northern rural area. The model well reproduces the chemical observations, with Normalized Mean Bias (NMB) of −40%~-24% for DAM1h O3, +7%~+18% for NOx and −14% ~-36% for CO and Normalized Mean Error (NME) of 28%~56% for
Here we select the same meteorological condition of July of 2015 and use different precursors' emissions in Domain 3 over Beijing, to predict Beijing summer O3 and its response to the change of precursors' emissions. The WRF-Chem simulations in Domain 3 based on 2010, 2013 and 2015 precursors' emissions are considered as the simulation scenarios of S2010, S2013 and S2015, in respective. The difference in predicted O3 of various simulations implies the independent influence of corresponding reduction in precursors’ emissions on Beijing summer O3 during 2010–2015. Then, based on 2015 emission condition, we further design another two reduction scenarios, 30% NOx and 30% VOCs emission reduction, and additionally simulate O3 for July of 2015 under NOx- or VOCs3
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DAM1h O3, 41%~68% for NOx and 42%~60% for CO. All NMBs and NMEs except NOx at MYX station are within the threshold for satisfactory performance proposed by the U.S. EPA (2013). And Fig. 2 shows that O3 temporal trend is successfully simulated, as well as the peak magnitudes. The predicted and observed value for DAM1h O3 is 83.7 ppb and 89.1 ppb at DS station, 83.2 ppb and 96.0 ppb at GY station, 66.7 ppb and 79.5 ppb at LLH station, and 73.6 ppb and 88.9 ppb at MYX station.
emission was predominantly from fossil fuel combustion in industrial boilers, residential stoves, road vehicles and non-road engines, respectively with the contribution of 16.2%~31.4%, 9.7%~11.3%, 49.1% ~53.7% and 9.8%~20.6% in our studied period. From 2010 to 2013, Beijing NOx emission presented a slight increasing trend and was contributed mainly by heavy-duty diesel vehicles related to freight transportation. Then from 2013 to 2015, Beijing NOx emission was brought down by 72.1 kilotons, which mainly from industrial fuel combustion (by 29.9 kilotons) and heavy-duty diesel vehicles (by 33.5 kilotons). For the spatial distribution, related power plants locate in CY, FT and SJS urban districts, major industrial boilers locate in FS, SY and CP suburban districts, vehicles mostly travel in urban and suburban roads, non-road engines mainly include flights in airport located in SY suburban district and machineries allocated in suburban building sites. Thus, NOx emission in southern suburbs of Beijing was largest, followed by northern suburbs and urban areas, and NOx emission in rural areas was lowest, as shown in Fig. 3. During 2010–2015, the bigger reduction in NOx emission occurred in urban districts of SJS (10.8 kilotons) and CY (8.9 kilotons), in suburban districts of FS (6.3 kilotons), DX (3.1 kilotons) and CP (2.5 kilotons).
3. Results and discussion 3.1. Emission change of precursors during 2010–2015 3.1.1. AVOCs emission change According to this study, AVOCs emission in Beijing reached around 325.3 kilotons in 2010 year, 231.8 kilotons in 2013 year and 190.7 kilotons in 2015 year, with a noticeable reduction of 41.3% during 2010–2015. The massive AVOCs emission was attributed to industrial solvent utilization (30.0%~33.3%), road vehicles (15.8%~23.6% from tail gas and 7.6%~10.3% from gasoline evaporation), petrochemical industries (19.8%~21.2%) and coal combustion in residential stoves (10.0%~11.8%). During the studied period, Beijing AVOCs emission reduction was contributed mainly by road vehicles (46.6 kilotons), industrial solvent utilization (43.1 kilotons) and petrochemical industries (23.9 kilotons). It resulted from a series of VOCs emission limits recently implemented in Beijing, including vehicle tail gas limits (DB11/ 946–2013 for light-duty gasoline vehicle, DB11/965–2013 for heavyduty vehicle, DB11/120–2014 for motorcycle), fossil oil vapor emission limits (DB11/206–2010 for oil store, DB11/207–2010 for oil tank truck, DB 11/208–2010 for service station), and also resulted from the industrial structure adjustment in Beijing, including restricting petrochemical and pharmaceutical manufacturing and to-be-eliminating printing and textile industry (http://www.ndrc.gov.cn). For example, in road vehicle sector, the elimination of gasoline vehicles never satisfying Emission Standards II brought about 49.7 kilotons VOCs reduction during 2010–2015; while new vehicles during that period only produced 11.8 kilotons VOCs emission increment. In Beijing, petrochemical manufacturing factories assemble in an industrial park located in FS district (southwestern suburb); industrial solvents are mostly utilized in automobile manufacturing, electric components manufacturing and printing, which distributed in DX and TZ districts (southeastern suburb) and SY district (northeastern suburb); road vehicle transportation depends heavily on population density and is allocated in urban and suburban roads; residential coal combustion dominantly occurs in southern and eastern suburbs and northern rural areas. As a whole, more AVOCs are released in urban areas, eastern and southern suburban areas than in northern suburban and rural areas, as shown in Fig. 3. The AVOCs emission reduction trend was: southern and eastern suburban areas > urban and northern suburban areas > rural areas. Then, to comply with emission input of air quality model, AVOCs emissions are further speciated into 28 assembled groups according to SAPRC99 mechanism. In result, Beijing AVOCs is composed primarily of ALK1, ALK2, ALK3, ALK4, ALK5, ETHE, OLE1, OLE2, BENZENE, ARO1, ARO2, MEOH, ACTE, MEK, PROD2, HCHO and CCHO, with the mass proportion of 2.93%~2.96%, 2.48%~2.68%, 4.10%~4.89%, 11.47%~13.07%, 6.49%~6.78%, 4.70%~4.91%, 9.24%~9.70%, 7.18%~8.41%, 4.52%~4.56%, 8.01%~8.20%, 12.13%~12.84%, 1.25%~1.59%, 1.64%~1.73%, 5.07%~5.69%, 4.62%~5.68%, 1.08% ~1.11% and 0.86%~0.92%. The change in chemical composition was not big during 2010–2015, due to the relatively even reduction of AVOCs from major emission sources.
3.2. Influence of AVOCs and NOx reduction on surface ozone Normally, in the conditions with relatively high VOCs/NOx ratios, photochemical O3 production is limited by NOx availability and it will increase with increasing NOx concentrations and be less sensitive to VOCs concentration change; while in conditions with relatively low VOCs/NOx ratios, O3 production is limited by radical availability and NOx inhibition, and O3 will increase with increasing VOCs concentration and decrease with increasing NOx concentration. Through combining with biogenic VOCs (BVOCs) emission (Chen et al., 2017), the ratio of VOCs (AVOCs + BVOCs) to NOx was calculated and introduced in Fig. 3. It can be seen that during 2010–2015, the low VOCs:NOx of < 2.0 continuously happened in urban areas and suggested a potential VOCs-sensitive condition and the active short-time ozone precursors; the high VOCs:NOx of 3.0–5.0 continuously happened in western and northern rural areas and possibly suggested a low VOCssensitive condition and the ageing ozone precursors; while northern and southern suburbs seem to move towards lower VOCs:NOx condition, for the anthropogenic emissions increasing with the urbanization development in these areas. It seems a conversion of the lower VOCssensitive regime into the higher VOCs-sensitive regime in Beijing suburbs during 2010–2015. Comparison between S2013 simulation to S2010 simulation shows that from 2010 to 2013, with a 28.7% reduction in VOCs emission and a 12.2% growth in NOx emission, DAM1h O3 would drop over the most part of Beijing as shown in Fig. 4(a), around by > 4 ppb in urban areas and eastern and northern suburbs, which might associate simultaneously with AVOCs emission reduction and NOx emission increase and reflects a potential VOCs sensitivity condition there. However, in southwestern suburbs, DAM1h O3 would occur a tiny decrease of 0–1 ppb although with the big AVOCs emission reduction in petrochemical industrial park, implying the low VOCs-sensitive condition there. In some parts of northern rural areas, DAM1h O3 would rise by 1–2 ppb, which indicates the influence of NOx increase on the NOxsensitivity region. Then, from 2013 to 2015, a continuous reduction in AVOCs emission and a fresh reduction in NOx emission would bring about a rise in DAM1h O3 of > 4 ppb in eastern urban and eastern suburban areas and around 1–3 ppb in western urban and northeastern suburban areas, but a fall in DAM1h O3 of 1–3 ppb in southern and western suburban areas and of > 2 ppb in northern rural areas, as shown in Fig. 4(b). The ozone increase in the urban areas and its adjacent north-east suburban areas implies a potential NOx-titration regime, where VOCs/NOx emission ratio lower than 1.0. And the ozone decrease in southern and western
3.1.2. NOx emission change In Beijing, annual NOx emission reached 211.3 kilotons in 2010 year, 238.3 kilotons in 2013 year and 166.2 kilotons in 2015 year. NOx 4
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Fig. 3. Spatial distribution of anthropogenic VOCs and NOx emissions and VOCs/NOx emission ratios over Beijing during 2010~2015 (eastern urban areas include DC and CY districts, western urban areas include XC, HD, FT and SJS districts, southern suburbs include FS, DX and TZ districts, northern suburbs include CP and SY, and rural areas include MTG, YQ, HR, MY and PG districts).
suburban areas and northern rural areas might associate with the NOx or VOCs emission reduction where VOCs/NOx emission ratio higher than 3.0. Overall, in the whole studied period of 2010–2015, the synergic reduction in VOCs emission by 41.3% and in NOx emission by 21.7% could obtain an evident ozone reduction all over Beijing, with DAM1h O3 decrease higher than 3 ppb, as presented in Fig. 4(c). According to Cheng et al. (2017), the average O3 during summer Beijing reached about 76 ppb in 2010, 68 ppb in 2013, and 80 ppb in 2015. And Ma et al. (2016) measured that DAM1h O3 significantly increased during the period of 2013–2015, compared to those during the period of 2004–2012. In addition, we also captured the monitored O3 in Beijing air quality stations, and found that DAM1h O3 in July of 2015 changed approximately by +10.2% in urban Beijing, +13.1% in
northern suburban Beijing and −7.5% in northern rural Beijing, compared to July of 2014. These trends are well consistent with our simulation results. However, the observed ozone is a comprehensive result of precursors' emissions, regional transport and meteorological factors. And our simulation results only present the role of local precursor's emissions. 3.3. Assessment of O3–VOCs-NOx sensitivity To assess sensitivity of ozone to its precursors, the indicators of species ratios involved in ozone photochemistry and their transition values were studied and determined. These indicators include H2O2/ HNO3, H2O2/(O3+NO2), O3/NOx, O3/NOy, HCHO/NOy and HCHO/ NO2. Values lower than the suggested transition values indicate a VOCs5
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Fig. 4. Monthly average difference in simulated DAM1h O3 for July of 2015 (a) between S2013 and S2010, (b) between S2015 and S2013, and (c) between S2015 to S2010
sensitivity chemistry, while values higher than the suggested transition values mean a NOx-sensitivity chemistry. Liu et al. (2010) used CMAQ model in China and suggested H2O2/HNO3 as the more robust indicator for O3 chemistry. Here, we presented the simulated H2O2/HNO3 over Beijing during afternoon (12:00–18:00) based on S2010, S2013 and S2015, as shown by Fig. 5. For the transition value of H2O2/HNO3, value of 0.2 was originally proposed by pioneer researches of Lu and Chang (1998) and Sillman et al. (1997). Then, Zhang et al. (2009) adjusted H2O2/HNO3 transition value to 2.4 for North America, and Liu et al. (2010) suggested 1.6 to fit China atmospheric condition. Based on the transition value of 0.2, VOCs-sensitivity regime is only given in center and eastern urban areas (DC, XC and CY districts), and the most areas of Beijing would be under NOx-sensitivity condition. While based on the adjusted value of 1.6, most of Beijing except northern and western rural areas would be under VOCs-sensitivity condition. Therefore, it is essential to further explore the sensitivity of Beijing photochemical ozone to its precursors. According to the simulated H2O2/HNO3 in Fig. 5, the chemistry regime of Beijing photochemical ozone changes towards VOCs-sensitive condition in S2013 compared to S2010, especially in urban and south suburban areas. However, it reverts to the S2010 chemistry nature in S2015. Thus, we aim at 2015 emission condition, give a 30% NOx and a 30% AVOCs emission reduction, and simulate another two emission
scenarios to conduct Beijing ozone sensitivity research. Sillman and He (2002) proposed the definition of NOx- or VOCssensitive condition: (a) NOx-sensitive: O3 in the scenario with reduced NOx is lower than O3 in the scenario with reduced VOCs by at least 2 ppb; (b) VOCs-sensitive: is defined analogously; (c) NOx and VOCs mixed: the scenarios with reduced NOx and with reduced VOCs have O3 reduction within 2 ppb of each other. According to the definition above, we further calculate DAM1h O3 reduction due to NOx- or VOCs-reduction for individual simulated grids and separate the simulated grids as a function of NOx- or VOCs-sensitivity in Fig. 6. For not all girds are identified as NOx-, or VOCs-, or mixed-sensitivity, the sum of probability in Fig. 6 would not be 100%. Simulation results shows that O3 in urban Beijing (DC, XC, CY, HD and FT districts) is predominantly sensitive to VOCs, 74% girds are distinguished as VOCs-sensitive and 7% grids as NOx-sensitive. Moreover, NOx-titration effect is noticeable and 56% of the urban grids show O3 concentration increasing in reduced NOx scenario. While, in northern suburbs (CY and SY districts), VOCs-sensitivity is still pronounced, 57% girds are classified as VOCs-sensitive, 16% grids as NOxsensitive and 20% grids as VOCs and NOx mixed sensitive. In southern suburban areas (FS, DX and TZ districts), western rural areas (MTG district) and northern rural areas (HR, MY and YQ districts), 36% of the grids present a mixed chemistry, 27% of the grids present the VOCs-
Fig. 5. Simulated monthly average H2O2/HNO3 ratio during afternoon of July 2015. 6
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Fig. 6. Beijing ozone reductions due to NOx emission reduction and VOCs emission reduction for July of 2015.
sensitive and 18%~27% grids present the NOx-sensitive. The apparent dominance of NOx-sensitivity is never found in Beijing rural areas, even 19% of the rural grids show O3 concentration increase in reduced NOx scenario. Then, we calculate the distribution of simulated H2O2/HNO3 value for VOCs- and NOx-sensitive grids. Castell et al. (2009) used 95th percentile for VOCs-sensitive distribution and 5th percentile for the NOx-sensitive distribution to determine the transition range of the indicators. The narrower transition range is, the more robust the indicator is to judge photochemical ozone sensitivity to VOCs or NOx. In our simulations, the 5th, 50th and 95th percentile for VOCs-sensitive distribution is 0.12, 0.60 and 2.71 in ozone attainment days and 0.14, 0.59 and 2.13 in ozone nonattainment days; the 5th, 50 the and 95 the percentile for NOx-sensitive distribution is 1.18, 4.99 and 17.10 in ozone attainment days and 1.15, 3.52 and 14.05 in ozone nonattainment days. The 95th percentile for VOCs-sensitive distribution is higher than 5th percentile for the NOx-sensitive distribution, with a transition range of [2.71, 1.18] in ozone attainment days, [2.13, 1.15] in ozone nonattainment days, and [2.48, 1.17] in all simulated days. The transition thresholds for H2O2/HNO3 indicator never show bigger variations among different days. Based on the monthly transition range of [2.48, 1.17], it can be seen that Beijing is almost under VOCs-sensitive regime, except some pockets of north rural districts. According to the above sensitivity results, the AVOCs reduction during 2010–2013 would bring about ozone pollution mitigation. On the other hand, the effective NOx reduction during 2013–2015 would lead to ozone pollution deterioration in urban and northern suburban areas for the NOx titration effect there. The sensitivity results well
demonstrate the ozone change trends due to the change of precursors’ emissions. 4. Conclusions Beijing as the capital of China is experiencing continuous summer ozone pollution in past two decades. The annual emission of ozone precursor over Beijing reached around 325.3 kilotons for AVOCs and 211.3 kilotons for NOx in 2010 year, and then respectively dropped to 190.7 kilotons and 166.2 kilotons in 2015, with a reduction of 41.3% and 21.3%, under the implementation of China's Air Pollution Prevention and Control Action Plan 2013–2017. Through the simulations with different precursors’ emissions based on the same meteorological condition, the independent influence of precursor control strategy on Beijing summer ozone is evaluated under the meteorological condition of July of 2015. Model simulation results show that AVOCs reduction and NOx increase in Beijing from 2010 to 2013 would lead to a significant DAM1h O3 decrease of > 4 ppb in urban areas and eastern and northern suburbs, a tiny DAM1h O3 decrease of 0–1 ppb in southern suburbs, but a rise DAM1h O3 of 1–2 ppb in some parts of northern rural areas. Then from 2013 to 2015, continuous AVOCs reduction and additional NOx reduction would produce a rise in DAM1h O3 of > 4 ppb in eastern urban and suburban areas and of 1–3 ppb in western urban and northeastern suburban areas, but a fall of 1–3 ppb in southern and western suburban areas and of > 2 ppb in northern rural areas. Overall, the synergic reduction in VOCs and NOx emission during 2010–2015 could effectively mitigate summer ozone pollution over Beijing, with DAM1h O3 decrease by > 3 ppb. 7
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Finally, based on 2015 emission condition, another two scenarios of 30% NOx and 30% VOCs emission reduction are designed and additionally simulated for ozone of July 2015, to determine O3-NOx-VOCs sensitivity chemistry over Beijing. The simulated DAM1h O3 reduction due to NOx- or VOCs-reduction shows that O3 of urban and northern suburban Beijing is predominantly sensitive to VOCs, with 74% girds and 56% grids distinguished as VOCs-sensitive in respective. While in southern suburban areas, western and northern rural areas, 36% of the grids present a mixed chemistry, 27% of the grids as the VOCs-sensitive and 18%~27% grids as the NOx-sensitive. The apparent dominance of NOx-sensitivity is never found in Beijing rural areas. The distribution of simulated H2O2/HNO3 value is further calculated for these distinguished VOCs- and NOx-sensitive grids. The 95th percentile for VOCs-sensitive distribution and 5th percentile for the NOx-sensitive distribution are respectively 2.48 and 1.17 in all simulated days. This transition thresholds implies that Beijing is almost under VOCs-sensitive regime, except some pockets of north rural districts.
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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. Acknowledgement This research was funded by National Natural Science Foundation of China (NSFC) under Grant No. 51678007, and Beijing Science and Technology Commission under Grants No. Z171100001117098. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.atmosenv.2019.116984. References Carter, W.P.L., 2007. A detailed mechanism for the gas-phase atmospheric reactions of organic compounds. Atmos. Environ. 24 (3), 481–518. Castell, N., Stein, A.F., Mantilla, E., Salvador, R., Millan, M., 2009. Evaluation of the use of photochemical indicators to assess ozone-NOx-VOC sensitivity in the Southwestern Iberian Peninsula. J. Atmos. Chem. 63, 73–91. Chen, G.L., 2017. Study of Pollutant Emission Inventory Improvement and the Impact of Raw Coal Combustion on PM2.5 in Beijing-Tianjin-Hebei Region [D]. Beijing University of Technology, Beijing. Cheng, L.J., Wang, S., Gong, Z.Y., Yang, Q., Wang, Y.Y., 2017. Pollution trends of ozone in ozone monitoring pilot cities from 2008 to 2016. In: Environmental Monitoring in China, vol 33. pp. 26–32. CNEMC (China National Environmental Monitoring Center), 2016. Pollutants Emission Factors for China's Industrial Sources. (Beijing). CNDRC (China National Development and Reform Commission), 2016. 2016 Yearbook of China Transportation and Communication. China communication press, Beijing. CNDRC (China National Development and Reform Commission), 2014. 2014 Yearbook of China Transportation and Communication. China communication press, Beijing. CNDRC (China National Development and Reform Commission), 2011. 2011 Yearbook of China Transportation and Communication. China communication press, Beijing. CNSB (China National Statistic Bureau), 2016a. China Energy Statistical Yearbook 2016. China statistic press, Beijing. CNSB (China National Statistic Bureau), 2016b. China Statistical Yearbook 2016. China statistic press, Beijing. CNSB (China National Statistic Bureau), 2014a. China Energy Statistical Yearbook 2014. China statistic press, Beijing. CNSB (China National Statistic Bureau), 2014b. China Statistical Yearbook 2014. China statistic press, Beijing. CNSB (China National Statistic Bureau), 2011a. China Energy Statistical Yearbook 2011. China statistic press, Beijing. CNSB (China National Statistic Bureau), 2011b. China Statistical Yearbook 2011. China
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Sensitivity of summer ozone to precursor emission change over Beijing during 2010–2015: A WRF-Chem modeling study
T
Wei Weia,b,∗, Yue Lia, Yunting Rena, Shuiyuan Chenga,b, Lihui Hana,b a b
Department of Environmental Science and Engineering, Beijing University of Technology, Beijing, 100124, China Key Laboratory of Beijing on Regional Air Pollution Control, Beijing, 100124, China
ARTICLE INFO
ABSTRACT
Keywords: Surface ozone Sensitivity Precursor emission change WRF-Chem simulation
Beijing as the capital of China releases massive air pollutants and experiences the worsening summer O3 pollution recently. This study estimates Beijing ozone precursor emission, anthropogenic VOCs (AVOCs) being 325.3 kilotons in 2010, 231.8 kilotons in 2013 and 190.7 kilotons in 2015 and NOx being 211.3 kilotons in 2010, 238.3 kilotons in 2013 and 166.2 kilotons in 2015. Then, we conduct surface O3 simulation based on WRF-Chem through using different precursor emissions, to evaluate the influence of precursor control measures on Beijing O3. From 2010 to 2013, AVOCs reduction in Beijing would lead to O3 decrease in urban and suburban areas and O3 increase in some parts of northern rural areas; while from 2013 to 2015, AVOCs and NOx reductions would produce O3 increase in urban and northern suburban areas and O3 decrease in southern suburban and northern rural areas. Overall, the synergic reduction during 2010–2015 could effectively mitigate summer O3 pollution over Beijing, with daily maximum 1-h ozone (DAM1h O3) reduction exceeding 3 ppb. Finally, based on 2015 emission condition, 30% NOx and 30% VOCs emission reduction are further simulated to study O3-NOx-VOCs sensitivity over Beijing. The simulated DAM1h O3 reduction due to NOx- or VOCs-reduction shows that O3 is predominantly sensitive to VOCs in urban and northern suburban Beijing, but seems to be control more by the mixed chemistry in southern suburban and northern rural Beijing. However, NOx-sensitive condition is never found in rural Beijing. The distribution of simulated H2O2/HNO3 for the distinguished VOCs- and NOx-sensitive grids shows that 95th percentile for VOCs-sensitive distribution and 5th percentile for the NOx-sensitive distribution are 2.48 and 1.17 in all simulated days. According to the determined transition values, most Beijing is under VOCs-sensitive regime on the condition of 2015 precursor emission.
1. Introduction Tropospheric or surface ozone (O3) is a major concern for air quality due to its adverse impact on human health (Lippmann, 1993) and ecosystem (U.S. NRC, 1991). Besides, O3 is a significant greenhouse gas with the third highest radiative forcing just after carbon dioxide (CO2) and methane (CH4) (IPCC, 2013). Surface ozone originates from stratospheric troposphere exchange and photochemical reactions between volatile organic compounds (VOCs) and nitrogen oxides (NOx). In between, photochemistry is the most important source and responsible for ~90% of surface ozone, approximately 4500 Tg per year in global troposphere, with remaining approximately 500 Tg transported from stratosphere (IPCC, 2013). Therefore, O3 has received worldwide attention from both the scientific and regulatory communities. In the past two decades, for the rapid urbanization and industrialization causing great increases in anthropogenic emissions into
∗
atmosphere, China has experienced severe air pollution problems, presented as fall and winter fine particulate matter pollution and summertime ozone pollution. Wang et al. (2017) reviewed China's ozone pollution and found that Beijing located in the Northern China Plain has the highest peak ozone concentrations. In the Northern China Plain, aircraft measurement by Tang et al. (2009) showed that summertime boundary-layer ozone increased by 2% per year during 1995–2005 and the daily maximum1-hour ozone (DAM1h O3) in urban Beijing also increased at a rate of 1.3% per year during 2001–2006; Ma et al. (2016) found an increase in daily maximum 8-h ozone (DAM8h O3) at Shangdianzi that is a background station in Beijing-Tianjin-Hebei region (BTH), at a rate of 1.1 ppb per year during 2003–2015; Sun et al. (2016) conducted a non-continuous observations at Mt. Tai and reported an ozone increase of 1.7%~2.1% per year during the summer months during 2003–2015. The air quality data published by China's national and local environmental agencies since 2013 (http://www.
Corresponding author. Key Laboratory of Beijing on Regional Air Pollution Control, Beijing, 100124, China. E-mail address: [email protected] (W. Wei).
https://doi.org/10.1016/j.atmosenv.2019.116984 Received 10 April 2019; Received in revised form 15 September 2019; Accepted 17 September 2019 Available online 19 September 2019 1352-2310/ © 2019 Elsevier Ltd. All rights reserved.
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mep.gov.cn), also reveals that surface O3 concentrations in major urban areas have continued to increase during 2013–2016. The highest 90th percentile of DAM8h O3 in 74 cities increased from 69.5 ppb in 2013 to 75.0 ppb in 2016, the percentage of nonattainment cities increased from 23% to 38%, and Beijing still has the highest 90th percentile of DAM8h O3 level (~93.3 ppb at 273 K, 101.3 kPa). All of these results point to a worsening photochemical pollution in China's major developed regions, especially in Beijing and its surrounding areas. Severe ozone pollution is consistently associated with the large emission of anthropogenic precursors. Oxidation of VOCs promotes RO2 radical production, RO2 enhances the conversion of NO to NO2, and NO2 photolysis results in the production and accumulation of O3. High concentration of NOx is the direct precursor of O3 pollution in developed region. Multi-resolution emission inventory for China (MEIC, http://meicmodel.org/) shows that in 2012, NOx emission in China and BTH reached 29.16 million tons and 3.04 million tons respectively, and annual NOx emission intensity exceeded 15 ton·km−2 in BTH. Then, with the implementation of China Air Pollution Prevention and Control Plan 2013–2017 (CAPPCP), in 2016 NOx emission in China and in BTH decreased to 22.51 million tons and to 2.29 million tons respectively, with a reduction of ~25%. On the other hand, anthropogenic VOCs (AVOCs) emission little changed during 2012–2016, remaining around ~28.0 million tons per year in China and ~2.6 million tons per year in BTH reported by MEIC. It throws a doubt whether NOx reduction brings about ozone increase of eastern China, for the complicated nonlinear chemistry involved in photochemical ozone formation. Thus, it is essential to capture the chemistry nature of photochemical ozone before developing the effective surface ozone control strategies. In China, three-dimensional air quality model has been widely applied in determination of NOx-sensitive or VOCs-sensitive in O3 photochemical production (Liu et al., 2010; Tie et al., 2013; Wang et al., 2015), apportionment of ozone contributing sources (Wang et al., 2009; Li et al., 2012) and evaluation of precursor control strategies (Xing et al., 2011; Qu et al., 2014). Liu et al. (2010) found the significant contribution of gas-phase chemistry and vertical transport to summer O3, and indicated a VOClimited O3 chemistry in winter, NOx-limited in summer, and either VOCor NOx-limited in spring and autumn over most of eastern China. Xing et al. (2011) applied CMAQ model in three megacities of eastern China (Beijing, Shanghai and Guangzhou), and concluded NOx control would likely be more effective than anthropogenic VOCs control during periods of heavy photochemical pollution. Tie et al. (2013) employed WRF-Chem model in Yangtze River Delta, showed a VOC-limited condition in Shanghai and its surrounding regional area, and suggested the VOCs control strategy to mitigate ozone pollution there. It can be seen that the nonlinear response of photochemical ozone to precursors over East China is still speculative and far from being understood. And recently with the considerable change in precursors’ emissions under CAPPCP, the chemistry nature of photochemical ozone over China may vary and will make this scientific issue more complex. This study aims to examine the sensitivity of surface ozone to precursor emission change over Beijing during 2010–2015. In Beijing, the seasonal variation of ozone has a summer maximum and winter minimum, and ozone pollution frequently occurs during July to August (Cheng et al., 2017). Thus, we focus on the vulnerable season of summer, mainly evaluate the influence of precursor reduction on Beijing summer ozone, and determine the photochemical ozone formation regime for summer Beijing, through a WRF-Chem modeling study. This study would be helpful for better understanding the roles played by precursor reduction and developing ozone control strategy in China.
year 2010, 2013 and 2015, according to following equations (1) and (2):
EVOC , s =
Aj × EFj, voc × (1
j, voc )
j
ENOx =
Aj × EFj, nox × (1
j, nox )
j
× Pj, s
(1) (2)
Where, E is the annual emission of AVOCs species s or NOx (ton); j is the emission source; Aj is the annual activity data of source j, mainly including fuel consumptions (kiloton), industrial product yields (kiloton), solvent consumptions (kiloton), vehicle kilometers travelled (VKT, kilometer), etc.; EFj is the uncontrolled VOCs or NOx emission factor for source j, expressed by g VOC/kg fuel, g VOC/kg product, g VOC/kg solvent or g VOC/km VKT; and ηj is the average removal efficiency of VOCs or NOx in Beijing source j (%); Pj,s is the mass proportion of organic species s in VOCs released from source j (%). In this study, total 150 types of sources are considered, mainly including industrial and residential fuel combustions, road and non-road transportations, petrochemical industries, industrial paint coating and ink printing, gasoline evaporation, oil storage and transportation, and so on. For these sources, previous inventory studies made literature research and summarized a set of EFs of AVOCs and NOx suitable for China (Wei et al., 2008; MEEC, 2014; CNEMC, 2016). The corresponding activity data for studied year are from the statistical year books. In detail, the consumption amounts of fossil fuels in industrial boilers and residential stoves from CNSB (2011a, 2014a and 2016a), the annual yields of various industrial products from CNSB (2011b, 2014b and 2016b), the vehicle population from CNDRC (2011, 2014 and 2016), and VKT from Lang et al. (2016) respectively. AVOCs and NOx control in industrial sources are respectively from the investigation of Li et al. (2017) and CNEMC (2016). And the species mass proportion of VOCs released from various sources are from Wei et al. (2008). 2.2. WRF-chem model configuration For ozone simulation, the option of regarding gas-phase chemical mechanism is especially important, and SAPRC-99 mechanism (Carter, 2007) is applied for its complicated VOCs grouped classes and related reactions. The aerosol module is the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) that uses 4 volatility bins with the Volatility Basis Set (VBS) for organic aerosol evolution. And in physical options, Purdue Lin is selected as microphysics option, Goddard as shortwave radiation option, RRTMG as longwave radiation, NOAH as land surface option, Monin-Obukhov as surface layer option, Yonsei University Scheme (YSU) as planetary boundary layer option, and KainFritsch as cumulus option. While considering the significant influence of aerosols on meteorology in China (Yang et al., 2016), this study turns on the aerosol feedback. In our simulation, the metrological initial and boundary conditions are predicted based on U.S. geological survey terrain and land use data (https://www2.acom.ucar.edu/wrf-chem) and U.S. national center for environmental prediction final operational global analysis data (http://rda.ucar.edu). Then the simulation is performed over three domains, as shown in Fig. 1. Domain 1 covers East Asia at a 36 km resolution, Domain 2 covers North-Eastern China at a 12 km resolution and Domain 3 mainly covers Beijing with a 4 km resolution. The simulations of Domain 1 and 2 mainly provide the boundary conditions, and the simulation of Domain 3 is used for air quality prediction analysis. Sharma et al. (2017) reviewed a large number of studies on surface ozone simulation and suggested the horizontal domain resolution of < 10 km, considering that coarse resolution always deteriorates simulation performance due to dilution of precursor emissions and premature mixing of urban and background air masses in coarser grid. Our horizontal resolution in Domain 3 (4 km × 4 km) satisfies this recommendation. For Domains 1 and 2, the anthropogenic emissions of gaseous pollutants (SO2, NOx, CH4, CO, NH3 and VOCs groups) and particulate matter (OC, EC, PM2.5
2. Methodologies 2.1. Emission estimate of precursors (AVOCs and NOx) An up-bottom approach is adopted to estimate speciated AVOCs emission and NOx emission at a high spatial resolution over Beijing for 2
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Fig. 1. WRF-Chem modeling domains (red block means the meteorological station and black dot mean the air quality station). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
Fig. 2. Time series of simulated and observed 1-h O3 in four stations (the red solid lines refer to the simulated O3, and the black dash lines refer to the observed O3). (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)
and PM10) are taken from MEIC (www.meicmodel.org); for Domain 3, VOCs and NOx emissions are from this study and other pollutants ’emissions were from Li et al. (2015) and Chen et al. (2017).
reduction scenario, to explore the formation regime of Beijing photochemical O3 during summer. 2.4. Model performance of S2015 simulation
2.3. Simulation scenarios design
Accurate modeling of ozone concentration is very complex due to its high reactivity with other pollutants and meteorological interactions. In meteorological evaluation, the Mean Bias (MB) for temperature at 2-m (T2), relative humidity at 2-m (HR2) and wind speed at 10-m (WS10) at MET station (as shown in Fig. 1) reaches 0.2K, −11.0% and 0.5 m/s, generally agreeing with the criteria promoted by Emery et al. (2001). In the evaluation of chemical simulations, four air quality stations of DS, GY, LLH and MYX (as shown in Fig. 1) are selected, which respectively represents the eastern urban area, western urban area, southern suburb area and northern rural area. The model well reproduces the chemical observations, with Normalized Mean Bias (NMB) of −40%~-24% for DAM1h O3, +7%~+18% for NOx and −14% ~-36% for CO and Normalized Mean Error (NME) of 28%~56% for
Here we select the same meteorological condition of July of 2015 and use different precursors' emissions in Domain 3 over Beijing, to predict Beijing summer O3 and its response to the change of precursors' emissions. The WRF-Chem simulations in Domain 3 based on 2010, 2013 and 2015 precursors' emissions are considered as the simulation scenarios of S2010, S2013 and S2015, in respective. The difference in predicted O3 of various simulations implies the independent influence of corresponding reduction in precursors’ emissions on Beijing summer O3 during 2010–2015. Then, based on 2015 emission condition, we further design another two reduction scenarios, 30% NOx and 30% VOCs emission reduction, and additionally simulate O3 for July of 2015 under NOx- or VOCs3
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DAM1h O3, 41%~68% for NOx and 42%~60% for CO. All NMBs and NMEs except NOx at MYX station are within the threshold for satisfactory performance proposed by the U.S. EPA (2013). And Fig. 2 shows that O3 temporal trend is successfully simulated, as well as the peak magnitudes. The predicted and observed value for DAM1h O3 is 83.7 ppb and 89.1 ppb at DS station, 83.2 ppb and 96.0 ppb at GY station, 66.7 ppb and 79.5 ppb at LLH station, and 73.6 ppb and 88.9 ppb at MYX station.
emission was predominantly from fossil fuel combustion in industrial boilers, residential stoves, road vehicles and non-road engines, respectively with the contribution of 16.2%~31.4%, 9.7%~11.3%, 49.1% ~53.7% and 9.8%~20.6% in our studied period. From 2010 to 2013, Beijing NOx emission presented a slight increasing trend and was contributed mainly by heavy-duty diesel vehicles related to freight transportation. Then from 2013 to 2015, Beijing NOx emission was brought down by 72.1 kilotons, which mainly from industrial fuel combustion (by 29.9 kilotons) and heavy-duty diesel vehicles (by 33.5 kilotons). For the spatial distribution, related power plants locate in CY, FT and SJS urban districts, major industrial boilers locate in FS, SY and CP suburban districts, vehicles mostly travel in urban and suburban roads, non-road engines mainly include flights in airport located in SY suburban district and machineries allocated in suburban building sites. Thus, NOx emission in southern suburbs of Beijing was largest, followed by northern suburbs and urban areas, and NOx emission in rural areas was lowest, as shown in Fig. 3. During 2010–2015, the bigger reduction in NOx emission occurred in urban districts of SJS (10.8 kilotons) and CY (8.9 kilotons), in suburban districts of FS (6.3 kilotons), DX (3.1 kilotons) and CP (2.5 kilotons).
3. Results and discussion 3.1. Emission change of precursors during 2010–2015 3.1.1. AVOCs emission change According to this study, AVOCs emission in Beijing reached around 325.3 kilotons in 2010 year, 231.8 kilotons in 2013 year and 190.7 kilotons in 2015 year, with a noticeable reduction of 41.3% during 2010–2015. The massive AVOCs emission was attributed to industrial solvent utilization (30.0%~33.3%), road vehicles (15.8%~23.6% from tail gas and 7.6%~10.3% from gasoline evaporation), petrochemical industries (19.8%~21.2%) and coal combustion in residential stoves (10.0%~11.8%). During the studied period, Beijing AVOCs emission reduction was contributed mainly by road vehicles (46.6 kilotons), industrial solvent utilization (43.1 kilotons) and petrochemical industries (23.9 kilotons). It resulted from a series of VOCs emission limits recently implemented in Beijing, including vehicle tail gas limits (DB11/ 946–2013 for light-duty gasoline vehicle, DB11/965–2013 for heavyduty vehicle, DB11/120–2014 for motorcycle), fossil oil vapor emission limits (DB11/206–2010 for oil store, DB11/207–2010 for oil tank truck, DB 11/208–2010 for service station), and also resulted from the industrial structure adjustment in Beijing, including restricting petrochemical and pharmaceutical manufacturing and to-be-eliminating printing and textile industry (http://www.ndrc.gov.cn). For example, in road vehicle sector, the elimination of gasoline vehicles never satisfying Emission Standards II brought about 49.7 kilotons VOCs reduction during 2010–2015; while new vehicles during that period only produced 11.8 kilotons VOCs emission increment. In Beijing, petrochemical manufacturing factories assemble in an industrial park located in FS district (southwestern suburb); industrial solvents are mostly utilized in automobile manufacturing, electric components manufacturing and printing, which distributed in DX and TZ districts (southeastern suburb) and SY district (northeastern suburb); road vehicle transportation depends heavily on population density and is allocated in urban and suburban roads; residential coal combustion dominantly occurs in southern and eastern suburbs and northern rural areas. As a whole, more AVOCs are released in urban areas, eastern and southern suburban areas than in northern suburban and rural areas, as shown in Fig. 3. The AVOCs emission reduction trend was: southern and eastern suburban areas > urban and northern suburban areas > rural areas. Then, to comply with emission input of air quality model, AVOCs emissions are further speciated into 28 assembled groups according to SAPRC99 mechanism. In result, Beijing AVOCs is composed primarily of ALK1, ALK2, ALK3, ALK4, ALK5, ETHE, OLE1, OLE2, BENZENE, ARO1, ARO2, MEOH, ACTE, MEK, PROD2, HCHO and CCHO, with the mass proportion of 2.93%~2.96%, 2.48%~2.68%, 4.10%~4.89%, 11.47%~13.07%, 6.49%~6.78%, 4.70%~4.91%, 9.24%~9.70%, 7.18%~8.41%, 4.52%~4.56%, 8.01%~8.20%, 12.13%~12.84%, 1.25%~1.59%, 1.64%~1.73%, 5.07%~5.69%, 4.62%~5.68%, 1.08% ~1.11% and 0.86%~0.92%. The change in chemical composition was not big during 2010–2015, due to the relatively even reduction of AVOCs from major emission sources.
3.2. Influence of AVOCs and NOx reduction on surface ozone Normally, in the conditions with relatively high VOCs/NOx ratios, photochemical O3 production is limited by NOx availability and it will increase with increasing NOx concentrations and be less sensitive to VOCs concentration change; while in conditions with relatively low VOCs/NOx ratios, O3 production is limited by radical availability and NOx inhibition, and O3 will increase with increasing VOCs concentration and decrease with increasing NOx concentration. Through combining with biogenic VOCs (BVOCs) emission (Chen et al., 2017), the ratio of VOCs (AVOCs + BVOCs) to NOx was calculated and introduced in Fig. 3. It can be seen that during 2010–2015, the low VOCs:NOx of < 2.0 continuously happened in urban areas and suggested a potential VOCs-sensitive condition and the active short-time ozone precursors; the high VOCs:NOx of 3.0–5.0 continuously happened in western and northern rural areas and possibly suggested a low VOCssensitive condition and the ageing ozone precursors; while northern and southern suburbs seem to move towards lower VOCs:NOx condition, for the anthropogenic emissions increasing with the urbanization development in these areas. It seems a conversion of the lower VOCssensitive regime into the higher VOCs-sensitive regime in Beijing suburbs during 2010–2015. Comparison between S2013 simulation to S2010 simulation shows that from 2010 to 2013, with a 28.7% reduction in VOCs emission and a 12.2% growth in NOx emission, DAM1h O3 would drop over the most part of Beijing as shown in Fig. 4(a), around by > 4 ppb in urban areas and eastern and northern suburbs, which might associate simultaneously with AVOCs emission reduction and NOx emission increase and reflects a potential VOCs sensitivity condition there. However, in southwestern suburbs, DAM1h O3 would occur a tiny decrease of 0–1 ppb although with the big AVOCs emission reduction in petrochemical industrial park, implying the low VOCs-sensitive condition there. In some parts of northern rural areas, DAM1h O3 would rise by 1–2 ppb, which indicates the influence of NOx increase on the NOxsensitivity region. Then, from 2013 to 2015, a continuous reduction in AVOCs emission and a fresh reduction in NOx emission would bring about a rise in DAM1h O3 of > 4 ppb in eastern urban and eastern suburban areas and around 1–3 ppb in western urban and northeastern suburban areas, but a fall in DAM1h O3 of 1–3 ppb in southern and western suburban areas and of > 2 ppb in northern rural areas, as shown in Fig. 4(b). The ozone increase in the urban areas and its adjacent north-east suburban areas implies a potential NOx-titration regime, where VOCs/NOx emission ratio lower than 1.0. And the ozone decrease in southern and western
3.1.2. NOx emission change In Beijing, annual NOx emission reached 211.3 kilotons in 2010 year, 238.3 kilotons in 2013 year and 166.2 kilotons in 2015 year. NOx 4
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Fig. 3. Spatial distribution of anthropogenic VOCs and NOx emissions and VOCs/NOx emission ratios over Beijing during 2010~2015 (eastern urban areas include DC and CY districts, western urban areas include XC, HD, FT and SJS districts, southern suburbs include FS, DX and TZ districts, northern suburbs include CP and SY, and rural areas include MTG, YQ, HR, MY and PG districts).
suburban areas and northern rural areas might associate with the NOx or VOCs emission reduction where VOCs/NOx emission ratio higher than 3.0. Overall, in the whole studied period of 2010–2015, the synergic reduction in VOCs emission by 41.3% and in NOx emission by 21.7% could obtain an evident ozone reduction all over Beijing, with DAM1h O3 decrease higher than 3 ppb, as presented in Fig. 4(c). According to Cheng et al. (2017), the average O3 during summer Beijing reached about 76 ppb in 2010, 68 ppb in 2013, and 80 ppb in 2015. And Ma et al. (2016) measured that DAM1h O3 significantly increased during the period of 2013–2015, compared to those during the period of 2004–2012. In addition, we also captured the monitored O3 in Beijing air quality stations, and found that DAM1h O3 in July of 2015 changed approximately by +10.2% in urban Beijing, +13.1% in
northern suburban Beijing and −7.5% in northern rural Beijing, compared to July of 2014. These trends are well consistent with our simulation results. However, the observed ozone is a comprehensive result of precursors' emissions, regional transport and meteorological factors. And our simulation results only present the role of local precursor's emissions. 3.3. Assessment of O3–VOCs-NOx sensitivity To assess sensitivity of ozone to its precursors, the indicators of species ratios involved in ozone photochemistry and their transition values were studied and determined. These indicators include H2O2/ HNO3, H2O2/(O3+NO2), O3/NOx, O3/NOy, HCHO/NOy and HCHO/ NO2. Values lower than the suggested transition values indicate a VOCs5
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Fig. 4. Monthly average difference in simulated DAM1h O3 for July of 2015 (a) between S2013 and S2010, (b) between S2015 and S2013, and (c) between S2015 to S2010
sensitivity chemistry, while values higher than the suggested transition values mean a NOx-sensitivity chemistry. Liu et al. (2010) used CMAQ model in China and suggested H2O2/HNO3 as the more robust indicator for O3 chemistry. Here, we presented the simulated H2O2/HNO3 over Beijing during afternoon (12:00–18:00) based on S2010, S2013 and S2015, as shown by Fig. 5. For the transition value of H2O2/HNO3, value of 0.2 was originally proposed by pioneer researches of Lu and Chang (1998) and Sillman et al. (1997). Then, Zhang et al. (2009) adjusted H2O2/HNO3 transition value to 2.4 for North America, and Liu et al. (2010) suggested 1.6 to fit China atmospheric condition. Based on the transition value of 0.2, VOCs-sensitivity regime is only given in center and eastern urban areas (DC, XC and CY districts), and the most areas of Beijing would be under NOx-sensitivity condition. While based on the adjusted value of 1.6, most of Beijing except northern and western rural areas would be under VOCs-sensitivity condition. Therefore, it is essential to further explore the sensitivity of Beijing photochemical ozone to its precursors. According to the simulated H2O2/HNO3 in Fig. 5, the chemistry regime of Beijing photochemical ozone changes towards VOCs-sensitive condition in S2013 compared to S2010, especially in urban and south suburban areas. However, it reverts to the S2010 chemistry nature in S2015. Thus, we aim at 2015 emission condition, give a 30% NOx and a 30% AVOCs emission reduction, and simulate another two emission
scenarios to conduct Beijing ozone sensitivity research. Sillman and He (2002) proposed the definition of NOx- or VOCssensitive condition: (a) NOx-sensitive: O3 in the scenario with reduced NOx is lower than O3 in the scenario with reduced VOCs by at least 2 ppb; (b) VOCs-sensitive: is defined analogously; (c) NOx and VOCs mixed: the scenarios with reduced NOx and with reduced VOCs have O3 reduction within 2 ppb of each other. According to the definition above, we further calculate DAM1h O3 reduction due to NOx- or VOCs-reduction for individual simulated grids and separate the simulated grids as a function of NOx- or VOCs-sensitivity in Fig. 6. For not all girds are identified as NOx-, or VOCs-, or mixed-sensitivity, the sum of probability in Fig. 6 would not be 100%. Simulation results shows that O3 in urban Beijing (DC, XC, CY, HD and FT districts) is predominantly sensitive to VOCs, 74% girds are distinguished as VOCs-sensitive and 7% grids as NOx-sensitive. Moreover, NOx-titration effect is noticeable and 56% of the urban grids show O3 concentration increasing in reduced NOx scenario. While, in northern suburbs (CY and SY districts), VOCs-sensitivity is still pronounced, 57% girds are classified as VOCs-sensitive, 16% grids as NOxsensitive and 20% grids as VOCs and NOx mixed sensitive. In southern suburban areas (FS, DX and TZ districts), western rural areas (MTG district) and northern rural areas (HR, MY and YQ districts), 36% of the grids present a mixed chemistry, 27% of the grids present the VOCs-
Fig. 5. Simulated monthly average H2O2/HNO3 ratio during afternoon of July 2015. 6
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Fig. 6. Beijing ozone reductions due to NOx emission reduction and VOCs emission reduction for July of 2015.
sensitive and 18%~27% grids present the NOx-sensitive. The apparent dominance of NOx-sensitivity is never found in Beijing rural areas, even 19% of the rural grids show O3 concentration increase in reduced NOx scenario. Then, we calculate the distribution of simulated H2O2/HNO3 value for VOCs- and NOx-sensitive grids. Castell et al. (2009) used 95th percentile for VOCs-sensitive distribution and 5th percentile for the NOx-sensitive distribution to determine the transition range of the indicators. The narrower transition range is, the more robust the indicator is to judge photochemical ozone sensitivity to VOCs or NOx. In our simulations, the 5th, 50th and 95th percentile for VOCs-sensitive distribution is 0.12, 0.60 and 2.71 in ozone attainment days and 0.14, 0.59 and 2.13 in ozone nonattainment days; the 5th, 50 the and 95 the percentile for NOx-sensitive distribution is 1.18, 4.99 and 17.10 in ozone attainment days and 1.15, 3.52 and 14.05 in ozone nonattainment days. The 95th percentile for VOCs-sensitive distribution is higher than 5th percentile for the NOx-sensitive distribution, with a transition range of [2.71, 1.18] in ozone attainment days, [2.13, 1.15] in ozone nonattainment days, and [2.48, 1.17] in all simulated days. The transition thresholds for H2O2/HNO3 indicator never show bigger variations among different days. Based on the monthly transition range of [2.48, 1.17], it can be seen that Beijing is almost under VOCs-sensitive regime, except some pockets of north rural districts. According to the above sensitivity results, the AVOCs reduction during 2010–2013 would bring about ozone pollution mitigation. On the other hand, the effective NOx reduction during 2013–2015 would lead to ozone pollution deterioration in urban and northern suburban areas for the NOx titration effect there. The sensitivity results well
demonstrate the ozone change trends due to the change of precursors’ emissions. 4. Conclusions Beijing as the capital of China is experiencing continuous summer ozone pollution in past two decades. The annual emission of ozone precursor over Beijing reached around 325.3 kilotons for AVOCs and 211.3 kilotons for NOx in 2010 year, and then respectively dropped to 190.7 kilotons and 166.2 kilotons in 2015, with a reduction of 41.3% and 21.3%, under the implementation of China's Air Pollution Prevention and Control Action Plan 2013–2017. Through the simulations with different precursors’ emissions based on the same meteorological condition, the independent influence of precursor control strategy on Beijing summer ozone is evaluated under the meteorological condition of July of 2015. Model simulation results show that AVOCs reduction and NOx increase in Beijing from 2010 to 2013 would lead to a significant DAM1h O3 decrease of > 4 ppb in urban areas and eastern and northern suburbs, a tiny DAM1h O3 decrease of 0–1 ppb in southern suburbs, but a rise DAM1h O3 of 1–2 ppb in some parts of northern rural areas. Then from 2013 to 2015, continuous AVOCs reduction and additional NOx reduction would produce a rise in DAM1h O3 of > 4 ppb in eastern urban and suburban areas and of 1–3 ppb in western urban and northeastern suburban areas, but a fall of 1–3 ppb in southern and western suburban areas and of > 2 ppb in northern rural areas. Overall, the synergic reduction in VOCs and NOx emission during 2010–2015 could effectively mitigate summer ozone pollution over Beijing, with DAM1h O3 decrease by > 3 ppb. 7
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Finally, based on 2015 emission condition, another two scenarios of 30% NOx and 30% VOCs emission reduction are designed and additionally simulated for ozone of July 2015, to determine O3-NOx-VOCs sensitivity chemistry over Beijing. The simulated DAM1h O3 reduction due to NOx- or VOCs-reduction shows that O3 of urban and northern suburban Beijing is predominantly sensitive to VOCs, with 74% girds and 56% grids distinguished as VOCs-sensitive in respective. While in southern suburban areas, western and northern rural areas, 36% of the grids present a mixed chemistry, 27% of the grids as the VOCs-sensitive and 18%~27% grids as the NOx-sensitive. The apparent dominance of NOx-sensitivity is never found in Beijing rural areas. The distribution of simulated H2O2/HNO3 value is further calculated for these distinguished VOCs- and NOx-sensitive grids. The 95th percentile for VOCs-sensitive distribution and 5th percentile for the NOx-sensitive distribution are respectively 2.48 and 1.17 in all simulated days. This transition thresholds implies that Beijing is almost under VOCs-sensitive regime, except some pockets of north rural districts.
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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. Acknowledgement This research was funded by National Natural Science Foundation of China (NSFC) under Grant No. 51678007, and Beijing Science and Technology Commission under Grants No. Z171100001117098. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.atmosenv.2019.116984. References Carter, W.P.L., 2007. A detailed mechanism for the gas-phase atmospheric reactions of organic compounds. Atmos. Environ. 24 (3), 481–518. Castell, N., Stein, A.F., Mantilla, E., Salvador, R., Millan, M., 2009. Evaluation of the use of photochemical indicators to assess ozone-NOx-VOC sensitivity in the Southwestern Iberian Peninsula. J. Atmos. Chem. 63, 73–91. Chen, G.L., 2017. Study of Pollutant Emission Inventory Improvement and the Impact of Raw Coal Combustion on PM2.5 in Beijing-Tianjin-Hebei Region [D]. Beijing University of Technology, Beijing. Cheng, L.J., Wang, S., Gong, Z.Y., Yang, Q., Wang, Y.Y., 2017. Pollution trends of ozone in ozone monitoring pilot cities from 2008 to 2016. In: Environmental Monitoring in China, vol 33. pp. 26–32. CNEMC (China National Environmental Monitoring Center), 2016. Pollutants Emission Factors for China's Industrial Sources. (Beijing). CNDRC (China National Development and Reform Commission), 2016. 2016 Yearbook of China Transportation and Communication. China communication press, Beijing. CNDRC (China National Development and Reform Commission), 2014. 2014 Yearbook of China Transportation and Communication. China communication press, Beijing. CNDRC (China National Development and Reform Commission), 2011. 2011 Yearbook of China Transportation and Communication. China communication press, Beijing. CNSB (China National Statistic Bureau), 2016a. China Energy Statistical Yearbook 2016. China statistic press, Beijing. CNSB (China National Statistic Bureau), 2016b. China Statistical Yearbook 2016. China statistic press, Beijing. CNSB (China National Statistic Bureau), 2014a. China Energy Statistical Yearbook 2014. China statistic press, Beijing. CNSB (China National Statistic Bureau), 2014b. China Statistical Yearbook 2014. China statistic press, Beijing. CNSB (China National Statistic Bureau), 2011a. China Energy Statistical Yearbook 2011. China statistic press, Beijing. CNSB (China National Statistic Bureau), 2011b. China Statistical Yearbook 2011. China
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