scholarly journals The 2015 and 2016 wintertime air pollution in China: SO<sub>2</sub> emission changes derived from a WRF-Chem/EnKF coupled data assimilation system

2019 ◽  
Vol 19 (13) ◽  
pp. 8619-8650 ◽  
Author(s):  
Dan Chen ◽  
Zhiquan Liu ◽  
Junmei Ban ◽  
Min Chen
Keyword(s):  
Data Assimilation ◽  
Emission Inventory ◽  
Southern China ◽  
Control Strategies ◽  
A Priori ◽  
River Delta ◽  
Western China ◽  
So2 Emissions ◽  
Emission Reductions ◽  
Emission Changes

Abstract. Ambient pollutants and emissions in China have changed significantly in recent years due to strict control strategies implemented by the government. It is of great interest to evaluate the reduction of emissions and the air quality response using a data assimilation (DA) approach. In this study, we updated the WRF-Chem/EnKF (Weather Research and Forecasting – WRF, model coupled with the chemistry/ensemble Kalman filter – Chem/EnKF) system to directly analyze SO2 emissions instead of using emission scaling factors, as in our previous study. Our purpose is to investigate whether the WRF-Chem/EnKF system is capable of detecting the emission deficiencies in the bottom-up emission inventory (2010-MEIC, Multi-resolution Emission Inventory for China), dynamically updating the spatial–temporal emission changes (2010 to 2015/2016) and, most importantly, locating the “new” (emerging) emission sources that are not considered in the a priori emission inventory. The 2010 January MEIC emission inventory was used as the a priori inventory (to generate background emission fields). The 2015 and 2016 January emissions were obtained by assimilating the hourly surface SO2 concentration observations for January 2015 and 2016. The SO2 emission changes for northern, western, and southern China from 2010 to 2015 and from 2015 to 2016 (for the month of January) from the EnSRF (ensemble square root filter) approach were investigated, and the emission control strategies during the corresponding period were discussed. The January 2010–2015 differences showed inhomogeneous change patterns in different regions, including (1) significant emission reductions in southern China; (2) significant emission reductions in larger cities with a wide increase in the surrounding suburban and rural regions in northern China, which may indicate missing raw coal combustion for winter heating that was not taken into account in the a priori emission inventory; and (3) significantly large emission increases in western China due to the energy expansion strategy. The January 2015–2016 differences showed wide emission reductions from 2015 to 2016, indicating stricter control strategies having been fully executed nationwide. These derived emission changes coincided with the period of the energy development national strategy in northwestern China and the regulations for the reduction of SO2 emissions, indicating that the updated DA system was possibly capable of detecting emission deficiencies, dynamically updating the spatial–temporal emission changes (2010 to 2015/2016), and locating newly added sources. Forecast experiments using the a priori and updated emissions were conducted. Comparisons showed improvements from using updated emissions. The improvements in southern China were much larger than those in northern and western China. For the Sichuan Basin, central China, the Yangtze River Delta, and the Pearl River Delta, the BIAS (bias, equal to the difference between the modeled value and the observational value, representing the overall model tendency) decreased by 61.8 %–78.2 % (for different regions), the RMSE decreased by 27.9 %–52.2 %, and CORR values (correlation coefficient, equal to the linear relationship between the modeled values and the observational values) increased by 12.5 %–47.1 %. The limitation of the study is that the analyzed emissions are still model-dependent, as the ensembles are conducted using the WRF-Chem model; therefore, the performances of the ensembles are model-dependent. Our study indicated that the WRF-Chem/EnSRF system is not only capable of improving the emissions and forecasts in the model but can also evaluate realistic emission changes. Thus, it is possible to apply the system for the evaluation of emission changes in the future.

scholarly journals 2015 and 2016 winter-time air pollution in China: SO<sub>2</sub> emission changes derived from a WRF/Chem-EnKF coupled data assimilation system

2019 ◽  
Author(s):  
Dan Chen ◽  
Zhiquan Liu ◽  
Junmei Ban ◽  
Min Chen
Keyword(s):  
Data Assimilation ◽  
Emission Reduction ◽  
Emission Inventory ◽  
Southern China ◽  
Control Strategies ◽  
River Delta ◽  
Central China ◽  
Western China ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. Ambient pollutants in China changes significantly in recent years due to strict control strategies implemented by the government. The control strategies also bring uncertainties to both the bottom-up emission inventory and the model-ready gridded emission inputs especially in winter season. In this study, we updated the WRF/Chem-EnKF Data Assimilation system to quantitatively estimate the gridded hourly SO2 emissions using hourly surface observations as constraints. Different from our previous study, in which meteorology and emission were both perturbed to obtain larger spread aiming to improve forecast skills; in this study, only emission was perturbed to ensure analyzed emission purely reflect necessary adjustments due to the emission uncertainties. In addition, direct emissions instead of emission scaling factors were used as analysis variable, which allowed for the detection of new emission sources. 2010 MEIC emission inventory (for January) was used as priori to generate 2015 and 2016 January analyzed emissions. The SO2 emission changing trends for northern, western and southern China from 2010 to 2015 and that from 2015 to 2016 (for the month of January) were investigated. The January 2010–2015 differences showed inhomogeneous change patterns in different regions: (1) significant emission reduction in southern China, (2) significant emission reduction in larger cities but widely increase in surrounding suburban and rural regions for northern China which may indicate the missing raw coal combustion for winter heating that not taken into account in the priori emission inventory; (3) significantly large emission increase in western China due to the energy expansion strategy. This not only reflected the changes during the five years, but also combined the uncertainties in the priori emissions. The January 2015–2016 differences showed widely emission reduction from 2015 to 2016, indicating the stricter control strategy fully executed nationwide. These changes were corresponded to facts in reality, indicating that the updated DA system was capable to detect the emission deficiencies and optimize the emission. By generating the hourly analyzed emissions, the diurnal pattern of emissions (in terms of hourly factors) were also obtained. Forecast experiments showed the improvements by using analyzed emissions were much larger in southern China than that in northern and western China. For Sichuan Basin, Central China, Yangzi River Delta, and Pearl River Delta, BIAS and RMSE decreased by 61.8 %–78.2 % and 27.9 %–52.2 %, respectively, and correlation coefficients increased by 12.5 %–47.1 %. However, the improvement in northern and western China were limited due to small spread. Another limitation of the study is that the analyzed emissions are still model dependent, as the ensembles are conducted through WRF/Chem model and thus the performances of ensembles are model dependent.

scholarly journals Optimization and Evaluation of SO2 Emissions Based on WRF-Chem and 3DVAR Data Assimilation

2022 ◽  
Vol 14 (1) ◽  
pp. 220
Author(s):  
Yiwen Hu ◽  
Zengliang Zang ◽  
Dan Chen ◽  
Xiaoyan Ma ◽  
Yanfei Liang ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Control Experiment ◽  
Southern China ◽  
A Priori ◽  
Time Lag ◽  
Correlation Coefficients ◽  
River Delta ◽  
Forecast Errors ◽  
Emission Inventories ◽  
So2 Emission

Emission inventories are important for modeling studies and policy-making, but the traditional “bottom-up” emission inventories are often outdated with a time lag, mainly due to the lack of accurate and timely statistics. In this study, we developed a “top-down” approach to optimize the emission inventory of sulfur dioxide (SO2) using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and a three-dimensional variational (3DVAR) system. The observed hourly surface SO2 concentrations from the China National Environmental Monitoring Center were assimilated and used to estimate the gridded concentration forecast errors of WRF-Chem. The concentration forecast errors were then converted to the emission errors by assuming a linear response from SO2 emission to concentration by grids. To eliminate the effects of modelling errors from aspects other than emissions, a strict data-screening process was conducted. Using the Multi-Resolution Emission Inventory for China (MEIC) 2010 as the a priori emission, the emission inventory for October 2015 over Mainland China was optimized. Two forecast experiments were conducted to evaluate the performance of the SO2 forecast by using the a priori (control experiment) and optimized emissions (optimized emission experiment). The results showed that the forecasts with optimized emissions typically outperformed the forecasts with 2010 a priori emissions in terms of the accuracy of the spatial and temporal distributions. Compared with the control experiment, the bias and root-mean-squared error (RMSE) of the optimized emission experiment decreased by 71.2% and 25.9%, and the correlation coefficients increased by 50.0%. The improvements in Southern China were more significant than those in Northern China. For the Sichuan Basin, Yangtze River Delta, and Pearl River Delta, the bias and RMSEs decreased by 76.4–94.2% and 29.0–45.7%, respectively, and the correlation coefficients increased by 23.5–53.4%. This SO2 emission optimization methodology is computationally cost-effective.

scholarly journals OMI measured increasing SO<sub>2</sub> emissions due to energy industry expansion and relocation in Northwestern China

2017 ◽  
Author(s):  
Zaili Ling ◽  
Tao Huang ◽  
Yuan Zhao ◽  
Jixiang Li ◽  
Xiaodong Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
Southern China ◽  
Eastern China ◽  
Step Change ◽  
River Delta ◽  
Northwestern China ◽  
Energy Industry ◽  
National Strategy ◽  
So2 Emissions ◽  
Mk Test

Abstract. The rapid economy growth makes China the largest energy consumer and sulphur dioxide (SO2) emitter in the world. In this study, we estimated the trends and step changes in the planetary boundary layer (PBL) vertical column density (VCD) of SO2 from 2005 to 2015 over China measured by the Ozone Monitoring Instrument (OMI). We show that these trends and step change years coincide with the effective date and period of the national strategy for energy development and relocation in northwestern China and the regulations in the reduction of SO2 emissions. Under the national regulations in the reduction SO2 emissions in eastern and southern China, SO2 VCD in the Pearl River Delta (PRD) of southern China exhibited the largest decline during 2005–2015 at a rate of −7 % yr-1, followed by the North China Plain (NCP) (−6.7 % yr-1), Sichuan Basin (−6.3 % yr-1), and Yangtze River Delta (YRD) (−6 % yr-1), respectively. The Mann–Kendall (MK) test reveals the step change points of declining SO2 VCD in 2009 for the PRD and 2012–2013 for eastern China responding to the implementation of SO2 control regulation in these regions. In contrast, the MK test and regression analysis also revealed increasing trends of SO2 VCD in northwestern China, particularly for several "hot spots" featured by growing SO2 VCD in those large-scale energy industry parks in northwestern China. The enhanced SO2 VCD is potentially attributable to increasing SO2 emissions due to the development of large-scale energy industry bases in energy-abundant northwestern China under the national strategy for the energy safety of China in the 21st century. We show that these large-scale energy industry bases could overwhelm the trends and changes in provincial total SO2 emissions in northwestern China and contributed increasingly to the national total SO2 emission in China. Given that northwestern China is more ecologically fragile and uniquely susceptible to atmospheric pollution as compared with the rest of China, increasing SO2 emissions in this part of China should not be overlooked and merit scientific research.

scholarly journals OMI-measured increasing SO<sub>2</sub> emissions due to energy industry expansion and relocation in northwestern China

2017 ◽  
Vol 17 (14) ◽  
pp. 9115-9131 ◽  
Author(s):  
Zaili Ling ◽  
Tao Huang ◽  
Yuan Zhao ◽  
Jixiang Li ◽  
Xiaodong Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
Southern China ◽  
Eastern China ◽  
Step Change ◽  
River Delta ◽  
Northwestern China ◽  
Energy Industry ◽  
National Strategy ◽  
So2 Emissions ◽  
Mk Test

Abstract. The rapid growth of economy makes China the largest energy consumer and sulfur dioxide (SO2) emitter in the world. In this study, we estimated the trends and step changes in the planetary boundary layer (PBL) vertical column density (VCD) of SO2 from 2005 to 2015 over China measured by the Ozone Monitoring Instrument (OMI). We show that these trends and step change years coincide with the effective date and period of the national strategy for energy development and relocation in northwestern China and the regulations in the reduction of SO2 emissions. Under the national regulations for the reduction of SO2 emissions in eastern and southern China, SO2 VCD in the Pearl River Delta (PRD) of southern China exhibited the largest decline during 2005–2015 at a rate of −7 % yr−1, followed by the North China Plain (NCP) (−6.7 % yr−1), Sichuan Basin (−6.3 % yr−1), and Yangtze River Delta (YRD) (−6 % yr−1). The Mann–Kendall (MK) test reveals the step change points of declining SO2 VCD in 2009 for the PRD and 2012–2013 for eastern China responding to the implementation of SO2 control regulation in these regions. In contrast, the MK test and regression analysis also revealed increasing trends of SO2 VCD in northwestern China, particularly for several hot spots featured by growing SO2 VCD in those large-scale energy industry bases in northwestern China. The enhanced SO2 VCD is potentially attributable to increasing SO2 emissions due to the development of large-scale energy industry bases in energy-abundant northwestern China under the national strategy for the energy safety of China in the 21st century. We show that these large-scale energy industry bases could overwhelm the trends and changes in provincial total SO2 emissions in northwestern China and contribute increasingly to the national total SO2 emissions in China. Given that northwestern China is more ecologically fragile and uniquely susceptible to atmospheric pollution than the rest of China, increasing SO2 emissions in this part of China should not be overlooked and merit scientific research.

scholarly journals Decoding long-term trends in the wet deposition of sulfate, nitrate and ammonium after reducing the perturbation from climate anomalies

2019 ◽  
Author(s):  
Xiaohong Yao ◽  
Leiming Zhang
Keyword(s):  
Wet Deposition ◽  
So2 Emissions ◽  
Emission Reductions ◽  
Deposition Fluxes ◽  
Climate Anomalies ◽  
Inflection Points ◽  
Long Term Trends ◽  
Emission Changes ◽  
The Impact

Abstract. Long-term trends of wet deposition of inorganic ions are affected by multiple factors, among which emission changes and climate conditions are dominant ones. To assess the effectiveness of emission reductions on the wet deposition of pollutants of interest, contributions from these factors to the long-term trends of wet deposition must be isolated. For this purpose, a two-step approach for preprocessing wet deposition data is presented herein. This new approach aims to reduce the impact of climate anomalies on the trend analysis so that the impact of emission reductions on wet deposition can be revealed. This approach is applied to a two-decade wet deposition dataset of sulfate (SO42−), nitrate (NO3−) and ammonium (NH4+) at rural Canadian sites. Analysis results show that the approach allows for robustly identifying inflection points on decreasing trends in the wet deposition fluxes of SO42− and NO3− in northern Ontario and Québec. The inflection points match well with the three-phase mitigation of SO2 emissions and two-phase mitigation of NOx emissions in Ontario. Improved correlations between the wet deposition of ions and their precursors' emissions were obtained after reducing the impact from climate anomalies. Furthermore, decadal climate anomalies were identified as dominating the decreasing trends in the wet deposition fluxes of SO42− and NO3− at a western coastal site. Long-term variations in NH4+ wet deposition showed no clear trends due to the compensating effects between NH3 emissions, climate anomalies, and chemistry associated with the emission changes of sulfur and nitrogen.

scholarly journals Retrospective analysis of 2015–2017 wintertime PM<sub>2.5</sub> in China: response to emission regulations and the role of meteorology

2019 ◽  
Vol 19 (11) ◽  
pp. 7409-7427 ◽  
Author(s):  
Dan Chen ◽  
Zhiquan Liu ◽  
Junmei Ban ◽  
Pusheng Zhao ◽  
Min Chen
Keyword(s):  
Data Assimilation ◽  
Control Strategies ◽  
Dominant Role ◽  
Fine Particulate Matter ◽  
Emission Control ◽  
River Delta ◽  
Control Measures ◽  
Central China ◽  
Assimilation Experiment

Abstract. To better characterize anthropogenic emission-relevant aerosol species, the Gridpoint Statistical Interpolation (GSI) and Weather Research and Forecasting with Chemistry (WRF/Chem) data assimilation system was updated from the GOCART aerosol scheme to the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) 4-bin (MOSAIC-4BIN) aerosol scheme. Three years (2015–2017) of wintertime (January) surface PM2.5 (fine particulate matter with an aerodynamic diameter smaller than 2.5 µm) observations from more than 1600 sites were assimilated hourly using the updated three-dimensional variational (3DVAR) system. In the control experiment (without assimilation) using Multi-resolution Emission Inventory for China 2010 (MEIC_2010) emissions, the modeled January averaged PM2.5 concentrations were severely overestimated in the Sichuan Basin, central China, the Yangtze River Delta and the Pearl River Delta by 98–134, 46–101, 32–59 and 19–60 µg m−3, respectively, indicating that the emissions for 2010 are not appropriate for 2015–2017, as strict emission control strategies were implemented in recent years. Meanwhile, underestimations of 11–12, 53–96 and 22–40 µg m−3 were observed in northeastern China, Xinjiang and the Energy Golden Triangle, respectively. The assimilation experiment significantly reduced both high and low biases to within ±5 µg m−3. The observations and the reanalysis data from the assimilation experiment were used to investigate the year-to-year changes and the driving factors. The role of emissions was obtained by subtracting the meteorological impacts (by control experiments) from the total combined differences (by assimilation experiments). The results show a reduction in PM2.5 of approximately 15 µg m−3 for the month of January from 2015 to 2016 in the North China Plain (NCP), but meteorology played the dominant role (contributing a reduction of approximately 12 µg m−3). The change (for January) from 2016 to 2017 in NCP was different; meteorology caused an increase in PM2.5 of approximately 23 µg m−3, while emission control measures caused a decrease of 8 µg m−3, and the combined effects still showed a PM2.5 increase for that region. The analysis confirmed that emission control strategies were indeed implemented and emissions were reduced in both years. Using a data assimilation approach, this study helps identify the reasons why emission control strategies may or may not have an immediately visible impact. There are still large uncertainties in this approach, especially the inaccurate emission inputs, and neglecting aerosol–meteorology feedbacks in the model can generate large uncertainties in the analysis as well.

scholarly journals Decoding long-term trends in the wet deposition of sulfate, nitrate, and ammonium after reducing the perturbation from climate anomalies

2020 ◽  
Vol 20 (2) ◽  
pp. 721-733
Author(s):  
Xiaohong Yao ◽  
Leiming Zhang
Keyword(s):  
Wet Deposition ◽  
So2 Emissions ◽  
Emission Reductions ◽  
Deposition Fluxes ◽  
Climate Anomalies ◽  
Inflection Points ◽  
Long Term Trends ◽  
Emission Changes ◽  
The Impact

Abstract. Long-term trends of wet deposition of inorganic ions are affected by multiple factors, among which emission changes and climate conditions are dominant ones. To assess the effectiveness of emission reductions on the wet deposition of pollutants of interest, contributions from these factors to the long-term trends of wet deposition must be isolated. For this purpose, a two-step approach for preprocessing wet deposition data is presented herein. This new approach aims to reduce the impact of climate anomalies on the trend analysis so that the impact of emission reductions on the wet deposition can be revealed. This approach is applied to a 2-decade wet deposition dataset of sulfate (SO42-), nitrate (NO3-), and ammonium (NH4+) at rural Canadian sites. Analysis results show that the approach allows for statistically identifying inflection points on decreasing trends in the wet deposition fluxes of SO42- and NO3- in northern Ontario and Quebec. The inflection points match well with the three-phase mitigation of SO2 emissions and two-phase mitigation of NOx emissions in Ontario. Improved correlations between the wet deposition of ions and their precursors' emissions were obtained after reducing the impact from climate anomalies. Furthermore, decadal climate anomalies were identified as dominating the decreasing trends in the wet deposition fluxes of SO42- and NO3- at a western coastal site. Long-term variations in NH4+ wet deposition showed no clear trends due to the compensating effects between NH3 emissions, climate anomalies, and chemistry associated with the emission changes of sulfur and nitrogen.

scholarly journals Changes in Power Plant NOx Emissions over Northwest Greece Using a Data Assimilation Technique

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 900
Author(s):  
Ioanna Skoulidou ◽  
Maria-Elissavet Koukouli ◽  
Arjo Segers ◽  
Astrid Manders ◽  
Dimitris Balis ◽  
...  
Keyword(s):  
Power Plant ◽  
Data Assimilation ◽  
Energy Production ◽  
Power Plants ◽  
Transport Model ◽  
A Priori ◽  
Filter Method ◽  
Nox Emissions ◽  
A Posteriori ◽  
Data Assimilation Technique

In this work, we investigate the ability of a data assimilation technique and space-borne observations to quantify and monitor changes in nitrogen oxides (NOx) emissions over Northwestern Greece for the summers of 2018 and 2019. In this region, four lignite-burning power plants are located. The data assimilation technique, based on the Ensemble Kalman Filter method, is employed to combine space-borne atmospheric observations from the high spatial resolution Sentinel-5 Precursor (S5P) Tropospheric Monitoring Instrument (TROPOMI) and simulations using the LOTOS-EUROS Chemical Transport model. The Copernicus Atmosphere Monitoring Service-Regional European emissions (CAMS-REG, version 4.2) inventory based on the year 2015 is used as the a priori emissions in the simulations. Surface measurements of nitrogen dioxide (NO2) from air quality stations operating in the region are compared with the model surface NO2 output using either the a priori (base run) or the a posteriori (assimilated run) NOx emissions. Relative to the a priori emissions, the assimilation suggests a strong decrease in concentrations for the station located near the largest power plant, by 80% in 2019 and by 67% in 2018. Concerning the estimated annual a posteriori NOx emissions, it was found that, for the pixels hosting the two largest power plants, the assimilated run results in emissions decreased by ~40–50% for 2018 compared to 2015, whereas a larger decrease, of ~70% for both power plants, was found for 2019, after assimilating the space-born observations. For the same power plants, the European Pollutant Release and Transfer Register (E-PRTR) reports decreased emissions in 2018 and 2019 compared to 2015 (−35% and −38% in 2018, −62% and −72% in 2019), in good agreement with the estimated emissions. We further compare the a posteriori emissions to the reported energy production of the power plants during the summer of 2018 and 2019. Mean decreases of about −35% and−63% in NOx emissions are estimated for the two larger power plants in summer of 2018 and 2019, respectively, which are supported by similar decreases in the reported energy production of the power plants (~−30% and −70%, respectively).

scholarly journals Variability and changes in Pearl River Delta water level: oceanic and atmospheric forcing perspectives

2021 ◽  
Author(s):  
Xiangbo Feng ◽  
Wei Zhang ◽  
Zhenglei Zhu ◽  
Amulya Chevuturi ◽  
Wenlong Chen
Keyword(s):  
Water Level ◽  
Pearl River Delta ◽  
Southern China ◽  
Northern South China Sea ◽  
River Delta ◽  
Pearl River ◽  
Decadal Variations ◽  
Oceanic Forcing ◽  
The Pearl River

AbstractUnderstanding water level (WL) fluctuations in river deltas is of importance for managing water resources and minimizing the impacts of floods and droughts. Here, we demonstrate the competing effects of atmospheric and oceanic forcing on multi-timescale variability and changes in the Pearl River Delta (PRD) WLs in southern China, using 52 years (1961–2012) of in-situ observations at 13 hydrological stations. PRD WL presents significant seasonal to decadal variations, with large amplitudes upstream related to strong variability of southern China rainfall, and with relatively small amplitudes at the coastal stations determined by sea level (SL) fluctuations of the northern South China Sea. We find that the strengths of atmospheric and oceanic forcing in PRD are not mutually independent, leading to a distinct contrast of WL–forcing relationships at upstream and coastal stations. In the transition zone, because of counteracts of atmospheric and oceanic forcing, no robust relationships are identified between WL and either of the forcing. We further show that in the drought season of the warm ENSO and PDO epochs, the effect of atmospheric (oceanic) forcing on PRD WL is largely enhanced (weakened), due to increased southern China rainfall and negative SL anomalies. Over the observation period, WL significantly decreased at upstream stations, by up to 28–42 mm/year for flood season, contrasting with the upward trends of <4.3 mm/year at coastal stations across all seasons. Southern China rainfall explains little of the observed WL trends, whilst SL rise is mostly responsible for the WL trends at coastal stations.

scholarly journals Ozone response to emission changes: a modeling study during the MCMA-2006/MILAGRO campaign

2009 ◽  
Vol 9 (6) ◽  
pp. 23419-23463 ◽  
Author(s):  
J. Song ◽  
W. Lei ◽  
N. Bei ◽  
M. Zavala ◽  
B. de Foy ◽  
...  
Keyword(s):  
Control Strategies ◽  
Monitoring Network ◽  
Ambient Air ◽  
Ozone Production ◽  
Daily Maximum ◽  
Chemical Production ◽  
Field Campaign ◽  
Ozone Concentrations ◽  
Urban Core ◽  
Emission Changes

Abstract. The sensitivity of ozone production to precursor emissions was investigated under five different meteorological conditions in the Mexico City Metropolitan Area (MCMA) during the MCMA-2006/MILAGRO field campaign using the gridded photochemical model CAMx driven by observation-nudged WRF meteorology. Precursor emissions were constrained by the comprehensive data from the field campaign and the routine ambient air quality monitoring network. Simulated plume mixing and transport were examined by comparing with measurements from the G-1 aircraft during the campaign. The observed concentrations of ozone precursors and ozone were well reproduced by the model. The effects of reducing precursor emissions on urban ozone production were performed for three representative emission control strategies. A 50% reduction in VOC emissions led to 7 to 22 ppb decrease in daily maximum ozone concentrations, while a 50% reduction in NOx emissions leads to 4 to 21 ppb increase, and 50% reductions in both NOx and VOC emission decrease the daily maximum ozone concentrations up to 10 ppb. These results along with a chemical indicator analysis using the chemical production ratios of H2O2 to HNO3 demonstrate that the MCMA urban core region is VOC-limited for all meteorological episodes, which is consistent with the results from MCMA-2003 field campaign; however the degree of the VOC-sensitivity is higher in the MCMA-2006 due to lower VOC/NOx emission ratio and VOC reactivity. Ozone formation in the surrounding mountain/rural area is mostly NOx-limited, but can be VOC-limited, and the range of the NOx-limited or VOC-limited areas depends on meteorology.

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