Importance of secondary decomposition in the accurate prediction of daily-scale ozone pollution by machine learning.

Machine learning (ML) models have been proven as a reliable tool in predicting ambient pollution concentrations at various places in the world. However, their performance in predicting the maximum daily 8-h averaged ozone (MDA8 O3), the metric often used for O3 pollution assessment and management, is relatively poorer. This is largely resulted from more irregular data fluctuations of the MDA8 O3 levels governed collectively by the synoptic condition, local photochemistry, and long-range transport. In order to improve the prediction accuracy of MDA8 O3, this study developed a secondary decomposition ML model framework which coupled the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) as the primary decomposition, the variational mode decomposition (VMD) as secondary decomposition, and the gate recurrent unit (GRU) ML model. By applying this secondary decomposition model framework on MDA8 O3 prediction for the first time, we showed that the prediction accuracy of MDA8 O3 is largely improved from R2 of 0.46 and RMSE of 30.4 µg/m3 for GRU without decomposition to R2 of 0.91 and RMSE of 12.6 µg/m3 over the Pearl River Delta of China. We also found that the prediction accuracy rate of O3 pollution non-attainments, an essential indicator for initiating contingency O3 pollution control, improved greatly from 14.9 % for GRU without decomposition to 72.5 %. The performance of O3 pollution non-attainment prediction is relatively higher in southwestern PRD, which is mainly due to greater number and severity of O3 non-attainments in southwestern cities located downwind of the emission hotspot area at central PRD. This study underscored the importance of secondary decomposition in accurately predicting daily-scale O3 concentration and non-attainments over the PRD, which can be extended to other photochemically active region worldwide to improve their O3 prediction accuracy and assist in O3 contingency control.

[Identification of Impacts from Meteorology and Local and Transported Photochemical Generation on Ozone Trends in Changsha from 2018 to 2020].

Ozone (O3) pollution in Hunan province has become the most important factor among the six common conventional pollutants (i.e., NO2, SO2, CO, O3, PM10, and PM2.5) in the atmospheric environment. Further investigation has indicated that the relevant studies of O3 are insufficient. Therefore, it is essential to clarify the key driving factors of O3 variations for government regulators. In this study, a combined method consisting of a generalized additive model (GAM), empirical orthogonal function (EOF), and absolute principal component scores (APCs) model was employed to identify and quantify the impacts of meteorology and local photochemical generation (local) and that transported from outside (nonlocal) on O3 variations from 2018-2020. Simultaneously, the driving factors of O3 annual values from 2018 to 2019 and from 2019 to 2020 in Changsha were analyzed. The results showed that O3 episodes were commonly caused by meteorology when the relative contribution from precursors was high, on the short-term time scale. Overall, on the temporal scale, meteorology and local were the driving factors for the increasing annual O3 from 2018 to 2019. Additionally, the contribution from meteorology, local, and nonlocal decreased from 2019 to 2020, leading to a lower level of O3 concentration in 2020. Geographically, the east, north, and south of Changsha were mainly affected by meteorology, local, and nonlocal, respectively. Throughout the three years, nonlocal exhibited a sustained decreasing trend, whereas the tendencies from meteorology and local varied by year and geography. Local contribution in the north of Changsha increased from 2018 to 2019, which was likely attributed to the increasing biogenic volatile organic compound emission (BVOCs), and it became lower in the south owing to the strengthened consumption by NOx. Impacts from meteorology on O3 in all sites were enhanced from 2018 to 2019. By contrast, local contribution decreased in the north and increased in the south with the decline in BVOC and NOx emissions from 2019 to 2020, when the meteorological impacts on O3 in the whole area became weak.

Direct identification of total and missing OH reactivities from light-duty gasoline vehicle exhaust in China based on LP-LIF measurement.

Considerable efforts have been devoted to characterising the chemical components of vehicle exhaust. However, these components may not accurately reflect the contribution of vehicle exhaust to atmospheric reactivity because of the presence of species not accounted for ("missing species") given the limitations of analytical instruments. In this study, we improved the laser photolysis-laser-induced fluorescence (LP-LIF) technique and applied it to directly measure the total OH reactivity (TOR) in exhaust gas from light-duty gasoline vehicles in China. The TOR for China I to VI-a vehicles was 15.6, 16.3, 8.4, 2.6, 1.5, and 1.6 × 104 sec-1, respectively, reflecting a notable drop as emission standards were upgraded. The TOR was comparable between cold and warm starts. The missing OH reactivity (MOR) values for China I to IV vehicles were close to zero with a cold start but were much higher with a warm start. The variations in oxygenated volatile organic compounds (OVOCs) under different emission standards and for the two start conditions were similar to those of the MOR, indicating that OVOCs and the missing species may have similar production processes. Online measurement revealed that the duration of the stable driving stage was the primary factor leading to the production of OVOCs and missing species. Our findings underscore the importance of direct measurement of TOR from vehicle exhaust and highlight the necessity of adding OVOCs and other organic reactive gases in future upgrades of emission standards, such that the vehicular contribution to atmospheric reactivity can be more effectively controlled.

Integrated assessment of volatile organic compounds from industrial biomass boilers in China: emission characteristics, influencing factors, and ozone formation potential.

Industrial biomass boilers (IBBs) are widely promoted in China as a type of clean energy. However, they emit large amount of volatile organic compounds (VOCs) and the emission characteristics and the underlying factors are largely unknown due to the sampling difficulties. In this study, three wood pellet-fueled and two wood residue-fueled IBBs were selected to investigate the characteristics of VOC emissions and to discover their underlying impacting factors. The emission factor of VOCs varied from 21.6 ± 2.8 mg/kg to 286.2 ± 10.8 mg/kg for the IBBs. Oxygenated VOCs (OVOCs) were the largest group, contributing to 30.3 - 73.6% of the VOC emissions. Significant differences were revealed in the VOC source profiles between wood pellet-fueled and wood residue-fueled IBBs. Operating load, excess air, furnace temperature, and fuel type were identified as the primary factors influencing VOC emissions. The excess air coefficient should be limited below 3.5, roughly corresponding to the operating load of 62% and furnace temperature of 630 °C, to effectively reduce VOC emissions. VOC emissions also showed great differences in different combustion phases, with the ignition phase having much greater VOC emissions than the stable combustion and the ember phases. The ozone formation potential (OFP) ranged from 4.3 to 31.2 mg/m3 for the IBBs, and the wood residue-fueled IBBs yielded higher OFP than the wood pellet-fueled ones. This study underscored the importance of OVOCs in IBB emissions, and reducing OVOC emissions should be prioritized in formulating control measures to mitigate their impacts on the atmospheric environment and human health.

Risk tradeoffs between nitrogen dioxide and ozone pollution during the COVID-19 lockdowns in the Greater Bay area of China.

Photochemical regime for ozone (O3) formation is complicated in the sense that reducing emission of nitrogen oxides (NOx) may increase O3 concentration. The lockdown due to COVID-19 pandemic affords a unique opportunity to use real observations to explore the O3 formation regime and the effectiveness of NOx emission control strategies. In this study, observations from ground networks during the lockdowns were used to assess spatial disparity of the Ratio of Ozone Formation (ROF) for nitrogen dioxide (NO2) reduction in the Greater Bay Area (GBA) of China. The health risk model from Air Quality Health Index (AQHI) system in Hong Kong was adopted to evaluate the risk tradeoffs between NO2 and O3. Results show that the levels of O3 increase and NO2 reduction were comparable due to high ROF values in urban areas of central GBA. The ozone reactivity to NO2 reduction gradually declined outwards from central GBA. Despite the O3 increases, the NOx emission controls reduced the Integrated Health Risk (IHR) of NO2 and O3 in most regions of the GBA. When risk coefficients from the AQHI in Canada or the global review were adopted in the risk analyses, the results are extremely encouraging because the controls of NOx emission reduced the IHR of NO2 and O3 almost everywhere in the GBA. Our results underscore the importance of using a risk-based method to assess the effectiveness of emission control measures and the overall health benefit from NOx emission controls in the GBA.

Measurement-based intermediate volatility organic compound emission inventory from on-road vehicle exhaust in China.

Intermediate volatility organic compounds (IVOCs) have great potential to form secondary organic aerosols (SOA) in the atmosphere. Thus, a high-resolution IVOC emission inventory is essential for the accurate simulation of SOA formation. This study developed the first nationwide on-road vehicular IVOC emission inventory in China based on localized measurement of the IVOC emission factors and volatility distributions for various vehicle types. The total vehicular IVOC emissions in China in 2019 were estimated to be 241.2 Gg. Heavy-duty trucks, light-duty trucks, and light-duty passenger vehicles contributed the most, accounting for 47.6%, 24.6%, and 16.9% of total vehicular IVOC emissions, respectively. Although much higher in number, gasoline vehicles contributed 15.0%, which was far less than the contribution of diesel vehicles. The two peaks in volatility bins B12-B13 and B16-B17 accounted for 42.2% and 23.7% of the total IVOC emissions, respectively. By gridding the emission inventory into a relatively high resolution of 0.1° × 0.1°, high-emission areas and hotspots were clearly identified. In general, eastern China had substantially higher vehicular IVOC emissions than western China. High-emission areas with emission intensity >10 Mg·grid-1 covered most of the North China Plain, Yangtze River Delta, and Pearl River Delta. The emission intensity over the downtown areas of Beijing and Shanghai exceeded 50 Mg·grid-1. In contrast, IVOC emissions over western China were relatively lower, with a network structure gathering around the traffic arteries serving inter-provincial transportation. This study underscored the importance of having a localized emission factor to better reflect the IVOC emission characteristics from Chinese vehicles and to improve the assessment of their environmental impacts.

Upgrading Emission Standards Inadvertently Increased OH Reactivity from Light-Duty Diesel Truck Exhaust in China: Evidence from Direct LP-LIF Measurement.

Vehicular exhaust is an important source of reactive gases responsible for the formation of ozone and secondary organic aerosols (SOAs) in the atmosphere. Although significant efforts have been made to characterize the chemical compounds associated with vehicular exhaust, there is still a wealth of compounds that are unable to be detected, posing uncertainties in estimating their contribution to atmospheric reactivity. In this study, by improving laser-induced fluorescence techniques, we achieved the first-ever direct measurement of the total OH reactivity (TOR) from light-duty diesel truck (LDDT) exhaust with different emission standards. We found that the TOR from the LDDT exhaust was 80-130 times the TOR from the gasoline exhaust measured in Japan. Unexpectedly, we discovered increased TOR emissions along with upgrading emission standards, possibly as a collective result of high combustion temperature in the engine and the oxidation catalysts in the exhaust after-treatment that favor production of highly oxidized organics in the stricter emission standard. Most of these oxidized organics are unable to be speciated by routine measurements, resulting in the missing OH reactivity increasing rapidly from 1.91% for China III to 42.0% for China V LDDT. Upgrading the emission standard failed to reduce the TOR from LDDT exhaust, which may inadvertently promote the contribution of LDDT to the formation of ozone and SOA pollution in China.

Optimized neural network for daily-scale ozone prediction based on transfer learning.

Tropospheric ozone (O3) pollution is worsening in China, and an accurate forecast is a prerequisite to lower the O3 peak level. In recent years, machine learning techniques have attracted increasing attention in O3 prediction owing to their high efficiency and simple operation. However, the accuracy of predicting the daily O3 level is low. This study proposed a novel model by coupling long short-term memory neural network with transfer learning (TL-LSTM), with meteorology and pollutant concentration information as the model input. L2 regularization was applied to reduce the risk of overfitting and to improve the accuracy and generalization ability of the model prediction. Our results indicated that by transferring the knowledge in the model configuration from the hourly LSTM module, TL-LSTM greatly improves the predictability of the daily maximum 8 h average (MDA8) of O3 in Hong Kong. The coefficient of determination (R2) increased from 0.684 to 0.783 and the mean square error (MSE) reduced from 1.36 × 10-2 to 1.05 × 10-2. Furthermore, R2 and MSE were the highest in summer, indicating an under-prediction of peak O3 levels. This was a result of the limited number of high O3 days, which did not provide sufficient knowledge for the model to make an accurate prediction. Sobol analysis indicated that wind speed was the most sensitive factor in O3 prediction, largely due to the development of land-sea breeze circulation which effectively traps pollutants and expedites O3 formation. The results clearly demonstrate the effectiveness of the TL-LSTM in predicting the daily O3 concentration in Hong Kong. Thus, TL-LSTM can be promulgated into other photochemically active regions to assist in O3 pollution forecasting and management.

Remarkable spring increase overwhelmed hard-earned autumn decrease in ozone pollution from 2005 to 2017 at a suburban site in Hong Kong, South China.

Ozone (O3) pollution has been a persistent problem in Hong Kong, particularly in autumn when severe O3 pollution events are often observed. In this study, linear regression analyses of long-term O3 data in suburban Hong Kong revealed that the variation of autumn O3 obviously leveled off during 2005-2017, mainly due to the significant decrease of autumn O3 in 2013-2017 (period II), despite the increase in 2005-2012 (period I). In addition, the rise of O3 in summer and winter also ceased since 2013. In contrary, O3 continuously increased throughout the spring of 2005-2017, especially in period II. Consequently, an incessant increase of overall O3 was observed during 2005-2017. A statistical model combining Kolmogorov-Zurbenko filter with multiple linear regressions, and a photochemical box model incorporating CB05 mechanism were applied to probe the causes of the above trends. In general, O3 production was controlled by VOC-limited regime throughout 13 years. The meteorological variability and regional transport facilitated the O3 growth in period Ι. In contrast, the unchanged O3 level in period II was attributable to the negative impact of meteorological variability and reduction of regional transport effect on O3 formation and accumulation, as well as the negligible change in locally-produced O3. In autumn of period II, the inhibitory meteorological variability, reduced regional transport, and alleviated local production were the driving force for the hard-earned decrease of O3. However, the remarkable rise of spring O3 was caused by the reduction of NOx, especially in the spring of period II. The findings of the long-term and seasonal variations of O3 pollution in Hong Kong are helpful for future O3 mitigation.

Identification of close relationship between large-scale circulation patterns and ozone-precursor sensitivity in the Pearl River Delta, China.

To curb the continuous deterioration of ozone (O3) pollution in China, identifying the O3-precursor sensitivity (OPS) and its driving factors is a prerequisite for formulating effective O3 pollution control measures. Traditional OPS identification methods have limitations in terms of spatiotemporal representation and timeliness; therefore, they are not appropriate for making OPS forecasts for O3 contingency control. OPS is not only influenced by local precursor emissions but is also closely related to meteorological conditions governed by large-scale circulation (LSC). In this study, a localized three-dimensional numerical modeling system was used to investigate the relationship between LSC and OPS in the Pearl River Delta (PRD) of China during September 2017, a month with continuous O3 pollution. Our results highlighted that there was a close relationship between LSC and OPS over the PRD, and the four dominant LSC patterns corresponded well to the NOx-limited, NOx-limited, VOC-limited, and transitional regimes, respectively. The clear linkage between LSC and OPS was mainly driven by the spatial heterogeneity of NOx and VOC emissions within and beyond the PRD along the prevailing winds under different LSC patterns. A conceptual model was developed to highlight the intrinsic causality between the LSC and OPS. Because current technology can accurately forecast LSC 48-72 h in advance, the LSC-based OPS forecast method provided us with a novel approach to guide contingency control and management measures to reduce peak O3 at a regional scale.

[Analysis of Ozone Pollution Spatio-temporal Evolution Characteristics and Identification of Its Long-term Variation Driving Factor over Hunan Province].

Despite the alleviation of particulate matter (PM), the ambient ozone (O3) concentration is continuously increasing in Hunan province where the investigation of O3 pollution has been rarely reported. Accordingly, the spatio-temporal evolution of O3 pollution was first analyzed based on hourly air quality data observed by national monitoring stations from 2015 to 2020 over 14 cities in Hunan province. Afterwards, the combination of meteorological data from the European Center for Medium-range Weather Forecast (ECMWF) and the generalized additive model (GAM) was applied to investigate the driving factors of the O3 long-term trend during this period. The results presented obvious diurnal, monthly, and seasonal characteristics of O3 variations. High O3 concentrations occurred in May and September monthly, and the peak O3 season was autumn. Furthermore, the 90th percentile O3 increased at a rate of 4.7 µg·(m3·a)-1 temporally, and high O3 values mainly occurred in the north-eastern region spatially, in contrast to the low O3 values in the western region. The modeling results indicated that the increase in O3 was mainly ascribed to precursor emissions. Furthermore, meteorology promoted a rise in O3 with the impact magnitude of 1 µg·(m3·a)-1. Remarkably, meteorology accelerated the O3 increases in spring, summer, and the eastern region, whereas it restrained increases in autumn, winter, and the northwest. The effect of meteorology on PM10 was different from O3 during this period. Overall, this study highlighted the importance of meteorological impacts when regulating emission reduction measures for O3 abatement. It required greater effort regarding O3 mitigation to offset the side-effect from meteorology in meteorology-sensitive seasons and regions. Additionally, the regional corporation is indispensable to reduce O3 transportation from upwind.

Quantification of temperature dependence of vehicle evaporative volatile organic compound emissions from different fuel types in China.

The evaporative emissions of volatile organic compounds (VOCs) from motor vehicles are dependent upon the ambient temperature. However, the quantitative relationship between evaporative VOC emissions and ambient temperature has rarely been reported, and it is not reflected in the Chinese VOCs emission inventory (EI). In this study, a series of evaporative tests were conducted on a parked gasoline-fueled vehicle in a Variable Temperature Sealed Housing Evaporative Determination chamber under seven temperatures from 298 K to 313 K at intervals of 2.5 K. Results showed that total hydrocarbon emissions at 313 K were 25.7, 12.3, and 26.7 times those at 298 K for China V, China VI, and ethanol-blended E10 fuels, respectively. China V consistently exhibited the lowest evaporative VOC emissions at all temperatures, while those of E10 surpassed even those of China VI and became the highest at 308 K and higher. Along with increasing temperature, the proportions of alkanes and alkenes gradually increased whereas those of aromatics and oxygenated VOCs decreased. Alkenes accounted for less than 20% of the evaporative VOC emissions but contributed to approximately 60% of the total OH loss (LOH) at 298 K and to over 70% at 313 K. cis-2-Butene and trans-2-butene were responsible for the greatest increase in LOH from China V, due to their higher OH reactivity. Our results clearly demonstrated the exponential increases of evaporative VOC emissions and the associated atmospheric reactivity with temperature, and also highlighted that upgrading the emission standard from China V to China IV and promoting the E10 fuel would not contribute to the reduction of evaporative VOC emissions. The strong temperature dependence of evaporative VOC emissions underscores the importance of developing a temperature-driven dynamic EI in China, and the functional relationships retrieved from this study form an essential step in developing such a dynamic EI.

Multi-factor reconciliation of discrepancies in ozone-precursor sensitivity retrieved from observation- and emission-based models.

Ground-level O3 pollution has been continuously worsening in China despite gradual improvement in other major pollutant levels. Understanding the sensitivity of O3 production to its precursors (OPS) is a prerequisite for formulating effective O3 control measures, but this has been hampered by significant discrepancies in OPS produced by traditional identification approaches using observation-based models (OBM) and emission-based models (EBM). In this study, by applying OBM and EBM in parallel within a month having significant O3 pollution in Shanghai, China, we demonstrated that a lack of carbonyl input, overestimation in NO2 monitoring data, and differences in simulation period and emission reduction area were the core factors leading to OPS discrepancies, and that a reliable OPS cannot be obtained unless these factors are reconciled. By collectively addressing these factors, the number of days with a consistent OPS from both models increased from 6-7 to 20-21 in a month, and the R value defined to quantify the discrepancy decreased by ∼55%. The contributions of these factors to OPS discrepancy differed greatly in urban and suburban settings, mainly caused by differences in pollutant emission and transport characteristics. Overall, OPS identified solely by OBM or EBM is associated with great uncertainty, while reliable OPS estimation can be achieved by a collective application of OBM and EBM with consensus on the above factors. The method demonstrated here could be applied to other photo-chemically active regions worldwide as part of efforts to address ozone pollution.

Understanding the underlying mechanisms governing the linkage between atmospheric oxidative capacity and ozone precursor sensitivity in the Yangtze River Delta, China: A multi-tool ensemble analysis.

Continued exacerbation of ozone (O3) pollution in China has driven the urgent need for an emission control strategy that efficiently reduces O3 levels. Determining O3 precursor sensitivity (OPS) and its driving factors is a prerequisite for formulating effective O3 control strategies. In this study, we proposed an atmospheric oxidative capacity-based indicator, HO2/OH, and demonstrated its effectiveness in indicating OPS over the Yangtze River Delta (YRD) of China by applying a localized comprehensive air quality model with extensions (CAMx) coupled with the Weather Research and Forecasting (WRF) model. A strong correlation was discovered between HO2/OH and OPS, and HO2/OH showed the best performance in separating NOx- and VOC-limited regimes in comparison with other commonly used indicators. A comprehensive analysis with ensemble diagnostic tools revealed the spatial heterogeneity of NOx and VOC emissions and the impact of regional transport controlling the relationship between OPS variations and the HO2/OH indicator over the YRD. The process analysis results show that days with higher contributions from horizontal advection favored OPS transitions in Shanghai, Nanjing, Hefei, Suzhou, and Wuhu, while vertical advection caused OPS transitions in Hangzhou and Ningbo. O3 source apportionment technology analysis indicated that the regional contributions from Zhejiang and Jiangsu/Anhui corresponded well to the NOx-limited and VOC-limited regimes, respectively. Our results provide a better understanding of the underlying mechanisms of the relationship between OPS and the HO2/OH indicator and can help guide contingency control measures for O3 despiking over the YRD and other photochemically active regions worldwide.

Emission source-based ozone isopleth and isosurface diagrams and their significance in ozone pollution control strategies.

In the past decade, ozone (O3) pollution has been continuously worsening in most developing countries. The accurate identification of the nonlinear relationship between O3 and its precursors is a prerequisite for formulating effective O3 control measures. At present, precursor-based O3 isopleth diagrams are widely used to infer O3 control strategy at a particular location. However, there is frequently a large gap between the O3-precursor nonlinearity delineated by the O3 isopleths and the emission source control measures to reduce O3 levels. Consequently, we developed an emission source-based O3 isopleth diagram that directly illustrates the O3 level changes in response to synergistic control on two types of emission sources using a validated numerical modeling system and the latest regional emission inventory. Isopleths can be further upgraded to isosurfaces when co-control on three types of emission sources is investigated. Using Guangzhou and Foshan as examples, we demonstrate that similar precursor-based O3 isopleths can be associated with significantly different emission source co-control strategies. In Guangzhou, controlling solvent use emissions was the most effective approach to reduce peak O3 levels. In Foshan, co-control of on-road mobile, solvent use, and fixed combustion sources with a ratio of 3:1:2 or 3:1:3 was best to effectively reduce the peak O3 levels below 145 ppbv. This study underscores the importance of using emission source-based O3 isopleths and isosurface diagrams to guide a precursor emission control strategy that can effectively reduce the peak O3 levels in a particular area.

Identification of two main origins of intermediate-volatility organic compound emissions from vehicles in China through two-phase simultaneous characterization.

Intermediate-volatility organic compounds (IVOCs) emitted from vehicles are generally in the gas phase but may partly partition into particle phase when measured under ambient temperature. To have a complete and accurate picture of IVOC emissions from vehicles, gas- and particle-phase IVOCs from a fleet of gasoline and diesel vehicles were simultaneously characterized by dynamometer testing in Guangzhou, China. The total IVOC emission factors of the diesel vehicles were approximately 16 times those of the gasoline vehicles, and IVOCs were mainly concentrated in the particle phase in the form of the unresolved complex mixture (UCM). The chemical compositions and volatility distributions of the gas-phase IVOCs differed much between gasoline and diesel vehicles, but were similar to those of their respective fuel content. This indicated that vehicle fuel is the main origin for the gas-phase IVOC emissions from vehicles. In comparison, the chemical compositions of the particle-phase IVOCs from gasoline and diesel vehicles were similar and close to lubricating oil content, implying that lubricating oil plays an important role in contributing to particle-phase IVOCs. The highest IVOC fraction in the particle phase occurred from B16-B18 volatility bins, overall accounting for more than half of the particle-phase IVOCs for both the gasoline and diesel vehicles. A conceptual model was developed to articulate the distributions of lubricating oil contents and their evaporation and nucleation/adsorption capabilities in the different volatility bins. The IVOCs-produced secondary organic aerosol (SOA) were 1.4-2.6 and 3.9-11.7 times POAs emitted from the gasoline and diesel vehicles, respectively. The tightening of emission standards had not effectively reduced IVOC emissions and the SOA production until the implementation of China VI emission standard. This underscores the importance of accelerating the promotion of the latest emission standard to alleviate pollution from vehicles in China.

Identification of close relationship between atmospheric oxidation and ozone formation regimes in a photochemically active region.

Understanding ozone (O3) formation regime is a prerequisite in formulating an effective O3 pollution control strategy. Photochemical indicator is a simple and direct method in identifying O3 formation regimes. Most used indicators are derived from observations, whereas the role of atmospheric oxidation is not in consideration, which is the core driver of O3 formation. Thus, it may impact accuracy in signaling O3 formation regimes. In this study, an advanced three-dimensional numerical modeling system was used to investigate the relationship between atmospheric oxidation and O3 formation regimes during a long-lasting O3 exceedance event in September 2017 over the Pearl River Delta (PRD) of China. We discovered a clear relationship between atmospheric oxidative capacity and O3 formation regime. Over eastern PRD, O3 formation was mainly in a NOx-limited regime when HO2/OH ratio was higher than 11, while in a VOC-limited regime when the ratio was lower than 9.5. Over central and western PRD, an HO2/OH ratio higher than 5 and lower than 2 was indicative of NOx-limited and VOC-limited regime, respectively. Physical contribution, including horizontal transport and vertical transport, may pose uncertainties on the indication of O3 formation regime by HO2/OH ratio. In comparison with other commonly used photochemical indicators, HO2/OH ratio had the best performance in differentiating O3 formation regimes. This study highlighted the necessities in using an atmospheric oxidative capacity-based indicator to infer O3 formation regime, and underscored the importance of characterizing behaviors of radicals to gain insight in atmospheric processes leading to O3 pollution over a photochemically active region.

Identification of long-term evolution of ozone sensitivity to precursors based on two-dimensional mutual verification.

Tropospheric ozone pollution has been continuously worsening in China during the past decade. Identification of long-term evolution of ozone sensitivity to precursors is essential to evaluating the impact of emission reduction measures on ozone pollution. Traditional observation-based model and 3-d numerical model are not suitable for analyzing long-term variation of ozone sensitivity to precursors. In this study, by transforming the conventional ozone isopleth plot into a VOCR isopleth plot in the functional space of NOx and ozone concentrations, we developed a novel approach to identify ozone sensitivity to precursors by simply using long-term monitoring data of ozone, NOx and temperature. This approach estimated ozone formation regimes (OFR) by ozone sensitivity to NOx and temperature separately, and the convergence of OFR serves as a way of mutual verification. We found that ozone formation was generally in the VOCR-limited or transitional regime in Shanghai, the largest metropolitan area in China. However, OFR was shifted to NOx-limited at Pudong station during 2017-19 due much to the stringent NOx emission control. OFR was also shifted to NOx-limited along with the increasing temperature. When temperature was over 30 °C, Shanghai was mostly in a NOx-limited OFR. This highlights that the NOx emission control measures need to be strengthened to reduce peak ozone levels more efficiently. Jinshan station exhibited a different trend with OFR shifted to VOCR-limited in 2017-19, which proved the effectiveness of VOCs emission control on petrochemical sector. However, OFR was shifted to NOx-limited when temperature was over 30 °C, suggesting more stringent VOCs emissions control should be targeted on days with higher temperature.

Characterization of VOC emissions from construction machinery and river ships in the Pearl River Delta of China.

Speciated characterization of Volatile Organic Compounds (VOCs), including oxygenated VOCs (OVOCs), from construction machinery and river ships in China is currently lacking. In this regard, we conducted field measurement on speciated VOC (including OVOC) emissions from six construction machinery and five river ships in the Pearl River Delta (PRD) region to identify VOC emission characteristics. We noticed that OVOC emissions from construction machinery and ships accounted for more than 50% of the total VOC emissions, followed by alkenes, aromatics and alkanes. Formaldehyde and acetaldehyde were the most emission species, accounting for 61.8%-83.2% of OVOCs. For construction machinery, the fuel-based emission factors of roller, grader and pile driver were 3.12, 3.12 and 7.36 g/kg, respectively. With the rigorous restraint by the national emission standards, VOC emissions of construction machinery had decreased considerably, especially during stage Ⅲ. Ozone formation potential was also significantly reduced due to the significant decrease in emissions of OVOCs and alkenes with higher reactivity. For river ships, the fuel-based emission factors of cargo ships and speedboat were 1.46 and 0.44 g/kg, respectively. VOC emissions from construction machinery and river ships in Guangdong Province in 2017 were 8851.0 and 4361.0 ton, respectively. This study filled the knowledge gaps of reactive gas emissions from different kinds of non-road mobile sources over the PRD, and more importantly, highlighted the necessity in adding OVOC measurement to give a complete and accurate depiction of reactive gas emissions from non-road mobile sources.

Synoptic condition-driven summertime ozone formation regime in Shanghai and the implication for dynamic ozone control strategies.

Regarding the continuous worsening of tropospheric ozone pollution, the scenario in Shanghai is a microcosm of the entire China. Understanding the ozone formation regimes (OFRs), their variations, and driving factors is a prerequisite for formulating effective ozone control strategies. Traditional OFR estimation by numerical model, which often involves sensitivity analysis on at least tens of scenarios, is labor-intensive and time-consuming; therefore, it is not appropriate to make OFR forecasts to guide ozone contingency control. In this study, by using a localized modeling system consisting of the Weather Research and Forecasting, Sparse Matrix Operator Kernel Emissions, and Community Multiscale Air Quality models and considering the latest emission inventory over the Yangtze River Delta of China, we discovered a strong connection between the variations of large-scale circulation (LSC) and OFRs over Shanghai in July 2017, thereby providing an alternative way to infer OFR. During the northward movement of Western Pacific Subtropical High from South China Sea, the wind field over Shanghai changed from weak westerly to moderate southwesterly and to one without a distinct direction. The local OFR shifted from anthropogenic volatile organic compounds (AVOCs)-limited to NOx-limited and ultimately to the transitional regime. Such a variation in OFR is essentially driven by the spatial heterogeneity of NOx and AVOC emissions in different directions of Shanghai, brought on by the wind under different LSC patterns. With the existing weather forecasting technology, the LSC patterns can be well-predicted 48-72 h in advance. Hence, we propose the adoption of a dynamic ozone control strategy for Shanghai with the priority control target on AVOC or NOx emission sources adjusted according to the LSC pattern and OFR forecasts in a forthcoming O3 pollution episode. This would serve to maximize the peak ozone reduction under varying pollution conditions.