Development of Ozone Reactivity Scales for Volatile Organic Compounds in a Chinese Megacity

. We developed incremental reactivity (IR) scales for 116 volatile organic compounds (VOCs) in a Chinese 15 megacity (Guangzhou) and elucidated their application in calculating the ozone (O 3 ) formation potential (OFP) in China. Two sets of model inputs (emission-based and observation-based) were designed to localize the IR scales in Guangzhou using the Master Chemical Mechanism (MCM) box model, and were also compared with those of the U.S. The two inputs differed in how primary pollutant inputs in the model were derived, with one based on emission data and the other based on observed pollutant levels, but the maximum incremental reactivity (MIR) scales derived from them were fairly similar. The 20 IR scales showed a strong dependence on the chemical mechanism (MCM vs. Statewide Air Pollution Research Center), but the discrepancy between China and the U.S. using a similar chemical mechanism was not large. With a given chemical mechanism, the MIR scale for most VOCs showed a relatively small dependence on environmental conditions. However, when the NOx availability decreased, the IR scales became more sensitive to environmental conditions and the discrepancy between the IR scales obtained from emission-based and observation-based inputs increased, thereby implying the necessity 25 to localize IR scales over mixed-limited or NOx-limited areas. This study provides recommendations for the application of IR scales, which has great significance for VOC control in China and other countries suffering from serious O 3 air pollution . vs. SAPRC) than to chemical environmental conditions. With a given chemical mechanism, the discrepancy between China and the U.S. was not large, thereby implying that the establishment of an accurate chemical mechanism is more important than IR localization. However, although there was a fairly good consistency between the localized MIR scales obtained from the emission-based and observation-based inputs, the IR discrepancy increased as the NOx availability decreased, thereby implying the necessity to 345 localize IR scales over mixed-limited or NOx-limited areas and the need for realistic scenarios in rapidly changing environments. The localized IR results in Guangzhou were taken as a case to clearly elucidate how to apply IR and OFP scales to deal with reactive VOC identification, which has great implications for VOC control in China and other countries suffering from serious O 3 pollution.


Introduction
Tropospheric ozone (O3) is an important component of photochemical air pollution and exerts great effects on atmospheric chemistry, climate change, and human and vegetation health (Agathokleous et al., 2020;IPCC, 2013;Lelieveld et al., 2008;30 Monks et al., 2015). Surface O3 pollution has become a major air quality issue in China in recent decades (Wang et al., 2017; and references therein). On a national scale, the O3 pollution situation has worsened despite significant improvements in other routinely monitored pollutants (e.g., SO2, NO2, CO, PM2.5, and PM10) (Chen et al., 2020;Li et al., 2019a;Liu and https://doi.org/10.5194/acp-2021-44 Preprint. Discussion started: 17 February 2021 c Author(s) 2021. CC BY 4.0 License. Sun et al., 2016;Wang et al., 2009;Xu et al., 2020;Zheng et al., 2018). Alleviating O3 pollution is the key to evaluating air quality control effectiveness during the Blue Sky Protection Campaign, and is also the 35 focus of air quality management in the 14th Five-Year Plan (2021-2025. Considering the significance of volatile organic compounds (VOCs) to O3 formation, growing importance has been attached to the VOC management. The O3 formation potential (OFP) scale has been extensively used to quantify the relative effects of individual VOCs on O3 formation and to aid in the development of cost-effective control strategies (Carter and Atkinson, 1989;Chang and Rudy, 1990). For a given VOC or VOC mixture, the OFP is determined by two factors, namely kinetic reactivity (KR) and mechanistic 40 reactivity (MR) (Carter, 1994a;Carter and Atkinson, 1989;Venecek et al., 2018). KR refers to the fraction of the given VOC (mixture) being reacted in a scenario, and MR refers to the O3 change caused by the reaction of the amount of the given VOC (mixture). To further quantify the OFP, Carter and Atkinson (1989) and Carter (1994a) defined two operational concepts of incremental reactivity (IR) and relative reactivity (RR). IR is defined as the grams of O3 change per gram of VOCs added to a base mixture, and RR is calculated as the IR of the target VOC divided by the IR of a reference VOC. 45 3 require further examination. Addressing these two concerns has great significance for O3 control in China and other countries suffering from serious O3 pollution.
In this study, we designed two sets of model inputs and adopted the Master Chemical Mechanism version 3.3.1 (MCMv3.3.1) box model to localize the IR scales in urban Guangzhou, a megacity of southern China. The two model inputs differed in 70 how the primary pollutant inputs in the model for Guangzhou were derived, with one based on emission data and the other based on observed pollutant levels, whereas the other inputs were the same. The obtained results were used to elucidate how to apply IR and OFP scales. In this paper, we first present and compare the localized emission-based and observation-based IR scales in urban Guangzhou. We then provide comparisons between the localized IR scales and U.S. IR scales and identify key factors affecting the IR scales of VOCs. Finally, we provide recommendations for the application of IR and OFP scales 75 to aid in VOC control in Chinese cities.

Typical urban pollution scenarios
Guangzhou is the regional center of the Pearl River Delta (PRD), one of the most developed regions in China ( Figure S1). In 2019, Guangzhou covered 7434 km 2 and the urbanization rate was 86 %. The area is home to over 15 million people, and 80 most of the residents live in urbanized districts. Two-year data from 1 January 2018 to 31 December 2019 used for IR localization were obtained from an urban site in Guangzhou ( Figure S1). Detailed information on the sampling site, measurement techniques, and quality assurance/control procedures are provided in the SI.
The 1-day observation-based model inputs were median diurnal profiles of 67 O3 episode days ( Figure S2), in which the maximum daily 8-hour average O3 mixing ratio exceeded the Chinese National Ambient Air Quality Standard, i.e., 75 ppbv 85 (Class II). During the 67 O3 episodes, the large amplitude (defined as the maximum minus the minimum) of the diurnal O3 cycle (104 ± 23 ppbv) indicated intense in situ photochemical O3 production. The weather conditions presented a high temperature (27.7 ± 3.7 °C) and moderate relative humidity (RH; 49 ± 14 %). These weather conditions are favorable for O3 formation. The O3 precursors NOx and VOCs exhibited a morning peak and another evening peak in the rush hours, and the observed average NOx and VOC mixing ratios (38.05 and 39.16 ppbv, respectively; Table S1) were comparable to those in 90 other megacities such as Beijing and Shanghai (Li et al., 2015;Liu et al., 2019;Sun et al., 2018). Within the observed VOC compositions (Figure 1a), alkanes made the largest contribution (59 %), followed by aromatics (20 %), alkenes (15 %), and alkynes (6 %). The average VOC/NOx ratio was 0.99 ± 0.46 ppbv ppbv-1. The diurnal variation in primary pollutants and high NOx concentrations were representative of urban pollution conditions greatly affected by fresh traffic emissions (with intense NOx emissions). 95 https://doi.org/10.5194/acp-2021-44 Preprint. Discussion started: 17 February 2021 c Author(s) 2021. CC BY 4.0 License.

Chemical box model Setup
A chemical box model was adopted for the IR calculation. The model was run based on the platform of F0AM (Framework for 0-D Atmospheric Modeling) (Wolfe et al., 2016), and built based on the near-explicit chemical mechanism of MCMv3.3.1 (http://mcm.leeds.ac.uk/MCM/), which describes the degradation pathways of 143 primary VOCs in detail (Jenkin et al., 2003;Saunders et al., 2003). In addition to state-of-the-art chemistry, the model also incorporated physical 100 processes, including solar radiation, diurnal evolution of the planetary boundary layer (PBL), dry deposition, and dilution with background air. A detailed description of the model configuration is provided in previous studies (Xue et al., 2014;Xue et al., 2013) and is also documented in the SI.
We designed two 1-day model inputs to compare the observation-based and emission-based IR scales (Table S2). With observation-based inputs, the model was constrained by the median diurnal profiles of NO, NO2, VOCs (39 compounds), 105 SO2, and CO concentrations observed in the 67 selected O3 episodes. With emission-based inputs, the model read the median diurnal profiles of the emission rates of NO, NO2, VOCs (116 compounds), SO2, and CO (see the SI for detailed methods to calculate the emission rate) and was initialized using observational data at 06:00 local time (LT; the initial time of model integration) (Table S3). The VOC composition factions calculated from the observed data were not the same as those calculated from the emission data because observational data were only available for 39 compounds (Figure 1). With 110 emission-based inputs, the initial concentrations of VOCs without available observational data were set as 0.10 ppbv, except for those of formaldehyde (0.50 ppbv) and acetaldehyde (0.30 ppbv). Sensitivity tests were conducted to examine the effect of uncertainty caused by such treatment in VOC initialization on the obtained IR scales, and the results showed that the effects were generally negligible (Table S4).
In addition to the above differences, the two model inputs shared a common setup. Specifically, the model was constrained 115 by the median diurnal profiles of meteorological parameters, including temperature, RH, and pressure obtained from the 67 selected O3 episodes; the HONO input was assumed to be equal to 2 % NOx input (Qin et al., 2009); radicals such as OH and HO2 were initialized according to 2-day pre-run results; and O3 was initialized using the observed data at 06:00 LT, and then its chemistry and concentrations were simulated with the constraints of other relevant species in the following integration. For both model inputs, the model was run with 06:00 LT as the initial time, and the integration lasted for 10 120 hours with a step of 1 hour. A series of sensitivity experiments (emission-based model inputs) with changing environmental conditions were conducted to identify possible reasons for the IR discrepancy between Guangzhou and the U.S.

Calculation of ozone reactivity scales for VOCs
The IR scales under three specified NOx conditions and base NOx conditions were localized in Guangzhou considering their dependence on NOx availability. Two major procedures, including NOx-adjusted runs and VOC-added runs, were used to 125 calculate the IR scales. The detailed methods were illustrated in previous studies (Carter, 1994a, b (Tan et al., 2019;Xue et al., 2014), the NOx-adjusted results of both inputs indicated that the O3 formation occurred in a VOC-limited regime in urban Guangzhou and the MIR scale is appropriate for urban Guangzhou conditions. This is probably also the case for other Chinese megacities (Ou et al., 2016;Xue et al., 2014). Identifying to which scale the base NOx condition has a good approximation is a prerequisite for determining the appropriate reactivity 140 scale to apply.
With prescribed NOx inputs for a specified NOx condition, the base run and a series of VOC-added runs were simultaneously performed. In the VOC-added runs, a small amount of the target VOC was added while other inputs were kept unchanged relative to the base run. The criterion used to determine the addition amount of the target VOC was that the model-simulated peak O3 change between the base run and VOC-added run should exhibit a near-linear relationship against 145 the amount added (Carter, 1994a, b). To make a more precise determination, we changed the original method by increasing the target VOC input in the VOC-added runs from small to large folds (1-20 fold with a bin precision of 0.01), and fitted the obtained derivatives (with a precision of 0.01) of the model-simulated peak O3 change relative to the target VOC change to a linear regression line to locate the point of interest. In this procedure, there was a difference in the treatment of the target VOC input between the emission-based and observation-based inputs. With emission-based inputs, the target VOC input was 150 composed of the initial concentration and emission rate throughout the scenarios during both the base run and VOC-added run, and both the initial and emitted VOCs were increased from small to large folds in the series of VOC-added runs. The base run only needed to be performed once and used for the IR calculation for all of the individual VOCs. In contrast, with the observation-based inputs, the target VOC was initialized but not constrained in the following integration, and only the initial target VOC was increased from small to large folds in the series of VOC-added runs. For the IR calculation of each 155 VOC, a base run needed to be performed.
With both inputs, the amount of the target VOC input was not directly quantified, but calculated by adding an inert tracer species "TRACE" to be emitted and initially present in the same amount as that of the target VOC (TRACE was only initially present in the same amount as that of the target VOC with observation-based inputs as there were no emission data). The final calculated concentration of TRACE was used as a measure of the target VOC input (Carter, 1994b). The difference 160 in the target VOC amount between the VOC-added run input and base run input was the small added amount. This calculation avoided complexities introduced by irrelevant physical factors such as the varying PBL height. The IR value of the target VOC was calculated as follows: where IRi represents the IR of VOCi, △O3 is the mass of additional O3 formed, and △VOCi is the amount of VOCi added to 165 the scenario. IR values for 116 VOCs (39 VOCs) were calculated with emission-based (observation-based) inputs. Because 39 VOC species were the same within the two inputs, the IR scales for these common VOC species were compared, as discussed in Section 3.1. This is also why the IR scales for 111 (79)  3 Results and discussion 170

Localized ozone reactivity scales for VOCs in Guangzhou
The IR scales for 116 VOCs under the MIR (MIR-Guangzhou), MOR (MOR-Guangzhou), EBIR (EBIR-Guangzhou), and base scenarios were localized ( Figure 3 and Table 1; the results refer to emission-based IR scales unless stated). Under all three specified NOx conditions, alkenes were the most reactive VOC group (IR ranges of 2.46-14.11, 1.08-5.17, and 0.03-2.52 g g -1 under the MIR, MOR, and EBIR scenarios, respectively). This was reasonable considering their fast reaction rates 175 with OH radicals (http://www.chemspider.com/). Within the alkenes, trans/cis-2-butene was one of the most reactive compounds. The other reactive VOC groups were aromatics (0.38-9.64, -0.04-3.95, and -0.43-2.10 g g -1 under the MIR, MOR, and EBIR scenarios, respectively) and oxygenated VOCs (OVOCs; -1.19-20.42, -1.36-7.30, and -1.65-3.42 g g -1 under the MIR, MOR, and EBIR scenarios, respectively). The IR scales of both VOC groups exhibited a wide distribution and relied heavily on the NOx conditions. Within the aromatics, trimethylbenzene isomers were among the most reactive 180 compounds. Within the OVOCs, aldehydes served as the most reactive sub-group, followed by ketones, alcohols, and other oxygenates. Biacetyl was the most reactive compound not only within OVOCs, but also within all of the defined VOCs.
Consistent with the results of Carter et al. (2010), the IR values of benzaldehyde and its homologues were negative because these compounds are strong radical and NOx sinks. A high proportion of compounds within the alkane (-0.10-1.29, -0.03-0.81, and -0.16-0.66 g g -1 under the MIR, MOR, and EBIR scenarios, respectively), alkyne (0.20, 0.12, and 0.07 g g -1 under 185 the MIR, MOR, and EBIR scenarios, respectively), and halocarbon (0.002-3.03, 0.002-1.60, and 0.001-0.94 g g -1 under the MIR, MOR, and EBIR scenarios, respectively) classes were unreactive or less reactive; therefore, these compounds are potential substitutes for more reactive compounds. Because the base NOx condition of urban Guangzhou was similar to the NOx condition of the MIR scenario, a high consistency was found between the base IR scale and the MIR scale (reduced https://doi.org/10.5194/acp-2021-44 Preprint. Discussion started: 17 February 2021 c Author(s) 2021. CC BY 4.0 License. major axis (RMA; Leduc, 1987) slope: 0.99; R 2 = 1), thereby indicating that O3 formation occurred in a strongly  limited regime and the MIR scale is the most appropriate for application in urban Guangzhou.
Despite the similarities, the IR scales showed significant dependence on the NOx availability, the degree of which varied among compounds (Figure 3). With the decrease in NOx availability, NOx became the key precursor to limit O3 formation, and the IR magnitudes rapidly decreased. Compared with those in the MIR scenarios, the average IR values of VOCs significantly decreased under the MOR (by -61 %) and EBIR scenarios (by -82 %). Owing to the varying sensitivity to NOx 195 availability, the relative ranks of several compounds also changed greatly. For example, the ranks of aldehydes (propionaldehyde, glyoxal, and butanal; Figure 3), which behave as significant radical sources , decreased much faster under low NOx conditions, in which O3 formation was limited more by the NOx availability than by the radical levels. The ranks of phenol and its homologues also presented marked deviations from the least square linear regression line. This was because the degradation products of phenol and its homologues behave as potent NOx sinks (i.e., 200 forming HNO3), which further lowers the NOx availability and reduces the IR of other VOCs. Overall, NOx availability is a dominant factor affecting both the IR ranks and magnitudes.
We also compared the MIR, MOR, and EBIR scales for 39 common VOC species obtained from both the emission-based and observation-based inputs (Figure 4). For most VOCs, a fairly good consistency of IR scales was found, as indicated by the modest to strong R 2 (0.95-0.98). The IR ranks of four VOCs (1-butene, ethyl benzene, n-dodecane, and styrene) differed 205 significantly between the two inputs. These four compounds were markedly sensitive to environmental conditions, and the IR for these compounds reflected a balance between the positive effects on O3 formation and the negative effects caused by radical inhibition. Although not mathematically significant (p = 0.47, 0.25, and 0.19 under the MIR, MOR, and EBIR scenarios, respectively; tested by one-way analysis of variance method), the discrepancy of the IR magnitudes between the emission-based and observation-based inputs was non-negligible, and the discrepancy increased as the NOx availability 210 decreased. Quantitatively, the average MIR values obtained from the observation-based inputs were lower (by -17 %) than those obtained by the emission-based inputs, but the average MOR and EBIR absolute values were higher (by 35 % and 49 %, respectively). Because both inputs shared similar physical configurations within the model, the discrepancy could have been related to the different chemical environmental conditions (such as VOC compositions) among the two inputs.
Possible reasons for the discrepancy are discussed in Section 3.2. Overall, the comparison results between the two inputs 215 suggest that a general MIR scale obtained from either emission-based or observation-based inputs can be used for OFP calculations in most VOC-limited areas, but not in mixed-limited or NOx-limited areas.

Comparison with ozone reactivity scales for VOCs in USA
MIR and MOR are the most appropriate for VOC-limited and mixed-limited conditions. Therefore, we focused on the comparison of these two scales between Guangzhou and a U.S. scenario (Figures 5 and 6). The MIR and MOR scales 220 comparison, which is referred to as MIR/Ethene-CA-MCM (Derwent et al., 2010). The MIR/Ethene scale was constructed for California conditions (a subset of the U.S. scenarios used by Carter (1994aCarter ( , 2010), but there was only a minor difference between the reactivity scales obtained from California scenarios and the average of all the U.S. scenarios using the SAPRC-07 mechanism ( Figure S3a), thereby indicating that the California scenarios can represent the U.S. reasonably well. With the same chemical mechanism (MCM), the MIR/Ethene scale resulted in higher consistency between China and California than 235 did the U.S. (ranks: R 2 = 0.93; values: R 2 = 0.90; Figure 6). The two calculations used different versions of MCM, namely v3.1 vs. v3.3.1, but the main differences concerned updates to mechanisms for some biogenic VOCs (Jenkin et al., 2015), whose reactivities were not used in the comparison. The five outliers shown in Figure 6 (n-nonane, n-decane, n-octane, benzene, and styrene) are compounds with both strong O3 formation and O3 inhibition characteristics and relatively low net reactivities that are highly variable because the relative importance of these opposing effects depends on environmental 240 conditions. However, the net reactivities are all relatively low, thereby resulting in the differences having much smaller effects on the rankings, as shown in Figure 6b.
The comparison illustrated that SAPRC and MCM diverged somewhat with respect to the understanding of atmospheric oxidation of a few compounds, although they shared a common representation of the MR of many other VOCs (Figures 5 and S3b) (Carter, 2010;Jenkin et al., 2003;Saunders et al., 2003). Furthermore, the IR scales showed a strong dependence 245 on the adopted chemical mechanisms, which indicates the need for accurate representation of explicit chemical mechanisms.
We designed a series of sensitivity tests to deduce other possible reasons for the IR discrepancy between China and the U.S., and also examined the effects of environmental conditions on the IR scales. As shown in Table 2, the effects of HONO levels on the IR scales were insignificant (within 7 %), whereas the VOC/NOx ratio and VOC composition were important factors. One quarter of the base VOC/NOx ratios in the Guangzhou scenarios tended to increase the overall IR values (by 19 % 250 and 26 % under the MIR and MOR scenarios, respectively). This factor was excluded as the possible reason for the discrepancy between Guangzhou and the U.S. owing to the lower VOC/NOx ratios in Guangzhou (0.99 vs. 6.60 in the U.S. average scenarios). The effects of the VOC composition change on the IR scales were double-edged. With the same total VOC mass, higher proportions of the reactive VOC class (such as alkenes) would increase the relative availability of VOCs We also examined the effects of other environmental conditions on the IR scales ( Table 2). The weakening of photolysis 270 rates by 50 % could significantly reduce the overall MIR (by -31 %; p < 0.01) and MOR values (by -13 %; p < 0.01), particularly the IR of aldehydes (such as propionaldehyde and glyoxal), the photolysis of which behaved as a dominant primary radical source and was more susceptible to photolysis intensity change. Another environmental condition considered was the effusion of VOCs from the urban scale to the regional scale. A regional scenario (the model integration time lasted for 3 days, whereas the other factors were kept unchanged; indicated as "3 days" in Table 2) was designed to extend the IR 275 evaluation to a larger spatial scale. The overall MIR and MOR values for the 116 VOCs changed by -5 % (p = 0.07) and -61 % (p < 0.01), respectively. Along the 3-day scale, the reactive VOC groups with a short lifetime were rapidly consumed, and their IR ranks dropped much faster (e.g., the median rank of alkenes dropped by -11 and -27 under the MIR and MOR scenarios, respectively). In contrast, the role of unreactive VOC groups became more important, which would build up and undergo extensive photochemical reactions along the 3-day scale (Stockwell et al., 2001). These two conditions were not 280 considered as possible reasons for the IR discrepancy between Guangzhou and the U.S. because both studies assumed a clear sky and set similar integration times (i.e., 10 hours).
We elucidated the effect of chemical mechanisms and major environmental conditions on the MIR and MOR scales. The results underline the need to explicitly define the representation of reaction pathways and products in chemical mechanisms.
Considering that the IR scales are more sensitive to environmental conditions with the decrease in NOx availability, it is 285 necessary to localize the O3 reactivity scales for VOCs using realistic scenarios under rapidly changing environments (especially under low NOx conditions).

Applications for Chinese cities
MIR-Carter 2010 is the most extensively used scale to quantify the OFP and identify the key reactive VOCs in Chinese cities.
To better address the aforementioned concerns regarding the IR application, two sets of model inputs were designed using 290 the megacity of Guangzhou to localize the IR scales under three specified NOx conditions. We revealed the strong dependence of IR scales on the adopted chemical mechanisms and demonstrated that both emission-based and observationbased inputs are suitable for the MIR calculation. Because O3 formation in most cities in China (and many other countries) is limited by VOCs, it is essential to clearly elucidate how to apply IR and OFP scales to deal with VOC control. Here, we provide recommendations on the application from three perspectives. 295 On IR localization: With a given chemical mechanism, the chemical environmental conditions would affect the MIR magnitudes but exert little effect on the MIR ranks of most VOCs, thereby demonstrating that a general MIR scale can be roughly used to identify the reactive VOCs in most VOC-limited areas. However, as the NOx availability decreased, the IR scale became more sensitive to the environmental conditions. It would be better to localize the MOR and EBIR scales over mixed-limited or NOx-limited areas. However, with a prescribed NOx availability, the IR scales were more sensitive to the 300 chemical mechanisms than to chemical environmental conditions, thereby implying that the establishment of an explicit and accurate chemical mechanism is more important than IR localization.

On the role of emission data and observational data for IR calculation:
The discrepancy between the IR scales obtained from the emission-based and observation-based inputs also obeyed the abovementioned "NOx availability" rule. Under high NOx conditions, the fairly good consistency between the MIR scales obtained from the emission-based and observation-305 based inputs suggested that both inputs can accurately estimate the actual environment and are suitable for the MIR calculation. However, the discrepancy between the MOR and EBIR magnitudes obtained from the two inputs was relatively large and cannot be overlooked, thereby underlining the need to use realistic scenarios for IR calculations, especially under low NOx conditions. On the OFP quantification: First, the IR scale used to quantify the OFP was determined by the relative availability of 310 VOCs and NOx. Because the MIR, MOR, and EBIR scales are the most appropriate for VOC-limited, mixed-limited, and NOx-limited areas, respectively, it is unreasonable to use the MIR scale to identify reactive VOCs or quantify the OFP in NOx-limited areas (generally rural or remote areas). Second, the observed VOC data were suitable for calculating the MIR scale, but caution should be taken when using them to quantify the OFP by multiplying the IR by observed concentrations.
For example, it is unreasonable to use the observed VOC data during periods with intense photochemistry to quantify the 315 OFP, which would underestimate the importance of reactive VOCs to O3 formation. For this purpose, we recommend using observed VOC data in the morning for OFP quantification. Furthermore, some VOCs (such as formaldehyde and acetaldehyde) have both primary and secondary sources. The secondary contributions should be removed for the OFP quantification, otherwise the contributions of secondary sources will be counted twice. Third, in comparison with the https://doi.org/10.5194/acp-2021-44 Preprint. Discussion started: 17 February 2021 c Author(s) 2021. CC BY 4.0 License. absolute OFP, the ROFP is a more reliable scale (Bowman and Seinfeld, 1995;Chang and Rudy, 1990;Japar et al., 1991;320 Russell et al., 1995). The ROFP is calculated as follows: where ROFPi represents the ROFP of VOCi; IRi and IRr represent the IRs of VOCi and the reference VOC, respectively; and [VOC]i and [VOC]r represent the observed concentrations (or emission quantity/emission rate) of VOCi and the reference VOC, respectively. Ethene is recommended as a reference species considering its well-defined chemical reaction pathways 325 and importance to O3 formation, and its use as the reference species in other studies (e.g., Derwent et al., 2010). The advantage of the ROFP is that it can minimize the effect of environmental variability In the future, more efforts are required to develop more comprehensive and realistic O3 reactivity scales for VOCs. The following directions are recommended: 1) model scenarios with realistic representations of physical factors, such as photolysis intensity, are needed to reduce the uncertainty caused by simple parameterizations; 2) emission inventories with 330 higher temporal and spatial resolutions and detailed VOC emission profiles are needed to reduce the uncertainty introduced by primary emissions; and 3) accurate representation of the chemical mechanisms within models is crucial. The chemical mechanism should represent the state of the science and appropriately represent all of the important VOCs present. In addition, because the mechanism significantly affects the IR results, it is important that the same chemical mechanism be used when assessing the effects of environmental conditions and localization on IR scales or OFP estimates in China or 335 elsewhere. To make comprehensive comparisons, a major work focusing on VOC reactivity scales obtained from the U.S. conditions vs. Chinese conditions and SAPRC vs. MCM is needed.

Conclusions
We designed two sets of model inputs (emission-based and observation-based) to localize the IR scales for VOCs in Guangzhou, southern China, and compared the localized IR results with those of extensively used U.S. IR scales. With a 340 prescribed NOx availability, the IR scales were more sensitive to chemical mechanisms (MCM vs. SAPRC) than to chemical environmental conditions. With a given chemical mechanism, the discrepancy between China and the U.S. was not large, thereby implying that the establishment of an accurate chemical mechanism is more important than IR localization. However, although there was a fairly good consistency between the localized MIR scales obtained from the emission-based and observation-based inputs, the IR discrepancy increased as the NOx availability decreased, thereby implying the necessity to 345 localize IR scales over mixed-limited or NOx-limited areas and the need for realistic scenarios in rapidly changing environments. The localized IR results in Guangzhou were taken as a case to clearly elucidate how to apply IR and OFP scales to deal with reactive VOC identification, which has great implications for VOC control in China and other countries suffering from serious O3 pollution.

Data availability 350
The emission-and observation-based inputs and model output used in the present study can be accessed from http://dx.doi.org/10.17632/2y752t39yn.1 (Zhang and Xue, 2021). The code for the MCM chemical box model can be downloaded from the F0AM website (https://github.com/AirChem/F0AM).

Author contributions
LK designed the research. CP and YW conducted the field campaigns. YZ conducted the chemical box modeling analyses 355 and wrote the paper. TC and JM helped in the creation of model. LK, WPLC, QZ, and WW helped in the interpretation of results and revised the original manuscript.

Competing interests
The authors declare that they have no conflict of interest.  181-193, 10.5194/acp-3-181-2003, 2003. 410 Jenkin, M. E., Young, J. C., and Rickard, A. R.: The MCM v3.3.1 degradation scheme for isoprene, Atmos. Chem. Phys., 15, 11433-11459, 10.5194/acp-15-11433-2015Phys., 15, 11433-11459, 10.5194/acp-15-11433- , 2015 Kurokawa, J., and Ohara, T.: Long-term historical trends in air pollutant emissions in Asia: Regional Emission inventory in       Table 2a. Dependence of emission-based MIR scales for major VOC groups on major environmental conditions. The base MIR scales were used as a benchmark (x-axis). Eight sensitivity scenarios: (2) 0.25*VOCs: both initial and emitted VOCs multiplied by 0.25, while other factors were kept unchanged, (3)-(6) X*VOC group: both initial and emitted VOC species contained in the target VOC group multiplied by X, and other VOC compositions increased or decreased to keep VOCs/NOx ratios constant, while other factors were kept unchanged, (7) HONO: both initial and emitted HONO were set to zero, and only the gas phase formation pathway (OH + NO = HONO) of HONO was included in the model, (8) 0.5*J: the photolysis rate was reduced to a half, while other factors were kept unchanged, (9) 3 days: the model integration time lasted for 3 days, while other factors were kept unchanged. Refer to