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• A wide range of transportation sectors including on-road mobile, non-road mobile, and oil storage and transportation sales were considered. • 3 km × 3 km grid-resolution emissions were allocated. • Future energy demand, air pollutants and greenhouse gas emissions were predicted based on LEAP model. • The emission peak and peak time under different scenarios were analyzed. Recently, the transportation sector in China has gradually become the main source of urban air pollution and primary driver of carbon emissions growth. Considering air pollutants and greenhouse gases come from the same emission sources, it is necessary to establish an updated high-resolution emission inventory for the transportation sector in Central China, the most polluted region in China. The inventory includes on-road mobile, non-road mobile, oil storage and transportation, and covers 9 types of air pollutants and 3 types of greenhouse gases. Based on the Long-range Energy Alternatives Planning System (LEAP) model, the emissions of pollutants were predicted for the period from 2020 to 2035 in different scenarios. Results showed that in 2020, emissions of SO 2 , NO x , CO, PM 10 , PM 2.5 , VOCs, NH 3 , BC, OC, CO 2 , CH 4 , and N 2 O in Henan Province were 27.5, 503.2, 878.6, 20.1, 17.4, 222.1, 21.5, 9.4, 2.9, 92,077.9, 6.0, and 10.4 kilotons, respectively. Energy demand and pollutant emissions in Henan Province are simulated under four scenarios (Baseline Scenario (BS), Pollution Abatement Scenario (PA), Green Transportation Scenario (GT), and Reinforcing Low Carbon Scenario (RLC)). The collaborative emission reduction effect is most significant in the RLC scenario, followed by the GT scenario. By 2035, under the RLC scenario, energy consumption and emissions of SO 2 , NO x , CO, PM 10 , PM 2.5 , VOCs, NH 3 , CO 2 , CH 4 , and N 2 O are projected to decrease by 72.0%, 30.0%, 55.6%, 56.0%, 38.6%, 39.7%, 51.5%, 66.1%, 65.5%, 55.4%, and 52.8%, respectively. This study provides fundamental data support for subsequent numerical simulations. [Display omitted] [ABSTRACT FROM AUTHOR]

Central Plains region of China, represented by Henan Province, is facing serious air pollution problems. Vehicular exhaust emissions had adverse impacts on the atmospheric environment. The first comprehensive and novel vehicle emission inventory for Henan Province using vehicle kilometers traveled, localized emission factors, and activity data at city-level was developed. Furthermore, 3 km × 3 km gridded emission and temporal variations were determined by using localized information. Results show that the total emissions of sulfur dioxide (SO 2), nitrogen oxides (NO x), carbon monoxide (CO), particular matter with aerodynamic diameter < 10 μm (PM 10), aerodynamic diameter < 2.5 μm (PM 2.5), volatile organic compounds (VOCs), VOCs-evaporation and ammonia in 2015 were 9.1, 533.4, 1190.7, 23.7, 21.6, 150.8, 31.5 and 10.4 Gg, respectively, and the emission intensities of the above pollutants were 0.05, 2.7, 6.0, 0.1, 0.1, 0.8, 0.2 and 0.05 g/km, respectively. Vehicles meeting the Primary China 1, China 3 and China 4 contributed 89.1%, 82.7%, 75.3%, 75.5%, 75.5%, 68.2%, 68.4% and 82.3% for SO 2 , NO x , CO, PM 10 , PM 2.5 , VOCs, VOCs-evaporation and ammonia emissions, respectively. Zhengzhou, Zhoukou, Nanyang, Luoyang, Shangqiu and Xinyang showed relatively higher emissions and contributed more than 50% of each pollutant. The spatial distribution indicated obvious characteristics of the road network, and high-level emission was concentrated in the downtown areas. Additionally, the ozone formation potential (OFP) based on the estimated speciated VOC emissions was 569.6 Gg in Henan Province. Aliphatic and aromatic hydrocarbons were the main species of VOCs, whereas olefins contributed the largest proportion of OFP, with 42.2%. Unlabelled Image [ABSTRACT FROM AUTHOR]

The Central Plain City Cluster represented by Zhengzhou is one of the most haze-polluted regions, especially for the heating period. As critical precursors of Secondary Organic Aerosol (SOA) and Ozone, the ambient Volatile Organic Compounds (VOCs) emitted from anthropogenic activities have aroused widespread concern. This study provided a revealing insight on the concentration level, chemical composition, multiple source apportionments (SAs), SOA formation potential (SOAp) and exposed health risk of VOCs before and during heating periods at a megacity site. The average concentrations of TVOCs during clear days before heating, pollution days before heating, clear days during heating, and pollution days during heating were 37.81 ± 17.21, 54.48 ± 17.83, 39.27 ± 16.38 and 63.98 ± 22.42 ppbv, respectively. Compared with the before heating period, the concentration of TVOCs increased by 3.9% and 17.4% on clear days and polluted days during the heating period, respectively. Among them, alkanes were the most abundant species of VOCs, followed by halocarbons and alkenes. The multiply SAs methods were applied to identify potential sources, and the contributions of source structures were reasonable and credible by comparing PMF and emission inventory. Vehicular exhaust was the largest contributor during the non-heating period (33.2%), while for the heating period, combustion source contributed the most to VOCs emission (24.2%). In terms of the contribution to SOAp formation, aromatics were the most abundant VOCs species, and combustion (29.4%) was the major source, followed by solvent usage (26.5%) and vehicular exhaust (24.6%). The non-carcinogenic risks of VOCs sources were significantly lower than the acceptable safety threshold, while all the specific VOCs sources posed carcinogenic risks except for biogenic emission. The ways of analysis and assessment in this study can highlight the need for more effective control strategies related to VOCs anthropogenic activities during the heating period in megacities of Central China. [Display omitted] • A systematic observation of ambient VOCs during heating and non-heating periods was carried out in Central China. • The contribution of combustion increased by 7.0% during heating period compared with non-heating period. • Aromatics were dominant triggering factors and dominate 97.2% of the total SOAp during heating period. • Combustion occupied 41.1% to non-carcinogenic risks, while solvent usage contributed 30.7% to carcinogenic risks. [ABSTRACT FROM AUTHOR]

Semi-volatile organic compounds (SVOCs) and intermediate volatile organic compounds (IVOCs) are key precursors for the formation of SOA, which is an important component of PM 2.5 , a representative pollutant of complex atmospheric pollution. It is important to understand the emissions of SVOCs and IVOCs. Based on the collected anthropogenic activity data and ratio of SVOCs and IVOCs to primary organic aerosols (POA), in this study, a newly 2017-based high-resolution S/IVOCs emission inventory in Central China represented by Henan Province was developed. The total emissions of SVOCs and IVOCs were 101.3 kt and 447.9 kt, respectively. SVOCs emission was mainly originated from residential combustion and industrial process, with the contribution of 44.4% and 20.8%, respectively. Industrial process and on-road mobile were the main contributors to IVOCs emission, accounting for 56.1% and 14.5% of total emission, respectively. This study further analyzes and compares S/IVOCs emissions of different cities based on the urban population. S/IVOCs emissions in 10 megacities, 5 large cities, and 3 small cities account for 74.9%, 16.4%, and 8.7% of total emissions, respectively. High SVOCs emissions were mainly distributed in eastern regions such as Shangqiu and Zhoukou which are agricultural cities, and that was in cities with developed industries and transportation, such as Zhengzhou and Jiaozuo, as for IVOCs. The uncertainties of SVOCs and IVOCs emissions established in this study are −60.7% - 62.2% and − 122.1% - 119.1%, respectively. Industrial process and on-road mobile are the emission sources with higher uncertainty of SVOCs and IVOCs emissions, respectively. It hopes to better understand the emission characteristics of S/IVOCs and provide more detailed basic data for air quality modelling simulation and various emission control policies. [Display omitted] • A first high-resolution SVOCs and IVOCs emission inventory in Central China was developed. • Residential combustion occupied44% of SVOCs emission, while IVOCs emission mainly from industrial process (56%). • SVOCs and IVOCs emission characteristics of megacities, large cities, and small cities were analyzed. • Monte Carlo simulation was used to evaluate the uncertainties. [ABSTRACT FROM AUTHOR]

Ammonia (NH 3) volatilization is one of the main pathways of nitrogen loss from cropland, resulting not only in economic losses, but also environmental and human health impacts. The magnitude and timing of NH 3 emissions from cropland fertilizer application highly depends on agricultural practices, climate and soil factors, which previous studies have typically only considered at coarse spatio-temporal resolution. In this paper, we describe a first highly detailed empirical regression model for ammonia (ERMA) emissions based on 1443 field observations across China. This model is applied at county level by integrating data with unprecedented high spatio-temporal resolution of agricultural practices and climate and soil factors. Results showed that total NH 3 emissions from cropland fertilizer application amount to 4.3 Tg NH 3 yr−1 in 2017 with an overall NH 3 emission factor of 12%. Agricultural production for vegetables, maize and rice are the three largest emitters. Compared to previous studies, more emission hotspots were found in South China and temporally, emission peaks are estimated to occur three months earlier in the year, while the total amount of emissions is estimated to be close to that calculated by previous studies. A second emission peak is identified in October, most likely related to the fertilization of the second crop in autumn. Incorporating these new findings on NH 3 emission patterns will enable a better parametrization of models and hence improve the modelling of air quality and subsequent impacts on ecosystems through reactive N deposition. [Display omitted] • A empirical model of NH 3 emissions from croplands was established. • Two emission peaks are found in April and October following the fertilization. • Total emission was estimated at 4.3 Tg NH 3 yr−1 in 2017 with an emission factor of 12%. • More emission hotspots were found in South China due to warming climate. The highly spatio-temporal resolution NH 3 emission inventory from cropland fertilization was developed by an empirical regression model in 2853 counties of China. [ABSTRACT FROM AUTHOR]

With the rapid development of the social economy in China, numerous Chinese cities are facing high levels of particulate matter (PM) pollution problems. In this study, high-resolution ZY-3 images and GIS techniques were used to establish the emission inventory of total suspended particle (TSP), particulate matter 10 (PM10) and particulate matter 2.5 (PM2.5) from fugitive dust sources in May 2016, and a spatial grid of 3 km × 3 km resolution was established to demonstrate the spatial distribution of PM emission. Results showed that the total emissions of TSP, PM10 and PM2.5 in Zhengzhou city were 237.5 kt·a−1, 103.7 kt·a−1 and 22.4 kt·a−1, respectively. Construction dust source was the main fugitive dust emission source in Zhengzhou city—the TSP, PM10 and PM2.5 emission of which account for 76.42%, 89.68% and 88.39%, respectively, of the total emission, followed by road dust source and soil dust source. PM emission was higher in Zhongyuan, Huiji, Jinshui and Zhengdong New District, while Zhongmou, Xingyang, Dengfeng and other remote areas had low PM emissions. Compared to other Chinese cities or regions, the PM emission from the construction dust source was at a high level in Zhengzhou city, while the PM emissions from the soil dust source and road dust source were at moderate levels. [ABSTRACT FROM AUTHOR]

The Central China represented by Henan Province is one of the most haze-polluted regions in China with high levels of black carbon (BC) and organic carbon (OC) emissions. In this study, a 2016-based BC and OC emission inventory of Henan Province was developed based on detailed activity data and latest emission factors from different sources involving particulate matter. The total annual emissions of BC and OC were estimated to be 117.6 kt and 162.8 kt, respectively. Industrial process (44.2%) and industrial combustion (17.0%) were the top two contributors for BC emission, whereas OC emission was mainly from biomass burning (36.8%). Typical industrial cities were the major contributors to BC emission, by contrast, relatively higher OC emission was concentrated on agricultural cities in the southeast of Henan Province. The OC/BC ratios of industrial cities were generally lower than those of southeastern agricultural cities. The monthly variations presented that the highest BC and OC emissions were concentrated in January and June, respectively. Overall, in this study, the quantitative uncertainty ranges on the 95% confidence interval were approximately −30%–47% for BC and −38%–65% for OC. The emission inventory was also verified by qualitative comparison with other studies and indirect evaluation of OC pri /EC ratios, and the result was within a reasonable range. The ways of discussion and evaluation in this study can provide reference for other regions. Image 1 • City-based BC and OC emission inventory covering particle-related sources was developed. • Industrial process occupied more than 40% of BC emission, while biomass burning contributed to significant OC emission. • The OC/BC ratios of industrial cities were lower than those of agricultural cities. • The quantitative uncertainty ranges were approximately −30%–47% for BC and −38%–65% for OC. [ABSTRACT FROM AUTHOR]

• A high-resolution refined speciated VOCs emission inventory of Central China was established. • 168 subsectors speciation of VOCs emission were established, alkanes (30.5 %) and aromatic hydrocarbons (28.8 %) were the main groups while toluene (6.6 %) was the highest specie. • Based on VOCs online data, tracer ratio method by trace gas CO and PMF receptor model were used to evaluate the species-specific emission and source structure. • Remote sensing satellite inversion of HCHO emission was used to indirectly verify the VOCs spatial distribution. Improving the accuracy of anthropogenic volatile organic compounds (VOCs) emission inventory is crucial for reducing atmospheric pollution and formulating control policy of air pollution. In this study, an anthropogenic speciated VOCs emission inventory was established for Central China represented by Henan Province at a 3 km × 3 km spatial resolution based on the emission factor method. The 2019 VOCs emission in Henan Province was 1003.5 Gg, while industrial process source (33.7%) was the highest emission source, Zhengzhou (17.9%) was the city with highest emission and April and August were the months with the more emissions. High VOCs emission regions were concentrated in downtown areas and industrial parks. Alkanes and aromatic hydrocarbons were the main VOCs contribution groups. The species composition, source contribution and spatial distribution were verified and evaluated through tracer ratio method (TR), Positive Matrix Factorization Model (PMF) and remote sensing inversion (RSI). Results show that both the emission results by emission inventory (EI) (15.7 Gg) and by TR method (13.6 Gg) and source contribution by EI and PMF are familiar. The spatial distribution of HCHO primary emission based on RSI is basically consistent with that of HCHO emission based on EI with a R -value of 0.73. The verification results show that the VOCs emission inventory and speciated emission inventory established in this study are relatively reliable. [Display omitted] [ABSTRACT FROM AUTHOR]

Organic aerosol (OA) is the largest and most complicated component of aerosols that has significant impacts on human health and global climate. However, current models cannot accurately predict the concentrations and sources of primary and secondary OA due to the oversimplification of traditional organic emission inventories. Traditional emission inventories do not consider important precursors of secondary organic aerosols (SOA), such as semi-volatile and intermediate-volatility organic compounds (SVOCs and IVOCs). To improve the accuracy of OA prediction and source identification, it is essential to refine precursor emissions. In this study, a full-volatility organic compounds emission inventory was established for the Central China, with Henan Province as a representative in 2020. The anthropogenic emissions of ultralow volatility organic compounds (xLVOCs), SVOCs, IVOCs, and VOCs were 53.9 kt, 55.3 kt, 182.1 kt, and 586.3 kt, respectively, effectively filling the gap of 181.3 kt in traditional organic compound emission inventory. Residential biomass burning was identified as the primary contribution source for xLVOCs and SVOCs, accounting for 70.1% and 42.2%, respectively. Industrial process was the main contributor for IVOCs and VOCs, accounting for 31.7% and 44.0% of their emissions, respectively. Meanwhile, the emission of volatile organic compound from different sources showed an increasing trend as volatility increased. The gas-phase emission was 212.1 kt, primarily from industrial process (33.9% contribution), while the particle-phase emission was 79.2 kt, mainly from domestic biomass combustion (65.0% contribution). xLVOCs and SVOCs emissions were mainly concentrated in cities with agricultural activities, such as Zhoukou, while IVOCs and VOCs were concentrated in highly industrialized and urbanized areas, such as Zhengzhou. It is hoped that the incompleteness of emission factors (EFs) for full-volatility organic compounds, which mainly contributes to the uncertainty of this study's results, can be further improved to better understand source contributions. [Display omitted] • The full-volatility framework fills a gap of 181.3 kt xL/S/IVOCs compared with the traditional framework. • Major xLVOCs and SVOCs emissions were from residential biomass burning, while industrial process contributed more IVOCs. • Emission characteristics for 9 different volatile organic compounds (log C* bins ranging from ≤ − 2 to 6) were discussed. • xLVOCs and SVOCs emissions were concentrated in agricultural areas, while IVOCs and VOCs were in urbanized areas. [ABSTRACT FROM AUTHOR]

A high – resolution emission inventory of primary air pollutants of 18 cities in Henan region, as the representative of central plains of China, was developed based on the combination of bottom – up and top-down methods. It was found that the emissions of sulfur dioxide (SO 2), nitrogen oxides (NO x), carbon monoxide (CO), particulate matter with an aerodynamic diameter of 10 mm or less (PM 10), particulate matter with an aerodynamic diameter of 2.5 mm or less (PM 2.5), Volatile Organic Compounds (VOCs) and ammonia (NH 3) in 2016 were 780.4, 1682.9, 7152.8, 1440.3, 757.2, 1110.7, and 982.0 Gg, respectively. The emissions of the three major PM 2.5 species, namely, Organic carbon (OC), Elemental carbon (EC), and sulfate (S O 4 2 − ), were 161.2, 83.1, and 64.6 Gg, respectively. Stationary combustion was the largest contributor to SO 2 , NO x , CO, and PM 2.5 emissions with 71.6%, 49.0%, 34.1%, and 24.7% contributions, respectively. Dust was the dominant source of PM 10 emissions (42.4%), whereas industrial process was the largest contributor to VOCs emission (34.8%). Agricultural source contributed 87.7% of NH 3 emission. The emissions were mainly distributed over the northwest and central part of Henan, and cities of Anyang, Zhengzhou, Luoyang, Pingdingshan, and Jiaozuo were the major contributors. Large NH 3 emissions occurred during May to September, and high emissions of other pollutants were found from October to January. According to the Gini coefficients of per capital Gross Domestic Product (GDP) distribution among multiple air pollutants, the SO 2 and NH 3 emissions had high regional disparity, and the cities of Anyang and Zhengzhou had a high economic – environment inequity. Furthermore, this results were evaluated by comparing with other studies and the trend of spatiotemporal observed ambient concentration, which proves that the results are reliable. This work may benefit the government to further understand current local emission characteristics and formulation of targeted air pollution control measures. Image 1 • The emission inventory shows that the main contribution of different pollutants and different region differed significantly. • Spatiotemporal variations and comparison of monitoring data were investigated. • The major speciation of PM 2.5 emissions were organic carbon (OC), elemental carbon (EC), and sulfate (S O 4 2 − ). • Regional disparity and inequity of emission at city level were discussed by using Lorenz curve and Gini coefficient. [ABSTRACT FROM AUTHOR]

In recent years, air pollution has been a serious problem in China, not only in the city but also in the countryside. Moreover, the statistics data of coal and solid biomass consumption for rural households are significantly underestimated, which has a negative impact on the air pollution control. In this study, Henan province, an agricultural province in China, is taken as a case to analyze the county-level emission characteristics and emission reduction potential of rural household combustion. Firstly, activity data at county-level are obtained through regression based on partial activity data from field survey in 2016, and a high-resolution emission inventory of multi-type air pollutants from rural residential combustion is established. Then, twelve abatement technologies are selected to replace coal and solid biomass used in heating and cooking. A new optimization model is established based on the rural household burden ratio to discuss the optimal emission reduction schemes at county-level under five substitution scenarios. The results show that the total emissions of SO 2 , NOx, PM 2.5 , PM 10 , CO, NH 3 and VOCs from rural residential combustion in Henan province are estimated at about 108.6, 30.9, 72.7, 113.5, 1141.9, 19.6 and 110.0 kt, respectively. The inventory results of different counties vary greatly, with PM 2.5 emissions ranging from 7.9 t to 1550.3 t. Counties with large emissions have more agricultural activities. Among the abatement technologies, air source heat pump (ASHP) and palisade structure (PS) are more suitable for promotion in rural areas. The PM 2.5 emissions in the five substitution scenarios are 99.0%, 98.8%, 99.1%, 98.6% and 98.8% lower than BAU-scenario, and S1-scenario is more conducive to rural emission reduction with considering the costs. It is suggested that the government should pay more attention to the air pollution caused by rural household combustion and improve the existing energy statistics system, especially for solid biomass. Abatement technologies suitable for heating and cooking in rural areas should be actively promoted, such as air source heat pump. Image 1 • Fuel consumption at county-level is obtained through regression models based on energy data from field surveys. • A high-resolution emission inventory of multi-type air pollutants from rural residential combustion is established. • A new optimization model is developed to obtain county-level optimal abatement schemes. • A new approach of air pollutants emission reduction is provided for rural areas. • The reduction ratio is reached 98.8% under the optimal reduction scenario. [ABSTRACT FROM AUTHOR]

Aiming to provide basic data support for the improvement of air quality in the study region, this study established the emission inventory and speciated emission inventory of PM 2.5 and VOCs in Henan Province, and further estimated the ozone formation potential (OFP) and secondary organic aerosols formation potential (SOAFP) of VOCs to identify key species, priority sources and typical cities. The 2017-based emissions of PM 2.5 and VOCs were 598 and 1079 kt, respectively. Industrial process, fugitive dust and biomass burning were the three major contributors to PM 2.5 , with a combined contribution of 79%, while industrial process, on-road mobile, solvent utilization and biomass burning were the four major contributors to VOCs emissions, with a combined contribution of 90%. Other unidentified species had the highest emissions, followed by carbonaceous components and inorganic elements and water-soluble ions. The total amount of OFP and SOAFP were 3482 and 81 kt. The species categories of VOCs that contributed large fractions to the emissions were alkanes, aromatic hydrocarbons and oxygenated VOCs, to the OFP were aromatic hydrocarbons, olefins, and oxygenated VOCs, and to the SOAFP were aromatic hydrocarbons and alkanes. Considering OFP and SOAFP together, industrial process, solvent utilization, on-road mobile and biomass burning are the key emission sources to control. The overall spatial distribution showed that PM 2.5 and VOCs emissions were relatively low in the southwest and southeast of Henan province, while emissions were high in densely populated, industrial, agricultural and transportation developed areas, and the spatial distribution characteristics of OFP and SOAFP were similar to those of VOCs emissions. [Display omitted] • A new 2017-based comprehensive emission inventory of PM 2.5 and VOCs in Central China was developed. • 47 subsectors speciation of PM 2.5 emissions and 168 subsectors speciation of VOCs emission were established. • OFP and SOAFP were estimated based on VOCs speciated emissions. • PM 2.5 and VOCs were concentrated in densely populated, industrial, agricultural and transportation developed areas. [ABSTRACT FROM AUTHOR]

Abstract: A highly resolved temporal and spatial Pearl River Delta (PRD) regional emission inventory for the year 2006 was developed with the use of best available domestic emission factors and activity data. The inventory covers major emission sources in the region and a bottom–up approach was adopted to compile the inventory for those sources where possible. The results show that the estimates for SO2, NOx, CO, PM10, PM2.5 and VOC emissions in the PRD region for the year 2006 are 711.4 kt, 891.9 kt, 3840.6 kt, 418.4 kt, 204.6 kt, and 1180.1 kt, respectively. About 91.4% of SO2 emissions were from power plant and industrial sources, and 87.2% of NOx emissions were from power plant and mobile sources. The industrial, mobile and power plant sources are major contributors to PM10 and PM2.5 emissions, accounting for 97.7% of the total PM10 and 97.2% of PM2.5 emissions, respectively. Mobile, biogenic and VOC product-related sources are responsible for 90.5% of the total VOC emissions. The emissions are spatially allocated onto grid cells with a resolution of 3 km × 3 km, showing that anthropogenic air pollutant emissions are mainly distributed over PRD central-southern city cluster areas. The preliminary temporal profiles were established for the power plant, industrial and on-road mobile sources. There is relatively low uncertainty in SO2 emission estimates with a range of −16% to +21% from power plant sources, medium to high uncertainty for the NOx emissions, and high uncertainties in the VOC, PM2.5, PM10 and CO emissions. [Copyright &y& Elsevier]

Intensive temporary air pollution control measures were implemented in Zhengzhou (ZZ), a megacity in central China, and six neighboring cities during the 2019 National Games of Ethnic Minorities. The Community Multiscale Air Quality (CMAQ) model and a high-resolution local emission inventory were applied to evaluate the control measures. Reductions of ~35–60% of primary PM (PPM), 45–65% of VOCs, ~5% of NH 3 , 35–45% of NO x , and 30–70% of SO 2 emissions in the central area (i.e., ZZ) and collaborative cities (i.e., the six neighboring cities) lead to significant reductions of daily PM 2.5 by 25–45% in ZZ. Hourly concentrations of PM 2.5 are reduced by as much as 100 μg m−3. Most of the reduction in PM 2.5 is due to primary PM, and NO 3 −, SO 4 2−, and NH 4 + ion concentrations only decrease by 5–6%. Emission reductions in the collaborative cities contribute to 10–30% of the decrease in PM 2.5 and PM 10 in ZZ. Concentrations of daily maximum 8-hr (DM8H) O 3 increase by 2–5% on high O 3 days. Isopleth analysis suggests that the local molar reductions ratio of NO x to VOC needs to be < 0.5 to avoid the increases. More stable meteorology conditions make emission controls in ZZ more effective for PM 2.5 and PM 10 but lead to higher increases in DM8H O 3. These results suggest that control of PPM emissions in ZZ is the most effective in reducing PM 2.5 and PM 10. However, reductions of precursor gaseous in ZZ and the six neighboring cities alone are not effective in reducing the secondary PM components and most likely lead to increases in DM8H O 3. Image 1 • First evaluation of temporary air pollution controls in a megacity in central China. • Most of the reduction in PM 2.5 is mostly due to local primary PM reductions. • Reduction of SO 2 and NO x changes secondary inorganic aerosol (SIA) slightly. • ΔNOx/ΔVOC needs to be < 0.5 to reduce O 3 if only local emissions are controlled. • Coordinated and broader regional controls are needed to further reduce SIA and O 3. [ABSTRACT FROM AUTHOR]