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Volatile organic compounds (VOCs) are the main precursors of pollution from ground ozone (O3) and PM2.5, which cause the deterioration of urban air quality. The emissions of VOCs from industrialized areas are significant and their characteristics are complex, which nowadays contribute significantly to the challenges of investigating the emission inventory. Taking a typical industrialized area in Tianjin as a case study, the anthropogenic VOCs emission inventory for 2020 was established in this study by using the activity data from a large-scale survey and the latest emission factors. The impact of VOCs on the environment was analyzed from the perspective of the combined control of PM2.5 and O3. The results showed that the total emission of VOCs in 2020 was about 1.68 Gg, mainly from industrial processes and mobile sources, which accounted for 38.4% and 36.5% of the total emissions, respectively. The top 10 emitted VOCs were toluene, acetone, ethylbenzene, m/p-xylene, i-pentane, n-hexane, formaldehyde, benzene, ethyl acetate and ethylene. The dominant species of O3 formation potential (OFP) were almost all aromatic hydrocarbons and alkenes, with m/p-xylene contributing the most to the OFP emissions (8.90%). The top 10 secondary organic aerosols formation potential (SOAP) emission species were aromatic hydrocarbons and long-chain alkanes, and the largest emission came from toluene (39.9%). An analysis of an ADMS diffusion model showed that VOCs emitted from traffic-heavy main roads and industrialized central areas had the greatest impact on the air quality in the surrounding areas. The VOCs concentration was higher in winter due to unfavorable meteorological conditions. Our research updated the VOC inventory of industrialized areas and evaluated VOCs species reactivity and their impact on ambient air quality. [ABSTRACT FROM AUTHOR]

The unprecedented lockdown of human activities during the COVID-19 pandemic has significantly influenced social life in China. However, understanding the impact of this unique event on the emissions of different species is still insufficient, prohibiting the proper assessment of the environmental impacts of COVID-19 restrictions. Here we developed a multi-air-pollutant inversion system to simultaneously estimate the emissions of NO x , SO 2 , CO, PM 2.5 and PM 10 in China during COVID-19 restrictions with high temporal (daily) and horizontal (15 km) resolutions. Subsequently, contributions of emission changes versus meteorological variations during the COVID-19 lockdown were separated and quantified. The results demonstrated that the inversion system effectively reproduced the actual emission variations in multi-air pollutants in China during different periods of COVID-19 lockdown, which indicate that the lockdown is largely a nationwide road traffic control measure with NO x emissions decreasing substantially by ∼40 %. However, emissions of other air pollutants were found to only decrease by ∼10% because power generation and heavy industrial processes were not halted during lockdown, and residential activities may actually have increased due to the stay-at-home orders. Consequently, although obvious reductions of PM 2.5 concentrations occurred over the North China Plain (NCP) during the lockdown period, the emission change only accounted for 8.6 % of PM 2.5 reductions and even led to substantial increases in O 3. The meteorological variation instead dominated the changes in PM 2.5 concentrations over the NCP, which contributed 90 % of the PM 2.5 reductions over most parts of the NCP region. Meanwhile, our results suggest that the local stagnant meteorological conditions, together with inefficient reductions of PM 2.5 emissions, were the main drivers of the unexpected PM 2.5 pollution in Beijing during the lockdown period. These results highlighted that traffic control as a separate pollution control measure has limited effects on the coordinated control of O 3 and PM 2.5 concentrations under current complex air pollution conditions in China. More comprehensive and balanced regulations for multiple precursors from different sectors are required to address O 3 and PM 2.5 pollution in China. [ABSTRACT FROM AUTHOR]

A series of carbon dioxide (CO2) emission inventories with high spatial resolutions covering China have been developed in the last decade, making it possible to assess not only the anthropogenic emissions of large administrational units (countries; provinces) but also those of small administrational units (cities; counties). In this study, we investigate three open-source gridded CO2 emission inventories (EDGAR; MEIC; PKU-CO2) and two statistical data-based inventories (CHRED; CEADs) covering the period of 2000–2020 for 16 prefecture-level cities in Shandong province in order to quantify the cross-inventory uncertainty and to discuss potential reasons for it. Despite ±20% differences in aggregated provincial emissions, all inventories agree that the emissions from Shandong increased by ~10% per year before 2012 and that the increasing trend slowed down after 2012, with a quasi-stationary industrial emission proportion being observed during 2008–2014. The cross-inventory discrepancies increased remarkably when downscaled to the city level. The relative differences between two individual inventories for half of the cities exceeded 100%. Despite close estimations of aggregated provincial emissions, the MEIC provides relatively high estimates for cities with complex and dynamic industrial systems, while the CHRED tends to provide high estimates for heavily industrial cities. The CHRED and MEIC show reasonable agreement regarding the evolution of city-level emissions and the city-level industrial emission ratios over 2005–2020. The PKU-CO2 and EDGAR failed to capture the emissions and their structural changes at the city level, which is related to their point-source database stopping updates after 2012. Our results suggest that cross-inventory differences for city-level emissions exist not only in their aggregated emissions but also in their changes over time. [ABSTRACT FROM AUTHOR]

The Beijing Daxing International Airport is a newly opened airport, and a comprehensive emission inventory of air pollution sources has not yet been established. The lack of basic inventory data will cause difficulties in controlling the air quality (AQ) in and around the airport. Based on actual flight data, we established a comprehensive emission inventory (carbon monoxide (CO), nitrogen oxides (NO X), hydrocarbons (HC), sulfur dioxide (SO 2), particulate matter (PM), and carbon dioxide (CO 2)) at Beijing Daxing International Airport. Furthermore, we evaluated the impact of airport emissions on the AQ of the surrounding areas using the ADMS-Airport model. The results showed that Beijing Daxing International Airport emitted 1.15 E+03, 1.76 E+03, 1.38 E+02, 1.16 E+02, 3.53 E+01, and 3.75 E+05 t of CO, NO X , HC, SO 2 , PM, and CO 2 , respectively, from July 1, 2020, to June 30, 2021. Engine exhaust emissions (landing and takeoff [LTO] cycles) dominated all airport pollutant emissions except for PM from the power plant. Among all aircraft types, B738 emitted the most CO 2 , as it accounted for almost half of all the flights. The AQ simulations showed that the air pollutant diffusion range was concentrated within 15 km of the airport and the surrounding areas. The contribution of airport emissions to NO X concentrations was most apparent under the most unfavorable meteorological conditions. Based on the average pollutant concentration during the study period, the Gu'an Li Hu Primary School station was the most affected. In particular, NO X concentrations at this station were approximately 50% higher in winter than in summer. Currently, the airport's contribution to pollution in the surrounding areas is insignificant. However, with the continuous increase in the number of flights at the airport, its impact on the AQ in the surrounding areas must be addressed in the future. [Display omitted] • An emission inventory including all airport-related sources was established. • The airport emissions made the most obvious contribution to NO X concentration. • Airport contributed more pollutant concentrations in clean weather than in polluted day. • The airport emissions have the most significant impact on the surrounding 5 km area. [ABSTRACT FROM AUTHOR]

China's fossil-fuel CO2 (FFCO2) emissions accounted for approximately 28 % of the global total FFCO2 in 2016. An accurate estimate of China's FFCO2 emissions is a prerequisite for global and regional carbon budget analyses and the monitoring of carbon emission reduction efforts. However, significant uncertainties and discrepancies exist in estimations of China's FFCO2 emissions due to a lack of detailed traceable emission factors (EFs) and multiple statistical data sources. Here, we evaluated China's FFCO2 emissions from nine published global and regional emission datasets. These datasets show that the total emissions increased from 3.4 (3.0–3.7) in 2000 to 9.8 (9.2–10.4) Gt CO2 yr-1 in 2016. The variations in these estimates were largely due to the different EF (0.491–0.746 t C per t of coal) and activity data. The large-scale patterns of gridded emissions showed a reasonable agreement, with high emissions being concentrated in major city clusters, and the standard deviation mostly ranged from 10 % to 40 % at the provincial level. However, patterns beyond the provincial scale varied significantly, with the top 5 % of the grid level accounting for 50 %–90 % of total emissions in these datasets. Our findings highlight the significance of using locally measured EF for Chinese coal. To reduce uncertainty, we recommend using physical CO2 measurements and use these values for dataset validation, key input data sharing (e.g., point sources), and finer-resolution validations at various levels. [ABSTRACT FROM AUTHOR]

Ships are considered important contributors to air pollution and have seriously health impact globally. Although many researchers have carried out studies on emission factors (EFs) in recent years, studies covering various types of ships are rare and the chemical characteristics of particulate matter (PM) emitted by them are unclear. Due to the diversity of different national fleets, the current emission inventory in China established by citing foreign EFs will lead to inaccurate calculation results and generate large uncertainty. In this study, the EFs for ocean-going, harbour, offshore and inland vessels were measured by the portable emission measurement system (PEMS). The specific compositions of PM were analyzed, including carbonaceous components, water-soluble ions (WSI), elements, and polycyclic aromatic hydrocarbons (PAHs). Combined with localized EFs, the ship emission inventory of Qingdao Port was established based on Automatic Identification System (AIS) data. The results show nitrogen oxide (NOx) is the primary pollutant discharged by all ships, followed by sulfur dioxide (SO 2). The emissions of SO 2 and PM from inland and offshore vessels fueled with high sulfur fuel (HSF) are significantly higher than other ships. Carbonaceous components accounted for 43.4%–53.9% of the total mass of PM, WSI accounted for 9.8%–14.3%, and elements accounted for 16.5%–28.6%. Although the use of low sulfur fuel (LSF) has reduced the emission of V and Ni from ships, it could still be treated as tracer elements of ship emissions. The annual emissions of SO 2 , NO X , PM 2.5 , THC and CO from ships in Qingdao port in 2020 were 9728.5, 38503.9, 1424.9, 1331.5 and 2440.4 tons, respectively. The ship emission inventory established based on EPA-recommended EFs resulted in underestimating approximately 16.8% of ship pollutants, especially for SO 2 and PM. Ocean-going ships and offshore vessels are major emitters in the study waters. This study is hoped to provide a valuable reference for the further regulation and policy formulation of ship emissions in China. [Display omitted] • On-board measurements were carried out on typical ships by PEMS. • EFs for gas pollutants and particle components of various vessel types are provided. • Fuel types have a significant impact on the particulate fraction of ships. • It reveals the current emissions from Chinese ships may be underestimated. • Approximately 16.8% of ship emissions in Qingdao Port are undervalued in 2020. [ABSTRACT FROM AUTHOR]

As the largest container port in northern China, the prosperous maritime trade has not only promoted the economic development of Qingdao port but also brought serious pollution to the air quality. Ship emissions have caused a significant influence on public health. The establishment of the Domestic Emission Control Area (DECA) is a key policy to reduce ship emissions in recent years. It has been implemented in Qingdao Port from January 1, 2019. To evaluate the environmental benefits of the DECA policy, this study established a bottom-up ship emission inventory in 2020 for Qingdao based on Automatic Identification System (AIS) data. Changes in ship emissions and their impact on air quality in Qingdao are evaluated for the same study area before and after the implementation of DECA policy. The total emissions in all study area for SO 2 , NO X , PM 10 , PM 2.5 , HC and CO in 2020 are 8.16 × 103, 3.31 × 104, 1.25 × 103, 1.15 × 103, 1.18 × 103, 2.15 × 103 tons (t), respectively, reductions of 67.9%, 15.4%, 63.2%, 62.9%, 27.2% and 23.2% compared with 2016, and reductions of 73.42%, 29.97%, 69.54%, 69.26%, 39.71%, 36.44% compared with the scenario without DECA in 2020. The inter-month change and spatial distribution of ship emissions are similar in both years. Shinan District, Shibei District and Huangdao District are most affected by ship emissions, with the largest influence in summer. The ship's contribution to air pollution in each area had been significantly reduced, especially for SO 2 and PM after DECA policy. However, the emission reduction of other pollutants is limited, so it is necessary to further enhance the DECA policy. Our research aims to conduct a comprehensive assessment of the environmental benefits for DECA policy, and provide support for the further improvement of the subsequent measures. [Display omitted] • High spatiotemporal resolution ship emission inventory for Qingdao in 2020 is updated. • Total ship emission in Qingdao during 2020 was 46,965.7 tons, 37.7% lower than 2016. • More than 50% of ship pollutants occur within the baseline of territorial sea. • Ship emissions in summer have the most significant impact on urban air quality. • DECA policy has reduced ship emission of SO 2 by 73.4% and PM 2.5 by 69.5%. [ABSTRACT FROM AUTHOR]

Emission control strategies are among the most effective ways to improve air quality, but the emissions reduced were usually estimated with high uncertainty. Here we present a modified ensemble Kalman filter (EnKF) to reduce the uncertainties of carbon monoxide (CO) and nitrogen oxides (NOx) emissions at one week and 5 km resolution by assimilating surface CO and nitrogen dioxide (NO 2) observations. By decoupling analysis steps from ensemble simulations, the modified EnKF avoids filter divergence and enables reuse of costly ensemble simulations, making high-spatiotemporal-resolution inversion affordable. This method is tested by a set of observing system simulation experiments. By assimilating synthetic observations from 400 sites, the errors of CO and NOx emissions over Beijing-Tianjin-Hebei (BTH) in the a priori emission inventory are reduced by 78% and 76%, respectively. Further application of this method estimates the emission reductions during China's Victory day parade using real surface observations. The changes of the emissions in each city are identified by this method, which suggests that the CO and NOx emissions over BTH region during the parade are reduced by 36% and 44%, respectively. Using the inversed emission inventory, the biases of CO and NO 2 simulations during the parade are reduced by 95% and 91%, respectively. This highlights the potentials of this method for improving high-spatiotemporal-resolution emission estimation. • A modified EnKF is presented to estimate emissions at one week and 5 km resolution. • The modified EnKF reduces computational costs and avoids filter divergence. • The method was validated by observing system simulation experiments. • Emission changes during China's Victory day parade are recognized by this method. • CO and NO 2 simulations are significantly improved after using the inversed emissions. [ABSTRACT FROM AUTHOR]

• Speed correction curves are introduced to improve the simulation of vehicle emission factors. • A multi-year emission inventory is developed in a typical middle-sized city based on detailed data. • The comparison of emissions is made between the middle-sized city and the megacities. • Four possible emission control policies are evaluated and discussed for middle-sized cities. Vehicle emissions are regarded as an important contributor to urban air pollution in China and most previous studies focused on megacities. However, the vehicle pollution in middle-sized cities becomes more severe due to the increasing vehicle population (VP) and lagged control policy. This study takes Langfang, a typical middle-sized city bordered by two megacities (Beijing and Tianjin), as the target domain to investigate vehicle emissions. The speed correction curves (SCC) are introduced to improve the vehicle emission factors (EF) simulation in official technical guidelines on emission inventory (GEI). A multi-year vehicle emission inventory (from 2011 to 2025) is developed in Langfang. From 2011 to 2017, the total vehicle emissions in Langfang decrease for carbon monoxide (CO), but increase for volatile organic compounds (VOCs), nitrogen oxides (NO x), and inhalable particles (PM 10), respectively. From 2018 to 2025, the emissions would increase more rapidly in Langfang than in Beijing and Tianjin, indicating the middle-sized cities may become a significant contributor to air pollution in China. Four possible control policies, including VP constrained (VPC), public transportation promotion (PTP), new energy vehicles promotion (NEP), and freight transportation structure optimization (FTO) are evaluated. The most significant emissions reductions are observed under the FTO for CO, NO x , and PM 10 , and under the VPC for VOCs. The spatial distributions of vehicle emissions show a high order of heterogeneity, indicating that local conditions should be considered in policy formulation in addition to national consistency. More comprehensive policies should be implemented to mitigate the vehicle pollution in middle-sized cities. [ABSTRACT FROM AUTHOR]