[Synergistic Benefits of Pollution and Carbon Reduction from Air Pollution Control in Hebei Province from 2013 to 2020].

Recently, China has been facing the dual challenges of air pollution control and carbon emission reduction. Pollution and carbon reduction have become a breakthrough point for green socio-economic transformation. Air pollutant and CO2 emission inventories provide a tool for monitoring pollution and carbon reduction; however, there have been some problems in previous studies, including incomplete species coverage, different source classifications, and narrow time scales. Based on the unified emission source classification system and estimation method, an emission inventory was developed for Hebei Province from 2013 to 2020, and the emission trends, structure change, driving force, synergistic benefits, and spatial distribution were analyzed. Hebei Province achieved a balance during the study period in socio-economic development and anthropogenic emission control. SO2 emissions decreased rapidly during the "Ten Atmospheric Measures" period. VOCs and NH3 emissions reduction were more significant during the "Blue Sky Defense War" period. The decrease rates of NOx and PM2.5 emissions were relatively stable, and CO2 emissions increased slightly. The coal-fired treatment effectively reduced the air pollutant and CO2 emissions and strengthening the emission standards for key industries reduced SO2, NOx, and PM2.5 emissions; however, the VOCs emission control requires improvement. Power and residential sources achieved co-reduction of air pollutants and CO2 and reducing residential coal optimized the energy structure, thereby leading to greater synergistic benefits in the residential source. The key pollution and carbon reduction areas in Hebei Province were Shijiazhuang, Tangshan, Handan, Baoding, and Langfang. The methods and conclusions in this study can provide technical and decision-making references for regional pollution and carbon reduction efforts.

[Evolution and Characteristics of Full-process Vehicular VOCs Emissions in Tianjin from 2000 to 2020].

Vehicle emissions are an important source of anthropogenic volatile organic compound (VOCs) emissions in urban areas and are commonly quantified using vehicle emission inventories. However, most previous studies on vehicle emission inventories have incomplete emission factors and emission processes or insufficient consideration of meteorological parameters. Based on the localized full-process emission factors attained from tested data and previous studies, a method to develop a monthly vehicular VOC emission inventory of full process for the long-term was established, which covered exhaust and evaporative emissions (including running loss, diurnal breathing loss, hot soak loss, and refueling emission). Then, the method was used to develop a full-process vehicular VOC emission inventory in Tianjin from 2000 to 2020. The results showed that the total vehicular VOC emissions in Tianjin rose slowly and then gradually decreased. In 2020, the total emissions were 21400 tons. The light-duty passenger vehicles were the dominant contributors and covered 75.00% of the total emissions. Unlike the continuous decline in exhaust emissions, evaporative emissions showed an inverted U-shaped trend with an increasing contribution to total emissions yearly, accounting for 31.69% in 2020. Monthly emissions were affected by both vehicle activity and emission factors. VOC emissions were high in autumn and winter and low in spring and summer. During the COVID-19 epidemic in 2020, vehicle activity was limited by closure and control, making VOC emissions significantly lower than those during the same period in previous years. The method and data in this study can provide technical reference and a decision-making basis for air pollution prevention and control.

[Vehicle Emission Inventory and Scenario Analysis in Liaoning from 2000 to 2030].

Vehicle emissions have become a major source of air pollution in urban cities. The vehicle emission inventory of the Liaoning province from 2000 to 2030 was established based on the COPERT model and ArcGIS, and the temporal and spatial distribution characteristics of six pollutants (CO, NMVOC, NOx, PM10, SO2, and CO2) were analyzed. Taking 2016 as the base year, eight scenarios of control measures were designed based on scenario analysis, and the effects of different scenarios on emission reduction were assessed. Results showed that during 2000-2016, CO, NMVOC, NOx, and PM10 emissions at first exhibited increasing trends, after which they decreased. Emissions of SO2 exhibited fluctuating trends, while the emissions of CO2 showed a continuous increase. Passenger cars and motorcycles were the main contributors of CO and NMVOC emissions. Heavy-duty trucks and buses were the main sources of NOx and PM10 emissions. Passenger cars were the major contributors to SO2 and CO2 emissions. Vehicle emissions were significantly higher in the central and southern in Liaoning Province. At the city level, vehicle emissions were mainly concentrated in Shenyang and Dalian. The scenario analysis showed that the implementation of stricter vehicle emission standards can enhance the emission reduction effect. Moreover, accelerating the implementation of new emission standards was beneficial to reduce emissions. The integrated scenario would achieve the maximum emission reduction, with reduction rates of CO, NMVOC, NOx, PM10, CO2, and SO2 at 30.7%, 14.3%, 81.7%, 29.4%, 12.3%, and 12.1%, respectively.

[Mobile Source Emission Inventory with High Spatiotemporal Resolution in Tianjin in 2017].

Mobile source emissions have become a major contributor to air pollution in urban areas. Most of the previous studies focus on the emissions from a single source such as on-road mobile source (vehicles) or non-road mobile source (construction machinery, agricultural machinery, ships, railway diesel locomotives, aircraft), but few studies investigate the mobile source emissions as a whole. In this study, we introduced a method for developing mobile source emission inventory with high spatiotemporal resolution, and applied this method in Tianjin in 2017 to analyze the emission compositions and spatiotemporal characteristics there. The results showed that the CO, VOCs, NOx, and PM10 emissions from the mobile sources were 183.03, 64.18, 149.85, and 8.36 thousand tons, respectively. The on-road mobile source was the main contributor to CO and VOCs emissions, accounting for 85.38% and 86.60%, respectively. The non-road mobile source was the main contributor to NOx and PM10 emissions, accounting for 57.32% and 66.95%, respectively. According to the temporal distributions, the mobile source emissions were lowest in February for all pollutants. Moreover, they were highest in October for CO and VOCs and in August for NOx and PM10. Holidays (such as Spring Festival and National Day) have a significant impact on the temporal distribution of the mobile source emissions. According to the spatial distributions, the CO and VOCs emissions were concentrated in urban areas and roads with heavy traffic flow (highways and national highways), and the NOx and PM10 were concentrated in urban areas and port areas. The spatial distributions of different pollutants were determined by the location of their major contributors. This study can provide the required data for fine air pollution control and air quality simulation in Tianjin. Moreover, this method can be applied to the other areas where a mobile source emission inventory needs to be developed.

[Pollution Characteristics and Emission Factors of VOCs from Vehicle Emissions in the Tianjin Tunnel].

The pollution characteristics and emission factors (EFs) of the volatile organic compounds (VOCs) of vehicles were investigated using the tunnel test method on weekdays and weekends in the Wujinglu Tunnel in Tianjin, China. Gas samples in the tunnel were collected with 3.2 L stainless steel canisters and 99 VOCs species were analyzed by gas chromatography-mass spectrometry (GC-MS). The concentration levels, variation characteristics, and EFs of the VOCs were analyzed. The ozone formation potentials (OFPs) and secondary organic aerosol formation potentials (SOAFPs) of the VOCs in the tunnel were calculated. Moreover, a comparison of the study results with current literature was conducted. The total concentrations of VOCs at the inlet and midpoint are (190.85±51.15) µg·m-3 and (257.44±62.02) µg·m-3, respectively. The total EFs are (45.12±10.97) mg·(km·veh)-1 and the EFs for alkanes, alkenes, alkynes, aromatics, halocarbons, and oxygenated volatile organic compounds (OVOCs) are (22.79±7.15), (5.04±1.20), (0.78±0.34), (9.86±2.81), (0.26±0.17), and (6.25±2.27) mg·(km·veh)-1, respectively. They are notably smaller than the values obtained in a previous test in 2009. Isopentane, toluene, ethylene, methyl tert-butyl ether (MTBE), and ethane were the top five species among the VOC EFs. The ratios of methyl tert-butyl ether/benzene (MTBE/B) and methyl tert-butyl ether/toluene (MTBE/T) are 1.07 and 0.77, respectively. This implies that the contribution of evaporative emissions from vehicles to VOCs emissions cannot be ignored. The OFPs and SOAFPs in the tunnel are (145.50±37.85) and (43.87±12.75) mg·(km·veh)-1, respectively. Compared with the test in 2009, the OFPs and SOAFPs are 94.23% and 90.88% smaller, respectively. The sharp decrease of the OFPs and SOAFPs is closely related to stricter emission standards and the upgrade of oil products.