Characterization of photochemical losses of volatile organic compounds and their implications for ozone formation potential and source apportionment during summer in suburban Jinan, China.

Volatile organic compounds (VOCs) undergo substantial photochemical losses during their transport from emission sources to receptor sites, resulting in serious implications for their source apportionment and ozone (O3) formation. Based on the continuous measurements of VOCs in suburban Jinan in August 2022, the effects of photochemical losses on VOC source contributions and O3 formation were evaluated in this study. The observed and initial concentrations of total VOCs (TVOC) were 12.0 ± 5.1 and 16.0 ± 7.4 ppbv, respectively. Throughout the observation period, alkenes had the most prominent photochemical losses (58.2%), followed by aromatic hydrocarbons (23.1%), accounting for 80.6% and 6.9% of the total losses, respectively. During high O3 episodes, the photochemical loss of VOCs was 6.9 times higher than that during the cleaning period. Alkene losses (exceeding 67.3%), specifically losses of isoprene, propylene, ethylene, and n-butene, dominated the total losses of VOCs during the O3 increase period. Eight sources of VOCs were identified by positive matrix factorization (PMF) based on the observed and initial concentration data (OC-PMF and IC-PMF, respectively). Concentrations of all emission sources in the OC-PMF were underestimated by 2.4%-57.1%. Moreover, the contribution of each emission source was over- or underestimated compared with that in case of the IC-PMF. The contributions of biogenic and motor vehicle exhaust emissions were underestimated by 5.3 and 2.8 percentage points, respectively, which was associated with substantial oxidation of the emitted high-reactive species. The contributions of coal/biomass burning and natural gas were overestimated by 2.4 and 3.9 percentage points, respectively, which were related to the emission of low-reactive species (acetylene, ethane, and propane). Based on our results, the photochemical losses of VOCs grossly affect their source apportionment and O3 formation. Thus, photochemical losses of VOCs must be thoroughly accounted to establish a precise scientific foundation for air-pollution control strategies.

High spatiotemporal resolution ammonia emission inventory from typical industrial and agricultural province of China from 2000 to 2020.

As a typical industrial and agricultural province, Shandong is one of China's most seriously air-polluted regions. One comprehensive ammonia emission inventory with a high spatial resolution (1 km × 1 km) for 136 county-level administrative divisions in Shandong from 2000 to 2020 is developed based on county-level activity data with the corrected and updated emission factors of seventy-seven subcategories. Annual ammonia emissions decrease from 1003.3 Gg in 2000 to 795.9 Gg in 2020, with an annual decrease rate of 1.2 %. Therein, the ammonia emissions associated with livestock and farmland ecosystems in 2020 account for 50.8 % and 32.9 % of the provincial total ammonia emission, respectively. Laying hen and wheat are the livestock and crop with the highest ammonia emissions, accounting for 23.3 % and 36.3 % of ammonia emissions from livestock and the application of synthetic fertilizers, respectively. Furthermore, waste treatment, humans and vehicles are the top three ammonia emission sources in urban areas, accounting for 5.0 %, 4.7 % and 1.3 % of total ammonia emissions, respectively. The spatial distribution of grids with high ammonia emissions is consistent with the distribution of intensive farms. Significant emission intensity areas mainly concentrate in western Shandong (e.g., Caoxian of Heze, Qihe of Dezhou, Yanggu of Liaocheng, Liangshan of Jining) due to the large area of arable land and the high levels of agricultural activity. Overall, prominent seasonal variability characteristics of ammonia emission are observed. Ammonia emissions tend to be high in summer and low in winter, and the August to January-emission ratio is 5.6. The high temperature and fertilization for maize are primarily responsible for Shandong's increase in ammonia emissions in summer. Finally, the validity of the estimates is further evaluated using uncertainty analysis and comparison with previous studies. This study can provide information to determine preferentially effective PM2.5 control strategies.

Impact of greening trends on biogenic volatile organic compound emissions in China from 1985 to 2022: Contributions of afforestation projects.

The rapid expansion of green areas in China has enhanced carbon sinks, but it also presents challenges regarding increased biogenic volatile organic compound (BVOC) emissions. This study examines the impact of greening trends on BVOC emissions in China from 1985 to 2001 and from 2001 to 2022, focusing on evaluating long-term trends in BVOC emissions within eight afforestation project areas during these two periods. Emission factors for 62 dominant tree species and provincial Plant Functional Types were updated. The BVOC emission inventories were developed for China at a spatial resolution of 27 km × 27 km using the Model of Emissions of Gases and Aerosols from Nature. The national BVOC emissions in 2018 were estimated at 54.24 Tg, with isoprene, monoterpenes, sesquiterpenes, and other BVOC contributing 26.94 Tg, 2.29 Tg, 0.44 Tg, and 24.57 Tg, respectively. Over the past 37 years, BVOC emissions experienced a slow growth rate of 1.7 % (0.79 Tg) during 1985-2001, followed by a significant increase of 12 % (6 Tg) from 2001 to 2022. BVOC emissions in the eight afforestation project areas increased by 2 % and 20 % during the two periods. From 2001 to 2022, at the regional scale, the Shelterbelt program for the middle reaches of the Yellow River area exhibited the largest rate of increase (43 %) in BVOC emissions. The Shelterbelt program for the upper and middle reaches of the Yangtze River made the most largest contribution (45 %) to the national increase in BVOC emissions. Afforestation projects have shifted towards planting more broadleaf trees than needleleaf trees from 2001 to 2022, and there also showed a change from herbaceous plants to broadleaf trees. These trends have led to higher average emission factors for vegetation, resulting in increased BVOC emissions. It underscores the importance of considering BVOC emissions when evaluating afforestation initiatives, emphasizing the need to balancing ecological benefits with potential atmospheric consequences.

High spatiotemporal resolution vehicular emission inventory in Beijing-Tianjin-Hebei and its surrounding areas (BTHSA) during 2000-2020, China.

One comprehensive emission inventory of CO, HC, NOX, PM10, PM2.5, BC, CH4, CO2 and N2O with high spatial resolution (0.01° × 0.01°) for 58 cities in Beijing-Tianjin-Hebei and its surrounding areas (BTHSA) during 2000-2020 are developed by using COPERT model and ArcGIS methodology. The results show that vehicular emissions of CO, HC, NOX, PM10, PM2.5, BC and CH4 have begun to decrease or slow their growth rates in recent years due to the implementation of measures to control vehicular emissions. However, vehicular emissions of CO2 increase rapidly due to little fuel economy improvement. Besides, the usage of selective catalytic reduction (SCR) systems by heavy duty truck (HDT) is the main factor impacting the growth trend of vehicular N2O emissions since 2017. By 2020, vehicular emissions of CO, HC, NOX, PM10, PM2.5, BC, CO2, CH4 and N2O are estimated at about 1.65 Mt, 0.35 Mt, 1.39 Mt, 87.44 kt, 55.06 kt, 15.57 kt, 527.71 Mt, 36.20 kt and 8.56 kt, respectively. Therein, China III, IV, IV and IV passenger cars (PCs) are the predominated models for vehicular emissions of CO, HC, CH4 and CO2, accounting for 19.59-28.26 % of the total vehicular emission of corresponding pollutant. Nevertheless, the major contributors of vehicular emissions of NOX, PM10, PM2.5, BC and N2O are China III (29.64 %), III (18.03 %), III (22.81 %), III (42.16 %) and V (22.28 %) HDTs, respectively. The gridded vehicular emissions vary significantly, with emissions of CO, HC, CH4 and CO2 being mainly concentrated in central urban areas of cities (e.g., Beijing, Tangshan, Zhengzhou, Tianjin, Qingdao, Jinan). Nevertheless, the grids with high vehicular emissions of NOX, PM10, PM2.5, BC and N2O are mainly distributed along the expressway and the suburban roads of cities (e.g., Linyi, Tangshan, Jining, Weifang, Shijiazhuang, Tianjin, Baoding). Finally, multi-year uncertainties of vehicular emission inventory are discussed.