[Source Analysis of Ozone and Its Precursors in Zibo Based on 3-D Air Quality Model].

Based on the ISAM module in the WRF-CMAQ model, this study analyzed the source contribution(both regional and sectoral) of O3 and its precursors(NO2 and VOCs) in Zibo in June 2021. Days with a maximum daily 8-h average(MDA8) O3 higher(lower) than 160 µg·m-3 were defined as polluted(clean) days. Differences in the source contribution between clean days and polluted days were compared, and a typical pollution period was selected for further process analysis. The results showed that NO2 in Zibo mainly came from local emissions in summer, with a relative contribution of 45.1%. Vehicle emissions(33.8%) and natural sources(20.7%) were the primary NO2 sources. VOC contributions from natural sources, solvent usage, and the petrochemical industry were significant, with a total contribution of 78.5%. The MDA8 contribution from local sources was 21.4%, whereas the impact of regional transport(32%) and surrounding cities(26.8%) was also substantial. Among local emission sources, vehicle emissions, the power industry, and the building materials industry contributed 10.9%-18.8% to local MDA8. On O3 pollution days, the MDA8 contribution from local emissions and surrounding cities increased. However, the relative contributions from local sources were similar under different pollution conditions.

[Characteristics of Soil NO Emissions in the Yangtze River Delta Region for Year 2018].

Soil NO emissions represent an important source of atmospheric nitric oxide (NO) and play an important role in atmospheric chemistry. Based on the latest BDSNP algorithm, this study estimated the soil NO emissions over the Yangtze River Delta region for the year 2018 and further analyzed the associated temporal and spatial variations and uncertainties. The results showed that the annual soil NO emissions in 2018 over the YRD region was 213.6 kt, accounting for 7.3% of the total anthropogenic NOx emissions. Areas with high emissions were mainly concentrated in northern Anhui Province and most parts of Jiangsu Province. In terms of monthly variations, soil NO emissions peaked in June, accounting for 19.9% of the annual emissions and 19.7% of anthropogenic NOx emissions in June. In terms of daily variations, soil NO emissions peaked around 16:00 and accounted for 5.5% of daily emissions. Soil NO emissions came from three components:soil background, nitrogen fertilizer application, and nitrogen deposition. Nitrogen fertilizer application was the main source of soil NO emissions, accounting for up to 77.8%. With the in-depth reduction in NOx emissions from motor vehicles and industries, the importance of soil NO emissions will become increasingly prominent.

[Role of Land Use Changes on Ammonia Emissions from Agricultural Ecosystems in the Yangtze River Delta Region from 2000 to 2018].

Based on Landsat satellite remote sensing images, this study interprets land use changes in the Yangtze River Delta (YRD) region from 2000 to 2018. Combined with changes in nitrogen fertilizer application, the changes in ammonia emissions from farmland ecosystem due changes in land use and nitrogen fertilizer application were further investigated. The results show that along with the rapid urbanization process, the area of cultivated land in the YRD region has gradually decreased from 276269 km2 (49% of total land area) in 2000 to 244001 km2 (44%) in 2018. The effects of changes in land use and nitrogen fertilizer application on ammonia emissions from farmland ecosystems mainly include emissions from soil background and nitrogen fertilizer application. From 2000 to 2018, ammonia emissions due to the application of nitrogen fertilizer decreased from 690 kt·a-1 to 541 kt·a-1 (relative decrease by 22%), while the ammonia emissions from the soil background reduced from 32 kt·a-1 to 29 kt·a-1 (decrease by 9%). During the past 20 years, urbanization in the YRD region has accelerated, and the area of cultivated land and the total amount of nitrogen fertilizer application have significantly reduced, thus resulting in reductions in ammonia emissions from the farmland ecosystem.

[Emission Inventory of Intermediate Volatility Organic Compounds(IVOCs) from Biomass Burning in the Yangtze River Delta During 2010-2018].

Intermediate volatility organic compounds (IVOCs) are important precursors of secondary organic aerosols (SOA) but are currently not included in the conventional emissions inventories. Biomass burning represents an important source of IVOCs that could contribute to SOA formation. This study estimated the IVOC emissions from biomass burning in the Yangtze River Delta (YRD) region from 2010 to 2018 based on the fire inventory from NCAR (FINN) and the IVOCs/primary organic aerosol (POA) ratio reported in literature. During this period, the total number of fire events over the YRD region presented a declining trend, with an average of 104 fire events detected per year. During 2016-2018, the average number of fire events was approximately 6000 per year, which was 60% less than that prior to 2016. In terms of the monthly variation, the period from May to August was the period with the most fires observed, which was followed by a small peak in October. The results calculated based on the IVOCs/POA ratio method showed that the IVOC emissions from biomass burning exhibited large differences with different combinations of POA/OC and IVOCs/POA ratios, ranging from a maximum of 305.7×104 t to as small as 10.5×104 t. Monte Carlo simulation revealed that the uncertainties associated with the IVOCs/POA ratio method range from -99% to 68%.

[Impact of Parameterization on the Estimation of Ammonia Emissions:A Case Study over the Yangtze River Delta].

Atmospheric ammonia plays an important role in the formation of secondary inorganic composition of PM2.5, which has attracted a high level of attention from researchers both in China and abroad. Quantifying ammonia emissions is of great scientific significance regarding research on the formation of secondary aerosol, realizing better model performance, and control of ammonia emissions. Previous studies have shown that agricultural activities are the dominant source of atmospheric ammonia, of which livestock and poultry farming contribute the most. Existing studies on estimating ammonia emissions from livestock and poultry farming activities are mostly based on emission factors and activities. However, the choice of different emission activities could lead to large differences in estimated ammonia emissions. This study makes a variety of assumptions from the selection of activity levels (volume vs. inventory) and emission coefficients (monthly vs. annual average temperature), and establishes eight scenarios from which to calculate atmospheric ammonia emissions from livestock and poultry farming in the Yangtze River Delta region in 2017. The results show that selection of different activity levels has the greatest impact on estimated ammonia emissions; estimation based on volume is higher than that based on inventory by 27.6%-34.1%. Calculation based on a more detailed monthly average temperature is higher than using average annual temperature by 3000 to 4000 tons per year. In addition, the spatial and temporal distributions of the ammonia emissions are also closely related to the choice of volume vs. inventory and the choice of monthly average temperature vs. annual average temperature. When using inventory as the emission activity, Zhoushan (Zhejiang Province) has the lowest ammonia emissions, while Huainan (Anhui Province) has the highest. In contrast, when volume is used, Lishui (Zhejiang Province) has the lowest ammonia emissions and Nanjing (Jiangsu Province) has the highest. Emissions calculations based on monthly average temperature are supposed to be more representative than those based on annual average temperature, with the highest emissions from May to September and the lowest in the winter (December, January, and February).

[Regional Air Pollution Process in Winter over the Yangtze River Delta and Its Influence on Typical Northern Cities].

In this study, we analyzed several pollution episodes that occurred in the autumn and winter of 2018-2019 using multiple methods including the hierarchical clustering analysis, backward trajectory, and potential source contribution analysis based on monitored air quality and meteorological data. Bengbu, being a representative city to the north of the Yangtze River Delta (YRD) region and located in a heavily polluted area during these two pollution processes, is the focus of this work. The results indicated that the northern part of the YRD region is affected because of unfavorable meteorological conditions such as weak ground pressure, high humidity, low temperature, low wind speeds, and regional transport. The regional pollution processes over the YRD region in the autumn and winter seasons exhibit characteristics of wide influence and long duration with mainly two types of pollution:regional transport and intra-regional accumulation. During the two selected pollution episodes, the average PM2.5 concentration in the northern YRD region reached 131.6 µg·m-3 and 115.4 µg·m-3, respectively. The former type had a shorter duration but exhibited rapid accumulation of pollutants in a short period of time with greater pollution intensity, wider pollution range, and deeper pollution intrusion. Qualitative and quantitative analysis of the potential sources of PM2.5 based on PSCF and CWT showed that the PM2.5 concentration during EP1 was due to transport from cities such as Linyi, Xuzhou, Suqian, and Lianyungang to the pollution trajectory. The CWT value generally exceeded 80 with the highest value near 200. In contrast, EP2 was affected by the neighboring cities such as Suqian, Suzhou, and Xuzhou, and the CWT value was over 60 with the highest approaching 160, indicating that the interaction among cities in the study area is significant. This study shows that cross-regional air pollution control strategies are particularly important for alleviating the pollution situation in the northern part of the YRD region.

[Emission Inventory of Intermediate Volatility Organic Compounds from Vehicles in the Yangtze River Delta in 2017 and the Impact on the Formation Potential of Secondary Organic Aerosols].

Intermediate volatility organic compounds (IVOCs) have a significant contribution to the formation of secondary organic aerosols (SOA) in the atmosphere, but are not included in the current emission inventory. In this study, IVOC emissions from vehicles are estimated for the Yangtze River Delta region (YRD) for 2017 based on two methods:the emission factor method and the IVOCs/POA scaling factor method. Uncertainties in the estimated IVOCs emissions and the impact on their potential formation are discussed. The results based on the emission factor method showed that the total vehicular IVOCs emission in the YRD in 2017 was 35800 tons, and that the formation potential of SOA was an estimated 695 tons. IVOCs emissions from trucks accounted for>70% of total IVOCs emissions in most cities in the YRD region. In terms of fuel type, IVOCs emissions from diesel vehicles were much higher than of those from gasoline vehicles. Results based on the IVOCs/POA scaling factor method showed that the emissions calculated by different combinations of IVOCs/POA ratios and POA/PM2.5 ratios that could vary significantly, with a maximum of 64.2×104 tons and a minimum of just 5.2×104 tons. The resultant SOA formation potential was 1.55×104 tons and 1032 tons for the maximum and minimum, respectively. This study shows that the results of IVOCs emissions based on different estimation methods are associated with large uncertainties, which could directly affect the simulation results of SOA in subsequent air quality models. Therefore, it is necessary to use different inventory results in air quality models and perform model evaluation of SOA in order to obtain more accurate IVOCs emission inventories of vehicles in the YRD region.

[Ozone source apportionment at urban area during a typical photochemical pollution episode in the summer of 2013 in the Yangtze River Delta].

With the fast development of urbanization, industrialization and mobilization, the air pollutant emissions with photochemical reactivity become more obvious, causing a severe photochemical pollution with the characteristics of high ozone concentration. However, the ozone source identification is very complicated due to the high non linearity between ozone and its precursors. Thus, ways to reduce ozone is still not clear. A high ozone pollution episode occurred during July, 2013, which lasted for a long period, with large influence area and high intensity. In this paper, we selected this episode to do a case study with the application of ozone source apportionment technology(OSAT) coupled within the CAMx air quality model. In this study, 4 source regions(including Shanghai, north Zhejiang, South Jiangsu and long range transport), 7 source categories (including power plants, industrial process, industrial boilers and kilns, residential, mobile source, volatile source and biogenic emissions) are analyzed to study their contributions to surface O3 in Shanghai, Suzhou and Zhejiang. Results indicate that long range transport contribution to the surface ozone in the YRD is around 20 x 10(-9) - 40 x 10(-9) (volume fraction). The O3 concentrations can increased to 40 x 10(-9) - 100 x 10(-9) (volume fraction) due to precursors emissions in Shanghai, Jiangsu and Zhejiang. As for the regional contribution to 8 hour ozone, long range transport constitutes 42.79% +/- 10.17%, 48.57% +/- 9.97% and 60.13% +/- 7.11% of the surface ozone in Shanghai, Suzhou and Hangzhou, respectively. Regarding the high O3 in Shanghai, local contribution is 28.94% +/- 8.49%, north Zhejiang constitutes 19.83% +/- 10.55%. As for surface O3 in Suzhou, the contribution from south Jiangsu is 26.41% +/- 6.80%. Regarding the surface O3 in Hangzhou, the major regional contributor is north Zhejiang (29.56% +/- 8.33%). Contributions from the long range transport to the daily maximum O3 concentrations are slightly lower than those to the 8-hourly O3, with the contribution of 35.35%-58.04%, while local contributions increase. As for the contributions from source sectors, it is found that the major source contributors include industrial boilers and kilns (18.4%-21.11%), industrial process (19.85%-28.46%), mobile source (21.30%-23.51%), biogenic (13.01%-17.07%) and power plants (7.08%-9.75%). Thus, industrial combustion, industrial processes, and mobile source are major anthropogenic sources of high ozone pollution in summer in the YRD region.

[Characteristics and influencing factors of carbonaceous aerosols in PM2.5 in Shanghai, China].

Organic carbon (OC) and elemental carbon (EC) in PM2.5 samples collected in urban (Xujiahui) and industrial (Baoshan) areas in Shanghai during 2007-2008 were analyzed with a DRI carbon analyzer using IMPROVE-TOR protocol. The results showed that the seasonal average concentrations of OC and EC were highest in the winter and lowest in the summer. The annual average concentrations of OC and EC were 8.10 and 3.91 microg x m(-3) at the urban sampling site, and 11.91 and 4.69 microg x m(-3) in the industrial area. The annual average OC/EC ratios at the two sites were 2.01 and 2.42, respectively. Strong correlations (R2 0.52-0.87) between OC and EC were found in all seasons, with the highest correlation coefficients in the winter ( R2 0.87 and 0.80) and the lowest in the spring (R2 0.52 and 0.58), indicating that the pollutant sources in spring was more complicated due to the varying wind directions. The annual average concentrations of secondary organic carbon (SOC) were 2.72 and 5.07 microg x m(-3) at the urban and industrial sites, accounting for about 30% of the total OC. The contribution of SOC to OC was the highest (about 40%) in the summer, in accordance with the high temperature and strong solar radiation in the summer. It was also found that precipitation had significant impact on the concentrations of OC and EC, especially in the winter. The average concentrations during periods without precipitation were two times higher than that during periods with precipitation in the winter, whereas no significant difference was found between the concentrations of OC and EC in the periods with and without precipitation in the summer, possibly due to the more stable atmospheric conditions during the periods with precipitation in comparison with those without precipitation. The OC/EC and SOC/OC ratios decreased significantly during precipitation.

Development of a compound-specific carbon isotope analysis method for 2-methyltetrols, biomarkers for secondary organic aerosols from atmospheric isoprene.

The stable carbon isotope compositions of 2-methyltetrols, biomarker compounds for secondary organic aerosols formed from isoprene in the atmosphere, have been determined by gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS). In this work, isoprene with various delta(13)C values was used to produce 2-methyltetrols via an oxidation reaction with hydrogen peroxide in sulfuric acid under direct sunlight. The target compounds with different stable carbon isotope compositions were then derivatized by methylboronic acid with a known delta(13)C value and measured by GC/C/IRMS. With delta(13)C values of 2-methyltetrols and methylboronic acid predetermined, isotopic fractionation is evaluated for the derivatization process. Through reduplicate delta(13)C measurements, the carbon isotope analysis achieved excellent reproducibility and high accuracy with an average error of <0.3 per thousand. The differences between the predicted and measured delta(13)C values range from -0.10 to 0.29 per thousand, indicating that the derivatization process does not introduce isotopic fractionation. The delta(13)C values of 2-methyltetrols could be calculated on the basis of the stoichiometric mass balance equation among 2-methyltetrols, methylboronic acid, and methylboronate derivatives. Preliminary tests of 2-methyltetrols in PM(2.5) aerosols at two forested sites were conducted and revealed significant differences in their isotope compositions, implying possible application of the method in helping us understand the primary emission, photochemical reaction, or removal processes of isoprene in the atmosphere.