Lamgalbraith1685

During the NTGEM period, the control of combustion sources and industrial sources was evident.In this study, according to the activity levels of volatile organic compounds (VOCs) sources and source profiles, a 2016-based inventory of the speciation emission of the VOCs was established and the ozone formation potential (OFP) were estimated in Zhengzhou. The results showed that the total VOCs emission in Zhengzhou in 2016 was 96215.3 t. The highest emission source was on-road mobile source (29.7%) followed by solvent use sources (28.1%). The species that contributed the highest emission was alkanes (29.8%) followed by aromatics (29.0%). The OFP in Zhengzhou in 2016 was 341291.0 t with the highest contributing source as on-road mobile (30.5%) followed by solvent use source (28.8%). Moreover, the light duty gasoline vehicle, use of interior wall coatings, vehicle surface coating, gas station loading and unloading, and manufacture of non-metallic mineral were the major secondary emission sources of OFP, which needed to be controlled for reducing ozone pollution in Zhengzhou. For VOCs species group, the higher contribution groups were aromatics (42.8%) and alkenes (38.9%). The sources that produced m/p-xylene, propylene, ethylene, and other species should be paid more attention.To understand the trends and characteristics of air pollution in Baoding in recent years, an analysis of air quality and air pollutant concentrations in Baoding from 2013 to 2018 was carried out. The results showed that 1 from 2013 to 2018, the comprehensive index of Baoding dropped from 11.6 to 6.6, the days of severe pollution decreased from 114 days to 27 days, and cumulative concentration of pollutants during severe pollution decreased from 57.34% to 20.59%. This indicated that the air quality of Baoding city has improved year on year from 2013 to 2018. Not only has the number of heavy pollution days and the annual average concentration of pollutants decreased, but also the proportion of cumulative concentrations of pollutants during heavy pollution has decreased. the difference between the average concentration level of Baoding city and "2+26" Cities is getting smaller and smaller. Selleck Trametinib ② Summer ρ(O3-8h) increased year on year. In 2017 and 2018, the heavy pollution days caused by O3 accounted for 17.0% and 14tion increased as compared to that during the high pollution season in 2017, indicating that the coal combustion was still one of the pollution sources that Baoding city needed to control. In summary, Baoding should strengthen the management and control of motor vehicles in autumn, and gradually change from the original coal control measures to a combination of coal control and diesel control in winter; in the future, the focus of air pollution prevention and control should be strengthened toward O3 pollution.To evaluate the effect of emergency emission reduction measures during the heavy air pollution episodes in Beijing, Tianjin, Hebei, and its surrounding areas, a scenario simulation method was used. The concentrations of PM2.5, PM10, SO2, NO2, CO, and O3-8h, air quality index (AQI), characteristics of heavy air pollution, and climate and meteorological factors were analyzed using the observation data available from October to December 2019. The 24 h, 72 h, and 144 h prediction results of NAQPMS model were analyzed. The uncertainties of the assessment and model prediction were discussed. The results showed that the average PM2.5 concentration in Beijing, Tianjin, and its surrounding 26 cities ("2+26" cities) from October to December 2019 was 64 μg ·m-3, indicating a decrease of 10 μg ·m-3 as compared with that during the same period in 2018. There were 4 occurrences of regional heavy air pollution episodes, with the average PM2.5 concentration of 156 μg ·m-3 of affected cities. The value of evaluation on meteorological condition index of PM2.5 pollution (EMI) of "2+26" cities ranged from -15.6%-16.8%. The meteorological conditions of 12 cities, including Beijing, Tianjin, and Shijiazhuang, deteriorated as compared with those during the same period in 2018, and the changes ranged from 3.2%-16.8%. However, the emergency emission reduction measures effectively reduced the occurrence of regional heavy air pollution episodes, the peak concentration of PM2.5 was decreased significantly, and no severe regional pollution episode occurred. The daily PM2.5 concentrations reduced by 2% to 9% in Beijing, Shijiazhuang, Baoding, Tangshan, and other cities during a typical heavy air pollution period. The quarterly average concentrations of PM2.5 in the "2+26" cities reduced by 1 to 3 μg ·m-3. The regional emergency emission reduction measures have played an active role in protecting the health of the people and improving the quality of ambient air.Black carbon (BC) is an important component of atmospheric particulate matter (PM) emitted during the combustion process. Light absorption and scattering exhibited by BC affect the exchange of solar energy on Earth. In this study, continuous measurements of atmospheric particulate BC were carried out, using a BC analyzer (AE33) in the suburban area of Nanjing from January 2019 to May 2019, to realize the diurnal variations of BC during the different seasons and potential sources of BC during the clean (CD, PM2.575 μg ·m-3). The results showed that the average concentration of BC was (3.8±2.3) μg ·m-3; a higher average BC concentration value of (4.3±2.6) μg ·m-3 was observed during the winter, exceeding that during the spring period by a factor of 1.3. The higher BC concentrations during the winter was attributed to the stagnant weather conditions and additional emissions. Significant diurnal cycles of BC were observed with higher BC concentrations during rush hours of traffic, suggesting traffic origins. The Ångström exponent were 1.32 and 1.30 during the spring and winter periods, respectively, indicating that the BC was mainly produced from the traffic emissions during both the seasons. This hypothesis was also supported by the average BC/CO ratio of 0.005, which was similar to that of BC derived by traffic emissions. Moreover, we discovered that the contributions of traffic emissions to BC were 68%-87% and 72%-86% during the haze and clean periods, respectively. This indicated enhanced contributions of coal combustion and biomass burning to BC in Nanjing during the haze events. Finally, using the potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analysis, we highlighted that the BC at the receptor site was mainly from the local emissions in the surrounding areas of Nanjing.Based on the online monitoring data of gaseous pollutants and components in PM2.5 from Chengdu super observatory of atmospheric environment, the meteorological factors and component characteristics of three haze pollution process in Chengdu from 2019 to 2020 were analyzed. The CMB model was adopted to simulate the sources and variation trends of PM2.5 pollution during the study period, and the causes of each pollution process were analyzed. The results showed that all the three pollution processes occurred under adverse meteorological conditions, where the relative humidity and temperature continued to rise and the wind speed and boundary layer height continued to decrease. The average daily relative humidity was greater than 70%, average daily temperature was greater than 8℃, average daily wind speed was less than 0.8 m ·s-1, and average daily boundary layer height was less than 650 m. During the three events of pollution, the main components were NO3-, OC, NH4+, and SO42-. Among them, the mass concentrationecondary nitrate, secondary sulfate, motor vehicles, and coal combustion were the main pollution sources during the study period. The PM2.5 concentration was positively correlated with the contribution of secondary nitrate and negatively correlated with the contribution of dust source.To investigate the characteristics of carbonaceous species in PM2.5 in Beijing after the implementation of the Action Plan for the Prevention and Control of Air Pollution, PM2.5 was continuously sampled in the heavily polluted southern urban area of Beijing from December 2017 to December 2018. The characteristics of organic carbon (OC) and element carbon (EC) were then determined. The results showed that the annual concentrations of PM2.5, OC, and EC in Beijing varied in wide ranges of 4.2-366.3, 0.9-74.5, and 0.0-5.5 μg ·m-3, respectively, and the average mass concentration were (77.1±52.1), (11.2±7.8), and (1.2±0.8) μg ·m-3. Overall, the carbonaceous species (OC and EC) accounted for 16.1% of the PM2.5 mass. The seasonal characteristics of the OC mass concentrations were winter [(13.8±8.7) μg ·m-3] > spring [(12.7±9.6) μg ·m-3] > autumn [(11.8±6.2) μg ·m-3] > summer [(6.5±2.1) μg ·m-3]. The concentration of the EC during the four seasons was low, ranging from 0.8 to 1.5 μg ·m-3. The annual average mass concentration and contribution of secondary organic carbon (SOC) were (5.4±5.8) μg ·m-3 and 48.2%, respectively, highlighting the significant contribution of the secondary process. With the aggravation of pollution, although the contribution proportion of OC and EC decreased, their mass concentrations during "heavily polluted" days were 6.3 and 3.2 times that of "excellent" days, respectively. Compare to non-heating period, the mass concentrations of PM2.5, OC, and SOC increased by 14.4%, 47.9%, and 72.1% in heating period, respectively, which emphasized the importance of carbonaceous species during heating periods. Potential source contribution function (PSCF) analysis showed that the southwest areas of Beijing (such as Shanxi and Henan province) were the main potential source areas of PM2.5 and OC. The high value area of the PSCF of EC was less and the main potential source area was in the south of Beijing (such as Shandong and Henan province).To explore the characteristics of water-soluble inorganic ions (WSIIs) in PM2.5 during the process of continuous improvement of air quality in Beijing in recent years, a continuous collection of PM2.5 sample campaign was conducted in Beijing from 2017 to 2018. The PM2.5 mass concentration and WSIIs were then determined. The results showed that the average concentration of PM2.5 in Beijing was (77.1±52.1) μg ·m-3, with the highest and lowest values during spring [(102.9±69.1) μg ·m-3]and summer [(54.7±19.9) μg ·m-3], respectively. The average concentration of WSIIs was (31.7±30.1) μg ·m-3, accounting for 41.1% of the PM2.5 mass, and the seasonal contributions were autumn (45.9%) > summer (41.9%) > spring (39.9%) ≥ winter (39.2%). SNA was an important component of the WSIIs that accounted for 86.0%, 89.5%, 74.6%, and 73.0% of the total WSIIs during spring, summer, autumn, and winter, respectively. With an increase in temperature, the concentration of NO3- increased initially and then decreased, while the concenh were relatively low, but the contribution of Ca2+ was high.To study the characterization and source apportionment of PM2.5 in Tianjin, based on high-resolution online monitoring data from 2017 to 2019, the concentrations and its chemical compositions and sources of PM2.5 were analyzed. The results showed that the average concentration of PM2.5 was 61 μg ·m-3. The primary chemical compositions of PM2.5 were nitrate, organic carbon (OC), ammonium, sulfate, elemental carbon (EC), and Cl- and their corresponding mass percentages to PM2.5 were 17.7%, 12.6%, 11.5%, 10.7%, 3.4%, and 3.1%, respectively. From 2017 to 2019, the concentrations of PM2.5 and its main chemical compositions exhibited a decreasing trend; the mass ratios of NO3- and NH4+ to PM2.5 exhibited an increasing trend, while the mass ratios of SO42-, OC, and EC to PM2.5 exhibited a decreasing trend; further, the mass ratio of Cl- exhibited a slight increasing trend. The concentrations of K+, Ca2+, and Na+ and their mass percentages to PM2.5 increased. The concentrations of PM2.5 and its primary components were relatively higher during heating season, and relatively lower during non-heating season.