[Review of UAV-based Atmospheric Fine Particulate Matter and Ozone Pollution Detection and Source Localization].

In recent years, the management of atmospheric fine particulate matter(PM2.5) pollution in China has achieved staged success, but ozone(O3) pollution has increased rapidly. Detection and source localization of atmospheric pollutants is the basis and key to controlling the combined pollution of PM2.5 and O3. With the rapid development of UAV technology and sensor technology, air pollution detection based on UAV platforms can effectively obtain the structural characteristics of PM2.5 and O3 near the surface and accurately trace the source of air pollution events by applying the computer algorithms, with the characteristics of high timeliness, flexibility, and spatial and temporal resolution. This will help researchers understand the distribution, changes, and sources of regional pollutants and provide a scientific basis for the synergistic control of combined air pollution. This study reviewed the traditional air pollution detection methods, summarized the types of UAV platforms and detection instruments commonly used in pollution detection, concluded the applications of UAV-based PM2.5 and O3 pollution detection and the algorithms of pollution source localization, and discussed the future trends of UAV-based air pollution detection.

[Pollution Characteristics and Source Apportionment of Volatile Organic Compounds in Lishui Area of Nanjing].

To understand the changes in the components of volatile organic compounds(VOCs), the contribution proportion of each component to ozone, and the VOCs sources, we monitored the VOCs for a year in Lishui. The results showed that theρ(TVOC) was 223.46 µg·m-3, ρ(alkanes) was 49.45 µg·m-3(22.3%), ρ(OVOCs) was 50.63 µg·m-3(22.66%), ρ(halogenated hydrocarbons) was 64.73 µg·m-3(28.95%), ρ(aromatic hydrocarbons) was 35.46 µg·m-3(15.87%), ρ(alkenes) was 18.26 µg·m-3(8.19%), and ρ(others) was 4.9 µg·m-3(2.2%). ρ(TVOC) was higher in summer(263.75 µg·m-3) and lower in winter(187.2 µg·m-3), with 246.11 µg·m-3 in spring and 204.77 µg·m-3 in autumn. The daily concentration of VOCs showed two peaks, one from 9:00 to 10:00 and another from 14:00 to 15:00, and the high concentration was mainly found in the urban main road area with dense human activities. The ozone formation potential(OFP) was 278.92 µg·m-3, and those of olefin and aromatic hydrocarbon were 114.47 µg·m-3(41.1%) and 113.49 µg·m-3(40.8%), respectively, contributing over 80%, which was an important precursor of ozone. On the other hand, the ratio of characteristic compounds to toluene/benzene(T/B) was 4.13, which indicated that it was greatly affected by the solvent usage. In the end, the results of positive matrix factorization(PMF) source apportionment showed that VOCs mainly came from solvent usage, industrial production, and traffic emissions. The VOCs pollution had a great influence on ozone, so it was necessary to strengthen the treatment of industrial production, solvent usages, and traffic emissions.

[Component Characteristics and Source Appointment of Volatile Organic Compounds in Lianyungang City].

Volatile organic compounds (VOCs) are important precursors of ozone and particulate matter; thus, their impacts on air quality are particularly significant. To study the composition characteristics and sources of VOCs in Lianyungang City, four national control sites were selected to conduct VOCs sampling and analysis on typical days in spring, summer, and autumn. Concentrations of VOCs, the effects of different components of VOCs on ozone formation were quantified, and the sources of VOCs were analyzed using the Positive Matrix Factorization model. The VOC concentrations were in the range of 27.46×10-9-40.52×10-9 in spring, 45.79×10-9-53.45×10-9 in summer, and 38.84×10-9-46.66×10-9 in autumn. Concentrations of oxygenated compounds accounted for 41%-48% of all measured VOCs. VOC species with higher concentrations were acetone, acrolein, and propionaldehyde, and the concentration of isoprene was higher in summer. Generally, VOC concentrations were higher at 09:00 than at 13:00 when acrolein, ethylene, and dichloromethane concentrations changed greatly. The ozone formation potential (OFP) of oxygenated compounds was the highest, followed by aromatics and alkenes, and the OFP of alkanes was the smallest. The VOC species with higher OFP were acrolein, propylene, and ethylene. The main sources of VOCs in Lianyungang were industry (49%), solvent usage (23%), transportation (14%), paint usage (10%), and natural sources (4%). The results suggest further investigating the oxygenated compounds with higher concentrations and higher OFP in Lianyungang City, and studying the impacts of industrial sources on VOCs.

[Pollution Characteristics and Source Apportionment of Fine Particulate Matter in Autumn and Winter in Puyang, China].

As one of the air pollution transmission channels around the beijing-Tianjin-Hebei region, Puyang frequently suffer from severe airpollution in autumn and winter. In order to study the characteristics and main sources of fine particulate matter during these periods, manual membrane sampling of PM2.5 was conducted at three national control sites from October 15, 2017, to January 13, 2018. Chemical composition analysis was conducted and, combined with a PMF receptor model, source analysis of the fine particles was also undertaken. The results show that the average mass concentration of PM2.5 in Puyang was 94.16 µg·m-3 in the autumn and winter of 2017, and Pushuihe station was the most polluted site. During the heating season, the three control stations all recorded the frequent occurrence of severe and serious pollution events, while the frequency of mild pollution events decreased. When heavy pollution events occurred, the concentrations of NO2 and CO increased significantly. The main components of PM2.5 were water-soluble ions (52.33%), OCEC (25.32%), and crustal elements (0.08%). The concentrations of NO3- were high while the concentrations of SO42- were low. When heavy pollution occurred, the concentrations of water-soluble ions, OC, EC, and K in PM2.5 increased significantly, while the concentrations of crustal elements decreased. During the sampling period, the conversion ratios of sulfur and nitrogen in Puyang were high and atmospheric oxidation was strong. The transformation of sulfur and nitrogen promoted the occurrence of heavy pollution. Emissions of NOx, CO, and VOCs were higher in Puyang in 2017, and the source apportionment results showed that the main sources of PM2.5 in autumn and winter were secondary inorganic salts (37%), industrial sources (16%), secondary organic aerosol (SOA, 14%), biomass combustion (12%), mobile sources (9%), coal burning (7%), and dust (4%). Secondary transformation played an important role in the development of heavy pollution events in Puyang. It is necessary to focus on the control of emissions from industrial sources, biomass combustion, moving source, and civil coal combustion.

[Concentration Characteristics and Influencing Factors of Atmospheric Particulate Matters in Spring on Weizhou Island, Beihai, Guangxi Province].

To investigate the characteristics of atmospheric environment and possible cross-boundary transports in the north of South China Sea, field experiments were carried out on Weizhou Island from March to April, 2015. The concentration and particle size distributions of atmospheric particulate matters were measured, and the concentration characteristics and the source of particulate matters were analyzed in combination with meteorological factors and back trajectory analysis. The results showed that:the PM1, PM2.5 and PM10concentrations were (21±12) µg·m-3, (35±19) µg·m-3, (43±20) µg·m-3, respectively. The mass concentrations of PM1, PM1-2.5 and PM2.5-10 accounted for 50%, 32%,18% of PM10 mass concentrations, respectively. Besides, the number concentrations of particulate matters with particle sizes of 0.5-1 µm, 1-2.5 µm and 2.5-20 µm accounted for 93.5%, 6.1% and 0.4% of the total number concentration, respectively. The particle number concentration was negatively correlated with visibility and air pressure. Backward trajectory analysis showed that air masses from southwest direction accounted for the highest frequency effect (45.9%), in this case, particulate matters with particle sizes of 0.5-1 µm, 1-2.5 µm and 2.5 µm had the minimum number concentration and NO had the highest concentration. Air masses from the east direction accounted for 34.1% of the frequency effect with the minimum SO2concentration and the highest O3 concentration. The concentrations of NO2, NOx, O3 and CO were the minimum when air masses came from the south direction which accounted for 12.5% of the frequency effect. Air masses from the northeast had the lowest frequency effect (7.4%), but had the maximum particle number concentration, mass concentration and the concentration of gaseous pollutants except O3 and NO. Atmospheric fine particles and gaseous pollutants on Weizhou island were affected by transport from Chinese mainland and Southeast Asia. Pollutants from Chinese mainland were mainly from industrial sources, while pollutants from Southeast Asia were mainly from the shipping business inside and outside ports.

Dry deposition velocity of atmospheric nitrogen in a typical red soil agro-ecosystem in Southeastern China.

Atmospheric dry deposition is an important nitrogen (N) input to farmland ecosystems. The main nitrogen compounds in the atmosphere include gaseous N (NH3, NO2, HNO3) and aerosol N (NH4+/NO3-). With the knowledge of increasing agricultural effects by dry deposition of nitrogen, researchers have paid great attention to this topic. Based on the big-leaf resistance dry deposition model, dry N deposition velocities (Vd) in a typical red soil agro-ecosystem, Yingtan, Jiangxi, Southeastern China, were estimated with the data from an Auto-Meteorological Experiment Station during 2004-2007. The results show that hourly deposition velocities (Vdh) were in the range of 0.17-0.34, 0.05-0.24, 0.57-1.27, and 0.05-0.41 cm/s for NH3, NO2, HNO3, and aerosol N, respectively, and the Vdh were much higher in daytime than in nighttime and had a peak value around noon. Monthly dry deposition velocities (Vdm) were in the range of 0.14-0.36, 0.06-0.18, and 0.07-0.25 cm/s for NH3, NO2, and aerosol N, respectively. Their minimum values appeared from June to August, while their maximum values occurred from February to March each year. The maximum value for HNO3 deposition velocities appeared in July each year, and Vdm(HNO3) ranged from 0.58 to 1.31 cm/s during the 4 years. As for seasonal deposition velocities (Vds), Vds(NH3), Vds(NO2), and Vds(aerosol N) in winter or spring were significantly higher than those in summer or autumn, while Vds(HNO3) in summer were higher than that in winter. In addition, there is no significant difference among all the annual means for deposition velocities (Vda). The average values for NH3, NO2, HNO3, and aerosol N deposition velocities in the 4 years were 0.26, 0.12, 0.81, and 0.16 cm/s, respectively. The model is convenient and feasible to estimate dry deposition velocity of atmospheric nitrogen in the typical red soil agro-ecosystem.

Atmospheric inorganic nitrogen deposition to a typical red soil forestland in southeastern China.

A 2-year monitoring study was conducted to estimate nitrogen deposition to a typical red soil forestland in southeastern China. The dry deposition velocities (V(d)) were estimated using big leaf resistance analogy model. Atmospheric nitrogen dry deposition was estimated by combing V(d) and nitrogen compounds concentrations, and the wet deposition was calculated via rainfall and nitrogen concentrations in rainwater. The total inorganic nitrogen deposition was 83.7 kg ha(-1) a(-1) in 2004 and 81.3 kg ha(-1) a(-1) in 2005, respectively. The dry deposition contributed 78.6% to total nitrogen deposition, in which ammonia was the predominant contributor that accounted for 86.1%. Reduced nitrogen compounds were the predominant contributors, accounting for 78.3% of total nitrogen deposition. The results suggested that atmospheric inorganic nitrogen could be attributed to intensive agricultural practices such as excessive nitrogen fertilization and livestock production. Therefore, impacts of atmospheric nitrogen originated from agriculture practices on nearby forest ecosystems should be evaluated.