Source apportionment and a novel approach of estimating regional contributions to ambient PM2.5 in Haikou, China

Temporal variations and chemical characteristics of marine PM2.5 at Dongsha Islands, South China Sea: Three-year measurement

The study of long-range transport effects on marine fine particles (PM2.5), particularly in remote sites such as the Dongsha Islands, is pivotal for advancing our understanding of air pollution dynamics on a regional scale and for formulating effective environmental policies. PM2.5 concentrations were examined over three consecutive years and grouped based on their transport routes. The backward trajectory simulation revealed that high PM2.5 concentrations were observed in the West Channel, originating from North and Central China, the Korean Peninsula, and the Japanese Islands, opposed to the East Channel. High PM2.5 concentrations, commonly observed in winter and spring, were mainly attributed to the Asian Northeastern Monsoons. Water-soluble inorganic ions constituted the major components, accounting for 37.8-48.7% of PM2.5, and followed by metal elements (15.5-20.0%), carbons (7.5-13.3%), levoglucosan (0.01-0.17%), and organic aerosols (0.2-2.2%). Secondary inorganic aerosols as the dominant source accounted for 8.3-24.7% of PM2.5, while sea salts were the secondary major contributor. High levoglucosan contribution (3.8-7.2%) in winter and spring was attributed to biomass burning, mainly from the Indochina Peninsula. Chemical mass balance receptor modeling resolved that major sources of PM2.5 were secondary sulfate, sea salts, fugitive dust, and industrial boilers. This study concluded that the long-range transport of PM2.5 gradually increased since fall, contributing 52.1-74.3%, highlighting its substantial impact on PM2.5 in all seasons except summer.

Spatial characteristics of fine particulate matter in subway stations: Source apportionment and health risks

Air in subway stations is typically more polluted than ambient air, and particulate matter concentrations and compositions can vary greatly by location, even within a subway station. However, it is not known how the sources of particulate matter vary between different areas within subway stations, and source-specific health risks in subway stations are unclear. We analyzed the spatial characteristics of particulate matter by source and calculated source-specific health risks on subway platforms and concourses and in station offices by integrating source apportionment with health risk assessments. A total of 182 samples were collected in three areas in six subway stations in Nanjing, China. Enrichment factors and the positive matrix factorization receptor model were used to identify major sources. The carcinogenic and non-carcinogenic health risks to subway workers and passengers were evaluated to determine control priorities. Seven sources of particulate matter were identified in each area, with a total of four subway sources and six outdoor sources over all the areas. The source contributions to total element mass differed significantly from the source contributions to human health risks. Overall, subway sources contributed 48% of total element mass in the station office and 75% and 60% on the concourse and platform, respectively. Subway-derived sources accounted for 54%, 81%, and 71% of non-carcinogenic health risks on station platforms, concourses, and office areas, respectively. The corresponding values for carcinogenic risks were 51%, 86%, and 86%. Among the elements, cobalt had the largest contributions to carcinogenic and non-carcinogenic risks, followed by manganese for non-carcinogenic risks and hexavalent chromium for carcinogenic risks. Reducing emissions from subway sources could effectively protect the health of subway workers and passengers.

Trends and Challenges Regarding the Source-Specific Health Risk of PM2.5-Bound Metals in a Chinese Megacity from 2014 to 2020

Identifying the health risk of PM_2.5 is essential for urban air pollution control. In 2013, China announced the ever-strict national Air Pollution Prevention and Control Action Plan, and its health benefit should be evaluated to provide reference for future policymaking. In this study, we conducted a seven-year (2014-2020) continuous observation of PM_2.5 in Shenzhen, the third largest city in China, which has relatively good air quality. The results showed that the annual mean PM_2.5 and total concentration of 21 associated metals dropped from 37.7 to 18.5 μg/m³ and from 2.4 to 1.1 μg/m³, respectively. Combining methods for source apportionment and health risk assessment, we found that the total carcinogenic risk (CR) of five hazardous metals (Cd, Cr, Ni, Co, and Pb) showed a clear decreasing trend. However, the total CR (1.8 × 10^-6) in 2020 still exceeded the widely acceptable risk level (i.e., 1 × 10^-6), with the primary contributor changing from industrial emissions (61%) to vehicle emissions (63%). Further analysis indicated that the CR of vehicles mainly came from Cr and Ni released by braking and tire wearing and has fluctuated in recent years, highlighting a great challenge of controlling nonexhaust emissions of vehicles (including electric cars) in the future.

Source apportionment of PM2.5 during different haze episodes by PMF and random forest method based on hourly measured atmospheric pollutant

Hourly measured PM2.5-bound species, gases, and meteorological data were analyzed by the PMF receptor model to quantify source contributions, and by the random forest to estimate decisive factors of variations of PM2.5, sulfur oxidation ratio (SOR), and nitrogen oxidation ratio (NOR) during different haze episodes. PM2.5 variation was influenced by CO (17%), SO2 (19%), NH3 (12%), O3 (10%), air pressure (P, 9.9%), and temperature (T, 10%) during the whole period. SOR was determined by SO2 (15%), temperature (T, 9.8%), relative humidity (RHU, 15%), and pondus hydrogenii (pH, 35%), and NOR was influenced by NOx (19%), O3 (14%), NH3 (13%), and RHU (15%). Three types of pollution episodes were captured. Process I was characterized by high CO (contributing 40% of PM2.5 concentration variation estimated by the random forest) due to coal combustion for heating during winter in northern China. According to the PMF, coal combustion (32%) and secondary sources (38%) were both the most important contributors in the first stage, and then, when the RHU increased to above 80%, the highest contribution was from secondary sources (40%). Process II was during the Spring Festival and was characterized by 8.8 μg m-3 firework contribution. High SO2 during this process, especially on the CNY's Eve, was observed due to the firework displays, and SO2 gave a high contribution (24%) to PM2.5 variation. Process III showed high ions and high RHU in summer with sulfate and nitrate contributing 44% and 22%, respectively. Furthermore, meteorological parameters and NH3 play a key role on SOR and NOR.

Improving apportionment of PM2.5 using multisite PMF by constraining G-values with a priori information

Rotational ambiguity in factor analyses prevents users from obtaining accurate source apportionment results. The rotational space in positive matrix factorization (PMF) can be reduced by constraining the solution with a prioriinformation such as source profiles. However, the only prior report on constraints using information on the source contributions was their use to ensure compatibility in the simultaneous analyses of PM_2.5 and PM₁₀ data. By combining data from three monitoring sites affected by a gear casting plant in Xi'an as an example, a methodology for improving the accuracy of PMF results by constraining source contributions using wind information was explored. Seven common factors derived from individual PMF analyses for each of the three sites (INDUS, URBAN, and RURAL) with different location characteristics, were then combined in a multisite PMF analysis. The factors were interpreted as nitrate with all site average contributions of 28.7%, sulfate (22.5%), coal combustion (19.3%), road traffic (12.8%), biomass burning (6.4%), soil (5.4%), and metallurgical industry (4.9%). Except for the INDUS site, contributions of metallurgical industry to the URBAN and RURAL sites were pulled down maximally to reduce the rotational space. The constrained solution substantially improved the results over the base run. The local and regional nature of the sources were identified by coefficient of divergence combined with Pearson correlation analysis, and further quantitatively estimated using Lenschow approach. On average, local sources contributed for 52.4% and 47.7% of the PM_2.5 mass concentrations at the INDUS and URBAN site respectively. The metallurgical industry showed the highest local contributions while sulfate was primarily regional. For the multisite analysis where there are considerable point source emissions, this methodology highlights the role of local wind directions to inform constraints on the results and obtaining more reliable solutions.

Research Progress of HP Characteristics, Hazards, Control Technologies, and Measures in China after 2013

In recent years, hazy weather (hazy weather (HW) has frequently invaded peoples’ lives in China, resulting in the disturbance of social operation, so it is urgent to resolve the haze pollution (HP) problem. A comprehensive understanding of HP is essential to further effectively alleviate or even eliminate it. In this study, HP characteristics in China, after 2013, were presented. It was found that the situation of HP is getting better year by year while it has been a pattern of high levels in the north and low levels in the south. In most regions of China, the contribution of a secondary source for HP is relatively large, and that of traffic is greater in the regions with rapid economic development. Hazards of HP were then summarized. Not only does HP cause harm to human health, but it also has effects on human production and quality of life, furthermore, property and atmospheric environment cannot be ignored. Next, the source and non-source control technologies of HP were first reviewed to recognize the weakness of HP control in China. This review provides more systematic information about HP problems and the future development directions of HP research were proposed to further effectively control HP in China.

Potential factors and mechanism of particulate matters explosive increase induced by free radicals oxidation

Atmospheric particulate pollution in China has attracted much public attention. Occasionally, the particle number concentration increases sharply in a short time period, which is defined as a "particulate matter explosive increase". Heavy particulate matter pollution not only reduces visibility but also has an adverse effect on human health. Hence, there is an urgent need to discover the causes of particulate matter explosive increase. During this campaign, the particle number concentration and free radicals were measured at a tall building on the campus of Lanzhou University of Technology. Additionally, we examined a series of chemicals to reproduce the observed particulate matter explosive increase in a smog chamber to determine its potential factors. Then, we analyzed the mechanism of particulate matter explosive increase in the presence of free radicals. We found that, among the potential inorganic and organic sources analyzed, a mixture of organic and SO₂ in the research region had a major effect on particulate matter explosive increase. Moreover, free radical oxidation has a large effect, especially in the formation of organic particulates.

Seasonal trends in the composition and sources of PM2.5 and carbonaceous aerosol in Tehran, Iran

Currently PM_2.5 is a major air pollution concern in Tehran, Iran due to frequent high levels and possible adverse impacts. In this study, which is the first of its kind to take place in Tehran, composition and sources of PM_2.5 and carbonaceous aerosol were determined, and their seasonal trends were studied. In this regard, fine PM samples were collected every six days at a residential station for one year and the chemical constituents including organic marker species, metals, and ions were analyzed by chemical analysis. The source apportionment was performed using organic molecular marker-based CMB receptor modeling. Carbonaceous compounds were the major contributors to fine particulate mass in Tehran, as OC and EC together comprised on average 29% of PM_2.5 mass. Major portions of OC in Tehran were water insoluble and are mainly attributed to primary sources. Higher levels of several PAHs, which are organic tracers of incomplete combustion, and hopanes and steranes as organic tracers of mobile sources were obtained in cold months and compared to the warm months. The major contributing source to particulate OC was identified as vehicles, which contributed about 72% of measured OC. Among mobile sources, gasoline-fueled vehicles had the highest impact with a mean contribution of 48% to the measured OC. Mobile sources also were the largest contributor to total PM_2.5 (40%), followed by dust (24%) and sulfate (11%). In addition to primary emissions, mobile sources also directly and indirectly played an important role in another 27% of fine particulate mass (secondary organics and ions), which highlights the impact of vehicles in Tehran. Our results highlighted and quantified the role of motor vehicles in fine PM production, particularly during winter time. The results of this study could be used to set more effective regulations and control strategies particularly upon mobile sources.

Source profiles and contributions of biofuel combustion for PM2.5, PM10 and their compositions, in a city influenced by biofuel stoves

Source and ambient samples were collected in a city in China that uses considerable biofuel, to assess influence of biofuel combustion and other sources on particulate matter (PM). Profiles and size distribution of biofuel combustion were investigated. Higher levels in source profiles, a significant increase in heavy-biomass ambient and stronger correlations of K⁺, Cl^-, OC and EC suggest that they can be tracers of biofuel combustion. And char-EC/soot-EC (8.5 for PM_2.5 and 15.8 for PM₁₀ of source samples) can also be used to distinguish it. In source samples, water-soluble organic carbon (WSOC) were approximately 28.0%-68.8% (PM_2.5) and 27.2%-43.8% (PM₁₀) of OC. For size distribution, biofuel combustion mainly produces smaller particles. OC1, OC2, EC1 and EC2 abundances showed two peaks with one below 1 μm and one above 2 μm. An advanced three-way factory analysis model was applied to quantify source contributions to ambient PM_2.5 and PM₁₀. Higher contributions of coal combustion, vehicular emission, nitrate and biofuel combustion occurred during the heavy-biomass period, and higher contributions of sulfate and crustal dust were observed during the light-biomass period. Mass and percentage contributions of biofuel combustion were significantly higher in heavy-biomass period. The biofuel combustion attributed above 45% of K⁺ and Cl^-, above 30% of EC and about 20% of OC. In addition, through analysis of source profiles and contributions, they were consistently evident that biofuel combustion and crustal dust contributed more to cation than to anion, while sulfate & SOC and nitrate showed stronger influence on anion than on cation.