Organophosphate Esters in Building Materials from China: Levels, Sources, Emissions, and Preliminary Assessment of Human Exposure.

Source characteristics and health risks of indoor organophosphate esters (OPEs) are limited by the lack of knowledge on emission processes. This study attempted to integrate the contents and emissions of OPEs from indoor building materials to assess human health effects. Thirteen OPEs were investigated in 80 pieces of six categories of building materials. OPEs are ubiquitous in the building materials and ∑13OPE contents varied significantly (p < 0.05) from 72.8 ng/g (seam agent) to 109,900 ng/g (wallpaper). Emission characteristics of OPEs from the building materials were examined based on a microchamber method. Depending on the sample category, the observed initial area-specific emission rates of ∑13OPEs varied from 154 ng/m2/h (carpet) to 2760 ng/m2/h (wooden floorboard). Moreover, the emission rate model was developed to predict the release levels of individual OPEs, quantify source contributions, and assess associated exposure risks. Source apportionments of indoor OPEs exhibited heterogeneities in multiple environmental media. The joint OPE contribution of wallpaper and wooden floorboard to indoor dust was up to 94.8%, while latex paint and wooden floorboard were the main OPE contributors to indoor air (54.2%) and surface (76.1%), respectively. Risk assessment showed that the carcinogenic risks of tris(2-chloroethyl) phosphate (3.35 × 10-7) were close to the acceptable level (1 × 10-6) and deserved special attention.

Indoor Emissions Contributed the Majority of Ultrafine Particles in Chinese Urban Residences.

Ultrafine particle (UFP) pollution should be controlled to reduce its effects on health. The design of control measures is limited owing to the uncertainty of source contributions in Chinese residences, where indoor UFP pollution is more severe than in Western residences. Herein, a source-specific, time-dependent UFP concentration model was developed by applying an infiltration factor model incorporating coagulation effects. A Monte Carlo framework with the UFP concentration model was employed to estimate the probabilistic distribution of source contributions in Chinese residences. The input parameter distributions were determined based on our survey and previous studies. The annually averaged indoor UFP concentration was estimated at (2.75 ± 1.71) × 104 #/cm3, ranging from 2.35 × 103 to 1.27 × 105 #/cm3 outside the kitchen, and at (5.48 ± 3.08) × 104 #/cm3, ranging from 2.90 × 103 to 1.94 × 105 #/cm3 in the kitchen. Indoor sources contributed more to indoor UFPs, accounting for 61% in the nonkitchen and 80% in the kitchen, surpassing their contribution to indoor PM2.5 in Chinese residences. Meanwhile, the indoor UFP emission contributions were higher than those in the United States, Canada, and Germany, owing to higher emissions from cooking and cigarette smoking. These results will aid in elucidating human exposure to UFPs and in designing more targeted control measures.

Characteristics of China's coal mine methane emission sources at national and provincial levels.

Methane (CH4) is the second most abundant greenhouse gas. China is the largest CH4 emitter in the world, with coal mine methane (CMM) being one of the main anthropogenic contributions. Thus, there is an urgent need for comprehensive estimates and strategies for reducing CMM emissions in China. However, the development of effective strategies is currently challenged by a lack of information on temporal variations in the contributions of different CMM sources and the absence of provincial spatial analysis. Here, considering five sources and utilization, we build a comprehensive inventory of China's CMM emissions from 1980 to 2022 and quantify the contributions of individual sources to the overall CMM emissions at the national and provincial levels. Our results highlight a significant shift in the source contributions of CMM emissions, with the largest contributor, underground mining, decreasing from 89% in 1980 to 69% in 2022. Underground abandoned coal mines, which were ignored or underestimated in past inventories, have become the second source of CMM emissions since 1999. From 2011 to 2022, we identified Shanxi, Guizhou, and Shaanxi as the three largest CMM-emitting provinces, while the Emissions Database for Global Atmospheric Research (EDGAR) v8 overestimated emissions from Inner Mongolia, ranking it third. Notably, we observed a substantial decrease (exceeding 1 Mt) in CMM emissions in Sichuan, Henan, Liaoning, and Hunan between 2011 and 2022, which was not captured by EDGAR v8. To develop targeted CMM emission reduction strategies at the provincial level, we classified 31 provinces into four groups based on their CMM emission structures. In 2022, the number of provinces with CMM emissions mainly from abandoned coal mines has exceeded that of provinces with mainly underground mines, which requires attention. This study reveals the characteristics of the source of CMM emissions in China and provides emission reduction directions for four groups of provinces.

Anthropogenic impacts and quantitative sources of nitrate in a rural-urban canal using a combined PMF, δ15N/δ18O-NO3-, and MixSIAR approach.

Nitrate (NO3-) pollution in irrigation canals is of great concern because it threatens canal water use; however, little is known about it at present. Herein, a combination of positive matrix factorization (PMF), isotope tracers, and Mixing Stable Isotope Analysis in R (MixSIAR) was developed to identify anthropogenic impacts and quantitative sources of NO3- in a rural-urban canal in China. The NO3- concentration (0.99-1.93 mg/L) of canal water increased along the flow direction and was higher than the internationally recognized eutrophication risk value in autumn and spring. The inputs of the Fuhe River, NH4+ fertilizer, soil nitrogen, manure & sewage, and rainfall were the main driving factors of canal water NO3- based on principal component analysis and PMF, which was supported by evidence from δ15N/δ18O-NO3-. According to the chemical and isotopic analyses, nitrogen transformation was weak, highlighting the potential of δ15N/δ18O-NO3- to trace NO3- sources in canal water. The MixSIAR and PMF results with a <15% divergence emphasized the predominance of the Fuhe River (contributing >50%) and anthropogenic impacts (NH4+ fertilizer plus manure & sewage, >37%) on NO3- in the entire canal, reflecting the effectiveness of the model analysis. According to the MixSIAR model, (1) higher NO3- concentration in canal water was caused by the general enhancement of human activities in spring and (2) NO3- source contributions were associated with land-use patterns. The high contributions of NH4+ fertilizer and manure & sewage showed inverse spatial variations, suggesting the necessity of reducing excessive fertilizer use in the agricultural area and controlling blind wastewater release in the urban area. These findings provide valuable insights into NO3- dynamics and fate for sustainable management of canal water resources. Nevertheless, long-term chemical and isotopic monitoring with alternative modeling should be strengthened for the accurate evaluation of canal NO3- pollution in future studies.

Characterization of spatial-temporal distribution and microenvironment source contribution of PM2.5 concentrations using a low-cost sensor network with artificial neural network/kriging techniques.

Low-cost sensors (LCS) network is widely used to improve the resolution of spatial-temporal distribution of air pollutant concentrations in urban areas. However, studies on air pollution sources contribution to the microenvironment, especially in industrial and mix-used housing areas, still need to be completed. This study investigated the spatial-temporal distribution and source contributions of PM2.5 in the urban area based on 6-month of the LCS network datasets. The Artificial Neural Network (ANN) was used to calibrate the measured PM2.5 by the LCS network. The calibrated PM2.5 were shown to agree with reference PM2.5 measured by the BAM-1020 with R2 of 0.85, MNE of 30.91%, and RMSE of 3.73 µg/m3, which meet the criteria for hotspot identification and personal exposure study purposes. The Kriging method was further used to establish the spatial-temporal distribution of PM2.5 concentrations in the urban area. Results showed that the highest average PM2.5 concentration occurred during autumn and winter due to monsoon and topographic effects. From a diurnal perspective, the highest level of PM2.5 concentration was observed during the daytime due to heavy traffic emissions and industrial production. Based on the present ANN-based microenvironment source contribution assessment model, temples, fried chicken shops, traffic emissions in shopping and residential zones, and industrial activities such as the mechanical manufacturing and precision metal machining were identified as the sources of PM2.5. The numerical algorithm coupled with the LCS network presented in this study is a practical framework for PM2.5 hotspots and source identification, aiding decision-makers in reducing atmospheric PM2.5 concentrations and formulating regional air pollution control strategies.

Identification of Factors Determining Household PM2.5 Variations at Regional Scale and Their Implications for Pollution Mitigation.

Indoor PM2.5, particulate matter no more than 2.5 µm in aerodynamic equivalent diameter, has very high spatiotemporal variabilities; and exploring the key factors influencing the variabilities is critical for purifying air and protecting human health. Here, we conducted a longer-term field monitoring campaign using low-cost sensors and evaluated inter- and intra-household PM2.5 variations in rural areas where energy or stove stacking is common. Household PM2.5 varied largely across different homes but also within households. Using generalized linear models and dominance analysis, we estimated that outdoor PM2.5 explained 19% of the intrahousehold variation in indoor daily PM2.5, whereas factors like the outdoor temperature and indoor-outdoor temperature difference that was associated with energy use directly or indirectly, explained 26% of the temporal variation. Inter-household variation was lower than intrahousehold variation. The inter-household variation was strongly associated with distinct internal sources, with energy-use-associated factors explaining 35% of the variation. The statistical source apportionment model estimated that solid fuel burning for heating contributed an average of 31%-55% of PM2.5 annually, whereas the contribution of sources originating from the outdoors was ≤10%. By replacing raw biomass or coal with biomass pellets in gasifier burners for heating, indoor PM2.5 could be significantly reduced and indoor temperature substantially increased, providing thermal comforts in addition to improved air quality.

Change of Composition, Source Contribution, and Oxidative Effects of Environmental PM2.5 in the Respiratory Tract.

Fine particulate matter is a leading air pollutant, and its composition profile relates to sources and health effects. The human respiratory tract hosts a warmer and more humid microenvironment in contrast with peripheral environments. However, how the human respiratory tract impacts the transformation of the composition of environmental PM2.5 once they are inhaled and consequently changes of source contribution and health effects are unknown. Here, we show that the respiratory tract can make these properties of PM2.5 reaching the lung different from environmental PM2.5. We found via an in vitro model that the warm and humid conditions drive the desorption of nitrate (about 60%) and ammonium (about 31%) out of PM2.5 during the inhalation process and consequently make source contribution profiles for respiratory tract-deposited PM2.5 different from that for environmental PM2.5 as suggested in 11 Chinese cities and 12 US cities. We also observed that oxidative potential, one of the main health risk causes of PM2.5, increases by 41% after PM2.5 travels through the respiratory tract model. Our results reveal that PM2.5 inhaled in the lung differs from environmental PM2.5. This work provides a starting point for more health-oriented source apportionment, physiology-based health evaluation, and cost-effective control of PM2.5 pollution.

Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region.

Fine particulate matter (PM2.5) exposure is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM2.5, and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM2.5-attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM2.5 (>95 µg/m3). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sectors in South Asia.

Transmission paths and source areas of near-surface ozone pollution in the Yangtze River delta region, China from 2015 to 2021.

Near-ground ozone in the Yangtze River Delta (YRD) region has become one of the main air pollutants that threaten the health of residents. However, to date, the transport behavior and source areas of ozone in the YRD region have not been systematically analyzed. In this study, by combining the ozone observational record with a HYSPLIT (hybrid single-particle Lagrangian integrated trajectory) model, we tried to reveal the spatiotemporal regularity of the airflow transport trajectory of ozone. Spatially, high ozone concentrations mainly clustered in industrial cities and resource-based cities. Temporally, the center of the ozone pollution shifted westward of Nanjing from 2015 to 2021. With the passage of time, the influence of meteorological elements on the ozone concentration in the YRD region gradually weakened. Marine atmosphere had the most significant impact on the transmission path of ozone in Shanghai, of which the trajectory frequency in 2021 accounted for 64.21% of the total frequency. The transmission trajectory of ozone in summer was different from that in other seasons, and its transmission trajectory was mainly composed of four medium-distance transmission paths: North China-Bohai Sea, East China Sea-West Pacific Ocean, Philippine Sea, and South China Sea-South China. The contribution source areas mainly shifted to the southeast, and the emission of pollutants from the Shandong Peninsula, the Korean Peninsula-Japan, and the Philippine Sea-Taiwan area increased the impact of ozone pollution in the Shanghai area from 2019 to 2021. This study identified the regional transport path of ozone in the YRD region and provided a scientific reference for the joint prevention and control of ozone pollution in this area.

Chemical composition, oxidative potential and identifying the sources of outdoor PM2.5 after the improvement of air quality in Beijing.

Air pollution poses a serious threat to human health. The implementation of air pollution prevention and control policies has gradually reduced the level of atmospheric fine particles in Beijing. Exploring the latest characteristics of PM2.5 has become the key to further improving pollution reduction measures. In the current study, outdoor PM2.5 samples were collected in the spring and summer of Beijing, and the chemical species, oxidative potential (OP), and sources of PM2.5 were characterized. The mean PM2.5 concentration during the entire study period was 41.6 ± 30.9 µg m-3. Although the PM2.5 level in summer was lower, its OP level was significantly higher than that in spring. SO42-, NH4+, EC, NO3-, and OC correlated well with volume-normalized OP (OPv). Strong positive correlations were found between OPv and the following elements: Cu, Pb, Zn, Ni, As, Cr, Sn, Cd, Al, and Mn. Seven sources of PM2.5 were identified, including traffic, soil dust, secondary sulfate, coal and biomass burning, oil combustion, secondary nitrate, and industry. Multiple regression analysis indicated that coal and biomass combustion, industry, and traffic were the main contributors to the OPv in spring, while secondary sulfate, oil combustion, and industry played a leading role in summer. The source region analysis revealed that different pollution sources were related to specific geographic distributions. In addition to local emission reduction policies, multi-provincial cooperation is necessary to further improve Beijing's air quality and reduce the adverse health effects of PM2.5.

Pollution source identification of nitrogen and phosphorus in the lower West Main Canal, the Ganfu Plain irrigation district (South China).

The degradation of surface water quality has been a widespread concern around the world. However, irrigation canal water does not attract much attention although it is important to agriculture and population. In this study, a 5-year water quality monitoring of surface water was conducted in the lower West Main Canal of the Ganfu Plain irrigation district to identify the levels and pollution sources of nitrogen and phosphorus.Over 75% of samples had total phosphorus (TP) concentrations of > 0.02 mg/L, and all samples had total nitrogen (TN) concentrations of > 0.2 mg/L, indicating a risk of eutrophication. The concentrations of NO3--N and NH4+-N averagely occupied 57% and 18% of TN, respectively. PCA analysis showed that phosphorus and nitrogen in canal water were associated with meteorological factors, urban life and surface runoff, agricultural cultivation, livestock-poultry breeding, and water-sediment interaction in the wet season, whereas they were affected by meteorological factors, industrial effluent, urban domestic sewage, and livestock-poultry breeding in the dry season. Absolute principal component score-multiple linear regression (APCS-MLR) model results revealed that (1) agricultural cultivation plus livestock-poultry breeding contributed 43.2% of TP in canal water in the wet season, while livestock-poultry breeding contributed 52.9% in the dry season, and (2) domestic sewage plus surface runoff contributed 29.4% of TN in the wet season, while livestock-poultry breeding contributed 45.9% in the dry season. The unidentified sources had significant contributions of > 20% for almost all variables. So further investigations are required for determining unidentified sources, and anthropogenic pollution control is imperative for canal water quality protection.

Traces of black carbon sources before and after the Covid-19 outbreak in Tehran, Iran.

The concentration of black carbon was measured in four sites of the industrial and high-traffic metropolis of Tehran with different land uses. Then, the contribution of biomass and fossil fuels in the emission of this pollutant was modeled using the Aethalometer model. The possible locations of important sources of black carbon dissemination were projected using PSCF and CWT models, and the results were compared in the two periods before and after the Covid-19 outbreak. Temporal variations of black carbon illustrated that BC concentration decreased in the period after the onset of the pandemic in all studied areas, and this decline was more explicit in the traffic intersection of the city. Diurnal changes of BC concentration indicated the significant impact of the application of the law banning night traffic of motor vehicles in reducing the BC concentration in this period, and probably the reduction of HDDV traffic has played the most important role in this reduction. The results related to the share of BC sources indicated that black carbon emissions are affected by an average of about 80% of fossil fuel combustion and wood combustion interferes with about 20% of BC emissions. Finally, speculations were made about the possible sources of BC emission and its urban scale transport using PSCF and CWT models, which indicated the superiority of the CWT model in terms of source segregation. The results of this analysis were further utilized to surmise black carbon emission sources based on the land use of receptor points.

Observation on the aerosol and ozone precursors in suburban areas of Shenzhen and analysis of potential source based on MAX-DOAS.

Long-term stereoscopic observations of aerosol, NO2, and HCHO were carried out at the Yangmeikeng (YMK) site in Shenzhen. Aerosol optical depths and NO2 vertical column concentration (NO2 VCD) derived from MAX-DOAS were found to be consistent with other datasets. The total NO2 VCD values of the site remained low, varying from 2 × 1015 to 8 × 1015 mol/cm2, while the HCHO VCD was higher than NO2 VCD, varying from 7 × 1015 to 11 × 1015 mol/cm2. HCHO VCD was higher from September to early November than that was from mid-late November to December and during February 2021, in contrast, NO2 VCD did not change much during the same period. In January, NO2 VCD and HCHO VCD were both fluctuating drastically. High temperature and HCHO level in the YMK site is not only driving the ozone production up but also may be driving up the ozone concentration as well, and the O3 production regime in the YMK site tends to be NOx-limited. At various altitudes, backward trajectory clustering analysis and Potential Source Contribution Function (PSCF) were utilized to identify possible NO2 and HCHO source locations. The results suggested that the Huizhou-Shanwei border and the Daya Bay Sea area were the key potential source locations in the lower (200 m) and middle (500 m) atmosphere (WPSCF > 0.6). The WPSCF value was high at the 1000 m altitude which was closer to the YMK site than the near ground, indicating that the pollution transport capability in the upper atmosphere was limited.

Spatial characteristics of VOCs and their ozone and secondary organic aerosol formation potentials in autumn and winter in the Guanzhong Plain, China.

As critical precursors of tropospheric ozone (O3) and secondary organic aerosol (SOA), volatile organic compounds (VOCs) largely influence air quality in urban environments. In this study, measurements of 102 VOCs at all five major cities in the Guanzhong Plain (GZP) were conducted during Sep.09-Oct. 13, 2017 (autumn) and Nov. 14, 2017-Jan. 19, 2018 (winter) to investigate the characteristics of VOCs and their roles in O3 and SOA formation. The average concentrations of total VOCs (TVOCs) at Xi'an (XA), Weinan (WN), Xianyang (XY), Tongchuan (TC), and Baoji (BJ) sites were in the range of 55.2-110.2 ppbv in autumn and 42.4-74.3 ppbv in winter. TVOCs concentrations were reduced by 22.4%-43.5% from autumn to winter at XA, WN and BJ. Comparatively low concentrations of TVOCs were observed in XY and TC, ranging from 53.5 to 62.7 ppbv across the sampling period. Alkanes were the major components at all sites, accounting for 26.4%-48.9% of the TVOCs during the sampling campaign, followed by aromatics (4.2%-26.4%). The average concentration of acetylene increased by a factor of up to 4.8 from autumn to winter, indicating the fuel combustion in winter heating period significantly impacted on VOCs composition in the GZP. The OH radical loss rate and maximum incremental reactivity method were employed to determine photochemical reactivities and ozone formation potentials (OFPs) of VOCs, respectively. The VOCs in XA and WN exhibited the highest reactivities in O3 formation, with the OFP of 168-273 ppbv and the OH loss rates of 19.3-40.8 s-1. Alkenes and aromatics primarily related to on-road and industrial emissions contributed 57.8%-76.3% to the total OFP. The contribution of aromatics to the SOA formation at all sites reached 94.1%-98.6%. Considering the potential source-area of VOCs, regional transport of VOCs occurred within the GZP cities.

Particle composition, sources and evolution during the COVID-19 lockdown period in Chengdu, southwest China: Insights from single particle aerosol mass spectrometer data.

In order to investigate the effects of the Coronavirus Disease 2019 (COVID-19) lockdown on air quality in cities in southwest China, a single particle aerosol mass spectrometer (SPAMS) and other online equipments were used to measure the air pollution in Chengdu, one of the megacities in this area, before and during the lockdown period. It was found that the concentrations of fine particulate matter (PM2.5), nitric oxide (NO), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO) decreased by 38.6%, 77.5%, 47.0%, 35.1% and 14.1%, respectively, while the concentration of ozone (O3) increased by 57.5% from the time before to the time during lockdown. All particles collected during the study period could be divided into eight categories: biomass burning (BB), coal combustion (CC), vehicle emissions (VE), cooking emissions (CE), Dust, K-nitrate (K-NO3), K-sulfate (K-SO4) and K-sulfate-nitrate (K-SN) particles, and their contributions changed significantly after the beginning of lockdown. Compared to before lockdown, the contribution of VE particles experienced the largest reduction (by 14.9%), whereas the contributions of BB and CE particles increased by 7.0% and 7.3%, respectively, during the lockdown period. Regional transmission was critical for pollution formation before lockdown, whereas the pollution that occurred during the lockdown period was caused mainly by locally emitted particles (such as VE, CE and BB particles). Weighted potential source contribution function (WPSCF) analysis further verified and emphasized the difference in the contribution of regional transmission for pollution formation before and during lockdown. In addition, the potential source area and intensity of the particles emitted from different sources or formation mechanisms were quite different.

Relative contribution of multi-source water recharge to riparian wetlands along the lower Yellow River.

Rivers play a vital role in both the formation and maintenance of riparian wetland hydrology. However, few studies have focused on the response of water recharge of riparian wetlands to altered hydrological processes induced by water-sediment regulation practices. To fill this gap, our study investigated the contribution of multi-source water recharge of riparian wetlands in the lower Yellow River, as well as its influence both during and before the water-sediment regulation scheme of Xiaolangdi Dam. Our study is based on hydrochemistry and isotopic methods, using a Bayesian mixing model and artificial neutral network model. The results showed that riparian wetlands were fed by mixed sources, including groundwater, canals, the Yellow River, and precipitation. However, seasonal evaporation introduced additional variation, which affected the relative contribution of these sources across seasons. Among these sources, the Yellow River served as the main water source for recharging riparian wetlands, and its contribution varied both spatially and temporally (across seasons). Specifically, proximity of riparian wetlands was the primary factor explaining spatial variation in the contribution of Yellow River, while climatic (12.38%) and hydrological variabilities (87.62%) explained seasonal variation. Among these climatic and hydrological variables, suspended sediment content was the most important factor-with a relative contribution of 36.33%. By determining the contribution of the Yellow River to the recharge of riparian wetlands, our study has provided information which is beneficial to adaptive management of river-fed riparian wetlands, especially under the implementation of water-sediment regulation practices.

Atmospheric Vanadium Emission Inventory from Both Anthropogenic and Natural Sources in China.

Vanadium is a strategically important metal in the world, although sustained exposure under high vanadium levels may lead to notable adverse impact on health. Here, we leverage a bottom-up approach to quantitatively evaluate vanadium emissions from both anthropogenic and natural sources during 1949-2017 in China for the first time. The results show that vanadium emissions increased by 86% from 1949 to 2005 to a historical peak value and then gradually decreased to 12.9 kt in 2017. With the effective implementation of air pollution control measures, vanadium emissions from anthropogenic sources decreased sharply after 2011. During 2011-2017, about half of vanadium emissions came from coal and oil combustion. In addition, industrial processes and natural sources also cannot be ignored, with the total contributions of more than 24%. The high levels of vanadium emissions were mainly distributed throughout the North China Plain and the eastern and coastal regions, especially in several urban agglomerations. Furthermore, the comprehensive evaluation by incorporating contrastive analysis, Monte Carlo approach, and GEOS-Chem simulation shows that vanadium emissions estimated in this study were reasonable and acceptable. The findings of our study provide not only a scientific foundation for investigating the health effects of vanadium but also useful information for formulating mitigation strategies.

Particle number emission rates of aerosol sources in 40 German households and their contributions to ultrafine and fine particle exposure.

More representative data on source-specific particle number emission rates and associated exposure in European households are needed. In this study, indoor and outdoor particle number size distributions (10-800 nm) were measured in 40 German households under real-use conditions in over 500 days. Particle number emission rates were derived for around 800 reported indoor source events. The highest emission rate was caused by burning candles (5.3 × 1013  h-1 ). Data were analyzed by the single-parameter approach (SPA) and the indoor aerosol dynamics model approach (IAM). Due to the consideration of particle deposition, coagulation, and time-dependent ventilation rates, the emission rates of the IAM approach were about twice as high as those of the SPA. Correction factors are proposed to convert the emission rates obtained from the SPA approach into more realistic values. Overall, indoor sources contributed ~ 56% of the daily-integrated particle number exposure in households under study. Burning candles and opening the window leads to seasonal differences in the contributions of indoor sources to residential exposure (70% and 40% in the cold and warm season, respectively). Application of the IAM approach allowed to attribute the contributions of outdoor particles to the penetration through building shell and entry through open windows (26% and 15%, respectively).

Persistent pollution episodes, transport pathways, and potential sources of air pollution during the heating season of 2016-2017 in Lanzhou, China.

As one of the most important industrial cities in Northwest China, Lanzhou currently suffers from serious air pollution. This study analyzed the formation mechanism and potential source areas of persistent air pollution in Lanzhou during the heating period from November 1, 2016 to March 31, 2017 based on the air pollutant concentrations and relevant meteorological data. Our findings indicate that particulate pollution was extremely severe during the study period. The daily PM2.5 and PM10 concentrations had significantly negative correlations with daily temperature, wind speed, maximum daily boundary layer height, while the daily PM2.5 and PM10 concentrations showed significantly positive correlations with daily relative humidity. Five persistent pollution episodes were identified and classified as either stagnant accumulation or explosive growth types according to the mechanism of pollution formation and evolution. The PM2.5 and PM10 concentrations and PM2.5/PM10 ratio followed a growing "saw-tooth cycle" pattern during the stagnant accumulation type event. Dust storms caused abrupt peaks in PM10 and a sharp decrease in the PM2.5/PM10 ratio in explosive growth type events. The potential sources of PM10 were mainly distributed in the Kumtag Desert in Xinjiang Uygur Autonomous Region, the Qaidam Basin and Hehuang Valley in Qinghai Province, and the western and eastern Hexi Corridor in Gansu Province. The contributions to PM10 were more than 120 µg/m3. The important potential sources of PM2.5 were located in Hehuang Valley in Qinghai and Linxia Hui Autonomous Prefecture in Gansu; the concentrations of PM2.5 were more than 60 µg/m3.

Preliminary copper isotope study on particulate matter in Zhujiang River, southwest China: Application for source identification.

Copper (Cu) is not only an essential metallic element for human and organisms, but also a toxic and pernicious element when its environmental content exceeds a certain threshold. However, to date, little is known about the isotopic compositions and sources of Cu in the suspended particulate matter (SPM) of fluvial ecosystems. To identify the potential sources of Cu in SPM in Zhujiang River (an important river in southwestern China with about 30 million people in the entire basin), we reported the Cu contents of SPM and the Cu isotopic compositions (expressed in δ65Cu) at 22 sites. The relative contribution rates of potential sources were also calculated based on the mixing model. The results indicate that the Cu contents varied from 14 mg kg-1 to 96 mg kg-1 with a relatively low enrichment factor (EF) value (mean value is 1.6). The amount of Cu transferred as suspended loads ranged from 5% to 98% (mean value 60%) in the sampling period. The EF and δ65Cu suggest a ternary mixture of fluvial SPM with the δ65Cu value fluctuating from 0.04‰ to 0.50‰ (mean value 0.17‰). Based on isotope ratios and mass balance equation, we calculate that the rock weathering contributes 76.4% particulate Cu in Zhujiang River, and the contributions of urban sludge and smelting tailings are 15.4% and 8.2%, respectively. These findings regarding to the application of Cu isotope have significant implications for tracing the Cu sources, which significantly supports the control and management of suspended particulate copper pollution in large rivers.