Traffic source–dominated volatile organic compound (VOC) samples were collected during four time-intervals in a day (Ⅰ: 7:30–10:30, Ⅱ: 11:00–14:00, Ⅲ: 16:30–19:30, and Ⅳ: 20:00–23:00) in a tunnel in summer, 2019, in Xi’an, China. The total measured VOC (TVOC) in periods Ⅰ and Ⅲ (rush hours, 107.2 ± 8.2 parts per billion by volume [ppbv]) was 1.8 times that in periods Ⅱ and Ⅳ (non-rush hours, 58.6 ± 13.8 ppbv), consistent with the variation in vehicle numbers in the tunnel. The considerably elevated ethane and ethylbenzene levels could have been attributed to emissions from compressed natural gas vehicles and the rapid development of methanol-fueled taxis in Xi’an in 2019. The mixing ratios of benzene, toluene, ethylbenzene, and xylenes (BTEX) contributed 9.4%–12.7% to TVOCs, and the contributions were nearly 40% higher in periods Ⅰ and Ⅲ than in Ⅱ and Ⅳ, indicating that BTEX levels were strongly affected by vehicle emissions. The indicators of motor vehicle emission, namely ethylene, propylene, toluene, m/p-xylenes, o-xylene, and propane, contributed to more than half of the ozone formation potential in this study. The noncarcinogenic risks of VOCs in this study were within the international safety standard, whereas the carcinogenic risks exceeded the standard by 2.3–4.6 times, suggesting that carcinogenic risks were more serious than noncarcinogenic risks. VOCs presented 2.2 and 1.4 times noncarcinogenic and carcinogenic risks during rush hours than during non-rush hours, respectively. Notably, the carcinogenic risk in period Ⅳ was comparable with that in period Ⅲ; however, the vehicle numbers and VOC mixing ratios were the lowest at night, which may have attributed to the increasing number and proportion of methanol M100-fueled vehicles in the tunnel. Therefore, VOCs emitted by new energy vehicles should also be seriously considered while evaluating fossil fuel vehicle emissions.

The spatial distributions, fluxes, and environmental effects of non-methane hydrocarbons (NMHCs) were investigated in the Yellow Sea (YS) and the East China Sea (ECS) in spring. The average concentrations of ethane, propane, i-/n-butane, ethylene, propylene and isoprene in the seawater were 18.1 ± 6.4, 15.4 ± 4.7, 6.8 ± 2.9, 6.4 ± 3.2, 67.1 ± 26.7, 20.5 ± 8.7 and 17.1 ± 11.1 pmol L⁻¹, respectively. The alkenes in the surface seawater were more abundant than their saturated homologs and NMHCs concentrations (with the exception of isoprene) decreased with carbon number. The spatial variations of isoprene were consistent with the distributions of chlorophyll a (Chl-a) and Chaetoceros, Skeletonema, Nitzschia mainly contributed to the production of isoprene, while the others’ distributions might be related to their photochemical production. Observations in atmospheric NMHCs indicated alkanes in the marine atmosphere decreased from inshore to offshore due to influence of the continental emissions, while alkenes were largely derived from the oceanic source. In addition, no apparent diurnal discrepancy of atmospheric NMHCs (except for isoprene) were found between daytime and night. As the main sink of NMHCs in seawater, the average sea-to-air fluxes of ethane, propane, i-/n-butane, ethylene and propylene were 31.70, 29.75, 18.49, 15.89, 239.6, 67.94 and 52.41 nmol m⁻² d⁻¹, respectively. The average annual emissions of isoprene accounted for 0.1–1.3% of the global ocean emissions, which indicated that the coastal and shelf areas might be significant sources of isoprene. Furthermore, this study represents the first effort to estimate the environmental effects caused by NMHCs over the YS and the ECS and the results demonstrated contributions of alkanes to ozone and secondary organic aerosol (SOA) formation were lower than those of the alkenes and the largest contributor was isoprene.

Food carts are common along streets in cities throughout the world. In North America, food cart vendors generally use propane, charcoal, or both propane and charcoal (P and C) for food preparation. Although cooking emissions are known to be a major source of indoor air pollution, there is limited knowledge on outdoor cooking’s impact on the ambient environment and, in particular, the relative contribution of the different cooking fuels. This field study investigated the air pollution the public is exposed to in the micro-environment around 19 food carts classified into 3 groups: propane, charcoal, and P and C carts. Concentrations near the food carts were measured using both real-time and filter-based methods. Mean real-time concentrations of PM₂.₅, BC₂.₅, and particle counts were highest near the charcoal food carts: 196 μg/m³, 5.49 μg/m³, and 69,000 particles/cm³, respectively, with peak exposures of 1520 μg/m³, 67.9 μg/m³, and 235,000 particles/cm³, respectively. In order of pollution emission impacts: charcoal > P and C > propane carts. Thus, significant differences in air pollution emissions occurred in the vicinity of mobile food carts, depending on the fuel used in food preparation. Local air pollution polices should consider these emission factors in regulating food cart vendor operations.

This is the first study to characterize the variation and emission of C₂-C₅ non-methane volatile organic compounds (NMVOCs) in a semi-urban site of western India based on measurements during February–December 2015. Anthropogenic NMVOCs show clear seasonal dependence with highest in winter and lowest in monsoon season. Biogenic NMVOCs likes isoprene show highest mixing ratios in the pre-monsoon season. The diurnal variation of NMVOC species can be described by elevated values from night till morning and lower values in the afternoon hours. The elevated levels of NMVOCs during night and early morning hours were caused mainly by weaker winds, temperature inversion and reduced chemical loss. The correlations between NMVOCs, CO and NOx indicate the dominant role of various local emission sources. Use and leakage of liquefied petroleum gas (LPG) contributed to the elevated levels of propane and butanes. Mixing ratios of ethylene, propylene, CO, NOx, etc. show predominant emissions from combustion of fuels in automobiles and industries. The Positive Matrix Factorization (PMF) source apportionments were performed for the seven major emission sectors (i.e. Vehicular exhaust, Mixed industrial emissions, Biomass/Fired brick kilns/Bio-fuel, Petrochem, LPG, Gas evaporation, Biogenic). Emissions from vehicle exhaust and industry-related sources contributed to about 19% and 40% of the NMVOCs, respectively. And the rest (41%) was attributed to the emissions from biogenic sources, LPG, gasoline evaporation and biomass burning. Diurnal and seasonal variations of NMVOCs were controlled by local emissions, meteorology, OH concentrations, long-range transport and planetary boundary layer height. This study provides a good reference for framing environmental policies to improve the air quality in western region of India.

This study aimed to apply an inverse-dispersion calculation method (IDM) to estimate the emission rate of volatile organic compounds (VOCs) for the complicated industrial area sources, through a case study on a petroleum refinery in Northern China. The IDM was composed of on-site monitoring of ambient VOCs concentrations and meteorological parameters around the source, calculation of the relationship coefficient γ between the source's emission rate and the ambient VOCs concentration by the ISC3 model, and estimation of the actual VOCs emission rate from the source. Targeting the studied refinery, 10 tests and 8 tests were respectively conducted in March and in June of 2014. The monitoring showed large differences in VOCs concentrations between background and downwind receptors, reaching 59.7 ppbv in March and 248.6 ppbv in June, on average. The VOCs increases at receptors mainly consisted of ethane (3.1%–22.6%), propane (3.8%–11.3%), isobutane (8.5%–10.2%), n-butane (9.9%–13.2%), isopentane (6.1%–12.9%), n-pentane (5.1%–9.7%), propylene (6.1–11.1%) and 1-butylene (1.6%–5.4%). The chemical composition of the VOCs increases in this field monitoring was similar to that of VOCs emissions from China's refineries reported, which revealed that the ambient VOCs increases were predominantly contributed by this refinery. So, we used the ISC3 model to create the relationship coefficient γ for each receptor of each test. In result, the monthly VOCs emissions from this refinery were calculated to be 183.5 ± 89.0 ton in March and 538.3 ± 281.0 ton in June. The estimate in June was greatly higher than in March, chiefly because the higher environmental temperature in summer produced more VOCs emissions from evaporation and fugitive process of the refinery. Finally, the VOCs emission factors (g VOCs/kg crude oil refined) of 0.73 ± 0.34 (in March) and 2.15 ± 1.12 (in June) were deduced for this refinery, being in the same order with previous direct-measurement results (1.08–2.65 g VOCs/kg crude oil refined).An inverse-dispersion calculation method was applied to estimate VOCs emission rate for a petroleum refinery, being 183.5 ton/month (March) and 538.3 ton/month (June).

A few studies on volatile organic compound (VOC) emission inventories in coal resource-based cities have been reported, and previous emission inventories lacked verification. Herein, using Yangquan as a case study, emission factor (EF) method and “(tracer ratio) TR - positive matrix factorization (PMF)” combined method based on atmospheric data were used to establish and verify the VOC emission inventory in coal resource-based cities, respectively. The total VOC emissions in Yangquan were 9283.2 t [-40.0%, 62.1%] in 2018, with industrial processes being the major contributors. Alkanes (35.8%), aromatics (25.0%), and alkenes (19.8%) were the main compounds in the emission inventory. The verification results for both species emission and source structure were in agreement, indicating the accuracy of VOC emission inventory based on EF method to a certain extent. However, for some species (ethane, propane, benzene, and acetylene), the EF method indicated emissions lower than those obtained from the TR results. Furthermore, the summer-time emission contribution from fossil fuel combustion indicated by the EF method (23.4%) was lower than that obtained from the PMF results (38.4%). Overall, these discrepancies could be attributed to the absence of a coal gangue source in the EF method. The verification results determined the accuracy of the VOC emission inventory and identified existing problems in the estimation of the VOC emission inventory in coal resource-based cities. In particular, not accounting for the coal gangue emissions may result in an underestimation of VOC emissions in coal resource-based cities. Thus, coal gangue emissions should be considered in future research.

The synthetic resin industry plays an important role in Volatile organic compounds (VOCs) emissions from industrial sources. However, owing to various products and their different emission characteristics, it is extremely difficult to study the source profiles of synthetic resins. In this study, the product-based pollution characteristics of VOCs from eight synthetic resin enterprises were investigated in Shanghai, China. Up to 133 VOCs were identified, including 106 based on the Photochemical Assessment Monitoring Stations (PAMS) and the Toxic Organics (TO-15) methods, and the remaining 27 were identified based on the new mass spectrometry analysis method. Aromatics (39.7%) and oxygenated VOCs (29.9%) accounted for a relatively high proportion in the synthetic resin industry. The product-based source profiles of each process unit are compiled. Generally, 1,4-dioxane, methyl isobutyl ketone, toluene, benzene, styrene, propane, and dichloromethane are the most abundant species in synthetic resin. Furthermore, the product-based ozone formation potentials (OFPs) and sources reactivity (SR) were calculated, the synthetic resin industry SR range from 0.3 g g⁻¹ to 4.6 g g⁻¹. Results suggest that toluene, benzene, styrene, propylene, ethylene, and oxygenated VOCs (including 1,4-dioxane, methyl isobutyl ketone, and aldehyde) should be preferentially controlled to reduce the OFPs. A three-level classification was established to evaluate the degree of photochemical pollution in different industries. Emission factors were calculated and ranked for eight synthetic resins. A VOC emission inventory of Chinese synthetic resin from 2005 to 2018 was compiled. It is estimated that the Chinese synthetic resin emitted 23.96 Gg of VOCs in 2018. In this study, a product-based VOC source profile and emission inventory of the synthetic resin industry were established for the first time. Finally, combined with product types, processes, and processing equipment, feasible recommendations for reducing VOC emissions in the synthetic resin industry are proposed.

Investigating the long-term trends of alkyl nitrates (RONO₂) is of great importance for evaluating the variations of photochemical pollution. Mixing ratios of C₁–C₅ RONO₂ were measured in autumn Hong Kong from 2002 to 2016, and the average level of 2-butyl nitrate (2-BuONO₂) always ranked first. The C₁–C₄ RONO₂ all showed increasing trends (p < 0.05), and 2-BuONO₂ had the largest increase rate. The enhancement in C₃ RONO₂ was partially related to elevated propane, and dramatic decreases (p < 0.05) in both nitrogen monoxide (NO) and nitrogen dioxide (NO₂) also led to the increased RONO₂ formation. In addition, an increase of hydroxyl (OH) and hydroperoxyl (HO₂) radicals (p < 0.05) suggested enhanced atmospheric oxidative capacity, further resulting in the increases of RONO₂. Source apportionment of C₁–C₄ RONO₂ specified three typical sources of RONO₂, including biomass burning emission, oceanic emission, and secondary formation, of which secondary formation was the largest contributor to ambient RONO₂ levels. Mixing ratios of total RONO₂ from each source were quantified and their temporal variations were investigated. Elevated RONO₂ from secondary formation and biomass burning emission were two likely causes of increased ambient RONO₂. By looking into the spatial distributions of C₁–C₅ RONO₂, regional transport from the Pearl River Delta (PRD) was inferred to build up RONO₂ levels in Hong Kong, especially in the northwestern part. In addition, more serious RONO₂ pollution was found in western PRD region. This study helps build a comprehensive understanding of RONO₂ pollution in Hong Kong and even the entire PRD.

Aquaculture activities in southern Chile demand floating devices to produce electricity powered by diesel generators. It has been recently proposed to replace this fuel with propane. However, little is known about the behaviour and possible environmental impacts of an accidental release of propane underwater. In this study we evaluated the impact of water temperature and salinity on the saturation and further release of propane under controlled laboratory experiments. Results showed that under extreme environmentally relevant scenarios (high and low temperature and salinity), propane saturated the water more quickly. However, while it is important to consider that saturation times can be similar (∼2 h), the magnitudes of propane dissolved can be different. Experiments showed that cold waters (5 °C) propane is dissolved twice than warm waters (20 °C). Residence time was more affected by water temperature and almost independent of water salinity. Propane may take at least 2 days to be released from waters (around 90% of the initial amount dissolved under laboratory conditions).Additionally, we evaluated the impact on dissolved oxygen displacement and the embryotoxicity of the dissolved fraction by using Zebrafish Embryo Toxicity Assay. Results showed that dissolved oxygen was quickly removed. However, the levels of dissolved oxygen were promptly recovered in the studied systems. We also observed that propane can generate genotoxic effects (3–10% mortality), but after 2 days the system can be almost free of propane and the effects may become much lower. Comparatively with the literature, propane showed to be less toxic than diesel and it is a viable and less environmentally hazardous replacement for diesel.

We investigate the distribution of volatile organic compounds (VOCs) over Indian subcontinent during a winter month of January 2011 combining the regional model WRF-Chem (Weather Research and Forecasting model coupled with Chemistry) with ground- and space-based observations and chemical reanalysis. WRF-Chem simulated VOCs are found to be comparable with ground-based observations over contrasting environments of the Indian subcontinent. WRF-Chem results reveal the elevated levels of VOCs (e. g. propane) over the Indo-Gangetic Plain (16 ppbv), followed by the Northeast region (9.1 ppbv) in comparison with other parts of the Indian subcontinent (1.3–8.2 ppbv). Higher relative abundances of propane (27–31%) and ethane (13–17%) are simulated across the Indian subcontinent. WRF-Chem simulated formaldehyde and glyoxal show the western coast, Eastern India and the Indo-Gangetic Plain as the regional hotspots, in a qualitative agreement with the MACC (Monitoring Atmospheric Composition and Climate) reanalysis and satellite-based observations. Lower values of RGF (ratio of glyoxal to formaldehyde <0.04) suggest dominant influences of the anthropogenic emissions on the distribution of VOCs over Indian subcontinent, except the northeastern region where higher RGF (∼0.06) indicates the role of biogenic emissions, in addition to anthropogenic emissions. Analysis of HCHO/NO₂ ratio shows a NOₓ-limited ozone production over India, with a NOₓ-to-VOC transition regime over central India and IGP. The study highlights a need to initiate in situ observations of VOCs over regional hotspots (Northeast, Central India, and the western coast) based on WRF-Chem results, where different satellite-based observations differ significantly.