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1.
Huan Jing Ke Xue ; 44(9): 4819-4831, 2023 Sep 08.
Article in Chinese | MEDLINE | ID: mdl-37699801

ABSTRACT

Atmospheric formaldehyde, a key precursor for ozone (O3) and secondary PM2.5, is carcinogenic and plays an important role in atmospheric photochemistry and the formation of secondary pollution. However, the lack of understanding of the emission sources of atmospheric formaldehyde limits the study on the formation mechanism of secondary pollution and the formulation of pollution control strategies. This study used the emission factor and source profile methods to establish the emission inventories of formaldehyde in Guangdong Province from 2006 to 2020 and identified the main emission sources of formaldehyde and spatial and temporal evolution characteristics. The results showed that the formaldehyde emissions in Guangdong Province fluctuated in the range of 39000-56000 tons during 2006 to 2020, exhibiting a very weak downward trend. Biomass combustion is an important source of formaldehyde emission in Guangdong Province, of which the contribution decreased from 58% in 2006 to 27% in 2020 owing to effective control measures implemented in Guangdong Province. The solvent use source became the predominant emission source of formaldehyde in 2020 by contributing up to 28%, primarily through plastic products and asphalt paving sources. The construction machinery and trucks fueled by diesel were important contributors of formaldehyde emissions from mobile sources. Although the formaldehyde emissions in the Pearl River Delta and the non-Pearl River Delta were equivalent, the spatial distributions showed that formaldehyde emission hotspots were concentrated in the center of the Pearl River Delta and the eastern and western areas of the non-Pearl River Delta. This was primarily because the solvent use and mobile sources were the main sources of formaldehyde emissions in the Pearl River Delta, whereas the biomass combustion source was the dominant source in the non-Pearl River Delta. Therefore, the formaldehyde emission mitigations of the industrial and mobile sources in the central region of the Pearl River Delta and the biomass combustion source in the western area of Guangdong should be further strengthened in the future.

2.
Huan Jing Ke Xue ; 43(2): 735-742, 2022 Feb 08.
Article in Chinese | MEDLINE | ID: mdl-35075847

ABSTRACT

Non-road diesel vehicle exhaust is an important emission source that affects air quality in China, yet knowledge regarding its chemical composition and potential influence factors remains limited. Six typical forklifts were selected to study the effect of diesel particulate filters (DPF) on the emission characteristics of volatile organic compounds (VOCs) and n-alkanes using online monitoring of gaseous components combined with offline analysis. The results showed that oxygenated volatile organic compounds (OVOCs), olefins, alkanes, aromatic hydrocarbons, and halogenated hydrocarbons accounted for 26%-37%, 16%-36%, 19%-22%, 13%-21%, and 4%-7% of the measured VOCs in forklift exhaust, respectively. The VOCs emission factors of low-power and high-power forklifts were(2.47±0.33)g·kg-1 and (1.48±0.24)g·kg-1, respectively. The forklift exhaust emission factors of total VOCs without and with DPF were(1.94±0.58)g·kg-1and (2.08±0.79)g·kg-1, respectively. Our results showed that DDF exerted minor impact on VOCs emission. However, it is worth noting that DPF can efficiently remove some types of OVOCs components. For example, the emission factors of acetaldehyde and acetone of the forklifts with DPF were reduced by 19% and 26%, respectively, compared to that of those without DPF. The carbon numbers of n-alkane fractions showed a bimodal distribution of C7-C17 and C24-C31, respectively, with C15 being the dominant peak carbon. The average emission factors of n-alkanes were (115±34) mg·kg-1 (without DPF) and (53.7±19)mg·kg-1 (with DPF), respectively, with a decrease of 53%, indicating that DPF can effectively reduce the emission of n-alkane in the exhaust of forklifts. Our results can provide scientific support for the precise control of non-road construction machinery exhaust emissions and the further improvement of regional air quality.


Subject(s)
Air Pollutants , Air Pollution , Volatile Organic Compounds , Air Pollutants/analysis , Air Pollution/analysis , Air Pollution/prevention & control , Alkanes , Vehicle Emissions/analysis , Volatile Organic Compounds/analysis
3.
Huan Jing Ke Xue ; 41(7): 3112-3120, 2020 Jul 08.
Article in Chinese | MEDLINE | ID: mdl-32608883

ABSTRACT

In this study, 127 light-duty gasoline cars and 10 light-duty gasoline trucks with different emission standards were selected to explore the influences of different conditions and vehicle parameters on the emission characteristics of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), hydrocarbons (HC), and methane (CH4) using a portable emission measurement system based on a chassis dynamometer under acceleration simulation mode. The results showed that the gaseous pollutants of light-duty gasoline vehicles displayed a relatively lower emission rate under the idle condition, which accounted for only 22.9% and 25.8% of the emission rate at the accelerated condition and constant speed condition, respectively. The pollutant emission characteristics were closely related to the working conditions. The emission rates of CO2 and NOx in the accelerated condition were less than those at the constant speed condition, while the emission rates of CO, HC, and CH4 in the accelerated condition were higher than those at the constant speed condition. In the constant low-speed condition, the emission factors of CO2, CO, NOx, HC, and CH4 were 383.20, 2.98, 1.60, 0.14, and 0.03 g·km-1 for light-duty gasoline cars, respectively, and 360.66, 2.64, 1.61, 0.0055, and 0.0027 g·km-1 for light-duty gasoline trucks, respectively. Tighter emission standards have caused significant reductions in emissions. The emission factors of CO, NOx, HC, and CH4 could be decreased by 87.5%, 97.3%, 97.9%, and 86.4%, respectively, from China Ⅰ to China Ⅴ. A non-linear relationship was found between the age, odometer, vehicle weight, and vehicular emissions. In addition, the engine displacement was positively correlated with vehicular emissions.

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