[Driving Forces and Mitigation Potential of CO2 Emissions for Ship Transportation in Guangdong Province, China].

Ships are important sources of carbon dioxide (CO2) emissions in Guangdong Province. The study of historical evolutions, drivers, and projected pathways of CO2 emissions can provide scientific support for the development of carbon peaking and carbon neutral strategies in Guangdong Province. The emission factor method, log-average index (LMDI) method, and scenario analysis method were adopted to estimate CO2 emissions, identify the drivers, and explore the mitigation potential from ships in Guangdong Province, separately. The results showed that:① CO2 emissions from ships in Guangdong Province increased from 3.319 4 million tons to 6.392 9 million tons from 2006 to 2020, with dry bulk carriers and container ships being the main ship types causing the increase in emissions. ② The positive drivers of CO2 emissions from ships in Guangdong Province from 2006 to 2020 were transport intensity (51%) and economic factors (49%), and the negative drivers were energy intensity (93%) and cargo class structure (7%). ③ Carbon peaking would not be reached by 2030 if Guangdong Province maintains the current policy (baseline scenario) for ship transportation. ④ Simultaneous optimization of the energy structure and promotion of the energy intensity (energy-efficient and low-carbon scenario) had a 56.51% potential to reduce CO2 emissions from ships compared to the baseline scenario. This can provide scientific support for Guangdong Province to develop a carbon peaking and carbon neutral control strategy for the shipping industry.

[Evolution Characteristics and Driving Forces of Carbon Dioxide Emissions and Sinks in the Pearl River Delta Region, China].

With the rapid economic and population growth, the Pearl River Delta(PRD) Region is one of the regions in China under the greatest pressure to be carbon neutral. This study analyzed the historical evolution characteristics of the carbon dioxide(CO2) emissions and sinks from 2006-2020 and identified the key drivers of the CO2 emissions and sinks based on the exponential decomposition method. The results showed that:① from 2006 to 2020, the total carbon emissions in the PRD Region increased from 218.22 million tons to 366.30 million tons, showing a fluctuating and rising evolution characteristic, with an overall increase of 67.86%. The carbon emission had not yet reached a peak. ② From 2006 to 2020, the total carbon sinks in the PRD Region decreased from 15.67 million tons to 15.53 million tons, showing a trend of fluctuation and decline, with an overall decrease of 0.94%. The carbon sinks were far lower than the carbon emissions, and there was still a large gap between carbon neutrality. ③ The main carbon emission sectors in the PRD Region were the energy sector(40.38%) and industrial sector(26.33%), and the carbon sinks mainly came from forestland(67.92%) and farmland(18.09%). ④ During the period from the "11th Five-Year Plan" to the "13th Five-Year Plan," the main positive driving factors for carbon emissions were economic growth and population size, whereas the main negative driving factor was energy intensity(energy use per unit GDP). However, since the "13th Five-Year Plan," the CO2 emission reduction potential released by reducing energy intensity has been weakening. In the future, the PRD Region needs to address the negative driving potential of the structural adjustment in energy, industry, transportation, and land use. ⑤ During the period from the "11th Five-Year Plan" to the "13th Five-Year Plan," the main positive driving factor for the carbon sink was the green scale, which was conducted by the increase in urban green space during the "11th Five-Year Plan." The main negative driving factor for the carbon sink was the carbon sink coefficient, which was caused by the natural disaster-induced yield reductions in crops with a high carbon sink coefficient, such as rice. Green space structure adjustment should be emphasized in the future. This study can provide scientific support for developing robust carbon-neutral policies in the PRD Region.

[Evolution Characteristics of Atmospheric Formaldehyde Emissions in Guangdong Province from 2006 to 2020].

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.

[Volatile Organic Compound Emission Characteristics and Influences Assessment of a Petrochemical Industrial Park in the Pearl River Delta Region].

The petrochemical industry is one of the major emission sources of volatile organic compounds (VOCs). However, the current studies have mostly focused on the identification of the chemical characteristics of non-methane hydrocarbon (NMHC) VOCs species from the petroleum refining sub-sector. Research on the characteristics of VOCs components in oxygenated VOCs (OVOCs) species and other important sub-sectors is still lacking. Therefore, eight enterprises at a petrochemical industrial park in the Pearl River Delta region were carefully selected to represent three major subsectors, namely petroleum refining, synthetic materials, and organic chemicals, for the petrochemical industry. The VOCs (including 22 OVOCs species) from stack emissions and fugitive emissions, as well as nearby sensitive sites, were sampled, and the source reactivity (SR), the thresholds of malodor, and the carcinogenic and non-carcinogenic risks were assessed. The main results were as follows:① the VOCs concentrations of the stack emissions from the petrochemical industrial park were between 0.2-46.3 mg·m-3. The VOCs species were greatly affected by the type of after-treatment technology. A major VOC species emitted from the combustion-based after treatments was formaldehyde, whereas the species emitted from the non-combustion-based equipment were acetone, 1,3-butadiene, acrylic, and isobutane. ② The fugitive VOCs emissions from the petroleum storage tank area were dominated by alkanes, whereas the other fugitive emission sites and the sensitive sites were dominated by OVOCs such as acetone, formaldehyde, and ethyl acetate. ③ The SRs were mainly contributed by OVOCs, aromatics, and olefins, with average proportions of 43.1%, 24.2%, and 21.1%, respectively, with the major species being formaldehyde, acetaldehyde, m/p-xylene, ethylene, and toluene. ④ The malodor appeared both in fugitive emission areas and the sensitive sites. The main odor components were OVOCs such as n-butyraldehyde, propionaldehyde, hexanal, and valeraldehyde. ⑤ The non-carcinogenic risks occurred in the fugitive emission areas and the sensitive sites of resin, alcohol, and aldehyde production, which were mainly caused by OVOCs such as free acetaldehyde, acrolein, and propionaldehyde. No carcinogenic risk was found in any of the sampled sites. This research can provide scientific support for the formulation of priority VOCs species-based precise control strategies in petrochemical industrial parks.

[Emission Characterstics of VOCs and n-alkanes from Diesel Forklifts].

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.

[Emission Characteristics of Light-Duty Gasoline Vehicle Exhaust Based on Acceleration Simulation Mode].

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.

[Marine Emission Inventory and Its Temporal and Spatial Characteristics in the City of Shenzhen].

To analyze the characteristic of marine emission in Shenzhen City, activity-based and fuel-based approaches were utilized to develop the marine emission inventory for the year of 2010, using the vessel files from the Lloyd's register of shipping (LR) and vessel track data from the automatic identification system (AIS). The marine emission inventory was temporally (resolution: 1 hour) and spatially (resolution: 1 km x 1 km) allocated based on the vessel track data. Results showed that total emissions of SO2, NO(x), CO, PM10, PM2.5 and VOCs from marine vessels in Shenzhen City were about 13.6 x 10(3), 23.3 x 10(3), 2.2 x 10(3), 1.9 x 10(3), 1.7 x 10(3) and 1. x 10(3) t, respectively. Among various types of marine vessels, emission from container vessels was the highest; for different driving modes, hotelling mode was found with the largest mission. Marine emissions were generally higher in the daytime, with vessel-specific peaks. For spatial distributions, in general, marine emissions were zonally distributed with hot spots in the western port group, Dapeng Bay and the key waterway.

[Anthropogenic ammonia emission inventory and characteristics in the Pearl River Delta Region].

Based on the collected activity data and emission factors of anthropogenic ammonia sources, a 2006-based anthropogenic ammonia emission inventory was developed for the Pearl River Delta (PRD) region by source categories and cities with the use of appropriate estimation methods. The results show: (1) the total NH3 emission from anthropogenic sources in the PRD region was 194. 8 kt; (2) the agriculture sources were major contributors of anthropogenic ammonia sources, in which livestock sources shared 62.1% of total NH3 emission and the contribution of application of nitrogen fertilizers was 21.7%; (3) the broiler was the largest contributor among the livestock sources, accounting for 43.4% of the livestock emissions, followed by the hog with a contribution of 32.1%; (4) Guangzhou was the largest ammonia emission city in the PRD region, and then Jiangmen, accounting for 23.4% and 19.1% of total NH3 emission in the PRD region respectively, with major sources as livestock sources and application of nitrogen fertilizers.

[Development of non-road mobile source emission inventory for the Pearl River Delta region].

Based on the collected activity data and emission factors, the Pearl River Delta (PRD) regional non-road mobile source emission inventory was developed by categories with the use of appropriate estimation methods for different non-road mobile sources. The results show that the total emissions of SO2, NOx,VOC, CO and PM10 from non-road mobile sources in the PRD region were about 6.52 x 10(4) t, 1.24 x 10(5) t, 4.54 x 10(3) t, 2.67 x 10(4) and 4.51 x 10(3) t, respectively. The marine source is the largest non-road mobile source contributor to SO2, NOx, CO and PM10 emissions, accounting for 96.4%, 73.8%, 39.4% and 50.5%, respectively; Freighter and dry bulk carrier are important marine emission contributors, sharing 89.8%, 81.8%, 77.3%, 79.5% and 81.7% of the total marine SO2, NOx, VOC, CO and PM10 emissions. The non-road mobile source has become the third largest SO2 and NOx contributor in the PRD region, accounting for about 8.6% and 13.5% of the regional total SO2 and NOx emissions.

Expression of hemagglutinin of avian influenza virus (AIV) and its application in diagnosis of AIV H9 subtype / 生物工程学报

In order to differently diagnose avian influenza virus (AIV) subtypes, the HA gene of AIV H9 subtype was cloned, expressed and utilized in an enzyme-linked immunoad sorbent assay (ELISA). HA gene (1683bp) of H9N2 AIV was amplified by RT-PCR from a strain of field isolated H9N2 AIV, and its identity was confirmed by sequencing. The HA gene was subcloned into prokaryotic expression vector pGEX-KG with its secretion signal sequence removed. The expressed HA-GST fusion protein in E. coli BL21 was characterized by SDS-PAGE and western blotting analysis as a 90kD protein with immunogenicity. The fusion protein was present primarily in inclusion bodies and was purified via denaturation and renenaturation. The HA-GST fusion protein was used to establish an indirect ELISA for the detection of antibodies to H9 subtypes of AIV. The assay has 91.57% specificity to H9 AIV, 92.31% sensitivity and excellent reduplication. It could be used to differently detect antibodies to H9 AIV.