Identify Primary Air Pollution Sources of BTEX by Using Positive Matrix Factorization (PMF): A Case Study of Ho Chi Minh City, Vietnam.

Ho Chi Minh City (HCMC) is one of the main socioeconomic and financial centers of Vietnam. The city also faces serious air pollution. However, the city polluted with benzene, toluene, ethylbenzene, and xylene (BTEX) has rarely been studied. We used positive matrix factorization (PMF) to analyze BTEX concentrations measured at two sampling locations to identify the main sources of BTEX in HCMC. The locations represented residential area (i.e., To Hien Thanh) and industrial area (i.e., Tan Binh Industrial Park). At the To Hien Thanh location, the average concentrations of benzene, ethylbenzene, toluene, and xylene were 6.9, 14.4, 4.9, and 12.7 µg/m3, respectively. At the Tan Binh location, the average concentrations of benzene, ethylbenzene, toluene, and xylene were 9.8, 22.6, 2.4, and 9.2 µg/m3, respectively. The results showed that PMF was a reliable model for source apportionment in HCMC. Traffic activities were the main sources of BTEX. Besides, industrial activities also contributed to BTEX emissions, especially the location near the industrial park. The majority of BTEXs at the To Hien Thanh sampling site come from traffic sources accounting for 56.2%. Activities from traffic and photochemical reactions (42.7%) and industrial sources (40.5%) were the main sources affecting BTEX emissions at the sampling site of Tan Binh Industrial Park. This study can be used as a reference for mitigation solutions to reduce the BTEX emission in HCMC.

An Innovative Method for BTEX Emission Inventory and Development of Mitigation Measures in Developing Countries-A Case Study: Ho Chi Minh City, Vietnam.

Benzene, toluene, ethylbenzene, and xylenes (BTEX) are carcinogenic pollutants. However, the average concentration in 1 h of some pollutants belonging to BTEX, such as benzene, in Ho Chi Minh City (HCMC) is higher than the national standard QCVN 06:2009/BTNMT by about ten times. This research is the first to calculate the emission of BTEX for developing countries on a city scale. This paper developed a method to calculate cold emission factors based on hot emission factors for BTEX. Five spreadsheets developed and calculated these cold emission factors for five vehicle categories. A comprehensive emission inventory (EI) for BTEX was conducted in HCMC to determine the cause of BTEX pollution. An innovative methodology with bottom-up and top-down combination was applied to conduct BTEX EI, in which the EMISENS model was utilized to generate the EI for road traffic sources, and the emission factors method was utilized for other emission sources. Among emission reasons, motorcycles contribute the highest to HCMC air pollution, responsible for 93%, 90%, 98.9%, and 91.5% of benzene, toluene, ethylbenzene, and xylene, respectively. Cars contributed 5%, 6%, 0.8%, and 6.5% of benzene, toluene, ethylbenzene, and xylene, respectively. For LDVs, the emission from benzene, toluene, ethylbenzene, and xylene accounted for 1%, 2%, 0.2%, and 1.9%. The major reasons for point sources were metal production, which had 1%, 2%, and 0.1% for benzene, toluene, ethylbenzene, and xylenes emissions. The area source had a minority emission of total BTEX in Ho Chi Minh City. Our findings can be used to invest in the most significant sources to reduce BTEX in HCMC. Our approach can be applied in similar urban areas in BTEX EI. This research also developed nine measures to reduce BTEX in HCMC for human health protection.

Estimation of Shipping Emissions in Developing Country: A Case Study of Mohammad Bin Qasim Port, Pakistan.

Transportation has the highest dependence on fossil fuels of any sector and accounts for 37% of carbon dioxide (CO2) emissions. Maritime transportation is responsible for around 940 million tons of CO2 and approximately 3% of global emissions annually. The significant increase in shipping activities around the globe has magnified the generation of toxic pollutants. In recent years, shipping emissions have received significant attention in developed countries due to global climate change, while in developing countries, researchers are making enormous efforts to tackle this catastrophic and pressing issue. This study considers Muhammad Bin Qasim Port (MBQP), Karachi, Pakistan as a case study. This study employed an activity-based or bottom-up approach with a standard procedure to estimate the various anthropogenic pollutants emissions including particular matters (PM10 and PM2.5), nitrogen oxide (NOx), sulfur dioxide (SO2), carbon monoxide (CO), CO2, methane (CH4), non-methane volatile organic compound (NMVOC), and hydrocarbon (HC) under different operational modes, i.e., hoteling, maneuvering, and reduced speed zones. The results indicated that CO2 was the highest contributor with a proportion of 92%, NOx 5%, and SO2 1.5% for all three operational modes. Moreover, the results indicated that container ships account for 64% of overall emissions, followed by tankers for 24%. Regarding the monthly trend, the findings revealed that November and December had the highest emission rates, with over 20% of the total emissions recorded. This study's findings will assist stakeholders and policymakers to prioritize maritime emissions in developing countries.

Chemical characterization and source apportionment of ambient nanoparticles: a case study in Hanoi, Vietnam.

PM0.1 has been believed to have adverse short- and long-term effects on human health. However, the information of PM0.1 that is needed to fully evaluate its influence on human health and environment is still scarce in many developing countries. This is a comprehensive study on the levels, chemical compositions, and source apportionment of PM0.1 conducted in Hanoi, Vietnam. Twenty-four-hour samples of PM0.1 were collected during the dry season (November to December 2015) at a mixed site to get the information on mass concentrations and chemical compositions. Multiple linear regression analysis was utilized to investigate the simultaneous influence of meteorological factors on fluctuations in the daily levels of PM0.1. Multiple linear regression models could explain about 50% of the variations of PM0.1 concentrations, in which wind speed is the most important variable. The average concentrations of organic carbon (OC), elemental carbon (EC), water-soluble ions (Ca2+, K+, Mg2+, Na+, NH4+, Cl-, NO3-, SO42-, C2O42-), and elements (Be, Al, V, Cr, Mn, Co, Ni, Cu, Zn, As, Se, Mo, Cd, Sb, Ba, Tl, Pb, Na, Fe, Mg, K, and Ca) were 2.77 ± 0.90 µg m-3, 0.63 ± 0.28 µg m-3, 0.88 ± 0.39 µg m-3, and 0.05 ± 0.02 µg m-3, accounting for 51.23 ± 9.32%, 11.22 ± 2.10%, 16.28 ± 2.67%, and 1.11 ± 0.94%, respectively. A positive matrix factorization model revealed the contributions of five major sources to the PM0.1 mass including traffic (gasoline and diesel emissions, 46.28%), secondary emissions (31.18%), resident/commerce (12.23%), industry (6.05%), and road/construction (2.92%).