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Local questionnaire surveys were conducted to collect representative activity data for calculation of annual emissions from residential combustion in Red River Delta (RRD), Vietnam, for 2010–2015. Multistage statistical sampling was implemented in the surveys for Hanoi Metropolitan Region (HMR) and deep rural area of Ninh Binh province (Con Thoi, Ninh Binh (CTNB)). Emission factors were scrutinized to select relevant ranges and central values for typical cookstoves in RRD. Large differences in the activity data (cooking activities, fuel-stove types, and fuel consumption) were found between three HMR strata (urban, suburban, and rural populations) and CTNB, respectively, which resulted in distinctly different annual emissions per capita. Annual 2010 emissions from residential combustion in RRD were estimated for toxic pollutants, in Gg/year, of 217 for CO, 1.5 NOx, 7.4 SO2, 33 NMVOC, 3.7 NH3, 16.9 PM2.5, 1.4 BC, and 7.1 OC, along with 171 t/year of total PAHs with 0.7 t/year of BaP, and greenhouse gases of 5395 CO2, 17.2 CH4, and 0.7 N2O Gg/year. Emissions increased by 1.5–7.8%, varying with species, over the 6-year period. Prevalent use of crop residue in CTNB induced its dominant shares in the residential combustion emissions not only in this deep rural area but also in the entire RRD domain. Spatial emission distribution exhibited high intensities over districts having high rural population density. Global warming potential results indicated the dominant role of black carbon, especially over the 20-year horizon. Switching from solid fuels to liquefied petroleum gas would reduce the emissions from this sector and bring in multiple benefits.

Fugitive emissions of toxic volatile organic compounds (VOCs) from fuel distribution systems are largely overlooked in air quality management (AQM) in developing Asia. We estimated annual VOCs emissions, associated ozone-forming potential (OFP) and global warming potential (GWP) from gasoline stations in Vietnam for 2010–2016. Current emission control included submerged filling for underground tanks and no vapor recovery for refueling vehicles. Estimated VOCs emissions in 2016 of 20.9 Gg (54.8 Gg of OFP, 292 Gg of 20-yr GWP) were 1.4 times above those in 2010. Spatially, VOCs emissions had high intensity over large urban areas and large economic regions, with Southeast economic region and Red River Delta shared 30% and 25% of the national emissions, respectively. High OFP intensities found over large urban areas would worsen ozone pollution where VOC-sensitive regime presents. Monthly emissions were higher during summer and winter holidays coinciding with intensive transportation. Hourly emissions showed peaks in morning and afternoon rush hours. Implementation of vapor recovery of USEPA Stage I (underground tank filling) and Stage II (vehicle refueling) control, respectively, would reduce VOCs emissions by 38% and 45%, while simultaneous implementations of both reduce emissions by 83%. Equal reductions would be seen for associated OFP/GWP. Control of VOCs emissions from gasoline stations helps improve air quality by reducing ambient levels of toxic VOCs and secondary pollutants of ozone and fine particles, and gain climate co-benefits through GWP reduction. Prepared spatial and temporal VOCs emissions distributions are useful for local AQM and air quality modeling studies.

On-road traffic emissions of Greater Yangon in 2015 were estimated using IVE model. Local surveys revealed the engine technology distributions, driving activities and flows for the fleets of bus, personal car (PC), pickup (PU), taxi, van and light duty truck. Vehicles in Greater Yangon were relatively new but recent use of leaded gasoline caused deactivation of catalytic converters that bring about high emission factors (EFs) of CO, VOC and NOx from gasoline-powered vehicles. Pre-Euro diesel-powered buses and trucks were high PM emitters while pre-Euro and Euro1 gasoline vehicles were high emitters of CO and VOC. Composite EFs of CO and VOC were the highest for PU (45.1 and 3.2 g/km, respectively) followed by taxi (34.2 and 2.6 g/km, respectively). CNG vehicles with their small number and low EFs contributed the least to total on-road traffic emissions. The bus fleet, despite being diesel-powered at only 28%, still had the highest EFs of PM and NOx, 1.6 and 2.7 g/km, respectively. Total emissions for 2015 (base case) in Greater Yangon from six surveyed fleets and the motorcycle fleet of CO; VOC; NOx; PM; BC; OC; CO2; CH4 and air toxics, in Gg/year, were 358; 41; 24; 3.8; 1.6; 0.9; 5358, 6.8 and 3.1, respectively. If all vehicles in this domain at least comply with Euro3 standard, the collective emission reduction from the base case of the air pollutants would be 71% while that of GWP (GHGs and short-lived climate pollutants) 43%, hence showing significant potential co-benefits.

Lack of robust data to assess the effects of different policies may hamper the design and implementation of effective solutions to reduce traffic emissions. This study analyzed the emissions of passenger fleets in Bandung, Indonesia, illustrated with three emission scenarios against the 2015 baseline. Local surveys were conducted to get traffic activity data for International Vehicle Emissions (IVE) modeling to generate emission factors (EFs) relevant to actual fleets and driving conditions in the city. EFs obtained for gasoline fleets that could have been affected by the leaded gasoline used prior 2006 were adjusted for the catalyst deactivation effect. Annual emissions (Gg/year) for CO, VOC, NOx, PM, BC, OC, NH3, air toxics and SO2 were 168, 36, 16, 1.8, 0.68, 0.72, 0.68, 4.7 and 0.42, respectively. Emissions of CO2, N2O and CH4 were 2679; 0.07 and 5.8 Gg/year, respectively. Collectively, the 20-year global warming potential (GWP) of the emissions was 6770 Gg/year CO2 eq. Analysis of potential interventions of technology intrusion of Euro3 (S1) and Euro4 (S2), and catalyst revamping (S3) showed potential co-benefits to air quality improvement and climate forcing mitigation. S1 would reduce the toxic pollutants emissions by 62% and GWP by 29%; corresponding reductions would be 68% and 45% for S2 and 47% and 16% for S3. Actual measurements are required to validate the potential emission reductions by catalyst revamping.

Residential combustion in Southeast Asia (SEA) releases large amounts of pollutants, including fine particles (PM2.5), black carbon (BC), organic carbon (OC) and greenhouse gases (GHGs). This study quantified the annual emissions from lighting and cooking by the residential sector in SEA during 2010–2018 to create a new regional emissions inventory (EI). Available survey data of urban/rural fuel consumption and carefully scrutinized emission factors relevant for SEA typical fuel-cookstoves were used. The period average SEA emissions from the sector in Gg yr−1 were 734 ± 6 (PM2.5); 70 ± 3 (BC); 327 ± 3 (OC); 312,436 ± 5154 (CO2); 943 ± 11 (CH4) and 35.7 ± 0.5 (N2O). Lighting contributed from 0.1% of N2O to 16.5% of BC of the total sectoral emissions. Biomass fuels and biomass derived fuels, mainly charcoal, accounted for more than 85% of BC and nearly 100% of OC emissions from cooking alone. Over the period, SEA annual emissions of BC reduced by 11% owning to the declining use of kerosene (14.2%) while emissions of all other species increased. Charcoal consumption was also reduced (−3.7%) while consumption of other fuels increased, maximum for LPG by 6.8%. Average SEA emissions per capita (kg cap−1 yr−1) of PM2.5; BC; OC; CO2; CH4 and N2O from the sector were 1.19; 0.11; 0.53; 507; 1.46 and 0.06, respectively. Spatial distributions showed the highest BC emission intensities over Java island of Indonesia and over several populated areas in SEA. BC was the key contributor to the total global warming potential (GWP) of the emissions, i.e. sharing 86%, 57% and 30% of the total GWP over 20-, 100- and 500-yr time horizons if biomass fuels burning CO2 emissions were assumed to be climate neutral. Interventions to eliminate kerosene use would effectively reduce BC emissions and bring about greater co-benefits.

This study developed a comprehensive emission inventory (EI) for thermal power plants (TPPs) and industrial activities in Vietnam for 2010. A combined top-down and bottom-up EI was conducted using fossil fuel consumption data of TPPs and industrial activities collected at the provincial level. Emission factors (EFs) were selected from literature considering the relevancy to the country emission sources. The best emission estimates, collectively from TPPs and industry activities, in Gg, was: 361 CO, 320 NO x , 529 SO 2 , 52 NMVOC, 13 NH 3 , 266 PM 10 , 79 PM 2.5 , 2.6 BC, 4.7 OC and 105,856 CO 2 , which were mainly contributed by the industrial activities. The range between low and high emission estimates were determined for each species and the largest ranges were found for BC and SO 2 . Spatial emission distributions showed higher intensities over major economic zones of the country. The lowest monthly emissions were seen in February coinciding with the Lunar New Year holiday which were followed by the peaks in March when the economic activities resumed. The net GWP of the emissions in 20-yr CO 2 equivalent was 59.7 Tg with CO 2 emissions having the largest share (87%) followed by BC (6%), whereas sulfates were the main cooling agent. Fuel switching to natural gas would significantly reduce emissions from TPPs while better combustion and emission control technologies applied in small and medium industries would reduce emissions of PM species including BC. The emission database developed in this study can be used in dispersion modeling for air quality management studies in Vietnam.

The study domain covered the Eastern region of Southern of Vietnam that includes Ho Chi Minh City (HCMC) and five other provinces. Rice production in the domain accounted for 13% of the national total with three crop cycles per year. We assessed ozone (O3) induced rice production loss in the domain for 2010 using simulated hourly surface O3 concentrations (WRF/CAMx; 4km resolution). Simulated O3 was higher in January-February (largely overlaps the first crop) and September-December (third crop), and lower in March-June (second crop). Spatially, O3 was higher in downwind locations of HCMC and were comparable with observed data. Relative yield loss (RYL) was assessed for each crop over the respective growing period (105days) using three metrics: AOT40, M7 and flux-based O3 dose of POD10. Higher RYL was estimated for the downwind of HCMC. Overall, the rice production loss due to O3 exposure in the study domain in 2010 was the highest for the first crop (up to 25,800metrictons), the second highest for the third crop (up to 21,500tons) and the least for the second crop (up to 6800tons). The low RYL obtained for the second crop by POD10 may be due to the use of a high threshold value (Y=10nmolm(-2)s(-1)). Linear regression between non-null radiation POD0 and POD10 had similar slopes for the first and third crop when POD0 was higher and very low slope for the second crop when POD0 was low. The results of this study can be used for the rice crop planning to avoid the period of potential high RYL due to O3 exposure.

This study estimated the lifetime cancer risk (LCR) attributable to 1,3-butadiene (BD) personal exposure and to other microenvironments, including residential home, outdoor, in-office, in-vehicle, and dining. Detailed life expectancy by country (WHO), inhalation rate and body weight by gender reported by USEPA were used for the calculation, focusing on adult population (25 ≤ Age < 65). LCR estimation of the adult population due to personal exposure exceeded the USEPA benchmark of 1 × 10− 6 in many cities. For outdoor BD exposure, LCR estimations in 45 out of 175 cities/sites (sharing 26%) exceeded the USEPA benchmark. Out of the top 20 cities having high LCR estimations, developing countries contributed 19 cities, including 14, 3, 1, 1 cities in China, India, Chile, and Pakistan. One city in the United States was in the list due to the nearby industrial facilities. The LCR calculations for BD levels found in residential home, in-vehicle and dining microenvironments also exceeded 1 × 10− 6 in some cities, while LCR caused by in-office BD levels had the smallest risk. Four cities/regions were used for investigating source distributions to total LCR results because of their sufficient BD data. Home exposure contributed significantly to total LCR value (ranging 56% to 86%), followed by in-vehicle (4% to 38%) and dining (4 to 7%). Outdoor microenvironment shared highly in Tianjin with 6%, whereas in-office contributed from 2–3% for all cities. High LCR estimations found in developing countries highlighted the greater cancer risk caused by BD in other cities without available measurement data.