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13. Technical note: Emission mapping of key sectors in Ho Chi Minh city, Vietnam using satellite derived urban land-use data

Author

Nguyen, Trang Thi Quynh, Takeuchi, Wataru, and Misra, Prakhar

Abstract

Emission inventories are important for both simulating pollutant concentrations and designing emission mitigation policies. Ho Chi Minh city (HCMC) is the biggest city in Vietnam but lacks of an updated spatial emission inventory. In this study, we propose a new approach to compile a comprehensive spatial emission inventory for major Short lived climate pollutants (SLCP) and Green house gases (GHG) (SO2, NOx, CO, NMVOC, PM10, PM2.5, BC, OC, NH3, CH4, N2O, and CO2) Our originality is the use of satellite derived urban land-use morphological maps which allow spatial disaggregation of emissions. Based on this approach, a comparable and consistent local emission inventory (EI) for HCMC has been prepared, including three key sectors as a successor of previous EIs. It provides annual emissions of transportation, manufacturing industries and construction and residential sectors at 1 km resolution. The target years are from 2009 to 2016. We consider both Scope 1 – all direct emissions from the activities occurring within the city and Scope 2 that is indirect emissions from electricity purchased. Transportation sector was found to be the most dominant emission sector in HCMC followed by Manufacturing industries, and Residential area, responsible for over 682 Gg CO, 84.8 Gg NOx, 20.4 Gg PM10 and 22 000 Gg CO2 emitted in 2016. Due to sharp rise in vehicle population, CO, NOx, SO2 and CO2 traffic emissions show increases of 80 %, 160 %, 150 % and 103 % respectively between 2009 and 2016. Among five vehicle types, motorcycle contributed around 95 % to total CO emission, 14 % to total NOx emission and 50–60 % to CO2 emission. Heavy vehicles are the biggest emission source of NOx, SO2 and PM while personal cars are the largest contributors to NMVOC and CO2. Electricity consumption accounts for the majority of emissions from Manufacturing industry and Residential sectors. We also found that Scope 2 emissions from manufacturing industry and residential areas in 2016 increased by 87 % and 45 % respectively in comparison with 2009. Spatial emission disaggregation reveals that central business districts like Quan 1, Quan 4 and Quan 7 express the highest emission intensities, which is over 1900 times of sub urban HCMC. Our estimates show relative agreement with several local inherent EIs, in terms of total amount of emission and sharing ratio among elements of EI. However, the big gap was observed when comparing with REASv2.1, a regional EI, which mainly applied national statistical data. This spatial emission inventory benefits not only proposing solutions to reduce anthropogenic emissions but also the simulation of pollution concentrations in city scale. Using our proposed method, the local emission maps in HCMC can be continuously updated and improved in the future.

Published
2020

22. Monitoring Effect of Spatial Growth on Land Surface Temperature in Dhaka

Author

Rahman, Md. Mustafizur, primary, Avtar, Ram, additional, Yunus, Ali P., additional, Dou, Jie, additional, Misra, Prakhar, additional, Takeuchi, Wataru, additional, Sahu, Netrananda, additional, Kumar, Pankaj, additional, Johnson, Brian Alan, additional, Dasgupta, Rajarshi, additional, Kharrazi, Ali, additional, Chakraborty, Shamik, additional, and Agustiono Kurniawan, Tonni, additional

Published
2020
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23. Monitoring and Mapping of Rice Cropping Pattern in Flooding Area in the Vietnamese Mekong Delta Using Sentinel-1A Data: A Case of An Giang Province

Author

Minh, Huynh Vuong Thu, Avtar, Ram, Mohan, Geetha, Misra, Prakhar, Kurasaki, Masaaki, Minh, Huynh Vuong Thu, Avtar, Ram, Mohan, Geetha, Misra, Prakhar, and Kurasaki, Masaaki

Abstract

Cropping intensity is one of the most important decisions made independently by farmers in Vietnam. It is a crucial variable of various economic and process-based models. Rice is grown under irrigated triple- and double-rice cropping systems and a rainfed single-rice cropping system in the Vietnamese Mekong Delta (VMD). These rice cropping systems are adopted according to the geographical location and water infrastructure. However, little work has been done to map triple-cropping of rice using Sentinel-1 along with the effects of water infrastructure on the rice cropping intensity decision. This study is focused on monitoring rice cropping patterns in the An Giang province of the VMD from March 2017 to March 2018. The fieldwork was carried out on the dates close to the Sentinel-1A acquisition. The results of dual-polarized (VV and VH) Sentinel-1A data show a strong correlation with the spatial patterns of various rice growth stages and their association with the water infrastructure. The VH backscatter (sigma degrees) is strongly correlated with the three rice growth stages, especially the reproductive stage when the backscatter is less affected by soil moisture and water in the rice fields. In all three cropping patterns, sigma degrees VV and sigma degrees VH show the highest value in the maturity stage, often appearing 10 to 12 days before the harvesting of the rice. A rice cropping pattern map was generated using the Support Vector Machine (SVM) classification of Sentinel-1A data. The overall accuracy of the classification was 80.7% with a 0.78 Kappa coefficient. Therefore, Sentinel-1A can be used to understand rice phenological changes as well as rice cropping systems using radar backscattering.

Published
2019

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