Soni Arti Roshan, Amrit Kumar, Shinde Amar Mohan
Research & Innovation Center, CSIR-NEERI, Mumbai, India.
Energy & Resource Management Division, CSIR-NEERI, Nagpur, India.
Environ Dev Sustain. 2022 May 9:1-16. doi: 10.1007/s10668-022-02311-9.
COVID-19 have significant impact on travel behaviour and greenhouse gases (GHG), especially for the most affected city in India, Mumbai metropolitan region (MMR). The present study attempts to explore the risk on different modes of transportation and GHG emissions (based on change in travel behavior) during peak/non-peak hours in a day by an online/offline survey for commuters in Indian metropolitan cities like MMR, Delhi and Bengaluru. In MMR, the probability of infection in car estimated to be 0.88 and 0.29 during peak and non-peak hour, respectively, considering all windows open. The risk of infection in public transportation system such as in bus (0.307), train (0.521), and metro (0.26) observed to be lower than in private vehicles. Furthermore, impact of COVID-19 on GHG emissions have also been explored considering three scenarios. The GHG emissions have been estimated for base (3.83-16.87 tonne), lockdown (0.22-0.48 tonne) and unlocking (2.13-9.30 tonne) scenarios. It has been observed that emissions are highest during base scenario and lowest during lockdown situation. This study will be a breakthrough in understanding the impact of pandemic on environment and transportation. The study shall help transport planners and decision makers to operate public transport during pandemic like situation such that the modal share of public transportation is always highest. It shall also help in regulating the GHG emissions causing climate change.
新冠疫情对出行行为和温室气体产生了重大影响,尤其是对印度受影响最严重的城市孟买大都市区(MMR)而言。本研究试图通过对MMR、德里和班加罗尔等印度大都市通勤者进行线上/线下调查,探索一天中高峰/非高峰时段不同交通方式的风险以及温室气体排放(基于出行行为变化)。在MMR,考虑所有车窗打开的情况下,高峰时段和非高峰时段乘坐汽车感染的概率分别估计为0.88和0.29。公共交通系统如公交车(0.307)、火车(0.521)和地铁(0.26)的感染风险低于私家车。此外,还考虑了三种情景来探讨新冠疫情对温室气体排放的影响。已对基础情景(3.83 - 16.87吨)、封锁情景(0.22 - 0.48吨)和解封情景(2.13 - 9.30吨)的温室气体排放进行了估算。据观察,基础情景下的排放最高,封锁情景下的排放最低。这项研究将在理解疫情对环境和交通的影响方面取得突破。该研究将有助于交通规划者和决策者在类似疫情的情况下运营公共交通,使公共交通的方式分担率始终保持最高。它还将有助于控制导致气候变化的温室气体排放。