Globally, the COVID-19 pandemic has had both positive and negative impacts on humans and the environment. In general, a positive impact can be seen on the environment, especially in regard to air quality. This positive impact on air quality around the world is a result of movement control orders (MCO) or lockdowns, which were carried out to reduce the cases of COVID-19 around the world. Nevertheless, data on the effects on air quality both during and post lockdown at local scales are still sparse. Here, we investigate changes in air quality during normal days, the MCOs (MCO 1, 2 and 3) and post MCOs, namely the Conditional Movement Control Order (CMCO) and the Recovery Movement Control Order (RMCO) in the Klang Valley region. In this study, we used the air sensor network AiRBOXSense that measures carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2) and particulate matter (PM2.5 and PM10) at Petaling Jaya South (PJS), Kelana Jaya (KJ) and Kota Damansara (KD). The results showed that the daily average concentrations of CO and NO2 mostly decreased in the order of normal days > MCO (MCO 1, 2 and 3) > CMCO > RMCO. PM10, PM2.5, SO2 and O3 showed a decrease from the MCO to RMCO. PJS showed that air pollutant concentrations decreased from normal days to the lockdown phases. This clearly shows the effects of ‘work from home’ orders at all places in the PJS city. The greatest percentage reductions in air pollutants were observed during the change from normal days to MCO 1 (24% to 64%), while during MCO 1 to MCO 2, the concentrations were slightly increased during the changes of the lockdown phase, except for SO2 and NO2 over PJS. In KJ, most of the air pollutants decreased from MCO 1 to MCO 3 except for CO. However, the percentage reduction and increments of the gas pollutants were not consistent during the different phases of lockdown, and this effect was due to the sensor location—only 20 m from the main highway (vehicle emissions). The patterns of air pollutant concentrations over the KD site were similar to the PJS site; however, the percentage reduction and increases of PM2.5, O3, SO2 and CO were not consistent. We believe that local burning was the main contribution to these unstable patterns during the lockdown period. The cause of these different changes in concentrations may be due to the relaxation phases during the lockdown at each station, where most of the common activities, such as commuting and industrial activities changed in frequency from the MCO, CMCO and RMCO. Wind direction also affected the concentrations, for example, during the CMCO and RMCO, most of the pollutants were blowing in from the Southeast region, which mostly consists of a city center and industrial areas. There was a weak correlation between air pollutants and the temperature and relative humidity at all stations. Health risk assessment analysis showed that non-carcinogenic risk health quotient (HQ) values for the pollutants at all stations were less than 1, suggesting unlikely non-carcinogenic effects, except for SO2 (HQ > 1) in KJ. The air quality information showed that reductions in air pollutants can be achieved if traffic and industry emissions are strictly controlled.

Exposure of commuters to pollutants on trains has been an essential topic of discussion in recent years due to its health implications. This review summarizes literature that measures particulate matter (PM) in trains to understand the concentration levels and health effects caused due to exposure. The databases searched were Scopus, Web of Science (WOS) and Google Scholar. Articles, conference papers and textbooks written in English, measuring PM in train carriages and published between 1998 and 2022 were selected for this review. Out of the 3247 articles identified, only 73 were included in this study. 15/20 articles agreed that concentration is significant at the underground segment by a factor of 7 than the counterpart above/ground levels. The review observed that 80% of the publication of in-train concentrations of PM10 and PM2.5 were above the WHO standard. In-train PM2.5 concentration ranges from 2 μgm−3 to 563 μgm−3, and in-train PM10 concentration ranges from 6 μgm−3 to 997 μgm−3. People’s activities, mechanical movement of train parts, train operation conditions and local emissions were the primary source of PM. Future research should focus on health damage due to PM exposure and the effect of the filtration system on PM levels in trains.

This paper reviews personal exposure and air pollutant levels in Asian city transport microenvironments. It examines PM10, PM2.5, PM1, CO2, CH2O, and TVOC exposure in cars, buses, walking, and subways/trains. PM2.5 was the most studied pollutant, followed by PM10, PM1, CO2, and TVOC. Limited research focused on CH2O exposure. Exposure concentrations varied among cities and transport modes. Motor vehicle emissions, traffic, road dust, and open bus doors were primary exposure sources. Train stations and outdoor environments contributed to pollutant levels inside trains. Factors influencing exposure included ventilation, travel conditions, seat location, vehicle type, and meteorology. Inhalation exposure doses varied by mode. The review recommends standardized measurements, improved ventilation, filters, clean energy, and public education to reduce exposure. More research is needed in diverse Asian cities. This review aids policymakers, researchers, and advocates for air quality and public health.