The world is currently going through the COVID-19 pandemic which has caused hundreds of thousands of deaths in just a few months. Considering the need for lockdown measures, most countries, including Malaysia, have implemented 'Movement Control Orders' (MCOs) as a prevention step to reduce the deadly spread of this disease. Local and worldwide media have reported the immediate improvement of air quality due to this event. Nevertheless, data on the effects of MCOs on air quality at local scales are still sparse. Here, we investigate changes in air quality during the MCO at an urban area using the air sensor network AiRBOXSense which measures monoxide (CO) and particulate matter (PM 2.5 and PM 10). In this study, air pollutant data during normal days were compared with MCO days using a reference analyser and AiRBOXSense. The results showed that the levels of the measured pollutants dropped by ~20 to 60% during the MCO days at most locations. However, CO in Kota Damansara (KD) dropped to 48.7%, but PM 2.5 and PM 10 increased up to 60% and 9.7% respectively during MCO days. Local burning activities in the residential area of KD are believed to be the main cause of the increased PM levels. This study has proven that air pollutant levels have significantly fallen due to the MCO. This air quality level information showed that the reduction of air pollutants can be achieved if traffic and industry emissions are strictly controlled.
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.
The northeast/winter monsoon over Malaysia often leads to extreme rainfall events and floods over the windward side of terrain due to the strong northeasterly winds. Comparatively, much less rain falls over the other are sheltered by the mountain ranges. Based on this consideration, the onset of monsoon in the region is best determined operationally using 925 hPa winds. Therefore, we propose the first, simple, single-variable-based method to determine the onset dates of winter monsoon is yet reliable and can be closely monitored for operational purposes. The onset date is defined in the third pentad when the average of three pentads of 925 hPa northerly wind speed is greater than 1 mÁs −1 , and at least one of three pentads must be greater than 2.5 mÁs −1 . The study also investigates the relationship between the interannual variability of onset date and El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Late-onset can be expected when La Niña develops in the boreal fall season. However, a similar association between monsoon onset and El Niño condition was not observed. The lead-lag correlation between the IOD and the onset dates shows that the onset is significantly negatively correlated with the IOD. During negative (positive) IOD events, a delay (early) onset is expected. Results also show that the relationship between the onset and IOD is more robust and linear than the ENSO.
Background: Biogenic Volatile Organic Compounds (BVOCs) such as isoprene (C5H8) are ozone (O3) precursors that can be emitted at significant concentrations from the oil palm tree (Elaeis guineensis). Reactions involving BVOCs can lead to increased levels of surface O3 which can significantly impair air quality and cause crop damage. This study focuses on the link between isoprene, surface O3 and carbon dioxide (CO2) over an oil palm plantation and the effects of meteorological factors such as temperature and irradiance on the gas concentrations. The mixing ratios of isoprene, surface O3 and CO2 were measured using a portable gas chromatograph with a photoionization detector called ‘iDirac’, an EcoTech O3 analyser, and LI-COR, respectively. Atmospheric models were used for measured selected gases estimation and validation purposes.Results: Results showed that isoprene and surface O3 had maximum daytime mixing ratios of ~25 ppb and ~57 ppb, respectively. CO2 mixing ratios were high during the night compared to the day, with a maximum night-time ratio of ~883 ppm. It is also showed that suppression of isoprene emissions from plants by high CO2 concentrations during the night was due to the reduction of dimethylallyl diphosphate (DMADP) in the leaf cells. The meteorological parameters temperature and light intensity were significantly correlated with isoprene and surface O3, with r2=0.91 and p<0.01 and r2=0.87 and p<0.01, respectively. The Model of Emissions of Gases and Aerosol from Nature (MEGAN) estimated emission rates of isoprene from the oil palm plantation are in the range ~5000 to ~7000 μgm-2 h-1 which are higher than previous studies on pristine forest. This information together with the the in-situ measurement information on isoprene emission flux is then fed into the WRF-CMAQ atmospheric chemistry model to study the effect of oil palm plantation expansion over the years (2000 – 2016) on the local atmospheric chemistry.Conclusions: The in-situ of isoprene measurement in oil palm plantation has provided the variations of atmospheric concentration at different time scale which is important in giving information of surface O3 production. The relationship between isoprene-surface O3 and CO2-isoprene were interconnected at different time and influenced by meteorological factors. The model has discovered regions that are converted into oil palm plantation has experienced rise in isoprene concentration in region that are converted into oil palm plantation, and it even can be carried downwind up to 100 km inland of the emission source.
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