CHARACTERISING SEASONAL VARIATIONS AND SPATIAL DISTRIBUTION OF AMBIENT PM2.5 CONCENTRATION BASED ON SHORT-TERM MONITORING IN DARKHAN CITY

The purpose of this study was to survey the seasonal variation of fine particulate matter (PM2.5) concentration and determine spatial distribution in Darkhan city. Air pollution research and reports have been few and far between in most of parts in Mongolia, especially in Darkhan with respect to quantitative aerosol particle concentration. In this study, we utilized “PM2.5sensor” to measure spatial and seasonal variation of particulate matter concentrations in the study area. The monitoring points were chosen by basing on their specific features and set up directly at ambience outdoor. In each season, we carried out measurement at 3 points, which covered the ger district and apartment district areas for one day. Whereas, at one point the ger district was sampled for 4 days in summer. Fine particulate matter concentrations were the highest in the ger district area because there are many households that use coal for their daily heating and cooking, and at the bared surface. As for seasonal variation, in winter pollution reached 400 times higher than other seasons. Furthermore, at the ger district area, PM2.5 concentration was as much as 20 times greater than other points and it was observed that this too had its impact on the apartment district as well. As regards the air quality index, the level of particulate matter in the ger district area is extremely unhealthy to hazardous in winter. While, good and moderate indexes were mostly identified at monitoring points during the springtime

Low-cost Air Quality Sensing Process: Validation by Indoor-Outdoor Measurements

Air pollution is a main challenge in societies with particulate matter PM2.5 as the major air pollutant causing serious health implications. Due to health and economic impacts of air pollution, low-cost and portable air quality sensors can be vastly deployed to gain personal air pollutant exposure. In this paper, we present an air quality sensing process needed for low-cost sensors which are planned for long-term use. The steps of this process include design and production, laboratory tests, field tests, deployment, and maintenance. As a case study we focus on the field test, where we use two generations of a portable air quality sensor (capable of measuring meteorological variables and PM2.5 to perform an indoor-outdoor measurement. The study found that all of the measurements shown to be consistent through validation among themselves. The sensors accuracy also demonstrate to be adequate by showing similar readings compared to the nearest air quality reference station.Peer reviewe

Preliminary Assessment of Methane Concentration Variation Observed by GOSAT in China

Atmospheric column-averaged methane (XCH4) observations from GOSAT are analyzed to study the spatiotemporal variation of XCH4 in China. Furthermore, we investigate the driving mechanism of XCH4 spatiotemporal variations, especially for high XCH4 values shown over Sichuan Basin, by analyzing both the emission mechanism of rice planting process and the regional atmosphere dynamic transportation. The results indicate that spatially the Sichuan Basin presents a higher XCH4 concentration than other regions in China and is 17 ppb higher than the paddy area in the same latitude zone. Seasonally, XCH4 in Sichuan Basin during rice harvest season is generally higher than that in early cultivation period. However, comparing to paddy area in the same latitude zone, Sichuan Basin shows a relatively higher XCH4 value during the winter of noncultivation period when the emissions from rice paddies are weak and surface air temperature is low. To further investigate the high XCH4 concentration during this low-emission period, we use the HYSPLIT model to simulate the atmosphere dynamic transport process, and the result suggests that the typical closed topography of Sichuan Basin, which may lead to CH4 accumulation and keep it from diffusion, is one possible reason for the high XCH4 value in winter

Intelligent Air Pollution Sensors Calibration for Extreme Events and Drifts Monitoring

Air quality low-cost sensors are affordable and can be deployed in massive scale in order to enable high-resolution spatio-temporal air pollution information. However, they often suffer from sensing accuracy, in particular when they are used for capturing extreme events. We propose an intelligent sensors calibration method that facilitates correcting low-cost sensors' measurements accurately and detecting the calibrators' drift. The proposed calibration method uses Bayesian framework to establish white-box and black-box calibrators. We evaluate the method in a controlled experiment under different types of smoking events. The calibration results show that the method accurately estimates the aerosol mass concentration during the smoking events. We show that black-box calibrators are more accurate than white-box calibrators. However, black-box calibrators may drift easily when a new smoking event occurs, while white-box calibrators remain robust. Therefore, we implement both of the calibrators in parallel to extract both calibrators' strengths and also enable drifting monitoring for calibration models. We also discuss that our method is implementable for other types of low-cost sensors suffered from sensing accuracy.Peer reviewe

Effect of molecular bending on the photodissociation of OCS

At 230 nm, the photodissociation of OCS via a hot band and a triplet state was investigated by selective probing of high rotational levels of product CO (Jϭ45-67) with photofragment imaging spectroscopy: . Additional two-photon IR excitation of the UV photoprepared OCS with intense 1.06 m laser pulses bleaches the UV processes listed above and induces a new excitation channel of OCS: OCS(vϭ0)ϩh(UV͒→OCS*, OCS*ϩ2h(IR͒→CO(X 1 ⌺ ϩ ,J ϳ74)ϩS( 1 S). The bending mode of OCS in the excited states plays a central role in the excitation and dissociation dynamics. Additionally, the alignment effect of OCS by nonresonant infrared laser pulse, which appears on the angular distribution of the photofragment, is discussed

Transit Pollution Exposure Monitoring using Low-Cost Wearable Sensors

Transit activities are a significant contributor to a person's daily exposure to pollutants. Currently obtaining accurate information about the personal exposure of a commuter is challenging as existing solutions either have a coarse monitoring resolution that omits subtle variations in pollutant concentrations or are laborious and costly to use. We contribute by systematically analysing the feasibility of using wearable low-cost pollution sensors for capturing the total exposure of commuters. Through extensive experiments carried out in the Helsinki metropolitan region, we demonstrate that low-cost sensors can capture the overall exposure with sufficient accuracy, while at the same time providing insights into variations within transport modalities. We also demonstrate that wearable sensors can capture subtle variations caused by differing routes, passenger density, location within a carriage, and other factors. For example, we demonstrate that location within the vehicle carriage can result in up to 25% increase in daily pollution exposure -- a significant difference that existing solutions are unable to capture. Finally, we highlight the practical benefits of low-cost sensors as a pollution monitoring solution by introducing applications that are enabled by low-cost wearable sensors.Peer reviewe

Mobile Measurement of PM2.5 Based on an Individual in Ulaanbaatar City

In the present study, we measured fine particulate matter (PM2.5) on the daily route of our study participant in order to determine her exposure and dose of PM2.5 in every microenvironment (ME). The measuring instrument, created by Nagoya University and Panasonic Corporation, Japan, was carried close to the breathing zone most of the time. Each data point was collected for 10–30 s or 2–6 cycles/min for 24 h from 1 October 2018 to 30 December 2018. Public transportation showed the highest level of PM2.5 compared with other MEs, including residence apartments, houses (ger district), the National University of Mongolia (NUM), food courts or restaurants, and other indoor locations. The personal daily average exposure to PM2.5 was 35 µg/m3 on 4 November 2018; on the other hand, this value was evaluated as the highest level of exposure compared to other measurement days. Interestingly, the study participant‘s exposure and dose of PM2.5 was lower than those stated in the World Health Organization (WHO) air quality guidelines, with 25 µg/m3 from 4:00 to 7:00