Measurement report: Effect of wind shear on PM₁₀ concentration vertical structure in the urban boundary layer in a complex terrain

The paper shows wind shear impact on PM10 vertical profiles in Kraków, southern Poland. The data used consist of background data for two cold seasons (September 2018 to April 2019 and September 2019 to April 2020) and data for several case studies from November 2019 to March 2020. The data are composed of PM10 measurements, model data, and wind speed and direction data. The background model data come from operational forecast results of the AROME model. PM10 concentration in the vertical profile was measured with a sightseeing balloon. Significant spatial variability of the wind field was found. The case studies represent the conditions with much lower wind speed and a much higher PM10 level than the seasonal average. The inversions were much more frequent than on average too. Wind shear turned out to be the important factor in terms of PM10 vertical profile modification. It is generated due to the relief impact, i.e. the presence of a large valley, blocked on one side with the hills. The analysis of PM10 profiles from all flights allows us to distinguish three vertical zones of potential air pollution hazards within the valley (about 100 m deep) and the city of Kraków: (1) up to about 60 m a.g.l. – the zone where during periods of low wind speed, air pollution is potentially the highest and the duration of such high levels is the longest, i.e. the zone with the worst aerosanitary conditions; (2) about 60–100 m a.g.l. – transitional zone where the large decrease in PM10 levels with height is observed; (3) above 100–120 m a.g.l. – the zone where air quality is significantly better than in zone 1, either due to the increase in the wind speed or due to the wind direction change and advection of different, clean air masses.

Multivariate Optimization of Extraction Variables of PAH in Particulate Matter (PM10) in Indoor/Outdoor Air at Campos dos Goytacazes, Brazil

Polycyclic aromatic hydrocarbons (PAH) are products of incomplete combustion of biomass and fossil fuels, that are produced on a larger scale by anthropogenic sources. Burning sugarcane plantations can be a source of atmospheric PAH in regions where this culture predominates. Campos dos Goytacazes, Brazil, is surrounded by sugarcane crops that still use fire as a facilitating method for the harvesting process. This study aims to evaluate the presence of outdoor and indoor PAH in 10 µm particulate matter (PM10) at one university in Campos dos Goytacazes. PM10 samples were collected from January to November 2018. Samples were extracted using an ultrasonic probe and analyzed by gas chromatography coupled to mass spectrometry (GC-MS). The ideal extraction conditions (3 min; 150 W; 50 mL) were defined by 23 full factorial design. The analysis showed a significant PM10 level increase (23.19 to 34.50 µg m-3 in outdoor, and 15.15 to 31.66 µg m-3 in indoor samples) and higher total PAH concentration in the harvesting season (outdoor: 0.73 ng m-3; indoor 0.52 ng m-3) than in non-harvesting season (outdoor: 0.49 ng m-3; indoor: 0.28 ng m-3), however, average PAH values found in outdoor samples in harvesting season did not show significant difference from non-harvesting season.

Variation of Particulate Matter (PM10) in a Semi-urban Area during 2015 Malaysia Haze

Particulate matter (PM10) is one of the most dangerous air pollutants released during haze phenomena which can disrupt lung function, circulatory system and reduce visibility. The aims of this study were to determine the trend of PM10 in Tanjung Malim, Perak during 2015 haze episode. The four months trend of PM10 was analyzed, along with daily trend for the highest concentration of PM10 recorded during the haze episode. In addition, the correlation between PM10 and meteorological parameters, such as wind speed, temperature, and humidity were also analyzed. Result indicated that, PM10 level during September and October 2015, have mostly exceeded the Recommended Malaysian Air Quality Guidelines (RMAQG) by Malaysian Government (150 μg/m3). From the 72h backward trajectories, it can be stated that most of the pollutants came from biomass burning in neighbouring country, during the southwest monsoon. Changes in PM10 concentration were possibly influenced by meteorological factors which play an important role in haze episode.

CO-BENEFIT MODELING AND OPTIMIZATION OF AIR POLLUTION CONTROL IN ISKANDAR MALAYSIA: A METHODOLOGY USING BenMAP

Malaysia is currently experiencing issues of local as well as transboundary air pollution. The issues are especially felt in areas that record high economic growth and rapid urbanization such as Iskandar Malaysia, a fast evolving economic-growth corridor in Southeast Asia. This has led to increased rate of particulate matter emissions, which further led to increase in the rate of respiratory-related health incidences. Many epidemiological studies have proven that particulate matters in the ambient air are associated with adverse health effects. This will affect the existing and future economy of Iskandar Malaysia, where the exposed population may lose their workdays and face increased medical spending. This study focuses on quantifying health and economic benefits from the reduction of particulate matter with a size of 10 micrometers or less in diameter (PM10) using the Environmental Benefits Mapping and Analysis Program (BenMAP) by US EPA. Health impact functions are used to quantify the relationship between a change in PM10 level and number of related health effects among the exposed population. The samples for this research include a continuous monitoring data on the 2014 monthly average of daily PM10, the 2014 population projection of Malaysian Census Data and the PM10 related health cases for 2014 which are focused in the Iskandar Malaysia region. PM10 data are collected from monitoring stations operated by the Department of Environment (DOE). Respiratory related cases such as Upper Respiratory Tract Infection, which is categorized as J10 in International Classification of Diseases, are collected from selected clinics within the study area. The final outcome of the modeling exercise compares the co-benefits of air pollution reduction between the baseline scenario and the control scenario for PM10 level in Iskandar Malaysia. The results of this study are useful in optimizing and improving the existing policies and strategies for controlling air pollution and PM10 emission in Iskandar Malaysia.

CO-BENEFIT MODELING AND OPTIMIZATION OF AIR POLLUTION CONTROL IN ISKANDAR MALAYSIA: A METHODOLOGY USING BenMAP

Malaysia is currently experiencing issues of local as well as transboundary air pollution. The issues are especially felt in areas that record high economic growth and rapid urbanization such as Iskandar Malaysia, a fast evolving economic-growth corridor in Southeast Asia. This has led to increased rate of particulate matter emissions, which further led to increase in the rate of respiratory-related health incidences. Many epidemiological studies have proven that particulate matters in the ambient air are associated with adverse health effects. This will affect the existing and future economy of Iskandar Malaysia, where the exposed population may lose their workdays and face increased medical spending. This study focuses on quantifying health and economic benefits from the reduction of particulate matter with a size of 10 micrometers or less in diameter (PM10) using the Environmental Benefits Mapping and Analysis Program (BenMAP) by US EPA. Health impact functions are used to quantify the relationship between a change in PM10 level and number of related health effects among the exposed population. The samples for this research include a continuous monitoring data on the 2014 monthly average of daily PM10, the 2014 population projection of Malaysian Census Data and the PM10 related health cases for 2014 which are focused in the Iskandar Malaysia region. PM10 data are collected from monitoring stations operated by the Department of Environment (DOE). Respiratory related cases such as Upper Respiratory Tract Infection, which is categorized as J10 in International Classification of Diseases, are collected from selected clinics within the study area. The final outcome of the modeling exercise compares the co-benefits of air pollution reduction between the baseline scenario and the control scenario for PM10 level in Iskandar Malaysia. The results of this study are useful in optimizing and improving the existing policies and strategies for controlling air pollution and PM10 emission in Iskandar Malaysia.

EXTREME VALUE ANALYSIS FOR MODELING HIGH PM10 LEVEL IN JOHOR BAHRU

Extreme value theory is a very well-known statistical analysis for modeling extreme data in environmental management. The main focus is to compare the generalized extreme value distribution (GEV) and the generalized Pareto distribution (GPD) for modeling extreme data in terms of estimated parameters and return levels. The maximum daily PM10 data for Johor Bahru monitoring station based on a 14 years database (1997-2010) were analyzed. It is found that the parameters estimated are more comparable if the extracted numbers of extreme series for both models are much more similar. The 10-years return value for GEV is while for GPD is . Based on the threshold choice plot, threshold is chosen and the corresponding 10-years return level is . According to the air pollution index in Malaysia, this value is categorized as hazardous.

Spatial distribution and interannual variation of surface PM₁₀ concentrations over eighty-six Chinese cities

The spatial distribution of the aerosols over 86 Chinese cities was reconstructed from air pollution index (API) records for summer 2000 to winter 2006. PM10 (particulate matter ≤10 μm) mass concentrations were calculated for days when PM10 was the principal pollutant, these accounted for 91.6% of the total 150 428 recorded days. The 83 cities in mid-eastern China (100° E to 130° E) were separated into three latitudinal zones using natural landscape features as boundaries. Areas with high PM10 level in northern China (127 to 192 μg m−3) included Urumchi, Lanzhou-Xining, Weinan-Xi'an, Taiyuan-Datong-Yangquan-Changzhi, Pingdingshan-Kaifeng, Beijing-Tianjin-Shijiazhuang, Jinan, and Shenyang-Anshan-Fushun; in the middle zone, high PM10 (119–147 μg m−3) occurred at Chongqing-Chengdu-Luzhou, Changsha-Wuhan, and Nanjing-Hangzhou; in the southern zone, only four cities (Qujing, Guiyang, Guangzhou and Shaoguan) showed PM10 concentration >80 μg m−3. The median PM10 concentration decreased from 108 μg m−3 for the northern cities to 95 μg m−3 and 55 μg m−3 for the middle and southern zones, respectively. PM10 concentration and the APIs both exhibited wintertime maxima, summertime minima, and the second highest values in spring. PM10showed evidence for a decreasing trend for the northern cities while in the other zones urban PM10 levels fluctuated, but showed no obvious change over time. The spatial distribution of PM10 was compared with the emissions, and the relationship between the surface PM10 concentration and the aerosol optical depth (AOD) was also discussed.