scholarly journals On the Temporal Variability of Air Pollutants’ Emissions – Case Study of Residential PM10 Emission in Silesian Metropolis

2020 ◽  
Vol 3 (1) ◽  
pp. 21-29
Author(s):  
Damian Zasina ◽  
Jarosław Zawadzki
Keyword(s):  
Air Pollutants ◽  
Air Pollutant ◽  
Hot Water ◽  
Pollutant Emission ◽  
Air Quality Modelling ◽  
Air Emission ◽  
Temporal Disaggregation ◽  
Monthly Distribution ◽  
Heating Degree Days

AbstractThe paper summarizes previous studies associated with carrying out of the air pollutant emission inventories. There are presented three approaches for obtaining monthly distribution of PM10 air emission: using expert’s judgement, modelling of the heating demand, and temporal disaggregation using the heating degree days (HDD). However some differences due to not considering hot water demand, it can be effectively used for obtaining temporal, and spatiotemporal distributions of air pollutants’ air emissions necessary for air quality modelling.

scholarly journals The Characteristics of PM2.5 Pollution and Policy Implications in Chungcheong Region

2021 ◽  
Vol 43 (6) ◽  
pp. 407-418
Author(s):  
Jiyoung Gong ◽  
Changsub Shim ◽  
Ki-Chul Choi ◽  
Sungyong Gong
Keyword(s):  
Power Generation ◽  
Air Quality ◽  
Air Pollutants ◽  
Air Pollutant ◽  
Policy Implications ◽  
Pollutant Emission ◽  
Air Quality Modelling ◽  
Emission Volume ◽  
High Level ◽  
Pm2.5 Concentration

Objectives : This study aims to discuss air quality policy improvement that reflect regional characteristics through analyzing recent PM2.5 concentration, air pollutant emission sources and those contributions to annual PM2.5 concentration in Chungcheong region (Daejeon Metropolitan City, Sejong Metropolitan Autonomous City, the Province of Chungcheongnam-do, and Chungcheongbuk-do) in South Korea. In addition, we identified the characteristics of the PM2.5 pollution at the level of fundamental local government, and demonstrated the number of vulnerable population exposed to high level of PM2.5 concentration in order to propose policy implications in Chungcheong region.Methods : Based on the national emissions estimates (CAPSS: Clean Air Policy Support System) and air quality modelling system, major sectors/sources of air pollutants emission and national contributions of PM2.5 concentrations in Chungcheong region were analyzed. Furthermore, the study identified the number of people exposed to the higher PM2.5 concentrations (>25 µg/m3) by the measurement data and demographics available in 2019.Results and Discussion : The national air pollutants emissions in Chungcheong region were emitted from Chungnam (about 59% of NOx emission volume, 89% of SOx, 70% of NH3, 54% of VOCs, 79% of PM2.5, and 68% of TSP respectively), mainly from industry, domestic, energy, and road sector. According to the results of the air quality modelling, Chungcheong region also had the largest contribution on the average annual PM2.5 concentration in South Korea (27%). Chungnam emitted the largest emission volume of air pollutants, mainly from industry and power generation sectors (especially in Dangjin, Seosan, and Boryeong), while Asan, Yesan, Hongseong, and Cheongyang were classified as the areas with higher PM2.5 concentrations (>25 µg/m3), showing a gap between the areas with large emission volume and high concentration. Chungbuk and Sejong had higher annual PM2.5 concentration due to the influence of external sources and their geographical characteristics. The largest vulnerable population (over 65 years old and under 18 years old) exposed to high PM2.5 concentrations annually lived in Cheongju. Chungbuk had about 40% more air pollutant emission volume than Chungnam, but about 17% more vulnerable population.Conclusions : At the current stage of “master plan” in Chungcheong region, it is important to mitigate air pollutants emissions on the basis of the local emissions characteristic at the level of fundamental local government (such as industry sector in Dangjin, Seosan, and Danyang/ Domestic buring in Cheongju, Cheonan, and Daejeon/power generation in Boryeong, Taean and Dangjin/ road in Daejeon, Cheongju, and Cheoan). In addition, Chungbuk requires management of the areas with higher PM2.5 concentration such as Goesan, Boeun, Okcheon, and Yeongdong located outside “air control zone”. To reduce high level of PM2.5 concentration in Chungcheong region, cooperation with neighboring local governments such as Gyeonggi Province is crucial, and policy solutions are needed between the stakeholders to resolve the disparity issues between areas with larger emission volume and higher PM2.5 concentration.

scholarly journals Estimation of the spatial distribution of maximum PM10 and PM2.5 concentration in Bandung City and surrounding countries using WRF-Chem Model (case study in July and October 2018)

2021 ◽  
Vol 893 (1) ◽  
pp. 012044
Author(s):  
H Salsabila ◽  
A Turyanti ◽  
DE Nuryanto
Keyword(s):  
Pollutant Dispersion ◽  
Meteorological Factor ◽  
Air Pollutant ◽  
Pollutant Concentration ◽  
Pollutant Emission ◽  
Dispersion Pattern ◽  
Model Case ◽  
The Public ◽  
Pollutant Distribution

Abstract Bandung is one of big cities in Indonesia with high activities on industrial and transportation that will increase the air pollutant emission and causes adversely affect the public health. Based on that matter, monitoring of air pollutant concentration is urgently needed to predict the direction of pollutant dispersion and to analyze which locations are vulnerable to maximum exposure of the pollutant. Field monitoring of air pollutant concentration needs much time and high cost, but modeling could help for this. One of the models that can be used to predict the direction of pollutant distribution is the Weather Research Forecasting/Chemistry (WRF-Chem) model, which is a model that combines meteorological models with air quality models. The output of the WRF-Chem running model on July and October 2018, which has been analyzed visually, showed the dispersion pattern of PM10 and PM2.5 is spread mostly to the west, northwest, and north following the wind direction. According to the output of the WRF-Chem model, Bandung Kulon is the most polluted subdistrict by PM10 and PM2.5 with an exposure frequency of 22 hours (PM10), 24 hours (PM2.5) on July 2018 and 19 Hours (PM10), 14 hours (PM2.5) on October 2018. The correlation value for meteorological parameters is quite high in July 2018 (R = 0.9 for wind speed and R = 0.82 for air temperature). So based on the meteorological factor, WRF-Chem model can be used to predict the direction of pollutant distribution.

scholarly journals Analysis of Environmental Benefits of Shore Power for Preventing and Controlling Air Pollution Caused by Vessels at Berth

2018 ◽  
Vol 53 ◽  
pp. 04036 ◽  
Author(s):  
Cheng Jieling ◽  
Li Haibo
Keyword(s):  
Energy Conservation ◽  
Fuel Consumption ◽  
Air Pollutants ◽  
Emission Reduction ◽  
Electric Energy ◽  
Air Pollutant ◽  
Environmental Benefits ◽  
Pollutant Emission ◽  
Current Status ◽  
Fuel Consumption Rate

When vessels are berthed at ports, the air pollutants emitted by auxiliary engines will cause severe pollution to the ports and surrounding environments. In view of this situation, the author first summarizes the Chinese policies and policies of foreign countries on emission of air pollutants from vessels at berth, and then analyses the current status of and measures for control of air pollutant emission from vessels at berth. Secondly, the author analyses the environmental benefits of using shore power for better controlling air pollutant emission from vessels at berth, compares vessels using shore power with vessels using generated power in the energy conservation and emission reduction effects based on the fuel consumption rate of different auxiliary engines and current status of pollutant emission from power generation in China etc., analyses the current status of shore power application in China, estimates the energy conserved and emission reduced when shore power is used by vessels at berth. Thirdly, the author identifies the scale of electric energy replacement by, and environmental benefits of, shore power at ports in China. This paper delivers innovative approaches to the comparison between the effects of energy conservation and emission reduction based on fuel consumption rates of different auxiliary engines and estimation of conserved energy and reduced emission.

scholarly journals Quantifying Air Pollutant Emission from Agricultural Machinery Using Surveys—A Case Study in Anhui, China

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 440
Author(s):  
Yi Ai ◽  
Yunshan Ge ◽  
Zheng Ran ◽  
Xueyao Li ◽  
Zhibing Xu ◽  
...  
Keyword(s):  
Fuel Consumption ◽  
Road Traffic ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Pollutant Emission ◽  
Agricultural Machinery ◽  
Activity Data ◽  
Road Traffic Emissions ◽  
Using Data

Diesel-powered agricultural machinery (AM) is a significant contributor to air pollutant emissions, including nitrogen oxides (NOx) and particulate matter (PM). However, the fuel consumption and pollutant emissions from AM remain poorly quantified in many countries due to a lack of accurate activity data and emissions factors. In this study, the fuel consumption and air pollutant emission from AM were estimated using a survey and emission factors from the literature. A case study was conducted using data collected in Anhui, one of the agricultural provinces of China. The annual active hours of AM in Anhui ranged 130 to 175 h. The estimated diesel fuel consumption by AM was 1.45 Tg in 2013, approximately 25% of the total diesel consumption in the province. The air pollutants emitted by AM were 57 Gg of carbon monoxide, 14 Gg of hydrocarbon, 74 Gg of NOx and 5.7 Gg of PM in 2013. The NOx and PM emissions from AM were equivalent to 17% and 22% of total on-road traffic emissions in Anhui. Among nine types of AM considered, rural vehicles are the largest contributors to fuel consumption (31%) and air emissions (33–45%).

scholarly journals Estimation of Air Pollutant Emissions in Eastern Indonesia from Non-Oil and Gas Sources (Case Study in Sulawesi and Papua)

2018 ◽  
Vol 3 (3) ◽  
pp. 152
Author(s):  
Dessy Gusnita ◽  
Dita Fatria
Keyword(s):  
Air Pollutants ◽  
Oil And Gas ◽  
Estimation Method ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Pollutant Emission ◽  
Eastern Indonesia ◽  
South Sulawesi ◽  
Emission Estimation ◽  
Papua Barat

<p>Estimation of air pollutant emissions from non-oil and gas sources in eastern Indonesia, namely Sulawesi and Papua provinces during the period 2014 – 2016 was conducted. This paper intended to estimate the emission of three air pollutants namely NOx, SO<sub>2</sub> and CO<sub>2</sub>. The aim was to find out the amount of pollutant and greenhouse gas (<em>GHG</em>) emissions in the Sulawesi and Papua regions. The method used was the emission estimation method based on statistical data of Gross Regional Domestic Income (GRDP) in the Papua and Sulawesi regions. The results from estimation of pollutant emissions was then carried out for pollutant emissions mapping. The pollutant emission estimation showed the emission of air pollutants in Sulawesi region was higher than Papua. The mapping of emissions in Sulawesi were consisted of four provinces, namely north, central, south and southeast Sulawesi. The Papua region were consisted of Papua and west Papua provinces. The highest emission in Sulawesi region was south Sulawesi. The CO<sub>2</sub> emission in Sulawesi was increase about 23% with the detail value; 84.4 tons in 2014; 94.3 tons in 2015; and 103.7 tons in 2016. The emission of NOx during 2014 until 2016 are 0.53, 0.58 and 0.64 tons, there was an increasing in the emission of NOx around 21%. In addition, SO<sub>2</sub> emission of south Sulawesi are 0.42 tons in 2014, 0.47 tons in 2015 and 0.51 tons in 2016, increased about 21 % during the year 2014 - 2016. In the Papua region, the emission in Papua was higher than Papua Barat province. CO<sub>2</sub> emissions in Papua during 2014 -2016 were 112, 124.8 and 144.99 tons, it means the CO<sub>2</sub> was increased 29%. The emission of NOx during 2014-2016 were 0.70, 0.77 and 0.89 tons, increased around 27%. In addition, SO<sub>2</sub> emission was increase 26% with the detail value; 0.56 tons in 2014; 0.61 tons in 2015 and 0.71 tons in 2016.</p><p> </p><p><strong><em></em></strong><strong><em><br /></em></strong><em></em></p>

scholarly journals Improving the Professional Level of Managers Through Individualized Recommendation to Enhance the Quality of Air Pollutant Management in China

2019 ◽  
Vol 11 (21) ◽  
pp. 6094
Author(s):  
Xiao ◽  
Qin ◽  
Fu ◽  
Zhang
Keyword(s):  
Air Pollutants ◽  
Recommendation System ◽  
Fossil Fuel ◽  
Rapid Development ◽  
Air Pollutant ◽  
Pollutant Emission ◽  
Full Picture ◽  
Regional Air Quality ◽  
Assessment Strategies

With the rapid development of the economy, and fossil fuel consumption lacking systematic emission controls, China has experienced substantially elevated concentrations of air pollutants, which not only degrades regional air quality but also poses significant impacts on public health. However, faced with the demand for a large number of experts in air pollution protection, people with real expertise for air pollutant management are difficult to find. Therefore, individualized recommendation is an effective and sustainable method for enhancing the professional level of managers and is good for improving the quality of air pollutant management. Thus, this paper initially proposes a novel framework to recommend strengths in air pollutant management. This framework comprises four stages: data preprocessing is the first stage; then, after constructing ability classifications and ability assessment strategies, activity experiences are transformed into corresponding ability values; next, a multilayer perceptron deep neural network (MLP-DNN) is used to predict potential types according to their ability values; finally, a hybrid system is constructed to recommend suitable and sustainable potential managers for air pollutant management. The experiments indicate that the proposed method can assess the full picture of people’s strengths, which can recommend suggestions for building a scientific and rational specialties recommendation system for governments and schools. This method can have significant effects on pollutant emission reduction by enhancing the professional level of managers with regard to air pollutant management.

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