• Title/Summary/Keyword: 미세먼지 측정망

Search Result 18, Processing Time 0.223 seconds

Study on Optimal Location of Air Pollution Monitoring Networks in Urban Area Using GIS : Focused on the case of Seoul City (GIS를 이용한 도심지 대기오염 측정망 최적위치 선정에 대한 연구 : 서울특별시를 대상으로)

  • Kim, Ayoung;Kwon, Changhee
    • Journal of the Society of Disaster Information
    • /
    • v.12 no.4
    • /
    • pp.358-365
    • /
    • 2016
  • Micro dust is closely related to real life. Especially, the micro dust forecasting system is being implemented from February 2014. Reliability of data through air pollution monitoring network is important. The Ministry of Environment operates 506 air pollution monitoring networks (11 types) to analyze national air quality and establish air policies. However, there is not enough system to confirm and check the site suitability of the measurement site. Therefore, this study analyzes urban space using GIS. Assess the appropriateness and equity of air pollution measurement facilities. The final goal is to reflect the results of the analysis into the Seoul Metropolitan Air Pollution Monitoring Network Installation Plan.

A Study on the Spatial Position Problem of PM Monitoring Stations Using Voronoi Technique and Density Analysis (보로노이 기법과 밀도분석을 활용한 미세먼지 측정소 공간적 위치 문제 연구)

  • Jeong, Jong-Chul
    • Journal of Cadastre & Land InformatiX
    • /
    • v.48 no.2
    • /
    • pp.185-195
    • /
    • 2018
  • In the Seoul Metropolitan City, the PM(pariculate matter) application used by the citizens provides the PM concentration of the nearest monitoring stations located on the PM monitoring stations. Currently, the selecting method of the PM monitoring network considered by the Ministry of Environment is based on considering the monitoring station distribution and population density only. In this study, we analyzed the distance between PM monitoring station and the administrative center point in addition to the above considerations. The number of test sites was verified and the range of coverage of each monitoring stations was indicated by using the Voronoi algorithm and hexagon grid. The spatial position problem of the PM monitoring station was suggested by spatial data analysis. The variables of spatial data analysis are single-family houses, apartments, $1^{st}$ class neighborhood, $2^{nd}$ class neighborhood, garbage disposal plant, hazardous material disposal facility, factory, and the density map. The analysis result of the selection criterion considering the additional variables for new PM monitoring stations was presented, in addition to the selection criteria provided by the Ministry of Environment.

Conformity Assessment of Machine Learning Algorithm for Particulate Matter Prediction (미세먼지 예측을 위한 기계 학습 알고리즘의 적합성 평가)

  • Cho, Kyoung-woo;Jung, Yong-jin;Kang, Chul-gyu;Oh, Chang-heon
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.23 no.1
    • /
    • pp.20-26
    • /
    • 2019
  • Due to the human influence of particulate matter, various studies are being conducted to predict it using past data measured in the atmospheric environment monitoring network. However, it is difficult to precisely set the measurement environment and detailed conditions of the previously designed predictive model, and it is necessary to design a new predictive model based on the existing research results because of the problems such as the missing of the weather data. In this paper, as a previous study for particulate matter prediction, the conformity of the algorithm for particulate matter prediction was evaluated by designing the prediction model through the multiple linear regression and the artificial neural network, which are machine learning algorithms. As a result of the prediction performance comparison through RMSE, 18.13 for the MLR model and 14.31 for the MLP model, and the artificial neural network model was more conformable for predicting the particulate matter concentration.

Development of the sustainable solar cell powered LTE based IoT fine dust detecting terminal (태양전지를 이용한 지속 가능형 LTE 기반 IoT 미세먼지 측정 단말기 개발)

  • Kim, Howoon;Woo, Dong Sik
    • Journal of IKEEE
    • /
    • v.25 no.1
    • /
    • pp.109-115
    • /
    • 2021
  • In this paper, the fine dust detecting terminal which can transmit data in real time was developed. The terminal used a wide spreading LTE network and was powered by solarcell and battery for easy installation and independent operation, because it did not need the wired power grid or wired communication network. The data showed the possibility of forecasting fine dust changes by analyzing with the data from public meteorologic data. The developed terminal will be helpful for predicting and analyse fine dust's more precise flow and effect on environment with an easy installation on any places.

Environmental Equity Analysis of Fine Dust in Daegu Using MGWR and KT Sensor Data (다중 스케일 지리가중회귀 모형과 KT 측정기 자료를 활용한 대구시 미세먼지에 대한 환경적 형평성 분석)

  • Euna CHO;Byong-Woon JUN
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.26 no.4
    • /
    • pp.218-236
    • /
    • 2023
  • This study attempted to analyze the environmental equity of fine dust(PM10) in Daegu using MGWR(Multi-scale Geographically Weighted Regression) and KT(Korea Telecom Corporation) sensor data. Existing national monitoring network data for measuring fine dust are collected at a small number of ground-based stations that are sparsely distributed in a large area. To complement these drawbacks, KT sensor data with a large number of IoT(Internet of Things) stations densely distributed were used in this study. The MGWR model was used to deal with spatial heterogeneity and multi-scale contextual effects in the spatial relationships between fine dust concentration and socioeconomic variables. Results indicate that there existed an environmental inequity by land value and foreigner ratio in the spatial distribution of fine dust in Daegu metropolitan city. Also, the MGWR model showed better the explanatory power than Ordinary Least Square(OLS) and Geographically Weighted Regression(GWR) models in explaining the spatial relationships between the concentration of fine dust and socioeconomic variables. This study demonstrated the potential of KT sensor data as a supplement to the existing national monitoring network data for measuring fine dust.

A study on the Concentration and Chemical Characteristics in the Ambient of Incheon (인천시 대기중 미세먼지의 농도 및 화학적 특성에 관한 연구)

  • 허화영;장기원;원경호;정용원
    • Proceedings of the Korea Air Pollution Research Association Conference
    • /
    • 2003.11a
    • /
    • pp.370-371
    • /
    • 2003
  • 인천시는 수도권의 외항으로 많은 발전을 하였으나, 반대 급부적으로 오염의 가중을 제어하지 못하고 있는 형편이다. 인천시의 여러 가지 환경문제 중에서도 대기환경 문제는 매우 심각하여 여러 가지 환경문제 중에서도 가장 민원이 많은 부분이다 또한 최근 들어 대기 중 먼지에 대한 관심은 주로 미세먼지에 집중되고 있으며, 우리나라의 먼지에 대한 대기환경기준과 대기오염 측정망의 항목은 공기역학적 직경 10$\mu\textrm{m}$이하의 PM$_{10}$으로 정해 놓고 있다. 그러나 최근 많은 연구에서 PM$_{10}$보다 미세한 먼지를 기준으로 설정하고 그 기준 농도도 낮추어야 한다는 주장이 제기되고 있다. (중략)

  • PDF

Particulate Matter Prediction using Multi-Layer Perceptron Network (다층 퍼셉트론 신경망을 이용한 미세먼지 예측)

  • Cho, Kyoung-woo;Jung, Yong-jin;Kang, Chul-gyu;Oh, Chang-heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2018.10a
    • /
    • pp.620-622
    • /
    • 2018
  • The need for particulate matter prediction algorithms has increased as social interest in the effects of human on particulate matter increased. Many studies have proposed statistical modelling and machine learning techniques based prediction models using weather data, but it is difficult to accurately set the environment and detailed conditions of the models. In addition, there is a need to design a new prediction model for missing data in domestic weather monitoring station. In this paper, fine dust prediction is performed using multi-layer perceptron network as a previous study for particulate matter prediction. For this purpose, a prediction model is designed based on weather data of three monitoring station and the suitability of the algorithm for particulate matter prediction is evaluated through comparison with actual data.

  • PDF

Spatial distribution of particulate matters in comparison with land-use and traffic volume in Seoul, Republic of Korea (서울시 토지이용과 교통량에 따른 미세먼지의 공간분포)

  • Jeong, Jong-Chul;Lee, Peter Sang-Hoon
    • Journal of Cadastre & Land InformatiX
    • /
    • v.48 no.1
    • /
    • pp.123-138
    • /
    • 2018
  • To sustainably monitor air pollution in Seoul, the number of Air Pollution Monitoring Station has been gradually increased by Korea's Ministry of Environment. Although particulate matters(PM), one of the pollutants measured at the stations, have an significant influence on human body, the concentration of PM in Korea came in second among 35 OECD member countries. In this study, using the data of PM concentration from the stations, distribution maps of PM10 and PM2.5 concentrations over Seoul were generated, and spatial factors potentially related to PM distribution were investigated. Based on a circumscribed hexagon about a circle in radius of 500 meters created as a basic unit, Seoul was sectionalized and PM concentration map was generated using the interpolation technique of 'inverse distance weighting'. The distributions of PM concentrations were investigated with commuting time by administrative district and the outcome was related with land-use type and volume of traffic. Results from this analysis indicated distribution pattern of PM10 concentration was different from that of PM2.5 by administrative district and time. The distribution of PM concentration was strongly related to not only the size of business and trafficked areas among the land-use type, but also the existence of urban green. Further analysis of the relationship between the PM concentration and detailed land-use and urban green maps can be helpful to identify spatial factors which have an impact on the PM concentration on the regional scale.

Spatial Information Application Case for Appropriate Location Assessment of PM10 Observation Network in Seoul City (서울시 미세먼지 관측망 위치 적정성 평가를 위한 공간정보 활용방안)

  • Jeong, Jong-Chul
    • Journal of Cadastre & Land InformatiX
    • /
    • v.47 no.2
    • /
    • pp.175-184
    • /
    • 2017
  • Recently, PM10 is becoming a main issue in Korea because it causes a variety of diseases, such as respiratory and ophthalmologic diseases. This research studied to spatial information application cases for evaluating the feasibility of the location for PM10 observation stations utilizing Geogrphic Information System(GIS) spatial analysis. The spatial Information application cases for optimal location assessment were investigated to properly manage PM10 observation stations which are closely related with public spatial data and health care. There are 31 PM10 observation stations in Seoul city and the observed PM10 data at these stations were utilized to understand the overall assessment of PM10 stations to properly manage using interpolation methods. The estimated PM10 using Inverse Distance Weighted(IDW) and Kriging techniques and the map of PM10 concentrations of monitoring stations in Seoul city were compared with public spatial data such as precipitation, floating population, elementary school location. On the basis of yearly, seasonal and daily PM10 concentrations were used to evaluate the feasibility analysis and the location of current PM10 monitoring stations. The estimated PM10 concentrations were compared with floating population and calculated 2015 PM10 distribution data using zonal statistical methods. The national spatial data could be used to analyze the PM10 pollution distribution and additional determination of PM10 monitoring sites. It is further suggested that the spatial evaluation of national spatial data can be used to determine new location of PM10 monitoring stations.

The Variation Analysis on Spatial Distribution of PM10 and PM2.5 in Seoul (서울시 PM10과 PM2.5의 공간적 분포 변이분석)

  • Jeong, Jongchul
    • Journal of Environmental Impact Assessment
    • /
    • v.27 no.6
    • /
    • pp.717-726
    • /
    • 2018
  • PM(Particulate Matter) cause serious diseases of air pollution. Most of the studies have analyzed local distribution trends using satellite images or modeling techniques. However,the method using the spatial interpolation method based on the meteorological value is insufficient in Korea. In this study, monthly spatial distribution of $PM_{10}$ and $PM_{2.5}$ in January, February, March, and April of 2018 Seoul Metropolitan City were analyzed based on 39 PM monitoring networks. In addition, a distribution map showing the difference between $PM_{10}$ and $PM_{2.5}$ was based on the distribution obtained through this study. The regions of high $PM_{10}$ and $PM_{2.5}$ emissions were selected. In addition, the correlation between $PM_{10}$ and $PM_{2.5}$ was confirmed through the distribution map. This study analyzed the spatial distribution variation results of analyzing $PM_{10}$ and $PM_{2.5}$ in Seoulthrough spatial analysis technique. As a result of this study, it was confirmed that $PM_{10}$ shows high measured value on the roadside measurement station.