Allocating optimum sites for air quality monitoring stations using GIS suitability analysis

Alsahli, Mohammad M. M.; Al‐Harbi, Meshari

doi:10.1016/j.uclim.2017.11.001

Cited by 25 publications

(18 citation statements)

References 29 publications

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“…In order to capture a cross section of the GKMA urban environment, we used parish level population distribution, observed satellite imagery from Google earth, knowledge of local context and availability of data for the 211 period of interest to identify four monitoring locations based on land use clusters i.e., residential/urban background and urban/traffic typically characteristic of land uses within the greater Kampala. This is also informed by the known pollution dynamics for various land uses (Harrison and Deacon 1998;Spangl et al 2007;Alsahli and Al-Harbi 2018).…”

Section: Study Location (Context)mentioning

confidence: 97%

Exploring PM2.5 variations from a low-cost sensor network in Greater Kampala, during COVID-19 imposed lockdown restrictions: Lessons for policy

et al. 2022

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Air pollution is considered a major public health risk globally, and the global South including sub-Saharan Africa face particular health risks, but there is limited data to quantify the level of pollution for different air quality contexts. The COVID-19 lockdown measures led to reduced human activities, and provided a unique opportunity to explore the impacts of reduced activities on urban air quality. This paper utilises calibrated data from a low-cost sensor network to explore insights from the diverse ambient air quality profile for four urban locations in Greater Kampala, Uganda before and during lockdown from March 31 to May 5 2020, highlighting the uniqueness of air pollution profiles in a sub-Saharan African setting. All locations saw year to year improvements in 24-hour mean PM2.5 between 9 μg/m3 and 25 μg/m3 and correlated well with reduction in traffic (up to approx. 80%) and commercial activities. The greatest improvement was observed in locations close to major transport routes in densely populated residential areas between 8:00 pm and 5:00 am. This suggests that the reduction in localised pollution sources such as nocturnal polluting activities including traffic and outdoor street cooking characteristic of fast-growing cities in developing countries, coupled with meteorological effects led to amplified reductions that continued well into the night, although meteorological effects are more generalised. Blanket policy initiatives targeting peak pollution hours could be adopted across all locations, while transport sector regulation could be very effective for pollution management. Likewise, because of the clustered and diffuse nature of pollution, community driven initiatives could be feasible for long-term mitigation.

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Section: Study Location (Context)mentioning

confidence: 97%

Exploring PM2.5 variations from a low-cost sensor network in Greater Kampala, during COVID-19 imposed lockdown restrictions: Lessons for policy

et al. 2022

View full text Add to dashboard Cite

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“…A very important factor in establishing effective air quality monitoring programs is to assign the optimal location for monitoring stations based on five criteria (population, wind direction, spatial proximity to roads, industries, and high traffic areas) that are considered the most important criteria [50]. Three important metropolitan regions of Mexico were selected to monitor according to their pollution indexes: Region Lagunera Coahuila-Durango, metropolitan area of Monterrey, N.L and the metropolitan area of Guadalajara, Jal.…”

Section: Location Measurement Site Selectionmentioning

confidence: 99%

Smart Multi-Sensor System for Remote Air Quality Monitoring Using Unmanned Aerial Vehicle and LoRaWAN

Camarillo-Escobedo

Flores

Marin-Montoya

et al. 2022

Sensors

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Deaths caused by respiratory and cardiovascular diseases have increased by 10%. Every year, exposure to high levels of air pollution is the cause of 7 million premature deaths and the loss of healthy years of life. Air pollution is generally caused by the presence of CO, NO2, NH3, SO2, particulate matter PM10 and PM2.5, mainly emitted by economic activities in large metropolitan areas. The problem increases considerably in the absence of national regulations and the design, installation, and maintenance of an expensive air quality monitoring network. A smart multi-sensor system to monitor air quality is proposed in this work. The system uses an unmanned aerial vehicle and LoRa communication as an alternative for remote and in-situ atmospheric measurements. The instrumentation was integrated modularly as a node sensor to measure the concentration of carbon monoxide (CO), nitrogen dioxide (NO2), ammonia (NH3), sulfur dioxide (SO2), and suspended particulate mass PM10 and PM2.5. The optimal design of the multi-sensor system has been developed under the following constraints: A low weight, compact design, and low power consumption. The integration of the multi-sensor device, UAV, and LoRa communications as a single system adds aeeded flexibility to currently fixed monitoring stations.

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“…Based on the previous studies, those five major criteria are acquired. The five main steps were involved in these suitability analyses are mentioned in Figure 1 (Alsahli & Al-Harbi, 2018). (Alsahli & Al-Harbi, 2018)).…”

Section: Geographic Information System (Gis)mentioning

confidence: 99%

A short review on different techniques used for site selection of air quality monitoring stations

Kollati

Debnath

2021

Ind. Eng. Decis. Mak.

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Air pollution has become a serious concern across the world in the last few decades. In specific cities, the air quality index value had changed from very unhealthy to a hazardous level of health concern. Air pollution has a serious impact on daily lives in those cities. Monitoring of air pollution is becoming necessary these days. Air quality monitoring stations are installed to get the air pollution data, which indicates in the air quality index (AQI) value. In order to contain a proper air quality index (AQI) value, it is essential to locate the air quality monitoring stations in the appropriate place of the study area. Several techniques were being used for site selection of air quality monitoring stations for the last few decades. In this short review, all such techniques have been studied systematically, and comprehensive analysis has been reported for further use by the scientific community and policymakers. In this study, the methods used in the site selection of air quality monitoring stations were categorized into four groups. (1) Multi-Criteria Decision Making (MCDM) techniques; (2) Geographical Information System (GIS); (3) hybrid techniques; and (4) miscellaneous. In the site selection of air quality monitoring stations, the decision-makers should consider various parameters based on the study area. While considering various parameters, the problem solving becomes complex. At this point, MCDM techniques, GIS, and Hybrid techniques are found to be helpful tools for the decision-makers.

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Allocating optimum sites for air quality monitoring stations using GIS suitability analysis

Cited by 25 publications

References 29 publications

Exploring PM2.5 variations from a low-cost sensor network in Greater Kampala, during COVID-19 imposed lockdown restrictions: Lessons for policy

Exploring PM2.5 variations from a low-cost sensor network in Greater Kampala, during COVID-19 imposed lockdown restrictions: Lessons for policy

Smart Multi-Sensor System for Remote Air Quality Monitoring Using Unmanned Aerial Vehicle and LoRaWAN

A short review on different techniques used for site selection of air quality monitoring stations

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