Pollution Mapping Research Articles

Railway Noise Pollution: An Investigation of Rail Systems in Terms of Noise Pollution Regulations and Land Usage

Noise pollution caused by transportation has become problem for societies with increasing traffic volumes and the development of cities day by day. In European countries and Turkey, transportation-related noise pollution has caused health problems as well as reducing the living standards of the people. It is necessary to carry out detailed studies in order to determine the problems caused by noise pollution, especially in the regions where industry and labor force are concentrated, and to solve these problems. The city of Izmir is one of the cities where the noise caused by the railway needs to be investigated. As a result of the studies carried out in the research area, the railway noise pollution map was created with the IDW method with the data obtained from 8 different points. Afterwards, the effect of railway systems on the land usage types of cities, noise pollution problems, and the period between 2000-2018 were examined. The negative effects of noise pollution caused by the railway in the hinterland of the suburban line in the study area and its effect on the land usage type were investigated with the EU and Turkey Noise Regulation and the land cover data of the European Environment Agency.

Воздействие мобильных и стационарных источников загрязнений на геоэкологическое состояние урбанизированных территорий в горном регионе

Introduction. The air quality problems facing the world today become aggravated by rapid urban population growth, uncontrolled urban and industrial expansion and a phenomenal growth in the number and time of car use. In general, geoecological pollution of the territory is caused by stationary and mobile sources. The industry in the most of the regions today is experiencing degradation to one degree or another. At the same time, operating plants and factories, especially those associated with the processing of toxic heavy metals, are mostly equipped with filter systems that significantly reduce the territory pollution. On the other hand, in recent years, road transport has taken the first place in terms of urban areas pollution. Road traffic is the largest source of many air pollutants that are harmful to health, but emissions from internal combustion engines are not the only source of pollution. Car tyres and parts of brake systems are also a significant source of environmental pollution. Thus, the assessment of the level of environmental pollution by road transport seems to be a very urgent task. Research methods. Experimental research methods were used in the work. The authors introduced a new integral index of atmospheric air pollution Zatm. The assessment of the level of atmospheric air pollution was carried out using the Ecolab gas analyzer based on a specially developed measurement technique. The data of the existing foreign works on the assessment of environmental pollution by tyre wear products were also considered as the source material. The obtained data were extrapolated to the territory of Vladikavkaz city. Map compilation was carried out using geoinformation modeling methods. Research results. As part of the study of tyre wear for the territory of Vladikavkaz city, it was found that about 258 tons of tyre wear products are emitted into the city’s environment per year, which is 860 grams per head of population. On the basis of the obtained data on the actual content of carbon monoxide, hydrocarbons С1-С10 and nitrogen and sulfur dioxides in the atmospheric air, a distribution map of the integral index of atmospheric air pollution Zatm in Vladikavkaz city was constructed. The map identified the sections of roads that are subjected to the greatest pollution Discussion. Traffic optimization models, in particular, “green corridors”, are currently being proposed as mitigation measures for pollutant emissions from road transport. Based on the analysis of the obtained data, which form the basis of the constructed maps of atmospheric air pollution in Vladikavkaz city, Recommendations for reducing the ecological load of road transport on the environment have been developed. Conclusion. Today, when most stationary sources (plants, factories, mining and processing centers, etc.) have practically stopped their activity or equipped with special treatment systems (filters, modern technologies), it is mobile pollution sources that emit the largest amount of pollutants. Road transport forms a high level of load on the geo-ecological state of the territory environment. The analysis of the obtained results made it possible to develop Recommendations for reducing pollutant emissions from road transport, which, due to the evergrowing number of vehicles and, as a result, increasing environmental pollution, is an actual result of the work. Resume. On the basis of the obtained data on the actual content of carbon monoxide, hydrocarbons and nitrogen and sulfur dioxides in the atmospheric air, a distribution map of the introduced integral index of atmospheric air pollution Zatm in Vladikavkaz city was constructed. The map identifies the sections of roads that are subjected to the greatest pollution. In addition to the exhausts of internal combustion engines, car tyres are also considered as a pollution source and the assessment is given according to the amount of emissions generated by their wear particles. Recommendations are given to reduce the ecological load of road transport on the environment. In the future, it is planned to carry out experimental investigations to study the dynamics of emissions, as well as to study the concentrations of other pollutants.

Development and application of a multi-scale modeling framework for urban high-resolution NO2 pollution mapping

Abstract. Vehicle emissions have become a major source of air pollution in urban areas, especially for near-road environments, where the pollution characteristics are difficult to capture by a single-scale air quality model due to the complex composition of the underlying surface. Here we developed a hybrid model CMAQ-RLINE_URBAN to quantitatively analyze the effects of vehicle emissions on urban roadside NO2 concentrations at a high spatial resolution of 50 m × 50 m. To estimate the influence of various street canyons on the dispersion of air pollutants, a machine-learning-based street canyon flow (MLSCF) scheme was established based on computational fluid dynamics and two machine learning methods. The results indicated that compared with the Community Multi-scale Air Quality (CMAQ) model, the hybrid model improved the underestimation of NO2 concentration at near-road sites with the mean bias (MB) changing from −10 to 6.3 µg m−3. The MLSCF scheme obviously increased upwind concentrations within deep street canyons due to changes in the wind environment caused by the vortex. In summer, the relative contribution of vehicles to NO2 concentrations in Beijing urban areas was 39 % on average, similar to results from the CMAQ-ISAM (Integrated Source Apportionment Method) model, but it increased significantly with the decreased distance to the road centerline, especially on urban freeways, where it reached 75 %.

Ubiquitous Micro Mapping of Air Pollution Using Vehicular Edge-Based Connected IoT Services

The phenomenon of air pollution is being discussed everywhere around the globe. The monitoring of air pollution is the crucial and first step to formulating any laws for pollution control. An exhaustive mapping and monitoring approach for air pollution can be of huge asset to our society. However, the initial step of monitoring needs to be performed with utmost care. The efforts in this direction have already been made, considering measures like installing air quality monitoring stations in parts of cities. But, the existing systems are stagnant, and the data aggregated from these stations is regarded as the pollution level of even far-fetched regions. This completely ignores the spatial variation of air pollution in different sub-regions and poses a significant challenge to getting insights at the sub-region level. A proposition for this obstacle has been discussed in this article. The proposed solution would be a great asset for government/non-government agencies to check pollution levels at different locations and plan countermeasures more effectively. In the proposed method, vehicles are fitted with edge computing-based Internet of Things (IoT) powered sensing devices. The networking ability of Vehicular Ad-hoc NETwork (VANET) is adopted for creating an IoT-connected environment to capture the pollution level of any sub-region in real-time, providing dynamic nature to the air pollution monitoring scheme. By leveraging the power of these technologies, it is easier to get pollution details of the complete route that the vehicle has to pass through to its destination. Travelling via a route with lesser pollution would be a boon for people with an aversion to air pollution or respiratory issues. Chandigarh, a Union Territory of India, has been taken under case study to verify state of the art. The city is already equipped with three continuous air quality monitoring towers by which the pollution levels of the whole 114 sq meter of the city are monitored. The results depict the variation of maximum and minimum values captured in a stagnant monitoring tower to the proposed dynamic system. Using the dynamic systems, air pollution levels of even different regions fall on the route between these monitoring stations. In summary, the edge-based vehicular system can be used to provide pollution-free route tracking, thereby changing the dynamics of healthy living.

GIS Based Mapping and Assessment of Noise Pollution in Gazipur City, Bangladesh

Noise pollution is an extensive concern for urban areas around the world. Gazipur is one of the significant hubs of the garment industry in Bangladesh. The purpose of the study was to address the highest sources of noise pollution in this City and identify the public perceptions of noise pollution. Noise levels have been measured from 38 locations of the City from 8.00 am to 6.00 pm including industrial, mixed, commercial, residential, and sensitive zones on both working and non-working days. ArcGIS based assessment using IDW spatial interpolation technique was used for the mapping of the measured noise levels across the study area. The highest average noise level (100.9 dB) was observed at Joydebpur Junction in the period of the evening (4.00 pm to 6.00 pm) and the lowest average noise level (47.5 dB) was observed in front of the Banghabandhu Satellite Ground Station in the period of the afternoon (12.00 pm to 2.00 pm). Heavy industrialization, vehicles horn, construction sites, traffic noise, loudspeakers, expired engines, loud talking, and outdoor parties are the extensive reasons for the increase in noise pollution in Gazipur City. Study showed that the noise level in every location was higher than the standard levels. Survey data indicated that city dwellers endure noise pollution headaches, irritable moods, sleeplessness, bad temper, and stress. This study strongly suggests that proper implementation of the existing laws helps to mitigate and reduce the noise pollution situation in the study area.

High-resolution mapping of the rainfall runoff pollution: case study of Shiwuli River watershed, China.

Rainfall runoff is the key factor of water quality deterioration in highly urbanized area, which is characterized by intensive human activities and frequent extreme weather events. Urban landscape system is composed of highly diverse and heterogeneous land patches, which makes the effective management of urban runoff pollution difficult. Therefore, high-resolution land-use data is imperative for the identification and analysis of spatial-temporal characteristics of urban runoff pollution. In this study, Shiwuli River watershed, a rapidly urbanizing area in China, is selected as the study area. We first interpret nine kinds of land-use types with a high-resolution remote sensing data of 2m [Formula: see text] 2m. Then, a localized Soil Conservation Service model based on field observation and rainfall experiments is applied to map the spatial-temporal pattern of runoff pollution. The results indicate that the COD, NH3-N, TP, and TN load generated by the runoff in the watershed accounted for 23.4%, 3.7%, 8.2%, and 9.0% of the total pollution load in 2016, respectively. Furthermore, the spatial-temporal pattern of the assessed runoff pollution was mainly subject to the distribution of rainfall and land-use patterns. We suggest that the sponge city construction combined with surface pollution control is an effective way to reduce the runoff pollution. This study highlights the necessity to identify spatial-temporal hotspots in developing precise pollution control measures, which provides valuable information for pollution control policy-making in Shiwuli River watershed and could serve as a reference for other river watersheds undergoing rapid urbanization.

Evaluation of Outdoor Environment PM10 Concentration in an Organized Industrial Zone Using Geographical Information System

Air pollution adversely affects human health, visibility distance, materials, plants and animal health. Air pollution’s impact on human health arises from inhaling high amounts of harmful substances in the atmosphere. Notably, our understanding of the damage caused by PM10 pollutants is improving daily. This study aims to measure and analyze PM10 pollution in the Konya Organized Industrial Zone at certain times and places. Measurements were taken at twenty-four locations in the morning, noon and evening hours. The results were compared with the Turkish Air Quality Assessment and Management Regulation, and pollution maps of the regions were created with Surfer Software and ArcGIS 10.1 programs. With the measurements, it was observed that the times at which the limit was exceeded were mainly the evening hours. While no limit exceedance was recorded in the morning hours, the average concentration value was observed once in those hours, and around noon the maximum value was observed five times. In this study, we correlated the measurement results, the values of the measurement points located in the city center and the average number of vehicles passing through the region. It was observed that the PM10 -induced air pollution in the Konya Organized Industrial Zone was caused by dense traffic during evening hours. To prevent traffic-related pollution in the region, it is recommended to increase the number of entrance and exit gates in the industrial zone and to plant trees in appropriate sections.

The Capability of Astrotourism on Preserving Sustainability: A Case Study in Malaysia

Astrotourism is tourism that uses astronomy as its main attraction. As astrotourism requires astronomy phenomena, it requires a location free from light pollution. As some have posited locations free from light pollution as one of the cultivating elements for maintaining sustainability, Astrotourism can be used to achieve sustainability. Sustainability can be put under the umbrella of Maqasid Syariah and halal tourism. It is thus of utmost importance to demonstrate the unique capabilities of Malaysia as a viable Astrotourism attraction and how it can help achieve the goal of sustainability, both of which are the objectives of this research. Two methods are employed in this study; the first is to identify potential Astrotourism sites using the dark sky database, light pollution mapping and Garstang formulation of light pollution. The second method is comprised of identifying the cultivating elements of sustainability. Through this method, three potential Astrotourism sites could enhance the notion of sustainability, including sustainability from the economic, wellbeing and biodiversity aspects and, more importantly, sustainability towards the holistic practice of Islam. This demonstrates the encompassing benefit of Astrotourism towards sustainability and its development potential in Malaysia.

Use of a drone-based sensor as a field-ready technique for short-term concentration mapping of air pollutants: A modeling study

While a network of low-cost sensors (LCS) boosts the capability in monitoring of air quality as covering a wide area, its fixed positioning hinders pinpointing of an unknown emitting source, its accuracy is variable over time, and its operation requires more periodic calibration than the USEPA's reference monitors. Alternatively, for short-term concentration mapping and regulatory compliance assessment, a drone equipped with a single reference sensor to detect the target air pollutant may provide a highly accurate concentration mapping tool as it offers flexibility to maneuver over hard-to-access terrains while addressing the abovementioned limitations. In this modeling study, we focused on a hypothetical point source emitting a certain air pollutant steadily inside a 1 km by 1 km study area. With respect to true concentrations generated from such source using USEPA's SCREEN3 Gaussian dispersion model and an inverse distance weighing (IDW) approach, we developed R and Python scripts to plot concentration and reliability maps for when a drone-based reference sensor/a stationary network of LCS is deployed to reconstruct the concentration maps. First, we compared the impact of the drone flight path on 1-hr-averaged concentration mapping of an air pollutant for locating a hidden point source or concentration accuracy determination at certain regions. Then, we conducted sensitivity analyses on the drone-based mapping reliability under different number of drone passes, wind speeds, and wind directions. Our results showed that compared to S-, N-, Z-, and diagonal-shape drone travel paths for the same travel total time, the time-averaged mapping accuracy of a zigzag drone flight is the best for pinpointing an unknown point source. For concentration mapping of known air polluting sources, which is intended to provide the utmost accuracy, an increase in the number of drone passes from the source to the downstream receptor points improves reliability of the projected dispersing plume. When flown under a windy condition (wind speeds above 3 m/s), concentration maps are underestimated for the most part, and the bias reduces when the drone travels in parallel to the wind direction. The outcomes of this study shed light on optimized development of the drone-based air quality sensors as proof-of-concept of a field-ready device to facilitate accurate short-term air quality monitoring or regulatory compliance of the air pollutants with hourly thresholds.

Neighborhood Emission Mapping Operation (NEMO): A 1-km anthropogenic emission dataset in the United States

We present an unprecedented effort to map anthropogenic emissions of air pollutants at 1 km spatial resolution in the contiguous United States (CONUS). This new dataset, Neighborhood Emission Mapping Operation (NEMO), is produced at hourly intervals based on the United States Environmental Protection Agency (US EPA) National Emission Inventories 2017. Fine-scale spatial allocation was achieved through distributing the emission sources using 108 spatial surrogates, factors representing the portion of a source in each 1 km grid. Gaseous and particulate pollutants are speciated into model species for the Carbon Bond 6 chemical mechanism. All sources are grouped in 9 sectors and stored in NetCDF format for air quality models, and in shapefile format for GIS users and air quality managers. This dataset shows good consistency with the USEPA benchmark dataset, with a monthly difference in emissions less than 0.03% for any sector. NEMO provides the first 1 km mapping of air pollution over the CONUS, enabling new applications such as fine-scale air quality modeling, air pollution exposure assessment, and environmental justice studies.

Polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) soil contamination in Lausanne, Switzerland: Combining pollution mapping and human exposure assessment for targeted risk management

In December 2020, high soil concentrations of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) were discovered across large parts of Lausanne, Switzerland. Concentrations reached up to 640 ng TEQWHO-2005/kg dry weight. The most likely source was a former municipal waste incinerator. A three-step, multidisciplinary approach to human health risk assessment was conducted to determine the potential population exposure to PCDD/Fs and identify appropriate preventive measures. First, exposure scenarios were developed based on contaminated land uses. Second, the toxicological risks of different scenarios were evaluated using a toxicokinetic model estimating increases in blood serum PCDD/F concentrations over background concentrations from the general population's food consumption. Third, a detailed geostatistical mapping of PCDD/F soil contamination was performed. Stochastic simulations with an external drift and an anisotropic model of the variogram were generated to incorporate the effects of distance from emission source, topography, and main wind directions on the spatial distribution of PCDD/Fs in topsoil. Three main scenarios were assessed: i) direct ingestion of soil by children in playgrounds; ii) consumption of vegetables from private gardens by children and adults; and iii) consumption of food from livestock and poultry raised on contaminated soil. The worst exposure scenario involved the consumption of eggs from private hen houses, resulting in PCDD/F concentrations in serum an order of magnitude higher than might normally be expected. No relevant increases in serum concentrations were calculated for direct soil ingestion and vegetable consumption, except for cucurbitaceous vegetables. Combining mapping and exposure scenario assessment resulted in targeted protective measures for land users, especially concerning food consumption. The results also raised concerns about the potential unsafe consumption of products derived from animals raised on land with PCDD/F concentrations only moderately over environmental background levels.

Integrating statistical and agent-based modelling for activity-based ambient air pollution exposure assessment

Assessment of long-term human exposure to spatiotemporally highly variable air pollution requires accounting for human space–time activity. Individual exposure and space–time track data are not available over large populations and for long periods and a modelling approach is required. However, activity-based exposure models face here challenges in setting up the model and overly-large computations. Aiming for long-term and large-population simulations, we propose an activity model which integrates statistical and agent-based modelling by treating mobility-related variables as random variables. Probability distributions for these variables are estimated or derived from mobility datasets containing observed activities. On top of the activity model, we implemented an exposure model. A case-study of exposure assessment was developed using hourly air pollution maps. The activity model can potentially integrate any mobility data and is thus applicable when limited time activity data is available at the individual level.

Review on invasion of microplastic in our ecosystem and implications.

Today the world is going through the "Plastic Age." Nowadays, it is difficult to find a commonly used convenient item that is nonplastic. Plastic production and consumption, thus, increased exponentially and plastic emerged as one of the major concerns for waste management. Recent studies confirmed a faster rate of plastic degradation than previously believed under various conditions (e.g. saltwater, UV, soil interaction) that microplastic has become a new type of health-hazardous pollution source. Much research has been conducted since the discovery of the "Pacific Garbage Patch," and the scope has expanded from marine to soil, groundwater, air, and food chain. This article underwent a substantial amount of literature review to verify the degree of microplastic pollution progression in major pillars of the environment (aqueous, terrestrial, airborne, bio-organism, and human). Multiple kinds of literature indicated a high possibility of vigorous interaction among the pillars that microplastic is not stationary at the point of contamination but travels across the nation (transboundary) and medium (transmedium). Thus, only the waste reduction policy (i.e. production and consumption reduction) would be effective through a single national or local effort, while pollution and contamination management require more of a collective, if not global, approach. For these characteristics, this article proposes two most urgently required actions to combat microplastic pollution: (a) global acknowledgement of microplastic as transboundary and transmedium pollution source that require international collective action and (b) standardization of microplastic related research including basic definition and experimental specification to secure global comparativeness among data analysis. Without resolving these two issues, it could be very difficult to obtain an accurate global status mapping of microplastic pollution to design effective and efficient global microplastic pollution management policies.

Device for automatic measurement of light pollution of the night sky

Research on light pollution of the night sky has been carried out in Toruń, Poland since 2017. Initially, the measurements were conducted within a network of 24 points using a handheld sky quality meter with lens (SQM-L) photometer (Unihedron, Canada). Based on these measurements, the first accurate maps of night sky pollution by artificial light in Toruń have been developed, both in seasonal and annual terms. Using the experience gained and elements of modern technology, a decision was made to construct an automatic network of mobile devices measuring light intensity at night, covering the entire city of Toruń. This paper presents the technical characteristics of the constructed automatic measurement devices that make up the distributed monitoring network and the process of testing and using the devices. The implementation of this project has started in 2020. To accommodate the evolving expectations of different user groups and the observed trends in the concept of Smart Cities, especially those related to the communication between devices of the Internet of Things, LoRaWAN was selected for data transmission. The first stage involved the construction of a prototype of an automatic, portable and cost-effective device, which was subjected to months of field testing under operational conditions. The device was built using off-the-shelf electronic components and a housing that met the requirements for outdoor use. The next stage was to calibrate the device by simultaneously comparing the obtained results with measurements taken using professional SQM devices. This was followed by the preparation of 35 identical devices, which are already operating in the measurement network in the city of Toruń. Elements of the network are prepared in a way that allows for further expansion and makes data available in the form of an application for many recipients.

Toward High-Performance Map-Recovery of Air Pollution Using Machine Learning

Mobile and pervasive sampling of urban air pollution has been increasingly valued as a sustainable method, in terms of economic and operational factors, for surveying atmospheric environment with high space-time resolution. Specifically, fine-granular air quality (AQ) inference provides fundamental progress toward data-driven urban management, as it estimates grid-level pollutant concentrations constantly using pollutant measurement data collected from fixed and mobile sensors. In this paper, we propose a tree-based multicascade space-time learning model (MCST-Tree) for AQ inference to recover pollution maps by exploiting multisource AQ samples (fixed and mobile) and heterogeneous urban feature sets (land-use, meteorology, population, traffic, etc.). This is implemented and evaluated in a study case of Chengdu (4900 km2, 14 June to 14 July 2018), which achieves map-recovery of PM2.5 distribution based upon the sparse measurements (ca. 16.2% space-time coverage) with high-performance (symmetric mean average percentage error (SMAPE) (%) = 14.13%; R2 = 0.94). Detailed evaluations are presented through the analysis of model performance, space-time coverage of mobile sampling, and AQ inference. We conduct a series of sensitivity analyses of mobile sampling coverage, and the experimental results show that it is a critical issue to enhance the model trust, which contributes to improve the R-square from 0.81 (fixed data + 10% mobile data) to 0.94 (fixed data + 100% mobile data). The results show that the mobile sampling significantly improves the space-time modeling capability, and our proposed model has great potential to achieve map-recovery for air pollution at high spatial-temporal resolution with high performance.

Validation of X-Ray Fluorescence Spectrometer Technique to Determine Heavy Metal Concentrations in Soil Samples

Heavy metal soil pollution had increased in recent years and this has produced adverse effects to human wellbeing’s health by being up taken in the food chain. A potential threat of heavy metal pollution was suspected at the Government Farm in Għammieri. This is due to heavy traffic and fireworks causing concern to the farmers who cultivate fruit and vegetables in these fields. Soil sampling with an instrument that can give rapid results was needed to analyse the data and give the real-time in-situ mapping of heavy metal pollution in the soil. Comparison between an X-Ray Fluorescent (XRF) spectrometer and an Inductively Coupled Plasma –Mass Spectrometer (ICP-MS), both of which are conventional analytical techniques, was performed to measure the heavy metals in the soil by using laboratory and field work. This was performed to make sure that the XRF that was being used, would give accurate results before testing larger sample size. The XRF used was situated at the Department of Chemistry, at the University of Malta, whilst the ICP-MS was situated in Germany, at an accredited laboratory. Five samples were collected from around the whole field, where each sample was split into 2 identical batches.

Microplastic rapid screening method development using automated mineralogy

Microplastic is a significant global problem. The rapid screening of environmental matter is highly beneficial to the efficient detection, analysis and mapping of microplastic pollution, however many current laboratory techniques to test samples are time-consuming and often involve hazardous chemicals. SEM-based automated mineralogy (AM) is a uniquely powerful tool for quantifying chemical, mineral and textural properties for a wide-range of sample types. This paper presents an attempt to use AM to identify and quantify microplastic within a heterogeneous surrounding matrix using QEMSCAN® (Quantification and Evaluation of Minerals by Scanning Electron Microscopy). Here, the standard AM processes are adapted to develop an entirely new methodology, involving the use of a novel mounting medium for sample preparation and the building of a Species Identification Protocol (SIP) using polymer standards. The results show potential, although challenges include the over-quantification of plastic and differentiation from natural matter. Additional challenges relate to limitations regarding the particular AM system used, which places restrictions on methodology, but which may be overcome with newer systems. This study indicates that, with further refinement, AM may have future potential as a high-throughput, cost-effective, initial screening step to identify highly microplastic-polluted areas and accelerate research into establishing solutions.

Improved Hyperlocal Air Quality Mapping: Can Traditional Deterministic Modelling Leverage Mobile Monitoring via Hybrid Modelling Approaches?

BACKGROUND AND AIM: Recent advances in mobile monitoring offer excellent opportunities to explore the hyperlocal variation of ambient air pollution. One example is Google Street View (GSV) car equipped with high-quality instruments. Here, some challenges are translating on-road pollution levels to the building façades and the scalability of such mapping at large spatial scales, e.g. national scale. Since "traditional” deterministic modelling has been a reliable method for pollution assessment and mapping, this talk aims to explore whether deterministic modelling, via hybrid modelling, can help address the challenges mentioned above and leverage mobile monitoring for improved pollution mapping. METHODS: Three GSV cars measured hyperlocal levels of nitrogen dioxide (NO2), black carbon (BC) and Ultrafine particles (UFP) on all streets of Amsterdam (N = 46664) and Copenhagen (N = 28499) from October 2018 to March 2020. The measurements were corrected and, among others, compared with pollution estimates from national prediction models, the Danish DEHM-UBM-AirGIS, and the Dutch NSL (National Collaborative Air Quality Programme). Further, model estimates are incorporated with GSV measurements to test and apply hybrid modelling approaches using statistical (e.g. kriging) and machine learning techniques. RESULTS: Overall, Amsterdam's measured pollution levels were relatively higher (e.g. median NO2 = 24 µg/m3) than in Copenhagen (median NO2 = 13 µg/m3). In addition, GSV NO2 measurements correlated moderately (Spearman’s r = 0.50) (N = 7004) with the NSL estimates in Amsterdam, whereas in Copenhagen, the Spearman’s correlation (r) was in the range 0.45 – 0.67 (N = 97 and 58234). CONCLUSIONS: High-quality mobile monitoring offers a great way to study the hyperlocal variation of air pollution. Since the modelled vs measured correlation was moderate to slightly high, combining both datasets may better predict external data. The presentation will reflect on hybrid model development. KEYWORDS: Mobile measurements, Google Street View, deterministic modelling, AirGIS, hybrid model

Association between Air Pollution and Squamous Cell Lung Cancer in South-Eastern Poland.

Air pollution is closely associated with the development of respiratory illness. The aim of the present study was to assess the relationship between long-term exposure to PM2.5, PM10, NO2, and SO2 pollution and the incidence of lung cancer in the squamous subtype in south-eastern Poland from the years 2004 to 2014. We collected data of 4237 patients with squamous cell lung cancer and the level of selected pollutants. To investigate the relationship between the level of concentrations of pollutants and the place of residence of patients with lung cancer in the squamous subtype, proprietary pollution maps were applied to the places of residence of patients. To analyze the data, the risk ratio was used as well as a number of statistical methods, i.e., the pollution model, inverse distance weighted interpolation, PCA, and ordered response model. Cancer in women and in men seems to depend in particular on the simultaneous inhalation of NO2 and PM10 (variable NO2PM10) and of NO2 and SO2 (variable NO2 SO2), respectively. Nitrogen dioxide exercises a synergistic leading effect, which once composed with the other elements it becomes more persistent in explaining higher odds in the appearance of cancers and could constitute the main cause of squamous cancer.

Maps of solid-fuel use and household air pollution

Nearly 3 million people are estimated to die from household air pollution every year, the overwhelming majority of whom live in low-income and middle-income countries (LMICs).1 Reliance on solid-fuel use for cooking, heating, and lighting substantially contributes to household air pollution. Thus, replacing solid fuels with clean energy sources in LMICs is a priority goal for public health.2 In view of the substantial health burden attributable to household air pollution, access to affordable clean energy is one of the Sustainable Development Goals (SDGs) set by the UN in 2015, which are to be achieved by 2030.