Community and environmental data-driven monitoring of waste management

ABSTRACT

Environmental operators perform their activities in accordance with the relevant legal provisions; however, this does not mean that they operate at their technological optima using the operational information available. The possible negative effects (odor, noise, etc.) of a sub-optimal operation can be felt first and foremost by those living in the immediate vicinity of the given object. It would be important to make effective use of these citizens feedback (quickly to revealing the root causes) thus minimize negative environmental impact of operations. The solution proposed in this paper is a portal called EnviroMind, which allows citizens feedback to be recorded in an easy, immediate, and structured way via a form and on the other hand, it provides a real-time graphical odor transmission model output in a dashboard to operators. Using this portal as a monitoring system the magnitude of the odor effect could be reduced and a smaller area around the industrial object could be affected. In a landfill monitoring pilot project where this monitoring system was used the decrease in the number of indicated odor observations was 85% and the decrease in maximal distance from landfill to odor detection positions was 45%. It is proposed to use EnviroMind monitoring system for all industrial objects which have a significant odor effect on the environment, because by using it we can make the odor effect visible to operators in real time, thus, the reaction time for solving the problem can be minimized.

Implications: monitoring is available online to the surrounding community, the affected population, so that quick responses and interventions are available; in the knowledge of the current technological activity carried out on the site its expected odor effect in the area can be determined, whether a protected area can be reached and what odor concentration is expected; in every 15 minutes model results to accurately track expected odor emission values; possibility of intervention, stopping or modification of the technology steps. Experience and main achievements of portal operation in a landfill monitoring pilot project from recent 3 years: the decreasing number of odor perceptions (the decrease in the number of indicated observations was 85%) and the cessation of odor effects in certain areas (and the decrease in maximal distance from landfill to odor detection positions was 45%).

Authors’ contribution

The work was divided amongst the authors as follows: Ferenc Péter Pach: system design, research management and data analysis, László Morzsa: system development (hardware and software), Gergely Erdős: system development support (data security validation and graphic design of the user interface), Imre Magyar: modeling of odor transmission, and Zoltán Bihari: DNA sequencing and determination of bacterial composition.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Abbreviation

AERMOD	=	American Meteorological Society/Environmental Protection Agency Regulatory Model
DNA	=	Deoxyribonucleic Acid
IPPC	=	Integrated Pollution Prevention and Control
MQTT	=	Message Queuing Telemetry Transport standard.

Supplementary material

Supplemental data for this paper can be accessed on the publisher’s website.

Web references

(w1) Waag, technology & society portal: https://waag.org/en/lab/smart-citizens-lab

(w2) Safecast Japan: portal: https://blog.safecast.org/about/

(w3) 16S Metagenomic Sequencing Library Preparation: https://support.illumina.com/content/dam/illumina-support/documents/documentation/chemistry_documentation/16s/16s-metagenomic-library-prep-guide-15,044,223-b.pdf

(w4) AERMOD Implementation Guide: https://www3.epa.gov/ttn/scram/models/aermod/aermod_implementation_guide.pdf

(w5) Vector computations of wind: http://www.webmet.com/met_monitoring/622.html

Additional information

Funding

The project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 774234 (see details in https://cordis.europa.eu/project/id/774234).

Notes on contributors

Ferenc Péter Pach

Ferenc Péter Pach graduated as master of engineering in information technology at Pannon University in 2004. Between 2004 and 2007 he participated in research and development projects of chemical systems and he received a PhD in 2008 (at Pannon University). Between 2007 and 2012 he worked as a data analyst in the pharmaceutical, telecommunication and retail sectors. He worked as a researcher between 2012 and 2015, with primary research in data mining and system and process development (secondary areas: biostatistics, bioinformatics). Since 2015 he has been working as a data scientist consultant in his own company, Tritoo Informatics Ltd. Peter works primarily in health and sustainability projects of the Institute of Advanced Studies Kőszeg.

László Morzsa

László Morzsa studied computer engineering at the Óbuda University. He completed his studies with a specialization in software technology at the University of Dunaújváros. He has experience in the development of geographic information systems, the design of databases and data cleaning. He works as a software and data engineer at the Institute of Advanced Studies Kőszeg in projects related to business and cultural networks and sustainability.

Gergely Erdős

Gergely Erdős studied at the Budapest University of Technology and Economics and at the Harvard Business School. He gained qualifications in big data and bioinformatics at the University of California, the University of Toronto and the Johns Hopkins University. His big data-based research focuses on the fields of healthcare, transport and environmental protection. The major objective of his research in the Institute of Advanced Studies Kőszeg is to identify the anomalies of patients pathways with colon and colorectal cancer.

Imre Magyar

Imre Magyar studied at the University of Veszprem and Budapest University of Technology and Economics. He got diploma M.Sc. in Chemical Engineering, later he got diploma of advanced level in Environmental Engineering and a postgraduate diploma in Occupational Health and Safety Engineering. He worked at the Pannon University as assistant professor and researcher. His educational and research activity was geographical information systems, environmental modeling and monitoring, and environmental information systems. Nowadays he works as environmental expert. His projects are related to environmental modeling (air pollutants, noise, hydrodynamics and transport in subsurface water, surface water), environmental and occupational monitoring (measuring workplace air properties, noise level, make air pollution and noise maps). He develops GIS based EHS information systems.

Zoltán Bihari

Zoltán Bihari is a molecular biologist who earned his PhD in biotechnology from the University of Szeged. During his research career, he was the Head of Department for Metagenomics and then the Head of the GMP-certified Laboratory of Medicine at Bay Zoltán Nonprofit Ltd. for Applied Research. Formerly, Zoltán was the Field Application Specialist of Illumina NGS products at GeneTiCA Ltd. His main areas of expertise are Next Generation Sequencing, metagenomics and human diagnostics. He has been coordinating R&D&I projects and supervising high-throughput NGS laboratories for 10 years. He is the Founder & CEO of an NGS service provider company, Xenovea Ltd.