Dr. Sumith Satheendran S.

Geography is concerned with what is seen in the wider world. It is a descriptive subject frequently linked to the humanities that only recently began utilizing quantitative tools.The use of GIS technology and software is pervasive in daily life, and everyone has some experience with it. These are not only tools for geographers.In contrast to geography, chemistry has always been a science of the hardly visible, dealing with enigmatic substances that are invisible to the naked eye and only reachable through knowledge that the average person equates more with magic than with geographic descriptions or the geometrical clarity of Galilean physics.

Chemicals are the industry that is most despised worldwide despite being crucial to human survival.Despite the fact that this complex and extensive enterprise affects every moment of modern life, the general public’s perception of it is rather unfavourable.”Without chemistry, existence is both unfathomable and incomprehensible”. This is not without justification. The industry has been connected to terrible events ever since the 1924 catastrophe at the chemical company’s (BASF) ammonium nitrate factory through the 1984 Bhopal Union Carbide plant disaster.The harmful effects of chemicals due to excessive exposure, improper use, ignorance of long-term effects of chemicals, etc. have also contributed to the negative public perception, claims S. K. Hazra, Chairman of the Safety and Health Expert Committee with the Indian Chemical Council, the top industry association.

Based on the author’s personal experience with geospatial assessment, this article offers a fundamental overview of Geographic Information Systems (GIS) for chemical professionals, including its applications, and trends. Geospatial analysis can be complementary in many scientific, economic, and environmental applications even though it is mutually incompatible with chemical engineering.The principles of GIS and chemical fate and transport modeling are both explored by GIS-based chemical fate modeling, which establishes a bridge between the two fields.

What Distinguishes a Model

Chemistry and modeling have undoubtedly benefited from the growth of GIS in recent years, which has made it easier to solve equations in space and time and allows for the representation of model findings in maps that can be combined with other environmental data. This facilitates comparisons between models and other spatial patterns, such as emission sources, air circulation, soil organic matter, etc., while also making it simpler to comprehend model output.

Chemical modeling, which was widely adopted during the 1980s digital revolution, has seen an exponential increase in the number of tools available to scientists and other professionals who need to simulate chemical reaction processes. This is especially true of the modeling of chemicals in the environment. In fact, it could be argued that there are currently more models available than there are actual issues that require a model.In the majority of cases, practitioners use the word “model” to refer to software that implements algorithms for the solution of specific equations; nevertheless, in a wider sense, a scientific model is meant to be an interpretation scheme that enables making predictions about the behaviour of a system [1, 2].

Utilisation of GIS for the Chemical Fate Model
Geographic Information Systems (GIS) have been shown to be beneficial during the past ten years for analyzingenvironmental chemical destiny and movement.GIS is also a great tool for storing and displaying maps. Identifying critical components that affect chemical fate and transport is one of the numerous advantages of GIS. GIS also facilitates the communication and justification of important model premises [3, 4, 5].

Models of fate and transport are useful for describing how chemicals disperse in the environment. They consist of a mathematical depiction of the procedures a chemical goes through when it is released, which can be categorized as follows:

• Phase partitioning in chemicals.
• Chemical processes.
• Transmission between various environmental media (air, water, soil, sediments, plants, and biota).
• Movement within a medium

What is GIS?
Geospatial Information Systems (GIS) have advanced since the early 1960’s when Roger Tomlinson completed ground-breaking work for the Canadian government typically, a GIS is defined as a hardware and software platform created to store, represent, and deal with spatial data.Examining the effects on the environment of the increased use of GIS technology in chemical emergency response, groundwater, chemical risk management, chemical fate and transport modeling, and geochemical quality of groundwater [6, 7, 8].

In response to worries sparked by the Bhopal tragedy, local emergency planning and prevention have received increasing attention globally. Several chemical emergency response systems for first responders have also been constructed. Geographical Information System (GIS) technology has succeeded in many industries and can be useful for responding to chemical emergencies.

Thinking Spatially
Environmental/Chemical models have been incorporated into GIS for at least 20 years. A number of conferences on the subject of integrating GIS and environmental modeling were held in the 1990s, at Boulder, Colorado, in 1991, 1993, 1996, and 2000.The conference proceedings attest to the fact that GIS was evolving into a common modelingtool employed by the scientific community.The various ways that a model can be connected to a GIS were covered in great detail during these sessions. According to the study’s findings, there is a trend for models to become fully embedded in GIS as they move from loose coupling to tight coupling. A utility programme was initially used to export model results for cartographic display in GIS because GIS and model software were initially entirely independent. A close linkage implies that models are executed from within the GIS [9, 10].

Not Just GIS
The current tendency is to make individual GIS features available in general programming languages or scripting/analysis environments like Python or R, even though traditionally GIS has grown as distinct packages. This opens up a perspective where GIS analysis and spatial thinking remain fundamental approaches made possible in various ways, allowing more and more software developers to integrate GIS data management, analysis, and communication functionalities in software that is different from GIS packages intended for that purpose.

References

1. Howard, P. H., Muir, D. C. G., February 2010. Identifying new persistent and bioaccumulative organics among chemicals in commerce. Environmental Science and Technology 44(7), 2277–2285. Weblink: http://dx.doi.org/10.1021/es903383a.
2. Muir, D. C. G., Howard, P. H., November 2006. Are there other persistent organic pollutants? A challenge for environmental chemists. Environmental Science and Technology 40(23), 7157–7166. Weblink: http://dx.doi.org/10.1021/es061677a.
3. Chen, W., Hertl, P., Chen, S., Tierney, D., 2002. A pesticide surface water mobility index and its relationship with concentrations in agricultural drainage watersheds. Environmental Toxicology and Chemistry 21(2), 298–308. Weblink:http://dx.doi.org/10.1002/etc.5620210211.
4. Loague, K., Corwin, D. L., Ellsworth, R., March 1998. The challenge of predicting nonpoint source pollution. Environmental Science and Technology 32(5), 130A–133A. Weblink:http://pubs.acs.org/doi/abs/10.1021/es984037j.
5. Corwin, D. L., Vaughan, P. J., Loague, K., July 1997. Modeling nonpoint source pollutants in the vadose zone with GIS. Environmental Science and Technology 31(8), 2157–2175. Weblink:http://dx.doi.org/10.1021/es960796v.
6. Loague, K., 1994. Regional scale ground-water vulnerability estimates: impact of reducing data uncertainties for assessments in Hawaii. Ground Water 32(4), 605–616.Weblink:http://dx.doi.org/10.1111/j.1745-6584.1994.tb00896.x.
7. Toose, L., March 2004. BETR-World: a geographically explicit model of chemical fate: application to transport of α -HCH to the arctic. Environmental Pollution128 (1–2),223–240.Weblink: http://dx.doi.org/10.1016/j.envpol.2003.08.037.
8. Verro, R., Calliera, M., Maffioli, G., Auteri, D., Sala, S., Finizio, A., Vighi, M., February 2002. GIS-based system for surface water risk assessment of agricultural chemicals. 1. Methodological approach. Environmental Science and Technology 36(7), 1532–1538.Weblink:http://dx.doi.org/10.1021/es010089o.
9. Pennington, D. W., Margni, M., Ammann, C., Jolliet, O., January 2005. Multimedia fate and human intake modeling: spatial versus nonspatial insights for chemical emissions in Western Europe. Environmental Science and Technology 39(4), 1119–1128. Weblink:http://dx.doi.org/10.1021/es034598x.
10. Schenker, U., Scheringer, M., Hungerbuhler, K., January 2008. Investigating the global ¨ fate of DDT: model evaluation and estimation of future trends. Environmental Science&Technology42(4),1178–1184.Weblink:http://dx.doi.org/10.1021/es070870h.