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Spatial identification and temporal prediction of air pollution sources using conditional bivariate probability function and time series signature

Althuwaynee OF, Pokharel B, Aydda A, Balogun AL, Kim SW, Park HJ

J Expo Sci Environ Epidemiol, 2021 07;31(4):709-726.
PMID: 33159165 DOI: 10.1038/s41370-020-00271-8

Accurate identification of distant, large, and frequent sources of emission in cities is a complex procedure due to the presence of large-sized pollutants and the existence of many land use types. This study aims to simplify and optimize the visualization mechanism of long time-series of air pollution data, particularly for urban areas, which is naturally correlated in time and spatially complicated to analyze. Also, we elaborate different sources of pollution that were hitherto undetectable using ordinary plot models by leveraging recent advances in ensemble statistical approaches. The high performing conditional bivariate probability function (CBPF) and time-series signature were integrated within the R programming environment to facilitate the study's analysis. Hourly air pollution data for the period between 2007 to 2016 is collected using four air quality stations, (ca0016, ca0058, ca0054, and ca0025), situated in highly urbanized locations that are characterized by complex land use and high pollution emitting activities. A conditional bivariate probability function (CBPF) was used to analyze the data, utilizing pollutant concentration values such as Sulfur dioxide (SO2), Nitrogen oxides (NO2), Carbon monoxide (CO) and Particulate Matter (PM10) as a third variable plotted on the radial axis, with wind direction and wind speed variables. Generalized linear model (GLM) and sensitivity analysis are applied to verify and visualize the relationship between Air Pollution Index (API) of PM10 and other significant pollutants of GML outputs based on quantile values. To address potential future challenges, we forecast 3 months PM10 values using a Time Series Signature statistical algorithm with time functions and validated the outcome in the 4 stations. Analysis of results reveals that sources emitting PM10 have similar activities producing other pollutants (SO2, CO, and NO2). Therefore, these pollutants can be detected by cross selection between the pollution sources in the affected city. The directional results of CBPF plot indicate that ca0058 and ca0054 enable easier detection of pollutants' sources in comparison to ca0016 and ca0025 due to being located on the edge of industrial areas. This study's CBPF technique and time series signature analysis' outcomes are promising, successfully elaborating different sources of pollution that were hitherto undetectable using ordinary plot models and thus contribute to existing air quality assessment and enhancement mechanisms.
Drinking water quality status in Malaysia: a scoping review of occurrence, human health exposure, and potential needs

Praveena SM, Aris AZ, Hashim Z, Hashim JH

J Expo Sci Environ Epidemiol, 2024 Jan;34(1):161-174.
PMID: 37563210 DOI: 10.1038/s41370-023-00585-3

BACKGROUND: Like other countries, surface water degradation in Malaysia is linked with common global issues. Although different aspects of drinking water suitability have been examined, the overall understanding of drinking water quality in Malaysia is poor.
OBJECTIVE: Hence, the present review aims to provide an understanding of drinking water (tap water, groundwater, gravity feed system) quality and its potential implications on policy, human health, and drinking water management law and identification of potential direction of future drinking water research and management needs in Malaysia.
METHODS: This study utilized a scoping review method. PRISMA Extension for Scoping Reviews was used for search strategy. Relevant studies were screened using the selected keywords and databases.
RESULTS: A total of 26 drinking water quality studies involving tap water, groundwater, and gravity feed systems have been selected for review. These studies found that the majority of Malaysian Drinking Water and WHO Drinking Water standards have been met. High levels of Cu, Cd, Fe and Pb were attributable to galvanized plumbing and pipe material corrosion. Variation of fluoride in tap water depends on dosage planning and operational processes of the public water supply. Pollutants (nitrate and ammonia) in groundwater and gravity feed system water have been linked to agricultural practices in rural areas. Microbiological quality in tap water is associated with growing biofilms inside the pipelines while in groundwater is caused by shallow surface events. However, only eight studies have reported about the human risks of chemical pollutants in tap water.
IMPACT STATEMENT: The review discusses the state of drinking water quality in Malaysia and its impact on public health. It suggests that policymakers can use this information to improve the quality of drinking water and enforce restrictions, while also raising public awareness about the importance of safe drinking water. The study can guide future research and initiatives in Malaysia, ultimately contributing to efforts to ensure access to clean and dependable drinking water.

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