Hydrochemistry and groundwater quality assessment around solid waste landfill sites in peri-urban Jaipur, NW India.

Jaipur, the capital city of Rajasthan State in northwestern India, is one of the fastest-growing urban centers in the country. The city and the region around it have documented a substantial drop in the water table due to the over-abstraction of groundwater resources to cater to the increasing water demands of the growing population. Consequently, the entire Jaipur district has been categorized as a "dark zone," prohibiting any further groundwater development activity. Besides its dwindling availability, water quality is also a matter of concern. In places, the water is geogenically contaminated and unsuitable for drinking purposes due to high levels of undesired elements in groundwater, such as high fluoride in the southern part and high chloride in the southwestern part of the district. Groundwater contamination can also occur through several anthropogenic factors, such as industrialization and excessive use of insecticides and pesticides. Water pollution through sewage disposal in open land-fill sites is also an important factor, especially in the growing urban centers. In this study, the water quality evaluation around three landfill sites in the Jaipur district, namely Mathura Das Pura and Langadiyawas (east of the city) and Sewapura (northwest of the city), was carried out. The cation-anion analysis of 45 groundwater samples collected around these sites reveals a wide variation in the abundance of constituent parameters. In a majority of cases, most of the parameters are within acceptable limits prescribed by the national and international agencies (Bureau of Indian Standards and World Health Organization). The fluoride content is more than the prescribed limit of 1.5 mg/l in several cases. This could be an intrinsic property of deeper aquifers. The majority of Mathura Das Pura and Langadiyawas samples classify as Na + K - CO3 + HCO3 to Mg - CO3 + HCO3 types in the Piper classification scheme, while a small proportion shows mixed water type characteristics, i.e., with no dominant parameter. Most of the samples have heavy metal abundances within the permissible limits while slightly elevated Cd and Pb levels were observed in some samples. A positive correlation between these two metals can be attributed to a common pollutant, possibly sourced from solid waste. The percent pollution index of Sewapura samples shows lower pollution levels (PPI < 40%) and a dominant chemical weathering trend while the majority of Mathura Das Pura-Langdiyawas samples show a high pollution effect (PPI 40 to 80%). In general, the chemical parameters of Sewapura (relatively new landfill site) samples define a more coherent group while water quality parameters in Mathura Das Pura and Langdiyawas (old landfill sites) samples show a wide variation, unsystematic distribution, and significantly higher than prescribed values for most of the hydrochemical parameters. The study shows that some of the water quality issues may be geogenic, while municipal waste dumping and leachate infiltration have adversely affected the groundwater quality.

Prediction of leachate quantity and quality from a landfill site by the long short-term memory model.

The long short-term memory (LSTM) model was first applied in this study for the prediction of the leachate quantity and quality at a real landfill site. In our LSTM model, in the learning phase from July 2003 to March 2018, three input data items consisting of the daily precipitation (DP), the daily average temperature (DAT), and the accumulated amount of landfilled waste presented the quantity of leachate generated with high accuracy. The DAT was important for the landfill site, particularly in a snow area because it contributes to the leachate generated during the spring thaw with low precipitation. In the testing phase from April 2018 to March 2019, our LSTM model predicted the leachate generated with a mean absolute percentage error (MAPE) of 26.2%. The concentrations of biological oxygen demand, chemical oxygen demand, total nitrogen, calcium ion and chloride ion in leachate were presented in the learning phase by six input data items: DP, DAT, and the daily amount of landfilled waste (incineration residue, incombustible waste, business waste, and combustible waste) with high R2 values. In the testing phase, the quality of leachate was predicted with the MAPE between 11.8% and 30.2%. Another year data from April 2019 to March 2020 was used to verify accuracy of our model with no overfitting. This study showed the possibility of applying the LSTM model to future predictions of leachate quantity and quality from landfill sites with an acceptable error for daily operation.

Application of multi-criteria decision-making techniques to develop modify-leachate pollution index.

The modify-leachate pollution index (m-LPI) was developed with the help of multi-criteria decision-making (MCDM) technique based on the landfill leachate pollution potential by considering the limitations of traditional methodologies. Across India, twenty major landfill sites (LS) were selected for which m-LPI was assessed. Twenty-five experts' opinions were taken for the determination of nine input criteria weights, such as pH, COD, TDS, Cl, Zn, Pb, Cu, annual rainfall, and landfill age with the help of a questionnaire-based survey. In this context, six MCDM techniques were investigated to develop m-LPI. Among different MCDM techniques selected, weighted aggregated sum product assessment (WASPAS) proved to be an effective one with an R2 value of 0.828 and IA value of 0.813. WASPAS gave first and last rank to Kadapa, Andhra Pradesh LS (1.677) and Turbhe, Maharashtra LS (2.193), respectively. The investigation revealed that around 90% of LS considered in the present study require leachate treatment. WASPAS sensitivity analysis showed that the least sensitive criteria were pH, followed by Cl and Zn. The m-LPI can be used by researchers and scientists to investigate and evaluate various challenges involved with solid waste management in LS.

Sustainable landfill sites selection using geospatial information and AHP-GDM approach: A case study of Abha-Khamis in Saudi Arabia.

Social, environmental, and technical factors must be combined to solve the complex problem of ever-growing municipal solid waste (MSW) and minimize its negative impact on the environment. Saudi Arabia has launched a US$13 billion tourism strategy to transform the Asir region into a year-round tourist destination and has pledged to welcome 10 million local and foreign visitors by 2030. The estimated share of Abha-Khamis will increase to 7.18 million tons of household waste per year. With a gross domestic product (GDP) of USD 820.00 billion by the end of 2022, Saudi Arabia can no longer afford to neglect the issue of waste production and its safe disposal. In this study, to account for all factors and evaluation criteria, a combination of remote sensing, geographic information systems and an analytical hierarchy process (AHP) was used to determine the best locations for municipal solid waste (MSW) disposal in Abha-Khamis. The analysis revealed that 60% of the study area consists of faults (14.28%), drainage networks (12.80%), urban (11.43%), land use (11.41%) and roads (8.35%), while 40% of the suitable area for landfill. Of these, a total of 20 sites ranging in size from 100 to 595 ha are distributed at reasonable distances from the cities of Abha-Khamis, which meet all the critical criteria for suitable landfill sites mentioned in the literature. Current research shows that the use of integrated remote sensing, GIS and the AHP-GDM approach significantly improves the identification of land suitability for MSW management.

Comparison of respiratory and skin disorders between residents living close to and far from Solous landfill site in Lagos State, Nigeria.

BACKGROUND: Solid waste dump sites have proven to have potentially high risk to human health as it serves as a source of air, soil and underground water pollution. AIM: This study aimed to assess and compare the knowledge, respiratory disorders and skin disorders between residents living close to and far from landfill sites in Lagos State, Nigeria. SETTING: Igando (a community within 5 km close to) and Badagry (a community beyond 5 km from) Solous Landfill sites in Lagos state, Nigeria. METHODS: A comparative cross-sectional study amongst 103 respondents recruited from each of the two study sites by multistage sampling method was carried out. Data were collected using pretested, structured, interviewer-administered questionnaire, and analysed using Microsoft Excel 2007, EPI Info 7 and WinPepi statistical software packages. Student t-test, Fisher's exact and Chi-square tests were carried out. The p ≤ 0.05 was considered statistically significant. RESULTS: The mean age of Igando and Badagry respondents was 34.18 ± 10.21 years and 32.62 ± 9.84 years, respectively. The two communities differed significantly (p 0.0001) with respect to distance of workplace from landfill site and duration of stay in the residential location. The mean knowledge score of respondents on respiratory and skin disorders associated with solid waste dump site close to landfill sites (82.53 ± 20.60) was statistically significantly higher than those of respondents far from landfill sites (71.84 ± 20.57) (p = 0.0003). Respiratory and skin disorders experiences of respondents close to landfill sites were statistically significantly (p 0.0001) higher than those of residents far from landfill sites with respect to wheezing, frequent sneezing, unpleasant odour, fever and skin rashes. CONCLUSION: Respiratory and skin disorders experienced by respondents close to landfill sites are higher than those of residents far from landfill sites. Landfill sites should not be located close to human settlements.

Modeling gaseous emissions and dispersion of two major greenhouse gases from landfill sites in arid hot environment.

As waste production exponentially increases, landfill continues to be the common method of waste disposal. Landfills represent significant anthropogenic sources of methane (CH4) and carbon dioxide (CO2); the main constituents of greenhouse gases (GHGs) resultant from microbial decomposition of organic waste. In the present study, ISC-AERMOD dispersion model was employed to estimate the release and dispersion rates of CH4 and CO2 from major landfill sites across Kuwait under different seasonal conditions. Results revealed that dispersions of CH4 and CO2 were influenced by the dominant northwestern and southeastern wind directions and thus, the dispersion of CH4 and CO2 extended predominantly toward northeastern direction. In terms of seasonal variation, the maximum concentrations of CH4 and CO2 were detected in winter and spring seasons, close to the landfill zone, and the dispersion of CH4 and CO2 fluxes during winter and spring seasons was longer than that during summer and fall seasons. Consequently, residential areas close to the disposal sites were exposed to higher concentrations of CH4 and CO2 gases during winter and spring. The findings of this study can serve as the basis for selecting suitable landfill locations under desert climatic conditions as determined by the distances over which gaseous emissions can diffuse.

Common Mental Health Disorders among Informal Waste Pickers in Johannesburg, South Africa 2018-A Cross-Sectional Study.

Waste-picking is an income-generating opportunity for individuals living in poverty. Waste picking is associated with a range of risk factors for common mental disorders (CMD). This study aimed to determine the prevalence and factors associated with CMD among waste pickers in Johannesburg. A cross-sectional study analyzed secondary data for 365 waste pickers. A validated Self-Reporting Questionnaire (SRQ-20) was used to assess CMD. Multivariable logistic regression was fitted to identify factors associated with CMD. The overall prevalence of CMD among waste pickers was 37.3%. The odds of having CMD were 2.5 and 3.2 higher in females and cigarette smokers, respectively (p = 0.019 and p = 0.003). Life enjoyment (Adjusted odds ratio [aOR] 0.54, p = 0.02) and a good quality of life (aOR 0.34, p ≤ 0.001) were associated with lower odds of CMD. The high prevalence of CMD among waste pickers was significantly associated with cigarette smoking, being female, not enjoying life, and a poor quality of life. Mental health awareness of CMD will assist with the prevention, early detection, and comprehensive management of CMD among waste pickers.

Prevalence of Respiratory Health Symptoms among Landfill Waste Recyclers in the City of Johannesburg, South Africa.

In developing countries, waste sorting and recycling have become a source of income for poorer communities. However, it can potentially pose significant health risks. This study aimed to determine the prevalence of acute respiratory symptoms and associated risk factors for respiratory health outcomes among waste recyclers. A cross-sectional study was conducted among 361 waste recyclers at two randomly selected landfill sites in Johannesburg. Convenience sampling was used to sample the waste recyclers. The prevalence of respiratory symptoms in the population was 58.5%. A persistent cough was the most common symptom reported (46.8%), followed by breathlessness (19.6%) and rapid breathing (15.8%). Approximately 66.4% of waste recyclers reported exposure to chemicals and 96.6% reported exposure to airborne dust. A multivariable logistic regression analysis showed that exposure to waste containing chemical residues (OR 1.80, 95% CI 1.01-3.22 p = 0.044) increased the odds of respiratory symptoms. There was a significant difference in respiratory symptoms in landfill sites 1 and 2 (OR 2.77, 95% CI 1.03-7.42 p = 0.042). Occupational health and safety awareness is important to minimize hazards faced by informal workers. In addition, providing waste recyclers with the correct protective clothing, such as respiratory masks, and training on basic hygiene practices, could reduce the risks associated with waste sorting.

[NH3 Emission Characteristics in Landfill Sites in Beijing].

NH3 is one of the main odors produced from landfill sites. It is also an important precursor of PM2.5. According to the NH3 of ambient air and non-organizational waste gas monitoring method, the research studied NH3 emission characteristics of two landfill sites in Beijing. The results showed that the NH3 concentrations in waste pit, sludge treatment workshop and leachate equalization basin were 0.078-0.341mg·m-3. The NH3 concentration of key processes was rising in daytime and decreasing in night. Temperature and relative humidity were main meteorological influencing factors, and NH3 concentration was low in rainy weather. The NH3 concentration declined significantly along downwind directions, by 60.00% at 100m out of boundary and 69.90% at 300 m. This reasearch provides scientific support for further study on localization of NH3 emission characteristics and NH3 emission monitoring management.