provided in Table 3 and shown in Figure 3. From each sampling location, water was gathered in 1-liter plastic containers and stored under refrigeration at 4°C. The surface water parameters considered for the analysis of physico-chemical properties are presented in Table 2.

Source: Central Pollution Control Board (CPCB), 2007-08

Source: Based on the field survey by the researcher, 2022.

2.2.3 Air Quality Monitoring

For air quality analysis, four monitoring sites were selected around the Shankarpur landfill based on the wind direction during both summer and winter seasons to ensure comprehensive coverage. The primary air quality parameters measured included PM₁₀, and PM_2.5, SO₂, and NOx. Sampling procedures have been followed the standard guidelines established by the WBPCB (Table 4). Detailed information about the sampling locations and wind directions are provided in Table 5 and shown in Figure 4. Laboratory analyses have been conducted to evaluate ambient air quality and identify pollution sources in the vicinity of the landfill.

The collected data was analyzed using statistical methods in SPSS, including Pearson correlation coefficients to identify relationships between pollutants and z-scores to detect outlier contamination levels. Spatial pollutant distribution was visualized using ArcGIS. To evaluate water and air quality, indices such as WQI and AQI were calculated to assess the severity of pollution relative to national standards.

2.2.4 Water Quality Index (WQI) Calculation

To calculate the WQI from sampled data on water quality, three-steps methodology was adopted. Firstly, key parameters were ranked ( ​\(K^n\)​  ) based on their importance in water quality assessment and environment impact. Secondly, the relative weight ( ​\(W_g\)​ ) of each parameter was calculated using Equation (1):

​\(W_g = \frac{K^n}{\sum_{g=1}^{n} K^n}\)​  (1)

Where, ​\(W_g\)​  is relative weight, \(K^n\)  indicates parameter rank and n is the total parameters.

Finally, a quality rating ( ​\(R_q\)​ ) was allotted to each parameter by comparing its measured concentration ( ​\(P_c\)​ ) against the permissible limit ( ​\(D_i\)​ ) specified by the BIS-2012 scaled to 100 using Equation (2):

​\(R_q = \frac{P_c}{D_i} \times 100\)​  (2)

Now, for computing the WQI, the SI value for each parameter was carried out. This value is then used in the following formula (Equation 3) (Ali and Ahmad, 2020):

​\(SIi=W_g×R_q\)​

​\(WQI= ∑ SIi\)​  (3)

Where, SIi is the sub-index of i^th parameter, \(R_q\)  indicates

the rating value based on the concentration of the q^th parameter, and n is the total number of parameters considered. Water quality is categorized into five classes based on the WQI values ranging from excellent to unsuitable for drinking.

Source: West Bengal Pollution Control Board (WBPCB), Durgapur Regional Office (2022).

Figure 3. Stations for surface water sampling

Figure 4. Stations for air quality sampling

Source: Based on field survey by the researcher, 2022.

2.2.5 Air Quality Index (AQI) Computation

AQI serves as a daily indicator to measure regional air pollution levels and its potential short-term health consequences. This index represents how the public understand about local air conditions may affect their well-being. In this study, AQI was calculated based on the methodology outlined by Kaushik et al., (2006). First of all, the air quality rating of each pollutant is calculated by the following formula (Equation 4):

​\(R = 100 \frac{\cdot O_v}{S_v} \)​  (4)

Where, ​\(R\)​  = quality rating, ​\(Q_v\)​  = observed pollutant concentration and ​\(S_v\)​  = the corresponding standard value from NAAQS.

If total ‘n’ numbers of pollutants are considered for air quality measuring, the geometric mean of these ‘n’ number of quality rating is calculated as (Equation 5):

​\(\text{GEO}_{\text{MEN}} = \text{anti}_{\text{log}} \left( \frac{\log x + \log y + \log z + \cdots + \log i}{N} \right)\)​ (5)

Where ​\(\text{GEO}_{\text{MEN}}\)​  is the geometric mean, while x, y, z, and i represent different values of air quality rating, and ​\(N\)​  is the number of values of air quality rating.

An AQI value between 51–100 indicates moderate air quality, which, while generally acceptable, may pose mild health risks particularly for individuals sensitive to air pollution, who could experience respiratory discomfort.

Figure 5: Groundwater quality index

3.1.2 Assessment of water quality index

In this study, groundwater quality index has been calculated as per the standard value of BIS, 2012. The status of groundwater and classification of water quality in WQI has been presented in Table 8 and Table 9. Table 8 shows that the quality of groundwater in 4 sampled stations out of total 11 stations named Raghunathpur, Main Gate, Natun Pally Punjabi Para and near-final dumping site exceeds the value of more than 294 which is unfit for drinking purpose. The water qualities in these places have been highly deteriorated due to heavy absorption of pollutants discharged from nearby solid waste dumping sites. There is an immediate need for water treatment for these places before uses.

The status of water quality in 1 sampled station Vidyasagar Primary Vidyalaya is very poor, which is considered only for restricted use in irrigation. The people in Bijra predominantly use the well water for drinking, bathing and other domestic activities. The quality of water in this place has been highly contaminated with heavy pollutants and has been considered as poor status as per the WQI (Figure 5).

The status of groundwater quality of only two sampled stations named Ispat Nagari Free Primary school and DPL Coke Oven Colony range from 241 to 255 have been considered as good which is fit for domestic, irrigation and industrial activities but not for drinking (Table 9). There is not a single groundwater sampled station which is suitable for drinking purposes in the study area, but majority of the people in ward numbers 1 and 2 uses well water for drinking purposes.

3.2 Improper Solid Waste Disposal and Surface Water Contamination

3.2.1 Analysis of surface water quality

The physico-chemical parameters of the analyzed surface water samples of Durgapur city, including statistical mean values of pre-monsoon and post-monsoon seasons, are presented in Table 10. Fifteen parameters of surface water have been selected for the analysis of the quality of sampled surface water bodies in the study area (Table 11). The measured values of each parameter of water have been compared with the standards given by BIS-2012 (Table 10).

The surface water quality analysis of the sampled locations reveals notable variations across key chemical parameters, with certain values approaching or exceeding BIS standards, particularly near waste dumping sites. Most sampled sites exhibit pH levels within the BIS range (6.5-8.5); however, one site near the final dump shows a higher pH of 8.7, indicating minor alkalinity likely due to waste leaching. The EC values range from 1710 to 2110 μS/cm, with maximum concentration found near the final dumping site, suggesting increased dissolved ions from contaminants. Total Dissolved Solids (TDS) levels remain within BIS’s permissible range of 500-2000 mg/l, though highest near the dumping area, indicating salinity and potential leachate influence.

Source: Calculated by the researcher, 2022.

Source: Research findings, 2022.

Source: Based on field survey, the samples tested by the Environmental Laboratory of A.M.U., Aligarh, 2022.

Note:      All units are in mg/l, max. except EC–μS/cm.

Source: Prepared by the researcher based on IS: 2012. 

Total hardness values range from 522 to 760 mg/l, exceeding the BIS acceptable limit of 200 mg/l but falling within the upper permissible limit of 600 mg/l in most locations, with hardness generally higher near the final dumping site. COD and BOD levels remain within permissible ranges, yet display slightly elevated concentrations near the final dumping site, hinting at organic contamination. Chloride levels across sampled sites are within BIS standards, though readings are highest near the dumpsite, highlighting potential contamination risks. Trace elements like arsenic, cadmium, and chromium are detected in concentrations below BIS thresholds, but mercury levels exceed safe limits across several sites, particularly near the final dumping site, suggesting bioaccumulative pollution from solid waste. Maximum lead concentrations are also noted at sites near the final dumping area, posing health risks, particularly for sensitive groups. In summary, the analysis points to significant pollutant influx in surface water near waste areas, requiring monitoring to mitigate health and ecological impacts.

3.2.2 Assessment of water quality index

Surface water quality index of the sampled stations was calculated considering the standard value of BIS, 2012. The status of surface water quality and classification of water quality in WQI are shown in Table 12 and 13, respectively. Considering the status of surface water quality of the sampled stations, SWQI was classified into six classes (Table 13). Table 12 shows that the quality of surface water in 2 sampled stations Raghunathpur, and Natun Pally Punjabi Para exceeds the value of more than 287 which has been considered as unsafe for any uses. Three stations viz. near Kada Road, Natun Pally near Punjabi Para and near Anandpausi Co-op. come under very poor status while another 3 sampled stations, i.e., near Fuljhore, Bijra Bandh and DCL colony ranging WQI from 257 to 272 come under the poor quality of water. The surface water quality in sampled stations near Ispat Free Primary School, Ashis Nagar Colony, and Khejurtala are considered as good quality of water. The water quality in these sampled stations is not much contaminated due to its distant location from open dumping sites (Figure 4).

3.3 Improper Solid Waste Disposal and Air Pollution

3.3.1 Analysis of ambient air quality

The status of ambient air quality of the sampled stations located in the vicinity of open dumping sites was analyzed for summer and winter seasons. The mean values of PM₁₀, PM_2.5, SO₂, and NOx in Table 14 and 15, respectively. The stations for ambient air quality monitoring were fixed considering the direction of wind flow in the area. The general wind direction during summer seasons is from south to north and from north to south during the winter season. Considering the locations of solid waste dumping site, two sampled stations were selected in the windward side and two stations on leeward side of the wind flow. The monitoring of AAQ was carried out as per the standard procedure. The details of the methodology for assessing air quality are presented in Table 4. The ambient air quality status around the landfill site was analyzed as per the Standards of Ambient Quality for landfills sites as suggested by MSW Rules 2016, MoEF, GoI (Table 16).

Tables 14 and 15 present the concentration levels of SO₂, NOₓ, PM₁₀, and PM₂.₅ across four stations near the dumping site during both summer and winter. It is found that SO₂ concentrations range from 15.1 to 18.4 μg/m³ in summer and 19.5 to 23.5 μg/m³ in winter, with the highest levels observed on the windward side of the sites. This variation is largely due to the combustion of sulfur-containing wastes like plastics and rubber. NOₓ concentrations vary from 15.2 to 19.2 μg/m³ in summer and 26.1 to 29.1 μg/m³ in winter. Both SO₂ and NOₓ levels remain within limits as specified by MSW Rules 2000, MoEF, Government of India. 

Source: Calculated by the researcher, 2022.

Source: Calculated by the researcher, 2022.

Figure 7. Buffer from the location of dustbins

Source: Calculation is based on the field survey and laboratory experiment, 2022.

Note: 1. SO₂- Sulphur dioxide, NOx- Nitrogen dioxide, 2. all units are in μg/m³

Source: Calculation is based on the field survey and laboratory experiment, 2022.

Note: 1. SO₂- Sulphur dioxide, NOx- Nitrogen dioxide, 2. all units are in μg/m³

Source: Developed by the author using guidelines from the Ambient Air Quality Standards for Landfills under the MSW Rules 2016, Ministry of Environment, Forest and Climate Change, Government of India. Note: The annual average values (*) are based on the arithmetic mean of at least 104 measurements taken twice per week over a year, while the 24-hour, 8-hour, or 1-hour maximum limits (**) must be met 98% of the time annually, allowing exceedances up to 2% of the time, provided they do not occur on two consecutive monitoring days.

Source: Calculated by the researcher, 2022.

Figure 8. Buffer from the location of open dumpsite

Figure 9. Buffer from densely populated areas

For particulate matter, PM₁₀ concentrations range from 208 to 233 μg/m³ in summer and 245 to 267 μg/m³ in winter, while PM₂.₅ levels are in between 57 and 84 μg/m³ in summer and 165 to 195 μg/m³ in winter. Higher concentrations in winter are attributed to poor air circulation. Although PM₁₀ exceeds regulatory limits at all stations, PM₂.₅ levels exceed standards at all stations except the southern station, downwind of the landfill.

3.3.2 Assessment of Air Quality Index (AQI)

The AQI was calculated following the method by Kaushik et al. (2006). The status of air quality index of the sampled stations for both summer and winter seasons is shown in Table 17. Table 17 shows that the values of SO₂ and NO_x in all the four sites remained within the acceptable limits. During the winter season, the values of SO₂ and NO_x were recorded higher than the summer season. But, the level of concentration of PM₁₀and PM_2.5 in all four stations during both summer and winter seasons were found to be exceeding the acceptable limits. The highest concentration of PM₁₀ and PM_2.5 is found in the south of landfill site-2 (windward) during the winter season which may affect the people living nearby the dumping site.

To further assess environmental impacts, spatial buffers were created around key pollution sources such as dustbins, open dumpsites, densely populated areas, and the Shankarpur landfill site. This helped in identifying zones affected by groundwater and surface water pollution, as well as air quality degradation (Figure 7, 8, 9 and 10). These buffer zones highlight regions at risk of groundwater, surface water, and ambient air pollution.

3.4 Environmental Impact Assessment of Improper Solid Waste Disposal

The environmental impact assessment of improper disposal of solid waste on surface water, groundwater, and the air was analyzed with help of standard statistical technique to find out the degree of correlation with improper management of solid waste and water and air. The correlation between groundwater quality and proximity to dustbins, open dumping sites, and densely populated areas is shown in Figure 11. The analysis reveals that nearness to dustbins, open dumping sites and densely populated areas are positively correlated with poor groundwater quality with R² value 0.85. It is found that the groundwater quality is good in those sampled stations which are far away from open disposal sites, dustbins and low vulnerable areas to solid waste management.

Figure 10. Buffer from air sampled stations

Figure 11. Correlation between groundwater quality and system of solid waste management

Figure 12. Correlation between surface water quality and system of solid waste management