Current World Environment

Introduction

Continuously deteriorating quality of ambient air jeopardising human health ^1–3. The severity of the problem varies in industrial and developing countries ^4,5. Quick motorisation, rapid industrial and urban growth, and flying technological advancement have put air quality at stake globally ^6–8. Many of the less developed countries becoming urbanised and industrialised do not have the resources or enough technologies to dispose of the pollutants with minimal environmental impacts ^5,9. Humankind's ability to spontaneously assess and manage health risks has become fundamental to survival in today's changing environment ^10,11.

Particulate matter pollution is now a serious worldwide concern due to its severe consequences on an ecosystem's biotic and abiotic components ^12,13. Megacities of Rajasthan state of republic India have also experienced high concentration levels of particulate matter in the last few years, which puts an additional load on the Indian economy ^14–18.

Fine particulate matter is getting more attention because of its small size. It has heterogeneous compositions of liquid and solid particles suspended in the environment. The size of dangerous particulates varies from large to too-small ^7,19. Some particulates are so large that they can be watched even through the bare eye, although the rest are so minute that they could only be monitored with the help of an electron microscope ^20,21. PM are broadly classified into two categories according to their aerodynamic diameter, i.e., PM_2.5 (Día  ? 2.5 µm) and PM₁₀ (Día  ?10 µm)  ^3,22.

Natural and man-made activities are answerable for the worst air quality ^5,23. Volcanic eruption, dust storms, wildfires, burning of fossil fuel in coal-based industries ^24–26, vehicular emissions ^25,27, power generation ^8,28, oil refineries ²⁵, and stubble and wood burning are the leading causes of particulate matter formation ^29,30.

The undesired detrimental effect of particulates on the health of humans has mild, moderate, or severe impacts according to their concentration level and duration of exposure. It has become a significant environmental risk factor for all-cause and disease-specific morbidity & mortality ³¹. Older age, Children, and pregnant women are susceptible to the exposure ^32,33. PM_2.5 exposure causes mortality from lung cancer ³⁴, all-natural causes in adults (30⁺ years), chronic pulmonary obstructive disease (COPD) ¹¹, acute lower respiratory infection (ALRI) ³², stroke ³⁵, ischemic heart disease (IHD) ³⁴, and Short-term impacts increase hospital admissions from diseases related to respiratory, cardiovascular disease (CVD), stroke, and adult mortality ³⁶.

The ultimate objective of this work is to measure particulate matter's severe impact on inhabitants and identify the ecological environment risk category of Kota city, Rajasthan (India), during the observation period of four years (2018-2022). Not sufficient studies were available in the literature for Kota to quantify environmental risk. The educational hub of the Rajasthan state (India), Kota, is a rapid-growing metropolis with two million inhabitants. Kota is suffering from the harmful impact of particulate matter pollution. 

Study Area & Research Methodology

Kota, an industrial and educational district of Rajasthan, ranks 16^th in terms of population, 24^th in a geographical area, and 7^th in population density in the Rajasthan State of India. The population of Kota was 19,51,014 in 2021 as per the census of India, 2011 ³⁷. PM₁₀ and PM_2.5 are the parameters selected for the study. Four-year air quality data is collected from January 2018 to December 2021. Seven monitoring sites on air quality were utilised to obtain the data to determine the city's air quality deterioration. Air quality stations for Kota are mentioned in Table 1.

Table 1: GPS locations of air monitoring sites available in Kota city, Rajasthan (India).

Figure 1: Study area map including air monitoring stations for Kota city, Rajasthan, (India).   Click here to view Figure

Figure 2: Step-by-step procedure followed in this study to complete the research work.   Click here to view Figure

The average PM₁₀ and PM_2.5 concentrations are also compared with other regional districts of Rajasthan, namely, Jaipur, Udaipur, Ajmer, Pali, Alwar, and Jodhpur, with an additional 10 continuously monitoring air quality stations, including one continuous air quality station for Kota. The research methodology for the study is exhibited in Figure 2. Human health risk assessment has been evaluated with the help of AirQ+ software (WHO invented), while ecological hazard risk categories were recognised through risk quotient (RQ). A comparison with different regional cities, namely, Jaipur, Udaipur, Ajmer, Pali, Alwar, and Jodhpur, has also been done for PM_2.5 andPM₁₀ concentrations. The dust ratio (PM_2.5/PM₁₀) is computed for Kota and regional cities to validate the increasing levels of fine particulates than the larger ones. The fine particles have the capability of penetrating deeper into the respiratory tract which has more severe consequences for human beings than the large ones. The standards for PM₁₀ and PM_2.5 prescribed by different agencies worldwide are shown in Table 2.

Table 2: Standards for particulate matter prescribed by global agencies ^{24,35,38–43}.

Environmental Risk Assessment

This study implements the environmental risk assessment for Kota due to particulate matter with the help of ecological environmental risk and human health risk assessments. Risk Quotient has been estimated to determine the hazard risk category for ecological environmental risk assessment. At the same time, the AirQ+ software is used to estimate human health risk analysis. 

Ecological Environmental Risk

Ecological environment risk is a semi-qualitative risk based on particulate matter's physical and chemical characteristics to evaluate the ecological environment's probable risk category (Table 3). A risk Quotient is calculated with the help of the following equation ^10,46:

RQ_p = C_AP/C_LP                                                        [1]

Where:

RQ_p = RQ for the p^th pollutant,

C_Ap = Ambient quantity of the p^th pollutant, µg/m³, and

C_Lp = Standard Limiting for the p^th pollutant, µg/m³.

Table 3: Classification of different categories of environmental risk.

Human Health Risk Assessment

WHO developed AirQ⁺ software, which is used to assess human health risks from particulate matter. Default relative risk (RR) values for mortality from COPD, IHD, stroke, all-natural causes, LC, ALRI,  HA-RD, HA-CVD, adult mortality, chronic bronchitis, bronchitis in kids, asthma in kids, postneonatal infant mortality, asthma symptoms in asthmatic kids were 1013, 132, 49, 101, 436, 436, 1260, 101, 1013, 1013, 66, 497, and 66 respectively, ^{32–34,36,47,48}. 

Results and Discussion

The results of this study reveal that PM_2.5 and PM₁₀ concentrations for Kota, Jaipur Ajmer, Udaipur, Pali, Jodhpur, and Alwar of Rajasthan were higher than those recommended by different agencies worldwide shown in Table 2. Particulate Matter concentrations for Kota, Jaipur, Ajmer, Udaipur, Pali, Jodhpur, and Alwar are shown in Figure 3. 

Figure 3: The concentration of particulate matter in prominent regional cities nearby Kota.   Click here to view Figure

The annual particulate matter concentrations are mentioned in Table 4 for each sampling location in the city. The PM₁₀ concentrations for Kota were 152, 118, 97, and 119 µg/m³ in 2018, 2019, 2020, and 2021, respectively. The PM_2.5 concentrations for Kota were 55, 58, 50, and 67 µg/m³ in 2018, 2019, 2020, and 2021, respectively. The dust ratio for Kota were 0.36, 0.49, 0.52, and 0.56 in 2018, 2019, 2020, and 2021 respectively. An increasing trend has been seen in the dust ratio during the observation of four years. The dust ratio varies from place to palace and year to year. The PM_2.5 concentration gradually increased during observation except in 2020 due to Covid-19 lockdown restrictions all over India in 2020 ^49,50. 

A decreasing trend has been observed for PM₁₀ till 2020, but it again starts increasing in 2021 with tremendous speed. Several studies suggest that these restrictions help to improve air quality worldwide. The annual particulate matter concentrations are exhibited in Figure 4 for each sampling location in the metropolitan area. 121 and 57 µg/m³ were the mean PM₁₀ and PM_2.5 concentration_, respectively. At the same time, the average dust ratio was 0.48. The dust Ratio (PM_2.5/PM₁₀) in prominent places of Rajasthan State, India, is graphically presented in Figure 5. The dust ratio for Kota city is gradually rising from 0.36 to 0.51. The dust ratio for Kota was 0.36 in 2018, 0.49 in 2019, 0.51 in 2020, and 0.56 in 2021. High dust ratio values confirm the higher concentration of fine particles (PM_2.5) compared to larger particles (PM₁₀). The fine particles have the capability of penetrating deeper into the respiratory tract and creating many adverse effects on the human body. Hence, it is becoming a more serious concern for the inhabitants of Kota city. 

Table 4: Annual PM₁₀ and PM_2.5 data for each station of Kota city, Rajasthan (India).

*NA stands for not availability of data.

Figure 4: Particulate matter concentration in Kota, Rajasthan State, India.   Click here to view Figure

Figure 5: Dust Ratio (PM2.5/PM10) in prominent places of Rajasthan State, India.   Click here to view Figure

Ecological Environmental Risk 

The risk quotient can be assessed by determining the potential risk of particulate pollutants to the ecological environment. The risk quotient values for PM₁₀ were 2.53, 1.96, 1.61, and 1.99 in 2018, 2019, 2020, and 2021, respectively, while the values for PM_2.5 were 1.36, 1.44, 1.25, and 1.68 in 2018, 2019, 2020, and 2021, respectively. The whole of India was suffering from Corona Virus outbreaks in 2021. The citizens strictly followed lockdown restrictions to complete their duty toward the nation. Transport and industrial activities were under the limitation of government orders which positively impacted the quality of ambient air. The air pollutants concentrations went down, and inhabitants had clean air to breathe. Several studies on air quality reveal a meaningful impact of lockdown restrictions on the air quality globally ^2,50–52, and a reduction in particulate matter pollution level was also seen in 2020 for Kota, also leading to low values of RQ for PM₁₀ and PM_2.5. The risk quotient values for Kota were calculated with the help of equation 1, which is mentioned in Table 5. The PM₁₀ and PM_2.5 for Kota were computed through the average of all monitoring stations' concentrations (Table 4). RQ values for each year for Kota city are evaluated from average PM₁₀ and PM_2.5 concentrations.  

Table 5: RQ value and relative risk category for PM₁₀ and PM_2.5.

*H stands for High.

Human Health Risk Assessment

The average annual PM₁₀ and PM_2.5 were 123 and 57 µg/m³, respectively, during the observation of four years for Kota city. The particulate matter concentration plays a vital role in conducting the impact analysis through software (AirQ+). The estimated effects of PM₁₀ and PM_2.5 are mentioned in Table 6. 

The ENACs for all-cause mortality from PM_2.5 exposure for a long period was maximum at the AQS-4 location with 6365 deaths, followed by the AQS-3 location (5128 deaths), AQS-5 location (5036 deaths), AQS-2 (4943 deaths), AQS-1 (4565 deaths), AQS-6 (4565 deaths), AQS-7 (4565 deaths). The average all-cause mortality for Kota city is 5024 due to PM_2.5 exposure for a long period.

Table 6: Station Wise Distribution of ENACs for Disease Caused by PM₁₀ and PM_2.5. 

*ENAC stands for the estimated number of attributable cases.

The lung cancer mortality was 1103 for the AQS-4 location, 903 for the AQS-3 location, 887 for the AQS-5 location, 872 for the AQS-2 location, and 809 for the AQS-1, AQS-6, and AQS-7 locations. The average lung cancer mortality for Kota city is 885 due to PM_2.5 exposure over a long period. The ALRI mortality was leading at the AQS-4 location (316 deaths), followed by the AQS-3 location (276 deaths), the AQS-5 location (273 deaths), the AQS-2 l 7 location (269 deaths), and 256 for the AQS-1, AQS-6, and AQS-7 locations. The average ALRI mortality for Kota city is 272 due to PM_2.5 exposure for a long period. The COPD mortality was maximum at the AQS-4 location with 543 deaths, followed by the AQS-3 location (471 deaths), AQS-5 location (465 deaths), AQS-2 (460 deaths), AQS-1 (436 deaths), AQS-6 (436 deaths), AQS-7 (436 deaths). The average COPD mortality for Kota city is 464 due to PM_2.5 exposure for a long period.

The IHD mortality was 2334 for the AQS-4 location, 2088 for the AQS-3 location, 2068 for the AQS-5 location, 2047 for the AQS-2 location, and 1962 for the AQS-1, AQS-6, and AQS-7 locations. The average IHD mortality for Kota city is 2060 due to PM_2.5 exposure for a long period. Stroke mortality was leading at the AQS-4 location (2171 deaths), followed by the AQS-3 location (1908 deaths), the AQS-5 location (1887 deaths), the AQS-2 location (1865 deaths), and 1777 for the AQS-1, AQS-6, and AQS-7 locations. The average stroke mortality for Kota city is 1880 due to PM_2.5 exposure for a long period. The postneonatal infant mortality due to PM₁₀ exposure for a long period was maximum at the S-4 location with 426146 deaths, followed by the AQS-3 location (364196 deaths), AQS-5 location (354092 deaths), AQS-6 (354095 deaths), AQS-2 (341237 deaths), AQS-1 (325475 deaths), AQS-7 (325475deaths). The average postneonatal infant mortality for Kota city is 355816 due to PM₁₀ exposure for a long period.

The chronic bronchitis incidence in adults was 16151 for the AQS-4 location, 14719 for the AQS-3 location, 14460 for the AQS-5 and AQS-6 locations, 14119 for the AQS-2 location, and 13685 for the AQS-1 and AQS-7 locations. The average chronic bronchitis incidence in adults for Kota city is 14469 due to PM₁₀ exposure for a long period. The prevalence of bronchitis in kids was foremost at the AQS-4 location (882 cases), followed by the AQS-3 location (782 cases), the AQS-5 and AQS-6 locations (765 cases), the AQS-2 location (743 cases), and 715 for the AQS-1, and AQS-7 locations. The prevalence of bronchitis in kids in Kota city is 767 due to PM₁₀ exposure for a long period. The hospital admission for respiratory disease (HA-RD) from PM_2.5 exposure for a short period was maximum at the AQS-4 location with 2153 cases, followed by the AQS-3 location (1532 cases), AQS-5 location (1487 cases), AQS-2 (1442 cases), AQS-1, AQS-6, and AQS-7 (1260 cases). The average HA-RD for Kota city is 1485 due to PM_2.5 exposure for a short period.

The hospital admission due to cardiovascular disease (HA-CVD) was 85 for the AQS-4 location, 60 for the AQS-3 location, 58 for the AQS-5 location, 56 for the AQS-2 location, and 49 for the AQS-1, AQS-6, and AQS-7 locations. The average HACVD for Kota city is 58 due to PM_2.5 exposure for a short period. The all-cause mortality in adults was leading at the AQS-4 location (1142 deaths), followed by the AQS-3 location (808 deaths), the AQS-5 location (784 deaths), the AQS-2 location (760 deaths), and 664 for the AQS-1, AQS-6, and AQS-7 locations. The average all-cause mortality in adults for Kota city is 784 due to PM_2.5 exposure for a short period. The asthma symptoms in asthmatic kids due to PM₁₀ exposure for a short period were maximum at the AQS-4 location with 430 cases, followed by the AQS-3 location (362 cases), AQS-5 location (352 cases), AQS-2 (338 cases), AQS-1, AQS-2, and AQS-7 (321 cases). The mean asthma symptoms in asthmatic kids for Kota city is 349 due to PM₁₀ exposure for a short period.

The EAP and ENACPL for long and short-term effects of PM_2.5 and PM₁₀ on humans. AirQ+ software gave the results at the ambient level tabulated in Tables 7 and 8, respectively. Notably, the higher concentration of particulate matter station has high ENACs, EAP and ENACPL.

Table 7: Station Wise Distribution of EAP (%) for Disease Caused by PM₁₀ and PM_2.5. 

*EAP stands for the estimated attributable proportion.

The individual station data is utilised to exhibit the spatial distribution of mortality due to all causes (natural), lung cancer, COPD, ALRI, Stroke and IHD in Kota city. The software employed to exhibit spatial variability is ESRI ArcGIS with the inverse distance weighing (IDW) interpolation method. 

Table 8: Station Wise Distribution of ENACPL for Disease Caused by PM₁₀ and PM_2.5.

*ENACPL stands for the estimated number of attributable cases per lac population.

The spatial variability maps for mortality due to all-natural causes (Figure 6), lung cancer (Figure 7), ALRI (Figure 8), COPD (Figure 9), IHD (Figure 10), and stroke (Figure 11) have been prepared through ESRI ArcGIS software. It can be easily verified through these maps that the peoples of the nearby area of station AQS-4 (Regional Office, RSPCB) are highly vulnerable to the adverse effect of particulate matter as this station has the peak average PM₁₀ and PM_2.5 concentrations among all. The AQS-4 station is only 3.5 km from the city's center, the aerodrome circle. The AQS-6 station (Sewage Treatment Plant, Balita) is situated on the outer periphery of Kota city, almost 12 km from the city's center, the aerodrome circle, and it is the least susceptible to the adverse effect of particulate matter due absence of air pollution sources.

Figure 6: Spatial distribution map for all-cause mortality in Kota city, Rajasthan (India).   Click here to view Figure

Figure 7: Spatial distribution map for lung cancer mortality in Kota city, (India).   Click here to view Figure

Figure 8: Spatial distribution map for ALRI mortality in Kota city, Rajasthan (India).   Click here to view Figure

Figure 9: Spatial distribution map for COPD mortality in Kota city, Rajasthan (India).   Click here to view Figure

Figure 10: Spatial distribution map for IHD mortality in Kota city, Rajasthan (India).   Click here to view Figure

Figure 11: Spatial distribution map for stroke mortality in Kota city, Rajasthan (India).   Click here to view Figure

Conclusion

The present study reveals that the particulate matter concentration for Kota during the observation period is clearly violating the standards prescribed by the different global agencies, namely, WHO, USEPA, and Indian NAAQS. Particulate matter pollution is identified as the foremost cause of air pollution in Kota. The air quality monitoring station situated at Regional Office, RSPCB shows the maximum degradation in the air quality due to the presence of different micro, small and medium enterprises. Transportation of goods with the help of heavy vehicles puts an additional deterioration in the ambient air quality. The amount of fine particulate matter (PM_2.5) gradually increases in Kota city as the dust ratio shows an increasing trend during the observation period. The fine particles have the capability of penetrating deeper into the respiratory tract and creating many adverse effects on the human body. Hence, it is becoming a more serious concern for the inhabitants of Kota city.

The environmental risk assessment of particulate matter results shows that neither the state capital, Jaipur, nor other prominent cities such as Kota, Ajmer, Udaipur, Pali, Jodhpur, and Alwar of Rajasthan are competent to maintain or keep below the particulate matter concentration within the safe limits prescribed by different agencies worldwide. In other words, metro cities of Rajasthan state are suffering from regularly growing levels of particulate matter pollution.

The ecological environment of Kota city is under massive threat as the hazard risk is in the high category (RQ>1) for PM₁₀ and PM_2.5. Ecological environment risk assessment suggests that Kota inhabitants are highly vulnerable to negative impacts caused by particulate matter. The order of mortality cases for Kota city evaluated through AirQ+ software is the all-natural cause (4565-6365) > IHD (1962-2333) > stroke (1776-2171) > lung cancer (809-1102) > COPD (436-542) > ALRI (255-316).

Improving the management of solid waste, restricting open burning, increasing green beltways, prohibiting old vehicles, planting different plants, and shifting towards clean energy vehicles would effectively lessen the consequence of particulate matter on people. 

Acknowledgements

We are grateful to CPCB and RSPCB for providing particulate matter data for the study. Highly obliged to University Departments, RTU, Kota (India), for providing financial support to this

study.

Conflict of Interest

There is no conflict of interest between the authors.

Funding Sources

There is no funding source.

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