Development and performance evaluation of statistical models correlating air pollutants and meteorological variables at Pantnagar, India

Abstract

Ambient air quality in respect of SO₂, NO₂ and total suspended particulate matter (TSPM) was monitored at Pantnagar, India from May, 2008 to April, 2009 and statistically analyzed with meteorological variables such as relative humidity (RH), wind speed (WS), precipitation (P) and mean air temperature (T). TSPM was found to be the major air pollutant causing significant deterioration of air quality with annual mean concentrations of 280 μg/m³. Further, weekly mean air pollutant concentrations were statistically analyzed through stepwise multiple linear regression analysis in respect of independent meteorological variables to develop suitable statistical models. Both NO₂ and TSPM concentrations were found to have been influenced by meteorological variables with coefficient of determination (R²) of 82.21 and 92.84%, respectively. However, atmospheric SO₂ revealed only 22.87% of dependencies on meteorological variables. Partial correlation coefficients revealed that wind speed has the maximum influence (77.80 and 31.50%) on proposed equations for NO₂ and SO₂, closely followed by weekly mean temperature (73.60 and 24.30%). However, in case of TSPM, individual contribution of ambient temperature (94.40%) was found maximum, followed by relative humidity (86.50%). Model performances were evaluated through both quantitative data analysis techniques and statistical methods. Nearly 98 and 95% of potential error has been explained by the model developed for TSPM and NO₂, while in case of SO₂, it is found as only 61%. Therefore, performances of models (for TSPM and NO₂) to predict ambient weekly mean concentrations based on forecasted weather parameters were found to be excellent, however, performance of model developed for SO₂ was found only satisfactory.

Introduction

In recent years, continuous industrial establishment, population expansion and increase in energy consumption have lead to the general deterioration of ambient air quality in most of the countries. Poor air quality has both acute as well as chronic health impacts (Nastos et al., 2010) and the severity of the impacts mostly depends upon two variable factors viz. ambient concentrations of the air pollutants and its exposure time. Further, concentrations of air pollutants are subject to alter depending on the local topography, source emission and surrounding meteorological conditions. However, among these variables, meteorological parameters are chiefly responsible for causing variations in the ambient concentrations of air pollutants (Banerjee and Srivastava, 2009a). It is now well established that unfavorable meteorological factors like atmospheric stability, can greatly aggravate the impacts caused by certain air pollutants. Therefore, over the past few decades, air quality in the urban areas has been interpreted with the combination of various meteorological factors (Olcese and Toselli, 1997, Tasdemir et al., 2005, Ilten and Selici, 2008). Chao (1991) investigated the relationships between air pollutants concentrations with meteorology which has helped in formulating appropriate policies to combat air pollution in Shanghai, China. Escourrou (1990) explored the influence of different climatic scales viz. general, local and regional climatic pattern on air pollutants in Paris, France. Miyazaki and Yamaoka (1991) established relationship between mean atmospheric dust concentrations with some climatic variables in Osaka, Japan. Tirabassi et al. (1991) concluded the presence of significant correlation between wind speed and ground-level concentrations of air pollutants in the city of Ravenna, Italy. Ilten and Selici (2008) reported that ambient TSPM and SO₂ concentrations are highly correlated with meteorological variables in Balikesir, Turkey. Giakoumi et al. (2009) indicated a significant relation of suspended particles and nitrogen oxides concentrations with meteorological variables in Athens, Greece. İçağa and Sabah (2009) found considerable dependencies between air pollutants and humidity, temperature and inversion, but no relationship between wind velocity and precipitation in Afyon, Turkey. However, Cuhadaroglu and Demirci (1997), through multiple linear regression analyses reported the absence of any strong relationships between ground-level air pollutants with meteorological factors in urban areas of Trabzon, Turkey. Tasdemir et al. (2005) supported these findings by their experiment in Bursa, Turkey, where weak correlation was found to persist between meteorological parameters and air pollutant variables.

In urban areas, combustion of fossil fuels to generate electricity, in industrial processes, transportation and space heating is the predominant anthropogenic source of atmospheric air pollutants (CO, NO₂, SO₂, TSPM etc.). TSPM is the general term that is used to denote the solid particles and liquid droplets present in the atmosphere. These are diverse in physical and chemical properties depending on their source (stationary, mobile or natural), geography and meteorology of the particular area. Epidemiological studies emphasized that exposure to airborne particles with aerodynamic diameter < 10 μm (Respirable Particulate Matter, RPM) induce negative health impacts (Nastos et al., 2010) and adverse meteorological factors may aggravate such kind of exposure. In addition to these, particulates are also responsible for causing reduced visibility and changes in the nutrient balance both through wet as well as dry deposition processes (US EPA, 1998). Atmospheric sulphur is one of the prominent anthropogenic pollutants, responsible for causing formation of sulphate aerosols, deposition of sulphate particles and generation of sulphuric acids droplets (H₂SO₄) under the apposite atmospheric conditions. Researches involving asthmatics indicated that significant proportion of population experience changes in pulmonary function and respiratory symptoms after very short periods of exposure to SO₂ (WHO, 2005). Sulphur-dioxide mostly generated through combustion of fossil fuels is therefore, closely associated with urban air pollution problems. Nitrogen oxides are the byproducts of fossil fuel combustion processes, therefore, emission from automobiles are significant contributors of atmospheric NO₂. Irritation in the respiratory tract is the predominant impact associated with NO₂ when it is converted to nitrates and nitric acid. However, protracted exposure may cause adverse impacts on the lung structure, metabolism and resistance against infections (Ali and Athar, 2008).

Elaborative knowledge on the effects of air pollutants on human health is a prerequisite for the development of effective air quality management policies. Geographical analyses have previously been used in the epidemiological studies in order to establish relationships between human health consequences and air pollution exposure. However, variability of air pollutant concentrations in a location has different characteristics based on the prevalent meteorological conditions (Olcese and Toselli, 1997). Moreover, as meteorological factors differ significantly under varying geographical conditions, it is therefore, essential to study the impact of meteorology on the variation of ground-level pollutant concentrations. The present study was therefore, carried out at the Crop Research Centre (CRC) of G.B. Pant University of Agriculture and Technology, Pantnagar, India to statistically evaluate the relationship between the monitored ambient air quality with meteorological variables. Although, the experimental site is basically an agricultural research station, but the development of Integrated Industrial Estate-Pantnagar (IIE-Pantnagar) adjacent to this research centre resulted in gradual increase of regional pollution (Banerjee and Srivastava, 2009a, Banerjee and Srivastava, 2011). Moreover, the climatic and geographic features of the study area are also unique as it located in the Tarai region of Himalayas and accounts for varying climatic extremes throughout the year. In order to accomplish the objectives, the characteristics of the local topography and climatic features were studied and further, seasonal trends of prevailing ambient air quality were analyzed. Furthermore, concentrations of SO₂, NO₂ and TSPMs were investigated to establish statistical relationship with the meteorological variables viz. relative humidity (RH), wind speed (WS), precipitation (P) and weekly mean temperature (T). Conclusively, to evaluate the model performance and applicability of the proposed models in the study area, monitored and model predicted concentrations were statistically compared.