Air Quality Modelling in Environmental Impact Assessment Studies of Different Sectors

Transcription

1 Air Quality Modelling in Environmental Impact Assessment Studies of Different Sectors T.V.B.P.S. Rama Krishna and S.R. Wate Environmental Impact & Risk Assessment Division CSIR National Environmental Engineering Research Institute Nehru Marg, Nagpur Air Quality Workshop: March 22,

2 Introduction Application of air quality modelling in environmental impact assessment studies of different sectors is crucial for identification, prediction and assessment of impacts from existing or proposed developmental projects. In India there are about 40 identified sectors where in EIA studies are mandatory for upcoming activities/industries and modification of existing activities/industries. Several sources of air pollution are envisaged from different activity like Large point sources in thermal power plants; Small to medium industrial stacks from chemical, fertilizer, refinery, steel, etc.; Area sources from mining of coal/minerals, solid waste dumping grounds; Mobile sources in town planning, highways, ports and harbours. 2

3 Available models for different sources of pollution Model Type Source Chemistry Duration ISCST3 Gaussian P, A, L, V N Short ISCLT3 Gaussian P, A, L, V N Long PAL Gaussian P, A, L N Short CDM Gaussian P, A N Long ADMS Gaussian P N Short HIWAY2 Gaussian L N Short CALINE3 CAL3QHC CAL3QHCR Gaussian L N Short ROADWAYS Numerical L Y Short UAM Numerical P, A, L Y Short AERMOD Gaussian P, A, L, V N Short Research Gaussian P, A, L, V N Short/Long

4 Present Study Mathematical models are the best available tools to quantitatively describe causeeffect relationships between sources of pollution and different components of environment. In this presentation the impacts on air environment due to: (a) Manmade fibre industry (b) Iron ore mine (c) Berthed ships in an Indian port (iv) Vehicular emissions 4

5 Methodology Industrial Source Complex Short Term (ISCST-3) model To predict the maximum ground level concentrations (GLCs) of SO 2 due to CS 2 plant, sulphuric acid plant and power plant and due to all three sources along with maximum GLCs of NOx and PM from power plant operated in a manmade fibre industry (NEERI, 2010). Fugitive Dust Model (FDM) SCREEN-3 model CALINE-4 model To assess the PM 10 concentration from different activities in an iron ore mining project. The emissions and GLCs are computed for two scenarios, without considering dust control measures and by considering dust control measures during the winter season (NEERI, 2009). Air pollution impact due to movement of ships and berthing at the five proposed berths in an Indian port on air environment is studied (NEERI, 2012). To predict impacts due to vehicular emissions on two major roads. 5

6 Case Studies Case I Case II : Impact due to Stacks/point sources using ISCST-3 Model : Impact due to Mining using FDM Case III : Impact due to Ships using SCREEN-3 Model Case IV : Impact due to Vehicular Emissions using CALINE-4 Model 6

7 Case I: Impact due to Stacks/point sources using ISCST-3 Model Sr. No. Stack Stack Height (m) Emission details for manmade fibre plant Stack Top Diameter (m) Stack Gas Temp ( o C) Stack Gas Velocity (m/s) Emissions Rate (g/s) SO 2 NOx SPM 1 CS 2 Plant H 2 SO 4 plant CPP Hourly meteorological data comprising: - wind speed (m/s) - wind direction (deg) - ambient temperature (K) - atmospheric stability - mixing height (m) Winter 7

8 Case I: Impact due to Stacks/point sources using ISCST-3 Model CS2 plant Max GLC of SO2: 8.4 µg/m3 Sulphuric acid plant Max GLC of SO2: 2.3 µg/m3 Captive Power Plant Max GLC of SO2: 2.8 µg/m3 8

9 Case I: Impact due to Stacks/point sources using ISCST-3 Model CS2 plant, sulphuric acid plant and power plant Winter Max GLC of SO2: 11.5 µg/m3 occurring at 1.4 km in SW direction 9

10 Case I: Impact due to Stacks/point sources using ISCST-3 Model S.No Pollutant Maximum GLC (µg/m 3 ) Distance from Source (km) Direction from Source (A) CS 2 Plant 1. SO SW (B) Sulphuric Acid Plant 1. SO SW (C) Captive Power Plant 1. SO SW 2. NOx SW 3. SPM SW Cumulative SO 2 GLCs due to (A) + (B) + (C) 1. SO SW 10

11 Case II: Impact due to Mining using FDM Different types of emissions are considered for mining operations: Drilling, blasting, dozing, grading, loading/unloading trucks, waste dumps, haul road dust, loading to stockpiles, loading to trains, ore stacks at siding and primary/secondary/tertiary crushing In the first scenario, the emissions are calculated for worst case without considering Environmental Management Plan (EMP) Sprinkling of water, wind break of greenbelt, and other measures etc. which are used to reduce SPM emission In second scenario, emissions are calculated considering implementation of EMP. 11

12 Case II: Impact due to Mining using FDM GLCs of SPM were predicted over an area of 25 km x 25 km. Modelling exercise is carried out for mining activities in the mining leasehold. GLCs of SPM are computed at least 0.5 km away from the mine boundary to determine contribution of mining activities to ambient air quality. 12

13 Case II: Impact due to Mining using FDM Distance in North Direction (m) Distance in East Direction (m) Max Conc.: 31 µg/m 3 on any Working Day within the Mining Area. The Maximum Concentration of SPM will be within 500 m of the Mining area Fig : Increase in GLCs of SPM due to Mining Activity during Winter Season (Without EMP) 13

14 Case II: Impact due to Mining using FDM Distance in North Direction (m) Distance in East Direction (m) Max Conc.: 12 µg/m 3 on any Working day within the Mining Area. The Maximum Concentration of SPM will be within 500 m of the Mining area Fig : Increase in GLCs of SPM due to Mining Activities during Winter Season (With EMP) 14

15 Case III: Impact due to Ships using SCREEN-3 Model The air pollution impact due to movement of ships and berthing at the five proposed berths in an Indian port on air environment is studied (NEERI, 2012). Berths are designed for operating ships with capacity ranging from 40,000 DWT to 100,000 DWT. It is assumed that all five berths are occupied with one ship each. Marine diesel oil is taken as the fuel used by ships. Pollutant emissions from the ships are estimated based on the emission factors for the pollutants SO 2, NOx and PM 10 with ships having four main (> 2000 KW) and four auxiliary (600 KW) engines in operation moving with medium speed (SKM, 2007; DEH, 2001). 15

16 Case III: Impact due to Ships using SCREEN-3 Model Maximum ground level concentrations of SO 2, NOx and PM 10 due to five ships berthed at five berths simultaneously are computed to be µg/m 3, µg/m 3 and 1.1 µg/m 3 on 24- hourly basis occurring at a distance of 600 m from the berths position. The predicted 24 hourly GLCs of SO 2, NOx and PM 10 are found to be less than the 24 hourly concentrations of 228 µg/m 3 for SO 2 and 50 µg/m 3 for PM 10 as given in ground level impact assessment criteria (DECC, 2005). However, the 24 hourly concentrations of NOx are found to be higher than the ground level impact assessment criteria of 98 µg/m 3. 16

17 Case IV: Impact due to Vehicular Emissions using CALINE-4 Model Hourly traffic volume on the two roads was monitored for different types of vehicles. GLCs are computed as 8 hourly averages for three periods of the day: hrs (morning traffic) hrs (evening traffic) hrs (night traffic) Computed GLCs due to different types of vehicles plying on the two major roads during different periods are exclusively due to vehicular traffic on these roads only as no background concentration is included in the calculations. 17

18 Case IV: Impact due to Vehicular Emissions using CALINE-4 Model Source Strength / Emission Rate q = TV * EF q - Source strength (g m -1 s -1 ) TV Traffic volume (Vehicles hr -1 ) EF - Emission factor (g km -1 vehile -1 )

19 Case IV: Impact due to Vehicular Emissions using CALINE-4 Model 300 CO 250 Concentration (ug/m 3 ) R1 R Morning Evening Night Time 19

20 Case IV: Impact due to Vehicular Emissions using CALINE-4 Model 70 NOx 60 Concentration (ug/m 3 ) R1 R Morning Evening Night Time 20

21 Case IV: Impact due to Vehicular Emissions using CALINE-4 Model 60 HC 50 Concentration (ug/m 3 ) R1 R Morning Evening Night Time 21

22 Case IV: Impact due to Vehicular Emissions using CALINE-4 Model Higher GLCs during the period hrs is due to the size of the relatively large traffic volume plying on these two roads and the slightly stable to moderately stable atmospheric stability conditions in the evening to night hours during winter months. Though the traffic volume on these roads is higher during the period hrs, the GLCs are lower than those observed during evening period, as the atmospheric stability conditions are slightly unstable and sufficient mixing could be possible during the daytime (morning to noon hours). However, during night ( hrs) the GLCs are low due to low traffic volume compared to daytime traffic on these roads. Predicted ground level concentrations of pollutants are observed to be less than the NAAQS which are given as 24 hourly averages for NOx and as 1 hourly average for CO. The NAAQS for NOx and CO are 80 µg/m 3 and 4000 µg/m 3 respectively. 22

23 Conclusions Case studies comprising impact assessment on air environment due to manmade fibre industry, mining activities, berthing of ships at a port and vehicular emissions using appropriate air quality models are discussed Short term air quality models were used for these studies Based on the outcome of the impact assessment, environmental management plan has been suggested considering either prevention at the source or intervention at the receptor through proper mitigation measures 23

24 Conclusions In the instant case, Mitigation measures were incorporated at the source of emissions to minimize the impacts on environment. In few cases, Where we have done validation, the additional impacts arising out of the proposed development were found to be maximally nullified showing no incremental increase in the concentrations at the receptors by adopting proper mitigation measures. The spatial variations of pollutants need to be addressed using regional air quality models to arrive at a proper strategic environmental management and action plans in areas where cluster of several polluting sources co-exist. 24

25 THANK YOU 25