Spatial distribution and sources of polycyclic aromatic hydrocarbons (PAHs) in soils from typical oil-sewage irrigation area, Northeast China

Air pollution is one of the major environmental problems in India, affecting health of thousands of 'urban' residents residing in mega cities. The need of the day is to evolve an 'effective' and 'efficient' air quality management plan (AQMP) encompassing the essential 'key players' and 'stakeholders.' This paper describes the formulation of an AQMP for mega cities like Delhi in India taking into account the aforementioned key 'inputs.' The AQMP formulation methodology is based on past studies of Longhurst et al., (Atmospheric Environment, 30, 3975-3985, 1996); Longhurst & Elsom, ((1997). Air Pollution-II, Vol. 2 (pp. 525-532)) and Beatti et al., (Atmospheric Environment, 35, 1479-1490, 2001). Further, the vulnerability analysis (VA) has been carried out to evaluate the stresses due to air pollution in the study area. The VA has given the vulnerability index (VI) of 'medium to high' and 'low' at urban roadways/intersections and residential areas, respectively.     

Receptor model-based source apportionment of particulate pollution in Hyderabad, India

Air quality in Hyderabad, India, often exceeds the national ambient air quality standards, especially for particulate matter (PM), which, in 2010, averaged 82.2?±?24.6, 96.2?±?12.1, and 64.3?±?21.2 μg/m³ of PM₁₀, at commercial, industrial, and residential monitoring stations, respectively, exceeding the national ambient standard of 60 μg/m³. In 2005, following an ordinance passed by the Supreme Court of India, a source apportionment study was conducted to quantify source contributions to PM pollution in Hyderabad, using the chemical mass balance (version 8.2) receptor model for 180 ambient samples collected at three stations for PM₁₀ and PM_2.5 size fractions for three seasons. The receptor modeling results indicated that the PM₁₀ pollution is dominated by the direct vehicular exhaust and road dust (more than 60 %). PM_2.5 with higher propensity to enter the human respiratory tracks, has mixed sources of vehicle exhaust, industrial coal combustion, garbage burning, and secondary PM. In order to improve the air quality in the city, these findings demonstrate the need to control emissions from all known sources and particularly focus on the low-hanging fruits like road dust and waste burning, while the technological and institutional advancements in the transport and industrial sectors are bound to enhance efficiencies. Andhra Pradesh Pollution Control Board utilized these results to prepare an air pollution control action plan for the city.     

Qualitative Detection of Volatile Organic Compounds in Outdoor and Indoor Air

The present work attempts to identify VOC's in outdoor and indoor air in Mumbai City India. Ambient air was adsorbed on especially fabricated stainless steel cartridge packed with activated coconut charcoal at uniform flow rate. Qualitative identification of VOC's was done by thermally desorbing air from the cartridges and subsequent analysis on Varian GC-MS using NIST Library. The outdoor monitoring locations include residential area, commercial area, industrial, airport, petrol pumps, traffic junctions, arterial roads, highways, slums, parking area, service garages and municipal dump sites. The indoor locations comprised of air-conditioned and non air-conditioned offices, bedrooms, shops and instrumentation laboratory. The identified VOC's include aldehydes, ketones, polynuclear aromatic hydrocarbons, aromatic acids, oxygenated hydrocarbons, amines, esters and halogenated compounds. Thirteen VOCs in outdoor air and seven in indoor air amongst those identified, figure in the list of Hazardous Air Pollutants listed in Title III of the U.S. EPA Clean Air Act Amendments of 1990.     

Real time remote monitoring of air pollutants and their online transmission to the web using internet protocol

Recent advances in both information and sensor technologies have enabled the development of Real Time Remote Monitoring (RTRM) capabilities for environmental management. An online and real time remote monitoring system for air pollution has been designed and installed at a traffic police station at Punjagutta in Hyderabad, India. The system is optimized using electrochemical sensors and a real time particulate matter analyzer. The system also monitors meteorological parameters such as temperature, humidity, rainfall, barometric pressure, wind speed and wind direction. The system periodically monitors both pollution and meteorological parameters at pre- programmed intervals of hr during peak periods and 1 hr during non peak periods of the day and continuously uploads to a predestinated web site (www.appcb.org/home.htm) using File Transfer Protocol. The web site renders a quick, simple and graphical display of air pollution levels and meteorological parameters and their significance to humans. The present paper highlights design considerations of a pollution monitoring system, system hardware and software requirements and practical limitations and future directions for real time remote monitoring of air pollution.     

Air Pollution and Heat Exposure Study in the Workplace in a Glass Manufacturing Unit in India

Air pollution in the workplace environment due to industrial operation have been found to cause serious occupational health hazard. Similarly, heat stress is still most neglected occupational hazard in the tropical and subtropical countries like India. The hot climate augments the heat exposure close to sources like furnaces. In this study an attempt is made to assess air pollution and heat exposure levels to workers in the workplace environment in glass manufacturing unit located in the State of Gujarat, India. Samples for workplace air quality were collected for SPM, SO₂, NO₂ and CO₂ at eight locations. Results of workplace air quality showed 8-hourly average concentrations of SPM: 165–9118 μg/m³, SO₂: 6–9 μg/m³ and NO₂: 5–42 μg/m³, which were below the threshold limit values of workplace environment. The level of CO₂ in workplace air of the plant was found to be in the range 827–2886 μg/m³, which was below TLV but much higher than the normal concentration for CO₂ in the air (585 mg/m³). Indoor heat exposure was studied near the furnace and at various locations in an industrial complex for glass manufacturing. The heat exposure parameters including the air temperature, the wet bulb temperature, and the globe parameters were measured. The Wet Bulb Globe Temperature (WBGT), an indicator of heat, exceeded ACGIH TLVs limits most of the time at all the locations in workplace areas. The recommended duration of work and rest have also been estimated.     

我国重点调查企业工业锅炉污染排放特征

基于中国2015年环境统计重点调查工业企业的逐台工业锅炉数据,分析了中国重点调查工业企业工业锅炉的现状、能源消耗、污染排放及治理水平等。统计数据分析表明:在能源消耗和废气污染物产生排放量上,燃煤工业锅炉占85%以上;燃煤工业锅炉规模越小,其烟粉尘排放强度越大;超过一半以上工业锅炉烟粉尘直排,烟粉尘去除率虚高;工业锅炉相对集中在东北、华北少数几个大省及热力、化工等少数几个重污染行业。对工业锅炉污染治理提出治理对策建议。     

Assessment of Dust Generation Due to Opencast Coal Mining– An Indian Case Study

Every mine in India has to obtain environmental clearance fromthe Govt. Air pollution is one of the most important parametersto be considered in preparing an EIA. However, there is no welldefined method for predicting thr air pollution impact due tomining. Increasing trend of opencast (O/C) mining leads toproduction of huge quantities of dust. Emission factor data havebeen utilised to quantify the generation of dust. The projectunder study is one of the largest opencast project (OCP) forcoking coal. The main sources of air pollution have beenidentified. The rate of emission per unit of a given activityknown as an emission factor has been utilised, taking localfactors into account. It has been estimated that due to topsoilremoval, overburden (O/B) removal, extraction of coal, sizereduction generated 7.8 t of dust per day. Wind erosiongenerated 1.6 t of dust per day and the whole operationproduced dust which accounted for 9.4 mt/day. They cause airpollution in the work zone and surrouding locations. Themethodology adopted may be used to quantify generation for otherprojects also.     

Waste management modeling by MARKAL model: A case study for Basilicata Region

Air pollution is one of the most pressing environmental problems which affects likewise urban, industrial and rural areas. Environmental planners, regulators and decision makers need reliable, scientifically based tools to find out strategies for controlling air pollution in a cost-effective way, taking into account the whole productive system. In this framework the basic elements of energy-environmental planning have to be extended to include also waste processing technologies amongst the usually considered pollution sources. Bottom-up optimizing models, based on linear programming techniques and customized for specific cases, represent a powerful tool in energy-environmental management. This paper focuses on the integrated modeling of material flows and energy system performed on a local scale case study (Basilicata Region, Southern Italy) using the linear programming model IEA-MARKAL. We have evaluated the feasibility of the model in representing the waste management system to estimate the environmental impact of the waste processing technologies in the context of the whole productive system. A sensitivity analysis has been carried out to emphasize the connections between tariffs, waste disposal technologies assessment and atmospheric emissions. This revised version was published online in July 2006 with corrections to the Cover Date.     

Forecasts using Box–Jenkins models for the ambient air quality data of Delhi City

The monthly maximum of the 24-h average time-series data of ambient air quality-sulphur dioxide (SO(2)), nitrogen dioxide (NO(2)) and suspended particulate matter (SPM) concentration monitored at the six National Ambient Air Quality Monitoring (NAAQM) stations in Delhi, was analysed using Box-Jenkins modelling approach (Box et al. 1994). Univariate linear stochastic models were developed to examine the degree of prediction possible for situations where only the past record of pollutant data are available. In all, 18 models were developed, three for each station for each of the respective pollutant. The model evaluation statistics suggest that considerably satisfactory real-time forecasts of pollution concentrations can be generated using the Box-Jenkins approach. The developed models can be used to provide short-term, real-time forecasts of extreme air pollution concentrations for the Air Quality Control Region (AQCR) of Delhi City, India.     

Status of air pollution caused by coal washery projects in India

The importance of coal washeries in India is growing as local coals have a high ash content. At present, there are 23 coal washeries with an annual rated input of 45 Million Tonnes. During the various operations in washeries, large amounts of dusts and gaseous pollutants are generated. Four coal washery projects were surveyed to study their air pollution characteristics. Air monitoring stations were set up in local industrial, residential and sensitive areas and air pollution samples were collected along with micro-meteorological data. Diurnal variations of SPM, SO₂ NO_x and CO are discussed. SPM concentrations were found to exceed the permissible limits at all locations. SO₂ and NO_x were also found to exceed the permissible limit in residential and sensitive areas. It was observed that about 50% of the dust particles were less than 10 µ in diameter. Benzene soluble matter in SPM ranged from 45–62%.