# name
Use of spatiotemporal characteristics of ambient PM2.5 in rural
                South India to infer local versus regional contributions

# metadata.dc.description.abstract[].value
This study uses spatiotemporal patterns in ambient
                concentrations to infer the contribution of regional versus
                local sources. We collected 12 months of monitoring data for
                outdoor fine particulate matter (PM2.5) in rural southern India.
                Rural India includes more than one-tenth of the global
                population and annually accounts for around half a million air
                pollution deaths, yet little is known about the relative
                contribution of local sources to outdoor air pollution. We
                measured 1-min averaged outdoor PM2.5 concentrations during June
                2015-May 2016 in three villages, which varied in population
                size, socioeconomic status, and type and usage of domestic fuel.
                The daily geometric-mean PM2.5 concentration was approximately
                30mugm(-3) (geometric standard deviation: approximately 1.5).
                Concentrations exceeded the Indian National Ambient Air Quality
                standards (60mugm(-3)) during 2-5% of observation days. Average
                concentrations were approximately 25mugm(-3) higher during
                winter than during monsoon and approximately 8mugm(-3) higher
                during morning hours than the diurnal average. A moving average
                subtraction method based on 1-min average PM2.5 concentrations
                indicated that local contributions (e.g., nearby biomass
                combustion, brick kilns) were greater in the most populated
                village, and that overall the majority of ambient PM2.5 in our
                study was regional, implying that local air pollution control
                strategies alone may have limited influence on local ambient
                concentrations. We compared the relatively new moving average
                subtraction method against a more established approach. Both
                methods broadly agree on the relative contribution of local
                sources across the three sites. The moving average subtraction
                method has broad applicability across locations.

# metadata.dc.relation.isformatof[].value
Reproducció del document publicat a:
                http://dx.doi.org/10.1016/j.envpol.2018.04.057

# metadata.dc.source[].value
Articles publicats en revistes (ISGlobal)

# metadata.dc.title[].value
Use of spatiotemporal characteristics of ambient PM2.5 in rural
                South India to infer local versus regional contributions