Search

We introduce an innovative method to distinguish soil nitrogen oxides (NOx = NO + NO2) emissions from satellite‐based total NOx emissions. To evaluate the approach, we compare the deviation between the tropospheric NO2 concentration observed by satellite and two atmospheric composition model simulations driven by the newly estimated soil NOx emissions and the Copernicus Atmosphere Monitoring Service (CAMS) inventory. The estimated average soil NOx emissions in Europe are 1.7 kg N ha−1 yr−1 in 2019, and the annual soil NOx emissions are approximately 1.7 times larger than that of the CAMS inventory. The discrepancy originates mainly from the forests, which would mean that the soil NOx emissions over forest areas in Europe are currently underestimated by the CAMS inventory. The model evaluation indicates that the simulations driven by DECSO‐soil emissions performed significantly better than using CAMS‐soil. Overall, the simulated RMSE% of DECSO‐soil is lower than that of CAMS‐soil, approximately 6% lower in spring and 2% lower in autumn. Our method can easily be extended to other regions in the world despite having monthly variations that are very different from those in Europe. Plain Language Summary: Soil nitrogen oxide emissions (NOx = NO + NO2) are an essential source of air pollution, accounting for about 15% of global NOx emissions. Unfortunately, soil emissions are not always accurately described by current bottom‐up inventories. Accurate quantification is beneficial for clarifying the contribution of biogenic sources to air quality and developing more targeted air quality measures. We present an innovative method for estimating soil NOx emissions from satellite‐based total NOx emissions. The newly estimated annual emissions in Europe are about 1.7 times higher than reported in previous studies, especially over forest areas. The method is evaluated by comparing the deviation between the simulated and satellite‐observed tropospheric NO2 concentrations. This method can also be extended to other regions in the world. Key Points: An innovative method is introduced to derive European soil NOx emissions from satellite NO2 observationsThe resulting soil NOx emissions are 1.7 times larger than widely used bottom‐up soil NOx emission estimatesThis satellite observation‐based method provides a valuable independent estimate of the soil NOx emissions [ABSTRACT FROM AUTHOR]

Over the past century, ammonia (NH3) emissions have increased with the growth of livestock and fertilizer usage. The abundant NH3 emissions lead to secondary fine particulate matter (PM 2.5) pollution, climate change, and a reduction in biodiversity, and they affect human health. Up-to-date and spatially and temporally resolved information on NH3 emissions is essential to better quantify their impact. In this study we applied the existing Daily Emissions Constrained by Satellite Observations (DECSO) algorithm to NH3 observations from the Cross-track Infrared Sounder (CrIS) to estimate NH3 emissions. Because NH3 in the atmosphere is influenced by nitrogen oxides (NOx), we implemented DECSO to estimate NOx and NH3 emissions simultaneously. The emissions are derived over Europe for 2020 on a spatial resolution of 0.2°×0.2° using daily observations from both CrIS and the TROPOspheric Monitoring Instrument (TROPOMI; on the Sentinel-5 Precursor (S5P) satellite). Due to the limited number of daily satellite observations of NH3 , monthly emissions of NH3 are reported. The total NH3 emissions derived from observations are about 8 Tgyr-1 , with a precision of about 5 %–17 % per grid cell per year over the European domain (35–55° N, 10° W–30° E). The comparison of the satellite-derived NH3 emissions from DECSO with independent bottom-up inventories and in situ observations indicates a consistency in terms of magnitude on the country totals, with the results also being comparable regarding the temporal and spatial distributions. The validation of DECSO over Europe implies that we can use DECSO to quickly derive fairly accurate monthly emissions of NH3 over regions with limited local information on NH3 emissions. [ABSTRACT FROM AUTHOR]

An improved divergence method has been developed to estimate annual methane (CH 4) emissions from TROPOspheric Monitoring Instrument (TROPOMI) observations. It has been applied to the period of 2018 to 2021 over the Middle East, where the orography is complicated, and the mean mixing ratio of methane (XCH 4) might be affected by albedos or aerosols over some locations. To adapt to extreme changes of terrain over mountains or coasts, winds are used with their divergent part removed. A temporal filter is introduced to identify highly variable emissions and to further exclude fake sources caused by retrieval artifacts. We compare our results to widely used bottom-up anthropogenic emission inventories: Emissions Database for Global Atmospheric Research (EDGAR), Community Emissions Data System (CEDS), and Global Fuel Exploitation Inventory (GFEI) over several regions representing various types of sources. The NO x emissions are from EDGAR and Daily Emissions Constrained by Satellite Observations (DECSO), and the industrial heat sources identified by Visible Infrared Imaging Radiometer Suite (VIIRS) are further used to better understand our resulting methane emissions. Our results indicate possibly large underestimations of methane emissions in metropolises like Tehran (up to 50 %) and Isfahan (up to 70 %) in Iran. The derived annual methane emissions from oil/gas production near the Caspian Sea in Turkmenistan are comparable to GFEI but more than 2 times higher than EDGAR and CEDS in 2019. Large discrepancies in the distribution of methane sources in Riyadh and its surrounding areas are found between EDGAR, CEDS, GFEI, and our emissions. The methane emission from oil/gas production to the east of Riyadh seems to be largely overestimated by EDGAR and CEDS, while our estimates as well as GFEI and DECSO NO x indicate much lower emissions from industrial activities. On the other hand, regions like Iran, Iraq, and Oman are dominated by sources from oil and gas exploitation that probably include more irregular releases of methane, with the result that our estimates, which include only invariable sources, are lower than the bottom-up emission inventories. [ABSTRACT FROM AUTHOR]

The Copernicus Atmosphere Monitoring Service (CAMS) provides daily analyses and forecasts of the composition of the atmosphere, including the reactive gases such as O3 , CO , NO2 , HCHO and SO2 ; aerosol species; and greenhouse gases. The global CAMS analysis system (IFS-COMPO) is based on the ECMWF Integrated Forecasting System (IFS) for numerical weather prediction (NWP) and assimilates a large number of composition satellite products on top of the meteorological observations ingested in IFS. The CAMS system receives regular upgrades, following the upgrades of IFS. The last upgrade, Cy48R1, operational since 27 June 2023, was major with a large number of code changes, both for IFS-COMPO and for NWP. The main IFS-COMPO innovations include the introduction of full stratospheric chemistry; a major update of the emissions; a major update of the aerosol model, including the representation of secondary organic aerosol; several updates of the dust life cycle and optics; updates to the inorganic chemistry in the troposphere; and the assimilation of Visible Infrared Imaging Radiometer Suite (VIIRS) aerosol optical depth (AOD) and TROPOspheric Monitoring Instrument (TROPOMI) CO. The CAMS Cy48R1 upgrade was validated using a large number of independent measurement datasets, including surface in situ, surface remote sensing, routine aircraft, and balloon and satellite observations. In this paper we present the validation results for Cy48R1 by comparing them with the skill of the previous operational system (Cy47R3), with the independent observations as reference, for the period October 2022 to June 2023, during which daily forecasts from both cycles are available. Major improvements in skill are found for the ozone profile in the lower–middle stratosphere and for stratospheric NO2 due to the inclusion of full stratospheric chemistry. Stratospheric trace gases compare well with the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) observations between 10 and 200 hPa, with larger deviations between 1 and 10 hPa. The impact of the updated emissions is especially visible over East Asia and is beneficial for the trace gases O3 , NO2 and SO2. The CO column assimilation is now anchored by the Infrared Atmospheric Sounding Interferometer (IASI) instead of the Measurements Of Pollution in The Troposphere (MOPITT) instrument, which is beneficial for most of the CO comparisons, and the assimilation of TROPOMI CO data improves the model CO field in the troposphere. In general the aerosol optical depth has improved globally, but the dust evaluation shows more mixed results. The results of the 47 comparisons are summarised in a scorecard, which shows that 83 % of the evaluation datasets show a neutral or improved performance of Cy48R1 compared to the previous operational CAMS system, while 17 % indicate a (slight) degradation. This demonstrates the overall success of this upgrade. [ABSTRACT FROM AUTHOR]

Since 2018, the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor (S5P) has provided unprecedented images of nitrogen dioxide (NO2) tropospheric columns at a relatively high spatial resolution with a daily revisit. This study aims at assessing the potential of TROPOMI–PAL data to estimate the national to urban NOx emissions in France from 2019 to 2021, using the variational mode of the recent Community Inversion Framework (CIF) coupled to the CHIMERE regional transport model at a spatial resolution of 10 km × 10 km. The seasonal to inter-annual variations in the French NOx emissions are analyzed. Special attention is paid to the current capability to quantify strong anomalies in the NOx emissions at intra-annual scales, such as the ones due to the COVID-19 pandemic, by using TROPOMI NO2 observations. At the annual scale, the inversions suggest a decrease in the average emissions over 2019–2021 of - 3 % compared to the national budget from the Copernicus Atmosphere Monitoring Service regional inventory (CAMS-REG) for the year 2016, which is used as a prior estimate of the national-scale emissions for each year by the Bayesian inversion framework. This is lower than the decrease of - 14 % from 2016 to the average over 2019–2021 in the estimates of the French Technical Reference Center for Air Pollution and Climate Change (CITEPA). The lower decrease in the inversion results may be linked in large part to the limited level of constraint brought by the TROPOMI data, due to the observation coverage and the ratio between the current level of errors in the observation and the chemistry-transport model, and to the NO2 signal from the French anthropogenic sources. Focusing on local analysis and selecting the days during which the TROPOMI coverage is good over a specific local source, we compute the reductions in the anthropogenic NOx emission estimates by the inversions from spring 2019 to spring 2020. These reductions are particularly pronounced for the largest French urban areas with high emission levels (e.g., - 26 % from April 2019 to April 2020 in the Paris urban area), reflecting reductions in the intensity of vehicle traffic reported during the lockdown period. However, the system does not show large emission decreases for some of the largest cities in France (such as Bordeaux, Nice and Toulouse), even though they were also impacted by the lockdown measures. Despite the current limitations for the monitoring of emissions at the national scale, or for some of the largest cities in France, these results open positive perspectives regarding the ability to support the validation or improvement of inventories with satellite observations, at least at the local level. This leads to discussions on the need for a stepwise improvement of the inversion configuration for a better extraction and extrapolation in space and time of the information from the satellite observations. [ABSTRACT FROM AUTHOR]

Since the launch of TROPOMI on the Sentinel-5 Precursor (S5P) satellite, NO 2 observations have become available with a resolution of 3.5× 5 km, which makes monitoring NO x emissions possible at the scale of city districts and industrial facilities. For Europe, emissions are reported on an annual basis for country totals and large industrial facilities and made publicly available via the European Environment Agency (EEA). Satellite observations can provide independent and more timely information on NO x emissions. A new version of the inversion algorithm DECSO (Daily Emissions Constrained by Satellite Observations) has been developed for deriving emissions for Europe on a daily basis, averaged to monthly mean maps. The estimated precision of these monthly emissions is about 25 % for individual grid cells. These satellite-derived emissions from DECSO have been compared to the officially reported European emissions and spatial–temporal disaggregated emission inventories. The country total DECSO NO x emissions are close to the reported emissions and the emissions compiled by the Copernicus Atmosphere Monitoring Service (CAMS). Comparison of the spatially distributed NO x emissions of DECSO and CAMS showed that the satellite-derived emissions are often higher in cities, while they are similar for large power plants and slightly lower in rural areas. [ABSTRACT FROM AUTHOR]

NOx is an important primary air pollutant of major environmental concern which is predominantly produced by anthropogenic combustion activities. NOx needs to be accounted for in national emission inventories, according to international treaties. Constructing accurate inventories requires substantial time and effort, resulting in reporting delays of 1 to 5 years. In addition to this, difficulties can arise from temporal and country-specific legislative and protocol differences. To address these issues, satellite-based atmospheric composition measurements offer a unique opportunity for the independent and large-scale estimation of emissions in a consistent, transparent, and comprehensible manner. Here we test the multi-source plume method (MSPM) to assess the NOx emissions over Germany in the COVID-19 period from 2019–2021. For the years where reporting is available, the differences between satellite estimates and inventory totals were within 75–100 kt (NO2) NOx (<10 % of inventory values). The large reduction in the NOx emissions (∼15 %) concurrent with the COVID-19 lockdowns was observed in both the inventory and satellite-derived emissions. The recent projections for the inventory emissions of 2021 pointed to a recovery of the 2021 emissions towards pre-COVID-19 levels. In the satellite-derived emissions, however, such an increase was not observed. While emissions from the larger power plants did rebound to pre-COVID-19 levels, other sectors such as road transport did not, and the change in emissions is likely due to a reduction in the number of heavier transport trucks compared to the pre-COVID-19 numbers. This again illustrates the value of having a consistent satellite-based methodology for faster emission estimates to guide and check the conventional emission inventory reporting. The method described in this work also meets the demand for independent verification of the official emission inventories, which will enable inventory compilers to detect potentially problematic reporting issues, bolstering transparency and comparability, which are two key values for emission reporting. [ABSTRACT FROM AUTHOR]

Meteorological fields calculated by numerical weather prediction (NWP) models drive offline chemical transport models (CTMs) to solve the transport, chemical reactions, and atmospheric interaction over the geographical domain of interest. HARMONIE (HIRLAM ALADIN Research on Mesoscale Operational NWP in Euromed) is a state-of-the-art non-hydrostatic NWP community model used at several European weather agencies to forecast weather at the local and/or regional scale. In this work, the HARMONIE WINS50 (cycle 43 cy43) reanalysis dataset at a resolution of 0.025° × 0.025° covering an area surrounding the North Sea for the years 2019–2021 was coupled offline to the LOTOS-EUROS (LOng-Term Ozone Simulation-EURopean Operational Smog model, v2.2.002) CTM. The impact of using either meteorological fields from HARMONIE or from ECMWF on LOTOS-EUROS simulations of NO2 has been evaluated against ground-level observations and TROPOMI tropospheric NO2 vertical columns. Furthermore, the difference between crucial meteorological input parameters such as the boundary layer height and the vertical diffusion coefficient between the hydrostatic ECMWF and non-hydrostatic HARMONIE data has been studied, and the vertical profiles of temperature, humidity, and wind are evaluated against meteorological observations at Cabauw in The Netherlands. The results of these first evaluations of the LOTOS-EUROS model performance in both configurations are used to investigate current uncertainties in air quality forecasting in relation to driving meteorological parameters and to assess the potential for improvements in forecasting pollution episodes at high resolutions based on the HARMONIE NWP model. [ABSTRACT FROM AUTHOR]

The rapid development of the economy and the implementation of environmental policies adapted in India has led to fast changes of regional SO2 emissions. We present a monthly SO2 emission inventory for India covering December 2018 to November 2023 based on the TROPOMI Level-2 COBRA SO2 dataset, by using an improved flux-divergence method and estimated local SO2 lifetime which includes both its chemical loss and dry deposition. We update the methodology to use the daily CAMS model output estimates of the hydroxyl-radical distribution as well as the measured dry deposition velocity to account for the variability in the tropospheric SO2 lifetime. The results show the application of the local SO2 lifetime improves the accuracy of SO2 emissions estimation when compared to calculations using a constant lifetime. Our improved flux-divergence method reduced the spreading of the point source emissions compared to the standard flux-divergence method. The averaged SO2 emissions covering the recent 5 years are about 5.2 Tg year-1, which is lower than the bottom-up emissions of 11.0 Tg year-1 from CAMS-GLOB-ANT v5.3. The total emissions from the 92 largest point source emissions are estimated to be 2.9 Tg year-1, lower than the estimation of 5.2 Tg year-1 from the global SO2 catalog MSAQSO2LV4. We argue that for other important regions that have high SO2 emissions, the variability in the SO2 lifetime becomes more important to account for estimating top-down SO2 emissions. [ABSTRACT FROM AUTHOR]

Over the past century ammonia (NH3) emissions have increased with the growth of livestock and fertilizer usage. The abundant NH3 emissions lead to secondary fine particulate matter (PM2.5) pollution, climate change, reduction in biodiversity and affects human health. Up-to-date and spatially and temporally resolved information of NH3 emissions is essential to better quantify its impact. In this study we applied the existing DECSO (Daily Emissions Constrained by Satellite Observations) algorithm to NH3 observations from the Cross-track Infrared Sounder (CrIS) to estimate NH3 emissions. Because NH3 in the atmosphere is influenced by Nitrogen Oxides (NOx), we implemented DECSO to estimate NOx and NH3 emissions simultaneously. The emissions are derived over Europe for 2020 on a spatial resolution of 0.2° ' 0.2° using daily observations from both CrIS and TROPOMI (on the Sentinel 5p satellite). Due to the sparseness of daily satellite observations of NH3, monthly emissions of NH3 are reported. The total NH3 emissions derived from observations are about 8 Tg/year with a precision of about 0.2 % over the European domain. The comparison of the satellite-derived NH3 emissions from DECSO with independent bottom-up inventories and in-situ observations indicates a consistency in terms of magnitude on the country totals, the results also being comparable regarding the temporal and spatial distributions. [ABSTRACT FROM AUTHOR]

Denitrification within the stratospheric vortex is a crucial process for Antarctic ozone hole formation, resulting in an analogous stratospheric "nitrogen hole". Sedimentation of large nitric acid trihydrate polar stratospheric cloud particles within the Antarctic polar stratospheric vortex that form during winter depletes the inner vortex of nitrogen oxides. Here, 2018–2021 daily TROPOspheric Monitoring Instrument (TROPOMI) measurements are used for the first time for a detailed characterization of this nitrogen hole. Nitrogen dioxide total columns exhibit strong spatiotemporal and seasonal variations associated with photochemistry as well as transport and mixing processes. Combined with total ozone column data two main regimes are identified: inner-vortex ozone- and nitrogen-dioxide-depleted air and outer-vortex air enhanced in ozone and nitrogen dioxide. Within the vortex total ozone and total stratospheric nitrogen dioxide are strongly correlated, which is much less evident outside of the vortex. Connecting the two main regimes is a third regime of coherent patterns in the total nitrogen dioxide column–total ozone column phase space – defined here as "mixing lines". These mixing lines exist because of differences in three-dimensional variations of nitrogen dioxide and ozone, thereby providing information about vortex dynamics and cross-vortex edge mixing. On the other hand, interannual variability of nitrogen dioxide–total ozone characteristics is rather small except in 2019 when the vortex was unusually unstable. Overall, the results show that daily stratospheric nitrogen dioxide column satellite measurements provide an innovative means for characterizing polar stratospheric denitrification processes, vortex dynamics, and long-term monitoring of Antarctic ozone hole conditions. [ABSTRACT FROM AUTHOR]

Satellite observations of tropospheric trace gases and aerosols are evolving rapidly. Recently launched instruments provide increasingly higher spatial resolutions with footprint diameters in the range of 2–8 km, with daily global coverage for polar orbiting satellites or hourly observations from geostationary orbit. Often the modelling system has a lower spatial resolution than the satellites used, with a model grid size in the range of 10–100 km. When the resolution mismatch is not properly bridged, the final analysis based on the satellite data may be degraded. Superobservations are averages of individual observations matching the resolution of the model and are functional to reduce the data load on the assimilation system. In this paper, we discuss the construction of superobservations, their kernels and uncertainty estimates. The methodology is applied to nitrogen dioxide tropospheric column measurements of the TROPOMI instrument on the Sentinel-5P satellite. In particular, the construction of realistic uncertainties for the superobservations is non-trivial and crucial to obtaining close to optimal data assimilation results. We present a detailed methodology to account for the representativity error when satellite observations are missing due to e.g. cloudiness. Furthermore, we account for systematic errors in the retrievals leading to error correlations between nearby individual observations contributing to one superobservation. Correlation information is typically missing in the retrieval products where an error estimate is provided for individual observations. The various contributions to the uncertainty are analysed: from the spectral fitting, the estimate of the stratospheric contribution to the column and the air-mass factor. The method is applied to TROPOMI data but can be generalised to other trace gases such as HCHO, CO, SO2 and other instruments such as OMI, GEMS and TEMPO. The superobservations and uncertainties are tested in the ensemble Kalman filter chemical data assimilation system developed by JAMSTEC. These are shown to improve forecasts compared to thinning or compared to assuming fully correlated or uncorrelated uncertainties within the superobservation. The use of realistic superobservations within model comparisons and data assimilation in this way aids the quantification of air pollution distributions, emissions and their impact on climate. [ABSTRACT FROM AUTHOR]

An improved divergence method has been developed to estimate annual methane (CH4) emissions from TROPOspheric Monitoring Instrument (TROPOMI) observations. It has been applied to the period of 2018 to 2021 over the Middle East, where the orography is complicated, and the mean mixing ratio of methane (XCH4) might be affected by albedos or aerosols over some locations. To adapt to extreme changes of terrain over mountains or coasts, winds are used with their divergent part removed. A temporal filter is introduced to identify highly variable emissions and further exclude fake sources caused by retrieval artifacts. We compare our results to widely used bottom-up anthropogenic emission inventories: Emissions Database for Global Atmospheric Research (EDGAR), Community Emissions Data System (CEDS) and Global Fuel Exploitation Inventory (GFEI) over several regions representing various types of sources. The NOX emissions from EDGAR and Daily Emissions Constrained by Satellite Observations (DECSO), and the industrial heat sources identified by Visible Infrared Imaging Radiometer Suite (VIIRS) are further used to better understand our resulting methane emissions. Our results indicate possibly large underestimations of methane emissions in metropolises like Tehran (up to 50 %) and Isfahan (up to 70 %) in Iran. The derived annual methane emissions from oil/gas production near the Caspian Sea in Turkmenistan are comparable to GEFI but more than two times higher than EDGAR and CEDS in 2019. Large discrepancies of distribution of methane sources in Riyadh and its surrounding areas are found between EDGAR, CEDS, GFEI and our emissions. The methane emission from oil/gas production in the east to Riyadh seems to be largely overestimated by EDGAR and CEDS, while our estimates, and also GFEI and DECSO NOX indicate much lower emissions from industry activities. On the other hand, regions like Iran, Iraq, and Oman are dominated by sources from oil and gas exploitation that probably includes more irregular releases of methane, with the result that our estimates, that include only invariable sources, are lower than the bottom-up emission inventories. [ABSTRACT FROM AUTHOR]

Since 2018, TROPOMI on-board Sentinel-5P provides unprecedented images of NO2 tropospheric columns at a relatively high spatial resolution with a daily revisit. This study aims at assessing the potential of the TROPOMI-PAL data to estimate the national to urban NO x emissions in France from 2019 to 2021, using the variational mode of the recent Community Inversion Framework coupled to the CHIMERE regional transport model at a spatial resolution of 10×10 km2. The seasonal to inter-annual variations of the NO x French emissions are analyzed. A specific attention is paid to the current capability to quantify strong anomalies in the NO x emissions at intra-annual scales such as the ones due to the COVID-19 pandemic, by using TROPOMI NO2 observations. The inversions lead to a decrease of the average emissions over 2019–2021 compared to 2016 of -3 % at national scale, which is lower than the decrease of -14 % between these years in the estimates of the French Technical Center for Air Pollution and Climate Change (CITEPA). This may be linked especially to the limited level of constraint brought by the TROPOMI data, due to the observation coverage and the ratio between the current level of errors in the observation and the chemistry-transport model, and the NO2 signal from the French anthropogenic sources. Focusing on local analysis and selecting the days during which the TROPOMI coverage is good over a specific local source, we compute the reductions in the NO x anthropogenic emission estimates by the inversions from spring 2019 to spring 2020. These reductions are particularly pronounced for the largest French urban areas (e.g., -26 % from April 2019 to April 2020 in the Paris urban area) and along major roadways, consistently with the reduction in the intensity of vehicle traffic reported during the lockdown period. [ABSTRACT FROM AUTHOR]

Since the launch of TROPOMI on the S5p satellite, NO2 observations have become available with a resolution of 3.5x5 km, which makes monitoring NOx emissions possible at the scale of city districts and industrial facilities. For Europe, emissions are reported on an annual basis for country totals and large industrial facilities and made publicly available via the European Environmental Agency (EEA). Satellite observations can provide independent and more timely information on NOx emissions. A new version of the inversion algorithm DECSO (Daily Emissions Constraint by Satellite Observations) has been developed for deriving NOx emissions for Europe on a daily basis, averaged to monthly mean maps. The estimated precision of these monthly emissions is about 25 % for individual grid cells. These satellite-derived emissions from DECSO have been compared to the officially reported European emissions and spatial-temporal disaggregated emission inventories. The country total DECSO NOx emissions are close to the reported emissions and the emissions compiled by the Copernicus Atmospheric Monitoring Service (CAMS). The comparison of the spatial distributed NOx emissions of DECSO and CAMS showed that the satellite-derived emissions are often higher in cities, while similar for large power plants and slightly lower in rural areas. [ABSTRACT FROM AUTHOR]