The charts illustrate the number of people who were affected by four types of noise pollution in day and night in cities and rural areas in 2007.
The bar chart demonstrates the amount of population in
cities
and rural areas
that were affected by traffic
, train, aircraft and industry noise
pollution
day and night
in 2007.
Overall
, although
traffic
pollution
accounted for the major noise
in both locations and durations, industry noise
was least minimal.
In details
, around 60 Fix the agreement mistake
detail
million
people
were subjected to daytime traffic
noise
in cities
compared to approximately 35 million
in rural areas
. At night
, the number of rural
population who was affected by Add an article
the rural
traffic
sound pollution
was almost half its counterpart in cities
, which were 24 and 48 million
people
respectively. On the contrary
, Industrial noise
pollution
was minimal as it was only noticed by less than a million
people
in cities
, as well as
inexistant
in rural Correct your spelling
inexistent
areas
.
Furthermore
, at daylight, train and aircraft noise
pollution
were
noticed by about 9 and 8 Correct subject-verb agreement
was
million
people
in urbanized areas
, respectively, whereas
in countryside areas
almost 8 and 3 million
people
complained in the same manner. Conversely
, at night
, while
train Correct word choice
apply
noise
pollution
had been a problem for about 7 million
people
in towns, in comparison to rural areas
which around 6 million
people
attested. Aircraft sound pollution
was same
at Correct article usage
the same
night
for both locations, less than a million
people
.Submitted by besoyam on
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Introduction: The introduction is missing.
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Introduction: The chart intro is missing.
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Introduction: The chart intro is missing.
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Vocabulary: Replace the words cities, areas, traffic, noise, pollution, night, million, people with synonyms.
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Vocabulary: The word "almost" was used 2 times.
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Vocabulary: The word "about" was used 2 times.
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Vocabulary: The word "around" was used 2 times.
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Vocabulary: Use several vocabularies to present the data in the second paragraph.
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